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The use of portable equipment for the activity concentration index determination of building materials: method validation and survey of building materials on the Belgian market
Journal of Environmental Radioactivity 127 (2014) 56e63
Contents lists available at ScienceDirect
Journal of Environmental Radioactivity journal homepage: www.elsevier.com/locate/jenvrad
The use of portable equipment for the activity concentration index determination of building materials: method validation and survey of building materials on the Belgian market M. Stals a, b, *, S. Verhoeven a, M. Bruggeman c, V. Pellens a, b, W. Schroeyers a, b, S. Schreurs a, b a b c
NuTeC (Nuclear Technological Centre), Wetenschapspark 27, 3590 Diepenbeek, Belgium Hasselt University, Agoralaan Gebouw D, 3590 Diepenbeek, Belgium Nuclear Research Centre SCKCEN, Laboratory of gamma spectrometry, Boeretang 200, 2400 Mol, Belgium
a r t i c l e i n f o
a b s t r a c t
Article history: Received 21 May 2013 Received in revised form 23 September 2013 Accepted 26 September 2013 Available online 22 October 2013
The Euratom BSS requires that in the near future (2015) the building materials for application in dwellings or buildings such as offices or workshops are screened for NORM nuclides. The screening tool is the activity concentration index (ACI). Therefore it is expected that a large number of building materials will be screened for NORM and thus require ACI determination. Nowadays, the proposed standard for determination of building material ACI is a laboratory analyses technique with high purity germanium spectrometry and 21 days equilibrium delay. In this paper, the B-NORM method for determination of building material ACI is assessed as a faster method that can be performed on-site, alternative to the aforementioned standard method. The B-NORM method utilizes a LaBr3(Ce) scintillation probe to obtain the spectral data. Commercially available software was applied to comprehensively take into account the factors determining the counting efficiency. The ACI was determined by interpreting the gamma spectrum from 226Ra and its progeny; 232Th progeny and 40K. In order to assess the accuracy of the B-NORM method, a large selection of samples was analyzed by a certified laboratory and the results were compared with the B-NORM results. The results obtained with the B-NORM method were in good correlation with the results obtained by the certified laboratory, indicating that the B-NORM method is an appropriate screening method to assess building material ACI. The B-NORM method was applied to analyze more than 120 building materials on the Belgian market. No building materials that exceed the proposed reference level of 1 mSv/year were encountered. Ó 2013 Elsevier Ltd. All rights reserved.
Keywords: Building materials NORM Euratom Basic Safety Standards Activity concentration Measurement
1. Introduction On average, one stays for 80% of the time indoors. Therefore, it is relevant to assess the radiation dose a person receives from the building materials. Most building materials contain certain amounts of the naturally occurring radionuclides 226Ra, 232Th and 40 K. Building materials of natural origin reflect the geology of their origin (Haquin, 2008). Besides this, the trend to re-use industrial by products in building material may enhance the building material activity concentration. Therefore, it is relevant to study NORM in building materials. Moreover, NORM in building materials will be legally regulated in the near future (Euratom, 2013). The Basic Safety Standards (BSS) is a European Directive concerning (among others) the protection of the public and the
* Corresponding author. NuTeC (Nuclear Technological Centre), Wetenschapspark 27, 3590 Diepenbeek, Belgium. Tel.: þ3211 370 794. E-mail address: [email protected] (M. Stals). 0265-931X/$ e see front matter Ó 2013 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.jenvrad.2013.09.012
workers against the dangers of ionizing radiation. It is expected that the EU member states will ratify the Directive by 2015. The new Euratom BSS, explicitly mentions natural radioactivity in building materials: “The competent authority shall make arrangements for the classification of identified types of building materials, as laid down in Annex 11,1 on the basis of their intended use and activity concentration index I.” The article also states that the radiological information shall be published before marketing the material. In order to determine the building material activity concentration index I, one has to determine the activity concentrations of the radionuclides 226Ra; 232Th and 40K. Different formulas exist for the calculation of the activity concentration index; e.g. (Steger et al.,
1
The Annex number is likely to change in final version of the text.
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57
1992) but the most widespread formula is the one used in the Euratom BSS:
I ¼
C
226 Ra
300
þ
C
232 Th
200
þ
C 40 K 3000
(1)
With: C ¼ activity concentration of the respective nuclide in secular equilibrium [Bq/kg] The activity concentration index (ACI) of a building material, whether bulk or superficial material shall not be higher than 1. If the index is higher than 1, a dose model should be calculated in order to determine the annual excess external dose. The activity concentration index is related to the excess gamma radiation dose resulting from the use of the respective materials. It is applicable for the material as a whole and not for its constituents. The extra gamma radiation dose due to the use of building materials may not exceed the reference level of 1 mSv/a. The constants in the formula are derived for a described room and a material with a certain density (EC, 1999). If the actual room or material circumstances differ from the circumstances on which Equation (1) is based, it may not be completely accurate. This causes, among relevant parties, some discussion concerning the applicability of one formula for all different building materials.2 If the allowed reference level of 1 mSv/year is exceeded, the competent authority shall decide on appropriate measures ranging from registration, dosimetric study, general application of relevant building codes, to specific restrictions on the envisaged use of such materials. The requirement to determine the activity concentration index implies that in the near future, numerous gamma spectrometric analyses have to be performed on building materials. With the B-NORM project, NuTeC strives for the development of an easy to operate; on-site measurement method (Bronson, 2008), that facilitates companies with gamma spectrometric measuring tools. This method is intended to be a valuable in situ screening tool that can be used additionally with “conventional” high resolution gamma spectrometry in a laboratory. 2. Materials and method 2.1. Materials: building materials The current paper is focused on building materials that are available on the Belgian market. The most common types of building materials that are applied in the construction of dwellings are studied. The results are discussed per type of building materials: tiles and stones; bricks, concrete, cement and gypsum. 2.2. B-NORM method In the B-NORM method, a Canberra Inspector 1000 (In1k) equipped with an intelligent stabilized 1.500 LaBr3(Ce) probe is used to obtain the spectral data. The LaBr3(Ce) probe is operated at ambient temperature and has improved properties compared to NaI(Tl) probes: it has a 2.9% resolution at 662 keV (7% for NaI(Tl)); 160% relative light output and a fast decay time of 16 ns. The In1k can be set-up in any room with a reasonable low and stable background. High background radiation is detrimental, especially when measuring low activity materials. Measuring in 100 nSv/h or higher background level should be avoided.
2
EAN-NORM round table workshop; “Transportation of NORM, NORM Measurements and Strategies, Building Materials" Nov. 29th e Dec. 1st 2011, Hasselt (Belgium).
Fig. 1. B-NORM method: setup for counting a sample.
In practice, e.g. when measuring in a supplier’s warehouse, one should make arrangements with the owner so that no materials are removed or positioned near the measuring location; because these actions will alter the background radiation during the acquisition. In a first stage, the background spectrum is acquired. This step is required for each different measurement location. Then, the sample is positioned in front of the probe and the spectrum is acquired. The spectrum acquisition itself is a “one-touch and let alone” operation that can be performed by untrained personnel. The sample geometry consists of well-positioned whole building materials, e.g. a stack of tiles, a stack of packs of tiles, a pallet of bricks or a stack of concrete testing cubes from the firm’s own material testing lab. An example of an actual measurement setup is shown in Fig. 1. We carefully determine the geometry dimensions, mass, shape, material composition and detector configuration and position. This information is loaded into Canberra In Situ Object Counting Software (ISOCS) to determine the counting efficiency of the measurement setup. The influence of the sample size and geometry is discussed under 3.1. Spectrum analysis is performed with Genie2000. The analysis includes (besides peak localization and net peak area calculation) a peaked background correction, efficiency correction, selection of applicable peaks from the nuclides of interest and an interference correction. When the activity concentrations of the nuclides are determined, the ACI (Activity concentration index) is calculated. The nuclide 226Ra can be assessed with the B-NORM method in two ways. First option is to directly determine 226Ra by measuring its 186.2 keV line and correcting 57.1% for natural 235U (185.9 keV). This correction is only correct if the assumption that the natural equilibrium has not been disturbed is true. The second option is to determine the 214Pb and 214Bi progeny of 226Ra. This option will be accurate only if the secular equilibrium is not disturbed. In fact, it can not be absolutely assured that any of these assumptions will lead to the actual, accurate determination of the activity of 226Ra. Since building materials are usually dense materials and the material thickness is large because we are not milling the materials, we assume the secular equilibrium condition to be met and therefore we calculate the 226Ra concentration via 226Ra progeny. 2.3. Method validation The current accepted “standard” method for gamma spectrometric analysis of solid substances is to analyze the sample in a laboratory with a lead-shielded high purity germanium detector. The geometry is a precisely defined, usually relatively small sample
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Fig. 2 shows that with a sample mass of over approximately 50 kg, the efficiency gain per unit of mass added to the sample strongly decreases. The efficiency gain per extra sample mass becomes little in larger samples, this has two main causes: (1) the “extra” material is positioned further away from the detector. Therefore, gammas have to travel a longer distance to reach the detector and the detector covers a smaller solid angle, lowering their detection efficiency, and (2) in a larger sample, gammas have to travel a longer distance through dense material, therefore the radiation will be attenuated thus reducing their detection efficiency. Taking practical work into account, a sample size of 25e 50 kg is a suitable balance between sample weight and detection efficiency.
