Direct measurement of the fast component of quartz optically stimulated luminescence and implications for the accuracy of optical dating

Quaternary Geochronology 5 (2010) 559–568

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Research Paper

Direct measurement of the fast component of quartz optically stimulated luminescence and implications for the accuracy of optical dating R.M. Bailey Oxford University Centre for the Environment, University of Oxford, South Parks Road, Oxford OX1 3QJ, UK

a r t i c l e i n f o

a b s t r a c t

Article history: Received 20 March 2008 Received in revised form 29 September 2009 Accepted 1 October 2009 Available online 8 October 2009

The usual practice in optical dating is to derive an equivalent dose (De) (and hence age) from integration of the initial part of the measured optically stimulated luminescence (OSL) signal. This ‘bulk’ OSL signal is known to comprise several semi-independent components, each of which decays at different rates during measurement, and thus contributes a different proportion to the bulk signal as measurement time progresses. Data are presented here which show a strong dependence of De on the bulk signal integration interval, with reduced De for later signal integration intervals resulting from lower medium component De values. This dependence leads to two problems: (i) deciding which signal integral to choose, and (ii) the possibility that all bulk signals will provide systematic age underestimation due to medium component signal contributions. Isolating the fast component of the bulk OSL signal provides a solution to both problems and several methods of achieving this are assessed; an efficient new method is described which is incorporated in to standard single-aliquot regenerative-dose measurement sequences. This method involves the direct measurement of the fast-component signal using infrared (830 nm) stimulation of quartz at 160  C, prior to the standard bulk OSL measurement with 470 nm stimulation. It is shown that the measured quartz infrared stimulated luminescence signals resolve pure fast-component signals and provide De estimates consistent with those from signal deconvolution. This approach can only be applied to samples with relatively bright luminescence emissions, but in these cases is expected to provide a more robust estimate of palaeodose. Ó 2009 Elsevier B.V. All rights reserved.

Keywords: Quartz OSL IRSL Dating Accuracy Component

1. Background Natural quartz can be used as an integrating dosimeter of ionising radiation and optically stimulated luminescence (OSL) signals from quartz are employed to estimate the depositional age of sediments (see Bøtter-Jensen et al., 2003 for examples). The usual practice is to base age estimates on the signal integrated over the initial part of the OSL decay curve (obtained using constant stimulation power), from zero time until w95% signal intensity is reached. The purpose of the work described here is to explore the practical problem of choosing an appropriate OSL signal, or part of such a signal, that gives the best chance of estimating accurately the absorbed dose. It has long been known that the OSL signal from natural quartz comprises several physically distinct components (Bailey et al., 1997; Singarayer and Bailey, 2003; Jain et al., 2003), each with distinct optical cross-sections, thermal stability and dose

E-mail address: [email protected]. 1871-1014/$ – see front matter Ó 2009 Elsevier B.V. All rights reserved. doi:10.1016/j.quageo.2009.10.003

saturation characteristic. A picture is emerging in the literature that sedimentary quartz samples with ‘bulk OSL’ dominated by fastcomponent signals provide accurate age estimates, while those with relatively large medium or slow component signals are associated with inaccurate ages (typically age underestimation) or poor signal behaviour (see Wintle and Murray, 2006 for discussion). In such cases, resolving the individual components and deriving ages from the fast component has been highly advantageous (e.g. Choi et al., 2003; Tsukamoto et al., 2003; Jain et al., 2005; Watanuki et al., 2005). Isolation of the fast component may also be advantageous in the context of poorly bleached samples, where the fast component is expected to be the most fully bleached part of the signal (see Bailey and Arnold, 2006 for example). A natural conclusion from these considerations is that dating should perhaps be based routinely and solely on the fast-component signal (Bailey et al., 1997) and to this end, several different methods for isolating the fast component are discussed in this paper. The magnitude of the fast, and other, signal components can be estimated from curve fitting (Bailey et al., 1997; Bulur et al., 2000; Singarayer and Bailey, 2003; Jain et al., 2003). However, the deconvolution of overlapping exponential functions is a difficult task.

