In this study, four different scenarios were developed to assess the impacts on energy demand and emissions: baseline (fossil diesel), B10, B20, and electric vehicle scenarios. These scenarios, depicted in Figure 1; Table 1, enabled the investigation of the energy and environmental impacts of various biodiesel blends and electricity as alternatives to petroleum diesel for use in internal combustion engines (ICEs) over 30 years. Current diesel consumption demand and emissions trends in Uganda were compared with projected trends for these scenarios. The demand for B10 and B20 was projected using the LEAP software based on Uganda’s current and future transportation fuel requirements. For B10, the biodiesel demand was calculated as 10% of the total diesel consumption, while for B20, it was 20%. The annual diesel consumption of Uganda is 1 billion liters. Therefore the annual biodiesel demand for B10 would be 100 million liters, and for B20, it would be 200 million liters (MEMD, 2022).

The trade-off between fossil diesel and biodiesel involves considerations of cost, energy density, and environmental impact. Biodiesel has a lower energy content (around 10% less) than fossil diesel, which may slightly increase the volume of fuel needed (Knothe et al., 2010). However, biodiesel’s renewable nature and potential for reducing CO₂ emissions make it a favourable alternative (Hill et al., 2006). The shift to B10 and B20 can reduce Uganda’s reliance on imported fossil diesel, thereby improving energy security and reducing the trade deficit (Popp et al., 2014).

The CO₂ emissions from biodiesel production depend on the feedstock used. Life Cycle Assessment (LCA) of castor, croton, and jatropha reveals varying impacts on emissions. Castor produces moderate CO₂ emissions due to its higher oil yield per hectare and lower fertiliser requirement (Roy et al., 2016). Croton yields low CO₂ emissions because it can grow on marginal lands with minimal inputs (Nyamai et al., 2015). Jatropha generates the lowest CO₂ emissions among the three, attributed to its drought resistance and high oil content (Achten et al., 2010). Based on these analyses, jatropha appears to be the most sustainable feedstock for minimising CO₂ emissions in biodiesel production.

Electric vehicles (EVs) use electric motors, which are fundamentally different from the internal combustion engines (ICEs) found in conventional vehicles. This difference has significant implications for energy efficiency, emissions, and overall vehicle performance. Electric motors are considerably more efficient than ICEs, which can convert over 85% of electrical energy from the battery to power the wheels. In contrast, ICEs only convert about 20%–30% of the energy from fuel to power the vehicle (DOE and EPA, 2022). This higher efficiency in electric motors results in reduced energy demand for EVs compared to vehicles with ICEs. Additionally, EVs produce zero tailpipe emissions, whereas ICEs emit CO₂ and other pollutants during fuel combustion, contributing to greenhouse gas emissions and air pollution (IEA, 2021). Therefore, The use of EVs presents a significant advantage in reducing emissions and improving air quality.

Moreover, electric motors have fewer moving parts than ICEs, leading to lower maintenance requirements and costs. EVs also provide instant torque, which results in quick acceleration and a smoother driving experience (Ehsani et al., 2018). The LEAP software models these differences by incorporating the higher energy efficiency of electric motors and the absence of tailpipe emissions in the EV scenario. Consequently, the projected energy demand and emissions reductions in the EV scenario are based on these inherent advantages of electric motors over ICEs.

In a related earlier study, Tibesigwa et al. (2021) evaluated CO2 emissions from biodiesel production across the entire lifecycle: plant farming, oil extraction, biodiesel conversion, and distribution and use. The study compared these stages to petroleum diesel, focusing on feedstocks like castor, croton, and jatropha, with jatropha resulting in lower emissions due to minimal input requirements. Differences in efficiency and emissions were noted between oil extraction methods, such as mechanical pressing and chemical solvent extraction. The energy-intensive transesterification process significantly contributed to the carbon footprint, especially for oils with higher free fatty acid content. Distribution and use included emissions from transportation and combustion, which were lower for biodiesel due to its renewable feedstock. The life cycle assessment (LCA), adhering to ISO 14040 standards and using Umberto LCA software, demonstrated the environmental benefits of biodiesel blends compared to fossil diesel.

