4.7 Article

Optimization of Chlorella variabilis. MK039712.1 lipid transesterification using Response Surface Methodology and analytical characterization of biodiesel

Journal

RENEWABLE ENERGY
Volume 179, Issue -, Pages 1663-1673

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.renene.2021.07.123

Keywords

Chlorella variabilis; Lipid extraction; Response surface methodology; Microalgae; Biodiesel

Funding

  1. Ministry of Education, Government of India [5-5/2014-TS]

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In this study, biodiesel was successfully produced from Chlorella variabilis MK039712.1 microalga oil by optimizing transesterification conditions, resulting in high yield. The chemical structure changes of transesterified algal oil were analyzed using Fourier Transform Infra-Red Spectroscopy, H-1 Nuclear Magnetic Resonance, and C-13 Nuclear Magnetic Resonance. Fuel properties were found to be comparable with ASTM standards.
Microalgae farming has gained interest because of the heavy processing requirement of non-renewable fuel sources and increased vegetable oil prices that prevent them from being used for biodiesel production. Chlorella varibilis MK039712.1, a freshwater microalga with 24.0 +/- 0.6% w/w lipid was isolated from Valparai, Coimbatore district, Tamil Nadu, India, that was dried, lysed to extract it for biodiesel production. The present study aims to produce biodiesel from the Chlorella variabilis MK039712.1 algal oil by optimizing the transesterification conditions by varying catalyst concentration, methanol to oil molar ratio, time, temperature using Response Surface Methodology. At 8:1 methanol to algal oil molar ratio, 0.3 wt % of catalyst, 65 degrees C reaction temperature and 120 min reaction time, a maximum of 96% biodiesel yield was obtained. The variations in chemical structure of the transesterified algal oil was analyzed using Fourier Transform Infra-Red Spectroscopy, H-1 Nuclear Magnetic Resonance and C-13 Nuclear Magnetic Resonance. The fuel properties were also determined and found comparable with the ASTM standards. (C) 2021 Elsevier Ltd. All rights reserved.

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