Testing the accuracy of quartz OSL dating using a known-age Eemian site on the river Sula, northern Russia

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1 Quaternary Geochronology 2 (27) Research paper Testing the accuracy of quartz OSL dating using a known-age Eemian site on the river Sula, northern Russia A.S. Murray a,, J.I. Svendsen b, J. Mangerud b, V.I. Astakhov c a Nordic Laboratory for Luminescence Dating, Department of Earth Science, University of Aarhus, Risø National Laboratory, DK-4 Roskilde, Denmark b Department of Geoscience and Bjerknes Centre for Climate Research, University of Bergen, Allégtaten 41, N-57 Bergen, Norway c Geological Faculty, St. Petersburg University, Universitetskaya 7/9, St. Petersburg 19934, Russian Federation Received 9 April 26; accepted 1 April 26 Available online 14 June 26 Abstract Quartz optically stimulated luminescence (OSL) forms the basis for the chronology of Weichselian ice advances in Arctic Eurasia developed over the last few years. There is almost no age control on this chronology before 4 ka, except for some marine sediments correlated with marine isotope stage (MIS) 5e on the basis of their palaeofauna. Results from more southern latitudes have shown that dose estimates based on quartz OSL and the single aliquot regenerative (SAR) dose procedure may underestimate the age of MIS 5e deposits. Here we use the same method to date well-described marine sediments, thought to have been deposited during the very beginning of the Eemian interglacial at 13 ka, and exposed in two sections on the river Sula in northern Russia. Various qualitycontrol checks are used to show that the OSL behaviour is satisfactory; the mean of 16 ages is 11272ka (s ¼ 9 ka). This represents an underestimate of 14% compared to the expected age, a discrepancy similar to that reported elsewhere. In contrast to SAR, the single aliquot regeneration and added (SARA) dose procedure corrects for any change in sensitivity during the first OSL measurement. The SARA results are shown to be 1% older than those from SAR, confirming the geological age estimate and suggesting that SAR ages may underestimate older ages (larger doses), despite their good performance in the younger age range. r 26 Elsevier Ltd. All rights reserved. Keywords: OSL dating; Eemian; MIS 5e; Quartz; Luminescence dating; Accuracy; SAR; SARA 1. Introduction Corresponding author. Tel.: ; fax: address: andrew.murray@risoe.dk (A.S. Murray). The last time the Barents Kara Ice Sheet advanced onto mainland Russia was during the Middle Weichselian (Valdaian) beyond the limit of 14 C dating (Svendsen et al., 24). In the large European project Quaternary Environment of the Eurasian North (QUEEN) the chronology of the glacial history, and indeed other stratigraphic events, was almost entirely based on optically stimulated luminescence (OSL) ages (QUEEN, 1999, 21, 24). From this chronology, it was concluded that the northern rim of the Eurasian continent was inundated at least twice during the Early/Middle Weichselian by the Barents Kara Ice Sheet. The precision and accuracy of these OSL ages is thus of considerable importance. An ageindependent test of internal consistency between sites spread over hundreds of km and with widely different present-day dose rates was obtained when samples from a number of sections in Lake Komi beach sediments all yielded ages in the range 8 1 ka (Mangerud et al., 24), but this did not test the accuracy of these ages. Some attempt has been made to test the method against marine isotope stage (MIS) 5e deposits, using individual samples and sites during the QUEEN project (e.g., Mangerud et al., 1999), but these were neither intensive nor systematic. Murray and Olley (22) have summarised a comparison between quartz single aliquot regenerative (SAR) OSL ages and independent age control. From their data, it was concluded that there is no significant systematic difference over the entire age range considered (up to about 6 ka). However it is also known that, at the individual grain level, one can observe sensitivity-corrected natural signals that lie above the SAR growth curve (Feathers, 23; Yoshida /$ - see front matter r 26 Elsevier Ltd. All rights reserved. doi:1.116/j.quageo

