VI. Magyar Radon Fórum

VI. Magyar Radon Fórum

A Konferencia Rendezői Pannon Egyetem Radiokémiai és Radioökológiai Intézet Radioökológiai Tisztaságért Társadalmi Szervezet Magyar Biofizikai Társaság Radioökológiai Szakcsoport

Elnök: Somlai János Titkár: Kovács Tibor

A kiadvány szerkesztőbizottsága: Kovács Tibor, Somlai János, Szabó Csaba

VI. Magyar Radon Fórum

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„IPAR A VESZPRÉMI MÉRNÖKKÉPZÉSÉRT” Alapítvány

ISBN: 978-615-5044-51-9 Kiadja a Pannon Egyetemi Kiadó 8200 Veszprém, Wartha V. u. 1. Pf.: 158 Telefon/fax: 88/624-133 E-mail: [email protected] Honlap: http://kiado.uni-pannon.hu/ Felelős kiadó: Egyházy Tiborné dr. Felelős vezető: a Pannon Egyetem Kiadó vezetője Borítóterv: Mód Rudolf Készült 23 A5 ív terjedelemben, B5 formátumban

TARTALOMJEGYZÉK Programfüzet.................................................................................................................. 8 A radon - vita folytatódik............................................................................................. 11 Gy. Köteles The European Map of Geogenic Radon....................................................................... 19 P. Bossew, V. Gruber, T. Tollefsen, M. De Cort Geogenic Radon Potential Mapping in Hungary ......................................................... 31 K. Zs. Szabó, Á. Horváth, Cs. Szabó Seasonal Variation of Nano Aerosols in Postojna Cave, Slovenia .............................. 37 M. Smerajec, A. Gregorič, I. Kobal, N. Kávási, J. Vaupotič Diurnal Variation of Radon and Air-Ions Concentrations in the Underground Low-Level Laboratory in Belgrade, Serbia ................................. 49 V. Udovičić, A. Dragić, R. Banjanac, P. Kolarž, S. Z. Žunić Radiological Concerns of the Red Mud Field of the Vicinity of Ajka (Hungary)....... 57 T. Kovács, J. Somlai, J. Kovács, P. Bui, Z. Sas, G. Szeiler Radiological Investigation of the Effects of Red Mud Disaster................................... 65 Z. Sas, J. Somlai, V. Jobbágy, T. Kovács, G. Szeiler A radoninhaláció biofizikai hatásainak kvantitatív leírása .......................................... 73 I. Balásházy, Á. Farkas, I. Szőke, B. G. Madas, G. Kudela Radonviszonyok a Markhot Ferenc Kórház új fürdőjében .......................................... 85 E. Deák, K. Nagy, N. Kávási, Y. Kobayashi, T. Kovács, I. Berhés, T. Bender, J. Vaupotič, S. Yoshinaga, H. Yonehara The Influencing Parameters of the Risk of Smoking: Is the Hazard of the Smokers Reducible? .................................................................... 95 P. Herke Radon and Thoron in Wine Cellars in Tokaj-Hegyalja ............................................. 103 E. B. Búzás, I. Csige

Radon Measurements in Hungarian Wine Cellars ..................................................... 111 Z. Sas, I. Asztalos, M. Förhécz, B. Kis, S. Kovács, J. Somlai, G. Szeiler, T. Kovács Jacobi Room Model Parameters for Radon Progeny at Turbulent Airflow ............... 117 N. Stevanovic, M. V. Markovic, D. Nikezic Some Thoughts on Radon Statistics........................................................................... 127 P. Bossew Dózisbecslési módszerek az úrkúti mangánérc-bányában ......................................... 137 T. Vigh, N. Kávási, T. Kovács, J. Vaupotič, V. Jobbágy, T. Ishikawa, H. Yonehara A Preliminary Radon Study in the Pál-völgy Cave (Budapest, Hungary) ................. 149 H. É. Nagy, Cs. Szabó, Á. Horváth, A. Kiss Preliminary Indoor Radon and Thoron Measurements in North-Western Romania .... 159 B.-D. Burghele, B. Papp, Z. Horvath, C. Cosma Radiological Investigation of Hungarian Clays (Used in Brick Factories)................ 163 Z. Sas, J. Somlai, V. Jobbágy, G. Szeiler, T. Kovács Intercomparsion of Radon Thoron Passive Detectors................................................ 171 J. Somlai, T. Ishikawa, Y. Omori, R. Mishra, B. K. Sapra, Y. S. Mayya, S. Tokonami, A. Csordás, T. Kovács

POSZTER SZEKCIÓ ............................................................................................. 187 External Doses from Radon Progeny......................................................................... 189 M. V. Markovic, D. Krstic, D. Nikezic, N. Stevanovic Complex Radon and Thoron Study on Hungarian Adobe Dwellings ........................ 197 Zs. Szabó, Cs. Szabó, Á. Horváth Radiation Hazard of Different Hungarian Building Materials................................... 203 P. Völgyesi, Zs. Szabó, H. É. Nagy, J. Somlai, Cs. Szabó Radon Emanation Fraction Measurements of Soils Developed on Different Source Rocks from Hungary ............................................... 211 D. Zacháry, H. É. Nagy, Zs. Szabó, K. Zs. Szabó, Á. Horváth, Cs. Szabó

Natural Radioactivity in the Török Spring of Gellért Hill ......................................... 219 Á. Freiler, Á. Horváth, A. Erőss Long-Term Integrating Radon/Thoron Measurements in a Dwelling, a Case Study ...... 227 Cs. Németh, T. Ishikawa, Y. Omori, G. Szeiler, T. Kovács The Last 4 Years’ Radon Activity Concentration Tendency in Tapolca Cave .......... 233 J. Somlai, N. Gál, A. Kopek, G. Szeiler, Z. Sas, T. Kovács, N. Kávási Radon Content of Drinking Water in Veszprém and in the Surrounding Settlements .... 241 Z. Sas, T. Pallósi, J. Somlai, G. Szeiler, I. Chirca, T. Kovács Radon Emanation of Slovenian Soil Samples............................................................ 249 R. Kardos, M. Horváth, T. Bujtor, J. Vaupotic, T. Kovács Development a Low Level Radon Measurement System Based on Pulse Shape Discriminating NDI Detector................................................. 255 T. Kovács, B. Máté, A. Csordás, J. Somlai Szerzői jegyzék .......................................................................................................... 261

A VI. Magyar Radon Fórum és A Radon a Környezetben Nemzetközi Workshop

PROGRAMFÜZET Veszprém, 2011. május 16 - 17

2011. május 16. hétfő 13.00

Köszöntő, a konferencia megnyitása – Dr. Rédey Ákos, a Pannon Egyetem Rektora

Szekció elnökök: C. Cosma, Cs. Szabó 13.30

A Radon Vita Folytatódik (The Radon-Debate Continues) – Gy. Köteles

14.00

Current Status of European Geogenic Map – P. Bossew

14.20

Geogenic Radon Potential Mapping in Hungary – K. Szabó, Á. Horváth, Cs. Szabó

14.40

Alternative SSNTD Based Radon Measurements – T. Kovács, T. Ishikawa, Y. Omori, R. Mishra, A. Csordás, J. Somlai

15.00

Kávészünet

Szekció elnökök: P. Bossew, T. Kovács 15.20

On the Measurement of Thoron Activity Concentration With Etched Track Type Detectors; The Temporal Changes of Radon in Soil Gas – I. Csige

15.40

Seasonal Variation of Nano Aerosols in the Postojna Cave – M. Smerajec, A. Gregorič, J. Vaupotič, I. Kobal

16.00

Baita-Stei Radon Prone Area: New Indoor, Water and Soil Measurements – C. Cosma, A. Dinu, R. Cs. Begy, T. Dicu, M. Moldovan, B. Papp, D. Nita, C. Candea, D. Fulea

16.20

Diurnal Variation of Radon in the Underground Low-level Laboratory in Belgrade, Serbia – V. Udovičić, A. Dragić, R. Banjanac, P. Kolarž, Z. S. Žunić

16.40

Radiological Investigation of the Effects of the Red Mud Disaster – T. Kovács, Z. Sas, J. Somlai, G. Szeiler

2011. május 17. kedd 09.20

Köszöntő, a második nap nyitása – Dr. Varga Kálmán, a Radiokémiai és Radioökológiai Intézet Igazgatója

Szekció elnökök: I. Csige, J. Somlai 09.30

A Radoninhaláció Biofizikai Hatásainak Kvantitatív Leírása – I. Balásházy

10.00

Radonviszonyok a Markhot Ferenc Kórház Új Fürdőjében – K. Nagy, E. Deák, Y. Kobayashi, N. Kávási, T. Kovács, I. Berhés, T. Bender, J. Vaupotič, S. Yoshinaga, H. Yonehara

10.20

A Dohányzási Kockázat Befolyásolási Pontjai: Csökkenthető-e a Dohányosok Veszélyeztettsége? – P. Herke

10.40

Kávészünet

11.00

Radon és Toron Tokaj-hegyaljai Borospincékben – E. B. Búzás, I. Csige

11.20

A Radon Szempontjából Kritikus Munkahelyek Vizsgálata az Egykori Mecseki Uránbánya Telephelyein – J. Jónás, A. Várhegyi, J. Somlai, G. Szeiler, T. Kovács, N. Kávási

11.40

Radon Mérések Magyarországi Borospincékben – Z. Sas, I. Asztalos, J. Somlai, M. Förhécz, B. Kis, G. Szeiler, T. Kovács

Szekció elnökök: P. Bossew, D. Nikezic 12.00

Poszter szekció External Doses from Radon Progeny – V. M. Markovic, D. Krstic, D. Nikezic, N. Stevanovic Radon Measurement in Water and Carbonated Water: Comparison Between Charcoal Adsorption and Lucas Cell (Luc 3A) Methods – D. Nita, C. Cosma Measurements of Rn-222 and Ra-226 Content in Thermal- and Carbonated Spring Waters from Harghita and Bihor County, (Romania) – R. Cs. Begy, C. Cosma Radon and Thoron Measurements Connected to Hungarian Adobe Houses – Zs. Szabó, Cs. Szabó, Á. Horváth Radiation Hazard of Different Hungarian Building Materials – P. Völgyes, Zs. Szabó, J. Somlai, Cs. Szabó Radon Emanation Fraction Measurements in Some Soils of Different Source Rocks from Hungary – D. Zachary, H. É. Nagy, Zs. Szabó, K. Zs. Szabó, Á. Horváth, Cs. Szabó Natural Radioactivity in Turkish Spring of Rudas Spa (Természetes radioaktivitás a Rudas fürdő Török-forrásában) – Á. Freiler, Á. Horváth

Long-term Integrating Radon/thoron Measurements in a Dwelling, Case Study – Cs. Németh, T. Ishikawa, Y. Omori, G. Szeiler, T. Kovács The change of radon activity concentration in Tapolca cave in the previous 4 years – N. Gál, J. Somlai, G. Szeiler, Z. Sas, T. Kovács, N. Kávási Radon content of drinking water in Veszprém and in the surrounding settlements – T. Pallósi, J. Somlai, G. Szeiler, Z. Sas, I. Chirca, T. Kovács Radon Emanation in Slovenian Soil Samples – R. Kardos, T. Bujtor, B. Máté, M. Horváth, J. Somlai, T. Kovács Development a low level radon measurement system based on pulse shape discriminating NDI Detector – T. Kovács, B. Máté, A. Csordás, J. Somlai 12.45

Ebéd

Szekció elnökök: Z. Žunić, I. Balásházy 14.00

Jacobi Room Model Parameters for Radon Progeny at Turbulent Airflow – N. Stevanovic, V. M. Markovic, D. Nikezic

14.20

Playing With Statistics of the Radon Topic – P. Bossew

14.40

Radon Levels and Dose Estimation Problems in Underground Manganese Mine in Hungary – T. Vigh, T. Kovács, N. Kávási, J. Vaupotič, V. Jobbágy

15.00

Radon Study in the Pálvölgy Cave (Budapest, Hungary) – H. É. Nagy, Cs. Szabó, Á. Horváth, A. Kiss

15.20

Kávészünet

Szekció elnökök: D. Nikezic, K. Nagy 15.40

Preliminary Indoor Thoron and Radon Measurements in North-Western Romania – B. D. Burghele, B. Papp, Z. Horvath, C. Cosma

16.00

Risk Assessment of Radon in Soil, in Baita-Stei Uranium Area (Romania) – B. Papp, C. Cosma

16.20

Radiological Investigation of Hungarian Clays (Used in Brick Factories) – Z. Sas, J. Somlai, V. Jobbágy, G. Szeiler, T. Kovács

16.40

A konferencia zárása

A radon - vita folytatódik

11

A RADON - VITA FOLYTATÓDIK Köteles György Országos "Frederic Joliot-Curie" Sugárbiológiai és Sugáregészségügyi Kutató Intézet, Budapest Abstract The radon-debate continues. The lecture presented the recent recommendations of the relevant international organizations like WHO and ICRP concerning the change of reference levels of radon concentration in indoor conditions. The decreasing reference values raise the problem whether the LNT relationship for lung cancer is valid below 200 or even 100 Bq per cubic meter indoor radon concentrations. Based on a few radiobiological and epidemiological data concerning the effects of low doses, the following conclusions have been derived: - Studies on the concentrations of natural radionuclides – especially dose of radon family– have to be continued. - Special emphasis should be put on the environmental modifying factors like indoor conditions, e.g. ventillation, levels in water (drinking water, spas, etc). - A sober balance of evaluations is required when the levels and biological effects are related. - At low concentrations the ever increasing experience in the biological effects of low radiation doses has to be considered. - At low doses mostly not the physical but the biological factors determine the effects, like antioxidant capacity, biological protective mechanisms for the repair of harms as well as for the elimination of seriously damaged cells. - Low doses even might stimulate the protective mechanisms. - LNT at low dose range is only an unvalidated model, however, for radiation protection service it has to be maintained until further biological reactions will be known. - The communication of the overestimated risk might lead to increased harm on somatic and mental health as well as in economy.

Bevezetés Örömmel tettem eleget a megtisztelő meghívásnak a már hagyománnyá vált radonkonferenciára. Őszintén örülök, hogy Somlai János tanár úr vezetésével a veszprémi Pannon Egyetem Radiokémiai és Radioökológiai Intézet kutató csoportja magas színvonalon megrendezi ezeket az eseményeket, immár hatodszor, melyek igen nagy jelentőségűek a kutatási eredmények megvitatásában, a továbbképzésben és ezeken keresztül nem utolsó sorban az oktatásban és tudományos ismeretterjesztésben. Ez a sokrétű célkitűzés, feladat azt is tükrözi, hogy a téma nem merülhet ki. A radon-problémának ugyanis több vetülete van, beleértve a képződést, a terjedést, a koncentráció kialakulásokat különböző környezetekben, a biológiai hatásokat, a szakmai és a közvéleményt is egyaránt izgató tüdőrák epidemiológiáját. S ki tudja,

Köteles Gy.

12

milyen új és új vonatkozások merülnek fel a jövőben. Az eddigiek során magam is többször foglalkoztam a radon hatás egynéhány sugárbiológiai vonatkozású kérdéskörével; az előző radon-konferenciákon is, amelyek szerkesztett változata megjelent a Radon Fórum kötetekben ismét Somlai János és Kovács Tibor ambícióját és odaadó munkáját dicsérve (1. táblázat) (1-6). 1. táblázat: Korábbi témafelvetéseim A VI. Radon Fórumon 2011. május 16-án elhangzott előadás szerkesztett változata

Radon a környezetünkben

1993

A radon-expozíció biológiai hatásai Szemelvények a radon biológiai hatásainak újabb irodalmából A radon-expozíció egészségi hatásairól

2004

Megjelenés és helye OMIKK Környezetvédelmi füzetek II. Magyar Radon Fórum

2006

III. Magyar Radon Fórum

3

2007

IV. Magyar Radon Fórum

4

Radon risk in spas?

2007

Centr. Europ. J. Occup. Environ. Medicine

5

Low dose response: Hormesis and adaptive response

2009

V. Magyar Radon Fórum

6

Cím

éve

Ref. 1 2

A radon-vita, nevezetesen az, hogy mekkora belsőtéri (indoor) radon koncentráció jelent elhanyagolható, vagy elfogadható kockázatot a lakosság tüdődaganatos megbetegedéseinek gyakoriságára, azért folytatódik, mert az illetékes nemzetközi szervezetek, az Egészségügyi Világszervezet (World Health Organisation - WHO) és a Nemzetközi Sugárvédelmi Bizottság (International Commission on Radiological Potection - ICRP) újabb ajánlásokat tettek az ajánlott határértékre vonatkozóan (7, 8). Újabb nemzetközi ajánlások Az Egészségügyi Világszervezet első alkalommal 1979-ben hívta fel a figyelmet a lakóterek levegőjében található radon lehetséges egészségi hatásaira. 1988-ban a radont emberre nézve rákkeltőnek minősítették. 1993-ban már nemzetközi összefogásra késztettek a radon-expozíció ellenőrzésére és a vele kapcsolatos egészségügyi kockázat becslésére és közlésére. 2005-ben nemzetközi együttműködést kezdtek az egészségi hatások csökkentése érdekében. Legutóbb pedig 2009-ben adták ki a „WHO Handbook on Indoor Radon - A Public Health Perspective” című kiadványukat (7). Ez a kötet számos, eddig ismert fizikai, méréstechnikai, biológiai, epidemiológiai adatot foglal össze. Többek között megállapítja, hogy a radonexpozíciónak tulajdonítható lakossági tüdőrák előfordulási gyakorisága 3–14% az érintett országban a radon koncentrációtól, valamint a számítási módszerektől


13

függően. Ennek csökkentése érdekében a WHO javasolja, hogy a belső terek levegőjében a referencia szint 100 Bq/m3 legyen. Ugyanakkor elismeri, hogy sok országban ez az érték nehezen, vagy nem tartható be, pl. a geológiai viszonyok miatt, ezért könnyítésként azt javasolja, hogy az érték ne haladja meg a 300 Bq/m3-t. Ez hozzávetőlegesen 10mSv/év sugárterhelést jelent a lakásokban lakókra. Az ICRP 1993 óta foglalkozik a radon-problémával, ugyanis ebben az évben adta ki 65. számú Közleményét a radon-222-vel szembeni védelemről az otthonokban és munkahelyeken (9). 2009-ben ők is megváltoztatták korábbi ajánlásukat (10), s a 2007ben ajánlott 600 Bq/m3 értéket 2009-ben 300 Bq/m3-re csökkentették az otthonokra vonatkozóan (8). Munkahelyekre nézve megmaradt az 1000 Bq/m3 érték. A mintegy másfél évtized során tett eddigi ajánlások értékeit a 2. táblázat tünteti fel. 2. táblázat: Ajánlott cselekvési szintek változása a munkahelyi és lakásokon belüli radon-222 koncentrációra, Bq/m3 Ajánló szervezet ICRP 65 IAEA SS 115 ICRP 103 UK HPA UK HPA ICRP, WHO WHO

Ajánlás éve 1993 1996 2007 2008 2009 2009 2009

Munkahely 500 – 1500 1000 1000

1000

Lakások 200 – 600 200 – 600 600 200 100 300 100

Ref. 9 11 10 12 13 7, 8 7

A viszonylag rövid idő alatt bekövetkezett referenciaszint csökkenés jogossága és indokoltsága számos szakértő ellenállását válthatja ki (14, 15). Néhány felvetett szempont az ellenérveléshez: 3 ● Nagyszámú mérés és felmérés alapján úgy tűnik, hogy 150 Bq/m alatt a tüdőrák előfordulása nem bizonyított. 3 ● Már a 200 Bq/m szinthez számított kockázati érték is a magasabb értékektől való extrapoláció révén adódott. Itt utalok az un. linear-no-threshold (LNT) dózis-hatás összefüggési modell vitájára, amiben a kis dózisok kockázatát a nagy dózisokból származtatják lineáris összefüggés alapján. Ez mai ismereteink szerint már elfogadhatatlan. ● A radon-kockázat megítélésénél figyelembe kell venni, hogy a nem-dohányzók radon-kockázata mintegy 25-ször kisebb, mint a dohányzóké (3. táblázat) (16). ● Az új nemzetközi ajánlásokhoz való igazodás meglehetősen nagy költségeket jelenthet az otthonok és munkahelyek tulajdonosainak, s ez az epidemiológiai adatok alapján nem látszik indokoltnak. Felmérések szerint olyan területeken érdemes mentesítést végezni, ahol a lakóépületek több mint 5%-ánál a radon-koncentráció magasabb, mint az ajánlott referenciaszint (17).

Köteles Gy.

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3. táblázat: Tüdőrák kumulatív kockázata a 75. életévig (tüdőrák haláleset/1000 személy) (16) Bq/m3 0 4,1 101

Nem dohányzók Dohányzók

100 4,7 116

400 6,7 160

800 9,3 216

Az új ajánlások alapja Az új ajánlásoknak, a korábbi ajánlásoknak is alapul szolgáló régi alapjai vannak. A hivatkozott lakossági epidemiológiai vizsgálatok közlése 1997-2006 közötti. A WHO tanulmányban részletes számadatok vannak táblázatban összefoglalva az európai, az észak-amerikai és a kínai nemzetközi összevont tanulmányokból ("pooling studies"). Ennek egy kivonatát mutatja a 4. táblázat. Az európai tanulmányról egy ábrát is közölnek, amely egy korábbinak leegyszerűsített változata (1. ábra). A szerzők akkor a statisztikai elemzés alapján lineáris küszöb-dózis nélküli összefüggést mutattak ki 16% becsült kockázati koefficienssel 100 Bq/m3 hosszantartó átlagos radonkoncentráció belégzése esetén. A szóban forgó WHO tanulmány 3 összesített adathalmazból 8%, 11% és 13% kockázatnövekedést mutatott ki 100 Bq/m3 szintnövekedésnél. A három adatból végül is 10% per 100 Bq/m3 értéket ad meg. 4. táblázat: Tüdőrák kockázati értékek összefoglalása különböző belső téri radonkoncentrációnál (7) Tüdőrákos Kontroll Expozíciós időA tanulmáesetek személyek tartomány nyok száma száma száma években Európai tanulmány Észak-amerikai tanulmány Kínai tanulmány A fenti eredmények súlyozott átlaga

Tüdőrák kockázat százalékos növekedése 100 Bq/m3-es koncentrációnként

13

7 148

14 208

5 – 35

8 (3, 16)

7

3 662

4 966

5 – 30

11 (0, 28)

2

1 050

1 995

5 – 30

13 (1, 36) 10


15

A

B 1. ábra: Tüdőrák relatív kockázati értékei különböző felmérések alapján (4). A B. ábra a szóban forgó WHO tanulmány ábrája (7)

Köteles Gy.

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A különböző belső téri radon koncentrációk relatív kockázatának értékelésénél is óvatosságra int az 5. táblázat áttekintése. 5. táblázat: Radon okozta hörgőrák kockázat különböző szintű koncentráció tartományokban (16) Bq/m3 < 25 25 – 49 50 – 99 100 – 199 200 – 399 400 – 799 > 800

Relatív kockázat 1,00 1,06 1,03 1,20 1,18 1,43 2,02

95% konf. interv. 0,87 – 1,15 0,98 – 1,15 0,96 – 1,10 1,08 – 1,32 0,99 – 1,42 1,06 – 1,92 1,24 – 3,31

Nyilván tiszteletre méltó ez a nagy statisztikai elemző munka. Kérdés azonban, hogy kis dózis-tartományban érvényes-e az LNT modell. Gondoljuk csak meg, hogy az ICRP szerint a maximálisnak mondott 300 Bq/m3 koncentráció belégzése mintegy 10mSv évi terhelést jelent. Ennek megfelelően a 100–150–200 Bq/m3 koncentráció értékek, amiket gyakran jelölnek meg, mint ajánlott referencia-szintet, s aminek szintén tulajdonítanak tüdőrák kockázatot (!), mintegy 3–5–7 mSv-nek felelnek meg. De ez a természetes háttér tartománya! Kérdés tehát, hogy van-e értelme ilyen szinteknél ijesztgetni a lakosságot tüdőrák kockázatokkal s következményesen költséges műszaki intézkedéseket tenni ennek csökkentésére. Ha egyáltalán ez reális lehetőség! Itt mutatkozik meg a precízkedő, egyoldalú „tudományosság” káros társadalmi hatása. Figyelembe véve a szóban forgó WHO tanulmány egyik táblázatát, miszerint az OECD országokban a belsőtéri radon-koncentráció 11–140 Bq/m3 között van, a világátlag pedig 39 Bq/m3, ezek az adatok nem indokolják a vészharang kongatását. Különösen félrevezetőnek és károsnak tűnik az ilyen kis koncentrációknál a kockázati értékek alapján kiszámítani és megadni, hogy hány ember halála várható radon okozta tüdőrák miatt évente, amint azt a tanulmány teszi! Következtetések a kis dózisok biológiai hatásainak vizsgálata alapján Korábban több közleményben (beleértve a Radon Fórumokat) foglalkoztam a kis dózisok biológiai hatásaival (1-6). Legutóbb pl. a hormezissel, azaz a kis dózisok pozitív hatásaival, vagy az alkalmazkodási válasszal (6). Két fő következtetés, hogy ● az LNT modell 100 mSv alatt érvénytelennek látszik, ● kis dózisok nemhogy károsak, hanem a sejtbiológiai folyamatok stimulálása révén –pl.: alkalmazkodási válasz– hasznosak lehetnek.


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Továbbá: ● A természetes radioizotópok – elsősorban a radoncsalád – koncentráció viszonyainak tanulmányozását az emberi környezetben tovább kell folytatni. ● Hangsúlyosan vizsgálni kell a környezeti módosító tényezőket, mint a belsőtéri (indoor) feltételek, koncentráció szintek a vizekben (ivóvizek, gyógyfürdő, stb.) ● Józan egyensúly keresés kívántatik a szintek és a biológiai hatások viszonyának tanulmányozásában és a következtetések levonásában. ● Folyamatosan követni kell a kis dózisú ionizáló sugárzás biológiai hatásaira vonatkozó kutatásokat. ● Kis dózisoknál többnyire nemcsak a fizikai, hanem a biológiai tényezők is meghatározzák a hatásokat, például antioxidatív kapacitás, valamint biológiai védekező mechanizmusok működnek az okozott károk helyreállításában, a súlyosan károsított sejtek kiiktatásában. ● Sőt, a kis dózisok stimulálni képesek a védekező mechanizmusokat, pl. hormesis, alkalmazkodási válasz. ● Bár az LNT modell kis dózisoknál egyre kevésbé igazolt, ezt sugárvédelmi, szervezeti megfontolásokból továbbra is fent kell tartani. ● A kockázat túlértékelése azonban fokozott károkhoz vezethet a testi és lelki egészség, valamint a gazdaság területén. Felhasznált irodalom 1. Gy. Köteles: Radon a környezetünkben. OMIKK Környezetvédelmi füzetek, 1993/3, 28, (1993) 2. Gy. Köteles: A radon biológiai hatásai. II. Magyar Radon Fórum, Veszprémi Egyetem, 4–13, (2004) 3. Gy. Köteles: Szemelvények a radon biológiai hatásainak újabb irodalmából. III. Magyar Radon Fórum Környezetvédelmi Konferencia, Pannon Egyetem, Veszprém, 9–13, (2006) 4. Gy. Köteles: A radon expozíció egészségi hatásairól. IV. Magyar Radon Fórum Környezetvédelmi Konferencia, Pannon Egyetem, Veszprém, 9–17, (2007) 5. G. J. Köteles: Radon risk in spas? Central European Journal of Occupational and Environmental Medicine, 13, 3–16, (2007) 6. G. J. Köteles: Low dose response: Hormesis and adaptive response. V. Magyar Radon Fórum Környezetvédelmi Konferencia, Pannon Egyetem, Veszprém, 9–17, (2009) 7. WHO Handbook on Indoor Radon, A public health perspective. World Health Organisation, Geneva, (2009) 8. ICRP 2009: International Commission on Radiological Protection: Statement on Radon. Oxford, (2009)

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Köteles Gy.

9. ICRP 65: Protection against Radon-222 at Home and at Work. ICRP Publication 65. Ann. ICRP 23(2), Oxford, (1993) 10. ICRP 103: The 2007 Recommendations of the International Commission on Radiological Protection. ICRP 103. ICRP, 37 (2–4), Oxford, (2007) 11. IAEA Safety series No115: International Basic Safety Standards for Protection against Ionizing Radiation and for the Safety of Radiation Sources. International Atomic Energy Agency, Vienna, (1996) 12. UK HPA 2008: Radon protection measures in new homes. United Kingdon Health Protection Agency, (2008) 13. UK HPA 2009: Health effects of radon exposure. United Kingdom Health Protection Agency, (2009) 14. D. Higson: A perspective on risks from radon. Australasian Radiation Protection Society, (2010) 15. D. F. Nelson: Exposure to low levels of radon appears to reduce the risk of lung cancer, new study finds. (2008) 16. S. Darby, D. Hill, A. Auvinen: Radon in homes and risk of lung cancer, collaborative analysis of individual data from 13 European case-control studies. British Medical Journal, 330, 223–227, (2005) 17. R. Denman, S. Parkinson, C. J. Groves-Kirkby, R. G. M. Crockett, P. S. Phillips, R. Tornberg: Cost Effectiveness and Health Benefits of Domestic Radon Remediation Programmes – An Update. (2010)

The European Map of Geogenic Radon

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THE EUROPEAN MAP OF GEOGENIC RADON Bossew Peter1, Gruber Valeria2, Tollefsen Tore2, De Cort Marc2 1

2

Bundesamt für Strahlenschutz, German Federal Office of Radiation Protection, Berlin European Commission, DG Joint Research Centre, Institute for Transuranium Elements, Ispra, Italy

Abstract A European map of geogenic radon is under development which shall display the geographical distribution of geogenic radon potential. This quantity measures the geological influence on indoor radon concentration which can be expected under certain anthropogenic conditions, like house type and living habits. In this article we review the concept of the radon potential, discuss some of the problems which the European mapping project raises and present its status.

Introduction After working on the European Indoor Radon Map (EIRM) for some years (1), the JRC has started to design a European map of geogenic radon potential. While the former one is based on observed indoor concentrations, the geogenic map should display the geographical distribution of the geogenic radon potential (RP) which quantifies “what Earth delivers in terms of radon”. We briefly recall the pathway from Rn generation to exposure. Rn results from decay of uranium which is ubiquitous in the environment, particularly in rock and soil. Once generated it can migrate in the medium and eventually reach the soil surface to exhale into the atmosphere, or the interface to a building, and enter inside. While generation and possibility of transport is determined by natural, namely geogenic factors, the infiltration rate or the actual transport into a building, and as result, the indoor concentration is controlled by the physical properties of the building, the life style of the inhabitants, and to some degree by meteorological conditions. Note that possible transport – controlled by permeability – turns into an actual one only under certain conditions, more precisely, the pressure gradient with depth or the pressure difference across the soil – house interface. The idea is to create a map of the natural part of this pathway, i.e. Rn generation, and transport possibility under average, or regionally typical climatic conditions. Thus the pathway is divided into two parts, one describing the natural (geogenic plus to some degree climatically controlled) part, and the second, the anthropogenic part. The latter sets the physical conditions through building types and life styles (however quantified) which transform the geogenic potential into an indoor concentration, which is radiologically relevant in the end.

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Bossew P., Gruber V., Tollefsen T., De Cort M.

Rationale and legal background The geogenic RP should exclude anthropogenic factors and seasonally and shortly varying meteorological factors. The first denote the influence on indoor radon concentrations due to human activity, such as construction types, building materials, and living habits, and are temporally variable and characteristic for each particular house (these factors may still show regional trends caused by regionally predominant climate and cultural preferences). For instance, two houses built differently on the same geological ground will have different average indoor radon concentrations, as will two identically built houses on the same ground, but with different living habits of the inhabitants. As another case, improving the insulation of a house can influence its indoor radon concentration. Therefore, one is interested in mapping a quantity which is closer to hazard, and which measures “what earth delivers” in terms of radon, irrespective of anthropogenic factors and temporally constant over a geologic timescale. This quantity or spatial variable, is called geogenic RP, and the idea of the European Geogenic Radon Map (2) is to map such a variable. A geogenic Rn map can serve to identify regions where elevated indoor concentrations can be expected for natural reasons and therefore special provisions, such as particular insulation, may have to be taken for new buildings. It can also help to decide – if not enough indoor measurements of existing buildings are available – where screening of buildings should be performed in order to identify the need for remediation. This rationale is closely related to the concept of radon prone areas or zones (RPZ): According to the draft of the new Euratom Basic Safety Standards (3) “A radon prone area is a geographic area or administrative region defined on the basis of surveys indicating that the percentage of dwellings expected to exceed the national reference level is significantly higher than in other parts of the countries.” In article 38, the document says: “Member States should establish a radon action plan. Member States should forward the action plan and information of any identified radon prone areas to the European Commission. The action plan and information on radon prone areas should be updated on a regular basis.” According to the (4), the JRC has the task to collect, present, evaluate and interpret radiological data from Member States, which lays the legal ground for the European Rn maps. Evidently, the methodical discussions about the European map can also promote national endeavours, as will be required once the BSS are European law. Target variable: the Radon potential One key question for the EGRM is how to define appropriately the target variable which quantifies the geogenic RP. Following the ideas presented in the introduction, a quantity which measures the RP could result from the following consideration. From the full transport (migration-reaction) equation of Rn in soil (5, 6, 7) the flux at depth x equals (in 1-dim case): J(x) = D C’(x) – C(x) v(x), where D is effective (i.e. adjusted for porosity, water content and solubility of Rn in water) diffusion constant,


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C is volumetric Rn concentration and v is effective migration velocity. The latter is given (for non-turbulent regime) by the Darcy law, v(x) = - (k/ μ) p’(x), where p’ is pressure gradient, k is permeability and μ is dynamic viscosity. Of course, also the “material constants” D and k can be (and are, in general) depth dependent in layered soils. The full equation can rarely be solved analytically. In situations relevant for Rn assessment, diffusive contributes much less than advective transport driven by pressure gradients. Normalizing to the source term or to the equilibrium Rn concentration C∞ (which depends only on Ra concentration in soil, emanation power and porosity), the flux can therefore be written approximately and up to leading factors, J ~ C∞ k p’. Now, the pressure difference across the soil – building interface is characteristic for the building. Thus, from physics, the most straightforward candidate for the RP appears to be the quantity J/p’ ~ C∞ k, which quantifies the potential (depending on p’) flux across the interface. The pressure difference usually amounts to a few Pa. With some algebra one can show that this is equal (up to a leading factor and higher-order terms in series expansion of the log) to C∞ / ((-log(k)-log(kmax)), or similar quantities which are numerically easier to manage than C∞ k, keeping in mind that practically k ranges between 10-14 and 10-10 = kmax m². Indeed, this definition of the RP has been proposed by Neznal et al. (8) and similarly more recently by Friedmann (2). The “coupling” of houses to the soil system has been demonstrated by numerical studies, e.g., by Riley et al. (1991) for investigating the effect of wind, and by Jiranek and Swoboda (7) who performed sensitivity analyses of the parameters of the combined soil – house system, which control the “transfer” soil – house. How the “coupling” to a building modifies the Rn distribution in soil has been shown by Jiranek (9). In international practice there have been various approaches to defining an RP, depending on the data realm which is quite different between European countries (and even regions of countries; this is called federalism), discussed in the next section. Even if one agrees that the relevant quantity is the one determined above, or a similar one, the big practical questions are: step 1. how to estimate it at a location or over a spatial unit, from available data; step 2. how to aggregate it into units which form the map supports. In many cases – notable exceptions are the Czech Republic and Germany – not enough observations (measurements) are available as a spatial data set {RP(xi)}, which would allow establishing the map (step 2) relatively easily with standard GIS and geostatistical tools. The question, therefore, is how to estimate RP out of controls (geology including soil properties and tectonics, Ra concentration) or proxies, such as indoor Rn, external dose rate and geochemical data (U or Ra concentrations). The logic is shown schematically in Figure 1 To complicate further, controls like geological class or Ra concentration, can serve as RP proxies themselves, and the variables which are together used as input variables for calculating the target variable, – the RP – can be of different nature. They can be ordinal data (numbers or ordered classes) or nominal categories (typically geological classes). Their geometric nature


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can be different, as they are attached to locations or “points” (typically: measurements of soil Rn or dose rate; “point” means that sampling support is small compared to distance between “points”), to lineaments (tectonics), or to areas (geological classes). The question is thus, how to process the input data into a target variable. The concept is visualized in Figure 2.

uo

us

input variables

in

RP

co

nt

1

c o r at e di g o n a ri 2 ca 3 l 4

A D

C∞ , k

5

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C ou nti

nu

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Figure 1: Concept, construction of the RP from controls and proxies

c o r at e d go 2 in a r ic 3 l a 4

co

controls controls

Rn index, I II categorical-ordinal III IV V

categorical, nominal

s

proxy

physically related

Rn potential, continuous l,

a d

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target variable l,

categorical,

control variables

b nominal

c

Figure 2: Concept, target, input and control variables

In most cases one tries to identify a multivariate way for defining a target quantity, namely the RP, out of available data. The rationale is that in general there is more information available than just radon concentrations in indoor or soil air. As said, the problem is how to merge different kinds of data, including possibly incomplete sets and data of varying quality, into one target variable. Experts have suggested using different approaches for the EGRM map, and we will shortly discuss them in the following. Multivariate cross-tabulation The most established way to define and map a RP appears to be classification by assigning scores to intervals of values (e.g. for radon concentration) or categories (for geology). It is therefore also a very good candidate for the EGRM. In a multidimensional table, “rows” in any dimension denote classes, like geological ones (nominal variables), or classes of concentration in soil gas, or soil permeability (ordinal classes). This approach is widely used; e.g. Germany (10), Czech Republic (8), France (11), USA (12). Uncertainty can be included by generating “uncertainty classes”, as demonstrated in the US radon map (EPA 1993) (12). Missing inputs to the table result in higher uncertainty. Since the US approach appears to be the most general of this type, so far, and also includes a classification of uncertainty, and has proven


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robust, it was suggested at the geogenic radon workshop in Prague 2010 that the experts should see if it can be adapted to the European data situation. As an example, the RP map of the Czech Republic is shown in Figure 3, taken from Miksova and Barnet (13). The classes are defined from the cross-tabulation shown in Table 1. An “interstage” category has been introduced to account for more complicated situations of quaternary surface geology.

Figure 3: RP map of the Czech Republic from Miksova and Barnet (13) Table 1: Cross-tabulation for defining Rn risk classes used in the Czech Republic 222

Rn concentration in soil air (kBq/m³)

< 10 10 – 20 20 – 30 30 – 70 70 – 100 > 100

permeability low (<2·10-13 m²) LOW LOW LOW MEDIUM MEDIUM HIGH

medium (2·10-13 … 2·10-12 m²) LOW LOW MEDIUM MEDIUM HIGH HIGH

high (> 2·10-12 m²) LOW MEDIUM MEDIUM HIGH HIGH HIGH

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Deterministic transfer approach The idea, brought forward by H. Friedmann (14) suggests estimating the RP, essentially defined as above, in a “deterministic” way as follows, for those cases when C∞ or k is not available: C∞ = f(z1, z2,..), i.e. “transfer function” from available variables, or by inserting default values, C∞ | g = f( | g, z2, …), where | g denotes the default (e.g. mean) value of variable z1 associated to controlling factor g (such as geological unit). The functions f must be determined from empirical data and physical knowledge. There is a steadily growing number of studies about relationships between Rn-relevant variables, some of which are referenced and discussed in the EGRM report. Friedmann RP Since a large number of indoor concentrations, but little soil Rn, data is available in Austria, Friedmann (2005) proposed to normalize indoor concentration so as to represent a proxy of the geogenic RP, as a “top down” approach, instead of the “bottom up” way, starting with purely geogenic variables. This requires knowing the impact of anthropogenic factors related to house type and living habits, like mean dependence on floor level or air exchange, and mean meteorology, which causes seasonal dependence. Normalizing to defined standard conditions leads to a local estimate of a quantity which is proportional to the geogenic RP, since anthropogenic factors are “factorized out” this way, on the average. The unit of Friedmann’s RP is the same as indoor concentration, i.e. Bq/m³. The Austrian RP map is shown in two versions in Figure 4 (14). The upper map displays the mean RP per administrative unit (municipality), while the lower map shows a refinement employing Bayesian correction and including geological information. The advantage of the method is that it allows estimating the geogenic RP from existing indoor data (on which the Austrian Rn survey was exclusively focussed when it started around 1990) without additional extensive soil Rn surveys. The disadvantage is that as a model-based approach it introduces model uncertainty: (1) uncertainty of the model which is estimated from data; and (2) also a model which performs well on the ensemble may lead to gross mis-estimation locally in individual cases, because naturally a model may badly cope with a situation (a building) which for some reason behaves differently from the ensemble. Evaluating this by comparing with a “bottom up” RP is under way. Another obvious disadvantage is that only locations with houses are covered, and any location in between has to be estimated again through modelling. A similar method has been applied in the UK, where the RP is defined as probability that indoor Rn exceeds 200 Bq/m³ in specifically defined standard houses (15, 16).


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Figure 4: Austrian RP map (15) Exceedance probability Since the risk related to Rn exposure can be thought to be related to the probability that a threshold or reference value is exceeded. (17) Proposed to map the local exceedance probability in ground-floor rooms. Of course this probabilistic variable includes some influence of anthropogenic factors, although part of it is “factorized out” by restricting it to ground-floor rooms. Given high local spatial variability of Rn variables, an exceedance probability is a more reasonable hazard measure than an expectation (e.g. the mean level over a pixel or any other mapping unit) as it includes also information on variability: the same mean, together with different dispersion of a distribution, yields different distribution tail areas, i.e. different exceedance probabilities. A map of classes of probability to exceed 100 Bq/m³ indoor Rn concentrations in ground-floor rooms is shown in Figure 5 (17).


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Figure 5: Map of probabilities that the indoor Rn concentrations in ground-floor rooms exceed 100 Bq/m³ (17) Joint distribution In integrating different numerical (more generally ordinal) variables, no functional dependencies are used, but instead the fact that the input variables, seen as multivariate field, have statistical correlation as intrinsic property, since they represent physically dependent quantities. Therefore the joint distribution could be used as a simple radon index. A first trial is shown in Figure 6. First, we calculated the empirical bivariate joint distribution of soil and indoor Rn. (The bivariate distribution of two random variables U and V is defined FU,V(u,v) := prob[u’

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NE corner of Germany remains blank due to lack of sufficient supporting data. (Further measurements in this region are under discussion.)

700000

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Figure 6: Tentative Rn hazard map of Germany; mapped quantity: estimated bivariate joint distribution of soil and indoor Rn concentrations. axis units: m; North-South is approximately parallel to the vertical; level unit: dimensionless fraction, see text European harmonization Even if a RP target variable is chosen, the question remains how to estimate it from nationally and regionally different input datasets. Diversity consists on two levels: (i) available datasets are different between countries and regions due to different monitoring strategies and designs; and (ii) the same nominal quantities are sometimes defined differently; a reported value results from an observation process (sampling design, sampling, sample processing, measurement, statistical evaluation, as applicable) following a protocol. Different protocols result in different values of the same “ideal” physical quantity. Understanding of this diversity is still incomplete. Continuing with mapping support, in current planning, the geogenic RP map will be created in the 10 km x 10 km grid using the ETRS-LAEA projection (18), similar to

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that used for the EIRM. However, if convincing arguments are being put forward, one may change to a vector-based approach, using geological units as mapping supports, which could still be projected to a grid, if wanted. The participants to an international working group established by the JRC compiled a list of variables which may serve as input variables to define the RP in a grid cell. At this stage of the project the availability of these data (geo-referenced, electronically accessible, data protected, etc.) in the countries is under investigation. Next, an agreement has to be found about a “cooking recipe” which performs steps 1 and 2 addressed above. Geology A particular case is the control variable “geology”. One has to identify mean or “default” values, or better: distributions, of input variables or of the RP itself over geological units, for: 1. estimating “missing” locations, i.e., where no observations are available except geological information; related to this, the default values serve as input in transfer models in case of missing input variable; 2. improving local estimation, if only few observations are available, by Bayesian refinement. The default distribution would enter as likelihood function; 3. spatial modelling, e.g. by external drift kriging, where residuals of observations against spatial means are the objects of analysis, instead of the observations themselves. This allows modelling of geological borders, across which the RP changes discontinuously; 4. assigning RP values or distribution statistics to geological units, if the mapping approach is chosen which uses polygons (representing the geological units) as mapping supports. For this purpose, geological classes should be defined so as to minimize the variability of Rn variables within, which is equivalent to choosing a classification scheme which is able to separate the range of the variable into classes which are as much as possible distinct (e.g. in the ANOVA sense). The problem is that, first, there is no recognized geological classification system with respect to Rn. Such a system will in general not coincide with traditionally defined geological classes based on genesis, stratigraphy (age) and petrography (rock texture) because of its different purpose. Second, classification systems are regionally different, which is a challenge to the requirement that they be consistent across borders. Since, also upper layers, like Quaternary surface, which in some classifications is not considered, and soil adds to Rn control – sometimes more than bed rock – this applies also for these media. As a possible solution, generally available data on a European scale are checked for usability as input variables or layers for the EGRM. For example the One Geology project (19) has collected geological data (age, lithology) from all participating countries and made them available. These data can be used as a basis by the experts to simplify


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and classify geological units regarding radon risk, which can then be used as one input variable (geology) to estimate the geogenic RP in a grid cell. But, of course, these classifications need supporting measurement data and surveys, knowledge and experience, and this will be a continuous point of discussion among the experts. Status and outlook The decision for the geogenic map has been taken at the 33rd International Geological Congress in Oslo, August 2008. An international expert group, coordinated by the JRC, was formed at this occasion. The group has since expanded due to considerable interest in the subject, and is still open for cooperation. The last meeting (apart from continuous informal discussions between the experts) was at the 10th International Workshop on the Geological Aspects of Radon Risk Mapping in September 2010 in Prague. There the group also decided to produce a progress report (2), which is currently (mid-2011) in preparation. It collects a status of knowledge in the relevant scientific fields and should be the basis for future discussions and decisions how to proceed with the EGRM. As a next step, to decide on the final strategy, a meeting is planned at the JRC (Ispra, Italy) for late 2011. Based on what we know so far, we currently design the mentioned “cooking recipe”, which should be the subject of further discussion and in the best case agreement until the next meeting, so that the actual production of the map could start 2012. Certainly technical questions, some of which have been addressed in this article, will remain to be solved for some time to come. The geogenic Rn map is part of the larger project “European Atlas of Natural Radiation”, envisaged by the JRC. The first step is the indoor Rn map, and maps of cosmic radiation and terrestrial gamma radiations are in preparation. Further maps, such as outdoor Rn, geochemistry or Rn in aquifers are in different stages of planning (20). References 1. T. Tollefsen, V. Gruber, P. Bossew, M. De Cort: Status of the European Indoor Radon Map. Radiation Protection Dosimetry, 145(2-3), 110–116, (2011) 2. EGRM report: The European Geogenic Map; working document, under development. Available from the JRC on request 3. EC: Draft Euratom Basic Safety Standards Directive Version, (24 February 2010) 4. Euratom treaty (Chapter III, art. 39) 5. V. C. Rogers, K. K. Nielson: Multiphase radon generation and transport in porous materials. Health Physics, 60(6), 807–815, (1991) 6. C. E. Andersen: Numerical modelling of radon-222 entry into houses: an outline of techniques and results. Science of the Total Environment, 272(1-3), 33–42 (2001)

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7. M. Jiranek, Z. Swoboda: Numerical modelling as a tool for optimisation of subslab depressurisation systems design. Building and Environment, 1994-2003, 42(5), (2007) 8. M. Neznal, M. Neznal, M. Matolin, I. Barnet, J. Miksová: The new method for assessing the radon risk of building sites. Czech Geological Survey Special Papers, 16, Czech Geological Survey, Prague, (2004) 9. M. Jiranek: Application of numerical modelling for the better design of radon preventive and remedial measures. NUKLEONIKA, 55(4), 451−457, (2010) 10. J. Kemski, A. Siehl, R. Stegemann, M. Valdivia-Manchego: Mapping the geogenic radon potential of Germany. Science of the Total Environment, 272, 217–230, (2001) 11. G. Ielsch, M. E. Cushing, Ph. Combes, M. J. Cuney: Mapping of the geogenic radon potential in France to improve radon risk management methodology and first applications to region Bourgogne. Journal of Environmental Radioactivity, 101, 813–820, (2010) 12. EPA: U.S. Environmental Protection Agency: EPA’s map of radon zones. Report, 402-R-93-071, (1993) 13. J. Miksová, I. Barnet: Geological support to the National Radon Programme (Czech Republic). Bulletin of the Czech Geological Survey, 77(1), 13–22, (2002) 14. H. Friedmann J. Gröller: An approach to improve the Austrian Radon Potential Map by Bayesian statistics. Journal of Environmental Radioactivity, 101(10), 804–808, (2010) 15. J. A. Gunby, S. C. Darby, J. C. H. Miles, B. M. R. Green, R. D. Cox: Factors affecting indoor radon concentrations in the United Kingdom. Health Physics, 64(1), 2–12, (1993) 16. J. Miles: Mapping radon-prone areas by lognormal modelling of house radon data. Health Physics, 74(3), 370–378, (1998) 17. J. Kemski, R. Klingel: Natural and anthropogenic influence on the indoor Rn concentration. Proceedings 38, Jahrestagung des FS, Dresden (2006) 18. A. Annoni, C. Luze, E. Guble, J. Ihd: Map Projections for Europe. European Communities, 131, (2001) 19. OneGeology project (last accessed 14 June 2011). 20. M. De Cort, V. Gruber, T. Tollefsen, P. Bossew, A. Janssens: Towards a European Atlas of Natural Radiation: goal, status and future perspectives. Pres. and article, ICRER, International Conference on Radioecology and Environmental Radioactivity, McMaster University, Hamilton, Canada, (2011)

Geogenic Radon Potential Mapping in Hungary

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GEOGENIC RADON POTENTIAL MAPPING IN HUNGARY Szabó Katalin Zsuzsanna1, Horváth Ákos2, Szabó Csaba1 1

Eötvös University, Lithosphere Fluid Research Laboratory, Department of Petrology and Geochemistry, Budapest 2 Eötvös University, Department of Atomic Physics, Budapest Abstract Soil gas radon as a main source of indoor radon can be the base of the radon risk mapping. Geogenic radon potential mapping takes into account the values of the soil gas radon concentration and soil permeability. In this study we measured these parameters at 59 sites of Pest County, Central Region of Hungary and established a geogenic radon potential mapping method. We characterized geological formations from radon point of view and made two maps based on 16 measurements for two towns that represent the geogenic radon potential of two towns in the studied area. During evaluation of the raw data we should consider the temporal variation of soil gas radon concentration. For better understanding of this aspect, we studied the fluctuation of it during a one year period in a high permeable soil, which allows studying the maximal fluctuation of radon concentration in soil. Our results show that it has daily and seasonal variation. Radon potential maps of two Hungarian towns (i.e., Piliscsaba and Pécel) indicate low and medium radon potential areas.

Introduction Several companies and institutions dealt with indoor radon concentration measurements in Hungary and the National Research Institute for Radiobiology and Radiohygiene and the Rad Labor performed nationwide surveys (1, 2) but there are neither nationwide data on soil gas radon concentration nor method to estimate it from other parameters (e.g., geology, soil type, gamma dose rate). Since the soil gas radon (Rnsoil) is the main source of indoor radon, the geogenic radon potential mapping is a possible way of radon risk mapping as it is applied in several countries (3, 4, 5). This method takes into account the soil gas radon concentration and the soil permeability that is the key influencing factor of radon movement of soil (3). The input parameter for radon potential is the annual average of Rnsoil, hence we should consider its temporal variation. Former studies show inconsistent judgment in this topic (6, 7, 8). Our main aims were to characterize the geological formations of the studied area from radon point of view, to establish a geogenic radon potential mapping method based on geological bases, to provide maps that represent the geogenic radon potential and to better understand the temporal variation of radon concentration in soil.

Szabó K. Zs., Horváth Á., Szabó Cs.

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Studied area and measurement sites The studied area is Pest County, Central Region of Hungary. It has diverse geological background such as Mesozoic sedimentary rocks (limestone and dolomite), Tertiary volcanic rocks (andesite and dacite), Tertiary sedimentary rocks (marl, clay and sandstone) and Quaternary sediments (loess, sand, gravel and clay) (Figure 1). During the site selection we take into account the geological background, which determines the Rnsoil, and 10×10 km or 1×1 km grid net, which is the recommended sampling design for Europe (decided at 8th International Radon Workshop in Prague, September 2006) (9), and also the populated areas. Grid net of 10×10 km is used for the whole studied area and 1×1 km grid net for the towns. Generally, 3 measurement sites are at each cell. In the whole area (6400 km2) 59 measurement site was performed till now and 16-16 sites in case of two towns, Piliscsaba (3 km2) and Pécel (6 km2). We performed single measurements at these sites, but at some sites on high permeable soil short-term and long-term measurements have been carried out, too.

