MEASUREMENT AND REPORTING OF RADON EXPOSURES.

ICRU REPORT No. 88

THE INTERNATIONAL COMMISSION ON RADIATION UNITS AND MEASUREMENTS (Published December 2015)

Journal of the ICRU Volume 12 No 2 2012 Published by Oxford University Press

Downloaded from http://jicru.oxfordjournals.org/ at City University, London on March 20, 2016

MEASUREMENT AND REPORTING OF RADON EXPOSURES


MEASUREMENT AND REPORTING OF RADON EXPOSURES Report Committee W. Hofmann (Chairman), University of Salzburg, Salzburg, Austria H.S. Arvela, Radiation and Nuclear Safety Authority – STUK, Helsinki, Finland N.H. Harley, New York University Medical Center, New York, New York, USA J.W. Marsh, Public Health England, Chilton, UK J. McLaughlin, University College of Dublin, Dublin, Ireland A. Ro¨ttger, Physikalisch-Technische Bundesanstalt (PTB), Braunschweig, Germany S. Tokonami, Hirosaki University, Hirosaki, Aomori, Japan

Z. Daraktchieva, Public Health England, Chilton, UK Xi. Detao, University of South China, Heugyang, China ICRU Sponsors E. Fantuzzi, ENEA, Istituto di Radioprotezione, Bologna, Italy H.-G. Menzel, Euorpean Organization for Nuclear Reserach (CERN), Geneva, Switzerland H.-G. Paretzke, Helmholtz Zentrum Mu¨nchen, German Research Center for Enviornmental Health, Neuherberg, Germany


Consultants


Journal of the ICRU Vol 12 No 2 (2012) Report 88 Oxford University Press

doi:10.1093/jicru/ndv019

The International Commission on Radiation Units and Measurements Introduction

(1) quantities and units of ionizing radiation and radioactivity, (2) procedures suitable for the measurement and application of these quantities in clinical radiology and radiobiology, and (3) physical data needed in the application of these procedures, the use of which tends to assure uniformity in reporting. The Commission also considers and makes similar types of recommendations for the radiation protection field. In this connection, its work is performed in cooperation with the International Commission on Radiological Protection (ICRP). Policy ICRU endeavors to collect and evaluate the latest data and information pertinent to the problems of radiation measurement and dosimetry and to recommend the most acceptable numerical values for physical reference data and techniques for current use. The Commission’s recommendations are kept under continual review in order to keep abreast of the rapidly expanding uses of radiation. The ICRU feels that it is the responsibility of national organizations to introduce their own detailed technical procedures for the development and maintenance of standards. However, it urges that all countries adhere as closely as possible to the internationally recommended basic concepts of radiation quantities and units. The Commission maintains and develops a system of quantities and units and concepts (e.g., for radiation therapy) and guidance for measurement procedures and techniques having the widest possible

Current Program The Commission recognizes its obligation to provide guidance and recommendations in the areas of radiation therapy, radiation protection, and the compilation of data important to these fields, and to scientific research and industrial applications of radiation. Increasingly, the Commission is focusing on the problems of protection of the patient and evaluation of image quality in diagnostic radiology and radiation oncology. These activities do not diminish the ICRU’s commitment to the provision of a rigorously defined set of quantities and units useful in a very broad range of scientific endeavors. The Commission is currently engaged in the formulation of ICRU Reports treating the following subjects: Bioeffect Modeling and Biologically Equivalent Dose Concepts in Radiation Therapy Key Data for Measurement Standards in the Dosimetry of Ionizing Radiation Monitoring and Assessment of Radiation Releases to the Environment Operational Radiation Protection Quantities for External Radiation Prescribing, Recording, and Reporting Brachytherapy Cancer of the Cervix Prescribing, Recording, and Reporting Ion-Beam Therapy Prescribing, Recording, and Reporting Stereotactic Treatments with Small Photo Beams Retrospective Assessment of Individual Doses for Acture Exposures to Ionizing Radiation

# Crown copyright 2015. Reproduced with the permission of the Controller of Her Majesty’s Stationery Office/Queen’s Printer for Scotland and Public Health England.


The International Commission on Radiation Units and Measurements (ICRU), since its inception in 1925, has had as its principal objective the development of internationally acceptable recommendations regarding:

range of applicability. Situations can arise from time to time for which an expedient solution of a current problem is required. The ICRU invites and welcomes constructive comments and suggestions regarding its recommendations and reports. These may be transmitted to the Chairman.

THE INTERNATIONAL COMMISSION ON RADIATION UNITS AND MEASUREMENTS

Small-Field Photon Dosimetry and Applications in Radiotherapy The Commission continually reviews progress in radiation science with the aim of identifying areas in which the development of guidance and recommendations can make an important contribution. The ICRU’s Relationship with Other Organizations

Bureau International des Poids et Mesures European Commission International Council for Science International Electrotechnical Commission International Labour Office International Organization for Medical Physics

The Commission has found its relationship with all of these organizations fruitful and of substantial benefit to the ICRU program. Operating Funds Financial support has been received from the following organizations: American Association of Physicists in Medicine Belgian Nuclear Research Centre Canadian Nuclear Safety Commission Federal Office Public Health, Switzerland Helmholtz Zentrum Mu¨nchen Hitachi, Ltd. International Radiation Protection Association International Society of Radiology Ion Beam Applications, S.A. Japanese Society of Radiological Technology MDS Nordion Nederlandse Vereniging voor Radiologie Philips Medical Systems, Incorporated Radiological Society of North America Siemens Medical Solutions U.S. Environmental Protection Agency U.S. Nuclear Regulatory Commission Varian Medical Systems In addition to the direct monetary support provided by these organizations, many organizations provide indirect support for the Commission’s program. This support is provided in many forms, including, among others, subsidies for (1) the time of individuals participating in ICRU activities, (2) travel costs involved in ICRU meetings, and (3) meeting facilities and services. In recognition of the fact that its work is made possible by the generous support provided by all of the organizations supporting its program, the Commission expresses its deep appreciation. Hans-Georg Menzel Chairman, ICRU Geneva, Switzerland


In addition to its close relationship with the ICRP, the ICRU has developed relationships with national and international agencies and organizations. In these relationships, the ICRU is looked to for primary guidance in matters relating to quantities, units, and measurements for ionizing radiation, and their applications in the radiological sciences. In 1960, through a special liaison agreement, the ICRU entered into consultative status with the International Atomic Energy Agency (IAEA). The Commission has a formal relationship with the United Nations Scientific Committee on the Effects of Atomic Radiation (UNSCEAR), whereby ICRU observers are invited to attend annual UNSCEAR meetings. The Commission and the International Organization for Standardization (ISO) informally exchange notifications of meetings, and the ICRU is formally designated for liaison with two of the ISO technical committees ICRU is a member of Consultative Committee for Units (CCU) – BIPM and Consultative Committee for Ionizing Radiation (CCRI(I) – BIPM and Observer to CCRI(II) and CCRI (III). ICRU also enjoys a strong relationship with its sister organization, the National Council on Radiation Protection and Measurements (NCRP). In essence, ICRU and NCRP were founded concurrently by the same individuals. Presently, this longstanding relationship is formally acknowledged by a special liaison agreement. ICRU also exchanges reports with the following organizations:

International Radiation Protection Association International Union of Pure and Applied Physics United Nations Educational, Scientific and Cultural Organization



Measurement and Reporting of Radon Exposures

1

Glossary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

3

Abstract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

17

Executive Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

19

1.

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

21

1.1 1.2 1.3 1.4 1.5

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21 22 23 23 24

2.

Health Effects of Radon Exposure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

25

3.

Radon and Radon Progeny Inhalation and Resultant Doses . . . . . . . . . . . . . . . . . . . . . . . . .

29

3.1 3.2

29 30 30 31 32 32 32 33 34 35 36 37 39 39 40 41 43 43

3.3

3.4 3.5 3.6

3.7 3.8

3.9

Indoor Radon . . . . . . . . . . . . Outdoor Radon . . . . . . . . . . . Thoron . . . . . . . . . . . . . . . . . . Protection Against Radon . Aim of the Present Report

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Lung Dose Assessment Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Radon versus Radon Progeny Doses. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2.1 Lung Doses due to Inhalation of Radon Gas and Thoron Gas . . . . . . . . . . . . . . . 3.2.2 Lung Doses due to Inhalation of Short-lived Radon Progeny . . . . . . . . . . . . . . . 3.2.3 Lung Doses due to Inhaled Thoron Progeny. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Lung Doses versus Other Organ Doses. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3.1 Doses to Internal Organs Arising from Inhalation of Radon Progeny . . . . . . . . 3.3.2 Doses to Internal Organs Arising from Inhalation of Radon Gas . . . . . . . . . . . . 3.3.3 Skin Dose from Deposited Radon Progeny . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3.4 Ingestion of Radon in Water. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Sensitive Target Cells in Bronchial Epithelium . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Personal and Environmental Parameters Affecting Lung Dosimetry . . . . . . . . . . . . . . Dependence of Doses on Physical Activities (Breathing Parameters) and Age . . . . . . 3.6.1 Dependence on Physical Activities. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.6.2 Dependence on Age . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Dependence on 222Rn Progeny Absorption Parameters . . . . . . . . . . . . . . . . . . . . . . . . . . Dependence on Radon Progeny Related Aerosol Parameters . . . . . . . . . . . . . . . . . . . . . 3.8.1 Radon Progeny Aerosol Parameters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.8.2 Sensitivity of Lung Dose from Inhalation of 222Rn Progeny to Aerosol Parameter Values . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Variability and Uncertainty of Individual Lung Doses . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.9.1 Comparison of Different Lung Dosimetry Models . . . . . . . . . . . . . . . . . . . . . . . . . 3.9.2 Intra- and Intersubject Variability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .


45 46 46 49


Preface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .


3.9.3

Inhomogeneity of Surface Activities and Resulting Doses within Bronchial Airways . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.9.4 Comparison of Bronchial Doses between Non-smokers and Smokers . . . . . . . 3.9.5 Contribution of Sensitive Target Cells in Bronchial Epithelium to Lung Cancer Risk. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.10 Human versus Experimental Animal Doses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.10.1 Animal Inhalation Experiments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.10.2 Animal Dosimetry Models. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.

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50 51 51 51

Characteristics and Behavior of Radon and Radon Progeny . . . . . . . . . . . . . . . . . . . . . . . . .

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4.1 4.2 4.3

55 56 57

Radon Sources . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Radon Decay Schemes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Behavior of Radon and Radon Progeny in Indoor Environments . . . . . . . . . . . . . . . . . 4.3.1 Steady-state Activity Concentrations of Radon and Thoron Gases in Indoor Air . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3.2 Steady-state Activity Concentrations of Radon Progeny in Indoor Air . . . . . . . 4.3.3 Radon Progeny Parameters Affecting Lung Dosimetry . . . . . . . . . . . . . . . . . . . . 4.4 Airborne Radon Activity Concentrations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.4.1 Radon in Homes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.4.2 Radon in Workplaces . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.4.3 Comparison of Radon in Homes and Indoor Workplaces . . . . . . . . . . . . . . . . . . . 4.4.4 Thoron in Homes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.5 Equilibrium Factor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.6 Attached and Unattached Fractions. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.6.1 Unattached Fraction, fp, for Radon (222Rn) Progeny . . . . . . . . . . . . . . . . . . . . . . 4.6.2 Correlation between Equilibrium Factor, F, and Unattached Fraction, fp, for 222Rn . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.6.3 Unattached Fraction, fp, for Thoron (220Rn) Progeny . . . . . . . . . . . . . . . . . . . . . . 4.7 Aerosol Size Distributions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.

58 59 60 60 60 61 63 64 64 66 66 67 68 68

Principles of Radon and Radon Progeny Detection Systems and Measurements . . . . . . . .

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5.1

71 71 71 73 73 74 75 75 78 81

5.2

5.3

5.4

Radon and Radon Progeny Metrology and Quality Assurance of Measurements . . . . 5.1.1 General Aspects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.1.2 Comparisons of Radon Measurements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Radon Gas (222Rn, 220Rn) in the Environment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.2.1 Radon Measurement Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.2.1.1 Airborne Radon . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.2.1.2 Waterborne Radon . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.2.1.3 Soilborne Radon . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.2.2 Radon Detection Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.2.3 Thoron Measurements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Radon and Thoron Progeny Activity Concentrations and Particles Size Distributions in the Environment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.3.1 Radon and Thoron Progeny . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.3.2 Radon Progeny Measurement Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.3.3 Measurement of the Unattached Fraction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.3.4 Radon Progeny Particle Size Distributions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.3.4.1 Number Size Distribution Measurements . . . . . . . . . . . . . . . . . . . . . . . . 5.3.4.2 Direct Activity Size Distribution Measurements . . . . . . . . . . . . . . . . . . Retrospective Measurements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.4.1 Surface Traps . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.4.2 Volume Traps . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.4.3 In-vivo Measurements of 210Pb. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

82 82 83 85 86 86 86 90 91 92 93


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Contents

5.5

Personal Monitoring for Radon and Radon Progeny . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.5.1 Personal Monitoring for Radon . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.5.2 Personal Monitoring for Radon Progeny. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

93 93 94

6 Strategies for Radon and Radon Progeny Measurements and Surveys . . . . . . . . . . . . . . . . .

95

6.1 6.2 6.3

106 107 108 110 111 111

Interpretation of Measurements. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

113

7.1

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113 113 113 115 116 116 117 118 119 120 121 122 123 123 123

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6.4

6.5 6.6

7.

7.2 7.3

7.4

Variations of Areal and Local Radon Activity Concentrations . . . . . . . . . . . . . . . . . . . 7.1.1 Worldwide Variation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.1.2 Spatial Variation within a House . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Diurnal and Seasonal Variations of Radon Activity Concentrations . . . . . . . . . . . . . . Physical Processes Affecting Indoor Radon Activity Concentrations . . . . . . . . . . . . . 7.3.1 Pressure Difference and Air Exchange . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.3.2 Radon Entry from Soil and Building Materials . . . . . . . . . . . . . . . . . . . . . . . . . . 7.3.3 Effect of Wind on Radon Entry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.3.4 Comparison of Driving Forces. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.3.5 Seasonal Correction Factors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.3.6 Atypical Seasonal Variations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.3.7 Long-term Variation in Annual Average Radon Activity Concentrations . . . . Thoron Interference on Radon Detection Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.4.1 Time Integrating Devices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.4.2 Continuous Devices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.4.3 Mathematical Analysis of Radon/Thoron Atmospheres using Nuclear Track Detectors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

95 96 97 97 98 98 98 98 99 99 99 101 101 101 101 102 102 103 103 104 104 104 105


Objectives: Areal and Individual Measurements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Radon versus Radon Progeny Measurements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Areal Surveys and Mapping . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.3.1 Goals of Radon Surveys . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.3.2 Sampling and Survey Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.3.2.1 Random Sample Surveys . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.3.2.2 Stratified Sampling. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.3.2.3 Choice of the Strategy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.3.2.4 Period of Measurement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.3.2.5 Detector Choice and Deployment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.3.2.6 Examples of Survey Practices. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.3.3 Use of Volunteer Data and Large Radon Mapping Data . . . . . . . . . . . . . . . . . . . . 6.3.4 Radon Maps. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.3.4.1 Geological Maps . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.3.4.2 Aerial Gamma Radioactivity Maps . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.3.4.3 Radon in Soil Gas Maps . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.3.4.4 Indoor Radon Maps . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.3.4.5 Combined Maps . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.3.5 Lognormal Modeling of Indoor Radon Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.3.6 Mapping the Proportion of Dwellings above Reference Level. . . . . . . . . . . . . . . Long-term versus Short-term Areal Measurements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.4.1 Integrating versus Time-resolved Measurements . . . . . . . . . . . . . . . . . . . . . . . . . . 6.4.2 Predicting the Annual Average Using Short-term Measurements . . . . . . . . . . . 6.4.3 Predicting the Past Thirty Years of Radon Exposure from Annual Radon Levels . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.4.4 Using Short-term Measurements to Make Action Decisions . . . . . . . . . . . . . . . . Homes and Workplaces . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Individual Exposure Assessment: Time-resolved Measurements . . . . . . . . . . . . . . . . . . 6.6.1 Comparison of Areal and Personal Exposure Assessment at Workplaces . . . . . 6.6.2 Comparison of Integral and Time-resolved Personal Measurements . . . . . . . . .


7.5

. . . .

125 125 127 132

Variabilities and Uncertainties of Radon and Radon Progeny Exposures and Dosimetry

135

8.1

135 135 135

7.6 8.

8.2

8.4

8.5

8.6 9.

. . . .

.. .. .. ..

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.1.1 The Meaning of Uncertainty in Metrology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.1.2 Variability of Long-term Average Radon Gas Exposures . . . . . . . . . . . . . . . . . . . 8.1.3 Classification of Uncertainties in Exposure Assessment for Epidemiological Studies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Uncertainty Evaluations: from the Realization of the Unit to the Field Measurement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.2.1 Radon Gas Activity Concentration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.2.1.1 Rn-220 Calibration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.2.1.2 Rn-222 Calibration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.2.1.3 Determination of an Average Activity Concentration in a Room . . . . . 8.2.2 Radon and Thoron Gas Exposures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.2.2.1 Non-direct Reading Devices: Rn-220 Exposure Calibration . . . . . . . . . 8.2.2.2 Non-direct Reading Devices: Rn-222 Exposure Calibration . . . . . . . . . Other Sources of Uncertainties in Assessment of the Annual Average Radon Activity Concentration. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.3.1 Uncertainties due to Spatial Variation of Indoor Radon Activity Concentration in Dwellings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.3.2 Uncertainties in Extrapolating a Short-term Measurement to an Annual Average. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.3.3 Uncertainties due to Long-term Variation in Annual Average Radon Activity Concentration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.3.4 Combined Uncertainty in the Estimation of Long-term Average Radon Activity Concentration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.3.5 Uncertainties Associated with the Estimate of Individual Exposure Obtained with Areal Measurements. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Uncertainties of Radon Progeny Measurements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.4.1 Measurand and Derived Quantities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.4.2 An Example for the Determination of Derived Quantities . . . . . . . . . . . . . . . . . Uncertainties of Dosimetric Results. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.5.1 Application of Different Dosimetric Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.5.2 Uncertainties of Model Parameter Values Used in Dose Calculations . . . . . . . 8.5.2.1 Sensitive Target Cells . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.5.2.2 Radon Progeny Size Distributions. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.5.2.3 Apportionment Factors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.5.2.4 Radiation Weighting Factor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.5.3 Intersubject Variability. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.5.4 Summary of Uncertainties of Dose Calculations . . . . . . . . . . . . . . . . . . . . . . . . . . Effect of these Uncertainties on the Analysis of Epidemiological Studies . . . . . . . . . .

137 137 138 138 138 139 141 141 141 143 143 143 143 144 144 144 145 145 147 147 147 147 148 148 148 148 149 149

Recommendations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

151

9.1 9.2 9.3 9.4

151 152 155 155

Good Practice Recommendations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Recommendations Regarding Measurement Strategies . . . . . . . . . . . . . . . . . Recommendations Regarding Measurement Techniques . . . . . . . . . . . . . . . . . Recommendations Regarding Recording and Reporting of Measurements .

.. .. .. ..

.. .. .. ..

. . . .

.. .. .. ..

. . . .


8.3

Variation of Aerosol Parameter Values for Radon Progeny . . . . . . . . . . . . . . . . . . 7.5.1 Equilibrium Factor, F, and Unattached Fraction, fp, for 222Rn . . . . . . . . . . 7.5.2 Particle Size Distributions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Estimation of Missing Exposure Data and Uncertainties Involved . . . . . . . . . . . .

Contents

Appendices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

157

Appendix A (Section 5) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

157

Appendix B (Section 7) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

161

Appendix C (Section 8) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

165

References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

169





Preface control of exposure. These reports recommend the use of action or reference values as operational radiation protection tools which have been implemented within national regulatory frameworks. In 2010, ICRP published a report (115) on Lung Cancer Risk from Radon and Progeny which reviewed epidemiological studies on residential and occupational exposures. One important conclusion of this report was that the nominal risk coefficient for exposure to radon should be taken to be twice that previously assumed. As a consequence, reference values, in terms of radon activity concentration in air, Bq m23, were lowered proportionally in many countries in accordance with recommendations by international organizations. The public interest in and concern for radon exposure increased substantially and the need for reliable, reproducible radon measurement procedures and techniques became more obvious. The objective of this report is, therefore, to provide conceptual and practical guidance for radon measurements in air and in water. The recommendations include guidance for the choice of strategies for radon and radon progeny measurements and surveys and for interpreting and reporting measurement results, appropriate for the goal of the measurements. The report also addresses methods to determine and reduce uncertainties associated with these measurements and resulting dosimetric estimates. It describes the state-of-the-art of radon measurement techniques which is expected to be of relevance in view of the reduced reference levels in dwellings and in the workplace as well as for epidemiological studies. The recommendations in this report are aimed at authorities planning radon surveys, at experts performing measurements and at scientists involved in epidemiological studies on lung cancer risk due to radon inhalation.



One of the principal objectives of the International Commission on Radiation Units and Measurements (ICRU) is to provide recommendations and guidance on performing and reporting radiation measurements. This Report on Measurements and Reporting of Radon Exposures presents the most recent recommendations for measurements in the field of radiation protection. Earlier ICRU publications on radiation protection measurements include Report 20 (1971), Radiation Protection Instrumentation and its Application, Report 53 (1994), Gamma-ray Spectrometry in the Environment, Report 56 (1997), Dosimetry for External Beta Rays for Radiation Protection, Report 69 (2003), Direct Determination of Body Content of Radionuclides and Report 75 (2006), Sampling for Radionuclides in the Environment. Epidemiological studies have demonstrated that inhalation of radon and its short-lived decay products can cause lung cancer. Increased lung cancer incidence in workers in uranium and other mines has been known since the nineteenth century but it was only in the middle of the last century that inhalation of radon and its progeny was recognized as the cause. The influence of radon on lung cancer risk to the general public was established even more recently. A large number of studies on radon activity concentrations in dwellings and mines worldwide were published in the second half of last century and the United Nations Scientific Committee on the Effects of Atomic Radiation (UNSCEAR) summarized the results in several reports. There has also been an increase in epidemiological studies on lung cancer incidence related to radon exposures in dwellings. The International Commission on Radiological Protection (ICRP) has addressed the issue of radiation protection against radon exposure and published a number of reports providing recommendations and guidance for the assessment and




Glossary: Definitions, Quantities, and Units

Absorbed Dose Absorbed dose, D, is defined as the quotient of d1, by dm, where d1 is the mean energy imparted by ionizing radiation, to matter of mass dm thus D¼

d1 : dm

The unit of absorbed dose is J kg2l. The special name for the unit of absorbed dose is gray (Gy). Absorbed Dose to Radon Exposure Conversion Coefficient The absorbed dose to radon exposure conversion coefficient defines the relationship between the absorbed dose to an organ/tissue or region and the exposure to inhaled short-lived radon progeny. The exposure can be expressed in terms of potential alpha energy exposure (Jm23 h) or exposure to radon (Bq m23 h) with a given equilibrium factor F. Note: There are published data in Gy WLM21 unit. Although the WLM is a not an SI unit, it is still used for the characterization of the radon progeny exposure, particularly to understand historical publications. Activity Number dN of spontaneous nuclear transitions or nuclear disintegrations of a radionuclide of amount N produced during a short time interval dt. A¼

dN : dt

The unit of activity is Bq. # Crown copyright 2015. Reproduced with the permission of the Controller of Her Majesty’s Stationery Office/Queen’s Printer for Scotland and Public Health England.


In contrast to other radiation measurements, the metrology of radon involves several rather sophisticated definitions, quantities, and units. Since these are rather uncommon, this glossary gives an overview about these special terms used in international standards and recommendations, technical descriptions, and scientific papers. General terms of statistics, metrology, and physics are not part of this glossary. The following definitions, quantities, and units are used in agreement with ICRU 85a, ICRP 103 (definition given in Annex B of ICRP 103, not from the glossary), ICRP 32, IEC 61577, and ISO 11665. In the special case that the definitions given in the above documents are not totally consistent or have need of further specification, e.g., modernization, this ICRU report aims to attempt to do so. The quantities describing the movement of air from the environment toward buildings are used in compliance with ISO 9972 and EN 13829:2000. Several more quantities, terms, or definitions are taken from ISO Nuclear Energy Vocabulary (Parts 1 and 2), the IAEA Glossary, the IEC’s International Electrotechnical Vocabulary (IEC 60050), the BIPMs International Vocabulary of Metrology, and also the ISO 17025. Nuclear data are taken from Monographie BIPM-5, while fundamental constants are based on CODATA evaluations. Note: The symbol Rn is used in the following text to refer to both, 222Rn and 220Rn. If a special isotope is named, it is done by purpose and the definition is only valid in this configuration.


Activity Concentration Activity A per unit volume V of the respective isotope. C¼

A V

Relevant activity concentrations can be marked by an index, for example, Cdeep is used as radon activity concentration in deep soil air. The unit of activity concentration is Bq m23. Activity Median Diameter (AMD) The activity median diameter AMD is the median of the activity distribution of diameters of unit density (kg m23) spheres. The unit of activity median diameter is m.

The activity median aerodynamic diameter AMAD is the median of the activity distribution of diameters of unit density (kg m23) spheres that have the same terminal settling velocity in air as the aerosol particle of interest. Activity Median Thermodynamic Diameter AMTD The activity median thermodynamic diameter AMTD is the median of the activity distribution of diameters of spherical particles that have the same diffusion coefficient in air as the aerosol particle of interest. Activity Size Distribution The activity size distribution of short-lived radon progeny represents the differential distribution of the fractions of attached or unattached activity concentrations as a function of thermodynamic or aerodynamic particle diameter. Aerodynamic Diameter See activity median aerodynamic diameter. Aerosol A suspension of solid or liquid particles in a gaseous medium. Airborne particles can have a wide range of sizes; typically from 0.5 nm to 10 mm. Note: The particle size of unattached radon progeny is of the order of magnitude of nm. If there is need for a more precise definition, then this report proposes 5 nm diameter as the upper limit for the unattached progeny (i.e., cluster carrying progeny). Aerosol Particle Size Distribution The aerosol particle size distribution is defined as a function corresponding to several partial concentrations (number of particles of a defined range of diameter per unit volume of air). The unit of the distribution is m23. Air Change Rate at Reference Pressure Air leakage rate per internal volume at the reference pressure difference across the building envelope. The unit of air change rate is h21. Note: The reference pressure is usually 50 Pa. It is abbreviated as n50 or ACH50. Air Leakage Rate The air leakage rate is the air flow rate across the building envelope. The unit of air leakage rate m3 h21. Note: This movement includes flow through joints, cracks, and porous surfaces, or a combination thereof, induced by the air-moving equipment specified in the standard ISO 9972. 4


Activity Median Aerodynamic Diameter (AMAD)

Glossary

Apportionment Factors To take account of potential differences in radiation sensitivity between regions of the lung, the equivalent dose to the bronchial, bronchiolar, and the alveolar regions are weighted by apportionment factors, which represent their relative contribution to the total radiation detriment of the lung. Attached Fraction

Attachment Rate The attachment rate X expresses the adsorption velocity of the unattached radon progeny to the atmospheric aerosol: X¼bZ where b is the attachment coefficient (m3 s21), and Z the aerosol number concentration (m23). The unit of attachment rate is s21. Breathing Frequency The breathing frequency is the number of breaths per unit time. The unit of breathing frequency is s21. Breathing Rate The breathing rate is the volume of air inhaled to the lung per unit time i.e., tidal volume multiplied by respiratory frequency. The unit of breathing rate is m3 s21. Calibration Is an operation that, under specified conditions, in a first step, establishes a relation between the quantity values associated with measurement uncertainties provided by measurement standards and corresponding indications with associated measurement uncertainties and, in a second step, uses this information to establish a relation for obtaining a measurement result from an indication. Note 1: A calibration may be expressed by a statement, calibration function, calibration diagram, calibration curve, or calibration table. In some cases, it may consist of an additive or multiplicative correction of the indication with associated measurement uncertainty. Note 2: Calibration should not be confused with adjustment of a measuring system, often mistakenly called “self-calibration,” nor with verification of calibration. Coarse mode Aerosol particles that are larger than 2 mm in diameter Confounder The presence of another independent variable associated with an exposure that accounts wholly or partially for the disease. 5


The fraction of the potential alpha energy concentration of short-lived radon progeny that is attached to the ambient aerosol particles. Note 1: The attached progeny may have a tri-modal activity size distribution, which can be approximated by a combination of three lognormal distributions (Porstendo¨rfer, 2001). These consist of the nucleation mode with AMD values between 10 and 100 nm, the accumulation mode with AMD values of 100 –450 nm, and a coarse mode with an AMD . 1 mm. Generally, the greatest fraction of the potential alpha energy (PAE) is in the accumulation mode. Note 2: If there is need for a more precise definition of attached progeny, then this report proposes 5 nm diameter as the lower limit for the attached progeny (i.e., aerosols carrying progeny). Note 3: The sum of attached and unattached fractions is equal to 1.


Deposition Velocity The deposition velocity, vg, is defined as: vg ¼

wðdÞ Zðz; dÞ

where w(d) is the number of particles with diameter d deposited per unit surface area and time and Z(z,d) is the concentration of particles with diameter d at height z above a surface. Note that the deposition velocity has the dimension of a velocity, but is not a velocity in a physical sense. Effect Modifier A variable that differentially ( positively or negatively) modifies the observed effect of a risk factor on disease status. The effect of the factor may be different for different groups.

The effective dose, E, is defined by a weighted sum of tissue equivalent doses, wTHT, as: X X X E¼ w T HT ¼ wT wR DT;R T

T

R

where wT is the tissue weighting factor for tissue T with

P

wT ¼ 1 and wR is the radiation weighting factor

T

(see definition) and DT,R is the mean absorbed dose from radiation type R in tissue T. The sum is performed over all organs and tissues of the human body considered to be sensitive to the induction of stochastic effects. The wT values are chosen to represent the contributions of individual organs and tissues to the overall radiation detriment from stochastic effects. The unit of effective dose is J kg21. The special name for the unit of effective dose is sievert (Sv). Note: The unit is the same for equivalent dose and effective dose as well as for some operational quantities. Care must be taken to ensure that the quantity being used is clearly stated. Effective Dose to Radon Exposure Conversion Coefficient The conversion coefficient gives the effective dose due to inhaled short-lived radon progeny. The exposure can be expressed in terms of potential alpha energy exposure (J m23 h) or exposure to radon activity concentration (Bq m23 h) with a given equilibrium factor F. The unit of effective dose to radon exposure conversion coefficient is Sv (J m23 h)21 or Sv (Bq m23 h)21. Note: there are published data in Sv WLM21 unit. Although the WLM is a not an SI unit, it is still used for the characterization of the radon progeny exposure, particularly to understand historical publications. Effective Leakage Area (ELA) ELA was developed by Lawrence Berkeley Laboratory (LBL) and is used in their infiltration model. The effective leakage area is defined as the area of a special nozzle-shaped hole (similar to the inlet of a Blower Door fan) that would leak the same amount of air as the building does at a pressure difference of 4 Pa. The unit of effective leakage is m2. Note 1: Once the leakage rate for the building has been measured, it can be used to estimate the cumulative size of all leaks or holes in the building’s air barrier. The estimated leakage areas not only provide a way to visualize the physical size of the measured holes in the building, but they are also used in infiltration models to estimate the building’s natural air change rate (i.e., the air change rate under natural weather conditions). Note 2: Equivalent leakage area (EqLA): EqLA is defined by Canadian researchers at the Canadian National Research Council as the area of a sharp-edged orifice (a sharp round hole cut in a thin plate) that would leak the same amount of air as the building does at a pressure difference of 10 Pa. The EqLA is used in the AIM infiltration model. Emanation Coefficient The emanation coefficient is defined as the fraction of radon atoms released into a rock or soil pore space from a radium-bearing grain. 6


Effective Dose

Glossary

Equilibrium Equivalent Activity Concentration The activity concentration of radon, CRn, in radioactive equilibrium with its short-lived decay products that has the same potential alpha energy concentration Cp as the non-equilibrium mixture to which the Ceq refers: Ceq;Rn-222 ¼ kPo-218 CðPo-218Þ þ kPb-214 CðPb-214Þ þ kBi-214 CðBi-214Þ þ kPo-214 CðPo-214Þ Ceq;Rn-220 ¼ kPo-216 CðPo-216Þ þ kPb-212 CðPb-212Þ þ kBi-212 CðBi-212Þ þ kPo-212 CðPo-212Þ: The weighting coefficients k are calculated by nuclear data and given in Table 1. Table 1. Coefficients for the calculation of the equilibrium equivalent concentration from measured activity concentrations of radon progeny u(kPo-218) 0.002 u(kPo-216) 0.223 1026

kPb-214 0.513 kPb-212 0.9133

u(kPb-214) 0.010 u(kPb-212) 0.0001

kBi-214 0.381 kBi-212 0.0866

u(kBi-214) 0.009 u(kBi-212) 0.0001

kPo-214 5.2 1028 kPo-212 8.05 10212

u(kPo-214) 1 1029 u(kPo-212) 6 10214

Since kPo-214 ,, 1, kPo-216 ,, 1, and kPo-212 ,, 1, the corresponding activity concentration can be omitted. Ceq;Rn-222 ¼ kPo-218 CðPo-218Þ þ kPb-214 CðPb-214Þ þ kBi-214 CðBi-214Þ Ceq;Rn-220 ¼ kPb-212 CðPb-212Þ þ kBi-212 CðBi-212Þ: The unit of equilibrium equivalent activity concentration is Bq m23. Note 1: For Rn-222, the following conversion is valid: Ceq ¼ Cp/[5.57(10) 1029 J Bq21] or Ceq ¼ Cp/ [3.47(7) 1010 eV Bq21] . Note 2: For Rn-220, the following conversion is valid: Ceq ¼ Cp / [7.565(8) 1028 J/Bq] or Ceq ¼ Cp/ [4.722(5) 1011 eV Bq21]. Equilibrium Factor The equilibrium factor is the ratio of equilibrium equivalent activity concentration Ceq and the radon activity concentration CRn. F¼

Ceq CRn

Note: In the case of 220Rn, the relatively long half-life of 212Pb may lead to cases where 220Rn completely disappears before 212Pb grows in; in this case, the quantity is not defined. Equivalent Dose The equivalent dose to an organ or tissue, HT, is defined by X HT ¼ wR DT;R R

where DT,R is the mean absorbed dose from radiation type R to tissue T, and wR is the radiation weighting factor for radiation R. The sum is performed over all types of radiations involved. The unit of equivalent dose is J kg21. The special name for the unit of equivalent dose is sievert (Sv). Note 1: The unit Sv is the same for equivalent dose and effective dose as well as for some operational dose quantities. Care must be taken to ensure that the quantity being used is clearly stated. Note 2: Values of equivalent dose to a specified tissue from any type(s) of radiation can be compared directly. Equivalent Dose to Radon Exposure Conversion Coefficient This conversion coefficient is the equivalent dose to an organ per unit exposure to radon progeny. The exposure can be expressed in terms of potential alpha energy exposure (J m23 h) or exposure to radon activity concentration (Bq m23 h) with a given equilibrium factor F. The unit of equivalent dose to radon exposure conversion coefficient is Sv (J m23 h)21 or Sv (Bq m23 h)21. 7


kPo-218 0.106 kPo-216 6.684 1026


Note: There are published data in Sv WLM21 unit. Although the WLM is not an SI unit it is still used for the characterization of the radon progeny exposure, particularly to understand the historical publications. Exposure to Radon The time-integral of the activity concentration during a defined period of time. PRn ðC; DtÞ ¼

ð

CRn dt

Dt

The unit of exposure to radon is Bq m23 h. Exposure to Radon Progeny

Friction Velocity The friction velocity is defined as the square root of the ratio of wall shear stress to the fluid density. Functional Residual Capacity The functional residual capacity is the air volume of the lung at the end of normal expiration. The unit of functional residual capacity is m3. Internal Volume Heated, cooled, or mechanically ventilated space within a building or part of a building subject to the measurement, generally not including the attic space, basement space, and attached structures. The unit of internal volume is m23. International System of Units (SI) System of units, based on the International System of Quantities, their names, and symbols, including a series of prefixes and their names and symbols, together with rules for their use, adopted by the General Conference on Weights and Measures (CGPM). K-factor The ratio of the equivalent dose to the lung per unit potential alpha energy exposure in homes for a given population group to that for a miner exposed in mines. Mean Absorbed Dose The mean absorbed dose in the region of an organ or tissue T, DT, is defined by Ð T ¼ T D

Dðx; y; zÞ rðx; y; zÞ dV Ð rðx; y; zÞdV T

where V is the volume of the tissue region T, D the absorbed dose at a point (x, y, z) in that region, and r the mass T , is usually written DT. The density at this point. In practice, the mean absorbed dose in an organ or tissue T; D 21 unit of mean absorbed dose is J kg . The special name for the unit of mean absorbed dose is gray (Gy). Note: When using the quantity absorbed dose in practical radiation protection applications, doses are averaged over tissue volumes. It is assumed that, for low doses, the mean value of absorbed dose averaged over a specific organ or tissue can be correlated with radiation detriment for stochastic effects in that tissue with an accuracy sufficient for the purposes of radiological protection. The averaging of absorbed doses in tissues or organs and the summing of weighted mean doses in different organs and tissues of the human body comprise the basis for the definition of the protection quantities which are used for limiting stochastic effects at low 8


See “Potential alpha energy exposure. ”

Glossary

doses. This approach is based on the Linear-No-Threshold (LNT) model and therefore allows the addition of doses resulting from external and internal exposure. Measurement A measurement is a process of experimentally obtaining one or more quantity values that can reasonably be attributed to a quantity. Note 1: Measurement implies comparison of quantities or counting of entities. Note 2: Measurement presupposes a description of the quantity commensurate with the intended use of a measurement result, a measurement procedure, and a calibrated measuring system operating according to the specified measurement procedure, including the measurement conditions. Measurand

Measurement Error The error of measurement is the measured quantity value minus a reference quantity value. Note 1: The concept of “measurement error” can be used both (a) when there is a single reference quantity value, which occurs if a calibration is made by means of a measurement standard with a measured quantity value having a negligible measurement uncertainty or if a conventional quantity value is given, in which case the measurement error is known, and (b) if a measurand is supposed to be represented by a unique true quantity value or a set of true quantity values of negligible range, in which case the measurement error is not known. Note 2: Measurement error should not be confused with production error or mistake. Measurement Result The result of a measurement is a set of quantity values being attributed to a measurand together with any other available relevant information. Note 1: A measurement result generally contains “relevant information” about the set of quantity values, such that some may be more representative of the measurand than others. This may be expressed in the form of a probability density function (PDF). Note 2: A measurement result is generally expressed as a single measured quantity value and a measurement uncertainty. Measurement Traceability The property of a measurement result whereby the result can be related to a reference through a documented unbroken chain of calibrations, each contributing to the measurement uncertainty. Metrology Metrology is the science of measurement and its application. Note: Metrology includes all theoretical and practical aspects of measurement in any field of application. Potential Alpha Energy (PAE) The potential alpha energy, 1p, is the total alpha energy emitted during the decay of a progeny atom along the decay chain up to 210Pb or 208Pb, respectively, for the decay chains of the 222Rn and 220Rn. The potential alpha energy 1p (X2A) of a progeny is calculated by the following equations according to the decay chains of 222Rn and 220Rn. The values for the transition probability p as well as the uncertainties assigned to the nuclear data are taken from the Monographie-5 of BIPM and the conversion from eV to J is by the data of CODATA (Tables 2 and 3). 222

Rn:

1p (Po-218) ¼ Sipi1i (Po-218) þ Skpk1k (Po-214), 1p (Pb-214) ¼ Skpk1k (Po-214), 9


The particular quantity that is subject to the measurement.

u(1p) (Po-218) 0.6 keV 0.00009 10212 J

1p (Po-218) 13688.9 keV 2.19321 10212 J

1p (Pb-214) 7687.9 keV 1.23174 10212 J

Potential alpha-energy u(1p) (Pb-214) 0.5 keV 0.00008 10212 J

Standard uncertainty (k ¼1)


u(1p) (Po-216) 5.1 keV 0.00081 10212 J

1p (Po-216) 14 582.7 keV 2.33641 10212 J

1p (Pb-212) 7804.2 keV 1.25036 10212 J

Potential alpha-energy u(1p) (Pb-212) 5.1 keV 0.00081 10212 J


1p (Bi-212) 7804.2 keV 1.25036 10212 J

Potential alpha-energy

1p (Bi-214) 7687.9 keV 1.23174 10212 J


u(1p) (Bi-212) 5.1 keV 0.00081 10212 J


u(1p) (Bi-214) 0.5 keV 0.00008 10212 J



10


Table 3. Potential alpha energy per atom for 220Rn progeny including standard uncertainty



Table 2. Potential alpha energy per atom for 222Rn progeny including standard uncertainty

Standard uncertainty (k ¼1) u(1p) (Po-212) 4.4 keV 0.00071 10212 Jh

1p (Po-212) 8785.2 keV 1.40754 10212 J

u(1p) (Po-214) 0.5 keV 0.00008 10212 J



1p (Po-214) 7686.7 keV 1.23155 10212 J



Glossary

1p (Bi-214) ¼ Skpk 1k (Po-214), 1p (Po-214) ¼ Skpk1k (Po-214). 220

Rn: (including the branching of the decay of 212Bi, pS ¼ Skpk):

1p (Po-216) ¼ Sipi1i (Po-216) þ Skpk1k (Bi-212) þ (12 pS) ffi Smpm1m (Po-212), 1p (Pb-212) ¼ Skpk1k (Bi-212) þ (12pS) ffi Smpm1m (Po-212), 1p (Bi-212) ¼ Skpk 1k (Bi-212) þ (12 pS) ffi Smpm1m (Po-212), 1p (Po-212) ¼ Skpk1k(Bi-212). The potential alpha energy is a quantity for characterizing radon progeny atmospheres, not radon atmospheres. The index refers to the radon isotope and the decay chain. Since 1p(Pb-214) ¼ 1p(Bi-214) 1p(Po-214) and 1p(Pb-212) ¼ 1p(Bi-212), the equations are rather simple:

where N is the number of the respective atoms. Since the value is not directly connected with a measurand, in contrast to the potential alpha energy concentration, it should be used for theoretical work (modeling and simulation) only. The unit of potential alpha energy is J. Potential Alpha Energy Concentration (PAEC) The concentration of any mixture of short-lived radon decay products in air in terms of the alpha energy released during complete decay through Pb-210 for Rn-222 progeny or through Pb-208 for Rn-220 progeny. Since 1p(Pb-214) ¼ 1p(Bi-214)1p(Po-214) and 1p(Pb-212) ¼ 1p(Bi-212), the equations are rather simple: CðPo-218Þ CðPb-214Þ CðBi-214Þ CðPo-214Þ 1p ðPb-214Þ Cp;Rn-222 ¼ 1p ðPo-218Þ þ þ þ lPo-218 lPb-214 lBi-214 lPo-214 Cp;Rn-220

CðPo-216Þ CðPb-212Þ CðBi-212Þ CðPo-212Þ 1p ðPb-212Þ þ ¼ 1p ðPo-216Þ þ þ 1p ðPo-212Þ lPo-216 lPb-214 lBi-214 lPo-212

The unit of potential alpha energy concentration is J m23. Note: Due to the short half-lives of 216Po and 212Po, these isotopes are in activity equilibrium with their parent nuclide: C (Rn-220) ¼ C (Po-216) and C (Bi-212) (1 2 pS) ¼ C (Po-212) with the transition probabilities pk for the a-decays of 212Bi resulting to pS ¼ Skpk, where C is the measurand, that is the activity concentration of the respective progeny. Potential Alpha Energy Exposure The time integral of the potential alpha energy concentration in air Cp over a given time period Dt. ð PðCp;Rn ; DtÞ ¼ Cp;Rn ðtÞ dt Dt

The unit of potential alpha energy exposure is J m23 h. Pressure and Pressure Difference Pressure p and pressure difference Dp from a reference pr. The unit of pressure and pressure difference is Pascal (Pa). Progeny The term progeny includes the whole set of short-lived decay products of a specified radon decay chain. A particular isotope is indicated by its chemical symbol followed by its mass number. The term progeny of 222 Rn refers to 218Po, 214Pb, 212Bi, and 214Po, while the term progeny of 220Rn refers to 216Po, 212Pb, 212Bi, 212 Po, and 212Tl. 11


1p,Rn-222 ¼ 1p(Po-218) NPo-218 þ1p (Pb-214) (NPb-214 þ NBi-214 þ NPo-214) 1p,Rn-220 ¼ 1p(Po-216) NPo-216 þ1p(Pb-212) (NPb-212 þ NBi-212) þ1p(Po-212) NPo-212.


Radiation Weighting Factor A factor by which the organ or tissue absorbed dose is multiplied to reflect the higher biological effectiveness of high-LET radiations compared with low-LET radiations. It is used to derive the equivalent dose from the absorbed dose averaged over a tissue or organ. See also Equivalent dose and Effective dose in this glossary. The radiation weighting factors represent consensus values of the maximum RBE values for a given radiation for radiation protection purposes and do not represent true RBE values. Radon Concentration The radon concentration, cRn,is defined as the amount of a constituent nRn divided by the volume of the mixture V cRn ¼

nRn V

Radon Entry Rate The radon entry rate is the radon activity entering the house per unit time. The flow rate of soil gas entering a house is caused by a combination of different processes (diffusion, exhalation, or convection). The radon entry rate covers all of these processes. The unit of radon entry rate is Bq s21. Radon Leakage Area (RLA) Leakage area for flow of radon, that is analogous to the effective leakage area used for building envelope air leakage. The unit of radon leakage area is m2. Reference Level A national reference level for radon represents the maximum accepted radon activity concentration in a residential dwelling and is an important component of a national program. For homes with radon activity concentrations above these levels, remedial actions may be recommended or required. When setting a reference level, various national factors such as the distribution of radon, the number of existing homes with high radon activity concentrations, the arithmetic mean indoor radon level, and the prevalence of smoking should be taken into consideration. Relative Biological Effectiveness (RBE) The ratio of a dose of a low-LET reference radiation to a dose of the radiation under consideration, that gives an identical biological effect. RBE values vary with dose, dose rate, and biological endpoint considered. In radiological protection, the maximum RBE for stochastic effects at low doses (RBEM) is of particular interest. Note: Radiation weighting is based mainly on an evaluation of the relative biological effectiveness (RBE) of the different radiations with respect to stochastic effects. The RBE is used in radiobiology for characterizing the different biological effectiveness of radiations. RBE values are given as the ratio of the absorbed doses of two types of radiation producing the same specified biological effect in identical irradiation conditions (dose value of a reference radiation divided by the corresponding dose value of the considered radiation which causes the same level of effect). RBE values for a specific radiation depend upon the conditions of exposure including the biological effect investigated, the tissue or cell type involved, the dose and the dose rate, and the dose fractionation scheme; therefore, for a given type and energy of radiation, there will be a range of RBE values. The RBEs reach maximum values (RBEM) at low doses and low dose rates. RBEM is therefore of particular interest for defining radiation weighting factors for use in radiological protection. The weighting factors are taken to be independent of the dose and dose rate in the low-dose region. Risk Risk relates to the probability or chance that an outcome, e.g., lung cancer, will occur. 12


The unit of radon concentration is mol m23. Note: Radon concentration is often used instead of radon activity concentration. This can cause confusion and should be avoided.

Glossary

† Excess absolute risk An expression of risk based on the assumption that the excess risk from radiation exposure adds to the underlying (baseline) risk by an increment dependent on dose but independent of the underlying natural or background risk. The lifetime excess absolute risk is the risk cumulated by an individual up to a given age (typically 90 years). † Relative risk The ratio of the incidence rate or the mortality rate from the disease of interest, e.g., lung cancer, in an exposed population to that in an unexposed population. The excess relative risk is defined as the relative risk minus 1. † Detriment-adjusted risk The probability of the occurrence of a stochastic effect, modified to allow for the different components of the detriment in order to express the severity of the consequences.

A multiplying factor applied to a measurement with duration of one or more months in order to derive a meaningful annual average radon activity concentration. Shape Factor The aerodynamic shape factor is a dimensionless constant used to relate the drag force experienced by an irregularly shaped particle moving in air relative to the particle’s equivalent volume diameter. Temperature and Temperature Difference Absolute temperature T and temperature difference DT (here: indoor2outdoor difference). The unit of temperature and temperature difference is K. Thermodynamic Diameter See activity median thermodynamic diameter. Tidal Volume The tidal volume is the air volume inhaled in a single breath for any given physical activity. The unit of tidal volume is m3. Tissue Weighting Factor This is a factor wT by which the equivalent dose to a tissue or organ is weighted to represent the relative contributions of that tissue or organ to the total radiation detriment from stochastic effects resulting from uniform irradiation of the body. It is defined such that: X wT ¼ 1 T

Total Lung Capacity The total lung capacity is the air volume of the lung at the maximum inspiratory level. The unit of total lung capacity is m3. Type A Evaluation of Measurement Uncertainty Type A evaluation of a component of measurement uncertainty is carried out by a statistical analysis of measured quantity values obtained under defined measurement conditions. 13


Seasonal Correction Factor


Type B Evaluation of Measurement Uncertainty Type B evaluation of a component of measurement uncertainty is determined by means other than a Type A evaluation of measurement uncertainty. Unattached Fraction A fraction of progeny may not become attached to airborne particles and this quantity is often referred to as the free or unattached fraction. The unattached fraction is defined as the fraction of the potential alpha energy concentration of short-lived radon progeny that is not attached to the ambient aerosol. Note 1: The particle size concerned is of the order of magnitude of nanometer. If there is need for a more precise definition of unattached progeny, then this report proposes 5 nm diameter as an upper limit for the unattached progeny (i.e., clusters carrying progeny). Note 2: The sum of attached and unattached fraction is equal to 1.

