Multilayer Nuclear Track Detectors for Retrospective Radon Dosimetry

Transcription

1 Multilayer Nuclear Track Detectors for Retrospective Radon Dosimetry V. V. Bastrikov 1, M. V. Zhukovsky 2 1 Experimental Physics Department, Ural State Technical University, Mira St., 19/5, , Ekaterinburg, Russia, bastrikov@bk.ru 2 Institute of Industrial Ecology, UB RAS, Sophy Kovalevskoy St., 20A, , Ekaterinburg, Russia Abstract. Contemporary short-term radon measurements are not necessarily the case for reliable radon related health risk assessments. The need to reconstruct the historical exposures of individuals over past decades has stimulated the development of new approaches for retrospective radon exposure estimations. The multilayer solid-state nuclear track detector has been developed for this purpose and is the subject of this paper. The measuring technique is based on the measurement of the long-lived radon decay product trapped in household glass artefacts and uses a several layers configuration of LR-115 track material. LR-115 track registration efficiency for radiation is zero-order, and the first layer response is fully determined by the glass background activity. Besides, the first layer shifts the energy of emitted alpha particles into the working range of the second layer. The mounting of additional layers enables the estimation of the relative content of uranium and thorium isotopes and its decay products in the glass artefact. The generalized compartment behaviour model of radon decay products in the dwelling has been also developed on the basis of the Jacobi room model. 1. Introduction The problem of natural radiation exposure is widely discussed today. Particular attention is given to the noble radioactive gas radon. Being a ubiquitous internal irradiation factor, radon determines effective dose in most cases. Moreover, annual public exposures can sometimes exceed dose limits for workers. Risk assessments made by the United Nations Scientific Committee on the Effects of Atomic Radiation (UNSCEAR) showed that 10 1% of lung cancers occur due to radon decay products [1]. The most significant limitative factor in modern radon epidemiological researches is the lack of retrospective radon exposure data. Cancer induction in the critical organ related to radon lungs has a prolonged latency period, and the most important determinant of risk is the total radon daughters exposure during the period from 5 to 30 years prior to disease. Contemporary radon levels measured directly in dwellings and work places can give inadequate historical exposure assessments. It is common knowledge that radon concentrations vary greatly within the day and within the season. Furthermore, different usage and ventilation conditions preferred by present and previous inhabitants, age-related and planned modifications of buildings result in different contemporary and past annual average radon levels. Finally, the occupant can change place of residence many a time, and radon measurements in every dwelling can be unrealizable. In recent years, several methods of retrospective radon exposure assessment have been developed. Some dwelling artefacts accumulate long-lived radon progeny in itself and keep a record of the historical radon levels. The surface of glass objects is one of such recorders. Formed during alpha decay of the short-lived and deposited on the glass surfaces, recoil nuclei receive sufficient energy (110 and 10 kev, respectively) to implant itself to a maximum depth of approximately 100 nm beneath the surface. Because of the 22-year half-life, (and derived as well) builds up within the time period over which the radon induced lung cancer expresses itself. Thus, the measurement of polonium surface activity can be used as a retrospective monitor for radon exposure. 1

2 The most informative artefacts are glasses and mirrors of the room furniture, looking-glasses, glass coverings on photographs, etc. Some of these objects are permanent lifelong companions and stay useful if a person changes his residence. This paper presents the retro detector developed on the base of solid-state nuclear track detectors LR-115 and considers two problems: the model development for description of airborne, deposited and implanted radon decay products behaviours in indoor environments; and the measurement of small activities against unknown background which may vary from sample-to-sample (typical polonium surface activities amount to mbq/cm 2 ). It should be mentioned that there were no such investigations in Russian Federation before. 2. Compartment room model The basis of most modern models is Jacobi model developed in 1972 [2]. This model describes processes of radon progeny generation, partitioning between different states, interaction with room aerosols and surface deposition. After the radon gas decay, newly generated high-density metals react immediately with air vapours and trace gases and form ultra small particles with diameters between 0.5 and 5 nm (unattached decay products). At the same time, decay products interact with existing aerosol particles in the atmosphere combining into radioactive aerosols (attached decay products) with wide size distribution among tens and thousands of nanometers. Both states deposit on the room surfaces, the deposition rate for the unattached fraction is nearly two orders higher than that for the attached state. Recoil implantation efficiencies for deposited unattached activity and deposited aerosols are also different, and so we differentiate these states in the model. Another additional state is the surface implanted activity. Alpha decay can lead not only to implantation of deposited activity, but to displacement or removal of the implanted atoms and detachment of the attached and deposited decay products. The model relies on considering the relative amounts of the various nuclides in different states and their interplay. Figure 1 schematically represents the model. Solid arrows correspond to decay driven processes, dotted arrows relate to attachment and deposition processes, dash-and-dot arrow symbolizes that a part of the long-lived activity is removed by cleaning. All processes of implantation of deposited radon progeny and recoil of implanted activity were modelled by means of Monte Carlo method. In order to take into account curved pathways of nuclei and range straggling, ion trajectories were computed with the help of SRIM-2003 software [3]. The target glass was assumed to have the following composition: O 60%, Si 25%, Na 10%, Ca 3%, Mg 1%, Al 1%; density 2. g/cm 3. Obtained values of the constants are as follows: for unattached deposited activity recoil implantation efficiency ( decay) 0.6; recoil implantation efficiency ( decay) 0.6; coefficient of implanted activity recoil 0.27; for attached deposited activity recoil implantation efficiency ( decay) 0.23; recoil implantation efficiency ( decay) 0.23; coefficient of implanted activity recoil Recoil implantation efficiency for attached radon decay products shows negligible dependence on the aerosol size. Figure 2 represents depth distributions of implanted recoil nuclei (implantation profiles) formed after decay of unattached deposited (fig. 2a) and after secondary decay of implanted (fig. 2b). 2

