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American Journal of  Environmental
Economics (AJEE) 

Study of  the Potential of  Forest Biomass for the Development of  Wood Energy Sectors 
in Congo Brazzaville

Djimbi Makoundi Daivy Dieu-Le-Veut1*, Djimbi Makoundi Christian Dieu-Le-Veut1, Ming Lei1, Lei Zhang1

Volume 4 Issue 1, Year 2025
ISSN: 2833-7905 (Online)

DOI: https://doi.org/10.54536/ajee.v4i1.4211
https://journals.e-palli.com/home/index.php/ajee

Article Information ABSTRACT

Received: December 13, 2024

Accepted: January 16, 2025

Published: March 15, 2025

This research explores the potential of  residual forest biomass in Congo-Brazzaville to 
support sustainable energy transition and reduce greenhouse gas emissions. Despite the 
country’s heavy reliance on wood energy, which accounts for 85% of  the energy mix, 
unsustainable practices threaten forest resources. Meanwhile, residues from logging and 
local wood processing, combined with the annual consumption of  wood energy (firewood 
and charcoal), represent a significant amount of  biomass which, if  properly utilized, could 
generate greater social and environmental benefits than it currently does. A multidimensional 
approach was adopted to assess this potential. An interactive tool, the Biomass Cogeneration 
(CHP) Project Analysis System, was developed to model biomass flows, estimate energy 
production (thermal and electrical), and analyze environmental, economic, and logistical 
impacts. The results show that optimized utilization of  forest residues could generate 
up to 591.7 MW of  energy, representing 99% of  the country’s installed energy capacity, 
while avoiding up to 240,005 tons of  CO2 emissions annually. By promoting the use of  
biomass residues for cogeneration, this study supports national energy transition objectives 
and provides concrete solutions to integrate biomass as a strategic resource within Congo’s 
energy mix.

Keywords

Biomass Cogeneration, Congo-
Brazzaville Energy Transition, 
Energy Mix, Forest Biomass, 
Forestry Residues

1 Hebei Key Laboratory of  Low Carbon and High Efficiency Power Generation Technology, North China Electric Power University, 
  Baoding 071003, Hebei, China
* Corresponding author’s e-mail: 120204300006@ncepu.edu.cn

INTRODUCTION 
Forest biomass, as a renewable resource, plays a central 
role in global efforts to promote a sustainable energy 
transition (Burg, 2018) and combat climate change 
(Kirilenko, 2007). In the Republic of  Congo, the vast 
tropical forests, which cover approximately 65% of  
the national territory, offer significant potential for the 
development of  wood energy sectors. If  sustainably 
managed, these resources can not only meet the country’s 
growing energy needs (Aguilar, 2009; Sajdak, 1981) but 
also contribute to diversifying its economy, historically 
dominated by oil exploitation.
Today, energy consumption in the Republic of  Congo 
highlights the dominance of  wood energy, which accounts 
for approximately 85% of  the national energy mix 
(Figure 1). Within this proportion, firewood and charcoal 
play a central role, serving as an essential energy source 
for the majority of  Congolese households, especially in 
urban and rural areas. These fuels are primarily used for 
cooking and domestic activities (Hall, 2002; Eshiamwata, 
2019), with annual consumption remaining high, reaching 
several million tons.
 This dependence underscores the importance of  wood 
energy in meeting basic needs, while also highlighting 
the pressures on national forest resources (Misra, 2014), 
often exacerbated by unsustainable practices. In parallel, 
waste from logging and wood processing constitutes 
a significant part of  forest residual Biomass (Sette Jr, 
2020; Lima, 2020). It is estimated that between 40% and 
60% of  harvested wood and between 60% and 70% of  
processed wood end up as unutilized residues. This waste, 

generated by industrial and artisanal activities, represents 
a considerable energy potential (Gao, 2016) that remains 
largely untapped (Kashif  et al., 2020). To address these 
challenges, this study proposes a multidimensional 
approach that explores both the potential of  residual 
forest biomass and the digital tools capable of  
improving decision-making. In particular, it focuses 
on the development and integration of  an interactive 
tool, the Biomass Cogeneration (CHP) Project Analysis 
System, designed to assist decision-makers and planners 
in evaluating the technical, economic, logistical, and 
environmental aspects of  biomass cogeneration projects.

Figure 1: Congo national energy mix

This application, developed in HTML with interactive 
features, enables the modeling of  biomass flows, 



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estimation of  thermal and electrical energy production, 
and analysis of  environmental impacts, particularly in 
terms of  greenhouse gas (GHG) emission reductions. 
Additionally, it offers a comprehensive financial evaluation, 
including indicators such as Return on Investment (ROI) 
and payback period, providing a robust foundation for 
planning economically viable and sustainable biomass 
projects. 
By incorporating updated data on wood energy 
consumption, processing residues, and their potential 
valorization, this study aims to demonstrate how the use 
of  this tool can not only maximize energy efficiency but 
also promote sustainable forest resource management. By 
supporting national objectives for energy transition and 
climate change mitigation, this research seeks to provide 
concrete and actionable solutions to transform biomass 
residues and wood energy into strategic resources at the 
heart of  Congo’s energy mix.