Fig. 2. Detection efficiency versus sample mass (concrete cube; 2.14 kg/dm3). Error bars show uncertainty of efficiency*mass (1 s).
beaker. The material to be analyzed is carefully milled and introduced into the sample beaker. Before analyzing the sample, the sample holder is usually tightly closed for 21 days in order to obtain secular equilibrium. The standard procedure is described in (NEN, 2001). In order to assess the results of the B-NORM method, 26 samples (14 tiles, 11 stones and 1 gypsum) were analyzed with the standard method (NEN, 2001) in an accredited laboratory.3 Tiles and stones were chosen because they offered a wide range of ACI. The sample milling for the laboratory analysis was performed by an accredited construction material testing laboratory. For 226Ra and ACI, the results from the certified laboratory were compared with the BNORM radium determination via 226Ra progeny. 3. Results and discussion
3.1.2. Relation between sample geometry and detection efficiency The B-NORM method is flexible concerning the geometry shape. Virtually any sample shape can be modeled and counted. In practice, one will usually position the building materials in a rectangular plane or cubical geometry. To gain information on how to position the sample in such a way that good detection efficiency is obtained, we studied two cases. Case 1 was to stack the sample like a cube. This results in shorter average distance to the detector, but gammas need to travel via a long path through dense material. Case 2 was to stack the sample like a flat rectangular plane. This results in longer average distance to the detector, but gammas do not need to travel via a long path through dense material. From common insights in detection efficiency, one will not chose to position the materials in an extremely flat or extremely thick configuration. The “flat plane geometry” proposed in the next paragraph has a thickness of 10 cm, which should be considered as a minimum recommended thickness. The two cases were calculated for concrete blocks with a density of 2.14 kg/dm3 and for aerated concrete blocks with low densities of 1.00 kg/dm3 and 0.60 kg/dm3; for gamma energies of 200, 800 and 1500 keV. The calculation was done for sample mass between sizes between 1 dm3 and 125 dm3. In this example, the flat plane has a thickness of 10 cm; while length equals width and varies according to sample volume, see Table 1. Equation (2) was calculated and the results are shown in Fig. 3
efficiency$massðplaneÞ efficiency$massðcubeÞ
3.1. Influence of sample size and geometry on the detection efficiency
relative efficiency ¼
With the B-NORM method, the efficiency curve is calculated by software. This allows for a wide variety of possible geometry sizes and shapes. However, not any size or shape may be suitable. It is interesting to determine a relation between sample mass (“size”); sample shape and detection efficiency: this will provide the necessary information to use a relevant sample size and shape.
Fig. 3 (a) shows that for the dense concrete, a flat plane geometry results in higher counting efficiency than a cubic geometry. The largest observed difference was approximately 22% for the 17.12 kg sample. The difference between the cube and flat plane diminishes in a larger geometry: the outer regions of our flat plane of only 10 cm thickness are located at a large distance from the detector. The flat plane thickness can be increased when counting large sample volumes to keep the outer edges of the geometry closer to the detector and thus increasing the detection efficiency. The energy of the gammas is only slightly relevant, especially at lower sample mass. It can be concluded that a relatively flat geometry yields a better efficiency then cube geometry, when the sample density is relatively high and especially when the sample volume isn’t too large. Fig. 3 (b) and 3 (c) show that for the aerated concrete with a relatively low density, the flat plane geometry is again a more efficient option. The difference compared to the cube geometry is approximately 20% for a 4.8 kg sample (density 0.6 kg/dm3). However the difference diminishes quickly with increasing sample volume. A cube geometry is more efficient than a (relatively flat) rectangular plane geometry when a large volume (larger than approximately 50 dm3) of low density material is counted.
3.1.1. Relation between sample size and detection efficiency A larger sample will result in enhanced detection efficiency, but it is expected that beyond a certain sample mass, only limited efficiency gain can be obtained by measuring an even larger sample. To establish the relation between sample mass and efficiency, we used the software to model a concrete cube, with the detector facecentered on the cube. We calculated the detection efficiency for various sample sizes between 1 dm3 and 125 dm3; this equals 2.14 kg and 267.5 kg respectively, when a material density of 2.14 kg/dm3 is assumed. The calculation was performed for photon energies of 200, 800 and 1500 keV.
3 Nuclear Research Centre SCKCEN e Laboratory of gamma spectrometry; Boeretang 200; 2400 Mol (Belgium).
(2)
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Table 1 Geometry parameters used for calculating the relation between geometry shape and detection efficiency. Geometry dimension cube (cm) 10 15 20 25 35 50
10 15 20 25 35 50
10 15 20 25 35 50
Geometry dimension plane (cm)
Mass of cube and plane (kg) density ¼ 2.14 kg/dm3
Mass of cube and plane (kg) density ¼ 1.00 kg/dm3
Mass of cube and plane (kg) density ¼ 0.60 kg/dm3
10 10 10 18.37 18.37 10 28.28 28.28 10 39.53 39.53 10 65.48 65.48 10 111.80 111.80 10
2.14 7.22 17.12 33.44 91.75 267.5
1.000 3.375 8.000 15.625 42.875 125.000
0.600 2.025 4.800 9.375 25.725 75.000
With the lower density materials, the influence of the gamma energy becomes more pronounced, the lower energy photons slightly favor the flat plane geometry. One can conclude that it is in most cases more efficient to build a rectangular plane geometry. If sample volumes are large (more than approximately 50 dm3) and material density is low (lower than approximately 1 kg/dm3), one should consider to build a cube geometry. Efficiency gains of up to 20% can be obtained by selecting a proper geometry.
concentration in Equation (1). This results in a theoretical minimum detectable ACI of less than 0.3, which is well below the ACI limit of 1 for bulk materials or surface materials. If the measurement result would be below MDA, no problem occurs since MDA is well below the ACI limits. A high background radiation is undesirable regarding the method MDA. Measurement in high background circumstance should be avoided.
3.2. B-NORM method detection limits
The B-NORM method is proposed as a screening tool for on-site building material ACI determination. To validate this, 26 building materials (14 tiles, 11 stones and 1 gypsum) that were analyzed with the B-NORM method are also analyzed with the reference analyses method in a certified laboratory. The materials were chosen to obtain a wide variety in ACI and activities of 226Ra, 232Th and 40K. The activities of 226Ra, 232Th and 40K and the ACI determined via the standard method are compared with the results obtained via the B-NORM method. Table 3 lists the samples that are studied in the intercomparison. Where traceable, the manufacturer of the mentioned tile is included. For stones, the place of origin is included. Besides these stones and tiles, one gypsum sample (Knauf Goldband) was included as well.