The uncertainty budget of a measurement uncertainty is the statement of the components of that measurement uncertainty, and of their calculation and combination. Note: An uncertainty budget should include the measurement model, estimates, and measurement uncertainties associated with the quantities in the measurement model, covariances, type of applied probability density functions, degrees of freedom, type of evaluation of measurement uncertainty, and any coverage factor. Uncertainty of Measurement A parameter associated with the result of a measurement that characterizes the dispersion of the values that could reasonably be attributed to the measurand. Note 1: The parameter may be, for example, a standard deviation (or a given multiple of it), or the half-width of an interval having a stated level of confidence. Note 2: Uncertainty of measurement comprises, in general, many components. Some of these components may be evaluated from the statistical distribution of the results of series of measurements and can be characterized by experimental standard deviations. The other components, which can also be characterized by standard deviations, are evaluated from assumed probability distributions based on experience or other information. Note 3: It is understood that the result of the measurement is the best estimate of the value of the measurand and that all components of uncertainty, including those arising from systematic effects such as components associated with corrections and reference standards, contribute to the dispersion. Volume Flow Rate The volume flow rate is a quantity equal to the infinitesimal volume dV of a substance crossing a given surface during a time interval with infinitesimal duration dt, divided by this duration, thus qV ¼

dV dt

The unit of volume flow rate is m3 s21. Note: In the special case of the volume flow rate of the lung, this quantity is the tidal volume divided by the inhalation time. Volume Referred volume of the respective calculation or measurement. The unit of volume is m23. Working Level (WL) Working level is a historical unit of potential alpha energy concentration. 1 WL ¼ 20.8 mJ m23. Note 1: Although the WL is not an SI unit, it is still used for the characterization of the radon progeny activity concentration, particularly to understand the historical publications. 14


Uncertainty Budget

Glossary

Note 2: 1 WL was originally defined as the concentration of potential alpha energy associated with the radon progeny in equilibrium with 100 pCi l21 (3700 Bq l21). However, in ICRP Publication 65, it was redefined as: Any combination of short-lived progeny of radon in 1 l of air that will result in the emission of 1.30 105 MeV of potential alpha energy (both definitions are identical within a few percent).

Working Level Month (WLM) Working Level Month is a historical unit of potential alpha energy exposure. 1 WLM ¼ 3.54 mJ h m23. It corresponds to the cumulative exposure from breathing an atmosphere at a concentration of 1 WL for a working month of 170 h. Note: The WLM is not an SI unit, but it is important to understand the historical publications (see Working Level). Downloaded from http://jicru.oxfordjournals.org/ at City University, London on March 20, 2016

15


Abstract


Lung cancer risk caused by the inhalation of radon (222Rn) and its short-lived progeny is related to lung dose, which cannot be directly measured. The only measurable parameters which allow the determination of lung doses are the radon and radon progeny activity concentrations and related size distributions. Although lung cancers are caused by the inhaled short-lived radon progeny and not by the radon gas, it is the radon gas which is commonly measured and not its progeny. Since radon gas measurements are much easier to carry out, require less expensive equipment and are especially suited for long-term measurements, the report focuses on the measurement of the radon gas for specific exposure conditions in homes and workplaces. The first objective of this report is to provide information on how to measure radon, covering measurement techniques of radon in air and water, currently available detection systems, and measurement strategies most appropriate for the desired goal of a measurement campaign. Critical measurement strategy decisions are the selection of the measured radionuclide (i.e., radon gas or radon progeny and related size distributions), choice of the measurement period (i.e., short-term or long-term measurements), the choice of detector and its deployment, the type of measurement (i.e., areal or personal measurements), the survey strategy (i.e., integral or time-resolved measurements), or the strategy to accomplish the specific goal of a survey (i.e., measurements describing the current status or retrospective measurements). The choice of a specific strategy depends on the purpose of the survey, and differs therefore between the demands of a nation-wide indoor radon survey or an epidemiological study. The second objective of this report is how to interpret and report the results of these measurements, the associated uncertainties, and the resulting dosimetric estimates. Care should be taken when reporting and interpreting radon measurements because measured radon activity concentrations exhibit significant spatial variations (i.e., local and areal), and temporal variations (i.e., diurnal, seasonal, and annual). Consequently, estimates of the average annual radon activity concentrations are typically used for radon surveys and are compared with reference levels for radiation protection purposes. Other factors that may affect the interpretation of radon measurement results and the related dose estimates include thoron (220Rn) interference on radon detection systems, variations of aerosol parameters, equilibrium factor, duration of exposure (i.e., occupancy times in a building or location) and breathing rates. Often encountered problems are the uncertainties in extrapolating short-term measurements carried out at different locations within a building, or at different times during a year or in different years to statistically reasonable average values. Finally, the third objective of this report is to provide recommendations on optimal measurement strategies, measurement techniques, recording and reporting of measurements for different measurement objectives, such as individual exposure, average population exposure in a region or country, epidemiological studies or compliance with reference levels in radiation protection.




Executive Summary inhalation of radon and its progeny, most notably lung cancer risk, are briefly discussed in Section 2. Since lung cancer risk is related to the dose delivered by alpha particles to sensitive target cells of the bronchial epithelium, Section 3 is devoted to dosimetric aspects of radon and radon progeny inhalation, focusing on lung dosimetry in order to establish relationships between lung doses and radon and radon progeny measurements. Although radiation doses in lung tissue cannot be measured, lung doses are related to radon and radon progeny exposure parameters in terms of dose per unit exposure, e.g., in mSv (Bq h m23)21 for radon measurements or in mSv WLM21 (Working Level Month) for radon progeny measurements. To assess lung cancer risk for specific exposure conditions in homes and workplaces, we have to measure the relevant radon exposure parameters, such as radon activity concentrations, radon progeny activity concentrations, and related size distributions. Thus, the radiological and aerosol characteristics of radon and its progeny and their behavior in indoor environments are described in detail in Section 4, thereby providing the necessary information as to which exposure parameters have to be measured to characterize the exposure conditions. After having identified the relevant exposure parameters, currently available detection devices and measurement techniques to measure these parameters are presented in Section 5. These include experimental detection systems that provide measurements of radon gas in air and water, radon progeny activity concentrations, and activity size distributions. The measurement techniques for personal monitoring of radon and its progeny are also discussed as well as retrospective measurements and personal monitoring for radon and its progeny for risk assessment purposes, e.g., in epidemiological studies. Before starting a measurement campaign, it is imperative to select a measurement strategy, which is appropriate for the desired aim of the campaign. Different measurement strategies for radon and radon progeny measurements are compared and evaluated in Section 6, comprising sampling strategies, detector



There are several isotopes of radon, but the most important ones from a radiation protection perspective are 222Rn (historical name: radon) and 220Rn (historical name: thoron). Since radon activity concentrations in homes are much higher than those of thoron in most locations, this report focuses on recommendations regarding measurements and reporting of inhaled 222Rn gas and its short-lived progeny. Lung cancers are caused by the inhaled short-lived radon progeny and not by the radon gas. However, radon gas measurements are much easier to carry out, require less expensive equipment, and are especially suited for long-term measurements. Thus, it is the radon gas that is commonly measured and not the short-lived radon progeny. Using a typical value of the equilibrium factor F appropriate to specific exposure conditions, measured radon activity concentrations can be used to estimate the contribution of radon progeny to lung dose. It is not possible, however, using measured radon activity concentrations to obtain information on unattached fractions and size distributions of radon progeny. However, despite these limitations, radon gas can be regarded as a reasonable surrogate for radon progeny for typical radon progeny exposure conditions. The objectives of this report are to provide guidance to organizations planning a measurement campaign and to individuals conducting such a survey of how to measure radon and its short-lived progeny, how to report the results of these measurements, and what are the uncertainties associated with these measurements. To accomplish this goal and to provide relevant information on radon and radon progeny behavior in homes, workplaces, and outdoors, the report is subdivided into nine sections, supplemented by three appendices, each addressing a specific issue related to radon and radon progeny measurements and their statistical interpretations. Section 1 sets the stage for the objectives of this report, providing basic information on radon levels typically encountered in dwellings and outdoors and discussing reference levels for the protection of the population against radon. To understand why it is necessary to measure radon levels in homes and workplaces, potential health effects caused by the


dosimetry-related uncertainties affect the analysis of epidemiological studies. Based on the previous sections, the final Section 9 provides recommendations on measurement strategies, measurement techniques and reporting of measurements for different measurement objectives, such as individual exposure, average population exposure in a region or country, epidemiological studies, or compliance with reference levels in radiation protection. For the benefit of the reader, the concepts of metrology and quality assurance relevant for radon and radon progeny measurements as well as examples for the analyses of uncertainties in the calibration by a primary radon activity standard and in interlaboratory comparisons are summarized in Appendix A (related to Section 5). To give practical advice for the analysis of measurement results, two detailed examples are given in Appendices B (related to Section 7) and C (related to Section 8). Appendix B describes a method to analyze the results of the nuclear track detector exposure at the Physikalisch-Technische Bundesanstalt (PTB) in Braunschweig, Germany, considering the crosssensitivity to radon and thoron and the determination of the associated decision threshold and the detection limit. A measurement method using solidstate nuclear track detectors, calibrated in the PTB radon reference chamber, for the determination of a calibration coefficient and how the information derived can be used in field measurements is described in Appendix C.

20


deployment, time of measurement, short-term or longterm measurements, and areal or individual measurements. The choice of a specific strategy depends on the purpose of the survey, and differs therefore between the demands of a nation-wide indoor radon survey or an epidemiological study. In general, measured radon activity concentrations exhibit significant spatial variations (i.e., local and areal) and temporal variations (i.e., diurnal, seasonal, and annual). Therefore, great care should be taken when interpreting radon and radon progeny measurements. The interpretation of results of radon and radon progeny measurements, discussed in Section 7, must consider the effects of spatial and temporal variations, thoron (220Rn) interference on radon detection systems, variations of aerosol parameter values, equilibrium factor, duration of exposure (i.e., occupancy times in building), and individual breathing rates. The variabilities and uncertainties of radon and radon progeny exposures and methods to derive meaningful average values from these measurements are further explored in Section 8. Often encountered problems are the uncertainties in extrapolating shortterm measurements carried out at different locations within a house, or at different times during a year or in different years to statistically reasonable average values. In addition to these measurement uncertainties, there are also uncertainties in dosimetric results based on these measurements, such as the application of different dosimetry models and the uncertainties in model parameter values. Both measurement and



1. Introduction

1.1

Indoor Radon

Uranium and thorium occur naturally in soil and rocks and provide a continuous source of radon.

Typically, uranium is present at concentrations of between 1 and 3 parts per million ( ppm) in most rocks and soils. The uranium content of a soil will be similar to the uranium content of the rock from which it was derived. Ra-226, which is the immediate parent of radon, is a decay product of uranium (Section 4.1). In general, the higher the uranium content and the gas permeability of a soil, the greater the radon activity concentration in soil gas and the probability that houses built on such soil will have high levels of indoor radon. The radon produced by the decay of radium in the soil subjacent to a house is usually the main source of indoor radon. Soil gas containing radon may enter a house by pressure-driven flow through the foundations. This is because the air in a house is generally warmer and at a lower pressure than the subjacent soil gas (Ma¨kelaïnen et al., 2001). In soil gas, radon activity concentrations typically range from less than 10 000 up to 100 000 Bq m23. Less than 1% of the indoor air in a house usually originates in the soil; the remainder coming from outdoor air, which is generally quite low in radon activity concentration. Houses with poorly sealed foundations, built on high permeability ground and with several entry points for soil gas, may draw more than 10% of their indoor air from the soil. Thus, even if the soil gas has only moderate levels of radon, the activity concentration of radon inside such houses may be relatively high. The radon exhaled from building materials in most cases does not significantly contribute to indoor radon levels. The radium content of building materials will be similar to the rock or clay from which they are made, which is generally low. However, some building materials which may have high concentrations of radium: alum shale concrete and building materials made of volcanic tuff, by-product phosphogypsum, and some industrial waste materials are examples of such materials (Keller et al., 2001). An increment to indoor radon levels might also come from water supplies. Surface reservoir water supplies and rivers usually contain very little radon. But groundwater may contain high activity concentrations of radon depending on the uranium/radium content of the aquifer formation. Public water works



Why is radon such an important issue? First of all, epidemiological studies have demonstrated that inhalation of radon and its short-lived progeny can cause lung cancer, i.e., radon is a potent carcinogen. Secondly, radon is a ubiquitous natural radionuclide which can be found everywhere in the world, i.e., everybody in a population is exposed to radon and not only a selected group, such as smokers, in the case of lung cancer, or more general, radiation workers. In recent years, several reports related to radon have been published, addressing primarily health effects aspects, particularly lung cancer risk (EPA, 2003; ICRP, 2010; NA/NRC, 1991; 1999a; WHO, 2009). It is not the intention of this report to duplicate these extensive reports, but rather to focus on issues not specifically addressed there, such as the optimal planning of measurements, their experimental realization and final reporting, and the uncertainties associated with such measurements and resulting dosimetric estimates. Although it does not deal with the risk aspect of radon inhalation, the issues addressed in this report do have the potential for improving such risk estimates. There are numerous isotopes of radon (Firestone and Shirley, 1999), but the most important ones for radiation protection are 222Rn (historical name: radon) and 220Rn (historical name: thoron). However, since radon activity concentrations in homes are much higher than those of thoron in most locations, with the exception of thorium-rich areas, this report focuses on recommendations regarding measurements and reporting of inhaled radon gas and its short-lived progeny. The comparison between radon and radon progeny doses in the bronchial region of the lung indicates that radon progeny doses are about two orders of magnitude higher than corresponding radon doses. This clearly illustrates that the dose to the lungs and hence the resulting lung cancer risk arises mainly from the inhalation of the short-lived progeny.


radon levels in the water, and industrial buildings with specific work practices and ventilation conditions. More information on radon in workplaces will be given in Section 4.4.2.

1.2

Outdoor Radon

Land masses are the main sources of outdoor radon, while sea waters, having very low radium concentrations, can be considered as radon sinks. Consequently, outdoor air radon levels are much lower (about 0.1 Bq m23) over oceans and seas than over a continental land mass such as mainland Europe (Chevillard et al., 2002). National data on average outdoor radon levels are quite limited. Averages appear to lie between 5 and 20 Bq m23 (UNSCEAR, 2008). The ratio of the radon activity concentration in outdoor air to the mean indoor radon activity concentration in European countries would appear to be in the range of about 7% (Czech Republic) to 20% (UK). In the USA, EPA has conducted measurements of outdoor radon in all 50 states. This survey and other state measurements were summarized in NA/NRC (1999b). A mean for the USA from 437 measurements is 14.8 + 5.3 Bq m23. Radon levels in outdoor air are determined mainly by the soil characteristics (uranium/radium content, porosity, and the consequent radon exhalation rate), local topology, and meteorological conditions. In some conditions, such as atmospheric temperature inversions in valleys with high radon fluxes from the

Figure 1.1. Mean indoor activity concentrations from 222Rn surveys in 50 countries (UNSCEAR, 2008).

22


using groundwater and private domestic wells often have closed systems with short transit times that do not remove radon from the water or permit it to decay. The radon is out-gassed from the water to the indoor air when the water is used for washing, cooking, and other purposes in a house. The areas where groundwater radon is most likely to make a significant contribution to indoor air are areas that have high levels of uranium in the underlying rocks. Radon activity concentrations as high as several thousand Bq l21 have been found in water from drilled wells in regions with granite rock or other uraniferous rocks and soils (NA/NRC, 1999b; UNSCEAR, 2008). A summary of all published data concluded that the contribution of radon in domestic water supplies to indoor air radon is about 1 Bq m23, if water with 10 000 Bq m23 of radon is being used in a house (NA/NRC, 1999b). The distribution of indoor radon gas levels in dwellings in many countries has been determined both by national surveys and in other investigations. Figure 1.1 illustrates the significant variability of measured mean indoor radon activity concentrations among 50 countries around the world (UNSCEAR, 2008), ranging from only a few Bq m23 in Cyprus to about 140 Bq m23 in the Czech Republic. Indoor workplaces include, for example, schools, hospitals, post offices, jails, shops, cinemas, office buildings, and common workshops. The primary workplaces where radon may cause health problems are underground mines, in particular uranium mines, waterworks in the case of sufficiently high

Introduction

1.3

Thoron

There are many isotopes of radon most of which have very short (,1 s) half-lives (Firestone and Shirley, 1999). As a consequence of these short halflives, very little of these isotopes can migrate from their source to contribute to the activity in indoor air. Apart from 222Rn, the only other radon isotope that can occur indoors in significant amounts is 220 Rn, commonly referred to as thoron. It is a member of the 232Th decay series and its immediate parent is 224Ra (Section 4.1). There has been an increasing interest in indoor thoron and its progeny in recent years. Due to its short half-life, thoron in the soil gas beneath a building cannot survive long enough, in most situations, to enter a building and thereby contribute significantly to the level of thoron in indoor air. Indoor thoron is generally due to the exhalation of thoron from thorium that may be present in the materials of the internal surfaces of the building. There are some building materials, such as volcanic tuff in Italy, that have been found to have a high rate of thoron exhalation (Nuccetelli and Bochicchio, 1998). While, in general, indoor thoron levels are low, uncommon situations have been identified in recent years, such as cave dwellings in China, where airborne thoron progeny concentrations can contribute significantly to radiation doses received by the occupants. In some cases, they have been found to exceed those from the radon (222Rn) progeny in the same location (Tokonami et al., 2004).

1.4

Protection against Radon

ICRP’s protection policy against radon is based on setting reference levels and applying the principle of optimization to reduce exposures as low as reasonably achievable. For indoor radon, the reference 23


level is expressed as an average annual radon activity concentration and represents a level where action would almost certainly be warranted to reduce exposure. In its 2007 recommendations, ICRP recommended an upper reference level of 600 Bq m23 for dwellings and 1500 Bq m23 for workplaces (ICRP, 2007). However, as ICRP now recommends a nominal risk coefficient for radon which is twice the previous value, the upper reference level for dwellings has been reduced to 300 Bq m23 (ICRP, 2010). It is the responsibility of national authorities to establish their own national reference levels, taking into account the prevailing economic and societal circumstances and specific local exposure conditions in their country. For dwellings, the World Health Organization (WHO) recommends a national reference level of 100 Bq m23, but states that if this cannot be implemented under the prevailing country-specific conditions, then the chosen value should not exceed 300 Bq m23 (WHO, 2009). This is consistent with ICRP’s recommendations (ICRP, 2010). A survey of 36 countries carried out by WHO found that almost all countries have reference levels between 200 and 400 Bq m23 for existing housing. Some countries have different reference levels for new and existing buildings with lower values for new houses (WHO, 2009). For comparison, the US Environmental Protection Agency (EPA) (EPA, 2003) proposes a desired action level of 74 Bq m23 (or 2 pCi l21) and recommends mitigation if the radon activity concentration exceeds 148 Bq m23 (or 4 pCi l21). In its Statement on Radon (ICRP, 2010), the Commission also recommended a level of 1000 Bq m23 as an entry point for applying occupational radiological protection requirements in existing exposure situations, replacing the 1500 Bq m23 upper reference level for workplaces. In its recent publication on “Radiological Protection against Radon Exposure” (ICRP, 2014), the Commission retains the upper reference level value of 300 Bq m23 for dwellings and recommends the same value of 300 Bq m23 for all mixed-use buildings (i.e., with access for both members of the public and workers) and workplaces. This includes, for example, schools, hospitals, post offices, jails, shops, cinemas, office buildings and common workshops. A specific graded approach is recommended by ICRP (2014) for workplaces: in workplaces where exposure to radon is not considered as occupational, the first step is to reduce the activity concentration of radon as low as reasonably achievable below the same reference level as set for dwellings. If difficulties are met in the first step, a more realistic approach is recommended as a second step, consisting

soil, short-term, elevated outdoor radon levels have been observed. Although high outdoor radon levels are rare, they could however be of local health significance in communities in areas such as former uranium mining districts where elevated radon exhalation from tailing ponds combined with meteorological and topological conditions could give rise to high outdoor radon levels of seasonal duration. A direct proportionality in risk between indoor and outdoor radon exposures based simply on the radon activity concentration should not, however, be assumed. This is because factors that influence lung dose such as the equilibrium factor between radon and its progeny and also aerosol characteristics can differ considerably between indoors and outdoors.


1.5

Aim of the Present Report

It is important to note that lung cancers are caused by the inhaled short-lived radon progeny and not by the radon gas. Thus, it is necessary to determine levels of the short-lived radon progeny. However, what is routinely measured is the radon gas and not its progeny. This raises the question: is radon gas an appropriate surrogate for short-lived radon progeny? As will be discussed in his report, radon gas measurements are much easier to carry out, require less expensive equipment, and are especially suited for long-term measurements. Lung cancer risk caused by the inhalation of radon and its short-lived progeny is related to lung dose, which cannot be measured in humans. What can be measured, however, are radon and radon progeny activity concentrations and related size distributions, which then serve as input data for dose calculations. Thus, the aim of this report is to advise: † how to measure radon and its progeny, † how to report the results of these measurements appropriate for the goal of a measurement, and † how to determine and reduce the uncertainties associated with these measurements and resulting dosimetric estimates The first objective is to give advice (i) to authorities planning radon surveys on measurement strategies and types of measurements required for a radon measurement program or an epidemiological study (Section 6), and (ii) to the personnel actually carrying out such measurement programs on the type of measurements that should be carried out to characterize radon and radon progeny exposures, such as aerosol size distributions and potential alpha energy (PAE) exposures in homes and workplaces (Sections 5 and 7). Both comprise measurements required for a radon measurement program to check that radon levels are below the reference levels both at home and in the workplace, measurements required for dose assessment, particularly if radon levels are close to reference levels, and measurements required for epidemiological studies to be related to lung cancer risk. The second objective is to analyze all potential uncertainties involved in the determination of radon exposures and related bronchial doses since the uncertainties associated with the exposure or dose axis of the exposure (dose) –effect relationship will affect the validity of any chosen reference level (Section 8). Finally, the third objective is to provide recommendations on (i) the proper measurement and complete recording of the results of measurements of radon, thoron, and their progeny, and (ii) on the correct reporting of these measurements (Section 9). 24


of optimizing protection using the actual parameters of the exposure situation, such as occupancy, together with a reference level of 10 mSv annual dose. If despite all reasonable efforts, individual doses remain above 10 mSv, then the workers are considered as occupationally exposed and the relevant requirements for occupational exposure would apply. However, for some workplaces, such as underground miners, national authorities may consider from the outset that workers’ exposure to radon is occupational. Occupational Health and Safety is a priority now in both developed and developing countries. Radon activity concentrations are increasingly monitored at workplaces and mitigation actions are implemented when required. Radon reference levels in homes suggested at the national and international level are based on epidemiologically obtained lung cancer data. Both lung cancer risk at low exposure levels as well as related radon activity concentrations are subject to significant statistical uncertainties. Thus, the question arises whether the recommended reference levels can be justified on statistical grounds. In other words, how accurate are the exposure (or dose) – effect relationships upon which these reference levels are based. First of all, the effect of radon exposures on lung cancer risk at low radon exposures is blurred by the presence of many confounding factors and effect modifiers which may act in a synergistic or antagonistic fashion. Secondly, the reconstruction of the past exposure history in epidemiological studies is extremely difficult as it is commonly based on a small number of measurements. Due to a latency period for bronchial tumors of about 5 years, the determination of statistically significant average radon concentrations over a period of many years is affected by local and temporal variations. In addition, all radon measurement devices are subject to statistical errors, due to instrumental errors or incorrect calibration. Since bronchial tumors are produced by inhaled radon progeny and not by the radon gas, uncertainties exist about the conversion of radon activity concentrations to radon progeny activity concentrations, as well as about the aerosol size distributions to which inhaled radon progeny are attached. Furthermore, different lung dosimetry models produce a range of doses in sensitive target cells for the same exposure conditions (Section 3.8.1). Finally, uncertainties of individual doses per unit exposure to radon and its progeny are caused by inherent inter-subject variability of lung parameters and related breathing patterns. Although the statistical errors associated with current lung cancer risk estimates at low radon exposures are also quite significant, these uncertainties are not considered in this report.



2. Health Effects of Radon Exposure In the joint analysis of underground miners described in the BEIR VI report (NA/NRC, 1999a), 6 out of the 11 cohorts had some smoking information. The analysis of these data showed that the relative risk (RR) of lung cancer with cumulative exposure to radon was linear for lifelong non-smokers and for current and ex-smokers. Assuming a RR model, the excess relative risk (ERR) per unit increase in radon exposure was higher among lifelong non-smokers compared with current and ex-smokers, although the confidence intervals overlapped. This suggests sub-multiplicative interaction between radon and smoking in causing lung cancer (i.e., less than the product of the individual risks from the two agents but more than the sum of the risks). However, the absolute risk of lung cancer per unit increase in radon exposure is much greater in smokers than in nonsmokers as smokers have much higher rates of lung cancer than non-smokers in the absence of radon exposure. Recently, a joint analysis of European epidemiological studies on uranium miners with smoking information was carried out (Hunter et al., 2013; Leuraud et al., 2011). As expected, the carcinogenic effect of radon exposure was confirmed even after adjustment for smoking. The results from analyzing the joint effects of radon and smoking indicated a sub-multiplicative interaction; the ERR WLM21 was greater for non-smokers compared with current or ex-smokers, although there was no statistically significant variation in the ERR WLM21 associated with smoking status. This is in agreement with the BEIR VI analyses (NA/ NRC, 1999a) and with the results from an updated analysis of the Colorado Plateau miner cohort (Schubauer-Berigan et al., 2009). In contrast, a recent nested case –control study of Czech uranium miners indicated that the combined effect from radon and smoking was closer to an additive than to a multiplicative interaction (Toma´sˇek, 2013). This was shown only when a modifying effect of time since exposure was used. If the interaction is additive as opposed to multiplicative then this would lead to higher estimates of lifetime risks for the nonsmoking population.



Radon has long been identified as a cause of lung cancer at higher activity concentrations and it was recognized as a human lung carcinogen by the National Institute for Occupational Safety and Health (NIOSH, 1971), the World Health Organization (WHO, 1986; 2009), and by the National Research Council (NA/NRC, 1999a). The main source of information on risks of radon-induced lung cancer has been epidemiological studies of underground miners (ICRP, 1993a), and more recent studies have provided informative data on risks at lower levels of exposure (Darby et al., 2005; 2006; Hunter et al., 2013; Lubin et al., 1997; NA/NRC, 1999a; Toma´sˇek et al., 2008a; Walsh et al., 2010). These studies have shown significant associations between cumulative radon exposure and lung cancer mortality at lower radon activity concentrations found in homes. In the BEIR VI report (NA/NRC, 1999a), risk models that take account of effect modifying factors such as time since exposure, age, and exposure rate have been derived from the joint analysis of 11 cohorts of miners from China, Czech Republic, USA, Canada, Sweden, Australia, and France. Also more recently, a risk model has been derived from the joint analysis of the French and Czech miner cohorts associated with low levels of exposure (Toma´sˇek et al., 2008a). Toma´sˇek et al. (2008b) used these risk models to calculate the lifetime excess absolute risk (LEAR) for reference populations defined by the International Commission on Radiological Protection (ICRP, 2010). Considering a chronic exposure during adulthood, recent estimates of LEAR are significantly greater (by about a factor of 2) compared with previous estimates. As a result, ICRP now recommends a detriment-adjusted nominal risk coefficient for a mixed adult population of non-smokers and smokers of 8 10210 per Bq h m23 for exposure to 222Rn in equilibrium with its progeny, i.e., 5 1024 per WLM or 14 1025 per mJ h m23 (ICRP, 2010). This new value is approximately double the previous nominal risk coefficient given in ICRP Publication 65 (ICRP, 1993a). It should be noted, however, that the LEAR estimate is dependent upon the background lung cancer rates assumed for the reference population and this strongly depends on the prevalence of smoking.


In addition to epidemiological studies of underground miners, case – control studies of lung cancer and residential radon exposures have been conducted. The results from 23 residential case – control studies and 6 pooled or meta-analyses are shown in Figure 2.1 (UNSCEAR, 2008). In particular, four joint analyses have been carried out based on data from Europe (Darby et al., 2005; 2006), North America (Krewski et al., 2005a, 2006), China (Lubin et al., 2004), and Germany (Wichmann et al., 2005). Each joint analysis demonstrated an increased risk

of lung cancer with increasing domestic radon activity concentration, considering exposures over a period of 30 years preceding the diagnosis of cancer. There was evidence of a risk of lung cancer even for those exposed to an activity concentration below 200 Bq m23 (Darby et al., 2006). The estimates of the RR of lung cancer per unit activity concentration of radon in the four joint analyses were close to each other. The combined estimate for Europe, America, and China was 1.09 per 100 Bq m23 during a 30 year exposure (UNSCEAR, 2008). However, when the


Figure 2.1. Residential radon risk estimates from individual or pooled studies (UNSCEAR, 2008). Note that all references for this figure are listed in the UNSCEAR Report.

26

Health Effects of Radon Exposure

Figure 2.2. Relative risk (RR) of lung cancer versus long-term average residential radon activity concentration in the European pooling study (Darby et al., 2005; 2006). Corrections for the year-to-year variability in the radon exposure were made. A best-fitted straight line with 95% confidence intervals is shown; ERR per 100 Bq m23 increase ¼ 0.16 (95% CI: 0.05–031). Risks are relative to the extrapolated risk at 0 Bq m23. Adopted from Darby et al. (2005; 2006).

year-to-year variability in the radon exposure was considered in the European study, the estimated RR increased to 1.16 (1.05 – 1.31) per 100 Bq m23. This was considered by ICRP as a reasonable estimate of the risk associated with low prolonged exposures in homes (ICRP, 2010). Figure 2.2 shows the RR versus the long-term average residential radon activity concentration obtained from the joint European study after correcting for random uncertainties in the radon measurements (Darby et al., 2005; 2006). The joint European residential study showed a statistically significant increasing trend in lung cancer risks with domestic radon exposure for both smokers and lifelong non-smokers (Darby et al., 2005; 2006). The estimated value of ERR did not differ significantly by smoking status. Consequently, Darby et al. (2006) assumed the same ERR for smokers and non-smokers (i.e., they assumed that the interaction of the risks from smoking and radon is multiplicative). Because the background lung cancer rates in current smokers (of 15 –24 cigarettes d21) is about 25 times greater than that in lifelong non-smokers, the absolute value of risk of lung cancer per unit increase in radon is also about 25 times greater in current smokers compared with lifelong non-smokers. However, for ex-smokers who gave up smoking more than 10 years ago, the lung cancer rates are only about 5 times greater than that for lifelong non-smokers (Darby et al., 2006). These estimates of the effect of smoking were based on male data only. The reason for this is that in recent years, European women’s smoking habits have 27


changed to become more like those of men and therefore using the data for males were more appropriate to estimate future risks among women. On the basis of results from the joint European residential studies (Darby et al., 2005; 2006), the absolute risk of lung cancer by age 75 years for lifelong non-smokers was estimated as 0.4%, 0.5%, and 0.7% for lifetime average residential radon activity concentrations of zero (theoretical non-exposure situation), 100 and 400 Bq m23, respectively (Darby et al., 2006). For current smokers (of 15–24 cigarettes d21), the corresponding estimates were about 25 times greater (10%, 12%, and 16%). Although comparisons between residential studies and miner studies are complex, appropriate comparisons of lung cancer risks estimates from miner studies and indoor studies show good consistency (Hunter et al., 2013; ICRP, 2010; Toma´sˇek et al., 2008a; UNSCEAR, 2008). For example, based on conversions from WLM to time-weighted average radon activity concentration, the ERR estimates from the joint European studies on uranium miners were in agreement with those from the joint analysis of the European residential radon studies (Hunter et al., 2013). It was estimated for Europe that lifelong exposure to radon in homes currently accounts for about 9% of deaths from lung cancer and hence about 2% of all cancer deaths (Darby et al., 2005). This was calculated assuming a population-weighted average radon activity concentration of 59 Bq m23 for Europe (UNSCEAR, 2000) with an RR of 1.16 per 100 Bq m23. Using a modified version of the BEIR VI risk model (NA/NRC, 1999a) with an estimated average residential radon activity concentration of 46 Bq m23, the US Environmental Protection Agency estimated that about 13% of the lung cancer deaths (i.e., 21 100 deaths) in the USA in 1995 were radon-related (EPA, 2003). Hence, radon is considered to be the second leading cause of lung cancer after smoking. The miner studies mainly considered exposures during adulthood; it was only the Chinese tin miner study where there were data on exposures in childhood and adolescence. There was no clear indication that the ERR depends on age at first exposure, but the data are sparse (NA/NRC, 1999a). In the residential studies, the exposure period considered was 30–35 years prior to diagnosis of lung cancer with an assumed lag time of 5 years from lung cancer induction to diagnosis. As most of the lung cancer cases occurred over the age of 50 years, adulthood exposures were mainly considered. Therefore, reliable information of risks of lung cancer arising from exposures to radon and its progeny during childhood is currently not available.


using a model based on geographical region, soil type, and house characteristics rather than by direct measurements in the homes in question. ICRP concluded that the review of the available epidemiological evidence to date shows no consistent evidence for an association between radon activity concentrations and cancer other than that of the lung (ICRP, 2010). In sharp contrast to the harmful effects of radon exposure, natural radon-rich thermal water and vapor have been used for decades in radon spas, such as Badgastein (Austria), Bad Schlema (Germany), or Misasa (Japan), for the treatment of various rheumatic diseases, such as ankylosing spondylitis (Tempfer et al., 2010). Some therapeutic benefits have been reported for carefully selected patient groups and pathologies (Deetjen et al., 2005). However, knowledge of the physiological and molecular mechanisms and their time sequence triggered by the radon exposure is still too fragmentary to understand why these reported beneficial effects can be produced by these relatively small radon doses.

28


Studies of underground miners generally have not shown any excess of cancer other than lung cancer to be associated with radon exposure (Darby et al., 1995; NA/NRC, 1999a; UNSCEAR, 2008). There have been some associations of extra-pulmonary cancers with radon exposure suggested in individual studies, but they have not been replicated in other studies and no consistent pattern has emerged. For example, excesses or trends with radon exposure were noted for leukemia (Rericha et al., 2006), kidney (Vacquier et al., 2008), liver, and stomach cancers (Kreuzer et al., 2008), but were not confirmed by other studies. Several large-scale residential case – control studies were unable to confirm an association between radon exposure and leukemia risk (CCSI, 2002; Lubin et al., 1998; Steinbuch et al., 1999). However, a recent residential study in Denmark suggested a significant positive association between radon activity concentrations and acute lymphocytic leukemia (Raaschou-Nielsen et al., 2008). A weakness of this study, acknowledged by the authors, was that the radon exposures were estimated



3. Radon and Radon Progeny Inhalation and Resultant Doses 3.1.

Lung Dose Assessment Models

(1) a morphometric lung model, detailing the anatomical structure of the lung in terms of the number of airway generations and their characteristics, such as diameter, length, branching, and gravity angles; (2) a respiratory physiology model, which defines the breathing patterns related to different physical activities; (3) a particle deposition model, which comprises extrathoracic, bronchial, and pulmonary deposition efficiencies, physical deposition mechanisms in cylindrical airways, and related analytical deposition equations for specific flow patterns; (4) a bronchial clearance model comprising mucociliary clearance and transport into the blood; (5) a dosimetry model, which specifies the geometry of alpha particle interactions with sensitive target cells at different depths in bronchial epithelium. Two different modeling approaches are currently used to calculate doses to the lungs following the inhalation of short-lived radon decay products:



Radon progeny doses to the bronchial region of the lung are about two orders of magnitude higher than corresponding doses produced by radon gas. Thus, currently used lung dosimetry models focus exclusively on the prediction of bronchial doses by inhaled radon progeny, neglecting the contribution by the inhaled radon gas. Following the inhalation of radon and its short-lived progeny, the highest doses are received by the bronchial region of the human lung produced by alpha particles emitted from short-lived radon progeny deposited on bronchial airway surfaces. Hence, the primary health effect due to radon inhalation is the formation of bronchogenic carcinomas predominantly in bronchial airways. Since it is not possible to measure bronchial doses directly, the primary dosimetric issue is the development of appropriate dosimetric models for the calculation of doses to sensitive target cells in bronchial tissue. Radon progeny were not recognized as the relevant contributors of dose from radon until the work of Bale (1980). Harley and Fresco (1951) and Harley (1980) showed that radon progeny retention in the lung was about 50% of the inhaled radon progeny activity. In evaluating the exposure of workers mining or processing radium-bearing materials, the hazard from the inhalation of radon progeny was concluded to be much more serious than that from radon itself. This was contrary to Evans and Goodman (1940) who had based the early guidelines for mines on the assumption that the important radiation dose to bronchial epithelium was the alpha radiation from radon gas. Bale (1980) estimated that the absorbed bronchial dose from radon progeny could be up to 8 times the dose from radon gas. The challenges in lung dosimetry of radon progeny result from the non-uniformity of the radon progeny deposition within the bronchial region and among bronchial airway surfaces, the short range of alpha particles in relation to the non-uniform distribution of sensitive target cells in bronchial epithelium, and the relationship between energy deposition (stopping power) and alpha particle range.

The human respiratory tract is composed of three functional regions: (i) the extrathoracic region, consisting of the nose, mouth, and pharynx, acting primarily as a filter to protect the lungs, (ii) the tracheobronchial or conductive region, consisting of bronchial and bronchiolar airways, whose primary task is to distribute inhaled air to the gas-exchange region, and (iii) the alveolar–interstitial (pulmonary) region, where the gas exchange between lung and blood takes place via the alveoli, but where also inhaled radon and progeny may be transferred to the other organs of the human body via the bloodstream. Bronchial and alveolar regions also differ in their clearance mechanisms, with relatively fast mucociliary clearance in the bronchial airways and relatively slow macrophage-mediated transport in the alveolar region. For a detailed description of the structure and function of the human respiratory, the reader is referred to the ICRP (1994) report on the Human Respiratory Tract Model. From a modeling point of view, lung dosimetry models comprise five submodels:


(1) Models in which the absorbed dose to sensitive target cells in bronchial airway generations is calculated, such as the deterministic and stochastic airway generation models proposed by Haque and Collinson (1967), Harley and Pasternack (1972; 1982), Hofmann (1982a), Hofmann et al. (2010), Jacobi (1964), Jacobi and Eisfeld (1980), James (1988), Winkler-Heil and Hofmann (2002), and Zock et al. (1996). These models are sometimes called anatomical or biological models. (2) Semi-empirical compartment models, such as the ICRP (1994) Human Respiratory Tract Model (HRTM), combine many airway generations into compartments to simplify dose calculations. These models are sometimes called pharmacokinetic or biokinetic models.

Table 3.1. Annual equivalent lung dose coefficients following continuous inhalation of radon gas and thoron gas References

222

1.1 7.5 5.8 6.2 2.9 5.9

Pohl and Pohl-Ru¨ling (1977) Jacobi and Eisfeld (1980)

Rn Rn 220 Rn 222 Rn 220 Rn 222 Rn

Peterman and Perkins (1988) Khursheed (2000)

constant activity concentration of 1 Bq m23 in the inhaled air, Jacobi and Eisfeld (1980) calculated dose equivalent rates to different tissues of the human body. For the inhalation of 222Rn, they reported an annual equivalent dose coefficient to the lung of 7.5 mSv (Bq m23)21 for inhaled radon and 5.8 mSv (Bq m23)21 for inhaled thoron (Table 3.1). A multicompartment model to simulate the dynamics of inert radioactive gases in the human body has been developed by Peterman and Perkins (1988), utilizing the blood flow and solubility data reported by Nussbaum and Hursh (1957). In this model, it is assumed that an inert gas is transported through the body to various organs via the blood stream. This model was used to determine equivalent doses resulting from inhalation of radon and thoron. Annual equivalent lung dose coefficients were 6.2 mSv (Bq m23)21 for radon inhalation and 2.9 mSv (Bq m23)21 for thoron inhalation (Table 3.1). A refined dynamic model for the retention of inert gases in the body for the calculation of inhalation dose coefficients has been published by Khursheed (2000). The annual equivalent dose coefficient for the lungs for the inhalation of radon gas was 5.9 mSv (Bq m23)21 (Table 3.1), which is very similar to the dose value predicted by Peterman and Perkins (1988). Annual lung equivalent dose coefficients for continuous inhalation of radon and thoron are listed in Table 3.1. Doses due to inhaled thoron are consistently lower than those for radon.

Radon versus Radon Progeny Doses Lung Doses due to Inhalation of Radon and Thoron Gas

3.2.2

Based on experimental observations of the radon concentrations in different organs and tissues of the human body, Pohl and Pohl-Ru¨ling (1977) derived organ doses following continuous inhalation of radon. For the human lung, they reported an annual equivalent dose coefficient of 1.1 mSv (Bq m23)21 for the inhaled radon gas alone (Table 3.1) (recalculated from published absorbed doses). Assuming steady-state conditions for the specific activities of 222Rn and 220Rn in body tissues at a

Lung Doses due to Inhalation of Short-Lived Radon Progeny

While the annual equivalent lung doses due to inhaled radon listed in Table 3.1 were expressed in terms of inhaled radon activity concentrations, bronchial equivalent doses produced by inhaled short-lived radon progeny are commonly expressed in terms of cumulative exposures, e.g., in mSv (Bq m23)21 or in mSv WLM21. The most important airborne radon progeny, from the perspective of radiation dose to lung tissue as a consequence of inhalation, are the alpha-emitting 30


3.2.1

Annual equivalent lung dose coefficient [mSv (Bq m23)21]

222

While the ICRP (1994) model can be applied to the inhalation of any radionuclide, the generation-based models were specifically developed for inhaled radon progeny. In general, the structure of the ICRP (1994) compartment model is the same as that of the airway generation models. There are, however, a few significant differences: (1) the lung structure consists of only three compartments, the large bronchial airways (BB), the smaller bronchiolar airways (bb), and the alveolar– interstitial region (AI), instead of single airway generations; (2) deposition fractions in tracheobronchial (TB) (TB ¼ BB þ bb) and AI compartments are obtained by appropriate fits to human experimental data and expressed as functions of particle and flow parameters (hence the name “semi-empirical”) instead of ab initio physical deposition calculations; (3) clearance pathways and related half-times refer to the whole compartment and not to single airway generations; and (4) doses to bronchial target cells are computed for the total alpha activity in a given compartment rather than for steady-state surface activities in individual cylindrical airway generations.

3.2

Radon isotope

Radon and Radon Progeny Inhalation and Resultant Doses

nuclides 218Po (half-life 3.07 min, Ea ¼ 6.11 MeV) and 214 Po (half-life 162 ms, Ea ¼ 7.83 MeV). Doses to sensitive basal and secretory cells for a variety of exposure conditions have been published in the past and are discussed in more detail in Section 3.9.1. Here, only a few model predictions are presented to illustrate the magnitude of bronchial doses relative to the doses delivered by the radon gas. To facilitate comparison with the dose predictions for the radon gas, reported radon progeny dose-exposure conversion coefficients for mine atmospheres (in mSv WLM21) were converted to annual equivalent dose coefficients in homes [in mSv (Bq m23)21] by assuming an equilibrium factor of 0.4 and a K-factor of 1 (Table 3.2). The comparison between radon and radon progeny doses in the bronchial region of the lung listed in Tables 3.1 and 3.2 demonstrates that radon progeny doses are about two orders of magnitude higher than corresponding radon doses. This clearly indicates that the dose to the lungs mainly arises from the inhalation of the short-lived progeny. While the above dose calculations have shown that radon progeny doses from alpha particles are primarily responsible for radiobiological effects in the lungs, their distribution throughout the lung is, however, relatively inhomogeneous, with significantly higher doses to the bronchial (BB) and bronchiolar (bb) airways than to the alveolar–interstitial region (AI). For comparison, regional dose distributions per unit exposure in WLM predicted by three lung dosimetry models for a reference worker are compiled in Table 3.3, differentiating between the attached, i.e., radon progeny attached to the ambient aerosol, and the unattached fractions. The three models applied here are (i) the RADEP/IMBA code (Marsh and Birchall, 2000), based on the ICRP Human Respiratory Tract Model (ICRP, 1994), a deterministic regional compartment model, (ii) the RADOS model (Winkler-Heil and Hofmann, 2002), a deterministic airway generation model, and (iii) the IDEAL-DOSE model (Hofmann et al., 2010), a stochastic airway generation model.

Table 3.3. Comparison of radon progeny absorbed dose coefficients in bronchial (BB), bronchiolar (bb) and alveolar– interstitial (AI) airways arising from the exposure to 1 WLM predicted by three lung dosimetry models (Winkler-Heil et al., 2007) Region

BB bb AI

Jacobi and Eisfeld (1980) James (1988) Harley et al. (1996) Porstendo¨rfer (2001) Marsh et al. (2005) Winkler-Heil et al. (2007)

144 436 326 395 439 268

RADEP/ IMBA

RADOS

IDEAL-DOSE

76.5 7.9 25.0 5.6 0.01 0.4

81.1 6.1 10.4 3.3 0.001 0.3

76.7 7.0 4.9 3.3 0.003 0.3

3.2.3

Lung Doses due to Inhaled Thoron Progeny

Except for the dual decay between 212Bi and 212Po, the structure of the thoron progeny decay scheme is similar to that for the short-lived radon progeny. Only radioactive half-lives, alpha particle energies and related energy-range relationships have to be replaced by the corresponding values for the thoron progeny. The most important airborne thoron progeny, from the perspective of radiation dose to lung tissue as a consequence of inhalation, is 212Pb (half-life 10.64 h). Lead-212 itself is a beta particle emitter, but when it decays, it gives rise to the alpha-emitting thoron progeny 212Bi (half-life 60.5 min, Ea ¼ 5.5–6.1 MeV) and 212Po (half-life 3 1027s, Ea ¼ 8.68 MeV). A summary of effective dose conversion coefficients for thoron progeny is given in Table 3.4. Values range from 1.5 to 5.7 mSv WLM21, depending on activity size distributions, unattached fractions, and the dosimetric lung models employed. Consistent with earlier dose calculations for inhaled radon progeny 31


Annual equivalent lung dose coefficient [mSv (Bq m23)21]

Unattached Attached Unattached Attached Unattached Attached

Absorbed dose per WLM (mGy WLM21)

Inspection of Table 3.3 reveals that the doses to the alveolar-interstitial region are between one and two orders magnitude smaller than those to the bronchial and bronchiolar regions. These results also demonstrate that the unattached fraction contributes to the total dose only in the bronchial and bronchiolar regions, but not in the alveolar region. Since bronchial doses are much higher than alveolar doses, the obvious target region relevant for lung tumors is the bronchial region. In addition to alpha particles, short-lived radon progeny also emit beta particles. Calculations by Markovic et al. (2011) produced dose-exposure conversion coefficients due to beta radiation of 0.21 mSv WLM21 for 222Rn progeny and 0.06 mSv WLM21 for 220 Rn progeny.

Table 3.2. Comparison of bronchial annual equivalent dose coefficients for inhaled short-lived radon progeny predicted by different lung models References

Mode


References

Effective dose conversion coefficient (mSv WLM21)

Harley and Pasternack (1973) Jacobi and Eisfeld (1980) ICRP (1987) James (1988) Marsh and Birchall (1999a; 1999b) UNSCEAR (2000) Porstendo¨rfer (2001) Ishikawa et al. (2007) Kendall and Phipps (2007) Li et al. (2010) Hofmann et al. (2014)

2.0 1.5 1.8 3.5 3.8 1.9 2.4 5.4 5.7 3.8 4.6

(Winkler-Heil et al., 2007), dose conversion coefficients based on the ICRP (1994) Human Respiratory Tract Model are higher than those obtained by dosimetric airway generation models. A comparison between dose conversion coefficients in terms of mSv per WLM for inhaled radon progeny (Rn) with those for inhaled thoron progeny (Tn) indicates that the ratio Rn:Tn is about 3 (Ishikawa et al., 2007). However, if expressed in terms of doses per unit equilibrium equivalent activity concentration of radon/thoron exposures (in Bq h m23), then the thoron progeny conversion coefficients are greater by about a factor 4 than those for short-lived radon progeny. This arises because 1 WLM corresponds to 4.68 104 Bq h m23 equilibrium equivalent activity concentration of thoron and to 6.37 105 Bq h m23 equilibrium equivalent activity concentration of radon over a period of 1 working month (170 h).

3.3

Lung Doses versus Other Organ Doses

In this section, the equivalent dose to the lung and to other organs are considered and compared. Doses arising from the inhalation of radon progeny and from the inhalation of radon gas are discussed separately. The external dose to the skin from radon progeny that have been deposited on the skin surface is also considered as well as doses from the ingestion of radon in water. 3.3.1

Doses to Internal Organs Arising from Inhalation of Radon Progeny

As described above, following exposure to radon and its progeny, the dose to the lung mainly arises from the inhalation of the short-lived progeny. Because of the short half-lives of the progeny, dose is delivered to the lung tissues before clearance can take place, either by absorption into blood or by particle

3.3.2

Doses to Internal Organs Arising from Inhalation of Radon Gas

Radon gas is soluble in water, body fluids, and tissue. Volunteer studies in which subjects have 32


transport to the alimentary tract. In comparison, doses to systemic organs and gastrointestinal tract regions are low and can generally be ignored in the calculation of effective doses. The equivalent dose to the extrathoracic region of the respiratory tract is similar to that of the lungs. However, its contribution to the effective dose is generally quite small as it is considered to be 1 of the 13 “remainder organs” and consequently has a small tissue weighting factor (ICRP, 2007). Typically, the lung dose contributes about 95% or more to the effective dose following the inhalation of 222Rn or 220Rn progeny. The longer radioactive half-life of the 220Rn decay product 212Pb (10 h) compared with the 222Rn progeny (,30 min) means that a greater fraction of 212Pb is absorbed in blood before decay takes place in the lung. Doses to the lung, extrathoracic region, systemic organs, and the gastrointestinal tract regions arising from the inhalation of radon progeny have been calculated by implementing the ICRP dosimetric and biokinetic models (Kendall and Smith, 2002; 2005; Marsh et al., 2012, for 222Rn progeny calculations; Ishikawa et al., 2007; Kendall and Phipps, 2007; Tschiersch et al., 2007, for 220Rn progeny calculations). These models include the ICRP Publication 66 Human Respiratory Tract Model (HRTM) (ICRP, 1994), the ICRP Publication 30 Gastrointestinal (GI) tract model (ICRP, 1980), the ICRP Publication 67 biokinetic models for polonium and lead (ICRP, 1993b), and the ICRP Publication 30 biokinetic model for bismuth (ICRP, 1980). For illustrative purposes, Table 3.5 gives annual equivalent doses to organs arising from the inhalation of 222Rn progeny calculated by Kendall and Smith (2002). These calculations apply to an adult continuously exposed to an indoor radon (222Rn) concentration of 200 Bq m23 (with equilibrium factor F ¼ 0.4, an indoor occupancy of 22 h d21, and an average breathing rate of 0.9 m3 h21). As can been seen from Table 3.5, the calculated doses to systemic organs and gastrointestinal tract regions are at least two orders of magnitude less than the lung dose, with the kidney receiving the highest organ dose outside the respiratory tract. The organ doses from the inhalation of thoron progeny calculated by Kendall and Phipps (2007) show that the lung dose is about 30 times or more greater than the doses to the systemic organs. The bone surfaces and the kidney receive the next two highest doses after the respiratory tract.