Figure 1: 1:100 000 geological map of Central Region of Hungary (10) Mesozoic sedimentary rocks (limestone and dolomite) are indicated with pink and purple, Tertiary volcanic rocks (andesite and dacite) are indicated with green, Tertiary sedimentary rocks (marl, clay and sandstone) are indicated with orange, beige and dark brown and Quaternary sediments (loess, sand, gravel and clay) are indicated with yellow, light brown, light blue and white), the borders of towns (black polygons) and the 10×10 km grid net (black grids).


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Methods Soil gas radon concentration was measured by RAD7 radon monitor coupled with RAD7 soil probe. The measurement depth was generally 80 cm. For mapping we used GRAB protocol, for studying temporal variation of Rnsoil we used SNIFF protocol (RAD7 manual). Permeability of soil was measured by RADON-JOK permeameter at the same depth, immediately after the radon measurement. To study the temporal variation of Rnsoil, we planned a one year measurement period. During this period one week measurement was carried out in every month. Radon potential of the sites was calculated into three categories (low-L, medium-M, high-H) based on multivariate cross-tabulation method (3). Results and discussion Beside the single measurements, we executed short term measurement at some sites and experienced daily periodicity in Rnsoil (Figure 2). Higher values are at night and lower in daytime. Therefore, we planned a long term measurement on a high permeable soil to understand the time dependence of the Rnsoil. Figure 3 shows the temporal variation of Rnsoil in a high permeable soil at 80 cm depth during an 8 months period from August 2010 to March 2011. The values can be divided into two groups, where the group means statistically one distribution M+3Q, where M is the fitted median, Q is the interquartile range. In summer the Rnsoil is about 2 times lower than in winter during the year. The statistical analysis for the original data shows that there are 5615 data points, with a median of 16.7 kBq m-3. For summer period the median is 8 kBq m-3, for winter period is 17.2 kBq m-3. This fluctuation means measured value of single measurements should correct in case of high permeable soil.

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34

number of 15 min integrated periods

Figure 3: Temporal variation of Rnsoil in a high permeable soil at 80 cm depth during an 8 months period from August 2010 to March 2011. Rnsoil is indicated by black dots. The circle shows the “summer group”, the ellipse shows the “winter group” Table 1 shows the result of measurements on different geological formations. Values are not corrected yet according to the temporal variation. Rnsoil varies highly in soils on Quaternary sediments which indicate that this formation is not homogeneous. High permeable soil was found on Tertiary sedimentary rocks and on Quaternary sediments. Mostly low and medium radon potential characterizes the study area and high RP was found in case of Quaternary sediments (fluvial sediment). Table 1: Radon potential (RP) of sites on different geological formations L=low, M=medium, H=high Geological formations Mesozoic sedimentary rocks (limestone and dolomite) Tertiary volcanic rocks (andesite and dacite) Tertiary sedimentary rocks (marl, clay and sandstone) Quaternary sediments (loess, sand, gravel and clay)

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35

The result of a simplified model of radon potential map is demonstrated for two towns, Piliscsaba and Pécel, in Figure 4. Average of the soil radon and permeability values was calculated for grid cells. This method shows low and medium radon potential cells in these towns. Piliscsaba

Pécel

Figure 4: Radon potential map of two Hungarian towns, Piliscsaba and Pécel, showing the 1×1 km grid net Transparent cells indicate low, blue cells medium, red cells high radon potential, respectively, where measurements were carried out, based on multivariate crosstabulation categorization method (3). The overlapping layers are the 1:100 000 geological map of central region of Hungary (10), the polygons of towns, measurement sites and the grid net. Summary Temporal variation of radon concentration in soil gas shows higher values at nights and during winter and lower values in the daytime and summer. These daily and seasonally variation confirms that single measurement should be corrected in case of measurement in high permeable soil. The results of single measurements in the studied area (Pest County) show that Rnsoil varies highly in soils on Quaternary sediments which indicates that this geological formation is not homogeneous. High permeable soil was recognized on Tertiary sedimentary rocks, and Quaternary sediments which have low radon potential. The study area can be charateized by mostly low and medium radon potential values. High radon potential was found only on some Quaternary sediments (e.g., fluvial sediment).

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Acknowledgement We thank the help of local authorities and Győző Jordán, financial support of Lithosphere Fluid Research Laboratory and Doctoral School of Environmental Sciences, Eötvös University and also useful comments of the reviewer. References 1. OKSER 2006: Az Országos Környezeti Sugárvédelmi Ellenőrző Rendszer (OKSER) 2006. évi jelentése. (in Hungarian), 40, (2007) 2. M. Minda, Gy. Tóth, I. Horváth, I. Barnet, K. Hámori, E. Tóth: Indoor radon mapping and its relation to geology in Hungary. Environmental Geology, 57, 601–609, (2009) 3. J. Kemski, A. Siehl, R. Stegemann, M. Valdivia-Manchego: Mapping the geogenic radon potential in Germany. The Science of the Total Environment, 272, 217–230, (2009) 4. I. Barnet, P. Pacheova, W. Preusse, B. Stec: Cross-border radon index map 1:100 000 Lausitz – Jizera – Karkonosze – Region (northern part of the Bohemian Massif). Journal of Environmental Radioactivity, 101, 809–812, (2010) 5. G. Ielsch, M. E. Cushing, Ph. Combes, M. Cuney: Mapping of the geogenic radon potential in France to improve radon risk management: methodology and first application to region Bourgogne. Journal of Environmental Radioactivity, 101, 813–820, (2010) 6. M., Neznal, M. Matolin, G. Just, K. Turek: Short-term temporal variations of soil gas radon concentration and comparison of measurement techniques. Radiation Protection Dosimetry, 108, 1, 55–63, (2004) 7. V. Petersell, G. Åkerblom, M. Enel, V. Mõttus, K. Täht: Radon Risk Map of Estonia: Explanatory text to the Radon Risk Map Set of Estonia at scale of 1:500 000 Report 2005:16. Swedish Radiation Protection Authority (SSI), Tallinn, (2005) 8. M. Castelluccio, M. Moroni, P. Tuccimei, M. Neznal, M. Neznal: Soil Gas Radon Concentration and Permeabilità at “Valle della Caffarella” Test Site (Roma, Italy). Evaluation of Gas Sampling techniques and Radon Measurements Using Different Approaches. Proceedings of the 10th international workshop on the geological aspects of radon risk mapping, Czech geological survey, Prague, 61–71, (2010) 9. 98th International workshop on the Geological aspects of Radon Risk Mapping Prague (Czech Republic), 26-30 September 2006 10. L. Gyalog: Geological map of Central Region of Hungary. Geological map of Hungary 1:100 000 (Budapest), Geological Institute of Hungary, (2005)

Seasonal Variation of Nano Aerosols in Postojna Cave, Slovenia

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SEASONAL VARIATION OF NANO AEROSOLS IN POSTOJNA CAVE, SLOVENIA Smerajec Mateja1, Gregorič Asta1, Kobal Ivan1, Kávási Norbert2, Vaupotič Janja1 1

2

Jožef Stefan Institute, Ljubljana Social Organization for Radio Ecological Cleanliness, Veszprém

Abstract At the train station and the lowest point along the tourist route in Postojna Cave, activity concentration of radon (222Rn) decay products and number concentration and size distribution of aerosol particles in the size range of 10–1100 nm were measured. In summer, aerosols were mostly composed of the <50 nm, while in winter, of the >50 nm fraction. As a consequence, the fraction of the unattached radon decay products, and hence dose conversion factor, is higher in summer than in winter.

Introduction In Postojna Cave, as in a great number of karst caves worldwide (1, 2), elevated activity concentrations of radioactive noble gas radon (222Rn, half-life t1/2 = 3.82 days) in air have been observed (3). Because of its α-transformation, radon is ubiquitously accompanied by its short-lived decay products (RnDP): 218Po (α, 3.05 min), 214 Pb (β/γ, 26.8 min), 214Bi (β/γ, 19.7 min) and 214Po (α, 164 µs) (4). In air, they form clusters and attach to atmospheric particulates (general aerosol), and eventually appear as radioactive aerosol with a bimodal size distribution in the 1–10 nm (unattached RnDP) and 100–500 nm (attached RnDP) size range (5). Elevated values of the fraction of unattached RnDP in the cave, the crucial parameter in radon dosimetry, have been ascribed to low concentration of general aerosol (6). In order to prove this hypothesis, measurements of RnDP activity concentration and number concentration as well as number size distribution of aerosol particles were carried out at two points in the cave in two yearly seasons (7, 8), for which the results are presented and shortly compared. Site description Postojna Cave (Figure 1) as the majority of karst caves, is only naturally ventilated. Its air temperature is practically constant around 9 °C and relative air humidity from 95 % to100 %, all the year round. It is practically a horizontal cave and the air flow in summer and winter time differs considerably. In winter, when the cave temperature is higher than outside, cave air is released from the cave into the outdoor atmosphere due to the air draught caused by the ‘chimney effect’ (9), thus allowing fresh and cold outdoor air to enter the cave through low lying openings. This effect is not operative in

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Smerajec M., Gregorič A., Kobal I., Kávási N., Vaupotič J.

summer, when the outside temperature is higher than in the cave, and air draught is minimal or reversed.

Figure 1: Layout of Postojna Cave Methods Radon decay products Individual activity concentrations of 222Rn, 218Po, 214Pb, 214Bi/214Po (CRn, C218Po, C214Pb and C214Bi = C214Po, respectively) have been measured using a EQF3020-2 device (Equilibrium Factor Monitor – System). Air is pumped for 6 minutes at a flow rate of 2.4 dm3 min–1 over a metal mesh grid on which particles smaller than 5 nm (considered as unattached RnDP) are separated from those above this size (considered as attached RnDP) and the two fractions are deposited electrostatically on two separate 150 mm2 semiconductor detectors. Gross alpha activity is measured during three consecutive intervals within 110 minutes after the end of pumping and, applying the Markov


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method (10), individual activity concentrations of 218Po, 214Pb and 214Bi in the unattached and attached fractions are obtained. The device also gives equilibrium equivalent activity concentration of RnDP (CRnDP), equilibrium factor between Rn and RnDP (F = CRnDP/CRn), fraction of the unattached RnDP with CRnDP denoting equilibrium equivalent activity concentration of the unattached RnDP only), as well as air temperature and humidity. General aerosols The term general is used here to comprise all particles: those without and those with RnDP associated (although the contribution of the latter in the number concentration is negligible (8)). Number concentration and size distribution of general aerosol particles have been measured with a Grimm Aerosol SMPS+C instrument (Scanning Mobility Particle Sizer + Counter), Series 5.400. For that purpose, the long DMA unit (Differential Mobility Analyzer) was used, designed for the 10–1100 nm size range. The DMA unit separates charged particles based on their electrical mobility, which depends on the particle size and electrical charge: the smaller the particle and the higher its electrical charge the higher is its mobility. Particles enter the CPC unit (Condensation Particle Counter) containing a heater saturator in which alcohol vapour molecules condense onto the entering particles, thus causing them to grow into droplets. The droplets are then detected with a laser beam (DLS detection) and counted. The frequency of measurement is one in seven minutes. The instrument gives the total number concentration CN(tot), size distribution dCN(d)/dlnd, with d, electrical mobility-quivalent particle diameter, and geometric mean of the particle diameter dGM. Because in Postojna Cave RnDP are attached to aerosols bigger than 100 nm (6), we selected 50 nm as the border between the unattached and attached fraction and were interested in concentrations of particles smaller than 50 nm and bigger than that, as well as the fraction of the smaller ones, xN(<50). Several 5–10 day measurements were carried out with the EQF3020-2 devices in summer 2009 and winter 2010 at the train station and the lowest point along the guided walking route in the cave. Within these periods, also the SMPS+C instrument was used, but for several hours only during morning visits, because the instrument is not designed for very humid environment and therefore its operation was kept minimised (Figure 2). In addition, in 2010 radon was measured once a month using alpha scintillation cells in late morning hours.


40

SMPS+C (Grimm)

EQF3020-2 (Sarad)

Figure 2: The lowest point in Postojna Cave with measuring devices Results and Discussion Radon activity concentrations at both measurement points obtained once a month with alpha scintillation cell are shown in Figure 3. They are significantly higher in summer than in winter because of the enhanced natural ventilation in winter caused by the chimney effect. Time variations of CRn, CRnDP, F and f un observed during one week measurements at the lowest point in summer and in winter are presented in Figure 4. In summer (Figure 4a), higher CRn values are observed during day time, when the air temperature outside is higher than overnight, and hence natural air drought lower. In winter (Figure 4b), this kind of diurnal variation is not seen; obviously the effect of enhanced air drought in this yearly season overwhelms the effect of air temperature difference in the cave and outside. Comparisons of f un values, which attract our main interest, for both points and both yearly seasons are summarized in Figure 5. They are higher and with wider scattering in summer than in winter (Figure 5a), and also higher and with wider scattering at the lowest point than at the train station (Figure 5b). Thus, dose conversion factor (8) is higher in summer (15.3 mSv WLM–1) than in winter (7.7 mSv WLM–1), according to the empirical equation DCF = 11.35 + 43fun (11, 12).


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Fgure 3: Radon activity concentrations obtained monthly with alpha scintillation cells at the train station and the lowest point in Postojna Cave in 2010 Figure 6 shows total concentrations of general aerosol and concentrations of particles of various sizes, obtained during morning hours at the lowest point in summer and winter. Generally, total concentration is markedly lower than in a dwelling (5100±1700 cm–3) (8). In summer (Figure 6a), total concentration decreased markedly during visits, mainly due to decrease in concentrations of particles smaller than 30 nm, while concentrations of particles bigger than 60 nm remained practically unchanged. This is presumably because the smaller particles are preferentially deposited on the cave surfaces (5), and caught by cloths (13) and uptaken by the lungs (14, 15) of visitors walking through the narrow corridor at the lowest point with a cross section of less than 5 m2. In winter (Figure 6b), the situation is different: total concentration, contributed mainly by particles bigger than 30 nm, is slightly and steadily increasing during morning hours. The fraction of particles smaller than 50 nm, associated with the unattached RnDP (xN(<50)), was more than 0.80 in summer, showing a steady decrease during visits (Figure 7a), while it was only around 0.05 in winter (Figure 7b). As evident from size distributions, the geometric mean of particle diameter was around 30 nm in summer (Figure 8a) and around 110 nm in winter (Figure 8b), as consequence of inflow of outside atmospheric aerosols. Our results point out that the reason for high f un values in the cave air is not solely a low concentration of general aerosols, as believed before (6, 16, 17), but also the dominating contribution of their <50 nm fraction to which the unattached RnDP are associated.


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Figure 4: Results of continuous radon measurements at the lowest point in the Postojna Cave: radon activity concentration (CRn), equilibrium factor between radon and its decay products (F), equilibrium-equivalent activity concentration of radon decay products (CRnDP) and fraction of unattached decay products (f un); a) in summer and b) in winter


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Figure 5: Box and whiskers plots of the fraction of unattached decay products (f un); a) at the lowest point in summer and winter and b) in summer at the lowest and the train station

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Figure 6: Time run of the total number concentration of the general aerosol (CN(tot)) and number concentrations of particles of various sizes (d / nm) (CN(d)) at the lowest point in Postojna Cave; a) in summer and b) in winter


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Figure 7: Time run of the number concentrations (CN(d)) of general aerosol particles smaller than 50 nm (CN(<50)) and bigger than that (CN(>50)), and the fraction of the smaller ones (xN(<50)) at the lowest point in Postojna Cave; a) in summer and b) in winter

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Figure 8: Size distribution (dCN(d) = dln(d / m) of general aerosol at the lowest point in Postojna Cave; a) in summer and b) in winter


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Conclusion Although the morning total number concentrations of the aerosol particles in summer and in winter were similar, it was mainly contributed by particles smaller than 50 nm (associated to the unattached RnDP) in summer, and by bigger than 50 nm in winter. This explains why f un values (and thus the calculated dose conversion factors) are by a factor higher in summer than in winter. The difference is caused by an enhanced inflow of fresh air, driven in winter by higher air temperature in the cave than outdoors, introducing outdoor aerosols (with an average xN(<50) of 0.39±0.17 (18)) into the cave.

Acknowledgments The study was financed by the Slovenian Research Agency within the project contract no. J1–0745 and a research program P1–0143. The authors thank Mr. Ivan Iskra for his help in operating the Grimm instrument. Cooperation of the Cave management and technical assistance of Mr. Stanislav Glažar is appreciated. References 1. M. S. Field: Risks to cavers and cave workers from exposures to low-level ionizing alpha radiation from Rn-222 decay in caves. Journal of Cave and Karst Studies, 69, 207–228, (2007) 2. N. Kávási, J. Somlai, T. Kovács, T. Szabó, A. Várhegyi, J. Hakl: Occupational and patient doses in the therapeutic cave, Tapolca (Hungary). Radiation Protection Dosimetry, 106, 263–266, (2003) 3. J. Vaupotič: Radon levels in karst caves in Slovenia. Acta Carsologica, 39, 503–512, (2010) 4. A. V. Nero: Radon and its decay products in indoor air: an overview, in Radon and its Decay Products in Indoor Air. New York, John Wiley & Sons, 1–53, (1988) 5. C. Papastefanou: Radioactive aerosols. Radioactivity in the Environment, Amsterdam, Elsevier, 171, (2008) 6. G. Butterweck, J. Porstendörfer, A. Reineking, J. Kesten: Unattached fraction and the aerosol size distribution of the radon progeny in a natural cave and mine atmospheres. Radiation Protection Dosimetry, 45, 167–170, (1992) 7. J. Vaupotič: Nanosize radon short-lived decay products in the air of the Postojna Cave. Science of the Total Environment, 393, 27–38, (2008) 8. J. Vaupotič: Nano aerosols including radon decay products in ambient air, in Chemistry, Emission control. Radioactive Pollution and Indoor Air Quality, Rijeka, InTech., 154–190, (2011) 9. J. Hakl, I. Hunyadi, A. Várhegyi: Radon monitoring in caves, in Radon measurements by etched track detectors. Singapore, World scientific Publishing Co. Pte. Ltd., 261–283, (1997)

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10. K. P. Markov, N. V. Ryabov, K. N. Stas: A rapid method for estimating the radiation hazard associated with the presence of radon daughter products in air. Atomic Energy, 12, 333–337, (1962) 11. J. W. Marsh, A. Birchall, G. Butterweck, M. D. Dorrian, C. Huet, X. Ortega, A. Reineking, G. Tymen, C. Schuler, A. Vargas, G. Vezzu, J. Wendt: Uncertainty analysis of the weighted equivalent lung dose per unit exposure to radon progeny in the home. Radiation Protection Dosimetry, 102, 229–248, (2002) 12. A. Birchall, A. C. James: Uncertainty analysis of effective dose per unit exposure from radon progeny and implications for ICRP risk-weighting factor. Radiation Protection Dosimetry, 53, 133–140, (1994) 13. M. Balcazar, A. Chavez, G. Pina-Villalpando, M. Alfaro, D. Mendoza: Radon decay products attached to clothes in a nuclear laboratory. Radiation Measurements, 31, 337–342, (1999) 14. W. Hofmann, G. Mainelis, A. Mohamed, I. Balásházy, J. Vaupotič, I. Kobal: Comparison of different modeling approaches in current lung dosimetry models. Environment International, 22, 965–976, (1996) 15. W. Hofmann, L. Koblinger: Monte-Carlo modeling of aerosol deposition in human lungs. Part II: Deposition fractions ant their senitivity to parameter variations. Journal of Aerosol Science, 21, 675–688, (1990) 16. Y. S. Cheng, T. R. Chen, P. T. Wasiolek, A. VanEngen: Radon and radon progeny in the Carlsbad Caverns. Aerosol Science and Technology, 26, 74–92, (1997) 17. O. Meisenberg, J. Tschiersch: Online measurement of unattached and total radon and thoron decay products. Applied Radiation and Isotopes, 67, 843–848, (2009) 18. M. Smerajec, J. Vaupotič: Nano-aerosols including radon decay products in outdoor and indoor air at a suburban site. Journal of Toxicology, in press, (2011)

Diurnal Variation of Radon and Air-Ions Concentrations in the Underground Low-Level Laboratory in Belgrade, Serbia

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DIURNAL VARIATION OF RADON AND AIR-IONS CONCENTRATIONS IN THE UNDERGROUND LOW-LEVEL LABORATORY IN BELGRADE, SERBIA Udovičić Vladimir 1, Dragić Aleksandar 1, Banjanac Radomir 1, Kolarž Predrag1, Žunić S. Zora 2 1

2

Institute of Physics, Belgrade, Serbia Institute of Nuclear Sciences “Vinča”, ECE LAB, Belgrade, Serbia

Abstract The underground low-level laboratory in Belgrade, Serbia exists for fourteen years, with the continuous monitoring of the radon concentration carried out during this period. The radon time series analysis based on the short-term measurements has shown that there are two periodicity at 1 day and 1 year. Besides the fact that the laboratory has the system for radon reduction, there is significant one day period which is the main subject of this work. It has been shown that the radon behavior in the underground low-level laboratory in Belgrade has the similar characteristics as in the other underground environment (caves, mines, boreholes…).

Introduction The Low-Background Laboratory for Nuclear Physics at the Institute of Physics in Belgrade is a shallow underground laboratory. The laboratory was built in the loamy loess cliff on the bank of the river Danube with the overburden of 12 m of soil. The experiments and routine measurements in the underground Low-Background Laboratory for Nuclear Physics require low levels of radon concentration with minimum temporal variations (1). Unfortunately, in the underground environments radon level has extremely high values (up to several kBqm-3) and temporal variations, especially the daily amplitude might be very intensive. The radon behavior in such specific environments is the subject of intensive research. This is confirmed by a number of scientific articles published in a few last years (2, 3, 4, 5, 6). The underground low-level laboratory in Belgrade, Serbia exists for fourteen years, with the continuous monitoring of the radon concentration carried out during this period. The radon time series analysis based on the short-term measurements has shown that there are two periodicity at 1 day and 1 year. Besides the fact that the laboratory has the system for radon reduction (7), there is significant one day period which is the main subject of this work. The physical origin of the obtained daily variation in the underground laboratory is not straightforward. The daily variability shows a weak correlation with the difference of external and internal temperature. Also, in this work we present the simultaneous measurements of the atmospheric fast ions and indoor radon concentration in the ground and underground low-level laboratory.

Udovičić V., Dragić A., Banjanac R., Kolarž P., Žunić Z. S.

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Experimental methods The all experiments are performed in the underground low-level laboratory in Belgrade. The laboratory is located on the right bank of river Danube in the Belgrade borough of Zemun, on the grounds of the Institute of Physics. The ground level part of the laboratory (GLL) is situated at the foot of the vertical loess cliff, which is about 10 meters high. The underground part of the laboratory (UL), of the useful area of 45 m2, is dug into the foot of the cliff and is accessible from the GLL via the 10 meters long horizontal corridor, which serves also as a pressure buffer for a slight overpressure in the UL (Figure 1).

Figure 1: Cross section of the Low-level and CR Laboratory at IOP, Belgrade, 44o49’N, 20o28’E, vertical rigidity cutoff 5.3 GV The underground low-level laboratory in Belgrade, Serbia exists for fourteen years, with the continuous monitoring of the radon concentration carried out during this period. The special designed system for radon reduction is consist of three stage: a) The active area of the laboratory is completely lined up with aluminium foil of 1 mm thickness, which is hermetically sealed with a silicon sealant to minimize the diffusion of radon from surrounding soil and concrete used for construction, b) the laboratory is continuously ventilated with fresh air, filtered through one rough filter for dust elimination followed by the battery of coarse and fine charcoal active filters and c) the parameters of the ventilation system are adjusted to give an overpressure of about 2 mbar over the atmospheric pressure. The radon monitor is used to investigate the


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temporal variations in the radon concentrations. For this type of short-term measurements the SN1029 radon monitor was used (manufactured by the Sun Nuclear Corporation, NRSB approval-code 31822). The device consists of two diffused junction photodiodes as a radon detector, and is furnished with sensors for temperature, barometric pressure and relative humidity. The user can set the measurement intervals from 30 min to 24 h. The radon monitor device records radon and atmospheric parameters readings every 2 h in the UL. The data are stored in the internal memory of the device and then transferred to the personal computer. The data obtained from the radon monitor for the temporal variations of the radon concentrations over a long period of time enable the study of the short-term periodical variations. The series taken during period of three years were spectrally analyzed by the Lomb-Scargle periodogram method (8). Aspirated Gerdien condenser is widely utilized instrument for the air-ion concentrations and mobility measurements. Cylindrical Detector of Air-Ions (CDI-06) is made in the Institute of Physics, Belgrade (9) (Figure 2). It is fully automated portable instrument with ability to alternatively measure concentrations of positive and negative air-ions, temperature (T), pressure (P) and relative humidity (RH).

Figure 2: Cylindrical Detector of Air-Ions (CDI-06) Results and discussion The descriptive statistics on the raw radon data are shown (Table 1). The radon data from radon monitor device SN1029 for the period of three years are spectrally analyzed. Lomb-Scargle periodogram analysis method has been used in spectral analysis of radon time series. The advantage of Lomb-Scargle method is well known statistical interpretation of peridogram. The results of spectral analysis of the raw radon data are presented (Figure 3).

Table 1: Descriptive statistics on the raw radon data Mean Radon concentration 13.50 (Bqm-3)

Standard deviation

Minimum

Median

Maximum

9.75

0

12.4

75

52


Figure 3: Lomb-Scargle periodogram for a measurement period of three years with time sampling of two hours It is obvious that the Lomb-Scargle periodogram shows very clean peak at 1 day and 1 year period. In the long term a clear seasonal variation of the radon concentration (monthly average) is obtained (Figure 4).

Figure 4: Seasonal variation of the radon concentration (monthly average)


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Special attention is made to the daily radon variability in the UL in Belgrade. Many authors are found that the daily variation in the radon concentration in the underground environments mainly depend on the difference of the outside atmospheric temperature and the internal temperature inside underground spaces (2, 4). The obtained results for one calendar year are presented (Figure 5).

Figure 5: Radon concentration (red line) in the UL versus the difference of the outside atmospheric temperature and the internal temperature inside UL (black line) for one calendar year. The Pearson correlation coefficient between radon concentration and the difference of external and internal temperature is 0.18 It is obvious that there exist a weak correlation between radon concentration and the difference of external and internal temperature. The Pearson correlation coefficient between radon concentration and the difference of external and internal temperature is 0.18. Also, the time series show that there are two different seasons according to the gradient of the temperature. One is winter time (from December to the June) with low values of the radon concentration and the second one is summer time (from June to November) when radon values rich the maximum. Also, in this work we present the simultaneous measurements of the atmospheric fast ions and indoor radon concentration in the GLL and UL. Air-ions and radon are important constituents of the air which can affect the human health. On the other hand, radon is the main source of the air-ions in the lower troposphere and variation of airion concentrations is attributed to changes of the radon activity (10). The short-term simultaneous measurements of the atmospheric fast ions and indoor radon concentration

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in the GLL and UL are shown (Figure 6) and (Figure 7). The radon concentration and positive air-ions + are average over all measurements interval.

Figure 6: Radon concentration (circle) versus atmospheric fast ions in the GLL (black line), r = 0.66, = 54 Bqm-3, + = 840 ionscm-3

Figure 7: Radon concentration (red line) versus atmospheric fast ions in the UL (black line), r = 0.17, = 12 Bqm-3, + = 227 ionscm-3


55

It is clear that the Pearson correlation coefficient r is decreased in the UL compared with the r value obtained in the GLL.

Conclusions It has been shown that the radon behavior in the underground low-level laboratory in Belgrade has the similar characteristics as in the other underground environment (caves, mines, boreholes…) because it has the same source and the places are complete surrounded with the soil. It is also not quite understood the influence of the meteorological parameters on the radon variability. In this work we tried to point out the correlation between daily radon variation and the difference of external and internal temperature in the UL. The further theoretical and experimental research work is necessary to explain physical mechanisms by which the temperature gradient is correlated with radon variations in the underground environments.

Acknowledgments This work is supported by the Ministry of Education and Science of the Republic of Serbia under project No. 43002. References 1. A. Dragić, D. Joković, R. Banjanac, V. Udovičić, B. Panić, J. Puzović, I. Aničin: Measurement of cosmic ray muon flux in the Belgrade ground level and underground laboratories. Nuclear Instruments and Methods in Physical Research A591, 470–475, (2008) 2. V. M. Choubey, B. R. Arora, S. M. Barbosa, N. Kumar, L. Kamra: Seasonal and daily variation of radon at 10 m depth in borehole, Garhwal Lesser Himalaya, India. Applied Radiation and Isotopes, 69(7), 1070–1078, (2011) 3. R. Viñas, A. Eff-Darwich, V. Soler, M. C. Martín-Luis, M. L. Quesada, J. de la Nuez: Processing of radon time series in underground environments: Implications for volcanic surveillance in the island of Tenerife, Canary Islands, Spain. Radiation Measurements, 42, 101–115, (2007) 4. S. M. Barbosa, H. Zafrir, U. Malik, O. Piatibratova: Multiyear to daily radon variability from continuous monitoring at the Amram tunnel, southern Israel. Geophysical Journal International, 182, 829–842, (2010) 5. M. Marušiakova, J. Hulka: Estimates of the annual average indoor radon concentration in Teleci in the Czech Republic. Radiation Protection Dosimetry, 145(2-3), 145–149, (2011) 6. J. Vaupotič: Nanosize radon short-lived decay products in the air of the Postojna Cave. Science of The Total Environment, 393(1), 27–38, (2008)

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7. V. Udovičić, B. Grabež, A. Dragić, R. Banjanac, D. Joković, B. Panić, D. Joksimović, J. Puzović, I. Aničin: Radon problem in an underground low-level laboratory. Radiation Measurements, 44, 1009–1012, (2009) 8. V. Udovičić, I. Aničin, D. Joković, A. Dragić, R. Banjanac, B. Grabež, N. Veselinović: Radon Time-Series Analysis in the Underground Low-Level Laboratory in Belgrade, Serbia. Radiation Protection Dosimetry, 145(2-3), 155–158, (2011) 9. P. Kolarž, B. P. Marinković, D. M. Filipović: Zeroing and testing units developed for Gerdien atmospheric ion detectors. Review of Scientific Instruments, 76, 046107–9, (2005) 10. P. Kolarž, D. M. Filipović, B. P. Marinković: Daily variations of indoor air-ion and radon concentrations. Applied Radiation and Isotopes, 67(11), 2062–2067, (2009)

Radiological Concerns of the Red Mud Field of the Vicinity of Ajka (Hungary)

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RADIOLOGICAL CONCERNS OF THE RED MUD FIELD OF THE VICINITY OF AJKA (HUNGARY) Kovács Tibor1, Somlai János1, Kovács József2, Bui Pál2, Sas Zoltán1, Szeiler Gábor1 1

University of Pannonia, Institute of Radiochemistry and Radioecology, Veszprém 2 University of Pannonia, Institute of Environmental Engineering, Veszprém

Abstract On 4th October 2010 the wall of the red mud reservoir No. X near Ajka in Hungary broke, and almost 800 000 m3 of strongly alkaline mud flooded the surrounding settlements. More than 100 people have suffered severe burns, and 10 died. The 226Ra and 232Th concentration of red mud is 5-7 times higher than the world average of that of soils. Due to the thin layer a dose rate increment of only 10-30 nGy/h was measured, which assuming staying outdoors means an effective excess dose of approximately 42 μSv/y. Inhalation of red mud dust would mean an extra dose of 2 μSv/y (taking the grain size and the dust concentration into account) for the workers and 1.2 μSv/y for the inhabitants. On the whole, it can be stated that the radiation exposure due to the accident is negligible.

Introduction The news on the dam failure of the red mud reservoir near Ajka, Hungary circuited the whole world. It was a serious industrial disaster with serious ecological consequences. It is a known fact that bauxite serving as the base material of aluminium production contains uranium, thorium, and their progenies, all of natural origin, in greater concentration (238U: 400-600 Bq/kg, 232Th: 300-400Bq/kg) (1) than the average radionuclide concentration measured in soils (238U: 33 Bq/kg, 232Th: 45 Bq/kg, 226 Ra: 32 Bq/kg, 40K: 412 Bq/kg) (2). Processing is done using the Bayer technology throughout the world (3). Bauxite is explored using concentrated NaOH. Red mud usually with high alkali-content is produced as a by-product of the process. Its red colour giving the name is due to its high (24-45 %) iron oxide-content. Depending on the aluminium-content of the bauxite the amount of red mud is 1 – 1.5 times the amount of produced alumina (Al oxy-hydroxide). This by-product is therefore generated in large quantities; it has high water-content and is strongly alkaline due to the NaOH remaining in it. Almost all of the radionuclides of natural origin in bauxite go into the red mud. Considerable amount of bauxite has been mined and processed in Hungary during the past decades. Alumina production in Ajka started in 1943. More than 30 Mt of red mud generated has been placed in 10 cassettes, two of them are in operation (dried out heaps were covered, and are being monitored) (4).

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Kovács T., Somlai J., Kovács J., Bui P., Sas Z., Szeiler G.

As it is known, the retaining wall of reservoir No. X broke on 4th October 2010, and almost 800 000 m3 of strongly alkaline (pH ≈ 13) mud flooded over the settlements nearby, and into the stream Torna. The mud flood of several meters height carried away buildings and people, and due to its high alkali-content more than 100 people suffered severe chemical burns, and ten people died. Red mud contaminated almost 10 km² of residential and agricultural territories. Since it was known that the radionuclide content of natural origin of red mud was relatively high, also the issue of radiological hazard was raised. Due to the radionuclides in red mud the gamma-dose rate may increase in the contaminated areas. Due to the 226 Ra-content of red mud radon exhalation must be expected which contributes to radon concentration in air. Furthermore, if the red mud dries it consists of an extremely fine-grained powder which can be resuspened by wind. Inhaling this airborne dust represents another pathway of radiation exposure. Therefore, gamma-dose rate was measured in the contaminated area during our work, together with radon concentration, the radionuclide concentration of red mud samples taken on site, the dust concentration, the grain size distribution of red mud. The expected radiation exposure was estimated from these data.

Materials and methods, results Gamma dose Dose rate was measured conventionally in a height of 1 m above ground over the territory contaminated by red mud in the residential area, in courts, gardens and along the roads. An Automess 6150 ADB ambient level dose rate meter was used for the measurements. The red mud layer was 2-8 cm thick in the territory. The measured dose rate varied between 110 and 135 nGy/h. In the specific surroundings it meant an increment of 10-30 nGy/h related to the uncontaminated area. (Note that the limit value originating from artificial sources in residential buildings is generally 500 nGy/h. In buildings in Ajka and in Tatabánya, where coal slag was built in, values of even 400-800 nGy/h can be measured, and were actually measured before due to the radioisotopes of natural origin. In some countries the so-called elevated background limit value was set out as 300 nGy/h (2).) If red mud was not removed and 2000 hours/year staying and a dose conversion of 0.7 Sv/Gy (1) was assumed taking the screening effect of less radiation-sensitive organs into consideration, then it would result in an excess dose of 0.042 mSv/y at most (which is negligible related to the natural background radiation of approximately 3 mSv/y).


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Radionuclide concentration of red mud samples Nine red mud samples taken from the territories of Kolontár and Devecser were dried and closed in a Marinelli beaker with a volume of 600 cm3. After reaching the equilibrium intensity was measured for 40 000 seconds using an HPGe detectory manufactured by ORTEC. The average radionuclide concentration of the samples was: 238U: 265 (197-332) Bq/kg, 232 Th: 264 (194-337) Bq/kg, 226Ra: 180 (143-237) Bq/kg, 40K: 283 (228-360) Bq/kg. On the whole, it can be stated that the radionuclide concentration of red mud is higher than the average radionuclide concentration of soils, but it is much lower than the activity limit values concerning radioactive materials, therefore, it is not considered a radioactive material. These materials are handled as NORM (NaturallyOccurring Radioactive Materials) in the literature (5, 6).

Radon concentration in the air A measurement station was set up in Devecser, where, besides other parameters (dust concentration, meteorological parameters, etc.) radon concentration was continuously monitored. Measurements were performed using an instrument type Alphaquard PQ 2000. Changes in radon concentration are shown on Figure 1. Radonconcentration (Bqm-3)

100 90 80 70 60 50 40 30 20 10 0 1

25

49

73

97

121

145

time (h)

Figure 1: Fluctuation of outdoor radon concentration in Devecser (07.10.2010 – 14.10.2010.) It can be assumed that the measured values – average 62 (36-94) Bq/m3 – are higher than they would be if Rn would stem only from exhalation of normal soil (world average is 10 Bq/m3 (2); in Germany: long-term mean 9 Bq/m3, varying regionally between about 3 and 40 Bq/m³ (7)) .This may partly come from the red mud spread over a great surface area, but probably the rest of the red mud located in the surroundings is not negligible either, and neither is radon exhaled from the fly-ash reservoirs containing radium in a quantity almost greater by a magnitude. (Reliable measurement results were not available.)


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However, the measured value is far below the newest 300 Bq/m3 ICRP (8) and WHO (9) recommendations related to dwellings (it used to be 600 Bq/m3 before). The activity level at workplaces in Hungary is 1000 Bq/m3 (10), which corresponds to limit effective dose to approximately 6.3 mSv/y for 2000 hours/year spent there. Therefore, the values measured here are lower by more than a magnitude. Taking into account 2000 hours/year spent there for those working in damage prevention the radiation exposure coming from radon would still only be 0.4 mSv/y, which is negligible.

Dust concentration, particle analysis When red mud dries up elevated dust generation must be expected. For the estimation of radiation exposure originating from this the grain size of red mud needs to be known. Based on previous surveys it was found that the most of the particles (94.7 %) belongs to the fine-grained category of 20 μm, which is considered the most dangerous fraction from the aspect of inhalation (Table 1).

Table 1: The grain size distribution of red mud Particle size (μm) > 125 80 – 125 63 – 80 30 – 63 20 – 63 < 20

Red mud (w/w %) 2.1 0.7 2.0 0.3 0.2 94.7

The distribution of the fraction below 20 μm obtained using the instrument type Fritsch Analysette 22 is shown on Figure 2.

Figure 2: Distribution of red mud grain-sizes


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The figure shows that the greater part of the dust is made up of the fraction lower than 10 μm (> 68 %). This is the range making up the respirable fraction, therefore it can be hazardous to health. Dust concentration below 10 μm had continuously been measured every hour between 7th and 13th October at the measuring station located in Devecser. Measuring instrument make Environment Sa type MP 101 integrated into a mobile measuring system was used for the measurements following EN 12341 standard (11). During this period the average dust concentration was 33.4 (0.1-114.6) μg/m3 (Figure 3). Dust concentration (μ gm-3)

140 120 100 80 60 40 20 0 1

13

25

37

49

61

73

85

97

109 121 133 145

time (h)

Figure 3: Variation of the dust concentration in the fraction <10 μm (hourly average) After analyzing data it can be stated that highest values were found during the night hours, when the dust concentration was increased due coal firing heating systems. (The constructed measurement system provided for the continuous data collection of meteorological parameters, therefore, this statement is verified.)

Calculating the radiation exposure originating from the inhalation of red mud During calculations radionuclides of long half-decay period were taken as reference according to the UNSCEAR publications (1, 2). The committed effective dose per year is calculated as: annual dose (µBq/y) = (activity concentration in dust, Bq/µg) x (particle concentration per air volume, µg/m³) x (dose coefficient, µSv/Bq) x (respiration rate, m³/y). The respiration rate was set 7300 m3/y (typical for adult population), and the factor of spending time outdoors as 0.2 (2) 1 μg/m3 of red mud dust concentration results in a bound effective dose of 36 nSv/y. Taking the present dust concentration data into account a bound effective dose of 1.2 μSv/y is assumed.


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Table 2: Committed effective dose originating from the inhalation of isotopes of long half-life period Measured radionuclide

Assumed equilibrium 238

238

U

U U 230 Th 234

226 226

Ra Pb 210 Po 210

Ra

232 232

235

Th Ra 228 Th 228

Th

U (~ 0.7 %) Total

Dose coefficient (μSv/Bq) 2.9 3.5 14 20.4 3.5 1.1 3.3 7.9 25 2.6 40 67.6 3.1

Act. conc. (Bq/μg)

Committed effective dose (pSv/ μg)

265·10-9

5.404

180·10-9

264·10-9 1.85·10-9

1.422

17.847 0.006 24.72

In case of those working in the area, taking the respiration performance of 1.2 m3/h and 2000 hours/year working hours into account, when 1 μg/m3 red mud dust concentration is inhaled a committed effective dose of 59.3 nSv/y can be expected. The dose limit of 1 mSv/y for the population would only be reached in case of continuously inhaling 16.9 mg/m3 red mud dust concentration which is very unrealistic. The above estimation is conservative in several aspects. It is assumed that all the dust comes from red mud, that the given dust concentration is valid for the whole year (which is an overestimation because of recultivation which started not long time after the accident), and that all the dust is of the grain size hazardous for the lungs (and for 226 Ra it was not taken into account that some part of the gaseous 222Rn leaves the area therefore the radon progeny concentration will be lower).

Conclusion The increment of radiation exposure caused by the contamination was examined from the aspect of those living in the contaminated areas, and those participating in the recultivation works. The average concentration of 238U and 232Th radionuclides in the red mud samples was 6-8 times higher than the average radionuclide concentration of soils. Due to the thin layer (5-8 cm) the gamma dose rate increment measured in a height of 1 m was only 10-35 nGy/h. The external radiation exposure originating from this is 0.04 mSv/y, and the committed effective dose due to the dust inhaled is 1-2 μSv/y.


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To sum it up, due to the red mud contaminating the area the radiation exposure of those living there and those performing recultivation work is negligible related to the background radiation of natural origin.

Acknowledgements Present publication was realized with the support of the project TÁMOP-4.2.2/B10/1-2010-0; and was supported by the Hungarian Science Foundation (OTKA Grant No. K 81975 and K 81933). References 1. United Nations Scientific Committee on the effects of Atomic Radiation, UNSCEAR 2000: Sources and effects of ionizing Radiation. Report to the General Assembly with Scientific Annexes ,United Nations, New York, (2000) 2. United Nations Scientific Committee on the effects of Atomic Radiation, UNSCEAR 2008: Sources and Effects of Ionizing Radiation, Report, 1, Sources Report to the General Assembly Scientific Annexes A and B, New York, (2008) 3. C. Schmitz: Handbook of aluminium recycling. Essen, Germany, (2006) 4. J. Fazekas: 75 éves a bauxitbányászat Magyarországon (in Hungarian). Bányászati és kohászati lapok, Bányászat, 134, 506–511, (2001) 5. J. Somlai, V. Jobbagy, J. Kovacs, S. Tarjan, T. Kovacs: Radiological aspects of the usability of red mud as building material additive. Journal of Hazardous Materials, 150, 541–545, (2008) 6. V. Jobbágy, J. Somlai, J. Kovács, G. Szeiler, T. Kovács: Dependence of radon emanation of red mud bauxite processing wastes on heat treatment. Journal of Hazardous Materials, 172, 1258–1263, (2009) 7. C. Dushe, K. Gehrcke, M. Kümmel: Exposure of the German Population to Outdoor Radon. 10th Intnatianl. Workshop on the geological aspects of radon risk mapping, Prague, Czech Republic, (2010) 8. ICRP, 2007: The 2007 Recommendations of the International Commission on Radiological Protection. ICRP Publication, 103, Ann, ICRP 37, 2–4, (2007) 9. WHO, 2009: Handbook on Indoor Radon World Health Organisation. Geneva, Switzerland, (2009) 10. Az egészségügyi miniszter 16/2000. (VI.8.) EüM rendelete, az Atomenergiáról szóló 1996. évi CXVI. törvény egyes rendelkezéseinek végrehajtásáról, Magyar Közlöny, 55, Budapest, (2000) 11. EN 12341:1999: Air quality, Determination of the PM10 fraction of suspended particulate matter, Reference method and field test procedure to demonstrate reference equivalence of measurement methods. (1999)

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Radiological Investigation of the Effects of Red Mud Disaster

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RADIOLOGICAL INVESTIGATION OF THE EFFECTS OF RED MUD DISASTER Sas Zoltán1, Somlai János1, Jobbágy Viktor2, Kovács Tibor1, Szeiler Gábor1 1

University of Pannonia, Institute of Radiochemistry and Radioecology, Veszprém 2 Social Organization for Radioecological Cleanliness, Veszprém

Abstract Hungary suffered one of the most serious ecological disaster on 4th October 2010 when the gate of red mud waste dump was damaged and approximately 800.000 m3 alkaline red sludge flooded the vicinity of the dumps. Beside the chemical danger the high natural radionuclide content represents significant danger for the inhabitants as well. Red mud samples were collected from the contaminated area and they were investigated from the radiological point of view. The Ra-226 activity concentrations were determined by gamma spectrometry. The emanation coefficient and the exhalation rate were investigated according to the moisture content.

Introduction The Bayer process is the main industrial method of bauxite refining to produce alumina (aluminum oxide). The bauxite is digested by hot solution of NaOH. The radionuclide content of the bauxite slightly exceeds the world average in soils, which mostly remains in the by-product of the Bayer process. The aluminum manufacturing in Ajka (Hungary) started in 1943 and up to now approximately 30 Mt of red mud has been produced, which is stored in ten waste pounds. Hungary was stricken by the most dangerous ecological disaster on 4th October 2010 when the gate of the waste pound was damaged and 800.000 m3 alkaline red sludge flooded and contaminated two villages, almost 1000 hectare of land field. Due to the disaster 10 people died and at least 100 suffered chemical scalds. To estimate the dose risk for workers and inhabitants, different types of measurements were required. The Ra-226 content varies on the covered area because the original radionuclide content of bauxite is not homogonous and the deposited sludge can follow the disparity according to the deposition place. The flood eroded the deposited sludge progressively and dumped various radium content in the villages and land fields. Radon is a radioactive noble gas whose half life (3.82 d) can be enough to get out of the matrix into the pore space and into the air as well. While the alpha particle is being ejected as result of alpha decay, the daughter element is recoiled and it can be released into the pore space where it can be embedded in adjacent particles. The emanation coefficient or emanation power defined as the amount of the quantitative rate of the released radon from the crystal structure into the pore space to the total amount generated. Many factors determine the radon activity concentration

Sas Z., Somlai J., Jobbágy V., Kovács T., Szeiler G.

66

such as, variation in radium particles concentration, density, homogeneity in radium distribution, grain size, volume of pore space, and last but not least the moisture content (1).

Figure 1: Locality of the red mud disaster The moisture content of the pore space can absorb the recoil energy, also the newly radon atom ends the recoil in the water-filled pore space as well. After the progenies lose their kinetic energy and are being absorbed into the water, they are now free to diffuse. This is the reason of the emanation coefficient increment and available free radon until the saturation is reached in pore space. Besides specific moisture content the emanation power fluctuation turn to descending tendency because the water constitutes contiguous layers among the grains, which inhibits the diffusion of radon (2). Due to diffusion and convection radon can exhaled from the pore space into the air. The water content also has effect on the exhalation because it inhibits the diffusion and the convection of the emanated radon in the pore space. The activity concentration of the released radon per unit surface is called radon exhalation. The radon exhalation depends on the emanation coefficient, water content, pressure, temperature, weather factors, internal structure of the solid phase and the diffusion depth as well. In this study the emanation coefficient and the exhalation rate of the red mud were examined.

Measurements and methods Sampling and sample preparation The red sludge samples were taken from the flooded area in vicinity of Devecser, village which suffered the biggest loss caused by red sludge contamination. Half of the samples have been heated at a temperature of 105 ± 3 °C until they had no change in their mass. After drying the samples were grinded, sieved under 0.63 mm and weighted. The remainder part of the red mud was dried gradually because the emanation factor depends on the moisture content.


67

Ra-226 activity concentration determination by gamma-spectrometry The dried and sieved samples were stored for 30 d in air-tight aluminum Marinelli beakers having a volume of 600 cm3 so that it would reach the secular equilibrium between the Ra-226 and the Rn-222. The determination of the Ra-226 activity concentration occurred via the radon progenies Pb-214 (295 keV) and Bi-214 (609 keV) by high resolution gamma ray spectrometry, using an ORTEC GMX40-76 HPGe detector with efficiency of 40 %, and an energy resolution of 1.95 keV at 1332.5 keV. The data and spectra were recorded by a Tennelec PCA-MR 8196 MCA. The system was calibrated with red mud reference material certified by Hungarian National Office of Measures. The sample measuring time was 80.000 s.

Determination of radon emanation factor In every case of emanation sampling 15 g of red mud (with different water content) were taken and putted into 50 cm3 glass ampoule and sealed. After 30 d which are necessary to reach the secular equilibrium the ampoules were broken in a special metal crush cell and the radon content of the ampoules were transferred into Lucas cells and measured with an EMI type SCA (3).

Determination of the exhalation rate The red mud samples were measured in a proprietary exhalation chamber with a volume of 4250 cm3. The chamber was developed from ordinary glass jar with steel cap. The radon leakage determination of the radon accumulation chambers was gauged with the help of a PYLON RN 2000A type passive radon source.

Figure 2: closed loop exhalation sampling system The sample holder was made from plastic with volume of 300 cm3 with a height of 60 mm, and with a surface of 46.69 cm2. The homogeneity of the inner air was ensured


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by small size 12 V DC ventilator which was placed inside the chamber. The sample holder was covered by radon permeable film against dusting to avoid contamination of the Lucas-cells. The chamber volume was more then ten times higher than the pore volume because of to avoid the back diffusion (4). The chambers were purged out with radon free N2 gas before the accumulation started to reduce the initial radon concentration to zero. The accumulation time was between from 16 to 24 h in case of the measurements. The exhalation rate dependency was investigated according to the sample height with dry red mud to define the specific exhalation rate, subsequently the moisture content dependency was defined. The samples were dried discontinuously and their water content was determined and regulated.

Results and discussion Gamma-spectrometry The results of the gamma spectrometry measurements are shown in the Figure 3. The activity concentration ranged between 143 and 237 Bq/kg with a 183 Bq/kg mean value. This shows that the Ra-226 content in case of the 15 examined samples is clearly higher than the worldwide median 32 Bq/kg value of the soil but it is common, compared to other radiological surveys of red mud (3, 5, 6).

Figure 3: Ra-226 activity concentration of the red mud samples Radon emanation The radon activity concentration was calculated with equation achieved the secular equilibrium. A Ra − 226 =

I − Bg F×e

− λt

× μ × t '×m × 3

(1)

after the samples (1)

Where ARn-222 is the radon activity in 1 kg sample (Bq/kg), I is the counts of the sample, Bg is the background counts, F is the counting efficiency of the cell, t is the


69

elapsed time from the sampling (s), μ is the efficiency of sampling, t’ is the measurement time, m is the weight of the sample (kg), and 3 is the radon and its progenies alpha correction factor. The radon emanation factor is calculated with equitation (2). ε=

A Rn −222 A Ra −226

(2)

Where ε is the emanation factor, ARn-222 is the amount of the released Rn-222 activity into the pore space in 1 kg sample (Bq/kg), and ARa-226 the Ra-226 is the activity concentration of the sample (Bq/kg). The results of the radon emanation power measurement are represented in Figure 4 where the effects of the absorbed water content on the emanation coefficient can be clearly observed. The emanation factor in case of the dry sample was 7.6 % and till ~20 % moisture content the emanation is increasing. This section demonstrates the recoiled radon stopping power of the pore water. The initial emanation value multiplied up to three times higher and reached a saturation value at 20 % moisture content. Over the saturation/maximum value a great descending tendency can be statable as a reason of the diffusion inhibition effect of the pore water. The higher water content (over 28 %) does not make the red sludge samples suitable to measure the emanation coefficient.

Figure 4: Emanation coefficient function of moisture content Radon exhalation In the exhalation chamber where the samples were enclosed the activity concentration was increasing during the accumulation time. The inhibition effect of the thickness for the diffusion length was determined with dry red mud. The results can be seen in the Figure 5. From 1 cm to 6 cm the specific exhalation is presumably constant. In case of 100 mm sample thickness the specific exhalation (mass standardized) decreased to ~60 % of the original value. Therefore it can be stated that the 60 mm is the optimal sample height if we take into consideration the amount of the emanated and exhaled radon according to the sample weight and diffusion interruption. The subsequent

70


experiments were executed with maximum 50–60 mm sample height where the specific exhalation is constant.

Figure 5: Specific (mass standardized) exhalation as function of sample thickness Figure 6 illustrates the given results of exhalation dependency as function of moisture content. The specific exhalation expressly increases with the water content up to ~20 % according to the emanation power changing.

