An Assessment of the Natural Radioactivity Content in Pigments and an Estimation of the Radiological Health Risk for the Public

Abstract

In this article, an investigation into the natural radioactivity content in natural inorganic pigments was carried out, together with the assessment of the radiological health risk for the public related to external exposure to ionizing radiations, via High-Purity Germanium (HPGe) γ-ray spectrometry measurements and the calculation of several indices like the absorbed γ-dose rate (D), the annual effective dose equivalent outdoor (AEDE_out) and indoor (AEDE_in), and the activity concentration index (I). From the obtained results, it was possible to reasonably exclude radiological hazard effects. In addition, Pearson’s correlation, principal component analysis (PCA), and hierarchical cluster analysis (HCA) were carried out with the aim of determining correlations between natural radioactivity content and radiological indices and with the analyzed samples. As a result, five clusters of the investigated pigments were recognized at the highest level of detail based on their chemical composition and mineralogical nature.

1. Introduction

Scientific research has been interested in the area of archaeology and history for several years, particularly those related to the chemical–physical characterization of materials [1,2]. Knowledge of the compositional features of the raw materials employed in the making of artworks is an additional tool for understanding the artworks themselves, i.e., their provenance, dating, trade, and manufacturing technology, in addition to their own historical–artistic significance and social framework to which the artwork belongs [3].

In the case of natural minerals and earths with coloring effects, namely iron and manganese oxides and hydroxides, a complete overview has already been provided [4,5,6,7,8]. In particular, the presence of pigment pieces of various sizes, pigment powders, and residues, and even paint drops in deposits, like seashells, stone and brick utensils, millstones, vessels of different kinds, and so forth, is well documented [9,10,11]. Moreover, the evidence of ochre processing laboratories (comprising raw materials, working tools, and/or holding vessels) in various time periods and locations reveals that the utilization of dyeing raw products was not random but a well-planned activity since prehistory, requiring a significant investment in time and effort in order to procure and process them [12,13,14].

However, a particularly new issue to be considered in this context relates to the characterization of pigments for painting as far as their natural radioactivity content is concerned and, from that, the evaluation of any potential radiation hazard to the health of the public.

As a matter of fact, natural pigments for painting can be considered environmental matrices due to the presence, in their mineralogical composition, of trace phases containing natural radioisotopes, including decay chains products of primordial uranium (²³⁸U and ²³⁵U), thorium (²³²Th), and ⁴⁰K radionuclide [2,15,16]. The attention placed on the aforementioned natural radioisotopes from a health point of view is due to the circumstance that their annual effective dose rate outdoor constitutes more than half of the radiation exposure for the population [2]. As extensively reported in the literature [17,18,19,20,21], this is a critical point since chronic exposure to uranium and thorium can have various adverse health impacts, such as acute lung disease and leukopenia, head, nose, lung, pancreatic, liver, bone, kidney, and leukemia cancers [22,23,24].

In this regard, the evaluation of the specific activity of the aforementioned natural radioisotopes in pigments for painting can be meaningful for the estimation of background radiation levels in order to assess the effects of radiation exposure on the public [21,25,26]. Noteworthy, it represents one of the aims of this study, together with the employment of multivariate statistical analyses to identify possible correlations between the radioactivity content and radiological indices and with the analyzed samples [27,28]. In particular, investigated pigments were grouped into five clusters, at the highest level of detail, based on chemical nature.

2. Materials and Methods

2.1. Description of the Samples

Investigated samples were commercial natural inorganic pigments for painting, i.e., Raw Sienna, Burnt Sienna, Raw Umber, Burnt Umber, Yellow Ochre, French Ochre, Green Earth from Verona, Terra Pozzuoli, Titanium Orange, and Titanium White, purchased from different factories. In total, fifty samples were analyzed and divided into ten groups (G#, # = 1, 2, …, 10) (five samples per group) according to their chemical nature (see Table 1). Each sample from the group was analyzed by using High-Purity Germanium (HPGe) γ-ray spectrometry, and then the values were averaged per group.

Photos of representative samples of the investigated pigments (one sample per group) are reported in Figure 1.

2.2. HPGE γ-Spectrometry Measurements

HPGe γ-ray spectrometry was used to estimate the natural radioactivity contents of different commercially available pigments. In addition, in order to evaluate any possible radiological health risk for the public, calculations of the absorbed γ-dose rate (D), annual effective dose equivalent outdoor (AEDE_out) and indoor (AEDE_in), and activity concentration index (I) were performed [29].

