Location: Bio-oils Research Unit
Title: Efficacy of specific gravity as a tool for prediction of biodiesel-petroleum diesel blend ratio Author
Submitted to: Fuel
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: April 26, 2012
Publication Date: June 7, 2012
Citation: Moser, B.R. 2012. Efficacy of specific gravity as a tool for prediction of biodiesel-petroleum diesel blend ratio. Fuel. 99:254-261. Interpretive Summary: This research reveals that an easily measured fuel property in some cases is effective at predicting the blend ratio of biodiesel to petrodiesel. The objective of this study was to determine whether or not specific gravity data could be used to calculate the ratio of biodiesel to petrodiesel in blends. Previous studies have determined that the reported ratio of biodiesel to petrodiesel sold at commercial stations in many cases varies significantly from the actual blend ratio. There is, therefore, an urgent need for an inexpensive method to accurately measure blend ratio at commercial stations. Specific gravity (ratio of the density of a sample to a reference material, usually water) of blends is fast, cheap, and easy to measure. This study revealed that if the specific gravities of biodiesel and petrodiesel fuels are known prior to blend preparation, then the use of specific gravity as a predictive tool is highly effective. These results will be important to biodiesel producers, distributors, and end-users (customers) because a new insight will be gained on prediction of biodiesel/petrodiesel blend ratio. This research may ultimately improve market penetration, availability, and public perception of domestically produced agricultural fuels, such as biodiesel, thus affording greater national independence from imported petroleum-based fuels.
Technical Abstract: Prediction of volumetric biodiesel/petrodiesel blend ratio (VBD) from specific gravity (SG) data was the subject of the current investigation. Fatty acid methyl esters obtained from soybean, palm, and rapeseed oils along with chicken fat (SME-1, SME-2, PME, RME, and CFME) were blended (0 to 20 volume percent) with three ultra-low sulfur (<15 ppm S) diesel (ULSD) fuels and SG at 15.6 deg C was measured. Least-squares statistical regression on SG data from each of the biodiesel/ULSD blend sets revealed highly linear relationships (R2 > 0.991) between SG and VBD. Blends with the highest R2 values from each of the ULSD fuels were used as model systems to develop predictive equations useful for calculation of VBD from SG. The results indicated that accurate prediction of VBD from SG was most effective when applied to blends prepared from the same fuel-types as the model systems used to develop the predictive equations.