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Fitting multiple-exponential functions is a well known ‘ill-posed’ problem (for discussion see Istratova and Vyvenko, 1998) and requires considerable effort in the context of quartz OSL data before confidence can be placed in the results obtained. A preferable solution would be to measure the fast component directly. Previous results (Singarayer and Bailey, 2004) show that the dependence of the photoionisation cross-section (s) on wavelength (l) differs for the fast and medium components. This, along with earlier observations (Spooner, 1994; Bailey, 1998) suggests that careful selection of stimulation wavelength can reduce the number of components observed during measurement, compared to standard 470 nm stimulation used for dating (i.e. the stimulation photon energy can be reduced below the effective threshold response of a component’s source trap, so that it is not sampled during the OSL measurement). It was demonstrated in Bailey (1998) that the exponential decay of the quartz IRSL (stimulated at 220  C) matches that of the initial part of blue/green-stimulated OSL signal. It was later confirmed by Singarayer and Bailey (2001, 2003) and then by Jain et al. (2003) that IR stimulation (l ¼ 830 nm) at a sample temperature of 160  C isolates (bleaches) only the fast component of the quartz OSL signal. A significant problem however is that at the stimulation powers typically available (w400 mW cm2), full depletion of the fastcomponent signal takes w6 ks (at 160  C), compared to w2 s for similar conditions under blue light stimulation (470 nm, 36 mW cm2), due to the strong wavelength-dependence of s. Typical dating measurements (Wintle and Murray, 2006) made in this way would take an impractically long time and this compares unfavourably to equivalent measurements using blue stimulation. Increased stimulation power may be one possible solution, although with higher stimulation powers significant heating of the sample (and the sample disc) may occur during measurement. Jain et al. (2005) have shown that the medium component is also bleached with IR stimulation at temperatures above w200  C. A further problem is that holding sample temperature at 160  C for several ks is likely to cause significant sensitivity change (luminescence emitted per unit radiation dose per unit mass) through the course of the measurement. Such changes would most likely lead to inaccurate estimates of the absorbed dose (De). Further, the slower signal depletion rate under IR stimulation reduces the signal-to-noise ratio in comparison to 470 nm stimulation. A method to circumvent these problems was suggested by Jain et al. (2005), in which a short (0.1 s) 470 nm stimulation OSL measurement was made both prior to and following IR bleaching at elevated temperature (190  C; which reduces IR bleaching time compared to 160  C; see Jain et al., 2005 for discussion). The difference in OSL levels was used as a measure of the fast-component signal magnitude. The main focus of this paper is on the use of an alternative approach for isolating the fast component using IR stimulation; the results obtained are compared to other methods for obtaining fast-component-dominated signals from the bulk OSL signal. The samples used are of quartz extracted from thirteen samples (each prefixed by MAL05) cored from a shoreline of palaeolake Chilwa, Malawi. The deposit comprised well-sorted coarse/medium sand, forming a series of stacked relict beach ridges bounding the northern limit of the former lake extent. The age of the deposit spans approximately 8–40 ka. Full sample descriptions are given in Thomas et al. (2009). These samples were chosen in the present study for two reasons: standard ‘bulk OSL’ De estimates show a strong dependence of De on integration interval (see Section 2) and as such are good examples of samples for which isolation of the fast component may be beneficial; the samples were relatively bright, with small aliquots (2 mm mask) yielding of the order of tens of thousands of counts s1 Gy1, over the first second of OSL measurement.

2. Assessing the suitability of bulk signal integration Sufficient numbers of favourable dating comparisons have been published to suggest that problems associated with non-fastcomponent ‘contamination’ of the bulk OSL signal are unlikely to be significant for all samples (unless, of course, an opposing factor is compensating in some way for this effect – see Section 6.2). It would therefore be useful to assess each sample aliquot individually for indications of malign component-related effects. The dependence of the calculated De on the bulk OSL signal integration interval (De(t); Bailey, 2003a) offers this possibility and has already been investigated, primarily in the context of attempts to identify incomplete signal resetting prior to sample deposition (e.g. Bailey, 2003a,b). Along with the potential for identification of incomplete bleaching prior to deposition, analysis of De(t) data can also potentially identify differences between the OSL components in properties such as thermal stability, signal enhancement due to thermal transfer or the accuracy/applicability of the chosen measurement protocol (e.g. the SAR method may not work equally well for all OSL components) (Bailey et al., 2003). Such differences in component properties/behaviour would be manifest in a dependence of De on integration interval. If a dependence of De on integration interval is indeed found then the sample De (and therefore age) is to some extent ‘tuneable’, arbitrarily, over that integration range for which chosen measurement protocol is shown to be effective. An example dataset is shown in Fig. 1a (equipment details are given in the caption to Fig. 1). The De of sample MAL05/1/1 was calculated using a range of signal integration limits (from 0 to t). As the interval is widened (t increases) De reduces (shown in square brackets are the ages calculated using each De value, assuming a dose rate of 1 Gy/ka). Thus, significant differences in the calculated age can be obtained by adjusting t and it is not possible to judge in such cases which age is likely to be most accurate. While it is the case that taking the shortest signal integration interval will provide the estimate of De least affected by the ‘contaminating effects’ of non-fast component signals (Fig. 1b), there is no guarantee that this estimate will itself be accurate (and again this is in some sense arbitrary as the component contribution of the first data channel depends on the chosen measurement resolution); however, such an approach may indeed be sufficient in some samples. Further analysis is necessary for samples which show strong De(t) dependence such as shown in Fig. 1 (notably a decrease in De through the measurement interval, in the case of older samples, as in Fig. 1) and the isolation of the fast-component signal may be a useful starting point. A number of different methods aimed at extracting a fast-component OSL signal (and subsequent De) are discussed in the following sections. 3. Direct isolation of the fast component The method proposed here is to sample the fast-component signal using a relatively short IR stimulation, rather than measuring the full (IRSL) signal decay. The slow depletion rate of quartz IRSL (a decay constant of w5  104 s1 under standard conditions described: l ¼ 830 nm, stimulation power w400 mW cm2 and a sample temperature of 160  C; compared to w2 s1 under 470 nm stimulation at 36 mW cm2) means that over a relatively short measurement period (e.g. 20 s) the fast component should yield an effectively constant, but relatively low, level of luminescence. The accurate assessment of this signal therefore requires a sound assessment of background levels. Fig. 2 shows an IRSL signal measured from quartz sample MAL05/1/1, at 160  C (l ¼ 830 nm, 400 mW cm2), following a zero and a 64 Gy b-dose and preheat at 260  C for 10 s. Infrared stimulation is off for the first and last 10 s of the measurement, to provide an estimate of measurement