Because of the possibility of the B-NORM method to perform measurements at different locations and on samples with different sizes, weights and compositions, it is not possible to determine a single detection limit that is valid in all cases. Therefore the detection limit was calculated for two different circumstances that resemble the vast majority of possible counting conditions. From the detection limit of each relevant gamma-ray emission line from 40 K, 214Pb, 214Bi and 228Ac, the according minimum detectable activity (MDA) was calculated. To calculate the MDA, the method originally described by (Currie, 1968) was used. The Genie 2000 software was setup to apply the Currie method for MDA calculation. The documentation (Canberra, 2009) describes in detail how the software performs the necessary calculations. From the calculated line MDA’s, the worst line MDA was accepted as nuclide MDA and the corresponding minimum detectable ACI was calculated. Results in a background of 20 nSv/h and 50 nSv/h are reported in Table 2, the probability for errors of the first and second kind are 0.05; k ¼ 1.654. The increase in MDA in 20 nSv/h vs. 50 nSv/h background is small since not only the background interference but also the continuum is a factor in calculating the MDA:
LD ¼ k2 þ 2LC
(3)
qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi Lc ¼ k mC þ mB þ s2C þ s2B
(4)
where LD is the limit of quantification; k is the confidence factor; Lc is the critical limit; mC is the true continuum; mB is the background interference; sC is the variance of the continuum; sB is the variance of the background interference. Since the continuum is relative large compared to the background interference, a slight increase in background only slightly increases the MDA. The nuclide MDA’s allow for the calculation of a theoretical minimum detectable ACI, by accepting the MDA as nuclide
3.3. Method validation
3.3.1. Activity of 226Ra The observed 226Ra concentrations varied between approximately 3e980 Bq/kg, according to the laboratory analysis. The high activity concentration of 980 Bq/kg was found in onyx multicolor. The next lower observed concentration is found in Café Maron; 189 Bq/kg; i.e. approximately 4 times less. Therefore, the onyx multicolor 226Ra concentration dominates the linear regression calculation, as shown in Fig. 4, left. Within the range 3e980 Bq/kg a very good correlation (r2 ¼ 0.99) between laboratory and B-NORM method is observed and the slope of the regression line is 0.95, promising accurate results within the 226Ra range of 3e980 Bq/kg. However, the nature of the un-weighted regression analysis implies that results in the lower concentration range may not be described well by the model, if the high outlier is retained. Therefore, the regression line is re-calculated without the onyx multicolor sample; Fig. 4, right. The correlation coefficient within the range 3e189 Bq/kg is appreciable (r2 ¼ 0.92), but the slope of the regression line is 0.80, indicating that the B-NORM method (the standard uncertainty in the given concentration range is approximately 15%) will yield slightly lower results than the laboratory analysis; for 226Ra concentrations lower than approximately 200 Bq/kg. Two possible causes for the lower B-NORM response are put forward. Firstly, in the B-NORM method, the sample is not encapsulated in radon-tight container for at least 21 days but measured as is and on-site. Thus, although our initial assumption was that radon loss via radon exhalation is minimal, it can be remarked that radon exhalation will reduce the amount of 226Ra progeny contained in the sample. Parameters influencing radon
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Fig. 3. Relation between geometry shape and detection efficiency: (a) Concrete, 2.14 kg/dm3; (b) aerated concrete, 1.00 kg/dm3; (c) aerated concrete, 0.60 kg/dm3. The uncertainty (1 s) of the efficiency calculation is 10% (200 keV); 8% (800 and 1500 keV).
emanation (among others) include grain size, permeability of the grains, and location of the radium atoms within the grains. Porosity, thickness of the material and moisture are prime factors influencing the radon diffusion length. When the diffusion length is longer, a larger portion of emanated radon will also be exhaled (de Jong, 2010a) resulting in a lower measured radium progeny concentration. Although results may vary for different materials,
it was reported that on average 22% of the radium content was exhaled as radon from 25 granite samples (Al-Jarallah et al., 2005). The radon exhalation rate is reported to be well correlated (r2 ¼ 0.90, n ¼ 25) with the total radium content (Al-Jarallah et al., 2005). The results obtained with the B-NORM method are in fair agreement with this observation of detecting 22% less radium in unsealed samples.
M. Stals et al. / Journal of Environmental Radioactivity 127 (2014) 56e63 Table 2 Nuclide MDA and minimum detectable ACI in different measurement circumstances. Nuclide
Line energy (keV)
Line MDA (Bq/kg)
Circumstance a1: 72000 s measurement of a 23.55 kg concrete sample, in a 20 nSv/h background ameasured during 72000 s. 214 Pb 295 7.7 214 Pb 351 5.4 214 Bi 609 4.7 228 Ac 911 9.4 228 Ac 969 16 40 K 1460 43 Circumstance A minimum determinable ACI: 0.13 Circumstance b1: 72000 s measurement of a 7.668 kg low-density brick sample, in a 20 nSv/h background measured during 72000 s. 214 Pb 295 11 214 Pb 351 8.9 214 Bi 609 5.9 228 Ac 911 16 228 Ac 969 26 40 K 1460 65 Circumstance B minimum determinable ACI: 0.19 Circumstance a2: 72,000 s measurement of a 23.55 kg concrete sample, in a 50 nSv/h background measured during 72,000 s. 214 Pb 295 8.4 214 Pb 351 4.7 214 Bi 609 5.1 228 Ac 911 10 228 Ac 969 18 40 K 1460 44 Circumstance A minimum determinable ACI: 0.13 Circumstance b2: 72,000 s measurement of a 7.668 kg low-density brick sample, in a 50 nSv/h background measured during 72,000 s. 214 Pb 295 12 214 Pb 351 8.6 214 Bi 609 6.6 228 Ac 911 17 228 Ac 969 27 40 K 1460 70 Circumstance B minimum determinable ACI: 0.20 a Background level given as indication. It is necessary to obtain the background spectrum and to perform peaked background subtraction.
Table 3 Samples included in inter-comparison. Manufacturer
Type
Tiles Azulev Atlas Concorde Savoia Essenza Pera Societé de caramique de chebadda Tervola (Foshan, China) Unknown Onna Alfalux Grespania Marco Polo Sintesi
Atrio carrara Harbor Millennium Nero Antracite 45 45 Blanco brillo 25 40 Blanco matte 20 25 Charbon black 33.3 33.3 Power dark gray 45 45 Nord blue Onna black-r 80 80 Pietra Blue naturale 60 60 Siberia blanco 30 60 Soft tobacco-r 60 60 Spazio Fumo 45 45
Origin
Stone
Stones Italy Belgium Brazil Italy Brazil Sweden Brazil Norway Pakistan Brazil Brazil
Basalto Vesuvius Belgische Arduin Café Marron Carrara Bianco Diamond Fall Imperial Red Kinawa Labrador Blue Onyx Multicolor Vert Tropical Yellow Juperana
61
Secondly, the background spectrum was acquired for each measurement location. When the measurement starts, the sample is put in front of the detector. This sample then contributes to background shielding. Since this shielding was absent during background acquisition, the B-NORM method will subtract an overestimated background spectrum, resulting in lower net peak areas. The obtained background spectra usually contain 226Ra and 40 K and only lower levels of 232Th, thus we do not expect the lower regression line slope in 232Th. Overall, the effect from obtaining unshielded background spectra is expected to be only of significant importance on lower ACI materials. These materials will pass the ACI screening test whatsoever, i.e. the ACI is lower than 1. 3.3.2. Activity of 232Th The observed 232Th concentrations varied between approximately 0e600 Bq/kg, according to the laboratory analysis. A good correlation (r2 ¼ 0.97) between laboratory and B-NORM results is observed (Fig. 5). The slope of the regression line is 1.03, indicating that B-NORM method yields accurate results within the studied range. The influence of thoron (220Rn) exhalation on the measurement of 232Th is negligible compared to that of radon (222Rn) exhalation on the measurement of 226Ra because of thoron’s much shorter half-life of only 55.6 s. The thoron diffusion length is about 77 times less than radon diffusion length (de Jong, 2010b), thus the bulk material may be considered large compared to the distance traveled by emanated thoron, and the exhaled thoron is small compared to total thorium. An interesting observation is the stone sample onyx multicolor: with both laboratory and B-NORM analysis, no 232Th was detected (laboratory 232Th MDA: 9 Bq/kg), while having a relatively high 226 Ra concentration of 980 Bq/kg. 3.3.3. Activity of 40K The observed 40K concentrations varied between below MDA (15 Bq/kg) to 920 Bq/kg, according to the laboratory analysis. All ceramic tiles bear a certain concentration of 40K, while three of the studied stones had 40K below MDA. Within the studied range of 17e920 Bq/kg, a good correlation (r2 ¼ 0.97) between laboratory and B-NORM method was observed (Fig. 6). The slope of the regression line is 0.78, indicating that the B-NORM method (the standard uncertainty in the given concentration range is approximately 15%, depending on geometry, background radiation and acquisition time) yields significantly lower results than the standard method. The B-NORM method may yield negative results when the 40K concentration is below or at the laboratory MDA, indicating that there must be overcompensation for background. Two reasons can be given for this over-compensation. Firstly, the LaBr3(Ce) inevitably contains some natural 138La, which can not be removed from the scintillation material (Milbrath et al., 2007). The 138 La yields 0.068 cps/cm3 (For the 1.500 crystal it is 2.95 cps) in the 1436 keV peak, summed with Ba X-rays (Gilmore, 2011). This makes it indistinguishable from the 1461 keV 40K peak. The ratio (net peak area/gross peak area) can be as low as 1/100, making the calculation easily prone to bias. Since the count rate from the internal 138La is constant, the statistical uncertainty on the peak area contribution from 138La is low (Milbrath et al., 2007). This is illustrated by the good correlation between the B-NORM method and laboratory method. Secondly, background overcompensation may occur, caused by the same reason as background over-compensation of 226Ra. I.e. the sample enhances the background shielding only during measurement and not during background acquisition. The B-NORM method will thus subtract an overestimated background spectrum, resulting in lower net peak areas. No relation between measurement site and background overcompensation could be established however.