2 A.S. Murray et al. / Quaternary Geochronology 2 (27) et al., 2). For these grains, the SAR procedure clearly overestimates the equivalent dose (D e ), and it is not unreasonable to assume that there must be other grains for which the natural signals do intersect the growth curve, but at too high a dose. Bailey (24) has suggested a model to explain this, but no significant testing has yet been carried out. On the other hand, close examination of the data presented by Murray and Olley (22) suggests that for samples correlated to MIS 5e, there is a tendency for the OSL ages to lie below the expected age. Murray and Funder (23) undertook a case study at such a site, which they argued must have been deposited between 128 and 132 ka. The SAR OSL age was ka, which is just consistent (within 2 standard errors) with the expected age range, but only when all estimates of systematic uncertainty were included. Schokker et al. (24) report a related investigated at a site on the lower Rhine. Stokes et al. (23) also report a comparison of five OSL ages with an oxygen isotope model age curve, and other independent age control, and again there is a tendency for their OSL ages to systematically underestimate the expected ages, but only by 1%; this was not considered significant by those authors. In our opinion, there seems little doubt that SAR ages perform well when compared with independent age control over the 14 C age range, but it is certainly possible that SAR underestimates ages by 1% around MIS 5e. This paper investigates this hypothesis by considering a further case study from Arctic Russia. 2. Site description and sampling On the river Sula (671. N, E), a northern tributary to the Pechora River, we have dated two sections (21 and 22) with well-exposed, foreshore marine sediments, described in Mangerud et al. (1999). A crucial point is that these sections contain an in situ mollusc fauna indicating coastal water several degrees warmer than at present day; these must certainly indicate a warm interglacial. These and related sites have, for decades, been ascribed to the socalled Boreal transgression that has, in turn, been accepted as correlated with the Eemian in the Russian literature (e.g., Devyatova, 1982; Lavrova, 1949; Lavrova and Troitsky, 196). Based on a detailed correlation with western European pollen stratigraphy by Funder et al. (22), we consider the sediments should have an age of about 13 ka (beginning of the interglacial), and following Murray and Funder (23) an uncertainty on this age of 72 ka is adopted. At the base of site 22 (Fig. 1), there is a dark silt and clay (poorly exposed during our visits) containing a rather cool mollusc fauna, which may possibly date from the Late Saalian deglaciation. The well-exposed sandy unit begins with a thin gravel in tabular foresets containing paired Mytilus edulis. The gravel is interpreted as a foreshore facies and is overlain by a generally upward fining sand with a parallel increase in bioturbation. The fauna is dominated by large in situ individuals of Arctica islandica Fig. 1. Location map and Sula 22 section, with sampling positions and SAR OSL ages. The sediment log (composite) from Sula 22 is from Ulvedal (23). (Log) refers to column 1, Table 1. and with a few Cerastoderma edule and Zirphaea crispata. The marine formation is cut by an erosional unconformity that is, in turn, overlain by Weichselian age sand and a black lacustrine clay (Fig. 1). The marine sand, from which all samples reported here were collected, was deposited in shallow water and during a short period, almost certainly less than 5 years. The site Sula 21 lies 4 km upstream of Sula 22, but the sediment sequence here is not as thick as at site 22. The correlation with site 22 appears secure. Both sites indicate that the corresponding Eemian shoreline was about 5 m above present sea level, which is explained by isostatic depression produced by the large Saalian (MIS 6) ice sheet that probably covered the entire region. 3. Measurement facilities and methods All OSL measurements were made on a Risø TL/OSL reader model DA12 or 15 (Bøtter-Jensen et al., 2) equipped with blue light stimulation (4773 nm; 5 mw cm 2 ). Photon detection was through 7.5 mm of U34 glass filter. Samples obtained in 22 were taken in opaque plastic tubes driven into a cleaned face in the section. The older samples (log numbers 1 3 and 6 [Sula 22] and 4 5 [Sula 21] in Table 1) were collected by digging the sediment from a recently cleaned section into black plastic bags. This was certainly not as good method as latter, but care was taken that the sand should not be exposed to light.