LITERATURE REVIEW
The exploration of  forest biomass as a renewable energy 
source has been widely discussed in the context of  
sustainable development and climate change mitigation. 
The extensive literature on this subject highlights the 
dual challenge of  meeting growing energy demands while 
conserving forest ecosystems (Berndes, 2016; Börjesson, 
2017). The Republic of  Congo, endowed with vast forest 
resources, represents a critical case study in harnessing 
forest biomass for energy production. This section 
reviews the significant contributions of  past studies, 
providing a theoretical basis and justification for the 
adopted variables, and develops hypotheses aligned with 
the study’s objectives.

Forest Biomass as a Renewable Energy Resource
Forest biomass has long been recognized as a key 
component of  renewable energy strategies. Majchrzak 
(2022) identifies forest residues as a sustainable alternative 
to fossil fuels, emphasizing their role in reducing 
greenhouse gas (GHG) emissions and supporting 
energy security. Similarly, Bridgwater (Bridgwater, 2006) 
underscores the importance of  optimizing biomass 
conversion technologies to maximize energy yield. These 
studies form the theoretical basis for investigating the 
potential of  residual forest biomass in the Republic of  
Congo. Further perspectives on biomass utilization are 
presented in ‘Sustainable Biomass Energy Production: A 
Review of  Current Technologies and Future Prospects’ 
published by E-Palli Publishers (Tiewul, 2024), which 
emphasizes the critical role of  technological innovation 
in maximizing biomass energy efficiency.

Variables Influencing Biomass Utilization
Several studies have identified critical variables that impact 
the feasibility and efficiency of  biomass utilization. For 
instance, Field (2008) and Vasileios (2018) highlight the 
importance of  quantifying biomass residues generated 
from logging and wood processing. These residues, 

estimated to constitute 40-60% of  harvested wood, 
represent a substantial energy potential if  effectively 
managed. Additionally, technological factors, such as 
cogeneration systems, have been shown to significantly 
influence energy recovery efficiency (Jankes, 2012). 
The role of  policy and logistical frameworks further 
complicates the integration of  biomass into energy 
systems. Similarly, ‘Integration of  Forest Residues in 
Developing Nations’ Energy Systems’ published by 
E-Palli Publishers (Kumar, 2024) highlights the specific 
challenges and opportunities in implementing biomass 
energy systems in developing countries, particularly 
relevant to the Congo context.

Sustainable Forest Management and Policy Implications
Sustainable forest management practices are pivotal in 
ensuring the long-term viability of  biomass resources. 
(Ladanai, 2009) Ladanai and Vinterbäck discuss global 
frameworks for sustainable biomass use, which align 
closely with Congo’s national forestry policies. Law No. 
16-2000 on forest management underscores the need 
for balancing economic exploitation with environmental 
conservation (KOUA, 2017). This dual approach is 
critical in developing biomass as a strategic resource 
within Congo’s energy mix.

Gaps in Literature and Hypothesis Development
Despite extensive research on biomass energy, gaps 
remain in understanding the socioeconomic and logistical 
challenges of  integrating biomass into national energy 
strategies. For instance, while Bakouetila (Bakouetila, 
2020) explores wood energy consumption patterns in 
Congo, limited attention has been given to optimizing 
residue collection and transportation logistics. This 
study hypothesizes that leveraging digital tools, such as 
the Biomass Cogeneration Project Analysis System, can 
address these gaps by providing data-driven insights for 
decision-making.

MATERIALS AND METHODS
This study adopts a multidimensional approach to evaluate 
the potential of  forest biomass for sustainable energy 
production in Congo-Brazzaville. The methodology 
incorporates quantitative and qualitative data collection, 
as well as modeling tools to simulate biomass flow and 
energy generation.

Data Sources
Data Data for this study were derived from various 
primary and secondary sources. The primary sources 
included field surveys on wood energy consumption 
patterns, while eight major secondary sources were 
consulted National forestry reports including the 
“National Report on the Evaluation of  Global Forest 
Resources 2015”, reports from the National Center for 
Forest Inventory and Management (CNIAF),
World Bank economic data (2016) on forestry sector 
contributions, FAO forestry statistics and assessments 



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from 2010 and 2015, Household Survey reports on Wood-
Energy Consumption in the Republic of  Congo, Ministry 
of  Forest Economy publications, Law No. 16-2000 
documentation on the Forest code, and national forestry 
policy documents covering 2014-2025. These sources 
provided comprehensive data on forest resources, wood 
production, biomass residue, and energy consumption 
patterns.

