Variability in quartz OSL signals caused by measurement uncertainties: Problems and solutions |
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| Institution: | 1. Centre for Archaeological Science, School of Earth and Environmental Sciences, University of Wollongong, Wollongong, NSW 2522, Australia;2. ARC Centre of Excellence for Australian Biodiversity and Heritage, University of Wollongong, Wollongong, NSW 2522, Australia;3. Department of Statistical Science, University College London, Gower Street, London WC1E 6BT, UK;4. School of Resources, Environment and Safety Engineering, Hunan University of Science and Technology, Hunan, China;1. Institute of Earth Surface Dynamics, University of Lausanne, 1015, Lausanne, Switzerland;2. Department of Earth Sciences, ETH Zürich, 8092, Zürich, Switzerland;3. Institute of Geological Sciences, University of Bern, 3012, Bern, Switzerland;4. Free University of Leysin, 1854, Leysin, Switzerland;5. Géosciences Rennes, CNRS UMR 6118, Université de Rennes 1, 35042, Rennes, France;6. Soil Geography and Landscape Group and the Netherlands Centre for Luminescence Dating, Wageningen University, 6708, Wageningen, The Netherlands;1. CNRS – Université Bordeaux Montaigne, UMR 5060, IRAMAT-CRP2A, Maison de l''archéologie, Esplanade des Antilles, 33607 Pessac Cedex, France;2. Center for Nuclear Technologies, Technical University of Denmark, DTU Risø Campus, DK-4000 Roskilde, Denmark;3. LSCE/IPSL, UMR CEA-CNRS-UVSQ, Avenue de la Terrasse, 91198 Gif sur Yvette Cedex, France;1. Institute for Geology, University of Innsbruck, 6020, Austria;2. ARC Centre of Excellence for Australian Biodiversity and Heritage, GeoQuest Research Centre, University of Wollongong, 2500, Australia;1. Faculty of Environmental Sciences and Engineering, Babe?-Bolyai University, Cluj-Napoca, Romania;2. Interdisciplinary Research Institute on Bio-Nano-Science, Babe?-Bolyai University, Cluj-Napoca, Romania;3. Faculty of Biology and Geology, Babe?-Bolyai University, Cluj-Napoca, Romania;4. Nordic Laboratory for Luminescence Dating, Department of Geoscience, Aarhus University, DTU Risø Campus, Roskilde, Denmark;5. Center for Nuclear Technologies, Technical University of Denmark, DTU Risø Campus, Roskilde, Denmark;6. Institute of Geography and Earth Sciences, Aberystwyth University, Aberystwyth, UK;7. McDonald Institute for Archaeological Research, University of Cambridge, Cambridge, UK;1. Center for Nuclear Technologies, Technical University of Denmark, DTU Risø Campus, DK-4000 Roskilde, Denmark;2. Nordic Laboratory for Luminescence Dating, Department of Geoscience, Aarhus University, DTU Nutech, Risø Campus, DK-4000 Roskilde, Denmark;3. Côa Parque, Fundação para a Salvaguarda e Valorização do Vale do Côa, Rua do Museu, 5150-610 Vila Nova de Foz Côa, Portugal;1. State Key Laboratory of Isotope Geochemistry, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, China;2. Department of Earth Sciences, University of Hong Kong, Hong Kong, China;3. Centre for Archaeological Science, School of Earth and Environmental Sciences, University of Wollongong, Wollongong, NSW 2522, Australia;4. Key Laboratory of Cenozoic Geology and Environment, Institute of Geology and Geophysics, Chinese Academy of Sciences, Beijing 100049, China |
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| Abstract: | We simulated the variability in measured quartz optically stimulated luminescence (OSL) signals and dose response curves (DRCs) caused by measurement uncertainties, including counting statistics and instrumental irreproducibility. We find that these measurement errors can give rise to large variations in the observed luminescence signal and contribute to among-aliquot or among-grain scatter in DRCs and equivalent dose (De) values. Different measurement systems (i.e., luminescence readers) may have different counting statistics properties and, hence, may exhibit differing extents of variation in the observed OSL signal, even for the same sample. Our simulation shows that the random measurement uncertainties may result in some grains or aliquots being ‘saturated’ (that is, the measured natural signal is consistent with, or lies above, the saturation level of the measured DRC) and that the rejection of these ‘saturated’ grains may result in a truncated De distribution, with De underestimation for samples with natural doses close to saturation (e.g., twice the characteristic saturation dose, D0). We propose a new method to deal with this underestimation problem, in which standardised growth curves (SGCs) are established and the weighted-mean natural signal (Ln/Tn) from all measured grains is projected on to the corresponding SGCs to determine De. Our simulation results show that this method can produce reliable De estimates up to 5D0, which is far beyond the conventional limit of ～2D0 using the standard SAR procedure. |
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| Keywords: | Counting statistics Standardised growth curves Instrumental irreproducibility |
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