Current and future economic performance of first and second generation biofuels in developing countries

Abstract

Net Present Value (NPV) and total production cost calculations aremade for first and second generation biofuels in 74 settings, covering 5 fuel output types, 8 feedstock types, 12 countries and 8 combinations of agricultural management systems between 2010 and 2030. Yields are assumed to increase due to better crop management and improved varieties. High NPVs (meaning profitable production) are calculated for cassava (up to 16,000 $/ha) and palmproduction (up to almost 7000 $/ha). But cassava can also have a negative NPV which indicates that the project investment is not without risk. The calculated NPVs for jatropha range from -900 to 2000 $/ha, while for sugarcane and soy the NPV is always positive, (2500–5000 $/ha and 200–3000 $/ha respectively) and therefore profitable. Total production costs in 2010 are estimated to vary from 5 to 45 $/GJ for 1st generation feedstocks in 2010, and from around 10–35 $/GJ in 2020, compared to 20–30 $/GJ for fossil fuels. Argentina and Malaysia are the regions with the lowest production costs for biofuel (soy and palm biodiesel for 11–15 $/GJ and 8–23 $/GJ respectively), although potential for cost reduction exists in other regions. Production costs of 2nd generation biofuels are estimated to be 17–26 $/GJ in 2020 and 14–23 $/GJ in 2030. Poplar based synfuel production in Ukraine has the lowest costs (14–17 $/GJ) and rice straw based bioethanol the highest (23–26 $/GJ) – for both the short and long term. The time between investment and benefits, as well as the size of investment and the alternative commoditymarkets, varies with the type of feedstock. The choice of feedstock therefore depends on the local agricultural system, and the preferences and means of the local farmers. Key to the competitive production of 2nd generation fuels is the optimisation of the conversion process, which dominates overall production costs (with 35–65% of total costs). Also important is the efficient organisation of supply chain logistics, especially for the low energy density feedstocks such as wheat straw – requires densification early in the chain. Key factors in the economic analysis are: labour costs and requirements, agricultural efficiency, conversion cost and biomass yields. Acquiring accurate location specific data is essential for detailed analyses.