Table 3.4. Summary of calculated effective dose conversion coefficients (mSv WLM21) for thoron progeny indoors based on adult male breathing conditions (ICRP, 2010; Li et al., 2010)


Organ/tissue

Lung Extrathoracic region Stomach Small intestine Colon Red bone marrow Bone surface Liver Breast Kidney Gonads Brain Bladder Muscle Skinc,d Effective dose

Annual equivalent doses to organs (mSv) Inhaled radon progenya

Inhaled radon gasb

Total

159 70.9 0.08 0.05 0.02 0.03 0.17 0.05 0.02 0.54 0.02 0.02 0.02 0.02 25.1 19.7

1.2 0.42 0.06 0.06 0.05 0.65 0.03 0.09 0.42 0.05 0.05 0.06 0.05 0.05 — 0.28

160 71 0.14 0.11 0.07 0.68 0.20 0.14 0.44 0.59 0.07 0.08 0.07 0.07 — 20

a

Doses from inhaled radon progeny were calculated by Kendall and Smith (2002) for an adult male sedentary worker with an indoor occupancy of 22 h d21 and a breathing rate of 0.9 m3 h21 (Table B.16B of ICRP Publication 66, ICRP, 1994). It was also assumed that the radon progeny were moderately soluble in the lung (i.e., Absorption Type M). b Doses from inhaled radon gas were calculated by Khursheed (2000) assuming 100% indoor occupancy. c External dose to skin taken from Eatough and Henshaw (1992). d External dose to skin taken from Harley and Robbins (1992).

inhaled radon or ingested radon-rich water have shown that radon is absorbed into the bloodstream via the lung or the GI tract and is retained in tissues with half-times varying from minutes to several hours or more (Gosink et al., 1990; Harley and Robbins, 1992; Harley et al., 1994; Hursh et al., 1965). The long-term retention half-times were assumed to be associated with retention in body fat. Retention half-times were also shown to decrease with exercise (Gosink et al., 1990). Following inhalation, most of the radon is exhaled, but some of it is absorbed in blood from the lungs whence it moves rapidly within the body. Radon gas absorbed in pulmonary blood is distributed in arterial blood to capillaries in tissues and organs and is then transferred from tissue to venous blood. The gas is again carried in the venous blood to pulmonary blood where some of it is exhaled, while the rest returns to arterial blood and the cycle continues. The extent to which radon is retained in a tissue depends mainly on the relative solubility of radon in the tissue and the blood flow rates to the tissue. Tissues with a rich blood supply and a low to moderate solubility of radon have retention half-times 33


of several minutes, whereas fatty tissues with a poor blood supply and high radon solubility have halftimes of several hours or more. Following continuous exposure to radon, equilibrium activity concentrations are reached typically within an hour for tissues with a low retention half-time of a few minutes, whereas for fatty tissues with a longer retention half-time, it can take several days to reach equilibrium. For continuous inhalation of 222Rn or 220Rn gas, Jacobi and Eisfeld (1980) calculated equilibrium dose rates to organs and tissues, including the lung, liver, kidney, spleen, red bone marrow, bone surfaces, and body fat. Organ doses have also been calculated with pharmacokinetic models for radon gas based on blood flow rates and radon solubility coefficients (Peterman and Perkins, 1988, for 222Rn and 220 Rn; Khursheed, 2000, for 222Rn). The radon solubility of a tissue is represented by a tissue-to-blood partition coefficient, defined as the ratio of the concentration of radon gas in tissue and blood at equilibrium. Values of these partition coefficients were mainly derived from the in vivo data in rats of Nussbaum and Hursh (1957). The rat data showed that radon is significantly more soluble in omental fat compared with other tissues. The annual organ doses calculated by Khursheed (2000) for a continuous exposure of 200 Bq m23 of 222Rn gas are given in Table 3.5. The organ receiving the highest dose from the inhaled 222Rn gas is the lung with the next two highest organs being red bone marrow (RBM) and breast due to their fat content. The lung dose from inhaling the radon gas, which was calculated from the decays in the lung air, is about 100 times lower than the dose to the lung from inhaling radon progeny (Tables 3.1 and 3.2). Khursheed (2000) calculated an annual equivalent dose to the RBM of about 0.65 mSv at a 222Rn activity concentration of 200 Bq m23 (Table 3.5). It was assumed that the RBM consisted of 40% fat cells and that the fat cells are uniformly distributed throughout the haematopoietic tissue. Similar annual doses have been calculated by Richardson et al. (1991) for the same radon activity concentration, 0.75 mSv for a 40 year old and 1.0 mSv for a 70 year old. In these calculations, they modeled the RBM as a mixture of spherical fat cells distributed uniformly in the marrow and considered the variation of the fat content with age. The dose to the haematopoietic tissue from alpha particles originating in the fat cells was calculated and the “selfabsorption” in the fat molecules, which reduces the dose, was taken into account. However, they assumed a 30% higher partition coefficient for fat than Khursheed (2000), based on solubility measurements of human extracted fat samples (Nussbaum and Hursh, 1958). These calculations were later revised following analysis of fat fractions and sizes of fat cells in

Table 3.5. Annual equivalent doses to organs arising from the inhalation of radon gas and radon progeny at an indoor 222Rn concentration of 200 Bq m23 with equilibrium factor F ¼ 0.4


3.3.3

Skin Dose from Deposited Radon Progeny

Radon progeny in the ambient air can deposit on surfaces including human skin. The alpha particles emitted will deliver a dose to the outer layers of the skin in areas exposed to the atmosphere such as the neck and the face, whereas skin protected by clothing and hair will in general receive a minimal dose. It has been assumed by many authors that the basal cell layer of the epidermis is the target cell layer for the induction of skin cancer. In places, where the skin is thin, such as the face, these target cells lie within the range of the alpha particles from the radon progeny on the skin surface. However, Charles (2004) noted that there are existing animal data that imply that the target cells are in the underlying dermis, in which case they may lie too deep to receive any significant dose from radon progeny on skin surfaces. He concluded that currently there is no definitive answer to the location and the identity of the target cells in the skin that play a dominant role in the induction of skin cancer. A number of authors have calculated external doses to the basal layer of the skin from radon progeny (Eatough and Henshaw, 1992; Harley and Robbins, 1992; Sevcova et al., 1978). The dose depends mainly on the deposition velocity of the radon progeny, which in turn depends on particle size and air movement. Eatough and Henshaw (1992) estimated an average external skin dose of 25 mSv yr21 (range 17–170 mSv yr21) for domestic exposure of 200 Bq m23 of 222Rn. These values relate to the basal cell layer of the face and neck with an assumed epidermal thickness of 50 mm. The estimated range mainly reflects the uncertainties in the deposition velocity of the radon progeny. Similar values were calculated by Harley and Robbins (1992) (10–200 mSv yr21). Based on experimental measurements of deposition rates of 218Po and 214Po, Fews et al. (1999) estimated an external skin dose for the face of about 100 mSv yr21 for an indoor exposure of 200 Bq m23. This value was consistent with the reported values found on personal

3.3.4

Ingestion of Radon in Water

Surface waters contain relatively low activity concentrations of dissolved radon, typically less than about 4000 Bq m23 (NA/NRC, 1999b). However, water from ground water systems can have relatively high levels of dissolved radon, with activity concentrations of 10 000 000 Bq m23 or greater (NA/NRC, 1999b). Because radon can easily be released by agitation in water, many uses of water release radon into the indoor air, which then contributes to the total indoor airborne radon activity concentration and thus to the inhalation pathway. Ingestion of water is also thought to pose a direct health risk through irradiation of sensitive cells in the gastrointestinal tract and in other organs once it is absorbed into the bloodstream. Thus, radon in drinking water can potentially produce adverse health effects in addition to lung cancer. Because of the relatively small volume of water used in homes, the large volume of air into which radon is dispersed, and the exchange of indoor air with the ambient atmosphere, radon in water typically adds only a small increment to the indoor air activity concentration. For example, a typical pattern of use of water containing radon at about 10 000 Bq m23 will on average increase the air radon activity concentration by only about 1 Bq m23, based on a transfer coefficient from water to indoor air of about 1.0 1024 (NA/NRC, 1999b). Since there is always radon in indoor air from the emanation of soil gas into indoor air, only very high activity concentrations of radon in water will make a significant contribution to the indoor airborne activity concentration. The transfer coefficient of radon in water to radon in air measured in a large bathroom in an energy-efficient home with a private well was 4.3 1024 (Harley et al., 2014). The stomach is the port of entry of ingested radon into the body and thus is of particular concern for 34


“wrist watch” dosimeters (Eatough et al., 1999). However, this skin dose will only contribute a small amount to the overall effective dose as the tissue weighting factor for the skin is 0.01 (ICRP, 2007). Sevcova et al. (1978) reported that in Czech miners, the excess basal cell carcinomas were on the forehead and cheek. Skin deposition per unit activity concentration of 222 Rn was measured to be significantly higher outdoors than for indoor exposure (Fews et al., 1999). This is likely because of the greater air movement and also because of the possibility of wet deposition from rainfall. The external equivalent skin dose to the face was estimated to be 95 mSv yr21 for a continuous outdoor exposure of 7 Bqm23 of 222Rn (Fews et al., 1999).

the marrow cavity of adult ribs. The calculations gave annual doses at 200 Bq m23 of 0.60–1.6 mSv to the RBM (Allen et al., 1995). In contrast, a lower value of 0.26 mSv was calculated for fatty marrow by Harley and Robbins (1992) as they assumed a lower partition coefficient for fat. In all these calculations, the actual spatial distribution between fat cells and haematopoietic tissue was not considered; a homogeneous mixture was assumed for simplicity, which would tend to overestimate the dose. Harley and Robbins (1992) also calculated doses to soft tissue, fatty tissue, bone surfaces, blood, and T lymphocytes.


3.4

Sensitive target cells in bronchial epithelium are defined as the cells receiving energy from ionizing radiation that lead to the development of lung cancer. Among the several cell types in bronchial tissue, basal cells have been selected as target cells by several authors since they are considered to be the progenitors of the ciliated and goblet cells in the epithelium and have a long lifetime (Ford and Terzaghi-Howe, 1992; NCRP, 1984; Robbins et al., 1990). Secretory or mucous cells have also been proposed as target cells for carcinogenesis (Johnson et al., 1990; McDowell et al., 1985). Thus, it is current practice to identify both cell types as the relevant target cells for cancer induction, assuming that the cell nucleus is the most likely actual target region. The locations of sensitive basal and secretory cell nuclei within the bronchial epithelium, labeled as BB in ICRP (1994), are illustrated in Figure 3.1. Radon progeny deposited on the top of the mucus layer and cleared from the initial deposition site by mucociliary action are usually assumed to be uniformly mixed within the viscous mucus gel layer, forming a uniformly distributed alpha particle surface source. Depending on the irradiation geometry (i.e., the distance between the alpha particle emission site and the location of target cell nuclei), a certain fraction of emitted alpha particles will actually reach basal and secretory cell nuclei. Since secretory cell nuclei are closer to the epithelial surface than basal cell nuclei, with an assumed mean depth of 25 mm, secretory cells receive a higher dose than the basal cells with an assumed mean depth 42 mm (NA/NRC, 1999a).

Table 3.6. Summary of estimates of equivalent dose coefficients to the stomach per unit activity of 222Rn ingested (NA/NRC, 1999b) Studies

Equivalent dose coefficient (Sv Bq21)

Von Doebeln and Lindell (1965) Hursh et al. (1965) Suomela and Kahlos (1972) Crawford-Brown (1989) Brown and Hess (1992) Harley and Robbins (1994) Sharma et al. (1997)

1.1 1027 1.1 1027 1.3 1027 3.0 1027 8.8 1028 1.6 1029 8.2 1028

Sensitive Target Cells in Bronchial Epithelium

35


The equivalent dose to the stomach wall was 8.4 1028 Sv Bq21. The assumption that radon equilibrates between the stomach contents and the wall (i.e., saturated diffusion) was made. For the ingestion pathway, NA/NRC (1999b) calculated an age- and gender-averaged stomach cancer risk from lifetime ingestion of radon dissolved in drinking water of 1.9 1029 for a radon activity concentration of 1 Bq m23. Estimates for the inhalation of radon released from water yielded a lung cancer risk due to lifetime exposure to radon in water at 1 Bq m23 of about 1.6 1028, based on a transfer coefficient of 1 1024, which is about an order of magnitude higher than the risk contributed by the ingestion pathway. Thus, most of the cancer risk posed by radon in drinking water arises from the transfer of radon into indoor air and the subsequent inhalation of radon decay products, and not from the ingestion of water.

risk assessment. Alpha particles emitted by radon and its short-lived progeny within the contents of the stomach cannot penetrate the mucus layer lining of the epithelium and therefore cannot reach the stem cells at risk in the stomach wall. Thus, the dose to the wall depends heavily on the extent to which radon diffuses from the contents into the wall. Once radon has entered the blood, through either the stomach or the small intestine, it is distributed among the organs according to the blood flow and the relative solubility of radon as described in Section 3.3.2. Radon dissolved in the blood that enters the lung will readily be removed from the body by exhalation. Doses to the stomach estimated in different studies are summarized in Table 3.6 (NA/NRC, 1999b). These estimates, exhibiting a wide range of values, differ primarily by the extent to which diffusion into the stomach wall is considered. For example, Hursh et al. (1965) assumed that ingested radon diffuses through the stomach wall to blood at a rate such that the activity concentration in the stomach wall is the same as that in the stomach contents (i.e., saturated diffusion). By contrast, Harley and Robbins (1994) assumed on the basis of the structure of the stomach wall and the counter-current flow of fluid from the stomach wall into the lumen that ingested radon cannot diffuse into the stomach wall with a sufficient depth to irradiate radiosensitive cells. However, NA/ NRC (1999b) assumed on the basis of a radon diffusion model that the time-integrated activity concentration of radon at the depth of the stem cells in the adult stomach wall is 30% of the activity concentration in the lumen. The resulting estimate of equivalent dose to the stomach wall was 2.4 1028 Sv Bq21 of 222Rn ingested. The corresponding effective dose was 3.5 1029 Sv Bq21 of ingested radon. Assuming either no diffusion or saturated diffusion gave values of effective dose of 2.1 1029 and 3.8 1028 Sv per Bq ingested radon, respectively (NA/NRC, 1999b). Khursheed (2000) calculated an effective dose of 1.0 1028 Sv Bq21 for ingestion of 222Rn of which 97% is contributed by the dose to the stomach wall.


The cell depths assumed in NA/NRC (1999a) and ICRP (1994) were based primarily on the study of Mercer et al. (1991). The bronchiolar region, labeled as bb in ICRP (1994), is characterized by a thinner epithelial tissue, which contains only secretory cells as the sensitive target cells (ICRP, 1994; NA/NRC, 1999a). Measurements made by Robbins et al. (1990) based on 10 000 electron micrographs of bronchial tissue samples from over 100 persons show that the cell depths are somewhat smaller than assumed by NA/ NRC (1999a). Robbins et al. (1990) measured values of 19 and 27 mm for secretory and basal cell nuclei, respectively. These tissue samples were dissected by airway generation so no ambiguity concerning specific generations exists. These values are also smaller than the published values of Gastineau et al. (1972). Baldwin et al. (1991) reported similar nuclear depths as in the Robbins et al. (1990) study; however, the airways were characterized by diameter which does not permit exact identification of airway generation as a range of diameters exists for each generation. The data of Robbins et al. (1990) based on a total number of 9954 basal cell nuclei and 8958 mucous cell nuclei are shown in Table 3.7. The ICRP (1994) model of target cell nuclei, i.e., secretory and basal cells, in the bronchial (airway generations 1-8) wall, based primarily on the histological measurements of Mercer et al. (1991), provides information on the ranges of nuclear depths from the surface of the epithelium. Moreover, ICRP (1994) presents depth ranges for secretory cell

Table 3.7. Depth (mm) of target cell nuclei for lung cancer induction below the epithelial surface (Robbins et al., 1990) Population

Basal cell nuclei (N)a Mucous cell nuclei (N)a

Male smokers Male non-smokers Male ex-smokers Female smokers Female non-smokers Female ex-smokers

28 + 1.8 (23) 26 + 1.6 (10)

22 + 1.4 (28) 18 + 1.3 (10)

25 + 2.1 (15) 27 + 1.6 (28) 27 + 1.5 (22)

18 + 1.4 (15) 20 + 1.6 (29) 17 + 1.0 (24)

30 + 2.0 (17)

20 + 1.3 (17)

a

Cell nuclei depth averaged over airway generation 3–6. The nucleus depth is from the midpoint of the nucleus to the free epithelial surface. N is the number of subjects and the uncertainty term is the standard error of the mean.

nuclei in the peripheral bronchiolar (airway generations 9–15) epithelium, while basal cells are rarely found in the bronchioles (Mercer et al., 1991). In the ICRP (1994) tissue model, it is implicitly assumed that basal and secretory cell nuclei are uniformly distributed within the defined regions. However, Mercer et al. (1991) found that cell nuclei were not uniformly distributed, but exhibited a distinct maximum within the reported ranges. Comparison of Tables 3.7 and 3.8 reveals that the secretory and particularly the basal cell nuclei depths reported by Robbins et al. (1990) are smaller than the average nuclear depths proposed by ICRP (1994). Since bronchial doses decrease with 36


Figure 3.1. Schematic model of the location of sensitive target cell nuclei (basal and secretory cells) throughout the bronchial epithelium (NA/NRC, 1991).


Range of depths in epithelial tissue (mm)

Bronchial Bronchiolar

Secretory cells

Basal cells

10– 40 (25)a 4 – 12 (8)

35 –50 (42.5) n.a.

a

Calculated average values, assuming a uniform distribution within the epithelium.

increasing depth in bronchial epithelium, cell nuclei located at different depths within the reported ranges will receive different doses. For example, the dose at 26 mm depth is about a factor of 2 higher than the dose at a depth of 42 mm. This highlights the significance of the target cell depth in bronchial dose modeling that attempts to account for alpha particle traversal of cell nuclei from radon decay products on the epithelial surface. Hence improved precision in bronchial dose modeling is possible with the use of more comprehensive data sets, i.e., global estimates of biological parameters. Regarding the depth distribution of target cell nuclei among the bronchial and bronchiolar airways, Baldwin (1994) reported a decrease in basal cell depths with penetration into the airway system, consistent with the corresponding reduction in airway diameters. Likewise, Mercer et al. (1991) measured the depth distributions of basal and secretory cells, among other cell types, for large and small bronchi, bronchioles, and terminal bronchioles, showing a decrease from trachea to terminal bronchioles for both cell types. Based on these measurements, Hofmann et al. (1996) defined the average depths of secretory, Ds, and basal, Db, cell nuclei as functions of the bronchial airway diameter, d: Ds ¼ 173:14 d2 þ 20:494 d þ 3:577 ðmaximum depth ¼ 25 mmÞ

ð3:1Þ

and Db ¼ 90:38 d2 þ 131:41 d 3:809 ðmaximum depth ¼ 44 mmÞ 3.5

ð3:2Þ

Personal and Environmental Parameters Affecting Lung Dosimetry

Absorbed doses in sensitive target cells in bronchial epithelium depend on several personal and environmental factors, which will be discussed in more detail in subsequent sections. While environmental 37


parameters can be determined on site by experimental methods for given exposure conditions, personal parameters are commonly based on average values obtained from anatomical and physiological studies. The most important personal factors affecting lung dosimetry are (1) extrathoracic, i.e., nasal and oral, geometry, (2) anatomical structure and linear airway dimensions of the lung, (3) physical activities and related breathing parameters, (4) bronchial clearance velocities, (5) spatial distribution and frequency of sensitive target cells in bronchial epithelium, (6) human subject age, and (7) smoking status. Individual variations of the structure of the nasal and oral passages in volunteers have been reported by Cheng et al. (1996), revealing significant fluctuations of the nasal cross-section and the shape of the nasal passages. Indeed, intersubject variations of measured deposition fractions could be attributed to corresponding fluctuations of these two anatomical parameters, thereby affecting the fraction of inhaled particles entering the lung. Since lung volumes can be correlated with body weight and height (ICRP, 1994), airway dimensions exhibit significant intersubject variations (Hofmann et al., 2002), which affect deposition of inhaled radon progeny and, in consequence, bronchial doses. In addition to this volumetric variability, also structural variability in terms of number of airways was observed (Hofmann et al., 2002). Physical activities and related breathing parameters, such as breathing frequency and tidal volume, determine the amount of inhaled activity per unit time as well as deposition fractions in a single breath, depending on the velocity of the airflow through the bronchial passages (see Section 3.6.1). Since daily activity patterns may be quite different among workers or members of the population at large, differences in breathing parameters may lead to a wide range of bronchial doses for identical exposure conditions. Mucociliary clearance velocities and transit times in bronchial airways are related to airway diameters and lengths and therefore reflect their intersubject variations (Asgharian et al., 2001). Indeed, Yeates et al. (1975) found significant intersubject variations of tracheal mucus velocities among a group of adult volunteers. Since bronchial mucus clearance velocities determine the distribution of nuclide-specific surface activities among bronchial airways, intersubject variations of bronchial clearance parameters will affect local doses. The thickness of the bronchial epithelium and resulting depths of sensitive target cells are related to airway diameters and thus exhibit corresponding intersubject variations (Mercer et al., 1991). Since doses to target cell nuclei are a function of their distance from the

Table 3.8. Range of depths of secretory and basal cell nuclei in bronchial (airway generations 1– 8) and bronchiolar (airway generations 9– 15) epithelium of the human lung (ICRP, 1994)


3.6 Dependence of Doses on Physical Activities (Breathing Parameters) and Age 3.6.1

Dependence on Physical Activities

Radiation doses to cells and tissues of the human respiratory tract are determined to a large extent by breathing parameters, such as the tidal volume, i.e., the air volume inhaled in a single breath, and the breathing frequency, i.e., the number of breaths per unit time, and the ventilation rate as the product of both parameters. Both tidal volume and breathing frequency are functions of the physical activity. The equivalent physical analogue normally used in deposition calculations is the flow rate, i.e., the tidal volume inhaled during the inspiration time (m3 s21). For radiation protection purposes, ICRP (1994) has defined four typical physical activities, i.e., resting (sleeping), sitting awake, light exercise, and heavy exercise, and has assigned typical parameter values for tidal volume and breathing frequency for each physical activity and for seven different age and gender classes (Table 3.9) (Note: The values for ages 3 months and 1 year were not included into this table because the dependence on physical activity is not very meaningful in small infants as they cannot control their activities). The effect of physical activity and related breathing parameters on bronchial doses reveals two specific features which act in an antagonistic fashion: The higher ventilation rate at higher physical activities relative to resting increases the inhaled amount of radon progeny in a single breath, thereby increasing the resulting doses. On the other hand, a higher flow rate at enhanced physical activities decreases the diffusion deposition efficiency of submicron radon progeny by decreasing the residence time in an airway, and thus decreasing the resulting doses (note: although deposition of larger particles by inertial impaction would increase with rising flow rate, Brownian motion dominates the deposition behavior of radon progeny). 38


operating physical deposition mechanisms are functions of the particle diameter. By the same token, the relative frequencies of the attached and unattached fractions determine the total fraction of deposited radon progeny and hence resulting bronchial doses (see Section 3.8). Deposition fractions of inhaled radon progeny depend exclusively on aerosol properties and breathing parameters and not on their activity concentrations. Thus, for defined aerosol parameters and inhalation conditions, ambient radon progeny concentrations affect bronchial doses in a proportional fashion, providing a simple relationship between bronchial dose and activity concentration.

airway surface, different target cell depths lead to different bronchial doses (see Section 3.4). Subject age affects not only the anatomical structure of the human lung but also breathing parameters (ICRP, 1994). While these changes are most apparent in the developing lung (Meńache et al., 2008) (Section 3.6.2), they have also been observed in an aging population, where a less efficient bronchial clearance may further enhance the effect of age on lung dosimetry. Epidemiological studies have demonstrated that bronchial tumors occur preferentially in smokers. Thus, the smoking status is another personal factor to be considered in lung dosimetry in addition to the well-documented carcinogenic effect of cigarette smoke. Exposure to inhaled cigarette smoke can increase the thickness of the bronchial epithelium, thereby reducing bronchial dose, but can also slow down mucus clearance velocities, change breathing parameters and the histology of the bronchial epithelium, thereby increasing bronchial doses (Baias et al., 2010) (Section 3.9.4). Albert and Lippmann (1971) and Albert et al. (1973), based on studies with inhaled radioactively labeled particles, showed that clearance in normal subjects consisted of two discrete phases of bronchial clearance. The first was completed within 1–2 h and the second within 4 – 10 h. The 90% clearance time, i.e., the time after which 90% of the inhaled particles were cleared from the lungs, were the same for both smokers and non-smokers. For comparison, Sanchis Aldas et al. (1971) measured an overall faster clearance of inhaled particles from the lung in smokers. They stated, however, that the clearance rate in the large proximal airways was slower than in nonsmokers (T1/2 ¼ 2.3 h in smokers; T1/2 ¼ 42 min in non-smokers), but faster in more peripheral airways. Several types of clearance abnormalities were observed in some subjects who smoked cigarettes or who had demonstrable lung disease. These included: (1) an extended delay in the onset of clearance or between clearance phases, (2) a spasmodic type of clearance with intermittent tracheal blockage, and (3) an extended period of clearance arrest with retrograde movement of particles from the hilar region to more distal lower lung regions (Albert and Lippmann, 1971). The most important environmental parameters affecting lung dosimetry are (1) attached and unattached size distributions, (2) attached and unattached fractions, and (3) radon progeny activity concentrations and their nuclide-specific distributions. The size distributions of inhaled attached and unattached radon progeny determine their deposition efficiencies in all airways of the human respiratory tract, from the nose to the alveolar airways, as all

Radon and Radon Progeny Inhalation and Resultant Doses Table 3.9. Reference respiratory values for a general Caucasian population at different levels of physical activity: resting (sleeping), sitting awake, light exercise, and heavy exercise. Breathing parameters are: Tidal volume VT (in l), breathing frequency f (in min21), and ventilation rate B (in m3 h21) as the product of tidal volume and breathing frequency (ICRP, 1994) Age/gender

Sitting awake

Light exercise

Heavy exercise

VT

f

B

VT

f

B

VT

f

B

VT

f

B

0.174

23

0.24

0.213

25

0.32

0.244

39

0.57

N/A

N/A

N/A

0.304

17

0.31

0.333

19

0.38

0.583

32

1.12

0.841 0.667

44 46

2.22 1.84

0.500 0.417

14 14

0.42 0.35

0.533 0.417

15 16

0.48 0.40

1.0 0.903

23 24

1.38 1.30

1.352 1.127

36 38

2.92 2.57

0.625 0.444

12 12

0.45 0.32

0.750 0.464

12 14

0.54 0.39

1.25 0.992

20 21

1.50 1.25

1.923 1.364

26 33

3.00 2.70

N/A, not applicable.

Bronchial target cell doses for different physical activity levels compiled in Table 3.10 were computed with the stochastic lung dosimetry model IDEAL-DOSE (Hofmann and Winkler-Heil, 2011; Hofmann et al., 2010). The comparison of doses produced by typical uranium mine exposure conditions (Winkler-Heil et al., 2007) has indicated that the IDEAL-DOSE code predicts slightly lower dose values than the IMBA code, based on the ICRP Human Respiratory Tract Model (ICRP, 1994). Aerosol size distributions and unattached fractions used for the physical activity calculations refer to typical indoor exposure conditions without smoking (Marsh et al., 2005) (Note: smoking affects the activity size distribution of the attached radon progeny as well as the unattached fraction). The results listed in Table 3.10 exhibit a consistent trend: For all ages, doses increase with rising physical activity from resting to heavy exercise by about one order of magnitude. This further indicates that the effect of increased ventilation rates clearly surpasses the effect of reduced deposition efficiencies. However, with increasing physical exercise, most humans switch from nasal breathing to partly oral breathing (ICRP, 1994), which slightly reduces the filtration efficiency of the extrathoracic region. Furthermore, the strong dependence of lung doses on breathing rate emphasizes the importance of reporting the physical activity related to a given radon measurement site. Thus, information on the radon or radon progeny activity concentration without reporting the associated physical activity pattern is insufficient for the correct assessment of individual lung doses.

3.6.2

Table 3.10. Effective dose conversion coefficients (mSv WLM21) for different levels of physical activity under typical indoor exposure conditions Age/ gender

Resting (sleeping)

Sitting awake

Light exercise

Heavy exercise

5 year 10 year Male Female 15 year Male Female Adult Male Female

8.5

12.4

27.8

N/A

6.0 6.0

7.6 7.6

31.7 31.7

80.6 63.2

4.8 4.5

5.7 5.1

21.7 23.5

57.7 58.2

4.4 3.6

5.5 4.3

18.7 19.2

46.2 52.1

N/A, not applicable.

childhood to adulthood have been reported. Phalen et al. (1985) made limited measurements of about 25 airways per cast provided by Mortensen et al. (1983) and used these measurements to develop their model of conducting airway dimensions as a function of age. Using equations developed in Phalen et al. (1985) for airway length and diameter as a function of height, Phalen and Oldham (2001) examined the deposition of particles in the bronchial and pulmonary regions of the lung for different ages. Mortensen et al. (1983; 1989) prepared silicon rubber casts of the lungs of a large number of children and made complete measurements of the conducting airways. Although limited by the lack of any airway measurements distal to the 10th generation, this database is unique in having complete length, diameter, and branching angle information on approximately 1000 airways in the first 10 generations.

Dependence on Age

Only a few measurements of the anatomical dimensions for the normal developing human lung through 39


5 year 10 year Male Female 15 year Male Female Adult Male Female

Resting (sleeping)


Based on the ICRP Human Respirator Tract Model (ICRP, 1994), Marsh et al. (2005) calculated dose-exposure conversion coefficients for typical home exposure conditions (Marsh et al., 2002) for ages ranging from 3 months to adulthood. The reported effective dose coefficients refer to two indoor exposure conditions: (i) typical home without smokers, and (ii) typical home with smokers. Values for the house with smokers were calculated assuming that subjects were in a smoke-filled living room, except while they were sleeping in a smoke-free bedroom. For the dose calculations presented in Table 3.11 (Marsh et al., 2005), the following parameters were assumed to be age-dependent: (1) Mass of the target tissue. (2) Respiratory frequency and tidal volume for each level of physical activity (see Table 3.9). (3) Average time spent at each level of exercise. (4) Lung capacities, such as functional residual capacity (FRC), regional dead spaces, and diameters of the trachea and of generations 9 and 16.

The effect of smoking on the exposure conditions and resulting lung doses in homes should be considered in epidemiological studies, involving nonsmoking members of the family living in the same house as smoking members. Harley (1984) calculated the bronchial dose in mines for the adult male, and in residences for the adult male, female, 10, and 1 year old. This calculation used Yeh and Schum (1980) lung dimensions with modifying (scaling) factors of 1.0, 0.76, 0.5, and 0.33, respectively. Calculated dose conversion coefficients in Table 3.11. Effective dose-exposure conversion coefficients (mSv WLM21) for different ages under typical home exposure conditions, differentiating between the effects of unattached and attached radon progeny (Marsh et al., 2005) Effective dose conversion coefficient (mSv WLM21) Age/gender

3 months 1 year 5 year 10 year 15 year Male Female Adult Male Female

40

Home without smokers

Home with smokers

Unatt.

Att.

Total

Unatt.

Att.

Total

2.6 3.4 3.7 4.9

7.0 7.9 7.6 8.6

9.6 11.3 11.3 13.5

1.7 2.4 2.3 2.4

6.5 7.4 7.1 8.0

8.2 9.8 9.4 10.4

4.1 4.1

7.3 7.4

11.4 11.5

2.3 2.0

6.7 6.8

9.0 8.8

4.8 4.7

8.1 8.0

12.9 12.7

2.4 2.0

7.5 7.2

9.9 9.2


Meńache et al. (2008) developed single-path wholelung models and lobar models of the lungs of 11 children between 3 months and 21 years of age based on a combination of the Mortensen et al. (1983; 1989) data and published information on distal airway dimensions. As of today, these morphometric models represent the most detailed airway geometries for particle deposition modeling purposes. Since the growth of tracheobronchial and pulmonary regions of the human lung has not been systematically measured, Hofmann (1982a; 1982b) pursued a different modeling approach: he assembled many measurements of the upper airways from different authors, extrapolated the systematic features identified there to the lower airways, and incorporated them together with limited data on the pulmonary airway into a mathematical description of the growing lung (Hofmann et al., 1989a, 1989b; Martonen et al., 1989). This age-dependent model is based on the structure of Weibel’s (1963) Model A, which describes the tracheobronchial tree by 17 symmetrically dividing generations. For comparison, the bronchial airway model published by Phalen et al. (1985) is based on the relatively few complete bronchial pathway measurements made in a single lobe and the findings extrapolated to all other lobes, based on the bronchial airway structure of the Yeh and Schum (1980) lung model. While the above airway generation models are partly based on measured morphometric data, particle deposition for different ages in the ICRP Human Respiratory Tract Model (ICRP, 1994) is modeled by applying age-specific modifying factors in the algebraic deposition efficiency equations for each lung compartment. These modifying factors were specified for the following ages: 3 months, 1, 5, 10 and 15 years (male and female), and adult (male and female) The effect of morphometric and physiological changes of the lung on doses to tracheobronchial and alveolar compartments was first described by Hofmann et al. (1979). This model was subsequently refined by replacing the compartmental system of the lung by the airway generation structure of Weibel’s Model A (1963) and bronchial generation doses to bronchial basal cells were computed for typical age-specific physical activity patterns (Hofmann, 1982a; Hofmann et al., 1989a). Height and weight can be used to scale physiological, respiratory, and morphometric lung parameters by allometric equations (ICRP, 1994). For example, allometric relationships have been published for the total lung capacity (TLC) as function of height and age, and tidal volume (VT) as function of weight (ICRP, 1994). Examples of variations of respiratory values for ethnic groups, such as Japanese, Chinese, Indian, African American, Senegalese, and Zimbabwian, are also listed in the ICRP (1994) report.


residences were 8, 10, and 18 mSv WLM21 for daily active and resting breathing cycles of 16 and 8 h for males, females, and the 10 year old. The calculated bronchial dose for the 1 year old was 14 mSv WLM21 assuming a constant daily breathing rate. These dose calculations reveal that doses to sensitive bronchial and bronchiolar cells do not vary appreciably with age, exhibiting a slight maximum at the age of about 10 years. For comparison, previous calculations with an airway generation model revealed a dose maximum at the age of about 4 years (Hofmann, 1982a). This difference is primarily caused by the definition of age-specific physical activity patterns, which affect the age-dependency of dose calculations (Hofmann et al., 1989b). The age-dependency of bronchial doses for defined average age-specific physical activities can also be seen in Table 3.10, based on computations with the stochastic IDEAL-DOSE model. There, doses decrease monotonously with rising age for each physical activity, indicating that children might receive higher doses than adults when exposed to the same exposure characteristics. This emphasizes the importance of radon measurements in schools. Note that the relatively weak dependence on age shown in Table 3.11, as opposed to the distinctly decreasing relationship with age illustrated in Table 3.10, is caused by the application of typical age-specific daily physical activity patterns, which are characterized by higher physical activities in adults when compared with children. In conclusion, the age-dependency of lung doses for defined physical activities predicted by different dosimetric models depends on assumptions regarding lung morphology, breathing parameters, mucociliary clearance velocities, and target cell depths for the different ages, as illustrated by the application of two different dosimetry models in Tables 3.10 (IDEAL-DOSE model) and 3.11 (ICRP model). Thus, documented variations in the morphology of the developing lung and related respiratory parameters introduce some uncertainties in radon progeny lung dosimetry, which may be comparable with the inherent biological intersubject variability (see Section 3.9.2).

† the dissociation of the particles into a material that can be absorbed into blood (i.e., dissolution), and † the uptake of material dissolved from particles, or material deposited in a soluble form. To represent time-dependent dissolution, it is assumed that a fraction (fr) dissolves rapidly at a rate sr while the remaining fraction (1 2 fr) dissolves more slowly at a rate ss. Uptake is usually assumed to be instantaneous, but for some elements, a fraction of the dissolved material is absorbed more slowly as a result of binding to the respiratory tract components. To represent time-dependent uptake, a fraction, fb, of the dissolved material is assumed to be retained in a bound state, from which it is transferred into blood at a rate sb, while the remaining fraction (1 2 fb) transfers to blood instantaneously. Because the bound state is considered to represent the interaction of an element in dissociated (ionic) form with cells forming the lining of the respiratory tract, the bound fraction fb and uptake rate sb are assumed to be element-specific. Bound material is not subject to particle transport. In the late 1960s experiments in which volunteers inhaled 212Pb ions, unattached or attached, to condensation nuclei gave overall absorption half-times from lungs to blood of about 10 h (Booker et al., 1969; Hursh and Mercer, 1970; Hursh et al., 1969; Marsh and Birchall, 1999a; 1999b). For simplicity and for dosimetry purposes, calculations were typically performed assuming that the 222Rn progeny (218Po, 214Pb, and 214Bi) are absorbed with a halftime of 10 h. Sensitivity analysis showed that the lung dose is sensitive to the absorption rates of the radon progeny if the assumed absorption half-times are less or comparable with their radioactive halflives (Marsh and Birchall, 2000; Zock et al., 1996). For example, it has been shown that the equivalent dose to the lung is reduced by more than 10% if the absorption half-time is less than 8 min for 218Po or less than 2 h for 214Pb or 214Bi compared with the assumption of a 10 h absorption half-time (Marsh and Birchall, 2000). Marsh and Bailey (2013) reviewed animal and volunteer data to determine lung-to-blood absorption rates for radon progeny. As stated above early experiments in which volunteers inhaled 212Pb ions, gave overall absorption half-times from lungs to blood of about 10 h. Animal experiments designed to investigate the clearance kinetics of lead ions in detail

Dependence on 222Rn Progeny Absorption Parameters

Particles deposited in the respiratory tract are cleared by two competitive processes: absorption to blood and particle transport to the alimentary tract and lymphatics. In the HRTM (ICRP, 1994), it is assumed that particle transport rates are the same for all materials, whereas absorption into blood is 41


3.7

material specific. The model assumes that the rate of absorption is the same in all regions of the respiratory tract except in the anterior nose (region ET1) where none occurs. The HRTM treats absorption to blood as a two-stage process:


showed two phases of absorption: about 10% is absorbed with a half-time of about 10–15 min, the rest with a half-time of about 10 h. Most studies in which the volunteers inhaled unattached 212Pb or 212 Pb attached to condensation nuclei suggest that if there is a rapid absorption component then this is likely to be only 5%. However, the volunteer data of Butterweck et al. (2002) suggest that unattached lead is more soluble; about 30% is rapidly absorbed to blood with a faster rate (sr . 100 d21). Experimental evidence was found supporting the existence of a bound fraction for lead. Lead ions deposited on nasal or bronchial epithelium of rats and rabbits cleared more slowly than insoluble particles deposited simultaneously. Similar half-times associated with slow uptake of lead in different ionic forms (e.g., nitrate, hydroxide, chloride) suggest that this is associated with binding (a characteristic of the element) rather than dissolution (a characteristic of the chemical form of the element). Estimated values of bound fraction from animal and volunteer studies ranged from 0.2 to 0.8 (Marsh and Bailey, 2013). The volunteer studies of Booker et al. (1969) indicated that unattached and attached 212Pb have similar absorption characteristics. This suggests that the attached 212Pb rapidly separates from its host following deposition in the respiratory tract. Rapid separation could occur because of alpha recoil and/or physiochemical interactions with the lung fluid. Booker et al. (1969) noted that “The attachment of 212 Pb to nuclei seems to be irreversible in air, but autoradiographs have shown (Heard, 1968) that the activity is largely desorbed in aqueous media” (Heard, 1968 personal communication). Based on these data and other experimental evidence, Marsh and Bailey (2013) assumed that the unattached and attached radon progeny have the same absorption characteristics. In the forthcoming Occupational Intakes of Radionuclide (OIR) document of the ICRP, for the purposes of dosimetry, specific absorption parameter values will be given for polonium, lead, and bismuth inhaled as a decay product of radon. In the preparation of this document, the ICRP Task Group on Internal Dosimetry (INDOS) has proposed absorption parameter values for radon progeny, which are given in Table 3.12. The parameter values chosen for lead as a decay product of radon are consistent with the values suggested by Marsh and Bailey (2013) based on their review. Neglecting particle transport, about 5% of the deposit [i.e., fr(1 2 fb)] is absorbed to blood rapidly with a half-time of 10 min, while the remainder is absorbed with a half-time of about 10 h. The fraction of the dissolved material, fb which is assumed to be bound is 0.5. The absorption parameter values chosen for bismuth were based on

Table 3.12. Values of the absorption parameters of the HRTM for inhaled radon progeny proposed by the ICRP Task Group on Internal Dosimetry (INDOS) Inhaled radon progeny

Polonium Lead Bismuth

Dissolution parameter values

Uptake parameter values

fr

sr (d21)

ss (d21)

fb

sb (d21)

1 0.1 1

3 100 1

— 1.7 —

0 0.5 0

— 1.7 —

the analysis of the volunteer data of Hursh et al. (1969) (Marsh and Birchall, 1999a; 1999b). In this study, volunteers were exposed to an aerosol of 212Pb and 212Bi attached to “natural” particles in room air and the amount of 212Bi excreted in urine was reported for one of the volunteers. The equivalent dose to lung and the effective dose calculated with the absorption parameter values given in Table 3.12 are only a few percent greater than the value obtained assuming a single absorption half-time of 10 h with no binding (Marsh and Bailey, 2013).

3.8 3.8.1

Dependence on Radon Progeny-Related Aerosol Parameters Radon Progeny Aerosol Parameters

The size distribution of an inhaled aerosol is one of the factors that determine the fraction of the intake that is deposited in each region of the respiratory tract. Deposition depends on the particle’s size as well as the subject’s breathing pattern and the geometry of the respiratory tract. A further consideration is that some of the ambient aerosols, to which radon progeny attach, are unstable in saturated air and grow very quickly on inhalation due to the high humidity in the respiratory tract (NA/NRC, 1991; Sinclair et al., 1974). For simplicity, this is generally modeled by assuming that the attached aerosol instantaneously grows by a given factor as the aerosol enters the nose or the mouth, while the size of the unattached progeny is assumed to remain constant in the respiratory tract (NA/NRC, 1991). The equivalent dose to the lung arising from the inhalation of short-lived radon progeny is directly proportional to the amount deposited in the bronchial (BB) and bronchiolar (bb) regions of the lung. However, despite the higher deposition fractions of attached radon progeny in alveolar airways, the dose to the BB and bb regions is much greater than 42


Rapid dissolution fraction fr, rapid dissolution rate, sr, slow dissolution rat, ss, bound fraction, fb.


dth

sffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi x Cðdae Þ ¼ dae r Cðdth Þ

ð3:3Þ

where C(dae) is the slip correction for a particle of aerodynamic diameter, dae, and C(dth) is the slip correction for a particle of thermodynamic diameter, dth. Note: examples of size distributions are given in Section 4.7. Porstendo¨rfer (2001) and his co-workers mainly carried out activity size measurements of the attached progeny with a low-pressure cascade impactor. However, some measurements in closed rooms without additional aerosol sources were carried out with both a low-pressure cascade impactor and a diffusion battery, which measures the thermodynamic diameter (Reineking et al., 1988; 1992a). Comparisons of these measurement results show that the value of the activity median thermodynamic diameter (AMTD) was similar to that of the activity median diameter (AMD) measured with the low-pressure cascade impactor with the differences being less than about 10%. Such differences are small compared with the uncertainties of the data evaluation procedure and the normal variation in the size distribution under realistic working or living conditions. For indoor measurements, it can therefore be assumed that the values of AMD determined with low-pressure cascade impactors are good approximations to the corresponding values of AMTD. Some authors have used Equation (3.3) to calculate the corresponding values of dth from the dae of the attached progeny measured with low-pressure cascade impactors. For such purposes, values of 1.4 g cm23 and 1.1 were assumed for r and x, respectively, under normal conditions in homes and buildings (Marsh et al., 2002; Reineking et al., 1988). The density and shape factor of the unattached progeny are generally assumed to be unity for dosimetry purposes. 43


deposition ffiffiffiffiffiffiffiffiffiffiffiffiffiffi by diffusion increases with the quotient p tR =dth (NA/NRC, 1991). Diffusion batteries measure dth, whereas lowpressure cascade impactors measure dae (see Section 5.3.4.2). The two diameters, dth and dae, are related via the particle density (r) and the shape pffiffiffiffiffiffiffiffifactor (x). For a first approximation, dth ¼ dae x=r. However, for small particles (dth, 1 mm) whose size approaches the mean free path of air molecules, the viscous drag is reduced and therefore the settling velocity increases. To take account of this, the slip correction (often called the Cunningham factor) needs to be applied to the above equation (Hinds, 1982; ICRP, 1994; Willeke, 1976) as follows:

that of the AI region because the mass of the target tissue in the BB and bb region are small (a few grams) compared with the mass of the alveolar– interstitial (AI) region (1 kg) (ICRP, 1994). To understand how the deposition in BB and bb depends on the aerosol parameters, it is necessary to describe the mechanisms of aerosol deposition in the respiratory tract. There are three major mechanisms, namely gravitational sedimentation, inertial impaction, and diffusion. In gravitational sedimentation, the particle falling under gravity experiences a viscous resistive force of the air, which increases as the particle accelerates. As a result, the particle reaches a constant velocity (i.e., the settling velocity) when the viscous force of the air is equal and opposite in direction to the gravitational force. The magnitude of the settling velocity depends on the physical size of the particle, its shape, and density. This settling can lead to deposition on respiratory surfaces and the probability of deposition increases with tR d2ae , where tR is the residence time and dae is the aerodynamic diameter (NA/NRC, 1991). The aerodynamic diameter is defined as the diameter of a unit density sphere that has the same terminal settling velocity in air as the particle of interest. Generally, gravitational sedimentation is important for particles with dae greater than about 0.5 mm. When an airstream carrying a particle is forced to change direction because of an obstacle, the inertia or momentum of the particle resists the change of direction. If the momentum is high enough, the particle will continue in its original direction and deposit on the obstacle. High linear velocities and abrupt changes in the direction of airflow occur in the nasal passages, pharynx, and at central airway bifurcations. The probability of deposition by inertial impaction increases with the product of d2ae and the respired flow rate. Generally, inertial impaction is important for particles with dae greater than about 2 mm (NA/NRC, 1991). Diffusion (i.e., Brownian motion) is the random motion of an aerosol particle caused by collisions with gas molecules. This motion can lead to contact with and deposition on respiratory surfaces. Diffusion is the dominant mechanism of deposition in the airways for small particles of less than 0.5 mm and is therefore important for radon progeny aerosols. Unlike gravitational sedimentation and inertial impaction, diffusion is independent of particle density. This means that dae is not a direct measure of diffusion and therefore for small particles, the size is best expressed in terms of the thermodynamic diameter. The thermodynamic diameter, dth, is defined as the diameter of a spherical particle that has the same diffusion coefficient in air as the particle of interest. The probability of


Figure 3.2. Regional deposition as a function of particle size calculated with the HRTM for a standard worker: blue continuous line, bronchial (BB) region; continuous line, bronchiolar (bb) region; dashed line, 1/2 ET equals half of the deposition in the extrathoracic (ET) region, approximating deposition during the inhalation phase (note: filtration in the ET region affects the fraction of particles entering the lung). Unit density and unit shape factor were assumed.

is the dominant deposition mechanism in this range. Initially, deposition in BB and bb increases between 0.6 nm and about 4 nm as more of the aerosol passes through ET. Deposition in BB and bb then decreases with particle sizes for dth , 400 nm as less is deposited by diffusion. As can be seen from Figure 3.2, the amount deposited in BB and bb is most sensitive to particle diameters in the unattached range (0.3 – 5 nm) and in the nucleation range (10 –100 nm). In comparison, it is less sensitive to particle diameters in the accumulation range (100 –500 nm). Note: examples of activity size distributions are given in Section 4.7. The dependence of the effective dose per WLM on particle size is displayed in Figure 3.3, calculated with the HRTM for a standard worker. As expected,

Figure 3.3. Effective dose per WLM as a function of particle size calculated with the HRTM for a standard worker. Unit density and unit shape factor was assumed.