Under this category, the modes of transport considered included road, rail, and water. Vehicle types for road transport were private cars, buses, taxis, rail transport trains, and ferries for water transport. Road transport is the dominant mode of transport in Uganda, with other modes like air, water, and rail still growing with limited utilisation (Atlassian/WFP, 2013). Therefore, in this analysis, road transport was assumed to comprise 96% of Uganda’s transport, with road and water transport taking 2% each. A summary of the percentage share of vehicle km under the passenger transport category is shown in Table 3.

Table 4 summarises the vehicle kilometerskilometerskilometers for freight transport (small, medium, and large trucks) for the base year 2019 (MoWT, 2022). It also contains data used for modeling the four different energy scenarios. Small trucks account for about half of the freight vehicle kilometers, with large and medium trucks taking the other half.

Three liquid fuels were considered when developing the different scenarios modeled by the LEAP software. These included B10, B20, and petroleum diesel. Information regarding the chemical properties of these biodiesel blends was not available in the LEAP software. These were obtained from literature sources as listed in Table 5.

GHG emissions for the base year were calculated using emission factors generated from the Technology and Environmental Database (TED), which is an integral tool in the LEAP software used to calculate environmental loadings of different energy scenarios. Emissions of different pollutants are computed as the product of fuel combustion and an emission factor, considering the corresponding characterization factors following the IPCC methodology. A summary of the non-biogenic emission factors for all the emission categories is shown in Table 6.

The energy demand estimate captures all non-biogenic emissions. Non-biogenic emissions are emissions from fuels of non-biological origin and include emissions from fossil fuels used in transport and other sectors such as industry and agriculture. The analysis uses a simple accounting methodology in which the energy transformation or conversion estimate captures the non-biogenic emissions from using fossil fuels to generate electricity, using the generation fuel sources of the individual generation plants. Biogenic emissions, which are emissions from biofuels (e.g., burning wood and charcoal), were not calculated in this study.

Figure 6 compares the projected energy demand for the passenger transport category, including the rail, road, and water transport modes for 2019 to 2050. Results show that energy demand will grow by 171%, 180%, and 159% for the rail, road, and water modes, respectively, by 2050. Under this scenario, total energy demand for the passenger transport category is forecasted to grow from 8.42 million Gigajoules in 2019 to 22.74 million Gigajoules in 2050. This growth is attributed to the projected increase in population and GDP per capita (World Bank, 2021), resulting from the anticipated demand for transport mobility. The highest growth (180%) is observed under the road transport mode. This validates the assertion that road Transport will continue to be the dominant mode in Uganda for passenger transportation for years to come as a result of the projected rapid urban population increase, the national economic growth, and rapid traffic increase over the next few decades.

Figure 7 shows the energy demand from 2019 to 2050 under the freight category, where small, medium, and large trucks are used to carry cargo. The total energy demand under the freight category is forecasted to rise by 68.38% (from 35.29 million GJ to 59.42 million GJ). The rise in freight volumes can be attributed to the projected population growth rate of 3% from 2023 and the corresponding projected economic growth of 4.2% per year (World Bank, 2021), which will lead to an eventual increase in demand for local and regional transportation of shipping goods. This validates the reported predicted growth in freight volumes of 560% in Uganda from 2019 to 2040 (MoWT, 2022).

Figure 8 compares the baseline, B10, and B20 scenarios under the passenger transportation category for 2019 to 2050. The projected total energy demand for B10 and B20 is lower than that for the baseline scenario by 13% and 38%, respectively. This is attributed to an increase in the proportion of biodiesel in the diesel blend from 2031 to 2050, which will result in a corresponding reduction in diesel demand (Wattana et al., 2022). For the freight transport category, as shown in Figure 9, the projected total energy demand for B10 and B20 is lower than that for the baseline scenario by 12% and 34%, respectively. These values are higher than those for passenger transport, which can be attributed to the difference in energy consumption between passenger and freight vehicles. Freight vehicles have lower fuel economy than passenger vehicles and thus require larger fuel volumes to cover similar distances (ATC and EPHC, 2008).

