1. Introduction
During recent decades, fossil fuels have represented around 80% of the global energy demand [
1]. The widespread reliance on fossil fuels for energy presents two major challenges. On the one hand, the combustion of fossil fuels is linked with environmental degradation and the emission of greenhouse gases (GHGs), which are the main contributors to climate change [
2]. On the other hand, fossil fuels are non-renewable resources, so they are subject to running out. The depletion of fossil fuels is one of the main concerns in global energy policy, as it directly affects prices and supply [
3]. Due to these reasons, a transition is needed toward cleaner ways of generating and using energy through renewable resources.
Although fossil fuels still have the largest share of global energy demand, the use of renewable energy is growing faster. From 2009 to 2020, renewable energy demand increased by 4.6% per year, compared to 0.9% of fossil fuels and 1.2% of global energy demand [
1]. This has led to an increase in modern renewables’ share of global energy demand from 8.7% in 2009 to 12.6% in 2020. Moreover, bioenergy plays an important role in the decarbonization and diversification of energy systems as part of modern renewables. The same REN21 report [
1] specifies that in 2020, 5.4% of global energy demand was supplied by modern bioenergy, representing 47% of all modern renewable energy.
Bioenergy is a form of renewable energy that is produced from organic matter, which is known as biomass. This biomass is generated from plants or is plant-derived, including waste from agriculture, forestry, livestock, sewage, municipal solid waste (MSW), and energy crops. Traditionally, biomass has been used for heat generation through the direct combustion of firewood and charcoal, as well as agricultural residues and dung. The primary technology for the traditional use of biomass in the Global South is inefficient stoves, which are still widely used for cooking and heating in the residential sector [
1]. In contrast, modern bioenergy can be used for different end-use applications (i.e., heating, power, and transport) with different biomass fuel types (i.e., solid, liquid, and gas) and at higher efficiency levels. A transition toward clean renewable energy requires the modernization of bioenergy systems as they can contribute to reducing the demand for fossil fuels in all sectors bringing economic and environmental benefits [
4].
Sub-Saharan Africa is the region with the largest reliance on the traditional uses of biomass in the world. When looking at just the cooking sector in this region, 923 million people have no access to clean cooking fuels [
5]. The use of solid biomass in traditional stoves is related to high levels of indoor air pollution, exposing women and children to numerous health issues [
6]. Moreover, a lack of access to clean cooking fuels has other impacts, such as a reduction in women’s time for income activities and their exposure to dangers while gathering fuel [
7], or high deforestation rates and landscape degradation, which contribute to the increase in GHG emissions [
8]. Modernizing the use of bioenergy in Sub-Saharan Africa would tackle these impacts while increasing access to clean energy. However, the transition to modern bioenergy use varies across countries due to diverse geographical, socio-economic, and cultural factors [
9]. Therefore, issues such as policy development, cross-sectoral approaches, financing, research, or capacity building have to be considered for each context, while the harmonization of standards and policy frameworks can enhance regional cooperation. Moreover, Maishanu et al. [
9] pointed out that a definition of information systems to determine sustainable bioenergy potential at the state and province level is essential to developing modern bioenergy systems.
One of the Sub-Saharan countries with the highest dependence on traditional biomass use is Mali. Located in the Sahel region, Mali is characterized by three different climate areas: tropical savanna in the south, hot semi-arid regions in the center, and hot desert in the north [
10]. Most people in Mali live in the southern part of the country, where annual precipitation variation is high during the rainy season, which develops from April to October. As of 2021, the estimated population in Mali was 21.9 million, an increase of more than 10 million in the previous 10 years [
11]. Although most of the population lives in rural areas, it was estimated that the share of people living in cities increased from 29.1% to 44.7% in the same period [
12]. This population growth and urbanization rate have resulted in the country experiencing an increase in energy demand in recent years, especially for traditional fuels [
13]. By 2020, biomass represented around 64% of the total energy supply, followed by oil at 33% and hydro at 3%, with solar, coal, and others being practically insignificant. However, when looking at electricity generation, hydro accounts for 57% of it, followed by oil at 38% and other fossil fuels, solar, and biomass at just around 3% [
14]. Only around 53% of the population has access to electricity. Moreover, there is a huge difference between urban and rural populations, as electricity access in urban areas is around 97% compared to 18% in rural areas [
15]. However, when comparing electrification to clean cooking fuel access, the latter is in a more critical situation.