3 14 ARTICLE IN PRESS A.S. Murray et al. / Quaternary Geochronology 2 (27) Table 1 Summary of dosimetry, D e measurements and luminescence ages Log no. Sample no. Field no. Depth (m) 238 U (Bq kg 1 ) 226 Ra (Bq kg 1 ) 232 Th (Bq kg 1 ) 4 K (Bq kg 1 ) Sat. (%) Obs. (%) Dose rate (Gy ka 1 ) SAR D e (Gy) n SAR age (ka) SARA D e (Gy) n SARA age (ka) /2 8 n.a. n.a. n.a. n.a. 27* n.a. n.a. n.a. n.a. 27* n.a. n.a. n.a. n.a. 27* y n.a. n.a. n.a. n.a. 27* y n.a. n.a. n.a. n.a. 27* * H H H H H H H H H H All samples from Sula 22 except those marked y, which are from Sula 21. The gamma spectrometry calibration etc. is described in Murray et al. (1987). Conversion factors from activity concentrations to dose rate are taken from Olley et al. (1996). Dose rates in the first five samples are based on field gamma spectrometry and laboratory beta counting; n.a. not available. Saturated water content (those marked * are estimated) corrections, calculated cosmic ray contributions and an internal quartz dose rate of.6 Gy ka 1 are included in the dose rate data. The uncertainties are estimated standard errors, and n is the number of individual aliquots contributing to D e.

4 A.S. Murray et al. / Quaternary Geochronology 2 (27) On return to the laboratory, the light-exposed material at the end of each tube was retained for dose rate and water content analysis; the inner portion was wet-sieved to recover the mm grain size. This was then cleaned, etched in the usual manner (HCl, H 2 O 2 and HF) and tested for feldspar contamination using infrared (IR) stimulation. No significant IR- (compared to blue) stimulated signal was detected in any sample. D e determination used a SAR protocol (Murray and Wintle, 2, 23) and the initial.8 s integral of the OSL signal, less a background estimated from the last 1 s of stimulation. Dose rate calculations are based on high-resolution gamma spectrometry (Murray et al., 1987). Calculated (Prescott and Hutton, 1994) cosmic ray dose rates range from, at the top of the Sula 22 profile,.14 Gy ka 1 to, at the bottom,.7 Gy ka 1. Natural and saturated water contents were measured in the laboratory. For calculation of total dose rates, we have assumed that the sediments were saturated by water or ice throughout the burial period; this is because Pleistocene permafrost started to degrade in this area only by 8ka 14 CBP(Tveranger et al., 1995), and patches of thin permafrost still occur nearby. Nevertheless, we must recognise that the Sula 22 section is located in the valley slope; during some of the time when the sediments were not frozen, it is possible that the upper part of the sequence was located above the ground water table. Five of the earlier samples taken in 1994 and 1995 (log numbers 1 5 in Table 1) are exceptions to the above, in that dose rates are based on field gamma counting and laboratory beta counting, and saturated water contents (needed only for beta dose rate calculations) are assumed, based on the measurements on the remaining samples. 4. Radionuclide concentrations All available radionuclide concentrations (log no in Table 1) are summarised in Table 1 and Fig. 2. Although there are peaks in the 226 Ra and 232 Th concentrations at 6 m depth, these do not contribute significantly to the total dose rates, which are dominated by 4 K at this site. Bq.kg -1 Bq.kg -1 Bq.kg -1 Gy.ka The average total dose rate is about 1 Gy ka 1, with a range of only 2% about this value. There is no evidence for gross radioactive disequilibrium between 238 U and 226 Ra, although the large uncertainties on the 238 U measurements limit the usefulness of this comment. 5. Luminescence characteristics Fig. 3 (inset) presents an example (using sample H22546) of a regenerated decay curve for this material (natural curves were indistinguishable from regenerated). The decay curves are typical for quartz, and appear to be dominated by the fast component (Bailey et al., 1997; Jain et al., 23). A representative growth curve is also shown in Fig. 3; this is well represented (solid line) by the sum of two saturating exponential curves (shown separately as dashed dot dot lines). The sensitivity-corrected natural signal intercepts the growth curve at about 55% of the saturation OSL value; it is interesting to note that, at the corresponding dose, the first exponential component of the growth curve is fully saturated (D ¼ 44 Gy), whereas the second component is only at 3% of its saturated value (D ¼ 45 Gy). The lack of dependence of D e on preheat temperature is shown in Fig. 4a,b, together with the corresponding recycling ratio and recuperation values. All results are insensitive to variations in preheat temperature; recuperation values may show a slight systematic trend, but nevertheless do not exceed 1.5% of the D e. A preheat temperature of 26 1C was selected for further work. A summary of all recycling ratios and recuperation values from all aliquots used for D e estimation in this study is given in Fig. 5; the great majority (8%) of recuperation values lie below 2%, and the mean recycling ratio (inset) is (n ¼ 263), with a relative standard deviation Corrected OSL Stimulation time, s Natural 3x1 4 2x OSL, (.16 s) -1 Depth, m Ra 232 Th 4 K Total dose rate 2 D e =168 Gy H Laboratory dose, Gy 1 Fig. 2. Radionuclide concentrations and total dose rates at Sula 22. Fig. 3. SAR growth curve for one aliquot of sample H22546 (Table 1, log 8). Recycling and recuperation points are shown as unfilled symbols. The best fit solid line is the sum of the two exponential growth curves shown as dashed dot dot lines. A typical regenerated OSL decay curve is shown inset.

