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Method development for forensic identification of biodiesel based on chemical fingerprints and corresponding diagnostic ratios.

作者信息

Yang Zeyu, Hollebone Bruce P, Wang Zhendi, Yang Chun, Brown Carl, Landriault Mike

机构信息

Key Laboratory of Catalysis and Materials Science of the State Ethnic Affairs Commission & Ministry of Education, Key Laboratory of Analytical Chemistry of the State Ethnic Affairs Commission, College of Chemistry and Materials Science, South-Central University for Nationalities, Wuhan 430074, PR China; Emergencies Science and Technology Section, EOALRSD, Science and Technology Branch, Environment Canada, Canada.

Emergencies Science and Technology Section, EOALRSD, Science and Technology Branch, Environment Canada, Canada.

出版信息

Forensic Sci Int. 2014 Jan;234:86-94. doi: 10.1016/j.forsciint.2013.11.001. Epub 2013 Nov 14.

Abstract

A forensic identification method based on the chemical fingerprinting of the first generation of biodiesel (fatty acid alkyl esters as effective components), and several corresponding diagnostic ratios was developed and validated. The distribution of major fatty acid methyl esters (FAMEs) and polar compounds (free fatty acids, glycerol, monoacylglycerides, and free sterols) in several representative above biodiesel products commercially available in Canada were positively quantified and compared, a number of cross-plots of diagnostic ratios of target FAMEs and sterols were developed for biofuel correlation and differentiation. It was found that the cross-plots of FAME ratios, for example, the sum of the di-unsaturated relative to saturated homologues of FAMEs (D/S) versus the sum of the mono-saturated to saturated FAMEs (M/S), and the sum of di-unsaturated to mono-saturated FAMEs (D/M) versus the sum of the mono-saturated to saturated FAMEs (M/S), could cluster samples clearly into their individual feedstock. The cross-plots of diagnostic ratios of individual major sterols (cholesterol, brassicasterol, campesterol, β-stiosterol and stigmasterol) to the total sterols were also developed and proved to be effective in identifying biodiesel sources due to their self-normalizing effect on sterol data. The case study of a mystery biodiesel spill using this method showed that the two real samples can be tightly clustered into biodiesel from animal fat (Ban) group. However, the significant discrepancy of free fatty acids, glycerol, monoacylglycerides and sterol concentrations between the two real samples indicated their different producing batches.

摘要

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