Currently, Mali is one of the countries in the world with the lowest access to clean cooking fuels. The National Institute of Statistics (INSTAT) estimated that, as of 2020, 47.4% of the population used firewood as the primary source for cooking, 47% used charcoal, and around 3.3% used oil or animal waste [
16]. When looking at access to clean cooking fuels and technologies as a whole, it is only around 0.9% of the population, with this value being stagnant during the last decade [
15]. This reliance on polluting fuels highlights the importance of assessing the biomass waste resources in the country and their potential implementation for a transition toward modern bioenergy systems in the residential cooking sector. Mali is mainly an agricultural country, greatly dependent on this activity to sustain its socio-economic development [
17]. Thus, there is considerable production of crop residues and livestock waste, which have not been quantified in detail so far. Moreover, MSW is poorly treated in the country. Waste disposal at uncontrolled open landfill sites is the most common practice. However, waste-to-energy technologies are preferred in the waste management hierarchy, as they are more socio-economically and environmentally beneficial [
18]. Therefore, MSW could also be a potential source of bioenergy generation.
As mentioned above, low clean cooking access in Malian households makes a transition in this sector indispensable, with modern bioenergy systems being potential alternatives. To develop these systems in the country, it is essential to determine the quantity of available biomass resources and how they could contribute to bioenergy production for cooking. In the literature, the estimations of bioenergy potential have been focused on specific regions and/or crops, with little attention given to demand in the cooking sector [
19,
20]. Regarding livestock waste, Arthur and Baidoo [
21] estimated the potential production of methane in the country by using animal manure, but without an energy-use perspective. These previous studies consider the entirely available biomass resources in the country, but without taking into account how the bioenergy resources for each waste stream can be applied in the cooking sector. In some cases where the bioenergy potential of a specific crop is quantified, its use for electricity production is prioritized. Using bioenergy for cooking could reduce the electric demand of rural households for their basic needs, thus helping to expand faster and in a more affordable way the electrification of the country [
22].
The aim of the present study, therefore, is to assess the potential production of bioenergy from crop residues, livestock waste, and MSW, considering the specific end products for each biomass resource to meet the cooking needs of Malian households. Moreover, the estimation of biomass resources and their respective bioenergy products is presented geographically, considering the differences between the regions of Mali. This differentiation helps to determine to what extent each biomass resource can contribute to the cooking demand of each region. For this purpose, the useful energy cooking demand per region in Mali is also estimated. It should be noted that an economic analysis of bioenergy fuel applications is not considered as it is outside the scope of this study. The reason is the lack of data for estimating feedstock prices and supply costs in the country, thereby increasing its complexity.
The present work is the first study to comprehensively assess sustainable biomass potential in Mali, which is a crucial step for promoting bioenergy systems. In order to determine the potential production of cooking biofuels, the proposed methodology compared different production routes for the available biomass. This means that one biomass resource can be used for the production of different biofuels. This is a different approach to other similar studies, where normally only one route of biomass resource to bioenergy end product is considered. This approach can allow technology developers to compare the efficiency of different production systems while considering alternative biofuels to meet the cooking energy demand. This can also raise awareness about the availability of biomass for cooking and if other energy systems are required to achieve a clean cooking transition.
This paper is structured as follows: The next section presents the methodology of the study, followed by the results and discussion section, where the main findings of the study are presented and discussed. Finally, the conclusion constitutes the last section.