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Fig. 4. B-NORM method (Y) vs. Standard method (): correlation of
Fig. 5. B-NORM method (Y) vs. Standard method (): correlation of concentrations. Error bars indicate 1 s.
226
Ra activity concentrations. Left: range 3e980 Bq/g; Right: range 3e189 Bq/g. Error bars indicate 1 s.
232
Th activity
Fig. 7. B-NORM method (Y) vs. Standard method (): correlation of ACI. Error bars indicate 1 s.
3.3.4. ACI The material data discussed above are used to calculate the ACI (Euratom, 2013), the ACI determined via the B-NORM method is compared to the ACI determined via the standard laboratory method. The ACI varies between < 0.1 and 3.91, according to the laboratory analysis. A good correlation (r2 ¼ 0.98) between laboratory and B-NORM results is observed (Fig. 7). The slope of the regression line is 0.95, which indicates that the B-NORM can accurately determine the building material ACI within the studied ACI range. Even though the regression line slopes for the 226Ra and 40K
component from the ACI are significantly less than 1, the ACI regression line shows a slope close to 1. This is because the 226Ra and 40K activity concentrations are divided by 300 and 3000 respectively, while the 232Th activity concentration is divided by 200. The B-NORM method may produce a relatively large relative standard deviation for low ACI building materials. This is not considered as a B-NORM method limitation, since the B-NORM method is intended to determine ACI as a screening tool and low ACI building materials will pass the screening whatsoever. 3.4. ACI determination of several building materials on the Belgian market More than 120 different materials on the Belgian market have been analyzed. These materials include tiles, stone, bricks, cement, concrete, gypsum and thermal insulation bricks. Table 4 presents an overview of the material categories analyzed with the B-NORM method. In the categories “tiles” and “stone”, several materials with Table 4 Activity concentration index (I) in building materials: number of samples (n); lowest measured index (Imin); average index (Iavg) and highest measured index (Imax).
Fig. 6. B-NORM method (Y) vs. Standard method (): correlation of centrations. Error bars indicate 1 s.
40
K activity con-
Building material
n
Imin
Iavg
Imax
Tiles Dimension stones Bricks Cement Concrete Gypsum Total
57 30 12 10 11 6 126
0.44 <0.1 0.37 0.21 0.11 <0,1
0.81 1.17 0.57 0.44 0.26 0.59 0.64
1.35 3.65 0,74 0.74 0.52 0.88
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ACI>1 have been encountered. The calculation of the dose model indicates that these materials are not liable of exceeding the reference level of 1 mSv/year. Tiles and stone are discussed separately under 3.4.1. 3.4.1. Tiles and dimension stones Several tiles and stones with an activity concentration index of >1 were observed. But, due to the superficial use of such materials,
the dose model shows that the reference level of 1 mSv/year would not be exceeded. The highest observed ACI during the B-NORM project was 3.65. All analyzed tiles do contain significant amounts 40K; while some dimension stones only have very low amounts of 40K. Nearzero ACI stones exist, but generally speaking, tiles have a lower ACI than dimension stone. The natural radioactivity in building materials reflects the origin of the base material, and a link between origin of tiles and ACI can be found. Dimension stones originate from many different mines spread out all over the world and each mine has its own radiological characteristics. The kind of stone (marble, granite, basalt,.) and the geological layer of origin are important and radionuclide concentration variations within the same mine may occur. Igneous stone generally contains higher ACI due to, during partial melting and fractional crystallization, uranium and thorium may be concentrated in the liquid phase and become incorporated into the more silica-rich products (Ebaid and Bakr, 2012). 3.4.2. Bulk materials All materials from Table 4, (except tiles and dimension stones) are regarded as bulk materials and are allowed to have an ACI up to 1. None of the studied materials exceeded this limit. A limited variety of the most common gypsum products available on the Belgian market is studied. These common products, accounting for the vast majority of commonly used gypsum based materials, have a relatively low ACI. It can be concluded from the low ACI that it is unlikely that significant amounts of phosphogypsum from maritime origin are used in the studied materials. No cement or concrete exceeded the ACI limit, even those materials that contained blast furnace slag. The application of blast furnace slag in concrete, in order to reduce the amount of Portland clinker needed, is an interesting pathway to reduce CO2 exhaust during cement production (Poffijn et al., 2011). Façade bricks and thermal insulating bricks have lower ACI than tiles, while both being made from clay. An explanation for this is that zircon is not used in bricks and bricks are made from different types of clay from different regions. 4. Conclusion The B-NORM method was validated against HPGe gamma spectrometry. Results indicate that the B-NORM method provides useful information on the NORM nuclide concentration and ACI of
63
the studied building materials. The B-NORM method can be applied to analyze the building materials on-site, as long as the background radiation is reasonable low and stable. It is an interesting tool to apply additionally to the standard method, e.g as a first filter. The BNORM method was applied to characterize over 120 building materials on the Belgian market. None of the characterized materials is liable to exceed the reference level of 1 mSv/year excess external dose.
Acknowledgements The B-NORM project (332 kEuro) is funded by EFRD (European Fund for Regional Development; 40%); HERMES (Flemish agency for entrepreneurship; 45%) and Hasselt University; 15%). The authors would like to express their gratitude towards the funders.
References Al-Jarallah, M.I., Fazal ur, R., Musazay, M.S., Aksoy, A., 2005. Correlation between radon exhalation and radium content in granite samples used as construction material in Saudi Arabia. Radiat. Meas. 40, 625e629. Bronson, F., 2008. To sample or not to sample e an investigation into the uncertainty from sampling followed by laboratory analysis versus in-toto gamma spectroscopy for situations of non-uniform radioactivity distribution. In: WM2008 Conference, Phoenix, AZ USA. Canberra, 2009. Genie 2000 3.2. CUstomization Tools Manual, V 3.2. Canberra Industries Incorporated, pp. 354e375. Currie, L.A., 1968. Limits for qualitative detection and quantitative determination. Application to radiochemistry. Anal. Chem. 40. de Jong, P., 2010a. Exposure to Natural Radioactivity in the Netherlands: The Impact of Building Materials. Rijksuniversiteit Groningen, Groningen (NL), pp. 11e15. de Jong, P., 2010b. Exposure to Natural Radioactivity in the Netherlands: The Impact of Building Materials. Rijksuniversiteit Groningen, Groningen (NL), p. 37. Ebaid, Y.Y., Bakr, W.F., 2012. Investigating the effect of using granite and marble as a building material on the radiation exposure of humans. Radiat. Prot. Dosim. 151, 556e563. EC, 1999. Radiological protection principles concerning the natural radioactivity of building materials (RP 112). In: Directorate-General Environment, N.S.a.C.P (Ed.). Euratom, 2013. Proposal for a Council Directive Laying Down Basic Safety Standards for Protection against the Dangers Arising from Exposure to Ionising Radiation. Brussels, 24 April 2013, Brussels. Gilmore, G., 2011. Scintillation spectroscometry. In: Gilmore, G. (Ed.), Practical Gamma-ray Spectrometry, second ed. John Wiley & sons, United Kingdom, pp. 205e220. Haquin, G., 2008. Natural radioactivity and radon in building materials. In: 12th International Congress on the International Radiation Protection Association, Argentina. Milbrath, B.D., Choate, B.J., Fast, J.E., Hensley, W.K., Kouzes, R.T., Schweppe, J.E., 2007. Comparison of LaBr3:Ce and NAI(Tl) scintillators for radio-isotope identification devices. Nucl. Instrum. Methods Phys. Res. Sect. A 572, 774e784. NEN, 2001. NEN 5697:2001 Radioactivity Measurements e Determination of the Natural Radioactivity in Stony Building Materials by Means of Semiconductor Gamma-ray Spectrometry, p. 29. Poffijn, A., Vanmarcke, H., Wiegers, R., 2011. The revision of the BSS and its implications for the building industry and EU society. In: 4th EAN NORM Round Table Workshop, Hasselt. Steger, F., Kunsch, B., Buchner, I., 1992. Önorm S 5200: radioactivity in building materials (A standard in Austria to Limit Natural Radioactivity in Building Materials). Radiat. Prot. Dosim. 45, 721e722.
