Quantitative priority estimation model for evaluation of various non-edible plant oils as potential biodiesel feedstock

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Abstract

Energy security, fluctuating petroleum prices, resource depletion issues and global climate change have driven countries to consider adding alternative and renewable energy options to their conventional energy share. The use of biofuel such as non-edible oils-based biodiesel is as an option over conventional diesel and could be important for the development of a sustainable and eco-friendly energy resource. The aim of the present study was to select the most feasible non-edible plant oil as biodiesel feedstock by using Analytic Hierarchy Process (AHP), one of the multi-criteria decision making methods based on priority estimation model. Among various non-edible plant oils which are widely available in the South-East-Asian region, selection of the most feasible plant oil was evaluated based on seven criteria; seed oil yield, oil yield, free fatty acid (FFA) content, cold filter plugging point, oxidation stability, easiness to grow in marginal land, and availability in tropical areas. The obtained results from priority determination showed that nyamplung was the most efficient feedstock of biodiesel for the industry with the criteria weightage of 0.180. It was followed by kemiri sunan (2 nd order) having weightage of 0.164, physic nut 0.150 (3 rd order), indian beech 0.107 (4 th order), indian milkweed 0.095(5 th order), lead 0.092 (6 th order), kapok 0.076 (7 th order), cassia 0.049 (8 th order), soursop 0.043 (9 th order) and monkey pod 0.043 (10 th order). This study highlights an insight into multi-criteria decision making technique to assess the feasible plant oil for biodiesel production that could aid decision-making in the industry and policy development, particularly for the South-East-Asian region.

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Ilham, Z., & Nimme, F. H. (2019). Quantitative priority estimation model for evaluation of various non-edible plant oils as potential biodiesel feedstock. AIMS Agriculture and Food, 4(2), 303–319. https://doi.org/10.3934/AGRFOOD.2019.2.303

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