2. Materials and Methods
In order to assess the bioenergy potential of the country and compare it with the cooking energy demand, the methodology was based on two main parts: desk research and fieldwork. The desk research included gathering data from official reports of the National Institute of Statistics, scientific papers, and other reports from governmental and international agencies. Those data and the data obtained after the fieldwork were analyzed. In the fieldwork, surveys of households in Bamako and a selected rural village were conducted regarding cooking practices and fuel consumption. This was complemented by separate interviews with local experts about the fuel market and energy demand.
The methodology is structured into three subsections. In the first subsection, the estimation of biomass resource potential is presented, including crop residues, livestock waste, and MSW. Subsequently, the estimation of bioenergy potential is presented, focusing on the production of briquettes, biogas, and bioethanol. Finally, the methodology for estimating the cooking energy demand in the Malian residential sector is presented.
2.1. Estimation of Biomass Resource Potential
In the literature, the potential of biomass resources for energy production is defined in several ways, encompassing theoretical potential, technical potential, economic potential, and sustainable potential [
23]. Some even consider ecological potential or implementation potential [
24]. Those terms are presented in the literature with different definitions, and in some cases, they might overlap. For example, Batidzirai et al. [
24] presented economic potential as a subset of technical potential, with this being a subset of theoretical potential.
This study is focused on the concept of sustainable potential, understood as the fraction of produced biomass waste at a given time that can be obtained without negative social or ecological effects. It means the share of biomass waste that is disposed of or burned, which could be collected. This is especially relevant for crop residues, as agricultural waste has many purposes in the Malian context, e.g., animal fodder or soil fertilizer. Waste already employed for feeding animals or incorporated into soil is not available for bioenergy production.
The estimation of sustainable biomass resource potential was calculated for different regions according to the country’s division before 2016 [
25]. The selected regions are Bamako, Gao, Kayes, Kidal, Koulikoro, Mopti, Ségou, Sikasso, and Tombouctou. Consequently, the current regions of Taoudénit and Ménaka are part of Tombouctou and Gao, respectively. The choice of the previous division for the estimation of sustainable biomass resource potential was due to easier data access, while the new division’s effect on the geographical distribution is not very significant. This previous division is also used for estimating bioenergy potential and cooking energy demand in the following sections.
Figure 1 shows cropland use in the country together with the administrative division, aiding in understanding the effect of climate areas on the distribution of agricultural land.
2.1.1. Crop Residues
Cereals are the major type of crop produced in Mali. The main crops grown for subsistence are millet, sorghum, rice, and maize (corn), representing almost 75% of total crop production for food in the country. When the production of cowpea, groundnut, and sweet potato is considered, this share increases to around 82% [
27]. Fruit crops like mango, banana, and orange also contribute significantly to food production. With their addition, more than 90% of the crops for food production in the country are included. Further, the country’s two main cash crops are also considered in this study. One is sugarcane, which has a high production potential in the Ségou region [
20]. The other is cotton, a major export and considered a key crop for socio-economic development, according to the Malian government [
28].
To estimate the crop waste potential, crop production quantities were obtained from the 2015 Statistical Yearbook of the Rural Development Sector published by the Malian Ministry of Agriculture [
27]. This statistical report is the most recent of its kind in the country. The equations and procedures used to estimate biomass resource potential in this study are based on similar cases for other countries in the literature [
29,
30,
31,
32]. These procedures rely on two main parameters associated with crop residues. The first is the residue-to-product ratio (RPR), which determines the mass of crop residue compared to the same type of crop production. The second is the surplus residue fraction (SRF), also known as the surplus availability factor [
30] or recoverability fraction [
32], among other terms. The SRF indicates the share of crop waste available for bioenergy production and not being used for other purposes, like animal fodder or bedding. Although animal bedding can be reused for energy purpose, its use as fertilizer is widespread in Sub-Saharan Africa [
33]. Therefore, animal bedding is not considered here for energy purposes. Equation (1) shows how the crop residue potential is calculated for each region of the country:
where
SCRP(j) is the sustainable crop residue potential at the
jth region (t/y);
n is the total number of crops considered;
CP(i,j) is the crop production of the
ith crop at the
jth region (t/y);
RPR(i) is the residue to product ratio of the
ith crop (-); and
SRF(i) is the surplus residue fraction of the
ith crop (%).
