Increasing Access to Electricity: An Assessment of the Energy and Power Generation Potential from Biomass Waste Residues in Tanzania

Abstract

Tanzania has a high rural population, of which many rely on off-grid diesel generators to produce electricity. The focus of this paper is to assess if the waste biomass residues in Tanzania have sufficient energy potential to produce renewable electrical energy for small-scale electricity generation using off-grid diesel generators coupled with anaerobic digestion (AD) and/or gasification. The gaseous fuel produced can then be used to substitute diesel fuel used in small-scale dual fuel diesel gen-sets; thus, providing more affordable electricity whilst reducing dependency on fossil fuels. The biomass waste streams estimated are those arising from agriculture, forestry, livestock, and urban human waste. To answer this question, the energy potentials of each of these biomass waste streams are quantified, followed by further calculations to determine the electricity generation capacity per stream based on overall efficiencies of 10 and 25%. The results show that combined these waste streams have an energy potential of 385 PJ (for the base year of 2018) generated from 26,924 kilotonnes (kt). Collectively, these residues can produce at least 1.2 times the electricity generated nationally in 2018 using AD and gasification coupled with a diesel gen-set engine.

1. Introduction

Access to electricity is a globally recognised requirement to eradicate poverty and has been chosen by the United Nations as a “sustainable development goal”, which has been defined as “Goal 7: ensure access to affordable, reliable, sustainable, and modern energy for all” [1]. Hence, access to electricity is pivotal in achieving this as many basic human activities rely solely on electricity as other forms of energy cannot be used as a substitute. Such examples include lighting, refrigeration, running of household appliances, etc.

Tanzania is considered to be a “least developed country” by the OECD Development Assistance Committee (DAC) and has a large growing population of 56.32 million as recorded in 2018 [2]. Only 35.6% of the total population have access to electricity [3]; this equates to over 36 million people living in Tanzania without any access to electricity.

In 2018, Tanzania had a rural population of 66.2%, with only 18.8% of this rural population having access to electricity [4,5]. Thus, lack of access to clean modern energy supplies is most acute in rural areas. Moreover, even for those with electricity, the supplies are intermittent and unreliable [6,7].

Many African governments, including Tanzania, recognise that one of the most economical methods of increasing electrification rates (especially within rural areas) is not by network grid expansions, but by utilising renewable energy sources, specifically mini and off-grid solutions [7]. For example, Bertheau et al. [8] consider that incorporating photovoltaic (PV) and storage systems with existing diesel-based off grid systems can lead to significant cost reductions in electricity generation by this method in Tanzania. To facilitate this, favourable governmental policies, economics, and training are required to facilitate the uptake of renewable energy opportunities. In general, energy policies are quite well developed in Tanzania; however, some sectors require further development, particularly, the biomass and off-grid sectors [9]. Government policies and agencies exist in Tanzania which support rural electrification and the use of local renewable energy sources. The Rural Energy Agency (REA) was established in 2005 to focus on rural electrification. In conjunction with other organisations, the REA has promoted off-grid electrification projects as decentralised solutions ranging from 1 to 10 MW [9]. The Rural Electrification Program Prospectus developed by the REA states that for rural communities, the focus is to increase electrification by using off-grid technologies where isolated mini-grids are supplied by renewable energy sources or hybrid systems. The focus is on mini-grids associated with hydro and biomass gasifiers plants or hybrid PV systems to settlements/villages/households located 10 km or more from the main grid [9]. To date, 6 MW of solar PV has been installed in Tanzanian communities [9]. Other approved small power producer agreements for isolated mini-grids were associated with solar (2 MW), three biomass plants (5.1 MW), and 2 hydropower projects [10]. Figure 1 shows that the existing power grid connects more densely populated urban regions, whereas mini-grids are sparsely distributed across rural areas of Tanzania [11].

For those relying on electricity generated by off-grid diesel generators the fuel costs are high, so these off-grid systems have a substantially higher running cost per kWh than grid-connected systems [7,8,12]. In 2013, it was estimated that energy generated nationally from off-grid private diesel-based generation was 300 MW [9,12]. High cost and dependency on fossil fuels of off-grid diesel generators are impediments to sustainable and economic development, especially in rural areas [8]. Moreover, 80% of Tanzanians still utilise biomass (firewood, charcoal, etc.) as a source of energy [13]. Whether burnt indoors or outdoors, the smoke produced is a pollutant linked to adverse health, in particular respiratory diseases which disproportionately affect women and children [12]. Those residing in the cooler climate of the southern highland regions of Tanzania, often cook indoors, thus increasing exposure to smoke pollutants [14]. This study looks at the potential for producing electricity by utilising existing equipment commonly used for small-scale electricity generation, i.e., the “diesel generator/diesel gen-set” by substitution of the diesel fuel with gaseous fuel and so running the engine in a dual fuel mode.

The two electricity generation technologies evaluated for this purpose are gasification and anaerobic digestion (AD). The feedstock for the generation of gaseous fuel is from the processing of the waste residues streams arising from agriculture, forestry, livestock, and urban human waste. Availability of feedstock and suitability of the technologies are considered viable for this region [15,16,17] and can be coupled with existing small-scale electrification equipment. The agricultural and forestry residues can be processed using gasification technology to produce an energy-rich combustible gas called syngas (producer gas). The livestock and urban waste residues can be processed using AD to produce biogas. AD technology is more feasible for processing the selected waste streams due to their high moisture content. These gases can be fed into a dual fuel internal combustion engine or an adapted diesel internal combustion engine (ICE) as a substitute for diesel. Production of electrical energy by utilisation of biomass waste residues can provide more affordable and renewable energy due to the decrease in diesel consumption, thus decreasing dependency on fossil fuels whilst increasing access to electricity, especially in rural locations.