44


To take account of the hygroscopic growth of attached progeny in the respiratory tract, it is generally assumed that dth increases by a factor between 1.0 and 2.0 as the particle enters the nose and mouth (James et al., 2004; Marsh et al., 2002; 2005; NA/NRC, 1991; Porstendo¨rfer and Reineking, 1999). Sinclair et al. (1974) found that atmospheric particles in their laboratory increased in diameter by about a factor of 2 when the relative humidity increases from 0 to 98%. The ambient aerosol originated from an industrial area close to the sea and the authors expected it to consist of a mixture of NaCl and (NH4)2SO4 salts with a mixture of acids (HNO3, H2SO4, and HCl). Based on this work, a panel of experts from the National Research Council assumed for dosimetry purposes a hygroscopic growth factor of 2 and that the density and the shape factor of these hygroscopically enlarged particles were both unity (NA/NRC, 1991). Li and Hopke (1993) measured hygroscopic growth factors of indoor combustion aerosols including cigarette smoke, incense smoke, candle flame, natural gas flame, and propane fuel flame. The average growth factors ranged from 1.5 to 1.9. In contrast, radon progeny attached to diesel particles or to an aerosol produced from cooking oil, for example, are hydrophobic (Dua and Hopke, 1996; Dua et al., 1999; Weingartner et al., 1997). Computed growth curves of NaCl particles reveal that hygroscopic particles below about 500 nm reach their equilibrium diameter already within the mouth/nose and the large bronchial airways (Ferron et al., 1988; Winkler-Heil et al., 2014). This suggests that the hygroscopic growth of unattached and attached radon progeny can be modeled by a constant equilibrium growth factor throughout the whole respiratory tract. In other words, deposition of hygroscopic radon progeny can be calculated for the equilibrium diameter, thereby greatly simplifying deposition calculations for hygroscopic particles. For illustrative purposes, Figure 3.2 shows the regional deposition, i.e., the fraction of inhaled particles deposited in a given region, as a function of particle diameter calculated with the HRTM (ICRP, 1994). Unit density and shape factor was assumed for simplicity. To model deposition in the HRTM semi-empirical equations based on experimental deposition data were used. However, a theoretical model of gas transport and particle deposition was used to calculate the fractional deposition in BB, bb, and AI regions of the lung. This was evaluated by considering aerodynamic (gravitational sedimentation, inertial impaction) and thermodynamic (diffusion) processes acting competitively. The deposition in the extrathoracic (ET) region decreases with particle size in the range 0.6 – 100 nm because diffusion


it has a similar shape to Figure 3.2, which gives the fractional deposition in the central airways (BB and bb regions) as a function of particle size. 3.8.2

fraction (fp) was approximated by: Effective dose per WLM ¼ 11:35 þ 43 fp mSv WLM1

ð3:4Þ

Sensitivity of Lung Dose from Inhalation of 222Rn Progeny to Aerosol Parameter Values

For fp ranging from 0.04 to 0.2, the effective dose per WLM varies from 13 to 20 mSv WLM21 [3.7 –5.6 mSv per (mJ h m23)]. Equation (3.4) can also be expressed in terms of dose per unit radon (222Rn) gas exposure: Effective dose per ðBq h m3 Þ ¼ 1:57 106 F 11:35 þ 43 fp mSv ðBq h m3 Þ1 ð3:5Þ Equation (3.5) follows from 3.4 as 1 WLM approximately equals (6.37 105/F) Bq h m23 of 222Rn gas exposure. The activity size distribution of the radon progeny depends on the exposure conditions. Results of calculations performed with the HRTM to approximate the effective dose per unit exposure to radon progeny for different exposure conditions are given in Table 3.13. The variation in doses for the home environment [10–21 mSv WLM21; 2.8 –5.9 mSv per (mJ h m23)] and for the workplace [11–26 mSv WLM21; 3.1 –6.3 mSv per (mJ h m23)] is due to

Table 3.13. Values of effective dose per unit exposure to 222Rn progeny calculated with the HRTM for different exposure scenarios Exposure scenario

Adults at homeb Home without cigarette smoke

Home with cigarette smoke Workplaceb Indoors With air conditioning on With air cleaner on Mines

Effective dose per unit exposurea

Publication

mSv WLM21

mSv (mJ h m23)21

Marsh and Birchall (2000) James et al. (2004) Marsh et al. (2005) James et al. (2004) Marsh et al. (2005)

15 21 13 16 –18 10

4.2 5.9 3.7 4.5–5.1 2.8

Harrison and Marsh (2012) Tokonami et al. (2003)

21 20 22 –24 56 16c – 26d 18 –21 12.5 (9c –13.5f ) 11c

5.9 5.6 6.2–6.8 16 4.5c –7.3d 5.1–5.9 3.5 (2.5c –3.8f ) 3.1c

Solomon et al. (1994) James et al. (2004)e Marsh et al. (2005) Harrison and Marsh (2012)

a

1 WLM ¼ 3.54 mJ h m23. An average breathing rate of 0.78 m3 h21 was assumed for an adult at home and a value of 1.2 m3 h21 for a standard worker. c For diesel-powered mines with diesel engines in operation. d For non-diesel areas of mine. e Calculations were performed with a time-weighted mean activity size distribution obtained from measurements in four different work areas of diesel-powered mines (NA/NRC, 1999a). f Without working actions. b

45


Marsh and Birchall (2000) performed a sensitivity analysis with the HRTM to identify those aerosol parameters that have most influence on lung dose arising from the inhalation of 222Rn progeny under the conditions found in houses. In this analysis, it was assumed that the size distribution of the attached progeny had been measured with a lowpressure cascade impactor and was therefore given in terms of the aerodynamic diameter. The aerosol parameters that most affected the equivalent dose to the lung per WLM were the unattached fraction, the activity median aerodynamic diameter (AMAD) of the nucleation mode, and the fraction of the attached Potential Alpha Energy Concentration (PAEC) associated with the nucleation mode. In contrast, the parameters that had little effect on the lung dose per WLM include parameters related to the coarse mode, the density and shape factor of the unattached and accumulation mode particles, and the equilibrium factor. For an adult at home, the effective dose per WLM as a function of unattached


Effective dose per WLM ¼ 6:1 þ 42 fp mSv WLM1

ð3:6Þ This gives a value of 10 mSv WLM21 [2.9 mSv per (mJ h m23)] with fp ¼ 0.1, which is lower than the corresponding value of 16 mSv WLM21 [4.4 mSv per (mJ h m23)] calculated with the HRTM [Equation (3.4)].

3.9

Variability and Uncertainty of Individual Lung Doses

3.9.1

Comparison of Results from Different Lung Dosimetry Models

Deterministic and stochastic models have been published in the past which permit the calculation of radon progeny doses to bronchial airway generations, the pulmonary region, and the dose to specific lung cancer target cells in each region. UNSCEAR (2008) summarized 13 principal bronchial dose models for radon progeny, published between 1956 and 1998, to determine a central value (Table 3.14). Dose factors are expressed in this table in terms of the equilibrium equivalent radon activity concentration. The wide 46


range of values from 5.7 to 71 nGy (Bq h m23)21, with an average value of 17.5 nGy (Bq h m23)21 illustrates model-specific differences in assumptions regarding unattached fraction, breathing rates, bronchial clearance mechanisms, and target cell depths as well as on the application of different morphometric models. Effective dose coefficients proposed by modeling efforts published after the publication of the UNSCEAR (2008) report are listed in Table 3.15 for uranium mining exposure conditions. Here, effective dose conversion coefficients are expressed in terms of the cumulative exposure to radon progeny in WLM. Dosimetry models comprise generation-based models and the compartmental ICRP (1994) model as well as deterministic and stochastic models. Compared with the wide range of dose factors listed in Table 3.14, the effective dose conversion coefficients shown in Table 3.15 are relatively similar to each other. In summary, the various parameters included in the models rely on relatively well-documented anatomical values such as airway dimensions, breathing rates, mucous clearance rates, and target cell depths. Other physical parameters that estimate exposure conditions such as unattached fraction, aerosol particle diameters are assumed conditions and vary significantly. One uncertainty calculation derived from published bronchial dose model parameter values is reported in NCRP Report No. 164 (NCRP, 2009). This Monte Carlo uncertainty derivation assumed that all model parameter values have a lognormal distribution. The analysis (NCRP, 2009) resulted in an overall arithmetic mean of 10 mSv WLM21 with SD of 5, and a geometric mean of 9 mSv WLM21 with GSD of 1.6. The dose conversion coefficient derived from modeling parameter uncertainties has a relatively large error, thus the potential for error term reduction exists. Marsh et al. (2002) carried out a parameter uncertainty analysis with the HRTM to calculate the probability distribution of the equivalent dose to the lung (wlung Hlung) per unit exposure to radon progeny in the home. It was assumed that the HRTM is a realistic representation of the physical and biological processes, and that the parameter values are uncertain. The parameter probability distributions used in the analysis were based upon published data and on expert judgment. Parameters considered include: (i) aerosol parameters, (ii) subject-related parameters such as breathing rate, fraction breathed through the nose, and particle transport rates, (iii) target cell parameters such as depth of basal and secretory cell layer, and (iv) absorption rates of attached and unattached radon progeny. The resulting distribution was approximately lognormal with a geometric mean of 14 mSv

different assumptions of the aerosol parameter values. For an indoor workplace with an air cleaner in operation, the unattached fraction was high (fp ¼ 0.56) resulting in a calculated effective dose of 56 mSv WLM21 or 16 mSv per (mJ h m23). Although, there was a reduction in the radon progeny activity concentration by the use of an air-cleaning device, the increased fp value showed that the air cleaner was not effective for dose mitigation (Tokonami et al., 2003). The calculations of James et al. (2004) used the reference activity size distributions for homes and mines given in the BEIR VI report (NA/NRC, 1999a). For the home, this was based on measurements carried out by Hopke et al. (1995) in six houses in the USA and Canada. Size distributions were recommended for homes with and without cigarette smoke. The resulting estimates of effective dose per unit exposure [16-21 mSv WLM21; 4.5–5.9 mSv per (mJ h m23)] were higher than those calculated by Marsh et al. (2005) [10– 13 mSv WLM21; 2.8 – 3.7 mSv per (mJ h m23)] based on activity size measurements carried out in Europe (Table 3.13). Porstendo¨rfer (2001), using an airway generation model developed by Zock et al. (1996), calculated the effective dose per unit exposure as a function of fp for different workplace scenarios and for a home. For example, the effective dose per WLM for an adult at home was given as:

a

0.8

1.2 Basal

1.2 1.1 Basal 0.9 1.2 Basal

0.9 Basal Basal 0.9 Basal 1.2

1.2 1.2

Breathing rate (m3 h21)

Bronchial cells: Basal (35 –50 mm), secretory (10–40 mm) Bronchiolar cells: secretory (4–12 mm)

Cells (27 mm)

Mean epithelium Cells (22 mm) Mean epithelium Cells (35–50 mm)

Average in 45 mm epithelium Mean TB region Basal cells (30 mm) Cells (22 mm) Cells (30 mm) Cells (22 mm) Mean epithelium

Target region

Cast of trachea and bronchi Deposition retention assumptions Findeisen/Landahl 6-region anatomical model Findeisen/Landahl 6-region anatomical model Weibel dichotomous airway model Weibel dichotomous airway model Weibel dichotomous airway model, correction for upper airway turbulent diffusion [M2] Yeh-Shum anatomical model [Y2] Same as Jacobi and Eisfeld [J2] Same as Jacobi and Eisfeld [J2] Yeh-Shum anatomical model [Y2], correction for upper airway turbulent diffusion Nikiforov and Schlesinger [N12] anatomical model, airway deposition from empirical data from human airway casts ICRP lung model [11]

Model type

Per unit 222Rn concentration (EEC). WLM converted to Bq h m23 using 0.27 1023 WL (Bq m23)21 and 170 h per working month.

0.08

1998 Marsh and Birchall [M2]

0.1 0.07 0.2 0.16 0.1

Janies et al. [J6] Harley and Pasternack [H6] Hofmann [H10] National Research Council [N10]

1980 1982 1982 1991

0.09 0.1 0.25 0.085 0.35 0.04 0.1

Unattached fraction

Parameter values


47

1996 Harley et al. [H4]

Chamberlain and Dyson [C1 ] ICRP [14] Jacobi [Jl] Altshuler et al. [A3] Haque and Collinson [H3] Harley and Pasternack [H5] Jacobi and Eisfeld [J2]

1956 1959 1964 1964 1967 1972 1980

Year Investigator

8.5 19 14

9

14 6.4 11 21

11 6.7 24 32 71 5.7 8.9

Dose factora [nGy(B q hm23)21]

Table 3.14. Doses from deposited radon progeny derived from principal dose models (UNSCEAR 2008). For the individual references listed in this table, the reader is referred to the UNSCEAR report



of Falk et al. (1997; 1999). However, the lung dose arising from exposure to radon progeny is not very sensitive to the bronchial clearance rates as the progeny are short-lived compared with these halftimes (Marsh and Birchall, 2000). Therefore, lung doses calculated with the revised model will not be significantly different for radon progeny. Effective doses per unit exposure to radon progeny calculated with the revised model for home and mine exposures were about 13 and 11 mSv WLM21, respectively (Marsh and Bailey, 2013).

Table 3.15. Comparison of effective doses per WLM obtained with different lung dosimetry models for uranium mining exposure conditions Effective dose conversion coefficients (mSv WLM21)

Harley (1984) Winkler-Heil et al. (2007)

6.9 (working þ diesel) 8.3 (RADOS) 8.9 (mean) (IDEAL-DOSE) 7.8 (median) (IDEAL-DOSE) 12.5 (HRTM; ICRP 1994) 10.6 (revised HRTMa) 11.5 (without sources) 11.2 (with sources) 5.7 (plus coarse aerosol) 9.0 (working þ diesel) 6.7 (without working) 8.9

Marsh et al. (2005) Marsh and Bailey (2013) Porstendo¨rfer (2002)

Porstendo¨rfer and Reineking (1999) Average value

3.9.2

Intra- and Intersubject Variability

In radiation protection, bronchial doses are routinely calculated for a standard or reference man by assuming defined average values for all anatomical and physiological parameters involved in radon lung dosimetry, therefore providing a single dose value for specified exposure conditions. In reality, however, these anatomical and physiological parameters can vary significantly within a given subject (intra-subject variability) or among different subjects (inter-subject variability), hence predicting a range of bronchial doses for the same exposure conditions. For example, sources of intra-subject variability are the asymmetry and variability of linear airway dimensions in bronchial and alveolated airways (Koblinger and Hofmann, 1985; 1990), mucociliary clearance velocities and transit times in bronchial airways (Hofmann and Sturm, 2004) and the location of target cells throughout the bronchial epithelium (Harley et al., 1996; Mercer et al., 1991). Sources of inter-subject variability are breathing parameters for defined physical activities (ICRP, 1994), daily physical activity patterns (ICRP, 1994), size and structure of nasal and oral passages (Cheng et al., 1996), size of the lung (FRC) (Hofmann et al., 2002), tracheobronchial mucociliary clearance rates (Yeates et al., 1975), and thickness of bronchial epithelium (Mercer et al., 1991). Hofmann et al. (2010) carried out an uncertainty analysis with a stochastic airway generation model to derive the frequency distribution of bronchial doses per WLM taking account of inter- and intra-subject variability, while aerosol parameter values were fixed for a mine atmosphere. In the stochastic dose model, inter-subject variability of bronchial doses was defined as the effect of morphological and physiological parameter variations on bronchial doses among a group of subjects for defined exposure conditions, where each subject is characterized by a dose distribution due to intra-subject variations. The primary biological parameters contributing to the intra- and inter-subject variability of bronchial doses were the variability of the extrathoracic and thoracic airway structure and airway dimensions, random variations of breathing

a

Calculated with the revised Human Respiratory Tract Model (HRTM) (Bailey et al., 2009). A full description of this model will be given in the ICRP Publication on “Occupational Intakes of Radionuclides, Part 1.”

WLM21 and a geometric standard deviation of 1.5. The limits of the 95% confidence interval corresponded to 6.3 – 31 mSv WLM21. Birchall and James (1994) also carried out a parameter uncertainty analysis with the HRTM to calculate the distribution of effective doses per unit exposure to radon progeny in a mine and obtained similar results for the statistical parameters of the dose distributions. To obtain an indication of the uncertainty caused by the structure of the human respiratory tract model, Winkler-Heil et al. (2007) compared predicted effective doses for radon progeny inhalation obtained using the HRTM, a deterministic airway generation model and a stochastic airway generation model. The same input parameter values were assumed for mine conditions. The three models yielded similar results, ranging from 8.3 to 11.8 mSv WLM21 (2.3 – 3.3 mSv per mJ h m23). The authors noted that one of the important issues affecting the comparison is the averaging procedure for the doses calculated in airway generation models. ICRP has recently updated the ICRP Publication 66 Human Respiratory Tract Model (ICRP, 1994) to take account of more recent data, mainly from volunteer studies (Bailey et al., 2009). Changes relate to particle transport from the nasal passages, bronchial tree, and alveolar region. In particular, the slow particle clearance component with a 23 d halftime assumed for the bronchial and bronchiolar regions has been revised. It is now assumed that slow particle clearance from the bronchial tree only occurs in the bronchiolar region with a half-time of about 3.5 d, which is based on the volunteer studies 48


Authors


3.9.3

inhomogeneous dose distributions within airway bifurcations. To illustrate this dose inhomogeneity, doses were calculated for three selected sites within an asymmetric bifurcation: T (carinal ridge), R1 (cylindrical section), and R2 (curved transition zone). For a cumulative exposure of 20 WLM, typical for residential radon exposures, resulting doses in secretory cells, located at a depth of 20 mm, ranged from 5.14 Gy at T to 4.33 1022 Gy at R1, with an intermediate value of 2.04 1021 Gy at R2 (Fakir et al., 2005). In general, about 10% of the bifurcation surface area receives a dose roughly 10 times higher than the average bifurcation dose. At the tip of the carinal ridge, this dose ratio may be about hundred times higher, although for an even smaller number of cells. The crucial question is then whether such local inhomogeneities of radon progeny surface activities are more carcinogenic than the same total activity uniformly distributed. For example, limited epidemiological data on lung cancer mortality following occupational inhalation of plutonium aerosols and the incidence of liver cancer and leukemia in thorotrast patients suggest a moderate enhancement factor for inhomogeneous versus uniform radionuclide distributions of the same total activity (Charles et al., 2003). Furthermore, histological studies have revealed that neoplastic and preneoplastic lesions are preferentially observed at carinal ridges in the human lung (Garland et al., 1962). Although no pertinent information is currently available for inhaled radon progeny, both findings suggest that carinal ridges in bronchial airway bifurcations are indeed the initial sites of bronchial tumor occurrence, consistent with the predicted local dose distributions.

Inhomogeneity of Surface Activities and Resulting Doses within Bronchial Airways

3.9.4

In lung dosimetry models, it is commonly assumed that radon progeny activities are uniformly distributed within the mucous-serous layer along the whole surface area. Consequently, each cell at a given depth in a given generation receives the same dose. However, experimental and modeling studies revealed a strong inhomogeneity of radon progeny deposition, with significantly enhanced deposition at the carinal ridge, together with an impaired mucus transport around the dividing wedge of the two daughter branches (Farkas and Szo¨ke 2013; Hofmann et al., 1990). The resulting inhomogeneous activity distributions, i.e., local accumulations of activity at carinal ridges due to enhanced deposition and reduced mucociliary clearance, together with a non-uniform irradiation geometry lead to

Comparison of Bronchial Doses between Non-Smokers and Smokers

Changes of several anatomical, physiological, and histological parameters, such as decreased or increased mucus velocity, increased thickness of the mucus layer, increased mucus viscosity, decreased lung volumes, increased breathing frequency, smaller tidal volumes, bronchial airway obstructions and destruction of the alveolar architecture, and basal cell hyperplasia as a result of cigarette consumption have been reported (Baias et al., 2010). Based on these observations, smokers were subdivided into four exposure categories by varying cigarette consumption and duration of exposure: Light short-term, light long-term, heavy short-term, and heavy long-term smokers. It is important to note that published physiological and morphological data vary widely among the different sources, so that 49


parameters, individual mucociliary clearance velocities, and variations of the thickness of the bronchial thickness and related depths of target cells (Mercer et al., 1991). Calculations of inter-subject variability indicated that the asymmetry and variability of the airway geometry is the most important factor, followed by the filtering efficiency of nasal passages and by the diameter-related thickness of the bronchial epithelium (Hofmann et al., 2010). Resulting bronchial dose distributions were approximated by lognormal distributions; BB: median ¼ 3.2 mGy WLM21, GSD ¼ 2.3; and bb: median ¼ 2.3 mGy WLM21, GSD ¼ 4. The results showed that the inter-subject variations were significantly higher in the peripheral bronchiolar airways than in the larger bronchial airways. These dose distributions were also much wider than the distributions obtained with the HRTM (Marsh et al., 2012). In deterministic dosimetry models, such as the HRTM, each individual is characterized by a single dose value. Thus, stochastic dosimetry models will, by definition, produce wider, more realistic dose distributions. Available morphometric models of the human tracheobronchial tree are based on measurements from a few laboratories of a small number of individuals. In order to determine the degree of inter-subject variability, analyses of airway lengths, diameters, and branching angles from accident victims were performed using solid silicone casts of the upper bronchial tree from eight human lungs (Nikiforov and Schlesinger, 1985). The results indicated that there are significant differences among subjects. The coefficient of variation was least for diameters (29%) and greatest for branching angles (78%), and intermediate for lengths (42%).


these categories represent only rough approximations. The results of bronchial dose calculations (Baias et al., 2010) are only briefly summarized here: (1) Calculated doses for light short-term smokers deviate only minimally from the doses in non-smokers as only small changes of morphological and physiological parameters have been reported; (2) for light long-term and heavy short-term smokers, doses will be reduced due to a thickening of the mucus layer and increased mucus velocities; and (3) doses for heavy long-term smokers can increase by up to a factor of 2 relative to non-smokers, caused by impaired mucus clearance, higher breathing frequencies, reduced lung volume, and airway obstructions (see Section 3.5 for human studies of lung clearance in smokers and non-smokers).

Bronchial doses (mGy WLM21)

BB (1 –9) bb (10 –16) BB þ bb

Basal Secretory Equal weighting

Weighted by density

2.77 2.30 2.54

3.34 1.85 2.60

6.23 2.33 4.28

4.50 2.05 3.27

dosimetric point of view, non-targeted cells do not affect the resulting doses listed in Table 3.16. Due to the columnar structure of the bronchial epithelium, the depth distributions of epithelial cells are the same as that of the secretory cells (Mercer et al., 1991) and hence doses based on scenario 1 are the same as the secretory cell doses. If the initial damage is produced in all epithelial cells, then the probability that this damage will occur in basal and secretory cells (scenario 2) is proportional to their relative volumetric densities and thus equal to the weighted bronchial cell doses. For the assessment of an average lung dose to be related to lung cancer risk, an additional weighting procedure has been introduced through apportionment factors for the BB, bb, and AI regions. Equal weighting (ABB:Abb:AAI ¼ 0.333:0.333:0.333) (ICRP, 1994) leads to an average lung dose of 2.36 mGy WLM21, while application of the apportionment factors (ABB:Abb:AAI ¼ 0.80:0.15:0.05) proposed by Porstendo¨rfer (2002) yields an average lung dose of 4.07 mGy WLM21.

Contribution of Sensitive Target Cells in Bronchial Epithelium to Lung Cancer Risk

At present, basal and secretory cells are considered to be the primary target cells in the bronchial epithelium (ICRP, 1994). Robbins et al. (1990) measured the volume density of basal, mucous, and indeterminate cells in four bronchial airway generations in smokers and non-smokers. A comparison of volume density of basal and mucous cell nuclei between smokers and non-smokers showed no statistically valid differences. However, the volume density of mucous cell nuclei was considerably less than that of basal cell nuclei in both smokers and non-smokers. Because of lack of more pertinent information, it is assumed that both cell types equally contribute to bronchial tumor induction. Hence bronchial doses are commonly expressed as the average of 50% basal and 50% secretory cell doses, except for the IDEAL-DOSE model, where basal and secretory doses are weighted by their relative nuclear volumetric densities (Winkler-Heil and Hofmann, 2005), based on the measurements of Mercer et al. (1991). As opposed to these direct effects, non-targeted mechanisms, where cells not hit at all exhibit a radiobiological response, may play an important role, particularly at low doses, where only a small fraction of cells is actually hit (Brenner et al., 2001; Fakir et al., 2009). In terms of cellular dosimetry, this would imply that all epithelial cells should be considered as initial target cells (scenario 1), although only basal and secretory cells may still be the primary recipient cells (scenario 2). Cell-specific and weighted doses to different sensitive target cells are presented in Table 3.16. These results indicate that the choice of different target cells or any combination thereof will lead to a range of values varying by about a factor of 2. From a

3.10

Human versus Experimental Animal Doses

Laboratory animals have been used as human surrogates to supplement epidemiological studies for the assessment of lung cancer risk following exposure to radon and its short-lived progeny. The primary advantage of laboratory animal studies is the possibility to conduct inhalation experiments under controlled exposure conditions and to investigate the effects of exposure characteristics, such as the equilibrium factor or the unattached fraction, and the contribution of concomitant carcinogenic pollutants and nonradiological cancer-related factors, such as cigarette smoke. Indeed, the uncertainty associated with the post-exposure assessment of radon and radon progeny exposure parameters in uranium miner and indoor radon cancer surveys is one of the major deficiencies of epidemiological studies. Moreover, for low 50


3.9.5

Table 3.16. Comparison of basal and secretory cell doses per unit exposure and their combination by applying different weighting procedures for uranium mining conditions (Marsh et al., 2005; Winkler-Heil et al., 2007)


cellular and tissue level in both animals and humans. To further explore this issue, dosimetry models for different animal species will be discussed in the following section.

level radon exposures in homes, the radiological radon and radon progeny effect may be masked by the concomitant exposure to other non-radiological co-carcinogens, which may act in a synergistic or antagonistic fashion, and hence cannot reliably be separated from the effects of these additional exposures. 3.10.1

3.10.2

Animal Dosimetry Models

Several types of laboratory animals, primarily adult males, have been used in radon inhalation experiments. These ranged from small rodents, such as CAF strain mice (Morken and Scott, 1966), Sprague–Dawley (Monchaux, 2005), and Wistar rats (Cross and Monchaux, 1999), and Syrian Golden hamsters (Desrosiers et al. 1978), to beagle dogs (Cross et al. 1982). Among these animals, the most extensive inhalation experiments were carried out with rats (Cross and Monchaux, 1999). A detailed report of the earlier animal inhalation experiments carried out in the USA can be found in the NCRP Report No. 78 (NCRP, 1984), while the results of the more recent inhalation studies with rats in the USA and in France are summarized in the papers of Cross (1988a, 1988b), Cross and Monchaux (1999), and Monchaux (2005). The frequencies of non-respiratory neoplasms such as bone, liver, and breast cancers were elevated, although no excess of tumors other than respiratory have been observed in the human underground miner studies. Tobacco smoke was observed to enhance the number of lung tumors by a factor of 2–4 when smoke exposure was given following 222Rn exposure (Cross, 1988b; Monchaux et al., 1994). Smoke exposure decreased the tumor latency period. NCRP (1984) summarized the risk models developed in rat studies and derived an estimated excess lifetime lung tumor risk coefficient of 3 1024 per WLM. This value is similar to the ICRP (2010) recommended estimate and to the UNSCEAR (2008) estimate of 5 1024 per WLM for human underground miner data as well as to the recently published estimate of 5 1024 per WLM for the human lifetime excess absolute risk for the ICRP reference population consisting of smokers and non-smokers (ICRP, 2010). These animal radon inhalation studies, particularly those with rats, revealed that the lung cancer risk per unit exposure observed is consistent with that reported for uranium miners over a wide range of radon exposure levels (Cross 1988a; Harley, 1988). This observation raises the questions whether the similarity of lung cancer incidences is due to the similarity of bronchial doses. An alternative interpretation could also be that doses are different, but that these differences are compensated by comparable differences in the carcinogenic response at the 51


Animal studies have been conducted primarily with rats; however, dogs, hamsters, and mice were also used as experimental animals. To compare species-specific risk estimates and thus to make risk extrapolations from animals to humans, detailed dosimetric models are needed to account for the various dissimilarities of morphometric and physiological parameters, which may impact on the resulting doses to sensitive target cells. The first dosimetry model for an animal lung was developed by Desrosiers et al. (1978), who calculated airway doses for three reference mine atmospheres in the Syrian Golden hamster lung, ranging from about 0.3 mGy WLM21 to about 14 mGy WLM21. These calculations indicated that all reference atmospheres produced radiation doses in the hamster lung which are lower in the upper bronchial airways than those predicted in humans. For inhalation experiments using dogs at the University of Rochester (UR) (Morken, 1973), doses to the trachea, the major bifurcation, and the whole lung were estimated by measuring the related radon progeny activity concentrations. Although these estimates were not based on a specific dosimetric model, they ranged from 3.6 to 207 mGy WLM21 for selected bifurcations and about 50 mGy WLM21 for the whole bronchial tree, which is about an order of magnitude higher than that estimated for the human bronchial region for the same exposure conditions (NCRP, 1984). Another experimental inhalation study with beagle dogs was conducted at the Battelle Pacific Northwest Laboratories (PNL) (Cross et al., 1982). To understand possible mechanistic differences between the responses of the human and dog lung to radon progeny exposure in terms of radiation doses, Harley et al. (1992) developed a dosimetric model for the dog lung. The computed alpha dose per unit exposure to basal cell nuclei in the upper bronchial airways ranged from 2 to 7 mGy WLM21 depending upon the exposure protocols used in the UR and PNL studies, respectively. The dose to the alveolar tissue in both studies was 3 mGy WLM21. For comparison, model predictions for the human lung under the same exposure conditions were 9 mGy WLM21 for the bronchial airways and 0.5 mGy WLM21 for the alveolar tissue. In the following years, practically all experimental animal radon inhalation studies were carried out

Animal Inhalation Experiments


particle diameters of the attached radon progeny (0.12 or 0.5 mm AMD) and unattached fractions (1.3% or 9.5%), doses to bronchial target cells ranged from 1.8 to 10.7 mGy WLM21, averaged over all bronchial generations (except the trachea) (Table 3.17). For comparison, the alpha dose to the alveolar region ranged from 1.8 (0.5 mm AMD) to 3.6 mGy WLM21 (0.12 mm AMD). The average bronchial dose value over all exposure conditions of 5.6 mGy WLM21 is very similar to the value for both occupational and environmental exposures for humans of about 5 mGy WLM21. The dosimetric model proposed by Hofmann et al. (1993) utilized the morphometric model of Yeh et al. (1979) for the Long Evans rat and applied it both to the Sprague – Dawley and Wistar rats due to their similarity (Mercer and Crapo, 1989). Since the anatomical dimensions of the Yeh et al. (1979) model reportedly refer to total lung capacity (TLC), linear airway dimensions were scaled down to an FRC of 40% TLC, assuming that diameters and lengths vary with the cube root of lung volume. Relative volumetric fractions of basal and secretory cell nuclei as functions of depth in bronchial epithelium were taken from Mercer et al. (1991). Doses were computed to basal and secretory cell nuclei in all bronchial airway generations for both the Battelle (0.3 mm AMTD) and COGEMA (assumed 0.15 mm AMTD) aerosol parameters and different equilibrium factors and unattached fractions. Computed mean bronchial dose ranged from 7.1 to 10.9 mGy Table 3.17. Model-derived dose conversion coefficients of the bronchial airways for different animal species and the human lung Animal

Dose conversion Reference coefficient (mGy WLM21)

Syrian hamster Beagle dog Balb/c mouse Rat (Sprague–Dawley, Wistar, Fisher) Rat (Long-Evans, Wistar, Sprague– Dawley) Rat (Long Evans, Wistar, Sprague–Dawley) Rat (Long Evans) Rat (Long Evans, Sprague–Dawley) Human

0.3–1.4 2–7 8.6–31.4 5.6 (1.8–10.7)

Desrosiers et al. (1978) Harley et al. (1992) Sakoda et al. (2013) Harley (1988)

8.8 (7.1–10.9)

Hofmann et al. (1993)

8.1 (7.2)a

Fakir et al. (2008)

8.6–18.3 7.8

Sakoda et al. (2013) Winkler-Heil et al. (2014) Harley et al. (1996) Hofmann et al. (1993) Fakir et al. (2008) Winkler-Heil et al. (2014)

a

6.0 3.6–5.0 6.3 5.8

Bronchial dose without crossfire from nuclide sources in alveolar tissue.

52


with rats. In particular, two major inhalation studies with radon progeny have been conducted in the USA at the Battelle Pacific Northwest Laboratories (PNL) (Cross, 1988a, 1988b; Cross and Monchaux, 1999; Cross et al., 1982; 1984; Gilbert et al., 1996), and in France at the Compagnie Generale des Matieres Nuclaires (COGEMA) (Chameaud et al., 1984; Monchaux, 2004; 2005; Monchaux and Morlier, 2002; Monchaux et al., 1994; 1999). These studies were complemented and augmented by rat inhalation experiments carried out in the UK at Harwell, focusing on cellular radiobiological effects (Collier et al., 1999; 2005). The wealth of information produced by these studies underscored the necessity to develop detailed dosimetric models for the rat bronchial tree (Fakir et al., 2008; Harley, 1988; Hofmann et al., 1993; Winkler-Heil et al., 2014). A complete bronchial morphometric model of the tracheobronchial tree for a female Long Evans black and white hooded rat has been reported by Raabe et al. (1976) and Yeh et al. (1979). On the other hand, the rats used in the US and French inhalation studies were male Wistar rats (Cross et al., 1984) and male Sprague – Dawley rats (Chameaud et al., 1981). A comparison of morphometric data for tracheobronchial airways between a Long Evans rat (Koblinger and Hofmann, 1988; Raabe et al., 1976; Yeh et al., 1979) and a Sprague – Dawley rat (Mercer and Crapo, 1989) indicated that the anatomical structures of both rat strains were very similar. Therefore, it is a reasonable assumption for modeling purposes that the morphometric data provided by Raabe et al. (1976) and Yeh et al. (1979) are a valid representation for all rat strains used in the inhalation studies, although differences in breathing parameters as a function of body weight have to be taken into account. Based on rigorous statistical analyses of the morphometric data provided by Raabe et al. (1976) for the Long Evans rat, Koblinger and Hofmann (1988) developed a stochastic model of the rat tracheobronchial tree, later supplemented by a corresponding stochastic model of the alveolar region based on measured data in a Sprague – Dawley rat (Koblinger et al., 1995). The first dosimetric model for radon progeny inhalation in the rat lung was developed by Harley (1988), based on the morphometric data for the female Long Evans black and white hooded rat provided by Raabe et al. (1976) and Yeh et al. (1979) and strain-specific breathing parameters for the Long Evans, Wistar or Sprague – Dawley, and Fisher 334 rats. Tracheobronchial doses were computed for the reference atmosphere reported by Cross (1988a) for the Battelle inhalation experiments and for the natural ambient aerosol reported by Chameaud et al. (1984) for the French studies. Depending on


WLM21 (Table 3.17), while corresponding alveolar doses ranged from 1.2 to 4.9 mGy WLM21. For comparison, bronchial cellular doses for the human lung for typical indoor exposure conditions are approximately 5.0 mGy WLM21, i.e., average doses to the rat bronchial tree are slightly higher than those to the human bronchial cells by about a factor 1.5 –2. More recently, Fakir et al. (2008) analyzed relevant microdosimetric quantities and investigated the contribution of crossfire alpha particles emitted from radon progeny deposited in the alveolar region to bronchial absorbed doses. Based on the dosimetric model of Hofmann et al. (1993) described above, hit frequencies, absorbed doses, and critical microdosimetric quantities were calculated for basal and secretory cell nuclei located at different depths in epithelial tissue for each bronchial airway generation and for defined indoor exposure conditions. Absorbed doses, considering the effect of crossfire, and cellular hit frequencies were slightly higher in rat airways than in corresponding human airways. Average absorbed doses, including alpha particle emissions from the mucus layer and the alveolar region and averaged over the entire bronchial tree (without trachea), were 8.1 mGy WLM21 for the rat and 6.3 mGy WLM21for the human lung (Table 3.17). While the contribution of crossfire alpha particles is insignificant in the human lung, it can reach 33% in peripheral bronchiolar airways of the rat lung. Based on the stochastic model of the rat lung (Koblinger et al., 1995), Winkler-Heil et al. (2014) recently performed dose calculations for typical indoor exposure characteristics. Since studies by Hofmann et al. (1999) have demonstrated that airway diameters are more appropriate morphometric scaling parameters to classify local deposition patterns across different species than the conventionally used airway generations, dose distributions as functions of airway diameter classes were computed for the human and rat lung. Assuming an AMTD of 0.3 mm for the attached fraction and 5 nm diameter for an unattached fraction of 3%, the mean bronchial doses were 7.8 mGy WLM21 for the rat and 5.8 mGy WLM21 for the human lung, respectively. Corresponding dose calculations for the human bronchial airways for the exposure conditions used already in the dose calculations for the rat lung (Fakir et al., 2008; Harley, 1988; Hofmann et al., 1993) are also listed in Table 3.17. In the human lung, alveolar doses are typically of the order of 10% or less of bronchial doses (Hofmann, 1982c), while alveolar doses in the rat lung range from about 16% up to 50% (Hofmann et al., 1993), depending on modeling assumptions. For comparison, Harley (1988) reported values in

the range from 51% up to 100%. Since both estimates are based on modeling assumptions, it cannot be decided on scientific grounds which values are more realistic. The results from the dosimetric analyses of radon progeny inhalation experiments with rats can be summarized as follows:

In conclusion, the animal studies performed in the USA and France have been entirely supportive of the human epidemiology. With the exception of tumor type (i.e., a greater prevalence of solid alveolar tumors and bronchiolar–alveolar carcinomas in animals), the lung cancer response is reasonably consistent with that in human exposures. The slightly different occurrences of bronchial carcinomas in the human and rat bronchial airways following exposure to radon and its short-lived progeny might be explained either by differences of doses to sensitive target cells in the bronchial epithelium or by differences in radiosensitivities of target cells in both species. Cross (1988) explained these observed differences in tumor incidences by assuming that rats are about twice as sensitive to lung cancer induction as humans for the same cumulative exposure. Dosimetric calculations (Hofmann et al., 1993; Winkler-Heil et al., 2014) suggest, however, an alternative interpretation, namely that differences in cancer risk might also be related to differences in bronchial doses, while both species have similar radiobiological sensitivities for the range of doses produced in the inhalation experiments. 53


(1) Absorbed doses and microdosimetric quantities are slightly higher in rat bronchial airways than in corresponding human airways. This confirms the a priori assumption in rat inhalation experiments that the rat lung is a suitable surrogate for the human lung. (2) The doses to the alveolar region relative to those to the bronchial airways are significantly higher in the rat than in the human lung. This may partly explain the experimental findings that approximately 70% of the observed tumors in the rat lung are bronchogenic carcinomas and 30% of bronchioalveolar origin (Cross, 1988), contrary to the cancer distribution reported for uranium miners with about 84% in bronchial–bronchiolar airways and 16% in the alveolar region (Ellett and Nelson, 1985; Saccomanno et al., 1996). Doses to the bronchiolar airways are further increased by high-energy transfer of crossfire alpha particles emitted from the alveolar region (this effect can be neglected in the human lung).




4. Characteristics and Behavior of Radon and Radon Progeny 4.1

Radon Sources



Radon is a naturally occurring radioactive gas, which has no taste, smell, or color. It is an inert noble gas that is encountered in elemental form either as a gas, or dissolved, usually in water. There are a number of isotopes of radon (Firestone and Shirley, 1999), but the most important isotopes for radiation protection are 222Rn and 220Rn. Radon-222 is a member of the uranium (238U) natural decay series and 220Rn is a member of the thorium (232Th) natural decay series (see Figures 4.1 and 4.2). Because of their origins, the isotopes 222Rn and 220Rn are commonly known as radon and thoron, respectively. Rn-222 is a direct decay product of 226Ra and 220Rn is a direct decay product of 224Ra. Uranium, radium, and thorium occur naturally in soil and rocks and provide a continuous source of radon. Radon can escape from the earth’s crust either by molecular diffusion or by convection and as a consequence is present in the air outdoors and in buildings. Radon escaping from ground to outdoor air is diluted to low activity concentrations, with the amount of dilution dependent on the atmospheric stability and the presence of wind and level of turbulence. However, radon activity concentrations can reach high levels within enclosed spaces, such as underground mines, caves, and buildings. In general, the problems posed by radon (222Rn) are much more widespread than those posed by thoron (220Rn). Because thoron has a short half-life (56 s), it is less able than radon to escape from the point where it is formed. As a consequence, building materials are the most usual source of indoor thoron exposure. In contrast, radon, which has a half-life of 3.8 d, can diffuse in soil more than a meter from the point where it is formed. As a result, the ground underneath buildings is usually the main source of indoor radon. Generally, high 222Rn levels in buildings are caused by pressure-driven convection flow because, as a result of warm indoor air, the air pressure at ground level in most buildings is slightly lower than the soil air pressure. This causes a flow of soil air into the building carrying radon with it. Other factors such as ventilation rates and meteorological conditions also affect the convection flow.

Therefore, there is a large variation of indoor 222Rn activity concentrations depending upon heating, ventilation rates, and meteorological conditions as well as the geology of the area. Buildings with concrete floors often have cracks around edges and gaps around service entries, such as water supply, electricity, or sewage pipes. Cracks and gaps also permit soil gas entry. If buildings have suspended timber floors, then the gaps between the floorboards are the main route of entry. In building areas where 222Rn levels are low, such as on upper floors of a block of flats, the main sources of radon may be building materials and outdoor air. Exposure to radon in buildings may also arise in areas contaminated with radium from past industrial activities. Radon is soluble in water. Radon-222 dissolved in water can de-gas and escape to indoor air leading to an additional source of exposure via inhalation. This is an important source of exposure for those employed in water works where ground water with a high radon activity concentration is treated or stored (NA/NRC, 1999b; Schmitz and Nickels, 2001; Trautmannsheimer et al., 2003). Other examples include those working in indoor areas of thermal spa facilities (Geranios et al., 2004; Soto and Go´mez, 1999) and those members of the public using drilled wells. In the latter case, ingestion of water should also be considered as a route of intake for radon. However, during showering, dish washing, or if boiled, most if not all the radon is expelled from the water. Moreover, geological factors which lead to high activity concentrations of radon in water may independently give rise to high levels of radon in indoor air. Because radon is inert, nearly all of the gas that is inhaled is subsequently exhaled. However, 222Rn decays into a series of solid short-lived radioisotopes, most of which attach to the ambient aerosol. A proportion of the inhaled radon progeny deposits in the respiratory airways of the lung. Because of their relatively short half-lives (,30 min), the radon progeny decay mainly in the lungs before clearance, either by absorption into blood or by particle transport to the alimentary tract, can take place. Two of the shortlived progeny, 218Po and 214Po, emit alpha particles


from 218Po to 214Po with half-lives of the order of minutes and the long-lived progeny from 210Pb to the stable 206Pb with half-lives of the order of days or years. Because of their long half-lives, resulting airborne activities are orders of magnitude smaller than those of their short-lived precursors. Thus, only the inhalation of short-lived radon progeny will be considered for the assessment of bronchial doses and resulting lung cancer induction. Half-lives and emitted radiations of radon and its short-lived progeny are listed in Table 4.1 (Be et al., 2004). Likewise, thoron progeny from 216Po to 208Tl have half-lives ranging from seconds to hours, before ending up at the stable 208Pb. Since the thoron decay scheme does not contain any long-lived progeny in contrast to the radon progeny, no distinction between short-lived and long-lived progeny is necessary. Half-lives and emitted radiations of thoron and its progeny are listed in Table 4.2 (Be et al., 2004). Concern for the potential hazards resulting from exposure to the isotopes of radon is commonly centered upon 222Rn and 220Rn. However, there is a

and it is the energy from these alpha particles that dominates the dose to the lung and the associated risk of lung cancer.

4.2

Radon and Thoron Decay Schemes

The decay schemes of the uranium (238U) natural decay series and of the thorium (232Th) natural decay series are illustrated in Figures 4.1 and 4.2 (Be et al., 2004). Both natural decay series have three characteristic features: † The first nuclide in the decay series has a very long half-life, comparable to the age of the earth (109 – 1010 years) † The final nuclide of the decay series is a stable lead isotope † Each decay series contains a radioactive noble gas From a dosimetric point of view, the decay products of Rn can be divided into two groups depending on their radioactive half-lives: the short-lived progeny 222

56


Figure 4.1. Natural decay series: 238U.

Characteristics and Behavior of Radon and Radon Progeny

third natural radioactive decay series originating from 235U, historically known as the actinium series, which contains another radon isotope, namely 219Rn or actinon. Because of its short half-life of only 3.96 s and the relatively low abundance of 235U in natural uranium, the 219Rn activity concentration in air is negligible when compared with that of 222Rn. Thus, actinon will not be discussed in the present report.

4.3

decay, interactions with aerosols, deposition on surfaces, and ventilation. Here, particular emphasis is placed on the behavior of radon and its progeny in comparison to that of thoron and its progeny. Starting with Jacobi in 1972, a number of similar room models have been developed to describe the behavior of these species in the indoor environment (Jacobi, 1972; Porstendo¨rfer, 1994; 2001). In these room models, it is assumed that 222Rn and its progeny are uniformly mixed in the indoor air. It is also assumed that there are no thermal gradients present and that the air is of uniform humidity throughout the room volume. In what follows in this section, unless otherwise specified, all activity concentrations both for the parent gases and their progeny are expressed in activity concentrations per unit volume of air (Bq m23).

Behavior of Radon, Thoron and Their Progeny in Indoor Environments

The activity concentrations of radon, thoron, and their progeny in indoor air arise as a result of the interplay of a number of complex processes. The most important of these processes are radioactive 57


Figure 4.2. Natural decay series: 232Th.

MEASUREMENT AND REPORTING OF RADON EXPOSURES Table 4.1. Main radioactive decay properties of short-lived progeny Radionuclide

222

Half-life

Alpha

Beta

Gamma

— — 0.67 (47%) 0.73 (41%) 1.02 (9%) 1.540(17%) 1.894 (7%) 3.270 (20%) —

— — 0.053 (15%) 0.295 (27%) 0.351 (46%) 1.120 (15%) 1.764 (15%)

3.823 d 3.07 min 26.9 min

5.59 (100%) 6.11 (100%) —

214

19.8 min

—

Bi

214

Po

162 ms

(4.2) may be simplified to

Rn and its

CiRn ¼ ERn =v þ CoRn

Main energies (MeV) and intensities

Rn Po 214 pb 218

222

7.83 (100%)

Similar equations apply to thoron, but in this case, the radioactive decay constant for the gas is lTn ¼ 45.4 h21 corresponding to a radioactive half-life of 56 s. Therefore, exhalation of thoron from indoor surfaces is generally the principal source of indoor thoron. In addition, because lTn is much greater than the range of v values under steady-state conditions CiTn ¼ ETn =lTn

220

Due to its short half-life, the activity concentration of thoron gas falls off rapidly with distance from its main source, the internal surfaces of the rooms. Therefore, in Equation (4.4), C iTn should be considered as a mean value of the thoron activity concentration in the room air rather than a uniform activity concentration throughout the room volume. Assuming the room surfaces are the main source of indoor thoron then the fall off of the thoron activity concentration with distance x from a room surface may be written as: p CTn ðxÞ ¼ ETn = ðlTn Da Þexpðx=La Þ

Rn and its

Radionuclide Half-life Main energies (MeV) and intensities Alpha 220

Rn Po 212 Pb

55.8 s 0.15 s 10.64 h

216

212

Bi

212

Po (64%) Tl (36%)

208

4.3.1

Beta

6.41 (100%) — 6.91 (100%) — — 0.331 (82%) 0.567 (13%) 60.5 min 6.17 (25%) 2.252 (55%) 6.21 (10%) 300 ns 8.95 (100%) — 3.06 min — 1.291 (24%) 1.524 (22%) 1.801 (49%)

Gamma 0.550 (0.12%) — 0.239 (82%) 0.040 (26%) 0.727 (7%) — 0.511 (25%) 0.583 (87%) 0.860 (13%) 2.614 (100%)

¼ CTn ð0Þ expðx=La Þ

Assuming the sources contributing to the radon activity concentration in a room are constant, the indoor radon activity concentration may be described by the following equation: dCiRn =dt ¼ ERn þ vCoRn ðlRn þ vÞCiRn

ð4:5Þ

where CTn(0) is the thoron activity concentration at the room surface (x ¼ 0), Da is its diffusion coefficient in air, and La ¼ (Da/lTn)1/2 is the diffusion length of thoron in air. La has been estimated to range from about 3 to 20 cm depending on the effective value of Da used. In any case at 1 m from a wall, the calculated thoron activity concentration will be less than 1% of its value at the wall surface. However, measurements of Doi et al. (1994), Harley et al. (2010), and Reddy et al. (2012) do not support such a rapid decrease. In their studies, thoron activity concentrations decreased only to 10–40% at 1 m distance from the source, most likely due to circulating air currents.

Steady-State Activity Concentrations of Radon and Thoron Gases in Indoor Air

ð4:1Þ

where C iRn is the indoor activity concentration of radon, CoRn the outdoor activity concentration of radon, lRn the decay constant of radon, v the ventilation rate, ERn the total volume-specific entry rate of radon to the indoor spaces from soil gas, exhalation of building materials, and release from water. Under steady-state conditions where a balance exists between the supply and removal rates of radon CiRn ¼ ðERn þ vCoRn Þ=ðlRn þ vÞ

ð4:4Þ

—

4.3.2

Steady-State Activity Concentrations of Radon Progeny in Indoor Air

Radon progeny in a room may be present in three forms. These are: (a) Unattached radon progeny: Immediately after formation following alpha decay of radon, the progeny so formed are mainly positively charged. They rapidly form charged or neutral clusters with water vapor molecules and trace gases that are present in the air. These unattached radon progeny are nanoparticles in the size range 0.5 –5 nm (Sections 4.6 and 7.5.2).

ð4:2Þ

In dwellings in temperate climate, v is generally in the range of 0.1–1.5 h21, values that are much greater than lRn ¼ 7.6 1023 h21. Thus, Equation 58


Table 4.2. Main radioactive decay properties of short-lived progeny

ð4:3Þ


Under steady-state conditions, we therefore obtain for the unattached and attached progeny activity concentration, respectively:

They play an important role in lung dosimetry (Section 3.8). (b) Attached radon progeny: Unattached radon progeny will attach to aerosol particles present in the air, forming attached radon progeny. The size distribution of attached progeny depends on the aerosol particle size distribution, the trace gases, and the attachment coefficient. (c) Deposited radon progeny: Both unattached and attached radon progeny deposit on room surfaces. Depending on the characteristics of the surfaces on which they deposit subsequent progeny produced by alpha decay on the surface may give rise to alpha recoil of implanted radon progeny in the surface. The presence of such implanted progeny activities in glass forms the basis for one type of retrospective radon measurement technique (Section 5.4).