5 16 ARTICLE IN PRESS A.S. Murray et al. / Quaternary Geochronology 2 (27) D e, Gy Recycling Ratio Frequency (a) mean 1.21±.5 (b) mean = 1.17±.12 (n=95) H22552; Cut heat 16 C Preheat temperature, C Fig. 4. (a) Preheat plateau for sample H22552 (Table 1, log 14; 3 aliquots at each temperature); (b) recycling and recuperation for the same aliquots. Frequency (n=272) Frequency Mean = 1.14 ±.4 (n=263) Measured/given dose ratio Recycling ratio Fig. 6. Summary dose recovery data for all aliquots (Table 1, log 6 16). Vertical line is drawn at mean value. 2 1 Recuperation, %N Recuperation, %N Fig. 5. Summary of all available recuperation and (inset) recycling data from this study (vertical line is drawn at mean value). (RSD) of 6%. Finally, Fig. 6 presents a summary of 95 dose recovery measurements for the last 11 samples in Table 1, with a mean of and a RSD of 12%. It is clear from all these summary statistics that our SAR protocol is able to measure a laboratory dose both accurately and precisely. It now remains to be tested whether it can do the same for a dose absorbed in nature. 6. Luminescence ages All the mean estimates of D e from 16 samples are summarised in Table 1. This data set includes the five samples for which dosimetry is based on field gamma and laboratory beta counting; these have been presented previously by Mangerud et al. (1999). Some values of D e (and thus ages) in Table 1 are significantly different from the earlier published values; the previous D e values were based on very few aliquots (between 3 and 7) and all have been completely remeasured to make them consistent with current practice. The dependence of D e on dose rate is shown graphically in Fig. 7. The two variables are highly correlated (R 2 ¼ :89) and the slope of the line is 113 ka, or 112 ka if the line is forced through the origin. For comparison, the lines representing the expected age range are shown dashed; only two or three of the data points are consistent with the expected slopes. The age data are presented as a histogram (inset to Fig. 7); they are normally distributed, and the mean age (weighted or unweighted) is ka, or 77 ka if a further 5% systematic uncertainty is included (Murray and Funder, 23). We conclude that the mean Equivalent dose, Gy expected age range Age, ka Frequency slope=113 ka slope= ka Dose rate, Gy.ka -1 Fig. 7. Relationship between equivalent dose and dose rate for all samples. The solid regression line is not forced through the origin. The expected age range is shown as two dashed lines. A histogram of all ages is shown inset.