Biomass waste residues are underutilised and/or wasted in this region [18]. Open dumping and/or open burning are common methods of waste treatment and disposal in such developing countries [19,20]. The Food and Agricultural Organisation (FAO) estimated that in 2018 burning crop residues (from maize, rice, sugar cane, and wheat) generated 379.3 kt of CO₂ equivalent emissions in Tanzania [21]. With the majority of these arising from maize alone (approx. 85%) [21]. Using waste biomass as a direct source of “solid biofuels” for energy generation is difficult due to the variable nature of these residues in terms of size, form, moisture content, and low density, etc [22]. Pre-treatment methods such as pelleting, briquetting, and torrefaction are becoming commonly used to overcome these issues thereby increasing the concentration, density, and heating values [22]. However, this paper will focus on methods of using such waste streams in the absence of such enhancement techniques.

Utilising these waste streams for gasification [15] or using AD technology [17,20] in this manner also provides an alternative waste management solution, thereby mitigating environmental and health issues associated with the current disposal methods. A small study conducted in northern rural Tanzania indicated that some of the benefits gained by those who adopting AD technology included an increase in farm incomes as well as a reduction in greenhouse gas emissions [23], whilst providing flexibility as can be used on a small or large scale [16,24]. Furthermore, using biogas for cooking mitigates the pollutant issues associated with low-grade fuels used in inefficient cookstoves. Thus, in summary, utilising biomass waste residues as feedstock for gasification or AD to produce small-scale renewable energy has additional benefits, especially to rural communities. These include environmental, social, and economic benefits [15,17,24].

Other alternatives to produce renewable power from these gaseous fuels involve using a dedicated gas engine or modification of existing internal combustion engines. Examples of some of the modifications required involve changes in the compression- ratio, the spark ignition time, and the air/gas mixing systems [25].

Anaerobic digestion technology combined with gas or dual fuel engines is well developed and globally used for energy production [26]. Its success in “newly industralised countries” has been enhanced by government support in the form of policies, subsidies, tax incentives, and/or feed-in tariffs [16,26]. Transferring this success to Africa is deemed as potentially promising if the various barriers can be overcome. One of the initial barriers to uptake, (especially on the smaller scale of 1–500 kW), revolves around the initial investment as developers may find these less financially attractive [16,26,27].

Gasification coupled with an internal combustion engine for energy production has penetrated various countries over a range of scales, especially in India [26,28]. Small-scale gasification units (<100 kW_e) are an attractive choice of technology for producing electricity from agricultural waste residues at a reasonable level of efficiency [26]. Small-scale biomass gasification units have the benefit of lower capital costs, thus making them more economically viable. Bhattacharya [29] states that to overcome the barriers associated with this technology on a medium to large scale, using small-scale units that are locally fabricated which can be successfully operated by operators with limited technical experience is the best solution. However, issues remain in terms of the reliability of these units based upon problems associated with a lack of technical expertise as well as with gas quality. This is due to the high tar content of the syngas produced and contamination of cleaning water [26,28]. There are many advantages and disadvantages with both processes when used for small-scale power generation with ICE. For gasification, the waste biomass residues can be easily collected and stored as are a natural by-product during harvesting or processing. Whereas for biogas, the residues may be dispersed over larger areas and must be manually collected and stored appropriately for the generation of biogas. Hence gasification is better suited for larger volumes of biomass residues.

This article firstly quantifies the raw energy potential (EP) of each of these four waste streams. A similar study incorporating all four waste streams does not appear to be available in the literature for Tanzania. Lyakurwa [30] quantified the energy potential from the ten main crops grown in Tanzania and that generated from livestock waste. However, the moisture content of the crop residues was not accounted for. Lyakurwa [30] concluded that utilisation and management of both these residues in the correct manner could generate renewable electricity, thereby increasing access to electricity thus reducing fossil fuel consumption. Terrapon-Pfaff [31] calculated the energy potential arising from the biomass residues from five key commercial crops in Tanzania. This study concluded that utilising certain agricultural process residues for energy generation could secure the energy supply as well as improve the sustainability of land-use practices in Tanzania. Kusekwa [18] identified all four waste streams as having huge energy potential with the potential to be realised using gasification or AD. Furthermore, he stated that converting such biomass residues into energy provides a commercial value to the biomass of interest; however, he did not quantify the energy potential of these streams.

When utilising biomass in gasification with an internal combustion engine for power generation, the overall efficiencies are dependent on the size of the power plant [32,33]. A review of the literature based on the use of syngas in ICE by Martinez et al. [34] shows that the overall efficiencies of downdraft gasification units coupled with diesel engines (sized 12 to 20 kW) varied from 11.69 to 25.0% [34,35,36,37,38]. Losses are experienced for various reasons including the thermal efficiency of the engine; however, a further factor that impinges on the overall efficiency is the calorific value (CV) of the syngas produced. This in turn is dependent on the quality and type of the biomass feedstock and the gasification operational parameters. Dual fuel operation diesel/biogas engines (1500 RPM) used for small-scale electricity generation typically have a maximum thermal efficiency of 23% [39]. A summary of some of the overall efficiencies seen in dual fuel engines for electricity generation is summarised in

Table 1. Overall efficiency of some dual fuel systems for electricity generation.