Biomass Flow Analysis
A key methodological tool used in this study is the Biomass 
Cogeneration (CHP) Project Analysis System, developed 
specifically to model biomass flow and evaluate energy 
generation potential. This interactive tool integrates the 
following inputs:
Volume of  wood production and residues (harvesting 
and processing waste).
Lower Heating Value (LHV) and density of  biomass.
Transportation and logistical parameters.
The system enables the estimation of  thermal and 
electrical energy production, taking into account different 
cogeneration technologies, such as steam turbines, Organic 
Rankine Cycle (ORC) systems, and Stirling engines.

Environmental and Financial Analysis
To assess the environmental impact, greenhouse gas 
(GHG) emissions were quantified using emission factors 
and avoided fossil fuel emissions. Financial evaluations 
included calculations of  Return on Investment (ROI), 
payback periods, and net present value (NPV) based on 
the selling prices of  electricity and heat.

Hypothesis Testing
The hypothesis of  this study posits that biomass residues, 
if  efficiently utilized, can contribute significantly to 
Congo’s energy mix and climate change mitigation efforts. 
This was tested using simulation data generated by the 
CHP system, cross-referenced with real-world data from 
forestry operations and energy consumption patterns.
By combining digital tools, field data, and analytical models, 
this study provides a comprehensive understanding of  
the potential for biomass energy development in Congo-
Brazzaville.
 
Mathematical Expressions and Symbols
To evaluate the amount of  energy that can be produced 
from forest biomass, in the form of  electricity and heat, 
when used as fuel in a cogeneration plant, the following 
formula is used   
To convert the volume of  residual biomass into bone-dry 
tonnes, we use the relationship
E=TMA∙PCI∙1000                 (1)
Where E represents the energy produced in (in 
megajoules, MJ), TMA is the mass of  forest biomass 
(in dry metric tonnes, DMT), the PCI corresponds to 
the lower heating value of  the fuel (in MJ/kg) and the 
constant 1000 converts metric tonnes into kilograms.
TMA=VMA∙d                  (2)

Where VMA is the volume of  biomass in m3 and d is the 
density in kg/dm3
The electrical power of  a cogeneration plant using forest 
biomass as an energy source is expressed as
Pe=(E- ηe)/t                 (3)
Where Pe is the electrical power expressed in megawatts 
electrical (MWe), t is the duration in seconds (s) and ηe 
represents the electrical efficiency of  the cogeneration plant.
The thermal power of  the cogeneration plant is given by:
Pth=(E- ηth)/t                   (4)
Where Pth represents the thermal power in megawatts 
thermal (MWth), ηe corresponds to the thermal efficiency 
of  the cogeneration plant and the electrical efficiency (ηe) 
of  a cogeneration plant using forest biomass generally 
ranges between 20% and 30% [6]. As for the thermal 
efficiency (ηth ), it varies from 55% to 70% for modern 
cogeneration plants. 
In our simulation, we opted for an electrical efficiency of  
25% and a thermal efficiency of  60%, which provides an 
overall efficiency of  85% for our plant.

RESULTS AND DISCUSSION
Forest Biomass Potential
Historically, the forestry sector was the main driver of  
Congo’s economy until the discovery of  oil. Even today, 
forestry remains significant, contributing 5.3% to the 
national GDP (2016, World Bank) and positioning the 
country as a major producer of  tropical hardwoods, 
including logs, sawn timber, and panels. Despite the 
vast potential of  300 tree species, only about 50 are 
commercially exploited, indicating substantial room 
for diversification and development in the forestry and 
biomass sectors. The national forestry policy of  the 
Republic of  Congo established for the 2014–2025 period, 
embodies an ambitious and sustainable vision aimed at 
positioning Congolese forests at the heart of  the green 
economy and national development. Recognizing the 
critical role of  forests in poverty alleviation, improving 
living conditions, and combating climate change, 
this strategic vision reflects Congo’s commitment to 
harmonizing economic development and environmental 
conservation while aligning with global objectives to 
combat deforestation and climate change.
The Republic of  Congo, covering 34.2 million hectares, is 
rich in forest resources, with over 22 million hectares of  
forest, making up about 65% of  the country’s land area 
and 11% of  Central Africa’s forest cover (FAO, 2010). Of  
this, 14.8 million hectares are designated as production 
forests, all of  which are publicly owned, with 11.6 million 
hectares currently allocated under forest concessions.
FAO estimates the annual deforestation rate in the Republic 
of  Congo at about 0.1%, or roughly 17,000 hectares. In 
2015, forest cover was reported at 23.5 million hectares, 
representing 69% of  the country’s territory. The annual 
deforestation and degradation rate was lower, around 
0.05%, or 12,000 hectares per year (CNIAF, 2015). This 
extensive public ownership highlights the government’s 
crucial role in managing these forests sustainably.



