Statistical modelling of single grain quartz D"e distributions and an assessment of procedures for estimating burial dose [An article from: Quaternary Science Reviews] Buy on Amazon

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Statistical modelling of single grain quartz D"e distributions and an assessment of procedures for estimating burial dose [An article from: Quaternary Science Reviews]

Book Details

PublisherElsevier
ISBN / ASINB000P6XM6S
ISBN-13978B000P6XM68
MarketplaceCanada  🇨🇦

Description

This digital document is a journal article from Quaternary Science Reviews, published by Elsevier in 2006. The article is delivered in HTML format and is available in your Amazon.com Media Library immediately after purchase. You can view it with any web browser.

Description:
It is possible to increase the accuracy of the optical dating of some Quaternary deposits by deriving age estimates from individual quartz grains. Age estimates from individual grains within single samples display varying degrees of inconsistency however and this paper address the difficulties in reducing complex distributions of single-grain age estimates to single accurate sample ages using existing statistical age models. A modelled response of the quartz OSL signal to irradiation and illumination (both in the laboratory and under natural conditions) was used to test the accuracy of various published statistical age-models. 'Aeolian' and 'fluvial' transport conditions were simulated by adjusting the wavelength range of the daylight spectrum and the incident photon flux during the simulated bleaching event. A heterogeneous mix of grains was produced using a Monte Carlo approach, in which key irradiation and bleaching parameters were varied for each simulated grain, and the accuracy of published statistical models assessed. Results suggest that no single age-model is appropriate for all modelled cases. A formal decision process is suggested and shown to make appropriate choices between the available age-models in each of the modelled cases and in ~85% of cases using 43 known-age sediment samples.
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