Application of different protocols and age-models in OSL dating of earthen mortars

The earthen mortars analyzed in this study are briefly described in Table 1. They came from two buildings located in Cremona, a small town in the Po valley, Northern Italy: Palazzo Raimondi (PR), built between 1493 AD and 1496 AD and Palazzo Soldi (PS), one of the most important residences of the town until the 15^th century. They are similar in size, typology and construction techniques and were chosen for the completeness of the diagnostic investigations, historical surveys and available building stratigraphy. Those aspects allowed identifying mortars belonging to precisely and accurately dated structures: the original construction phase for Palazzo Raimondi (1495 AD) and a late 18^th century restoration phase at Palazzo Soldi. The mortar samples were collected without exposing the material to daylight by means of a darkened environment made with a textile and using a red lamp. They were sampled using a chisel and a hammer. First of all the surface layer of the mortar was removed and then the inner part was collected and put into a black plastic bag. The upper and lower bricks in contact with each mortar joint were sampled as well. The mortars were very similar, consisting in an angular to subangular, moderately to poorly sorted, coarse to fine grained quartz-rich aggregate dispersed in a silty-clayey matrix. The matrix (grain size < 63 μm) usually ranged between 5 and 10 wt%, seldom reaching 20 wt%, and was composed of predominant quartz and fresh and/or weathered phyllosilicates. Little amount of carbonates might be present in the fine fraction due to lime addition to the mortars, especially in post-17^th century samples. The aggregate (grain size > 63 μm) ranged between 75 and 95 wt%, mainly composed of quartz grains (30–40%), metamorphic rock fragments (mica schist and quartz-rich rocks, 5–30%), feldspars (5–10%), phyllosilicates (5–15%), amphiboles (0–5%), carbonates (0–5%), brick fragments (0–5%) and rare lime lumps (Cantù et al., 2015).

Table 1

List of the analyzed samples with weight and their yield in 150–250 μm quartz.

For OSL measurements, samples were chemically treated, separated and prepared according to the standard procedures (Preusser et al., 2008; Mejdahl, 1985) to obtain the 150–250 μm size quartz fraction. Table 1 also reports the samples weight and their yield in 150–250 μm quartz.

Multi-grain aliquots were prepared by fixing the quartz grains onto 10 mm diameter stainless steel disks with silicon oil (covered area: about 3 mm diameter, corresponding to roughly 300 grains). For the single-grain procedure, the quartz grains were mounted on special 10 mm diameter aluminium disks with a grid of 10×10 holes holding the individual crystals.

OSL measurements were carried out with a Risø TL/OSL DA-20 reader. Photons were detected by a bialkali photomultiplier tube (EMI 9235QB) coupled to a 7.5 mm Hoya U-340 band pass UV filter (280–380 nm). Artificial β irradiations were given using a ⁹⁰Sr-⁹⁰Y source delivering 0.13 ± 0.01 Gy/s.

OSL measurements were performed using the single-grain procedure. The small aliquot multi-grain procedure was applied if a minimum of 10 multi-grain aliquots could be prepared.

The multi-grain aliquots were stimulated by an array of blue LEDs (470 ± 30 nm) with a constant stimulation power of 54 mW/cm² or with IR LEDs (830 ± 10 nm) with a constant stimulation power of 360 mW/cm². The samples were stimulated at 125°C for 40 s. Single-grain measurements were performed using the single-grain laser attachment of the Risø system. The stimulation source was a 10 mW Nd:YVO₄ solid-state diode-pumped laser emitting at 532 nm, which can be focused sequentially on each of the 100 grains mounted on the disk (Bøtter-Jensen et al., 2003). Each grain was stimulated for 1 s at 125°C.

The OSL signal of multi-grain aliquots was obtained integrating the first 0.64 s and subtracting the background signal (mean of the OSL signal of the last 8 s). The OSL signal of single-grains was obtained integrating the first 0.2 s less the background (OSL signal of the 0.7–0.9 s range).