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A recent estimate on forest land use in Congo, conducted 
by the FAO and published in the National Report on the 
Evaluation of  Global Forest Resources 2015

savannas make up 4.4%, open forests constitute 0.9%, 
and forest plantations, mangroves, and agricultural land 
each contribute less than 1%. According to satellite 
imagery data of  2003 and 2004, the total forested area 
was covered approximately 65.2% of  the country’s land.

Standing Wood
The 2009-2014 National Multi-Resource Forest Inventory 
of  the Republic of  Congo, along with the 1984 assessment 
of  the extent and potential of  timber forest resources, 
as reported in a publication by the Ministry of  Forest 
Economy. The total standing volume of  living trees (in 
1000 m³) with a diameter greater than or equal to 20 
cm is estimated at 4 billion cubic meters. Based on their 
distribution across different land categories: forests, other 
wooded lands, other lands, and inland waters. Forests 
are by far the primary source of  standing wood, with an 
estimated volume of  4,313,491 thousand cubic meters, 
representing nearly 99.7% of  the total recorded volumes. 
Other wooded lands, which include savanna woodlands 
and other intermediate vegetation formations, contribute 
approximately 0.05% of  the total volume. Other lands and 
inland waters contribute significantly less, accounting for 
about 0.26% and 0.016% of  the total volume, respectively.

Table 1: Summary of  CNIAF based on satellite imagery 
from 2003-2004
Categories Surface (in hectares)
Dense forest on dry land 13.558.000
Flooded dense forest 8.472.300
Open forest 310.000
Forest plantation 50.895
Mangrove 5.000
Wooded/shrub savanna 10,028,700
Grassy savanna 1,512.500
Agricultural land 250.000
Total land area 34.187.395

Table 2: Standing volumes for trees with a diameter ≥ 20 cm by overall class
Estimation Forest Other Forested Lands Other Lands Continental waters  Total
Wooded areas 4 313 491 2 222 11 344 708 4 327 765
Other, Lands Waters 196 0,5 1,5 2,5 127
Continentales 3,6% 43% 53% 56% 3,6%

Table 3: Exploitable volumes by global class (in 1000 m³)
Estimation Forest Other Forested Lands Other Lands Continental waters  Total
Volume/(1000 m³) 981 301 223 1 762 0 983 285
Other Lands Waters 44,6 0,1 0,2 0 29

The composition of  this vast ecosystem is divided into 
several categories. Dense forests on dry land represent 
approximately 39.7% of  the total land area, while flooded 
dense forests account for about 24.8%. Wooded and 
shrub savannas cover roughly 29.3% of  the area. Grassy 

The average volume per hectare in Table 2 varies 
significantly across categories. Forests stand out with a 
high density of  196 m³/ha, reflecting their substantial 
carbon storage capacity, while other wooded lands 
show a very low volume of  0.5 m³/ha, indicating 
sparse and likely degraded vegetation. “Other lands” 
and “inland waters” also exhibit modest volumes of  
1.5 m³/ha and 2.5 m³/ha, respectively. The relative 
standard error, which measures data uncertainty, is low 
for forests (3.6%), ensuring high reliability. However, 
the high margins of  error for other categories (43% 
to 56%) highlight the need to improve data collection 
and precision. The low contribution of  these categories, 

which account for a marginal share of  the total volume, 
reduces their impact on the overall uncertainty of  the 
estimates.

Exploitable Volumes
The Congo has a total exploitable wood volume estimated 
at 981 million m³, this potential represents 29 m³ of  wood 
per hectare, accounting for approximately 22.7% of  the 
total standing volume Table 3. In forested areas, this 
density reaches about 45 m³ per hectare. However, outside 
forest zones, the exploitable volume is significantly lower, 
with only 223,000 cubic meters in other wooded lands 
and 1.8 million m³ in non-forested lands.

Forestry regulations and environmental constraints play a 
major role in limiting the exploitation of  forest resources 
in Congo-Brazzaville, particularly under Law No. 16-2000 
on the Forest code. This law establishes strict rules on 
sustainable forest management, ecosystem conservation, 
and exploitation quotas to ensure a balance between the 
economic use of  forests and biodiversity preservation

National Structure of  Wood Production and Wood 
Energy Consumption
In Congo-Brazzaville, forestry exploitation is mainly 
divided into two types: industrial forestry exploitation 
Figure 2 and artisanal forestry exploitation Figure 3, 
(Lescuyer, 2011; Kimpouni, 2008). 
Industrial forestry exploitation is generally carried 



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out by companies or multinational corporations. It is 
characterized by large-scale logging, often on an extensive 
scale, to extract wood primarily intended for export 
around 1.3 million cubic meters of  wood each year though 
some is also sold on local markets for the production 
of  furniture, paper, plywood, and other wood-derived 
products. This activity is heavily concentrated in regions 
such as northern Congo, including areas like Sangha, 
Likouala, and Cuvette, where vast forest concessions are 
granted to logging companies.