Figure 6: Specific radon exhalation as function of moisture content In Figure 7 the emanation factor and the specific exhalation rate are illustrated in function of moisture content simultaneously. Due to the given results a saturation value can be perceptible in case of the exhalation, (which depends on the diffusion rate in water). Figure 7 clearly shows the specific exhalation correlated with the emanation coefficient. The increment of the exhalation rate is approximately linear as a function of emanation coefficient.


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Figure 7: Emanation coefficient vs. specific exhalation Conclusion The Ra-226 content of the measured red sludge samples is higher than the world average in soil, the given results are not unusual if them compared with red mud samples from different countries. The dependency of the emanation coefficient as a function of moisture content was examined. The given results clearly proved that the moisture content of the pore space increases the emanation coefficient up to a threshold value as a result of recoil energy absorption. The increment in case of dry samples was three times higher than the initial value. The inhibition effect of the pore water appears after the threshold value where the pore water generates contiguous layers, which disrupts the diffusion of the released radon. The diffusion length was given constantly up to 6 cm sample thickness. Due to that fact the mass standardized specific exhalation was established to compare the results independently from the thickness and the weight of the measured samples. The tendency of the specific exhalation as a function of moisture content has the same tendency as the emanation coefficient. The dependency is approximately linear.

Acknowledgements Present publication was realized with the support of the project TÁMOP-4.2.2/B10/1-2010-0; and was supported by the Hungarian Science Foundation (OTKA Grant No. K 81975 and K 81933).

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References 1. M. Y. Menetrez, R. B. Mosley: Evaluation of radon emanation from soil with varying moisture content in a soil chamber. Environment International, 22(1), 447–453, (1996) 2. H. Sun, D. J. Furbish: Moisture content effect on radon emanation in porous media. Journal of Contaminant Hydrology, 18(3), 239–255, (1995) 3. V. Jobbágy, J. Somlai: Dependence of radon emanation of red mud bauxite processing wastes on heat treatment. Journal of Hazardous Materials, 172(2–3), 1258–1263, (2009) 4. P. Tuccimei, M. Moroni: Simultaneous determination of 222Rn and 220Rn exhalation rates from building materials used in Central Italy with accumulation chambers and a continuous solid state alpha detector: Influence of particle size, humidity and precursors concentration. Applied Radiation and Isotopes, 64(2), 254–263, (2006) 5. United Nations Scientific Committee on the Effects of Atomic Radiation: UNSCEAR 2008, Sources and Effects of Ionizing Radiation. Annex B, New York, (2010) 6. A. Akinci, R. Artir: Characterization of trace elements and radionuclides and their risk assessment in red mud. Materials Characterization, 59(4), 417–421, (2008)

A radoninhaláció biofizikai hatásainak kvantitativ leírása

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A RADONINHALÁCIÓ BIOFIZIKAI HATÁSAINAK KVANTITATÍV LEÍRÁSA Balásházy Imre1, Farkas Árpád1, Szőke István1, Madas Balázs Gergely1, Kudela Gábor2 1

Magyar Tudományos Akadémia KFKI Atomenergia Kutatóintézet, Budapest 2 Eötvös Loránd Tudományegyetem, Informatika Kar, Budapest

Abstract Histological studies performed on lungs of former uranium miners have demonstrated strong correlation between the locations of primary airway deposition hot spots, located along the carinal regions of large bronchial airways, and neoplastic lesions. In the present work, a stochastic whole respiratory tract model and a computational fluid dynamics (CFD) approach have been applied to simulate deposition distributions of inhaled radon progenies in the whole respiratory system, and within the central human airways, respectively. The computed deposition patterns were then applied to describe local microdosimetric and biological processes within a computerised model of the bronchial epithelium, based on anatomical data. A simple biophysical model, the so called triggering – response approach and a mutagenesis model have been coupled with the CFD methods to calculate probabilities of alpha-hit, cellular dose, cell death, cell transformation and mutation. Distribution of the cellular radiation dose revealed that some cells and cell clusters may receive high doses, even at low exposure level, due to the high inhomogeneity of radio-aerosol deposition. In the hot spots, the rate of mutation originating from cell cycle shortening, caused by the large number of inactivated cells, can be significantly higher than that caused by direct alpha-hits.

Bevezetés Az ionizáló sugárzás kis dózisai legjelentősebbnek ismert biológiai hatása a rák betegség kialakulása, mely kis valószínűséggel és csak évek múlva jelentkezhet. E daganatos betegség esetleges kialakulását sztochasztikus folyamatként írja le a sugárbiológia és a sugárvédelem. A késői hatás és a kis valószínűségek miatt, az ionizáló sugárzás okozta rák mechanizmusának leírása, valamint a besugárzás dózisához kapcsolódó halálozási kockázatnak a jellemzése igen nehéz feladat és évtizedek óta a sugárbiológia és a sugárvédelem alapkérdéseiként ismertek. A lineáris küszöb nélküli dózis–hatás összefüggés, az LNT (Linear Non-Threashold) hipotézis a kis dózisok tartományában az egyik legvitatottabb kérdés e tudományterületeken. Kis dózisnak ma a 100 mSv effektív dózis alatti terheléseket nevezik. A téma fontosságát jelzik a következők: Az ionizáló sugárzás szerepe, a megnövekedett orvosi, technikai és ipari alkalmazások miatt az utóbbi évtizedben jelentősen erősödött. Az ionizáló sugárzásnak kitett populáció is növekedett. E sugárzások biológiai és egészségügyi hatásainak minél pontosabb ismerete – a sugárzás elleni védekezés tervezése és az esetleges irreális félelmek elkerülése miatt –

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Balásházy I., Farkas Á., Szőke I., Madas B. G., Kudela G.

az atomenergetikának is egyik fontos elemévé vált. Számos jelentős sugárvédelmi szervezet például az ICRP (International Commission on Radiological Protection), az UNSCEAR (United Nations Scientific Committee on the Effects of Atomic Radiation), az NCRP (National Council on Radiation Protection and Measurements) álláspontja szerint az emberiség közel egy százaléka a radon-leányelemek belégzése okozta tüdőrákban hal meg. Ugyanakkor ezen állítást számos kutató kétségbe vonja, mert publikációk ezrei utalnak az ionizáló sugárzás kis dózisai pozitív, azaz hormetikus biológiai hatásaira. Az emberi egészségre gyakorolt hatás minél pontosabb ismerete sürgős mind a sugárzásnak kitett emberek, mind a szabályozó hatóságok számára. E témakör az Európai Unió kiemelt kutatási témái közé tartozik. Az ionizáló sugárzás kis dózisai emberi egészségre gyakorolt hatása többféle módszerrel vizsgálható, de mindegyik módszer körül komoly nehézségek merülnek fel. A humán kísérletekkel etikai gondok adódnak. Az állatkísérletek emberre vonatkozó extrapolálhatósága kérdéses, és e kísérletek szintén etikai problémákat vonhatnak maguk után. Az epidemiológiai tanulmányok a biológiai folyamatok mechanizmusairól gyakorlatilag semmit sem mondanak, nem adnak megfelelő választ az LNT hipotézis kérdésére, mert túl sok, a biológiai hatást befolyásoló paraméter keveredik bennük, és sokszor a statisztika sem elegendően nagy. Egyelőre úgy tűnik, hogy leginkább egy, az összegyűlt in vitro, orvosi és epidemiológiai információkat egyesítő, komplex tüdőrák-keletkezési modell járhat majd sikerrel e tématerületen. A radon-leánytermékek okozta tüdőrák kialakulását a következő okok miatt választottuk elemzésünk tárgyául: A kis terhelések dózis–hatás összefüggését egyrészt ott érdemes tanulmányozni, ahol a legtöbb az adat, ez az ionizáló sugárzásokra vonatkozóan a radonleányelemek okozta tüdőráknál valósul meg. Másrészt olyan sugárbiológiai hatást érdemes vizsgálni, amely jelentős és lehetőleg lokális biológiai elváltozást okoz. Ilyen az alfa-sugárzás. A radon és leányelemei elsősorban alfasugárzással fejtik ki a biológiai reakciót, ezért a radon okozta tüdőrák vizsgálatánál az elemzéshez kiválasztott ezen két szempont találkozik. Harmadszor az emberiség sugárterhelésének, több mint a fele a radon-leányelemektől származik. Ezenkívül hazánk a tüdőrák-statisztikák élén szerepel, azaz az egy lakosra jutó tüdőrákgyakoriság hazánkban a legnagyobb az egész Földön. Az USA Környezetvédelmi Hivatalának álláspontja szerint az USA-ban a dohányzás után a radon a legfőbb tüdőrák-kockázati faktor, nemdohányzóknál és passzív dohányosoknál az első tüdőrákokozó tényező. Évente kb. 21 ezer ember hal meg az USA-ban a radon bomlástermékei okozta tüdőrákban (1, 2). Európában ma minden 10–18. ember hal meg e betegségben, ennek kb. 9 %-a tulajdonítható a radonnak (3). Ez azt jelenti, hogy Európában a lakosság közel 1 %-a a belélegzett radonbomlástermékek áldozata. A radon egy nemesgáz, a légutakban nem ülepszik ki, felezési ideje 3,8 nap és így igen nagy valószínűséggel anélkül halad át egy-egy légúton, hogy közben elbomlana. A leánytermékek azonban elektrosztatikusan töltöttek, nagy valószínűséggel vízmolekulákhoz és részecskékhez tapadnak és így kiülepedhetnek a légutak falára. Egyszerű számításokkal belátható, hogy a radon-


75

leányelemek centrális légúti sugárterhelése több mint két nagyságrenddel nagyobb, mint a belélegzett radon gázé. A radon-leánytermékek közt béta-sugárzó is van. A béta-sugárzás ionizáló képessége három nagyságrenddel kisebb, mint az alfa-sugárzásé, ezért biológiai hatását számításainkban egyelőre elhanyagoltuk. A bystander hatás (szomszéd hatás) miatt azonban tervezzük, hogy ezzel a témakörrel is foglalkozzunk majd.

A radon-leánytermékek teljes légzőrendszeri depozícióeloszlása Az uránbányászok tüdejének szövettani tanulmányozása arra mutat, hogy erős a korreláció a radon-leánytermékek primer légúti depozícióeloszlása és a neoplasztikus (rákos) sejtsérülések térbeli eloszlása között. A pre-neoplasztikus és a neoplasztikus sejtsérülések zöme, valamint a hisztológiai elemzések alapján becsült tüdőrákkeletkezési régiók nagy része, a 3–5. légúti elágazások csúcsainak környezetében (az úgynevezett karina régiókban) helyezkednek el. Ha a cél a rákkialakulás folyamatainak leírása, akkor a terhelés eloszlását legalább a rák kialakulását alapvetően meghatározó paraméterek eloszlásának jellemző mérettartományában érdemes leírni. Ez a mai sugárbiológia szerint valószínűleg a sejtmag, a sejt, vagy a sejtkörnyezet szintje. Természetesen lehetséges, hogy ez nem elegendő, és a sejten, vagy a sejtmagon belüli folyamatoknak van kulcsszerepe a rák kialakulásában. Mivel azonban a depozíciós forró területek mérete jóval nagyobb, mint a sejtek mérete, ezért még ez esetben is elegendő, ha e forró területek terheléseloszlásának főbb paramétereit határozzuk meg, mert abból már Monte Carlo módszerrel modellezhetők a sejten belüli terhelések vagy alfa-találatok. A sejtszintű terhelések eloszlásainak meghatározása nélkül nemigen várható áttörés e szakterületen. A radon-leánytermékek kiülepedéseloszlása ugyanis erősen inhomogén a centrális légutak felülete mentén, és így az átlagterhelés nem sokat mond a sejtszintű folyamatokra vonatkozóan. Az aeroszol részecskékre ki nem tapadt radon-leánytermékek átmérője kb. 1 nm. Ez a leánytermék ionja és az ahhoz adszorbeálódott néhány vízmolekula méretét jelenti. A részecskékre kitapadt frakció leggyakoribb átmérője gyakorlatilag megegyezik a levegőben lévő aeroszol részecskék szám szerinti eloszlásának leggyakoribb átmérőjével, amely aerodinamikai ekvivalens átmérőben kb. 200 nm (4). Ha a sztochasztikus tüdőmodellel (5) a teljes és a regionáli radonleánytermék kiülepedéseloszlását a ki nem tapadt és a kitapadt frakciókra meghatározzuk, akkor könnyű fizikai munkának megfelelő légzés esetén felnőtt emberre az 1. ábrán látható eloszlásokat kapjuk.


76 100

Kiülepedett rész (%)

90

1 nm

80

200 nm

70 60 50 40 30 20 10 0 felső légúti

bronchiális

pulmonáris

összes

(orr, száj, garat, gége)

Könnyű fizikai munkának megfelelő légzés

1. ábra: A sztochasztikus tüdőmodellel számolt kitapadt és ki nem tapadt radonleányelemek regionális és teljes légzőrendszeri kiülepedéseloszlása, könnyű fizikai munkának megfelelő légzés esetén, felnőtt emberre vonatkozóan Mint várható volt, a ki nem tapadt hányad kiülepedési valószínűsége jóval nagyobb, kivéve a mély (pulmonáris) régióban, ahová alig jutnak le e részecskék, mert diffúzió révén már kiülepedtek a légzőrendszer feljebb lévő szakaszaiban. Megjegyzendő, hogy, ugyan a ki nem tapadt frakció kiülepedési valószínűsége nagyobb a bronchiális régióban, mint a kitapadté, ez nem jelenti azt, hogy ezeknek a bronchiális légúti terhelése nagyobb, mert az uránbányák és a lakások levegőjében legfeljebb csak néhány százalék a ki nem tapadt hányad. Ezenkívül a ki nem tapadt részecske nagy valószínűséggel csak 218Po lehet, aminek alfa-energiája kisebb, az alfa-nyoma pedig rövidebb, mint a 214Po-é. A rövidebb alfa-nyom kisebb valószínűséggel éri el a bazális sejteket. Az természetesen igaz, hogy a 218Po-ból 214Po lesz, és így a kisebb energiájú alfa-nyomot egy nagyobb energiájú fogja követni kb. ötven perccel később. Az 1. ábráról még nem látható, hogy miért a centrális légutakban alakul ki a radonleányelemek előidézte tüdőrák. Ez egyben arra is rámutat, hogy az egész légzőrendszeri tüdő- és mikrodozimetriai modellek nem igazán alkalmasak sem a biofizikai, sem a biológiai folyamatok vizsgálatára, sem kockázatbecslésre. Ha a sztochasztikus tüdőmodellel kapott légúti generációnkénti depozíciós frakciót elosztjuk az adott generáció felületével, azaz generációnkénti depozíciósűrűséget számolunk, akkor a nagy centrális légutaknál éles terhelés maximumot kapunk (2. ábra). Ez azt mutatja, hogy már a légúti generációkra átlagolt terhelés is maximumot ad a 3–5. generációknál, éppen ott, ahol a korai uránbányászoknál a neoplasztikus sejtsérüléseket kimutatták.

Felületegységre kiülepedett rész (%)/cm2


77

0.030 0.025

bronchialis

0.020

acinaris 0.015 0.010 0.005

0

5

10

15

20

25

30

Generációszám

2. ábra: A légúti generációnkénti átlagos depozíciósűrűség eloszlása kitapadt radonleányelemek esetében könnyű fizikai munkának megfelelő légzésnél Ahhoz, hogy a sejtszintű terheléseloszlást meghatározhassuk, háromdimenziós tüdőgeometriára és numerikus áramlástani számításokra van szükség. E számítási módszer lehetővé teszi az adott feladathoz megfelelő pontosságú radonleányelemkiülepedéseloszlás meghatározását.

Inhalált radon-leánytermékek sejtszintű kiülepedéseloszlásának leírása Az inhalált radonszármazékok légúti lokális kiülepedését numerikus levegő- és részecskeáramlási számításokkal érdemes manapság meghatározni. E CFD (computational fluid dynamics, azaz numerikus áramlástani) módszerek a transzportegyenletek numerikus megoldásán alapulnak, és az áramlási térre jellemző paraméterértékeket a választott geometriának (itt a légutak geometriájának) kis térrészeire adják meg. A radon-leányelemek egészségre gyakorolt hatásának tanulmányozásakor célszerű e térrészt a sejtkörnyezet méretével összemérhető nagyságúnak venni. Az inhalált radionuklidok kiülepedéseloszlásának numerikus áramlástani módszerrel történő szimulációja magába foglalja a háromdimenziós légutak geometriájának digitális rekonstrukcióját és térdiszkretizációját (behálózását), a légúti levegőáramok áramlási terének meghatározását, a radioaktív részecskék légúti trajektóriáinak és kiülepedési helyeinek pontos meghatározását, valamint a kiülepedéseloszlás kvantifikálását. A biológiai hatás pontos leírásának alapvető előfeltétele a morfológiailag minél realisztikusabb, háromdimenziós légutak számítógépes megszerkesztése. E területen két fő leírásmód létezik: (i) mért morfometriai adatokon alapuló, matematikailag nagyjából egzaktul definiált felületeket tartalmazó, idealizált geometriák létrehozatala; (ii) orvosi képalkotó módszerekkel felvett rétegfelvételeken alapuló geometriák


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szerkesztése. Mindkét módszernek léteznek előnyei és hátrányai is. Az első eljárással készült geometriák főbb előnyei, hogy reprodukálhatók és viszonylag könnyen behálózhatók. A CT (komputertomográf), vagy MR (mágneses rezonancia) alkalmazásával készített kétdimenziós metszeteken alapuló háromdimenziós légúti felületek realisztikusabbak, de az orvosi képalkotó eszközök mai felbontóképessége mellett csak a nagyobb légutak, azaz a felső légutak és a nagyobb bronchusok geometriája rekonstruálható, és e geometriák berácsozása is bonyolult. Ilyen módon előállított centrális légúti geometriát mutat a 3. ábra.

szegmentális hörgők

jobb főhörgő jobb felső lebenyhörgő szubszegmentális hörgők

bal főhörgő

közbeeső hörgő

jobb középső lebenyhörgő jobb alsó lebenyhörgő

3. ábra: A centrális légutak egy részének digitálisan rekonstruált 3D geometriája és fontosabb anatómiai elemei Ahhoz, hogy levegőáramlást és részecskedepozíciót számíthassunk a légutakban, a geometriát térdiszkretizálni szükséges. Ez megfelelő numerikus háló generálását jelenti. Tetraéderes nem strukturált rácsot hoztunk létre, melynek cellái közel szabályosak voltak. A berácsozott geometriában numerikus levegőáramlási számításokat végeztünk a FLUENT CFD kereskedelmi kóddal, majd 1nm és 200 nm aerodinamikai átmérőjű részecskék kiülepedéseloszlását határoztuk meg alvó és nehéz fizikai munkának megfelelő légzési módok mellett, ugyanezen FLUENT CFD programcsomaggal. Az első a ki nem tapadt radon-leányelemek az utóbbi a kitapadt radon-leányelemek kiülepedéseloszlását modellezte. A 4. ábra a ki nem


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tapadt hányad kiülepedéseloszlását mutatja be két légzési mód mellett. A számítások és az ábra tanúsága szerint még az 1 nm átmérőjű részecskék depozícióeloszlása is erősen inhomogén.

4. ábra: Ki nem tapadt (1 nm átmérőjű) radon-leánytermékek inhaláció alatti kiülepedéseloszlása pihenésnek (bal panel) és nehéz fizikai munkának (jobb panel) megfelelő légzési módok mellett Mikrodozimetriai számítások és a biofizikai hatások modellezése A radon-leányelemekből származó sejtszintű terhelés meghatározásához a numerikus áramlástani modelljeinkhez illeszkedő sztochasztikus mikrodozimetriai modelleket dolgoztunk ki. Az alfa-részecskék nyomvonalait a különböző energiájú alfa-részecskék levegőben és lágy testszövetben érvényes hatótávolságaira vonatkozó irodalmi adatok segítségével határoztuk meg. Az 5. ábra így számított alfa-nyomokat ábrázol a 4–5. légúti generáció egy idealizált geometriáján. A rákkeletkezést meghatározó folyamatok lokális, sejtszintű, jellege miatt szükségszerű az epithelium sejtszerkezetének háromdimenziós numerikus előállítása. Irodalmi adatok (6, 7) alapján modelleztük a hámszövet sejt- és sejtmagszerkezetét, hogy kiszámíthassuk a centrális légutak hámszövetét felépítő jellemző sejttípusok sejtjeinek és sejtmagjainak terhelését.

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5. ábra: A lument átszelő faltávoli alfa-nyomok (sárga vonalak) és közvetlenül a szövetbe hatoló falközeli alfa-nyomok (piros vonalak) egy 4–5. légúti generációnak megfelelő idealizált geometriájú elágazásban. A kinagyított képen a nyomvonalaknak a szövetbe hatoló szakaszai láthatók Meghatároztuk a sejtmagok és a sejtek egyszeres és többszörös találati valószínűségét. Jellemeztük a sejtmag- és a sejtdózisok eloszlását. Megállapítottuk, hogy a centrális légutak felülete mentén, homogén aktivitáseloszlást feltételezve – mint ahogy a mai mikrodozimetriai és rákkeletkezési modellek számolnak – a kisdózis-tartományban gyakorlatilag nincs többszörös sejtmag- vagy sejttalálat, és a többszörös találat valószínűsége lineárisan nő a dózissal. Ezekkel ellentétben, realisztikus kiülepedéseloszlás esetén a légúti elágazások csúcsaiban előforduló, úgynevezett forró depozíciós területeken gyakorlatilag minden sejt többszörös találatot kap, ha a centrális légúti átlagos sejtdózis 10 mGy feletti, ezenkívül a többszörös találatok valószínűsége messzemenően nem lineárisan nő a dózissal e terhelés tartományban. Ez azt jelenti, hogy már az úgynevezett kisdózis-tartományban is összefüggő sejtterületeket érhetnek nagy dózisok. E területek mérete a centrális légutak elágazásainak csúcsaiban néhány vagy néhányszor tíz négyzetmilliméter, ami már a kisdózis-tartományban is szövetszintű károsodást jelenthet. Megvalósítottunk egy összetett sugárbiológiai modellt a radoninhaláció fenti mikrodozimetriai modelljének, valamint a sejthalál és a sejttranszformáció úgynevezett „jelzés-válasz” modelljének (8) integrálásával. Külön jellemeztük a direkt és a bystander hatásokat. Megállapítottuk, hogy a sejthalál és a sejttranszformáció valószínűségeinek eloszlása térben erősen inhomogén, és értékük a légúti elágazások csúcsaiban az átlaghoz képest nagy. Az eredmények szerint a bystander hatástól elhalt és még inkább a bystander hatástól transzformálódott sejtek száma nagyobb, mint a primer hatástól elhalt, illetve transzformálódott sejtek mennyisége (6. ábra). Itt meg kell jegyeznünk,


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hogy a „jelzés-válasz” modellben in vitro sejtkísérletekből kapott adatok kerültek alkalmazásra és a bystander hatás lényegesen eltérhet in vitro és in vivo esetekben.

6. ábra: Átlagos sejthalál (bal panel) és sejttranszformáció (jobb panel) valószínűségek változása az új-mexikói uránbányában eltöltött idő függvényében. A jobboldali panel a direkt hatást nem ábrázolja, mert annak mértéke két nagyságrenddel kisebb, mint az indirekt (bystander) hatásé Alfa-találati valószínűséget, sejtdózist, sejthalált és sejttranszformáció valószínűséget határoztunk meg az új-mexikói uránbányában eltöltött 12,3 órás terhelés esetében könnyű fizikai munkának megfelelő légzésnél felnőtt férfire (7. ábra). Csak a belégzés alatti terhelés lett figyelembe véve. A számítási eredmények szerint a bystander sejthalál 3-5-ször gyakoribb, mint a közvetlen sejthalál, és a bystander sejttranszformáció valószínűsége több mint két nagyságrenddel nagyobb, mint a direkt sejttranszformációé. Az in vitro adatokon nyugvó irodalmi „jelzés-válasz” modellben a bystander effektus hatótávolsága 1 mm, ami in vivo körülmények között lényegesen különböző lehet és így a bystander effektus mértéke is különbözhet. A 7. ábra jobb alsó panelje szerint az elágazás csúcsában gyakorlatilag nincs sejttranszformáció, ugyanis ott szinte minden sejt elhalt. Ez látszólag ellentmond annak a tapasztalatnak, hogy a radonleányelemek okozta neoplasztikus sérülések leggyakrabban az elágazások csúcsaiban fordulnak elő. A fenti modell azonban figyelmen kívül hagyja, hogy a sejtpusztulás önmagában növeli a szövetre jellemző átlagos mutációszámot. A magas sejtpusztulási gyakoriság ugyanis hosszú távon megnövekedett sejtosztódási gyakoriságot eredményez, hiszen a szövet csak úgy képes ellátni a feladatát, ha a sejtszám csupán korlátozott mértékben tér el a normál értéktől.


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találati valószínűség

sejtdózis

direkt sejthalál

bystander sejthalál

direkt transzformáció

(Gy)

bystander transzformáció

7. ábra: Találati valószínűség (bal felső panel), átlagos sejtdózis (jobb felső panel), sejthalál valószínűség (középső panelek) és sejttranszformáció valószínűség (alsó panelek) eloszlása a 4–5. generációban könnyű fizikai munkának megfelelő, 12,3 órás, az új-mexikói uránbányában eltöltött terhelés esetén, csak belégzésre Az adott sejtben felhalmozódott mutációk száma arányos azoknak az osztódásoknak a számával, amelyeken a sejt korábban „átesett”, a magasabb sejtosztódási gyakoriság nyomán megnövekszik az egységnyi idő alatt kialakult mutációk száma is. Számításaink szerint a krónikus és sűrűn ionizáló sugárzásból származó terhelés elsősorban így járul hozzá a szövet sejtjeiben kialakult mutációk számához, nem pedig azáltal, hogy közvetlen DNS sérüléseket okoz. Ezt a jelenséget részletesen elemeztük egy most megjelent cikkben (9).


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Következtetések Az inhalált radon-leányelemek légzőrendszeri kiülepedésének több nagyságrendbeli inhomogenitása azt eredményezi, hogy vannak olyan sejt-környezetek, amelyek már az úgynevezett kisdózis-tartományban (100 mSv effektív dózis alatt) is igen nagy dózisokat kapnak. Nem igaz az a korábbi irodalmi állítás, miszerint a természetben csak kis dózisokban érheti az emberi szöveteket alfa-sugárzás. Ebből az is következik, hogy a radoninhaláció biológiai hatását és leíró biofizikai modelleknek a nagy dózisok biológiai hatásait is tudniuk kell jellemezni (10, 11). A kis dózis tartományon belül is vannak olyan szövettartományok a centrális légutak csúcsaiban, amelyekben a terhelés nagyfokú inhomogenitása miatt jelentős mértékű sejthalál következik be. Ez a környező osztódásra képes sejtek sejtciklusának megrövidülése miatt fokozott mértékű mutációt eredményez és hiperpláziához vezethet. Hosszan tartó ilyen terhelés az onkogén mutációk megnövekedett valószínűsége miatt rák kialakulását is előidézheti. Valószínűleg meghatározható lesz, hogy a hosszú idejű és nagymértékű sejthalál az úgynevezett forró depozíciós területeken milyen terhelés értékek felett eredményez szövetváltozást, azaz „determinisztikus” hatást. E folyamatba a terhelés ideje is beleszól, ezért itt nem beszélhetünk küszöbdózisról, hanem csak valamiféle küszöb dózisintenzitásról. Ennek értéke nyilván számos paramétertől függ, például a nyák vastagságától, a mukociliáris tisztulástól, a légzési módtól. Ami biztosan nem várható az az ionizáló sugárzás adott kis dózisainak egy-egy meghatározott értékkel jellemzett kockázata, ugyanis a kis dózis tartományban a kockázat a dózison kívül még számos egyéb paramétertől is függ. Ha a dózist csökkentjük, akkor egy adott érték alatt az egyéb paraméterek hatásai mellett a dózis szerepe kezd elhanyagolhatóvá válni. Ezenkívül nem szabad figyelmen kívül hagynunk, hogy a későn jelentkező hatásoknál, így például a rákbetegség esetében, a kockázat a dózison kívül, nemcsak a besugárzás adataitól és az emberi szervezet terhelés idejére vonatkozó paraméter értékeitől függ, hanem számos a terhelést követő – az emberi szervezetet ért – történéstől is. Így elvben sem létezik a dózis-hatást leíró egyetlen görbe. A biológiai hatást csak egy igen sokdimenziós felület írhatja le. E kutatásoktól azt várjuk, hogy belátható időn belül további hasznos adatokat nyújtanak a sejttalálatok, a sejtmag- és a sejtdózisok, a sejthalál, a mutációk, a sejttranszformáció és számos egyéb mikrodozimetriai és sugárbiológiai paraméter értékére a terhelés függvényében a legkisebb dózisoktól az igen nagy dózisokig. Ezenkívül ezen adatok segítenek az ionizáló sugárzás biológiai hatásainak megértésében és az egészségre gyakorolt hatás folyamatainak leírásában. Terveink szerint a légúti levegőáramlási és aeroszol depozíciós eredményeink a közeljövőben kísérleti berendezéseink (12, 13) validálásra kerülnek

Köszönetnyilvánítás A kutatást az OTKA K61193, valamint az ETT 317-08 projektek támogatták.

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Felhasznált irodalom 1. R. W Field: A Review of Residential Radon Case-Control Epidemiologic studies Performed in the United States. Reviews on Environmental Health 16, 3, (2001) 2. EPA: Assessment of risks from radon in homes. United States Environmental Protection Agency, Air and radiation 6608J, EPA 402-R-03-003, Washington, DC, (2003) 3. S. Darby, D. Hill, A. Auvinen, J.M. Barros-Dios, H. Baysson, F. Bochiccio, H. Deo, R. Falk, F.Forastierre, M. Hakama, I. Heid, L. Kreinbrock, M. Kreuzer, F. Lagarde, I. Mäkeläinen, C. Muirhead, W. Oberaigner, G. Pershagen, A. Ruano-Ravina, E. Ruosteenoja, A. Schaffrath Rosario, M. Tirmarche, L. Tomášek, E. Whitley, H. E. Wichmann, R Doll.: Radon in homes and risk of lung cancer: collaborative analysis of individual data from 13 European case-control studies. British Medical Journal 330, 223–226, (2004) 4. T. Haninger: Size distributions of radon progeny and their influence on lung dose. Radon and Thoron in the Human Environment, Proceedings of the 7th Tohwa University International Symposium, Editors: A. Katase and M. Shima, World Scientific: Singapore, (1997) 5. L. Koblinger, W. Hofmann: Monte Carlo modeling of aerosol deposition in human lungs. Part I: Simulation of particle transport in a stochastic lung structure. Journal of Aerosol Science, 21, 661–674, (1990) 6. R. R. Mercer, L.R. Michael, D. C. James: Radon dosimetry based on the depth distribution of nuclei in human and rat lungs. Health Physics 61, 117–30, (1991) 7. R. R. Mercer, L.R. Michael, V. L. Roggoli, D. C. James: Cell number and distribution in human and rat airway. American Journal of Respiratory Cell and Molecular Biology 10, 613–624, (1994) 8. H. Fakir, W. Hofmann, W. Y. Tan, Sachs R.K.: Triggering-response model for radiation-induced bystander effects. Radiation Research, 171, 3, 320–331, (2009) 9. B. G. Madas, I. Balásházy: Mutation induction by inhaled radon progeny modeled at the tissue level. Radiation and Environmental Biophysics 50, 553–570, DOI 10.1007/s00411-011-0382-9, (2011) 10. I. Balásházy, W. Hofmann, Á. Farkas, I. Szőke: Modelling carcinogenic effects of low doses of inhaled radon progenies. Journal of Radiological Protection 22, A89–A93, (2002) 11. I. Balásházy, Á. Farkas, B.G. Madas and W. Hofmann: Non-linear relationship of cell hit and transformation probabilities in low dose of inhaled radon progenies. Journal of Radiological Protection 29, 147–162, (2009) 12. A. Kerekes, A. Nagy, A. Czitrovszky, D. Oszetzky: Air flow measurements with a realistic transparent hollow airway model. Proceedings, 18th International Conference on Advanced Laser Technologies. September 09-16. Holland, 134–135, (2010) 13. A. Kerekes, A. Nagy, A. Czitrovszky, D. Oszetzky: Airflow experiments with hollow bronchial airway model. International Aerosol Conference. 2010 August 29 September 03. Helsinki, Finland. P1F4, (2010)

Radonviszonyok a Markhot Ferenc Kórház új fürdőjében

RADONVISZONYOK A MARKHOT FERENC KÓRHÁZ ÚJ FÜRDŐJÉBEN Deák Eszter1, Nagy Katalin1, Kávási Norbert2,3, Kobayashi Yosuke3, Kovács Tibor4, Berhés István5, Bender Tamás6, Vaupotič Janja7, Yoshinaga Shinji3, Yonehara Hidenori3 1

Markhot Ferenc Kórház, Reumatológia Osztály, Eger Radioökológiai Tisztaságért Társadalmi Szervezet, Veszprém 3 Research Center for Radiation Protection, National Institute of Radiological Sciences, Chiba, Japan 4 Pannon Egyetem, Radiokémiai és Radioökológiai Intézet, Veszprém 5 Markhot Ferenc Kórház, II. számú Belgyógyászat, Eger 6 Budai Irgalmasrendi Kórház, Budapest 7 Department of Environmental Sciences, Radon Center, Jožef Stefan Institute, Ljubljana 2

Összefoglalás 2009 májusában került átadásra az egri Markhot Ferenc Kórház Reumaosztályának új fürdőkomplexuma, melyben évi 1400 fekvő és több ezer járóbeteg balneoterápiás kezelése folyik. Az új fürdőterápiás részleg a következő medencékből épül fel: radon terápiás medence, amely vizét a Török Fürdő Pezsgő medencéjének forrásából kapja, kénes medence, amely a vizét az AT 10 forrásából kapja, súlyfürdő medence, illetve egyéni tornához használatos 2 medence, amelyekben vízvisszaforgatással kezelt víz van. Munkánk során 7 napon keresztül, napi háromszori mintavétellel ellenőriztük a radon terápiás medence radon tartalmát, illetve a légtéri radon koncentráció óránkénti változását a fürdőterápiás részleg négy pontján, a tangentor szobában, a radon terápiás medence mellett, egy alagsori masszőrszobában, és egy első emeleti orvosi vizsgálószobában. A radon terápiás medence vizének vizsgálata során a radon koncentráció változásában periodikusság nem volt megfigyelhető, a vizsgálatunk ideje alatt az átlag 69 Bq/dm3, a maximum 76 Bq/dm3, a minimum radon koncentráció pedig 59 Bq/dm3-nek adódott. A légtéri radon koncentráció átlaga a radon terápiás medencénél 129 Bq/m3, a maximum 268 Bq/m3, a minimum 8 Bq/m3 volt a vizsgálatunk alatt. Ugyanez a tangentor szobában 106 Bq/m3, 416 Bq/m3 és 7 Bq/m3, a masszőrszobában 62 Bq/m3, 202 Bq/m3 és 5 Bq/m3, az orvosi vizsgálószobában pedig 61 Bq/m3, 195 Bq/m3 és 13 Bq/m3 volt. Méréseink arra irányultak, hogy felmérjük az új fürdőben a légtér és a víz radonviszonyait, részben a terápiás körülmények pontos ismerete, részben az ott dolgozók sugárvédelmi szempontjainak megállapításához.

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Deák E., Nagy K., Kávási N., Kobayashi Y., Kovács T., Berhés I., Bender T., Vaupotič J., Yoshinaga S., Yonehara H.

Bevezetés Radonterápia az Egri Török Fürdőben Eger egyik legnagyobb természeti kincse a föld mélyéből előtörő radioaktív hévize. Az egri termálforrások vizét, az ott kialakult meleg vizű tavakat a város népe már ősidők óta használta fürdésre. A fürdő működését már az 1448-ból származó középkori oklevél is tanúsítja Karthauzi Fürdő néven, mint „Balneum Carthusiensium” (1). Gorové László, Eger történeteiben azt írja: „a fürdők jóval a törökök bejövetele előtt már használtattak...” (2). A fürdő legjelentősebb korszaka a török hódoltság alatti felvirágzás volt. 1610 és 1617 között épült a ma is látogatható Török Fürdő elődje, Arnaut Pasa fürdője, melynek forrása radontartalmú gyógyvíz. 1934-ben Bárány Géza és Frank Tivadar városi tanácsnok munkájának eredményeképpen az akkori belügyminiszter véglegesen gyógyvízzé, illetve gyógyfürdővé minősítette a fürdőt. 1965-ben a fürdő épületéhez dél felől, úgynevezett nyaktaggal 25 ágyas reumakórház csatlakozott, létrehozva az első olyan kórházi létesítményt, mely a modern reumatológia és balneológia követelményeinek megfelelően az egri gyógyvíz orvosi felhasználására épült (3). 1979-ben új terápiás egységekkel bővülve megnyílt a Heves megyei kórház egri reumatológiai osztályának átépített gyógyfürdője Török Fürdő néven. 2009 májusában került átadásra az új fürdőkomplexum, melyben évi 1400 fekvő és több ezer járóbeteg balneoterápiás kezelése zajlik. Az új fürdőterápiás részleg a következő medencékből épül fel: radon terápiás medence, 31 °C, amely vizét a Török Fürdő Pezsgő medencéjének forrásából kapja, kénes medence, 38 °C, amely vizét az AT 10 forrásából kapja, súlyfürdő medence, illetve egyéni tornához használatos 2 medence, amelyekben vízvisszaforgatással kezelt víz van. Az új létesítményben a radon terápiás medence mellett iszappakolás, súlyfürdő, masszázs, tangentor (víz alatti sugármasszázs), egyéni és csoportos vízalatti torna vehető igénybe.

Terápiás vizek radontartalma Az alkalmazott balneológiai radon terápia sarokpontja a terápiás vízben lévő radon mennyisége. Az 1. táblázatot áttekintve látható, hogy a világon alkalmazott terápiás vizek radon koncentrációja igen széles tartományban mozog, néhány száz, de akár több ezer Bq/dm3 is lehet. Hogy a víz radontartalma mennyiben befolyásolja a terápia végrehajtását (pl. fürdési idő, ismételt fürdések száma stb.) egyelőre nem tisztázott, azt az orvosok általában empirikus úton határozzák meg. Magyarországon jelenleg 37 Bq/dm3 radon szükséges az egyszerű radioaktív gyógyvíz minősítés eléréséhez (4).


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1. táblázat: Különböző országok radonterápiás vizeinek radon-koncentrációja Radonterápia helye Taishan (Kína) Tskhaltubo (Grúzia) Nanshui (Kína) Polichnitos spa (Görögország) Rudas (Magyarország) Badgastein (Ausztria) Bad Steben (Németország) Bad Elster (Németország) Merano (Olaszország) Jachymov (Csehország)

Radon koncentráció [Bq/dm3] 57 101 280 210 339 662 800 1300 2000 4000-4500

A radonnak tulajdonított gyógyhatások A radonfürdő legfőbb indikációs területét a gyulladásos és degeneratív reumatológia kórképek adják. A fájdalomcsillapítás céljából alkalmazott balneoterápiás kezelés során általában 3-4 hétig tartó kúrák alatt a betegek naponta vagy másnaponta töltenek 20-30 percet a radonfürdőben. Egyszeri fürdő hatása nem észlelhető, a hónapokig tartó fájdalomcsillapító hatás csak ismételt, kúraszerű fürdőzésekkel érhető el (5). A relatíve rövid, 20-30 perces fürdési idő alatt a radon a bőr szarurétegeiben rakódik le, itt dózistól függően gátlást fejt ki a bőr Langerhans sejtjeire, melyek az immunrendszerben játszanak fontos szerepet. Lipidoldékonysága révén a test zsírban gazdag szerveiben oszlik el, mint pl. a belső elválasztású mirigyek és az idegrostok, melyeket lipidtartalmú hüvely vesz körül. Fájdalomcsillapító hatását a szervezet saját endorphin termelésének stimulálásával fejti ki. Emellett fokozza a sejtek anyagcseréjét, csökkenti a DNS szintézist, stimulálja a DNS repairt, stimulálja az ivarszervek működését, aktiválja az adrenalin termelést, javítja a kapillarizációt, fokozza a húgysavkiválasztást, radonfürdő után csökken a vérnyomás. Immunrendszere gyakorolt hatása dózisfüggő, a magas sugárdózisok elnyomják, alacsonyabb dózisok stimulálják az immunrendszert. Magasabb radonexpozíció esetén megnő a hörgőrák, a bronchuscarcinomák előfordulási gyakorisága (6). Annak ellenére, hogy a radonterápia hatékonysága régi idők óta ismert, elfogadottsága igen változó. Mivel köztudott, hogy az ionizáló sugárzás rákot és teratogén károsodásokat okozhat, a radont az egyik legveszélyesebb környezeti anyagként tartják számon. A sugárvédelmi szervezetek fenntartják a véleményüket, hogy az ionizáló sugárzásnak nincs küszöbértéke, és a radon nemcsak az uránbányákban jelent egészségre ártalmas kockázatot, hanem relatíve alacsony koncentrációkban is, mint pl. a lakóházakban és a gyógyfürdőkben.

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Szabályozás A radont illetően több nemzetközi, illetve egy magyar szabályozás létezik. A szabályozások különbséget tesznek munkahely és lakóház szerint a megengedhető maximális koncentrációról, illetve éves sugárterhelésről. A magyar szabályozás, az 1996. évi CXVI. Atomenergiáról szóló törvény 16/2000 (VI.8) EüM végrehajtási rendelete, munkahelyekre vonatkozóan 1000 Bq/m3-es radonkoncentráció értéket határoz meg, mint cselekvési szintet (7). Ez 0,4-es egyensúlyi faktor és 2000 óra/év munkaidő esetén 6,3 mSv/év sugárterhelést jelent.

Vizsgálatok, célkitűzések A Török Fürdőben 2003 augusztusától kezdődően végzünk radon méréseket. Mind a vízben, mind a levegőben és a feltörő buborékban megmértünk a radon szintjét, valamint a dolgozókat érintő sugárdózist (8). 2009. július 26-augusztus 1. között az Egészségügyi Minisztérium 2000/16-os végrehajtási rendeletének megfelelően az új terápiás területen is elvégeztük a radon jelenléte miatt megkövetelt sugárvédelmi vizsgálatokat. A vizsgálataink három részből épültek fel: 1. Az új radon terápiás medence radon-koncentrációjának meghatározása (minimális szint 37 Bq/dm3) 2. Az új fürdőkomplexum légtéri radon-koncentráció és egyensúlyi faktor meghatározása sugárvédelmi okokból (cselekvési szint átlagban évi 1000 Bq/m3, ajánlott egyensúlyi faktor 0,4) 3. Munkavégzők radontól származó sugárterhelésének becslése (elfogadható szint: 6,3 mSv/év)

Mérési eszközök, módszerek, számítások Víz radon A vízminták radon tartalmának meghatározása a félvezető detektorral felszerelt RAD7 radon mérőeszközzel történt, a vízminta elemzéshez szükséges kiegészítő felszerelések használatával. A radon terápiás medence radon tartalmát 7 napon keresztül, napi háromszori mintavétellel ellenőriztük. A mintavételek időpontja 7:00, 11:00, és 15:00 órakor volt.

Légtéri radon A légtéri radon koncentráció meghatározásához 7 napon keresztül, 4 darab, félvezető detektorral felszerelt RAD7 radon mérőeszközt használtunk. A mérőeszköz egy beépített folyamatos működésű szivattyú alkalmazásával juttatta a mérendő levegőt a mérőtérbe, aminek óránkénti átlagos radon koncentrációját határozta meg.


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A vizsgálati pontok a következők voltak: 1. radon terápiás medence mellett, 2. medencével egy szintben lévő tangentor szoba, 3. alagsori masszőrszoba és 4. az egyik első emeleti orvosi vizsgálószoba.

Dózisbecslés A belélegzett radontól és leányelemeitől származó sugárterhelés becslése a következő egyenlet felhasználásával történt

E = CRn · F · t · D

(1)

Ahol: E: effektív dózis (Sv) CRn: átlagos radon koncentráció (Bq/m3) F: egyensúlyi faktor t: munkaidő (2000 h) D: munkahelyre vonatkozó ICRP dózis-konverziós tényező (7.9·10-9 Sv/Bqm-3h).

Eredmények Radon koncentráció a terápiás vízben Vizsgálatunk ideje alatt a radon terápiás medence vizének radontartalma 58,7 és 75,9 Bq/dm3 között változott, az átlag 69 Bq/dm3-nek adódott. Változásokra vonatkozó egységes tendencia nem volt megfigyelhető. Ugyanakkor az egri Török Fürdő korábban vizsgált pezsgő-medencéjének átlagos radon koncentrációja közel 30 Bq/dm3-el haladja meg a most mért értékeket, ami arra utal, hogy az innen átvezetett terápiás víz szállítás közben veszít radon tartalmából, de még a szükséges mennyiségben (37 Bq/dm3) rendelkezésre áll (8). Más országok radonterápiás vizeihez viszonyítva az új fürdőkomplexum és a Török Fürdő forrásvizeinek radon tartalma jóval alacsonyabb, de a gyógyítás szempontjából ugyanúgy hatékony. Mind a négy vizsgált helyiségben megfigyelhető a radon koncentrációjának napi ingadozása, ami az éjszakai órákban csúcs kialakulást, a nappali órákban pedig erőteljes csökkenést jelent, ez utóbbi a munka végzésével járó ajtók nyitásának, szellőztetésnek köszönhető. A vártnak megfelelően a terápiás tértől legtávolabb lévő helyiségekben, a masszőr szobában, és az orvosi vizsgálószobában volt a legalacsonyabb a kialakuló radon koncentráció, átlagban 62 Bq/m3, (maximum 202 Bq/m3, minimum 5 Bq/m3), illetve 61 Bq/m3, (maximum 195 Bq/m3, minimum 13 Bq/m3). A terápiás medence tér esetében és a tangentor helyiségben már magasabb radon koncentráció a jellemző, de az előírt 1000 Bq/m3 cselekvési szinthez képest jóval alacsonyabb. Előbbi esetén az átlag 129 Bq/m3, (maximum 268 Bq/m3, minimum


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8 Bq/m3), ugyanez az utóbbi esetében 106 Bq/m3, (maximum 416 Bq/m3, minimum 7 Bq/m3). Korábban a Török Fürdőben mért légtéri radon koncentráció 200 és 2000 Bq/dm3 között változott, napszaktól és időszaktól függően (8). Tehát az új fürdőterápiás épületben jóval alacsonyabb a légtéri radon koncentráció.

2. táblázat: Radon koncentráció a terápiás medencében Dátum 2009. július 26. 2009. július 27. 2009. július 28. 2009. július 29. 2009. július 30. 2009. július 31. 2009. augusztus 1.

Idő [h] 7:00 11:00 15:00 7:00 11:00 15:00 7:00 11:00 15:00 7:00 11:00 15:00 7:00 11:00 15:00 7:00 11:00 15:00 7:00 11:00 15:00

Átlag Maximum Minimum Pezsgőfürdő (korábbi vizsgálat)

Radon koncentráció [Bq/dm3] 60,3 61,5 58,7 67,0 66,0 75,9 69,2 67,9 68,5 75,9 71,2 73,4 73,8 67,3 70,0 75,7 70,6 69,6 69,3 69,0 72,6 69 75,9 58,7 96,3

Hiba [Bq/dm3] 3,0 3,1 3,0 2,8 3,2 3,4 3,2 3,2 3,2 3,4 3,1 3,3 3,3 3,2 3,3 3,4 3,3 3,2 3,2 3,2 3,3 3,1 3,4 3,0 13,4


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1. ábra: Radon koncentráció a terápiás medencében 450

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2. ábra: A légtéri radon koncentráció változása az új fürdőterápiás részleg különböző helyiségeiben


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Egyensúlyi faktor vizsgálata A tangentor helyiségben figyeltük meg a legmagasabb radon koncentrációt, ezért itt végeztük el az egyensúlyi faktor vizsgálatát. Ekkor az átlagos radon koncentráció 163 Bq/m3 volt (maximum 889 Bq/m3, minimum 63 Bq/m3), míg az egyensúlyi faktor átlag 0,1 (maximum 0,34, minimum 0,03). 1000

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3. ábra: Egyensúlyi faktor a tangentor helyiségben Dózisbecslés eredménye A mért adatok birtokában dózisbecslést végeztünk egy munkaévre vonatkozóan. Számításunk során az átlagos radon koncentráció 104 Bq/m3, az egyensúlyi faktor 0,1, a munkaidő pedig 2000 óra volt. Az így kapott éves dózis 0,16 mSv/év, ami jóval kevesebb mint a megengedett 6,3 mSv/év, de alacsonyabb a korábban a Török Fürdőben monitorozott két munkavégző dózisnál is (0,57 és 0,82 mSv/év) (8).

E = CRn · F · t · D Ahol: E: CRn: F: t: D:

effektív dózis (Sv/év) átlagos radon koncentráció (104 Bq/m3) egyensúlyi faktor (ajánlott 0,4, mért 0,1) munkaidő (2000 óra/év) dózis-konverziós tényező (7.9 ·10-9 Sv/Bqm-3h).

(2)


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A páciensek sugárterhelése ennél még alacsonyabb. Bennfekvő betegek esetén maximum 10 fürdő lehetséges tíz nap alatt, míg bejárók esetében 15 alkalom, öt hét alatt. Évi két kúra a nagy betegszám miatt nem megoldható, tehát 60 óránál több nem lehetséges, amit egy páciens a fürdőben tölthet.

Összefoglalás Az egri Markhot Ferenc Kórház Reumaosztályának új fürdőterápiás épületében végzett vizsgálataink szerint az átlagos radon szint nem éri el az előírt 1000 Bq/m3-es cselekvési szintet, de a Török Fürdőben végzett vizsgálatokhoz képest is alacsonyabb. A mért egyensúlyi faktor is alacsonyabb, negyede az ajánlott értéknek, így a becsült dózis is jóval a megengedett 6,3 mSv/év alatt van. A fürdőterápiás épületben előforduló radon koncentráció, és a belőle származtatható dózis becslése alapján az itt dolgozók egészségügyi kockázata minimális, a megengedhető szint alatt van. A Török Fürdő pezsgő medencéjéhez képest az új terápiás medence átlagos radon koncentrációja 30 Bq/dm3-rel alacsonyabb, de így is meghaladja a terápiához előírt 37 Bq/dm3-t. Az adatok pontosítása érdekében, amint lehetőség nyílik rá, egyszerre fogjuk tanulmányozni a felújított Török Fürdő forráson lévő medence vizeinek, és az új fürdőrészleg terápiás medence vizének radon tartalmát. Az Egerben található terápiás vizek radontartalma világviszonylatban alacsony koncentrációjúnak mondható. A terápiás kezelések azonban hatékonynak és eredményesnek bizonyulnak. Ez jelentheti azt is, hogy a túlzott, több ezer Bq/dm3-es terápiás vizek alkalmazása szükségtelen, csak felesleges sugárterhelésnek teszi ki a munkavégzőket és kezelteket, vagy azt, hogy a gyógyító hatás nem a radonnak, hanem a víz más összetevőinek, vagy az összetevők együttesének köszönhető.

Irodalomjegyzék 1. http://egertermal.hu/egertermal.hu/hu/wellnes_furdotortenet.html 2. J. Nagy: Eger története. Gondolat Kiadó, Budapest, (1978) 3. D. Agyagási, I. Cornides, B. Kleb, K. Papp, Gy. Péczely, Gy. Scheuel, J. Suba, I. Sugár: Eger gyógyvizei és fürdői. Eger Város Tanácsa V. B. Műszaki Osztálya és a Heves megyei Idegenforgalmi Hivatal kiadása, Eger, (1983) 4. M. Csermely: Gyógyfürdők és gyógyvizek. White Golden Book Kft, Budapest, (2002) 5. H. G. Pratzel, P. Deetjen: Radon in der Kurortmedizin. I.S.M.H. Verlag Geretsried, München, (1997) 6. C. Sainz, A. Dinu, T. Dicu, K. Szacsvai, C. Cosma, L. S. Quindós: Comparative risk assessment of residential radon exposures in two radon-prone areas, Ştei (Romania) and Torrelodones (Spain). Science of The Total Environment, 407(15), 4452–4460, (2009)

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7. Az egészségügyi miniszter 16/2000. (VI.8.) EüM rendelete, az Atomenergiáról szóló 1996. évi CXVI. törvény egyes rendelkezéseinek végrehajtásáról, Magyar Közlöny, 55, Budapest, (2000) 8. N. Kávási, J. Somlai, T. Kovács, T. Sebestyén, K. Nagy, J. Bereczky, I. Berhés: Sugárvédelmi mérések az Egri Török Fürdőben. XXVIIII. Sugárvédelmi Továbbképző Tanfolyam, Keszthely, (2005)

The Influencing Parameters of the Risk of Smoking: Is the Hazard of the Smokers Reducible?