To evaluate the absorbed radiation dose, D_e (Eq. 1.1), the Single Aliquot Regenerative-dose (SAR) protocol was used (Wintle and Murray, 2006; Murray and Wintle, 2003 and 2000), applying from three to five regeneration doses. A zero dose point was given after the highest regeneration dose measurement cycle to check the recuperation of the signal, followed by the repetition of the first regeneration dose for the recycling test. The purity of quartz samples was tested by OSL post IR measurements (Duller, 2003). The pre-heat temperature was chosen by means of the pre-heat plateau test.

For each sample, many D_e have to be evaluated, in principle one for each multi-grain aliquot or one for each single-quartz grain. They were estimated using the Risø Analyst 4.31.7 software by interpolating the natural sensitivity-corrected signal onto the dose response curve. The uncertainties associated to such individual D_e were calculated from counting statistics, curve fitting and assuming an instrumental reproducibility error of 2.5%.

To get the best estimate of the true value of a sample’s D_e, all the individual values were statistically elaborated using the software R and Luminescence 0.4.4 package (http://CRAN.R-project.org/package=Luminescence), applying the statistics briefly described below:

To obtain the annual dose-rates of Eq. 1.1, the radioactivity of the samples and of the surrounding bricks was measured. These analyses were necessary to evaluate the true value of the D_e absorbed by the single samples, as described in the following. ²³⁸U and ²³²Th concentrations were derived from alpha counting of the crushed bulk mortars and adjacent bricks using ZnS (Ag) scintillator discs and assuming a Th/U concentration ratio equal to 3.16 (Aitken, 1985). Contribution due to ⁴⁰K content was obtained from the total concentration of K measured by flame photometry. The saturation water content of both mortars and bricks ranged from 10 to 12%. Taking into account the wet climate of the area and the high humidity conditions at the sampling points, the 75 ± 15% of saturation was assumed for calculations. The attenuation of the beta particles in coarse grain quartz was taken into account (Bell, 1979). The gamma external contribution mainly derives from the radioactivity of a 30 cm diameter sphere centered at the sampling point (Aitken, 1985). Such contribution was evaluated from the radioactivity concentrations of the mortars themselves and of the surrounding bricks (Galli et al., 2014). The contribution of each material to the annual dose-rate was evaluated applying the infinite matrix approximation, with updated conversion factors (Guérin et al., 2011). The radiation-matter interactions are similar in bricks and mortars, since the effective atomic mass Z* is similar in the two materials, and so do the mass attenuation coefficients (evaluated to approximately 3·10^–2cm²/g at 2.5 MeV). To model our system we considered a sequence of homogenous 50 mm thick bricks assembled with 10 mm-thick mortar layers, as obtained after in situ measurements. In these conditions the brick contribution to the external dose rate within the interaction sphere does not exceed 40%.

The main results of radioactivity measurements are reported in Table 2, together with the resulting dose-rates, including a 0.15 mGy/a cosmic ray contribution (Prescott and Hutton, 1994).

Table 2

Radioactivity concentration in mortars (column 2–4) and bricks (column 5–7), derived annual total dose rates and calculated expected D_e.

Because both the annual dose-rate and the age of the samples are known, their true D_e can be derived by the inverse formula of Eq. 1.1: De(GY)=Age (a)⋅Dose rate (Gy/a)$$\begin{array}{} \text{D}_{\text e}\text{(GY)}=\text{Age (a)}\cdot\text{Dose rate (Gy/a)} \end{array}$$(3.1)

Such D_e are obtained by multiplying the data of column 4 of Table 1 by those of column 8 of Table 2. They are listed in Table 2, column 9. They have been taken as reference values to which compare the experimental results given by the different experimental protocols and/or statistic elaborations, and referred to, in the following, as expected D_e.