While this activity is quite profitable for the country, 
generating export revenues of  over 300 million USD 
annually, it mainly focuses on profitability, prioritizing 
international demand over the local value-added 
processing of  this resource.
Local industrial units of  various sizes process logs into 
finished or semi-finished products. The demand for 
wood as a construction material is growing rapidly in 
the country, where it is widely used in sectors such as 
carpentry, joinery, and flooring.

Figure 2: Industrial forestry exploitation  

The woodworking and furniture sectors are also 
experiencing strong demand (Antwi-Boasiako, 2016), 
with the development of  small and medium-sized 
specialized enterprises that cater to local and regional 

needs for furniture. Local artisans use wood to produce 
furniture such as tables, chairs, beds, and wardrobes, as 
well as decorative objects and handcrafted items

Table 4: Total gross standing volume of  the ten (10) most common tree species in Congolese
Commercial name Density (mc/ha) Superficie forestière nationale Area (ha) Material (m3)
Sapelli 8.62 22.471.300 193.702.606
Limba 7.01 22.471.300 157.523.813
Niové 4.16 22.471.300 93.480.608
Tali 3.50 22.471.300 78.649.550
Ayous 3.08 22.471.300 69.211.604
Kossipo 2.85 22.471.300 6443.205
Padouk 2.31 22.471.300 51.908.703
Azobé 1.95 22.471.300 43.819.035
Iroko 1.83 22.471.300 41.122.479
Sipo 1.43 22.471.300 32.133.959



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Based on this national data, the total gross standing 
volume of  the ten (10) most widespread tree species 
in Congolese forests was documented by the National 
Center for Forest Inventory and Management (CNIAF/
DF) in its national report titled Global Forest Resources 
Assessment 2005 and presentend in Table 4. This report 
highlights the availability of  biomass and the potential 
of  Congo’s forest resources with a total volume of  1.016 
billion m³ mainly dominated by two species, Sapelli and 
Limba, which together account for over 42% of  the total 
volume. Sapelli alone contributes 23.46%, making it the 
most significant species, followed by Limba at 19.08%. 
These species illustrate the richness of  the Congolese 
forests and their economic potential (Ifo, 2016). However, 

they represent only a small fraction of  the 150 large tree 
species present in Congo.
Artisanal forestry exploitation is mainly carried out by 
local individuals, small operators, or community groups for 
energy need (Wood energy) in the entire national territory, 
unlike industrial logging, which is limited to forests rich 
in high-value timber (Mbete, 2014). It is characterized 
by selective logging on a small scale, primarily aimed at 
meeting local and regional needs rather than exports. Each 
year, this sector processes several thousand cubic meters 
of  wood, it continues to be used in households in the 
Republic of  Congo. Households rely on wood energy for 
all long cooking processes, such as beans and traditional 
dishes like saka saka, mouaba, cassava, etc.

Figure 3: Artisanal forestry exploitation 

Trees with a diameter of  10 cm or less are widely 
exploited due to their availability, they are directly used 
as firewood or transformed into charcoal through 
rudimentary processes, such as traditional carbonization 
in earthen kilns or artisanal furnaces. While these 
practices are essential to meet local energy needs, they 
lead to uncontrolled deforestation and expose users to 
risks of  intoxication from wood gas emissions (Gauthier, 
2012; Öztürk, 2002). The use of  wood energy varies 
significantly across the country’s departments Figure 4, 
which can be categorized into three main consumption 

areas: high, medium, and low.
Brazzaville and Pointe-Noire, which are respectively the 
political and economic capitals of  the country, represent 
the high consumption areas, collectively consuming over 
60% of  the wood energy. Brazzaville accounts for more 
than 45.23%, and Pointe-Noire for 18.68% of  the annual 
wood consumption. This is due to the high population 
density and concentrated energy needs in these cities. 
The medium consumption areas represent 18.2% of  the 
annual wood energy, including the departments of  Niari 
7.5%, Bouenza 5.99%, and Pool 4.71%.

Figure 4: Wood consumption by departments in Congo Brazzaville 2024



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The departments of  Plateaux, Kouilou, Likouala, Sangha, 
Cuvette, Lékoumou, and Cuvette-Ouest are classified as 
low consumption areas, with each department consuming 
below 3%. Collectively, they account for a total of  17.88% 
of  the annual wood consumption.

Cogeneration
Cogeneration, also known as Combined Heat and Power 
(CHP), is an efficient technology that simultaneously 
produces electricity and heat from a single energy 
source.