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THE INFLUENCING PARAMETERS OF THE RISK OF SMOKING: IS THE HAZARD OF THE SMOKERS REDUCIBLE? Herke Paula Szigetszentmiklósi SZ.R.I.- Tüdőgondozó, [email protected] Abstract Only 30% of the people, who want leave smoking, can quit it in fact (1, 2). What happens with the rest (70%)? Can we offer such facilities, what's destination is to minimize the risk of smoking, to keep the "get out of" motivation to a more ideal life-situation and to modify the therapy-worsen effects of smoking on obstructive patients? People are standing in interaction with his micro- and macro-environment and with the tobacco and its smoke has to be watched in its complexity. The presentation analyzes these aspects and trying to find influence points on them. Conclusion: there is no way to make smoking harmless, but we can avoid the accumulation of risk-factors with some changes in our lifestyles.

Introduction The smoker people and the plant tobacco are standing in interaction with his microand macro-environment and together. The smoke of tobacco has to be watched in its complexity, because it is not just a mixture of inflammatory and carcinogenic materials, but the source of maybe the most addictive compound, the nicotine and its smoke is an active transporter. These two functions should not be belittled. The thirst for nicotine is not a human own: the humming-birds visit the flowers with higher nicotine content (3). Its smoke makes such a perfect aerosol, that it could surely get into the small airways, while it whirls and precipitates a lot of environment-materials. The quality of the tobacco is influenced from many factors (4, 5, 6). Kind of the tobacco: for the small-leaf (oriental) tobacco is the low nicotine-content (0,5-1%) and fine flavor characteristic, at the same time the big-leaf tobacco has a variable quality and nicotine-content. The azotic compounds and the polysaccharides worsen the quality of the tobacco but the monosaccharides and disaccharides amend it.

Growing conditions and the origin Unfortunately, the intensive phosphate-containing fertilizing raises the polonium level (210Po) of the end-product. The alpha-ray isotope, 210Po can the lungs damage. It is important to know that the content of tar, TSNA, nicotine, and polonium change not parallel. Consequently, decreasing the tar and nicotine content does not significantly decrease the risk factor of tobacco due to its 210Po and 210Pb content (7, 8).

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Herke P.

The way of refining (drying, fermentation, additives) The long-fermentation increases the amount of the tobacco-specific N-nitrosamines (TSNA), one’s of the most potent carcinogens, which present in smokeless tobacco, snuff and tobacco smoke. The ignition helping materials: they lower the amount of sniffs while smoking. There can be significant differences in the burning-speed of the cigarettes depending on the quality of the paper. Next to the increase of the natural porosity of the paper the burning rate of the cigarettes can be intensified with different impregnation materials used in the paper-producing. The use of the tobacco It has two main ways since the ancient times: with smoke and without smoke. Currently, the most frequently way is the cigarette. The research of the smoke-filters was a logical step (9). Their use has been spread since 1954. Types are paper and acetate. The effect of the filter is raised by adding active carbon-particles to the acetate, along with other additives. In the most expensive filters these are made in several layers. The use of smoke-filters did not result the hoped protecting effect, but several important components can be effective reduced with apposition of active-carbon. The carbon monoxide level can be decreased with filter ventilation. It has spoken very much about nicotine in the last decades and different nicotinepoor products have appeared. In the European Union since the 1. January of 2004 the main smoke of the single cigarettes must not contain more than 10 mg tar 1 mg nicotine and 10 mg carbon monoxide. The "weak" "light" cigarettes (these markings are now banned) did not come up to expectations. The proportion of the adenocell carcinoma has increased to the planocell cc. The accepted justification is that its smoke inhales the smoker deeper and keeps it longer inhaled for the higher dose nicotine and that conduces to dawn of the adenocarcinomas in the small airways. I think, that we cannot leave out of consideration the fact, that roughly at the time of the appearance of the light cigarette, significant changes eventuated in the lifestyle of the people. People spend less time in open air, the walling has changed and with the application of more non-conductive doors and windows the aeration of our houses decreased. After the common electrification, the televisions, the microwaves and the computers came into general use in the house-holdings. Why is it important to think about it? After the smoking the second factor of the cause of lung cancer are the radon and its progenies. The radon is harmless in open air. Closed places behave themselves like a trap: the radon get into the inner rooms and its amount can be ten or hundred times when the radon-daughters alpha-particles disengage. The direct radonimpact does not mean a high risk for the human organism (in opposite to the gamma-, x-, ultraviolet-rays) but the inhaled alpha particles can effect DNS-damages on the


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lung-tissue and mutation. In the rooms, where cigarette-smoke is, the radon concentration is significantly higher, than in smoke-free areas (10) (Table 1). 300 250

If 1,000 people who smoked were exposed to this level over a lifetime

i/l

i/l

20 pC

/l

/l

10 pC

8p Ci

4p Ci

/l 2p Ci

i/l

i/l

If 1,000 people who never smoked, were exposed to this level over a lifetime 1, 3p C

p u e l o d p l g e e t

0, 4 p C

c

o

l u 200 n g 150 100 c a 50 n c 0 e r

radon level

Figure 1: Lifetime risk of lung cancer deaths from EPA Assessment of Risks from Radon in Homes (EPA 402-R-03-003) Table 1: Dose-equivalence Bq/m³ 74 148 400 800 1000

pCi/l 2 4 11 22 26

In electromagnetical-field – for example during working on computer or near to working labor-saving devices – the radon and its decays concentrate themselves higher (11). Now try to imagine a computeraddict-smoker in his pressurized room: not just the carcinogen substances of the smoke and the decompose-products of radon intensify their effect, but the isotopes use the smoke as a conveyance, so they get into the periphery of the lung. Moreover the tracheobronchial sedimentation of the radionuclides is inhomogeneous; the difference could be the four hundredfold (12, 13, 14). Than try to eliminate smoke as well they won’t give up smoking: a solution could be the renaissance of snuff and chewing-tobacco.

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The advantages of „smokeless tobacco”: ● There is no inhaled smoke, tar, carbon-monoxide: does not increase the risk (if there is no concurrent smoking) of lung cancer and COPD. There is no passive smoking. ● It can help to get out of smoking. ● The chance of the cardiovascular attaches is lower than by the cigarettes. Disadvantages of „smokeless tobacco”: ● all kind keeps up the nicotine-addiction ● per type variable: carcinogenesis, lesions of the oral mucosa, pancreas diseases (15, 16). Maybe the Swedish Snus is the best documented now. Nowadays it is in free commerce only in Sweden and Denmark (in the other parts of the EU is banned). Through the very hart manufacturing regulations and sterilization, it has a very low TSNA content. With its consumption connected mortality is just 2% of the cigarette. Disadvantages: reversible mucosa-lesions, tooth loose and gum diseases. The risk of pancreas-tumor and the oesophageal squamous cell cc. (noncardia stomach-cancer), is the twice than by the non-smokers. The people use it daily; have an increased chance to mouth- and pharyngeal-cancer and its mortality increases in a small measure too (17, 18, 19, 20). (Newer publications are confuting the growth of tumorous incidence) (21). Its using is rarely encountered in Hungary, so as the using of the Belgian makla ifirka (22, 23, 24). The American Marlboro and Camel Snus are one of the low-riskant smokeless products too, but their main parameters are worse than the parameters of the Swedish Snus. The other smokeless tobaccos should be avoided, through their high mouth-cancer incidence. The next opportunity to lessen the risks: we have to leave the tobacco so only the pure nicotine stays. Of course it makes people addict and it is not unrisky. But there is no inhaled smoke, it makes much weaker irritation (locally too) than the tobacco tincture (25). ● Nicotine laden chew-gum and patch (nicotine replacement therapy / NRTs ). ● Nicotine-laden products: Several nicotine-laden products are available in the USA, but their medical-effects are unknown.

Electrical cigarette contents no tobacco. When smokers draw on the business end of the tube, nicotine vapor is inhaled into the lungs. The excess cigarette-like "smoke" vapor, then emitted from the end of the e-cigarette, completes the cigarette smoking illusion. The U.S. Food and Drug Administration (FDA) looks at the electronic cigarette as an unapproved new drug due to the lack of scientific evidence of the safety and effectiveness of this smoking substitute. Through authorizations-reasons only the ecigarettes with 0% nicotine content are in circulation in Hungary.


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Therapy and smoking It is an international data, that nearly the 50% of the under cure standing patients smoke. Well-known fact is: the smoking effects steroid resistance by the obstructive patients and worse the success of the therapy. In the year 2009 has appeared the publication of Giovanni Invernizzi and his collaborators (25). It demonstrated, the particles of the smoke (under 1 μm) stay in the lung for minutes after smoking („residual tobacco smoke”) and come into contact with the inhaled medicine. They lessen the active substance, and constitute virtual steroid resistance together with the therapy-worsen effect of smoking. On the top of that the inhaled medicines come into contact with the environmental tobacco smoke (ETS) too, and it can be the reason of the lessened steroid sensitivity by smokers.

Conclusion There is no way to make smoking harmless. Our intention is the full pretermission of nicotine and the tobacco. For the people, who do not want or cannot get out of smoking, will be the following advices helpful to avoid the accumulation of damaging factors: ● Do not buy cigarettes with uncontrolled quality. If you smoke than smoke only cigarettes with combined filter! ● Lower nicotine content does not mean that the cigarette is more harmless, listen to the other substances. ● Do not smoke in closed places! ● Air the smoking places! ● Do not smoke near to working labor-saving goods or in front of the computer! ● If you choose the smokeless tobacco: in accordance to our knowledge, the Swedish Snus has the lowest medical-risk. ● The nicotine-laden chewing-gum and patch can moderate the lack’s symptoms of the nicotine-addiction and help by getting out of smoking. ● The electrical cigarette vindicate the nicotine-addiction, but have not got any smoke or stack gases so in accordance to our knowledge, its medical-risk is lower, than the risk of traditional smoking. ● If you use inhalators but you smoke: the therapical effect will be the best, in smoke free places, when you had min. a ten minute long break after smoking. ● Inhale the morning-medicine in the bed yet “with pure lung”-before the first “morning-cigarette”. It is my confidence, with this instruction we are able to avoid not just the accumulation of the risk-factors, but we can give possible challenges to the often depressive patient. Some successful steps can boost the self-confidence of the patient and vindicate the „get out of” motivation.

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Herke P.

References 1. I. Vadász : A tüdőgyógyászat és a dohányzás mai összefüggései, (2003) 2. J. Mucsi, É. Farkas: A dohányzásról leszokást segítő programot CHAMPIX alkalmazásával. 2007. jan. 1. és dec. 31. között megkezdett esetek feldolgozása. (2007) 3. Kolibris fliegen auch auf bitteren Nektar, www.scinexx.de/wissen-aktuell-87402008-08-29.html 4. B. Kerekes: A dohányszárítás elmélete és gyakorlata. Akadémia Kiadó, Budapest, (2006) 5. Pénzügyminisztérium Sajtóközleménye: Polónium-210 – radioaktív anyag a dohánytermékek füstjében. A Magyar Dohányipari Szövetség Közleménye, (2008) 6. L. Boros, I. Győri, J. Hamza: Gyártmányfejlesztés a dohányzás egészségkockázatának csökkentéséért. Az agrárinnovációtól a társadalmi aszimmetriákig című tudományos rendezvény anyaga. 7. T. Kovács, J. Somlai, K. Nagy, G. Szeiler: 210Po and 210Pb concentration of cigarettes traded in Hungary and their estimated dose contribution due to smoking. Radiation Measurements, 42(10), 1737–1741, (2007) 8. Á. Márton: Romániában forgalmazott cigaretták 210Po koncentrációja és a rendszeres fogyasztásukból eredő sugárterhelés becslése. XI. Erdélyi TDK, Kolozsvár, (2008) 9. M. J. Taylor: Cigarette Smoke and Filtration. Oktatóanyag, Filtrona Filters. 10. A. Hayam, G. Abdel: The Association between Indoor Radon and Tobacco Smoke. Indoor and Built Environment, 15(3), 289–293, (2006) 11. Bandics, L. Bátki, S. Matéz: Dohányzás, radon, polónium, elektroszmog, tüdőrák. Magyar Orvos, Melánia Kiadó, 11(7-8), 48–49, (2003) 12. S. X. Yao, J. H. Lubin, Y. L. Qiao, J. D. Boice, J. Y. Li, S. K. Cai, F. M. Zhang, W. J. Blot: Exposure to radon progeny, tobacco use and lung cancer in a casecontrol study in southern China. Radiation Measurements, 138(3), 326–336, (1994) 13. C. M. Alavanja: Biologic damage resulting from exposure to tobacco smoke and from radon: implication for preventive interventions. Oncogene, 21, 7365–7375, (2002) 14. Á. Farkas: Radio-aeroszolok lokális légúti kiülepedésének vizsgálata numerikus áramlástani módszerekkel. ELTE Fizikai Doktori Iskola, PhD-dolgozat. 15. Luo, W. Ye, K. Zendehdel, J. Adami, H. O. Adami, P. Boffetta, O. Nyrén: Oral use of Swedish moist snuff (snus) and risk for cancer of the mouth, lung, and pancreas in male construction workers: a retrospective cohort study. Lancet, 369(9578), 2015–2020, (2007). 16. G. Taybos: Oral changes associated with tobacco use. American Journal of Medical Sciences, 326(4), 179–182. (2003)


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17. P. Boffetta, B. Aagnes, E. Weiderpass, A. Andersen: Smokeless tobacco use and risk of cancer of the pancreas and other organs. International Journal of Cancer, 114(6), 992–995, (2005) 18. G. Bolinder, L. Alfredsson, A. Englund, U. de Faire: Smokeless tobacco use and increased cardiovascular mortality among Swedish construction workers. American Journal of Public Health, 84(3), 399–404, (1994) 19. D. H. Roth, A. B. Roth, X. Liu: Health risks of smoking compared to Swedish snus. Inhalation Toxicology, 17(13), 741–748, (2005) 20. E. Janzon, B. Hedblad: Swedish snuff and incidence of cardiovascular disease. A population-based cohort study. BMC Cardiovascular Disord, 9(21), Epub, (2009) 21. A. Roosaar, A. L. Johansson, G. Sandborgh-Englund, T. Axéll, O. Nyrén: Cancer and mortality among users and nonusers of snus. International Journal of Cancer, 123(1), 168–173, (2008) 22. A. Scheifele, A. Nassar, P. A. Reichart: Prevalence of oral cancer and potentially malignant lesions among shammah users in Yemen. Oral Oncol, 43(1), 42–50, (2007) 23. Foulds, H. Furbrg: Is low-nicotine Marlboro snus really snus? Harm Reduct Journal, 5, 9, (2008) 24. P. Herke: Dohányzás – füstmentesen. Medicina Thoracalis, 378–390, (2009) 25. D. Yildiz, Y. S. Liu, N. Ercal, D. W. Armstrong: Comparison of pure nicotine- and smokeless tobacco extract-induced toxicities and oxidative stress. Archives of Environmental Contamination and Toxicology, 37(4), 434–439, (1999) 26. G. Invernizzi, A. Ruprecht, C. De Marco, R. Mazza, G. Nicolini, R. Boffi: Inhaled steroid/tobacco smoke particle interactions: a new light on steroid resistance. Respiratory Research, 10, 48, (2009)

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Radon and Thoron in Wine Cellars in Tokaj-Hegyalja

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RADON AND THORON IN WINE CELLARS IN TOKAJ-HEGYALJA Búzás Eszter Bíborka1, Csige István2 1

Reformed High School of Sárospatak 2 MTA Atommagkutató Intézete

Abstract It is known, that the quantity of radon can accumulate mostly in closed, airless, underground places. This gas cause bigger lung cancer risk (the second biggest risk after smoking). There is a significant viticulture in Tokaj-hegyalja. The wine cellar owners, and workers, and the tourists can spend more or less time in cellars. During this research we have been examining the changes of radon and thoron in time and space in some cellars to estimate the load of radiation of radon. We have been examining the content of radon in 20 cellars in Hercegkút, Sárotaljaújhely, Olaszliszka, Sárazsadány and Sárospatak. The 222Rn-levels have a variation between 0.1 kBq/m3 and 5.8 kBq/m3 in the examined cellars. The quantity of radon increases in summer and decreases in winter.

Introduction The radon-activity concentration accumulates in closed places without ventilation, for example in wine cellars. The problem is unique, because the decrease of the quantity of radon, the ventilation, can be carried out only by natural ways to maintain the climate of the cellar. That’s why it is important to particularly know the reasons of airflow (and the reasons of radon gas flow, as well).

Ways of measurement Radamon The Radamon type etched track detector (developed by MTA Atommagkutató Intézet Radon Csoport), This is a plastic cylinder (its diameter is 35 mm, its height is 18 mm), and inside of it there is a CR-39 (allyl-diglikol-carbonate) type etched track detector which has got 1-2 cm2 area. The Radamon contains a paper filter to separate the solid parts of air and the decomposition of radon, and it also contains a polyethylene filter to filter out thoron. We used twin detectors during the measures, one of them had no polyethylene filter so we were able to define the quantity of thoron (the detector with two filters cannot filter out thoron due to the short half-life).

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AlphaGUARD The other way of measurement was the AlphaGUARD, which is an ionization chamber-type multiparameter 222Rn monitor (it has 0.56 liter volume, it works on 750 V, and a digital processing unit is linked to it). We used this machine to measure continuously the quantity of radon, pressure, temperature and humidity.

Measuring locations We started the series of measurements with 20 wine cellars ● in Hercegkút (11 cellars), ● in Sárospatak (4 cellars), ● in Sátoraljaújhely (2 cellars), ● in Olaszliszka (2 cellars) and ● in Sárazsadány (1 cellar). The most of the wine cellars are in the area of World Heritage area (which was made in 2002 by the UNESCO World Heritage Committee). From a geological point of view, the locations of measurements are mostly sandy/clayey fine-grained grounds. But there is a cellar which is in gravelly soil (S20), or in Hercegkút the cellars on Gombos hill are in rhyolite and andesite tuff. And in Sátoraljaújhely there is condensed perlite rhyolite (in case of S1).

Results and conclusions On the Figure 1 we can see the annual average radon level of the 20 cellars (the measurement period was from the summer of 2008 to the spring of 2009). The values are the average of the 4 measurement (1 measurement = a season). In Cellar 1 there is a very high average value, mostly 4000 Bq/m3.

Figure 1: Annual average (average of 4 data) 222Rn-activity concentration (Bqm-3) in 20 cellars


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Factors which define 222Rn-activity concentration The 222Rn-activity concentration formed in the airspace of the cellars is determined by many factors: ● The quality of the soil and the walls of the cellar, so the quantity of the leaking radon gas of them. ● The ventilation, which is mostly dependent of the outer temperature: o In winter: as the outer temperature becomes lower than the cellar’s, circulation begins: the outer, denser air flows in at the floor of the entrance of the cellar, passes on, warms up, rises, and flows out at the top of the entrance of the cellar. This continuous circulation results in the decrease of the quantity of the radon gas. o In summer: the outer, much warmer air is superseded by the cellar’s denser, colder air. There is no circulation so the quantity of radon increases. This effect can be observed on the graph about the results of the AlphaGUARD instrument’s measurements (Figure 2). On the graph the 3rd curve from the top to the bottom shows the outer (blue) and the inner (red) temperature curves according to the time. The results of the measurements of the 222Rn-activity concentration are shown on the 2nd curve from the top (red line filled with yellow).

Figure 2: The result of the measure with AlphaGuard in cellar S19 between 28. September 2009. – 11. November 2009


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We can see that sometimes the quantity of radon of the cellar was higher between 28th Sept. and 12th Oct. (it overrated the level of 2000 Bq/m3), this time the outer temperature was higher, than the inner temperature (the blue temperature-curve was above the red one). However on 13th Oct., when the outer temperature decreased beneath the cellar’s temperature the level of radon suddenly decreased (to a few 100 Bq/m3). It can be also observed that as on 22nd Oct. the outer temperature rose above the cellar’s temperature the level of radon started to rise again (about to the level of 500 Bq/m3). Model calculations were performed to understand the formation of 222Rn-activity concentration in the airspace of the cellars. The speed of ventilation (v=q/V, where q is the volume of air, which comes into the cellar in a unit time, and V is the volume of the cellar) is a significant data from the aspect of the radon concentration in the cellar because the radon activity concentration in the outer air (C0) is very low, almost negligible compared to the radon-activity concentration of the air of the cellar (C), so the better the basement ventilated is, the smaller the radon content of the cellar’s airspace is. Let the whole area of the wall be: A [m2]. On the wall (the floor of the cellar, too) the radon Current Activity density: j, [Bqm-2s-1]. This amount means the activity of radon atoms which flow out of unit surface in unit time. The unit of radon flow is [s-1], exactly [mols-1], the radon activity flow density unit is: [Bqm-2s-1], this is the multiplication of radon flow density and decay constant of 222Rn (λ=2.09838·10-6 s-1), . We can write down the following equation to define the change of concentration in time:

(1) 222

Rn-activity (2)

In a stationary case, when the 222Rn-activity concentration doesn’t change in time in the airspace of the cellar, the upper equation can equal with zero, and by this way we get an usual algebraic equation, which can be solved to the 222Rn-activity concentration of the airspace of the cellar. This situation occurs when the source of strength of the radon and the speed of ventilation of the cellar are both stable during a given, long time. According to this we can regroup the equation to calculate the radon activity concentration in the cellar. (3) In so far as we fix the other parameters, this formula shows how the radon activity concentration depends on the natural ventilation.


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For example: when we calculate with the following data:

j = 10 mBqm–2s–1, A = 200 m2, V = 2000 m3 and C0 = 10 Bqm–3.

(4)

The result is on Figure 3.

Figure 3: 222Rn-activity concentration, depending on the ventilation rate when there are fixed parameters (j = 10 mBqm–2s–1, A = 200 m2, V = 2000 m3 and C0 = 10 Bqm–3) The Radon activity concentration in the measured wine cellars was between a few hundreds and a few thousands, it means that the ventilation rate in the particular cellars is 0.03-0.30 h-1. So the whole air of the cellars’ airspace is replaced during about 3.3-33-3 hours.

Vertical distribution of 222Rn-activity concentration In the S29-signed cellars we have been examining this problem with the help of the vertically located detector in the small collateral of the limb. The 222Rn-activity concentration‘s values are almost the same in every height, but the 220Rn-(thoron)activity concentration near to the floor and ceiling (walls) is higher. This is due to the short half-life, as the complete mixing of the air requires more time, than the thoron for further decomposition. It can be observed, that while the 222Rn-activity concentration‘s values are relatively low, the thoron’s concentration is relatively higher. The measures we later did show that at the same collateral’s entrance the thoron-activity concentration is very low, almost undetectable. This shows that the ventilation of the collateral’s ending is lower, than the ventilation of the entrance.

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Summary During these measures we can prove that in the cellars the 222Rn-activity concentration is variable in different seasons, which can be explained by the ventilation of the cellar. We took measurements to know how the 222Rn-activity concentration changes vertically in the inner cellar. According to this it is explicable that the 222Rnconcentration is independent, but the 220Rn concentration is dependent on the distance from the walls. We can significantly reduce the radon activity concentration in our homes and workplaces by frequent ventilation, and lessen the risk of lung cancer. Unfortunately in cellars and other closed places it is more difficult to ventilate. To make this natural process easier, a hole is drilled into the ceiling of the cellar which is called soulhole, and with this hole the circulation of the air is faster. Despite this it is also usual in some measured cellars that the radon activity concentration overrates the 1000 Bq/m3 limit according to the season, but not at the same extent (which limit is defined at workplaces, for 8 hour-long worktime). But this high activity concentration doesn’t have to be a concern because in our measured cellars the owners usually stay significantly less than 8 hours in the cellars.

References 1. R. Bartók, I. Csige: CR-39 type maratott nyom-detektor érzékenységének növelése. Sugárvédelem, 2, 25–30, (2009) 2. T. Budai, L. Gyalog: Magyarország földtani atlasza országjáróknak, Magyar Állami Földtani Intézet, Budapest, (2009) 3. I. Csige, É. Svingor: Természetes eredetű sugárzások a környezetben. Fejezetek a környezetfizikából. Egyetemi Jegyzet, Debreceni Egyetem, Debrecen, (2004) 4. I. Csige: Radon and Space Radiation Protection Measurments, Ph.D dissertation, Kossuth Lajos Egyetem, Debrecen, (1997) 5. S. Darby, D. Hill, A. Auvinen, J. M. Barros-Dios, H. Baysson, F. Bochicchio, H. Deo, R. Falk, F. Forastiere, M. Hakama, I. Heid, L. Kreienbrock, M. Kreuzer, F. Lagarde, I. Mäkeläinen, C. Muirhead, W. Oberaigner, G. Pershagen, A. RuanoRavina, E. Ruosteenoja, A. Schaffrath Rosario, M. Tirmarche, L. TomáBek, E. Whitley, H. E. Wichmann, R. Dol: Radon in homes and risk of lung cancer: collaborative analysis of individual data from 13 European case-control studies. BMJ, doi:10.1136/bmj.38308.477650.63, (2004) 6. T. Győrfi, I. Csige: Az atmoszférikus légnyomás változásainak hatása egy borpince légterében lévő 222Rn-aktivitáskoncentrációra. Sugárvédelem, 2, 44–49, (2009) 7. I. Nikl: The radon concentration and absorbed dose rate in Hungarian dwellings. Radiation Protection Dosimetry, 67(3), 225–228, (1996)


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8. R. Machintosh, J. Al-Khalili, B. Jonson, T. Pena: Az Atommag - Utazás az anyag szívébe. Akadémia Kiadó, Budapest, (2003) 9. Gy. Rontó, I. Tarján: A biofozika alapjai, Semmelweis kiadó, Budapest, (1999) 10. Gy. Somogyi, I. Nikl, I. Csige, I. Hunyadi: Radon aktivitás-koncentrációjának mérése és a belégzésből eredő sugárterhelés meghatározása hazai lakások légterében. Izotóptechnika, Diagnosztika, 32, 177–183, (1989)

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Radon Measurements in Hungarian Wine Cellars

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RADON MEASUREMENTS IN HUNGARIAN WINE CELLARS Sas Zoltán, Asztalos István, Förhécz Márta, Kis Balázs, Kovács Sándor, Somlai János, Szeiler Gábor, Kovács Tibor University of Pannonia, Institute of Radiochemistry and Radioecology, Veszprém Abstract The aim of the survey was to determine the Rn-222 activity concentrations in some wine cellars from different wine districts of Hungary. Earlier studies showed that radon can accumulate in the air of subterranean premises such as caves, cellars, mines and other underground places because of insufficient aeration conditions. The seasonal variation of the originating radon concentration of the underground places justifies longtime measurements with passive detectors, in practice at least 1 year long surveys. During the fermentation large quantities of CO2 are generated which is life-threatening and must therefore be controlled, but it can also influence the sensitivity of the detectors of radon measurement. To get precise dose estimation the influencing parameters which have effect on the measurement have to be determined.

Introduction In Hungary there are several famous, traditional wine districts. The wine cellars are the places of processing, fermentation and storage of the wine and for wine tourism as well. The natural radioactive content of the surrounding wall of the cellars greatly influences the level of the natural radioactive exposure of the owner, the workers and the guests. The role of radon in the evolution of lung cancer is proven. It is generally known that more than the half of the natural radiation exposure is derived from the inhalation of the naturally occurring radon and its short-lived progenies. The radon is a radioactive noble gas with relatively long half life (3.82 d) and this time can be enough to escape from the matrix of rock, soil or building materials into the pore space and subsequently into the air as well. Radon can accumulate in the subterranean premises such as cellars, caves, mines and other underground places where persons work or spend their time. Therefore the determination of the radon activity concentration and the received effective dose is important. Different legislation can be found in the world concerning radon levels at workplaces. Following the European Union suggestion, a reference level for radon concentration in the air at workplaces was established in several European countries. In Hungary, the relevant legislation has come into effect on 1 January 2003. Based on the ICRP 65 (1) publication and in Hungary the action level was defined 1000 Bq/m3 average radon concentration with 0.4 equilibrium factor and 2000 h per year exposure time. Due to the permitted radon activity concentration and the considered features the maximum of the received committed effective dose equals 6.3 mSv/year (2).

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Sas Z., Asztalos I., Förhécz M., Kis B., Kovács S., Somlai J., Szeiler G., Kovács T.

In this study CR-39 type track detectors were used to carry out the radon monitoring of the examined cellars. As a result of the fermentation process large amounts of CO2 are generated. Its presence can influence the sensitivity of the detector material for Rn (3). Therefore, to get a precise measurement value the influencing effect of the CO2 must be accounted for. This is why we also investigated this effect.

Materials and methods Sampling places The radon measurements were carried out in 14 wine cellars which are located in 4 different wine districts. The locality of the measurement places can be seen in Figure 1. The extent and the structure of the cellars are different (simple gallery or gallery with branches). The originating radon concentration of the air in the cellars greatly depends on the circumstances (weather and aeration conditions, Ra-226 content, emanation and exhalation rate of the gallery). For this reason the track detectors were placed into several rooms and branches of one cellar. During the investigation which took at least one year the detectors were replaced in every month. People usually spend their time sporadically in the cellars. In this investigation we assume that the measured mean Rn concentration represents well the mean concentration to which people are exposed during their visits (4). The CR-39 type track detectors were surrounded by polypropylene containers to avoid the tracks from the progenies of the Rn-222 and also prevent the entering of Rn-220 into the detector cavity. After the etching the detectors were ready to count the tracks and the activity concentrations were calculated from the received values.

Figure 1: Location of the surveyed wine districts


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Carbon dioxide treatment The influencing effect of the CO2 was determined in different concentrations. The track detectors were placed into a steel accumulation chamber with volume of 60 l. The radon content was ensured with PYLON RN 2000A type passive radon source (activity of 105 ± 0.4 % kBq). (Figure 2) The Radon activity concentrations were monitored with the help of Gentiron product ALPHAGUARD PQ 2000 radon monitor. The time of exposure varied between 48 – 96 h and the radon activity concentration was approximately 15000 Bq/m3 during the experiments. The CO2 levels were ensured with common soda siphon. In function of the number of the used CO2 cartridges the carbon dioxide level were estimated and the real concentration was measured with Servomex 1410B type NDIR analyzer.

Figure 2: Radon accumulation set for CO2 treatment Results and discussion Radon activity concentration in cellars Results of the Rn-222 activity concentration measurements of the win cellars are summarized in Figures 3 to 6. “AVG” denotes the average over the individual values. The results clearly show that the average radon activity concentrations in the examined wine cellars do not exceed the 1000 Bq/m3 acting level. The seasonal variation of the radon level can be seen so this fact indicates the adequacy of long-term integrated measurement to get precise dose estimation.

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Figure 3: Radon in cellars of Eger

Figure 4: Radon in cellars of Balaton district

Figure 5: Radon in cellars of Szekszárd

Figure 6: Radon in cellars of Mór

Effect of CO2 concentration to detecting efficiency of the track detectors Figure 7 shows the effect of carbon dioxide on the track density dependency of CR-39 in different CO2 atmospheres. The sensitivity of the track detectors appears to decrease slightly with increasing concentration of the treating gas. The received few result are not enough to clearly state the dependency but motivate further experiments with various levels of CO2 concentration. If the experiments show a significant influence of CO2 concentration on the sensitivity of CR-39 detectors, this effect has to be taken into consideration as correction for calculation of the Rn-222 activity concentration. Anyway, in wine cellars the CO2 level measurement is recommended to avoid the death by suffocation, hence values for correcting Rn measurements are usually available.

Figure 7: Track density in function of CO2 concentration


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Summary The aim of this study was to get information from the radon activity concentration of some wine cellars of four different Hungarian wine districts. In Hungary the legal action level is 1000 Bq/m3 average radon concentration over the working hours, which applies also to wine cellars. The average radon concentration of the examined places was lower than the limit in case of all cellars. The observed seasonal fluctuations show that long term measurements are required to obtain representative values of the mean Rn concentrations at these underground workplaces. Also the disturbing effect of high CO2 concentration was investigated. In the range of investigated CO2 concentrations the track density of the detectors slightly decreased with increasing carbon dioxide concentration.

Acknowledgement Present publication was realized with the support of the project TÁMOP-4.2.2/B-10/1-2010-0 References 1. ICRP65, International Comission on Radiological Protection, Protection against: 222 Rn at Home and at Work. Oxford, Pergamon Press, ICRP Publication No. 65, (1994) 2. Hungarian Regulation 10 16/2000 VI.8., Ministry of Health implementing the provisions of the law No. CXVI. of the year 1996 of nuclear energy, Hungarian Bulletin, 55, Budapest, Hungary, (2000) 3. I. Csige: Post-irradiation sensitization of CR-39 track detector in carbon dioxide atmosphere. Radiation Measurements, 28(1-6), 171–176, (1997) 4. C. Sainz, L. S. Quindós, I. Fuente, J. Nicolás, L. Quindós: Analysis of the main factors affecting the evaluation of the radon dose in workplaces: The case of tourist caves. Journal of Hazardous Materials, 145(3), 368–371, (2007)

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Jacobi Room Model Parameters for Radon Progeny at Turbulent Airflow

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JACOBI ROOM MODEL PARAMETERS FOR RADON PROGENY AT TURBULENT AIRFLOW Stevanovic Nenad, Markovic M. Vladimir, Nikezic Dragoslav University of Kragujevac, Faculty of Science, Kragujevac, Serbia Abstract In this paper Jacobi room parameters were determined for turbulent indoor airflow. The relationships between deposition rates of unattached and attached radon progeny with ventilation rate and attachment rate were determined in this paper. These parameters are functions of friction velocity, u*, which characterizes turbulent airflow. It was shown that parameters of the Jacobi model are not independent.

Introduction The Jacobi room model describes behavior of radon and its progeny in a closed space; it consists of a set of parametric differential equations (1). This model takes into account radioactive decay, removal by ventilation, attachment and deposition. The attachment is the process when progeny collides to the ambient aerosol, where attached progeny is created. Deposition is process when free or attached progeny deposits on the room walls. Parameters which describe these processes are decay constants λi, ventilation rate λv, attachment rate λa, and deposition rates of unattached and attached progeny λdu, λda, respectively, all in s-l (or traditionally in h-1). The outputs of the model are radon and progeny concentrations in closed space for a given set of parameters. In many calculations, these parameters were treated as independent and their best estimations were used; even in some works (1) these parameters were chosen uniformly and randomly in some range given in Table 1.

Table 1: Characteristic values for the parameters usually used in literature Parameters λv λa λd u λd a

Best estimation (h-1) 0.55 50 20 0.2

Range of values (h-1) 0.1-2 10-100 5-110 0.05-1.1

Many factors have influence on real values of parameters, such as: room dimensions, S/V ratio, aerosols concentration and their size distribution, indoor airflow, etc. Concentrations of radon progeny in different modes (attached or unattached) strongly depend on Jacobi parameters and their values must be precisely

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determined. Recently, Jacobi room parameters were determined using Brownian motion model (3) assuming that airflow was not present within a room. This assumption was justified when there was no significant air movement in the room i.e. the ventilation rate, λv is equal or close to zero. Deposition of radon progeny depend on the indoor airflow and activity size distribution. Natural ventilation is defined as the movement of air through openings, in and out, due to wind or static pressures, created by difference in temperature between interior and exterior of the building or due to the combination of these acting together (4). Ventilation in some room additionally influences on airflow distribution and ventilation rate. It can be concluded that ventilation and deposition rates are in correlation and can not be treated as independent parameters, as it was usually done in many simulations. The objective of this paper is finding a relationship between Jacobi parameters when turbulent indoor airflow exists. Turbulent indoor airflow and deposition velocity were characterized and expressed through the friction velocity, u*.

Methodology Unattached and attached fractions Newly formed radon progeny are usually positively charged particles. During their motion they collide with molecules of water vapor and form clusters. Such clusters are known as unattached progeny. Dimensions of clusters are about 1 nm and their size distribution is described by one modal log - normal distribution, fu(d) as

f u (d ) =

e

−

(ln d − ln AMTD )2 2 ⋅ ln 2 (σ )

2π ⋅ d ⋅ ln (σ )

(1)

where AMTD = 0.9 nm and σ = 1.35. Activity median thermodynamic diameter (AMTD) is the particle diameter, thermodynamically classified, for which 50% of the total airborne activity, is associated with particles of thermodynamic diameter is greater than the AMTD (5). The activity size distribution of attached ambient progeny was presented by one modal log normal distribution as (5) f a (d ) =

e

−

(ln d −ln AMAD )2 2⋅ln 2 (σ )

2π ⋅ d ⋅ ln (σ )

(2)

where geometric standard deviation, σ, is function of AMAD as follows (5) ⎛ ⎝

σ = 1 + 1 .5 ⋅ ⎜ 1 −

1 ⎞ ⎟ 100 ⋅ AMAD1.5 + 1 ⎠

(3)


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Activity median aerodynamic diameter (AMAD) is the diameter in an aerodynamic particle size distribution for which the total activity above and below this size are equal, where a log-normal distribution of particle sizes is assumed.

Ventilation rate Vertical profile of wind speed in urban environment is described by log-law model (4) as U (z ) =

u * ⎛ z + z0 ⎞ ⎟ ln⎜ k ⎜⎝ z0 ⎟⎠

(4)

where, k is constant and has the value of k = 0.4, z is height and z0 is aerodynamic surface roughness and for cities and village has value z0 = 1 m4. On another side, if U [cm/s] is inlet air speed in the room, Se is surface where air enter in the room, V is room volume, then the ventilation rate is given as

λv [h −1 ] =

U ⋅ S e ⋅ 3600 V

(5)

By combining these equations the following expression could be written

λv =

S e ⋅ 3600 u * ⎛ z + z 0 ⎞ ⎟ ⋅ ln⎜⎜ V k ⎝ z 0 ⎟⎠

(6)

If inlet area is 20 x 20 cm2 on the height z = 1.5 m (6), then friction velocity due to ventilation is equal to u* =

V λv 3.3 ⋅ 10 6

(7)

This friction velocity presents contribution to total friction velocity in the room due to ventilation.

Attachment of radon progeny to ambient aerosols Besides the fast reactions of neutralization and cluster formation, the decay products of the radon isotopes tend to attach to existing ambient aerosols with a number size distribution Z(d). The activity size distribution fa(d) of the radionuclide and the number size distribution Z(d) in the atmosphere are different because the attachment process is a function of particle size. Their relationship is given by the following expression (7) f a (d ) = β (d )

Z (d )

λa

where β(d) is attachment coefficient given as

(8)


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β (d ) =

2π ⋅ D0 ⋅ d 8 ⋅ D0 d + d ⋅ v0 d + 2 ⋅ l 0

(9)

where, D0= 0.054 cm2/s is diffusion coefficient of unattached radon progeny clusters; v0= 172 m/s and l0= 6⋅10-8 m are their mean thermal velocity and mean free path, resp. These values were accepted from ref. 7. (7) and attachment coefficient β(d) only depends from aerosol diameter for aerosols diameters lower than 10 μm. There is no influence of indoor airflow on progeny attachment. Function Z(d) was normalized to unit aerosol concentration as

∫ Z (d )dd p

p

=1

(10)

The attachment rate for unit aerosols concentration (Z=N0= 1 m-3) can be calculated as

λ a1 =

1

f (d ) ∫ β (d ) dd a

(11)

p

p

p

where λ1a =

λ

a . N0 According to Eq. (11), attachment rate was calculated and presented in Figure 1.

Figure 1: Attachment rate as function on AMAD Attachment rate for unit aerosols concentration as a function on AMAD (Figure 1) can be presented as

λa1 = 4.5 ⋅ 10 −8 ⋅ AMAD1.5 .

(12)


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For ambient aerosols, with diameter up to 10 µm, attachment rate does not depend from airflow and only depends from aerosols distribution.

Deposition velocity Zhao and Wu (2006) extended particle deposition model developed by Lai and Nazaroff (2000) following mechanisms of particle transport: Brownian diffusion; turbulent diffusion; gravitational settling and turbophoresis, defining the particle flux, J, as J = −(ε p + D )

∂C − ivs C + Vt C . ∂y

(13)

The expression for particle deposition velocity can be shortly written as (8) vd (u*, d p ) = u * ⋅

F (30, u*, d p ) G (u*, d p )

.

(14)

The deposition velocity is function of friction velocity - u* and particle diameter - dp. The average deposition velocity for unattached and attached progeny atoms, as a function on friction velocity, was calculated as v du ,a (u *) =

∫ v (u*, d )⋅ f (d )dd ∫ f (d )dd d

p

u ,a

u ,a

p

p

p

.

(15)

p

Deposition velocity of unattached fraction as function of friction velocity is presented on Figure 2, where, fu is given by Eq (1).

Figure 2: Deposition velocity of unattached fraction as function on u*


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In order to determine correlation between deposition velocity and friction velocity, curve on Figure 2 was fitted using iteration method of changing initial constants in probe linear function. It has been obtained that curve in Figure 1 could be presented by following equation v du = 0.042 ⋅ u * .

(16)

Deposition velocities of attached fraction to vertical walls, floor and ceiling in examined range of friction velocity were presented in Figure 3. For examined friction velocity, deposition velocities of attached fraction have values up to 0.004 cm/s.

Figure 3: Deposition velocities of attached fraction on vertical wall and floor as function on friction velocity In order to determine correlation between deposition velocity and friction velocity, curves on Figure 3 was fitted by linear functions and obtained following equations v dawall = 1.26 ⋅ 10 −4 ⋅ u * v da floor = 1.22 ⋅ 10 − 4 ⋅ u * + 4.33 ⋅ 10 − 4

(17)

v daceiling = 1.21 ⋅ 10 − 4 ⋅ u *

Deposition rates of unattached and attached fractions If deposition velocity of unattached radon progeny is vdu [cm/s], then deposition rate, λdu [h-1], is given as

λud (u *) =

S ⋅ 3600 ⋅ vdu (u *) . V

(18)


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where S and V are surface and volume of the room, respectively. Deposition rate of unattached progeny, given by Eq. (18), was presented on Figure 4.

Figure 4: Deposition rate of unattached fraction as function u* On another side, indoor aerosols carrying attached progeny have larger diameters and gravitational force has significant influence on deposition velocity at floor and ceiling. Consequently, deposition velocity on the floor is larger than that on the vertical wall. Hence, deposition rate of attached fraction is defined as

λad (u *) = 3600 ⋅

vdawall (u *) ⋅ S wall + vda floor (u *) ⋅ S floor + vdaceiling (u *) ⋅ S ceiling V

. (19)

where Swall, Sfloor and Sceiling are surface of the vertical walls, floor and ceiling, respectively. vdawall, vdafloor and vdaceiling are corresponding deposition velocities. Deposition rate of attached radon progeny, as function on friction velocity was presented on Figure 5, where AMAD was treated as parameter. Based on these results, deposition rate of attached progeny can be written as (9)

λad = 0.944 ⋅ AMAD 2.85 + 0.0009 ⋅ AMAD −1.02 ⋅ u * .

(20)

Deposition rate of attached progeny depends on friction velocity and aerosols size distribution characterized by AMAD parameter. Finally, from Eqs. (12) and (20), deposition rate as function of attachment rate, friction velocity and ventilation rate can be presented as

λad = 8.58 ⋅ 1013 ⋅ λa11.9 + 9.8 ⋅ 10 −9 ⋅ λa1 −0.68 ⋅ (u * +9.09 ⋅ λv ) .

(21)


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Figure 5: Deposition rate of attached fraction as function on u* Figure 6 presents deposition rate of the attached fraction, λad, as a function of friction velocity, given by Eq. (21), for different ventilation rates, λv and attachment rates, λa1. 0.5

λv = 0.1 h-1 λv = 1 h-1

-1 a λd (h )

0.4

λa1 = 1 ⋅ 10− 9

h −1 m −3

λa1 = 5 ⋅ 10 − 9

h −1 m −3

0.3

0.2

0.1

0.0 0

5

10

15

20

25

30

u* (cm/s)

Figure 6: Deposition rate of attached fraction as function on friction velocity for different attachment rate As was expected, λad linearly increases with friction velocity for different λv and λa1. The deposition rate increases with the ventilation rate, as is shown in Figure 6. The


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deposition rate λad, decreases with the attachment rate, λa1. Larger λa1 corresponds to larger AMAD, which describes aerosols with larger diameters. Such aerosols have smaller diffusion coefficient and slower deposition velocities. Hence, deposition rate coefficient is smaller if attachment rate increases. The influence of attachment rate on the deposition rate coefficient is larger if the friction velocity increases. For examined friction velocity, u* ≤ 30 cm/s, aerosols concentration N0 = 1010 m-3, ventilation rate from 0.1 up to 1 h-1 and attachment rate coefficient from 10-100 h-1, the range of deposition rate of attached fraction is 0.012-0.46 h-1.These values are shown in Table 2 and compared with other authors. It could be seen that ranges of all data sets are similar.

Table 2: Deposition rate of unattached and attached fractions

Unattached fraction Attached fraction

Ref. 2

Deposition rate (h-1) Ref. 3 Ref. 6,9 Ref. 10

5-110

30-47

3-110

2.4-4.8

4

0.05-1.1

0.005-0.021

0.012-0.48

0.036-0.072

0.04

Ref. 11

Conclusion Influence of aerosols characteristics and indoor airflow on Jacobi room parameters was investigated in this paper. It was shown that these parameters are not independent and relationships between them were established. If attachment rate increases, deposition rate coefficient decreased and this is significant for larger friction velocity. Deposition rates decrease with friction velocity. Deposition rate of attached fraction is in the range λad = (0.012-0.46) h-1 when ventilation rate, λv, is between (0.1-1) h-1 and attachment rate coefficient, λa, varies from (10-100) h-1.

References 1. W. Jacobi: Activity and potential α energy of 222Rn and 220Rn daughters in different air atmosphere. Health Physics, 22, 441–450, (1972) 2. K. Amgarou, L. Font, C. Baixeras: A novel approach for long-term determination of indoor 222Rn progeny equilibrium factor using nuclear track detectors. Nuclear Instruments and Methods in Physics Research A, 506, 186–198, (2003) 3. N. Stevanovic, V. M. Markovic, V. Urosevic, D. Nikezic: Determination of parameters of the Jacobi room model using the Brownian motion model. Health Physics, 96(1), 48–54 (2009) 4. P. M. Straw: Computation and Measurement of Wind Induced Ventilation. Doctoral dissertation, University of Nottingham, (2000)

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5. International Commission on Radiological Protection. Human respiratory tract model for radiological protection. A report of a Task Group of the International Commission on Radiological Protection. Pergamon Press, Oxford, (1994) 6. N. Stevanovic, V. M. Markovic, D. Nikezic: Deposition rates of unattached and attached radon progeny in room with turbulent airflow and ventilation. Journal of Environmental Radioactivity, 100, 585–589, (2009) 7. J. Porstendörfer: Properties and behaviour of radon and thoron and their decay products in the air. Journal of Aerosol Science, 25(2), 219–263, (1994) 8. B. Zhao, J. Wu: Modeling particle deposition from fully developed turbulent flow in ventilation duct. Atmospheric Environment, 40, 457–466, (2006) 9. N. Stevanovic, V. M. Markovic, D. Nikezic: Relationship between deposition and attachment rates in Jacobi room model. Journal of Environmental Radioactivity, 101, 349–352, (2010) 10. E. Knutson, A. George, J. Frey, B. Koh: Radon daughter plateout. Health Physics, 45, 445–452, (1983) 11. J. Porstendörfer, Behaviour of radon daughter products in indoor air. Radiation Protection Dosimetry, 7, 107–113, (1984)

Some Thoughts on Radon Statistics

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SOME THOUGHTS ON RADON STATISTICS Bossew Peter Bundesamt für Strahlenschutz, German Federal Office of Radiation Protection, Berlin Abstract Spatial modelling of radon related variables remains a challenge. Reasons are their complex dependencies, often high variabilities over short distances and imperfect information about controlling factors. This article presents selected issues of coestimation, transfer models, variability modelling, understanding spatial anomalies, and thoughts about estimating “Rn-prone zones”.

Introduction Given its radiological importance, one attempts to model Rn with the aim of describing its spatial distribution and predicting expected values over spatial units, such as administrative units, towns, or at a location. Although Rn physics is simple, in principle, the variety of controlling factors which are known only to a limited degree result in high variability and make modelling complicated. Therefore, much of the variability over a unit can in practice not be explained “deterministically”, i.e. based on physical parameters of the system which controls Rn generation and transport, but only by statistical means. In this contribution I want to address a number of issues which appear relevant in the context of spatial modelling. None of these problems has been solved satisfactory so far, in Rn science, and the following should merely be considered as steps towards asking the right questions.

Co-estimation, transfer If one wants to model the distribution of one “target” Rn quantity, say indoor concentration (in practice one often deals with long-term means in ground floor rooms, to reduce “longitudinal” variability, i.e. the variability between realizations of this quantity due to locally coexisting controlling factors, like different floors, different room usage patterns etc.), one may rely not only on measurements (observations, samples) of this quantity, but may want to include also secondary quantities, i.e. control factors (like geology) or physically related quantities (such as soil Rn concentration or external dose rate etc.). The concept is summarized in Figure 1. The problems are: 1. modelling the relation between the “input” quantities; 2. estimating the target quantity at a given location or spatial unit, integrating information from observed target and secondary quantities.

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128

estimate: = E[Z0 | z0i, z1j], FZ0(x)|(z0i, z1j)

Z0*

Z0(x)= primary quantity

physically ⇒ statistically related

data (observations): {z0(xi), z1(xj)}

Z1(x)= secondary quantity

controls

Figure 1: Idea of co-estimation In reality, one may even want to estimate a target variable different from both Z0 and Z1, like a radon potential which is possibly derived from different physical quantities; this may render the procedure even more complex, but we shall not discuss this at this stage. In general, observations are not available at the same locations. The general procedure for including categorical controls (g; such as geological classes) is a spatial GLM approach as done by regression kriging (Hengl et al. 2004), while a practical (though less exact) solution may be found in external drift kriging, as e.g. shown i n Bossew et al. (2008): Perform ANOVA of Z by g, identify a set of {gk} which significantly sorts Z into classes, define Y(x):=Z(x)-E[Z|g(x)] and perform spatial estimation (like kriging) on the “residuals” Y(x), and back-transform Z(x*)=Y(x*)+E[Z|g(x*)]. The inaccuracy mainly consists in that the estimation of E[Z|g] does not account for spatial association of the data which are used to estimate it, as the full regression kriging approach would do, whose practical implementation may however be difficult. The actual co-estimation is more complicated. One wants to estimate Z0 at x*, while the observations of Z0 and Z1 are made on different locations, i.e. the sampling sets of Z0 and Z1, ξ0={xi}, the locations where z0 has been sampled, ξ1 in analogy, are different, viz. ξ0 ≠ ξ1. The general solution is co-kriging (Goovaerts 1997, pp. 203 ff.; Goovaerts 1998; Chilès and Delfiner 1999; pp. 292 ff) or equivalent co-simulation (Verly 1994; Soares 2001; Horta and Soares 2010). The practical problem is that it requires estimation of cross-variograms γ(ij) between the variables Z(i), Z(j) which appears prohibitive in practice. Two possible ways are suggested:


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Collocation: If a “transfer function” f01 is known, Z0 = f01(Z1), one can estimate Z0 at the locations where Z1 has been observed, Z0#(ξ1), and add the results to the observations of Z0; the new and larger dataset is then {z0(ξ0), z0#(ξ1)}. Using this for further spatial estimation effectively includes information from Z1 into the estimation of Z0. If however the transfer function is not known, it must be estimated from data on a collocated sample set; i.e. by observations or estimates on the same locations. To this end, one would first estimate Z1 at the locations ξ0, i.e. where Z0 has been observed, yielding Z1*(ξ0); then use the bivariate set (z0(ξ0), z1*(ξ0)) for establishing the transfer function. Evidently this two-step procedure is neither elegant, nor exact as it requires two spatial estimation steps for estimating Z0** out of given observations z0(ξ0) and z1(ξ1), via z1*(ξ0) and z0#(ξ1).

“Markov-1 screening hypothesis”: A possible approximate solution has been proposed for such situations, Almeida and Journel 1994; Goovaerts 1997 (p. 237 ff); Remy et al. 2009 (p. 60 f, and references there). If one can reasonably assume E[Z1(x) | Z0(x), Z0(y)] = E[Z1(x) | Z0(x)] (hence the name of the method), theory yields, for the cross-covariances: C01(h) = (C01(0) / C00(0)) * C00(h), h:=|x-y|. This means that only the variance of Z0, C00(0), and the covariance between Z0 and Z1, C01(0), are needed, as well as the variogram (or the covariance) of Z0, γ00(h) or C00(h). C01(0) may be estimated, again, from an analysis of a collocated set, as above, or by estimating the nugget of the crossvariogram, which may be much less demanding than estimation of the full crossvariogram. In any case, the practical feasibility remains to be investigated for Rn quantities.