To determine the RPR and SRF values for the selected crops, studies in Mali were prioritized. When this was not possible, the values were assumed using studies for the given crops in other Sub-Saharan regions. RPR and SRF were determined for the main residue types for each crop.
Table 1 shows the input parameters used in the estimation of the sustainable crop residue potential. It should be noted that the waste produced by cowpea crops is commonly used as fodder for animals, so it was not considered for bioenergy production [
34].
The use of average parameters adds uncertainty to the estimation of sustainable biomass potential, not only for crop residues but also for livestock waste and MSW. Nygaard et al. [
19] already pointed out this problem in their study of the rice waste potential in the Office du Niger, showing a lack of scientific data regarding parameters used, such as the RPR. Although in the current study the use of data from the studied country or region was prioritized, the results have to be taken to some extent with a degree of uncertainty. Moreover, when data on potential estimates were available for certain crops or regions, the results were compared to observe if there were significant deviations.
2.1.2. Livestock Waste
Livestock waste refers to the dung produced by farm animals. According to the 2015 Statistical Yearbook data [
27], the main types of animals are cattle, sheep, goats, horses, donkeys, camels, pigs, and poultry. In this same report, the total number of heads for the different livestock types in all the regions of the country is given. The equations and procedures to estimate the biomass resource potential from livestock waste are based on similar previous studies for different regions [
30].
In order to determine the livestock waste potential, it is necessary to determine the quantity of manure produced by each type of animal. This quantity depends on different factors such as animal age, feeding habits, type of fodder, and even temperature. Moreover, the availability factor is used to estimate the total quantity of livestock waste suitable for bioenergy production. This factor represents the share of waste that can be collected and is not used for other purposes. Equation (2) shows how the sustainable livestock waste potential for bioenergy production is estimated for each region:
where
SLWP(j) is the sustainable livestock waste production at the
jth region (t/y);
NA(i,j) is the number of heads of the
ith animal at the
jth region;
YM(i) is the daily manure yield of the
ith animal in [t/(day·animal)];
AF(i) is the availability factor for the
ith animal (-); and
Dy is a conversion factor representing the number of days in a year (d/y), i.e., 365.
Due to the lack of literature data on livestock waste production in Mali, different worldwide studies for manure yield and available factor values were considered (
Table 2). As these values are affected by the different aforementioned conditions, average values were assumed for the Malian context. The manure yield for cattle and camels was considered 15 kg per day and head, 10 kg for horses and donkeys, 1.6 kg for sheep and goats, 3.12 kg for pigs, and 0.05 kg for poultry. In the case of the availability factor, it was chosen as 0.35 for cattle; 0.25 for sheep and goats; 0.5 for horses, donkeys, and camels; 0.9 for pigs; and 0.75 for poultry.
2.1.3. Municipal Solid Waste
For the estimation of biomass resource potential from MSW, there are different approaches in the literature. While some studies consider the entire population [
30], others only consider urban areas [
43]. In this study, urban population is used for estimating MSW generation, as there are no known strategies for waste collection in rural areas of the country, and usually, the waste generated per capita in these areas is low. Data on the total population for 2015 was available from the 2015 Statistical Yearbook [
27]. The share of urban population was estimated using data from the last official census from the National Institute of Statistics (INSTAT) in 2009 [
44] and using an average increase in urban population of 0.8% annually between 2009 and 2015 [
45]. According to the INSTAT census, urban populations consist of urban municipalities with at least 5000 inhabitants. The estimated values of the population are shown in
Table 3.