Figure 5: CHP cogeneration technology

This approach is highly valued for its energy efficiency, 
superior to conventional energy production systems 
(Maraver, 2013). Cogeneration systems can achieve overall 
energy efficiencies of  up to 80-90%, whereas traditional 
electricity-only production methods often have efficiencies 
of  around 35-40%. The recovery of  heat, a key feature 
of  cogeneration, allows the exploitation of  heat that 
would otherwise be lost in conventional systems, using 
this energy for building heating, industrial processes, or 
hot water production. Biomass cogeneration technology 
can employ different cogeneration technology Figure 5 
to convert biomass into both heat and electricity (Abbas, 
2020), including steam turbines, steam engines, Organic 
Rankine Cycle (ORC), and Stirling engines. Each of  these 
technologies has distinct characteristics and applications.
                
Conversion of  Residual Forest Biomass into Energy 
through Cogeneration
The total wood production for the year 2018 was estimated 
at 1.8 million m³ (anhydrous metric volume). According 
to the study report from the Household Survey on Wood-
Energy Consumption in the Republic of  Congo, it is 
estimated that 40% to 60% of  harvested wood and 60% 
to 70% of  wood intended for processing end up as waste. 
To evaluate the volumes of  residual biomass available 
for the year 2022, we used an average of  these values, 
incorporating both harvesting and processing data, to 
provide a cautious yet realistic estimate of  the residual 
biomass potential. The Low eating value is 17.810mj/kg.
The estimation of  biomass residues from industrial 
forestry operations is based on two main categories: 
harvested wood and processed wood.
The total wood production for the year 2018 was 

estimated at 1.8 million m³ (anhydrous metric volume). 
Assuming that the logging waste percentage ranges from 
40% to 60%, the average will be: 
Average logging waste = (40 + 60) / 2 = 50%.
If  50% of  the total volume is considered waste, the 
quantity of  logging waste is calculated as follows: Logging 
waste = 1.800000 m³×50% = 900000 m³.
If  44% of  the wood produced is exported as logs, the 
remaining quantity intended for local processing is 
given by: Wood for local processing =1800000×0.56 = 
1008000m³. Of  the wood processed locally, 60% to 70% 
is considered waste. The average of  this waste is:
Average waste after processing = (60 + 70) / 2 = 65%. 
The quantity of  waste after processing will therefore 
be Waste after processing = 1008000m³ × 0.65 = 
655200m³. The total forest waste is the sum of  logging 
waste and waste after processing: Total forest waste = 
900000+655200 = 1555200m³.
TMA=1555200×0.69=1073088 tonnes
The calculation of  Total energy give
E=(1000×1073088×17.810)/1000=19112592.48GJ
Electric power
Pe=(19112592.48×0.25)/31557600=151.4 MW
Thermal Power
Pth=(19112592.48×0.6)/31557600=363.38MW
According to the law (Law 33-2020), which requires the 
processing of  all logs within the national territory, 100% 
of  the wood produced is allocated for local processing. 
This means that the entire 1,800,000 m³ is subject to the 
65% waste processing average. The waste generated after 
full processing would amount to: Waste after processing 
(with law) = 1800000×65% = 1170000m³. The total 
forest waste after the application of  the law is then: Total 



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forest waste (with law) = 900000+1170000 = 2070000m³.
TMA=2070000×0.69=1428300 tonnes
The calculation of  Total energy give
E=(1000×1428300×17.810)/1000=25438023GJ
Electric power
Pe=(25438023×0.25)/31557600=201.5 MW
Thermal Power
Pth=(25438023×0.6)/31557600=483.6MW
To determine the total amount of  wood actually felled 
in the forest, we need to take into account the losses 
generated throughout the production process where 
Wood felled will be the some of  the Total production and 
the Logging waste. Wood felled = 1800000 + 900000 = 
2700000 m³

Conversion of  Biomass (firewood) into Energy 
through Cogeneration
According to the estimation of  the evolution of  firewood 
and charcoal consumption by department, conducted 
as part of  the household survey report on wood-energy 
consumption in the Republic of  Congo, the projected 
consumption for the year 2024 was 482,665 tonnes of  
firewood and 285,397 tonnes of  charcoal.
Taking into account that 8.3 kg of  firewood is required 
to produce 1 kg of  charcoal (according to the study on 
wood-energy consumption in the cities of  Brazzaville and 

Nkayi – FAO and UNDP, 2004), the total wood-energy 
consumption amounts to 3,457,281.30 tonnes.
TMA=3457281.295×0.8=2765825.036 tonnes
The calculation of  Totale energy give
E=(1000×2765825.036×17.810)/1000=49244542442 
GJ
Electric power
Pe=(49244542.442×0.25)/31557600=390.2 MW
Thermal Power
Pth=(49244542.442×0.6)/31557600=936.1 MW
If  the energy production from the CHP biomass plant, 
powered by the amount of  firewood consumed across the 
entire national territory for the year 2024, is distributed by 
the percentage of  charcoal consumption per department, 
this graph is obtained.
Analyzing the regional distribution of  this biomass 
production, based on the amount of  firewood consumed 
in 2024 Figure 6, Brazzaville accounts for 31.3% of  
electricity production 88.24 MW and 37.7% of  thermal 
production 211.69 MW, followed by Pointe-Noire 
with 12.9% 36.44 MW and 15.6% 87.43 MW. Other 
departments are distributed as follows: Cuvette-Ouest 
0.8% electricity, 1.0% thermal, Likouala 2.0%, 2.4%, 
Lékoumou (1.2%, 1.5%), Sangha 2.0%, 2.4%, Niari 5.2%, 
6.3%, Pool 3.3%, 3.9%, Plateaux (2.1%, 2.6%), Kouilou 
2.4%, 2.8%, and Bouenza 4.1%, 5.0%.

