Assessment of Fuel Quality Parameters and Selection of Bacteria Using PROMETHEE-GAIA Algorithm.

Area of Science:

• Biomass energy
• Sustainable fuels

Background:

• Biodiesel, a mixture of fatty acid methyl esters (FAME), is increasingly important due to its eco-friendly properties.
• Biodiesel fuel quality is dictated by the structural characteristics of fatty acids (FA), including chain length, unsaturation, and branching.
• Assessing fuel properties like cetane number (CN), iodine value (IV), and cold filter plugging point (CFPP) is crucial for evaluating FAME quality.

Purpose of the Study:

• To evaluate fuel quality parameters for produced FAME.
• To select the most promising biodiesel-producing strain using a decision analysis algorithm.

Main Methods:

• Transesterification process to produce FAME from long-chain FAs and methanol.
• Evaluation of key fuel quality parameters of FAME (CN, IV, CFPP, HHV, CP, PP).
• Application of Preference Ranking Organization Method for Enrichment of Evaluation (PROMETHEE) and Graphical Analysis for Interactive Aid (GAIA) for strain selection.

Main Results:

• The study outlines a method for assessing FAME fuel quality.
• PROMETHEE-GAIA analysis is presented as a powerful tool for multi-criteria decision-making in strain selection.
• The described methodology facilitates the identification of superior biodiesel-producing organisms.

Conclusions:

• Effective selection of biodiesel-producing strains is vital for efficient large-scale production.
• PROMETHEE-GAIA offers a robust framework for evaluating and ranking potential strains based on fuel quality and lipid content.
• This approach aids in optimizing biodiesel feedstock selection for enhanced fuel properties.