6 A.S. Murray et al. / Quaternary Geochronology 2 (27) SAR luminescence age underestimates the expected age of 13 ka by up to 14% (depending on the duration of the transgression). There are various possible explanations for such an underestimate: (i) Dose rate effects: The laboratory dose rate is 41 9 times that in nature, and a combination of charge competition and trap stability effects could mean that the laboratory-generated growth curve does not apply to the natural signal. However Bailey (24) predicts that this effect should lead to an age overestimation, rather than the underestimation we find here. (ii) Variations in dose rate: It is assumed that the dose rate has been constant through time. If the sediment was deposited out of secular equilibrium, or if, after deposition, it behaved as an open system with respect to radioactive nuclides, then this assumption may be incorrect. Murray and Funder (23) argued that this was the explanation for two of their 22 ages appearing as outliers in their coastal marine Eemian site on the south-east coast of Denmark. Even with those two excluded, their mean OSL age underestimated by 9%. We are less concerned by this possibility here; despite a factor of two variations in measured dose rate, the relative standard deviation in the ages is only 8%, and there are no outliers in our age distribution. (iii) Inaccurate estimation of the intensity of the fast component: The initial OSL signal is often contaminated by a thermally less stable slow (S3) component (Singarayer and Bailey, 23; Jain et al., 23). If this slow component contributes significantly to the initial intensity of the OSL signal, then dose underestimation may result when comparing the natural signal (in which this component has thermally faded) with a regenerated signal (in which it does not have time to fade). This would result in a decrease in D e with stimulation time. However, significant contamination would be surprising. The lifetime of the slow (S3) component is about 1 times that of the fast component (Jain et al., 23; Singarayer and Bailey, 23) and it is clear from the decay curves (e.g. inset to Fig. 3) that the initial intensity of the slow component can only be a small fraction of that of the fast. This, coupled with background subtraction using the last 1 s of a total of 4 s stimulation (5S3 lifetime), makes it unlikely that significant contamination has occurred in these cases. The preheat plateau test (Fig. 4) is specifically intended to isolate a thermally stable signal; nevertheless, it must be recognised that our data are not sufficiently sensitive to exclude a 14% difference between the D e at the selected preheat of 26 1C and at the maximum of 3 1C (the observed difference in D e at these two temperatures is 5714%). This issue is considered further in Section 7. (iv) Changes in sensitivity during first stimulation: Murray and Wintle (2) pointed out that SAR protocols such as ours cannot detect changes in sensitivity (from whatever cause) occurring during the preheating or stimulation of the natural OSL signal; nevertheless, they were able to show that such changes were not significant for two samples with much smaller D e than those considered here. They suggested that for single aliquot work, the only reliable argument for the absence of this effect was agreement with known age. However there is a procedure for detecting such changes if multiple aliquots are used the single aliquot regeneration and added (SARA) dose procedure (SARA; Mejdahl and Bøtter-Jensen, 1994). This approach is employed in Section Testing for dependence of D e on integration interval The only reliable way to test for slow-component contamination of the fast component is (i) by fitting linearly modulated OSL data to separate the various components, and then determining the D e value using only the fast-component intensity or (ii) by using an instrumental approach to separate the fast component using preferential IR bleaching of the fast component at elevated temperature (Jain et al., 24). However, there is no established routine approach suitable for application to the 42 OSL signals used here. A less conclusive but more practical approach is to examine the variation of D e with integration time as the integration time is shortened, the signal is dominated more and more by the fast component. To investigate this dependence, all OSL decay curves from the later analyses (log numbers 6 16 in Table 1) were reanalysed using varying initial integration intervals, 1 2 channels, 1 5, 1 1, etc. (each channel corresponds to.16 s). Then all the D e values from all aliquots, derived using the various integration times, were normalised to each other by the results obtained using the shortest integration interval, and these normalised results averaged over all samples. The results (inset to Fig. 8) were fitted with a single exponential decay. From these data, the Measured dose, Gy Integration time, s Norm. D e D e = 146±1 Gy Slope =.88± Laboratory dose, Gy Fig. 8. Typical SARA data set (sample log 8), showing the doses measured using SAR plotted against the doses added in the laboratory. Inset: effect of changing integration interval on equivalent dose. Dose estimates for all aliquots for all samples were normalised to the value obtained by summing channels 1 and 2 (point at.32 s).

