Dating peat profiles using tephra: stratigraphy, geochemistry and chronology

In this article we provide a brief overview of the protocols for dating peat profiles using tephrochronology. A standardised methodology for the detection, extraction and analysis of tephras is presented and the relevant problems and limitations are discussed.

The Hekla 1947 tephra in the North of Ireland: regional distribution, concentration and geochemistry.

A cryptotephra layer from the eruption of Hekla in 1947 has recently been discovered in Irish peatlands. This tephra layer represents the most recent deposition of volcanic ash in the UK prior to the eruption of Eyjafjallajökull in 2010. Here we examine the concentration and geochemistry of the Hekla 1947 tephra in 14 peat profiles from across Northern Ireland. Electron probe microanalysis of individual tephra shards (n?=?91) reveals that the tephra is of dacitic–andesitic geochemistry and is highly similar to the Hekla 1510 tephra, although spheroidal carbonaceous particle profiles can be used for successful discrimination of the two layers. The highest concentrations of Hekla 1947 are found in western sites, probably reflecting the pathway of the ash fall event due to the prevailing wind direction. Comparable tephra concentrations from two cores (1?km apart) from a single bog and from nearby sites may suggest that tephra shard concentrations in peat profiles reflect ash fallout densities across a specific region, rather than site-specific factors associated with peatlands. This paper firmly establishes Hekla 1947 as a useful chronostratigraphic marker for the twentieth century, although within a restricted zone.

The lateritic profile of Balkouin, Burkina Faso: geochemistry, mineralogy and genesis

This study reports on the geochemical and mineralogical characterization of a lateritic profile cropping out in the Balkouin area, Central Burkina Faso, aimed at obtaining a better understanding of the processes responsible for the formation of the laterite itself and the constraints to its development. The lateritic profile rests on a Paleoproterozoic basement mostly composed of granodioritic rocks related to the Eburnean magmatic cycle passing upwards to saprolite and consists of four main composite horizons (bottom to top): kaolinite and clay-rich horizons, mottled laterite and iron-rich duricrust. In order to achieve such a goal, a multi-disciplinary analytical approach was adopted, which includes inductively coupled plasma (ICP) atomic emission and mass spectrometries (ICP-AES and ICP-MS respectively), X-ray powder diffraction (XRPD), scanning electron microscopy with energy dispersive spectrometry (SEM-EDS) and micro-Raman spectroscopy.

The geochemical data, and particularly the immobile elements distribution and REE patterns, show that the Balkouin laterite is the product of an in situ lateritization process that involved a strong depletion of the more soluble elements (K, Mg, Ca, Na, Rb, Sr and Ba) and an enrichment in Fe; Si was also removed, particularly in the uppermost horizons. All along the profile the change in composition is coupled with important changes in mineralogy. In particular, the saprolite is characterized by occurrence of abundant albitic plagioclase, quartz and nontronite; kaolinite is apparently absent. The transition to the overlying lateritic profile marks the breakdown of plagioclase and nontronite, thus allowing kaolinite to become one of the major components upwards, together with goethite and quartz. The upper part of the profile is strongly enriched in hematite (+ kaolinite). Ti oxides (at least in part as anatase) and apatite are typical accessory phases, while free aluminum hydroxides are notably absent. Mass change calculations emphasize the extent of the mass loss, which exceeds 50 wt% (and often 70 wt%) for almost all horizons; only Fe was significantly concentrated in the residual system.

The geochemical and mineralogical features suggest that the lateritic profile is the product of a continuous process that gradually developed from the bedrock upwards, in agreement with the Schellmann classic genetic model. The laterite formation must have occurred at low pH (? 4.5) and high Eh (? 0.4) values, i.e., under acidic and oxidizing environments, which allowed strongly selective leaching conditions. The lack of gibbsite and bohemite is in agreement with the compositional data: the occurrence of quartz (± amorphous silica) all along the profile was an inhibiting factor for the formation of free aluminum hydroxides.

Using geostatistical Bayesian Updating to integrate airborne radiometrics and soil geochemistry to improve mapping for mineral exploration

Mineral exploration programmes around the world use data from remote sensing, geophysics and direct sampling. On a regional scale, the combination of airborne geophysics and ground-based geochemical sampling can aid geological mapping and economic minerals exploration. The fact that airborne geophysical and traditional soil-sampling data are generated at different spatial resolutions means that they are not immediately comparable due to their different sampling density. Several geostatistical techniques, including indicator cokriging and collocated cokriging, can be used to integrate different types of data into a geostatistical model. With increasing numbers of variables the inference of the cross-covariance model required for cokriging can be demanding in terms of effort and computational time. In this paper a Gaussian-based Bayesian updating approach is applied to integrate airborne radiometric data and ground-sampled geochemical soil data to maximise information generated from the soil survey, to enable more accurate geological interpretation for the exploration and development of natural resources. The Bayesian updating technique decomposes the collocated estimate into a production of two models: prior and likelihood models. The prior model is built from primary information and the likelihood model is built from secondary information. The prior model is then updated with the likelihood model to build the final model. The approach allows multiple secondary variables to be simultaneously integrated into the mapping of the primary variable. The Bayesian updating approach is demonstrated using a case study from Northern Ireland where the history of mineral prospecting for precious and base metals dates from the 18th century. Vein-hosted, strata-bound and volcanogenic occurrences of mineralisation are found. The geostatistical technique was used to improve the resolution of soil geochemistry, collected one sample per 2 km2, by integrating more closely measured airborne geophysical data from the GSNI Tellus Survey, measured over a footprint of 65 x 200 m. The directly measured geochemistry data were considered as primary data in the Bayesian approach and the airborne radiometric data were used as secondary data. The approach produced more detailed updated maps and in particular maximized information on mapped estimates of zinc, copper and lead. Greater delineation of an elongated northwest/southeast trending zone in the updated maps strengthened the potential to investigate stratabound base metal deposits.

Spatial Distribution of Soil Geochemistry in Geoforensics

Two common scenarios in Geoforensics (definition in text) are considered: the provenance, or localization of unknown samples and the question of sample variability at scenes of crime/alibi locations. Both have been discussed in forensic and soil science publications, but mostly within a theoretical or non-forensic context. These previous publications provide context for the two case study scenarios (one actual, one based on a range of criminal casework) that consider provenance and variability. A challenging scientific question in geoforensics is the provenance question: ‘where may this sample have come from?’ A question the Tellus data can assist in answering. The question of variation between samples maybe less of a challenge, yet variation between a suspect sample within a scene of crime requires detailed sampling. Variation on a larger (tens to hundreds of kilometres) scale may provide useful intelligence on where a sample came from. To summarise, databases such as Tellus and TellusBorder may be used as effective tools to assist in the search for the origin of displaced soil and sediment