With the urban population defined, Equation (3) is used to estimate the sustainable MSW potential for bioenergy production:
where
SMSWP(j) is the sustainable MSW potential at the
jth region (t/y);
UP(j) is the urban population at the
jth region;
MSWG(j) is the MSW generation at the
jth region [t/(person·day)];
RC(j) is the rate collection at the
jth region; and
Dy is a conversion factor representing the number of days in a year (d/y), i.e., 365. For the generation of MSW, it was determined a value of 0.65 kg/(person·day) (6.5·10
−4 t/(person·day)) for the entire country, while the average rate collection in Mali is 85% according to the literature [
46,
47].
2.2. Estimation of Bioenergy Potential
The sustainable biomass resource potential of Mali can be a source for the production of bioenergy, thus helping to increase access to energy for its population. Although the contribution of biomass to the production of clean cooking fuel is low in Mali, there are some existing applications both in the commercial and pilot-scale phases. The main bioenergy fuels used in the country, besides firewood, are solid briquettes for improved cook stoves (ICSs), biogas, and bioethanol [
48]. The following subsections show the methodology used to estimate their potential production from biomass resources.
2.2.1. Briquettes Potential
Briquettes are formed in different shapes by the compression of biomass, such as agricultural waste. The compression of biomass allows it to have a longer burning time and an improved density for handling it. Therefore, briquettes substitute charcoal and firewood in many countries for cooking purposes [
49]. In order to estimate the potential of briquettes in Mali, only the application of crop residue and its densification is considered. With this assumption, a calculation can be performed using the heating content of the biomass resources, as was conducted in previous similar cases [
29]. A lower heating value (LHV) is used. Equation (4) is used to determine the bioenergy potential for each region:
where
Ebriquettes(j) is the briquette bioenergy potential at the
jth region (TJ/y);
SRCP(i,j) is the sustainable residue crop potential of the
ith crop at the
jth region (t/y); and
LHV(i) is the low heating value of the
ith crop (TJ/t). The values of LHV were obtained from the literature from case studies in Sub-Saharan Africa, as shown in
Table 4.
All crop residues were considered except for sweet potato waste. According to Bot et al. [
51], sweet potato waste is not suitable for the production of briquettes due to its properties, which is consistent with the lack of studies on briquette production from this biomass resource. Therefore, sweet potato waste was only considered for biogas and bioethanol potential.
2.2.2. Biogas Potential
Biogas is a mixture of methane, carbon dioxide, and other gases in small proportions. The relatively high methane content of biogas makes it suitable for energy purposes; however, the quantity of methane depends on different parameters, with the feedstock being one of the most relevant. The production of biogas is based on the anaerobic digestion of organic matter, including biomass such as crop residues, livestock waste, or MSW [
52]. In this work, all biomass resources were considered for the estimation of the biogas potential. Concerning crop residues, the potential bioenergy from anaerobic digestion was determined using the methane yield of different crop wastes, following a similar procedure to Kemausuor et al. [
39]. Equation (5) shows bioenergy potential estimation from the anaerobic digestion of crop residues:
where
Ebiogas,cr(j) is the biogas energy potential at the
jth region (TJ/y);
SCRP(i,j) is the sustainable residue crop potential for the
ith crop at the
jth region (t/y);
DM(i) is the dry matter content of the
ith crop (-);
YCH4 is the methane yield of the
ith crop (m
3 CH
4/t DM); and
UCH4 is the energy density of methane in (TJ/m
3). The energy density of methane was considered to be 36 MJ/m
3 [
53]. The values for dry matter (DM) and methane yield were obtained from the literature, as shown in
Table 5.
For the potential biogas production from livestock waste, first the volume of biogas produced is calculated using Equation (6). The production of biogas depends on the quantity of total solids (TSs) present in a given kind of livestock dung [
40]. Once the volume of biogas per livestock waste is estimated, it is possible to determine the bioenergy potential through its methane content:
where
Vbiogas,lw(j) is the volume of biogas from livestock waste at the
jth region (m
3/y);
SLWP(i,j) is the sustainable livestock waste potential of the
ith waste at the
jth region (t/y);
TS(i) is the total solids of the
ith waste (-); and
Ybiogas is the biogas yield of the
ith waste (m
3/t TS).