7 18 ARTICLE IN PRESS A.S. Murray et al. / Quaternary Geochronology 2 (27) channel (.8 s) integration used in this work underestimates by o3% the value of D e that is obtained when the integration interval is extrapolated to zero. While not conclusively proving that the slow (S3) component does not affect our results significantly, the consistency of this 3% with the variation observed from the preheat plateau (Fig. 4) gives us confidence that any such effect is small. 8. Allowing for initial sensitivity change comparing SAR and SARA D e estimates In the SARA procedure (Mejdahl and Bøtter-Jensen, 1994), groups of aliquots from a single sample are each given a different added dose before any other treatment. The apparent dose in each aliquot is then measured, and the measured dose plotted against the laboratory dose (Fig. 8). In our implementation of this procedure we have used SAR to measure the individual aliquots. Murray (1996) modelled this procedure, and discussed the assumptions required for these data to lie on a straight line, which, when extrapolated back to the laboratory dose axis, would intercept at D e. Any sensitivity change during the first preheat and OSL measurement is reflected in the slope of the regression; in the absence of sensitivity change, this is of unit slope. Fig. 8 illustrates this process with a data set of 48 aliquots from log number 8 in Table 1. The data are clearly consistent with the fitted straight line (of slope.887.4), and the intercept on the horizontal axis is Gy (c.f. SAR 1374 Gy). This process has been repeated for all 16 samples, and the SARA D e and ages are listed in Table 1. The mean slope is (n ¼ 16) and the mean ratio of SARA to SAR D e is (n ¼ 16). Including a systematic uncertainty of 5% gives an average SARA age of 12478ka (n ¼ 16), completely consistent with the expected age. The typical uncertainty on individual ages is 13 ka, to be compared with the observed standard deviation of the 13 ages of 18 ka; it can be deduced that there may be an unexplained residual dispersion of about 1% in the ages. Nevertheless, sensitivity change in the first measurement of these samples appears to contribute significantly to the 14% discrepancy between SAR ages and the expected age. 9. Discussion and conclusions Most (but not all) of the testing of the reliability of quartz single aliquot regenerative (SAR) optically stimulated luminescence (OSL) dating has been undertaken by comparison with 14 C or with other independent dating methods with a younger range of applicability (e.g., Murray and Olley, 22). The application reported in this paper, of SAR dating to an northern Eurasian Eemian deposit, appears to support the suggestion that SAR may begin to underestimate the true age to some degree for samples older than about 4 ka, with a discrepancy of about 1% at 13 ka. From the work reported here, some of this underestimate probably arises from changes in sensitivity during the measurement of the natural signal, and some may arise from contamination of the quartz fastcomponent OSL signal by a less-stable slow component (although this is less certain). However, it would be unwise to accept these two mechanisms as the only sources of significant systematic uncertainty in our OSL ages; open system radionuclide behaviour and inaccurate estimates of long-term water contents are two obvious potential sources of significant systematic error that cannot readily even be identified, far less quantified. More case studies are required before we can state confidently that (i) SAR underestimates are to be expected in this age range, and (ii) the single aliquot regeneration and added does (SARA) approach is more accurate. Even if this proves to be true, it is not clear that SARA should be used instead of SAR in such older material; because of the need to add laboratory doses on top of the natural dose, SARA can only be applied to samples where the natural dose lies at a small fraction of the saturation limit. Moreover, SARA is a timeconsuming multiple aliquot procedure. It provides a lightintensity weighted-average value of equivalent dose (D e ), and precludes any study of the distribution of dose within a sample; it cannot be applied to single grains. Nevertheless, SARA remains the only established measurement procedure that automatically corrects for sensitivity change in the first measurement. Acknowledgements This work is a contribution to the research projects PECHORA II (Paleo Environment of the Russian Arctic) and ICEHUS (The Ice Age development and human settlement in northern Eurasia) both financially supported by the Research Council of Norway. Support from the Nordic Centre of Excellence programme of the Joint Committee of the Nordic Natural Science Research Councils is also gratefully acknowledged. Editorial handling by: R. Gru n References Bailey, R.M., 24. Paper I simulation of dose absorption in quartz over geological timescales and its implications for the precision and accuracy of optical dating. Radiation Measurements 38, Bailey, R.M., Smith, B.W., Rhodes, E.J., Partial bleaching and the decay form characteristics of quartz OSL. Radiation Measurements 27, Bøtter-Jensen, L., Bulur, E., Duller, G.A.T., Murray, A.S., 2. Advances in luminescence instrument systems. Radiation Measurements 32, Devyatova, E.I., Late Pleistocene Natural Environment and Its Impact on Human Population in the North-Dvina Basin and in Karelia. Institute of Geology, Petrozavodsk (in Russian). Feathers, J.K., 23. Single-grain OSL dating of sediments from the Southern High Plains, USA. 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