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Fig. 1. (a) An example ‘natural’ OSL decay is shown for sample MAL05/1/1, measured under the standard conditions (described below), following a preheat at 260  C for 10 s. De estimates derived from selected individual data points along the decay curve are also shown. The labelled arrows indicate the precise De value and in square brackets is shown the difference in age compared to the De calculated using the initial data point at 0.05 s (calculations use an example environmental dose rate of 1 Gy/ka). Optically stimulated luminescence measurements were made using a standard automated Risø TL/OSL DA-15 reader fitted with a blue (470D20 nm) diode array (sample stimulation power nominally 36 mW cm2), IR stimulation (l ¼ 830 nm, 0.4 W cm2) and a calibrated 90Sr/90Y beta-source (Bøtter-Jensen et al., 1999). The ultra-violet (w370 nm) component of the emitted luminescence was measured using a photomultiplier (Electron tubes, series 101482) filtered with three Hoya U-340 glass filters. OSL measurements were made in air, at a sample temperature of 130  C unless otherwise stated. (b) OSL signal fitted to a sum of three exponential decays, representing the fast and medium components, plus another exponential accounting for the slower OSL components. The fitted sum of exponentials is also shown, overlaying the measured signal. The residuals to the fit are shown directly above the main figure.

background (a procedure adopted in all subsequent IRSL measurements reported), which appears to be stable either side of the IRSL measurement. The signal is relatively small but distinguishable from the background. The integrated counts in measurements subsequently made and described here typically amount to several thousands of counts and therefore contribute a random error component of the order of 1–2%, which is acceptable in the context of dating measurements. Even though previous work (e.g. Singarayer and Bailey, 2004) suggests strongly that the IRSL signal should comprise solely fast-component signal, it is important to confirm for the quartz extracted from the present sediments that the source of any observed IRSL signal is indeed the same as the fast-component signal observed in blue-stimulated quartz OSL measurements. An

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experiment was performed in which repeated cycles of IRSL and OSL measurements were made, the rationale being that the IRSL sampled the fast-component signal (without depleting it significantly), while the intervening OSL measurement (blue light stimulation) progressively bleached the bulk signal. The observed IRSL should then give a measure of the rate at which the blue light bleached the fast component. The integrated IRSL count rate should decay approximately exponentially over the course of the repeated cycles and the decay rate should be the same as that obtained from deconvolution of the fast-component signal directly from the (blue-stimulated) bulk OSL signal. Results are shown in Fig. 3 (for both raw and integrated data; note that blue stimulation power is 1.8 mW cm2 for this experiment). The decay of the integrated net IRSL is exponential, to a good approximation, whereas the OSL has the non-exponential form typical of the bulk quartz OSL signal when measured under the conditions described. An exponential fit to the IRSL data yields a decay rate of 0.103  0.003 s1; deconvolution of the observed bulk OSL signal yields a fast component with a decay rate of 0.104  0.002 s1. These data are therefore consistent with the observed IRSL signal being a reliable sample of the fast-component signal.

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Time (s) Fig. 2. An example quartz IRSL measurement from a single aliquot of sample MAL05/1/ 1. The IR stimulation is off for the first and last 10 s of the measurement in order to gauge the background contribution. The signals plotted were regenerated with b-doses as shown (0 Gy measured prior to the 64 Gy data), and the aliquot was preheated at 260  C for 10 s prior to each measurement.

A modified single-aliquot regenerative-dose (SAR) procedure was used in which a single IRSL measurement (sample temperature 160  C) was made prior to both the natural/regeneration (Lx) and test dose (Tx) OSL measurements (the net IRSL signals being Ax and Bx respectively). Full details of the measurement procedure are given in Table 1. The bulk OSL signal was integrated over the time range during which the signal decayed to w90–95% of the initial intensity; the full IRSL signal was integrated and background subtracted based on the measured background values for each aliquot (as described above). An additional IRSL measurement at 20  C was included prior to measurement of Ax and Bx (steps 3 & 8 in Table 1). This step serves two purposes. Presence/absence of this IRSL signal is a check on the purity of the quartz sample, with respect to feldspar. Additionally,

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Time (s) Fig. 3. The main figure shows data from an experiment in which both IRSL (w400 mW cm2 stimulation power) and blue-stimulated OSL (w1.8 mW cm2 stimulation power) were repeatedly measured from a single aliquot of sample MAL05/1/5. Data from the OSL measurements are plotted (versus cumulative bleaching time) in inset (a), showing the non-exponential form of the overall signal decay. Data from the repeated IRSL measurements are shown in inset (b), plotted versus measurement time. The normalized net signal integrals of the IRSL and OSL measurements are shown in the main figure, plotted against cumulative OSL bleaching time. The near exponential decay of the IRSL (fast component) signal is indicated by the fit, and contrasts with the non-exponential form of the bulk OSL signal.

