Forensic differentiation of biogenic organic compounds from petroleum hydrocarbons in biogenic and petrogenic compounds cross-contaminated soils and sediments

“Total petroleum hydrocarbons” (TPHs) or “petroleum hydrocarbons” (PHCs) are one of the most widespread soil pollutants in Canada, North America, and worldwide. Clean-up of PHC-contaminated soils and sediments costs the Canadian economy hundreds of million of dollars annually. Much of this activity is driven by the need to meet regulated levels of PHC in soil. These PHC values are legally required to be assessed using standard methods. The method most commonly used in Canada, specified by the Canadian Council of Ministers of the Environment (CCME), measures the total hydrocarbon concentrations in a soil by carbon range (Fraction 1: C₆–C₁₀; Fraction 2: C₁₀–C₁₆, Fraction 3: C₁₆–C₃₄: and Fraction 4: C₃₄+). Using the CCME method, all of the materials extractible by a mixture of 1:1 hexane:acetone are considered to be petroleum hydrocarbon contaminants. Many hydrocarbon compounds and other extractible materials in soil, however, may originate from non-petroleum sources. Biogenic organic compounds (BOCs) is a general term used to describe a mixture of organic compounds, including alkanes, sterols and sterones, fatty acids and fatty alcohols, and waxes and wax esters, biosynthesized by living organisms. BOCs are also produced during the early stages of diagenesis in recent aquatic sediments. BOC sources could include vascular plants, algae, bacteria and animals. Plants and algae produce BOCs as protective wax coating that are released back into the sediment at the end of their life cycle. BOCs are natural components of thriving plant communities. Many solvent-extraction methods for assessing soil hydrocarbons, however, such as the CCME method, do not differentiate PHCs from BOCs. The naturally occurring organics present in soils and wet sediments can be easily misidentified and quantified as regulated PHCs during analysis using such methods. In some cases, biogenic interferences can exceed regulatory levels, resulting in remediation of petroleum impacts that are not actually present. Consequently, reliance on these methods can trigger unnecessary and costly remediation, while also wasting valuable landfill space. Therefore, it is critically important to develop new protocols to characterize and differentiate PHCs and BOCs in contaminated sediments. In this study, a new reliable gas chromatography–mass spectrometry (GC–MS) method, in combination with a derivatization technique, for characterization of various biogenic compounds (including biogenic alkanes, sterols, fatty acids and fatty alcohols) and PHCs in the same sample has been developed. A multi-criteria approach has been developed to positively identify the presence of biogenic compounds in soil and sediment samples. More than thirty sediment samples were collected from city stormwater management (SWM) ponds and wetlands across Canada. In these wet sediment samples, abundant biogenic n-alkanes, thirteen biogenic sterols, nineteen fatty carboxylic acids, and fourteen fatty alcohols in a wide carbon range have been positively identified. Both PHCs and BOCs in these samples were quantitatively determined. The quantitation data will be used for assessment of the contamination sites and toxicity risks associated with the CCME Fraction 3 hydrocarbons.     

The use of different dispersive Raman spectrometers for the analysis of uranium compounds

The performances of three different Raman spectrometers were compared and evaluated as a suitable tool for the analysis of a range of uranium compounds with a view to application in nuclear forensics. These included uranium ore concentrates of different chemical composition and uranium dioxide in the form of powder and sintered fuel pellet. The three spectrometers are termed as ‘portable’ or ‘hand-held’ from Ahura Scientific (785 nm), ‘Senterra’ from Bruker (532 and 785 nm), ‘T64000′ from HORIBA Jobin Yvon (488.0, 514.5, 647.1 and 752.5 nm). Figures of merit such as sensitivity, signal-to-noise ratio and detection capability were compared. The portable Raman displayed fairly good sensitivity and process related impurities could be detected despite the miniaturisation but it was unable to measure darkly coloured powders such as calcined ore concentrates or uranium dioxide powder. The bench-top spectrometer Senterra had the best sensitivity for all the seven measured uranium compounds and the best signal-to-noise ratio for six of the compounds. Laboratory T64000 had the best resolution and at the same time resulting in the poorest sensitivity among the three spectrometers for all compounds measured. However, T64000 has very low level of noise therefore leading to better signal-to-noise that were comparable, if not better than the portable or Senterra. All industrial compounds measured in this study could not be measured with higher frequency laser thus impeding the observation of N–H or O–H vibration bands, of which the latter could be observed with laboratory synthesized material.     

一种基于三角形区域生长的图像篡改检测方法

针对现有的多数图像篡改检测算法中存在着的对旋转、缩放等篡改失效和计算量大等问题,利用三角形具有抗平移、旋转、尺度缩放的优越特性,提出了一种新的图像篡改检测算法.首先,利用Delaunay三角剖分算法对提取的Harris特征角点进行三角剖分,进行相似三角形的初始匹配.然后,以匹配的相似三角形顶点为种子点,建立三角形组,再进行一次相似三角形的匹配,实现对篡改区域的三角形生长.最后,利用区域面积阈值和数学形态学准确定位出篡改区域.实验结果表明,该算法与同类算法相比不仅能有效地对抗旋转、缩放,噪声等后期处理操作,而且对篡改区域有很好的检测和定位效果并具有计算复杂度低的特点.     

