Optimizing Algal Oil Extraction and Transesterification Parameters through RSM, PCA, and MRA for Sustainable Biodiesel Production

文献类型： 外文期刊

第一作者： Tang, Lingdi

作者： Tang, Lingdi;Otho, Ali Raza;Laghari, Mahmood;Brohi, Sheeraz Aleem;Junejo, Abdul Rahim;Hao, Li;Chandio, Farman Ali;Mari, Irshad Ali;Channa, Jamshed Ali;Otho, Sohail Ahmed;Dahri, Jahangeer

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关键词： algal oil extraction; transesterification; biodiesel; response surface methodology; principal component analysis; multivariate regression analysis

期刊名称：CATALYSTS （ 影响因子：4.0； 五年影响因子：4.0 ）

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年卷期： 2024 年 14 卷 10 期

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收录情况： SCI

摘要： This study presents a comprehensive optimization of algal oil extraction and transesterification for sustainable biodiesel production. Freshwater Spirogyra algae underwent Soxhlet extraction using n-hexane. response surface methodology (RSM), principal component analysis (PCA), and multivariate regression analysis (MRA) were employed to investigate the effects of biomass-solvent ratio (BSR), algae particle size (APS), and extraction-contact time (E-CT) on algal oil yield (AOY). The extracted oil was then converted to biodiesel via transesterification, and the impacts of the methanol-oil ratio (MOR) and transesterification-contact time (T-CT) on biodiesel conversion efficiency (BCE) were analyzed. Results demonstrate that optimal BSR, APS, and E-CT for maximal AOY are 1:7, 400 mu m, and 3-4 h, respectively. For transesterification, a MOR of 12:1 and a T-CT of 4 h yielded the highest BCE. Predictive models exhibited exceptional accuracy, with R2 values of 0.916 and 0.950 for AOY and BCE, respectively. The produced biodiesel complied with ASTM D6751 and EN 14214, showcasing its potential for renewable energy applications.

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