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Optimization of the Transesterification of Waste Cooking Oil with Mg-Al Hydrotalcite Using Response Surface Methodology

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  • Laureano Costarrosa

    (Department of Physical Chemistry and Applied Thermodynamics, EPS, Edificio Leonardo da Vinci, Campus de Rabanales, Universidad de Córdoba, Campus de Excelencia Agroalimentario ceiA3, 14014 Córdoba, Spain)

  • David Eduardo Leiva-Candia

    (Department of Physical Chemistry and Applied Thermodynamics, EPS, Edificio Leonardo da Vinci, Campus de Rabanales, Universidad de Córdoba, Campus de Excelencia Agroalimentario ceiA3, 14014 Córdoba, Spain)

  • Antonio José Cubero-Atienza

    (Department of Rural Engineering, EPS, Edificio Leonardo da Vinci, Campus de Rabanales, Universidad de Córdoba, Campus de Excelencia Agroalimentario ceiA3, 14014 Córdoba, Spain)

  • Juan José Ruiz

    (Department of Physical Chemistry and Applied Thermodynamics, EPS, Edificio Leonardo da Vinci, Campus de Rabanales, Universidad de Córdoba, Campus de Excelencia Agroalimentario ceiA3, 14014 Córdoba, Spain)

  • M. Pilar Dorado

    (Department of Physical Chemistry and Applied Thermodynamics, EPS, Edificio Leonardo da Vinci, Campus de Rabanales, Universidad de Córdoba, Campus de Excelencia Agroalimentario ceiA3, 14014 Córdoba, Spain)

Abstract

Nowadays, biodiesel has become a very promising alternative to fossil diesel fuel, regarding environmental concerns and fuel resource depletion. Biodiesel is usually produced through homogeneous or heterogeneous transesterification of different fatty raw materials. Although main research has been carried out with homogenous catalysts, heterogeneous catalysts may be of interest due to ease of recovery and recycling, as well as readiness for continuous processing. In this work, calcined Mg-Al hydrotalcite (HT) was used for the heterogeneous transesterification of waste cooking oil. Three reaction parameters, namely, reaction time, amount of catalyst, and methanol-to-oil molar ratio, were optimized by means of Response Surface Methodology (RSM) at constant temperature (65 °C), using a Box-Behnken design. Optimal fatty acid methyl ester (FAME) content (86.23% w / w FAME/sample) was predicted by the model with an R-squared value of 98.45%, using 3.39 g of HT (8.5% w / w oil) and an 8:1 methanol-oil molar ratio, for a duration of 3.12 h. It was observed that calcination of HT, while avoiding the previous washing step, allowed the presence of chemical species that enhanced the effect of the catalyst. It can be concluded from this field trial that calcined and nonwashed Mg-Al hydrotalcite may be considered an effective basic catalyst for the production of biodiesel from waste cooking oil. Also, RSM proved to be a useful tool for predicting biodiesel yield.

Suggested Citation

  • Laureano Costarrosa & David Eduardo Leiva-Candia & Antonio José Cubero-Atienza & Juan José Ruiz & M. Pilar Dorado, 2018. "Optimization of the Transesterification of Waste Cooking Oil with Mg-Al Hydrotalcite Using Response Surface Methodology," Energies, MDPI, vol. 11(2), pages 1-9, January.
  • Handle: RePEc:gam:jeners:v:11:y:2018:i:2:p:302-:d:129384
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    References listed on IDEAS

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    1. Ma, Yingqun & Wang, Qunhui & Zheng, Lu & Gao, Zhen & Wang, Qiang & Ma, Yuhui, 2016. "Mixed methanol/ethanol on transesterification of waste cooking oil using Mg/Al hydrotalcite catalyst," Energy, Elsevier, vol. 107(C), pages 523-531.
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    7. Muhammad Qasim & Tariq Mahmood Ansari & Mazhar Hussain, 2017. "Combustion, Performance, and Emission Evaluation of a Diesel Engine with Biodiesel Like Fuel Blends Derived From a Mixture of Pakistani Waste Canola and Waste Transformer Oils," Energies, MDPI, vol. 10(7), pages 1-16, July.
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    Cited by:

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    3. Jume, Binta Hadi & Gabris, Mohammad Ali & Rashidi Nodeh, Hamid & Rezania, Shahabaldin & Cho, Jinwoo, 2020. "Biodiesel production from waste cooking oil using a novel heterogeneous catalyst based on graphene oxide doped metal oxide nanoparticles," Renewable Energy, Elsevier, vol. 162(C), pages 2182-2189.
    4. Fábio Antônio do Nascimento Setúbal & Sérgio de Souza Custódio Filho & Newton Sure Soeiro & Alexandre Luiz Amarante Mesquita & Marcus Vinicius Alves Nunes, 2022. "Force Identification from Vibration Data by Response Surface and Random Forest Regression Algorithms," Energies, MDPI, vol. 15(10), pages 1-15, May.
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