The electric scenario evaluates the impact of adopting electric vehicles (EVs) in Uganda’s transport sector, focusing primarily on the passenger transportation category. The assumptions and energy demand projections are based on the following:

The electric scenario assumes a significant penetration of electric vehicles in the passenger transport category, with the replacement of 50% of diesel-powered passenger vehicles by purely electric vehicles from 2031 to 2050. The electricity for these EVs is assumed to come from Uganda’s grid, which is projected to increasingly rely on renewable energy sources, such as hydropower, solar, and wind, as part of the country’s efforts to diversify its energy mix and reduce reliance on fossil fuels (MEMD, 2022). In the electric scenario, the freight utility continues to use 100% fossil diesel. This is because the current infrastructure and technology for electric freight vehicles are not yet viable in Uganda for the projected period. Thus, no electricity is used for freight transport in this scenario.

Figure 10 compares the baseline, B10, B20, and electric vehicle scenarios under the passenger transportation category for 2019 to 2050. The projected total energy demand for B10, B20, and electric scenarios is lower than that for the baseline scenario by 13%, 38%, and 80%, respectively. The increase in biodiesel proportion in these blends results in reduced diesel demand from 2031 to 2050.

For the freight transport category, as shown in Figure 11, the projected total energy demand for B10, B20, and electric scenarios are lower than that for the baseline scenario by 12%, 34%, and 76%, respectively. This is attributed to the fact that freight transport vehicles have a lower fuel economy than passenger transport vehicles (ATC and EPHC, 2008). However, it should be noted that these reductions in energy demand for the electric scenario apply only to passenger vehicles. The continued use of fossil diesel in freight transport highlights the need for further technological advancements and infrastructure development to support electric freight vehicles in the future.

The electric scenario’s projected total energy demand for each transportation category is the lowest since electric vehicles can achieve 65% higher energy conversion efficiency than fossil fuel-powered vehicles, which leads to a corresponding reduction in energy demand (DoE and EPA, 2022). Source of Electricity for EVs: The electricity required for charging passenger EVs in this scenario is assumed to be sourced from Uganda’s national grid. As Uganda continues to invest in renewable energy projects, the grid’s reliance on hydropower, solar, and wind energy is expected to increase, reducing the carbon footprint of electricity generation (MEMD, 2022).

Estimates of greenhouse gas emissions in units of CO₂ equivalent are presented in Figure 12 for all scenarios. Compared to the baseline scenario, B10, B20, and Electric, cumulative greenhouse gas emissions will decrease by 8.38%, 25.13%, and 38.35%, respectively, in the years 2030–2050. The reduction in CO₂ emissions can be attributed to the decrease in diesel demand due to the decreased proportion of diesel in the transportation fuel mix. Results for B10 and B20 agree with previous findings by (Raheman et al., 2013), who found reductions in GHG emissions by 10.97% and 21.16%, respectively, relative to fossil diesel when used in a high-speed internal combustion engine. GHG emissions were the lowest for the electric vehicle scenario. These findings agree with (Kosai et al., 2022), who obtained a similar trend for GHG emissions for electric vehicles versus biodiesel ICE vehicles. Due to the expected zero CO₂ emissions for fully electric cars, a 100% reduction in emissions during the running of the vehicles would have been expected relative to fossil diesel. However, as indicated during scenario development, a 100% shift to the use of electric vehicles in place of diesel vehicles will not be tenable under the electric scenario.

As shown in Figure 13, passenger and freight transport categories are expected to have their CO₂ emissions increase substantially from 2019 to 2050 if the status quo that depends on fossil diesel is maintained. The projected GDP per capita and population growth for Uganda (World Bank, 2021) are major contributing factors to the increase in transport mobility and the resulting emissions. Therefore, the use of cleaner fuels is critical in the reduction of transport-related emissions. Very important too is for vehicle designs to be made more energy-efficient.

CO₂ emissions from road transport for the baseline scenario, as illustrated by Figure 14, are expected to increase at a much faster rate than for rail and water for 2019–2050. This is collaborated by the fact that over 95% of passengers and goods are transported on the road. Efforts by the Government of Uganda include plans to strengthen multimodal transport, Bus-Rapid Train (BRT) system, and non-motorized transport (MoWT, 2022).