Power (kW)	Overall Efficiency (%)	Dual Fuel Type	Reference
<10	10	Gasification/diesel	[32]
10–100	10–20	Gasification/diesel	[32]
<50	20	Gasification/diesel	[33,40,41]
25–50	>25	Gasification/diesel	[33,40,41]
100	18	Gasification/diesel	[33,40]
12–16	21–24	Gasification/diesel	[34,35]
15–20	25	Gasification/diesel	[34,37]
11.44	11.69	Gasification/diesel	[34,36]
17.5	16.6	Gasification/diesel	[34,38]
68.4	11.7–20.7	Gasification/diesel	[42]
5.5	Max 23	Biogas/diesel	[39]

.

The main objective of this paper is to quantify the energy potential of each waste stream. The base year of 2018 was chosen due to the range of full data available for this period. The energy potential available from these waste residue streams is then to be converted into actual electricity generated using either AD and/or gasification. The value of this potential can then be realised by comparing it to the actual electricity generated nationally during the same year (2018). This goes to highlight how renewable and sustainable electricity can be generated whereby reducing the dependence on fossil fuels.

2. Materials and Methods

Based on the literature reviewed, for this paper, we calculate the overall efficiency of these dual fuel systems (from biomass to net electricity) at a lower and upper end. Overall efficiency values for this range were chosen at 10 and 25% based on the values quoted in the open literature, as shown in Table 1. This range is also suitable for power generation when processing biomass waste using AD. Dual fuel operation diesel/biogas engines have a thermal efficiency of 23% [39]. Hence to derive the final “Net GWh_e” value, any transmission, and distribution (T & D) losses have then to be considered. The ‘Net GWh_e’ calculated for the agricultural, forestry, and urban human waste stream was derived using Equation (1). For the livestock waste stream, the Net GWh_e, was calculated using Equation (2) (based on microgrid losses of 10%) [43].

$$Net GWhe= Gross GWhe \times \left(\frac{overall efficiency}{100}\right) \times \left(\frac{100- \% T \& D losses}{100}\right),$$

(1)

$$Net GWhe=Gross GWhe \times \left(\frac{overall efficiency}{100}\right)\times \left(\frac{100- \% microgrid losses}{100}\right)$$

(2)

2.1. Agricultural Residues

For this calculation, values for the Residue to Product Ratio (RPR), Moisture content (MC), Fraction Availability (FA), and Lower Heating Values (LHV) were obtained for the crops of interest. The RPR is dependent on many variables which include processing and harvesting techniques, type/variety of crop, growing conditions such as the amount of water, nutrients and fertiliser used, and so forth [44]. Hence the values quoted in the open literature vary from study to study. As with other biomass assessment studies available in open literature, the more commonly used figure from literature was used. Further, not all the agricultural residues produced can be used or are available for bioenergy purposes due to competing uses such as animal bedding, fodder, fertiliser, briquette manufacture, etc. Again, literature sources quote variable figures for the % availability or a FA factor. For this study, the most common/utilised FA figure for this region was used. To calculate the energy potential from these residues, data from the FAO was collated for the base year of 2018 [45]. This base year provided the most current complete data set. The realistic electricity generation potential from all the residue streams was calculated based on an overall power potential generation efficiency of 10% and 25% as shown in Table 1 [32,33,34,35,36,37,38,39,40,41,42].

For the agricultural, forestry, and urban human waste residues, the T & D losses were also accounted for. For the base year of 2018, these losses stood at 16.9% [46]. Some crops have been excluded as either very small quantities were produced, or there is little information available on open literature for the values of RPR, MC, FA, or LHV. Agro-based woody crop residues have also been excluded such as prunings from various trees.

The data used for calculations for the energy potential arising from key agricultural, perennial plantation and oil seed crops are shown in

Table 2. Perennial plantation crop residue data.

Crop	Type	RPR	FA	MC (%)	LHV (MJ/kg)
Cashew	Husks	2.10 [31,47]	0.17 [31]	6.5 [31,47]	14.9 [31,47]
Coffee	Husks	0.25 [31,47]	1.0 [31]	15 [47,48]	12.38 [47,48]
Coconut	Husks	0.419 [47,48]	0.884 [49]	10.3 [47,48]	18.62 [47,48]
Coconut	Shells	0.12 [47,48]	0.75 [47,50,51]	8.7 [47,48]	18.09 [47,48]
Oil, Palm	Shell	0.065 [48,52]	0.625 [49]	10 [48,52]	18.83 [48,52]
Oil, Palm	Fibre	0.13 [48,52]	0.80 [50,52,53]	40 [48,52]	11.34 [48,52]
Oil, Palm	Empty bunches	0.23 [48,52]	0.614 [49]	50 [48,52]	8.16 [48,52]
Soybean	Straw	2.5 [47,48]	0.767 [49]	15 [47,48]	12.38 [47,48]
Soybean	Pods	1 [47,48]	0.767 [49]	15 [47,48]	12.38 [47,48]
Sorghum	Straw	1.25 [47,48]	0.766 [49]	15 [47,48]	12.38 [47,48]
Seed cotton	Stalk	3.743 [47,50]	0.8 [54]	12 [47,50]	13.07 [49]
Sisal	Pulp	24 [31,47,55]	1 [31]	91 * [31,47]	14.4 [31,47]
Sisal	Ball/fibre	3.55 * [30]	1 ** [31]	71 *** [55]	14.4 ** [31,47]

* Average value used. ** Assumed as per sisal pulp. *** Assumed (by difference).

