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Quantitative assessment of Pb sources in isotopic mixtures using a Bayesian mixing model

Quantitative assessment of Pb sources in isotopic mixtures using a Bayesian mixing model
Quantitative assessment of Pb sources in isotopic mixtures using a Bayesian mixing model

Lead (Pb) isotopes provide valuable insights into the origin of Pb within a sample, typically allowing for reliable fingerprinting of their source. This is useful for a variety of applications, from tracing sources of pollution-related Pb, to the origins of Pb in archaeological artefacts. However, current approaches investigate source proportions via graphical means, or simple mixing models. As such, an approach, which quantitatively assesses source proportions and fingerprints the signature of analysed Pb, especially for larger numbers of sources, would be valuable. Here we use an advanced Bayesian isotope mixing model for three such applications: Tracing dust sources in pre-Anthropogenic environmental samples, tracking changing ore exploitation during the Roman period, and identifying the source of Pb in a Roman-Age mining artefact. These examples indicate this approach can understand changing Pb sources deposited during both pre-Anthropogenic times, when natural cycling of Pb dominated, and the Roman period, one marked by significant anthropogenic pollution. Our archaeometric investigation indicates clear input of Pb from Romanian ores previously speculated, but not proven, to have been the Pb source. Our approach can be applied to a range of disciplines, providing a new method for robustly tracing sources of Pb observed within a variety of environments.

2045-2322
1-16
Longman, Jack
26a3c4e3-79d6-4102-9708-a5b02b97121d
Veres, Daniel
67b7de50-1043-4bfb-a5df-bc87feeefc63
Ersek, Vasile
d6247272-dbeb-4449-9eca-bb1a4a75a9ca
Phillips, Donald L.
056b2a99-412d-48c7-bfed-1d984ad11b93
Chauvel, Catherine
4d8ed955-ac33-414f-9e55-7c1ddab70149
Tamas, Calin G.
98e0d54f-1560-4315-88bd-29d72885834f
Longman, Jack
26a3c4e3-79d6-4102-9708-a5b02b97121d
Veres, Daniel
67b7de50-1043-4bfb-a5df-bc87feeefc63
Ersek, Vasile
d6247272-dbeb-4449-9eca-bb1a4a75a9ca
Phillips, Donald L.
056b2a99-412d-48c7-bfed-1d984ad11b93
Chauvel, Catherine
4d8ed955-ac33-414f-9e55-7c1ddab70149
Tamas, Calin G.
98e0d54f-1560-4315-88bd-29d72885834f

Longman, Jack, Veres, Daniel, Ersek, Vasile, Phillips, Donald L., Chauvel, Catherine and Tamas, Calin G. (2018) Quantitative assessment of Pb sources in isotopic mixtures using a Bayesian mixing model. Scientific Reports, 8 (1), 1-16, [6154]. (doi:10.1038/s41598-018-24474-0).

Record type: Article

Abstract

Lead (Pb) isotopes provide valuable insights into the origin of Pb within a sample, typically allowing for reliable fingerprinting of their source. This is useful for a variety of applications, from tracing sources of pollution-related Pb, to the origins of Pb in archaeological artefacts. However, current approaches investigate source proportions via graphical means, or simple mixing models. As such, an approach, which quantitatively assesses source proportions and fingerprints the signature of analysed Pb, especially for larger numbers of sources, would be valuable. Here we use an advanced Bayesian isotope mixing model for three such applications: Tracing dust sources in pre-Anthropogenic environmental samples, tracking changing ore exploitation during the Roman period, and identifying the source of Pb in a Roman-Age mining artefact. These examples indicate this approach can understand changing Pb sources deposited during both pre-Anthropogenic times, when natural cycling of Pb dominated, and the Roman period, one marked by significant anthropogenic pollution. Our archaeometric investigation indicates clear input of Pb from Romanian ores previously speculated, but not proven, to have been the Pb source. Our approach can be applied to a range of disciplines, providing a new method for robustly tracing sources of Pb observed within a variety of environments.

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s41598-018-24474-0 - Version of Record
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More information

Accepted/In Press date: 26 March 2018
e-pub ahead of print date: 18 April 2018

Identifiers

Local EPrints ID: 420167
URI: http://eprints.soton.ac.uk/id/eprint/420167
ISSN: 2045-2322
PURE UUID: 20a87559-7fc3-48ce-917a-62c48bfe7e2b

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Date deposited: 30 Apr 2018 16:30
Last modified: 07 Oct 2020 00:41

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