Preparation and physicochemical properties of naturally grown green Spirogyra algae biodiesel

In this study, biodiesel was produced from a naturally grown green algae (Spirogyra). The algae were cultivated in an open pond for 180 days without any fertilizers or nutrients. The dried algae powder to oil yield and significant fuel properties of viscosity, density, cetane number, calorific value...

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Bibliographic Details
Published in:Chemical Industry & Chemical Engineering Quarterly 2023-01, Vol.29 (1), p.75-85
Main Authors: Kalyani, Teku, Prasad, L.S.V., Kolakoti, Aditya
Format: Article
Language:English
Subjects:
Air pollution
Algae
algae biodiesel
algae cultivation
Biodiesel fuels
Calorific value
Carbon dioxide
Cetane number
Chemicals
Correlation coefficients
Diesel fuels
Experimentation
Fatty acids
Fertilizers
Flash point
fuel properties
Nutrients
Optimization
Optimization techniques
Outdoor air quality
Solvent extraction processes
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Summary:In this study, biodiesel was produced from a naturally grown green algae (Spirogyra). The algae were cultivated in an open pond for 180 days without any fertilizers or nutrients. The dried algae powder to oil yield and significant fuel properties of viscosity, density, cetane number, calorific value, flash point, pour, and cloud points are investigated for B10 to B100 blends. The results of solvent oil extraction show that at a 1:2 (algae powder to solvent) ratio and 65 ?C, algae oil yield was 22.66%. Furthermore, Box-Behnken assisted response surface optimization technique was implemented. From the 29 random experiments, 96.24% Spirogyra algae oil biodiesel (SAOBD) yield was achieved under the optimum conditions of 50 ?C, 180 minutes, the molar ratio of 9:1, and catalyst concentration of 0.5 wt%. The fatty acid composition reveals that 73.95 wt% saturated FAC was observed in SAOBD. The significant fuel properties are measured by following ASTM-D6751 standards, and 40% SAOBD in diesel fuel could be an optimum blend ratio for engine experimentation. Finally, regression equations with high correlation coefficients (R2) were developed to predict the various blend ratios for the fuel properties.
ISSN:1451-9372
2217-7434
DOI:10.2298/CICEQ220215015K