,

Table 3. Agricultural crop residue data.

Crop	Type	RPR	FA	MC (%)	LHV (MJ/kg)
Cassava	Stalks	0.062 [47,48,56]	0.2 [50,57]	15 [47,48]	17.5 [47,48]
	Peelings	0.25 [56]	0.3 [56]	50 [48]	10.61 [56]
Groundnuts including shells	Shells	0.477 [47,48]	1.0 [56]	8.2 [47,48]	15.66 [47,48]
	Straw	2.3 [48,56]	0.5 [50,58,59]	15 [48]	14.4 [56]
Maize	Straw/stalk	2.0 [48,50,58]	0.7 [48,50,58]	15 [48,50,58]	19.66 [48,50,58]
	Cob	0.273 [47,48]	0.863 [49]	7.53 [47,48]	16.28 [47,48]
	Husk	0.2 [48,50,56,60]	0.6 [50,56,60]	11.11 [50,56,60]	15.56 [50,56,60]
Millet	Straw/stalk	1.75 [47,48]	0.8 [47,50]	15 [47,48]	12.39 [47,48]
Rice, paddy	Straw	1.757 [47,48]	0.684 [49]	12.71 [47,48]	16.02 [47,48]
	Husk	0.267 [47,48]	1.0 [49]	12.37 [47,48]	19.33 [47,50]
Sugar	Top and leaves	0.30 [48,61]	0.986 [49]	10 [50,61]	15.81 [48,50,61]
	Bagasse	0.29 [47,48]	0.8 [47,50]	50 [47,50,57]	18.10 [47,48]

and

Table 4. Oilseed crop residue data.

Oilseed Crop	% Oil from Seed	Waste Type	Waste (Based on % of Seed/Bean)	LHV (MJ/kg)
Sesame	50 [62]	Cake	35 * [63]	9.54 ** [64,65,66]
Sesame		Hull	15 [63,67]	18.22 [68]
Cotton	12 [54]	Cake	50 [54]	18.6 [69]
Cotton		Hull	26 [54]	18.01 [70,71]
Sunflower	40 [72]	Cake	35 [73]	15.86 [72]
Sunflower		Hull	25 [73]	19.5 [74]

* Assumed (by difference). ** Average value calculated from the lit source.

.

The energy potential of the agricultural residues (EP_residue) was calculated using the method by Bhattacharya et al. [75] as shown in Equations (3) and (4). In Equation (3), ARG is the amount of a residue generated annually on a dry basis (t yr⁻¹), and AH is the annual harvest of the crop or product (t). In Equation (4), the EP_residue represents the total energy potential of each residue (J t⁻¹), the sum of the SAF and EUF correlates to the fractional availability, whereby SAF represents the surplus availability factor, and the EUF represents the energy use factor. Both factors are dimensionless.

ARG = Σ (RPR × AH)

(3)

EP_residue = ARG × (SAF + EUF) × LHV_residue

(4)

2.2. Forestry Waste

The logging industry produces significant residues, some of which are considered as waste and are usually left to decompose. Some of the forestry residues have competing uses and are therefore unavailable for bioenergy purposes. Thus, an FA factor is applied when carrying out the potential energy calculations as quoted in the literature [48,50]. The energy potential was considered from this forestry industry using production data from the FAO, based on 1,616,000 m³ of non-coniferous roundwood and 15,000 m³ of plywood [76].

This data from the FAO is quoted in volume (solid volume), and for the EP calculations, a mass value is required. Thus, to convert, a basic density value for each type of residue stream was required. The basic density figure for the residues arising from the solid wood and plywood was calculated based on an oven-dried (od) weight over a green volume. This average basic density was calculated based on the following facts [77]:

• The most important industrial plantation species are various species of pines, cypress, eucalyptus, and teak.
• Most of the commercial wood grown (~85%) is dominated by softwoods.
• Softwood plantations cover approximately 85% of the gross plantations area. This is dominated by varies species of pines.
• The remainder (15%) will be assumed to be made of various hardwood species.

Thus, an average figure for the overall basic density was calculated using known values for the species of interest present in Tanzania [77]. These values are shown in

Table A1. Raw data of the softwood tree species for the basic density calculation.

Species Name (Common/Scientific)	OD wt/Green Volume (g/cm3)	Source(s)
Slash Pine/Pinus elliottii	0.54	[78]
Caribbean Pine/Pinus caribaea	0.51	[80]
Patula Pine/Pinus patula	0.45	[81]
Khasi Pine/Pinus kesiya	0.45	[82]
Radiata Pine/Pinus radiata	0.41	[83]
African Juniper/Juniperus procera	0.44	[84]
Mexican Cypress/Cupressus lusitanica	0.40	[85]
Average SG	0.457

and

Table A2. Raw data of the hardwood tree species for the basic density calculation.