For the HPGe γ-spectrometry analysis, pigments were desiccated in order to completely remove moisture and to achieve constant mass in Marinelli hermetically closed boxes of 250 mL capacity [30].

Additionally, samples were analyzed for 70,000 s in order to evaluate the activity concentration of ²²⁶Ra, ²³²Th, and ⁴⁰K, as reported in [31]. The minimum detectable activity (MDA) is of the order of 0.1 Bq kg⁻¹ dry weight, d.w., in all cases, according to [30].

The Ortec HPGe detector operating parameters are reported in Table 2 [31].

The detector was placed inside lead sumps in order to screen the background environmental radiation. Noteworthy, calibrations in terms of efficiency and energy were carried out via the use of a 250 mL capacity Marinelli multi-peak gamma source (BC-4464) [32]. The density correction in the efficiency curve for detection was directly carried out by using the Gamma Vision 8.0 (Ortec) software during data analysis [33].

In order to assess the specific activity (Bq kg⁻¹ d.w.) of ²²⁶Ra, ²³²Th, and ⁴⁰K, the following formula was used [34]:

(1)$C=\frac{N_E}{{\epsilon }_E\times t\times {\gamma }_d\times M}$

where N_E indicates the net area of a peak at energy E; ε_E and γ_d are the efficiency and yield of the photopeak at energy E, respectively; M is the pigment mass (kg); and t is the counting time (s).

The measurement uncertainty was estimated as reported in [35] and the Italian Accreditation Body (ACCREDIA) confirmed the quality of the experimental results [36].

2.3. Assessment of Radiological Hazards Effects

For the evaluation of radiological hazard effects for the public, several radiological parameters, such as the absorbed γ-dose rate (D), the annual effective dose equivalent outdoor (AEDE_out) and indoor (AEDE_in), and the activity concentration index (I), were estimated [37,38].

2.3.1. Absorbed γ-Dose Rate (D)

This index was calculated as follows, according to the literature [2]:

D (nGy h⁻¹) = 0.462C_Ra + 0.604C_Th + 0.0417C_K(2)

where C_Ra, C_Th, and C_K are the mean activity concentrations of ²²⁶Ra, ²³²Th, and ⁴⁰K in the pigments, respectively [39].

2.3.2. Annual Effective Dose Equivalent Outdoor (AEDE_out) and Indoor (AEDE_in)

The annual effective dose equivalent for the public was assessed by using the equations below [2]:

AEDE_out (mSv y⁻¹) = D (nGy h⁻¹) × 8760 h × 0.7 Sv Gy⁻¹ × 0.2 × 10⁻⁶(3)

AEDE_in (mSv y⁻¹) = D (nGy h⁻¹) × 8760 h × 0.7 Sv Gy⁻¹ × 0.8 × 10⁻⁶(4)

Both values must be lower than 1 mSv y⁻¹ so that the radiological health risk is negligible [40].

2.3.3. Activity Concentration Index (I)

This index was defined by [40]:

I = C_Ra/300 + C_Th/200 + C_K/3000(5)

It must be lower than 1 in order to have a negligible radiation risk.

2.4. Statistical Treatments

For the statistical treatments, the XLSTAT 2016 software (Addinsoft, New York, NY, USA) was employed [41].

In particular, the principal component analysis (PCA), together with Pearson’s correlation and hierarchical cluster analyses (HCA), was carried out (i) to identify correlations among the original variables, (ii) to find principal components able to account for the greatest amounts of sample variance [41], and (iii) to decrease the number of variables, consistent with Ward’s algorithm, which groups samples according to the measure of dissimilarity between them in terms of Euclidian distance [42].

3. Results and Discussion

3.1. The Specific Activity of the Radionuclides

The average specific activities C_Ra, C_Th, and C_K of, respectively, the ²²⁶Ra, ²³²Th, and ⁴⁰K radionuclides detected in the investigated pigments are reported in Table 3.

Noteworthy, the activity concentration of ²²⁶Ra, ²³²Th, and ⁴⁰K, ranges from (0.75 ± 0.18) Bq kg⁻¹ d.w. (G10) to (80.8 ± 9.8) Bq kg⁻¹ d.w. (G9); from (1.1 ± 0.2) Bq kg⁻¹ d.w. (G10) to (54.1 ± 6.7) Bq kg⁻¹ d.w. (G6); and from (7.6 ± 3.8) Bq kg⁻¹ d.w. (G10) to (1022 ± 116) Bq kg⁻¹ d.w. (G2), respectively.