while the large majority of refined quartz samples yield no IRSL above background counts (when measured at 20  C), some do retain a relatively weak IRSL signal which is resistant to physical/chemical sample treatment (possibly associated with feldspar inclusions). The measured quartz IRSL signals (Ax & Bx) are relatively weak and so are sensitive to even low levels of feldspar IRSL contamination (which would not, for example, be significant in comparison to bulk OSL signals Lx and Tx). Steps 3 & 8 of the general measurement cycle shown in Table 1 are included to reduce the impact of any such contamination. A further check on signal purity was achieved through examination of the signal form observed in the IRSL (Ax & Bx) measurements. Infrared stimulation of quartz at 160  C, for 40 s (steps 4 & 9, Table 1), should yield an effectively constant level of IRSL (i.e. no appreciable signal decay over the course of the measurement). A decaying IRSL signal under these conditions would be grounds to reject the aliquot from further analysis (implicit here is

the assumption that the aliquot has been adequately preheated, prior to measurement; this point is discussed below). The addition of IRSL measurements (steps 4 & 9) has no significant effect on the fastcomponent signal, and hence the Lx signal (expected to be depleted by <0.01%). This modified SAR procedure allows measurement of both the bulk OSL signal (470 nm stimulation) and the fast-component signal (830 nm stimulation) to be measured within the same measurement sequence. In this context the OSL measurement serves the dual purpose of measuring the bulk OSL signal and also depleting the fast component fully prior to subsequent irradiation and IRSL measurement. The relatively low signal levels observed in step 9 (Bx) induced a significant degree of scatter in the normalized results (Ax/Bx), particularly apparent in the dose response data. However, from the data obtained, it was possible to show that the Tx values appear to adequately correct for sensitivity changes induced by irradiation and preheating. The ability of both Tx and Bx to adequately correct the Ax signal for sensitivity change was assessed by repeating the measurement cycle whilst maintaining bi at 20 Gy. Regenerated signal data (Lx, Ax) were found to be proportional to the sensitivitymonitoring signal (Tx, Bx). Relevant data are shown in Fig. 4 (further details are given in the caption). In subsequent analyses the bulk signal (Lx) and the fast-component (IRSL) signal (Ax) were corrected for sensitivity change using the Tx (bulk OSL) signal. 4.2. Preheat dependence The dependence of the quartz IRSL signal on preheat temperature (PH1; step 2) was assessed in the context of dose response using the SAR procedure described above, for PH1 temperatures of 220, 240, 260, 280  C (each held for 10 s). Examples of the measured IRSL signals (step 4, Table 1), and further details of the measurement procedure, are given in Fig. 5. At lower PH1 temperatures a clear phosphorescence contribution to the background measurement is observed (the first and last 10 s of the measurement, with the IR stimulation switched off); this presumably results from thermal de-trapping of charge during the hold at 160  C. At higher temperatures, less thermally stable traps are depopulated during preheating and consequently contribute less phosphorescence during the background measurement periods. Dose response data for aliquots measured using PH1 temperatures of 220  C and 240  C (not shown) typically were scattered (i.e. did not follow a smooth exponential-like growth form) and the repeatpoint (‘re-cycling’) ratios were significantly different from unity. These problems are at least in part due to difficulties in subtracting an appropriate background. For PH1 temperatures of 260  C and 280  C, the observed background remains stable either side of the IRSL measurement and is dose-independent.

Table 1 Details of the modified SAR measurement procedure for obtaining estimates of De. The full cycle of 11 steps is repeated several times, for different values of bx, including cycles duplicating bx values (to calculate ‘repeat ratios’) and a cycle with bx ¼ 0 to assess the contribution of thermally transferred charge to Ax & Lx. A background measurement (‘bg’) is included prior to, and following, each IRSL measurement, and is discussed in the main text. Step

Conditions

Purpose

1: b-dose, bx/Natural dose 2: Preheat 1, PH1 3: IR-bleach 4: IRSL measurement, Ax 5: OSL measurement, Lx 6: Standard b-dose, bstd 7: Preheat 2, PH2 8: IR-bleach 9: IRSL measurement, Bx 10: OSL measurement, Tx 11: Signal bleaching

20  C, specified dose 260  C, 10 s 20  C, 20 s, l ¼ 830 nm, 0.4 W cm2 160  C, 40 s (þ2  20 s bg), l ¼ 830 nm, 0.4 W cm2 130  C, 100 s, l ¼ 470 nm, 32 mW cm2 5 Gy, 20  C 220  C, 10 s 20  C, 20 s, l ¼ 830 nm, 0.4 W cm2 160  C, 40 s (þ2  20 s bg), l ¼ 830 nm, 0.4 W cm2 130  C, 100 s, l ¼ 470 nm, 32 mW cm2 200  C, 100 s, l ¼ 470 nm, 32 mW cm2

Signal regeneration Accelerate thermal processesa Monitor, and reduce effects of, minor contamination Sample the fast-component signal Measure bulk OSL & bleach aliquot Provide standardizing signal Induce thermally unstable processesa Monitor, and reduce effects of, minor contamination Sample the fast-component signal Measure bulk OSL & bleach aliquot Reduce residual OSL prior to next cycle

a

The redistribution of both electrons and holes trapped in relatively thermally unstable states.

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derived De value for each of the different PH1 temperatures, for both the bulk OSL signal (Lx/Tx) and the fast-component signal (Ax/Tx). These data are discussed below. As a test of this procedure, a dose recovery test was performed on 12 aliquots of sample MAL05/1/4. The natural signal was bleached with blue (470 nm) light at room temperature for 200 s, followed by a pause for 1000 s and another similar bleach for 200 s. Negligible OSL was observed in the second bleach. A b-dose of 45 Gy (bR) was administered and the De of the aliquots measured using the procedure described in Table 1. The resultant ratio De/bR (ideally unity) was 0.97  0.04 for the bulk OSL signal (Lx/Tx data) and 0.97  0.03 for the fastcomponent signal (Ax/Tx data), suggesting the adopted procedure is appropriate for accurate measurement of De, at least for this sample.