Contents lists available at ScienceDirect
Journal of Environmental Radioactivity journal homepage: www.elsevier.com/locate/jenvrad
The use of portable equipment for the activity concentration index determination of building materials: method validation and survey of building materials on the Belgian market M. Stals a, b, *, S. Verhoeven a, M. Bruggeman c, V. Pellens a, b, W. Schroeyers a, b, S. Schreurs a, b a b c
NuTeC (Nuclear Technological Centre), Wetenschapspark 27, 3590 Diepenbeek, Belgium Hasselt University, Agoralaan Gebouw D, 3590 Diepenbeek, Belgium Nuclear Research Centre SCKCEN, Laboratory of gamma spectrometry, Boeretang 200, 2400 Mol, Belgium
a r t i c l e i n f o
a b s t r a c t
Article history: Received 21 May 2013 Received in revised form 23 September 2013 Accepted 26 September 2013 Available online 22 October 2013
The Euratom BSS requires that in the near future (2015) the building materials for application in dwellings or buildings such as offices or workshops are screened for NORM nuclides. The screening tool is the activity concentration index (ACI). Therefore it is expected that a large number of building materials will be screened for NORM and thus require ACI determination. Nowadays, the proposed standard for determination of building material ACI is a laboratory analyses technique with high purity germanium spectrometry and 21 days equilibrium delay. In this paper, the B-NORM method for determination of building material ACI is assessed as a faster method that can be performed on-site, alternative to the aforementioned standard method. The B-NORM method utilizes a LaBr3(Ce) scintillation probe to obtain the spectral data. Commercially available software was applied to comprehensively take into account the factors determining the counting efficiency. The ACI was determined by interpreting the gamma spectrum from 226Ra and its progeny; 232Th progeny and 40K. In order to assess the accuracy of the B-NORM method, a large selection of samples was analyzed by a certified laboratory and the results were compared with the B-NORM results. The results obtained with the B-NORM method were in good correlation with the results obtained by the certified laboratory, indicating that the B-NORM method is an appropriate screening method to assess building material ACI. The B-NORM method was applied to analyze more than 120 building materials on the Belgian market. No building materials that exceed the proposed reference level of 1 mSv/year were encountered. Ó 2013 Elsevier Ltd. All rights reserved.
Keywords: Building materials NORM Euratom Basic Safety Standards Activity concentration Measurement
1. Introduction On average, one stays for 80% of the time indoors. Therefore, it is relevant to assess the radiation dose a person receives from the building materials. Most building materials contain certain amounts of the naturally occurring radionuclides 226Ra, 232Th and 40 K. Building materials of natural origin reflect the geology of their origin (Haquin, 2008). Besides this, the trend to re-use industrial by products in building material may enhance the building material activity concentration. Therefore, it is relevant to study NORM in building materials. Moreover, NORM in building materials will be legally regulated in the near future (Euratom, 2013). The Basic Safety Standards (BSS) is a European Directive concerning (among others) the protection of the public and the
* Corresponding author. NuTeC (Nuclear Technological Centre), Wetenschapspark 27, 3590 Diepenbeek, Belgium. Tel.: þ3211 370 794. E-mail address: [email protected] (M. Stals). 0265-931X/$ e see front matter Ó 2013 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.jenvrad.2013.09.012
workers against the dangers of ionizing radiation. It is expected that the EU member states will ratify the Directive by 2015. The new Euratom BSS, explicitly mentions natural radioactivity in building materials: “The competent authority shall make arrangements for the classification of identified types of building materials, as laid down in Annex 11,1 on the basis of their intended use and activity concentration index I.” The article also states that the radiological information shall be published before marketing the material. In order to determine the building material activity concentration index I, one has to determine the activity concentrations of the radionuclides 226Ra; 232Th and 40K. Different formulas exist for the calculation of the activity concentration index; e.g. (Steger et al.,
1
The Annex number is likely to change in final version of the text.
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57
1992) but the most widespread formula is the one used in the Euratom BSS:
I ¼
C
226 Ra
300
þ
C
232 Th
200
þ
C 40 K 3000
(1)
With: C ¼ activity concentration of the respective nuclide in secular equilibrium [Bq/kg] The activity concentration index (ACI) of a building material, whether bulk or superficial material shall not be higher than 1. If the index is higher than 1, a dose model should be calculated in order to determine the annual excess external dose. The activity concentration index is related to the excess gamma radiation dose resulting from the use of the respective materials. It is applicable for the material as a whole and not for its constituents. The extra gamma radiation dose due to the use of building materials may not exceed the reference level of 1 mSv/a. The constants in the formula are derived for a described room and a material with a certain density (EC, 1999). If the actual room or material circumstances differ from the circumstances on which Equation (1) is based, it may not be completely accurate. This causes, among relevant parties, some discussion concerning the applicability of one formula for all different building materials.2 If the allowed reference level of 1 mSv/year is exceeded, the competent authority shall decide on appropriate measures ranging from registration, dosimetric study, general application of relevant building codes, to specific restrictions on the envisaged use of such materials. The requirement to determine the activity concentration index implies that in the near future, numerous gamma spectrometric analyses have to be performed on building materials. With the B-NORM project, NuTeC strives for the development of an easy to operate; on-site measurement method (Bronson, 2008), that facilitates companies with gamma spectrometric measuring tools. This method is intended to be a valuable in situ screening tool that can be used additionally with “conventional” high resolution gamma spectrometry in a laboratory. 2. Materials and method 2.1. Materials: building materials The current paper is focused on building materials that are available on the Belgian market. The most common types of building materials that are applied in the construction of dwellings are studied. The results are discussed per type of building materials: tiles and stones; bricks, concrete, cement and gypsum. 2.2. B-NORM method In the B-NORM method, a Canberra Inspector 1000 (In1k) equipped with an intelligent stabilized 1.500 LaBr3(Ce) probe is used to obtain the spectral data. The LaBr3(Ce) probe is operated at ambient temperature and has improved properties compared to NaI(Tl) probes: it has a 2.9% resolution at 662 keV (7% for NaI(Tl)); 160% relative light output and a fast decay time of 16 ns. The In1k can be set-up in any room with a reasonable low and stable background. High background radiation is detrimental, especially when measuring low activity materials. Measuring in 100 nSv/h or higher background level should be avoided.
2
EAN-NORM round table workshop; “Transportation of NORM, NORM Measurements and Strategies, Building Materials" Nov. 29th e Dec. 1st 2011, Hasselt (Belgium).
Fig. 1. B-NORM method: setup for counting a sample.
In practice, e.g. when measuring in a supplier’s warehouse, one should make arrangements with the owner so that no materials are removed or positioned near the measuring location; because these actions will alter the background radiation during the acquisition. In a first stage, the background spectrum is acquired. This step is required for each different measurement location. Then, the sample is positioned in front of the probe and the spectrum is acquired. The spectrum acquisition itself is a “one-touch and let alone” operation that can be performed by untrained personnel. The sample geometry consists of well-positioned whole building materials, e.g. a stack of tiles, a stack of packs of tiles, a pallet of bricks or a stack of concrete testing cubes from the firm’s own material testing lab. An example of an actual measurement setup is shown in Fig. 1. We carefully determine the geometry dimensions, mass, shape, material composition and detector configuration and position. This information is loaded into Canberra In Situ Object Counting Software (ISOCS) to determine the counting efficiency of the measurement setup. The influence of the sample size and geometry is discussed under 3.1. Spectrum analysis is performed with Genie2000. The analysis includes (besides peak localization and net peak area calculation) a peaked background correction, efficiency correction, selection of applicable peaks from the nuclides of interest and an interference correction. When the activity concentrations of the nuclides are determined, the ACI (Activity concentration index) is calculated. The nuclide 226Ra can be assessed with the B-NORM method in two ways. First option is to directly determine 226Ra by measuring its 186.2 keV line and correcting 57.1% for natural 235U (185.9 keV). This correction is only correct if the assumption that the natural equilibrium has not been disturbed is true. The second option is to determine the 214Pb and 214Bi progeny of 226Ra. This option will be accurate only if the secular equilibrium is not disturbed. In fact, it can not be absolutely assured that any of these assumptions will lead to the actual, accurate determination of the activity of 226Ra. Since building materials are usually dense materials and the material thickness is large because we are not milling the materials, we assume the secular equilibrium condition to be met and therefore we calculate the 226Ra concentration via 226Ra progeny. 2.3. Method validation The current accepted “standard” method for gamma spectrometric analysis of solid substances is to analyze the sample in a laboratory with a lead-shielded high purity germanium detector. The geometry is a precisely defined, usually relatively small sample
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Fig. 2 shows that with a sample mass of over approximately 50 kg, the efficiency gain per unit of mass added to the sample strongly decreases. The efficiency gain per extra sample mass becomes little in larger samples, this has two main causes: (1) the “extra” material is positioned further away from the detector. Therefore, gammas have to travel a longer distance to reach the detector and the detector covers a smaller solid angle, lowering their detection efficiency, and (2) in a larger sample, gammas have to travel a longer distance through dense material, therefore the radiation will be attenuated thus reducing their detection efficiency. Taking practical work into account, a sample size of 25e 50 kg is a suitable balance between sample weight and detection efficiency.