Figure 6: Wood Energy disponibility  

Contribution of  Biomass Energy to the Congolese 
Energy Mix
The total installed capacity in Congo-Brazzaville Figure 7 
is estimated at 596 MW, distributed among hydropower, 
gas power plants, and thermal power plants.
Key infrastructures include the Moukoukoulou 
hydropower plant 74 MW, the Djoué hydropower plant 
15 MW, the Imboulou hydropower plant 120 MW, the 
Djeno gas power plant 50 MW, the Congo gas power 
plant 300 MW, as well as the diesel thermal power plants 
of  Brazzaville 32.5 MW and Oyo 4.5 MW. Additionally, 
there is an electrical interconnection with the Democratic 
Republic of  Congo via the 225 kV Brazzaville-Kinshasa 
line, providing a transit capacity of  100 MW, though only 
local production is considered in this analysis.

Figure 7: Current Distribution of  Installed Capacity in 
Congo-Brazzaville



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Figure 8: Potential Impact of  Biomass on the Energy Mix

If  we see the potential Impact of  Biomass on the Energy 
Mix Figure 8 by integrating biomass energy from forest 
residues and logging activities, approximately 151.4 MW 
of  electricity could be added to the Congolese energy 
mix, representing nearly 25% of  the currently installed 
capacity. With the implementation of  Law 33-2020, which 
mandates the local processing of  100% of  logs, biomass 
energy generated from logging residues could reach 201.5 
MW, representing 33.8% of  the installed capacity. This 
specific source could thus become a major contributor 
to the national energy mix. Furthermore, converting 
biomass from firewood into electricity is estimated at 

390.2 MW, accounting for approximately 65% of  the total 
installed capacity. Combined, the two biomass sources 
(forest residues and firewood) could supply a total of  
591.7 MW, representing 99.3% of  the current installed 
capacity, nearly doubling the existing capacities in the 
energy mix. Biomass could contribute 65% to 99% of  the 
Congolese energy mix, depending on scenarios for local 
log processing and firewood conversion into electricity.  

Analysis of  clean Energy Projects
As part of  the optimization and energy valorization 
of  biomass, the biomass cogeneration (CHP) project 

Figure 9: Diagram flow of  the (CHP) program



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analysis system developed provides a methodological 
tool to assess the technical, logistical, environmental, and 
economic aspects of  projects.
This system relies on key data to model biomass flows, 
energy production, greenhouse gas (GHG) emission 
savings, and expected financial returns.
Figure 9 illustrates the flow diagram of  data and   
processes in a biomass cogeneration project. It highlights 
the main steps, from biomass supply to the production 
and distribution of  thermal and electrical energy. Each 
element in the diagram plays a specific role in assessing 

the available resources and their conversion into energy.
The system was designed to meet several key needs, including 
assessing the availability of  biomass resources, such as residues 
from forest operations and processing, and calculating the 
potential for thermal and electrical energy production. It 
also analyzes the logistics required for transporting biomass 
resources and evaluates energy distribution and its impact 
on local communities. Additionally, the system quantifies 
environmental benefits in terms of  greenhouse gas (GHG) 
emission reductions and examines the project’s economic 
profitability and financial indicators.

Figure 10: Main Page

Figure 11: Supply source

The main Figure 10 input parameters include the wood 
production volume (m³), which represents the total annual 
quantity of  wood produced and serves as the basis for waste 
calculations, and the percentage of  cutting and processing 
waste, which estimates the proportions of  residues 
generated during production. Other key parameters 

include the capacity of  semi-trailers (m³) used for biomass 
transportation, the Lower Heating Value (LHV) indicating 
the energy content of  the biomass in MJ/kg, and the 
density (kg/dm³) for converting biomass volumes into 
mass. Together, these parameters enable accurate modeling 
of  biomass supply and the associated logistical flows.



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By clicking on Add Supply Source, the users can configure 
multiple biomass sources Figure 11 by specifying key 
parameters such as volume (m³), Lower Heating Value 
(LHV) in MJ/kg, moisture content (%), which directly 
affects the quality and quantity of  energy produced, and 
density (kg/dm³). 
In the Results section, the system generates key indicators, 
including the volume of  cutting and processing waste, 

which reflects the total amount of  available biomass, and 
the total dry matter (DM), representing the biomass mass 
after moisture removal. It also calculates heat and electricity 
production, indicating the thermal and electrical energy 
generated, as well as hourly consumption, which is the 
amount of  biomass required to sustain production. Finally, 
for logistics, the system estimates the number of  semi-
trailers needed per day to transport the biomass efficiently.

