Testing the applicability of standardised growth curves (SGCs) for OSL signals of quartz grains from the Yangtze Delta,China

The standardised growth curve (SGC) technique has the potential to save instrument time for equivalent dose (D_e) determination when applying single-aliquot regenerative-dose (SAR) protocol during optically stimulated luminescence (OSL) measurements. In this study, we test the applicability of two commonly used SGC procedures for OSL signals of quartz grains from aqueous deposits of the Yangtze Delta in China, which have been reported for weak luminescence signals and suffering from partial bleaching. Multiple silt-sized and sand-sized fractions of quartz samples from eight cores are used to construct SGCs by test dose standardisation (TD-SGC) and least-squares normalisation (LS-SGC), respectively. Three strategies, i.e. region-specific (SGC_R), region with core-specific (SGC_R + C) and core-specific (SGC_C), are adopted to categorise these normalised data into different SGC datasets. The large variability of dose response signals is substantially reduced by the SGC procedures for most of these datasets. Hence, common SGCs for a variety of samples from the Yangtze Delta can be established, irrespective of their distinctive particle sizes and luminescence characteristics. The D_e values are then estimated using both TD-SGC and LS-SGC procedures for samples from a specific core. Comparing to the full SAR protocol, the TD-SGC procedure roughly gives reproducible D_e estimates lower than ～100 Gy while the LS-SGC procedure derives generally consistent D_e estimates of up to ～230 Gy. Although LS-SGC_C and LS-SGC_R + C procedures replicate the most consistent D_e values, the LS-SGC_R procedure performs better in efficiency with a slightly less accuracy. In addition to careful comparison of LS-SGC and full SAR procedures, we suggest that a synchronous ratio derived by the chosen regenerative dose and its response signal for re-normalisation can be used to predict the LS-SGC D_e reliability on samples from similar sedimentary environments.