Species Name (Common/Scientific)	OD wt/Green Volume (g/cm3)	Source(s)
Black Wattle/Acacia mearnsii	0.59	[86]
Australian Blackwood/Acacia melanoxylon	0.54	[87]
Sheaok/Casuarina spp	0.62	[97]
Spanish Cedar/Cedrela odorata	0.38	[88]
Camphor/Cinnamomum camphora	0.43	[89]
Iroko/Chlorophora regia	0.55	[79]
River Red Gum/Eucalyptus camaldulensis	0.67	[90]
Blue Gum/Eucalyptus maidenii	0.68	[91]
Rose Gum/Eucalyptus grandis	0.48	[92]
Southern Silky Oak/Grevillea robusta	0.49	[93]
Olive/Olea capensis	0.72	[94]
Idigbo/Terminalia ivorensis)	0.43	[95]
Teak/Tectona grandis	0.55	[96]
Average SG	0.548

of the Appendix A [78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97]. The average figure calculated for the basic density of solid wood was 471 kg/m³ based on a ratio of 0.85:0.15 being applied (softwood to hardwoods).

For the sawdust residues, a fixed value of 220 kg/m³ was used. This is the basic density (od/green volume) data for the sawdust residues derived from a mix of pine and hardwood [98]. LHV figures on a dry ash-free (daf) used in the calculation were obtained from literature as shown in

Table A5. Source(s) and data used for the calculation of the forestry residues.

Type	Residue	LHV Data Source	LHV Daf (MJ/kg)
Logging and Sawmilling	Solid Wood	[101,102]	18.89 20.69
Logging, Sawmilling, and Plywood	Dust	[100]	18.46
Plywood	Solid Wood	[99,103]	18.06 20.34

in the Appendix A [99,100,101,102,103]. In some cases, a range was used for the calculations due to the range of values quoted in the literature.

2.3. Energy from Animal Waste

Energy potential from the animal waste produced from five key animals was considered for this study: cattle, goats, chicken, pigs, and sheep. Collecting and processing such livestock waste via AD allows the organic content of the waste to be realised by the production of biogas.

Biogas produced can be burned directly to produce energy or can be upgraded/cleaned to remove any unwanted gases and impurities to produce biomethane.

Data regarding the number of live animals for the base year was obtained from the FAO database [104]. Data from open literature from 2010 suggests that the population of dairy cattle during this period only makes up 3.24% of the total cattle population [105], and this will be used in these calculations. According to Sajjakulnukit et al. [49], the cattle type influences the amount of manure produced daily, with dairy cattle producing three times more daily waste than beef or buffalo. The energy potential from the animal manure that is recoverable (EP_manure) was calculated using Equations (5)–(7) as shown below [75]. In Equation (5), the ABP_manure is the amount of biogas from recoverable manure (Nm³/yr), EP_manure is the energy potential of the recoverable manure (J/yr) and the LHV _biogas represents the lower heating value of biogas (J/m³). In Equation (6), DMR represents the amount of dry matter recoverable from a type of animal manure (kg DM/yr), vs. is the fraction of volatile solids in dry matter (kg vs. kg⁻¹ DM) and Y_biogas is the biogas yield (Nm³ kg⁻¹ VS). In Equation (7), the DM is the amount of dry matter (kg/head/day), NA represents the number of animals, and FR is the fraction of animal manure recoverable.

EP_manure = ABP_manure × LHV_biogas

(5)

ABP_manure = Σ (DMR × vs. × Y _biogas)

(6)

DMR = DM × NA × FR × 365

(7)

It is known that the quantity and quality of manure produced are dependent on numerous variables which include the quality and quantity of nutrition supplied to the animal, the live weight of the animal, etc. Data used in terms of manure produced per animal (kg/head/day) is shown in

Table A3. Data sources for the fresh waste calculation of animal waste.

Animal	Fresh Waste (kg/Head/Day)	Source
Cattle–Beef	5	[49]
Cattle–Dairy	15	[49]
Chicken	0.03	[49]
Pigs 1	1.2	[49]
Sheep	1	[106]
Goat	1	[106]

¹ Data based on a native swine.

in the Appendix A. It was assumed that the beef cattle produced a value of 5, the dairy cattle 15, chickens 0.03, and the pigs/native swine 1.2 [49]. The data for the sheep was assumed to be the same as that of a goat, which was 1 kg/head/day [106].

Data used for the volatile solid/dry matter ratio (VS/DM), for all the animals, was assumed, as quoted by Bhattacharya et al. [107]. The remaining data used to calculate the EP_manure from the cattle waste, was as quoted by Sajjakulnukit et al. [49]. For the chicken and pig calculations, all remaining data used (FA, % DM, and the biogas yield) was from Sajjakulnukit et al. [49] and Bhattacharya et al. [107]. For the sheep and goats, the FA used was as quoted by Simonyan and Fasina [50], the DM content as per Ozcan et al. [108], and the biogas yield data from Bhattacharya et al. [107]. All the data used to calculate the EP_manure from livestock waste is summarised in Table A3 and

Table A4. Source(s) and data used for the calculation of the EP from livestock waste.

Animal	FA	(%) DM	VS/DM Ratio	Biogas Yield (m3/kg VS)
Cattle–Beef	0.5 [49]	17.44 [49]	0.934 [107]	0.307 [49]
Cattle–Dairy	0.8 [49]	17.44 [49]	0.934 [107]	0.307 [49]
Chicken	0.8 [49]	33.99 [49]	0.465 [107]	0.18 [107]
Pigs	0.8 [49]	35.22 [49]	0.893 [107]	0.217 [49]
Sheep	0.3 [50]	25 [108]	0.912 [107]	0.31 [107]
Goat	0.4 [50]	25 [108]	0.598 [107]	0.31 [107]

in the Appendix A. It is assumed that the LHV of the biogas produced from both livestock and human waste is 20 MJ/m³, as used in various other studies for the same purpose [109,110,111]. It is proposed that the electricity produced from the biogas will be fed into a local mini-grid. Electrical losses do occur within mini-grids and are dependent on the size and the type of the grid, as well as the age of the equipment. Hirsch et al. [43] states that these losses can vary from 5 to 15% depending on the number of conversions between AC and DC modes. For this calculation, an average loss figure of 10% will be utilised.