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Regeneration signal (L x , A x ) (103 counts) Fig. 4. Plots of the sensitivity-monitoring signal (Tx, Bx) against the regenerated signal (Lx, Ax) for aliquots of sample MAL05/1/4. The procedure described in Table 1 was used to measure 14 SAR cycles, each time with the regeneration dose (bx) remaining constant at 20 Gy. Three separate aliquots were measured and the data points from all three are included in the figure. Open squares show the relationship of the IRSL regeneration (Ax) and IRSL test-dose (Bx) signals; open triangles show the relationship of the IRSL regeneration (Ax) and OSL test-dose (Tx) signals; crosses show the relationship of the OSL regeneration (Lx) and OSL test-dose (Tx) signals. The fits shown to each dataset are linear fits, constrained to pass through the origin and confirm that for each dataset the test-dose signal is a good monitor of the sensitivity change affecting the regeneration signal.

A standard temperature of 260  C for PH1 was chosen for all subsequent measurements; example dose–response data are shown in Fig. 6. The inset to Fig. 6 shows the dependence of the

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The SAR method outlined in Table 1 was applied to each of the thirteen Malawian samples. Two of these samples (MAL05/1/3 and MAL05/1/4) were studied in more detail, with several additional methods of obtaining fast component-dominated De values (described below) compared to those derived from the fitting of pseudo-LM-OSL data (Bulur, 2000) (summary data plotted in Fig. 8). The implicit assumption in this comparison is that fitting LM-OSL data provides true assessment of the fast component De. The LM-OSL method is the best-tested method and is (along with direct fitting of the CW-OSL data) the way in which the fast component is defined currently. For the remaining samples, comparison was made between the De values obtained using the bulk signal OSL method and that using the IRSL method described in Table 1. Summary plots for these datasets are shown in Fig. 9.

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Fig. 6. An example IRSL (fast component) dose response curve (sample MAL05/1/4). The regenerated data are fitted to a saturating exponential function. The plotted intersection of the natural and regenerated data shows the De, with uncertainty indicated by the error bar (uncertainty was calculated using Monte Carlo sampling of the natural and regeneration points [n ¼ 1000], assuming Gaussian errors in all cases; the standard deviation of the sampled De values provides the reported error in De; see Grine et al., 2007 for details). The inset shows the PH1-dependence of the De values derived for OSL data (Lx/Tx: solid symbols) and IRSL data (Ax/Tx: open symbols).

5.2. Extrapolated OSL A limiting case for the approach of shortening the time integral (to weight the integral towards the fast component) would be to derive De from the intensity measured at t ¼ 0 (i.e. an integral of zero width, where the ‘contaminating’ influence of non-fast components would be minimized). This was estimated by fitting the initial decay to a single exponential function and extrapolating back to zero time. An example is shown in Fig. 7a, where the first three points were used to fit the exponential (as was the case in all such calculations of De). The time-range of the extrapolation, however, covers over a duration equivalent to a significant fraction of the time-range over which the fitting was performed and concern arises over the validity/accuracy of such an extrapolation. To assess the accuracy of the extrapolation, the inset to Fig. 7a shows data, for a similar OSL curve measured at a higher temporal resolution. Taking approximately the same points (in time) as for the fitting in the main figure (as highlighted in the inset figure) allows a comparison between the otherwise naive extrapolation and the measured data (for this curve). The comparison is favourable, suggesting the treatment does not introduce significant inaccuracies. 5.3. Component analysis of De(t) data Estimates of De for the fast and medium OSL components can also be derived by fitting an appropriate function to De(t) data; this

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5.1. Short and long signal integrals De(t) data for aliquots of these 13 samples generally show strong dependence of De on integration interval. De values for both shorter and longer integrals are therefore compared for each aliquot. To define the integration intervals, an example OSL curve (‘natural’ signal, sample MAL05/1/2) is shown in Fig. 7a: the longer and shorter integration intervals span from 0 to 0.96 s and 0 to 0.24 s respectively, and are indicated by arrows to the dashed and solid vertical lines. In respect of weighting the signal integral towards larger fast component proportion, the shorter integral is clearly preferable and a comparison of these two integrals is therefore instructive (as is examination of De(t) data).

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Time (s) Fig. 7. The main part of Fig. 7a shows measured OSL data for sample MAL05/1/2. The arrows to vertical lines show the integration intervals for the long and short integrals described in the main text. The solid line is a single-exponential fit to the first three data points, extrapolated back to t ¼ 0. The inset shows the same aliquot measured at higher temporal resolution. The solid symbols correspond to times equivalent to the first three data point shown in the main figure. The fit shown is to these three points. Fig. 7b shows example De(t) data for three different aliquots (sample MAL05/1/4) and fits to Eq. (1). The majority of De(t) datasets had similar form to that marked ‘typical’. The data above and below those labelled ‘typical’ represent the most extreme exceptions to the common form.

is the fourth method. Eq. (1) follows the work of Li and Li (2006), in which Df and Dm are the De values for the fast and medium components, lf and lm are the signal decay rates during OSL measurement and k is a scaling factor relating the proportion of fast and medium component magnitudes (t is measurement time). This analysis requires that the slow components of OSL are effectively removed by background subtraction and that neither fast nor medium components are near saturation (Li and Li, 2006).