Cj u ¼ ðlj Cj1u þ lj Rj1 Cj1 a Þ=ðlj þ b Z þ qu þ vÞ ð4:8Þ and Cj a ¼ ðvCj a;o þ ð1 Rj1 Þlj Cj1 a þ b Z Cj1 u Þ=ðlj þ qa þ vÞ

dCj u =dt ¼ lj Cj1u þ lj Rj1 Cj1a ðlj þ X þ qu þ vÞCj u

ð4:6Þ The activity concentration of the jth radon progeny in the attached state, Cja, may be written as dCj a =dt ¼ vCj a;o þ ð1 Rj1 ÞlCj1 a þ XCj1u ð4:7Þ

vg ¼ wðdÞ=Zðz; dÞ

ð4:10Þ

where w(d) is the number of particles with diameter d deposited per unit surface area and time and Z(z,d) is the concentration of particles with diameter d at height z above a surface. In the literature, the deposition velocity is often normalized by the friction velocity u*: vg þ ¼ vg/u*, where u* depends on the air velocity profile and the roughness of the surface. Normalized deposition velocities as functions of particle diameter are displayed in Figure 4.4 for different rough and smooth surfaces (Porstendo¨rfer, 1994). Two observations can be made: (i) deposition

Figure 4.3. Schematic representation of the behavior of radon progeny in an enclosed space. Adopted from NA/NRC (1991) and Porstendo¨rfer (1994).

59


with C0a ¼ 0 and C0u ¼ C0 (radon gas activity concentration). Here, Rj21 is the recoil factor of the j21th attached radon progeny. This is the desorption fraction of the jth progeny so formed from the aerosol particle surface following an alpha decay. In other words, Rj21 is the probability that an attached radioactive atom, j –1, desorbs from its host following alpha decay. For typical indoor aerosols from considerations of recoil energy and particle size, Rj21 can be expected to be close to 1, but the experimentally determined value of Rj21 ¼ 0.8 is generally used (Mercer, 1976). For beta decay, the recoil factor is negligible, i.e., R2 ¼ R3 ¼ 0. The term b Z in Equations (4.8) and (4.9) is the attachment rate (X) of radon progeny to aerosols where b is the mean attachment coefficient and Z is the number concentration of the aerosol particles (McLaughlin, 1972) [see Equation (4.14)]. The parameter q a and q u represent the attached and unattached radon progeny deposition rates to room surfaces, respectively. The parameter Cja,o is the activity concentration of the attached radon progeny j in outdoor air. It is assumed that the unattached radon progeny in outdoor air is removed by plate-out (surface deposition) during ventilation. In rooms, deposition of radon progeny on walls and furniture is a major determinant of steady-state activity concentrations in indoor air. Deposition can be characterized by the deposition velocity vg:

The different physical mechanisms affecting the behavior of radon progeny in a room are illustrated in Figure 4.3. In the steady state, well-mixed room model, the following equations may be used to describe the behavior of both unattached and attached radon progeny j with decay constant lj (see Figure 4.3). The activity concentration of the jth radon progeny in the unattached state, Cju, may be written as

ðlj þ qa þ vÞCj a

ð4:9Þ


velocities increase with increasing roughness of the surface, and (ii) the minimum of deposition lies between particle diameters of 0.2 and 0.7 mm for all surfaces. For a well-mixed room air, the deposition rates q for attached and unattached radon progeny [Equations (4.6–4.9)] are related to the deposition velocities vg [Equation (4.10)] via the surface to volume ratio S/V by (Porstendo¨rfer, 1994): q ¼ vg S=V

Radon Progeny Parameters Affecting Lung Dosimetry

As described in more detail in Section 3 of this report, estimates of lung doses due to the inhalation of short-lived radon progeny are strongly dependent on the choice of input parameters and other model assumptions. This leads to some uncertainty in estimated absorbed doses. In this regard, two of the most important parameters of airborne indoor air progeny are the equilibrium factor, F (Section 4.5), and their size distributions (Sections 3.7 and 4.7). Measurements in indoor air in several countries have shown F values in dwellings to lie generally between 0.2 and 0.8. In contrast to this, for a number of physical reasons, the F-value in outdoor air is usually higher and in the range 0.6–0.8. Indoor F values outside a range of 0.2–0.8 are very rare and would only arise in either extremely low or high aerosol concentrations, respectively, or under other unusual indoor air conditions not commonly met in most dwellings. Based on actual measurements, both ICRP (1993a) and UNSCEAR (2008) have adopted a typical worldwide F-value of 0.4 for indoor air and 0.8 for outdoor air. As most large-scale surveys of radon exposure are based on measurements of radon gas and not of its progeny, this value of 0.4 is generally used for practical reasons in estimating lung doses to the general population. The size distributions of both unattached and attached indoor radon progeny and their partitioning between these two modes are also parameters of importance in dose estimation. This is because of the different deposition patterns of these modes in the respiratory tract. The unattached (sometimes called ultrafine) mode lies in the 0.5–5 nm size range, while the attached mode, reflecting the indoor aerosol size distribution, is generally found in the 100-300 nm size range (Sections 3.7 and 4.7). Although the fraction of unattached activity is usually low, nevertheless because of its high deposition efficiency in human airways, it makes a disproportionate contribution to lung dose in comparison to the attached

Figure 4.4. Deposition velocity vg normalized by the friction velocity u* as a function of aerosol particle diameter for different smooth and rough surfaces: grass (solid line), filter paper (dot-dash line), and Al foil (broken line). Taken from Porstendo¨rfer (1994).

activity fraction. Attached activity deposition in the bronchial tree is typically only a few percent, whereas about 40% of the inhaled unattached progeny deposit in the bronchial tree.

4.4 4.4.1

Airborne Radon Activity Concentrations Radon in Homes

For epidemiological and health risk reasons, radon activity concentrations were measured in significant numbers of dwellings on all continents, involving almost 5 billion people in 67 countries (Chambers and Zielinski, 2011). Currently, the database on radon activity concentrations in dwellings is growing. A summary of these data was presented in UNSCEAR and WHO publications (UNSCEAR, 2008; WHO, 2009). In the conclusions of UNSCEAR, the worldwide geometric mean value of radon activity concentration is 37 Bq m23 (GSD: 2.2). The minimum value is below 10 Bq m23 (Egypt, Cyprus, Australia), while the higher values of 243 Bq m23 (Spain) and of 2745 Bq m23 as an arithmetic mean for Iran are measured in high background areas. In surveys of some thousands of dwellings monitored, sites above 1000 Bq m23 are expected, although their frequency is less than 1% (Hamori et al., 2006; Toma´sˇek et al., 2001; Zˇunic et al., 2007). Annual mean indoor radon activity concentrations depend on a large number of factors (Section 7). If these factors act multiplicatively and independently, 60


4.3.3

ð4:11Þ

Characteristics and Behavior of Radon and Radon Progeny Table 4.3. Long-term indoor radon surveys in some European Countries from National Summary Reports Country and population (millions)

No. of dwellings sampled

Measurement period and approx. duration

Mean value (Bq m23)

Geom. Mean (Bq m23)

Percent over 200 Bq m23

Max (Bq m23)

Czech Republic (10.2) Denmark (5.5) Finland (5.2) Germany (82.4) Ireland (4.2) Italy (58) UK (61)

.150 000 3120 2866 .50 000 11 319 5361 450 000

1984–present 1 year 1995–1996 1 year 2006–2007 1 year 1978–2003 1 year 1992–1999 1 year 1989–1998 1 year 1980–2005 3–12 months

140 64 96 49 89 70 20

110 53 62 37 57 52 14.9

12–18 2.9 10.4 1.6 7.5 4.1 0.5

25 000 590 33 000 .10 000 1924 1036 17 000

Source: http://rem.jrc.ec.europa.eu/RemWeb/publications/EUR_RADON.pdf

Table 4.4. Indoor radon Non-European countries

activity

concentrations

in

some

Country (pop.in millions)

Mean value (Bq m23)

Geom. mean (Bq m23)

Geom. STD (Bq m23)

Maximum (Bq m23)

Argentina (39) Australia (18) Canada (30) China (1316) India (945) Japan (125) South Korea (49) USA (250)

35 11 34 44 57 16 53 46

25 8 14 34 42 13 43 25

2 2.1 3.6 — 2.2 1.8 1.8 3.1

211 420 1720 586 210 310 1,350 Not listed

Source: UNSCEAR (2000).

were carried out in areas where high radon levels were expected on the basis of geological characteristics. It should be noted that representative radon surveys have not yet taken place in countries with the largest populations such as China and India. 4.4.2

Radon in Workplaces

Indoor workplaces include, for example, schools, hospitals, post offices, jails, shops, cinemas, office buildings, and common workshops. The primary workplaces where radon may cause health problems are underground mines, in particular uranium mines, waterworks in the case of sufficiently high radon levels in the water, and industrial buildings with specific work practices and ventilation conditions. More information on radon in workplaces will be given in Section 6.5. For a significant proportion of the population, the time spent in buildings is increased by a modern life style. Therefore, public buildings with a high density of people (e.g., kindergartens, schools, hospitals) have been monitored for radon. Table 4.5 gives some typical values of radon activity concentrations measured at selected workplaces in different countries for non-uranium mines, caves, and spas. In several workplaces, the radon activity 61


then the distribution of radon activity concentrations can be approximated as lognormal (Miles, 1998). Some publications suggest that measured radon data fit a lognormal distribution (Gunby et al., 1993; Nero et al., 1994; White et al., 1992), but in other literature, this was not confirmed (Goble and Socolow, 1990; Kies et al., 1996). It now seems that the “log-normal mysticism” (To´th et al., 2006) remains an open question in environmental statistics, despite many endeavors aimed at clarification (Bossew, 2010) (see Section 6.3.5). A summary of indoor radon surveys carried out in a number of European countries is given in Table 4.3 (Dubois, 2005). It is important, however, to note that the survey designs were not the same for each country. Dwellings were selected in some countries on the basis of population density. Where this approach was used, more measurements were made in large centers of population than in low population rural areas. In this approach, estimates can be made of the collective exposure and health risk of the general population in a country. Such information is useful to the relevant authorities for the development of national radon control strategies. National surveys in other countries were made on a geographical basis where the strategy was to achieve the same density of dwelling sampling per unit area irrespective of the population density distribution. The database from a carefully designed survey can be used in conjunction with other national databases, to produce both population-weighted data and geographically based data. Notwithstanding the differences in European survey designs, the data presented in Table 4.3 give a reasonably accurate overview of average radon activity concentrations in contemporary European dwellings. In Table 4.4, a summary is given of indoor radon data for a number of large non-European countries (UNSCEAR, 2000). The maximum radon activity concentration values quoted in Table 4.4 are the maximum values found in the national surveys. Much higher indoor radon activity concentrations are often found in targeted surveys because they

MEASUREMENT AND REPORTING OF RADON EXPOSURES Table 4.5. Examples of radon activity concentrations at some selected workplaces in the world taken from UNSCEAR (2008) and other sources Country Mine Hungary Kosovo Metohia Pakistan Argentina Iran

UK India

Interval

Site

Device

Ref

817 (575– 957)a (200–800) 192 (121– 408) 4800 (1800– 6000) 3500 (1000– 10 400) 2370 (580–4700) 990 (500– 1770) 220 (40– 590) 137 (15– 630) 150 (50– 390) 19 (11– 34) 5 (2– 10) 172; 340b (50 –587) 64; 4365b (18.9– 19 351)

One year

Manganese Lead/Zinc 6 Coal Gold/Touristic Turquoise Bauxite Lead 2 Coal 2 Manganese Poshpate Lead/Zinc Chromites 3 Lignite Copper

PADC PADC CN PADC Pulse ionization chamber

Ka´va´si et al. (2009) Jakupi et al. (1997) Qureshi et al. (2000) Anjos et al. (2010) Fathabadi et al. (2006)

PADC Active

30 d, Summer 6–8 h

2 months 7–47 h

5 Coal Coal Copper Gold Lead/Zinc Manganese Mica Mercury Lead 5 Coal

Scintillation cell Scintillation cell SSNTD

C ¸ ile et al. (2010) Malanca and Gaidolfi (1997) Page and Smith (1992) Mishra and Subba Ramu (1988)

Scintillation cell

Kobal et al. (1990)

Creswell Crags Guacharo, AlfredoJahn, so on Altamira Al-Somman Platea Petralona

PADC PADC, CN

Gillmore et al. (2002) Sajo´-Bohus et al. (1997)

Scintillation cell PADC SSNTD

57 caves Go¨kgo¨l Cehennemag˘zı

SSNTD SSNTD

Lario et al. (2005) Al-Mustafa et al. (2005) Papastefanou et al. (2005) Solomon et al. (1996) Aytekin et al. (2006)

65 613 (27– 1244) 5.3 1244.7 19 186.1 38.6 78.8 1419 (590–76 900) 658 (185– 1050) 256 (30– 465)

2–82 weeks

(27– 7800) (100–80 000)

1 year 1–6 months

Spain Saudiarabia Greece

3562 (186–7120) 74– 451 88 000

1 year 6 months

Australia Turkey

500; 795b (26330) 1918.8 (20– 5833) 657 (304– 885) 4000– 5000

6 months Winter/spring 2 months Summer

4600 (500–12 400) 5300 (1900– 8400)

1 year 214 d

Hospital Santana

PADC SSNTD

40.3 (10.9– 109) 149; 2380b (27-8263)

5 months 2–3 d

9 spas 5 spas

94; 1511b (54– 2040)

1 year

1 spa

CN Pulse ionization chamber PADC

Slovenia

Caves UK Venezuela

Czech Hungary Brazil Baths Croatia Greece Hungary

Grab sampling

1 year

SSNTD

Thinova´ and Burian (2008) Somlai et al. (2007a) Alberigi et al. (2011) Radolic´ et al. (2005) Vogiannis et al. (2004a) Ka´va´si et al. (2011)

a

Arithmetic mean (minimum – maximum). Minimum arithmetic mean; maximum arithmetic mean (minimum–maximum). PADC, poly-allyl diglycol carbonate; CN, cellulose nitrate; SSNTD, solid-state nuclear track detector.

b

concentration is below 100 Bq m23 (lead/zinc mine, Iran; coal, gold, manganese, and mica mines, India; spa, Croatia), but for some caves and mines, the radon activity concentration is more than 1000 Bq m23. For example, radon activity concentrations of about 80 000 Bq m23 have been measured in a mercury mine (Slovenia) and in caves (Venezuela and Greece, Petralona).

The radon activity concentrations in caves can reach high levels because of the low air exchange rate due to poor ventilation. The caves are natural formations with a special microclimate and to preserve this microclimate, forced ventilation cannot be applied. In mines, forced ventilation is compulsory due to occupational health and safety requirements, and as a result, a significant reduction in radon 62


Turkey Brazil

Radon (Bq m23)


activity concentrations can be achieved. However, in areas with inefficient ventilation, high radon levels can be expected. Forced ventilation is very important when operating a bath in natural spas, due to the high relative humidity. The area of a bath is much smaller than that of a mine or cave, and the source of the radon, primarily the spa, is localized and therefore, the ventilation efficiency is high, resulting in relatively low radon activity concentrations. 4.4.3

Comparison of Radon in Homes and Indoor Workplaces

Radon exposures in homes have been monitored in numerous studies and extensive national surveys (Section 6.3.2.6). Radon progeny activity concentrations in mines are subject to regulatory control and are well measured. Surveys in workplaces are sparse and radon activity concentrations in typical workplaces are not well known. Only in the special cases of schools, spas and caves have representative surveys been carried out. Section 4.4.2 describes examples of workplace surveys. Table 4.6 shows example results of occupancyweighted average radon activity concentrations from national or regional workplace surveys, including a comparison with residential surveys. National surveys aiming at a good representativeness in the whole country have been carried out in Japan and Finland. The Italian survey is based on random samples of workplaces and dwellings in the Tuscany area. The results of Table 4.6 indicate that the national average long-term radon activity concentration at workplaces may be higher (Italy and Japan) or lower (USA, Finland) than the corresponding residential exposures by a factor of 3. These national average radon activity concentrations are affected by the national occupancy times at workplaces and the radon activity concentration during working hours. For example, in the case of Finland, occupancy times of 0.73 at home and 0.14 at workplaces, together with the average radon activity concentration listed in Table 4.6, result in a workplace exposure of 5.5%

Table 4.6. Workplace mean (N), median (Bq m23) and dwellings mean (N), median (Bq m23) in national or regional radon surveys in worplaces and dwellings (N is the number of measured sites). Country

Type of workplace

Workplace mean (N), median (Bq m23)

Dwellings mean (N), median (Bq m23)

Reference

USA, NM Japan Italy, Tuscany Ireland Finland

Offices All All Schools All

24.3 (65), 18.5 20.8 (940), 15.3 —, 43 (1159) 93 (4000), — 30 (333), —

75.0 (47), 55.5 15.5, (705) 11.7 —, 32 (1541) 91 (91019), — 104 (520), —

Whicker and McNaughton (2009) Oikawa et al. (2006) Sanada et al. (1999) Bucci et al. (2011) Long and Fenton (2011) Ma¨kelaïnen et al. (2005)

63


relative to residential exposure. Application of the Finnish occupancy factors to the Italian results would give a value of 15%. A representative survey in both workplaces and homes, based on random population sampling, was carried out in Finland (Ma¨kelaïnen et al., 2005). The survey included simultaneous measurements in the homes and workplaces of the 520 participants. In addition, 123 participants had a personal radon monitor in their pocket or handbag during the survey. The questionnaire included a section on time spent at work, at school and outdoors, and possibly time spent at a summer residence (recreational dwelling) during the previous year. The measurements covered a 2-month period, starting from 15 February to 9 April 2001. Table 4.7 shows the key results of the workplace survey. The assessment of radon activity concentration during the daily working hours would be biased if only day-and-night integrating alpha-track dosimeters were used. Therefore, the radon activity concentration in the workplace during working hours was obtained by multiplying the radon activity concentration measured with alpha-track dosimeters by a correction factor of 0.5, defined as the ratio of the average radon activity concentration during working hours to that of the whole week (Annanma¨ki et al., 1996). The arithmetic and geometric means of the dwellings, 104 and 68 Bq m23, are in good agreement with the earlier national survey. The arithmetic and geometric mean workplace activity concentrations of the participants based on integrating detectors were 30 and 20 Bq m23, which is about 30% of the corresponding activity concentration in dwellings (Table 4.7). A 1-week continuous radon monitoring with 1 h measurement period was carried out in 13 randomly selected workplaces in order to determine the ratio of the average radon activity concentration during working hours to that of the whole week. A later analysis of these data gave a mean ratio of 0.55. This is in agreement with the factor of 0.5 used in the study. The minimum and maximum ratios were 0.08 and 0.87, the median was 0.58 and the 25% and 75% quartiles were 0.3 and 0.8. The mean proportion of

MEASUREMENT AND REPORTING OF RADON EXPOSURES Table 4.7. Basic statistics of the radon activity concentrations of the Finnish national home and workplace survey, measured using 2-month alpha-track detectors (Ma¨kelaïnen et al., 2005)

Number Arithmetic mean (Bq m23) Standard deviation (Bq m23) Geometric mean (Bq m23) Geometric standard deviation

Living room

Bed-room

Dwelling mean

Work-place

Personal monitor

Occupancy-weighted radon activity concentration

447 99 151 64 2.4

492 103 165 65 2.4

520 104 159 68 2.4

333 30 40 20 2.6

339 85 122 58 2.2

309 88 118 62 2.2

4.4.4

Thoron in Homes

In most buildings, doses from thoron (220Rn) progeny are a small proportion of those from radon (222Rn) progeny due to the generally low thorium activity concentrations of the building materials. However, recent measurement campaigns reported increased thoron activity concentrations in homes worldwide (McLaughlin, 2010). Indeed, potential alpha-energy concentration levels from 220Rn and its progeny were found to be comparable with those from radon progeny (Bi et al., 2010). Table 4.8 gives a summary of some long-term measurements of indoor thoron gas and its progeny (McLaughlin, 2010).

Figure 4.5. Radon activity concentrations measured by personal monitors versus occupancy-weighted mean radon activity concentration calculated using the participant’s occupancy factors from the questionnaire study and the radon activity concentrations measured at her/his dwelling and workplace in the Finnish national workplace survey, based on 123 observations (Ma¨kelaïnen et al., 2005).

concentration (PAEC) as the existing non-equilibrium mixture. It is estimated from 4.5

Equilibrium Factor EEC ¼ F 222 Rn gas activity concentration ð4:12Þ

Because radon progeny in the air can be removed by deposition on surfaces and ventilation, the activity concentrations of the short-lived radon progeny in the air are not in equilibrium with that of the radon gas. This is quantified by the equilibrium factor, F, which is a measure of the degree of disequilibrium between the radon gas and its progeny. The inhaled decay products and not radon gas deliver the majority of the alpha particle dose to the bronchial airways (see Section 3). Thus, the equilibrium factor is of dosimetric importance because it is used to estimate the progeny activity concentration in air when measurements of radon and not progeny are made. The equilibrium factor, F, is defined as the ratio of the equilibrium equivalent activity concentration (EEC) to the radon gas activity concentration. The EEC is the activity concentration of radon gas, in equilibrium with its short-lived progeny, which would have the same potential alpha energy

Many of the published determinations of the equilibrium factor were based on short-term samples and high sampling air flow that may have affected the equilibrium in interior spaces. The determination of the equilibrium factor requires measurement of both radon gas and its progeny. Radon can be measured using passive detectors, but the progeny usually require electrically operated equipment (see Sections 5.2 and 5.3). If real-time measurement of the Working Level (WL) is made along with radon gas measurements, the equilibrium factor F can be estimated from F ¼ ðWL 3700Þ=222 Rn gas activity concentration ðBq m3 Þ;

ð4:13Þ

based on the original definition of the WL, i.e., 1 WL equals the PAEC associated with radon progeny in 64


the time Finns spent at home or at work/school/ public buildings or outdoors was 0.73, 0.14, and 0.09, respectively. Figure 4.5 exhibits the radon activity concentration measured using the personal monitor versus the occupancy-weighted calculated radon activity concentrations.

Characteristics and Behavior of Radon and Radon Progeny Table 4.8. Recent long-term measurements of indoor thoron and its progeny Country

Number of dwellings

Thoron activity conc. (Bq m23) Mean (Min–Max)

EETCa (Bq m23) Mean (Min–Max)

Korea (2007) Canada (2007) Ottawa Canada (2009) Winnipeg Hungary (2007) China (2004) Shanxi China (2006) Gansu Gejiu Yunnan Ireland (2009) Serbia (2006)

450 93 117 72 193 102 49 29 205 137

40 (?–731) 53 (5 –924) 34 (5 –297) 98 (1 –714) 153 (10–865) 351 (0–1471)

0.89 (? –5.82)

1.6 (0.3–4.9) 2.77 (0.8–5.7)

3297 (39 –7908) 22 (0 –174) 160 (2–945)

10.2 (2–23.9) 0.47 (0.1–3.7)

a

Table 4.9 Summary statistics for measurements of the equilibrium factor F mean and (range), taken from Harley et al. (2012a) Measurements

F

Reineking and Porstendo¨rfer (1990) 79 measurements in 10 rooms Hattori and Ishida (1994) 4500 measurements, 2 nuclear power plants (high ventilation) Hopke et al. (1995) 143 samples in 2 houses with a smoker Hopke et al. (1995) 422 samples in 5 non-smoking houses Clouvas et al. (2003) 4-h measurements for 29 weeks in a lab Clouvas et al. (2003)4-h measurements in 25 apartments Chen and Marro (2011) Grab samples in 12 576 houses Harley et al. (2012a) 3 month measurements in 2 labs and 6 houses

0.30 + 0.1 (0.15, 0.49) 0.30 + 0.1 (0.1, 0.6) 0.48 + 0.11 (0.25, 0.80) 0.38 + 0.17 (0.11, 0.97) 0.62 + 0.09 (0.46, 0.82) 0.47 + 0.09 (0.2, 0.7) 0.54 + 0.15 (0.20, 0.82) 0.75 + 0.12 (0.59, 0.95)

equilibrium with 100 pCi l21 of 222Rn gas. The potential alpha energy is rounded to 1.3 105 MeV l21 of air (2.08 105 J m23). Some selected values of F are given in Table 4.9. UNSCEAR (2008) selected central values for F of 0.4 (indoors) and 0.6 (outdoors). The indoor value was mainly based on measurements in dwellings in the USA (Hopke et al., 1995) and in India (Ramachandran and Subba Ramu, 1994). These selected average values may be subject to change as new measurements are made. If dose is calculated from radon gas measurements, better data (large scale measurements) regarding the equilibrium factor will reduce the uncertainty in the dose estimates. In rooms with additional aerosol sources, such as cigarette smoke, values of the equilibrium factor are usually higher than in clean rooms. At higher aerosol particle concentrations, the unattached fraction is lower as more radon progeny are attached. Since attached radon progeny deposit with a much smaller probability on room surfaces than unattached progeny, higher particle concentrations lead to higher equilibrium factors (Porstendo¨rfer, 1994). For thoron progeny, an F-value is a less useful quantity, since thoron activity concentrations in air vary significantly with position in a room due to its very short half-life (55.8 s), leading to a position-

dependent relationship between thoron gas and its progeny (Tokonami, 2010).

4.6

Unattached Fractions

After decay of radon gas, the freshly formed radionuclides react rapidly with water vapor and possibly H2SO4 to grow from 0.5 nm to clusters of about 1.2 nm diameter (Andreae, 2013; Kulmala et al., 2013; UNSCEAR, 2006). Growth of the particle increases to about 2 nm with ammonia, organic amines, and oxidized organic molecules and from biogenic hydrocarbons stabilizing the growing clusters; the clusters then can grow to 5 nm (Andreae, 2013; Kulmala et al., 2013; Porstendo¨rfer, 2001). These are referred to as the unattached progeny. The unattached progeny diffuses rapidly, attaches readily to other aerosols and surfaces and deposits very efficiently (100%) in the respiratory tract if inhaled. Approximately 60% of the inhaled unattached progeny deposits in the extrathoracic region and about 40% in the bronchial tree. The degree of attachment to aerosol particles depends on the ambient aerosol concentration: X¼bZ 65

ð4:14Þ


EETC is the equilibrium equivalent thoron concentration.


where X is the attachment rate (s21), b the attachment coefficient (m3 s21), and Z the aerosol number concentration (m23) (Porstendo¨rfer, 1994). The radon decay product 218Po is formed as a positively charged atom from radon decay. A fraction of 218 Po atoms are neutralized and as stated above, all 218 Po rapidly form molecular clusters of about 0.5 to 5 nm diameters with water vapor or other constituent molecules. Within 1–100 s, the unattached 218Po may attach to the local aerosol particles. Subsequently, unattached 214Pb atoms may be formed by the decay of unattached 218Po or by the recoil of a fraction of 218 Po from attached 218Po due to the alpha decay (note: since 214Pb is a beta emitter with a half-life of 26.9 min, no unattached 214Bi and 214Po are formed). El-Hussein (1996) determined an average 218Po attachment rate of 0.025 s21in three rooms with different aerosol sources and ventilation rates. This leads to a half-life of a 218Po atom in the unattached state of 27 s. The steady-state activity concentration of unattached 218Po and 214Pb is mainly dependent on the aerosol concentration and can change significantly due to normal aerosol concentration fluctuations (El-Hussein, 1996). Raabe (1969) calculated the attachment coefficient and reported a value of about 1026, while El-Hussein (1996) measured an average value of 1025. Neglecting the removal processes of ventilation and surface deposition, it can be shown that the steady-state fraction of unattached 218Po activity is (Porstendo¨rfer, 1994; Raabe, 1969):

Unattached Fraction, fp, for Radon (222Rn) Progeny

The unattached fraction, fp, is defined as the fraction of the PAEC of the short-lived progeny that is not attached to the ambient aerosol (note: the unattached fractions f218 and f214 discussed in the previous section refer to the individual 218Po and 214Pb activity concentrations). The magnitude of fp primarily depends on the number concentration of particles of the ambient aerosol, Z, and can be estimated with the semi-empirical equation given by Porstendo¨rfer (2001): Radon ð222 RnÞ progeny : fp ¼

414 Z ðcm3 Þ

ð4:17Þ

Porstendo¨rfer (2001) measured fp using a single screen diffusion battery with 50% penetration for 4 nm diameter particles (Section 5.3.3). A condensation nuclei counter was used to measure Z for particle diameters greater than 5 nm. Equation (4.17) agrees fairly well with data for 2000 , Z , 7 105 cm23 (Porstendo¨rfer, 2001). At lower particle concentrations (Z , 400 cm23), the agreement with the data is poor (Cheng et al., 1997). Further, the above equation may underestimate fp in situations where the radon progeny are far from equilibrium, as is the case in some modern mines, which are ventilated at a high rate to reduce radon activity concentrations (Cavallo et al., 1999). The fp values are between 0.03 and 0.08 for “normal” indoor air quality with aerosol particle concentration in the range (5–15) 103 cm23 (Porstendo¨rfer, 2001). Measurements of fp for 222Rn progeny in indoor workplaces such as schools and offices show a wide range of values, typically between 0.03 and 0.15 and with some values greater than 0.20 (Hattori and Ishida, 1994;

ð4:15Þ

and of 214Pb is f214 ¼ l214 ðl218 þ R1 b ZÞ=½ðl218 þ b ZÞðb Z þ l214Þ

ð4:16Þ where, f218 is the ratio of 218Po (unattached)/total 218 Po; f214 the ratio of 214Pb (unattached)/total 214Pb; Z the aerosol particle concentration (cm23); b the attachment coefficient for any species, charged or uncharged (s21) (1025); b Z the attachment rate X (s21); l218, 214 the decay constant for 218Po and 214 Pb; R1 the recoil factor for 218Po. For example, using El-Hussein coefficients, for an aerosol particle concentration of 103 particles cm23, f218 ¼ 0.00379/(0.01 þ 0.00379) ¼ 0.27 or about 27% of the 218Po activity concentration. If the aerosol concentration were to increase to 2 103 cm23, the steady-state unattached fraction of 218Po would be 0.16 or about 16%, a reduction by a factor of almost 2 in unattached activity concentration (Figure 4.6).

Figure 4.6. Unattached fractions as a function of aerosol concentration. Measured attachment coefficients for 218Po and 214 Pb are taken from El-Hussein (1996).

66


f218 ¼ l218 =½b Z þ l218

4.6.1


4.6.2

variation between F and fp based on measurements in indoor air (Marsh et al., 2002). This negative correlation between F and fp has also been observed in a tourist cave (Vaupoticˇ, 2008a). The correlation can be explained as follows for conditions where the ventilation rate is not too high: when the aerosol particle concentration is high, the unattached fraction is low, and the equilibrium factor is relatively high as more of the radon progeny are attached and stay in the air. More stay in the air because plate-out rates (i.e., deposition rates) for the aerosol-attached nuclides are significantly lower than those for the unattached nuclides (Figure 4.4, Porstendo¨rfer, 1994). This is also illustrated in Figure 4.8, which shows the relationship between F and fp as a function of the attachment rate (X) and the particle concentration (Z) (Porstendo¨rfer, 1994; Porstendo¨rfer and Reineking, 1992). Taking account of this negative correlation between F and fp, it has been shown that for indoor air, the radon gas concentration is a better index of dose than the PAEC under a range of aerosol conditions normally encountered (James et al., 1988; Marsh and Birchall, 1998; Vanmarcke et al., 1989; Vargas et al., 2000). UNSCEAR (2008) reported a similar range of dose factors with the values of fp normally observed. On this basis and because of some practical considerations, such as less complex and expensive equipment, radon gas measurements are generally carried out in homes and indoor workplaces. However, in mines with forced ventilation, a consistent correlation between F and fp is unlikely, so control of radon exposure in mines is typically in terms of PAE exposure. The actual relationship between F and fp depends primarily on the ratio of the deposition rates of the attached and unattached radon progeny (q a/q u). The deposition rate q depends on the surface to volume

Correlation Between Equilibrium Factor, F, and Unattached Fraction, fp, for 222Rn

For 222Rn and its progeny in indoor air, F is negatively correlated with the unattached fraction, fp (Chen et al., 1998; Huet et al., 2001a; Marsh et al., 2002; NA/ NRC, 1991; Tokonami et al., 1996b; Vanmarcke et al., 1989; Vargas et al., 2000; Vaupoticˇ, 2007; Vaupoticˇ and Kobal, 2006). As an example, Figure 4.7 shows the

Figure 4.7. Variation of unattached fraction with equilibrium factor in indoor air. Adopted from Marsh et al. (2002). Measurements were carried by Huet et al. (2001a; 2001b), Reineking and Porstendo¨rfer (1990), and Vargas et al. (2000).

67


Hattori et al., 1995; Porstendo¨rfer, 2001; Tokonami et al., 1996a; Vaupoticˇ, 2008a; Yu et al., 1998). Similar values have also been measured in dwellings (Chen et al., 1998; El-Hussein, 2005; Hopke et al., 1995; Huet et al., 2001a; Kojima and Abe, 1988; Kranrod et al., 2009; Mohamed, 2005; Reineking and Porstendo¨rfer, 1990; Tokonami et al., 1996b; Vargas et al., 2000; Yu et al., 1996). In working places with additional aerosol sources due to technical processes, combustion and human activities, the particle concentration can be high (. 4 104 cm23) and, as a consequence, the fp value is low (around 1% or less) (Porstendo¨rfer, 2001). However, fp is greater than 0.10 for poorly ventilated rooms (ventilation rate , 0.5 h21) without additional aerosol sources, rooms with an operating air cleaner, and poorly ventilated underground caves. In such places, the particle concentration may be less than 4 103 cm23. For example, El-Hussein (2005) measured fp and particle concentrations in 25 rooms of different houses with low ventilation rates (, 0.3 h21). The particle concentrations ranged from 1.2 103 to 5 103 cm23 and the corresponding fp values ranged from 0.02 to 0.22 with a mean of 0.09. The relative activity ratios of unattached radon progeny (218Po:214Pb:214Bi) in indoor air have been measured to be approximately 1:0.1:0 (Kojima and Abe, 1988; Reineking and Porstendo¨rfer, 1990). Thus, most of the unattached activity is associated with the 218Po. More recently, El-Hussein et al. (1999) measured a higher activity ratio of about 214 Pb/218Po ¼ 0.5 for unattached progeny in closed room air. For the attached progeny, the measurements gave mean values around 214Pb/218Po ¼ 0.7 and 214Bi/218Po ¼ 0.5. Although the relative activity concentrations of the individual radon progeny will vary with environmental conditions of exposure, the equivalent dose to the lung per WLM is relatively insensitive to these ratios (Marsh and Birchall, 2000). In contrast, the dose per WLM is very sensitive to the unattached fraction. Although the unattached fraction is small compared with the attached fraction, it has a disproportionately large effect on the bronchial dose because of its greater deposition efficiency in the bronchial region.


compared with that of the radon progeny. Therefore, the fp value for the thoron progeny is lower than that for the radon progeny under the same conditions. The semi-empirical equation of fp for thoron progeny derived by Porstendo¨rfer and his colleagues is given by Equation (4.18) (Porstendo¨rfer, 2001). Reasonable agreement was obtained between Equation (4.18) and the data of Tschiersch et al. (2007), for 900 , Z , 3 104 cm23. Thoron ð220 RnÞ progeny : fp ¼

150 Z ðcm3 Þ

ð4:18Þ

4.7.

Aerosol particle size for radon decay products is defined as their activity median diameter in air. Specific definitions include thermodynamic diameter, the diameter of a spherical particle that has the same diffusion coefficient in air as the particle of interest and aerodynamic diameter which is approximately equal to the physical (volume equivalent) diameter of the particle times the square root of its “effective density.” The effective density is the ratio of the density to its shape factor. The particle size distribution for radon progeny has predominantly two modes, the unattached diameter from 0.5 to 5 nm and the attached from 100 to 450 nm (accumulation mode), with medians of about 1–2 and 100 –300 nm, respectively. Sinclair et al. (1974) were the first to measure activity size distributions in indoor and outdoor air. NCRP (1984) summarized particle size distributions measured in New York and New Jersey residences and showed unattached and attached median diameters of 1 and 125 nm, respectively. Other attached modes are sometimes observed; these are the nucleation mode, with diameters of 10s of nanometer and the coarse mode, with diameters of a few 1000s of nanometer. These are typically introduced when there is a specific source such as small aerosols released in cooking or large aerosols from dispersion activities. However, the nucleation mode has also been measured for an aged aerosol (i.e., without additional aerosols) in a moderately ventilated room and in closed rooms of

Figure 4.8. The unattached fraction (fp) and the equilibrium factor (F) in rooms with different aerosol sources as a function of the attachment rate (X) and particle concentration (Z). Taken from Porstendo¨rfer (1994).

ratio (S/V) and the deposition velocity (vg) [Equation (4.11)], which in turn depends on the particle size and the roughness of the surface (Figure 4.4). Since the ratio S/V is the same for both attached and unattached radon progeny, the ratio of the deposition rates varies with surface roughness, as unattached radon progeny may experience a rougher surface than the larger attached radon progeny. Thus, the roughness of the surface areas of the room as well as the particle size distribution are factors that affect the relationship between F and fp. The ventilation rate and the radon entry rate also affect this relationship. 4.6.3

Aerosol Size Distributions

Unattached Fraction, fp, for Thoron (220Rn) Progeny

There are fewer published measurements of fp for thoron progeny compared with radon progeny. However, because of the relatively long radioactive half-life of the thoron decay product 212Pb (10 h), more of the 212Pb is likely to become attached 68


The unattached fraction of thoron progeny (220Rn) for “typical” indoor air with aerosol particle concentration of (5 –15) 103 cm23 is between 0.01 and 0.03 (Porstendo¨rfer, 2001). From measurements of outdoor and indoor 212 Pb/220Rn ratios, UNSCEAR (2008) has assumed average equilibrium factors of 0.003 for outdoors and 0.02 for indoors.


houses (Porstendo¨rfer, 1996; Reineking et al., 1994) (Section 7.5.2). As an example of a typical measurement in a typical home, Figure 4.9 shows the relative size distribution of the PAEC of radon progeny in indoor air in closed rooms of homes, i.e., without additional aerosol sources (Porstendo¨rfer, 1996). For comparison, Figure 4.10 displays the relative activity size distributions of the short-lived radon and thoron progeny 214Po and 212Po in outdoor air, averaged over a three-week measurement campaign (Gru¨ndel et al., 2005). Aerosol size distributions or radon progeny activity size distributions for specific atmospheres are summarized in NA/NRC (1999a). Aerosol size distributions were measured in rooms with a gas stove or side-stream cigarette smoke (Li and Hopke, 1993), 218 Po and214Po activity size distributions in closed rooms, with or without aerosol sources (Reineking and Porstendo¨rfer, 1986), and 218Po distributions in rooms with cooking, cigarette smoke, or a kerosene heater (Tu and Knutson, 1988). These and other published activity size measurements are summarized by Marsh et al. (2002) including those measurements carried out in rooms with aerosols produced by smoking, cooking, gas combustion, tiled stove heating, fumigating sticks, candle burning, and by electric heaters. Although the published activity size distributions to date appear to have similar activity median diameters (Section 7.5), some effort should be made to obtain recent measurements over a wide range of conditions, especially in new buildings. Building

Figure 4.10. Relative activity size distributions of 214Po and 212Po in outdoor air, averaged over a 3-week measurement campaign (Gru¨ndel et al., 2005).

codes have changed in the past two decades due in part to radon reduction and energy-efficient techniques and new construction materials. Volunteer studies and research studies with casts of the human lung demonstrate that the particle size 69


Figure 4.9. Relative size distribution of the PAEC of radon progeny in indoor air in closed rooms (Porstendo¨rfer, 1996).


of an inhaled aerosol along with breathing rate are the major factors controlling the site and amount of deposition in the respiratory tract (Section 3.7). Therefore, bronchial dose models rely mainly on the

assumed aerosol particle size distribution. Better precision in dosimetric modeling will be obtained with more global information on particle size distribution in a variety of residential conditions.


70



5. Principles of Radon and Radon Progeny Detection Systems and Measurements

5.1.1

General Aspects

Performing a measurement that is able to contribute to a scientific or legal purpose implies that the measurement should be suited to the purpose with regard to (1) its capability (e.g., measured quantity, sampling type, long- or short-term measurement), (2) its physical properties (e.g., maintained accuracy, traceability, uncertainty, detection limit, range of application), and (3) cost efficiency (e.g., instrument cost, man power, quality assurance expenses). Before it can be used as a basis for a further study, for example, radon mapping or epidemiology, existing data should be assessed with regard to criteria 1 and 2. Data that will be assessed in the future must be characterized precisely to choose an optimal method with regard to all three criteria. The design of a study has to yield all information that is required for criterion 1, in particular, the usability of the measurand or measurands, which can be activity concentration, potential alpha energy concentration, equilibrium factor, unattached and attached fraction, exposure to radon, or exposure to radon progeny. Depending on the aim of the study, each of these quantities alone or in combination can be an appropriate choice. The sampling type can be either grab, continuous, or integrating. This is normally a characteristic quality of a special type of device and sometimes linked to the duration of a measurement. Thus, for example, solid-state nuclear track detectors (SSNTD) are integrating devices used for long-term measurements (normally weeks or months). In the case of high levels of radon activity concentration, short-term measurements with these devices can also be appropriate. The physical properties of a measurand must be identified from the data of the producer of the device (data from qualification or type tests), from calibration

certificates of the respective devices used in the measurement, and from international standards. The economic consideration in the choice of a measurement principle should include the costs of operation, man-power for the analysis of the data, and also quality assurance. The concepts of metrology and quality assurance relevant for radon and radon progeny measurements as well as examples for the analyses of uncertainties in the calibration by a primary radon activity standard and in interlaboratory comparisons are summarized in Appendix A. 5.1.2

Comparisons of Radon Measurements

Until now, numerous radon comparisons have been performed worldwide. In the 1980s, the rising concern about radon-induced lung cancer triggered the start of global comparison programs based on a common radon atmosphere in which multiple radon and radon progeny detection systems (active as well as passive ones) were exposed. The Organisation for Economic Co-operation and Development (OECD)/ Nuclear Energy Agency and the Commission of the European Communities (CEC) ran the “Programme on radon and thoron dosimetry”, starting in 1983 (OECD, 1985). The responsibility for managing the program was shared by the former Australian Radiation Laboratory (ARL) for the Pacific region, the US Department of Energy (DOE), the former Environmental Measurements Laboratory (EML), and the US Bureau of Mines for North America, as well as the former National Radiological Protection Board (NRPB) (now Public Health England) for Europe. Following this line of work, the International Atomic Energy Agency (IAEA) drew up an “International Radon Metrology Programme” together with the CEC, beginning in 1992. Measurements were performed at EML in 1990, 1992, 1994, 1995, and 1996 and at the US Environmental Protection Agency (EPA) in 1994. These international programs were flanked by multiple national efforts. For example, the Environmental Measurements Laboratory of the US Department of Energy developed



5.1 Radon and Radon Progeny Metrology and Quality Assurance of Measurements


a 2.82 2.82 2.4 m calibration chamber and performed calibrations based on a National Institute of Standards and Technology (NIST) Standard Reference Material (SRM) 226Ra solution. The chamber calibrations were performed using 2 l pulse ionization chambers (Fisenne et al., 1990). To summarize the many comparisons, it can be noted that these programs provided: - a large database on different radon and radon progeny measuring systems in different applications, - a basis for the new development of detectors and analytical methods, and - routines for quality assurance. In view of the many radon quantities measured in parallel in these comparisons, they were not able— and also did not intend—to provide modern metrological information like uncertainty budget, traceability information, and correlation analysis (ISO 17025) (ISO, 2005). Due to the “Arrangement on the mutual recognition of the equivalence of national standards and of calibration certificates issued by national metrology institutes (MRA)” in 1999, the situation for metrological comparisons changed drastically. Since then a comparison has to deal with a single quantity, the result of each participant has to be given in the form of a value with an assigned uncertainty. Furthermore, the uncertainty budget for the calculation of the result has to be included, as well as the information about the traceability of each input quantity to national or international standards. These restrictions are fundamental for the assessment of the result of each participant with regard to the comparison reference value (CRV). In the case of radon, there is an additional characteristic to be taken into account: the respective quantities can only be realized by use of a reference atmosphere which cannot be transported (Honig et al., 1998). Therefore, a comparison of the radon activity concentration can only be performed by applying a transfer standard (the CRV is the calibration factor of the transfer standard, i.e., a secondary standard) or by using a common reference atmosphere (the CRV is the activity concentration). The first approach has the advantage of comparing the quality of the realization of reference atmospheres in a realistic way: Each participant works at his radon chamber according to a well-established quality system. Moreover, the usage of a primary standard is possible (Paul et al., 2002). The system under test and the 222Rn gas activity standard are enclosed in the chamber. The activity concentration chosen for the point of calibration is calculated and 72


compared with the reading of the system under test for the calculation of the calibration coefficient. After calibration, the system under test can now be used as a transfer or secondary standard. A calibration by a secondary standard is based on a comparison of the system under test to a reference instrument (secondary standard) which was calibrated in or traceable to a reference atmosphere in the past. The radon activity concentration chosen for the point of calibration is established, and both systems are exposed to it. The reading of the reference instrument and the system under test are observed simultaneously for the calculation of the calibration factor. The second approach of a common reference atmosphere for the conduct of the comparison has the advantage of providing the CRV in a shorter time, but it does not achieve uncertainties as small as the first approach. In the BIPM key comparison database, an example of each approach can be found: the European Association of National Metrology Institutes (EUROMET) has EUROMET.RI(II)-S1.Rn-222 (identical to Euromet project 657) (Ro¨ttger et al., 2005; 2006) for the first approach using 1, 3, and 10 kBq m23 radon activity concentrations for the point of calibration and the Euro-Asian Cooperation of National Metrology Institutions (COOMET) has COOMET.RI(II)-S1.Rn-222 (2009) for the second approach. The Euromet comparison demonstrated the ability of all 12 participants to perform a calibration of the radon activity concentration with an uncertainty below 12% for a level of confidence of 95% (Figure 5.1), indicating a satisfactory degree of equivalence. The smallest uncertainty was below 3% for a level of confidence of 95%. The results of most participants of a radon comparison are correlated due to the common traceability to one single radon gas standard producer. This makes a careful correlation analysis necessary to achieve an appropriate CRV. The Coomet comparison (COOMET.RI(II)S1.Rn-222, 2009) demonstrated the ability of six participants to measure the radon activity concentration simultaneously in the range of 75 Bq m23 to 12 kBq m23 in a stable reference atmosphere created at the National Scientific Center, Institute of Metrology (NSC IM) Kharkiv, Ukraine. The degree of equivalence was found to be satisfactory, although it has to be mentioned that in the lower activity range (,1 kB qm23), the uncertainties were much higher than the typical uncertainties (4–15% at a level of confidence of 95%) reached in the other activity ranges. In addition to comparisons of national institutes, there are also interlaboratory radon comparisons

Radon and Its Progeny Detection Systems and Measurements

taking place. As a rule, comparisons are conducted by recognized reference laboratories. Interlaboratory radon comparisons help to ensure a uniform quality standard and will preferably be organized for passive radon instruments (nuclear track detectors, activated charcoal detectors, electrets). The comparisons are often used for the purposes of determining the performance and surveillance of approved radon services. Regular annual radon intercomparisons are conducted by various test institutions. The intercomparisons are designed for instruments using solid state nuclear track detectors, electrets, or activated charcoal detectors and run with similar procedures: radon services submit a sufficient number of instruments of the same type to the provider of an intercomparison. Depending on the applied test scheme, devices are randomized and grouped according to the number of exposures. The number of instruments to be submitted depends on the number of exposures and the need for additional transfer instruments being used for measurement effects during storage and delivery. After exposure, the instruments are returned to radon services in order to determine the exposures to radon and report the results to the provider of the intercomparison. Finally, the provider prepares a report with the measurements and reference data. Radon services interested in participating in a radon intercomparison can get further information about providers and organizational conditions from the European Information System on Proficiency Testing Schemes (eptis) available via the Internet.

5.2 5.2.1

Radon Gas (222Rn, 220Rn) in the Environment

Radon Measurement Methods

Because radon is ubiquitous and soluble in water, it is present in air, water, and soil. The final quantification of radon activity concentration usually occurs in an air sample as radon is a gas under atmospheric pressure and temperature. To measure the activity concentration of radon in water, either the radon is extracted by bubbling air through the water or the radon is measured directly using liquid scintillation techniques where the water sample is mixed with a scintillation cocktail (Section 5.2.1.2). Both active and passive methods can be used to measure radon. For the active method, an air sample is forced by pressure into the measuring chamber, while for the passive method, movement due to natural diffusion takes place. In terms of the sampling time, the measurement methods can be categorized into three different methods: grab sampling, short-term continuous sampling, and time-integrating sampling (longterm) (NCRP, 1988). For the grab sampling method, the sampling duration is several seconds, minutes, or hours and the result reflects the radon activity concentration at the time of the measurement. For short-term continuous sampling, the sampling duration is several hours or days and the radon activity concentration is registered typically for 30, 60 min, or 2 h intervals. In this case, the temporal fluctuation of the radon activity concentration can be detected. For time-integrating sampling, the 73


Figure 5.1. Results of the Euromet comparison 657 at an activity concentration of 10 kBq m23 for the obtained calibration factor k of the participants identified by code: i ¼ 1 . . . N (1, PTB; 2, BfS; 3, STUK; 4, BEV; 5, ARCS; 6, Inte-UPC; 7, IRSN; 8, SUJCHBO; 9, PSI; 10, SSI; 11, HPA; 12, MPA).