2.4. Urban Human Waste

The energy potential from human waste was calculated based on the urban population figures for 2018 [112]. The following assumptions were used for the calculations: an average of dry matter of 0.090 (kg/head/day) [50,107], a VS/DM ratio of 0.667, an average biogas yield of 0.20 m³/kg vs. [107] and a net CV of 20 MJ/m³. Again, electrical T & D losses will be factored in [46], as it will be assumed that the biogas generated from towns and cities will be fed into the national grid.

3. Results

3.1. Agricultural Residues

The annual energy potential from the crops is summarised in Figure 2 and

Table 5. The energy potential arising from waste agricultural residues.

Crop	Amount (t)	Residue	Dry Residue (t)	EPresidue (PJ)	% of Total EPresidue
Cashew nuts, inc shell	313,826	Husks	104,753.5	1.56	0.46
Cassava	8,372,217	Stalks	88,243.2	1.54	1.45
		Peelings	313,958.1	3.33
Coconuts	436,800	Husks	145,124.7	2.70	0.99
		Shells	35,891.9	0.65
Coffee, green	43,193	Husks	9178.5	0.114	0.034
Groundnuts, inc shell	670,000	Shells	293,383.6	4.59	4.16
		Straw	654,925.0	9.43
Maize	6,273,151	Straw/Stalk	7,465,049.7	146.76	53.26
		Cob	1,366,658.6	22.25
		Husks	669,144.5	10.41
Millet	316,194	Straw	376,270.9	4.66	1.38
Oil, palm fruit	75,086	Shells	2745.3	0.052	0.044
		Fibre	4685.4	0.053
		EB	5301.8	0.043
Rice, paddy	3,414,815	Straw	3,582,280.1	57.39	21.62
		Husks	798,971.4	15.44
Seed cotton	269,393	Stalks	709,870.0	9.28	3.87
		* Cake	134,696.5	2.51
		* Hull/husks	70,042.2	1.26
Sesame seed	640,000	* Cake	224,000	2.14	1.15
		* Hull	96,000	1.75
Sisal	32,460	Pulp	70,113.6	1.01	0.44
		Ball/fibre	33,417.6	0.48
Sorghum	672,235	straw	547,115.3	6.77	2.01
Soybeans	21,321	Straw	34,750.6	0.43	0.18
		Pods	13,900.2	0.17
Sugar cane	3,117,812	Tops/leaves	830,023.9	13.12	5.84
		Bagasse	361,666.2	6.55
Sunflower seed	1,000,000	* Cake	350,000	5.55	3.09
		* Hull	250,000	4.88
		TOTAL	19,642,162.2	336.9

* Residues arising from oilseed crops.

. Figure 2 shows the % energy potential available from each crop type. This is calculated as a % from the EP_residue for each crop (PJ) over the sum/total EP_residue available from all the agricultural crop residues.

Table 6. Summary of the electrical generation potential using agricultural residues.

Data	GWh Equivalent
Gross GWhe at 100% efficiency	93,580
For an overall efficiency of 10% before any losses	9358
Net GWhe (for an overall efficiency of 10%) after T&D losses	7775
For an overall efficiency of 25% before any losses	23,395
Net GWhe (for an overall efficiency of 25%) after T&D losses	19,438

National electricity generated in 2018 = 7230 GWh [46].

summarises the electrical generation potentials from the agricultural residue waste stream. These are expressed as Gross GWh_e and Net GWh_e before and after T & D losses, at overall efficiencies of 10% and 25%.

3.2. Forestry Residues

The energy potential of the forestry residues has been calculated based on literature LHVs. In some cases where literature LHV’s vary, a high and low energy potential value (PJ¹ and PJ²) has been calculated to reflect this variation, as shown in

Table 7. The EP available from the forestry residues in Tanzania.

Type	Residue	% Availability	Residues		Energy Potential
			m3	OD Mass (t)	PJ (1)	PJ (2)
Logging	Solid Wood	40	646,400	304,454	5.75	6.30
	Dust	20	323,200	71,104	1.31	1.31
Sawmilling	Solid Wood	38	614,080	289,232	5.46	5.98
	Dust	12	193,920	42,662	0.79	0.79
Plywood	Solid Wood	45	6750	3179	0.06	0.06
	Dust	5	750	165	0.003	0.003
Total			1,785,100	710,797	13.4	14.4

PJ ⁽¹⁾ and PJ ⁽²⁾ calculated values reflect the different literature values of the LHV used (see Table A5 in the Appendix A).

and

Table 8. Summary of the electrical generation potential available from forestry residues.

Data	GWh Equivalent Based on PJ (1)	GWh Equivalent Based on PJ (2)
Gross (100% efficiency)	3715	4014
Overall efficiency of 10% before any losses	372	401
Net GWhe (for an overall efficiency of 10%) after T&D losses	309	334
Overall efficiency of 25% before any losses	929	1004
Net GWhe (for an overall efficiency of 25%) after T&D losses	772	834

National electricity generated in 2018 = 7230 GWh [46]. PJ ⁽¹⁾ and PJ ⁽²⁾ calculated values reflect the different literature values of the LHV used (see Table A5 in the Appendix A).

