A comprehensive review of biodiesel production methods from various feedstocks

摘要

This article reviews the performance of biodiesel production from various feedstocks and analyzes the associated challenges. The existing literature survey dealt with the potential and important feedstocks like edible oil, non-edible oil, animal fat and algae oil for the biodiesel production. The result shows that the various sources have different yield due to processes variables. The yield of biodiesel differs with the feedstocks due to physico-chemical properties of sources and the process variables. In order to increase the biodiesel yield, the novel technologies are warranted in the bioenergy research field. Recent research focuses on the cheap, abundant feedstocks, novel production and purification technologies for biodiesel. Transesterification by enzyme has advantageous in view of conversion, yield and reusability whereas low yield of chemical catalyst catalyzed transesterification reactions in recent years. Lipase mediated transesterification has increased the rate of reaction followed by high conversion. But the activity of free enzyme is reduced as stability is low. In order to overcome this drawback, the immobilized lipase mediated transesterification methodology has been introduced in recent studies. Nanobiocatalyst focuses exclusively on the transesterification of oils using methanol to produce fatty acid methyl esters (FAME). Importantly, the lipase binds on magnetic particles with various size ranges, confirming stability and giving more reactive centers. Analytical methods such Fourier transform infrared spectra and transmission electron microscopy are used to characterize the structure of nanoparticles which exhibit better resistance to temperature and pH, stirring speed, enzyme loading, viscosity of oil and alcohol/oil molar ratio and free fatty acid. For the analysis of FAME, Gas Chromatography - Mass Spectroscopy (GC-MS) was extensively used. Nowadays microwave and ultrasound assisted transesterification techniques increases the conversion rate of oils into biodiesel. These methods may require less energy, compared to the conventional method. This method may require less energy, compared to the conventional method. In addition, the statistical (response surface methodology) and stochastical (artificial neural network and genetic algorithm) optimization techniques are expected to provide the best process response to the highest acid conversion and efficiency.