  Df k exp lf t þ Dm expðlm tÞ   De ðtÞ ¼ k exp lf t þ expðlm tÞ

(1)

During fitting, the individual De values were weighted as 1=s2De (sDe being the error on De) with initial values for constants lF and lM obtained from fitting of the associated OSL decay curves to multiple exponential decays representing the fast, medium and slow components (Bailey et al., 1997; with constraints based on the

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Fig. 8. A comparison of results from different methods for obtaining De, for two different samples (a–e: MAL05/1/3; f–j: MAL05/1/4). Each data point represents an estimate from a single aliquot and the method used is indicated (and described in previous sections of the main text). De estimates from each of the methods are plotted against the De obtained for the fast component from deconvolution of LM-OSL data (also described in the main text). The horizontal lines intersecting the vertical axis indicate the 1s range of the De estimate from the LM-OSL fast component (calculated using the Central Age Model (CAM) of Galbraith et al. (1999)). The open symbol indicates the estimate from the method shown (also calculated using the CAM) (note that 0,0 is not shown). The diagonal line (x ¼ y) is included to aid visual comparison. All errors shown are 1s.

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Fig. 9. Comparison of De estimates obtained using the IRSL method outlined in Table 1 with those obtained from the bulk OSL signal. Each data point represents data from a single aliquot. The following list gives the name of each sample used; the first name corresponds to the solid symbols and the second to the open symbols: (a) MAL05/1/3, MAL05/1/8; (b) MAL05/1/10, MAL05/1/4; (c) MAL05/1/1; (d) MAL05/5/2, MAL05/5/3; (e) MAL05/1/5, MAL05/1/7; (f) MAL05/4/5, MAL05/4/4. Note that (0,0) is not shown.

optical cross-section values of Singarayer and Bailey, 2003) and was performed using Microcal Origin (Version 6.0). Example data and fits are shown in Fig. 7b. The majority of the data followed the form highlighted ‘typical’; the other forms shown represent the more extreme exceptions to this case. 6. Discussion 6.1. Isolation of fast component In principal, and for the samples reported here, isolation of the fast component of quartz OSL appears to be possible using IR

stimulation at high temperature and the IRSL measurement procedure described, when included in the usual SAR measurement sequence (Table 1), gives a fast component De that can be compared directly to similar bulk OSL results. The measurements reported above show the IRSL regeneration data (Ax) to be proportional to the measured Tx value (for common doses) and that dose recovery and repeat (‘re-cycling’) ratios are close to unity. Based on the data presented (Fig. 4), there appears to be no reason to doubt that the IRSL fast-component signal can be used to estimate accurately the palaeodose. Whether or not there is any advantage in isolating the fast component for any given sample is a more difficult question to address. If there is no obvious dependence of De on integration

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interval (De(t)) over the initial part of the signal decay (to say, 10% of initial intensity), then any malign effect present due to non-fastcomponent contributions to the bulk signal may be deemed unimportant and fast component isolation may offer little advantage. Where there is a strong De(t) dependence, then the De derived from the bulk signal is effectively ‘tuneable’, over a limited range, by adjustment of the signal integration interval. It is possible that all bulk signal integrals may suffer to some extent from any existing malign effects associated with the slower-bleaching components and isolation of the fast component would be essential in such cases. A pragmatic approach is to routinely assess the De(t) form and to quantify any differences observed between the fast and bulk De estimates where possible. 6.2. Comparison of methods for isolating the fast component The question as to which method is best (most efficient/effective) for isolating the fast component is not simple to answer. Direct measurement (using IR stimulation at 160  C) would be preferable where possible, as there is no requirement of signal deconvolution and simple integration of a ‘pure’ fast-component signal (the IRSL signal) would be possible. Measurement of the full IRSL decay (or bleaching of the fast component for OSL signal subtraction) requires lengthy measurement sequences and is likely to be impractical. The IR-stimulation method described in Table 1 circumvents this problem, but introduces a new requirement, that of relatively bright samples and is therefore unlikely to routinely produce sufficiently large signals for the majority of samples (without further technological advances in filtering, for example). The method is also highly sensitive to feldspar contamination, which cannot be chemically removed in samples where feldspar is in the form of inclusions within the quartz grains (e.g. Baril, 2004). In this case, the best method is likely to be the deconvolution of LMOSL curves: the optical cross-sections of the most rapidly decaying feldspar signals are considerably smaller (slower bleaching) than the quartz fast component (under 470 nm stimulation) and hence a ‘clean’ signal can be obtained from quartz in the presence of significant feldspar contamination using deconvolution. Where samples are free of feldspar contamination, but too dim for IR stimulation to yield adequate count rates, a preferable choice may be to fit De(t) data to Eq. (1) to obtain Df (as suggested by Li and Li, 2006), or to base the De estimate on the value obtained by extrapolating the OSL signal to zero time (Fig. 7a), rather than using the signal integral. As shown in Fig. 8a–c & f–h, as the integration interval is reduced, and in the limit of a zero width interval (the extrapolated intercept at t ¼ 0), the De more closely approximates that from the LM-OSL fitted fast component estimate. Extrapolation of the bulk OSL signal to zero time is a relatively straightforward procedure to implement at the data processing stage and is shown here to be equivalent to full component separation. In the present case, the statistical uncertainty in Df is considerably higher than in other estimates of the palaeodose. The central estimates of De (here calculated using the Central Age Model of Galbraith et al. (1999)), are in both cases within 1s limits of the similar range calculated for the LM-OSL-derived fast component (Fig. 8d,i). The relatively large uncertainties of individual Df estimates could be problematic if they were to mask patterns of scatter related to incomplete bleaching, for example, and hinder the use of statistical methods such as the Minimum Age Model (Galbraith et al., 1999). Any advantage the Df and extrapolated-OSL methods may have over fitting exponential components to CW-OSL or LM-OSL data is purely practical, however (data processing being less labour intensive). Ultimately, if LM-OSL fitting can be well-constrained and shown to be reliable (by, for example, comparing results before