Transfer function Modelling the transfer function may be a tricky task on its own. At a location, one has, in general, estimates of the quantities which are subjected to analysis of their dependence, in many cases with considerable uncertainties. If the data are the original observations z(xi), uncertainties are essentially the ones of the sampling procedure. For values which are spatial estimates z(x*) at un-sampled locations x*, additional uncertainty results from the estimation procedure. Given sometimes high local variability, one may prefer estimating a probabilistic transfer function instead of a “deterministic” one. For example if indoor concentration (Cin) shall be estimated from soil Rn (Cs), the traditional transfer approach is Cin = f(Cs; α), where α may be factors related to geogenic and anthropogenic conditions, like permeability for geogenic, and house type for anthropogenic factors. The probabilistic approach would be stated as follows: Given a local distribution of Rn in soil, FCs, a transfer “functional” φ would result in an estimated distribution

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FCin = φα[FCs] of indoor concentrations. Again one had to estimate φ from collocated observations. A possible solution may go a detour over estimating the joint distribution of Cin and Cs, or any n-tuple of variables which form a multivariate Z(x) =(Z1,…,Zm)(x). One can show that (under mild conditions, via Sklar’s theorem; e.g. Wikipedia “copula”), for the joint distribution, FZ = cΘ(FZ1,…FZm), i.e. a function of the marginals, with cΘ called the copula parameterized by Θ. Once estimated, the conditional distributions can be calculated, which is effectively what we want from the transfer functional. Again, this approach still remains to be tested in practice for Rn variables. The uncertainty of the sampling procedure includes, as applicable, sampling proper, sample processing, measurement, but also uncertainty of the definition of the quantity (e.g., short term measurement as estimate of long-term mean, incomplete and inaccurate knowledge of controlling factors) and uncertainty due to the sampling design (related to representativeness of sampling), i.e. all kind of longitudinal uncertainty. Establishing a complete and reliable uncertainty budget has not yet been achieved.

Variability models, log-normal modelling Log-normal modelling (e.g. Miles and Appleton 2005; Cinelli et al. 2011) assumes that locally, i.e. over a given spatial unit, Rn is univariately log-normally distributed. This allows simple estimation of exceedance probabilities, which are considered hazard proxies, p(U) := prob[Z >T](U) = Φ((µ(U) – ln T) / σ(U)), for Z~LN(µ(U), σ(U)) within spatial unit U, T a threshold, and Φ standard normal. The parameters µ and σ can be estimated from data, if enough are available within U. Otherwise one has to resort on default values assigned to geological units, or variability models for σ. These can also help Bayesian refining local estimates. This kind of modelling does not account for spatial correlation structure within unit U, i.e. skips geostatistics, which makes the procedure much simpler. However, the underlying variability model remains a crucial issue. The empirical dispersion calculated from the data stems not only from the spatial variability of Z over U, but also from uncertainty of data themselves. Thus the “objective” variability Var[Z](U) will be smaller than the observed empirical Var({zi})(xi∈U). One may think on a variance decomposition of the type, Var({zi}) = Var[Z] + E[σ²i], the latter term being the individual data uncertainty. In any case, one would like to have a model of Var[Z](U) or at least of Var({zi})(U). As an example of the latter, for the Friedmann RP in Austria (essentially a normalized indoor concentration; Friedmann 2005) an approximate power-type dependence of the coefficient of variation (CV({zi})) on radius of a circular U has been found, as shown in Figure 2.


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2

CV

1.3 1 0.9 0.8 0.7

slope=0.343±0.007 r=0.995 rmin=1 km, rmax=100 km

0.6 0.5 0.4 1000

10000

100000

radius (m)

Figure 2: dependence between mean coefficient of variability (CV) of the radon potential in a circle, and its radius Again this remains to be verified for other datasets, and the full distribution FZ(U) should be investigated in dependence of |U|, instead of just the dispersion measure CV. The investigation of the rich dataset of the European indoor map (status described in Tollefsen et al. 2011) showed that the dispersion within 10 km x 10 km cells (which are the mapping supports), which equals mean geometric standard deviation (GSD) = 2.1, is not regionally constant. Instead, there seems to be slight dependence on Rn level itself, GSD ~ GM (geometrical mean), which would suggest a “proportional effect” (e.g. Manchuk et al. 2009). At the moment it is however not clear to which degree this might be a sample size effect, since as a consequence of sampling designs in some countries (UK, FI, BE), regions with higher Rn levels have been sampled more intensively. From a physical point of view one may assume that dispersion depends on geology, because different geological structures may be heterogeneous to a different degree. There are no investigations about this question yet, to my knowledge.

Anomalies In a spatial setting, an anomaly is an observation which does not match the observations in its neighbourhood, or its spatial support, i.e. the area on which this anomalous observation occurs. Outlier is called an observation within a data set which does not match the assumed parent distribution of the set. A spatial anomaly is not necessarily an outlier from the univariate, or marginal data distribution, nor is a

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univariate outlier necessarily an anomaly. However, in the conceptual framework of random fields, a sample, or local realization, which is anomalous with respect to its vicinity, is by definition an outlier of the expected conditional multivariate distribution over this vicinity; “conditional” is to be understood as subject to observations and structural information on the field, such as its variogram. Since an observation is the result (a) of the process which one wants to assess and (b) of the observation process (sampling design and procedure, measuring), the physical cause for an anomalous value can be either process. Anomalies of type (a) are “true” ones and will be retained, as they are actually valuable information about the investigated phenomenon, while one will try to correct for type (b). The tasks are therefore: 1. to find a method to identify anomalies; 2. to distinguish between the two types; 3. if it is of type (b), to correct for it. Neither task is trivial. Ideally, the result of any method (1) should be independent of the absolute size of a value, but dependent only on the local structural properties, i.e. “second-order stationary”. First attempts were made in course of the European indoor Rn map, as part of QA: In its first stage a simple algorithm was applied which fulfils the requirement only to some extent. It is based on the statistics of differences between means of neighbouring cells; for details see Dubois et al. 2010. Better methods may be based on local conditional estimation uncertainty, or on analysis of local Hölder exponents. The latter is based on a concept stemming from analysis (e.g. Wikipedia “Hölder condition”; important in multifractal analysis, e.g. Muzy et al. 1994, Meneveau and Chhabra 1990 or Struzik 2000). In our context the local Hölder exponent, also called singularity strength, is defined, α(x) := - lim (δ→0) log(Z(Vδ(x)) / log(δ), with Vδ(x) : a vicinity of linear size (like radius) δ around x; Z(Vδ(x)) : the expectation of Z within V. The Hölder exponent may be interpreted as local measure of anomaly. For its “coarse” estimate, e.g. Cheng 1999 (eq. 14) proposed: α = - ln(Z(Vδ1) / Z(Vδ2)) / ln(δ1 / δ2), for two “small” vicinities around x. This works well for spatially regular samples, like grid cells but badly, however, for irregularly located samples, and a more complicated algorithm has been proposed in Bossew (2008). For Figure 3, the α were computed for the European indoor Rn data, the empirical distribution calculated and the cells flagged whose p(α) values exceed 0.1 and 1% critical limits. High p values (red) denote “hot spots”, low values (blue), “cold spots”. Vδ1 and Vδ2 were defined as 3x3 cells and the central cell, respectively. Each cell is


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10 km x 10 km large, Z is the arithmetical mean of individual indoor concentration measurements (ground floor, long-tern average).

Figure 3: Anomalies identified according to the Hölder criterion Radon-prone zone Conceptually, Radon prone zones (RPZ) are called areas in which one must expect particularly high Rn concentrations (indoor, or some geogenic potential). Although this sounds intuitively simple, it is not if an exact definition is attempted. A first logical approach could be a connected set, or “patch” AE, AE := {x: E[Z](x) > T}; closely related to what has been called excursion set by Adler (1981). (A set is connected if any two points within can be connected by a curve fully contained in the set.) However, if a field Z is sufficiently rough (e.g. with high Hölder exponents), deliberately many deliberately small such patches will occur. Practically, one will therefore modify the definition, AE = ∪ V: E[Z](x∈V) > T , again connected. In words, this is the patch of connected pixels (V), in each of which the expectation of Z(x) is greater than T. Obviously AE depends on the pixel size |V|: Reducing it may cause a zone AE to be divided in several disconnected fragments; likewise, larger pixels (lower map resolution)

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may let distinct patches merge into one. This means, that a RPZ depends on the resolution of the map (pixel size |V|) of which it is composed, but this effect seems inevitable. One just has to keep it in mind. A second approach is the following. In the conceptual framework of random fields, given observations {zi}, there are infinitely many possible realizations of Z(x), conditional to the observations. A logical definition of RPZ is therefore, the mean area of all connected excursion sets resulting from possible realizations, EA := E[{x: Z(x) > T}]. A “pixelized” version can be designed as above. The two definitions of the RPZ give different results, in general, since the mean of many “random objects” EA is not the same as the union of means AE. In practice, the EA concept means calculating a “mean” of differently shaped and sized areas. While this is clear for the size, one would still have to discuss what it means for the shape of an area. A pragmatic way which in fact is followed by some goes like this: The domain – in practice a country – is divided into administrative units, and a mean Rn value is assigned to each unit. If this value exceeds a threshold, the unit is called RPZ. Of course, such “rough” approach renders the above considerations irrelevant.

References 1. R. J. Adler: The geometry of random fields. John Wiley & Sons, (1981) 2. A. S. Almeida, A. G. Journel: Joint simulation of multiple variables with a Markov-type coregionalization model. Mathematical Geology, 26(5), 565–588, (1994) 3. P. Bossew: Anomalies in environmental radiometric fields, part 2: Identifying anomalies based on the local singularity strength. Report, (2008) 4. P. Bossew, G. Dubois, T. Tollefsen: Investigations on indoor Radon in Austria, part 2: Geological classes as categorical external drift for spatial modelling of the Radon potential. Journal of Environmental Radioactivity, 99 (1), 81–97, (2008) 5. Q. Cheng: Multifractality and spatial statistics. Computers and Geosciences 25(9), 949–961, (1999) 6. J-P. Chilès, P. Delfiner: Geostatistics - modelling spatial uncertainty. John Wiley & Sons, (1999) 7. G. Cinelli, F. Tondeur, B. Dehandschutter: Development of an indoor radon risk map of the Walloon region of Belgium, integrating geological information. Environmental Earth Sciences, 62, 809– 819, (2011) 8. G. Dubois, P. Bossew, T. Tollefsen, M. De Cort: First steps towards a European atlas of natural radiation: status of the European indoor radon map. Journal of Environmental Radioactivity, 101(10), 786–798, (2010)


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9. H. Friedmann: Final results of the Austrian Radon Project. Health Physics, 89, 339–348, (2005) 10. P. Goovaerts: Geostatistics for Natural Resources Evaluation. Oxford University Press, Oxford, (1997) 11. P. Goovaerts: Ordinary cokriging revisited. Mathematical Geology, 30(1), 21–42, (1998) 12. T. Hengl, G. B. M. Heuvelink, A. Stein: A generic framework for spatial prediction of soil variables based on regression-kriging. Geoderma, 120, 75–93, (2004) 13. A. Horta, A. Soares: Direct sequential co-simulation with joint probability distributions. Mathematical Geosciences, 42, 269–292, (2010) 14. J. G. Manchuk, O. Leuangthong, C. V. Deutsch: The Proportional Effect. Mathematical Geosciences, 41(7), 799–816, (2009) 15. Ch. Meneveau, A. B. Chhabra: Two-point statistics of multifractal measures. Physica A, 164, 564–574, (1990) 16. J. C. H. Miles, J. D. Appleton: Mapping variation in radon potential both between and within geological units. Journal of Radiological Protection, 25, 257–276, (2005) 17. J. F. Muzy, E. Bacry, A. Arneodo: The multifractal formalism revisited with wavelets. International Journal of Bifurcation and Chaos, 4(2), 245–302, (1994) 18. N. Remy, A. Boucher, Wu Jianbing: Applied Geostatistics with DGeMS. Cambridge University Press, Cambridge, (2009) 19. A. Soares: Direct sequential simulation and cosimulation. Mathematical Geology 33(8), 911–926, (2001) 20. Z. R. Struzik: Determining local singularity strength and their spectra with the wavelet transform. Fractals, 8(2), 163–179, (2000) 21. T. Tollefsen, V. Gruber, P. Bossew, M. De Cort: Status of the European Indoor Radon Map. Radiation Protection Dosimetry, 145(2-3), 110–116, (2011) 22. G. Verly: Sequential Gaussian co-simulation: A simulation method integrating several types of information. Geostatistics Troia '92. Proceedings of the 3rd International Geostatistical Congress, Troia, Portugal, Kluwer Academic Publishers, 2, Dordrecht, 543–554, (1993)

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DÓZISBECSLÉSI MÓDSZEREK AZ ÚRKÚTI MANGÁNÉRC-BÁNYÁBAN Vigh Tamás1, Kávási Norbert2, Kovács Tibor3, Vaupotič Janja4, Jobbágy Viktor5, Tetsuo Ishikawa2, Hidenori Yonehara2 1

2

Mangán Bányászati és Feldolgozó Kft, Úrkút Research Center for Radiation Protection, National Institute for Radiological Sciences, Chiba 3 Pannon Egyetem, Radiokémai és Radioökológiai Intézet, Veszprém 4 Department of Environmental Sciences, Radon Center, Jožef Stefan Institute, Ljubljana 5 Radioökológiai Tisztaságért Társadalmi Szervezet, Veszprém Abstract In connection with dose estimation, one of the important parameters of the dose conversion factor is the ratio of unattached short-lived radon progeny. Application of the dose conversion factor used in surface workplaces considerably reduces the reliability of dose estimation in the case of mines. During this work investigated the concentration of radon and its short-lived radon progeny and identified the unattached fraction of short-lived radon progeny. Equilibrium factor was calculated simultaneously at two faces of a Hungarian manganese ore mine. During working hours the average radon concentrations were 220 Bq m-3 and 530 Bq m-3 at the faces; the average short-lived progeny concentration was 90 Bq m-3 and 190 Bq m-3, the average equilibrium factors were 0.46 and 0.36, and the average unattached fractions were 0.21 and 0.17. The calculated dose conversion factor was between 9 and 27 mSv WLM-1.

Bevezetés Az 1996. évi CXVI. sz., az atomenergiáról szóló törvény 2000-ben megjelent 16/2000 (VI. 8.) EüM sz. végrehajtási rendelete 2. számú mellékletének a dóziskorlátok, radonkoncentrációk munkavállalókra vonatkozó cselekvési szintjei című I. fejezete szerint az 1.3 és a 2-es pontjai, illetve ezen melléklet 1. számú függelékének 26. pontja, valamint a sugárterhelés ellenőrzése című IV. fejezet 1.5 és 1.6 pontjai alatt találhatók a területre vonatkozó előírások [16/2000. (VI. 8.) EüM rendelet az atomenergiáról szóló 1996. évi CXVI. törvény egyes rendelkezéseinek végrehajtásáról]. Ugyanezen rendelet 1. sz függelék a 2. sz. melléklethez című fejezete konkrétan előírja, hogy földalatti bányaüzemek munkavállalóinak sugárterhelését akkor is ellenőrizni kell, ha az kizárólag természetes forrásból ered. A végrehajtási rendelet 2003. január 1.-ével lépett életbe. A végrehajtási rendelet cselekvési szintként éves átlagban 1000 Bq/m3-t határoz meg a radon koncentrációjára nézve levegőben. Dózisbecsléssel kapcsolatban az alkalmazandó egyensúlyi faktorra és dóziskonverziós tényezőre vonatkozóan a rendelkezések nem tartalmaznak leírást. Az ICRP által ajánlott 0,4-es egyensúlyi faktorral és 7,9⋅10-9 Sv/Bqhm-3 dóziskonverziós tényezővel számítva, 1000 Bq/m3-es radon-koncentráció 6,3 mSv sugárterhelést jelent.

Vigh T., Kávási N., Kovács T., Vaupotič J., Jobbágy V., Ishikawa T., Yonehara H.

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A munkavállalókra ható éves effektív dózis számításának módszerei A munkavállalóra ható effektív dózis számítása az alábbiak szerint valósítható meg: 1. módszer: jogszabály előírása és az ICRP ajánlásai alapján, 2. módszer: az egyensúlyi faktor egyedi meghatározása alapján, 3. módszer: a radon rövid felezési idejű leánytermékei kötött és nem kötött frakciójának egyedi meghatározása alapján.

1. Módszer részletesen A fentebb ismertetett jogszabályi rendelkezések és az ICRP ajánlásaiban szereplő DCF és F értékek alkalmazásával történik az éves effektív dózis meghatározása az alábbi képlet szerint:

E = CRn ⋅ F⋅ t ⋅ DCF

(1)

ahol: E - éves effektív dózis [mSv/év], t - tartózkodási idő [h/év], DCF - munkahelyre vonatkozó ICRP dóziskonverziós tényező [7,9⋅10-9 Sv/Bqhm3], F - 0,4 az ICRP65 ajánlása alapján.

2. Módszer Kávási (2006) korábbi vizsgálatai alapján javasolta, hogy a munkavállalók radontól származó becsült sugárterhelése jelentősen pontosítható az egyensúlyi faktor egyedi meghatározásával. Az egyensúlyi faktor meghatározása az egyensúlyi ekvivalens koncentráció közvetlen mérése alapján történik, ami Pylon WLx műszer segítségével határozható meg. A Pylon WLx műszer által jelzett munkaszint értékekből a következőképpen számolható az egyensúlyi ekvivalens koncentráció:

EEC = WL ⋅ 3700 ahol:

(2)

EEC - egyensúlyi ekvivalens koncentráció [Bq/m3], WL - munkaszint.

Egyensúlyi faktor számítása

F = EEC/CRn ahol: F - egyensúlyi faktor, CRn - a mért radon-koncentráció [Bq/m3].

(3)


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3. Módszer A bányában munkaidőben a radonkoncentráció éves átlaga a cselekvési szint alatt van. A fenti számítási módszerek alapján a sugárterhelés kisebb, mint 6,3 mSv/év, ugyanakkor az ICRP65-ben is megfogalmazásra került, hogy egy lakásban és egy bányában mért ugyanazon radontól ill. leányelem-koncentrációból származó sugárterhelés nem lehet azonos, mivel eltérőek a levegő minőségi paraméterek (páraés aeroszoltartalom), melyek hatással vannak a leányelemek levegőben lévő arányára. Pontosabban a leányelemek kötött ill. nemkötött frakciójára, ami befolyásolja, hogy a légzőrendszer mely részei lesznek intenzívebb sugárterhelésnek kitéve. A sugárterhelés nagyságát a nehéz fizikai munkavégzés által kiváltott nagyobb légzésteljesítmény is befolyásolja. A levegőbe jutó radonból keletkező rövid életű leányelemek rendszerint pozitív töltésű ionok, amelyek rövid idő alatt 10 nm-nél kisebb ioncsoportokat (cluster) képeznek a levegőben levő vízzel, oxigénnel vagy nyomnyi mennyiségű egyéb gázokkal. Ezeket a cluster-eket hívjuk nemkötött bomlástermékeknek. A cluster-ek néhány másodperctől pár percig tartó idő alatt rátapadnak a környező tárgyak felületére illetve aeroszolokra. Ezeket az aeroszolokat, amelyek mérete 10-1000 nm-ig terjed, kötött frakciónak nevezzük. Amennyiben a fenti paramétereket mérni tudjuk, akkor azt érvényesíteni lehet a DCF meghatározása során. Erre többféle modell létezik, jelen munkában a Porstendörfer által meghatározott metódust alkalmaztuk. A leányelemek nem kötött frakciójának számításához használt összefüggés: f un =

c cun + catt un

(4)

ahol: fun - nem kötött frakció, Cun - a radon rövid felezési idejű nem kötött leányelemeinek potenciális alfa-energia koncentrációja (nJ m-3), Catt - a radon rövid felezési idejű kötött leányelemeinek potenciális alfa-energia koncentrációja (nJ m-3). A dóziskonverziós tényező számításához alkalmazott ún. Porstendörfer-formula, az fun ismeretében: Szájon át történő belélegzés esetén: DCFM = 101 fun + 6,7(1-fun)

(5)

Orron át történő belélegzés esetén: DCFN = 23 fun + 6,2(1-fun)

(6)

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ahol: DCFM/N - a dózis konverziós tényező, M index esetén szájon, N index esetén orron keresztül történő belélegzés esetén [mSv WLM-1]. Kombinált DCF nehéz fizikai munkavégzés (pl. bányászok) esetére: DCFC = 0,6 DCFM + 0,4DCFN

(7)

ahol: DCFC - a dózis konverziós tényező kombinált légzés esetén. A munkavégzőkre ható effektív dózis számítása a DCF meghatározását követően az alábbiak szerint történt: F ⎞⎛ t ⎞ ⎛ E = ⎜ C Rn ⎟⎜ ⎟ DCF 3700 ⎝ ⎠⎝ 170 ⎠

(8)

ahol: E- effektív dózis [mSv/év], t - munkaidő [h/év]. Mind a nemzetközi ajánlások, mind az európai országok legtöbbje és a hazai szabályozás is a cselekvési szintet éves átlagra vonatkoztatják. Ez logikusan azt jelenti, hogy legalább egy teljes éven át tartó vizsgálatsorozattal határozható meg a cselekvési szint.

Korábbi eredmények az 1. és 2. módszerrel Kávási N. PhD-dolgozatában foglalta össze először a vizsgált területen meghatározott dózis-értékeket (Kávási, 2006) és fogalmazott meg módszertani jellegű megállapításokat a bányászati dózisbecslés gyakorlati kivitelezését illetően. Téziseiben megállapította, hogy a dózisbecsléshez alapul vett radon-koncentrációk egzakt meghatározásához bányák esetén minimum egy évre kiterjedő méréssorozatot kell felvenni. A különböző munkafolyamatokkal érintett területeken eltérő radonkoncentrációk alakulhatnak ki, ezért törekedni kell a munkavégzők által huzamos tartózkodással érintett valamennyi terület felmérésére. Megállapította, hogy a bányabeli körülmények között mért egyensúlyi faktor az ajánlott értékhez (0,4) képest jelentős eltérést is mutathat, ezért földalatti munkaterületek esetén törekedni kell a meghatározására. Megállapította továbbá, hogy mivel a földalatti légterek radonkoncentrációja jelentősen függ a szellőztetés alkalmazási körülményeitől, a dózisbecslést a munkaidő alatt mért radon-koncentráció alapján kell elvégezni. Vizsgálatai során megállapította, hogy a mangánércbánya különböző munkakörökben dolgozó munkavállalóinak sugárterhelése nem éri el az évi 5 mSv-et, sem az irodalomban ajánlott F=0,4, sem az általa meghatározott F=0,58 egyensúlyi faktorral számítva.


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A 3. módszer eredményei A 2009. augusztus 11-19 közötti időtartamban kettő mérési pont kijelölésére nyílt lehetőség, mindkettőt termelő munkahelyen alakítottuk ki. Az 1. ábrán „3” számmal jelölt mérési pont a 3. munkahelyet, az „5” számmal jelölt mérési pont az 5. munkahelyet jelenti. Utóbbi esetén a mérőhely azonos volt a 2009. januári mérésekkel. A méréseket Pylon Wlx berendezéssel végeztük, így a radon aktivitás-koncentráción túl az egyensúlyi ekvivalens koncentráció és az egyensúlyi faktor meghatározására is sor kerülhetett.

1. ábra: Mérési hálózat 2009. augusztus 11-19. között Az eredményeket a 2. és 3. ábrán közöljük. Mindkét munkahelyen munkaidőn kívül 3000-4000 Bq/m3 aktivitáskoncentráció alakul ki. Ezt azonban a szellőztető rendszer rövid idő alatt 100-500 Bq/m3 körüli értékre csökkenti (5. munkahely esetében átlagosan 220, szélsőértékben 110-625, 3. munkahely esetében 530, szélsőértékben 340-820 Bq/m3). A szellőztető rendszer leállítását követően csaknem ugyanilyen gyorsan vissza is áll az eredeti érték. A 3. munkahelyen hétvégén igen nagy érték is kialakult (8000 Bq/m3).

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2. ábra: A 3. munkahely eredményei (Megjegyzés: a függőleges vezetőrácsok az adott nap 12.00 óránál vannak)

3. ábra: Az 5. munkahely eredményei. (Megjegyzés: a függőleges vezetőrácsok az adott nap 12.00 óránál vannak)


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Összevetve az eredményeket a korábbi években végzett folyamatos és integrális mérésekével, azt találjuk, hogy a 2009.-ben mért értékek nagyobbak. Az 5. munkahely 2004. évi folyamatos radonmérése alkalmával átlagosan 700, a 3. munkahelyen 400 Bq/m3 munkaidőn kívüli radonkoncentrációt mértünk, míg 2009.-ben ez az érték átlagosan 3000-4000 Bq/m3. A bányalevegő radon-koncentrációjának korábbi integrális és folyamatos méréssorozatai alapján egyértelműen megállapítható, hogy a szellőztető rendszer üzemeltetése nélkül nagyobb radon-koncentrációk alakulnának ki a bányában. Megállapítható ugyanakkor az is, hogy a szellőztető rendszer a jelenlegi kivitelében alkalmas arra, hogy több napos üzemszünet (hétvége) után kialakuló nagy radonkoncentrációkat is rövid idő alatt hatékonyan csökkentsen. A radontól származó tényleges sugárterhelés becsléséhez elengedhetetlen fontosságú az egyensúlyi faktor ismerete. A földalatti munkahelyeken Kávási (2006) vizsgálatai alapján az eltérő légcsere, illetve a speciális munkafolyamatok miatt a szakirodalomban javasolt 0,4-es értéktől jelentősen eltérő értékek is adódhatnak. Ezért a radonkoncentráció mellett szükséges mérni a munkaszintet is, továbbá meghatározni a tényleges egyensúlyi faktort illetve időbeli változásait. A 2009. aug. 11.-19. között, két munkahelyen végzett folyamatos radon- és munkaszint-mérés eredményei alapján meghatározott egyensúlyi faktort és annak időbeli változását a 2. és 3. ábrán bemutattuk. Az 1. táblázatban közöljük a munkaidőben mért egyensúlyi faktor átlagos, illetve szélsőértékeit.

1. táblázat: Az egyensúlyi faktor értékei a 3. és 5. munkahelyeken 2009.08.11.-19. között Munkahely 3 5

Átlaga 0,36 0,46

Egyensúlyi faktor Minimuma 0,21 0,27

Maximuma 0,58 0,74

Az egyensúlyi faktorra vonatkozó fenti átlagértékek közel állnak az irodalomban ajánlott F=0,4 értékhez. Az ICRP által ajánlott dóziskonverziós tényezővel, 1848 óra éves tartózkodással és a fent megadott, munkaidőre vonatkozó átlagos radon koncentrációval számolva az effektív dózis a 3. munkahelyen E = 2,8 mSv/év, az 5. munkahelyen E = 1,5 mSv/év értékben határozható meg. Mindkét érték messze alatta marad a 6,3 mSv/év határértéknek. A munkahelyi radontól származó dózisbecslés a fentebb ismertetett 3. módszer szerint is elvégezhető, ha a dóziskonverziós tényezőt az ajánlott érték alkalmazása helyett közvetlenül meghatározzuk. Ehhez szükséges a radon rövid felezési idejű leánytermékei nemkötött frakciójának (fun) meghatározása. A fenti mérés során erre is lehetőség nyílt. Az erre vonatkozó eredményeket a 4. ábrán mutatjuk be.

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4. ábra: A radon rövid felezési idejű leánytermékei nemkötött frakciója 2009. aug. 11.-19. között a 3. és 5. munkahelyen (Megjegyzés: a függőleges vezetőrácsok az adott nap 12.00 óránál vannak) A 4. ábrán jól látható, hogy a szellőztető rendszer a nemkötött frakció értékére is hatást gyakorol, ami azt bizonyítja, hogy a sugárterhelés szempontjából az egyik igen fontos paraméter befolyásolható, a bányaszellőztetés megfelelő alkalmazásával csökkenthető. A másik említésre méltó jelenség, hogy hétvégén, természetes körülmények között akár 0,8 is lehet az fun értéke, ami nagyban kiemeli a szellőztetés fontosságát, mivel ennek hiányában többszörös dózisra kell számítani a munkaidőben jellemző értékhez képest. Ez felhívja a figyelmet arra, hogy szellőztetés hiányában hosszú idejű tartózkodás a bányában kerülendő. A mérés ideje alatt munkaidőben a fun átlaga az 5. munkahelyen 0,33 (min-max sáv: 0,22-0,46), a 3. munkahelyen 0,17 (0,07-0,23) volt. Figyelemre méltó a kétszeres különbség, ami e paraméter tekintetében is az 5. munkahely javára fennáll. A fentebb megadott összefüggések segítségével meghatározható a kombinált dóziskonverziós tényező, majd ebből az effektív dózis, az egyéb paraméterek változatlanul hagyása mellett. Ekkor az éves effektív dózis az 5. munkahely esetében E5 = 8,14 mSv/év, a 3. munkahely esetében E3 = 9,66 mSv/év értéknek adódott. Meg kell jegyezni, hogy az fun paraméter mérését az ismertetett egyetlen alkalommal hajtottuk végre, nyári időszakban. Feltételezhető, hogy az fun értékének alakulását is befolyásolja a radonméréseknél tapasztalt szezonális ingadozás. Ezért javasolható a mérést a téli és nyári időszakban, lehetőleg több hónapban, visszatérő jelleggel megismételni és az éves effektív dózis meghatározásához az fun értékét e mérésekből képzett statisztikai átlag formájában célszerű figyelembe venni.


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Következtetések Az eltérő módszerek alapján végzett dózisbecslés eltérő eredményt hozott. A munkavédelmi kockázatértékelés logikája szerint ilyen esetekben a munkavállalóra nézve kedvezőtlenebb eredményt kell figyelembe venni és ennek megfelelő intézkedéscsomagot kidolgozni. Esetünkben a probléma tüneti kezelését két oldalról lehet megvalósítani: a szellőztetés fokozásával vagy a tartózkodási idő csökkentésével. Azonban a szellőztetés fokozásának is van egészségkárosító hatása, amelynek kockázata becsülhetően nagyobb, mint ebben az esetben a sugárvédelmi kockázat (krónikus légúti megbetegedések, sorozatos meghűlés, reuma, egyéb krónikus gyulladásos állapotok, stb.). A tartózkodási idő csökkentése a bánya hatósági úton történő sugárveszélyessé minősítése útján valósítható meg. Ennek indokoltsága azonban aggályos. Egyfelől a nemzetközi sugárvédelmi gyakorlatban elegendő az ajánlásokban szereplő dóziskonverziós tényező alkalmazása, és mint láttuk, ezt alkalmazva a munkahely megfelel az előírásoknak. Másfelől a jelenlegi állapot szerint alacsony a végrehajtott mérések száma egy ilyen intézkedés megalapozásához. Mindezeket figyelembe véve az alábbi sugárvédelmi beavatkozásokat fogalmaztuk meg a bánya vezetése felé: ● Az áthúzó szellőztetést és a munkahelyi szellőztetést nyári időszakban munkakezdés előtt 2 órával javasolt megkezdeni, a berendezések automatizált indításával. ● A szellőztető berendezéseket el kell látni olyan berendezéssel, ami működésképtelenségüket állandó felügyelet alatt álló helyszínre (esetünkben külszíni portaszolgálat) hang- és fényjelzéssel kijelzi. Szervezési intézkedésekkel meg kell valósítani az ilyen esetekre az azonnali javítás lehetőségét (ügyeletes karbantartó szakember és aknaszállítógép-kezelő folyamatos alkalmazásával). ● A szellőztetési rendszer ellenőrzésére fokozott figyelmet kell fordítani (a gépészeti berendezések, a villamos energia-ellátó berendezések, a légterelő berendezések, a vágatok, a különszellőztető csővezetékek állapotának ellenőrzése, munkahelyi légcsere mérése stb.). ● A szellőztetés tartós szüneteltetése vagy meghibásodása esetén a földalatti térségekből a munkavállalókat ki kell vonni és csak a felelős műszaki vezető által meghatározott szellőztetési időtartamot követően lehet a bányát újratelepíteni. ● A személyi dozimetria módszereivel célszerű ellenőrizni a dolgozók tényleges sugárterhelését.

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Felhasznált irodalom 1. W. D. Bennett, K. L. Zeman, A. M. Jarabek: Nasal contribution to breathing with exercise: effect of race and gender. Journal of Applied Physiology, 95, 497–503, (2003) 2. M. Karmi: Mine health and safety management. Society for Mining, Metallurgy and Exploration, Inc. Littleton, 297–306, (2001) 3. T. C. Chu, H. L. Liu: Simulated equilibrium factor studies in radon chamber. Applied Radiation Isotopes, 47(5), 543–550, (1996) 4. V. Dankelmann, A. Reineking, J. Porstendörfer: Determination of neutralization rates of 218Po ions in air. Radiation Protection Dosimetry, 94(4), 353–357, (2001) 5. Eff-Darwich, R. Viñas, V. Soler, J. de la Nuez, M. L. Quesada: Natural air ventilation in underground galleries as a tool to increase radon sampling volumes for geologic monitoring. Radiation Measurements, 43(8), 1429–1436, (2008) 6. EüM, 2000. 16/2000. (VI. 8.) EüM rendelet. Az atomenergiáról szóló 1996. évi CXVI. törvény egyes rendelkezéseinek végrehajtásáról. Magyar Közlöny, 55, Budapest, 3214–3215, (2000) 7. W. Hofmann, R. Bergmann, I. Balásházy: Variability and inhomogenity of radon progeny deposition patterns in human bronchial airways. Journal of Environmental Radioactivity, 51(1), 121–136, (2000) 8. IAEA, 1994. International Atomic Energy Agency. International Basic Safety Standards for Protection against Ionizing Radiation and for the Safety of Radiation Sources. Safety Series No. 115-I. IAEA, Vienna, (1994) 9. ICRP, 1987. International Commission on Radiological Protection. Lung cancer risk from indoor exposures to radon daughters. ICRP Publication 50, Oxford, (1987) 10. ICRP, 1991. International Commission on Radiological Protection. Recommendations of the International Commission on Radiological Protection. ICRP Publication 60, Oxford, (1991) 11. ICRP, 1994a. International Commission on Radiological Protection. Protection against 222Rn at home and at work. ICRP Publication 65, Oxford, (1994) 12. ICRP, 1994b. International Commission on Radiological Protection. Human respiratory tract model for radiological protection. ICRP Publication 66, Oxford, (1994) 13. N. S. Jarvis, A. Birchall, A. C. James, M. R. Bailey, M. D. Dorrian: LUDEP 2.0, personal computer program for calculating internal doses using the ICRP 66 respiratory tract model. National Radiological Protection Board, NRPB-SR287, Chilton, (1996) 14. N. Kávási: Az évi átlagos radon-koncentráció és a sugárterhelés meghatározása különböző munkaterületeken, Doktori (PhD) értekezés, Pannon Egyetem, Veszprém, (2006)


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A Preliminary Radon Study in Pál-völgy Cave (Budapest, Hungary)

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A PRELIMINARY RADON STUDY IN THE PÁL-VÖLGY CAVE (BUDAPEST, HUNGARY) Nagy Hedvig Éva1,2, Szabó Csaba1, Horváth Ákos2, Kiss Attila3 1

Eötvös University, Department of Petrology and Geochemistry, Lithosphere Fluid Research Lab, Budapest 2 Eötvös University, Department of Atomic Physics, Budapest 3 Danube-Ipoly National Park Directorate, Pál-völgy Cave, Budapest Abstract We had been doing radon measurements in Pál-völgy Cave (Budapest, Hungary) for one and a half year. The main aim of our study was to determine the time dependent radon concentration and the sources of the radon in the cave. The radon concentration in the cave air had been measured continuously by AlphaGUARD radon monitor and outside the cave meteorological parameters had also been collected simultaneously. The radon concentration of the air in the Pál-völgy Cave varied between 104-7776 Bq/m3, the average value was 1884±85 Bq/m3 (for one year). These data strongly depends on the outside air temperature. If the temperature outside is higher than inside the cave (12 °C) the radon concentration increases. This is the reason of the seasonal periodicity of radon concentration typical of caves. The correlation coefficient between the radon concentration in the cave and the outside air temperature is 0.76. To determine the source of the radon, besides the wall rock Szépvölgy Limestone and Buda Marl, clayish cave sediments have been collected for physical and geochemical analysis. Content of such radioactive isotope as 226Ra, 232Th, 40K in the clayish cave sediments show results typical for soils. However, the radon and thoron exhalation rates of these samples, 2-12 Bq/kg for 222Rn and 1-12 Bq/kg for 220Rn, respectively, are higher than expected based on the 226Ra content. These results can be related to high percentage of fine grain size fraction corresponding to high specific surface, which provides high possibility and feasibility of radon exhalation.

Introduction Radon-222 is an inert radioactive element with a half-life of 3.8 days. It belongs to the radioactive uranium series and occurs in soil gas in varying activities (1). There are three radon isotopes (219Rn action, 220Rn thoron, and radon 222Rn) which are gaseous and they may be released from the ground, rocks and also from building materials and are accumulated with their short-lived daughters in closed spaces. Radon gas, once released, is normally dispersed into the atmosphere. However, radon, that enters poorly ventilated enclosed spaces, including natural caves and basements of homes, can build up to harmful concentrations (2). When radon gas is inhaled densely ionizing alpha particles can interact with biological tissue in the lungs. Since even a single alpha particle can cause major genetic damage to a cell, therefore it is unlikely that there is a threshold concentration

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Nagy H. É., Szabó Cs., Horváth Á., Kiss A.

below which radon does not have the potential to cause lung cancer (3), which has been studied for several decades. It has been known for a long time that elevated radon activity concentrations may be found in underground places like in karst caves (4, 5, 6, 7, 8, 9, 10, 11). The values depend on the radon exhalation rate from the surfaces in the cave, the volume and shape of the cave, the inflow of outside air and the degree of its mixing with the cave air. The influence of meteorological conditions on the radon levels and their temporal variations depends mostly on the shape of the cave and the number and directions of cracks and fissures connecting the cave rooms with the outdoor atmosphere (12). In karst areas, radon can migrate under the surface (13). Our major goal was to determine the time dependence and the source of the radon in the Pál-völgy show cave by study of clayish cave sediments.

Studied cave Pál-völgy Cave is situated in the Buda Hills, which is the NE part of the Transdanubian Central Range. The explored length of the cave is around 19 kilometeres, of which 500 meters is paved, lit, and open to the public (14). The wall rock of the cave is dominantly Eocene Szépvölgy Limestone Formation. Above the limestone Eocene Buda Marl and Oligocene Tard Clay are deposited. A huge multiphase hydrothermal cave system developed in the Szépvölgy Limestone and partially in the Buda Marl resulted in a long-term complex paleokarstic evolution from the Late Eocene to the Quaternary (15). The galleries of the maze system are decorated with characteristic dissolution forms and mineral precipitations, as well as with dripstones at some places. The mineral assemblage of the cave contains 22 types of speleothems, some of which are rare or even unique in Hungary (14). Six measurement points from seven are located in the Szépvölgy Limestone Formation, but one, the #6 measurement point is located in the Buda Marl Formation (Figure 1). The #2 measurement point was chosen for long term radon concentration monitoring, based on previous studies and short term measurements.


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Figure 1: The map of the studied cave section. The blue area is the show cave, the orange line marks our track, the green points with numbers are the measurement points Methods To determine the time dependence of radon concentration, we had been measuring the radon concentration constantly for one and a half years by use of AlphaGuard radon monitor with 1 hour integrated time. Simultaneously, meteorological parameters (i.e., air temperature, humidity, air pressure) were measured outside the cave by use of a meteorological station (FWS 20 Weather Station). To determine the source of the radon, clayish cave sediment samples were collected (from drilling and from the upper layer). The radon concentration in the air and the meteorological parameters (i.e., temperature, humidity and air pressure) were


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measured inside the cave. The radon and thoron exhalation rate by RAD 7 and radon chamber, and radioactive isotope content of 226Ra, 232Th, 40K by high purity germanium detector of clayish cave sediments were determined in laboratory.

Results Time dependence of radon concentration The radon concentration in the cave was measured continuously for one and a half years from October 2009 to February 2011. In the first four months the radon concentration was mostly below 1000 Bq/m3. The values are order of magnitude higher in the spring-summer period than in the autumn-winter period. In summer the radon concentration reached even 7000 Bq/m3 (Figure 2). The correlation coefficient between the radon concentration and the outside air temperature is 0.76. The average value of the cave air temperature is 12 °C. If the air temperature outside the cave is higher than this value the radon concentration increases inside the cave.

Figure 2: The result of long term radon concentration monitoring. The black line marks the values of radon concentration, the green line shows the outdoor air temperature


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Spatial distribution of radon concentration We measured the radon concentration in the cave by active detectors at four different points simultaneously to study the spatial variation of the radon concentration, which was higher farther from the entrance. In the same 16-hour measurement period the average radon concentration was 375 Bq/m3 at the closest point to the entrance (#2), at the second closest point (#3) this value was 478 Bq/m3, and at the next point (#5) it was 546 Bq/m3 (Figure 3). At the measurement point #6 which is located in the Buda Marl Formation of the cave, the average value of radon concentration was 1095 Bq/m3, this value is approximately twice as high as the values measured in the Szépvölgy Limestone Formation (Figure 3).

Figure 3: The average values of radon concentration in four different points inside the cave at the same 16-hour measurement period


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Figure 4: The time dependence of the radon concentration during the 16-hour measurement period at the four different measurement points The source of radon To determined the source of the radon, clayish cave sediments were collected by digging (from the upper layer) and by drilling. Specific activity of 226Ra, 232Th and 40 K, and the radon and thoron exhalation rates were measured on the samples. Our results (Table 1) are in the same order of magnitude than the worldwide average values for radionuclide concentrations in soils (16). The radium activity varies between 25-35 Bq/kg (limestone generally contains in average about 16-31 Bq/kg of 238U (17)) the thorium between 21-30 Bq/kg, and the potassium between 239-386 Bq/kg (Table 1). The results of radon and thoron exhalation rates show typical values for soils, except one sample, the clayish cave sediment sample, collected from the cave section, which is located in the marl. The radon exhalation rate of this sample was 12 s-1kg-1 (Table 1, #6 point).

Table 1: The specific 226Ra, 232Th, and 40K activity and radon and thoron exhalation rates of the clayish cave sediment samples collected from the surface. In the second column is the bedrock which is covered by clay Sample #2 point #3 point #5/1 point #5/2 point #6 point

Rock limestone limestone limestone limestone marl

226

Ra (Bq/kg) 27±4 26±4 37±5 35±4 32±4

232

Th (Bq/kg) 21±1 22±1 31±2 30±1 26±1

40

K (Bq/kg) 239±8 265±9 386±11 276±8 315±9

222

Rn (s kg-1) 2 2 2 5 12 -1

220

Rn (s-1kg-1) 1.0 1 2 3 2


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Two drillings were made inside the cave. At #2 measurement point it reached depth of 125 cm and at #5 point depth of 200 cm. The specific activity of radium, thorium and potassium, and radon and thoron exhalation rates were measured in the collected samples. All of these values are similar to those of average soil on the world (16).

Table 2: Specific 226Ra, 232Th, and 40K activity, and radon and thoron exhalation rates of clayish cave sediment samples collected by drilling at the #5 measurement point Sample

Depth

5A 5B 5C 5D 5E

0-10 cm 10-30 cm 30-145 cm 145-180 cm 180-200 cm

226

Ra (Bq/kg) 35±7 30±6 34±7 39±6 59±7

232

Th (Bq/kg) 28±3 27±3 28±3 31±2 30±3

40

K (Bq/kg) 298±15 313±16 345±15 366±15 352±17

222

Rn (s kg-1) 3 2 1 2 2 -1

220

Rn (s kg-1) 9 7 7 6 7 -1

Table 3: Specific 226Ra, 232Th, and 40K activity, and radon and thoron exhalation rates of clayish cave sediment samples collected by drilling at the #2 measurement point Sample

Depth

2A 2B 2C

0-40 cm 40-100 cm 100-125 cm

226

Ra (Bq/kg) 19±5 54±9 43±6

232

Th (Bq/kg) 18±2 39±4 26±2

40

K (Bq/kg) 200±11 353±20 265±13

222

Rn (s kg-1) 1 2 2 -1

220

Rn (s-1kg-1) 6 12 6

Discussion The measured radon concentration values can be compared to published data. Similar values have been measured in other karst caves (17). The arithmetic average of worldwide mean radon concentration is 2.8 kBq/m3 (17). During our measurement period (2009. October – 2011. February) the yearly average radon concentration in the studied cave was 1.9 kBq/m3. In 1993 the yearly mean radon concentration was 2.01 kBq/m3 in the same cave (18). Based on the simultaneously measured meteorological parameters and radon concentration, the latter one strongly depends on the outdoor air temperature. If the outdoor air temperature is lower than the cave air temperature, which is 12 °C, thus in autumn and in winter, the air is flowing from outside into the cave, and the radon concentration is low in the cave. However, in the reverse situation, when the outdoor air temperature is higher than the cave air temperature, the fresh air cannot flow into the cave, because the air is flowing out from the cave. Therefore, the new air is coming through the cracks, fractures and cavities of the carbonate rocks inside the cave and the radon concentration increases. Similar results were found by Duenas et al, (19) and Jovanovic (20). One year long continuous 222Rn level monitoring inside the Altamira Cave (northern Spain) shows values ranging from 186 Bq/m3 to 7120 Bq/m3,

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with an annual average of 3562 Bq/m3 (21). In the studied cave the radon concentration varied between 104-7776 Bq/m3, hence in the same order of magnitude as that of Pál-völgy Cave, but the annual average was still lower, 1884 Bq/m3 than in the Altamira Cave. Based on these, the degree of ventilation in the two caves is similar, however due to the differences in clime the annual average radon concentration is dissimilar. Based on the spatial variation of radon concentration (Figure 4), it is clear that the radon concentration is strongly dependents on the local ventilation, hence it is possible to obtain highly various results in the same cave at different places (22). Radon levels increased with increasing distance into the cave, i.e. away from the greater air ventilation that exists in the entrance areas (Figure 4). Gillmore et al (23) observed the same phenomena in a Permian limestone cave in UK. To sum up our knowledge in connection with the source of the radon, it can be stated that the radioactive isotope content of clayish cave sediments shows typical values for soils. The radon exhalation rate of the clayish cave sediment, collected from the Buda Marl, shows the highest value. Consequently, the radon concentration was two times higher in the section of the cave located in the Buda Marl than those in the Szépvölgy Limestone. These results suggest that the Buda Marl and the clayish cave sediments, derived from Buda Marl, are the most likely rock of the radon sources.

Conclusion The radon concentration of the air in the Pál-völgy Cave varied between 104-7776 Bq/m3, the average value is 1884±85 Bq/m3 (for one year) and it strongly depends on the outside air temperature. Content of such radioactive isotope as 226Ra, 232 Th, 40K in the clayish cave sediments show results typical for soils. Due to the higher content of smallest grain size fraction, the Buda Marl can be a candidate for radon source.

Acknowledgements We are grateful to Péter Völgyesi and Ábel Szabó for their valuable help during the measurements in the cave and to the fellows of the Lithosphere Fluid Research Lab.


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References 1. L. Oufni, M. A. Misdaq, M. Amrane: Radon level and radon effective dose rate determination in Moroccan dwellings using SSNTDs. Radiation Measurements, 40, 118–123, (2005) 2. A, Thompson, P. D. Hine, J. S. Poole, J. R. Greig: Environmental geology in land use planning: a guide to–good practice. Report to the Department of the Environment–Transport and the Regions, Symonds Travers–Morgan, East Grinstead, 80, (1998) 3. H. Zeeb, F. Shannoun: WHO Handbook on indoor radon, A public health perspective. World Health Organization, 95, (2009) 4. M. H. Wilkening, D. E. Watkins: Air exchange and 222Rn concentrations in the Carlsbad Caverns. Health Physics, 31, 139–145, (1976) 5. K. A. Yarborough: Radon- and thoron-produced radiation in Natural Park Service caves, Proceedings of the Symposium Natural Radiation Environment III, Washington D. C., U. S. Department of Energy, CONF 780422, 1371–1395, (1980) 6. P. L. Fernández, L. S. Quindós, J. Soto, E. Villar: Radiation exposure levels in Altamira Cave. Health Physics, 46, 445–447, (1984) 7. C. Papastefanou, M. Manolopoulou, E. Savvides, S. Charalambous: Natural radiation dose in Petralona Cave. Health Physics, 50, 281–286, (1986) 8. I. Kobal, B. Smodis, M. Skofljanec: Radon-222 air concentrations in the Slovenian karst caves of Yugoslavia. Health Physics, 50, 830–834, (1986) 9. I. Kobal, B. Smodis, J. Burger, M. Skofljanec: Atmospheric 222Rn in tourist caves of Slovenia, Yugoslavia. Health Physics, 52, 473–479, (1987) 10. L. S. Quindós, A. Bonet, N. Diaz-Caneja, P. L. Fernández, I. Guiterez, J. R. Solana, J. Soto, E. Villar: Study of the environmental variables affecting the natural preservation of the Altamira Cave paintings located at Santillana del Mar, Spain. Atmospheric Environment, 21, 551–560, (1987) 11. M. Bahtijari, J. Vaupotic, A. Gregoric, P. Stegnar, I. Kobal: Exposure to radon in the Gadime Cave, Kosovo. Journal of Environmental Radioactivity, 99, 343–348, (2008) 12. J. Hakl, I. Csige, I. Hunyadi, A. Várhegyi, G. Géczy: Radon transport in fractured porous media – Experimental study in caves. Environment International, 22, 433–437, (1996) 13. T. A. Przylibski: Radon concentration changes in the air of two caves in Poland. Journal of Environmental Radioactivity, 45, 81–94, (1999) 14. K. Takácsné Bolner: Pál-völgyi-barlang, Duna-Ipoly Nemzeti Park Igazgatóság, Kecskemét, (2004)

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15. L. Korpás, M. Lantos, A. Nagymarosy: Timing and genesis of early marine caymanites in the hydrothermal palaeokarst system of Buda Hills, Hungary. Sedimentary Geology, 123, 9–29, (1999) 16. J. Hakl, I. Hunyadi, I. Csige, G. Géczy, L. Lénárt, A. Várhegyi: Radon transport phenomena studied in karst caves – International experiences on radon levels and exposures. Radiation Measurements, 28, 675–684, (1997) 17. UNSCEAR (United Nations Scientific Committee on the Effects of Atomic Radiation) Annex B, United Nations, New York, (2008) 18. P. Szerbin: Natural radioactivity of certain spas and caves in Hungary. Environment International, 22(1), 389–398, (1996) 19. C. Duenas, M. C. Fernández, S. Canete: 222Rn concentrations and the radiation exposure levels in the Nerja Cave. Radiation Measurements, 40, 630–632, (2005) 20. P. Jovanovic: Radon measurements in karst caves in Slovenia. Environment International, 22(1), 429–432, (1996) 21. J. Lario, S. Sánchez-Moral, J. C. Canaveras, S. Cuezva, V. Soler: Radon continuous monitoring in Altamira Cave (northern Spain) to assess user’s annual effective dose. Journal of Environmental Radioactivity, 80, 161–174, (2005) 22. R. M. Amin, M. F. Eissa: Radon level and radon effective dose rate determination using SSNTDs In Sannur cave, Eastern desert of Egypt. Environmental Monitoring Assess. 143, 59–65, (2008) 23. G. K. Gillmore, P. S. Phillips, A. R. Denman, D. D. Gilbertson: Radon in the Creswell Crags Permian limestone caves. Journal of Environmental Radioactivity, 62, 165–179, (2002)

Preliminary Indoor Radon and Thoron Measurements in North-Western Romania

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PRELIMINARY INDOOR RADON AND THORON MEASUREMENTS IN NORTH-WESTERN ROMANIA Burghele Bety-Denissa, Papp Botond, Horvath Zoltán, Cosma Constantin Faculty of Environmental Sciences and Engineering, “Babeş-Bolyai” University, Cluj-Napoca Abstract The north-western part of Romania is known to have an important radon activity concentration; however, it is also well known that thoron interfere with most radon instruments. A preliminary study was started in this area with discriminative radonthoron solid-state nuclear track detectors. The measured radon and thoron concentration ranged from 31 to 343 Bq/m3 and from 63 to 227 Bq/m3 respectively. From the analyzed locations more than half (57%) presented radon higher than 100 Bq/m3, the World Health Organization (WHO) reference limit for housing. Furthermore more detailed measurements are planed in this area for the near future in order to have a better evaluation of public exposure to thoron and radon.

