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Biodiesel synthesis from Saussurea heteromalla (D.Don) Hand-Mazz integrating ethanol production using biorefinery approach

Author

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  • Rozina,
  • Ahmad, Mushtaq
  • Zafar, Muhammad
  • Ali, Nasir
  • Lu, Houfang

Abstract

Biodiesel is a renewable and substitute fuel to diesel engines. The main limit for adoption of biodiesel on industrial scale as an alternative fuel is the high cost of its synthesis process using raw methanol during transesterification reaction. Using bio-refinery approach and inexpensive high-quality oil feedstock is an effective means to produce low-cost biodiesel. In this study Saussurea heteromalla a novel non-edible seed with high oil contents (30 wt%) was subjected first time to integrated synthesis of biodiesel and ethanol. Transesterification and simultaneous saccharification along with fermentation process was applied to produce biodiesel and ethanol respectively. Alkaline pretreatment with sodium hydroxide (8% w/v) at 100 °C was used to enhance ethanol yield from 30% to 80%. A highest biodiesel yield of 99% was achieved via optimized parameters of 6:1 alcohol to oil ratio with 0.26 wt% catalyst in 55 min time at 65 °C temperature using Response Surface Methodology. It was observed that 112.2 ± 1.6 g of biodiesel and 42.0 ± 0.5 g of ethanol were produced using 1 kg of Saussurea heteromalla seed oil. In addition, the fuel properties of prepared biodiesel were in accordance to ASTM D 6751 and EN 14214 standards.

Suggested Citation

  • Rozina, & Ahmad, Mushtaq & Zafar, Muhammad & Ali, Nasir & Lu, Houfang, 2017. "Biodiesel synthesis from Saussurea heteromalla (D.Don) Hand-Mazz integrating ethanol production using biorefinery approach," Energy, Elsevier, vol. 141(C), pages 1810-1818.
    • Handle: RePEc:eee:energy:v:141:y:2017:i:c:p:1810-1818
    DOI: 10.1016/j.energy.2017.11.074
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    2. Nordmeier, Akira & Chidambaram, Dev, 2018. "Use of Zymomonas mobilis immobilized in doped calcium alginate threads for ethanol production," Energy, Elsevier, vol. 165(PB), pages 603-609.
    3. Gülüm, Mert & Onay, Funda Kutlu & Bilgin, Atilla, 2018. "Comparison of viscosity prediction capabilities of regression models and artificial neural networks," Energy, Elsevier, vol. 161(C), pages 361-369.

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