It should be noted that additional factors have to be taken into account in order to assess hazard indices, as reported in the following section.

3.2. Dose Rate and Dose Assessment and Hazard Indices

Table 4 reports the calculated values of the radiological hazard indices (D, AEDE_out, AEDE_in, I).

Equation (2) was used to calculate D, giving values that range between 1.3 nGy h⁻¹ and 66.6 nGy h⁻¹, with a mean value of 37.7 nGy h⁻¹. The variability of the absorbed dose rates can be attributable to the different content of natural radionuclides in the mineralogical phases of the analyzed pigments [44].

Furthermore, Equations (3) and (4) were used in order to evaluate AEDE_out and AEDE_in, respectively, giving values that range from 0.002 mSv y⁻¹ to 0.082 mSv y⁻¹, with an average value of 0.046 mSv y⁻¹ for AEDE_out, and from 0.008 mSv y⁻¹ to 0.328 mSv y⁻¹, with an average value of 0.185 mSv y⁻¹ for AEDE_in, respectively. All values were found to be lower than 1 mSv y⁻¹, which was set as the maximum limit by [40].

Finally, I, assessed using Equation (5), is lower than unity in all cases [40].

3.3. Statistical Features

First of all, before moving forward with any relevant statistical process, the suitability of the normal distribution assumption of the data was verified. For this purpose, Bartlett’s test was run [45], giving a p-value of 0.04 [46].

Moreover, activity concentrations of the investigated radionuclides, together with the radiological indices, were tested for Pearson’s correlation analysis, which put forward evidence that variables are all positively correlated.

Moreover, the Group IDs, C_Ra, C_Th, C_K, D, AEDE_out, AEDE_in, and I variables were elaborated via the PCA algorithm, giving significant factors reported in Table 5.

The results of PCA analysis are reported in Figure 2, where PC1 and PC2 are put into evidence, accounting for the 95.12% of the total variance.

The figure clearly shows that the variables are all positively correlated and in agreement with Pearson’s correlation matrix.

Moreover, via analysis of the biplot, we can identify four areas that group the considered samples: the first one composed of G1, G2, and G4; the second one of G3 and G8; the third one of G5 and G10; and the last one of G6, G7, and G9. The different behavior evidenced by the PCA algorithm can be strictly dependent on the chemical composition and mineralogical nature of the investigated pigments [47,48,49,50,51].

Finally, the dendrogram reporting the HCA statistical results is shown in Figure 3.

The automatic cut (dotted line), placed on the dendrogram at a 0.104 distance, involves the formation of five clusters. In detail, the first cluster regrouped G1, G2, and G4, whereas G3 and G8 fell into the second cluster. The third cluster was composed of G5 and G10, whereas the fourth and the fifth clusters were formed of G6 and G7 (the fourth one) and G9 (the fifth one), respectively.

From HCA, samples were grouped into five clusters (C1, C2, C3, C4, and C5) (see Figure 4), in very good agreement with the results provided by PCA, from which four clearly distinguishable areas are provided.

In particular, HCA provided more detailed information regarding G9 that should, accordingly, be considered in its own right.

4. Conclusions

The natural radioactivity content of commercial inorganic pigments for painting was investigated vis High-Purity Germanium (HPGe) γ-ray spectrometry.

In particular, calculations of the absorbed γ-dose rate (D), the annual effective dose equivalent outdoor (AEDE_out) and indoor (AEDE_in), and the activity concentration index (I) were carried out to evaluate radiation hazards for human health, giving values lower than the threshold limits for the public in all cases.

Moreover, Pearson’s correlation, principal component, and hierarchical cluster multivariate statistical analyses were developed with the aim of determining correlations between them and the analyzed samples. In particular, an excellent accordance was found between Pearson’s correlation, PCA, and HCA results, with the latter increasing the degree of detail, regrouping into five clusters the group IDs on the basis of the chemical composition and mineralogical nature of the investigated pigments. This is another key result of this paper.

Finally, the evaluation of the radiation risk for human health due to the total (external + internal) exposure of pigment radioactivity to different groups of the population, i.e., pigment ore miners, pigment production workers, pigment storage and transportation workers, and pigment users, in different exposure conditions, will be carried out in the future.

Author Contributions

Conceptualization, F.C. and V.V.; methodology, F.C.; validation, D.M.; formal analysis, A.F.M., A.B., S.M. and M.D.; investigation, F.C., G.P. and V.V.; resources, F.C. and D.M.; data curation, F.C.; writing—original draft preparation, F.C.; supervision, D.M. and V.V. All authors have read and agreed to the published version of the manuscript.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Data are contained within the article.