Fig. 2. Detection efficiency versus sample mass (concrete cube; 2.14 kg/dm3). Error bars show uncertainty of efficiency*mass (1 s).
beaker. The material to be analyzed is carefully milled and introduced into the sample beaker. Before analyzing the sample, the sample holder is usually tightly closed for 21 days in order to obtain secular equilibrium. The standard procedure is described in (NEN, 2001). In order to assess the results of the B-NORM method, 26 samples (14 tiles, 11 stones and 1 gypsum) were analyzed with the standard method (NEN, 2001) in an accredited laboratory.3 Tiles and stones were chosen because they offered a wide range of ACI. The sample milling for the laboratory analysis was performed by an accredited construction material testing laboratory. For 226Ra and ACI, the results from the certified laboratory were compared with the BNORM radium determination via 226Ra progeny. 3. Results and discussion
3.1.2. Relation between sample geometry and detection efficiency The B-NORM method is flexible concerning the geometry shape. Virtually any sample shape can be modeled and counted. In practice, one will usually position the building materials in a rectangular plane or cubical geometry. To gain information on how to position the sample in such a way that good detection efficiency is obtained, we studied two cases. Case 1 was to stack the sample like a cube. This results in shorter average distance to the detector, but gammas need to travel via a long path through dense material. Case 2 was to stack the sample like a flat rectangular plane. This results in longer average distance to the detector, but gammas do not need to travel via a long path through dense material. From common insights in detection efficiency, one will not chose to position the materials in an extremely flat or extremely thick configuration. The “flat plane geometry” proposed in the next paragraph has a thickness of 10 cm, which should be considered as a minimum recommended thickness. The two cases were calculated for concrete blocks with a density of 2.14 kg/dm3 and for aerated concrete blocks with low densities of 1.00 kg/dm3 and 0.60 kg/dm3; for gamma energies of 200, 800 and 1500 keV. The calculation was done for sample mass between sizes between 1 dm3 and 125 dm3. In this example, the flat plane has a thickness of 10 cm; while length equals width and varies according to sample volume, see Table 1. Equation (2) was calculated and the results are shown in Fig. 3
efficiency$massðplaneÞ efficiency$massðcubeÞ
3.1. Influence of sample size and geometry on the detection efficiency
relative efficiency ¼
With the B-NORM method, the efficiency curve is calculated by software. This allows for a wide variety of possible geometry sizes and shapes. However, not any size or shape may be suitable. It is interesting to determine a relation between sample mass (“size”); sample shape and detection efficiency: this will provide the necessary information to use a relevant sample size and shape.
Fig. 3 (a) shows that for the dense concrete, a flat plane geometry results in higher counting efficiency than a cubic geometry. The largest observed difference was approximately 22% for the 17.12 kg sample. The difference between the cube and flat plane diminishes in a larger geometry: the outer regions of our flat plane of only 10 cm thickness are located at a large distance from the detector. The flat plane thickness can be increased when counting large sample volumes to keep the outer edges of the geometry closer to the detector and thus increasing the detection efficiency. The energy of the gammas is only slightly relevant, especially at lower sample mass. It can be concluded that a relatively flat geometry yields a better efficiency then cube geometry, when the sample density is relatively high and especially when the sample volume isn’t too large. Fig. 3 (b) and 3 (c) show that for the aerated concrete with a relatively low density, the flat plane geometry is again a more efficient option. The difference compared to the cube geometry is approximately 20% for a 4.8 kg sample (density 0.6 kg/dm3). However the difference diminishes quickly with increasing sample volume. A cube geometry is more efficient than a (relatively flat) rectangular plane geometry when a large volume (larger than approximately 50 dm3) of low density material is counted.
3.1.1. Relation between sample size and detection efficiency A larger sample will result in enhanced detection efficiency, but it is expected that beyond a certain sample mass, only limited efficiency gain can be obtained by measuring an even larger sample. To establish the relation between sample mass and efficiency, we used the software to model a concrete cube, with the detector facecentered on the cube. We calculated the detection efficiency for various sample sizes between 1 dm3 and 125 dm3; this equals 2.14 kg and 267.5 kg respectively, when a material density of 2.14 kg/dm3 is assumed. The calculation was performed for photon energies of 200, 800 and 1500 keV.
3 Nuclear Research Centre SCKCEN e Laboratory of gamma spectrometry; Boeretang 200; 2400 Mol (Belgium).
(2)
M. Stals et al. / Journal of Environmental Radioactivity 127 (2014) 56e63
59
Table 1 Geometry parameters used for calculating the relation between geometry shape and detection efficiency. Geometry dimension cube (cm) 10 15 20 25 35 50
10 15 20 25 35 50
10 15 20 25 35 50
Geometry dimension plane (cm)
Mass of cube and plane (kg) density ¼ 2.14 kg/dm3
Mass of cube and plane (kg) density ¼ 1.00 kg/dm3
Mass of cube and plane (kg) density ¼ 0.60 kg/dm3
10 10 10 18.37 18.37 10 28.28 28.28 10 39.53 39.53 10 65.48 65.48 10 111.80 111.80 10
2.14 7.22 17.12 33.44 91.75 267.5
1.000 3.375 8.000 15.625 42.875 125.000
0.600 2.025 4.800 9.375 25.725 75.000
With the lower density materials, the influence of the gamma energy becomes more pronounced, the lower energy photons slightly favor the flat plane geometry. One can conclude that it is in most cases more efficient to build a rectangular plane geometry. If sample volumes are large (more than approximately 50 dm3) and material density is low (lower than approximately 1 kg/dm3), one should consider to build a cube geometry. Efficiency gains of up to 20% can be obtained by selecting a proper geometry.
concentration in Equation (1). This results in a theoretical minimum detectable ACI of less than 0.3, which is well below the ACI limit of 1 for bulk materials or surface materials. If the measurement result would be below MDA, no problem occurs since MDA is well below the ACI limits. A high background radiation is undesirable regarding the method MDA. Measurement in high background circumstance should be avoided.
3.2. B-NORM method detection limits
The B-NORM method is proposed as a screening tool for on-site building material ACI determination. To validate this, 26 building materials (14 tiles, 11 stones and 1 gypsum) that were analyzed with the B-NORM method are also analyzed with the reference analyses method in a certified laboratory. The materials were chosen to obtain a wide variety in ACI and activities of 226Ra, 232Th and 40K. The activities of 226Ra, 232Th and 40K and the ACI determined via the standard method are compared with the results obtained via the B-NORM method. Table 3 lists the samples that are studied in the intercomparison. Where traceable, the manufacturer of the mentioned tile is included. For stones, the place of origin is included. Besides these stones and tiles, one gypsum sample (Knauf Goldband) was included as well.