Introduction Preliminary measurements were started in a three counties located in north-western part of Romania; this area is known to have high concentrations of radon (1). Several Raduet discriminative radon-thoron solid-state nuclear track detectors have been placed in dwellings, cellars, schools and offices. All detectors were deployed 30 cm from the wall in locations with less possible ventilation throughout a period of three months. These measurements were particularly focused on areas which are rich in thorium, in traditional homes built of traditional materials such as mud bricks and rammed earth where thoron and its progeny can significantly contribute to the radiation exposure of the dwellers. Many people in Romania, mostly at the countryside, inhabit such buildings. In Romania the presence of radon and its impact on the population has been widely analyzed whereas thoron concentration didn’t benefit from the same attention. However, many of the radon measurements cannot be very accurate considering that thoron interfere with most of the radon instruments. From radiological protection point of view, many indoor surveys in Europe and Asia have revealed that the dose contribution to the inhalation of 220Rn and its progeny can be equal to or even exceed that of 222Rn and its progeny (2). Many studies showed that thoron is present in dwellings almost everywhere, in Japan (3), Korea (4), Hungary (5), India (6), China (7) and many other countries.

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Burghele B.-D., Papp B., Horvath Z., Cosma C.

Materials and methods For this experiment we were using solid state nuclear track detectors based on CR-39, commercially known as RADUET (8). The detector consists of two different diffusion chambers. Each chamber is made of an electroconductive plastic and is cylindrical with an inner volume of about 30 cm3. The CR-39 (poly-allyl diglycol carbonate) is used as the detecting material and placed at the bottom of the chamber with sticky clays. Radon in air can penetrate into the chamber through an invisible air gap between its lid and bottom through diffusion. Since this air gap functions as the high diffusion barrier, thoron can scarcely go into the chamber with a small pathway due to its very short half life (55.6 s), compared with that of radon (3.82 d). In order to detect thoron more effectively, six holes of 6 mm in diameter are opened at the side of the other chamber and are covered with an electroconductive sponge. The conversion factors are determined by the National Institute on Radiological Sciences (NIRST) in Japan’s radon/aerosols chamber and thoron chamber, respectively. In other words, the CR-39 chip inside the Rn-channel registers only those tracks, which come from radon decay. And the Tn-channel registers all the tracks coming from both radon and thoron progeny. This means that the counted track density in the Tn-channel is the sum of the tracks originated from both radon and thoron progeny. Proper calibration data and combination calculation is able to extract the individual radon and thoron activity data from these two tracks density values.

Results After three month exposure, the detectors are etched using RB4 Etching Unit with 6.25 N sodium hydroxide at 90°C during 4.5 hours. A neutralization step, with 1% HCl followed the etching process for 20 minutes. The track counting on the etched chips is done by the track reader software which provides two track densities – one for Rn-channel and a second one for Tn-channel. The thoron concentration can be calculated from the difference of the tracks number densities related to the given surfaces of the two detectors. From 35 radon – thoron paired detectors thoron was less than detection limit in 11 cases. However, 24 detectors showed the presence of thoron with concentrations varying widely from 63 to 227 Bq/m3. The measured radon concentration ranged from 31 to 343 Bq/m3. The ratio 220Rn/222Rn concentration varied from 0.1 to 1.0 with an arithmetic mean of 0.6. From the analyzed locations more than half (57%) presented radon higher than the WHO limit (reference limit for housing being 100 Bq/m3).

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Table 1: Results of simultaneous radon and thoron measurements in North-Western Romania Minimum (Bq/m3) 31 63

Radon Thoron a

Maximum (Bq/m3) 348 227

AMa

SDb

197 106

136 77

Arithmetic mean Standard deviation

b

Figure 1: Intercomparison between most representative values form different analyzed locations The thoron concentration was also monitored in one of the cellars using a radon and thoron monitor, called Rad7, based on a semiconductor detection method. After a 10 minutes measurement the 220Rn activity concentration had a mean value of 180 Bq/m3 while radon tends to an equilibrium activity of 600 Bq/m3. Intercomparison exercises(9) with NIRST – Japan, Cantabria – Spain, Veszprem – Hungary and RIM – Czech Republic in 2010 provided very good result with differences under 10% which confirms the reliability of measurements made in our laboratory. This study concluded that thoron must not be neglected when the radon activity concentration is measured. Further more detailed measurements are planed in this area for the near future in order to have a better evaluation of public exposure to both thoron and radon.

Acknowledgement This paper was realised with the support of POSDRU CUANTUMDOC “DOCTORAL STUDIES FOR EUROPEAN PERFORMANCES IN RESEARCH AND INOVATION” ID79407 project funded by the European Social Found and Romanian Government.

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References 1. C. Cosma, K. Szacsvai, A. Dinu, D. Ciorba, T. Dicu, L. Suciu: Preliminary integrated indoor radon measurements in Transylvania (Romania). Isotopes in Environmental and Health Studies, 45(3), 259–268, (2009) 2. S. Akiba, S. Tokonami, F. Bochicchio, J. McLaughlin, L. Tommasino, N. Harley: Thoron: its metrology, health effects and implications for radon epidemiology. A summary of roundtable discussions. Radiation Protection Dosimetry, 1–5, (2010) 3. Cs. Németh, S. Tokonami, T. Ishikawa, H. Takahashi, W. Zhuo, M. Shimo: Measurements of radon, thoron and their progeny in Gifu prefecture, Japan. Journal of Radioanalytical and Nuclear Chemistry, 265(1), 9–12, (2006) 4. C. K. Kim, Y. J. Kim, H.-Y. Lee, B. U. Chang, S. Tokonami: 220Rn and its progeny in dwellings of Korea. Radiation Measurements, 42, 1409–1414, (2007) 5. T. Kovács: Thoron measurements in Hungary. Radiation Protection Dosimetry, 141(4), 328–334, (2010) 6. R. S. Khera, M. S. K. Khokhar, V. B. Rathore, T. V. Ramachandran: Measurement of indoor radon and thoron levels in dwellings and estimation of uranium, thorium and potassium in soil samples from central part of India. Radiation Measurements, 43, 414–417, (2008) 7. Y. Yamada, S. Quanfu, H. Yonehara, et al.: Radon–Thoron Discriminative Measurements in Gansu Province, China, and Their Implication for Dose Estimates. Journal of Toxicology & Environmental Health: Part A, 69(7/8), 723–734, (2006) 8. S. Tokonami, H. Takahashi, Y. Kabayashi, W. Zhuo: Up-to-date radon-thoron discriminative detector for a large scale survey. Review of Scientific Instruments, 76, 113505, (2005) 9. M. Janik, S. Tokonami, A. Sorimachi, T. Ishikawa, C. Kranrod: Technical Report on the 3rd International Intercomparisons for Integrating Radon/Thoron Detectors with the NIRS Radon/Thoron Chambers. National Institute of Radiological Sciences, NIRS, Japan, (2010)

Radiological Investigation of Hungarian Clays (Used in Brick Factories)

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RADIOLOGICAL INVESTIGATION OF HUNGARIAN CLAYS (USED IN BRICK FACTORIES) Sas Zoltán, Somlai János, Jobbágy Viktor, Szeiler Gábor, Kovács Tibor University of Pannonia, Institute of Radiochemistry and Radioecology, Veszprém Abstract In Hungary the most commonly used bulk amounted building material is the brick. The natural radioactive content of the 27 different kinds of clays, which are used as base material in brick factories were investigated in radiological point of view. The activity concentration of the K-40, Ra-226, Th-232 were determined by gamma spectrometry and the I-index was calculated. The radon emanation and the exhalation were also measured.

Introduction Owing to the modified habits of the mankind the passed time in indoor conditions attains the 80 %. Due to that fact the composition of the surrounding materials gets into the focal point of interest. The determination of the natural radioactive content of the building materials is very momentous to estimate the received radiation exposure of the inhabitants. The most commonly used building materials in Hungary and in numerous country of the world are the bricks, which made from clays. The natural radionuclide content of the clays and the manufactured clay products contribute natural background radiation in two ways. On the one hand the gamma radiation of the primordial radionuclides (K-40; U-238; Th-232) and their daughter elements increase the external dose of the body. On the other hand the inhaled Rn-222, Rn-220 and their progenies augment the risk of the evolution of the lung cancer. The radon is a radioactive noble gas with relatively long half life (3.82 d) and this time can be enough to get out of the matrix into the pore space and into the air as well. While the alpha particle ejected as a result of the alpha decay the daughter element is recoiled and it can be released into the pore space or it can be embedded in adjacent particles. The emanation coefficient or emanation power is defined as the amount of the quantitative rate of the released radon from the crystal structure into the pore space to the total amount of the generated. So many factors determine the amount of the emanated radon such as, density, homogeneity in radium distribution, grain size, volume of pore space, and last but not least the moisture content (1). Due to the diffusion and convection the radon can be exhaled from the pore space into the air. The water content also has effect on the exhalation because it inhibits the diffusion and the convection of the emanated radon in the pore space.

Sas Z., Somlai J., Jobbágy V., Szeiler G., Kovács T.

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The amount of the activity of the released radon per unit time per unit surface called radon exhalation. The radon exhalation depends on the emanation coefficient, water content, pressure, temperature, other weather conditions, internal structure of the solid phase and the diffusion depth as well.

Measurements and methods Sampling and sample preparation The clay samples that used in brick factories as building material were taken from different clay extraction sites in Hungary. The samples have been either heated at a temperature of 105 ± 3 °C until they had no change in their mass and dried. After drying the samples were sieved under 0.63 mm and weighted.

Figure 1: Provenience of the clay samples Ra-226 activity concentration determination by gamma-spectrometry The dried and sieved samples were stored for 30 d in air-tight aluminum Marinelli beakers with volume of 600 cm3 to reach the secular equilibrium between the Ra-226 and the Rn-222. The determination of the Ra-226 activity concentration occurred via the radon progenies Pb-214 (295 keV) and Bi-214 (609 keV) by high resolution gamma ray spectrometry, using an ORTEC GMX40-76 HPGe detector with efficiency of 40 %, and an energy resolution of 1.95 keV at 1332.5 keV. The data and spectra recorded by a Tennelec PCA-MR 8196 MCA. The system was calibrated with clay reference material certified by Hungarian National Office of Measures. The sample measuring time was 80 000 s in every case.


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Determination of radon emanation factor In every case of emanation sampling 20 g dried clay were taken and put into 50 cm3 glass ampoule and sealed parallel with the exhalation sample preparation. After 30 days which necessary to reach the secular equilibrium the ampoules were broken in a special metal crush cell (2). The produced radon was pressed trough an air filter, which filters the gas from the charged radon progenies and the residual solid grains. The filter was connected to a Lucas cell with volume of 1 dm3. After sampling the cells were stored for 3 hours to the short live progenies of the radon can reach the secular equilibrium. During the 3 hours long storing time almost the total amount of discussed gas and the Po-216 is decayed and their α-particles does not contribute to alpha counting. The following progenies the Pb-212 and the Bi-212 with half life of 10.64 h and 1.01 h are beta emitters and them have no effect in case of alpha counting as well (3). To perform the measurement an EMI photomultiplier was used for 1000 s measurement time three times in case of every cells. The cells were calibrated by a PYLON RN 2000A type passive radon source (activity of 105 ± 0.4 % kBq) in a volume of 210.5 dm3 Genitron EV 03209 type calibration chamber.

Determination of the exhalation rate The clay samples were measured in a proprietary exhalation chamber with volume of 4250 cm3. The chamber was developed from ordinary glass jar with steel cap. The radon leakage determination of the radon accumulation chambers was carried out with the help of a PYLON RN 2000A type passive radon source. The sample holder was made from plastic with volume of 300 cm3 with a height of 60 mm, and with surface of 46.69 cm2. The homogeneity of the inner air was ensured by small size 12 V DC ventilator which was placed inside the chamber. The sample holder was covered by radon permeable film against dusting to evade the contamination of the Lucas cells. The chamber volume was more then ten times higher than the sample volume because of to avoid the back diffusion effect (4). The chambers were purged out with radon free N2 gas before the accumulation to reduce the initial radon concentration to zero. The accumulation time ranged between from 16 to 24 h in case of the measurements. During sampling the chamber was connected in a closed loop system (Figure 2) wherein the radon increment was flowed by a radon proof pump and passed through an air filter into a Lucas cell and the amount of the transferred radon was measured according to the emanation measurement method. The volumes of the Lucas cell, the pipes and the pump were added into the chambers owing to volume correction.


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Figure 2: Closed loop exhalation sampling system Results and discussion Gamma-spectrometry The results of the gamma-spectrometry measurements are shown in Figure 3. The mean Ra-226 activity concentration of the 27 examined samples was 36.1 ± 6.6 Bq/kg (16.1 to 104.7 Bq/kg), the mean Th-232 41.3 ± 9.3 Bq/kg (32.0 to 50.2 Bq/kg) and the average of the K-40 content was 807.6 ± 98.2 Bq/kg (533.8 to 1126.5 Bq/kg). The given results exceed the average of the soils (UNSCEAR Report, 2008) twelve times in case of the Ra-226 and 7 times in case of the Th-232, whilst the K-40 content transcend the reference value in every samples. The clay-based building materials have higher K-40 content than the world average (UNSCEAR Report, 2008 Annex B, Tables, Public.xls).

Figure 3: Results of gamma spectrometry


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I-index The European Commission (EC) set guidelines on the radiological protection principles concerning the natural radioactivity of building materials (RP-112 document) for the Member States (5). Doses to members of the public should be kept as low as reasonably achievable. Within the EU, doses exceeding 1 mSv/y should be taken into account from the radiation protection point of view. The following activity concentration index (I) is derived for identifying whether a dose criterion is met: I=

C Ra − 226 C Th −232 C K −40 + + 300 Bq / kg 200 Bq / kg 3000 Bq / kg

(1)

where CRa-226, CTh-232, CK-40 are the Ra-226, Th-232 and K-40 activity concentrations (Bq/kg) in the building material. The activity concentration index shall not exceed the values presented in Table 1. The received I-indexes of the investigated clay samples can be found in Figure 4.

Table 1: Limits of the activity concentration index Dose criterion Materials used in bulk amount; e.g. concrete, brick Superficial and other materials with restricted use e.g. tile, board

0.3 mSv/a

1.0 mSv/a

I ≤ 0.5

I ≤ 1.0

I ≤ 3.0

I ≤ 6.0

Figure 4: I-index of the clay samples


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Due to the calculated I-index results the following conclusions can be stated. Owing to the low natural radionuclide content of the examined Hungarian clay samples the I-indexes of the samples do not exceed the stricter 1.0 limit which indicates 1.0 mSv/a dose surplus in case of bulk amounted inbuilt. The received average value was 0.59 so that all of the applied clay samples suitable for building material production.

Radon emanation The radon emanation values were calculated in knowledge of the radium content and the emanated radon content of sealed ampoules. The received result can be seen in Figure 5. The emanation ranged between 8.4 ± 2.0 % – 34.0 ± 5.9 % with mean of 18.1 ± 3.9 %. On the basis of the measured radon emanation values a fluctuation can be observe, which could be caused by many factors, such as the different radium distribution or it can be caused by the size of the mineral grains and the permeability features as well.

Figure 5: Emanation coefficient of the clay samples Radon exhalation In the exhalation chamber where the samples were enclosed the activity concentration was growth during the accumulation time. The increment of the exhaled radon activity is not linearly multiplies due to decay of the radon atoms. To get the correct value the giving out must be determined. The “K” factor eliminates uncertainty of the measurement in function of time, which can be defined in the following manner: The number of the exhaled radon atoms is in direct ratio to the elapsed time and the exhalation rate as well. This is the reason why it can be negligible if the exhalation taken into consideration as a unit value. NH = E × t

(2)


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The real activity of the radon during the accumulation can be determined with the equitation of the secular equilibrium: A t = 1 − A 0 × exp(−λ × t )

(3)

The number of the radon atoms after decay in function of the elapsed accumulation time can be calculated with equitation 4. Nt =

At λ

(4)

The ration between the NH and the Nt produce the “K” accumulation correction factor which can be calculated in the following way: K=

Nt A = t × t −1 NH λ

(5)

K=

1 − exp(−λ × t ) λ×t

(6)

The received exhalation results can be found in Figure 6.

Figure 6: Specific exhalation (mass standardized) of the clay samples The mean value of the specific exhalation rate of the measured clay samples was 13.3 mBqkg-1h-1 and the results varied between 5.8 – 49.2 mBqkg-1h-1. The exhalation features are very different because of the different characteristic of the investigated materials. In the case of the BSZ I sample the Ra-226 content was the highest (104.7 Bq/kg) among the examined sample and the exhalation rate almost reached the 50 mBq/kg-1h-1, which was the highest measured result.

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Conclusion Clays that used as starting materials in Hungarian brick factories were collected from several regions of the country. The natural radionuclide contents of the samples were determined with gamma spectrometry and the I-index was calculated. The Ra-226 and the Th-232 contents correspond to the world average of the soils, nevertheless the K-40 activity concentration exceeded the mean value because the high potassium content of the clays. The emanation coefficient and the specific exhalation rate were measured as well. The emanation coefficient ranged between 8.4 ± 2.0 % – 34.0 ± 5.9 % with mean of 18.1 ± 3.9 %. The mean value of the specific exhalation rate of the measured clay samples was 13.3 mBqkg-1h-1 and the results varied between 5.8 – 49.2 mBqkg-1h-1. The received emanation and specific exhalation rate results are ordinary results if we compare them with other measurements which can be found in the literature. The inbuilt of the examined clay or the produced brick products doesn’t spell danger in radiological aspect. On the basis of the received values statable that the natural radioactivity content of Hungarian clays and the emanation and exhalation features do not spell danger for the inhabitants.

Acknowledgement Present publication was realized with the support of the project TÁMOP-4.2.2/B-10/1-2010-0 References 1. M. Y. Menetrez, R. B. Mosley, R. Snoddy, S. A. Brubaker Jr.: Evaluation of radon emanation from soil with varying moisture content in a soil chamber. Environment International, 22(1), 447–453, (1996) 2. V. Jobbágy, J. Somlai, J. Kovács, G. Szeiler, T. Kovács: Dependence of radon emanation of red mud bauxite processing wastes on heat treatment. Journal of Hazardous Materials, 172(2-3), 1258–1263, (2009) 3. H. Sun, D. J. Furbish: Moisture content effect on radon emanation in porous media. Journal of Contaminant Hydrology, 18(3), 239–255, (1995) 4. P. Tuccimei, M. Moroni, D. Norcia: Simultaneous determination of 222Rn and 220Rn exhalation rates from building materials used in Central Italy with accumulation chambers and a continuous solid state alpha detector: Influence of particle size, humidity and precursors concentration. Applied Radiation and Isotopes, 64(2), 254–263, (2006) 5. European Commission, Radiological Protection Principles Concerning the Natural Radioactivity of Building Materials, Radiation Protection Report RP-112, EC, European Commission, Luxembourg, (1999)

Intercomparsion of Radon Thoron Passive Detectors

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INTERCOMPARSION OF RADON THORON PASSIVE DETECTORS Somlai János1, Ishikawa Tetsuo2, Omori Yasutaka2, Mishra Rosaline3, Sapra B. K.3, Mayya Y. S.3, Tokonami Shinji4, Csordás Anita5, Kovács Tibor1 1

Institute of Radiochemistry and Radioecology, University of Pannonia, Veszprem 2 National Institute of Radiological Sciences, Chiba 3 Radiological Physics and Advisory Division, Bhabha Atomic Research Centre, Mumbai 4 Institute of Radiation Emergency Medicine Hirosaki University, Hirosaki 5 Social Organization for Radoecological Cleanliness, Veszprem Abstract In case of new, modern houses with good heat-insulation the role of indoor air quality comes to the foreground. Major part of radiation exposure made up of radon isotopes and its progenies may become accumulated due to reduced natural ventilation. Therefore, it is outstandingly important to review and make previous radon surveys more precise. Among the factors disturbing the measurement of radon the presence of thoron may also influence the measured radon value, therefore making the estimated radiation exposure imprecise. Thoron had previously been surveyed mainly in Asia, however, according to recent surveys made in some European locations a significant thoron concentration also needs to be taken into account. In this survey several SSNTD detectors available commercially and capable of measuring both radon and thoron were placed at the same time in 79 houses in Hungary with different exposition periods (1-3 months). The majority of the surveyed homes were family houses, the track detectors were placed on the ground floors. In order to measure thoron the distance of the detector sets were fixed as 15 cm from the walls. In 7 cases CD/DVD-based retrospective radon measurements were performed besides the trace detector measurements. The standard deviation of the measurement results of the track detectors capable of radon measurement was 10 %, while the standard deviation in case of (DRPS) Direct Radon Progeny Sensors was 28 %, which is acceptable. Great differences were found between the data given by the wide-spread detector RADUET capable also of measuring thoron, and that of the (DTPS) Direct Thoron Progeny Sensors made in India. The average deviation was 42 %, however, based on the preliminary measurement data it can be stated that considerable thoron concentration was measured in some houses in Hungary. Based on the results obtained the main component of the radiation is still radon, however, the accuracy of further radon surveys may be disturbed by the thoron being present.

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Somlai J., Ishikawa T., Omori Y., Mishra R., Sapra B. K., Mayya Y. S., Tokonami S., Csordás A., Kovács T.

Introduction Radon (222Rn), thoron (220Rn) and their progenies are considered to be the major contributors to human exposure from natural sources (1). Although the radon presents the main concern of inhalation dose contributor for general public, in the last years the thoron has gained increasing attention among health physicists. The presence of thoron has two consequences. First it made confounding effects on the accurate radon measurement (2), second the thoron itself should be considered in radiological viewpoint because it might result in radiation exposures comparable to those due to radon (3). Both effects were considered to be relatively small therefore they were usually neglected. Despite the fact that the parent element of thoron 232Th is usually present in soil and rocks in a higher concentration than the parent element of radon, the measurable thoron concentration is usually negligible related to radon in indoor air. Mostly the short lifetime of radon and the inhomogeneous distribution of thoron are responsible for this. The thoron concentrations, mainly because of its short half-life (55.6 s), is highly inhomogeneous with a strong dependence on the distance from the source (4). However, there are isotopes of longer lifetime present among the thoron progenies, yet these are capable of spreading in the air by sticking to aerosol particles, and establishing a more or less homogeneous concentration distribution, therefore the radiation dose contribution is not negligible. Despite of this the number of indoor thoron surveys is surprisingly small. This also has several reasons, primarily because the measurement of thoron involves more difficulties compared to that of radon. On the second hand, in countries where significant thoron concentration is expectable the measurement of radon and thoron among the population is not widespread (primarily due to economical issues). Therefore, thoron has spread in literature more or less as a phenomenon specific in Asia (5, 6, 7, 8).However, nowadays, more and more studies deal with what role 220Rn (thoron) plays in the field of radiation exposure of the population. Previous studies showed that thoron (220Rn) was present in a considerable extent in traditional Japanese houses (5, 6), it was found higher than average concentration in Mexico City (9) and it has gained an important part in surveys in India (7) and China (8). During the past years several studies on indoor thoron measurement have been published in Europe, too (10, 11, 12, 13). Indoor radon measurement is relatively a great tradition in Hungary, however, rather few studies called the attention to thoron measurement. Somlai have studied (14) in the beginning of the 1990s the quantity of progenies generated during the decay of radon and thoron entering the atmosphere in the coal mine during breaking-up, using a Pylon WLx monitor. During the 2000s the amount of radon and thoron progenies were inspected in several mines, caves in short periods


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of time (15), however, these studies called attention to thoron as a factor effecting the accuracy of radon measurement. Specific research work related to thoron was carried out by Hunyadi and colleagues, they measured the distribution of thoron and radon in residential buildings, using detectors elaborated on their own and placed in a net pattern they examined the thoron concentration depending on the distance from the walls, ceilings (16). In the middle of the 2000s Hamori performing radon measurements of the largest number in Hungary (17) have also started thoron measurements. In 2003, the Institute of Radiochemistry and Radioecology, University of Pannonia and the Social Organisation for Radio Ecological Cleanliness in a joint work started wide-scale thoron survey in Hungary, using radon-thoron discriminative passive detectors (11, 18). This study introduces the results of dwellings of the village located near the closed and remediated uranium mine and several high radon risk workplaces as mine, cave and bath according to the Hungarian Regulations (19). During the first survey performed in 2003 besides several measurement technique and methodology difficulties listed above even further issues and questions arose, but based on the results of the first survey it could be stated that in certain regions of Hungary thoron is present in a significant amount in the air of certain homes. Measurement results showed great uncertainty, therefore the trace detector measurement method of thoron had been harmonized in cooperation with several research institutions (Pannon University, Hungary Babes-Bolyai University, Romania, Jozef Stefan Istitute, Szlovenia, NIRS, Japan). The next survey was performed in 2006-2007, where in order to reduce the high level of uncertainty identical measurement protocols and one type of Cr-39 based RADUET (Radosys) dosimeters were used (11). In this study, eliminating the errors made in previous surveys series of measurements have been performed throughout a year in 79 houses using SSNTD type detectors available on the market.

Materials and methods Types of detectors used and their processing. NRPB and NRPB SSI (CR-39) 2 pieces of CR-39 detector chips were used for measuring radon concentration. One of the chips was put out in a previously already used yellow case, while the other one was put out in a conductive black case (Figure 1). Upon completion of a measurement the plastics are removed from their holders and chemically etched for 3 hours in a 6.25 M NaOH solution at 90 ºC. The tracks are viewed using a Optical Microscope and analysed using a Virginia 99 image analysis system. Tracks are accepted as genuine if their size and shape fall within acceptable limits.

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Figure 1: Cross section of the NRPB diffusion chamber RADUET (CR-39) and RnDp/TnDp (CR-39) The radon and thoron measurements were performed using a “RADUET” discriminative passive measuring devices. The RADUET detector includes two CR-39 (poly allyl diglycol carbonate, PADC) detectors in two diffusion chambers of different permeability (Figure 2). The thoron concentration can be determined from the difference of the track number density related to the given surfaces of the two detectors (20).

Figure 2: Diffusion chambers of the Raduet detector RnDp/TnDp (CR-39) detectors contain 8 CR39 chips and different density aluminium foils on the CR-39 surface see 3 figures: In case of both detector types, after exposition the detectors were etched by 6.25 N sodium hydroxide solution, at 90 °C for 4 hours.


175

The detectors were evaluated using a microscope unit controlled by RadoMeter 2000 software.

Figure 3: Rn-Tn progeny monitor and the detector housing

Blank

RnP I

RnP II

TnP

Figure 4: Elements measured by CR-39 placed in the Rn-Tn progeny monitor, Blank: background, RnP I: Radon progeny I (Po-218), RnP II Radon progeny II (Po-214), TnP: Thoron progeny (Po-212)


176

DRPS/DTPS (LR115) In the case of DRPS/DTPS the etching was carried out with 2.5 N NaOH, on 60 °C for 1 hour with continuous stirring (21). The tracks formed are counted with an automatic track-counting technique using a spark counter (22). For this type it is important to mention that it is capable of measuring progeny concentration, the radon/thoron concentration calculated from this is only an estimated value as there was no opportunity to measure EEC, from which the actual equilibrium factor can be identified.

Figure 5: Structure of the DTPS/DRPS (23) Detector set used for the measurement In case of radon several harmonized protocols exist (24, 25, 26, 27) concerning the placement, optimum measurement period, placement within a building of the detectors. However, for the measurement of thoron, despite the great number of surveys and measurements, there is no unified protocol, almost everywhere different evaluation protocols are used even within the SSNTD techniques (28, 29, 30). Therefore, the results gained show rather great differences. In order to avoid this the detectors were placed 15-20 cm away from the wall (in most cases this is the direct source of thoron), arranged as shown in Figure 6. The detector sets were exposed for 3-6 months.


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Figure 6: The detector-set Measuring sites Workplaces In case of workplaces smaller office buildings were appointed, where people work only in daytime in 8 hours. At the weekends these buildings are empty. There are no ventilation systems in these buildings, ventilation is carried out by opening the windows. The detector sets described in the previous point were placed at the measurement points.

Dwellings (D) and Cellars (C) Based on the experience gained from previous surveys performed in Hungary (31), those settlements were selected, where either the geological abilities of the territory or the nature of building materials used make higher radon/thoron concentration values expectable.

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The houses selected are located in 5 counties in Hungary. 80 % of the selected houses are one-storey houses, and the rest were houses with attic. Concerning building materials 90 % of the houses had been built using traditional building materials (clay and straw mortar or brick-clay), and in the rest of the houses coal slag was built in them. Detector sets described in the previous point were placed at the measurement points.

Figure 7: Sampling area in Hungary Results and Discussion By the evaluation of the results two aspects were taken into consideration: how much the different track detector types are capable of performing measurements in accordance with each other, and, on the other hand, what differences are found at the same measurement point during a measurement of several cycles. For both aspects the results are classified according to the purpose of the location (residential house, workplace).

Workplaces One of the groups of measurement sites include workplaces. Figure 8 shows a workplace selected as an example. In case of the rest of the workplaces similar pictures are shown in the diagram. The figure shows how the different types of track detectors measured radon and thoron next to each other, and what changes are observable between the measurements performed in the two different points of time. Taking the first aspect into consideration it can be stated that the values measured by the Raduet and the two NRPBs are close to each other, however, the detector from India shows a great degree of over-measurement. This statement is true both for radon and thoron. However, this inaccuracy results from the design of the detector as it is not


179

radon and thoron concentration we measure but progeny. The radon and thoron concentration values calculated from the measured progeny concentration are estimated values, it is unsuitable for actual comparison with the other types. Seasonal changes cannot be taken into consideration in case of workplaces. It is also shown on the figure that no significant change in the concentration has occurred between the two measurement points in time, that is the measured values refer to the whole year. 120

Radon concentration [Bq/m3]

2010.Nov 100

2011.Apr

80 60 40 20 0 Raduet

DRPS

NRPB

NRPB SSI

Types of the track detector

Thoron concentration [Bq/m3]

35

2010.Nov

30

2011.Apr

25 20 15 10 5 0 Raduet

DTPS Types of the track detector

Figure 8: Joint measurement of the different track detector types at a workplace selected as an example, and comparing the different measurement cycles for radon and thoron

180


In case of workplaces it is a general fact that Raduet and NRPBs measured similar values, while the DRPS/DTPS (LR115) detector measured a higher value – estimated from progeny – in most cases. In only a few cases this was not observable: in these cases the values measured by the DRPS/DTPS (LR115) detectors were almost identical to the values measured by the other three types of detectors.

Dwellings The second group of measurement locations includes residential houses. Based on the values measured the dwellings can be divided into 2 groups: radon concentration values below and over 100 Bq/m3. The sets belonging to the different groups showed similar measurement results. First, let us inspect the dwellings with radon concentration below 100 Bq/m3. Generally, the values measured by the Raduet and NRPBs were rather similar, except for some cases. Most of the DRPS/DTPS (LR115) detectors showed a significant degree of over-measurement after calculating the radon and thoron concentration values using the recommended equilibrium factors; it occurred in only a few cases when values similar to the other cases were obtained. This fact highlights that it is rather probable that great differences can be found between the values of the equilibrium factors. Therefore, the implementation of the EEC measurement is planned at the measurement points (there was no sufficient amount of measured data at the time of writing the paper) In case of dwellings with higher radon concentration the situation is just the opposite. The Raduet and NRPBs also give similar results, however, the DRPS/DTPS (LR115) track detector shows significant under-measurement in most cases. Seasonal changes in case of dwellings cannot be taken into consideration, just as in case of workplaces. Figure 9 shows a general example for both types. In case of thoron there is no need to classify the measurement points as DRPS/DTPS (LR115) detectors also give lower measurement results for thoron than the Raduet detectors even in low and high concentration. However, in case of high radon concentration it is not sure that the thoron concentration will be high as well, and vice versa. Two examples of this are shown in Figure 10. In the first case radon concentration was high (890 Bq/m3), but thoron concentration was low (55 Bq/m3). In the second case it was just the opposite; high thoron concentration (259 Bq/m3) was measured, but the radon concentration was low (41 Bq/m3). Results show that radon and thoron change irrespective of each other in some cases.


181


140 120 100 80 60 40 20 0 Raduet

DRPS

NRPB

NRPB SSI

Types of the track detector 200


180 160 140 120 100 80 60 40 20 0 Raduet

DRPS

NRPB

NRPB SSI

Types of the track detector

Figure 9: Values measured using different traces detectors, in dwellings with low and high radon concentration


182 1200

Activity concentration [Bq/m3]

Thoron concentration 1000

Radon concentratoin

800 600 400 200 0 I.

II.

Figure 10: Joint change in radon and thoron concentration Summary During the survey 79 houses were inspected in Hungary from a total of 5 counties, with different exposition periods (1-3 months). Mainly family houses were selected, and as far as it was possible, the detector sets were placed at the ground floor. For the research work several types of track detectors (NRPB, Raduet, DRPS/DTPS, Radon thoron porogeny monitor) were used, which behaved in different manners depending on the radon and thoron concentration, and the purpose of the measurement location. Two types of the detectors measured radon and thoron concentration directly, while the third one measured progeny concentration. Actually, this is a better method as from the aspect of radiation exposure the major part of radiation is caused not by radon and thoron, but their progenies. Raduet and NRPB measured similar values in case of workplaces and dwellings, and also in case of lower and higher activity concentration levels. On the contrary, the DRPS/DTPS (LR115) track detectors generally showed over-measurement, while in case of higher concentration levels they showed under-measurement, which is caused by the previously mentioned fact that DTPS/DRPS measures progeny concentration, and the actual values greatly differ from the recommended equilibrium values, therefore the radon and thoron concentration values can only be estimated. For the identification of a more accurate radiation exposure and for a better comparability of detectors the measurement of the EEC, the attached and unattached fraction at the measurement points are also planned in the future.


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Acknowledgements The authors would like to thank Csaba Szabó and Ákos Horváth and their students (ELTE University) for the placing of detectors and useful data. This research is supported by Hungarian Research Found (OTKA No. K 81975 and K 81933); and was realized with the support of the project TÁMOP-4.2.2/B-10/1-2010-0. References 1. United Nations Scientific Committe on the effects of Atomic Radiation: Sources and effects of ionizing Radiation. UNSCEAR 2000 Report to the General Assembly with Scientific Annexes, United Nations, New York, (2000) 2. S. Tokonami, M. Yang, T. Sanada: Contribution from thoron on the response of passive radon detectors. Health Physics, 80, 612–615, (2001) 3. W. Chung, S. Tokonami, M. Furukawa: Preliminary survey on radon and thoron concentrations in Korea. Radiation Protection Dosimetry, 80, 423–426, (1998) 4. E. Gargioni, A. Honig, A. Röttger: Development of a calibration facility for measurements of the thoron activity concentration. Nuclear Instruments & Methods, 506, 166–172, (2003) 5. M. Doi, S. Kobayashi: Spatial distribution of radon and thoron concentrations in the indoor air of a traditional Japanese wooden house. Health Physics, 66, 43–49, (1994) 6. J. Ma, H. Yonehara, T. Aoyama, M. Doi, S. Kobayashi, M. Sakaunoe: Influence of air flow on the behavior of thoron and its progeny in a traditional Japanese house. Health Physics, 72, 86–91, (1997) 7. R. Mishra, S. P. Tripathy, D. T. Khating, K. K. Dwivedi: An extensive indoor 222 Rn/220Rn monitoring in Shillong, India. Radiation Protection Dosimetry, 112, 429–433, (2004) 8. Q. Guo, J. Sun, J. Chemg, B. Shang, J. Sun: The levels of indoor thoron and its progeny in four areas of China. Journal of Nuclear Science and Technology, 38, 799–803, (2001) 9. T. Martinez, M. Navarrete, P. Gonzalez, A. Ramirez: Variation in indoor thoron levels in Mexico City dwellings. Radiation Protection Dosimerty, 111, 111–113, (2004) 10. J. Vaupotič, I. Čeliković, N. Smrekar, Z. S. Žunić, I. Kobal: Concentrations of 222 Rn and 220Rn in indoor air. Acta Chimica Slovenica, 55, 160–165, (2008) 11. T. Kovacs: Thoron measurements in Hungary. Radiation Protection Dosimetry, 141, 328–334, (2010) 12. G. Sciocchetti, M. Bovi, G. Cotellessa, P. G. Baldassini, C. Batella, I. Porcu: Indoor Radon and Thoron Surveys in High Radioactivity Areas of Italy. Radiation Protection Dosimetry, 45(1-4), 509–513, (1992)

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Preliminary results of indoor radon thoron survey in Hungary

POSZTER SZEKCIÓ

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External Doses from Radon Progeny

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EXTERNAL DOSES FROM RADON PROGENY Markovic M. Vladimir, Krstic Dragana, Nikezic Dragoslav, Stevanovic Nenad Faculty of Science, Department of Physics, University of Kragujevac, Kragujevac, Serbia Abstract Great deal of work has been devoted to determine doses from alpha particles emitted by 222 Rn and its progeny. In contrast, contribution of beta particles and following gamma radiation to total dose has been neglected by most of the authors. The present work describes a study of the detriment of 222Rn progeny on the humans due to external exposure. Doses and dose conversion factor (DCF) were determined for beta and gamma radiation in main organs and remainder tissue, taking into account 222Rn progeny 214 Pb and 214Bi distributed in the atmosphere of standard room for ORNL phantom in the middle of the room. DCF was found to be 5.83 μSv/WLM. Skin and muscle tissue from remainder receives largest dose.

Introduction Inhalation of the short-lived radon decay products (218Po, 214Pb, 214Bi/214Po) in homes, in the outdoor atmosphere and at work places yield the greatest amount of the natural radiation exposure of man (1,2). Radon is known to present a risk of lung cancer when it, or rather its decay products, are inhaled. Almost all of the radon and its progeny hazards refer to exposure to alpha particles. Besides alpha, beta particles and following gamma radiation is present in decaying process of radon progeny. 214Pb and 214Bi are radon short lived progeny which are decaying emitting beta particles following by the intensive gamma radiation. Beta particles have continuous spectra with energies up to about 3.3 MeV and are much more penetrating than alpha particles. Due to long range of beta particles and gamma radiation humans can bee exposed from radionuclides distributed in atmosphere of rooms and closed spaces. This contribution can be significant since Potential Alpha Energy Concentration - PAEC in the air is larger than its fraction which is deposited in the lungs. Calculation of doses and determination of dose conversion factor (DCF) from radon progeny present in the atmosphere as an external source of radiation was performed in this paper.

Methodology Behavior of radon and its progeny in dwellings is described by the parametric differential equations, primary given by the Jacobi (3). Room model takes into account radioactive decay, removal by ventilation, attachment and deposition. Parameters which describe these processes are decay constants λi, ventilation rate λv, attachment

Markovic M. V., Krstic D., Nikezic D., Stevanovic N.

190

u

a

rate λa, and deposition rates of unattached and attached progeny λd , λd respectively, all in s-l (or traditionally in h-1). The steady-state solutions that describe the partitioning of 222Rn progeny concentrations within a reference room are given by: ∂N iu = λi N iu−1 + pi −1λi N ia−1 − λi + λa + λv + λud N iu ∂t

(1)

∂N ia = λa N iu + (1 − pi −1 )λi N ia−1 − (λi + λv + λad )N ia ∂t

(2)

(

)

Superscripts u and a stand for airborne-unattached and aerosol-attached 222Rn progeny within a reference room. pi–1 is the associated recoil factor or the desorption probability of the i-th daughter due to the decay of its attached precursor i−1 (pi–1 = 0.8 in the case of α-emissions and pi–1 = 0 for β-emissions). Ni is number u progeny concentrations. Note that for the noble gas 222Rn (i = 0), we have N0 = N0 and a d N0 = N0 =0, and that for each 222Rn progeny i, its airborne concentration is then u a Ni = Ni + Ni. Table 1 summarizes the typical range of variation and the baseline values of indoor ventilation, aerosol-attachment and surface deposition (aerosol-attached and airborneunattached) rates (4).

Table 1: Parameters of Jacoby room model (h-1) Parameter Ventilation rate Aerosol attachment rate Unattached plate-out rate

Symbol λv λa

Attached plate-out rate

λd

u

λd

a

Range of parameters 0.2 - 2 5 - 500 5 - 110

Baseline 0.55 50 20

0.05 - 1.1

0.2

To calculate DCF from exposure to airborne progeny atoms, it is necessary to know absorbed doses in human body and activities of airborne progeny atoms present in the room atmosphere. According to Jacobi room model (3), this activities reefer to u d fraction of airborne unattached, Ci , and attached, Ci , progeny atoms. This fraction is calculated using best estimated values of parameters from Table 1. Concentration of radon in the room is 3700 Bq/m3 which correspondent to unit exposure. Activity concentrations of radon progeny (in Bq/m3 per one working level (WL) and their fractions of radon concentrations were presented in Table 2.


191

Table 2: Activity concentration of radon progeny (in Bq/m3 per one WL) and their fractions C214Pb 50.10 1327.17

unattached attached

C214Bi 1.46 1004.71

f214Pb 0.0135 0.359

f214Bi 3.93⋅10-4 0.271

To calculate absorbed dose (in MeV/g per one particle of radiation) in all main organs and the remainder tissue of the human body (5) MCNP5 software (6) was used. This software performs simulation of radiation transport through analytical model of the human body – ORNL (Oak Ridge National Laboratory) mathematical phantom (7). Two different input files were created: adult male and adult female (8). ORNL mathematical phantom was placed in the middle of the standard room with dimensions 4×5×2.8m. Using MCNP5 software simulations were performed for beta particles and gamma radiation from 214Pb and 214Bi with starting positions randomly generated in the volume of the room, since distribution of radon and its progeny in the room was taken to be uniformly (9). Spectrums of β- and γ radiation from 214Pb and 214Bi are taken from Markovic et (10) al. . Particle energy was sampled according to yields using random method incorporated in MCNP. In order to simulate emission of whole spectrum of β- and γ radiations, large number of “histories” was created - 108 to ensure low statistical error in simulation. As a result of computation, mean absorbed dose per one particle, DTn, R , of radiation (β or γ) from the room atmosphere as a source was obtained for adult male and female ORNL phantom. To estimate DCF in mSv/WLM, DTn, R per one particle of radiation should be recalculated in the following way. Activities of radon progeny in room were given in Table 2. Since DTn, R obtained in simulation is given per quantum or per particle of radiation, and activities per disintegration, to derive absorbed dose per one working level months (WLM) one need to know the yields of certain type of radiation. Yield of β- radiation is 1, while yield for 214Pb γ spectrum is 0.98, and for 214Bi is 1.37(11). Using data for activities and yields and DTn, R obtained from simulation, absorbed doses,

DTn, R , per WLM for different types of radiation R (β or γ) and nuclide n (212Pb or 212Bi) in the main organs of the human body and remainder tissue T were obtained: DTn, R = DTn, R ⋅ An ⋅ YRn

(3)

Equivalent dose, HT in some organ T, was obtained as: HT = ∑

∑β γw

n R= ,

R

DTn, R ,

(4)


192

where wR is radiation weighting factor whose values for β- and γ radiation are equal to 1. Summation per n was done to include contribution from 214Pb and 214Bi both. After obtaining the equivalent dose for the organs and remainder of male and female ORNL phantom, effective dose (12) was calculated as: E = wbreasts H breasts + ∑ wT

H T ,m + H T , f 2

T

,

(5)

with HT,m as equivalent dose for male, and HT,f for female phantom. wT is tissue weighting factors taken from (13). Eqs (4, 5) give equivalent and effective dose which per unit exposure presents DCF. From the above calculations effective dose per one WLM, from beta and gamma radiation of radon progeny was determined.

Results Absorbed doses in all main organs and remainder tissue from beta and gamma radiation due to radon progeny distributed in the atmosphere of the room are calculated as described in Eq. 3 for adult male and female phantoms. In Table 3 absorbed doses are presented for beta particles and in Table 4 for gamma radiation.

Table 3: Absorbed doses in human organs of adult male and female phantom from βradiation of 214Pb and 214Bi, distributed in the room, in (μGy/WLM) 214

μGy/WLM Lung Skin Liver Stomach Bladder testes/ovaries Esophagus Colon Thyroid bone surface bone marrow Brain Breasts Remainder

male 3.6⋅10-3 84.4 6.5⋅10-3 1.5⋅10-3 5.7⋅10-4 1.0⋅10-4 3.0⋅10-4 2.0⋅10-3 2.0⋅10-4 1.8⋅10-2 1.1⋅10-2 4.0⋅10-3 1.6

214

Pb (β) female 2.0⋅10-3 71.5 3.8⋅10-3 1.5⋅10-4 8.4⋅10-5 1.0⋅10-6 2.0⋅10-4 1.7⋅10-3 1.1⋅10-4 1.4⋅10-2 9.4⋅10-3 5.5⋅10-3 8.8⋅10-3 1.2

male 2.5⋅10-2 61.7 4.0⋅10-2 4.0⋅10-3 1.3⋅10-3 3.4⋅10-2 1.0⋅10-3 6.8⋅10-3 7.9⋅10-2 0.80 0.63 4.5⋅10-2 24.2

Bi (β) Female 1.6⋅10-2 312.1 3.6⋅10-2 9.2⋅10-3 4.3⋅10-3 1.0⋅10-4 5.0⋅10-4 1.4⋅10-2 8.2⋅10-2 1.00 0.80 3.8⋅10-2 2.7 18.3


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Table 4: Absorbed doses in human organs of adult male and female phantom from γ radiation of 214Pb and 214Bi, distributed in the room, in Gy/WLM) μGy/WLM Lung Skin Liver stomach bladder testes/ovaries esophagus colon thyroid bone surface bone marrow brain breasts remainder

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male 6.1⋅10-3 3.8⋅10-3 2.8⋅10-3 3.1⋅10-3 2.7⋅10-3 3.0⋅10-3 2.4⋅10-3 2.5⋅10-3 1.4⋅10-3 3.8⋅10-3 3.8⋅10-3 3.3⋅10-3 2.6⋅10-3

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Pb (γ) female 6.1⋅10-3 4.7⋅10-3 2.9⋅10-3 3.7⋅10-3 2.8⋅10-3 2.7⋅10-3 2.7⋅10-3 2.5⋅10-3 2.7⋅10-3 4.0⋅10-3 4.2⋅10-3 3.4⋅10-3 3.6⋅10-3 2.7⋅10-3

male 2.4⋅10-2 1.3⋅10-2 1.1⋅10-2 1.3⋅10-2 1.0⋅10-2 1.1⋅10-2 1.0⋅10-2 1.0⋅10-2 5.2⋅10-3 1.1⋅10-2 1.1⋅10-2 1.3⋅10-2 1.0⋅10-2

Bi (γ) Female 2.3⋅10-2 1.6⋅10-2 1.1⋅10-2 1.4⋅10-2 1.1⋅10-2 1.0⋅10-2 1.1⋅10-2 1.0⋅10-2 1.0⋅10-2 1.2⋅10-2 1.2⋅10-2 1.3⋅10-2 1.3⋅10-2 1.1⋅10-2

Doses from gamma radiation are mostly homogeneously distributed in the organs of male and female phantom. High penetrating ability enables gamma radiation to pass through whole body and deposit energy within whole volume of the phantoms. In contrast, beta particles induces largest dose in the skin. Larger doses also receive remainder tissue, female breasts, bone surface and bone marrow. Beta particles lose their energy within the human tissue more rapidly than gamma radiation which explains dose distribution in Table 3. Maximum energy of beta particles for 214Pb is 1024 keV. This value for 214Bi is 3272 keV. Gamma radiation from 214Bi has greater energy with gamma lines up to 3.3 MeV. Absorbed dose received from beta and gamma radiation emitted by 214Bi are much greater than that for 214Pb and in some cases difference is order of magnitude. By multiplying of absorbed doses with radiation weighting factors, the equivalent dose from external source is derived from Eq. 4, and presented in Table 5.

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Table 5: Equivalent dose from 214Pb and 214Bi per WLM in main organs and remainder tissue of ORNL phantoms of the adult male and female (in μSv/WLM). male Lung Skin Liver stomach bladder testes/ovaries esophagus colon thyroid bone surface bone marrow brain breasts remainder

-2

5.8⋅10 146.0 6.0⋅10-2 2.1⋅10-2 1.5⋅10-2 4.8⋅10-2 1.4⋅10-2 2.1⋅10-2 8.5⋅10-2 0.83 0.66 6.5⋅10-2 25.85

female 4.7⋅10-2 383.6 5.4⋅10-2 2.7⋅10-2 1.8⋅10-2 1.3⋅10-2 1.4⋅10-2 2.8⋅10-2 9.5⋅10-2 1.00 0.83 6.0⋅10-2 2.76 19.59

Organs that receive the highest dose from radon progeny inside room is skin and female breasts. This result is quite expectable when considering conditions of irradiation. It is interesting to note that the second largest dose was received by remainder tissue. Detail analysis showed that muscle tissue (which is a member of organs which constitute the remainder) receives most of the dose: 232.57 and 195.74 μSv/WLM for male and female phantom, respectively. Muscle tissue receives the largest dose for given conditions of irradiation. Effective dose from beta and gamma radiation from radon progeny distributed in the room is 5.83 μSv/WLM, (form Eq. 5).

Conclusion Skin and muscle tissue from remainder are most exposed. DCF is calculated to be 5.83 μSv/WLM. Other organs and tissues receive far less dose. DCF from beta and gamma radiation is small when compare with DCF from alpha particles. Exposure to alpha radiation is limited to internal exposure with exception of deposition on skin. Main way of exposure to alphas is by inhalation where dose is limited to lungs mostly. Relative biological effectiveness of alpha particles is twenty times larger than electrons and gamma radiation. On the other hand, whole human body is exposed to beta and gamma radiation and it is interesting that one of remainder tissue receives the largest dose.


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Acknowledgment This work was supported by Serbian Ministry of Science, through the project No 171021. References 1. National Council on Radiation Protection and Measurements NCRP Report no. 93: Ionizing radiation exposure of the population of the United States. Bethesda, Maryland, (1987) 2. ICRP 32: Limits for inhalation of radon daughters by workers. Pergamon Press, Oxford, 6(1), 1–24, (1981) 3. W. Jacobi: Activity and potential α energy of 222Rn and 220Rn daughters in different air atmosphere. Health Physics, 22, 441–450, (1972) 4. K. Amgarou, L. Font, C. Baixeras: A novel approach for long-term determination of indoor 222Rn progeny equilibrium factor using nuclear track detectors. Nuclear Instruments and Methods in Physics Research A, 506, 186–198, (2003) 5. ICRP 60: Recommendations of the International Commission on Radiological Protection. Pergamon Press, Oxford, 21(1-3), 1–201, (1991) 6. J. F. E. Briesmeister: MCNP-a general Monte Carlo N-Particle Transport Code, Version 4B, LA-12625-M. Los Alamos National Laboratory, New Mexico, Los Alamos, (1997) 7. K. F. Eckerman, M. Cristy, J. C. Ryman: The ORNL mathematical phantom series. http://ordose.ornl.gov/resources/Mird.pdf, (1996) 8. D. Krstic: Input files with ORNL-mathematical phantoms of the human body for MCNP-4b. http://www.pmf.kg.ac.yu/radijacionafizika/InputFiles.html, (2011) 9. V. Urosevic, D. Nikezic, S. Vulovic: A theoretical approach to indoor radon and thoron distribution. Journal of Environmental Radioactivity, 99, 1829–1833, (2008) 10. V. Markovic, N. Stevanovic, D. Nikezic: Absorbed fractions for electrons and beta particles in sensitive regions of human respiratory tract. Radiation and Environmental Biophysics, 47, 139–145, (2008) 11. Table of Radioactive Isotopes. Periodic Table linked to decay data for known isotopes of each element, http://ie.lbl.gov/education/isotopes.htm 12. ICRP 74: Conversion factors for use in radiological protection against external radiation. Pergamon Press, Oxford, (1996) 13. ICRP 103: Quantities used in radiological protection. Pergamon Press, Oxford, Annex B, 247–322, (2007)

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Complex Radon and Thoron Study on Hungarian Adobe Dwellings

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COMPLEX RADON AND THORON STUDY ON HUNGARIAN ADOBE DWELLINGS Szabó Zsuzsanna1, Szabó Csaba 1, Horváth Ákos 2 1

Lithosphere Fluid Research Lab, Department of Petrology and Geochemistry, Eötvös University, Budapest 2 Department of Atomic Physics, Eötvös University, Budapest

Abstract Adobe building material samples were taken from three distinct areas of Hungary (N-Békés County, E-Mecsek Mts. and Sajó and Hernád Rivers Valleys) and studied in laboratory. Radon exhalation rates of the samples were estimated by two different techniques, growth curve and equilibrium methods, as parallel comparison experiment. Thoron exhalation rates, 226Ra, 232Th activities and grain size distributions were also determined. Winter indoor radon and thoron concentration measurements were carried out in 50 adobe dwellings at N-Békés County. Our results show that the equilibrium method provides lower radon exhalation rates than the growth curve method and a good correlation (R = -0.86) was found between the ratio of results and the degree of radon loss from the measurement circle. When the loss is below 0.005 h-1 both methods provide reliable estimation. Radon and thoron exhalation rates of adobe samples (8±2, 7±2 s-1 kg-1, respectively) are similar and can be considered high. The measured activities of 226Ra and 232Th (30±4, 26±5 Bq kg-1, respectively) are close to the average values of Hungarian soils. Grain size distribution shows peak between 10-20 μm. A weak correlation was found between the amount of 10-20 μm particles and radon exhalation rates and between the amount of 0-10 μm particles and thoron exhalation rates. Winter indoor radon and thoron concentrations (278±209, 244±202 Bq m-3 with medians 245, 211 Bq m-3, respectively) show that both radon isotopes can be important contributors to the inhalation dose of inhabitants of adobe dwellings.