3 Airborne Airborne Deposited Deposited unattached attached unattached attached 222 Rn Implanted 100 nm Glass 210 Bi 210 Bi 210 Bi cleaning 206 Pb 206 Pb 206 Pb FIG. 1. Compartment room model representation. 1 N N x (а) 1 N N x (b) Implantation depth (nm) Implantation depth (nm) FIG. 2. Implantation profiles of recoil nuclei. 3

4 3. Polonium-210 surface activity measurement 210 The surface activity of Po, emitting 5.3 MeV alpha particles, is usually measured by mounting solid- state nuclear track detectors on the glass surface for the period of several months. There is a wide variety of detector configurations that differ in used materials and methods of analysis. One of the main detector requirements is discrimination of alpha background activity of the glass. This activity is formed by natural radionuclides the members of decay chains of uranium and thorium. The energetic-angular distribution of background activity is continuous with maximum energy of 8.8 MeV from 212 Po. The retro detector developed in this work uses the cellulose-nitrate detector material LR-115 produced by Kodak Pathé. Background discrimination technique is based on using multilayer detector configuration. The LR-115 material has a narrow energy window and is sensitive to alpha particles from energies of 1.2 MeV up to.2 MeV. The first layer does not detect polonium activity and its response is fully determined by alpha background. Besides, the first layer shifts the energy of alpha radiation from into the working range of the second layer. The use of additional layers allows more accurate assessment of the background activity and estimation of the relative content of uranium and thorium isotopes and its decay products in glass. 210 Detectors response to Po surface activity and U, Th-series specific activity was determined by Monte Carlo modelling using SRIM-2003 software. The alpha particle detection efficiency of LR-115 detectors was obtained from [] (fig. 3a). Table 1 contains calculated values of track formation rates in four layers of LR-115 for different sources (normalized on the total activity of all alpha nuclides). Figure 3b shows modification of the energy distribution of the particle flux density in front of different layers for the 8.8 MeV monoenergetic alpha particles. 1 N N E (b) Alpha energy (MeV) Layer FIG. 3. LR-115 efficiency versus the alpha energy for incidence angles (from the outer to the inner) 0, 30, 0, 50, 55, 60 [ ] (а); Relative energy distribution of the particle flux density in front of layers (b). Table 1. Detector response for polo nium and background radionuclides. track formation rate (track/cm 2 s) 238 U (1 Bq/g) equilibrium shift between U and Ra (1 Bq/cm 2 ) 232 Th eq (1 Bq/g)

5 As one can see from the Table 1, polonium activity is detected only by second layer. It is possible to make rough estimate of polonium surface activity A Po (Bq/cm 2 ) by using only two layers: where A Po 5.32 = ( N N 1 ) (1) T detector exposure period (s); S detector working surface area (cm 2 ); N i track counts in the layer i. Uncertainty arising from unknown relative content of background nuclides is less then 15%. The relative content of alpha-emitting radionuclides of uranium A U (Bq/g) and thorium A Th (Bq/g) series can be estimated from three layers analysis: A U A Th A Po 10 = ( 0.61 N1 2.3 N 3 ) (2) 10 = ( 0.3 N N 3 ) (3) 1 = ( 1.7 N N N3 ) () The fourth layer gives a possibility to carry out another estimate of the background content and makes the surface activity measurement method self-consistent. Figure shows relative distribution of track counts between the layers measured on the glass sample exposed to high radon concentrations in the course of a year (fig. a) and on the natural uranium- and thorium-containing mineral (fig. b) (а) (b) Layer number Mean Min-Max Layer number Mean Min-Max FIG.. Relative track counts distribution for different sources. 5

6 . Conclusions 1. The generalized compartment behaviour model of radon decay products in the room atmosphere was developed and verified. 2. The detector for retrospective radon decay products dosimetry was developed. The detector measures slight surface activities of the glass implanted and distinguishes natural background activity of the glass artefacts. Design features consist in use of multilayer package of solid-state nuclear track detectors of the same type, what significantly decrease the influence of systematic uncertainty of material. 3. Laboratory calibration works were conducted and they confirmed the results of theoretical modelling. References 1. Sources and effects of ionizing radiation. UNSCEAR UN. New York. (2000). 2. Jacobi, W., Activity and Potential Alpha Energy of Rn-222 and Rn-220 Daughters in Different Air Atmospheres. Health Physics, V. 22, N. 5: (1972). 3. Ziegler, J.F., Biersack, J.P., SRIM The stopping and Range of Ions in Matter. IBM, version (2003).. Marocco, D., Bochicchio, F., Experimental determination of LR-115 detector efficiency for exposure to alpha particles. Radiation Measurements N. 3: (2001). 6