Because of the possibility of the B-NORM method to perform measurements at different locations and on samples with different sizes, weights and compositions, it is not possible to determine a single detection limit that is valid in all cases. Therefore the detection limit was calculated for two different circumstances that resemble the vast majority of possible counting conditions. From the detection limit of each relevant gamma-ray emission line from 40 K, 214Pb, 214Bi and 228Ac, the according minimum detectable activity (MDA) was calculated. To calculate the MDA, the method originally described by (Currie, 1968) was used. The Genie 2000 software was setup to apply the Currie method for MDA calculation. The documentation (Canberra, 2009) describes in detail how the software performs the necessary calculations. From the calculated line MDA’s, the worst line MDA was accepted as nuclide MDA and the corresponding minimum detectable ACI was calculated. Results in a background of 20 nSv/h and 50 nSv/h are reported in Table 2, the probability for errors of the first and second kind are 0.05; k ¼ 1.654. The increase in MDA in 20 nSv/h vs. 50 nSv/h background is small since not only the background interference but also the continuum is a factor in calculating the MDA:
LD ¼ k2 þ 2LC
(3)
qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi Lc ¼ k mC þ mB þ s2C þ s2B
(4)
where LD is the limit of quantification; k is the confidence factor; Lc is the critical limit; mC is the true continuum; mB is the background interference; sC is the variance of the continuum; sB is the variance of the background interference. Since the continuum is relative large compared to the background interference, a slight increase in background only slightly increases the MDA. The nuclide MDA’s allow for the calculation of a theoretical minimum detectable ACI, by accepting the MDA as nuclide
3.3. Method validation
3.3.1. Activity of 226Ra The observed 226Ra concentrations varied between approximately 3e980 Bq/kg, according to the laboratory analysis. The high activity concentration of 980 Bq/kg was found in onyx multicolor. The next lower observed concentration is found in Café Maron; 189 Bq/kg; i.e. approximately 4 times less. Therefore, the onyx multicolor 226Ra concentration dominates the linear regression calculation, as shown in Fig. 4, left. Within the range 3e980 Bq/kg a very good correlation (r2 ¼ 0.99) between laboratory and B-NORM method is observed and the slope of the regression line is 0.95, promising accurate results within the 226Ra range of 3e980 Bq/kg. However, the nature of the un-weighted regression analysis implies that results in the lower concentration range may not be described well by the model, if the high outlier is retained. Therefore, the regression line is re-calculated without the onyx multicolor sample; Fig. 4, right. The correlation coefficient within the range 3e189 Bq/kg is appreciable (r2 ¼ 0.92), but the slope of the regression line is 0.80, indicating that the B-NORM method (the standard uncertainty in the given concentration range is approximately 15%) will yield slightly lower results than the laboratory analysis; for 226Ra concentrations lower than approximately 200 Bq/kg. Two possible causes for the lower B-NORM response are put forward. Firstly, in the B-NORM method, the sample is not encapsulated in radon-tight container for at least 21 days but measured as is and on-site. Thus, although our initial assumption was that radon loss via radon exhalation is minimal, it can be remarked that radon exhalation will reduce the amount of 226Ra progeny contained in the sample. Parameters influencing radon
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Fig. 3. Relation between geometry shape and detection efficiency: (a) Concrete, 2.14 kg/dm3; (b) aerated concrete, 1.00 kg/dm3; (c) aerated concrete, 0.60 kg/dm3. The uncertainty (1 s) of the efficiency calculation is 10% (200 keV); 8% (800 and 1500 keV).
emanation (among others) include grain size, permeability of the grains, and location of the radium atoms within the grains. Porosity, thickness of the material and moisture are prime factors influencing the radon diffusion length. When the diffusion length is longer, a larger portion of emanated radon will also be exhaled (de Jong, 2010a) resulting in a lower measured radium progeny concentration. Although results may vary for different materials,
it was reported that on average 22% of the radium content was exhaled as radon from 25 granite samples (Al-Jarallah et al., 2005). The radon exhalation rate is reported to be well correlated (r2 ¼ 0.90, n ¼ 25) with the total radium content (Al-Jarallah et al., 2005). The results obtained with the B-NORM method are in fair agreement with this observation of detecting 22% less radium in unsealed samples.
M. Stals et al. / Journal of Environmental Radioactivity 127 (2014) 56e63 Table 2 Nuclide MDA and minimum detectable ACI in different measurement circumstances. Nuclide
Line energy (keV)
Line MDA (Bq/kg)
Circumstance a1: 72000 s measurement of a 23.55 kg concrete sample, in a 20 nSv/h background ameasured during 72000 s. 214 Pb 295 7.7 214 Pb 351 5.4 214 Bi 609 4.7 228 Ac 911 9.4 228 Ac 969 16 40 K 1460 43 Circumstance A minimum determinable ACI: 0.13 Circumstance b1: 72000 s measurement of a 7.668 kg low-density brick sample, in a 20 nSv/h background measured during 72000 s. 214 Pb 295 11 214 Pb 351 8.9 214 Bi 609 5.9 228 Ac 911 16 228 Ac 969 26 40 K 1460 65 Circumstance B minimum determinable ACI: 0.19 Circumstance a2: 72,000 s measurement of a 23.55 kg concrete sample, in a 50 nSv/h background measured during 72,000 s. 214 Pb 295 8.4 214 Pb 351 4.7 214 Bi 609 5.1 228 Ac 911 10 228 Ac 969 18 40 K 1460 44 Circumstance A minimum determinable ACI: 0.13 Circumstance b2: 72,000 s measurement of a 7.668 kg low-density brick sample, in a 50 nSv/h background measured during 72,000 s. 214 Pb 295 12 214 Pb 351 8.6 214 Bi 609 6.6 228 Ac 911 17 228 Ac 969 27 40 K 1460 70 Circumstance B minimum determinable ACI: 0.20 a Background level given as indication. It is necessary to obtain the background spectrum and to perform peaked background subtraction.
Table 3 Samples included in inter-comparison. Manufacturer
Type
Tiles Azulev Atlas Concorde Savoia Essenza Pera Societé de caramique de chebadda Tervola (Foshan, China) Unknown Onna Alfalux Grespania Marco Polo Sintesi
Atrio carrara Harbor Millennium Nero Antracite 45 45 Blanco brillo 25 40 Blanco matte 20 25 Charbon black 33.3 33.3 Power dark gray 45 45 Nord blue Onna black-r 80 80 Pietra Blue naturale 60 60 Siberia blanco 30 60 Soft tobacco-r 60 60 Spazio Fumo 45 45
Origin
Stone
Stones Italy Belgium Brazil Italy Brazil Sweden Brazil Norway Pakistan Brazil Brazil
Basalto Vesuvius Belgische Arduin Café Marron Carrara Bianco Diamond Fall Imperial Red Kinawa Labrador Blue Onyx Multicolor Vert Tropical Yellow Juperana
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Secondly, the background spectrum was acquired for each measurement location. When the measurement starts, the sample is put in front of the detector. This sample then contributes to background shielding. Since this shielding was absent during background acquisition, the B-NORM method will subtract an overestimated background spectrum, resulting in lower net peak areas. The obtained background spectra usually contain 226Ra and 40 K and only lower levels of 232Th, thus we do not expect the lower regression line slope in 232Th. Overall, the effect from obtaining unshielded background spectra is expected to be only of significant importance on lower ACI materials. These materials will pass the ACI screening test whatsoever, i.e. the ACI is lower than 1. 3.3.2. Activity of 232Th The observed 232Th concentrations varied between approximately 0e600 Bq/kg, according to the laboratory analysis. A good correlation (r2 ¼ 0.97) between laboratory and B-NORM results is observed (Fig. 5). The slope of the regression line is 1.03, indicating that B-NORM method yields accurate results within the studied range. The influence of thoron (220Rn) exhalation on the measurement of 232Th is negligible compared to that of radon (222Rn) exhalation on the measurement of 226Ra because of thoron’s much shorter half-life of only 55.6 s. The thoron diffusion length is about 77 times less than radon diffusion length (de Jong, 2010b), thus the bulk material may be considered large compared to the distance traveled by emanated thoron, and the exhaled thoron is small compared to total thorium. An interesting observation is the stone sample onyx multicolor: with both laboratory and B-NORM analysis, no 232Th was detected (laboratory 232Th MDA: 9 Bq/kg), while having a relatively high 226 Ra concentration of 980 Bq/kg. 3.3.3. Activity of 40K The observed 40K concentrations varied between below MDA (15 Bq/kg) to 920 Bq/kg, according to the laboratory analysis. All ceramic tiles bear a certain concentration of 40K, while three of the studied stones had 40K below MDA. Within the studied range of 17e920 Bq/kg, a good correlation (r2 ¼ 0.97) between laboratory and B-NORM method was observed (Fig. 6). The slope of the regression line is 0.78, indicating that the B-NORM method (the standard uncertainty in the given concentration range is approximately 15%, depending on geometry, background radiation and acquisition time) yields significantly lower results than the standard method. The B-NORM method may yield negative results when the 40K concentration is below or at the laboratory MDA, indicating that there must be overcompensation for background. Two reasons can be given for this over-compensation. Firstly, the LaBr3(Ce) inevitably contains some natural 138La, which can not be removed from the scintillation material (Milbrath et al., 2007). The 138 La yields 0.068 cps/cm3 (For the 1.500 crystal it is 2.95 cps) in the 1436 keV peak, summed with Ba X-rays (Gilmore, 2011). This makes it indistinguishable from the 1461 keV 40K peak. The ratio (net peak area/gross peak area) can be as low as 1/100, making the calculation easily prone to bias. Since the count rate from the internal 138La is constant, the statistical uncertainty on the peak area contribution from 138La is low (Milbrath et al., 2007). This is illustrated by the good correlation between the B-NORM method and laboratory method. Secondly, background overcompensation may occur, caused by the same reason as background over-compensation of 226Ra. I.e. the sample enhances the background shielding only during measurement and not during background acquisition. The B-NORM method will thus subtract an overestimated background spectrum, resulting in lower net peak areas. No relation between measurement site and background overcompensation could be established however.