Table 6 shows the considered values for TS and biogas yield according to the literature. Different literature was reviewed, selecting average values for the Malian context. For TS, it was selected a value of 0.2 for cattle and pigs; 0.25 for sheep, goats, horses, donkeys, and camels; and 0.29 for poultry. For biogas yield, 0.6 m
3/t TS was chosen for cattle, horses, donkeys, and camels and 0.4 for the rest.
Equation (7) shows how the bioenergy potential from the anaerobic digestion of livestock waste is estimated:
where
Ebiogas,lw(j) is the bioenergy potential produced from the anaerobic digestion of livestock waste at the
jth region (TJ/y);
Vbiogas,lw(j) is the volume of biogas from livestock waste at the
jth region (m
3/y);
cCH4(i) is the content of methane in biogas for the
ith livestock waste (%); and
UCH4 is the energy density of methane (TJ/m
3). The energy density of methane was considered to be 36 MJ/m
3 [
53]. In terms of methane content, it was considered that poultry waste has a share of 50%, while for the dung of other animals, the share is 60% [
40].
In the case of MSW, its organic biodegradable fraction was considered for the production of biogas, as this is a correct practice according to the literature [
61]. Equation (8) shows how the bioenergy potential from the anaerobic digestion of MSW is calculated:
where
Ebiogas,MSW(j) is the bioenergy potential from the anaerobic digestion of MSW at the
jth region (TJ/y);
SMSWP(j) is the sustainable MSW potential at the
jth region (t/y);
OF is the organic biodegradable fraction of MSW (%);
VS is the volatile solid (VS) content of MSW (%);
YCH4 is the methane yield of MSW (m
3/t VS); and
UCH4 is the energy density of methane (TJ/m
3).
The average values for the organic biodegradable fraction in MSW at the country level in Mali are between 18 and 21% [
46,
62]. For this study, an average value of 20% was considered. For the case of VS content, a value of 23% was chosen, with an average methane yield of 415 m
3/t VS for MSW [
63].
2.2.3. Bioethanol Potential
Bioethanol is a biofuel with a high octane number, which is the result of the fermentation of simple sugars in diverse plant biomass, such as agricultural residues. The most commonly used feedstock for the production of bioethanol is lignocellulosic biomass [
64]. In the case of MSW, a previous study showed that its use for ethanol production is less advantageous than for biogas [
65]. Similarly, Kemausuor et al. [
39] only selected MSW for biogas production and not for bioethanol in a study in Ghana. Therefore, only crop residues were considered for the production of bioethanol in the present study.
In order to produce bioethanol through fermentation, the lignocellulosic biomass has to be converted into glucose. This conversion requires a pre-treatment process, which usually involves a hydrolysis step [
66]. Following a similar procedure to Kemausuor et al. [
39], the stoichiometric yields and conversion efficiencies of the process were considered. Equation (9) shows how the bioenergy potential of bioethanol is calculated:
where
Ebioethanol(j) is the bioenergy potential from bioethanol production at the
jth region (TJ/y);
SCRP(i,j) is the sustainable crop residue potential for the
ith crop residue at the
jth region (t/y);
DM(i) is the dry matter content of the ith crop residue (-);
cglu(i) is the concentration of glucan at the
ith crop residue (g/g TS);
yhyd is the glucose yield during hydrolysis (g/g);
yeth is the ethanol yield during fermentation (g/g);
ηpre is the efficiency in the conservation of glucan in the pre-treatment (%);
ηenz is the efficiency of the enzymatic conversion of glucan (%); and
Ueth is the energy content of bioethanol (TJ/t).