Conflicts of Interest

The authors declare no conflicts of interest.

Footnotes

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Figures and Tables

Figure 1. The investigated Raw Sienna (a), Burnt Sienna (b), Raw Umber (c), Burnt Umber (d), Yellow ochre (e), French Ochre (f), Green Earth from Verona (g), Terra Pozzuoli (h), Titanium Orange (i), and Titanium White (j) pigments.

Figure 2. PCA biplot. Green circles represent areas that group the considered samples.

Figure 3. Dendrogram reporting the HCA statistical results. Different colors represent clusters that group the considered samples.

Figure 4. HCA statistical results after cut at 0.104. Colors indicate clusters that group the investigated samples.

Table 1

Investigated pigments, together with their identification code (Group ID), chemical characterization, and number of analyzed samples for each group.

Group ID	ChemicalCharacterization		Origin	Number of Samples
G1	Raw Sienna	Fe2O3 ∙ nH2O + Al2O3 ∙ MnO2 + SiO2 ∙ H2O	Italy	5
G2	Burnt Sienna	Fe2O3 ∙ nH2O + Al2O3 ∙ MnO2	Italy	5
G3	Raw Umber	CaSO4 · 2H2O + CaSO4 + CaCO3 + FeO(OH) + clay	Italy	5
G4	Burnt Umber	CaSO4 · 2H2O + CaSO4 + Fe2O3 + CaCO3 + clay	Italy	5
G5	Yellow Ochre	Fe2O3 ∙ nH2O	Italy	5
G6	French Ochre	SiO2 + Al2O3 + Fe2O3	Germany	5
G7	Green Earthfrom Verona	K(Mg,Fe2+)(Fe3+,Al)[Si4O10](OH)2 + (K,Na)(Fe3+,Al,Mg)2(Si,Al)4O10(OH)2	Germany	5
G8	Terra Pozzuoli	Fe2O3 · nH2O	Germany	5
G9	Titanium Orange	Ti-Sb-Cr-O Rutile	Germany	5
G10	Titanium White	TiO2	Germany	5

Table 2

The HPGe detector operating parameters [31].

HPGe Detector
Full Width at Half Maximum	1.94 keV
Peak-to-Compton ratio	65:1
Relative efficiency	37.5% (at the 1.33 MeV 60Co γ-line)
Bias voltage	−4800 V
Energy range	5 keV–2 MeV

Table 3

The average specific activities C_Ra, C_Th, and C_K, of, respectively, ²²⁶Ra, ²³²Th, and ⁴⁰K (Bq kg⁻¹ d.w.), evaluated for the investigated groups of pigments.

Group ID	CRa(Bq kg−1 d.w.)	CTh(Bq kg−1 d.w.)	CK(Bq kg−1 d.w.)
G1	12.1 ± 3.8	23.1 ± 6.5	546 ± 67
G2	15.3 ± 4.9	23.0 ± 6.4	1022 ± 116
G3	13.5 ± 4.1	5.8 ± 2.9	486 ± 56
G4	8.3 ± 3.1	15.2 ± 4.8	873 ± 98
G5	10.6 ± 3.3	13.3 ± 3.9	104 ± 21
G6	55.9 ± 6.8	54.1 ± 6.7	196 ± 38
G7	26.5 ± 4.8	48.5 ± 5.9	136 ± 25
G8	3.5 ± 1.8	1.5 ± 0.9	43.7 ± 5.8
G9	80.8 ± 9.8	26.4 ± 4.8	32.4 ± 5.1
G10	0.75 ± 0.18	1.1 ± 0.2	7.6 ± 3.8

Table 4

Radiological hazard indices. See text for details [43].

Group ID	D(nGy h−1)	AEDEout(mSv y−1)	AEDEin(mSv y−1)	I
G1	42.3	0.052	0.208	0.34
G2	63.6	0.078	0.312	0.51
G3	30.1	0.037	0.148	0.24
G4	49.4	0.061	0.244	0.39
G5	17.3	0.021	0.084	0.14
G6	66.6	0.082	0.328	0.52
G7	47.2	0.058	0.232	0.38
G8	4.4	0.005	0.020	0.03
G9	54.6	0.067	0.268	0.41
G10	1.3	0.002	0.008	0.01
Average	37.7	0.046	0.185	0.30

Table 5

Significant factors extracted before the PCA elaboration.

PC1	PC2	PC3
5.244	1.414	0.341
74.917	20.203	4.874
74.917	95.121	99.995

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