Forensic Comparison of Soil Samples Using Nondestructive Elemental Analysis

Abstract

Soil can play an important role in forensic cases in linking suspects or objects to a crime scene by comparing samples from the crime scene with samples derived from items. This study uses an adapted ED-XRF analysis (sieving instead of grinding to prevent destruction of microfossils) to produce elemental composition data of 20 elements. Different data processing techniques and statistical distances were evaluated using data from 50 samples and the log-LR cost (C ). The best performing combination, Canberra distance, relative data, and square root values, is used to construct a discriminative model. Examples of the spatial resolution of the method in crime scenes are shown for three locations, and sampling strategy is discussed. Twelve test cases were analyzed, and results showed that the method is applicable. The study shows how the combination of an analysis technique, a database, and a discriminative model can be used to compare multiple soil samples quickly.

A novel approach based on X-ray fluorescence and photon attenuation to the analysis of soils for forensic investigation

“…This technique combines particle analysis with Raman spectroscopy that can be employed to probe the molecular chemistry of specific particles of interest (Kammrath et al, 2018). Scanning electron microscopy and energy dispersive X-ray spectrometry are other quantitative methods usually used to analyze soils (Bergslien, 2013;Nakai et al, 2013;Woods et al, 2014;Uitdehaag et al, 2017;Prandel et al, 2019;. These methods allow the investigator to map particles in terms of their mineralogy (Kikkawa et al, 2019).…”

A case study in forensic soil comparison

“…Soil composition is very complex, including naturally occurring rocks, minerals, plant fragments, and anthropogenic substances, which makes it different in color and texture. Considering such a complexity, a variety of methods have been developed for forensic science purposes, involving color comparison [6], elemental analysis [7,8], mineral identification [9]. There have been also reports about examination of plant fragments [10], organic matter [11,12], pollen grains, and spores [13].…”

Predicting the Geographic Origin of Heroin by Multivariate Analysis of Elemental Composition and Strontium Isotope Ratios

“…In order to evaluate the type 1 error rate (false exclusion), the match criteria The selection of useful elements for forensic comparison was also performed during the procedure for determining match criteria. The selected elements ( 23 Na, 24 Mg, 27 Al, 51 V, 52 Cr, 55 Mn, 66 Zn, 88 Sr, 90 Zr, 111 Cd, and 137 Ba) were chosen on the basis of their analytical performance with the SRM NIST 1570a shown on Table 16, and for producing the lower rates of false inclusions and exclusions than were observed when using other elements. All pairwise comparisons were calculated using the R programming language (RStudio version 1.0.143) [64].…”

“…The following isotopes were measured in low resolution: 9 Be, 11 B, 23 Na, 53 Cr, 85 Rb, 88 Sr, 90 Zr, 93 Nb, 95 Th, 238 U. The following isotopes were measured in medium resolution: 24 Mg, 27 Al, 31 P, 32 S, 43 Ca, 44 Ca, 47 Ti, 51 V, 52 Cr, 53 Cr, 55 Mn, 56 Fe, 59 Co, 60 Ni, 63 Cu, 66 Zn, 69 Ga. The following isotopes were measured in high resolution: 39 K, 72 Ge, 75 As, 77 Se.…”

“…Leave-one-out essentially treats each sample as an unknown and predicts its assignment without participating in the model. 24 Mg, 52 Cr, 57 Fe, 66 Zn, 90 24 Mg, 52 Cr, 57 Fe, 66 Zn, 90 23 Na, 24 Mg, 27 Al, 51 V, 52 Cr, 55 Mn, 66 Zn, 88 Sr, 90 [61].…”