.

Table 8 summarises the electrical generation potentials from the forestry residues. These are expressed as Gross GWh_e and Net GWh_e before and after T & D losses, at overall efficiencies of 10 and 25%.

3.3. Livestock Residues

The ABP_manure and the EP_manure were calculated from the livestock data as shown in

Table 9. The energy potential (EP) available from the livestock residues in Tanzania.

Type of Animal	NA (Head)	FA	DM (%)	DMR (kt DM/y)	VS/DM	Biogas Yield (m3/kg VS)	ABPManure (Mm3/y)	EPmanure (PJ)
Cattle: Beef	26,398,742	0.5	17.44	4201.1	0.934	0.307	1204.6	24.09
Cattle: Dairy	883,960	0.8	17.44	675.2	0.934	0.307	193.6	3.87
Chicken	37,992,000	0.8	33.99	113.1	0.465	0.18	9.5	0.19
Pigs/swine	520,853	0.8	35.22	64.3	0.893	0.217	12.5	0.25
Sheep	7,945,775	0.3	25.0	217.5	0.912	0.31	61.5	1.23
Goat	18,497,912	0.4	25.0	675.2	0.598	0.31	125.2	2.50
TOTAL				5946.4			1607	32.1

and

Table 10. Summary of the electrical generation potential from livestock residues.

Data	GWh Equivalent
Gross GWhe at 100% efficiency	8927
For an overall efficiency of 10% before microgrid losses	893
Net GWhe (for an overall efficiency of 10%) after microgrid losses	803
For an overall efficiency of 25% before microgrid losses	2232
Net GWhe (for an overall efficiency of 25%) after microgrid losses	2008

National electricity generated in 2018 = 7230 GWh [46].

and Figure 3. Figure 3 shows the % energy potential available from each animal type. This is calculated as a % from the EP_manure in PJ generated from the waste of each animal over the sum/total EP_manure available from all the livestock waste residues.

Table 10 summarises the electrical generation potentials from the livestock residues. These are expressed as Gross GWh_e and Net GWh_e before and after microgrid losses, at overall efficiencies of 10 and 25%.

3.4. Urban Human Residues

The biogas yield and the energy potential available from the urban human waste residues are shown in

Table 11. The biogas potential and EP available from urban human waste in Tanzania.

Item	Value
Urban population in 2018 [112]	19,022,085
Average dry matter production, (kg/head/day) [50,107]	0.090
Total dry matter/year, (tonnes)	624,875.5
Total Biogas produced (M m3 in 2018)	83.4
LHV of biogas (MJ/m3)	20
Biogas yield, (Biogas m3/kg VS) [107]	0.20
Total EP (PJ) in 2018	1.67

.

Table 12. Summary of the electrical generation potential from urban human waste.

Data	GWh Equivalent
Gross—at 100% efficiency	463
For an overall efficiency of 10% before any losses	46
Net GWhe (for an overall efficiency of 10%) after T&D losses	38
For an overall efficiency of 25% before any losses	116
Net GWhe (for an overall efficiency of 25%) after T&D losses	96

National electricity generated in 2018 = 7230 GWh [46].

summarises the electrical generation potentials from the urban human waste stream. These are expressed as Gross GWh_e and Net GWh_e before and after T & D losses, at overall efficiencies of 10 and 25%.

4. Discussion

4.1. Agricultural Residues

The total solid biomass residue from this stream produced in 2018 equates to approximately 19,642 kt, which had a total calculated energy potential of 337 PJ. The residues from this stream can produce between 7775 and 19,438 GWh of electricity after incorporating T & D losses. A range is quoted as this is based on overall efficiencies of 10 and 25%. This stream is theoretically capable of generating 1.1 to 2.7 times equivalent of the annual electricity produced in 2018. This is reflective of the large agricultural sector present in this country. Some of these waste residues have alternate uses, including use in energy cogeneration from the sugar and sisal production [55]. However, overall a large amount remains underutilised [18,55]. It is recognised that in Tanzania, the potential for utilising such residues to produce more sustainable power/electricity generation is high but underexploited [12]. Furthermore, low grass productivity combined with high fertiliser costs produce challenging conditions for farmers in this country, hence using crop residues for farming purposes such as fodder or fertiliser remains a priority for many farmers [55]. Hence, the decision to utilise waste agricultural residues for producing small-scale electricity versus the competing uses has to be considered locally, on a case by case basis with careful consideration based on the type of crop residue.

Due to the high volumes of agricultural residues available, theoretically, these residues could be utilised for large-scale energy generation; however, there are issues associated with the cost of transportation from the agricultural centres to the large power generation plants. The cost issues lie with the low bulk density residues of these residues. Furthermore, the availability of these crop residues is seasonal; hence there will be periods when the supply is intermittent. Utilising these residues locally as an energy source for small- scale energy generation avoids these issues mentioned. For the small-scale applications, as considered in this paper, it is feasible to utilise/store these residues in bulk near the point of consumption. Ideally, such residues should be stored close to the gasification unit coupled with an ICE/diesel generator (which is linked to either the national grid or a mini-grid).

4.2. Forestry Residues

The mean energy potential of these forestry residues is calculated at 13.9 PJ. The residues from this stream can produce on average between 322 and 803 GWh of electricity after incorporating T & D losses, as it is assumed this energy will be fed into the national/mini-grid. The energy potential from this stream is relatively small; it is only capable of generating at best, 11% of the annual electricity produced in 2018.

