Forensic soil provenancing in an urban/suburban setting: A simultaneous multivariate approach. Issue 3 (17th January 2022)

• Record Type: Journal Article
• Authors: de Caritat, Patrice; Woods, Brenda; Simpson, Timothy; Nichols, Christopher; Hoogenboom, Lissy; Ilheo, Adriana; Aberle, Michael G.; Hoogewerff, Jurian
• Is Part Of: Journal of forensic sciences. Volume 67:Issue 3(2022)
• Page Start: 927
• Page End: 935
• Publication Date: 2022-01-17
• Subjects: geochemical mapping -- geographic information system (GIS) -- performance analysis -- soil forensics -- soil properties -- Spearman's correlation coefficients (rS); Medical jurisprudence -- Periodicals; Forensic sciences -- Periodicals; Forensic Medicine -- Periodicals; Gerechtelijke geneeskunde; Gerechtelijke chemie; Gerechtelijke psychiatrie; 363.2505
• DOI: 10.1111/1556-4029.14967
• Languages: English
• ISSNs: 0022-1198

Abstract

Abstract: Soil is a ubiquitous material at the Earth's surface with potential to be a useful evidence class in forensic and intelligence applications. Compositional data from a soil survey over North Canberra, Australian Capital Territory, are used to develop and test an empirical soil provenancing method. Mineralogical data from Fourier Transform InfraRed spectroscopy (FTIR) and geochemical data from X‐Ray Fluorescence (XRF; for total major oxides) and Inductively Coupled Plasma‐Mass Spectrometry (ICP‐MS; for both total and aqua regia ‐soluble trace elements) are obtained from the survey's 268 topsoil samples (0–5 cm depth; 1 sample per km 2 ). The simultaneous provenancing approach is underpinned by (i) the calculation of Spearman's correlation coefficients ( rS ) between an evidentiary sample and all the samples in the database for all variables generated by each analytical method; and (ii) the preparation of an interpolated raster grid of rS for each evidentiary sample and method resulting in a series of provenance rasters ("heat maps"). The simultaneous provenancing method is tested on the North Canberra soil survey with three "blind" samples representing simulated evidentiary samples. Performance metrics of precision and accuracy indicate that the FTIR (mineralogy) and XRF (geochemistry) analytical methods offer the most precise and accurate provenance predictions. Maximizing the number of analytes/analytical techniques is advantageous in soil provenancing. Despite acknowledged limitations, it is concluded that the empirical soil provenancing approach can play an important role in forensic and intelligence applications.