Anionic forensic signatures for sample matching of potassium cyanide using high performance ion chromatography and chemometrics

Potassium cyanide was used as a model toxicant to determine the feasibility of using anionic impurities as a forensic signature for matching cyanide salts back to their source. In this study, portions of eight KCN stocks originating from four countries were separately dissolved in water and analyzed by high performance ion chromatography (HPIC) using an anion exchange column and conductivity detection. Sixty KCN aqueous samples were produced from the eight stocks and analyzed for 11 anionic impurities. Hierarchal cluster analysis and principal component analysis were used to demonstrate that KCN samples cluster according to source based on the concentrations of their anionic impurities. The Fisher-ratio method and degree-of-class separation (DCS) were used for feature selection on a training set of KCN samples in order to optimize sample clustering. The optimal subset of anions needed for sample classification was determined to be sulfate, oxalate, phosphate, and an unknown anion named unk5. Using K-nearest neighbors (KNN) and the optimal subset of anions, KCN test samples from different KCN stocks were correctly determined to be manufactured in the United States. In addition, KCN samples from stocks manufactured in Belgium, Germany, and the Czech Republic were all correctly matched back to their original stocks because each stock had a unique anionic impurity profile. The application of the Fisher-ratio method and DCS for feature selection improved the accuracy and confidence of sample classification by KNN.     

Detection of fentanyl in binary mixtures with cocaine by use of surface-enhanced Raman spectroscopy

Abstract

The ongoing epidemic pertaining to overdose deaths has been attributed to the synthetic opioid fentanyl due to its use as an adulterant in other, less potent drugs of abuse. Detection of low quantities of fentanyl would, therefore, be extremely useful in a forensic science laboratory. While Raman spectroscopy is particularly effective at distinguishing between classes of drugs, weak signatures can prove difficult when dealing with microscopic samples. Surface-enhanced Raman scattering spectroscopy provides the enhancement necessary to make Raman a viable approach for the detection of small amounts of fentanyl. This work explores the use of a paper-based substrate loaded with silver nanoparticles for the recovery of small quantities of fentanyl in cocaine, where it was identified at a lower limit of 500?ng (～65?ppm) in mixtures. Linear relationships were investigated between intensity and concentration for diagnostic peaks associated with fentanyl and cocaine, which in turn sheds light on the attenuation of the enhancement intensity as a result of competitive binding to silver nanoparticles. This work demonstrates a potentially simple and qualitative pathway for the forensic analysis of fentanyl as an adulterant in cocaine.     

A review of the determination of persistent organic pollutants for environmental forensics investigations

The field of environmental forensics emerged in the 1980s as a consequence of legislative frameworks enacted to enable parties, either states or individuals, to seek compensation with regard to contamination or injury due to damage to the environment. This legal environment requires stringent record keeping and defendable data therefore analysis can sometimes be confined to data to be obtained from certified laboratories using a standard accredited analytical method. Many of these methods were developed to target specific compounds for risk assessment purposes and not for environmental forensics applications such as source identification or age dating which often require larger data sets. The determination of persistent organic pollutants (POPs) for environmental forensic applications requires methods that are selective but also cover a wide range of target analytes which can be identified and quantified without bias. POPs are used in a wide variety of applications such as flame retardants, fire suppressants, heat transfer agents, surfactants and pesticides mainly because of their chemical inertness and stability. They also include compounds such as dioxins that can be unintentionally produced from industrial activities. POPs are persistent in the environment, bioaccumulative and/or toxic and therefore require analytical methods that are sensitive enough to meet the low detection limits needed for the protection of the environment and human health. A variety of techniques, procedures and instruments can be used which are well suited for different scenarios. Optimised methods are important to ensure that analytes are quantitatively extracted, matrix coextractables and interferences are removed and instruments are used most effectively and efficiently. This can require deviation from standard methods which can open the data up to further scrutiny in the courtroom. However, when argued effectively and strict QA/QC procedures are followed the development and optimization of methods based on investigation specific scenarios has the potential to generate better quality and more useful data.     

Characterization of uranium tetrafluoride (UF4) with Raman spectroscopy

The Raman spectrum of uranium tetrafluoride (UF₄) is unambiguously characterized with multiple Raman excitation laser sources for the first time. Across different laser excitation wavelengths, UF₄ demonstrates 16 distinct Raman bands within the 50–400 cm⁻¹ region. The observed Raman bands are representative of various F–F vibrational modes. UF₄ also shows intense fluorescent bands in the 325–750 nm spectral region. Comparison of the UF₄ spectrum with the ZrF₄ spectrum, its crystalline analog, demonstrates a similar Raman band structure consistent with group theory predictions for expected Raman bands. Additionally, a demonstration of combined scanning electron microscopy and in situ Raman spectroscopy microanalytical measurements of UF₄ particulates shows that despite the inherent weak intensity of Raman bands, identification and characterization are possible for micron‐sized particulates with modern instrumentation. The published well‐characterized UF₄ spectrum is extremely relevant to nuclear materials and nuclear safeguard applications. Published 2016. This article is a U.S. Government work and is in the public domain in the USA. Journal of Raman Spectroscopy published by John Wiley & Sons Ltd.     

基于免疫Agent的计算机动态取证

针对目前计算机取证技术因为取证时间的滞后而缺乏实效性的不足，提出了一种基于人工免疫原理和Multi—Agent理论的计算机动态取证方法．该方法结合了人工免疫系统在入侵检测中的优势及Multi-Agent系统在体系结构上的分布式特点，能够在网络攻击一旦发生的时候动态地收集实时数字证据，并通过安全有效的方式将证据及时、完整地加以保存，为证据的收集和分析工作提供可信的原始数据．同时能够确保数字证据安全有效地传输及保存．实验表明该方法能够确保证据的真实、完整和有效，为计算机动态取证的实现提供了一种新的思路．