Abstract Police in the UK received information that a person had been reported as missing. Despite a diligent search and investigation, the person was not found. Several years later police received intelligence giving the location of a grave believed to contain the remains of the person previously reported as missing and now believed to be a victim of homicide. This new information suggested the missing person had been murdered and their remains were buried in a shallow, unmarked grave. Following a systematic search, the murder victim's body was found at a shallow depth, less than 1 m. Following the forensic recovery of the body, soil samples were collected at, beneath the floor of the grave, along the strike of the grave, downslope and upslope. Analysis of the soil samples showed elevated levels of putrescine, at nearly 150 ppb in the soils beneath, downslope and for several metres upslope from the body at localities where detector dogs had showed an ‘interest’ before the grave was discovered. The mineralogical analysis, using integrated automated mineralogy and petrology detected the presence of diagenetic calcite in the soil profile beneath the grave. Additionally, the organic analysis detected the presence of elevated stanols at the grave and down slope.

Abstract The use of soil evidence to identify an unknown location is a powerful tool to determine the provenance of an item in an investigation. We are particularly interested in the use of these indicators in nuclear forensic cases, whereby identification of locations associated with, for example, a smuggled nuclear material, may be used to indicate the provenance of a find. The use of soil evidence to identify an unknown location relies on understanding and predicting how soils vary in composition depending on their geological/geographical setting. In this study, compositional links between the mineralogy of 40 soils and the underlying bedrock geology, as documented in local-scale geological maps, were established. The soil samples were collected from locations with broadly similar climate and land use across a range of geological settings in a ‘test bed’ 3500 km 2 area of SW England. In this region, the soils formed through chemical weathering of the bedrock, representing a worst case scenario for this type of forensic geolocation owing to the high degree of alteration of the parent rock during soil formation. The mineralogy was quantified using automated scanning electron microscopy–energy dispersive X-ray spectrometry analysis based on QEMSCAN technology. Soil mineralogy and texture as measured using this technique are consistent with the underlying geology as indicated by regional-scale geological mapping. Furthermore, differences between individual units of the same bedrock lithology, such as different granites, were identified by examining trace mineralogical signatures. From an investigative viewpoint, this demonstrated that rapid automated mineral profiling of soil samples could be used, in conjunction with readily available geological mapping or similar datasets, to provide indication of the areas from which a soil sample of unknown origin could, or could not, have been sourced.

Abstract Granites ( sensu lato ) come in many types and flavours, defining distinct magmatic series/suites/types. A good classification not only gives generally accepted and understandable names to similar rocks but also links the bulk chemical composition to the stoichiometry of the constituent minerals and, potentially, also to the likely source, magmatic evolution and tectonic setting. The ‘ideal’ granitoid classification should be based on chemical criteria amenable to an objective treatment. Statistical analysis helps to identify the most discriminant variables. The key properties are (1) acidity/maficity, (2) alkalinity (balance of Na + K v. Ca), (3) aluminosity (balance of Al v. Ca, Na and K), (4) Fe/Mg balance and (5) Na/K balance and K contents at the given SiO 2 level. These are used by successful classifications, e.g. the I/S dichotomy is based mainly on aluminosity, while the Frost et al. (2001 ; ‘A geochemical classification for granitic rocks', Journal of Petrology , 42 , 2033–2048, https://doi.org/10.1093/petrology/42.11.2033 ) classification includes all but Na/K. Even though it is commonplace to use weight percentages of oxides, we suggest that a better strategy is to employ simple atomic parameters (e.g. millications-based) that can be directly linked to modal proportions and compositions/crystal structure of individual rock-forming minerals. This facilitates a petrological interpretation, which, in turn, can be related to petrogenesis and, ultimately, to likely tectonic setting(s).

Abstract Felsic magmatic bodies are exposed widely in the Bomdila region of the western Arunachal Himalaya, NE India. The litho-units of this region are primarily composed of two-mica (muscovite–biotite (ms–bt)) granite gneiss, referred to herein as the Bomdila granite gneiss (BGGn), and the metasediments of the Bomdila Group forming an integral part of the NE Lesser Himalayan thrust sheet. Phase petrology, whole-rock elemental geochemistry and zircon U–Pb–Lu–Hf isotopes of the BGGn have been investigated in order to decipher the origin and timing of felsic magmatism and its implications for understanding the pre-Himalayan tectonic environment. Modally, the BGGn can be classified into monzogranite, syenogranite and quartz-rich granitoids. The composition of muscovite (Ti = 0.03–0.07, average Na = 0.07 and Al IV = 2.50–2.90 apfu), biotite (FeO t /MgO = 3.1–4.6, 2Al⇌3Fe and Mg⇌Fe substitutions, and the presence of siderophyllite) and tourmaline (Fe/Fe + Mg = 0.56–0.96, Ca < 0.17 apfu) implies their primary magmatic nature crystallized typically in a peraluminous (S-type) felsic parental melt. This is further supported by the presence of ms–bt, whole-rock molar Al 2 O 3 /CaO + Na 2 O + K 2 O (A/CNK = 1.03–1.64) and normative corundum. Whole-rock multi-cationic parameters indicate a syn-collisional tectonic environment. However, the content of Rb (average 300 ppm) and high-field strength elements (HFSEs) in the BGGn indicates syn- to post-collisional tectonic settings. The BGGn parental melt was most likely to have been generated by dehydration melting of metasedimentary sources at middle–upper crustal depths. Geochemical modelling constrains the evolution of the parental melt of the BGGn by a moderate degree of fractional differentiation ( F = 0.45) involving a biotite–plagioclase–K-feldspar–muscovite–titanite–apatite (bt–pl–Kfs–ms–ttn–ap) assemblage. Laser ablation-multicollector-inductively coupled plasma-mass spectrometry (LA-MC-ICP-MS)-analysed zircons from the BGGn yield a weighted mean 207 Pb/ 206 Pb age of 1752 ± 23 Ma as the crystallization age for the zircons in the BGGn melt, which falls well within the period of magmatism formed during the Columbia supercontinent accretionary orogen. The observed negative ε Hf (t) values (−1.67 to −7.99) and three-stage Hf-model ages (2818, 2586–2424 and 2393–2250 Ma) of zircons, strongly point to the involvement of ancient continental crust and source heterogeneity (Neoarchean–Paleoproterozoic continental crust) in the generation of the BGGn melt. The reworked ancient crustal components would have once been part of the northern Indian lithosphere, as indicated by the observed 207 Pb/ 206 Pb concordant ages (2436, 2136, 2013 Ma) of the inherited zircons.