4.3. Livestock Residues

This data shows that there is significant energy potential from the collection of animal manure to produce biogas, equivalent to 32.1 PJ. The residues from this stream can produce between 803 to 2008 GWh of electricity, after incorporating microgrid T & D losses. A range is quoted as this has been calculated on overall efficiencies of 10 and 25%. This is equivalent to generating approximately 11 to 28% of the annual electricity produced in 2018. The utilisation of this technology is highly feasible in this country when utilising this waste stream as most of the livestock/animals are concentrated in certain regions of the country in the arid/semi-arid regions. For example, a study by Mwakaje, [113] in southwest Tanzania revealed that there is potential to develop biogas technology in this region due to its high population density (high demand) with a large number of indoor-fed cattle and/or pigs. The constraints identified by Mwkaje [113] were cost/affordability and water scarcity, to a lesser degree, lack of technical support. Again, Rupf et al. [17] echoed this by reiterating that various factors need consideration for the usage of biodigesters in Africa. These include feedstock availability, water supply, energy demand, local materials and labour, and the level of commitment to operate and maintain the biodigester effectively. Other factors that may affect uptake are the local culture and the location [114]. Roopnarain [27] identified further barriers as cost implications, lack of communication, lack of ownership, and the negative image of the technology caused by past failures.

In addition, the livestock numbers may vary from household to household and over an annual period [114]. The benefits of establishing communal biogas digesters include the reduction or shared cost within householders, as well as providing a more continuous feedstock [114]. The biogas produced could be piped/distributed within small communities to produce electricity using dual fuel engines. Existing diesel/spark gen set engines can be converted to run on dual fuel mode to utilise this biogas.

4.4. Urban Human Waste Residues

Tanzania has a biomass energy potential that can be generating by processing urban human waste using AD which can be estimated as 1.67 PJ of energy. The residues from this stream can produce between 38 and 96 GWh of electricity depending on the overall efficiency of the processes/conversions involved after incorporating mini-grid losses. The energy potential from this stream is very small due to the low level of urbanisation in 2018 whereby approximately 66.2% of the total Tanzanian population lived in rural regions [4]. Hence this waste stream can generate at best, only 1% of the annual electricity produced in 2018 (after accounting for T & D losses).

4.5. The Combined Energy Potential of All Four Waste Streams

Figure 4 shows the raw EP of each waste stream. Approximately 87.6% of all the raw EP arises solely from agricultural residues.

Table 13. A summary of the biomass assessment results for Tanzania.

		GWhe for Overall Efficiencies of:
Residue:	Gross GWhe at 100% Efficiency	10% before Losses	25% before Losses	10% after Losses	25% after Losses
Agricultural	93,580	9358	23,395	7775	19,438
Forestry	* 3865	* 387	* 966	* 322	* 803
Livestock	8927	893	2232	803	2008
Urban Human	463	46	116	38	96
TOTAL	106,835	10,684	26,709	8938	22,345
% of the electricity generation capacity possible (2018)	1478	148	369	124	309

* Average value used. Electricity generated in 2018 = 7230 GWh [46].

shows that when all the residues are combined for 2018, Tanzania has a huge net energy-generating potential. The net electricity generation potential accounts for the overall efficiency of the technologies, and any transmission/distribution losses which may occur due to the national or a microgrid. Calculations show that the net electricity generation potential from these combined residues is equivalent to generating approximately 1.2 to 3.1 times of the total electrical energy generated in 2018. However, one should take into consideration that these residues have seasonal availability hence to ensure a continuous supply, the usage of the residues will require some management.

Utilising AD for livestock and urban human waste slurries is technically feasible; however, there are many barriers to overcome to make this a reality in many rural locations. The barriers include the large, fixed capital costs required for set up, and lack of technical expertise [16,27]. Governmental subsidies and interventions are required to provide training, and this needs to be promoted by favourable governmental policies. This technology becomes more feasible in a centralised village location scenario, whereby the costs and feedstocks can be shared. This also enables a more continuous supply of biogas to be generated which can be transported via a network to a larger number of users.

5. Conclusions

The agricultural waste residues have the highest estimated energy potential followed by the livestock residues. The energy potential from the other two waste streams is much smaller due to a small forestry/logging industry combined with a low urban population. However, overall, combined these residues have a huge energy potential of 385 PJ which is generated from approximately 26,924 kilotonnes of dry waste. This study shows that renewable and sustainable energy can be generated from these residues as the net electricity generation potential from these combined residues (after accounting for T & D losses) is equal to approximately 1.2 to 3.1 times of the total electrical energy generated nationally in 2018. This can in turn lead to a reduction in the usage and dependency on fossil fuels, whilst making access to electricity more affordable. However, it is more economical and practical to utilise these residues on a village scale using small gasifiers near the point of production/storage. This entails the residues being stored near the gasification unit coupled with an ICE/diesel generator (linked to either the national grid or a mini-grid). The gas produced can be fed into the air intake of an existing ICE used to produce small-scale electricity.

Utilising these waste residues offers further advantages which benefit the environment as the usual disposal/waste management techniques associated with these waste streams are avoided. To utilise these waste streams using the technologies discussed in this paper, it is very important to match supply with demand whilst considering the seasonal and regional availability of the feedstock. Further work is required to determine which communities would benefit from which technology based on the local availability/supply logistics of these waste residue streams, any competing uses, the population density, and any government incentives which can influence the uptake in this region.