Journal
RENEWABLE & SUSTAINABLE ENERGY REVIEWS
Volume 63, Issue -, Pages 62-92Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.rser.2016.05.035
Keywords
Biodiesel; Edible vegetable oils; Non-edible vegetable oils; Transesterification; Specifications; Prediction models
Funding
- University of Malaya High Impact Research Grant from Ministry of Higher Education Malaysia [HIR-MOHE- D000038-16001]
- University of Malaya High Impact Research Grant from University of Malaya Bright Spark Unit
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In recent decades, the concern over depletion of the world's petroleum reserves and environmental pollution has increased the demand to develop a renewable and environmental friendly fuel. Biodiesel, which mainly consists of Fatty Acid Methyl Esters (FAME) is one of the best substitutes for diesel fuel. Currently, vegetable oils, edible or non-edible, are the main resources of biodiesel. This review aims at providing comprehensive information and analyzes on biodiesel produced from edible and non-edible vegetable oils, their composition and specifications. Accordingly, the Fatty Acid (FA) profiles of 28 edible vegetable oils and 40 non-edible vegetable oils were collected. Their main specifications including sulfur content, density, viscosity, flash point, cloud point, pour point, cold filter plugging point, cetane number, iodine number, heating value, acid value and carbon residual before and after transesterification (vegetable oil and biodiesel, respectively) were analyzed in detail. Many researchers have developed prediction models to quantify biodiesel specifications to optimize its manufacturing and obtain biodiesel with the best specifications. Three factors that are especially influential are the fatty acids profiles, the degree of unsaturation within the FA structures and molecular weight. Accordingly, many models have been constructed on these features. There are also models that quantify the relationship between the biodiesel specifications and its thermodynamic properties or other specifications. Accordingly, the second part of this work was conducted on the existing prediction models. All the models were discussed along with their deviation in prediction. (C) 2016 Elsevier Ltd. All rights reserved.
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