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M. Stals et al. / Journal of Environmental Radioactivity 127 (2014) 56e63
Fig. 4. B-NORM method (Y) vs. Standard method (): correlation of
Fig. 5. B-NORM method (Y) vs. Standard method (): correlation of concentrations. Error bars indicate 1 s.
226
Ra activity concentrations. Left: range 3e980 Bq/g; Right: range 3e189 Bq/g. Error bars indicate 1 s.
232
Th activity
Fig. 7. B-NORM method (Y) vs. Standard method (): correlation of ACI. Error bars indicate 1 s.
3.3.4. ACI The material data discussed above are used to calculate the ACI (Euratom, 2013), the ACI determined via the B-NORM method is compared to the ACI determined via the standard laboratory method. The ACI varies between < 0.1 and 3.91, according to the laboratory analysis. A good correlation (r2 ¼ 0.98) between laboratory and B-NORM results is observed (Fig. 7). The slope of the regression line is 0.95, which indicates that the B-NORM can accurately determine the building material ACI within the studied ACI range. Even though the regression line slopes for the 226Ra and 40K
component from the ACI are significantly less than 1, the ACI regression line shows a slope close to 1. This is because the 226Ra and 40K activity concentrations are divided by 300 and 3000 respectively, while the 232Th activity concentration is divided by 200. The B-NORM method may produce a relatively large relative standard deviation for low ACI building materials. This is not considered as a B-NORM method limitation, since the B-NORM method is intended to determine ACI as a screening tool and low ACI building materials will pass the screening whatsoever. 3.4. ACI determination of several building materials on the Belgian market More than 120 different materials on the Belgian market have been analyzed. These materials include tiles, stone, bricks, cement, concrete, gypsum and thermal insulation bricks. Table 4 presents an overview of the material categories analyzed with the B-NORM method. In the categories “tiles” and “stone”, several materials with Table 4 Activity concentration index (I) in building materials: number of samples (n); lowest measured index (Imin); average index (Iavg) and highest measured index (Imax).
Fig. 6. B-NORM method (Y) vs. Standard method (): correlation of centrations. Error bars indicate 1 s.
40
K activity con-
Building material
n
Imin
Iavg
Imax
Tiles Dimension stones Bricks Cement Concrete Gypsum Total
57 30 12 10 11 6 126
0.44 <0.1 0.37 0.21 0.11 <0,1
0.81 1.17 0.57 0.44 0.26 0.59 0.64
1.35 3.65 0,74 0.74 0.52 0.88
M. Stals et al. / Journal of Environmental Radioactivity 127 (2014) 56e63
ACI>1 have been encountered. The calculation of the dose model indicates that these materials are not liable of exceeding the reference level of 1 mSv/year. Tiles and stone are discussed separately under 3.4.1. 3.4.1. Tiles and dimension stones Several tiles and stones with an activity concentration index of >1 were observed. But, due to the superficial use of such materials,
the dose model shows that the reference level of 1 mSv/year would not be exceeded. The highest observed ACI during the B-NORM project was 3.65. All analyzed tiles do contain significant amounts 40K; while some dimension stones only have very low amounts of 40K. Nearzero ACI stones exist, but generally speaking, tiles have a lower ACI than dimension stone. The natural radioactivity in building materials reflects the origin of the base material, and a link between origin of tiles and ACI can be found. Dimension stones originate from many different mines spread out all over the world and each mine has its own radiological characteristics. The kind of stone (marble, granite, basalt,.) and the geological layer of origin are important and radionuclide concentration variations within the same mine may occur. Igneous stone generally contains higher ACI due to, during partial melting and fractional crystallization, uranium and thorium may be concentrated in the liquid phase and become incorporated into the more silica-rich products (Ebaid and Bakr, 2012). 3.4.2. Bulk materials All materials from Table 4, (except tiles and dimension stones) are regarded as bulk materials and are allowed to have an ACI up to 1. None of the studied materials exceeded this limit. A limited variety of the most common gypsum products available on the Belgian market is studied. These common products, accounting for the vast majority of commonly used gypsum based materials, have a relatively low ACI. It can be concluded from the low ACI that it is unlikely that significant amounts of phosphogypsum from maritime origin are used in the studied materials. No cement or concrete exceeded the ACI limit, even those materials that contained blast furnace slag. The application of blast furnace slag in concrete, in order to reduce the amount of Portland clinker needed, is an interesting pathway to reduce CO2 exhaust during cement production (Poffijn et al., 2011). Façade bricks and thermal insulating bricks have lower ACI than tiles, while both being made from clay. An explanation for this is that zircon is not used in bricks and bricks are made from different types of clay from different regions. 4. Conclusion The B-NORM method was validated against HPGe gamma spectrometry. Results indicate that the B-NORM method provides useful information on the NORM nuclide concentration and ACI of
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the studied building materials. The B-NORM method can be applied to analyze the building materials on-site, as long as the background radiation is reasonable low and stable. It is an interesting tool to apply additionally to the standard method, e.g as a first filter. The BNORM method was applied to characterize over 120 building materials on the Belgian market. None of the characterized materials is liable to exceed the reference level of 1 mSv/year excess external dose.
Acknowledgements The B-NORM project (332 kEuro) is funded by EFRD (European Fund for Regional Development; 40%); HERMES (Flemish agency for entrepreneurship; 45%) and Hasselt University; 15%). The authors would like to express their gratitude towards the funders.
References Al-Jarallah, M.I., Fazal ur, R., Musazay, M.S., Aksoy, A., 2005. Correlation between radon exhalation and radium content in granite samples used as construction material in Saudi Arabia. Radiat. Meas. 40, 625e629. Bronson, F., 2008. To sample or not to sample e an investigation into the uncertainty from sampling followed by laboratory analysis versus in-toto gamma spectroscopy for situations of non-uniform radioactivity distribution. In: WM2008 Conference, Phoenix, AZ USA. Canberra, 2009. Genie 2000 3.2. CUstomization Tools Manual, V 3.2. Canberra Industries Incorporated, pp. 354e375. Currie, L.A., 1968. Limits for qualitative detection and quantitative determination. Application to radiochemistry. Anal. Chem. 40. de Jong, P., 2010a. Exposure to Natural Radioactivity in the Netherlands: The Impact of Building Materials. Rijksuniversiteit Groningen, Groningen (NL), pp. 11e15. de Jong, P., 2010b. Exposure to Natural Radioactivity in the Netherlands: The Impact of Building Materials. Rijksuniversiteit Groningen, Groningen (NL), p. 37. Ebaid, Y.Y., Bakr, W.F., 2012. Investigating the effect of using granite and marble as a building material on the radiation exposure of humans. Radiat. Prot. Dosim. 151, 556e563. EC, 1999. Radiological protection principles concerning the natural radioactivity of building materials (RP 112). In: Directorate-General Environment, N.S.a.C.P (Ed.). Euratom, 2013. Proposal for a Council Directive Laying Down Basic Safety Standards for Protection against the Dangers Arising from Exposure to Ionising Radiation. Brussels, 24 April 2013, Brussels. Gilmore, G., 2011. Scintillation spectroscometry. In: Gilmore, G. (Ed.), Practical Gamma-ray Spectrometry, second ed. John Wiley & sons, United Kingdom, pp. 205e220. Haquin, G., 2008. Natural radioactivity and radon in building materials. In: 12th International Congress on the International Radiation Protection Association, Argentina. Milbrath, B.D., Choate, B.J., Fast, J.E., Hensley, W.K., Kouzes, R.T., Schweppe, J.E., 2007. Comparison of LaBr3:Ce and NAI(Tl) scintillators for radio-isotope identification devices. Nucl. Instrum. Methods Phys. Res. Sect. A 572, 774e784. NEN, 2001. NEN 5697:2001 Radioactivity Measurements e Determination of the Natural Radioactivity in Stony Building Materials by Means of Semiconductor Gamma-ray Spectrometry, p. 29. Poffijn, A., Vanmarcke, H., Wiegers, R., 2011. The revision of the BSS and its implications for the building industry and EU society. In: 4th EAN NORM Round Table Workshop, Hasselt. Steger, F., Kunsch, B., Buchner, I., 1992. Önorm S 5200: radioactivity in building materials (A standard in Austria to Limit Natural Radioactivity in Building Materials). Radiat. Prot. Dosim. 45, 721e722.