5.2.1.1 Airborne Radon Grab Sampling. Most radon grab sample techniques use an alpha scintillation cell which was introduced in the 1950s by Damon and Hyde (1952), Lucas (1957), and Van Dilla and Taysum (1955). There are two methods for collecting a representative air sample. In the first method, an air sample is drawn directly into the alpha scintillation cell by a vacuum pump. The second method is one of the older and simpler methods of radon sampling, which is performed with an airtight, radon proof collapsible bag to sample air over the desired sampling time period (Pohl and Pohl-Ru¨ling, 1976; Sill, 1977). After the sampling period, the activity concentration of radon in the bag is transferred to a scintillation cell. The main purpose of the collapsible bag is to avoid the variation in pump flow rate due to build-up of back pressure in a container. The pump flow rate is not critical as long as it is suitable for the size of the bag and the sampling duration. However, variation of the flow rate over the collection time period of the sample will affect the accuracy of the measurement, thus requiring pumps with controlled flow rates. To measure the radon activity concentration, the scintillation cell is sealed after air sampling, either by direct collection or via collection in a bag. The inner surface of the cell is coated with zinc sulfide (ZnS), which emits pulses of light (scintillations) when struck by an alpha particle. To count these scintillations, the cell, which is fitted with a clear window, is optically coupled with a photomultiplier tube. The scintillations resulting from alpha particles emitted by the radon and the radon progeny in the air sample are counted. After a few hours, approximate secular equilibrium is reached and the pulse rate is proportional to the radon activity concentration in the cell. Advantages of these techniques include their sensitivity and the rapidity with which the results can be obtained. Some disadvantages include the fact that radon levels can show large spatial and temporal variations. The detection limit of these techniques depends on the size of the scintillation cell, the background level, or sensitive volume, and ranges from 1 to 37 Bq m23 for a 30 min counting interval (George, 1996).

Time-Integrating Sampling. This method is often used in national radon surveys for human exposure or dose estimation and in epidemiological studies. Integration over a long period of time has the advantage to average out short-term fluctuations of radon levels due to diurnal and seasonal variations. The sample collection occurs in a passive way, by diffusion, using a diffusion container with a radon detector, e.g., a solid-state nuclear track detector (SSNTD) or an electrically charged teflon disk inside it. In the container, the temperature gradients are

Short-term Continuous Sampling. Independent of the short-term sampling method, a filter medium 74


is applied which admits radon gas but inhibits the entry of its progeny into the measuring chamber. Both direct ( pulse ionization chamber) and indirect (electric field collection) detection methods can be used. During the active sampling in the electric field collection method, radon enters the measuring chamber via a filter medium. Positively charged 218 Po is formed from the decay of radon in the sampling air of the chamber (Dua et al., 1983). The positive 218Po ions are collected electrostatically on the negative electrode of a semiconductor detector. The advantage of the continuous sampling device is that a temporal variation of radon activity concentration can be observed. The disadvantage is the cost, the noise of the pump, and the requirement of electric power if the operation is longer than about 2 weeks. A commonly applied passive method uses an activated charcoal collector, where the collector allows continuous adsorption on the active sites of the carbon beds (George, 1984; Kappel et al., 1993). The most useful configuration has a diffusion barrier to separate the charcoal from the ambient air which improves the uniformity of response to variations of radon activity concentration with time. In addition, it is well known that charcoal is also a very good absorber of water vapor, which can reduce the adsorption efficiency for radon, thus requiring a moisture correction (Iimoto et al., 2004). During the measurement period (typically 2–7 d because the half-life of radon is only 3.8 d), the adsorbed radon undergoes radioactive decay. A device commonly used by several groups consists of a circular container filled with activated charcoal (George, 1984; Kappel et al., 1993) or a specially designed plastic scintillation vial with a small, porous cartridge, containing charcoal, fixed near the top of the vial (Kappel et al., 1993; L’Annunziata, 2003; Passo and Floeckher, 1991). After exposure, the device is tightly sealed to maintain maximum sensitivity and returned to a laboratory for the analysis of the quantity of radon adsorbed by using gamma spectrometry or liquid scintillation (Carnoba et al., 1999).

sampling duration may be either days, months, or 1 year. The result is given as the integrated average and therefore provides no information about the temporal change in radon activity concentration within the duration of the measurement.


Figure 5.2. Membrane tube system for continuous measurement (Surbeck, 1996).

5.2.1.2 Waterborne Radon. Radon in water can be determined by measuring the radon released by bubbling air through the water. This measurement is a typical grab sampling method where many active devices can be applied (Cosma et al., 2008; Somlai et al., 2007a; Todorovic et al., 2011; Zmazek et al., 2002). Continuous measurements are also available by using gas transfer membranes for radon and water separation (Figure 5.2) (Surbeck, 1996). Passive measurements are carried out with SSNTDs and gas transfer membranes (Tommasino et al., 2012). An alternative passive grab sampling method is the use of a liquid scintillation counter (LSC), where the water sample containing radon is mixed with a scintillation cocktail, e.g., Toluene (Prichard et al., 1992; Salonen, 2010; Yasuoka et al., 2004; Yokoyama et al., 2011). Figure 5.3 shows the pulse-height spectrum in an LSC produced by radon and its progeny in water. For long-term measurements, SSNTDs are also used as cheap and simple detection materials (Figure 5.4) (Marques et al., 2004; Va´sa´rhelyi et al., 1997). In this radon measurement device, radon diffuses from the water sample into the airspace above. The fiberglass filter reduces vapour entry and avoids thoron entry into the detection volume.

Figure 5.3. Pulse height spectrum of radon and its decay products obtained in a typical radon-in-water measurement by LSC (Yasuoka et al., 2004).

Figure 5.4. Device for the long-term measurement of radon in water (grab sampling) using an SSNTD detector (Marques et al., 2004).

5.2.1.3 Soilborne Radon. When radium decays in soil grains, a fraction of the resulting atoms escape from the mineral grains to air-filled pores— this is referred to as emanation. The radon gas is subsequently transported through the pores of the material and some of it reaches the surface before decay. The amount of activity released per unit surface area and per unit time is the exhalation rate.

Exhalation Measurements (In situ). Radon exhalation from the ground surface affects both indoor and outdoor radon activity concentrations. Therefore, it is important to clarify the exhalation process of radon from the soil to the atmosphere. Moreover, measurement of the radon exhalation rate is applied to 75


small, which reduce the effect of convection inside the chamber and hence plate-out on the SSNTD or electric charging of the teflon disk (Frank and Benton, 1973). Some designs use a plastic bag as a filter for the whole detecting device (Durrani and Ilic, 1997; Nikezic and Yu, 2004; Tommasino et al., 1986). For measurement of indoor radon activity concentrations, exposures of 3 months to 1 year are required, because this technique is not sensitive to low level radon. A new type of personal exposure meter for radon gas has been developed for the purpose of individual monitoring (Karinda et al., 2008). Since this meter is based on a passive technique, it is applicable to indoor measurements over a long period of time and is thus particularly suitable for epidemiological studies (see Section 5.5.1).


where IRn is the production rate of radon (s21), lRn the decay constant of radon (s21), V the volume of the accumulation chamber (m3), and v the sampling flow rate (m3 s21). The radon atom concentration in the accumulation chamber is obtained with Equation (5.3), where C is the constant of integration, NRn ¼

For the initial condition (t ¼ 0, NRn ¼ 0) in Equation (5.3), the constant of integration C is calculated by Equation (5.4), C¼

Continuous and Grab Sampling (Active). For a continuous measurement system, a ventilation-type accumulation chamber is used for radon exhalation rate determination. A diagram of the flow-through exhalation rate measurement system is shown in Figure 5.5 (Hosoda et al., 2011). The accumulation chamber is set on the ground surface. The air inlet fixed at 2 m above the ground surface is connected by a tube to the accumulation chamber inlet. The air in the accumulation chamber is continuously drawn into the scintillation or Lucas cell (Lucas, 1957). A manometer connected to the accumulation chamber outlet measures the pressure difference between inside and outside the accumulation chamber. The radon atom concentration NRn (m23) in the accumulation chamber is evaluated with Equation (5.2), VdNRn ¼ IRn dt lRn VNRn dt NRn vdt

IRn C þ eðlRn þðv=V ÞÞt ðlRn þ ðv=V ÞÞV lRn þ ðv=V Þ ð5:3Þ

IRn V

ð5:4Þ

When Equation (5.4) is substituted into Equation (5.3), Equation (5.5) is obtained, NRn ¼

IRn f1 eðlRn þv=VÞt g ðlRn þ ðv=VÞÞV

ð5:5Þ

The radon activity concentration ARn (Bq l21) is obtained with Equation (5.6) using Equation (5.5), ARn ¼

lRn IRn f1 eðlRn þv=VÞt g ðlRn þ ðv=VÞÞV

ð5:6Þ

The generation rate of radon activity ERn (Bq s21) is then evaluated with Equation (5.7) using Equation (5.6)

ð5:2Þ

ERn ¼ lRn IRn

v VARn lRn þ V ¼ v lRn þ t V 1e

ð5:7Þ

Thus, the exhalation rate of radon JRn (Bq m22 s21) can be estimated with Equation (5.8),

JRn

v VARn lRn þ V ¼ v ! t lRn þ V S 1e

ð5:8Þ

where S is the surface area under the accumulation chamber (m2). Grab sampling measurement is also possible using a ventilation-type accumulation chamber. The radon exhalation rate JRn by grab sampling is estimated with Equation (5.9), obtained from

Figure 5.5. A flow-through exhalation rate measurement system.

76


research fields such as health physics, environmental science, and geosciences (Ishimori and Maruo, 2005; Lawrence et al., 2009; Sahoo et al., 2010; Somlai et al., 2006b). In environmental science, radon can be used as a tracer for the evaluation of the environmental behavior of air pollutants (Iida et al., 1996). Data on radon exhalation rate from a soil surface are needed for a calculation model of atmospheric transport (Sakashita et al., 2004). In geosciences, the relationship between the behavior of exhaled radon and earthquakes has been studied for more than 30 years. Increases in radon activity concentration in soil, ground water, and the atmosphere as precursor phenomena of earthquakes have been reported by many researchers (Igarashi et al., 1995; Yasuoka and Shinogi, 1997).


Figure 5.7. Schematic diagram of the experimental system used to evaluate the emanation coefficient of radon.

Equation (5.8). JRn ¼

lRn VARn Sð1 elRn t Þ

ð5:9Þ Emanation (Ex situ). The emanation coefficient is the fraction of radon formed in the soil grains that escapes into the pores. In other words, the ratio between the radon that escapes into the pore spaces to the total amount of radon generated (equivalent to the radium activity concentration in the case of secular radioactive equilibrium between radon and radium). An accumulation method has commonly been used to calculate the radon emanation coefficients from soils, rocks, and building materials (Chao et al., 1997; Hosoda et al., 2009; Tuccimei et al., 2006). An airtight accumulation chamber equipped with a scintillation cell monitor is used to measure the emanation coefficient. Each sample is enclosed in an accumulation chamber as shown in Figure 5.7 for 1– 3 d. The emanated radon is transferred from the accumulation chamber to the scintillation cell. In general, the radon activity concentration in the accumulation chamber will increase gradually until it reaches a secular radioactive equilibrium activity concentration (Aeq) after about 30 d. This equilibrium activity concentration in the accumulation chamber is considered to be equal to the radon activity concentration in the pore space amongst the solid grains. The growth curve can be expressed as

Grab Sampling (Passive). Radon and thoron exhalation rate measurements can be accomplished using a special scintillation cell system (Figure 5.6) (Sa¨gusa et al., 1996; Shimo et al., 1994). It is composed of the accumulation chamber (skirt section) that covers the ground, scintillation detector with aluminized Mylar sheet, light guide, photomultiplier tube, pulse counter, and timer. A large-area acrylic sheet is coated with a ZnS(Ag) scintillator. This ZnS(Ag) scintillator is connected to a photomultiplier tube via a tapering light-guide. The purpose of the skirt section is to collect radon and thoron gases that are exhaled from the ground surface. Measurements can be recorded over consecutive 30 s intervals during a total recording period of 30 min. The thoron exhalation rate JTn is obtained by the following formula: ð5:10Þ JTn ¼ ðN10 Nb ÞCFT where N10 is the count rate 10 min after the start of the measurement (cpm), Nb the count rate of the background (cpm), and CFT is the calibration coefficient for 220Rn. Since the count rate of 220Rn and its decay product (216Po) reaches equilibrium 7–8 min after starting the measurement, the count rate at 10 min is used for N10. On the other hand, the count rate of 222Rn and its decay products (218Po and 214Po) is based on the count rate after 30 min. The radon exhalation rate JRn is obtained by the following formula:

At ¼ Aeq ð1 exp ðltÞÞ

ð5:11Þ JRn ¼ ðN30 N10 ÞCFR where N30 is the radon count rate 30 min after the start of the measurement, and CFR is the calibration coefficient for 222Rn.

ð5:12Þ

where At is the activity concentration of radon measured at time t (Bq m23), t the accumulation time of the sample (s), and Aeq the radon activity concentration in equilibrium (Bq m23). The radon emanation 77


Figure 5.6. Diagram of the system used for simultaneous in situ measurement of radon and thoron exhalation rates from the ground.


depth, but deploying them in a pipe is also possible using an automatic exchanger (Chavez et al., 1997).

coefficient can be defined as (Morawska, 1989): Aeq V ð5:13Þ ARa M where f is the radon emanation coefficient; ARa the radium activity concentration of the sample (Bq kg21), which can be determined by gamma spectrometry; V the gas empty volume (the chamber volume minus the sample volume, m3); and M the sample mass (kg). f ¼

5.2.2.

Radon Detection Systems

Soil Gas Measurement (In situ). The measurement of soil gas radon can use either active or passive methods. These measurements are usually made for geological purposes. As it is an in situ measurement, grab-sampling is the most widespread method using a scintillation cell system or other measuring systems (Buzinny et al., 2009; Genrich, 1995; Neznal et al., 2004a; Papastefanou, 2007; Shweikani and Hushari, 2005). For the sampling, a sampling probe is used, collecting soil gas from a depth of 50– 100 cm. Continuous measurement is also possible using a soil air flow system (Figure 5.8) (Fronˇka et al., 2008). In the case of the passive method, the SSNTDs are the preferred method with maximum 1– 2 weeks exposure time as radon activity concentrations with some hundreds kBq m23 occur in the soil gas, which due to track density saturation effects may exceed the high level detection limit (Mazur et al., 1999; Tanner, 1991). The track detectors are usually placed in a protective chamber and buried at some

Scintillation Detector. The different types of the scintillators can be divided into two large groups: (1) Inorganic scintillators (2) Organic scintillators. For radon measurements, the most frequently used inorganic scintillator material is the ZnS(Ag). A typical application is where the inner part of an alpha scintillation cell, apart from its window, is coated with ZnS(Ag) (alpha scintillation cell) and is optically coupled to a photomultiplier tube. The most common detector based on this procedure for radon measurement is the alpha scintillation cell. The device has become known as the Lucas cell as it was developed by Lucas (1957). The flask designed by Lucas has the shape of a right circular cylinder with a hemispherical cap. Its diameter and volume are 5 cm and 100 cm3, respectively. Typically, the detection efficiency is 75–80% and its background count rate is about 0.1 cpm. Under these conditions, the uncertainty in measuring a sample containing 10 Bq m23, using a 3 h measurement and backgroundcount intervals, is about 30%. Improved efficiency may be achieved by extracting radon from a larger volume of air and transferring it to the cell (Ingersoll et al., 1983; Lucas, 1957). Gas-Filled Detector. The various types of gas-filled detector include: (1) Ionization chambers (2) Proportional counters (3) Geiger Mueller (GM) counters. For radon measurements, the pulse ionization chamber (PIC), i.e., an ionization chamber operated in the pulse mode, is frequently used. In this case,

Figure 5.8. Continuous soil radon monitoring system (Fronˇka et al., 2008).

78


For radon measurements the a-particle detection method is the primary one as radon, during its decay, emits a-particles exclusively, while the shortlived decay products of radon emit a-, b-particles and g-rays, depending on the individual radionuclide (see Section 4.2). The method, when detection focuses on a-particles from radon and its progeny, is called the direct method. For the indirect method, only a- or b-particles or g-rays emitted from radon progeny are detected by the two-filter method (Thomas and Leclare, 1970) or the electrostatic collecting method (Iimoto et al., 1998) and the radon activity concentration is recalculated from these data (Figure 5.9).


In addition, silicon PIN photodiodes are often used as a relatively cheap detector (Ui et al., 1998).

no charge multiplication takes place and the output signal is proportional to the particle energy dissipated in the detector. Since the signal from an ionization chamber is not large, only strongly ionizing particles such as alphas, protons, fission fragments, and other heavy ions are easily detected by such detectors.

Solid-State Nuclear Track Detectors. The most widely used technique for integrating measurements of radon activity concentration is based on plastic or polymeric materials (Durrani and Ilic, 1997; Nikezic and Yu, 2004). These materials are often called solidstate nuclear track detectors (SSNTD) or alpha-track detectors. The most common materials in use for radon detection are cellulose nitrate (CN) film, poly-allyl-diglycol carbonate (PADC), and polycarbonate (PC) plastic. The passage of an alpha particle through an SSNTD produces a narrow primary damage trail or latent track along the length of its path in the material (typically 20–70 mm), which can be made visible by chemical or electrochemical etching (Table 5.1). The use of such alpha track detectors for passive long-term integrating measurements of indoor radon is very popular for large-scale surveys (Alter and Oswald, 1983; 1987). Several designs of measuring devices have been used for indoor radon surveys, for example, bare technique, diffusion technique, etc. Details of these devices can be found in recent publications (Azimi-Garakani et al., 1988; Bartlett et al., 1986a, 1986b; Mellander

Semiconductor Detector. The following different types of semiconductor detectors may be used: (1) (2) (3) (4) (5) (6)

Surface-barrier detector Diffused-junction detector Silicon lithium-drifted detector Germanium lithium-drifted detector Germanium or high-purity germanium detector CdTe, CdZnTe, and HgI2 detectors.

For radon measurements, surface-barrier detectors are most commonly used in two-filter measurement systems (Brunke et al., 2002; Tokonami et al., 1996c; Whittlestone and Zahorowski, 1998) or in electrostatic collection (Iida et al., 1991; 1996; Iimoto et al., 1998) indirect measurement methods as it can provide a high resolution spectrum of particle energies. Due to the energy discriminative ability of this detector, thoron analysis is also possible (Durridge, 2000; Iimoto et al., 1998). 79


Figure 5.9. Radon detection methods according to the detected radiation.

MEASUREMENT AND REPORTING OF RADON EXPOSURES Table 5.1. Etching conditions for several types of SSNTD Type of SSNTD

Etching conditiona

Reference

CN

NaOH solution 2.5 N at 608C for 130 min

Cherouati and Djeffal (1988)

PADC thickness 0.5–0.7 mm

NaOH solution 6 N at 60 8C for 6 h KOH solution 6.25 N at 60 8C for 6 h

Kenawy and Morsi (1991) Langroo et al. (1991)

PADC thickness 1 mm

NaOH solution 26 N at 68 8C for 17 h KOH solution 25.4 N at 608C for 3 h, followed with electrochemical etching at 30 8C for 5 h, with 30 kV cm21 at 2 kHz

Pahapill et al. (1996)

Chemically etching used a mixed solution of 8 mol l21 of C2H5OH and KOH (ratio 4:1) and electro-chemical etching in 6 N KOH solution (containing 20% by volume of alcohol): applying a high voltage of 800 at 2 kHz for 3 h at room temperature.

Gomez et al. (1993)

and Enflo, 1992; Stoop et al., 1997; Tokonami et al., 2005; Zhuo et al., 2002). The devices described in these reports are generally based on the use of SSNTDs. For the bare technique, the SSNTD material is mounted open-faced or bare on a wall in a building to record directly alpha particles from the airborne radon. However, this technique shows that the effect of radon progeny plate-out on the detector is obviously more significant than that of the radon gas. In measurements made under natural conditions, the effect of plate-out becomes very large due to meteorological factors, such as wind velocity and temperature differences (Porstendo¨rfer, 1994) and the simultaneous plate-out of aerosol particles and thoron progeny on the detector surface (Abu-Jarad and Fremlin, 1982). In addition, many researchers noted that this technique was unstable and difficult to calibrate (Abu-Jarad et al., 1981; Hadler et al., 1991; Ma¨kelaïnen, 1986). In spite of these difficulties, this technique has been used in some major epidemiological studies (Darby et al., 2005; Krewski et al., 2005a). For some track detectors (especially those of the open variety), possible interference from thoron and its progeny must be taken into account (see Section 7.4). The diffusion technique is widely used for radon surveys, with the advantage that it is not affected by the decay products in ambient air. Here, the SSNTD material is mounted inside a small, almost airtight, closed container. Air containing radon can enter the container by diffusion, but not the radon progeny which are prevented from penetrating into the container by an effective diffusion barrier. Alpha particles from radon that enter the chamber and its in-grown progeny are detected by the SSNTD. After exposure, the tracks due to alpha particles are made visible by chemical or electrochemical

etching, usually in alkaline solutions. The etching process used depends on the type of SSNTD material, the alkaline solution concentration, its temperature, and time period for etching. Some etching conditions for various SSNTDs are shown in Table 5.1. After etching, the number of tracks can be determined using optical microscopy by manual scanning and counting (CN, PC, and PADC) (Tokonami et al., 1996d), automatic counting system with special software such as image analyzer for PADC (Tokonami et al., 2003), spark counter for CN (Huang et al., 1986), and microfiche reader for PC (Baixeras et al., 1997). Most radon alpha track detectors are counted over a small area (cm2). The radon activity concentration can be estimated by using a calibration coefficient. Every SSNTD-based radon detector design should be calibrated in a radon calibration chamber at least once a year. Determination of the calibration coefficient requires exposure of the SSNTD to a known radon activity concentration in a radon exposure chamber. These exposures are used to obtain or verify the calibration coefficient between net track production rate per unit area and radon activity concentration. Based on the surveyed literature, it would seem that the calibrations were performed at radon activity concentrations in the range of about 2000–10 000 Bq m23 (Eappen and Mayya, 2004; Khan et al., 1990; Langroo et al., 1991; Subba Ramu et al., 1988). If radon detectors are well designed to measure 222 Rn, the radon activity concentration can be simply calculated according to the following equation, G BG ð5:14Þ FT where CRn is the radon activity concentration (Bq m23); G and BG are the gross and background track density (track cm22), respectively; F is the calibration CRn ¼

80


PC

Bochicchio et al. (1996)


coefficient (tracks cm22 Bq21 m3 h21); and T the exposure time (h). The background track density is obtained using unexposed detectors during the same time period as the exposed detectors. The detection limit for this technique for a 3 month long exposure is 5–10 Bq m23, depending on the size of the scanned detector area (George, 1996). Since several studies have revealed that some of the detectors are affected by thoron interference, Equation (5.14) cannot be applied in this case. Their evaluation is described in detail in Section 7.4.

and A and B are the constants for a particular electret configuration. 5.2.3

Vi Vf BG TCF

ð5:15Þ

BðVi þ Vf Þ 2

ð5:16Þ

CF ¼ A þ

where RnC is the radon activity concentration (Bq m23); T the exposure period (d); Vi and Vf are the measured initial and final electrets voltages (V), respectively; CF is the conversion coefficient (V per Bq m23 d); BG the radon activity concentration equivalent of the natural g background radiation;

Figure 5.10. One possible construction of the continuous 220Rn monitor using the electrostatic collection method (Iimoto et al., 1998).

81


The theory and methodology of thoron measurements are the same as for radon measurements. Application of the Lucas cell system as a direct measurement is the preferred way to measure thoron activity concentrations for both grab (Eappen et al., 2008; Knutson et al., 1994; Sumesh et al., 2012) and continuous sampling methods (Eappen et al., 2007; Falk et al., 1992; Iimoto et al., 1998). Electrostatic collection using a semiconductor detector (Figure 5.10) is also a frequently used indirect method and used for many commercial monitors. In many large-scale radon and thoron surveys, radon –thoron discriminative detectors are used (Tokonami et al., 2005). Figure 5.11 shows overviews of a radon –thoron discriminative detector. The detector consists of two different diffusion chambers, a low and a high air-exchange-rate chamber. Each chamber is made of an electro-conductive plastic. PADC is used as the detecting material and a piece of it is attached to the bottom of the chamber with adhesive putty. Radon in air can penetrate into the low air-exchange-rate chamber through an invisible air gap between its lid and bottom by means of diffusion. Since this air gap functions as a very effective diffusion barrier, thoron can scarcely enter the chamber through such a small pathway due to its very short half-life (55.8 s), compared with that of radon (3.82 d). In order to detect thoron more effectively, some holes are opened at the side of the other chamber and are covered with an electro-conductive sponge. This chamber is referred to as the high air-exchange-rate chamber.

Electret Detectors. An electret passive environmental radon monitor is a continuously integrating radon detector consisting of a small chamber having a charged Teflon disk (electret) at the bottom and a filtered inlet at the top (Kotrappa et al., 1988; 1990). After radon gas passively enters into the chamber through the filter, alpha particles emitted from the decay of radon and its progeny ionize the air molecules and these ions are collected by the electret. This causes the voltage level of the electret to decrease. The radon activity concentration can then be obtained by the following equation (Kotrappa et al., 1990): RnC ¼

Thoron Measurements


and Sathish, 2011), consisting of two cylindrical cups, one cup recording tracks from both 222Rn and 220 Rn and the other cup tracks only from 222Rn.

It is not easy to remove the lid in this detector unless a cutting tool is used. This design feature acts as a protection against unwelcome human interference in the measurements. Due to its small size, this detector can be put into most post-boxes and thus permits easy and cost-effective transportation. Following exposure of the detectors, the PADC plates are taken out of the chamber and are chemically etched and alpha tracks are counted with a track reading system. Using two alpha track densities (number of tracks cm22) from the low and high air-exchange-rate chambers (NL and NH), radon and thoron activity concentrations can be obtained by solving the following two equations: NL ¼ XRn CFRn1 T þ XTn CFTn1 T þ BG

ð5:17Þ

NH ¼ XRn CFRn2 T þ XTn CFTn2 T þ BG

ð5:18Þ

5.3

5.3.1

Radon and Thoron Progeny Activity Concentrations and Particle Size Distributions in the Environment Radon and Thoron Progeny

The dose to the lungs is predominantly caused by the deposition of radon progeny in bronchial airways (Aurand et al., 1956; Jacobi, 1964; 1984). In radiation protection, however, for reasons of simplicity and costs, the measurement of radon is the preferred method for the estimation of human exposure to its progeny. To interpret these measurements, a value for the equilibrium factor, F, is required to estimate the radon progeny activity concentration in air. Since the lung dose also depends on the unattached fraction, fp, the separation and measurement of the attached and unattached fraction of the radon progeny is of interest. It is achieved by splitting the equilibrium-equivalent activity concentration into an attached and an unattached equilibrium-equivalent activity concentration. For 222Rn and its progeny, mean values of F and fp measured in dwellings and indoor workplaces range from 0.2 to 0.7 (Sections 4.5 and 7.5.1) and from 0.03 to 0.2 (Sections 4.6.1 and 7.5.1), respectively. Under conditions where the ventilation rate is not too high, measurements have shown that F is negatively correlated with fp (Section

where XRn and XTn are the mean activity concentrations of radon and thoron during the exposure period in Bq m23 ; CFRn1 and CFTn1 are the radon and thoron calibration coefficients for the low air-exchange-rate chamber in number of tracks cm22 Bq21 m3 h21; CFRn2 and CFTn2 are the radon and thoron calibration coefficients for the high air-exchange-rate chamber in number of tracks cm22 Bq21 m3 h21; T the exposure time in hours; and BG the background alpha track density on the CR-39 detector in tracks cm22. A similar method to measure 222Rn and 220Rn in situations where both gases are present is the SSNTD-based twin cup detector (Ramachandran 82


Figure 5.11. Overviews of 222Rn– 220Rn discriminative detectors (Tokonami et al., 2005).


set up at the German radon reference chamber in the Physikalisch-Technische Bundesanstalt (PTB). This is worldwide the only primary standard for traceable calibrations of 222Rn or 220R progeny activity concentrations. Radon progeny size distributions are covered in Sections 4.7, 5.3.3, and 7.5.2. 5.3.2

Radon Progeny Measurement Methods

The radon progeny activity concentration is defined as the activity concentration (Bq m23) of the specific decay products 218Po, 214Pb, and 214Bi – 214Po in air. The measurement of individual nuclides is rare but not a difficult one (Scott, 1981; Tsivoglou et al., 1953). The first measurements of radon progeny used a charged wire for collection with progeny measurement in an electroscope (Elster and Geitel, 1902). Later, measurements in mines were made to determine the new unit of exposure, the Working Level (WL), which was assumed to be related to risk (Kusnetz, 1956). These consisted of a short-term filtered air sample followed by a single measurement with a scintillation probe and it was stated that the WL could be estimated within 13% accuracy. Individual progeny could be calculated using the same sampling method followed by 3 count intervals (Tsivoglou et al., 1953). All types of electronic instruments that are based on grab sampling, continuous sampling, and integrating measurement methods can be used for radon progeny activity measurements in air under certain conditions. A radon progeny measurement has to yield at least one of the following results: (a) the activity concentration of one or more shortlived radon progeny, (b) the potential alpha energy concentration or exposure of short-lived radon progeny, (c) the equilibrium equivalent activity concentration. In order to do this, the instrument has to have a sampling assembly, a radiation detection assembly, and a data processing and recording unit (Figure 5.12). The international standards IEC 61577-1 (IEC, 2006), IEC 61577-2 (IEC, 2000), IEC 61577-3 (IEC, 2011), and IEC 61577-4 (IEC, 2009) and ISO 11665-2 (ISO, 2012a) and ISO 11665-3 (ISO, 2012b) define the conditions under which such a system can be operated, what technical requirements exist, and what kind of calibration is required. It has to be emphasized that there are quite a number of prototype devices available, as well as a small number of 83


4.6.2). Therefore, fundamental studies concerning the correlation of F, fp, and the environmental parameters such as aerosol particle concentration will be of interest. Both the equilibrium factor F and the unattached fraction fp are relative measures of the amount of short-lived radon progeny in air, either in sum or for the unattached part. It is important to note that several measurements of F and fp in typical environments (rooms used for normal purposes, outdoor, mines, etc.) (Huet et al., 2001a; 2001b; Porstendo¨rfer, 2001; Reineking and Porstendo¨rfer, 1990; Vargas et al., 2000) provide a set of data to estimate the exposure caused by radon progeny on the basis of a radon activity concentration measurement. Naturally, these results have quite large systematic uncertainties, but taking into account the quite comparable statistical and systematic uncertainties of a radon activity concentration measurement with a passive device, the application of typical F and fp values is a reasonable method in most cases of radiation protection. Nevertheless, this method is highly dependent on the availability of data for F and fp in different environments, which have to be measured by a portable, for example, active system that has to be calibrated under well-defined conditions by a much more accurate method. Thoron (220Rn) has a relatively short half-life of 55.8 s. For this reason, the exhalation of thoron from the ground is usually of less significance, compared with 222Rn. This is, however, not always valid to the same extent for building materials. Already simple measurements of radon progeny in normal living spaces or workspaces show that—in addition to the progeny of radon (218Po, 214Pb, and 214Bi– 214Po)— also the progeny of thoron (212Pb– 212Bi and 212Po) sometimes occur in relevant activity concentrations. This is, among other things, due to the half-lives of the 220Rn progeny, which are considerably longer than those of 222Rn. To evaluate the relevance for radiation protection, it is important to note that at identical activity concentrations of radon and thoron, the potential alpha energy concentration for thoron progeny has a value which is 14 times higher than that of radon progeny at equilibrium. For the determination and evaluation of radiation exposures by natural radionuclides, it is, therefore, in special cases, also necessary to correctly measure thoron and its progeny, in addition to radon. For the measurement of the individual short-lived radon and thoron progeny, a precise method is required for the separation and measurement of each short-lived progeny activity concentration in air. For calibration purposes, a special sampling system together with a measuring system by simultaneous ag-spectrometry (Paul et al., 1999) was developed and


Figure 5.12. Sampling assembly, radiation detection assembly, and data processing and recording unit are mandatory for radon progeny measurements. The detector can be a surface barrier detector (PIPS) performing the measurement on- or offline, a photomultiplier associated with a sensitive scintillation surface such as ZnS(Ag), a HP Ge-detector, or even SSNTDs.

Ns;Po ðtÞ ¼ Figure 5.13. Sampling techniques for PAEC measurements: sampling unit and activity measurement are separated (a) or together in one unit (b) (Porstendo¨rfer, 1996).

cPo ð1 expðlPo tÞÞ lPo

ð5:19Þ

cPo cPb ð1 expðlPb tÞÞ þ Ns;Pb ðtÞ ¼ lPo lPb cPo ðexpðlPb tÞ expðlPo tÞÞ lPo lPb ð5:20Þ

commercial devices. The inherent quality of radon progeny measurements performed with these instruments is by nature not to be compared with the quality of radon gas measurements performed with well-tested radon devices qualified as transfer standards in comparisons. This does not limit the applicability of radon progeny measurement instruments, but makes a careful handling of the quality assurance necessary. Sampling techniques for the radon progeny measurement can be divided into two groups (Figure 5.13): (a) sampling and activity measurement are separated, i.e., the measurement of the activity is performed after completion of a collection cycle, or (b) sampling system and activity detection are combined in one unit, i.e., the measurement of the activity is performed during sampling (Porstendo¨rfer, 1996). There are quite a number of algorithms that can be used in combination with measuring set-ups incorporating filters or screen/filter combinations together with gross a-counting or a-spectrometry. Sometimes, b or g counting is used to supplement or replace a counting.

Ns;Bi ðtÞ ¼

cPo cPb cBi ð1 expðlBi tÞÞ þ þ lPo lPb lBi cPo cPb ðexpðlPb tÞ þ lBi lPb lBi lPb cPo lPb expðlBi tÞÞ ðlBi lPb ÞðlPo lPb Þ ðexpðlPb tÞ expðlBi tÞÞ cPo lPb þ ðlPo lBi ÞðlPo lPb Þ ðexpðlBi tÞ expðlPo tÞÞ

ð5:21Þ

To shorten the equations, the following abbreviations are used: Po for 218Po, Pb for 214Pb, and Bi for 214 Bi. The calculation for 214Po has been omitted, because it is in activity equilibrium for all practical purposes with 214Bi due to its very short half-life of 164 ms. 84


The process of taking a sample on a target (filter or screen) of the short-lived radon progeny from a radon atmosphere is governed by a set of differential equations (Bateman, 1910). These equations work equally well for 222Rn and 220Rn. These equations describe the build-up of the radon progeny activities, assuming a constant collection rate CRnP. Initial condition for the number of particles is N(RnP; t ¼ 0) ¼ 0 for all isotopes. N(RnP) is the absolute number and lRnP is the decay constant of the respective radon progeny (RnP). During the time interval of t[ [0 : ts] with ts as sampling time, the number of short-lived progeny Ns,RnP(t) for an ideal collection on a target is given by:


The collection rate CRnP(s21) is defined as :

CRnP

CðRnPÞ Vfl S ¼ lRnP

ð5:22Þ

where C(RnP) is the: airborne RnP activity concentration (Bq m23); Vfl is the air flow through the sample (m3 s21); and S the dimensionless collection efficiency of the target. The activity A of the respective isotopes building up during the sampling time ts and the measured decays (integral of the decay function in a given time interval tm after the sampling was stopped) is given in Figure 5.14. In the case of grab sampling, a delay time td has to be included to allow for the delay between the end of sampling and the start of the measurement. The number of short-lived radon progeny on the target after the collection is finished, Nd,RnP(t . ts), is given by Nd;Po ðtÞ ¼ Nc;Po ðts Þ expðlPo tÞ

Nd;Pb ðtÞ ¼ Nc;Pb ðts Þ expðlPb tÞ þ

Nc;Po ðts Þ lPo lPo lPb

ðexpðlPb tÞ expðlPo tÞÞ

Nd;Bi ðtÞ ¼ Nc;Bi ðts Þ expðlBi tÞ þ

ð5:23Þ

ð5:24Þ

Nc;Pb ðts Þ lPb lBi lPb

ðexpðlPb tÞ expðlBi tÞÞ Nc;Po ðts ÞlPo lPb þ ðexpðlPb tÞ ðlBi lPb ÞðlPo lPb Þ Nc;Po ðts ÞlPo lPb expðlBi tÞÞ þ ðlPo lBi ÞðlPo lPb Þ ðexpðlBi tÞ expðlPo tÞÞ

5.3.3

In principle, two methods exist for the determination of the unattached fraction (Porstendo¨rfer, 1996; Tu and Knutson, 1988): (1) estimation of the unattached fraction from a number concentration measurement, and (2) direct measurement of the unattached fraction based on diffusion methods. Based on the measurement of the number concentration by means of a condensation nuclei counter (CNC) and the semi-empirical relationship between the unattached fraction of the PAEC and the number concentration [Equation (4.17) in Section 4.6.1], the unattached fraction can be determined with an error of 10 –20% (Tu and Knutson, 1988). The most frequently used methods for the direct measurement of the unattached fraction of the radon progeny are based on their diffusion properties. Because of their small size, unattached progeny have higher diffusivities than the attached progeny and thus diffuse more rapidly to surfaces, such as

ð5:25Þ

The activity on the target increases during the collection time t e [0 : ts] and decreases after the end of the collection due to the radioactive decay (see Figure 5.14). The integral activity in the time interval t e [td : td þ tm] yields the sum of decays U of the chosen isotope on the target during this time interval:

URnP ðtc ; td ; tm Þ ¼

td þt ðm

Nd;RnP ðtc Þ lRnP dt

td

¼

td þt ðm

ARnP ðtc Þ dt:

Measurement of the Unattached Fraction

ð5:26Þ

td

85


The determination of the respective U can be performed by time analysis of subsequent gross a, or a-b-counting or a-spectrometry measurements with different delay times or by a single a-g-spectrometry measurement. One widely used analysis (with numerous modifications and additions in the literature) is the so-called Thomas method (Thomas, 1972) that bases the analysis of the progeny activity collected on a filter by a sampling system with subsequent gross a-counting by a detector comprising a photomultiplier associated with a sensitive scintillation surface in ZnS(Ag). A detailed instruction including the analysis of counts, and the uncertainty analysis and conditions for sampling is given in ISO 11665-3 (ISO 2012b). The detection limit and decision threshold have to be calculated according to standards ISO 11929 (ISO, 2010). The techniques to measure the PAEC are broadly the same as those for the individual determination, but are simpler to execute and to analyze. For example, the method originally proposed by Kusnetz (1956) is based on a single gross alpha count of a filter sample. The basis of this method is that, about 1 h after sampling, the counts from 214Po formed on the filter by decay of the precursor nuclides increase and the count rate corresponds reasonably well to the PAEC at the time of sampling and is almost independent of the progeny equilibrium. A potential alpha energy concentration integrated measuring system for short-lived radon progeny is shown in ISO 11665-2 (ISO 2012a).


Figure 5.15. Two measurement methods for the determination of the unattached fraction of the PAEC: (a) the difference method, and (b) the direct method (Porstendo¨rfer, 1996).

the walls of tubes or the wires of a wire screen. These collection devices are called therefore diffusion batteries (see Section 5.3.5.2). Since a fraction of the attached progeny is also deposited on the screens, though with a much smaller probability, the measured activities have to be corrected, e.g., by using alpha spectroscopy (Reineking and Porstendo¨rfer, 1990).

For the direct determination of the unattached fraction by means of diffusion methods two methods can be used (Figure 5.15) (Porstendo¨rfer, 1996). The difference method is based on two parallel measurements of the PAEC, one measurement in connection with a diffusion battery (DB) for removal of the unattached progeny, and subsequent measurement of the activities deposited on the two filters by alpha 86


Figure 5.14. Collection and decay of short-lived radon progeny for an activity concentration C(RnP) ¼ 1 Bq m23 and a volume air flow of : Vfl ¼ 1023m3 min21. In this example, the characteristic times are chosen to be ts ¼ 1200 s, td ¼ 60 s and tm ¼ 300 s.


scanning mobility particle sizer in connection with a CNC (Tu and Knutson, 1988). For particle size measurements in the diameter range from about 100 nm to 5 mm, an optical aerosol spectrometer is the preferable choice because of its considerably higher size resolution when compared with a cascade impactor. By means of these measurement systems, the size fractionated particle number concentration can be registered at given time intervals.

5.3.4

5.3.4.2 Direct Activity Size Distribution Measurements. There are two measurement techniques suitable for the direct measurement of activity size distributions (Reineking et al., 1988): (i) the wire screen diffusion battery, and (ii) the cascade impactor. The screen diffusion batteries can be used for particle diameters between 0.5 and 200 nm, i.e., for unattached and attached radon progeny, and the cascade impactor is operated in the size range from 60 to 10 000 nm, i.e., only for attached progeny. Therefore, the combination of both systems is an expensive but complete measurement technique for classifying the entire size spectrum of the radon progeny.

Radon Progeny Particle Size Distributions

As already discussed in the previous section for unattached radon progeny, indirect and direct methods can be also be used to determine the activity size distributions of the attached radon progeny (Porstendo¨rfer, 1996, Reineking et al., 1992a): (1) the indirect approach utilizing the measurement of the number size distribution of the carrier aerosol, and (2) the direct approach of measuring the activity size distribution. 5.3.4.1 Number size distribution measurements. The decay products of radon attach quickly to ambient aerosol particles. The activity size distribution C(d) of the aerosol, which is to be determined, and the number size distribution Z(d), which can be measured, are different because the attachment probability b(d) is a function of particle diameter d. The relation between both size distributions is given by: CðdÞ ¼ C=X bðdÞZðdÞ

Diffusion Batteries. The physical principle of a diffusion battery is the removal of particles on the walls of a tube or the wires of a wire screen, arranged as a series of tubes or wire screens, by Brownian motion (diffusion). Due to the inverse relationship between particle diameter and the diffusion coefficient, the smaller the particle the higher is the deposition on the tube walls or wire screens. For size distribution measurements with the wire screen diffusion battery technique, several screen stages with different penetration characteristics (“graded” wire screens) between 0.5 and 100 nm are needed (Figure 5.16). A wire screen diffusion battery may consist of two distinctly different configurations that may be termed as “series” or “parallel” (Holub et al., 1988; Hopke et al. 1992; Knutson et al., 1984; 1988; Porstendo¨rfer, 1996). The penetration P, the ratio of the particle or activity concentrations C/Co, depends on the diffusion coefficient D(d), which is a function of particle diameter d, the flow velocity vo, and a screen parameter, which characterizes the mesh density and the configuration of the system. A detailed account of the historical development of diffusion batteries, the principal physical mechanisms, their different designs, and applications can be found in Knutson (1999). The series system consists of a number of individual wire screens with different 50% cut-off penetration values operated sequentially, thus yielding as many stages as wire screens. After sampling, the activity collected on each wire screen and on the

ð5:27Þ

with C¼

ð1

CðdÞ dd

ð5:28Þ

0

where C is the radionuclide activity concentration and X the attachment rate expressing the adsorption velocity of the decay product to the aerosol with the number particle concentration Z(d). Values for X are given in Section 4.6. The procedure is to measure the number size distribution Z(d) and to calculate the activity size distribution C(d) by means of the attachment coefficient b(d). This method of determination includes the inaccuracy of the attachment coefficient derived theoretically and experimentally confirmed only for spherical particles. The number size distribution in the size range from a few nanometer up to about 200 nm can be measured with an electrostatic classifier or a 87


spectrometry. For the direct method, radon progeny collected on a screen are directly determined by means of alpha spectrometry. After screen filtration, the non-collected fraction of the radon progeny is sampled on a membrane filter and registered with a second alpha spectrometer unit. The direct measurement technique is more difficult to calibrate, but has a higher accuracy for small fp values than the difference method.


Figure 5.16. Principle of a parallel wire screen diffusion battery for the measurement of radon progeny activity size distributions. Adapted from Porstendo¨rfer (1996).

backup filter is measured simultaneously with a set of parallel gross alpha counters, such as ZnS(Ag) scintillation detectors or by alpha spectroscopy (Holub and Knutson, 1987). Since the ratio of activity collected on the front and back faces of a wire screen depends on the nature of the activity size distribution as well as on the screen parameters, this dependence must be considered in the data evaluation (Holub and Knutson, 1987; Solomon and Ren, 1992). For the determination of unattached size distributions, finer meshes are used than for the attached fraction. The parallel configuration system consists of a number of wire screen stages operated in parallel, with each stage containing a specific set of wire screens and a backup filter (Figure 5.16). In connection with simultaneous sampling and alpha-spectroscopic counting during and after sampling, a substantial improvement in sensitivity and accuracy associated with measurements of low, ambient radon progeny activity concentrations can be obtained (Ramamurthi and Hopke, 1991; Reineking and Porstendo¨rfer, 1986). Such a parallel system of wire screen diffusion batteries for a high sampling flow rate of 2 m3 h21 makes it possible to measure size distributions of activity concentrations as low as 5 Bq m23 (Reineking and Porstendo¨rfer, 1986). The observed activity concentration of the radon progeny deposited on a given screen then allows the reconstruction of the corresponding activity-weighted

Cascade Impactors. An impactor operates under the principle that if a stream of particle-laden air is directed towards a surface, particles of sufficient inertia will impact upon the surface, while smaller particles with less inertia will follow the air stream lines and thus will not be collected (see Figure 5.17). By operating several impactor stages at different flow conditions, the aerosol particles can be classified into several size ranges from which the size distribution can be determined. The single stages are usually operated in a series (cascade) arrangement, also 88


size distribution using either the Twomey (1975), the expectation-maximization (Maher and Laird, 1985), or the Simplex algorithms (Nelder and Mead, 1965), while the penetration characteristics of the wire screen stages can be calculated using the Cheng and Yeh (1980) penetration theory. For example, using the Simplex algorithms, the relative activity size distribution of a given radon progeny can be approximated by a sum of log-normal distributions. Problems associated with the wire screen method, such as the resuspension of deposited progeny by recoil effects, the limited knowledge in the characterization of the screen diffusion batteries in the small diameter range, or the weakness in the mathematical algorithms used in the data deconvolution, prompted Michielsen et al. (2005) and Michielsen and Tymen (2007) to develop an annular diffusion channel (ADC) battery, which allows a continuous measurement. It consists of five annular diffusion channels of different lengths plus a reference filter, operating in parallel. The alpha particles emitted by the 218Po and 214Po collected, or formed on the filter, are detected by an alpha detector, placed in the inner tube of the diffusion channel opposite the filter. Each unit of the diffusion battery is characterized by a particle penetration curve. The slope of the channel penetration curve is steeper than that of a screen, which indicates a higher selectivity of the ADC relative to the wire screen method. A similarly constructed cylindrical diffusion tube (CDT) has been reported by Vargas et al. (2005). Another method to measure radon progeny size distributions was proposed by Johansson et al. (1984) who used a combination of an electrical aerosol analyzer (EAA) and alpha spectrometry. Through a modification of the EAA, each size fraction was collected on a filter and subsequently measured by alpha spectrometry. A miniature integrating particle size sampler was developed by Harley et al. (2012a), consisting of an impactor, four graded screens, and a backup filter. Sampling is for extended periods (months) and the measurement is the deconvolution of the 210Pb, 210Po measurement on the six filtration stages.


Figure 5.17. Low-pressure computer-controlled online alpha impactor with eight stages developed for measuring semi-continuously the size distribution of the radon progeny aerosols over longer time periods (note: only two stages of the eight-stage unit are shown here) (Kesten et al., 1993).

Comparison of Activity Size Distributions Measured by Diffusion Battery and Cascade Impactor. Reineking et al. (1988) measured the activity size distributions obtained by both a high volume diffusion battery and a low pressure cascade impactor in connection with alpha and gamma spectroscopy (Figure 5.18). In order to compare the results of the diffusion batteries and of the impactor, activity median aerodynamic diameters (AMAD) were calculated to a first approximation from diffusion equivalent activity median thermodynamic diameters (AMTD) by multiplying them with the square root of the particle density. Assuming a density of 1.4 g cm23 yielded mean AMADs of the attached fraction of 214 nm (218Po) and 234 nm (214Bi/214Po). These values are slightly higher than the AMADs measured with the impactor. In other words, the comparison of these measurement results shows that the value of the AMTD measured with the diffusion batteries was similar to that of the AMAD measured with the impactor with the differences being less than about 10%.

known as the cascade impactor. The aerosol stream is passed from stage to stage with continually increasing velocities and decreasing particle cut-off sizes. The most important characteristic of an impactor is the collection efficiency curve, which gives the fraction of particles of a given size collected from the incident stream as a function of particle size. Ideally, an impactor should collect all particles larger than a certain cut-off size upon the plate, while all other particles follow the gas flow out of the impaction region. In reality, however, the efficiency curve of a typical impactor stage spans over a range of particle sizes, although impactors are normally designed to have sharp cut-off characteristics, i.e., steep efficiency curves (Reineking et al., 1984). The size range of an impactor can be lowered to smaller sizes by increasing the value of the Cunningham correction, i.e., by applying low pressures in the impactor. Such low-pressure impactors can be used to separate particles down to 50 nm (Hering et al., 1978; 1979). Since impactors are used to measure the size distribution of attached radon progeny, the unattached clusters of radon progeny

Combined Diffusion and Impaction Methods. A combination of a cascade impactor associated in 89


are removed from the entrance air by a tube diffusion battery mounted in front of the impactor system (Gru¨ndel et al., 2005; Reichelt et al., 2000). In general, the activity impacted on the various impactor stages is measured by alpha spectroscopy, using either solid-state detectors or scintillation counters. However, by replacing the impactor by a surface barrier alpha detector, the individual radon progeny can directly be measured by alpha spectroscopy during sampling (Figure 5.17). Such a lowpressure computer-controlled online alpha impactor with eight stages was developed to measure semicontinuously the size distribution of the radon daughter aerosol over longer time periods (Kesten et al., 1993). This online impactor with a sampling rate of 5 m3 h21 makes it possible to measure the activity size distribution also for low activity concentration levels of radon progeny. An interesting alternative method to measure the alpha activity deposited on impactor plates was developed by Iida et al. (2008). Since most of impactor/alpha spectrometry devices are expensive, too large, less portable, and cumbersome to conduct in the environment, they proposed to use imaging plates as a reusable sensor for the detection and storage of ionizing radiation energy in photostimulant phosphor crystals. Thus, the imaging plate detects and stores the image of alpha particles and these images of alpha spots are subsequently analyzed by a computer program.


Figure 5.18. Comparison of activity size distributions measured in closed rooms without additional aerosol sources with the diffusion battery technique, yielding diffusion equivalent diameters (upper panel) and with the cascade impactor, providing aerodynamic equivalent diameters (lower panel) (Reineking et al., 1988).