Figure 12: Distribution

In the Distribution section Figure 12, the system includes 
a comprehensive analysis of  energy distribution, allowing 
for the simulation of  losses related to energy transportation 
from production to consumers. It provides key indicators 
such as the percentage of  delivered electricity and heat. 

It also calculates per capita and household consumption, 
offering a clear view of  the project’s impact on households 
and local communities. Finally, it estimates the project’s 
total reach by determining the number of  households 
and inhabitants that can be served.

Figure 13: Data Visualizations



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The Visualizations section Figure 13 provides a clear 
representation of  the data to facilitate its interpretation. 
The Volume Distribution section allows for an interactive 
visualization of  volume distribution in the form of  a 
diagram, offering a global view of  the energy balance. 

The Power Distribution section enables a comparison 
of  thermal and electrical power, providing an overview 
of  energy production. The Energy By Source section 
illustrates the energy contributions of  each type of  biomass, 
highlighting their respective roles in overall production.

Figure 14: GES Analysis

Figure 15: Operation profit

The GES Analysis section Figure 14 provides a detailed 
analysis of  the environmental benefits by quantifying 
the reductions in greenhouse gas (GHG) emissions. 
By inputting the average emissions per vehicle (tCO2/

year) and the avoided emissions from fossil fuels (tCO2/
MWh), the Results subsection displays the CO2 emissions 
avoided, expressed in tons of  CO2 per year, as well as the 
equivalent number of  cars removed from circulation.

The Operation Profit section Figure 15 includes a 
comprehensive financial analysis, enabling a detailed 
evaluation of  the economic viability of  projects. This 
analysis is based on several key elements, including costs 
related to initial investment, maintenance, and operation, 
as well as estimated revenues based on the selling prices of  
electricity and heat, expressed in $/MWh. It also considers 
financial parameters such as the project duration (in years), 
interest rate (%), and availability rate (%).
In the Results section, the system provides the total 
required investment, annual revenues generated, and 
operational profits. Additionally, essential financial 
indicators, such as Return on Investment (ROI), Net 
Present Value (NPV), and payback period, are included 
to assess the profitability and economic sustainability of  
the project.

Simulation Results with the Biomass Cogeneration 
(CHP) Analyzer
2020, which requires all logs to be processed within the 
national territory, the simulation indicates a total biomass 

production of  2,070,000 m³, generating an electrical 
output of  201.52 MW and a thermal output of  403.05 
MW. This project could supply energy to 1,048,159 
residents and 235,908 households while avoiding 240,005 
tons of  CO₂ emissions annually, equivalent to removing 
52,121 vehicles from circulation. On the financial side, 
with an investment cost of  $300 million and sales prices 
of  $70/MWh for electricity and $60/MWh for heat, the 
project generates an annual profit of  $230.05 million, 
with a payback period of  8.5 years and an internal rate of  
return (IRR) of  11.2%.

CONCLUSION
This study has highlighted the significant potential of  
forest biomass residues in the context of  sustainable 
energy transition in Congo-Brazzaville. Given the 
country’s heavy reliance on wood energy, which accounts 
for 85% of  the national energy mix, the energy recovery 
of  residues from logging and wood processing activities, 
as well as wood biomass energy (firewood and charcoal) 
intended for annual use, emerges as a strategic solution. 



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The findings demonstrate that an optimized exploitation 
of  these resources could not only generate up to 591.7 
MW of  energy but also prevent up to 240,005 tons of  
CO2 emissions per year, thereby significantly contributing 
to national climate and energy objectives.
The multidimensional approach adopted, combined 
with the development of  an interactive tool for biomass-
based cogeneration project analysis, has demonstrated 
the technical, economic, and environmental feasibility 
of  such valorization. Moreover, the integration of  
biomass into the national energy mix goes beyond mere 
energy diversification. It also aligns with a sustainable 
development framework, supporting the responsible 
management of  forest resources and the creation of  
socio-economic benefits for local communities.
In a context where the Congolese government is 
committed to transforming the forestry sector into a 
driver of  a green economy, this research provides a solid 
foundation for policies and concrete actions. It offers 
pragmatic solutions to address critical challenges such as 
reducing energy poverty, mitigating climate change, and 
preserving natural resources.
Finally, this study calls for collective efforts involving 
public authorities, private stakeholders, and local 
communities to turn this potential into reality. Synergy 
between technological innovation, an adapted regulatory 
framework, and community engagement will be essential 
to making forest biomass a cornerstone of  sustainable 
energy development in Congo-Brazzaville.

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