The selected values of DM content per crop residue are shown in
Table 5, while the concentration of glucan per crop residue is shown in
Table 7. The selected indices used in Equation (9) were obtained from the study of Kemausuor et al. [
39] in Ghana. The glucose yield during hydrolysis was considered 1.11 g/g, while the yield of glucose converted into ethanol during fermentation was 0.51 g/g. For the efficiency values, 90% was assumed for the pre-treatment and 80% was assumed for the enzymatic conversion of glucan. The energy content of bioethanol was considered at 26 MJ/kg [
67].
2.3. Estimation of the Cooking Energy Demand of Malian Households
The demand for cooking energy in the residential sector of Mali was compared with the bioenergy potential of the country. The demand was estimated based on the share of the population without access to clean cooking fuels in the country. While the population in Mali is given in
Table 3, the share of people without access to clean cooking is 99.1% [
15]. Although firewood has been the predominant fuel for cooking, charcoal consumption has increased in the last few years, especially in urban areas. As the rate of access to clean cooking is very low in Mali, it can be assumed that almost all households consume either firewood or charcoal. The share of consumption of each fuel per region according to INSTAT [
16] is shown in
Table 8, considering only the population without access to clean cooking fuels.
When observing the type of fuel consumed for cooking in urban or rural areas, it is noticed that firewood is still predominant in rural areas, with comparatively little charcoal consumption. Therefore, it is crucial to target fuel consumption per capita in Mali according to differences between urban and rural regions. In this regard, a structured questionnaire-based survey was conducted in Bamako and a rural village with the help of local university staff to facilitate the interaction with the population. The survey in Bamako addressed 360 households, including households from all six different communes that form the city. For the small rural village, Katibougou was selected, which is located in the Koulikoro region, around 70 km northeast of Bamako. This village was selected because it represents a typical rural Malian village, and its location is optimal to perform the fieldwork. In this village, 25 (out of 100) households were surveyed. These surveys helped to estimate the population distribution per household and their size, the type of stoves and fuels used for cooking, and the quantity of fuel used and their costs.
Among all the households that were surveyed in the urban area of Bamako, 30% had up to ten family members, 33% had between eleven and twenty family members, and 37% had more than twenty members. Regarding the types of fuels used, 32% of the households relied only on charcoal, 28% relied on a combination of charcoal and firewood, and 25% relied on a combination of charcoal, firewood, and butane gas. The households using only firewood comprised 3%, and only 1% cooked without traditional cooking fuels (butane gas). In order to determine the average charcoal and firewood consumption, only households that were not using modern cooking fuels were considered, comprising 229 households in the sample. This was conducted to avoid possible bias from households using electricity or butane gas, as the consumption of firewood and charcoal depends on cooking practices. On average, the firewood consumption per capita was calculated as 0.498 kg per person per day, while for charcoal, it was 0.334 kg per person per day.
For the households surveyed in Katibougou, 28% had up to 10 family members, 48% had between eleven and twenty, and 24% had more than twenty members. Concerning the types of fuels used, most of the population relied on firewood as their main source of energy for cooking. In total, 72% of the households relied only on firewood for cooking, while 28% used a combination of firewood and charcoal. Even in this second case, all the households presented higher consumption values for firewood than for charcoal. This helped to validate the assumption that only firewood can be considered in the estimation of the cooking energy demand in rural areas. Therefore, when calculating the firewood demand per capita, only 72% of the households using firewood as the only resource were considered. On average, the firewood consumption per capita was determined to be 1.081 kg per person per day.
In the literature, previous studies have targeted the fuel consumption per capita in Mali according to differences between urban and rural regions. Morton [
68] targeted rural areas in a survey to define firewood consumption as 1.041 kg per person per day. Although fuelwood demand in rural areas has not shown an important variation in the last 20 years, in urban areas, a huge part of the population has shifted from firewood to charcoal [
16]. Therefore, most surveys conducted a long time ago reflect different cooking fuel consumption practices that exist nowadays in those regions. One recent survey regarding this topic was carried out by the French Agricultural Research Centre for International Development (CIRAD) [
69]. In their report, they estimated the firewood consumption per capita in rural areas for cooking food and heating water as 1.320 kg per person and day. For urban areas, this rate was 0.400 kg per person and day. For charcoal, only urban areas were considered, with an average consumption value of 0.203 kg per person per day.
