Optically simulated luminescence (OSL) dating techniques are widely used for the determination of the burial ages of Quaternary sediments (e.g., Li et al., 2002, 2014; Zhao et al., 2007; Yi et al., 2015; Peng et al., 2022). To obtain accurate OSL ages, optically sensitive charges that were previously accumulated in the mineral (quartz and feldspar) grain should be completed zeroed (or bleached) by sunlight prior to the last deposition of sediments (Godfrey-Smith et al., 1988; Peng et al., 2020). However, heterogeneous bleaching of quartz OSL signals has been frequently reported in the literature, especially for younger sediments with smaller equivalent dose (D_e) values (e.g., Lian and Huntley, 1999; Li, 2001; Zhang et al., 2003; Olley et al., 2004; Arnold et al., 2009; Pietsch, 2009; Hu et al., 2010; Costas et al., 2012; Ou et al., 2015; Mahadev et al., 2019).

Aeolian sediments are the most readily available materials for OSL dating in semi-arid/arid regions (Peng et al., 2022), and are thought to be the most unlikely influenced by heterogeneous bleaching (Wintle, 1993) due to their longer time of exposure to sunlight before deposition compared to water-lain sediments. Although many authors reported that their aeolian samples under analyzed were fully bleached before deposition (e.g., Bailey et al., 2001; Ballarini et al., 2003; Stokes et al., 2004; Singarayer et al., 2005; Zhao et al., 2012; Gong et al., 2013; Fu et al., 2015; Long et al., 2019; Yang et al., 2020), there is a growing lines of evidence indicating that it is not a sufficient guarantee that aeolian sediments under all deposition environments were fully bleached (e.g., Lian and Huntley, 1999; Spooner et al., 2001; Goble et al., 2004; Olley et al., 2004; Tissoux et al., 2010; Costas et al., 2012; Fan et al., 2013, 2022; Buckland et al., 2019). Accordingly, it is important to assess the bleaching degree of aeolian sediments in a region-specific scale to obtain accurate OSL ages for young samples to establish reliable geochronological framework on a century to decadal time scale.

Tengger Desert is a major proximal desert upwind to the Chinese Loess Plateau and aeolian dust released therein has significantly influenced region- and hemisphere-scale environments (Peng et al., 2022). Fan et al. (2013) assessed the bleaching degree of fine-grained quartz (11–63 μm) OSL signals near the Lanzhou city 200 km south to the Tengger Desert and indicated that most (but not all) the investigated samples were fully bleached. Fan et al. (2022) investigated the bleaching degree of coarse-grained quartz (90–125 μm) OSL signal of dune sands from the hinterland of the Tengger Desert and suggested that approximately a half of the studied samples were heterogeneously bleached. However, the bleaching characteristics of coarse-grained quartz OSL signals of aeolian sediments along the margin of the Tengger Desert have not been formally assessed yet, although a growing number of chronostratigraphic records from the desert margin were dated using coarse-grained quartz OSL (e.g., Qiang et al., 2010; Yin et al., 2013; Peng et al., 2016, 2022). In this study, near-surface coarse aeolian samples collected around the margin of the Tengger Desert were investigated to assess their multi-grain quartz OSL signal bleaching degrees using both empirical and numerical simulation methods.

Twelve aeolian samples collected from nine different sites around the margin of the Tengger Desert were investigated (Figure 1A). The maximum distance between these sites and the mobile sand sea of the desert are smaller than 60 km. Samples were collected at the near-surface of the outcrops (with an average depth of ∼0.86 m) and were expected to have D_e values approaching zero. Sample TDN6-4 is sandy loess and the remaining samples are aeolian sand. The results of grain-size analysis demonstrate that most samples are dominant by coarse fractions with particle diameters greater than 63 μm (Figure 1B). The reader is referred to Peng et al. (2022) for further information on the samples.