Introduction Thoron (220Rn) is the only one gaseous isotope of 232Th decay chain, which similarly to radon (222Rn) in 238U decay chain, increases radiation dose obtained by humans from natural sources. Risk originated from thoron is considered low in many cases (1) due to its short half-life (55.6 s) compared to radon (3.8235 d). However, several studies (2, 3, 4, 5, 6, 7) show higher values in dwellings made mostly by soil even as Hungarian adobe buildings. Adobe is a natural building material made from clay, sand (simply soil), water and organic material and after mixing, it is dried on the sunshine without any burning procedure what could close the pores. Our goals are to obtain knowledge on radiological hazard of Hungarian adobe in line with testing a time consuming radon mass exhalation rate measurement technique.

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Szabó Zs., Szabó Cs., Horváth Á.

Study sites Three distinct areas were selected for collecting adobe samples made from local soil. These areas are N-Békés County (SE-Hungary), E-Mecsek Mts. (S-Hungary) and Sajó and Hernád Rivers Valleys (NE-Hungary), where alluvial sediments of Körös and Berettyó Rivers, loess and redeposited loess are prevailing, respectively (8). Indoor measurements were carried out in 6 settlements of N-Békés County selected on the basis of geological (8) and geographical differences.

Methods Mass exhalation rates of radon and thoron Radon mass exhalation rates of 27 adobe samples, cut to about 200 g cubic bodies, were estimated by two different techniques using Al-accumulation chambers and RAD7 detectors. One technique (i.e., growth curve method) is based on measuring the growth curve of increasing radon concentration in the closed Al-chamber for 10 days (9, 10, 11, 12). The ground of the other technique (i.e., equilibrium method) is the measurement of the radon equilibrium concentration for 4 hours after 3 weeks (about 5 T1/2) keeping it in the sealed chamber. The latter technique was built up by Ákos Horváth recently and it is faster for high number of samples but cannot take into account the process of leakage. For the case of thoron only the equilibrium concentrations can be used because of its short half-life (55.6 s). 226

Ra and 232Th activity concentrations

Activity concentrations of 226Ra and 232Th of 20 samples were analyzed by gamma-ray spectrometry using GC1520 - 7500SL HPGe detector. Gamma rays originated from powdered samples placed into Al-containers, were measured for 16 hours. The detection efficiencies were determined by Monte-Carlo simulation. Absolute transition probabilities come from NuDat 2.5 database (13). 226Ra-analysis was done by its own 186.1 keV peak taking into account that it overlaps with 235U’s 185.7 keV peak (14). For 232Th activity concentration analysis the 228Ac peak at 911 keV was used.

Grain size distributions Grain size distributions of 18 samples, each with 200-500 g weight, were determined by wet sieving and laser grain size analysis. Wet sieving was carried out by Fritsch sieves coupled with Fritsch Analysette3 sieve shaker. Numbers of different sized grains with diameters below 63 μm were measured by Fritsch Analysette22 laser grain size analyzer.


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Indoor radon and thoron concentrations Three months (28. November 2010 - 27. February 2011) winter indoor radon and thoron concentration measurements were carried out in 50 adobe dwellings in 6 settlements of N-Békés County. Raduet monitors (Radosys, Ltd.) as type of double track detector (15, 16) were used placed to 10 cm distance from the adobe walls.

Results and discussion Comparison of radon mass exhalation rate measurement methods Neither the growth curve nor the equilibrium radon mass exhalation rate measurement methods can provide reliable results when the leakage is too revealing. Hence, here only radon mass exhalation rate data of 20 samples were considered from the measured 27 ones. Since the time consuming equilibrium method does not allow taking into account the leakage, which produce radon loss from the measurement circle, it is obvious why it shows less radon mass exhalation rates (with 39±26%) than the growth curve method. The radon loss processes are described by the value of α [h-1] calculated in growth curve method. We found that the ratio of results of equilibrium and growth curve methods, which is 1 in the ideal case, shows a negative correlation (R = -0.86) with α of each experimental setup and approaches 1 when α is 0. This means that the time consuming equilibrium method also provides a good estimation of radon mass exhalation rate below a certain controlled degree of radon loss. We consider the results of equilibrium method acceptable when α is below 0.005 h-1, in this case the two methods give more than 75% fitting results. These results provide a way to carry out higher number of reliable measurements in shorter period of time.

Properties of adobe samples The determined radon and thoron mass exhalation rates of adobe samples show no correlation with each other, however the averages and standard deviations are similar (7.6±2, 6.6±2 s-1 kg-1, respectively). We compare these results to radon and thoron mass exhalation rates of different Serbian building materials but excluding adobe (17). In the reference most of the samples showed radon mass exhalation rates below 10 s-1 kg-1 and all of the samples thoron mass exhalation rates below 3.3 s-1 kg-1. Hungarian adobe building material samples show similar radon but significantly higher thoron mass exhalation rates. The reason is probably the technology of adobe making what provide possibility for short half-lived thoron to leave the building material through opened pores. All of the measured 226Ra and 232Th activity concentrations of the Hungarian adobe samples (27±3, 30±5 Bq kg-1, respectively) are close to the average values of Hungarian soils (1). Adobe building materials originated from E-Mecsek Mts. contain a bit higher amount of 232Th (34±3 Bq kg-1) than other samples (27±4 Bq kg-1) but it still

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can be considered average soil value. More detailed results of gamma-ray spectrometry measurements are presented by Völgyesi et al. (18) in this volume. Both radon and thoron emanation fractions calculated from mass exhalation rates and mother radionuclide concentrations are between 10 and 40%. These are in the range of normal values 5 to 70% for rocks and soils (19). Grain size distributions show maximum around 10-20 µm and no differences were observed between adobe samples. A weak connection exists between the amount of 10-20 µm grain size and radon emanation fraction (R = 0.58), and between the amount of 0-10 µm grain size and thoron emanation fraction (R = 0.52) what shows that short half-lived thoron can escape mainly from the finest grain sized fractions.

Winter indoor radon and thoron concentrations in N-Békés County The measured indoor radon and thoron concentrations 10 cm distance from the walls show no correlation with each other, although the averages and standard deviations are similar: 278±209 Bq m-3 for radon (outliers with uncertainties: 1024±114, 817±83 Bq m-3) and 244±202 Bq m-3 for thoron (outliers with uncertainties: 1389±138, 634±133 Bq m-3). The medians are 245 Bq m-3 for radon and 211 Bq m-3 for thoron. These results indicate that thoron can be an important contributor to the inhalation dose in Hungarian adobe dwellings and needs further study. We emphasize that these are winter measurements what normally show higher values than the annual average (20).

Figure 1: Box and whisker plots of winter indoor radon and thoron concentrations (Bqm-3) in adobe dwellings at N-Békés County. nradon = 50, nthoron = 50


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Conclusions 1. A tightly gas proof circuit is required for the best estimation of radon mass exhalation rate. When α is below 0.005 h-1 the equilibrium method gives a good estimation on a time consuming way for high number of samples. 2. Hungarian adobe is a potential thoron exhaling building material. Grain size distributions of adobe samples affect the processes of radon and thoron exhalation on different ways. 3. Results of indoor radon and thoron measurements suggest that radon is and thoron can be an important contributor to the inhalation dose in Hungarian adobe dwellings.

Acknowledgement The authors gratefully thank the help of local people, Angéla Barossné Szőnyi, Ottó Csorba, Zsolt Homoki, Győző Jordán, Gábor Kocsy, Hedvig Éva Nagy, Botond Papp, Péter Szabó and Péter Völgyesi and also the support of Lithosphere Fluid Research Lab (Eötvös University, Budapest), Doctoral School of Environmental Sciences (Eötvös University, Budapest) and Radosys, Ltd. (Budapest). The authors are thankful for the work of the reviewer. References 1. UNSCEAR: Annex B, Exposures from natural radiation sources in: Sources and Effects of Ionizing Radiation, Report to the General Assembly with scientific annexes. New York, 83–156, (2000) 2. IAEA: Annex 1, Control of exposure to thoron, in: Radiation protection against radon in workplaces other than mines. Safety Reports Series No. 33, Vienna, 41–44, (2003) 3. C. Németh, S. Tokonami, T. Ishikawa, H. Takahashi, W. Zhuo, M. Shimo: Measurements of radon, thoron and their progeny in a dwelling in Gifu prefecture, Japan. International Congress Series, 1276, 283–284, (2005) 4. G. Sciocchetti, M. Bovi, G. Cotellessa, P. G. Baldassini, C. Battella, I. Porcu: Indoor radon and thoron surveys in high radioactivity areas of Italy. Radiation Protection Dosimetry, 45(1-4), 509–514, (1992) 5. B. Shang, B. Chen, Y. Gao, Y. W. Wang, H. X. Cui, Z. Li: Thoron levels in traditional Chinese residential dwellings. Radiation and Environmental Biophysics, 44(3), 193–199, (2005) 6. Y. Yamada, S. Tokonami, W. Zhuo, H. Yonehara, T. Ishikawa, M. Furukawa, K. Fukutsu, Q. Sun, C. Hou, S. Zhang, S. Akiba: Rn-Tn discriminative measurements and their dose estimates in Chinese loess plateau. International Congress Series, 1276, 76–80, (1999)

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7. H. Yonehara, S. Tokonami, W. Zhuo, T. Ishikawa, K. Fukutsu, Y. Yamada: Thoron in the living environments of Japan. International Congress Series, 1276, 58–61, (1999) 8. L. Gyalog: 1:100 000 Geological map of Hungary (digital version). Geological Institute of Hungary, (2005) 9. N. Jonassen: The determination of radon exhalation rates. Health Physics, 45, 369–376, (1983) 10. E. Stranden: Building materials as a source of indoor radon, in: W. W. Nazaroff, A. V. Nero Jr.: Radon and its Decay Products in Indoor Air. John Wiley and Sons, New York, 113–130. (1988) 11. N. P. Petropoulos, M. J. Anagnostakis, S. E. Simopoulos: Building materials radon exhalation rate: ERRICCA intercomparison exercise results. The Science of the Total Environment, 272, 109–118, (2001) 12. A. Sakoda, K. Hanamoto, Y. Ishimori, T. Nagamatsu, K. Yamaoka: Radioactivity and radon emanation fraction of the granites sampled at Misasa and Badgastein. Applied Radiation and Isotopes, 66(5), 648–652. (2008) 13. NuDat 2.5 database (Brookhaven National Laboratory: http://www.nndc.bnl.gov/nudat2/) 14. Y. Y. Ebaid, S. A. El-Mongy, K. A. Allam: 235U–γ emission contribution to the 186 keV energy transition of 226Ra in environmental samples activity calculations. International Congress Series, 1276, 409–411, (2005) 15. WHO: Radon Measurements, in: WHO Handbook on Indoor Radon: A Public Health Perspective. World Health Organization, Geneva, 21–40, (2009) 16. M. Doi, S. Kobayashi, K. Fujimoto: A passive measurement technique for characterisation of high risk houses in Japan due to enhanced levels of indoor radon and thoron concentrations. Radiation Protection Dosimetry, 45, 425–430, (1992) 17. P. Ujic, I. Celikovic, A. Kandic, I. Vukanac, M. Durasevic, D. Dragosavac, Z. S. Zunic: Internal exposure from building materials exhaling 222Rn and 220Rn as compared to external exposure due to their natural radioactivity content. Applied Radiation and Isotopes, 68, 201–206, (2010) 18. P. Völgyesi, Zs. Szabó, H. É. Nagy, J. Somlai, Cs. Szabó: Radiation hazard of different Hungarian building materials, In this volume (2011) 19. W. W. Nazaroff, B. A. Moed, R. G. Sextro: Soil as source of indoor radon: generation, migration and entry, in: W. W. Nazaroff, A. V. Nero Jr.: Radon and its Decay Products in Indoor Air. John Wiley and Sons, New York, 57–112, (1988) 20. P. C. Deka, S. Sarkar, B. Bhattacharjee, T. D. Goswami, B. K. Sarma, T. V. Ramachandran: Measurement of radon and thoron concentration by using LR-115 type-II plastic track detectors in the environ of Brahmaputra Valley, Assam, India. Radiation Measurements, 36, 431–434, (2003)

Radiation Hazard of Different Hungarian Building Materials

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RADIATION HAZARD OF DIFFERENT HUNGARIAN BUILDING MATERIALS Völgyesi Péter1, Szabó Zsuzsanna1, Nagy Hedvig Éva1, Somlai János2 Szabó Csaba1 1

Lithosphere Fluid Research Lab, Department of Petrology and Geochemistry, Eötvös University, Budapest 2 Department of Radiochemistry, University of Pannonia, Veszprém

Abstract Building materials and their additives contain radioactive isotopes, which can increase both external and internal radioactive exposures of humans. External exposure is mostly due to gamma radiation of natural radioactive decay chains occurring in building materials, whereas internal exposure is due to radon (and thoron) exhaled. Estimating these exposures, we applied two indices, based on 226Ra, 232Th and 40K activity concentration data which were determined by gamma-ray spectrometry. The main aims of this study are to qualify 40 Hungarian adobe and artificial building material samples and evaluate the usage of applied indices. Measured radionuclide concentrations, and hence calculated indices of adobe samples are highly homogeneous but heterogeneous for artificial samples. Adobes show lower hazard indices than artificial samples because of low values of 226Ra activity concentration. Only five coal slag samples and one slag concrete sample, among the studied 40 samples, exceeded the threshold value. The estimated radiation hazard increases if radon exhalation of the building materials were taken into account instead of considering only gamma radiation. This value of the adobe samples indicate lower radon exhalation rates than that of the artificial samples, whereas several studies show opposite experiences. Limitations of these indices cannot be neglected.

Introduction Naturally occurring radionuclides are present in soil and in building materials. Since people spend 80% of their time indoors, knowledge of natural radioactivity levels in building materials is important (1). Naturally occurring 226Ra, 232Th and 40K, sometimes in enhanced amount, in building materials can indicate both external and internal radiation exposures of individuals. External exposure is due to gamma radiation; internal exposure is due to radon, and also thoron, exhaled from building materials and accumulated in indoor air. This paper presents a comparative study on two types of Hungarian building materials (i.e., adobe and artificial types) as potential radon sources using indices for external and internal exposure. Our main aims are to qualify the building materials based on calculated indices and evaluate the usage of the applied indices considering the potential of building materials for radon exhalation.

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Völgyesi P., Szabó Zs., Nagy H. É., Somlai J., Szabó Cs.

Samples Adobe and artificial building material samples were collected. Three distinct areas were selected for collecting adobe samples made from the local soil. These selected areas are Békés County (SE-Hungary), E-Mecsek Mts. (S-Hungary) and Sajó and Hernád Rivers Valleys (NE-Hungary), where alluvial sediments of Körös and Berettyó Rivers, loess and redeposited loess are prevailing, respectively (2). Seven samples were studied from Békés County, six from E-Mecsek Mts. and seven from Sajó and Hernád Rivers Valleys. The artificial building materials contain six coal slag samples, three coal slag concrete samples, six gas silicate samples with fly ash, one ytong sample (i.e., gas silicate produced with sand instead of fly ash), two brick samples and two concrete samples from several locations in the Central Hungarian region. Altogether 20 adobe (all of them used in bulk amount) and 20 artificial samples were studied. A detailed study of these adobe samples were carried out by Szabó et al (3). in this volume.

Methods Gamma-ray spectrometry Activity concentrations of 226Ra, 232Th and 40K were analyzed by gamma-ray spectrometry using GC1520-7500SL HPGe detector of Department of Atomic Physics, Eötvös University. Gamma rays, on powdered and weighted samples placed into aluminum containers, were measured for at least 16 hours. The detection efficiencies were determined by Monte-Carlo simulation. Absolute transition probabilities come from NuDat 2.5 database (4). Analysis of 226Ra was performed by its own 186.1 keV peak taking into account that it is overlapping with 235U’s 185.7 keV peak (5). Peak of 228 Ac at 911 keV for 232Th and own peak at 1461 keV for 40K activity concentration analysis were used.

Indices To qualify building materials, we used two indices. Both external (Hex) and internal hazard indexes (Hin) were calculated from the activity concentrations of 226Ra, 232Th and 40 K which are widely used recently (e.g.6). Both indices have a threshold value 1 (unit) and the building materials can be qualified being safe below this value. Eq.(1) shows the way of calculation of the external hazard index. H ex =

C 226 Rn C 232Th C 40 K + + ≤1 370 289 4810

where Hex is the external hazard index, C226Ra is the 226Ra, C232Th is the 232Th and C40K is the 40K activity concentration (Bq kg-1).

(1)


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The objective of this index is to limit the radiation dose to 1 mSv y-1 (7). Note that this calculation does not take into account the wall thickness and the existence of doors and windows(8). Internal hazard index is described by Eq.(2) below. H in =

C 226 Rn C 232Th C 40 K + + ≤1 185 289 4810

(2)

where Hin is the internal hazard index. This calculation takes into account that 226Ra decays to radon, which can be accumulated indoor and can increase radiation hazard. The denominator of 226Ra activity concentration was decreased (9). This estimation neglects other acting factors, such as “airflow patterns, frequency of air changes, and type and porosity of building materials” (10). Note that below we show both uncertainties of individual data and standard deviations of average values.

Results and discussion Activity concentrations of 226Ra, 232Th and 40K All of the measured 226Ra, 232Th and 40K activity concentrations of adobe samples (27 ±3, 30 ±5, 339 ±36 Bq kg-1, respectively, Table 1) are close to the average values of Hungarian soils (11). The activity concentrations of artificial building materials (187 ±422, 28 ±14, 202 ±117 Bq kg-1, respectively) are also shown in Table 1.

Table 1: Average 226Ra, 232Th and 40K activity concentrations and standard deviations of the measured values of the studied building materials showing the significant differences based on the aerial distribution of adobes and types of artificial building materials All adobe samples E-Mecsek Mts. Other adobes All artificial samples Coal slag Other artificial samples

C226Ra (Bq kg-1) 27 ±3 187 ±422 106 ±101 56 ±59

C232Th (Bq kg-1) 30 ±5 34 ±3 27 ±4 28 ±14 -

C40K (Bq kg-1) 339 ±36 202 ±117 -

Activity concentration of 226Ra in artificial samples can be much higher than that of adobes, whereas the average 232Th activity concentration is almost the same for both types of building materials. Furthermore, adobes contain higher amount of 40K compared to artificial samples. Also, adobe building material samples show a rather homogeneous distribution in radionuclides (lower standard deviations) than the artificial ones (Table 1).

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In details, our results show that adobe building materials, originated from E-Mecsek Mts., contain a bit higher amount of 232Th (34 ±3 Bq kg-1) than other adobe samples (27 ±4 Bq kg-1) (Table 1), but other significant differences were not recognized based on the area of sampling. In case of artificial building materials the coal slag samples have the highest 226Ra content. Not taking into account the one coal slag sample showing extremely high value (1937 ±59 Bq kg-1), the average 226Ra activity concentration of the five other coal slag samples is twice higher (106 ±102 Bq kg-1) than that of other types of artificial building materials (56 ±60 Bq kg-1) (Table 1). Activity concentrations of 232Th and 40K do not show similar property based on the type of artificial samples.

Calculated Hex and Hin indices Hex and Hin indices of all adobe samples (0.26 ±0.03, 0.33 ±0.03, respectively) are much less than the threshold value 1 (unit). Adobes of E-Mecsek Mts. have a bit higher values (0.28 ±0.02, 0.36 ±0.02, respectively) than those in Békés County and Sajó and Hernád Rivers Valleys (0.25 ±0.03, 0.32 ±0.03, respectively) because of the increased 232Th activity concentration (Table 1). Artificial building materials show higher averages and remarkable heterogeneity, based on standard deviations (0.66 ±1.15, 1.16 ±2.29, respectively), furthermore, some of them exceeds the threshold both in case of Hex (in two samples) and of Hin (in six samples). Five coal slag samples, four with Hin of 1.41 ±0.48, one with Hin of 10.61 ±0.33 and one slag concrete sample with Hin of 1.47 ±0.05 showed being hazardous mainly because of their high 226Ra content.

Estimated radiation hazard increase of building materials considering radon exhalation A simple calculation, the following Eq.(3) can be used to define HR% to show how much hazard is due to exhaled radon, based on the difference between Hex and Hin indices. ⎛H ⎞ H R % = 100⎜⎜ in − 1⎟⎟ ⎝ H ex ⎠

(3)

where HR% is in %. We use HR% (Eq.3) values to present the estimated radiation hazard increase if we consider radon exhalation of building materials (Hin, Eq.2) instead of only gamma radiation (Hex, Eq.1). The results of the HR% calculation are summarized by boxwhisker plots on the Figure 1. The HR% values of adobe samples (28 ±3%) are lower and vary in narrower range than those of artificial samples (56 ±19%). The maximum value of artificial samples is almost 100% (Figure 1) indicating that this building material is double hazardous by its Hin than its Hex value because of the high 226Ra activity concentration. This building material is the coal slag sample mentioned above what shows extremely high 226Ra activity concentration (1937 ±59 Bq kg-1).


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Figure 1: Box-whisker plots of HR% for adobe and artificial building material samples. nadobe = 20, nartificial = 20 To evaluate the applied hazard estimations (Hex, Hin), we compare HR% values of the studied building materials to indoor concentrations measured in different dwellings (12, 13). HR% of adobe samples indicate less radon exhalation rates than in the artificial samples, whereas the cited papers above reported higher indoor radon concentrations in adobe dwellings than those of other types of building materials, like brick, concrete, stone. These results light on the limit of applied indices because the HR% average of artificial samples (48 ±16%), not considering coal slag samples showing the highest values, is almost the double than that of adobe building materials (28 ±3%). Note that recent studies(14, 15, 16, 17, 18) show higher thoron concentrations in dwellings made mostly by soils, even as the Hungarian adobe buildings, than in other dwellings built by artificial building materials. Even the Hin takes no into account the possibility of hazard increase due to thoron exhalation.

Conclusions 1. Radionuclide concentrations and calculated indices in adobe samples are very homogeneous, whereas these data are heterogeneous in artificial samples. 2. Adobes show lower hazard indices than artificial samples because of smaller values of 226Ra activity concentration. Only five coal slag samples and one slag concrete sample, among the studied 40 samples, exceeded the threshold value. 3. We defined HR% for the increase of the estimated radiation hazard if the radon exhalation of building materials is taken into account (Hin) instead of considering only gamma radiation (Hex). HR% values of adobe samples indicate lower radon exhalation rates than those of artificial samples whereas in several studies the experience is the opposite. Hence, limitations of these indices cannot be neglected.

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Acknowledgements We very much thank the help of local people, inhabitants, Ottó Csorba, Győző Jordán, Zoltán Kiss and Lithosphere Fluid Research Lab. Present publication was realized with the support of the project TÁMOP-4.2.2/B-10/1-2010-0 References 1. K. Kovler: Radiological constraints of using building materials and industrial by-products in construction. Construction of Building Materials, 23, 246–253, (2009) 2. L. Gyalog: 1:100 000 Geological map of Hungary (digital version). Geological Institute of Hungary, (2005) 3. Zs. Szabó, Cs. Szabó, Á. Horváth: Complex radon and thoron study on Hungarian adobe dwellings. In this volume, (2011) 4. NuDat 2.5 database (Brookhaven National Laboratory: http://www.nndc.bnl.gov/nudat2/) 5. Y. Y. Ebaid, S. A. El-Mongy, K. A. Allam: 235U–γ emission contribution to the 186 keV energy transition of 226Ra in environmental samples activity calculations. International Congress Series, 1276, 409–411, (2005) 6. H. Al-Sulaiti, N. Alkhomashi, N. Al-Dahan, M. Al-Dosari, D. A. Bradley, S. Bukhari, M. Matthews, P. H. Regan, T. Santawamaitr: Determination of the natural radioactivity in Qatarian building materials using high-resolution gamma-ray spectrometry. Nuclear Instruments and Methods in Physics Research A, doi:10.1016/j.nima.2011.01.020 (2011) 7. ICRP: Publication 60, Recommendations of the International Commission on Radiological Protection. Pergamon Press Annals of the ICRP, Oxford, (1990) 8. R. Hewamanna, C. S. Sumithrarachchi, P. Mahawatte, H. L. C. Nanayakkara, H. C. Ratnayake: Natural radioactivity and gamma dose from Sri Lankan clay bricks used in building construction. Applied Radiation and Isotopes, 54(2), 365–369, (2001) 9. R. Krieger: Radioactivity of construction materials. Betonwerk Fertigteil-Technik 47, 468, (1981) 10. J. Beretka, P. J. Mathew: Natural radioactivity of Australian building materials, industrial wastes and by-products. Health Physics, 48, 87–95, (1985) 11. UNSCEAR: Annex B, Exposures from natural radiation sources in: Sources and Effects of Ionizing Radiation, Report to the General Assembly with scientific annexes. New York, 83–156, (2000) 12. P. C. Deka, S. Sarkar, B. Bhattacharjee, T. D. Goswami, B. K. Sarma, T. V. Ramachandran: Measurement of radon and thoron concentration by using LR-115 type-II plastic track detectors in the environ of Brahmaputra Valley, Assam, India. Radiation Measurements, 36(1–6), 431–434, (2003)


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13. M. Minda, G. Tóth, I. Horváth, I. Barnet, K. Hámori, E. Tóth: Indoor radon mapping and its relation to geology in Hungary. Environmental Geology, 57, 601–609, (2009) 14. C. Németh, S. Tokonami, T. Ishikawa, H. Takahashi, W. Zhuo, M. Shimo: Measurements of radon, thoron and their progeny in a dwelling in Gifu prefecture, Japan. International Congress Series, 1276, 283–284, (2005) 15. G. Sciocchetti, M. Bovi, G. Cotellessa, P. G. Baldassini, C. Battella, I. Porcu: Indoor radon and thoron surveys in high radioactivity areas of Italy. Radiation Protection Dosimetry, 45(1-4), 509–514, (1992) 16. B. Shang, B. Chen, Y. Gao, Y. W. Wang, H. X. Cui, Z. Li: Thoron levels in traditional Chinese residential dwellings. Radiation and Environmental Biophysics, 44(3), 193–199, (2005) 17. Y. Yamada, S. Tokonami, W. Zhuo, H. Yonehara, T. Ishikawa, M. Furukawa, K. Fukutsu, Q. Sun, C. Hou, S. Zhang, S. Akiba: Rn-Tn discriminative measurements and their dose estimates in Chinese loess plateau. International Congress Series, 1276, 76–80, (1999) 18. H. Yonehara, S. Tokonami, W. Zhuo, T. Ishikawa, K. Fukutsu, Y. Yamada: Thoron in the living environments of Japan. International Congress Series, 1276, 58–61, (1999)

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Radon Emanation Fraction Measurements of Soils Developed on Different Source Rocks from Hungary

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RADON EMANATION FRACTION MEASUREMENTS OF SOILS DEVELOPED ON DIFFERENT SOURCE ROCKS FROM HUNGARY Zacháry Dóra1, Nagy Hedvig Éva1,2, Szabó Zsuzsanna1, Szabó Katalin Zsuzsanna1, Horváth Ákos2, Szabó Csaba1 1

Lithosphere Fluid Research Lab, Department of Petrology and Geochemistry, Eötvös University, Budapest 2 Department of Atomic Physics, Eötvös University, Budapest

Abstract We collected soil and clayish cave sediment samples from Pest County (Central Hungarian Region) and Mecsek Mts. (SW-Hungary). The main aim of our study is to relate the calculated radon emanation fraction to the soil and sediment types and their bedrocks, from which the soil and sediment developed, and looking for connections between the radon emanation fraction values and the grain size of soil samples. The samples derive from the upper layer of soils, which developed on loess (24 samples), sand (17 samples), and red sandstone (4 samples), and from clayish cave sediments which developed on limestone (11 samples). Radium-226 activity concentration, radon mass exhalation rate and radon emanation fraction of the soils and sediments were determined. All of the measured 226Ra activity concentrations were in the same order of magnitude, only the soil developed on sand shows lower average value (24.1±10.3 Bq/kg) than the worldwide average (32 Bq/kg), whereas the loess and limestone originated samples have elevated average values (36.8±13.6 Bq/kg and 37.0±11.8 Bq/kg, respectively). The higher average value on red sandstone (79.7±37.5 Bq/kg) is the consequence of the geological background of that area. The sand and limestone originated samples have similar average radon mass exhalation rate values (20.6±12.3 mBq/kg/h and 16.0±9.6 mBq/kg/h, respectively), whereas soils developed on loess and red sandstone have higher average values (32.9±26.6 mBq/kg/h and 73.4±24.8 mBq/kg/h, respectively). The average radon emanation fraction is the smallest in samples on limestone (6.1±3.7 %) and highest in those on loess (16.6±12.8 %). Although the radon emanation fraction depends on many physical properties (e.g. the humidity, porosity, density), our study shows that the grain size distribution of the sample is the most important factor.

Introduction Radium-226 originates from the decay of 238U found at least in ppt quantities in all soils and rocks, although the amount varies according to the soil and bedrock type. In general, granites, phosphatic rocks and organic material rich shales have elevated radionuclide concentrations. Radon (222Rn), which derives from the decay of 226Ra, can enter indoor air mostly by diffusion and advection from the ground and building materials. Therefore, after smoking radon is the second most common cause of lung cancer deaths based on a survey in the United States and the UK (1).

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Zacháry D., Nagy H. É., Szabó Zs., Szabó K. Zs., Horváth Á., Szabó Cs.

The radon emanation fraction is the ratio of radon escaped into the atmosphere related to the total amount of radon generated in the sample. The typical radon emanation fraction for rocks and soils ranges from 5% to 70%, a regular value is approximately 25% (2). The radon emanation fraction depends on the spatial distribution of the 226Ra in the grains of soils and rocks, and porosity, density, water content and structure of the sample and temperature and pressure changes in the environment (2, 3, 4). The amount of the emanated radon should decrease when grain size increases due to the decrease of specific surface area of the grains (5). This work is focused on the radon emanation fraction in our previously studied samples. We show our results of samples originated on different bedrock using the same analytical technology. The main aim of our study, firstly, is to relate the calculated radon emanation fraction to soil and sediment types and their bedrocks, from which the soil and sediment developed, and also looking for correlations between the radon emanation fraction values and the grain size of the samples. Secondly, this paper provides information about radon emanation potential of different sedimentary rocks and also database for the Hungarian radon potential mapping.

The studied areas The studied soil samples are collected from Pest County (Central Hungarian region) and Mecsek Mts., Kővágószőlős (SW-Hungary) (Figure 1). Pest County is located in Central Hungary, which is mostly covered by Quaternary sediments (loess, sand and clay). We collected clayish cave sediments from Pál-völgy Cave located in Budapest. The cave formed on Eocene Szépvölgy Limestone and Eocene Buda Marl Formations. The majority of the cave is found in the Eocene Szépvölgy Limestone Formation. Kővágószőlős is located in Southwest Hungary. The main rock type of this area is the U-bearing Permian fluvial red sandstone (Kővágószőlős Sandstone Formation), which has mineable amounts of 238U, and uranium mine was operated in this region. The grain size of the samples differs from each other according to the rock type. In soils on loess the dominated fractions consist of the finest grain size fractions (0.01-0.05 mm), whereas the other soil and sediment samples are dominated by courser grain size fractions (i.e., 0.063-2 mm).


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Figure 1: Sample location of Pest County and Kővágószőlős (Mecsek Mts.) in Hungary Materials and methods We collected soil samples from the upper layer (0-30 cm) of the soil from Pest County (24 soil samples on loess and 17 soil samples on sand) and from Kővágószőlős (4 soil samples on red sandstone). The clayish cave sediments are from Pál-völgy Cave in Budapest (11 sediment samples on limestone). The 226Ra activity concentration of the samples was measured by gamma-ray spectroscopy using high purity germanium detector (HPGe) and the radon mass exhalation rate of the samples was determined by accumulation chamber technique coupled to RAD7 radon detector (6, 7, 8, 9). The radon emanation fraction was calculated through the following equation (Formula 1) (10): (1) where F is the radon emanation fraction (%), E is the radon mass exhalation rate (μBq/kg/s), R is the 226Ra activity concentration of the sample (Bq/kg), λ is the 222Rn decay constant (1/s).


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Results The 226Ra activity concentration ranges from 22.8±2.5 Bq/kg to 83.0±9.1 Bq/kg with an average of 36.8±13.6 Bq/kg in soils developed on loess, 10.0±1.1 Bq/kg to 39.8±4.4 Bq/kg with an average of 24.1±10.3 Bq/kg in soils developed on sand, 19.0±4.5 to 59.1±7.3 Bq/kg with an average of 37.0±11.8 Bq/kg in clayish cave sediments developed on limestone and 57.1±6.3 Bq/kg to 135.7±14.9 Bq/kg with an average of 79.7±37.5 Bq/kg in soils developed on red sandstone (Table 1). The worldwide average 226Ra concentration in soils is 32 Bq/kg (11). From our samples the soil developed on sand shows lower average value than the worldwide average, whereas those originated from loess and limestone have a little elevated values. The higher average value of soils on red sandstone is a consequence of the elevated 238U content in that area.

Table 1: The measured 226Ra activity concentrations, radon mass exhalation rates and the calculated radon emanation fraction values of the samples. The standard deviation is represented next to the measured and calculated values Host rock 226

Ra activity concentration (Bq/kg) Radon mass exhalation rate (mBq/kg/h) Radon emanation fraction (%)

Value

Loess

Sand

Limestone

Min Max average Min Max average Min Max average

22.8±2.5 83.0±9.1 36.8±13.6 5.7±0.2 110.5±3.0 39.2±26.6 1.8±0.2 52.9±6.0 16.6±12.8

10.0±1.1 39.8±4.4 24.1±10.3 5.2±0.1 48.1±1.3 20.6±12.3 2.3±0.3 31.7±3.6 13.2±8.7

19.0±4.5 59.1±7.3 37.0±11.8 4.0±0.1 40.8±1.1 16.0±9.6 1.5±0.3 15.4±1.8 6.1±3.7

Red sandstone 57.1±6.3 135.7±14.9 79.7±37.5 36.5±1.0 89.4±2.4 73.4±24.8 8.0±0.9 19.4±2.2 13.4±6.1

The radon mass exhalation rate value ranges from 5.7±0.2 mBq/kg/h to 110.5±3.0 mBq/kg/h with an average of 32.9±26.6 mBq/kg/h in soils developed on loess, 5.2±0.1 mBq/kg/h to 48.1±1.3 mBq/kg/h with an average of 20.6±12.3 mBq/kg/h in soils developed on sand, 4.0±0.1 mBq/kg/h to 40.8±1.1 mBq/kg/h with an average of 16.0±9.6 mBq/kg/h in clayish cave sediments developed on limestone, and 36.5±1.0 mBq/kg/h to 89.4±2.4 mBq/kg/h with an average of 73.4±24.8 mBq/kg/h in soils developed on red sandstone (Table 1). The sand and limestone originated samples have similar radon mass exhalation rate values of minimum, maximum and average, whereas the soils developed on loess and red sandstone have elevated values. The maximum radon mass exhalation rate value is typical of soils developed on loess, but the highest average value is calculated for soils collected on red sandstone. The radon emanation fraction ranges from 1.8±0.2% to 52.9±6.0% with an average of 16.6±12.8% in soils developed on loess, 2.3±0.3% to 31.7±3.6% with an average of


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13.2±8.7% in soils developed on sand, 1.5±0.3% to 15.4±1.8% with an average of 6.1±3.7% in clayish cave sediments developed on limestone and 8.0±0.9% to 19.4±2.2% with an average of 13.4±6.1% in soils developed on red sandstone (Table 1). The widest range (1.8±0.2% to 52.9±6.0%) and the highest value (52.9±6.0%) are in the soils developed on loess, the smallest values (1.5±0.3% to 15.4±1.8%) are in clayish cave sediments where the bedrock is limestone (Figure 2). The elevated values in soils developed on loess are the consequence of the fine grain size. The smallest grain size has the highest quantity of the emanated radon atoms due to the increased specific surface area of the grains.

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Figure 2: The calculated radon emanation fraction values of the studied samples collected on loess (a), sand (b), limestone (c) and red sandstone (d) The 226Ra activity concentration vs. the radon mass exhalation rate shows that most of the samples are in the same order of magnitude, only some soils developed on loess have elevated (>60 mBq/kg/h) radon mass exhalation rate values (Table 1, Figure 3). Furthermore, soil samples developed on red sandstone and two loess originated soil samples have higher (>60 Bq/kg) 226Ra activity concentration values (Figure 3).


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Figure 3: 226Ra activity concentration vs. radon mass exhalation rate of the studied samples developed on loess, sand, limestone and red sandstone Conclusion All of the measured 226Ra activity concentrations show the same order of magnitude, only soils developed on sand have lower average value (24.1±10.3 Bq/kg) than the worldwide average (32 Bq/kg), whereas samples derived from loess (36.8±13.6 Bq/kg) and limestone (37.0±11.8 Bq/kg) display elevated average values. The highest average value of soils collected on red sandstone (79.7±37.5 Bq/kg) is due to the adjacent geological formation containing high U-minerals. Sand and limestone originated samples have similar average radon mass exhalation rate values (20.6±12.3 mBq/kg/h and 16.0±9.6 mBq/kg/h, respectively), whereas those collected on loess and red sandstone have elevated average values (32.9±26.6 mBq/kg/h and 73.4±24.8 mBq/kg/h, respectively). The average radon emanation fraction is the smallest one on the limestone originated samples (6.1±3.7 %), and the highest on soils developed on loess (16.6±12.8 %). Although the radon emanation fraction depends on many physical properties (e.g. humidity, porosity, density), our study indicates that the grain size of the sample is the most important factor. The smallest grain size has the highest emanation fraction values because of the extended specific surface area. From the studied samples those

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developed on loess have the smallest grain size, therefore they have the highest radon emanation fraction values.

Acknowledgement The authors would like to thank to all members of the LRG. We thank Ottó Csorba of Department of Atomic Physics, Eötvös University, for the gamma spectroscopy measurement and Zsófia Bakacsi for the availability of some samples. References 1. J. D. Appleton: Radon in air and water. Medical Geology, 227–262, (2005) 2. W. W. Nazaroff, B. A. Moed, R. G. Sextro: Soil as source of indoor radon: generation, migration and entry. in W. W. Nazaroff, A. V. Jr. Nero: Radon and its Decay Products in Indoor Air, 57–112, (1988) 3. E. Stranden, A. K. Kolstad: The influence of moisture and temperature on radon exhalation. Radiation Protection Dosimetry, 7, 55–58, (1984) 4. S. A. Durrani, R. Ilič: Radon Measurements by Etched Track Detectors. World Scientific Publishing Co Pte Ltd, 11, (1997) 5. M. Markannen, H. Arvela: Radon emanation from soil. Radiation Protection Dosimetry, 45, 269–272, (1992) 6. K. Zs. Szabó: Study of radioactivity in soils from Pest County (in Hungarian). M.Sc. Thesis, Lithosphere Fluid Research Lab, Department of Petrology and Geochemistry, Department of Atomic Physics, Eötvös University, Budapest, 67, (2009) 7. Zs. Szabó: Study of radon and thoron distribution in the NE Zsámbék basin (in Hungarian). M.Sc. Thesis, Lithosphere Fluid Research Lab, Department of Petrology and Geochemistry & Department of Atomic Physics, Eötvös University, Budapest, 57, (2009) 8. H. É. Nagy, Cs. Szabó, Á. Horváth: Study of the dynamics and sources of the radon concentration in Pálvölgy show cave, Budapest (in Hungarian). VII. Environmental Scientific Conference of the Carpathian Basin, Kolozsvár (Cluj, Transylvania), 114–118, (2011) 9. H. É. Nagy: Environmental studies near closed uranium mine in the Mecsek Mts (Hungary) (in Hungarian). Thesis of the National Scientific Conference of Students, Lithosphere Fluid Research Lab, Department of Petrology and Geochemistry & Department of Atomic Physics, Eötvös University, Budapest, 46, (2007) 10. A. Sakoda, K. Hanamoto, Y. Ishimori, T. Nagamatsu and K. Yamaoka: Radioactivity and radon emanation fraction of the granites sampled at Misasa and Badgastein. Applied Radiation and Isotopes, 66, 648–652, (2008) 11. UNSCEAR (United Nations Scientific Committee on the Effects of Atomic Radiation) Annex B, United Nations, New York, (2008)

Natural Radioactivity in the Török Spring of Gellért Hill

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NATURAL RADIOACTIVITY IN THE TÖRÖK SPRING OF GELLÉRT HILL Freiler Ágnes1, Horváth Ákos2, Erőss Anita3 1

Eötvös Loránd University, Budapest Department of Atomic Physics, Eötvös Loránd University, Budapest 3 Department of Physical and Applied Geology, Eötvös Loránd University, Budapest 2

Abstract The thermal water of Török spring of Gellért Hill has one of the highest radon concentrations (620 Bq/L) measured among springs in Hungary. Previous studies identified the source of this radon level in form of red bacterial deposits in the spring cave. In this study our aims were i) to estimate the potential amount of the radon-emitter material , ii) to look after other possible Rn-sources by determining the radon exhalation of the samples. To achieve these goals radiological and mineralogical methods were used. We examined four groups of possible source materials, all were deposits in the spring cave: water surface deposit, red bacterial deposit, laminated deposit and carbonate mud. We found that the main source of radon is indeed the red bacterial deposit as the previous works stated but in addition the laminated deposit can be a radon source as well, but in a smaller extent. According to our estimation the amount of the radon-emitter material must be about 7 cm thick in the spring cave. The order of magnitude of this number is coherent with our observations.

Introduction In this study the natural radioactivity of the Török spring at the foot of Gellért Hill (located at the central region of Budapest, Hungary) was examined. The bases of the research were the results of previous investigations of Palotai et al. (2005) and Erőss (2010). Palotai et al. (2005) summarized the results of archive measurements in a comprehensive study. By conducting further measurements, they identified a radon concentration-maximum around the location of the Török spring. In her PhD Thesis, Anita Erőss identified that the source of this radon is a red, bacterial deposit. It contains iron-hydroxides which can adsorb the radon’s parent element, the radium, from the thermal water. Here radium decays while radon concentration of the spring water grows.

The aims of the work The main aim was to make quantitative estimate of the radon exhalation properties of the possible materials that can be found in the spring cave. We looked for other Rn-sources in the spring water beyond to the red bacterial deposit. For this purpuse we collected four types of samples and determined their specific radon-exhalation.

Freiler Á., Horváth Á., Erőss A.

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Furthurmore, the measured values of this new physical property allowed us to give estimation about the potential amount of the radon-emitter material that can produce the known radon concentration of the water.

Materials and Methods The four types of the solid samples are water surface deposit (A), red bacterial deposit (B), laminated deposit (C) and carbonate mud (D). (A) A thin solid layer covered the surface of the water in the spring cave. We sampled this from an about 20 cm × 20 cm area at several location and time. We call it the surface deposit. (B) Red color, low density material can be found in the bottom of the water around the whole spring cave area that is identified as bacterial origin by Anita Erőss in earlier studies. We sampled it from several place under the water, each about 10 grams. (C) The laminated deposit is a solid sample gathered at and slightly below the water level, it was attached to rocks of the wall of the cave at the sides. (D) Carbonate mud is the major material of the bottom of the water. This is a light bright (almost white) powder type material. The samples are originated from 0 cm to 10 cm depth. We carried out two types of measurements: radiological and mineralogical investigations. As the first radiological measurement (M1) we determined the radoncontent of the spring water by liquid scintillation spectroscopy. The sampling procedure began with 10 ml of water sampling into a syringe, and it was filled into a glass vial that already had contained 10 ml of OPTIFLUOR-O liquid scintillator material. 15 minutes long counting was used to determine the radon content in the laboratory, and a previous calibration procedure was applied using known activity radium solutions. The second type of radiological measurements was the gamma spectroscopy. We determined the specific radium-activity of the solid samples using a low background coaxial HPGe detector. The detector is surrounded by at least 10 cm thick lead and 6 mm thick copper shield. Each measurement lasted 24 hours long, and a 2 days long background measurement was carried out to subtract the contribution of gamma-photons arised out of the samples. The radium content was determined then by the net area of the 186 keV peak in the gamma-spectrum according to the standard method: A=

N η ⋅ I ⋅t

(1)

where A is the activity, N is the peak net area, η is the efficiency, I is the relative intensity of the 186 keV gamma-photon (3.28%) and t is the time of the measurement (generally 24 h). The efficiency was determined by Monte Carlo simulation that took into the account the geometric features of the measurement, the self absorption and the probabilities of interaction in the detector volume. This calculation was tested already using standard samples with known activities. We used I=3.28% for the relative intensity. This value assumes that there are no uranium atoms in the samples. This statement was verified


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investigating the 143 keV and 1001 keV peaks that contribute to the direct daughters of uranium isotopes. We will discuss it in the results section. One of our goals was to determine which type of material is the source of the high radon content of the Török spring. Therefore specific radon-exhalation (M) of the solid samples into air and into water was determined. The exhalation into air measurements consist of an exhalation chamber, desiccant and RAD7 radon monitor. M is the number of outcoming radon atoms per second per unit mass of the sample. That was calculated from the measured exhalation (E), E = outcoming atom/s. In the measurement the samples were closed into the exhalation chamber for 3 weeks. After the radon concentration reaches its maximum we determined in using the setup mentioned above. The size of the samples were smaller that the average diffusion lengths of the radon in soils. The radon atoms of the samples come out into the water in the natural environment, therefore we examined the solid samples specific exhalation into the water, too. The radon exhalation into water was also determined 2 times for each sample. Small amount of the samples were put into a liquid scintillation vial in addition with distilled water and 10 ml scintillator. After 3 weeks the equilibrium radon concentration was measured. During the mineralogical investigations we determined the main crystal phases by X-ray powder diffraction. Scanning electron microscopy was applied for the determination of minor components. Finally, elementary composition was determined by X-ray fluorescence analysis.

Quantitative estimate for the amount of the radon source material For the quantitative estimation of the necessary amount of each of the four types of deposits to produce the measured high radon level in the water of the spring we used the following assumptions and simplifications. All the radon come from that type of solid sample, the water doesn't flow, the depth of water is everywhere d=0.5 m, the density of the deposit is 3000 kg/m3 (it is the average density of CaCO3). The measured parameters are: ● M - the specific exhalation of the radon-emitter material (Bq/kg) ● c - radon-content of the spring water (Bq/L) Calculated or estimated parameters are: F – the surface of the basin (m2) V – total volume of the water (m3) A – total radioactivity of the water (Bq) m – weight of the radon-emitter material (kg) W – volume of the radon-emitter material (m3) d – thickness of the radon-emitter material (cm).

● ● ● ● ● ●

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Results The radon concentration of the spring water was determined 4 times in our study period. Other authors made radon measurements also in this spring, before (Palotai et al. 2005, Erőss 2010). To describe the radon level of the spring water we used the average of the two most recent studies: ours and that of Palotai et al. The average radon concentration is 617±22 Bq/L. This radon level is the highest among the known Hungarian spring and subsurface waters. The specific radium activities of all deposit types are displayed on Figure 1. These values are the averages of several samples collected in the spring cave. The red, bacterial deposit and the laminated deposit have the highest Ra-activities 1200–1300 Bq/kg. This is a surprisingly high value since the global average of the activity is about 25–26 Bq/kg.

Figure 1: Specific radium activity of the four deposit groups The peak at 1001 keV referring to the mother isotopes of radium in the uranium chain, so corresponds directly to 238U have not appeared in any of these spectra. Therefore we made a conclusion that the radium had separated from the uranium by some geological processes here. On one hand the radium and the uranium dissolves into the thermal water in different way, on the other hand these elements make precipitation also differently. Our results proved that the radium is a precipitation in the (B) and (C) type samples from the dissolved radium of the thermal water, but the uranium is not. Figure 2 shows the specific radon-exhalation of the samples into the air (pale blue) and into water (dark blue). The exhalation of the red, bacterial deposit is the highest ~550 Bq/kg into the water and into the air, too, according to 2–2 measurements of samples.


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Specific exhalation (Bq/kg)

700 600

Specific exhalation into the air

500

Specific exhalation into the water

400 300 200 100 0 Red, bacterial deposit

Laminated deposit

Water surface deposit

Carbonate mud

Name of the group

Figure 2: Specific radon exhalation into air and into water Estimation of the necessary amount of the radon-emitter material The geometric parameters of the spring cave can be estimated based on the maps of the spring (Alföldi et al., 1968) and by in situ experiences. The surface of the basin (42 m2) and the volume of the water (8.5 m3) were approximated by rectangular shape. To estimate the total radioactivity of the spring water in the spring cave we used the measured radon concentration of the water (c):

A = c · V = 5 · 106 Bq

(2)

The total exhalation of the radon source material (E) should be about the same as the total activity of the water since this system is in equilibrium A=E. The necessary mass of the radon-emitter material can than be estimated from the measured exhalation parameters (M=E/m). The volume of the radon emitter material (W) than can be estimated if we know its density: W=

m

ρ

=

E = 3 m3 M ⋅ρ

(3)


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To estimate the thickness of the radon emitter material we can use the following equations, where F is the total are of the surface of the bottom and sides of the water phase: d=

W = 7cm F

(4)

Using the measured parameters of the red bacterial deposit (and/or) the laminated deposit material, situated in the Török spring pool, the total source must be about 7 cm thick. This is a realistic value, so it can ensure the 620 Bq/L radon-content. With the mineralogical measurements we tried to reveal the material environment where the radium is located in these samples. The result of the X-ray Powder Diffraction and Scanning Electron Microscopy results both showed that all of the samples are CaCO3 deposits: calcite and aragonite. On Figure 3 we only demonstrate the secondary electron image of calcite (Figure 3A), and of aragonite (Figure 3B) measured by Scanning Electron Microscope.

Figure 3A: Secondary electron image of a water surface deposit sample it has calcite crystal structure

Figure 3B: Secondary electron image of a laminated deposit sample it has aragonite crystal structure

Summary In this study we examined the source of the radon in a natural spring water that has one of the highest radon level of subsurface water in Hungary. We proved that uranium is missing from the two potential radon source material therefore the origin of this radon is a radium precipitation. The mechanism of this deposit was investigated in the PhD thesis of Anita Erőss and she demonstrated that in this thermal water bacteria govern the process. Here we gave the first quantitative estimate for the amount of the source material for the radon content of the water. The question of our study was whether the red bacterial deposit can be alone the origin of the very high radon level of the water of Török spring. Investigating four groups of samples they showed significant radiological differences. The red bacterial deposit and the laminated deposit have the highest Ra-activity (1300 Bq/kg), and the


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highest radon exhalation. The exhalation of the red bacterial deposit is about 550 Bq/kg, and the laminated deposit is about 300 Bq/kg, respectively. According to our estimation the radon-emitter material must be about 7 cm thick in the bottom and sides of the spring cave pool. The order of magnitude of this number is coherent with our observations. The laminated deposit can be a radon source as well, however in a smaller extent. In addition, we determined the main crystal phases of the radium bearing solid samples.