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and after removing the fast component using long IR stimulation, e.g. Singarayer and Bailey, 2004) then this method is preferable where IR isolation of the fast component is not possible. The ideal case is, of course, to show that multiple methods give indistinguishable results. 6.3. Relationship between IR-De, bulk-OSL-De and LM-OSL-fastcomponent De De values obtained from IR stimulation are, on the whole, either the same, or larger than, those obtained using bulk OSL signal integration (blue stimulation): taking in to account the 1s errors on each De estimate, 10% of the IR-based-De values were lower than the OSL-based-De values, 43% were indistinguishable and 47% were higher (see Fig. 9). As indicated in Fig. 9d, the group of De values that systematically underestimate those of the LM-OSL-fastcomponent were found to have likely feldspar contamination (decaying non-zero IRSL signals were observed during room temperature IR stimulation in step 3 of the procedure outlined in Table 1). For the non-contaminated samples, estimates of De obtained from IR stimulation overlap (at 1s) with those from the LM-OSL fast component (Fig. 8e,j); the individual De values from IRSL are mostly higher, however. There is no obvious reason why this should be the case as both methods are expected to accurately isolate the fast component. Whether this observation is due to random (statistical) fluctuation, systematic errors in the fitting of LM-OSL data or to a real physical effect, requires further investigation. Where fast component De values are higher than those for the bulk OSL signal (for any method of fast component isolation), the difference is generally greater for larger De values (Fig. 9). If it is assumed that the fast component yields the most accurate estimate of the palaeodose, this suggests the bulk signal may be systematically underestimating the palaeodose in some samples. In contrast to this suggestion, previous work (Bailey, 2004; Bailey et al., 2005) suggests that the De (based on integration of the initial OSL signal) will overestimate the true palaeodose by w10% for doses above w40 Gy due to a charge competition effect during irradiation (related to differences between natural and laboratory dose rates). However, even though relevant laboratory measurements agreed with the theoretical predictions, suggesting the competition effect does indeed exist, observations from known age samples have typically provided either accurate ages or slight age underestimation (e.g. Murray and Funder, 2003). In light of the present findings, it seems possible that the predicted overestimate due to charge competition may be offset to some extent by the underestimate due to bulk signal effects described in this paper. The degree of compensation in such cases would depend on the age (palaeodose) of the sample. There may also be differences in the degree of cancellation at the inter-aliquot and inter-grain level, due, for example, to the relative contributions from different OSL signal components, the strength of the competition effect and the environmental dose rate to each grain. The potential exists therefore, if both the dose-rate effect and the ‘component effect’ can be significantly reduced, both greater precision and greater accuracy in palaeodose estimates may be obtained. This might be achieved in practice by resolving the fast component (using LM-OSL, or IR stimulation, for example) and by pulsing the irradiation during De measurement (Bailey, 2004). From the data presented here, it appears the medium component is less stable than the fast component, leading to underestimation of De when longer signal integration intervals are used. However, empirical observations (e.g. Bailey et al., 1997; Singarayer and Bailey, 2003; Jain et al., 2003) have shown the medium component to be at least as thermally stable as the fast component. Simple thermal fading of the signal is therefore ruled out as the cause of De underestimation in the medium component sensu

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stricto. A number of possibilities exist: the possibility of there being more than one ‘medium component’ (i.e. hitherto undefined OSL components with similar optical cross-sections but different thermal stabilities to the medium component as currently defined) and athermal instability of the medium component will be presented elsewhere. 6.4. Potential practical improvements Perhaps the most significant obstacle to the general application of the method described in Table 1 is the prohibitively low IRSL signal count rate expected in a large proportion of quartz samples. A possible practical solution is to change the emission filtering, given that the photomultipliers commonly used for optical dating have considerably lower (but non-zero) quantum efficiency for IR photons than for blue photons (stimulation with 830 nm at w400 mW cm2 equates to 1.7  1018 photons s1 cm2, 470 nm at w36 mW cm2 equates to 8.5  1016 photons s1 cm2). Ideally the filter must block all blue and IR photons but pass the quartz UV emission. Initial experiments yielded no significant advantages: various combinations of UG11, UG12, BG39 and U340 filters produced signal-to-noise ratios no better than the standard 6 mm U340 filter. 7. Conclusion The fast component of quartz OSL can be sampled using relatively short (e.g. 40 s) IRSL measurements at 160  C. Such measurements can be incorporated in to standard SAR procedures, yielding a fast component De values which can be compared directly to that derived from integrating the bulk OSL signal. De estimates obtained this way for 11 samples (and through other related methods) were found to be either indistinguishable from, or larger than, their bulk-signal equivalents and consistent with values derived from fitting of LM-OSL signals. Acknowledgements Professor Ann Wintle is thanked for providing detailed helpful comments on an earlier version of this manuscript. Dr. Mayank Jain is thanked for helpful suggestions made during the reviewing process. Editorial handling by: R. Roberts References Bailey, R.M., 1998. Depletion of the quartz OSL signal using low photon energy stimulation. Ancient TL 16, 33–36. Bailey, R.M., 2003a. Paper I: The use of measurement-time dependent single-aliquot equivalent-dose estimates from quartz in the identification of incomplete signal resetting. Radiation Measurements 37, 673–683. Bailey, R.M., 2003b. Paper II: The interpretation of measurement-time-dependent single-aliquot equivalent-dose estimates using predictions from a simple empirical model. Radiation Measurements 37, 685–691. Bailey, R.M., Singarayer, J.S., Ward, S., Stokes, S., 2003. Identification of partial resetting using De as a function of illumination time. Radiation Measurements 37, 511–518.

