BiodieselAnalyzer : a user-friendly software for predicting the properties of prospective biodiesel

Software Fatty acids profile Algal biodiesel The procedures used to experimentally determine the quality parameters of a biodiesel are lengthy and expensive. Occasionally it may be impossible to obtain a sufficient amount of oil for the relevant analyses. This is often the case for algal biodiesel, for example. Here we report on a new software package, the BiodieselAnalyzer Version 1.1, for predicting the properties of a prospective biodiesel. BiodieselAnalyzer can estimate 16 different quality parameters of a biodiesel based on the fatty acid methyl ester profile of the oil feedstock used in making it. The current version of the BiodieselAnalyzer is intended for the Windows platform and is publically available at http://www.brteam.ir/biodieselanalyzer.


Introduction
Supplying energy sustainably is a major challenge facing us.Consumption of fossil fuels continues to increase despite its severe and potentially irreversible consequences on the global climate.Biodiesel derived from renewable oils is a potential alternative to petroleum diesel.
Biodiesel typically consists of monoalkyl esters of fatty acids derived from vegetable oils and animal fats.Biodiesel is mostly produced through transesterification of the feedstock oil.Biodiesel derived from various oils is already in commercial use.Depending on the fatty acid composition of the feedstock oil used in making the biodiesel, its properties can vary greatly.Providing the end user with a sufficient assurance on fuel properties and quality is of great importance.Consequently, biodiesel standards have been developed in various regions.Examples are the European biodiesel standards EN 14214 and the American standard ASTM D6751.Experimental determination of the quality parameters of a biodiesel sample requires considerable amount of time and money.Examples of the attributes of interest are the kinematic viscosity, the oxidation stability (OS), the cold flow properties, and the cetane number (CN).In some cases, it may be impossible to obtain a sufficiently large sample of a biodiesel from an emerging feedstock oil for detailed analyses.Such is commonly the case for algal biodiesel, for example.Notwithstanding this, the properties of a biodiesel may be predicted using information on the fatty acid profile of the parent oil as all the relevant properties depend directly on the fatty acids (FAs) composition of the feedstock oil.A model relating the FA profile of the feedstock oil and the biodiesel produced from it may be used as a bioprospecting tool for rapidly estimating the potential usefulness of a new feedstock oil (Bigelow et al., 2001, Ramírez-Verduzco et al., 2012, Talebi et al., 2013).
Here we introduce a user-friendly public domain computer software, the BiodieselAnalyzer  , for estimating the properties of a biodiesel from the fatty acid profile of the parent oil.This software is based on the previously published highly-reliable modeling data including ours (Talebi et al., 2013).

Input data
The only input data required by the BiodieselAnalyzer  is the fatty acid profile of the feedstock oil as determined by gas-chromatography (GC).Once the weight percent of the individual fatty acids present in the oil has been entered (Figure 1), pressing 'continue' leads the user to a new page where the various calculated properties of the prospective biodiesel are given under different tabs (Figure 2).

Analysis
BiodieselAnalyzer  provides the estimated properties under the following tabs: Unsaturation Level, including the amount of the saturated and the unsaturated fatty acids and the degree of unsaturation (DU); the Cetane Number; the Cold Flow Properties including the cloud point (CP) and the cold filter plugging point (CFPP); the Oxidation Stability including the allylic (APE) and the bis-allylic position equivalents (BAPE); the Higher Heating Value (HHV); the kinematic viscosity; and the Density.The Equations 1-12 provided below are used in estimating the various properties from the fatty acid methyl ester profile (FAME) and the structure of the relevant fatty acids (Krisnangkura, 1986).
The cetane number (CN) is calculated as follows (Knothe, 2006): The saponification value (SV) and iodine value (IV) for use in the above equation are calculated using the following equations: SV = ∑(560×N)/M (Eq.2) IV = ∑(254×D N)/M (Eq. 3) In the above equations D is the number of double bonds in the fatty ester, M is the molecular mass of the fatty ester, and N is the percentage of the particular fatty ester in the oil sample.
The degree of unsaturation (DU) is calculated using the amounts of the monounsaturated (MUFA) and polyunsaturated fatty acids (PUFA) present in the oil; thus: DU = MUFA + (2×PUFA) (Eq.4) The allylic position equivalents (APE) and bis-allylic position equivalents (BAPE) are calculated using the equations previously developed by Knothe (Knothe, 2002): APE = ∑(apn×Acn) (Eq.5) BAPE = ∑(bpn×Acn) (Eq.6) where apn and bpn are the numbers of allylic and bis-allylic positions in a specific fatty acid, respectively, and Acn is the amount (mass percent) of each fatty acid in the mixture.

Fig. 1 .
Fig. 1.Input data page for entry of the fatty acids profile as determined by gas chromatography.

Fig. 1 .
Fig. 1. Results page where the prospective biodiesel properties are predicated.