Identification and quantification of indirect land and resource use changes – Challenges caused by expanding liquid biofuel production

Abstract

The indirect effects of bioenergy and transport biofuels with a special focus on indirect land use changes (ILUC) and indirect impacts on resource use was studied. Three case studies were examined. First, a literature review of Brazilian sugarcane ethanol production is presented. Second, it was assessed how the increase in liquid biofuel production alters the allocation of land use patterns and other sources of non-CO2 greenhouse gas emissions in Finland by using general equilibrium (CGE) modeling. Third, the influence of forest-based transportation biofuel production on the resource use in energy system and carbon stocks of forests in Finland was assessed by using partial equilibrium (PE) modeling. A variety of definitions, identification and quantification methods related to indirect effects presented in literature were compiled. However, in practice, it is often difficult to recognize the type of the effect in question, and what is the actual driver behind the change. The methods to assess the significance of ILUC were also reviewed. The monitoring data alone cannot be used to distinguish direct and indirect land use change emissions from each other, but it serve as a basis for various scenarios and assumptions on expected future development trends. To conclude, main problem in ILUC is the fact that deforestation mainly takes place in countries that are currently not committed to the binding targets for GHG emission limitations or reductions. Furthermore, ILUC is mainly promoted by increasing global demand and trade of agricultural products. Without effective policy measures there is a significant risk that the current biofuel promotion policies will increase ILUC and respective negative impacts. Both methodology to identify and quantify ILUC and management and policy approaches to mitigate negative LUC and ILUC impacts need to be further developed. System-level modeling can provide useful information on potential impacts of various policies and measures but probably too many uncertainties and inaccuracies are included in such modeling to be used to quantify the impacts in practice.