Stochastic modelling of multi-grain equivalent dose (De) distributions: Implications for OSL dating of sediment mixtures
Stochastic modelling of multi-grain equivalent dose (De) distributions: Implications for OSL dating of sediment mixtures
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DOI：
10.1016/j.quageo.2008.12.001
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发表时间：
2009-06-01
影响因子：
2.7
通讯作者：
Roberts, R. G.
中科院分区：
文献类型：
--
作者：
Arnold, L. J.;Roberts, R. G.
最近的一些光释光（OSL）研究引用沉积后混合作为一个主要来源的等效剂量（D-e）散射在一系列沉积环境，包括那些以前被认为是“最适合”的OSL测年。沉积物混合的潜在危险性意味着这个问题往往只能通过对D-E数据集进行仔细的统计分析来确定。本研究的目的是解决一些重要的问题与混合的D-E分布的表征和统计处理在多粒度的分析，使用模拟的D-E数据集与一个简单的随机模型。使用这种蒙特卡罗方法，我们能够生成理论分布的单颗粒D-e值，然后随机混合在一起，模拟多颗粒等分D-e分布包含已知数量的混合组件和已知的相应的掩埋剂量。一系列的敏感性测试进行了使用沉积物混合物与不同年龄的剂量成分，不同数量的混合成分，和不同类型的剂量成分分布（完全漂白，非均匀漂白和显着过度分散的D-电子分布）。我们的建模模拟的结果揭示了固有的问题时遇到的混合沉积样品的多粒度D-E估计技术。“体模”剂量成分（即不对应于原始单颗粒混合成分的离散剂量群体）是多颗粒D-e分析的“平均”效应的必然结果，并且阻止了对所有测试的多颗粒混合物用有限混合物模型（FMM）识别正确数量的混合成分。我们的研究结果警告使用的FMM的多粒等分De数据集，即使等分组成的只有几粒。(C)2008爱思唯尔有限公司保留所有权利。
A number of recent optically stimulated luminescence (OSL) studies have cited post-depositional mixing as a dominant source of equivalent dose (D-e) scatter across a range of sedimentary environments, including those previously considered 'best suited' for OSL dating. The potentially insidious nature of sediment mixing means that this problem may often only be identifiable by careful statistical analysis of D-e data sets. This study aims to address some of the important issues associated with the characterisation and statistical treatment of mixed D-e distributions at the multi-grain scale of analysis, using simulated D-e data sets produced with a simple stochastic model. Using this Monte Carlo approach we were able to generate theoretical distributions of single-grain D-e values, which were then randomly mixed together to simulate multi-grain aliquot D-e distributions containing a known number of mixing components and known corresponding burial doses. A range of sensitivity tests were undertaken using sediment mixtures with different aged dose components, different numbers of mixing components, and different types of dose component distributions (fully bleached, heterogeneously bleached and significantly overdispersed D-e distributions). The results of our modelling simulations reveal the inherent problems encountered when dating mixed sedimentary samples with multi-grain D-e estimation techniques. 'Phantom' dose components (i.e. discrete dose populations that do not correspond to the original single-grain mixing components) are an inevitable consequence of the 'averaging' effects of multi-grain D-e analysis, and prevent the correct number of mixing components being identified with the finite mixture model (FMM) for all of the multi-grain mixtures tested. Our findings caution against use of the FMM for multi-grain aliquot De data sets, even when the aliquots consist of only a few grains. (C) 2008 Elsevier Ltd. All rights reserved.