The values from our own survey were compared with those in the literature. For firewood consumption in rural areas, these values were similar to Morton [
68], but lower than CIRAD [
69]. For firewood and charcoal consumption in urban areas, values from our own survey were slightly higher than those from the literature. In order to choose the values that better reflect the average consumption of the population, interviews with local experts were conducted. When transforming consumption per capita into consumption per household, local experts noticed that values from our own survey could better reflect average family expenditures on cooking fuels. Therefore, the consumption rates from the performed survey were preferred for the calculation of the cooking energy demand.
Knowing the population per region, its distribution per rural and urban areas, and the average consumption rates, it is possible to estimate the annual cooking fuel demand with Equations (10) and (11):
where
Cfirewood(j) is the annual firewood consumption at the
jth region (t/y);
Pncc(j) is the population with no access to clean cooking fuels at the
jth region;
rfirewood(j) is the share of people consuming firewood at the
jth region (%);
cfw,u(j) is the annual consumption of firewood in urban areas per capita at the
jth region [t/(person·y)];
cfw,r(j) is the annual consumption of firewood in rural areas per capita at the
jth region [t/(person·y)];
UP(j) is the share of the urban population at the
jth region (%); and
RP(j) is the share of the rural population at the
jth region (%). And for Equation (11):
where
Ccharcoal(j) is the annual charcoal consumption at the
jth region (t/y);
Pncc(j) is the population with no access to clean cooking fuels at the
jth region;
rcharcoal(j) is the share of people consuming charcoal at the
jth region (%); and
cch(j) is the annual consumption of firewood per capita at the
jth region [t/(person·y)].
Once the annual consumption of charcoal and firewood per region is estimated, it is possible to calculate the energy demand in two different ways. The first option is to calculate the final energy demand, which is equivalent to the product of the annual consumption and the energy content of the fuel. However, to compare different fuels, it is required to consider the different efficiencies of stoves. Therefore, in this case, the useful energy demand is calculated using Equations (12) and (13):
where
Ed,firewood(j) is the useful energy demand from firewood at the
jth region (TJ/y);
Cfirewood(j) is the annual firewood consumption at the
jth region (t/y);
Ufirewood is the energy content of firewood (TJ/t); and
ηtr,stove is the efficiency of traditional cooking stoves in Mali (%). For the energy content of firewood, its LHV was used, assuming a value of 16 MJ/kg [
70]. The efficiency of the traditional cooking stove for firewood was considered 12%, as traditional three-stone stoves are still common in the country [
71]. For Equation (13):
where
Ed,charcoal(j) is the useful energy demand from charcoal at the
jth region (TJ/y);
Ccharcoal(j) is the annual charcoal consumption at the
jth region (t/y);
Ucharcoal is the energy content of charcoal (TJ/t); and
ηch,stove is the efficiency of traditional charcoal cooking stoves in Mali (%). In this case, the LHV for charcoal was used for the energy content, assuming a value of 31.8 MJ/kg [
70]. For the efficiency of the traditional charcoal stove, a value of 19% was assumed, according to the literature [
71].
Moreover, to compare the useful energy demand with the useful energy potential in the cooking sector, the values from the bioenergy potential have to be multiplied by the efficiency of their respective stoves. In order to enhance the use of briquettes and improve the cooking conditions of the population, ICSs are considered. Different programs have been launched in Mali to increase the use of these ICSs. A value of 30% was selected, which is equivalent to an ICS compatible with briquettes that have already been implemented in areas of the country [
72]. For biogas and bioethanol stoves, an efficiency of 55% was considered [
73,
74].