Raw samples were processed with the standard procedure (see Peng et al., 2022 and reference therein) to extract the 90–125 μm (or 63–90 μm, i.e., sample TDN6-4) quartz fractions which were subsequently contained in the inner part (four to five mm in diameter) of the discs for OSL measurements. Post-IR OSL signals were measured with a Risø-TL/OSL-DA-20 reader equipped with IR LEDs (870 nm, 48 mW/cm²) and blue LEDs (470 nm, 48 mW/cm²) to suppress the contribution of feldspar luminescence (e.g., Banerjee et al., 2001). Post-IR OSL signals were collected at 130°C for 40 s (with 400 channels). The preheat temperatures before the natural and regenerative OSL measurements were 260 and 220°C, respectively. The test dose used for sensitivity correction was 7.9 Gy throughout the measurements. D_e measurements were conducted using the single-aliquot regenerative-dose (SAR) (Murray and Wintle, 2000) and the standardized growth curve (SGC) (Roberts and Duller, 2004) methods. SAR D_e was determined by a full protocol with one natural cycle and six regenerative cycles. SGC D_e was determined by projecting the sensitivity-corrected natural OSL signal (L_n/T_n) onto a pre-determined SGC. OSL data analysis was performed using the R package “numOSL” (Peng et al., 2013; Peng and Li, 2017).

Numerical simulations were performed to generate heterogeneously-bleached D_e distributions (e.g., Peng, 2021) so as to validate the bleaching performance of the measured multi-grain aliquots. Single-grain OSL sensitivities were simulated from the empirical distribution of a measured sand dune sample according to the method of Rhodes (2007). OSL signals were generated using a pre-determined dose-response curve (DRC) described by a single saturating exponential function (e.g., Li et al., 2017). The heterogeneous bleaching process of the single-grain quartz OSL was simulated by assuming that the fast-component OSL signal decays exponentially with sunlight exposure duration with a bleaching rate of 0.4 s⁻¹ which allows the OSL signal to decay to less than 2% of its initial level after a bleaching duration of 10 s (Peng et al., 2020). This is consistent with the sunlight bleaching experiment work carried out by Godfrey-Smith et al. (1988) who predicted that 90% of the natural optical signal should be erased following a 10 s exposure to sunlight. The methodologies and terminologies used to simulate the baseline doses, baseline signals, residual signals, residual doses, burial doses, and natural doses were consistent with those of Peng et al. (2020). To synthetize multi-grain D_e distributions, a random sampling protocol (without replacement) was used to draw subsets from 1,000 simulated noise-free single-grain OSL datasets, and each subset containing OSL signals from N _g heterogeneously-bleached grains were superposed and noised to generate a “measured” multi-grain D_e value (and associated standard errors). The process was implemented repeatedly to generated “measured” multi-grain D_e distributions. The “measured” OSL signal was simulated by taking into account the counting statistics, instrument irreproducibility, and intrinsic over-dispersion (e.g., Li et al., 2017; Peng et al., 2020; Peng, 2021).

A positive correlation was identified between L_n/T_n and corresponding SAR D_e in several samples (Figure 4), suggesting that these multi-grain aliquots might have been influenced by heterogeneous bleaching (e.g., Fan et al., 2013). However, we noted that it is improper to diagnose them as heterogeneously-bleached samples based solely on the L_n/T_n versus D_e plot. For example, although the natural OSL intensity of sample TDN15-1 is close to the background level (Figure 2B), an obvious positive relationship is observed between L_n/T_n and D_e (Figure 4B), suggesting the diagnosis method is inapplicable. This may because 1) the huge uncertainty of the calculated SAR D_e caused by poor counting statistics and 2) the “averaging” effect arising from the multi-grain results discount the usefulness of the L_n/T_n versus D_e plot; In the first situation, L_n/T_n and D_e values have large uncertainties and in the second situation, an increase of D_e as a function of L_n/T_n may merely result from the superposition of signals originated from different grains. Wallinga (2002) demonstrated that a correlation between natural OSL and associated D_e should only be expected for heterogeneously-bleached multi-grain samples when the OSL sensitivity of individual grains is similar. In addition, Fan et al. (2013) suggested that the L_n/T_n versus D_e plot is only applicable for the portion of the plot containing only positive D_e values. An alternative method for bleaching degree diagnosis is inspecting the D_e distribution, that is, tight D_e distributions are expected for undisturbed and fully-bleached samples (e.g., Olley et al., 2004; Arnold et al., 2009). The D_e distributions obtained using the SGC method demonstrate small between-aliquot variations and the resultant CAM D_e estimates are very small (Figure 5). However, it has been pointed out that the detection of heterogeneous bleaching based solely on this method may fail if a large number of grains are presented within an aliquot (e.g., Wallinga, 2002; Duller, 2008). Accordingly, it is best that the bleaching degree of OSL signals of multi-grain aliquots can be assessed using multiple methods.