5.4 series with a granular bed diffusion battery was developed by Boulaud and Chouard (1992) and Tymen et al. (1992), covering a broad range of particle diameters from 0.0075 to 15 mm. The inertia unit comprises an eight-stage cascade impactor with an operational cut-off diameter in the 0.35 –7.5 mm range. The diffusion unit consists of six parallel pipes 20 cm long and 4 cm in diameter containing granular beds of different depths. The diameters of the beads vary between 1 and 5 mm depending on the desired collection efficiency. The sixth pipe is empty and serves as a reference filter. The six filters collect particles that have passed through the impactor and the different granular beds. After sampling, all filters and collecting plates are analyzed by alpha spectroscopy.

Retrospective Measurements

A number of factors limit the accuracy of reconstructing the historical radon exposure of subjects in residential epidemiological studies. The most important of these are: the residential history of the subjects, radon exposures elsewhere, and changes that may have occurred in the radon levels in current and previous residences. Most people change residence a number of times during their lifetime. Contemporary radon measurements should, therefore, be made in as many previous residences as possible if a reasonable estimate of the time-weighted cumulative exposure to radon is to be made. As radon levels in a residence may change over the years due to changes in lifestyle, energy conservation practices and in the fabric of a dwelling the contemporary radon activity concentration may differ substantially from those in the years of most relevance for the induction of lung cancer. In dealing with subject residence mobility, it should also be noted that as indoor radon levels in most countries are log-normally distributed persons in high radon dwellings on moving are more likely to move to dwellings with lower rather than higher radon levels. High mobility, therefore, reduces the variability of the exposure in the study subjects and may necessitate an increase in the size of the required study sample in the interests of maintaining

Comparison between Direct and Indirect Methods. The direct measurement using the diffusion battery method involves tedious, complicated, and timeconsuming procedures and detection of radon progeny activity concentrations using this method is very difficult for low radon progeny levels. Hence the indirect method via the measurement of the number size distribution may indeed present a viable alternative. To compare both direct and indirect methods, Tu and 90


Knutson (1988) compared the direct measurement data obtained by a diffusion battery with data simultaneously measured by an electrical aerosol size analyzer (EAA), which sizes particles by means of their electrical mobility. The radon progeny attachment theory (Porstendo¨rfer, 1994) was then used to calculate 218Po particle size distributions from the numberweighted particle size distribution measured by the EAA. Although indirect measurements agreed very closely with direct measurements, a systematic difference was observed, i.e., geometric mean diameters from the direct measurements were larger than those from the indirect measurements, which may be attributed to the approximations made in the indirect measurements. In general, the primary advantage of the indirect method is the much finer size distribution relative to the rather coarse distributions obtained from diffusion batteries or cascade impactors. On the other hand, the main problem associated with the application of the indirect methods is the necessary conversion of the measured number size distribution to an activity size distribution through attachment theory. Thus, a reliable determination of the activity size distribution of the short-lived radon and thoron daughters is only possible through direct measurements.


5.4.1

Surface Traps

It has been known for over 100 years that exposure to radon could give rise to an “active deposit” of both its short-lived and long-lived progeny on surfaces such as glass (Crookes, 1903). The activity measured on the surface of the glass was found to have two main components. One component could be easily removed by simple cleaning, while the other was permanently implanted and could only be removed by abrasion of the glass itself. The permanently implanted component arises as a result of alpha recoils following the decays of 218Po and 214Po and is found typically up to a maximum depth of approximately 100 nm into the surface of the glass. When a glass object such as a mirror is exposed to indoor air containing radon, its short-lived progeny activity deposited on its surface will over time give rise, due to the alpha recoil implantation process, to a build-up of long-lived progeny such as 210Pb within the glass (Cornelis et al., 1993). It was first proposed in the late 1980s that surface implanted 210Po could be used as a retrospective monitor for radon exposure (Lively and Ney, 1987; Lively and Steck, 1993). The half-life of 210Pb of 22 years controls the rate of growth for the build-up of this nuclide and its descendant, the alpha emitter 210 Po, in the exposed glass. Glass objects in a dwelling exposed to radon and its airborne progeny can be therefore considered to constitute a 210Po “surface trap.” This surface trap can be considered as a form of record of the integrated historical activity concentrations of radon and its short-lived progeny in the indoor air. The relationship between the radon concentration in a room and surface implanted 210Po is 91


complex. It is dependent on parameters such as the characteristics of the room aerosol, room geometry, air movement patterns, and ventilation rate (Cornelis et al., 1993; Walsh and McLaughlin, 2001). Under typical indoor conditions, a radon exposure of approximately 1 kBq m23 yr might be expected to give rise to a 210Po surface implanted activity of approximately 1 Bq m22. Po-210 emits a 5.3 MeV alpha particle and in a thin surface layer of glass can be accurately measured using surface barrier detectors and PICs. Their use for this purpose has been largely confined to laboratory calibration work. For practical and economic reasons in large-scale surface trap field studies, the 210 Po activity is measured in a dwelling by mounting SSNTDs on the surface of chosen glass objects. Protocols have been prepared to assist in the selection of suitable glass artefacts for such purposes (McLaughlin, 1998). A variety of SSTND configurations and methods of analysis are in use in which alpha tracks from the surface 210Po alpha activity are distinguished from those due to the intrinsic alpha activity of the glass (Falk et al., 1996; Fitzgerald and McLaughlin, 1996; McLaughlin, 1998; Trotti et al., 1996). Using modified versions of the Jacobi (1972) room model together with either standard room parameters or best estimates, it is possible to estimate the mean radon activity concentration to which the glass was exposed. If, for example, 210Po is measured on a personal glass object of known history, such as the glass covering a family photograph of known age, this measurement can be used to estimate the radon exposure of an individual over past decades, even if changes of residence have occurred. It should be noted that this method is non-destructive as it does not damage the glass surfaces. The behavior of radon progeny at the air–glass surface interface and of factors such as the mass loading of dust deposits and routine cleaning processes can influence the efficiency of alpha recoil implantation. These topics have been the subject of considerable study both by computer simulation and experimentally (Roos and Samuelsson, 2005; Roos and Whitlow, 2003). The findings of such studies have been of importance to the development of surface trap field protocols and in the interpretation of the implanted activity measurements. An important and critical assumption in the surface trap method is that 210Pb resulting from recoil implantation remains effectively immobile in the surface layer of glass over exposure periods comparable to the lifetime of individuals exposed to radon in their homes. By means of ion beam implantation, the diffusion of 209Pbþ ions in soda-lime glass has been studied under conditions that mimic the alpha recoil implantation of 210Pb (Ekman et al., 2006). No statistically significant loss of 209Pb from the glass was

an adequate study power. This is of most relevance to studies carried out in the USA and Canada, which are societies with high residence mobility. In order to address these difficulties, there is a need for alternative approaches to determine radon exposure which are not based on the measurement of contemporary radon in present and past residences. A number of such approaches have been developed. These are largely based on the measurement of the long-lived radon progeny 210Po or its precursor 210Pb, originating from radon in the indoor air and which have built up in a variety of household objects or even in the skeleton of exposed persons. These approaches, in principle, make it possible to reconstruct the radon exposure of persons over past decades. Three such techniques involving these longlived radon progeny are discussed here: 210Po surface traps; 210Po volume traps; and skeletal 210Pb. Generically, these techniques are called retrospective radon techniques. They are time-integrating methods.


5.4.2

Volume Traps

Another approach to the retrospective assessment of radon exposure is the use of what are termed 210Po 92


volume traps. These may be divided into two categories. Included in the first category are spongy and porous household materials, such as mattresses and other soft furnishings found in all dwellings. Radon gas may freely diffuse into these porous materials and will decay within them. The radon progeny 218Po so formed will deposit on the surfaces of the pores. This will give rise to a build-up within the porous volume trap of long-lived radon progeny such as 210 Pb and 210Po (Samuelsson and Johansson, 1994). By means of radiochemical methods, the 210Po in small samples of such volume trap material can be measured (Oberstedt and Vanmarcke, 1996), assuming uniform distribution within the volume trap. For a typical volume trap, such as the sponge filling of a sofa, an inbuilt 210Po specific activity of approximately 0.05 mBq cm23 (kBq m23 yr) would be obtained. Protocols have been developed to reduce background effects from radon progeny carried into the pores by household dust. The principal advantage of the volume trap method is that it is a direct monitor of the radon gas activity concentration in the dwelling in the past. In comparison to surface traps, another advantage of the volume trap method is that the 210 Po concentration is independent of aerosol conditions and other room parameters, which directly influence the deposition of radon progeny onto surfaces. There are, however, a number of practical disadvantages with this method. The principal one is that it is a destructive method requiring the permission of the dwelling occupant to remove samples of material from household furnishings. Due to the relatively high costs associated with radiochemical analysis, the cost of using it in large-scale surveys might prove prohibitive in comparison to the nondestructive surface trap method. This volume trap method has been used in surveys of high radon dwellings in Norway, Germany, and Serbia. In these field surveys, it has proved to be a viable field retrospective technique (Paridaens and Vanmarcke, 1999). The second category of volume trap methods exploits the property of the solubility of radon gas in commonly used polycarbonate materials such as CDs and DVDs (Dimitrova et al., 2011; Pressyanov, 2012; Pressyanov et al., 2001). The polycarbonate material of a CD will absorb radon which will subsequently decay within the material. The latent tracks produced in the polycarbonate material by the alpha particles following the decay of the absorbed radon and its progeny will be directly proportional to the mean activity concentration of the radon in the air of a dwelling. These tracks can be made visible for counting by electrochemical etching. To eliminate a background contribution to the track density from non-absorbed radon and its progeny in the air above the CD, a surface layer of approximately 80 mm is

observed for annealing temperatures as high as 600oC. Extrapolating to room temperature, this work implies that alpha recoil implanted 210Pb in glass from the decay of 222Rn will be very effectively retained in the approximately 80 nm surface layer of the glass in which it is located. A number of studies involving the use of glass 210 Po surface traps as retrospective radon monitors have taken place (Mahaffy et al., 1993; Steck and Field, 1999). They have, for example, been used in Europe in the former uranium mining districts of the east of Germany, in a Swedish epidemiological case – control study of non-smokers, and in high natural radiation areas in Yugoslavia (Falk et al., 2001; Zˇunic´ et al., 1999). In the Swedish study, the surface trap measurements were used to provide an alternative estimate of individual radon exposure which could be compared with that based on contemporary radon measurements. This study also allowed the usefulness of the retrospective technique to be assessed. Results from 315 measurements on 165 persons were evaluated and in most cases, retrospective measurements were made on two glass objects associated with the same individual. It is estimated for this study that the precision of the exposure assessment by this technique is approximately 20%. A residential epidemiological study in Missouri showed significantly increased lung cancer risks when long-term radon exposures were estimated on the basis of glass surface trap measurements. Exposure estimates for the same subjects based on contemporary radon in air measurements showed no significant increased risks. This suggests that the glass surface trap estimates are a more relevant exposure proxy than contemporary air-based estimates for relating past radon exposure to lung cancer risk (Alavanja et al., 1999; Lagarde et al., 2002). In this context, it should be noted that it is not radon gas but its short-lived radon progeny, in particular the unattached fraction that delivers the most significant doses to the bronchial epithelium. Glass surface trap measurements correlate mainly with the concentration of unattached radon progeny in the air which plate out on surfaces, such as glass (Cornelis et al., 1992; Lagarde et al., 2002; Walsh and McLaughlin, 2001). Therefore, surface trap measurements should in principle be more relevant to dose and risk quantification in residential radon epidemiological studies than radon gas measurements.


5.4.3

In vivo Measurements of 210Pb

Estimates of long-term radon exposures can also, in principle, be made by the in-vivo measurement of 210 Pb in the human skeleton in a low-level shielded gamma counting chamber. The feasibility of such an approach was investigated by researchers at BfS Berlin. In this work, measurement of the 210Pb skull activity of a small number of volunteers, who had been exposed to high levels of radon, was carried out using low energy germanium detectors in a shielded chamber. A major background problem with this approach is that only approximately 2% of skeletal 210 Pb is estimated to be due to the inhalation and subsequent decay of indoor air short-lived radon progeny. On average, 86% of the 210Pb is due to ingestion and approximately 12% as a result of direct inhalation of atmospheric 210Po. Smoking and the consumption of some alcoholic beverages can add substantially to the body burden of this nuclide (Salmon et al., 1998). For human subjects with a high exposure to radon over many years, such as 20 years of exposure to 2000 Bq m23 of radon, a measurable contribution may be made to skeletal 210Pb. This assumption is based on the known correlation between radon exposure and skeletal 210Pb in uranium miners. This approach to long-term radon exposure assessment in humans will for the foreseeable future only be realistic for subjects exposed to very high levels of radon. Measurements of 210Pb in subjects living in the same areas and with a similar dietary intake may be used to distinguish those in dwellings with high radon levels from those in dwellings with low radon levels. Similar work in the USA uses the measurement of skull 210Pb as a means to estimate lung exposure from the inhalation of radon progeny, but in this case, this technique seems to be only realistic for individuals living in very high indoor radon environments for long durations (Laurer et al., 1999).

5.5. 5.5.1

Personal Monitoring for Radon and Radon Progeny Personal Monitoring for Radon

For personal monitoring of radon, radon activity concentrations should be recorded over a certain 93


time interval and at a specific location. Several measuring techniques are currently available. For example, eyeglass lenses were used for the estimation of the personal exposure (Fleischer et al., 2001). They are composed of poly-allyl-diglycol carbonate (PADC). They were calibrated in a radon chamber and tested by being worn for various periods from 1 to 5 years. Average radon activity concentrations for wearers ranged from 14 to 130 Bq m23 (Fleischer et al., 2001). A monitor for personal exposure measurement in residences was reported by Harley et al. (1991), utilizing a solid-state-nuclear-track detector (SSNTD) as the radon detector and a CaF2 chip as a gammadetector. The device was tested in 52 homes in the Chicago area with 84 occupants wearing the detectors. In China, Detao and Fuqi (1997) developed a passive radon personal dosimeter with electrostatic collection by electret which greatly improved the sensitivity of radon monitoring. Two versions of this personal dosimeter are currently available, a “sensitive” and a “less sensitive” “miner radon personal dosimeter”. The sensitive “miner radon personal dosimeter” was used in copper, lead, and zinc mines, where radon dose was surveyed for 100 different exposure scenarios of workers. While this dosimeter type is suitable for monitoring individual cumulative doses for several days, the “less sensitive” type “miner radon personal dosimeter” is suitable for monitoring over periods of more than 1 month. An electronic radon dosimeter based on deposition of radon progeny on a semiconductor detector coupled with an alpha spectrometer offers some advantages compared with passive dosimeters (Streil et al., 2002). In that dosimeter, approximately the size of a small mobile phone, radon gas diffuses through a membrane into the measurement chamber, with a semiconductor detector placed opposite to the entry window. Charged radon progeny produced by decay inside the chamber are collected at the detector surface due to the electric field applied between the detector and the chamber wall. The system detects alpha decays from both the collected radon progeny and the radon gas. A multi-channel-analyzer (MCA) processes all incoming events. An integral spectrum and a record of five peak-areas (each assigned to a single nuclide) at every time step are stored for computing activity concentration and dose values. To calculate the dose values, the equilibrium factor and the dose conversion coefficient (dependence on particle size and lung model) must be known. These parameters can be changed by the user or transferred to the dose management system to be adapted to local exposure conditions. The computed dose and the

removed by etching. The track density below that depth is proportional only to the absorbed radon and its ingrown progeny. This second category of a volume trap method also has the disadvantage of being a destructive method, but the content of CDs and DVDs can, if required, be saved prior to the etching procedure.


5.5.2

measurement of the activity concentration of radon while applying an equilibrium factor, a personal exposure to progeny measuring system might be a solution. This condition might be met in the case of mining. The application of such a device will be subject to the national approving authority. The first recording of personal radon progeny exposure data began in some mines in the 1960s. Personal monitors worn by individuals provide more information than the combination of radon or radon progeny activity concentrations at fixed locations plus records of where time is spent. A number of personal monitors were developed and tested for uranium miners, but many did not survive the rugged environment and rough treatment by the miners. One such type still in use is the one first described by Duport et al. (1980) for the French uranium mines. This active device uses a pump to collect the radon progeny, which then pass through collimators with different filters for energy discrimination and are subsequently recorded on a polycarbonate track-etch detector. Commercial real-time personal samplers and working level monitors are sometimes used in mining operations, mainly to document decay product activity concentrations for dosimetric applications. For example, Su (2007) developed a kind of passive radon/gamma personal dosimeter in China. There are also some miner radiometers (or personal exposure measuring systems) available, which all include a sampling assembly with an active pump, as given in Figure 5.12. They might include a radiation detection assembly and data processing unit. Until now, there appears to be only one patent (though it has different numbers EP0021081A2, EP0021081B1, US4385236) dating from 1980, for a portable instrument for selectively detecting alphaparticles derived from radon without an active pump.

Personal Monitoring for Radon Progeny

In environments where the activity concentration of (or exposure to) radon progeny cannot be judged (or not judged with the required accuracy) by a

94


radon activity concentrations are displayed online during the exposure time and pre-established dose limits can be watched by an alert function. A new electronic personal exposure meter for radon gas was reported by Karinda et al. (2008). The exposure meter consists of a radon diffusion chamber and two silicon detectors with 200 mm2 active area each. Radon gas diffuses through 10 holes (4 mm in diameter) into the detection chamber. The holes are covered by a filter in order to prevent radon progeny in the outside air to enter the chamber. Thus, the device is independent of aerosol concentration and humidity. Alpha detectors inside the chamber register the alpha radiation emitted by the decay of 222Rn and its progeny (218Po and 214Po). The exposure meter is optimized with respect to short-term (days) and long-term (.1 year) measurements of indoor radon activity concentrations and personal radon exposure, while the low power consumption allows long-term measurements for more than a year without recharge interruptions. The exposure meter records measured activity concentration levels in adjustable time intervals allowing a time-resolved analysis. The low weight (150 g) and small casing (113 29 62 mm) allows the exposure meter to be carried comfortably on a person. Its advantages over the film badge dosimeters are: online information on exposure available (without interrupting the measurement), time-resolved exposure monitoring, and lower measurement uncertainties achievable.



6. Strategies for Radon and Radon Progeny Measurements and Surveys

– to establish the range, mean, and distribution of radon activity concentrations in homes to inform overall exposure estimates and national strategies, – to identify “radon prone” or similar areas to support decisions on surveys, public advice, building control, etc., – to determine the indoor radon activity concentration in specific premises to support decisions about remediation or other radon control, and to confirm the immediate and ongoing effectiveness of remediation, – to inform epidemiological investigations of the health impact of radon exposure, – to determine radon exposures in workplace situations where exposures might be high and where area-based measurements are inappropriate, – to investigate random and systematic variations in radon activity concentrations, e.g., short- and longterm, to ensure that other measurements can be properly interpreted in relation to reference levels or to support site-specific dose assessments, – to estimate historic exposures in a specific location or building, and – to investigate relevant indoor air parameters, e.g., F-value, to establish default parameter values for general use in appropriate circumstances or to determine site-specific values where defaults are not appropriate. These different reasons for measuring radon determine the appropriate measurement strategy and impact on the choice of an appropriate measurement method. 6.1

Objectives: Areal and Individual Measurements

The choice between individual and areal radon and radon progeny measurements depends on the objective of the intended measurements. If the primary

objective is to determine airborne activity concentrations for specific individuals, such as in epidemiological studies, then individual exposure assessment is needed. However, if the primary objective is to determine whether the radon activity concentration in a specific house or room is below a certain limit, then areal measurements are the appropriate choice. If the spatial and temporal exposure conditions remain relatively stable, then individual exposures may reasonably be approximated by areal measurements. The objective of area monitoring for radon in dwellings and workplaces is the determination of a long-term average radon activity concentration representative of the exposure of residents and workers. These measurements are preferably carried out over a long-term period to cover daily and seasonal variations. In the case of short-term measurements, appropriate corrective measures must be taken in order to correct measurements which are not sufficiently representative. However, an individual assessment of radiation exposure is required, when a given individual frequently changes exposure sites with different exposure conditions or when the exposure conditions at a given site are subject to considerable spatial and temporal fluctuations. In the case of occupational exposures, areal measurements are commonly performed to investigate whether exposures are below a certain established reference level. If that level is exceeded, then further measurements may be required to demonstrate compliance with annual dose limits. In this case, individual measurements might be required. In terms of measurement equipment and methodology, areal and individual measurements have to meet different needs. In the case of areal measurements, measurements are taken with stationary devices which must be installed at positions at which the activity concentrations and the activity size distribution of radon progeny are representative of those to which individuals are exposed. In order to derive individual exposures from areal measurements, individual occupancy times and related physical activities must be considered (Section 3.6.1).



There are multiple reasons for measuring radon and multiple methods are available for its measurement. Motivations to measure radon activity concentrations are:


An individual assessment of the exposure to radon and short-lived progeny can be achieved by a measurement device carried by the monitored person, preferably worn outside on the upper part of the trunk. In the case of varying physical activities, breathing rates must be monitored to assess lung doses. For practical reasons, areal measurements of radon and radon progeny activity concentrations are normally used to assess individual exposures.

6.2

Radon versus Radon Progeny Measurements

Epidemiological studies of lung cancer risk following exposure to radon and its short-lived progeny have been carried out for two defined population groups: workers exposed to radon in uranium mines and the population at large exposed to radon in homes (Lundin et al., 1971; NA/NRC, 1999a). The measurement of all physical parameters relevant for radon lung dosimetry and related risk analysis is the primary objective of the assessment of the exposure to inhaled radon and radon progeny. The relevant dose for the induction of bronchial tumors is the dose to sensitive bronchial epithelial cells produced by inhaled radon progeny. Hence, the physical parameters required for these dose calculations are the activity concentrations of the short-lived radon progeny and their related aerosol size distributions, distinguishing between attached and unattached radon progeny. Although all radon progeny quantities are measurable, they are not suitable for large-scale surveys because of the relatively sophisticated, and therefore expensive, equipment required. Therefore, the measurement of radon progeny characteristics is commonly replaced by the measurement of radon activity concentrations, such as in home and workplace radon surveys. For example, radon progeny activity concentrations in uranium mines were traditionally expressed in terms of the Working Level (WL) or the Working Level Month (WLM). This leads to the fundamental question whether radon activity concentrations are an adequate surrogate for radon progeny activity concentrations. If the equilibrium factor, F, between the individual radon progeny activity concentrations and the radon activity concentration for a specific exposure situation is known, then radon progeny activity concentrations can be converted to an equilibrium equivalent radon activity concentration and vice versa. In both cases, the correct conversion from radon progeny activity concentrations to radon activity concentrations hinges upon the accurate determination of the equilibrium factor (Section 4.5). It is current 96


practice, however, to assume typical values for equilibrium factors derived from measurements made under similar exposure conditions, e.g., in homes or in mines. Hence, the conversion procedure contains an inherent element of uncertainty. While radon progeny activity concentrations can be converted into radon activity concentrations or vice versa, at least in principle, radon progeny size distributions for attached and unattached fractions cannot be related to radon activity concentrations. A strong dependence of bronchial doses on the size distribution of the inhaled aerosols has been observed (NA/NRC, 1991). For example, the dose-exposure conversion coefficient of unattached radon progeny (less than 5 nm in diameter) is about an order of magnitude higher than the corresponding value for attached progeny (about 200 nm in diameter) (Section 3.8.1). This effect of radon progeny size distributions on dose cannot be captured by the radon activity concentration, which adds another element of uncertainty to the relationship between radon activity concentrations and bronchial doses and, in further consequence, lung cancer risk. Presently, the recognized lung cancer risk in residences or mines is based upon epidemiological studies using measurements of radon gas or radon progeny without regard to physical atmospheric parameters. The first lung cancer risk estimate in an epidemiological study was determined in underground mines using radon progeny (WL) measurements (NIOSH, 1971). Presently, the broad similarity of lung cancer risks from either residential or mining studies suggests that radon with a central estimate of equilibrium factor is an adequate surrogate for radon progeny. Both radon gas and WL are atmospheric quantities and thus surrogates for the relevant carcinogenic bronchial dose. It should be noted that measurements have shown that the equilibrium factor, F, is negatively correlated with the unattached fraction, fp, for conditions where the ventilation rate is relatively low (Section 4.3.3). Taking into account of this negative correlation between F and fp, it has been shown that for indoor air, the radon gas activity concentration is a more robust indicator of dose than the potential alpha energy concentration (PAEC) under a range of aerosol conditions normally encountered (Section 4.6.2). Radon progeny (WL) measurements provide the most direct information for calculating dose. For this reason, occupational exposures, such as in some underground mines, require WL measurements because of legal requirements for documentation of dose. However, uncertainty in calculating the lung dose remains unless the associated aerosol particle size distribution is measured or well known.

Strategies for Radon and Radon Progeny Measurements and Surveys

6.3 6.3.1

Areal Surveys and Mapping

Goals of Radon Surveys

Radon surveys form an essential initial step in the establishment of a national or regional radon program aiming to reduce the population risk. WHO (2009) reviews the goals and organization of national radon programs as well as the role of radon surveys and radon mapping. Font (2009) provides a review of the goals, design, and quality assurance of radon surveys. When targeting the residential and workplace exposure, the key objectives of the surveys are: (1) Obtaining the distribution of the annual average radon activity concentration to which the population is exposed in a country or in an area. (2) Exploring the seasonal variation and correction factors so that radon measurements can be interpreted to determine the annual average radon activity concentration. (3) Finding the geographic areas where high radon exposures are most likely (radon-prone areas). (4) Exploring the radon activity concentration and exposures of workers at workplaces and in public buildings. School surveys and exposure of children is an important target area. (5) Targeted surveys for exploring the exposure of special population or housing groups. For example, the results of radon prevention measures can be studied by measuring a random sample of new buildings. This is a new and important aspect because the radon activity concentration in new constructions determines the likely future exposure to radon. As stated in (2), one of the common goals of radon surveys is to identify areas having elevated percentages of dwellings with radon activity concentrations above the national reference level. In the radon literature, the terms “high radon area,” “elevated radon area,” “radon-prone area,” or even “radon affected area” are used in this context. There is, however, as yet no universal definition for these terms and they may be perceived and defined in a different way in each country. For example, a country such as the Netherlands with an arithmetic mean indoor radon activity concentration of 13.5 Bq m23 is considered not to have a high radon area. If, however, an area with a mean value of 100 Bq m23 were to be 97


identified in the Netherlands, then this might be considered a high radon area. Then again, in countries like Finland or the Czech Republic where the arithmetic mean radon value is 96 Bq m23, an area with a mean value of 100 Bq m23 would not be so considered. Some countries such as Ireland and the UK have specific but different definitions of a high radon area. In Ireland, a High Radon Area is defined as any 10 km 10 km grid square where it is predicted on the basis of the national survey that 10% of the homes will exceed the Radon Reference Level of 200 Bq m23. In the UK, a Radon Affected Area is defined as any 1 km 1 km grid square with a probability that 1% or more of present or future homes will be above the Radon Action Level of 200 Bq m23. The European Union (EU) Directive on Basic Safety Standards for Ionizing Radiation states that “Member States shall identify areas where the radon concentration (as an annual average) in a significant number of buildings is expected to exceed the relevant national reference level” (EU, 2014). Such definitions have practical implications for the development of a national radon action plan. The EU Directive on Basic Safety Standards for Ionizing Radiation (EU, 2014) and the International Atomic Energy Agency Basic Safety Standards (IAEA, 2014) include a requirement that EU and IAEA Member States should have national radon action plans. Similarly, the WHO Handbook on Indoor Radon (2009) gives guidelines for national radon programs. The Directive includes a list of elements that should be considered in such action plans. This list includes a strategy for radon surveys and information to establish radon-prone areas. The WHO Handbook also states that national radon programs should aim to reduce the overall population risk and the individual risk for people living with high radon activity concentrations. If the ultimate objective of a national radon action plan is to reduce the national health burden due to radon exposure, then caution needs to be exercised when considering identified high radon areas. In particular, the population density distribution should be considered as an important input into the development of any strategy used to deal with high radon areas. In an average low radon area, but with a high population density, there may be more citizens at a high level of radon exposure than in an average high radon area of low population density. The strategy to be adopted in dealing with such contrasting situations should be developed on the basis of objective cost-effectiveness analyses rather than on the basis of automatic prioritization and targeting of high radon areas for remedial and preventative action.

Thus, in conclusion, radon gas measurements can be an adequate surrogate for radon progeny and for dose calculations. However, uncertainty remains unless two factors are well known, the equilibrium factor and the particle size distribution.


6.3.2

Sampling and Survey Methods

approaches discussed in that report are also applicable to the sampling of radon activity concentrations. 6.3.2.1 Random Sample Surveys. Most random sample surveys are based on a representative sample from the housing stock. The addresses may be sampled, e.g., by using the postal addresses obtained from the national postal office, the telephone register, customer listings of utilities, or the electoral registers. When estimating the mean population exposure, the need for relevant correction factors should be taken into account, such as type of house, building material, or population density. A representative random sample from the population provides the best basis for estimating the population exposure. Population registers or census data can be used when choosing the participants. Persons under the age of consent can be replaced by the eldest of the parents. Normally corrections are needed due to variation in participation rate in different areas or house types.

– Specification of the objective – Target population, parameters to be estimated – Inventory of resources, budget, staff, data processing, and detectors – Choice of radon detector, installation, and collection of detectors – Requirements as to time schedule and accuracy required – Data collection method, questionnaire design – Information security and confidentiality (i.e., implementation of guidelines on data protection) – Sampling design, sample selection mechanism, and sample size determination – Data processing methods, including editing and imputation – Specification of formulas for statistical quantities and measures of precision – Training of personnel, organization of field work – Allocation of resources to different survey operations – Allocation of resources to control and evaluation

6.3.2.2 Stratified Sampling. In stratified sampling, the population is divided in subgroups called “strata.” Each stratum is then sampled as an independent subgroup. Stratified sampling is a powerful and flexible method that is widely used in practice. The method provides the following benefits: (1) Flexibility when a specified precision is wanted for a specified subpopulation. (2) Since practical aspects related to response, measurements, and information material may differ greatly from one subpopulation to another, the choice of sampling can be made differently in different subpopulations to increase the efficiency of the survey. (3) For administrative reasons, the survey organization can be divided into several geographic districts.

Preliminary or pilot surveys can be used to test the survey strategy, detectors, exposure times, and procedure to install and collect the detectors. Questionnaire forms and the questions play an important role in getting data regarding factors affecting radon activity concentration. Question design is affected by the goals of the survey and, for example, housing and occupancy characteristics in the country. Questionnaires should be pre-tested by a representative test group in order to get feedback. A strict ongoing quality assurance program is required for the radon measurements including traceability to a qualified primary standard. Although ICRU Report No. 75 (ICRU, 2006) refers to the sampling of radionuclides in environmental media, the statistical principles of the sampling

6.3.2.3 Choice of the Strategy. In the surveys of exposure of the population to indoor radon, either random sample surveys or stratified sampling can be utilized. Choosing the dwellings is based, for example, on population or dwelling registers. Many biases can distort the results, so statistical expertise is needed in the design. The accuracy of a random sample survey is highest in high population density areas. Using stratified sampling, the varying population densities and special conditions of different regions can be taken into account. The strategies for workplace surveys are variable. A high-quality representativeness regarding buildings has been achieved in surveys where all schools, day-care centers, or public buildings in the country or region have been measured. The number of 98


It is clear from the published literature that no standardized measurement protocol for indoor radon surveys exists. The actual protocol used in an individual survey depends on many factors such as the objective of the survey and the resources available. In the case of national surveys, as distinct from regional or local surveys, a general consensus has been developing over recent years on how such a survey should be conducted. The principal objective of a national survey usually is to obtain the population distribution of annual average radon activity concentrations. The database from a national survey can then be used as an information platform to plan and develop national strategies to deal with radon exposures of the population. The following general aspects are important in survey planning (Font, 2009; Sa¨rndal et al., 1992).


surveys. Even though it is possible to manage technical problems due to the effect of humidity and heat with charcoal detectors, the main problem with their use in national surveys arises from the 3.82 d half-life of radon. In effect, because of the half-life of radon, charcoal detectors have a radon “memory” of less than 2 weeks and therefore cannot be used to determine the long-term (.3 months) average radon concentration in a dwelling. Charcoal detectors are, on the other hand, quite useful as screening devices and have in the past also been used in connection with survey results in the USA (Price and Nero, 1996). In a dwelling, it is recommended that radon be measured in at least two rooms. High occupancy rooms, such as the main living room and principal bedroom, are preferred. As most of the indoor radon in a dwelling comes from the ground subjacent to the building, the lowest inhabited level of the building is recommended as one of the measurement locations. Positioning of the detectors in a room is important both to obtain a representative value of the long-term average radon activity concentration in the room and for protecting the detector from conditions likely to affect it negatively. For these reasons, the detectors should not be placed close to doors and windows in order to reduce the effect of the intake of outdoor air or of air from other parts of the dwelling. The location at which the devices are installed should be representative of the average ventilation in the room. Distortions of strong sources of heat such as direct sunlight, ovens or radiators, and heat-emitting facilities on windowsills should be avoided, as should conditions of high humidity as may be found in bathrooms and cooking areas. The detectors should be deployed at least 10 cm from walls, should be approximately in the normal breathing zone (1 –2 m height) and should be inaccessible to children and pets. The surface where the device lies should be non-masonry. The detectors should be used under normal living and ventilation conditions and not with the dwelling purposely sealed or closed during the measurement period. The dates of the commencement and cessation of measurement must be recorded. Spatial variation within a house is reviewed in Section 7.1.2. Because of spatial variation of indoor radon, more than one detector may be required when carrying out areal monitoring of indoor workplaces (Section 6.5.1). For example, Public Health England gives a guide to employers for the number of detectors required for areal monitoring of radon in a workplace. See website: www.ukradon.org/information/ workplace (accessed January 2015)

6.3.2.4 Period of Measurement. In a national survey, the measurement period should ideally be 1 year. For practical reasons, this may not be possible, in which case a measurement period of at least 3 months is recommended. Both short-term and annual radon measurements were made in 158 homes in a radon prone area in Iowa (Barros et al., 2014). In this case, short-term and annual measurements were highly correlated (r ¼ 0.87). Section 6.4 deals with the accuracy of short- and long-term measurements as predictors of the annual average. Using seasonal correction factors, the radon activity concentrations determined for measurement periods between 3 months and 1 year can be converted into annual values. If a national survey is carried out in a phased fashion (say four sequential 3-month measurement periods or three 4-month periods) then in principle the results could be used to generate specific seasonal correction factors. Seasonal correction factors will be discussed further in Section 7.3.5. Apart from the use of seasonal correction factors, other temporal correction factors may be needed depending on the detector type used. For example, in the case of nuclear track detectors, it may be necessary to correct for detector background, for the aging and fading of tracks and for track saturation effects (Section 8.2.2.2). 6.3.2.5 Detector choice and deployment. Passive, etched-track (nuclear track) detectors are the detectors of choice for large-scale national surveys but electret ionization chambers can be considered as a suitable alternative. As national surveys usually require radon to be measured in some hundreds of dwellings, the use of active electronic radon monitors would be impractical, primarily on the basis of cost. The use of charcoal canisters to measure radon is also not recommended for long-term national

6.3.2.6 Examples of Survey Practices. Reviews of radon surveys and mapping in the USA 99


measurements in the buildings and the choice of the rooms measured are important factors in determining the exposure to workers or citizens staying in the building. A strategy has often been to choose work spaces with the highest risk, for example, underground spaces and work rooms on the lowest level in high rise buildings, an approach which may yield biased results. A marked difference between radon activity concentration during working hours and the diurnal average may set special requirements for workplace surveys. The diurnal variation may be marked and time-resolved radon monitor measurements may be needed for accurate exposure determinations (see Section 7.2). Also, the effect of seasonal variation may be different in workplaces compared with residential buildings.


random sample, which would have involved an unfeasibly large fraction of the approximately 8000 Italian towns. Therefore, a simple random sampling was used only for the 50 “large towns” (i.e., over 100 000 inhabitants), whereas smaller towns were combined into randomly selected 150 clusters. The final total numbers of sampled dwellings and towns that resulted were slightly higher than the foreseen 5000 and 200, respectively. The UK and Austrian surveys represent random sample surveys based on dwelling sampling. In the UK, it was estimated that the sample reflected the population distribution without corrections (Wrixon et al., 1988). In the Austrian (Friedmann, 2005) survey, the measurements were made mainly during spring and autumn. Homes were selected at random from the telephone register. The chosen number of measurements in an area was proportional to the number of inhabitants in the area. Finally, 1 in 200 homes (1 in 700 inhabitants) were selected. The sample size was reduced in larger cities (multistoried houses) by concentrating on ground floor homes and homes in suburbs for the estimate of radon risk from ground sources. Later corrections were made in order to obtain the mean exposure in larger towns. Approximately 40 000 measurements were performed in about 16 000 rooms, with several detectors in each house. The national radon survey in Ireland was geographically based using the 10-km grid squares of the national grid as the unit area (Fennell et al., 2002). Radon measurements were carried out in 11 319 houses throughout the country. The latest French survey is based on previous national surveys complemented with more recent data, yielding a total of 12 261 measurements (Billon et al., 2005). When estimating the exposure of the population, corrections for season of measurements, housing characteristics, and population density have been implemented. According to a national occupancy study, an indoor occupancy factor of 0.9 was used. For Switzerland and Germany, the distributions of radon activity concentrations are based on national radon data from different sources (Menzler et al., 2008). In the Swiss study, measured radon values were corrected for seasonal effects, adjusted for floor level, averaged by dwelling, and weighted with the population size for each community. The estimate of the radon distribution in Germany was based on a weighted selection of indoor radon studies. The emphasis on high-risk houses was taken into account. In the latest Japanese study, 3900 homes were selected and the number of homes in each prefecture was allocated by the Neyman allocation method to reduce the variance in population-weighted radon 100


and Europe are available (Chambers and Zielinski, 2011; Dubois, 2005, Dubois et al., 2010; EPA, 1993). The WHO Handbook on Indoor Radon (2009) gives a brief summary and guidance on radon surveys. Example results from surveys in European and Non-European countries are given in Tables 4.3 and 4.4. Section 1.1 reviews the UNSCEAR (2008) summary of the worldwide radon database. An overview of radon surveys in 32 European countries (Dubois, 2005) shows that in the majority of countries, random selection of dwellings is basic to the survey. In many of these cases, the sampling frequency has been proportional to population density and special emphasis has been given to radon-prone areas. In some countries, the surveys were based on multiple types of previous survey results (France, Germany, Switzerland) or the survey material was taken from the first stage, nonrepresentative local surveys. Census data ( population registers)-based sampling has been used only in few cases (Finland, Portugal, Norway). The national radon surveys in the USA (Marcinowski et al., 1994) and Italy (Bochicchio et al., 2005) are good examples of the stratified approach. In the US study, a stratified, three stage sampling procedure was used to identify differences in radon levels across EPA’s (US Environmental Protection Agency) 10 regions, and to ensure ample coverage for areas that were expected to have highly variable radon levels, resulting in 22 regional strata. In each region, counties were assigned into one of three radon potential categories: high, medium, or low. The division was carried out using previous radon survey results and geographical data. A multistage process was used to select the housing units, including Census Bureau information on urbanization, residence heating, and ventilation characteristics. The total sample size was 11 423. The survey data were collected through personal interviews with respondents and by placing radon measurement devices in their homes for 1 year, with at least one detector on every floor. The interview covered 77 questions related, for example, to characteristics of the resident’s home and time spent in different levels of the home. To generate an unbiased population estimate, it was necessary to use sampling weights to reflect the unequal probabilities of selecting the sample. A special Quality Assurance Project was developed, including procedures for data collection, sample custody, detector analysis and calibration, and data processing. Italy (Bochicchio et al., 2005) has used a two-stage stratified sampling scheme. In the survey, each of 21 regions were subdivided into the two strata of large and small towns, giving a total of 42 strata. The door-to-door approach prevented the use of a simple


6.3.3

Burke et al. (2010) in Ireland, the weighting technique for correction of the bias due to over-sampling of high radon areas was not effective when regional weights were used. To be effective, it was necessary to apply weights at a localized level. Volunteer data are valuable in decision-making at the regional level due to adequate measurement density. In the UK, it was also found that volunteers from radon measurement campaigns and householders who were more willing to have a radon measurement had higher radon levels than those less willing (Miles, 2001). More willing householders were likely to be in a higher socioeconomic group living in a detached house with good level of heating, and less likely to live in a block of apartments. In comparison, houses with a lower level of heating or upper floors of apartments are more likely to have lower radon levels. 6.3.3.2 Large radon mapping data. In a Finnish study of a database of 92 000 houses, weighting was applied by calculating the parameters in 1 km2 cells and weighting the cells by the number of dwellings in the cell (Valmari et al., 2011). Such random sample surveys provide the best basis for decision-making and for exploring the future trends in national indoor radon activity concentrations. 6.3.4

Radon Maps

Radon maps using a variety of data have been developed to evaluate the radon potential of an area, i.e., an indication of the radon activity concentration to be present in this area. These data may include parameters, such as indoor radon measurements, uranium or radium content of the soil, permeability and moisture of the soil, soil radon gas, and the gamma signal from 214Bi. The radon potential is estimated indirectly from these parameters, and then mapped. The maps are named after the main parameter used to estimate the radon potential. Some radon potential maps are a combination of several parameters.

Use of Volunteer and Large Radon Mapping Data

6.3.4.1 Geological Maps. Geological maps of the type of topsoil mineral soils together with uranium or radium concentration of the mineral soils and the underlying rocks form an important basis for radon predicting activity concentrations in a specific area where no indoor radon measurements are available. It is important to know the radon activity concentrations of the near-surface materials, as this may influence the indoor radon, which usually comes from the upper several meters of the earth’s surface. Geological maps are useful for understanding the physical properties such as permeability

6.3.3.1 Volunteer data. Many countries have collected indoor radon data on a voluntary basis in connection with radon campaigns or from other privately organized radon measurements. These kinds of volunteer measurement tend to be biased due to over-sampling of high radon areas, i.e., the average indoor radon level computed from volunteer data will probably be artificially higher than the overall average indoor radon level computed for a country from more representative data. In the study of 101


activity concentration (Suzuki et al., 2010). The method utilizes the size of population and the SD of the radon activity concentration in each prefecture based on a former national survey. Andersen et al. (2001) have used Bayesian statistics in the Danish survey order to get the best estimate of the percentage of houses exceeding the reference value. In the Indian survey, altogether 1500 measurements were carried out in 25 regions over a span of 3 years (Ramachandran and Sathish, 2011). The period of measurement was 90 d. A similar regionbased survey has been carried out as a coordinated project in 7 Arab countries with altogether 1426 measurements (Al-Azmi et al., 2012). The survey aimed at a density of 1 – 2 detectors in each 1 km2. Cities from different parts of the countries were chosen. Varying approaches were needed to achieve public participation in the survey. Finland is one of the few countries where the national surveys are based on random sampling from the population register. In this approach, corrections are needed due to differences in participation rate in areas or house types (e.g., apartments and low-rise houses) with different radon activity concentrations. In the latest Finnish random sample survey in 2006, these corrections decreased the populationweighted national average from 109 to 96 Bq m23 (Ma¨kelaïnen et al., 2009). Reducing radon activity concentrations in new buildings is an important challenge. Taking a random sample from houses that have received building permission is an efficient tool to explore the effect of preventive measures carried out at the national level. The Finnish new construction survey in 2009, in comparison with the previous national radon survey (Ma¨kelaïnen et al., 2009), showed that radon activity concentrations were reduced by 30% due to new regulations and practical guidelines (Arvela et al., 2012). Examples of results on workplace surveys have been presented in Section 4.4.2.


6.3.4.2 Aerial Gamma Radioactivity Maps. Radioactivity maps are developed from the measured aerial gamma radioactivity data over a certain region. The data are then used to quantify and describe the radioactivity of rocks and soils. The majority of the gamma-ray signal is derived from the upper 20– 25 cm of surface materials. A gamma-ray detector is mounted in an aircraft that is flown over an area at a certain altitude, which is usually 120 – 150 m. The 214Bi signal is used to trace back the 238 U equivalent, assuming that the uranium and its decay products are in secular equilibrium. There is a good match between areas identified on aeroradioactivity maps as having high levels of surface uranium and areas for which high levels of indoor radon have been reported. However, the signal can be blocked by the water in the surface layer and therefore the uranium content will be underestimated on the maps. Phillips et al. (1993) used the aerial gamma radioactivity data to predict areas with elevated radon potential in the USA and Appleton et al. (2008) used aerial gamma radioactivity data to predict areas with elevated radon potential in Northern Ireland. They compared the maps obtained from geological and indoor radon data with the maps modeled from the airborne radiometric and soil geochemical data. Although the analysis showed good correlation, the conclusion was that the airborne radiometric maps should be validated by indoor measurements.

6.3.4.4 Indoor Radon Maps. Indoor radon activity concentration is highly variable; it is established that the average indoor radon activity concentration varies by more than an order of magnitude between different areas. Radon maps provide information about the spatial variation of indoor radon activity concentrations. Radon maps based on direct measurements of indoor radon activity concentration form the least error-prone basis for residential radon maps. House radon data have been obtained by national or target surveys (Section 6.3.2.6). The national surveys are better designed for statistical analysis because of the selected sampling methodology-population weighting, but they contain too few measurements per sampling area. The data from target surveys undertaken to identify homes with high radon levels in areas of known elevated radon potential contain many more results. These surveys are deliberately 102


6.3.4.3 Radon in Soil Gas Maps. Measurements of radon gas in soil air can be used as a predictor of indoor radon. The radon activity concentration of soil air can be measured by passive or active devices, following different protocols (Section 5.2.1.3). The passive device provides a better estimate of the soil radon because of long-term measurements. However, it has to be protected from the soil moisture, which affects the precision of the measurements. The active method involves measuring the radon in the sample of soil air gas, collected from a probe driven into the ground. This method provides data quickly, but these short-term measurements may vary greatly due to daily, weekly, and seasonal changes in soil and atmospheric conditions that are averaged out during long-term measurements. Radon activity concentration in soil gas surveys using active devices on a national or large-scale level were carried in several European countries. The methods applied for mapping of the soil gas radon were described in Barnet et al. (2005), Kemski et al. (2005), Neznal et al. (2004), and Scheib et al. (2006). In national mapping practices based on soil gas radon activity concentration, the permeability of the topsoil mineral soil type is normally included in the assessment procedure, because variations in permeability of soil cause a greater variation in indoor radon activity concentrations than variations in soil gas radon activity concentration. Soil gas radon activity concentration or corresponding uranium concentration results are valuable, especially when exploring areas with elevated natural radioactivity in soils. There is a lack of qualified studies on the success of the soil gas radon mapping, e.g., in predicting houses exceeding the reference level in areas classified as high and low risk.

of the materials at the surface. Permeability of the soil and subfoundation filling materials is the most important factor affecting leakage flow of radonbearing soil into dwellings. Therefore, radon activity concentrations are higher in areas of coarse top-soil types such as gravel and sand and lower in areas of less permeable soil types such as clay. The most radon-prone areas of UK, Devon and Cornwall, lie on granites intruded into folded sedimentary rocks. The granites are characterized by moderate to high levels of uranium. The radon potential is a function of uranium concentration, mineralogy, and permeability. However, if purely uranium concentration or radium content of rock is used to estimate the number of homes above a threshold, they will provide an inaccurate result, because the relationship between these parameters and radon potential appears to vary between different geological formations. For example, high permeability can result in high radon potential even where the bedrock uranium concentrations are moderate, as Ball and Miles (1993) showed. Therefore, pure geological maps should be used only in conjunction with indoor measurements to provide reliable measures of radon in homes.


biased because of their purpose, but they still can be used for mapping purposes. The long-term measurements are preferable for mapping purposes in order to average the short-term radon variations (Section 6.4). There are some uncertainties in magnitude of the mapped parameter arising from both measured data and mapping contributions. The uncertainties in measured data are due to the choice of measured homes, the duration of measurement, the method of measurement, and the temporal (diurnal, seasonal) variation. The uncertainties in the mapping are due to the modeling distribution of activity concentrations, the working assumptions about spatial variation and the grouping of data points into the wrong geological category. The parameter mapped may be the mean indoor radon activity concentration, the proportion of homes above a reference level, or the non-numerical risk categories low, medium, or high. However, for practical applications of policy options for reducing the risk of radon exposure to the population, the maps of the proportion of houses exceeding a reference or action level are most useful. Various types of area boundaries are used in the analysis of data and the presentation of maps. Boundaries can be administrative, geological, or arbitrary such as grid squares. Geological and arbitrary divisions are common choices due to straightforward determination of an area and simplicity of data analysis. Nevertheless, as pointed out by Dubois et al. (2010), there are uncertainties of the indoor radon measurements inside the area boundaries mainly due to the true variability of the radon activity concentration within the cell, the number of observations in the cell, and the uncertainties related to the seasonal variability of indoor radon activity concentration.

the geology, the aerial radioactivity, the soil permeability, and the foundation type. The radon potential was defined by the authors as low, medium, and high. Ielsch et al. (2010) developed a methodology to derive a map of the geogenic radon potential in France. They determined the capacity of the geological units to produce radon based on their uranium content. This initial map was then improved by taking into consideration the major fault lines and underground mines, which control the preferential pathways of radon through the ground. Lognormal Modeling of Indoor Radon Data

Studies by Cohen (1986), Gunby et al. (1993), Hamori et al. (2006), Kim et al. (2003), Marcinowski et al. (1994), Miles (1994; 1998), Nero et al. (1986), and White et al. (1992) showed that the distribution of indoor radon activity concentrations in many countries can be approximated by a lognormal distribution. This means that the logarithm of the radon activity concentration follows a Gaussian function. The reason why the radon activity concentration follows this distribution can be understood in terms of multiplicative factors affecting the relationship between radium in the ground and radon in the indoor air. Miles (1994) showed that the measured indoor radon activity concentration, Ri, in any home can be expressed by Ri ¼ Ro þ Rsource A B C . . .