References 1. E. Baradács: Hévizek és ásványvizek radon- és rádiumtartalma. PhD értekezés, Debreceni Egyetem, (2002) 2. A. Erőss: Characterization of fluids and evaluation of their effects on karst development at the Rozsadomb and Gellert Hill, Buda Thermal Karst, Hungary. PhD Thesis, Eötvös Loránd University, (2010) 3. M. Palotai, Sz. J. Mádlné, Á. Horváth: A budapesti Gellért- és a József-hegy felszín alatti vizeiben mért radon- és rádiumtartalom lehetséges forrásai. Általános Földtani Szemle, 29, 25–40, Budapest, (2005) 4. L. Alföldi, L. Bélteky, T. Böcker, J. Horvath, H. Kessler, K. Korim, J. Oravecz, G. Szalontai: Budapest hévizei. Vízgazdálkodási Tudományos Kutatóintézet, Budapest, 365, (1968)

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Long-Term Integrating Radon/Thoron Measurements in a Dwelling, a Case Study

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LONG-TERM INTEGRATING RADON/THORON MEASUREMENTS IN A DWELLING, A CASE STUDY Németh Csaba1, Ishikawa Tetsuo2, Omori Yasutaka2, Szeiler Gábor3, Kovács Tibor 3 1

University of Pannonia, Institute of Physics and Mechatronics, Veszprém 2 National Institute of Radiological Sciences, Chiba, 3 University of Pannonia, Institute of Radiochemistry and Radioecology, Veszprém Abstract Three types, altogether 12, integrating track etch detectors were placed in a dwelling close to each other for a year. The results of indoor radon and thoron concentrations show high inconsistency and variability. In the radon measurement the maximum and minimum values differ in one order of magnitude. In a same type of detector groups the differences between the minimum and maximum values were more than 50%, for all of the three types. The difference between the group averages is more than 600%. Two types of detectors provided information about thoron concentration as well. Here the difference between the two averages is found to be more than 200% and the difference between the minimum and maximum values was more than 20 times. These findings emphasize the need of the regular intercomparisons and the continuous quality control.

Introduction Among the many sources for radiation exposure to the general population the contribution of radon and thoron and their decay products represents the largest fraction of the annual effective dose from natural radioactivity (1). This is the main reason why radon/thoron surveys are conducted in different living environments. Passive integrating radon/thoron detectors are commonly used to determine the time-averaged radon/thoron concentrations. Basing on these measurements annual average doses are assessed. Also, many countries established action levels (2, 3, 4, 5), expressed in annual average radon concentration, trying to avoid excess doses from radon. The solid state nuclear etch track detectors are passive integrating detectors and are widely accepted for medium- and long-term Rn assessment (6, 7). For practical reasons, the detectors are usually placed less than a whole year on the surveyed site, and some authors use seasonal correction factors in order to calculate the annual averages of radon concentrations (8, 9). In this study integrating radon/thoron measurements were carried out in a dwelling over one year. 12 detectors (CR-39) were placed in a room exactly for one year before being were evaluated and the results compared. There are considerable inconsistences between the results.

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Németh Cs., Ishikawa T., Omori Y., Szeiler G., Kovács T.

Methods and measurements The test place was a living room in the first level of a two level building. The building has no basement. The 12 detectors were placed very close to each other. They situated on a bookshelf close to the wall (this is especially relevant for the thoron measurements) and at 1.5 m height above floor. Three types of passive integrating etch track detectors were tested. Each of them had CR-39 polycarbonate plate as the detector material. The main differences were the containers (and the evaluation methods also were a little different). The three types: T1: NRPB, T2: Radopot and T3: Raduet. The last two allow to detect the thoron concentrations as well, parallel with the ones of radon. T1: The TASTRAK CR-39 was in a NRPB chamber made from plastic, developed by National Radiation Protection Board (NRPB), U.K. These detectors were evaluated in the Institute of Radiochemistry and Radioecology, University of Pannonia. T2: The Radopot is a twin detector containing a plastic container with CR-39 polycarbonate plate inside only for radon detection and an almost identical other container enhancing its air change for detecting both radon and thoron (10). T3: The Raduet is a developed version of the Radopot, where the two parts of the twin detector are implanted in a cardboard holder which helps to keep the appropriate distances from the wall (95 mm between the wall and the center of the container). These detectors were developed in a collaboration of the National Institute of Radiological Sciences (NIRS), Japan and a Hungarian factory, RADOSYS. The Radopot and Raduet detectors were sent to evaluate to NIRS. The measurement period was from 01. December 2007 until 01. December 2008, exactly one year.

Results and discussion The results of radon measurements are summarized in the Table 1. In the case of the T1 detectors the maximum is 65% higher than the minimum. The average is 116 Bq/m3. In the case of the T2 detectors the maximum is 55% higher than the minimum. The average is 17 Bq/m3. In the case of the T3 detectors the maximum is 100% higher than the minimum. The average is 50 Bq/m3. Considering the all of the detectors the maximum is 11 times higher than the minimum. The all average is 47 Bq/m3. The differences between the averages provided by the three types of detectors: T2: 17 Bq/m3 (take it as 100%), T3: 50 Bq/m3 (294%), T1: 116 Bq/m3 (680%). This means, if someone just applies randomly one of these detectors the result can be very uncertain.


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Table 1: The measured radon concentrations Type T1 (NRPB)

T2 (Radopot)

T3 (Raduet)

Rn conc. (Bq/m3) 145 88 13 20 20 18 14 47 37 48 74 44

Average (Bq/m3)

Min-Max.

116

145 - 88

17

13 - 20

50

37 - 74

The T2 and T3 group both contain 5 data; therefore it can be informative to calculate the measurement uncertainties inside these groups. For the T2(Rn) group the standard deviation (SD) is 3.3 Bq/m3 or 19%; the standard error (SE = the SD of the average) is 1.5 Bq/m3, which is 9%. For the T3(Rn) group the SD is 14 Bq/m3 or 28%; the SE is 6.2 Bq/m3 or 13%. These uncertainties within the each group can acceptable. However, the group means are not consistent. The reason of this can be a calibration error (T2, T3 and both). The T2 and T3 detectors provided results for the thoron concentrations as well. It can be seen in Table 2. The difference between the two averages is more than 200%. The min.-max. values for all detectors are: 16 – 328 Bq/m3. It means more than 20 times difference. For the T2(Tn) the min. - max. are: 50 – 83 Bq/m3, and for the T3(Tn) the min. - max. are: 16 – 328 Bq/m3. This means that the measurement with the T3 detector shows higher uncertainty than the T2 in the case of thoron.

Table 2: The measured thoron concentrations Type 2 (Radopot)

T3 (Raduet)

Tn conc. (Bq/m3) 38 50 83 73 62 16 187 90 328 39

Average (Bq/m3)

Min-Max.

61

50 - 83

132

16 - 328

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Here for the T2(Tn) group the SD is 18 Bq/m3 or 29%; the SE is 8 Bq/m3, (13%). For the T3(Tn) group the SD is 128 Bq/m3 or 97%, the SE is 57 Bq/m3 or 43%. The uncertainties within the T3(Tn) group are very considerable. The uncertainties of the results within the groups of T2(Rn) T3(Rn) and T2(Tn) can acceptable but not for the T3(Tn) group. The differences between the group averages are very high.

Conclusions Three slightly different types, altogether 12 piece, integrating track etch detectors were placed in a dwelling close to each other for a year-long period of radon and thoron measurements. Some of the results show unexpectedly high inconsistency and variability. In the radon measurement the maximum and minimum values differ in one order of magnitude. In a same type of detector groups the differences between the minimum and maximum values were more than 50%, for all of the three types. The difference between the group averages is more than 600%. Two from the three types of detectors provided information about thoron concentration as well. Here the difference between the two averages is found to be more than 200% and the difference between the minimum and maximum values was more than 20 times. From these findings we do not want to conclude any general statement about the reliability of these kinds of measurements; also we do not want to question all dose contribution results based on these integrating measurements. This is just a note to emphasize the need of the regular intercomparisons and the continuous quality assurance.

References 1. United Nations Scientific Committee on the effects of atomic radiation, UNSCEAR: Sources and Effects of Ionizing Radiation. UNSCEAR 2000 Report, New York, (2000) 2. International Commission on Radiological Protection, ICRP: Protection against 222 Rn at Home and at Work. ICRP Publication 65, 23(2), Oxford, Pergamon Press, (1994) 3. European Commission: Radiation Protection 88, Recommendations for the implementation of Title VII of the European Basic Safety Standards concerning significant increase due to natural radiation sources. Office for Official Publications of the European Commission, Radiation Protection Series, (1997) 4. S. Risica: Italian Basic Safety Standards legislation. Journal of Radiological Protection, 21, 81 (2001)


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5. The Radiation Protection Authorities in Denmark, Finland, Iceland, Norway and Sweden: Naturally Occurring Radioactivity in the Nordic Countries – Recommendations. (2000) 6. S. Tokonami, M. Yang, T. Sanada: Contribution from thoron on the response of passive radon detectors. Health Physics, 80, 612–615, (2001) 7. M. Janik, S. Tokonami, T. Kovács, N. Kávási, C Kranrod: International intercomparisons of integrating radon detectors in the NIRS radon chamber. Applied Radiation and Isotopes, 67, 1691–1696, (2009) 8. M. J. Woods, J. J. Dean, S. M. Jerome, D. K. Modna: Review of rapid methods for assessing radon levels in domestic premises. DETR report; DETR/RAS/99.01 (2000) 9. Cs. Németh, V. Jobbágy, N. Kávási, J. Somlai, T. Kovács, S. Tokonami: Radon and Thoron parallel measurements in dwellings nearby a closed Hungarian uranium mine. Nukleonika, 55(4), 459–462, (2010) 10. W. Zhuo, S. Tokonami, H. Yonehara, Y. Yamada: A simple passive monitor for integrating measurements of indoor thoron concentrations. Review of Scientific Instruments, 73, 2877–2881, (2002)

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The Last 4 Years’ Radon Activity Concentration Tendency in Tapolca Cave

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THE LAST 4 YEARS’ RADON ACTIVITY CONCENTRATION TENDENCY IN TAPOLCA CAVE Somlai János1, Gál Nelli1, Kopek Annamária2, Szeiler Gábor1, Sas Zoltán1, Kovács Tibor1, Kávási Norbert3 1

University of Pannonia, Institute of Radiochemistry and Radioecology, Veszprém, 2 Balaton Uplands National Park, Csopak 3 Social Organization for Radioecological Cleanliness, Veszprém

Abstract More and more attention has been given to improve workplace conditions in the last few decades, primarily to reduce the many different health risks. In the air that accumulates in underground workplaces radon may constitute such a health risk. The radon concentration in the show cave in Tapolca is especially high in summer months, with the annual average (7342 – 10 370 Bq/m3) much more, than the recommended action level (1000 Bq/m3). As the hours spent in the cave by the workers depend on the number of visitors, the radiation dose was estimated on the basis of personal dosimeters. The personal radiation dose is significant, especially for those employed during the whole year. Taking into consideration the actual working hours, and the equilibrium factor F=0.4 given in the literature, it approaches and even exceeds the dose limit of 20 mSv/year. With a well-organized work schedule, as well as the employment of outside workers during the summer period, the dose limit of 20 mSv/year can probably be maintained. During the survey the monthly radon concentration of the cave and the cave lounge were monitored. The received results were compared with the average annual temperature and pressure, the results appears to indicate correlation between the investigated parameters.

Introduction Radon can accumulate in the subterranean premises such as caves, mines and other underground places where people work. The quality of workplace air plays a significant role in health risk management, and international regulations set out strict limits on the quantity of carcinogenic materials permitted. The carcinogenic effect of radon as a radioactive noble gas is well-known (1) and some new epidemiological studies show strong correlation in case of low radon level, as well (3). More than half of the natural radiation dose effecting people is caused by radon and its progenies (4). Most of the international recommendations and legislation cover the maximum level of radon allowed at workplaces (5). The activity level recommended by the ICRP 103 for annual average radon concentration is 1500 Bq/m3. Hungarian regulations (6) for workplaces set a radon concentration level of 1000 Bq/m3 as an annual average activity level, which thus means 6.3 mSv/year radiation dose at an equilibrium factor of 0.4 and 2000 working hours/year. The ICRP 2009 annual report and the WHO 2009 report recommend 1000 Bq/m3 action level of the workplace. If this limit is exceeded

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Somlai J., Gál N., Kopek A., Szeiler G., Sas Z., Kovács T., Kávási N.

and it is not possible to decrease it, then such a workplace would be determined to be a hazardous radiation workplace. With these regulations, workers may receive a maximum radiation dose of 100 mSv/5 year (that is an average of 20 mSv/year) and there is a limitation that the dose must not exceed 50 mSv within one year. Taking into consideration the ever constantly high radon concentration in the cave and the long hours spent there by workers, the limit of 20 mSv/year was taken as a reference value for the radiation dose limit. The development of high radon concentration can be expected in places where the radon source is 226Ra and it occurs in high concentration in walls and building materials (7) enclosed in surrounding air spaces. This is especially so if the degree of ventilation is low (8, 9), and thus, the emanated radon can easily accumulate. The latter conditions almost always exist in underground air spaces such as in cellars, mines, and caves, so special attention should be given to the quality of air in such workplaces. In caves which are popular for tourists, the health effect of high radon concentrations is insignificant for the visitors due to the short exposure times (10). However, for those working in the cave, the extra dose must be taken into consideration in all cases (11, 12). The show cave in Tapolca is one of the most visited show caves in Hungary, as a pond located in the cave has proved to be very popular. Based on prior measurements, the values of radon concentration generated in the cave fluctuate within a wide-scale on a seasonal basis, similarly to other caves of its piedmont type (13) and in the summer months it exceeds an activity concentration value of 10.000 Bq/m3, while in winter the activity concentration is usually lower. Due to the high fluctuation of radon concentration and the intense changes in other parameters, several researchers have drawn the attention to the inaccuracy of dose estimations carried out in such workplaces (14). Accurate dose estimation is only possible if a very accurate determination of the average radon concentration is performed. The radon concentration measurements should be carried out for an appropriately long time, of course, during working hours if possible (15). For the precise dosimetry, knowing the concentration of radon progenies is also essential (16). This study describes the change of radon concentration in the caves and in the shelter room in the Tapolca cave, and the radiation dose originating from radon (and it’s progenies) for those working there in the years of 2007-2010. Correlations between collective effective dose and radon concentration as well as correlations between radon concentration and weather conditions like average annual outdoor temperature or outdoor pressure were analysed.


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Materials and methods Location of the study The monthly average radon concentration level was measured for 4 years in the show caves, and in the shelter room of the Tapolca cave, located in Hungary.

Radon measurement Measurement of the integral radon concentration in caves and in the shelter room was done by using CR-39 type TASTRAK nuclear track-etch detectors that were placed in holders made by the National Radiation Protection Board, U.K. After a one-month exposure period, the detectors were etched in 6 M NaOH solution at 80±0.5 °C for 2 hours. The track detectors had been calibrated in an airtight radon chamber (EV 03209, produced and calibrated by Genitron Instruments GmbH) by employing a PYLON RN 2000A calibration standard source.

Personal dosimetry Trace detectors were used as personal radon dosimeters. Detectors were worn by the workers fixed to their clothes, and out of working hours they were kept in a room with a controlled low radon concentration.

Calculation of radiation exposure Knowing the measured radon concentration (CRn) the committed effective dose was calculated using the equation: E = CRn × F × t × K

(1)

E: committed effective dose (mSv) CRn: average radon concentration (Bq/m3) F: average equilibrium factor (used the recommended 0.4) t: time spent inside during the period investigated (h) K: dose conversion factor (IBSS-115: action level 1000 Bq/m3 (F = 0.4, t = 2000 h/year, Committed Effective Dose = 6.3 mSv/year).

Results and discussion Results of radon measurements The monthly average radon concentration values measured in the cave and in the shelter room in the period of 2007 – 2010 are presented in Figure 1, and Figure 2. It can be seen that the radon concentration is much higher in hotter summer months, but it even reaches high values in some of the winter months, so the cave is not a typical piedmont cave. Probably other connected caverns influence its radon concentration. Similar radon concentration profile can be observed in the case of the


236

cave shelter. During summer the measured values were appreciably over the recommended 1000 Bq/m3 acting level. The annual average radon concentration of the cave and the shelter room are listed in Table 1.

Figure 1: Monthly average radon activity concentration (min-max) in the cave in the period of 2007-2010 years

Figure 2: Monthly average radon activity concentration (min-max) in the shelter room in the period of 2007-2010 years Table 1: The annual average radon concentrations of the cave and the shelter room Year 2007 2008 2009 2010

Annual average radon concentration (Bq/m3) Cave Cave shelter 10370 1405 8702 1083 9272 1014 7343 706


237

The reduction of the inner radon concentration is not possible without significant intervention, which can greatly modify the climatic conditions in the cave. This is the reason why the workplace would be determined to be a hazardous radiation workplace.

Workers’ radiation dose The committed effective dose values calculated on the basis of the number of actual working hours using the equilibrium factor F = 0.4, as required by law, and the monthly results from the track detectors worn by the workers. During the examined 4 year-long period two persons were employed permanently in the cave and further two in the cave shelter. The suffered committed effective doses of the workers, which were calculated based on the detected radon concentration values of personal dosimeters, were correlated with the annual average radon concentration of the cave (Figure 3 and 4) Due to the received results the following consequences can be stated. The calculated committed effective doses of the workers in the observed area correlate with the average annual radon concentrations of the monitored workplaces. Personal dosimeters are appropriate tools for this task. The correlation between the outdoor temperature and the pressure was examined during the investigation. As a result of the comparison slightly correlation can be stated in case of the cave and the cave shelter as well, though the radon concentration is probably influenced by the interactions of further factors. Due to the similarity the committed effective dose of the employees can be monitored with the radon measurement of the workplace.

Figure 3: Correlation between the collective committed effective dose of the permanent stuff (2 persons) (calculated by personal dosimeter) and the yearly average radon concentration measured in the cave

238


Figure 4: Correlation between the collective committed effective dose of the permanent stuff (2 person) (calculated by the data of personal dosimeters) and the yearly average radon concentration measured in the cave shelter

Figure 5: Correlation between annual average radon level and outer average temperature

Figure 6: Correlation between annual average radon level and outer average air pressure


239

Summary It can be stated that the radon concentration, especially in summer months, is high in the cave and in the shelter room. Although slightly correlation can be observed between the outdoor temperature and the pressure, the evidence may in fact suggest that the radon concentration in the cave is influenced by the interaction of further factors (weather conditions). The correlation between the received average annual radon concentration and the given suffered effective dose of the employees which was calculated from the results of the personal dosimeter clearly prove that the continuous radon measurement of the workplaces suitable for the dose estimation of the workers.

Acknowledgement Present publication was realized with the support of the project TÁMOP-4.2.2/B-10/1-2010-0 References 1. R. W Hornung, J. A. Deddens, R. J. Roscoe: Modifiers of Lung Cancer Risk in Uranium Miners from the Colorado Plateau. Health Physics, 74(1), 12–21, (1998) 2. V. E. Archer, S. D. Wagoner, F. E. Lundin: Cancer Mortality among Uranium Mill Workers. Journal of Occupational Medicine, 15(1), 11–14, (1973) 3. S. Darby, D. Hill, H. Deo, A. Auvinen, J. M. Barros-Dios, H. Baysson, F. Bochicchio, R. Falk, S. Farchi, A. Figueiras, M. Hakama, I. Heid, N. Hunter, L. Kreienbrock, M. Kreuzer, F. Lagarde, I. Mäkeläinen, C. Muirhead, W. Oberaigner, G. Pershagen, E. Ruosteenoja, A. Schaffrath Rosario, M. Tirmarche, L. Tomásek, E. Whitley, H-E. Wichmann, R. Doll: Residential radon and lung cancer detailed results of a collaborative analysis of individual data on 7148 persons with lung cancer and 14 208 persons without lung cancer from 13 epidemiologic studies in Europe. Scandinavian Journal of Work Environmental Health, 32, 1–84, (2006) 4. United Nations Scientific Committee on the Effects of Atomic Radiation. Sources and Effects of Ionizing Radiation. UNSCEAR 2000 Report to the General Assembly, with Scientific Annexes.Vol I: Sources. New York, (2000) 5. ICRP (International Commission on Radiological Protection). Protection against radon-222 at home and at work. ICRP Publication 65, Oxford, Pergamon Press, (1994) 6. Hungarian Regulation 10 16/2000 VI.8., Ministry of Health implementing the provisions of the law No. CXVI. of the year 1996 of nuclear energy. Hungarian Bulletin No. 55, Budapest, Hungary, (2000) 7. C. R. Cothern, J. E. Smith Jr: Environmental Radon. Environmental Science Research, Plenum Press, New York and London, (1987)

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8. J. Hakl, I. Hunyadi, I. Csige, G. Gécky, K. L. Lénart, A. Várhegyi: Radon transport phenomena studied in karst caves—international experiences on radon levels and exposures. Radiation Measurements, 28, 675–684, (1997) 9. C. Dueñas, M. C. Fernández, S. Cañete, J. Carretero, E. Liger: 222Rn concentrations, natural flow rate and the radiation exposure levels in the Nerja Cave. Atmospheric Environment, 33, 501–510, (1999) 10. S. B. Solomon, R. Langroo, J. R. Peggie, R. G. Lyons, J. M. James: Occupational exposure to radon in Australian tourist caves: an Australia-wide study of radon levels, Yallambie Vic, 3085, (1996) 11. I. Kobal, M. Ančik, M. Škofljanec: Variations of 222Rn air concentration in Postojna cave. Radiation Protection Dosimetry, 25, 207–211, (1988) 12. J. T Duffy, J. S Madden, G. M Mackin, A. T. McGarry, P. A. Colgan: A reconnaissance survey of radon in show caves in Ireland. Environment International, 22(1), 415–423, (1996) 13. K. Balogh, I. Csige, J. Hakl, E. Hertelendi, I. Hunyadi, E. Koltay, Á. Kovách, I. Rajta: Fejezetek a környezetfizikából. Kézirat KLTE-ATOMKI Közös Fizikai Tanszék, Debrecen, (1994) 14. N. Kávási, J. Somlai, T. Kovács, C. Németh, T. Szabó, Z. Gorjanacz, A. Várhegyi, J. Hakl: Difficulties in Radon Measurements at Workplaces. Radiation Measurements, 41, 229–234, (2006) 15. SSI (Swedish Radiation Protection Institute). Radon Legislation and National Guidelines. Åkerblom, G: ISSN 0282–4434, (1999) 16. Y. Ishimori: Time-integrated monitoring of radon progeny around a closed uranium mine in Japan. Journal of Environmental Radioactivity, 51–61, (2007) 17. M. S. Field: Risks to cavers and cave workers from exposures to low-level ionizing a radiation from 222Rn decay in caves. Journal of Cave and Karst Studies, 69(1), 207–228, 2007 18. P. Jovanovic: Radon measurements in karst caves in Slovenia. Environment International, 22(1), 429–432, (1996) 19. W. Zahorowski, S. Whittlestone, J. M. James: Continuous measurements of radon and radon progeny as a basis for management of radon as a hazard in a tourist cave. Journal of Radioanalytical and Nuclear Chemistry, 236, 219–225, (1998) 20. N. Kávási, J. Somlai, T. Kovács, T. Szabó, A. Várhegyi, J. Hakl: Occupational and patient doses in the therapeutic cave, Tapolca (Hungary). Radiation Protection Dosimetry 106, 263–266, (2003) 21. International Basic Safety Standards for Protection against Ionizing Radiation and for the Safety of Radiation Sources. Safety series No. 115, International Atomic Energy Agency, Vienna, 1996 22. P. Szerbin: Radon concentrations and exposure levels in Hungarian caves. Health Physics 71, 362–369, (1996)

Radon Content of Drinking Water in Veszprém and in the Surrounding Settlements

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RADON CONTENT OF DRINKING WATER IN VESZPRÉM AND IN THE SURROUNDING SETTLEMENTS Sas Zoltán, Pallósi Tamás, Somlai János, Szeiler Gábor, Chirca Ion, Kovács Tibor University of Pannonia, Institute of Radiochemistry and Radioecology, Veszprém Abstract Half of the natural radiation dose on humans is caused by the radon gas belonging to the decay chain of uranium and its daughter elements. Released from the rocks it can get into drinking waters and after consumption they can increase the radiation dose on humans. In this study the 222Rn concentration of mains water in 120 settlements in Balaton Highland, Hungary was measured. The average Rn concentration was 5.56 (0 – 24.3) Bq dm-3. Owing to previous studies, which dealt with the Rn concentration of mains water inspected in the Southern Great Plain region, it can be stated that the Rn concentration of mains water here is, as an average, half of the Rn concentration of fountains in the same region. This decrease in radon probably happens during the water management and storage of mains drinking waters. The 222Rn concentration of springwaters examined in the region of the Balaton Highland as well and the received result exceed the average Rn concentration of drinking waters (average 27.1 Bq dm-3). The radiation dose originating from the consumption of mains drinking water in case of adults does not reach the value of 0.1 mSv year-1, even in case of a conservative assessment (1 dm3 day-1 water consumption and 10-8 Sv Bq-1 dose conversion factor).

Introduction Radon (222Rn) is a naturally occurring radioactive noble gas with a half life of 3.82 days. It is a member of the 238U decay series and its presence in the environment is associated mainly with the trace amounts of its immediate parent, 226Ra, in rock and soil. Since radon is an inert gas, it can move through porous media such as soil or fragmented rock (1, 2, 3, 4). Where the pores are saturated with water, radon is dissolved into the water and transported (5). The concentrations of radon in water vary markedly generally being highest in well water, intermediate in ground water (6, 7) and lowest in surface water (reference values 100, 10, and 1 kBq m-3 (8, 9, 10)). For that very reason, several research workers have been surveying radon concentration of drinking waters and surface waters, and found that the concentration of radon and its progeny in drinking waters in the Carpathian basin generally exceeds the average values (11, 12, 13, 14). Knowing the radon concentration values of surface and other waters is not only important from the aspect of dosimetry. It provide information about the geological and hydro-geological characteristics of the environment (15). It can also act as a natural tracer (16, 17).

Sas Z., Pallósi T., Somlai J., Szeiler G., Chirca I., Kovács T.

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However, the radon concentration of drinking waters is surveyed due to the dosimetry aspect, as nowadays increasingly more attention is paid to the restriction of radiation exposure of the citizens from natural sources. The WHO (18) and the EU Council (19) recommends a reference level of effective dose received from drinking water consumption at 0.1 mSv year-1. The dose received from 3H, 40K, and 222Rn is not incorporated in this value. There are difficulties in applying the reference level of dose to derive activity concentrations of 222Rn in drinking water, as radon is released from water during handling, stirring, transferring water from one container to another. Water that has been left to stand has reduced activity and boiling completely removes radon. The limit value of 222Rn related to drinking waters is regulated by the European Comission. (Commission recommendation on the protection of the public against exposure to radon in drinking water supplies, 2001/928/Euratom). On the bases of these, the following action should be taken for water supplied as part of a commercial or public activity: to protect human health above 100 Bq dm-3, member state should set a reference level for radon A level higher than 1000 Bq dm-3, remedial action is deemed to be justified on radiological protection grounds. Seven countries in the EU (Denmark, Finland, Germany, Greece, Ireland, Sweden and the Czech Republic) have set reference levels for radon in drinking water. Reference levels are in the range of 20 to 1000 Bq dm-3, which is in accordance with EU recommendations. Different limit values are given in several countries for public water supply, private water supply, mineral water or all drinking waters, and in some countries a special limit is given concerning infants. Values introduced in country are given in Figure 1. USA Sweden recommended

Slovakia

directive

Russia Romania Norway Finnland Czech 0

100

200

300

400

500

600

Bq dm-3

Figure 1: Reference levels for radon concentration in drinking water in some countries


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Measurements and methods During our work the radon concentration of the mains drinking waters of several settlements in the Balaton Highland region were measured. The radiation dose originating from the consumption of drinking water was determined. Nearby the tap water sampling places, some well water was investigated, as well.

Sampling A tap water sampling locations are shown in Figure 2. In the springtime 53 tap waters were measured.

Figure 2: Sampling locations By the sampling of drinking waters generally the fountains on the street, installed on the mains water pipeline were used. Approximately 20 l of water was let out before sampling. Then water was taken with the help of barrels and it was poured into the sampling cylinder, which was immediately closed. Right after the sampling, the radon content was determined. When sampling could only be carried out inside a building, water was let out for 10 minutes before taking the sample in order to let out water from the possibly stagnant pipe section, and to receive parameters characteristic of the fresh water.

Measurement of 222Rn concentration 222

Rn was measured from 190 cm3 water samples, from which the radon gas was bubbled out into a vacuumed Lucas-cell of Pylon 110 A type, with the help of a Pylon WG 1001 portable equipment. In order to ensure the equilibrium between the radon and the daughters, measurements were performed after three hours. Lucas-cells were connected to the Pylon AB-5 radon monitor and the intensity was measured for 3 x 10 minutes.


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The efficiency of the Lucas-cells was determined by measuring gas mixture with well-defined radon concentration. This mixture was produced in Genitron EV 03209 calibrated radon chamber with a Pylon RN 2000 radon emanation source In case of radon, degassing efficiency was determined by using water with approximately 10 Bq dm-3 radon concentration. Radon from water was driven to three different vacuumed Lucas cells in succession. The value measured in the first cell was compared to the total amount of radon driven through. The measured degassing efficiency (min-max) was 97 (96-98) %.

Dose assessment The committed effective dose contribution of citizens was calculated by equation (1) E=K·G·C·t

(1)

where E K G C T

is the committed effective dose from ingestion (Sv) is the ingesting dose conversion factor of 222Rn (Sv Bq-1) is the water consumption (dm3 day-1), is the concentration of 222Rn (Bq dm-3) is the duration of consumption, here 365 days.

As the International Atomic Energy Agency (IA), Basic Safety Standards (BSS) does not have dose conversion factors for the intake of 222Rn, in this case factors found in the UNSCEAR 1993 were considered. The committed effective dose per unit intake from the ingestion of radon in water is 10-8 Sv Bq-1 for adults, while 2 x 10-8 Sv Bq-1 for children (United Nation 1993). Global data on the consumption of drinking water are limited. In studies the average daily consumption is usually found to be less than 2 liters per capita, but there is a considerable variation between individuals. The water intake is likely to vary with climate, physical activity, habits of life, economical status etc. As it was mentioned in the introduction, the radon concentration of drinking waters decreases during storage, processing etc., so by the evaluation of dose, the consumption of interest is that of water taken directly from the tap. As citizens regularly using springs say, their daily spring water consumption is 1 dm3. The annual effective dose was also estimated by a consumption of 1 dm3 day-1, even in the case of tap water.

Results and discussion Radon concentrations The measured radon concentrations are demonstrated in Figure 3. The received main value is 5.4 Bq dm-3 and the 10 Bq dm-3 was exceeded only 6 times. The maximum measured value was 32 Bq dm-3, which is still greatly lower than the EU recommended 100 Bq dm-3 action level.

245

(Bq/dm3)


Figure 3: The measured radon activity concentrations in tap water Dose assessment In case of 1 liter per day water consumption, the committed effective dose from ingestion of 222Rn, calculated for different age groups In case of adults the estimated dose was given 20.3 (1.13-88.7) µSv year-1 while in case of children the calculated value was the double 40.6 (2.26-177) µSv year-1. The results clearly show that assuming adults directly consuming 1 liter of tap water (as drinking water), a radiation dose of 20 µSv year-1 is expectable, which is negligible besides to the world average of 2.4 mSv year-1 originating from of natural radiation sources. (It does not reach the value of 0.1 mSv year-1 even in case of maximum concentration.) Calculating with an average radon concentration, low doses are received by children. Taking the actual consumption into consideration, even smaller values are expectable. Besides the tap water sampling, well water was taken in 12 settlements. The received results can be seen in Figure 4.

Figure 4: Results of the parallel tap water and well water measurement

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According to the results, it can be slightly stated that the radon content of the well water generally higher than the tap water. The phenomenon can be explained by the different radium content of the reservoir rock and by the fact that tap water is normally stored in artificial reservoirs before usage.

Summary The average value (5.3 Bq dm-3) of 222Rn concentration of the 53 mains drinking water samples examined in the regions in Balaton Highland is low. None of them approached the EU recommended 100 Bq dm-3 action level. In case of the measured and compared well water measurement, the determined radon content was higher in almost every case, which can be caused by the different storing circumstances and time before usage. As a summary, it can be stated that in case of adults, the radiation dose originating from consuming mains drinking water does not reach the value of 0.1 mSv year-1, even by a conservative estimation (1 dm3 day-1 water consumption and dose conversion factor of 10-8 Sv Bq-1), therefore no intervention for reducing the 222 Rn concentration of drinking waters is necessary.

Acknowledgement Present publication was realized with the support of the project TÁMOP-4.2.2/B-10/1-2010-0 References 1. A. B. Tanner: Radon migration in the ground: A review, in the natural radiation environment, University of Chicago Press, Chicago, 161–190, (1964) 2. A. B. Tanner: Radon migration in the ground: A supplementary review, in the natural radiation environment III. Symposium Proceedings, Houston, 5–56, (1980) 3. N. M. Soonawala, W. M. Telford: Movement of radon in overburden. Geophysics, 45, 1297–1315 (1980) 4. I. Csige: Radon a környezetben, in: Fejezetek a környezet fizikából, Debrecen, 123–145, (2003) 5. J. N. Andrews and D. F. Wood, Mechanism of radon realize in rock matrieces and entry into groundvaters, Trans. I.M.M. Sect. B, 81, 198–209, (1972) 6. T. A. Przylibski, K. Mamont-Cie la, M. Kusyk, J. Dorda, B. Kozowska: Radon concentrations in groundwaters of the Polish part of the Sudety Mountains (SW Poland). Journal of Environmental Radioactivity, 75(2), 193–209, (2004) 7. V. M. Choubey, S. K. Bartarya, R. C. Ramola: Radon in groundwater of eastern Doon valley, Outer Himalaya. Radiation Measurements, 36(1-6), 401–405, (2003) 8. G. Karahan, N. Öztürk, A. Bayülken: Natural radioactivity in various surface waters in Istanbul, Turkey. Water Research, 34(18), 4367–4370, (2000)


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9. P. K. Hopke, T. B. Borak, J. Doull, J. E. Cleaver, K. F. Eckerman, L. C. S. Gundersen, N. H. Harley, C. T. Hess, N. E. Kinner, K. J. Kopecky, T. E. Mckone, R. G. Sextro, S. L. Simon: Health risks due to radon in drinking water. Environmental Science & Technology, 34, 921–926, (2000) 10. M. S. Al-Masri, R. Blackburn: Radon-222 and related activities in surface waters of the English Lake District. Applied Radiation and Isotopes, 50(6), 1137–1143, (1999) 11. T. Kovacs, E. Bodrogi, J. Somlai, V. Jobbagy, G. Patak, Cs. Nemeth: Ra-226 and Rn-222 concentrations of spring waters in Balaton Upland of Hungary and the assessment of resulting doses. Journal of Radioanalytical Nuclear Chemistry, 258(1), 191–194, (2003) 12. Zs. Kasztovszky, P. Szerbin, R. Kuczi: On the natural radioactivity of waters in Hungary. Central European Journal of Occupational and Environmental Medicine, 2(4), 335–347, (1996) 13. S. Žunić, I. Kobal, J. Vaupotič, K. Kozak, J. Mazur, A. Birovljev, M. Janik, I. Čeliković, P. Ujić, A. Demajo, G. Krstić, B. Jakupi, M. Quarto, F. Bochicchio: High natural radiation exposure in radon spa areas: a detailed field investigation in Niška Banja (Balkan region). Journal of Environmental Radioactivity, 89, 249–260, (2006) 14. C. Cosma, D. Ristoiu, A. Poffijn, G. Meesen: Radon in various environmental samples in the Herculane spa, Cerna Valley, Romania. Environment International, 22, 383–388, (1996) 15. J. E. Gringrich: Radon as a geochemical exploration tool. Journal of Geochemical Exploration, 21, 19–39, (1984) 16. K. K. Ellins, A. Roman-Mas, R. J. Lee: Using 222Rn to examine groundwater/surface water discharge interaction in the Rio Grande de Manati, Puerto Rico. Journal of Hydrology, 115, 319–341, (1990) 17. P. G. Cook, G. Favreau, J. C. Dighton, S. Tickell: Determining natural groundwater influx to a tropical river using radon, chlorofluorcarbons and ionic environmental tracers. Journal of Hydrology, 277, 74–88, (2003) 18. World Health Organization, Guidelines for Drinking-Water Quality, 1, Recommendations, Geneva, (1993) 19. Council Directive 98/83/EC: The quality of water intended for human consumption. Official Journal, L, 330/45, (1998) 20. Commission Recommendation of 20 December 2001 on the protection of the public against exposure to radon in drinking water supplies, 2001/928/Euratom, (2001)

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Radon Emanation of Slovenian Soil Samples

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RADON EMANATION OF SLOVENIAN SOIL SAMPLES Kardos Richárd1, Horváth Mária2, Bujtor Tibor1, Vaupotic Janja3, Kovács Tibor1 1

Inst. of Radiochemistry and Radioecology, University of Pannonia, Veszprém 2 Social Organisation for Radioecological Cleanliness, Veszprém 3 Jozef Stefan Institute, Ljubljana

Abstract Radiological maps have been more and more widespread lately, and the development of the geographic information system and complex data administration methods has allowed for the establishment of a database which would in the future help the work of decisionmakers. Attached to a complex radiological survey covering Slovenia, this work includes the measurement of the radon emanation of 60 pieces of soil samples taken from different areas of Slovenia. Two different instruments were used for the measurements. One is an EMI photomultiplier is connected with the NP 420 single channel amplitude analyser, the other is a NDI detector from GammaTech. Measurements were carried for 1000 seconds. The following results were gained: the emanation factor was between 0.96±0.2-61±0.7 %, the highest values were by the carbonates and by the tertiary sediments. The emanation factors show high variation, the average value was between 40-60 %. High emanation factors were measured by the carbonates and by the tertiary sediments. The highest emanation factor was measured in the Southern region, but in the other two regions were some high emanation factors.

Introduction Nowadays the estimation of the risks of natural effects, that endanger homes and work places, gains more and more importance. One of the most important factors is the radiation risk of these areas. For this mainly the radon and it’s daughter elements are responsible. Our aim is assessing the radon potential of a specific area, and displaying it with a detailed radon map. The map has to keep in mind, besides radon concentration, a lot of other influential factors (meteorological, pedological, radiological) (1). The concentration of radon in dwellings is influenced by the Ra-226 concentration in soil. It is important to establish a database, which provides information on the exposure from radon in the given area.

Kardos R., Horváth M., Bujtor T., Vaupotic J., Kovács T.

250

Sampling and sampling sites The measured soil samples were collected by Janja Vaupotic and her research team in 2006. The sampling points were divided to seven different lithological categories: clay-gravel deposits, carbonates, clastic sediments, sea and lake sediments, gravel sediments, tertiary sediments and metamorf rocks. 70 soil samples were collected, the samples came from three different regions of Slovenia: northwest, northeast and south (Figure 1). On the basis of Placer’s study in 2008 Slovenia is in the area which connects the Alps and the Dinaric mountains, and the part of the Eastern Alps, the Southern Alps, the Dinarides, the Pannonian Basin and the Adriatic-Apulia foothills. The current tectonic structure of the Slovenian region was formed during the Tertiary mountain formations after the collision of the Apulian Plate and the Eurasian Plate, on which the Apulian Plate shifted over. The main fault zones at the Northern parts of Slovenia are the Sava fault zone and the Periadriatic seam (2).

Figure 1: Location of sampling sites in Slovenia


251

Materials and methods The alpha-particle forming from the decay of radon can be detected by scintillation detectors. For measuring alpha radiation the ZnS(Ag)-scintillator is commonly used. The direct method are used of measuring radon emanation, based on measuring the emanated amount of radon (4). In this case after the sampling the soil samples are put into a 50 cm3 glass ampoule, then measured it's weight. The ampoules filled with known amount of soil (25 g) are sealed airtight, and then rest for a month to reach the equilibrium between the Ra-226 and the forming Rn-222 in it. Then the ampoule is put into a breaking chamber, it is broken, and the radon is driven into a Lucas-cell by nitrogen gas. The cell's background is measured before the driving three times. After the driving trough 3 hours of waiting is necessary, to reach equilibrium between radon and the short half-life daughter products (5). After the 3 hours of waiting time the counts are measured in the Lucas cells by two different instruments. One is an EMI photomultiplier is connected with the NP 420 single channel amplitude analyser, the other is a NDI detector from GammaTech (3).

Results and discussion According to Figure 2 it is found that the values measured using the two measuring systems are in conformation, so the NDI measuring system can replace the outdated single-channel measuring system in the future. Another advantage of the new measuring device is that its measurement accuracy and detection limit can be further improved. The emanation factor was between 0.96±0.2-61±0.7 %, the highest values were by the carbonates and by the tertiary sediments. The emanation factors show high variation, the average value was between 40-60 % (7). In Figures 3, 4, 5 the emanation factors of the samples can be seen. In the Table 1 can be seen the emanation factors of the lithological categories.

Figure 2: Radon emanation measurements with NDI and NP 420 P


252

Table 1: The emanation factors of the lithological categories Lithological categories Carbonates Tertiary sediments Clay-gravel deposits gravel sediments Clastic sediments Sea or lake sediments (1 sample)

Emanation factor (%) 1.3±0.2-60.7±0.7 1.6±0.3-45.9±1.7 1±0.2-21.3±1.3 1.2±0.3-30.6±1.2 1.5±0.4-11.4±1 1.5±0.4-11.4±1

Figure 3: The emanation factors from the south sampling area

Figure 4: The emanation factors from the northwest sampling area


253

Figure 5: The emanation factors from the northeast sampling area Conclusion In this study the radon emanation analysis of 60 Slovenian soil samples were performed using a NDI detector and a single channel amplitude analyser. Measured values may have an important role in the establishment of geogenic radiological mapping. The emanation factor was between 0.96±0.2-61±0.7 %. High emanation factors were measured by the carbonates and by the tertiary sediments. The highest emanation factor was measured in the Southern region, but in the other two regions were some high emanation factors.

References 1. A. Sakoda, Y. Nishiyama, K. Hanamoto, Y. Ishimori, Y. Yamamoto, T. Kataoka, A. Kawabe, K. Yamaoka: Differences of natural radioactivity and radon emanation fraction among constituent minerals of rock or soil. Applied Radiation and Isotopes, 68(6), 1180–1184, (2010) 2. L. Placer: Principles of the tectonic subdivision of Slovenia. Geologija, 51, 205–217, (2008) 3. A. Abbady, A. G. E. Abbady, R. Michel: Indoor radon measurement with The Lucas cell technique. Applied Radiation and Isotopes, 61(6), 1469–1475, (2004) 4. J. Somlai, V. Jobbágy, K. Somlai, J. Kovács, Cs. Németh, T. Kovács: Connection between radon emanation and some structural properities of coal-slag as building material. Radiation Measurements, 43(1), 72–76, (2008)

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5. O. Baykara, M. Doğru, M. İnceöz, E. Aksoy: Measurements of radon emanation from soil samples in triple-junction of North and East Anatolian active faults system in Turkey, Radiation Measurements, 39(2), 209–212, (2005) 6. C. Baixeras, B. Erlandsson, L. Font, G. Jönsson: Radon emanation from soil samples. Radiation Measurements, 34(1-6), 441–443, (2001) 7. P. S. Miklyaev, T. B. Petrova, V. K. Vlasov, A. M. Afinogenov, O. V. Kiryukhin, I. E. Vlasova: Influence of Clay Properties on Radon Emanation. Moscow University Chemistry Bulletin, 64(5), 314–316, (2009)

Development a Low Level Radon Measurement System Based on Pulse Shape Discriminating NDI Detector

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DEVELOPMENT A LOW LEVEL RADON MEASUREMENT SYSTEM BASED ON PULSE SHAPE DISCRIMINATING NDI DETECTOR Kovács Tibor1, Máté Borbála1, Csordás Anita2, Somlai János1 1

Institute of Radiochemistry and Radioecology, University of Pannonia, Veszprém 2 Social Organization for Radioecological Cleanliness, Veszprém

Abstract Scintillation detectors, including the ZnS(Ag) scintillator are widely used even for measuring the radon concentration of alpha-radiating isotopes found in environmental samples. During our work a new kind of coat was examined: the cell was coated from the inside with ZnS applied on a plastic sheet and the measurement parameters were determined using an NDI intelligent detector system. The single-channel analyser system was replaced by the intelligent NDI detector manufactured by Gamma Műszaki Zrt. and manual coating of ZnS(Ag) was replaced by using plastic sheets coated with ZnS(Ag) prefabricated by Eljen Technologies. This paper presents the results of the cell’s parameters’ examination. The background is lower than by the old type cells, so the detection limit, too. Similar values were obtained for the efficiency-test related to the cells of the old type. The prefabricated plastic ZnS coating is rather advantageous related to previous solutions: it is easier to handle, after being contaminated it is replaced in a simpler way, its cheaper to procure.

Introduction Scintillation detectors, including the ZnS(Ag) scintillator are widely used even for measuring the radon concentration of alpha-radiating isotopes found in environmental samples (1, 2). The replacement of the outdated single-channel analysing system having been used in the institute of radio-chemistry and radio-ecology for several decades has become relevant as the new tasks (low MDA, portability, easy usage) required the elaboration of a new measuring system. A joint objective with Gamma Műszaki Zrt. was the elaboration of a device fulfilling the above requirements (3). During the elaboration work, besides replacing the single-channel analyzer, also the revision of involving ZnS necessary in case of the contamination of ZnS(Ag) was targeted (4). During our work a new kind of coat was examined: the cell was coated from the inside with ZnS applied on a plastic sheet and the measurement parameters were determined using an NDI intelligent detector system. NDI is the innovation of Gamma Műszaki Zrt., which, in opposition with older measuring systems, includes all necessary electronic units. It does not only forward data but it analyses and separates different signals according to width and amplitude.

Kovács T., Máté B., Csordás A., Somlai J.

256

A great advantage is that it is mobile and does not require great background capacity. Furthermore, the software used for measurements is easy and simple to use.

Materials and methods Optimum detector settings The single-channel analyser system was replaced by the intelligent NDI detector manufactured by Gamma Műszaki Zrt., which is also capable of discriminating energy and signal shapes coming from the photo-multiplayer. Although, ZnS(Ag) is not energy selective, however, according to our previous experiences the background noise, light, and any beta-radiation can successfully be separated using a signal shape discriminator (5). With the measurement the optimum settings of the NDI were identified, and comparing measurements were performed for the two measurement systems (NP-420 P single-channel spectrometer and NDI). Optimum measuring system settings are as follows: high voltage: 2000 V, discriminatory level: 16, and range of amplitude: 70-511.

Involving Lucas cells In the past contaminated Lucas cells were coated with ZnS(Ag) powder manually. This procedure required great expertise and a long time. Therefore the manual coating with ZnS(Ag) has been replaced by plastic sheets coated with ZnS(Ag) prefabricated by Eljen Technologies (4).

Figure 1: Lucas cell with the new coating Determining the efficiency of Lucas cells In case of the established Lucas cells the efficiency was determined for each cell. This was done in a certified radon calibration chamber using a certified source marked Pylon model 2000A generating air with known radon concentration, so that the efficiency of the Lucas cells could be determined. Radon concentration set in the calibration chamber was verified using Genitron, Alphaguard device.


257

Detection limit, measurement accuracy, identifying linearity This measuring system is primarily used for the measurement of very small activity levels – units in mBq – and also for determining the radon and radium content of water samples. Therefore, the applicability of this method was inspected among such circumstances. With the measurement of solutions of different known Ra-226 concentration levels (45-720 mBq/180 ml) the precision, accuracy, and the linearity of the measuring system was found. 180 ml of the model solutions was poured into an emanation cell. After a waiting period of two weeks the radon gas dissolved in the water was driven out from the water sample using inert carrier gas, and it was let into a vacuumed scintillation cell through a filter system. Since ZnS is sensitive to moisture radon driven out from the water sample had to be prevented from taking moisture into the cell during blowing-through. This was provided for by inserting a calcium chloride drying tube between the emanation chamber and the Lucas-cell. Calcium chloride grains do not catch radon, but only moisture.

Results and discussion Determining the detection limit The diagram on background measurement shows that in the beginning the measured number of pulses was high and then it reduced to an almost constant value. This does not cause any problem during most of the radon measurements as in most of the cases radon measurement is performed 3 hours after letting it into the Lucas cell (after setting of the balance between radon and its progenies). The background values measured after coating the cell were rather high (20–25 pulse/1000 sec), but this value reduced to a lower level after a few days. This value increased by a negligible degree during the use, that is the contamination level was low. Comparing the coating with ZnS powder and the plastic sheets the achievable detection limit was also lower by the ZnS sheet coating. In case of manually coated Lucas cells the background was average 20-30 pulse/1000 sec, in certain cases it even reached 40 pulse/1000 sec, while in case of the new cell type the background remained under 10 pulse/1000 sec, which means a detection limit of 10-15 mBq (6). During the determination of efficiency a similar value was found related to the old type cells. The operability of the cell was inspected on a wide range of activity concentration, and after determining the efficiency a relatively constant value was found within the inspected range. The efficiency of the cells with the new coat was 47±7 %. The linearity graph shows that the calibration water sample line shows a lower measurement of 20 %. The cause for this lower measurement may be the slight level radon adsorption of the adsorber tube or the leakage in the blowing-through system.

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258

Figure 2: Background 70

Efficiency (%)

60 50 40 30 20 10 0 0

200

400

600

800

Theoretical activity (mBq)

Figure 3: Efficiency

Measured activity (mBq)

800 y = 0,7793x + 26,628 R2 = 0,9942

600 400 200 0 0

200 400 600 Theoretical activity (mBq)

800

Figure 4: Linearity The Ra-226 concentration values measured using the single-channel and the NDI are rather similar, just as in case of radon emanation.


259

Conclusion Based on the measurements performed using the NDI system it can be stated that the detection limit has greatly reduced (10-15 mBq), and also the ratio of signal and noise has improved. Optimal settings of the measuring system are the followings: high voltage: 2000 V, discrimination level: 16, and the amplitude range is: 70-511. The prefabricated plastic ZnS coating is rather advantageous related to previous solutions: it is easier to handle, after being contaminated it is replaced in a simpler way, its cheaper to procure. Concerning its parameters it has a low background (10 pulse/1000 sec), its efficiency (47 ± 7 %) is close to that of the cells of the old type (55 %).

Acknowledgement Present publication was realized with the support of the project TÁMOP-4.2.2/B-10/1-2010-0 References 1. M. Ardid, J. L. Ferrero, A. Herrero: Study of the background on a ZnS(Ag) alpha counter with a plastic veto detector. Nuclear Instruments and Methods in Physics Research A, 557, 510–515, (2006) 2. K. P. Eappen, R. N. Nair, Y. S. Mayya: Simultaneous measurement of radon and thoron using Lucas scintillation cell. Radiation Measurements, 43, 91–97, (2008) 3. www.gammatech.hu 4. www.eljentechnology.com 5. T. Kovács, E. Bodrogi, P. Dombovári, J. Somlai, Cs. Németh, A. Capote, S. Tarján: 238 U, 226Ra, 210Po concentrations of bottled mineral waters in Hungary and their committed effective dose. Radiation Protection Dosimetry, 108(2), 175–181, (2004) 6. L. Currie: Limits for qualitative detection and quantitative determination: application to radiochemistry. Analytical Chemistry, 40, 586–591, (1968)

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SZERZŐI JEGYZÉK Asztalos I. Balásházy I. Banjanac R. Bender T. Berhés I. Bossew P. Bui P. Bujtor T. Burghele B.-D. Búzás E. B. Chirca I. Cort M. De Cosma C. Csige I. Csordás A. Deák E. Dragić A. Erőss A. Farkas Á. Förhécz M. Freiler Á. Gál N. Gregorič A. Gruber V. Herke P. Horváth Á. Horváth M. Horvath Z. Ishikawa T. Jobbágy V.

111 73 49 85 85 19, 127 57 249 159 103 241 19 159 103 171, 255 85 49 219 73 111 219 233 37 19 95 31, 149, 197, 211, 219 249 159 137, 171, 227 65, 137, 163

Kardos R. Kávási N. Kis B. Kiss A. Kobal I. Kobayashi Y. Kolarž P. Kopek A. Kovács J. Kovács S. Kovács T.

249 37, 85, 137, 233 111 149 37 85 49 233 57 111 57, 65, 85, 111, 137, 163, 171, 227, 233, 241, 249, 255 Köteles Gy. 11 Krstic D. 189 Kudela G. 73 Madas B. G. 73 Markovic M. V. 117, 189 Máté B. 255 Mayya Y. S. 171 Mishra R. 171 Nagy H. É. 149, 203, 211 Nagy K. 85 Németh Cs. 227 Nikezic D. 117, 189 Omori Y. 171, 227 Pallósi T. 241 Papp B. 159 Sapra B. K. 171 Sas Z. 57, 65, 111, 163, 233, 241 Smerajec M. 37

262

Somlai J.

Stevanovic N. Szabó Cs. Szabó K. Zs. Szabó Zs. Szeiler G. Szőke I.

57, 65, 111, 163, 171, 203, 233, 241, 255 117, 189 31, 149, 197, 203, 211 31, 211 197, 203, 211 57, 65, 111, 163, 227, 233, 241 73

Tokonami S. Tollefsen T. Udovičić V. Vaupotič J. Vígh T. Völgyesi P. Yonehara H. Yoshinaga S. Zacháry D. Žunić S. Z.

171 19 49 37, 85, 137, 249 137 203 85, 137 85 211 49

VI. Magyar Radon Fórum

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