Selection of the best biodiesel blend among existing studies using AHP topsis approach

Abstract

Climate change is now a reality. The efforts to mitigate its impacts and reach the requirements of the intergovernmental panel on climate change are multidisciplinary. In order to decrease the dependance on fossil fuels, petroleum diesel in particular, biodiesel emerged as an alternative source. It is being produced from a wide variety of sources and used by blending it with petroleum diesel in different volume percentages. Some studies aimed to choose the best biodiesel type or the best blend to be used, but none tried to choose the best biodiesel blend among the best ones already studied and targeting eight different sources. Sources were chosen according to production data worldwide, and among those showing the most promising future. So, in this study a Multi Criteria Decision Making (MCDM) approach of hybrid AHP and TOPSIS is used to choose the best blend. The model targeted two main criteria properties and emissions, and eight subcriteria, assigning their weights via AHP. Properties subcriteria were assessed based on their impact on performance and emissions subcriteria based on their impact on climate change following a Life Cycle Assessment (LCA) approach. Two extra alternatives were introduced, the Best and the Worst, and data was assigned according to existing norms. TOPSIS was performed to get the score of the best blend. Results show that for an equal weight of criteria, 20% of sunflower biodiesel blend (SN20) is the best. Moreover, with sensitivity analysis, and after introducing the economic scenario, SN20 was the most robust choice of biodiesel blend that outperformed in all the criteria studied.