Biodiesel has been emerging as the main alternative to fossil fuels in transportation in Europe. According the OECD-FAO outlook 2011-2020, the biodiesel use in the European Union (EU) will increase by almost 85% over the projection period and 75% of the global production is expected to come from vegetable oil. However, questions have been raised concerning the sustainability of biofuels, namely related with the expansion of feedstock cultivation to satisfy increasing production levels. A study conducted in 2009-2012 by the EU found an increase on greenhouse gas (GHG) emissions due to conversion of agricultural land for planting first-generation biofuel crops (which are produced from food crops). For this reason, on October 17th 2012, the EU published a proposal to reduce the food-based fuels required by the Renewable Energy Directive for the transportation energy mix by 2020. In this context, waste oils (WO) have been gaining prominence as an alternative feedstock for biodiesel production due to is potential to improve the environmental performance of biodiesel compared with energy crops feedstock. Another benefit of using WO is the potential cost reduction of biodiesel production. According the US Energy Information Administration, 70-95 % of the biodiesel costs are associated to feedstock cultivation. However, WO presents high uncertainty and variation (U&V) in chemical characteristics due to the high variability of provenance. This can influence biodiesel quality and may result in significant market limitations. Another limitation is the low availability of collected WO. A strategy to deal with these issues is to blend WO with virgin oils, such as soybean, rapeseed, and palm oil. Mathematical programming blending models were applied to manage feedstock quality variation in material recycling processes and in the blending of virgin oil feedstock to produce biodiesel. The main aim of this research is to develop a mathematical programming life-cycle model to optimize the blend of virgin and waste oils for biodiesel production. The following questions are raised: How to address the U&V of the chemical properties of WO to the biodiesel quality? How to develop a feedstock blending model for virgin oils and WO? What would be the main environmental and economic benefits and drawbacks? What are optimal feedstock blendings for biodiesel production in compliance with technical standards and reduced environmental impacts? To answer these questions, multiobjective optimization will be applied in order to obtain optimal blends that minimize production costs and environmental impacts in a life-cycle perspective, incorporating uncertainty and variability. The outcome of this research can be used by biodiesel producers, policymakers, as well as consumers and also as support information for biodiesel certification schemes.
University of Coimbra- MIT Portugal Programe
Prof Fausto Freire and Prof Luis Dias