Considering the abovementioned concerns on the detection of heterogeneous bleaching based on the multi-grain results presented here, we further applied a simulation approach to validate the bleaching degree of these samples. When a grain number of 200 (i.e., the expected minimum grain numbers for the measured aliquots of Figure 5) and a small baseline dose (10 Gy) were applied, the CAM D_e calculated using the simulated multi-grain aliquots were 2.22 ± 0.013 Gy (Figure 6C), 1.24 ± 0.011 Gy (Figure 6F), and 0.2 ± 0.0068 Gy (Figure 6I), respectively, if the proportion of fully-bleached grains are small (5%), moderate (50%), and large (95%). When a grain number of 200 and a relatively large baseline dose (50 Gy) were applied, the CAM D_e estimates were 10.37 ± 0.047 Gy (Figure 7C), 4.76 ± 0.029 Gy (Figure 7F), and 0.62 ± 0.011 Gy (Figure 7I), respectively. The measured D_e distributions containing both positive and negative D_e values and tight dose distributions (Figure 5B–l) are more similar to the one of Figure 6I simulated with a large proportion of fully-bleached grains and a small baseline dose. In addition, a small baselined dose and a proportion of fully-bleached grains of 50% (i.e., Figure 6F) yield a CAM D_e similar to the measured sample TDN6-4 (Figure 5A). These results validate that the measured multi-grain aliquots of Figure 5 (except TDN6-4) had small residual doses before the last exposure to sunlight and most of their grains (at least 95%) were fully bleached before deposition. Yang et al. (2020) reached a similar conclusion for their coarse-grained aeolian samples collected from the middle Hexi Corridor to the west of the Tengger Desert.

The bleaching of optically sensitive electrons within a quartz grain depends on both the transport medium and the deposition mechanism. The distance or time duration of transport (Spooner et al., 2001; Singhvi and Porat, 2008) and the deposition process (Rhodes, 2011; Fan et al., 2013) are two major factors influencing the bleaching degree of aeolian sediments, that is, a longer transport distance and a slower deposition rate enable higher degree of bleaching. Since most of the investigated aeolian samples were collected along the margin of the Tengger Desert (with relatively short transport distance), transport distance should not be a critical factor responsible for the good bleaching performance. A possible mechanism prompting a high degree of bleaching is that these near-surface samples have experienced strong wind-driven erosion/reworking processes before their final deposition. This is likely to occur in relatively high-energy environments characterized by intermittent strong winds such as the Tengger Desert (e.g., Fan et al., 2002; Lv et al., 2009; Zhang et al., 2014). The extremely high volume abundances in the uppermost part of the grain-size distributions (see Figure 1B) suggest that almost samples acquired their sorting characteristics in a high-energy environment. An already halted/deposited quartz grain will have a chance to be exposed to sunlight if it subsequently suffers from at least one cycle of erosion/reworking, which explains why the measured multi-grain D_e distributions can be successfully reproduced by the simulation model fed with a small baseline dose. Rhodes (2011) emphasized the importance of total transport time and the repeated burst of movement interspersed with temporary shallow burial or halts on the bleaching of grains and pointed out that the last transport event before the final deposition is not necessarily the most important if the grain has been exposed for sufficient duration during previous movement/rework. In addition, the negligible volume abundances of fine particles contained within almost aeolian samples (Figure 1B) suggest that the bleaching of these coarse grains might have not been severely influenced by the phenomena of aggregation (or the adhering of fine particles to coarser ones) (e.g., Derbyshire et al., 1998) which impedes the bleaching of aggregated grains by attenuating of sunlight during transportation.

The bleaching degree of multi-grain coarse quartz OSL signals from the margin of the Tengger Dessert was investigated by both empirical analysis and numerical validation. The tight D_e distributions and small D_e values indicate that these multi-grain aliquots may have been fully bleached before deposition. A numerical modelling method is able to reproduce multi-grain D_e distributions similar to the measured ones only if the vast majority of the grains within an aliquot are fully bleached and the baseline dose is relatively small during the simulation. These results reassure us to strengthen the conclusion that most investigated samples are fully bleached before deposition, which may be explained by the wind-driven erosion/reworking of the already stopped near-surface sediments and/or the absence of severe aggregation of grains.