Transformations in EU biofuels markets under the Renewable Energy Directive and the implications for land use, trade and forests

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The Renewable Energy Directive of the European Union (EU-RED) established targets to be met by 2020, including a separate and uniform target for all Member States of 10% renewable energy in the transport sector. Biofuels used to achieve the EU targets must meet sustainability criteria, including restrictions on the types of land and minimum GHG reduction levels. The expansion in biofuels markets offers economic opportunities for developing countries to export to the EU while developing their own domestic markets. Imported biofuels can also have lower land use impact and GHG emissions than those produced in the EU. The current global biofuels market is dominated by the EU, Brazil and the US, with only the EU having a sustained level of imported biofuels or feedstocks. The EU market is dominated by domestic production of biodiesel, mainly from rapeseed, whereas imports are dominated especially by bioethanol from Brazil and soya biodiesel from Argentina. Least Developed Countries (LDCs) benefit from several different preferential tariffs, and are slowly beginning to export to the EU; in the case of bioethanol, Brazil dominates even with preferential tariffs, and thus the trade balance is more related to domestic demand in Brazil. For biofuels to be considered sustainable, they must be accredited by a voluntary or national scheme recognized by the European Commission or through a bilateral or multilateral agreement. The actual costs for compliance include not only direct costs of certification but also the cost of developing new information systems, administrative procedures and modifying equipment or management processes. Smaller farmers and producers will tend to have more difficulty absorbing additional costs; for reasons of equity institutional and technical support should be provided, especially in LDCs. Bilateral or multilateral agreements could provide such support and could also potentially provide direct incentives for using degraded lands and related measures to promote good governance in land use policies. The market for biofuels has thus experienced a rapid transformation, with many sustainability certification schemes vying for approval by the EU and the private sector. Technological advances, especially via second generation biofuels, have brought the biofuel industry closer to other biomass-based industries, such as pulp and paper or forestry; in the long-term, it is expected that biorefineries will produce multiple energy and non-energy products in a flexible and more efficient manner. The option of different final markets also implies increased competition for feedstock, just as agricultural biofuels created some competition with food or feed. This somehow blurs the borders between biofuels and biomass, opening options for broader and more comprehensive sustainability initiatives that can cover all biomass-based materials and products or services. Another concern arises from land use change; if biofuels demand leads directly or indirectly to deforestation or forest degradation, the goals of the EU-RED will not be met. The EU-RED provisions address direct land use change (dLUC) fairly well although some smaller forested areas are not covered and thus not protected by the definitions. High-yielding crops such as sugar cane and sugar beet tend to have lower indirect land use impacts, whereas lower-yielding first generation feedstocks such as wheat or soya can have significant land use impacts and GHG emissions. The use of a general factor for indirect Land Use Change (iLUC) rather than a crop-specific factor related to indirect land use change could thus penalise those feedstocks and regions that actually have lower impacts. The National Renewable Energy Action Plans suggest a significant level of imports of 25-37% but do not distinguish between intra-EU trade and external trade. Significant uncertainties remain in iLUC modelling, particularly in sub-national land use dynamics and the general difficulty in capturing socio-economic variables in large models, and methodological improvements are needed

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