The multi-grain protocol was used for the six mortars listed in Table 3, those for which more than ten quartz aliquots could be prepared. Individual D_e values were rejected if one of the following criteria was not satisfied: recycling ratio between 0.9 and 1.1, recuperation < 5%, IR test < 10%.

Table 3

Multi-grain technique: Expected D_e and D_e evaluations with different statistical models.

Eventually, the percentage of acceptable aliquots ranged from 40 to 70%, as shown in Table 3, also reporting the D_e results given by weighted mean, CAM, MAM and ul-MAM models. The same results are visualized in Fig. 1, grouped by model and normalized to the expected D_e.

Fig. 1

All the models overestimate the D_e, CAM giving the worse results. Regardless the statistic model used for data elaboration, the multi-grain protocol gives D_e values higher than expected, which will lead to a significant and systematic age overestimation. This is reasonably caused by an ineffective or inhomogeneous bleaching of the quartz grain. This can be due to the presence of hard to bleach grains and/or insufficient exposure to sunlight during the preparation of the mortar. Whatever the reason, the quartz grains did not receive enough sunlight to fully erase the luminescence signal acquired over geological time and the bleaching process results in an incompletely and heterogeneously reset grain mixture. The multi grain technique is therefore unsuitable for this typology of samples.

For the single-grain analysis, between 3200 and 4800 grains for each sample were measured. The percentage of grains giving a detectable OSL signal ranged between 15 and 25% (Table 4, 4^th column). Even if relatively bright, the grains were rejected if one of the following conditions occurred: the signal was less than 3 standard deviations above the background, the recycling ratio was out of 0.75–1.25 range, the error associated to the test dose was >25%, the dose response curve determined from laboratory regeneration doses did not intersect with the natural signal. In such a way, less than 4% of the grains could be used for D_e evaluation (Table 4, 5^th column).

Table 4

Single-grain technique: expected D_e and D_e evaluations with different statistical models.

The radial plots and the distributions of the individual D_e obtained for the 10 mortar samples are visualized in Fig. 2 (Palazzo Raimondi) and Fig. 3 (Palazzo Soldi), showing a high dispersion with D_e values up to hundreds of Gy. These data were elaborated to get the best estimate of the the sample’s D_e according to the various statistical models. The D_e results obtained with the weighted mean are from to 2 to 5 times higher than expected, the mean error being about 6%. The CAM (Table 4, column 9^th) gives results approximately 10 to 20 times higher than expected, with higher errors (10–30%). The over-dispersion parameter (OD) is also reported in Table 4, column 6^th. It corresponds to the standard deviation value of the CAM D_e (Galbraith et al., 1999). The intrinsic D_e over-dispersion, required for the application of both the Minimum Age Model and the Internal-External Consistency, is also shown in Table 4, column 7^th. It was measured with the dose recovery test (Urbanova et al., 2015). The grains were individually bleached by double green light illumination intercalated to a 10000 s pause. A known beta dose (2.58 ± 0.05 Gy) was given to the sample and subsequently measured. The OD values so obtained varied between 20 and 30%, being considerably lower than the over-dispersion of the archaeological D_e (see Table 4, 6^th column). The contribution of the extrinsic factors to the OD is therefore consistent, indicating the incomplete bleaching as the responsible of the observed huge spread of D_e.

Fig. 2

Fig. 2

Fig. 3

Fig. 3

The results of the MAM (column 10^thTable 4) were always higher than expected while those of un-logged MAM (column 11^thTable 4) were consistent (±1σ) with the expected ones for five samples out of ten. The same was found with the IEU model (column 12^thTable 4), for which the OD calculated with the dose recovery test was added in quadrature to the uncertainties of each individual D_e (Thomsen et al., 2012, 2007 and 2003). All the D_e results of Table 4, normalized to the expected D_e, are visualized in Fig. 4a, grouped by method. Fig. 4b shows only the results of ul-MAM and IEU.

Fig. 4