Bailey, R.M., Arnold, L.J., 2006. Statistical modelling of single grain quartz De distributions and an assessment of procedures for estimating burial dose. Quaternary Science Reviews 25, 2475–2502. Bailey, R.M., Smith, B.W., Rhodes, E.J., 1997. Partial bleaching and decay form characteristics of quartz OSL. Radiation Measurements 27, 123–136. Bailey, R.M., Armitage, S.J., Stokes, S., 2005. An investigation of pulsed-irradiation regeneration of quartz OSL and its implications for the precision and accuracy of optical dating (Paper II). Radiation Measurements 39, 347–359. Bailey, R.M., 2004. Paper Idsimulation of dose absorption in quartz over geological timescales and its implications for the precision and accuracy of optical dating. Radiation Measurements 38, 299–310. Baril, M.R., 2004. Emission and excitation spectra of feldspar inclusions within quartz. Radiation Measurements 38, 87–90. Bøtter-Jensen, L., Duller, G.A.T., Murray, A.S., Banerjee, D., 1999. Blue light emitting diodes for optical stimulation of quartz in retrospective dosimetry and dating. Radiation Protection Dosimetry 84, 335–340. Bøtter-Jensen, L., McKeever, S.W.S., Wintle, A.G., 2003. Optically Stimulated Luminescence Dosimetry. Elsevier, Amsterdam. Bulur, E., 2000. A simple transformation for converting CW-OSL curves to LM-OSL curves. Radiation Measurements 32, 141–145. Bulur, E., Bøtter-Jensen, L., Murray, A.S., 2000. Optically stimulated luminescence from quartz measured using the linear modulation technique. Radiation Measurements 32, 407–411. Choi, J.H., Murray, A.S., Cheong, C.S., Hong, D.G., Chang, H.W., 2003. The resolution of stratigraphic inconsistency in the luminescence ages of marine terrace sediments from Korea. Quaternary Science Reviews 22, 1201–1206. Galbraith, R.F., Roberts, R.G., Laslett, G.M., Yoshida, H., Olley, J.M., 1999. Optical dating of single and multiple grains of quartz from Jinmium rock shelter, northern Australia, part 1, Experimental design and statistical models. Archaeometry 41, 339–364. Grine, F.E., Bailey, R.M., Harvati, K., Nathan, R.P., Morris, A.G., Henderson, G.M., Ribot, I., Pike, A.W.G., 2007. Late Pleistocene human skull from Hofmeyr, South Africa, and modern human origins. Science 315, 226–229. Istratova, A.A., Vyvenko, O.F., 1998. Exponential analysis in physical phenomena. Review of Scientific Instruments 70, 1233–1257. Jain, M., Murray, A.S., Bøtter-Jensen, L., 2003. Characterisation of blue light stimulated luminescence components in different quartz samples: implications for dose measurement. Radiation Measurements 37, 441–449. Jain, M., Murray, A.S., Bøtter-Jensen, L., Wintle, A.G., 2005. A single-aliquot regenerative-dose method based on IR (1.49 eV) bleaching of the fast OSL component in quartz. Radiation Measurements 39, 309–318. Li, S.H., Li, B., 2006. Dose measurement using the fast component of LM-OSL signals from quartz. Radiation Measurements 41, 534–541. Murray, A.S., Funder, S., 2003. Optically stimulated luminescence dating of a Danish Eemian coastal marine deposit: a test of accuracy. Quaternary Science Reviews 22, 1177–1183. Singarayer, J.S., Bailey, R.M., 2001. Component resolved bleaching spectra of quartz OSL and implications for dating. Presented at 13th Solid State Dosimetry Conference, Athens, 2001. Singarayer, J.S., Bailey, R.M., 2003. Further investigations of the quartz optically stimulated luminescence components using linear modulation. Radiation Measurements 37, 451–458. Singarayer, J.S., Bailey, R.M., 2004. Component-resolved bleaching spectra of quartz optically stimulated luminescence: preliminary results and implications for dating. Radiation Measurements 38, 111–118. Spooner, N.A., 1994. On the optical dating signal from quartz. Radiation Measurements 23, 593–600. Thomas, D.S.G., Bailey, R.M., Shaw, P.A., Durcan, J.A., Singarayer, J.S., 2009. Late Quaternary highstands at Lake Chilwa, Malawi: frequency, timing and possible forcing mechanisms in the last 44 ka. Quaternary Science Reviews 28, 526–539. Tsukamoto, S., Rink, W.J., Watanuki, T., 2003. OSL of tephric loess and volcanic quartz in Japan and an alternative procedure for estimation De from a fast component. Radiation Measurements 37, 459–465. Watanuki, T., Murray, A.S., Tsukamoto, S., 2005. Quartz and polymineral luminescence dating of Japanese loess over the last 0.6 Ma: comparison with an independent chronology. Earth and Planetary Science Letters 240, 774–789. Wintle, A.G., Murray, A.S., 2006. A review of quartz optically stimulated luminescence characteristics and their relevance in single-aliquot regeneration dating protocols. Radiation Measurements 41, 369–391.