Suppajariyawat Praew, Elie Mathieu, Baron Mark, Gonzalez-Rodriguez Jose
School of Chemistry, University of Lincoln, Joseph Banks Laboratories, Green Lane, Lincoln, Lincolnshire LN6 7DL, United Kingdom; Central Institute of Forensic Science, Ministry of Justice, 499 Sukpraprute Building 16th Floor, Prachachuen Rd., Bang-Sue, Bangkok 10800, Thailand.
School of Chemistry, University of Lincoln, Joseph Banks Laboratories, Green Lane, Lincoln, Lincolnshire LN6 7DL, United Kingdom.
Forensic Sci Int. 2019 Aug;301:415-425. doi: 10.1016/j.forsciint.2019.06.001. Epub 2019 Jun 11.
Ammonium nitrate fuel oil (ANFO) is one of the most favorite explosives used in terrorist attacks. This explosive is a complex mixture of 95-96% ammonium nitrate (AN) and 4-5% liquid hydrocarbons (fuel oil). In this study, we analyze a variety of ANFO explosive mixtures in order to classify their different sources of origin by observing the difference in fuel components. The study was performed by mixing ammonium nitrate with eight different diesel brands collected in Lincoln, UK in two seasons (winter and summer). The samples were extracted using appropriate solvent and extracts were subsequently analyzed in sextuplicate by gas chromatography-mass spectrometry (GC-MS) and Fourier transform infrared spectroscopy (FTIR). A classification model was performed using principal component analysis (PCA) and Lineal Discriminant Analysis (LDA). In this study, four fatty acid methyl ester (FAME) contents were observed by GC-MS in all summer samples but found lack in some winter sample resulting in seasonal variation effect. The classification of pre-blast ANFO samples was achieved using GC-MS and FTIR in a combination with PCA/LDA. The results significantly showed the variation of specific diesel components and providing different classification performance among ANFO samples with high classification performance. Therefore, this study can be beneficial in forensic investigation that the use of diesel components are able to classify among different ANFO samples.
硝酸铵燃油炸药（ANFO）是恐怖袭击中最常用的炸药之一。这种炸药是95 - 96%的硝酸铵（AN）和4 - 5%的液态碳氢化合物（燃油）的复杂混合物。在本研究中，我们分析了多种ANFO炸药混合物，通过观察燃料成分的差异来对其不同来源进行分类。该研究是通过将硝酸铵与在英国林肯收集的八个不同柴油品牌在两个季节（冬季和夏季）混合进行的。样品用适当的溶剂萃取，随后萃取物用气相色谱 - 质谱联用仪（GC - MS）和傅里叶变换红外光谱仪（FTIR）进行六次重复分析。使用主成分分析（PCA）和线性判别分析（LDA）建立了一个分类模型。在本研究中，通过GC - MS在所有夏季样品中观察到四种脂肪酸甲酯（FAME）含量，但在一些冬季样品中未发现，从而产生了季节变化效应。使用GC - MS和FTIR结合PCA/LDA实现了爆炸前ANFO样品的分类。结果显著显示了特定柴油成分的变化，并在具有高分类性能的ANFO样品中提供了不同的分类性能。因此，本研究在法医调查中可能是有益的，因为柴油成分的使用能够对不同的ANFO样品进行分类。