ð6:1Þ

where Ro is the outdoor radon activity concentration, Rsource a term depending on the radium content in the ground; and A, B, C. . . are terms depending on factors such as permeability of the ground beneath, number and size of entry routes, under-pressure in the building, and ventilation of the building. The equation can be rewritten as:

6.3.4.5 Combined Maps. Miles and Appleton (2005) developed a method, which combines the results of indoor radon measurements by grid squares and geological units in houses in order to produce Radon Affected Area maps of the UK. The land area is first divided using a combination of bedrock and superficial geological characteristics derived from geological maps. Then each of the individual indoor radon measurements is allocated to the appropriate bedrock– superficial geological combination underlying it. The combined method allows for a better estimation of the number of homes above the action level than that obtained from either method separately. Gundersen and Schumann (1996) developed a method to derive a radon potential map of the USA based on the available indoor radon measurements,

lnðRi Ro Þ ¼ lnðRsource Þ þ lnðAÞ þ lnðBÞ þ lnðCÞ þ . . .

ð6:2Þ

The distribution of ln(Ri – Ro) is expected to be normal if there are a sufficient number of independent and randomly distributed terms. If ln(Ri –Ro) is normally distributed, then (Ri – Ro) is said to be lognormally distributed. The distribution of (Ri – Ro) in the UK within large areas, 5 km grid squares, and within geological units were approximately lognormal (Gunby et al., 1993; Miles, 1994). A lognormal distribution can be characterized by its geometric mean (GM) and its geometric standard deviation (GSD). The probability density function 103


6.3.5


f(y) of normal distribution y ¼ ln(x) with mean m and standard deviation s is 1 ðy mÞ2 fð yÞ ¼ pffiffiffiffiffiffiffiffiffiffiffi e 2s2 2ps2

ð6:3Þ

The probability density function F(x) of a lognormal distribution is 1 ðlnx mÞ2 ;x . 0 FðxÞ ¼ pffiffiffiffiffiffiffiffiffiffiffi e 2s2 x 2ps2

ð6:4Þ

The arithmetic mean m of normal distribution f (y) is the logarithm of the geometric mean (GM) of lognormal distribution F(x): pffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi ð6:5Þ GM ¼ N x1 x2 x3 . . . xn lnðGMÞ ¼

1 ðlnx1 þ lnx2 þ lnx3 . . . þ lnxn Þ n lnðGMÞ ¼ m

ð6:6Þ ð6:7Þ

ln(GSD) ¼ s

NRL ¼ 1

ð6:8Þ

ð6:9Þ

Other techniques have been developed to reduce the influence of the extreme values on the sample mean and the sample standard deviation. Miles (1994) applied a “sort technique” to calculate GM and GSD and found that this was a more accurate method compared with using standard formulae, if sufficient data are available. Miles (1994; 2002) developed mapping methods to estimate GM and GSD for each grid square when the data are sparse. Miles and Appleton (2005) showed that the Bayesian estimate of GSD could be used to improve the estimates in areas where the data are sparse.

The GM is equal to the median of the lognormal distribution and the 68% confidence interval is given by (GM/GSD; GM GSD). Although the distribution of indoor radon activity concentrations usually follows a lognormal distribution, this should be checked in each survey. For example, small areas with elevated radon activity concentration may affect the distribution. The statistical parameters calculated should include at least the arithmetic mean, the standard deviation, the geometric mean, and geometric standard deviation. When reporting the results, it is important to provide also an estimation of the uncertainty of the key parameters. A brief review of the interpretation of survey results is available (Font, 2009). In population-weighted surveys, the final goal is to estimate the exposure distribution of the population of a country or region and the percentage of houses exceeding the reference levels. Many biases can distort the result of radon surveys. The use of adequate statistical experience in the data analysis is therefore important (WHO, 2009).

6.3.6

ð lnðRLRo Þ

1 ðy mÞ2 pffiffiffiffiffiffiffiffiffiffiffi e dy 2s2 2ps2 1 ln(RLRo Þm ¼1F s

The standard deviation s of a normal distribution f(y) is the logarithm of the geometric standard deviation (GSD) of a lognormal distribution F(x):

6.4

Long-Term versus Short-Term Measurements

Strong temporal and seasonal variation is one of the characteristics of indoor radon activity concentration. Therefore, the length of measurement and the season of measurement affect strongly the estimation of the annual average radon activity concentration. Seasonal variation is considered in Sections 7.3.5 and 7.3.6. Both short-term and long-term measurements have been used in radon measurements. The length of short-term measurement varies normally from 2 d to 1–3 months. The US EPA (1992) defines measurements shorter than 90 d as short-term measurements. The length of long-term measurements

Mapping the Proportion of Dwellings above Reference Level

To prevent members of the public receiving high exposures to radon, and to reduce average exposures, it is necessary to identify the areas at risk. 104


This allows national and local governments to identify the most affected areas, and to estimate the number of homes exceeding the reference level in each area. Different approaches and methods have been used to calculate the proportion of homes above reference levels. Assuming a lognormal distribution of indoor radon activity concentrations, the proportion of the distribution above the reference level (RL) can easily be calculated. The procedure developed by Miles (1998) involves subtracting the outdoor radon activity concentrations from the measured indoor values and taking the natural logarithm, i.e., ln(Ri 2 Ro). The arithmetic mean and the standard deviation of these corrected indoor values are then calculated. The proportion of homes above the reference level RL, NRL, for a normal distribution y ¼ ln(Ri – Ro), with mean m and standard deviation s, can be calculated using the cumulative standard normal distribution function F, as follows:


6.4.1

Integrating versus Time-Resolved Measurements

Time-resolved measurements are more informative than integrating measurements, giving typically the hourly radon activity concentration for the whole measurement period, in addition to the average of the total period. Due to the high price of such continuous radon monitors, time-resolved measurements have been mostly used in research. These kinds of measurements carried out with several instruments monitoring simultaneously can give information of activity concentration differences, radon sources, and radon transport between different spaces. Strong diurnal variation in radon activity concentration, when there is a clear difference between the temperatures of day and night, normally indicates an important role for convective flow of radonbearing soil air (Section 7.2). Time-resolved measurements are needed at workplaces when there is need to explore the true radon activity concentration during working hours. Such measurements are needed when an integrating measurement has given a radon activity concentration clearly higher than the action level. Figure 6.1 shows an example of a workplace where the average radon activity concentration during working hours (130 Bq m23) was only 3% of the average during 1 week (4900 Bq m23) (Reisbacka, 2008). A reduction in the mechanical air exchange rate and changes in the indoor pressure conditions during night-time increases the radon activity concentration remarkably.

Figure 6.1. Variation of the radon activity concentration in a university seminar room resulting from variations in the adjustment of mechanical ventilation during workdays and the weekend, beginning on 15 December 2006.

105


required or recommended by national authorities is typically from 1 month to 1 year. In the USA, shortterm tests with a duration of 2 – 7 d have often been used in radon testing. In a 2005 survey of radon measurement techniques and protocols in European countries, the longterm integrating passive technique was the most common method (Synnott and Fenton, 2005). Measurement periods of 1 month to 1 year were used. Some countries such as Sweden, Finland, and France recommend that measurements are carried out during the heating season (October to April) as during this period higher radon activity concentrations indoors would normally be expected. Other countries, for example, the UK and Ireland, carry out radon measurements over any 3-month period throughout the year and apply seasonal correction factors (Section 7.3.5). Baysson et al. (2003) analyzed 11 000 measurements in France and determined seasonal correction factors for 2 and 6 month measurements to obtain an annual average. A 1 year measurement is the best choice for the determination of the annual average radon activity concentration, but in practice has the disadvantage of a reduced detector return rate and a long delay for the measurement results. In national surveys carried out in many countries, a 1 year measuring period has been widely adopted either using only one detector for the whole period or two or more subsequent measurements covering the whole 1 year period. The latter approach gives valuable information on seasonal variations.


6.4.2

Predicting the Annual Average using Short-Term Measurements

Table 6.1. Variation of the ratio of short-term to annual average radon activity concentrations for different measurement periods Measurement period

Coefficient of variation, COV, of period/ annual average ratioa Minnesota 75 housesb

Two days: closed Four days: closed One week Monthly: normal Two months Three months Semi annual

UK 91 housesc

Finland 326 housesd

76% 70% 63%e 40% 25% 17%

25%

45% 29% 22% 18%

a

COV ¼ 100 (GSD21), where GSD is the geometric standard deviation of the period/annual average radon activity concentration ratio. b Steck (2005), corrected for instrumental variation. Closed-house conditions during the 2 and 4 d measurements means keeping all windows closed, keeping doors closed except for normal entry and exit, and not operating fans or other machines which bring in air from outside. c Miles et al. (2012). d Arvela et al. (2015). e Derived from other UK results.

Figure 6.2. Short-term screening measurements versus annual average radon activity concentration in Minnesota (Steck, 2005).

Figure 6.3a exhibits a typical seasonal variation pattern with high radon activity concentrations in winter and lower activity concentrations in summer. For comparison, Figure 6.3b shows an atypical variation pattern with highest activity concentrations in summer including some results from monthly and short-term measurements from the same 1-year period (Section 7.3.6). The introduction of seasonal correction factors (SCF) increases the prediction accuracy, provided the length of measurement is long enough (see Section 7.3.5). In a Canadian study, two consecutive 106


Two main factors affect the value of short-term measurements as predictors of the annual average in a home. First, the short period of time, which gives only a poor indication of the annual average radon activity concentration. Second, lower statistical accuracy as well as inaccuracies in calibration and background effects play a more important role in short-term when compared with long-term measurements. Unless the detector accurately records changes in radon activity concentrations, the resulting estimate for the average activity concentration may not be accurate. Strong day-to-day temporal variation which can result from weather or house operational changes have been observed. On the other hand, the detector’s response is usually calibrated under steady radon activity concentrations. Blind testing has shown that temporal fluctuations in radon activity concentration and increased humidity had a negative influence on the precision (Sun et al., 2006; 2008). The annual average radon activity concentration in living spaces (AALS) is commonly used for radon risk assessment purposes. However, occupancy time and breathing rates are needed for an accurate dose assessment. In an attempt to get a quick, inexpensive estimate of AALS, single short-term (2 –4 d) measurements in the lowest lived-in level under closed house (usually winter) conditions have been used. This approach yields only poor estimates in many cases. In three separate groups of Minnesota houses, the geometric standard deviation (GSD) of short-term measurements about the AALS was 1.5 – 1.8 (Steck, 1990; 2005). This means that the 95% confidence interval (CI) of AALS predicted from short-term measurements covers a factor of 10. Wintertime short-term measurements generally over-estimated the AALS by about 20%, while shortterm measurements taken in all seasons were scattered symmetrically around the AALS (Section 7.3). Table 6.1 gives the coefficient of variation of the various temporal measurement intervals based on Midwest USA, UK, and Finnish studies. The annual average radon activity concentration at the measurement site was used as the “gold standard”: the results show a COV of greater than 25% for measurements of duration less than 3 months. Figure 6.2 shows the linear regression and the large variation between short-term screening measurements (2–4 d in the same house) and the annual average radon activity concentration in about 200 houses in the Minnesota study (Steck, 2005). (Note: the distribution of seasonal/annual average ratios in 91 UK houses measured in 3 months periods during 2 years is shown in Figure 7.6.)


provide a fairly large database of geographically dispersed, short-term monitoring data, can be used to predict annual average living-area radon activity distributions for regions, individual states, and individual counties. This type of analysis illustrates the feasibility of using long-term concentration measurements to “calibrate” short-term data, even if the long- and shortterm measurements are from different homes. Seasonal variations and SCF for short-term measurements are reviewed in Section 7.3.

6-month measurements in 4508 homes were used (Krewski et al., 2005b). Predicted annual average radon activity concentrations, based on SCF, were in reasonable agreement with the observed average value. Roughly 15– 30% of the predicted annual average radon activity concentrations were within 10% of the observed values. The concordance between observed and predicted values falling below or above 150 Bq m23 approached 90%. The results for shorter measurement periods in the Canadian study were not equally promising (Section 7.3.5). Although a single short-term measurement in a home is a poor predictor of the home’s annual average, collections of such measurements can be used to characterize regional annual average radon activity concentrations (Price and Nero, 1996). In the USA, the State Residential Radon Surveys (SRRS), which

6.4.3

Predicting the Past Thirty Years of Radon Exposure from Annual Radon Levels

Health studies on the harmful effects of radon face a considerable challenge to estimate the radon 107


Figure 6.3. (a) Typical seasonal variation for houses in Finland with high radon activity concentration in winter and lower activity concentration in summer (Arvela et al., 1988). (b) Sample results from one measurement location with monthly and short-term measurements (Steck, 2005). This house in Minnesota, USA, represents an atypical seasonal variation with a summer maximum.


6.4.4

result correctly identifying a house above the action threshold ( predictive value of a positive test) or of a house below the action threshold ( predictive value of a negative test). Generally speaking, the farther the bulk of the results are from the threshold, the more effective the test is. For example, in the USA where the action level is 150 Bq m23 and 90% of the charcoal canister test results were below that level, the correct classification rate was 93% (White, 1994). On the other hand, in a region where only 60% of the results were below the action level, the correct classification rate fell to 55%. A UK study has compared the predictive power of 1 week, 1 and 3 month measurement periods during a 1 year period (Groves-Kirkby et al., 2006). Table 6.2 indicates the threshold levels above/below which there can be 95% confidence that the indicated annual level is greater/less than the Action Level of 200 Bq m23. These results are given for track-etch detectors. The results and conclusions are bound to the regional distribution of the radon activity concentration and cannot be applied directly to other areas. Calculated estimates are based on GSD values of Table 6.1. The levels can be estimated as 200/GSD2 and 200 GSD2 where the GSD is 1.45 for 1 month and 1.25 for 3 months. The levels are in good agreement with the observed UK values. It should be noted, however, that this kind of estimation can only be carried out if the distributions of the radon activity concentrations are rather similar. 6.5

Homes and Workplaces

The primary goal of both residential and workplace radon monitoring is to identify the homes and workplaces where reference levels are exceeded. Strategies of residential and workplace radon surveys and the principles of identifying radon affected areas have been considered in Section 6.3. Information from radon maps can be used to support decisions to carry out radon measurements

Using Short-Term Measurements to Make Action Decisions

Table 6.2. Threshold levels above/below which there can be 95% confidence that the indicated annual level is greater/less than the Action Level of 200 Bq m23 (Groves-Kirkby et al., 2006). The levels in parentheses give the corresponding level derived using the GSD-values of Table 6.1

Short-term measurements are often used to make remedial action decisions. Often the decision protocol uses a well-defined radon threshold for that action. The actual effectiveness of the remediation action decision depends on the actual radon distribution among investigated homes, spatial and temporal variation of the radon within a given home, and measurement result variation due to intrinsic errors from calibration and analysis errors. The correct classification rate of a testing protocol may be the best single indicator of its effectiveness. Useful measures include the probability of a test

Confidence level (95%) (Bq m23)

Lower Upper a

Track-etch

Track-etch

One week

One month

Track-etch, HPA advicea Three months

75 518

109 (95) 478 (421)

130 (128) 300 (313)

UK Health Protection Agency (HPA) advice: seasonal correction carried out (now Public Health England).

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activity concentration over long periods in the past based on areal measurements (Steck, 2009). The normal practice in current epidemiological studies has been to use one or more year-long contemporary radon gas measurements for retrospective radon exposure reconstruction. As an example, in most studies of the combined North American radon risk analysis, an attempt was made to monitor all in-state homes occupied for a period of at least 1 year within the exposure time window of interest, 5 – 30 years prior to diagnosis of lung cancer (Krewski et al., 2005a, 2006). The radon measurements spanned on average an exposure period of 19.2 years covering 77% of the 25 years period. If past activity concentrations are significantly different from present activity concentrations, then a systematic bias may be introduced in the risk assessment. If radon exhibits year-to-year variations, then the variation will have a tendency to obscure the risk. However, the studies reviewed in Section 7.3.7 show that in most cases, the annual variation in homes ranges typically between 20 and 30% (COV), without showing a persistent temporal trend. At individual sites, however, Harley et al. (2011) and Steck (2009) observed clear temporal trends, depending on climate and exposure to wind. House modifications and installation of new heating, ventilation, and air conditioning (HVAC) systems may be the reason for a few observed dramatically large radon changes. New retrospective measurement techniques have been studied in order to improve the accuracy in the determination of past exposures. These approaches, in principle, make it possible to reconstruct the radon exposure of a person using, for example, household objects. Section 5.4 reviews the current experience achieved using these techniques. As an example in the residential epidemiological study in Missouri, longterm exposure was estimated on the basis of glass surface trap measurements (Alavanja et al., 1999).


compliance with regulatory requirements. These requirements include determination of individual exposure or dose, recording of exposures, compliance with reference levels and dose limits, information and training of workers and health surveillance for workers. In advance of a decision on the appropriate monitoring strategy, the purpose of the monitoring and the particular measurement conditions must be taken into consideration. Therefore, it is necessary to consider whether the monitoring is carried out to determine the exposure of a person to radon or radon progeny, or to assess the radon situation in dwellings or at workplaces. The objectives and principles for selecting either areal or individual monitoring practices have been reviewed in Sections 4.4.3 and 6.1. Table 6.3 presents general recommendations for selecting an appropriate measurement strategy. The detector choice and deployment have been considered in Section 6.3.2.5. Area monitoring at workplaces should monitor the working area of one or more persons working under similar exposure conditions in order: – to determine the annual average radon activity concentration, or – to determine the average potential alpha energy concentration of short-lived radon progeny or any other relevant quantity which is appropriate for the calculation of the lung dose and the effective dose. The measurements should be taken with stationary devices during the common operation cycle which should encompass all work procedures affecting the exposure to radon and radon progeny. Comprehensive

Table 6.3. Recommendations for selecting an appropriate measurement strategy

Radon

Radon progeny

Personal measurement

Area measurement

In homes

Commonly not used

At workplaces

Persons with frequently changed location at workplaces where the equilibrium factor does not vary significantly

In homes

Commonly not used

At workplaces

In specific exposure situations for persons who frequently change their location at workplaces where considerable spatial and temporal fluctuations of aerosol particle concentration occur

Long-term measurement in rooms with high occupancy time (e.g., living room and sleeping room) for determining the compliance with reference values In cases where the equilibrium factor does not vary significantly; for determining the exposure to radon the occupancy time and the physical activity of the monitored person must be recorded separately Only occasionally (e.g., when particular aerosol particle sources influence the equilibrium factor) In cases where spatial fluctuations of the aerosol particle concentration can be neglected; for determining the exposure to radon decay products the occupancy time and the physical activity of the monitored person must be recorded separately

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in homes and workplaces. For example, if an indoor workplace is in a radon-prone area, then radon measurements are usually recommended. For radiation protection purposes, the appropriate measurement result should be compared with the relevant reference level. If mitigation is carried out to reduce radon exposure, then repeat measurements should be made to confirm the effectiveness of the mitigation system and records of the measurements should be kept (WHO, 2009). Remediated premises should be re-measured periodically to ensure that radon levels remain low. Measurements should also be repeated after any significant building work or changes to an operational cycle affecting exposure conditions such as changes to the heating, ventilation, and air-conditioning operation. High radon activity concentrations have been observed in underground mines and as a consequence, the control of radon in mines is regulated. Mining environments and atmospheric conditions set special requirements for radon and radon progeny monitoring. Underground workplaces form a similar work environment with a potential radon risk. In industrial buildings, large work spaces, special indoor air environments, building and foundation structures, and ventilation strategies affect the assessment of radon entry and indoor radon activity concentrations as well as monitoring. Diurnal and seasonal variations in radon activity concentration affect the monitoring practices. At workplaces, diurnal variations in ventilation practices may have a very remarkable effect on monitoring results (see Figure 6.1). The large range of individual occupancy times in workplaces affects monitoring requirements. In workplaces where workers’ exposure to radon is considered as an occupational exposure, radon and radon progeny monitoring is required to demonstrate


knowledge of the operation cycle is therefore necessary. The measurement device must be installed at a position at which the activity concentration and the activity size distribution of radon progeny are representative of those to which the workers are being exposed. The sampling of radioactive substances should ideally be taken at a height of 165 cm for standing work and 110 cm for sitting work in the immediate proximity to the worker (VDI, 1980). Deviation from this rule can be allowed if evidence can be provided that the sampling is taken in the working area with the highest exposure to radon progeny. Area monitoring at workplaces will preferably be applied in cases where spatial fluctuations can be neglected. In order to calculate individual exposures, the individual occupancy times of the person at the workplace must be recorded. For the demonstration of compliance with reference levels or exposure limits, both passive and active radon detectors can be utilized in workplace monitoring. The following aspects might be considered:

(e.g., the air flow through fans or pumps), to ensure sustained effectiveness of the mitigation system (WHO, 2009). (6) If any significant building work has taken place or changes to the operational cycle affecting exposure conditions has occurred, such as changes to the heating, ventilation, and air-conditioning operation, then measurements would need to be repeated. (7) If passive instruments are used, it must be ensured that the instruments are stored in a low radon environment at times at which no monitoring takes place.

6.6

Individual Exposure Assessment: Time-Resolved Measurements

In epidemiological case –control studies, radon activity concentrations in living rooms and bedrooms of current and past dwellings of lung cancer cases and controls were normally assessed retrospectively by means of passive radon detectors (Darby et al., 2005; 2006). Based on these measurements, individual radon exposures to the inhabitants were then estimated for a period of several decades in the past. The important factors of differences in breathing rate and workplace exposure were not considered in these studies. The period 5–30 years prior to diagnosis or death from lung cancer is currently considered as the relevant time of radon exposure. Because a long period of time in the past has to be analyzed for radon exposures for each individual in the cohort, the question arises as to whether a few locally measured indoor radon activity concentrations can indeed be used as a measure for individual radon exposures. Different strategies have been applied to quantify indoor radon activity concentrations. Details of the various procedures commonly used in epidemiological studies can be found in Darby et al. (2006). For example, radon measurements were performed during the time of the study in the last available home occupied for at least 2 years, or in all dwellings in the study area, or in all dwellings occupied for at least 1 year in the previous 25 or more years. For periods where radon activity concentrations could not be determined experimentally, they were estimated indirectly based on mean radon activity concentrations obtained from individuals in the control groups. Radon measurements were commonly performed using passive detectors over various exposure periods ranging from several months to 1 year.

(1) Long-term monitoring with an hourly recording device. This strategy gives both the long-term exposure and the exposure during working hours. (2) Passive instruments for screening purposes. In normal cases when the working time radon activity concentration is lower than the nonworking time activity concentration, the integrated long-term radon activity concentration below the reference level indicates that it is likely that the radon activity concentration in working hours is below the reference level. (3) If the measured radon activity concentration obtained with a passive device only slightly exceeds the reference level, then further measurements with a continuous monitoring device and hourly recording can be applied. These results can be utilized for the calculation of the average radon activity concentration in working hours. (4) In cases where the reference level using a passive device is significantly exceeded, e.g., by a factor of 2 or more, the reference level for the working time average is also likely to be exceeded. (5) If mitigation measures have been taken to reduce radon activity concentrations, then follow-up measurements are required to test their effectiveness. Long-term measurements should be made at the same locations as the original measurements; however, short-term measurements may also be started at the same time. If the levels are sufficiently reduced, long-term tests should be repeated periodically (e.g., every few years), in addition to regular physical checks 110


Long-term and short-term measurements and the effect of diurnal variation in radon activity concentration have already been considered in Section 6.4.


6.6.1

strategies such as personal and time-resolved monitoring should be considered. An assessment of the individual radiation exposure can be achieved by personal sampling in which the sampler is worn by that monitored individual. The sampling must be taken in the breathing zone of the worker. The objective of areal measurements with stationary devices is the monitoring of the working area of one or more persons working under similar exposure conditions. The measurement device must be installed at a position at which the activity size distribution of radon progeny and the activity concentration are representative of those to which the workers are exposed. This method will preferably be applied in cases where spatial fluctuations can be neglected. In order to calculate individual exposures, the individual occupancy times of the person at the workplace must be recorded. 6.6.2

Comparison of Integral and Time-Resolved Personal Measurements

Measurement methods and techniques for timeresolved personal monitoring are listed in Section 5.5.1 for radon gas and in Section 5.5.2 for radon progeny. Time-resolved measurements giving typically the hourly radon exposure assessment for the whole measuring period are more informative than integrating measurements. Because of the relatively high price of such radon monitors, time-resolved measurements have mainly been used in research efforts. Harley et al. (1991) used a radon monitor for personal exposure measurements in 52 homes in the Chicago area with 84 occupants wearing the detectors. They found that the integrated personal exposure was 70% of that predicted by the first floor radon activity concentrations. Personal radon measurements were not well correlated with measurements made in basements. A new electronic personal exposure meter (Karinda et al., 2008) was used to measure radon activity concentrations in 12 tombs located in the Valley of the Kings, Egypt (Gruber et al., 2011). Because the active exposure meters used are easy to handle, the guards agreed to wear them for 2–3 d, and individual radon exposures could be quantified for the first time with high time resolution for these individuals. The results obtained demonstrate that the occupational dose from radon exposure inside the tombs depends on location and period of stay inside the tomb. In another application of the electronic personal exposure meter (Karinda et al., 2008), this detector was worn by 23 individuals over a period of about

Comparison of Areal and Personal Exposure Assessment at Workplaces

In workplaces where workers’ exposure to radon is considered as occupational, the determination of the individual exposure or dose is required to demonstrate compliance with reference levels and dose limits. A decision on an appropriate measurement strategy should be based on a detailed consideration of the exposure conditions. The exposure conditions to be considered include the aerosol characteristics, the ventilation conditions, the occupancy time of the worker at the workplace, and the type of the work activity, which determines the inhalation rate. Depending on the exposure conditions, areal as well as personal monitoring may be applied. For example, because conditions in mines are highly variable, 111


In order to extrapolate the measured data to mean annual indoor radon activity concentrations, seasonal adjustment factors were applied if available. In most cases, one detector was placed in the living room and another one in the bedroom as these are the two most frequently occupied rooms. Measured radon activity concentrations were then weighted by the time the investigated individuals spent in either room in order to calculate a mean radon activity concentration for a given dwelling. Sometimes, changes in building and ventilation characteristics between the investigated individual and the current inhabitants of a dwelling were also taken into account. Details of the various procedures commonly used in epidemiological studies can be found in Darby et al. (2006). Even if assessments of indoor radon activity concentrations in epidemiological studies as described above are carried out with the utmost care, they may not necessarily be a good proxy for the individual radon exposure. For example, the time the investigated individuals spent outside their homes, e.g., outdoors, in the office or in other dwellings, etc., is not known due to the retrospective nature of the measurements. Furthermore, lung doses are determined not only by the radon activity concentrations in air but also by individual breathing patterns, which depend on the physical activity of that individual. Ideally, estimates of individual exposure could be improved with the use of personal passive monitors or with active personal monitors that permit the determination of indoor radon activity concentrations as a function of time. In principle, such time-resolved measurements could be used with individual breathing pattern data to obtain better estimates of “individual dose.” However, for residential epidemiology studies, personal monitoring is currently not a practical option, especially for long-term measurements.


1 week to investigate whether indoor radon activity concentrations measured at home can indeed be used as a measure for individual radon exposure (Gruber et al., 2015). For comparison purposes, areal measurements were performed over the same period with passive detectors placed in the living room and the bedroom of the participants, and their radon exposure in the home was estimated based on these measurements weighted by their relative occupancy of these rooms. Areal measurements were also performed at the workplace of the participants. The comparison showed that the total individual

radon exposure measured with the personal exposure meter was on average a factor of 2 higher than the estimated exposure at home based on measurements in the living room and the bedroom. This difference was caused primarily by the higher radon activity concentrations in the offices when compared with those measured in the home. However, limitations of this study are that the measurements were of short-term duration (1 week) and most of the participants worked for the same organization, and therefore, the results are unlikely to be representative. Downloaded from http://jicru.oxfordjournals.org/ at City University, London on March 20, 2016

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7. Interpretation of Measurements 7.1

Worldwide Variation

National indoor radon surveys have been carried out in a number of countries around the world using different survey designs and exhibiting significant areal variations. The European indoor radon map (Dubois et al., 2010) provides an extensive overview of radon activity concentrations and areal variation in Europe (status end of June 2009). The map is based on 10 km 10 km grid data. The data provided by national authorities include results from 770 998 measurements in 16 422 cells with the following descriptive statistics: Number of measurements per cell: † arithmetic mean (AM): 47 † median (MED) with absolute deviation (MAD): 5+4 (MAD ¼ MED f|(AMi – MED (AMi)|g, AMi ¼ AM in cell i) † range: 1 – 2400 Radon activity concentrations: † arithmetic mean (AM) of all cell means with coefficient of variation (COV) (COV ¼ SD/AM): 98 Bq m23 + 156% (Figure 7.1) † median (MED) of all cell means with absolute deviation (MAD) ¼ 62 + 22 Bq m23 (Figure 7.1) † median of all cell medians (MED + MAD) ¼ 53 + 28 Bq m23 † percentage of all cell means .400 Bq m23: 2.28% † coefficient of variation (COV) and geometric standard deviation (GSD) within cells (MED + MAD) ¼ (60 + 27) %, 1.91 + 0.36% (Figure 7.2) The indoor radon map shows that there is no observable geographic trend in radon activity concentrations. High radon activity concentrations can be observed in all European countries, mainly due to varying bedrock and soil geology. Such high radon areas are associated, for example, with granites and volcanic areas. On a regional scale, smaller “clusters” of cells with higher or lower radon activity concentration can be observed. Figure 7.1 shows that the mean of the radon activity

concentrations varies greatly in EU countries, from 20 to 210 Bqm23, and the median from 20 to 180 Bq m23. It should be noted, however, that the results are based mainly on non-representative volunteer data; nor has any population weighting been carried out. In many countries, the measurements have been focused on high radon areas. Spatial variation between the cells is shown in Figure 7.2. The country-specific reported GSDs vary typically from 1.7 to 2.2, the median for all countries being 1.91. This means that typically 95% of the measurements for a cell are in the range of 0.27 –3.7 of the cell GM (GM/1.912 2 GM 1.912) (GM: geometric mean). Steck (1992) has analyzed spatial variations in the upper Midwest of the USA in order to examine the ability of standard radon measurement protocols to predict the long-term radon activity concentration in houses. In this study, 243 houses were monitored for at least 1 year. Table 7.1 summarizes the pertinent distribution parameters for spatial units ranging in size from a single floor of a house to the state of Minnesota. House-to-house variations within a town-sized cluster can be substantial. The table shows that the best estimate for the house-to-house variation about the town’s mean radon activity concentration is 74%. For larger geographical units, county, region, and state, the variation is still greater. The house-to-house variation in towns is in agreement with a median COV of 60% observed in the 10 km 10 km squares of European countries (Figure 7.2). The European and Midwest US results are in good agreement with many regional and national radon surveys (Table 7.2). In the examples in the table, the GSD varies from 1.8 to 2.6. In the Irish study, the overall GSD was 2.40. It should be noted that in the individual 10 km 10 km squares (total 837) of the European indoor radon map, the GSD ranged from 1.23 to 5.86. 7.1.2

Spatial Variation within a House

Variation between two rooms in the ground floor is caused by room-to-room variations in convective air flows from beneath the floor slab, in air exchange, and, on a smaller scale, also by the role of building



7.1.1

Variations of Areal and Local Radon Activity Concentrations


Figure 7.1. Estimated spatial mean radon activity concentration for European countries based on the arithmetic means of the 10 km 10 km cells within the countries.

Figure 7.2. Median COV and GSD within 10 km 10 km cells in European countries.

Table 7.1. Spatial variation of indoor radon activity concentration in the USA in units of different size (Steck, 1992) Subunit

Unit

Ma

Nb

Distribution typec

COVd (%)

Geom. mean

Geometric standard deviation

Range Min

Range Max

Floor Floor House House House House Town Town Country Region

Room House Town County Region State Region State State State

19 416 227 171 343 243 39 39 14 7

5 208 40 14 7 1 7 1 1 1

Normalized Ratio Deviation Deviation Deviation Deviation Normalized Normalized Normalized Normalized

60 78 74 98 101 105 60 46 23 11

0.82 0.54 1.74 1.98 2.01 2.05 0.77 0.72 0.98 1.02

1.60 1.78 1.45 1.30 1.19 — 1.60 1.46 1.23 1.11

0.3 0.1 1.1 1.4 1.8 — 0.5 0.3 0.7 0.9

2.3 3.7 3.9 3.5 3.0 — 1.6 1.6 1.3 1.3

a

Number of subunits. Number of units. c All distributions are lognormal. Normalized-type distributions are constructed from ratios of each subunit’s value to the unit’s average. Ratio ¼ first floor radon/ basement radon. Deviation distributions are distributions of subunit standard deviations and are not normalized. d Coefficient of variation, COV ¼ 100 (GSD21) for normalized distributions. For deviation type distributions, COV ¼ 100 (GM21). b

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materials as a radon source. Room volume and the coupling to other parts of house, such as the second floor and the staircase, also affect the results. Table 7.3 shows radon activity concentration ratios between different levels of houses and between different rooms at the same level. For example, Chen et al. (2008) determined the ratio of the geometric means of 4238 bedrooms and 3669 basements measured in over 4400 houses. Together with other Canadian results, the mean of the ratios in altogether 5486 houses was 0.60 (Chen, 2003). Since the radon activity concentrations on the first and second floor were not significantly different from each other, they were combined in the category “upstairs.” One study of 52 homes included the ratio of detectors worn by men and women to first and second floor activity concentrations (Harley et al., 1991). Note that “ground” floor in the European studies (Arvela et al., 2012; Wrixon et al., 1988) indicate the same level in the house as the “first” floor in the American studies (Fisher et al., 1998; Harley et al., 1991; Marcinowski et al., 1994; Steck, 1992). The original terminology was intentionally not changed in order to avoid confusion when consulting the corresponding papers. The second floor to first floor or first floor to ground floor radon activity concentration ratios of 0.66–0.9 are indicative of air flows between the stories and dilution of radon activity concentration when the first floor air is mixing with the upstairs air volume. Due to vents, flows of outdoor air, and variations in source strength, the radon activity concentration may be also higher upstairs. Direct air flow to the second floor through pipe penetrations and the intermediate floor may increase second floor radon activity concentrations.

Interpretation of Measurements

Most of the measurements in Table 7.3 lasted for 1 year. The high GSD values of the concentration ratio suggest that significant variation can exist in the annual radon activity concentrations within a house. The observed geometric standard deviations (GSDs) in the range of 1.3–1.9 indicate that a radon measurement at only one location can incorrectly estimate the average radon activity concentration by a factor of 2. The database for the variation of observations presented in Table 7.3 and the uncertainty estimation of the annual average exposure to radon is very limited. Heid et al. (2004) have analyzed the uncertainties of the between-measurements variability in the German radon epidemiology study (Wichmann et al., 2005). Two simultaneous measurements carried out in the bedrooms and living rooms of 4000 dwellings were analyzed. The result of a variance analysis yielded an SD of the log of error estimate of 0.3. This was estimated to be a good approximation for the COV. In summary, the COV of 30% has been utilized in the uncertainty analysis of Section 8.3 as a conservative and “best estimate” of the error in different exposure estimates due to the variations of radon activity concentrations between rooms. This approximation represents the variation between rooms both on the same floor and on different levels above the basement.

Table 7.2. Examples of geometric standard deviation (GSD) in regional and national radon surveys Country

Survey

No. of dwellings

GM (Bq m23)

GSD

Japana Italyb Irelandc Finlandd Canadae

National National National National Winnipeg

899 5361 11 319 2866 2916

12.7 52 57 70 97.6

1.78 2.1 2.40 2.45 2.58

7.2 Diurnal and Seasonal Variations of Radon Activity Concentrations The values of indoor radon activity concentrations are affected by many physical processes. For example, radon entry is affected by radon emanation from

a

Sanada et al. (1999), bBocchiccio et al. (2005), cFenell et al. (2002), two detectors per dwelling, dMa¨kelaïnen et al. (2009), e Letourneau et al. (1992).

Table 7.3. Ratios and geometric standard deviations (GSD) between radon activity concentrations at different levels of houses. Activity concentration ratios (means or geometric means, GM) or the mean coefficient of variation COV of radon activity concentration in different rooms on the same level Country

House type

Number

Ratio

Ratio statistic

Ratio

Canadaa Canadab Canadac USAd USAe USAf USAf Finlandg USAe UKh Finlandg USAf Finlandg USAi USAi

Basement Basement Basement Basement Basement Basement þ 1 floor Basement þ 2 floors Semi-basement — No basement No basement No basement, 1 level No basement, 1 level Basement Basement

1260 4238/3669 5486 208 4350/2716 471 417 249 1561/4350 ,2093 421 1.111 2241 52 52

Living room/basement Bedroom/basement Upstairs/ basement First floor/ basement First floor /basement First floor/basement First floor/basement First floor/basement Second floor/first floor First floor / ground floor First floor/ground floor Room 1/room 2 Room 1 /room 2 First floor/basement Second floor/first floor

Ratio of means Ratio of GM Mean of ratios GM of ratios Ratio of means Mean of ratios Mean of ratios GM of ratios Ratio of means Ratio of means GM of ratios — GM of ratios Ratio of means Ratio of means

0.68 0.59 0.60 0.54 0.40 0.61 0.53 0.67 0.90 0.66 0.84 — 0.99 0.57 0.80

a

GSD

COV (%)

1.78

1.85

34.0%

1.54 — 1.38

19.8% 9.5% 14.4% 6.5% 10.3

Letourneau et al. (1992), bChen et al. (2008), cChen (2003), dSteck (1992), eMarcinowski et al. (1994), fFisher et al. (1998), gArvela et al. (2012), hWrixon et al. (1988), iHarley et al. (1991).

115


In houses with basements and semi-basements, the walls in contact with soil increase radon activity concentrations in basements, especially when doors leading to the ground floor are closed. The geometric mean (GM) of the first floor/basement ratio in Table 7.3 is typically 0.4–0.7, which is lower than the first floor/ground floor ratio in non-basement houses (0.7–0.8). The air exchange between basement and first floor varies in different national housing practices, affecting the radon activity concentration ratio. Due to additional room-specific radon sources, the variation expressed as GSD also increases to a level of 1.85 from the lower level of 1.54 observed in houses with no basement. The mean coefficient of variation (COV) between radon activity concentrations in rooms on the same level of the house given in Table 7.3 is typically 9– 15%. In the Iowa study (Fisher et al., 1998), the overall mean COV (SD) for radon concentrations obtained from detectors placed in different locations on the same floor was 9.5% (10.7%) with a range of 0–119%.


CRn ¼ S=(NV)

Figure 7.3. Diurnal variation of the radon activity concentration established in each level of a detached two-storey house with natural ventilation (measured from 27 February 2009 to 10 March 2009) (Beck, 2012).

7.3

ð7:1Þ

Physical Factors Affecting Indoor Radon Activity Concentrations

Physical mechanisms affecting indoor radon activity concentrations are: pressure difference and air exchange, radon entry from soil and building materials, effect of wind on radon entry, stack effect, and exhaust ventilation, as well as meteorological parameters causing seasonal and long-term variations. This information is very import for reporting radon exposures.

21

where S is the radon entry rate (Bq h ); N the house air exchange rate (h21) ; and V the volume of the house (m3). Variations in radon activity concentration are created by variations in the entry and air exchange rates. A house of greater height indicates a larger house volume and generally lower radon activity concentration. However, house height and volume are connected also to entry rate and air exchange. Low air exchange rate increases the radon activity concentration. Figure 7.3 shows a representative example of diurnal variation in radon activity concentration. The results show the diurnal variations of the radon activity concentration in the cellar, first, and second floor of a detached house with natural ventilation measured over 12 d. In houses with natural ventilation, a night-time maximum is typical due to the cold outdoor temperature at night. The increased indoor–outdoor temperature difference and the resulting pressure difference amplifies the flow of radon-bearing soil air into living spaces and increases radon levels. Sections 7.3.2 and 7.3.3 deal with the processes affecting radon entry. For comparison, the diurnal variation of the radon activity concentration in a workplace is illustrated in Figure 6.1 (Section 6.4.1). A typical seasonal variation is characterized by a higher winter activity concentration compared with summer activity concentration. Seasonal variations are addressed in Sections 7.3.5 and 7.3.6.

7.3.1

Pressure Difference and Air Exchange

Indoor–outdoor pressure difference and house air exchange play an important role in the variation with time in radon activity concentration. Natural ventilation is currently the most common ventilation strategy in residential houses. Natural ventilation is based on the pressure differentials and air flows in the envelopes of the buildings created by indoor–outdoor temperature difference and wind. The physics of natural air exchange rate can be expressed, for example, using the following well-tested model (Sherman and Modera, 1984): 2

Q ¼ ELA ½( fsr 2 DT 1=2 ) þ ( fwr v)2 1=2 N ¼ QV 1

ð7:2Þ ð7:3Þ

where Q (m3 h21) is the total infiltration rate; ELA the effective leakage area (m2); DT the indoor–outdoor temperature difference; fsr the stack parameter, fwr the wind parameter; and v the wind speed. N is the house air exchange rate (h21); and V the house interior 116


mineral grains into soil air, pressure difference-driven air flow in porous soil media and through gaps of the base floor, by infiltration in the building shell, exhalation from building materials, and climate outdoors. Radon entry processes increase the radon activity concentration in indoor air, while air exchange of the building decreases the radon activity concentration. The same mechanisms that drive the air exchange also drive the radon entry from the soil. A forced mechanical ventilation further complicates the situation. Therefore, it is important to understand interactions between ventilation and radon entry processes. Different ventilation strategies aim at keeping the air exchange, impurities, and moisture content of indoor air at an acceptable level. In the case of radon progeny, other effects such as plate-out to room surfaces affect their activity concentration. Different radon entry mechanisms, such as emanation from building materials and pressure-driven flow, may contribute in different ways to variations in radon activity concentrations. The radon activity concentration in indoor air, CRn, can be expressed by the following simplified equation


volume (m3). The stack parameter is affected, for example, by the house height and distribution of leakages in the building shell. Envelope leakages and shielding against wind in the house surroundings affect the wind parameter. ELA describes the airtightness of the building and ranges from less than 0.002 m2 in very air-tight houses to 0.2 m2 in very leaky houses. A widely used recommendation for a qualified air exchange is 0.5 h21, which indicates one change of the air volume in the house every 2 h. A widely used indicator for air-tightness of the building is the air exchange rate at 50 Pa pressure difference (ACH50). Energy saving construction has altered ventilation practices by reducing air exchange rates. In Nordic countries, most new dwellings are today provided with balanced ventilation with a heat exchanger. Natural ventilation depends strongly on climatic factors, air-tightness of the building shell, and the use of ventilation windows or fresh air vents. Mechanical or forced ventilation may be either by mechanical exhaust ventilation or by supply and exhaust ventilation. The latter is also called balanced ventilation. Mechanical ventilation adds a forced component to natural ventilation. Therefore, air exchange is no longer solely dependent on climatic effects, as in the case of natural ventilation [Equations (7.2) and (7.3)]. Negative pressure differences from indoors to outdoors in houses are the key factor driving both air exchange and inflow of radon-bearing soil air into buildings. Pressure difference due to the “stack effect” is proportional to indoor–outdoor temperature difference and house height. The stack effect is caused by the difference in densities of the air columns of different temperatures indoors and outdoors. The colder air column outdoors with a higher density compared with the less dense air column indoors causes a pressure difference over the wall and floor structures. Typical pressure differences in houses with natural ventilation at an outdoor temperature of 0oC are 1–3 Pa. Mechanical exhaust ventilation increases the pressure difference in a leaky house less than in a house with an air-tight structure. The resulting typical pressure difference in moderately tight houses is 4–10 Pa. The use of balanced ventilation with equal supply and exhaust air flows affects only slightly the pressure difference. However, increased air-tightness, e.g., in a modern passive construction, may result in remarkable pressure differences when the airflows are not balanced (Arvela et al., 2015). In cold and cool climates, e.g., in Nordic countries, balanced ventilation may need to be adjusted for a minor negative pressure difference in order to avoid long-term moisture problems. Typical pressure differences in Nordic houses with balanced ventilation are from 1 to 5 Pa (Jokisalo et al., 2008). All measures affecting pressure difference indoors affect radon entry and radon activity concentration.

Opening windows increases air exchange. Opening windows, especially in the lower parts of the house, reduces or nearly brings to zero the pressure difference at floor level and affects strongly the seasonal variation between spring and autumn seasons. 7.3.2

Radon Entry from Soil and Building Materials

Qradon ¼ Cdeep RLA vo ðDP=Po Þn

ð7:4Þ

where Cdeep is the soil gas radon activity concentration in deep soil; RLA the radon leakage area (m2) analogous to the effective leakage area of the building shell [Equation (7.2)] and combines all information about the flow resistance of foundation structures and building soil. DP represents the pressure difference at floor level. The factor vo represents the reference velocity related to the reference pressure Po. The leakage exponent n varies from 0.5 to 1 depending on the role of gaps and soil in the total flow resistance. The flow resistance of the soil is determined by the air permeability of the soil. Soil types cover a very wide range of permeabilities, spanning more than 5 decades. Clay represents a highly impermeable soil and coarse gravel a very high permeability. Figure 7.4 shows the strong effect of soil permeability on radon

Figure 7.4. Convective radon entry rates into a typical basement through a 0.003 m slab-footer gap as a function of soil permeability. The permeability of the 0.15 m thick layer of gravel beneath the basement slab is the variable parameter. The basement is at 25 Pa pressure with respect to the atmosphere (Revzan and Fisk, 1992).

117


Convective entry of soil gas is the dominant source of indoor radon in most houses with elevated concentrations (Nazaroff, 1992) (Section 5.2.1.3). The driving force for this entry is the small indoor– outdoor pressure difference, typically 1–10 Pa. The radon entry rate Qradon can be determined by the pressure difference and resistance to flow of soil gas at entry routes (Sherman, 1992).


The role of building materials is highest in houses with masonry wall structures. Radon exhalation from concrete is higher than from burned clay brick or from furnace blast light-weight concrete block. Globally, the typical range of 226Ra activity concentration in masonry building materials is quite limited (10 –60 Bq m23), resulting also in a limited range of the radon exhalation rate. As a general rule, the lower the radon activity concentration in masonry houses, the more probable is a significant contribution from building materials to indoor radon activity concentration. Soil moisture is an important factor affecting soil gas radon activity concentration and therefore also indoor radon activity concentrations. Partitioning of radon gas between the water and air fractions of soil pores is the main factor increasing soil air radon activity concentration with the increasing water saturation factor. Soil temperature is also an important factor. Andersen (2001) provides a good review of these effects. Rose et al. (1990) have studied seasonal variation in different temperature, soil type, and soil moisture regimes in the USA, utilizing a theoretical analysis of soil gas radon activity concentrations. The study concludes that among the many effects of water on soil gas radon, the effect of the varying proportion of pore space occupied by water appears to be among the largest and most universal. The study estimates that soil gas radon will be most elevated by moisture effects in the eastern USA. In some states, the summer activity concentration of soil radon was predicted to be higher than the winter activity concentration. A more recent review of the experimental and theoretical estimates, together with soil moisture measurements over a period of 10 years, indicates that variation in soil moisture is an important factor affecting the seasonal variation in indoor radon activity concentration (Arvela et al., 2015). Year-to-year variation in radon activity concentration may be markedly affected by long-term variation in soil moisture. 7.3.3

Effect of Wind on Radon Entry

Wind has a significant effect on radon entry rate and indoor radon activity concentrations (Riley et al., 1996; 1999). Wind first establishes depressurization of the house, followed by a steady-state groundsurface pressure field which causes an inflow of soil gas and radon. Table 7.4 summarizes the effect when only depressurization of the house has been considered. Depressurization of the house and the soil gas pressure field reach a steady-state after perturbation with a characteristic time of seconds to minutes. Soil gas concentration will reach a steady-state with a characteristic time that is determined by (1) soil gas 118


entry through a 0.003 m slab-footer gap. Note that a 0.15 m thick layer of gravel beneath the slab affects the radon entry rate by a factor of 3–5. All gaps and openings in the floor construction provide entry routes for radon-bearing soil air. In basements, radon-laden soil gas flows through cracks in the floor slab and walls, block wall cavities, plumbing connections, and sump wells. In most cases, the resistance of soil is much larger than the resistance of leakage gaps and openings in the foundations. The flow through porous media, such as soil, is generally linear with respect to pressure. Therefore, in a house with a floor slab in ground contact, the flow rate of soil air can be assumed to be proportional to the pressure difference at floor level. In this case, the exponent n in Equation (7.4) is equal to unity. In crawl space houses, the leakage follows the same physical laws as air infiltration in the building shell; the leakage flow is proportional to pressure difference to the power of 0.5 –0.7. Radon entry from soil is highest during cold periods such as night-time and winter. Similarly, air exchange is elevated during these periods. However, the effect of radon entry is stronger and, normally, winter activity concentrations are higher than summer activity concentrations (Figure 7.7). The process of radon exhalation from all building materials containing 226Ra is different from pressure difference-driven air flow. The emission is based on radon emanation from mineral grains into the pore space of the material. Thereafter, diffusion results in radon exhalation from building material surfaces into room air. Thoron is emitted from building materials in a similar way. Radon emission from building materials in a living environment is basically a process with only a minor variation. The moisture content of building material is a potential factor increasing radon emanation from masonry materials (Sakoda et al., 2012). Radon emanation from concrete increases typically by a factor of 2 when relative humidity in the atmosphere increases from 0 to 80% (Cozmuta et al., 2003). However, this effect is not fully understood for normal living conditions. Therefore, the radon activity concentration due to building materials is essentially controlled by the air exchange in the building. In a house with natural ventilation, radon activity concentration due to building materials has a maximum in summertime when the air exchange is lowest and a minimum in winter when air exchange is highest. Increased air exchange through open windows in summertime reduces strongly the summer activity concentration. Simple modeling estimates confirm the difference between seasonal patterns with radon entry from building materials or pressure-driven soil air flow (Arvela et al., 1988).


Table 7.4. Effect of different driving forces on radon activity concentration normalized to soil activity concentration and total leakages (Sherman, 1992). In this presentation, the driving forces do not affect the soil gas radon activity concentration Driving force

Stack effect, basement Stack effect, slab-on-ground Wind Exhaust ventilation

Normalized radon activity concentration Representative

Range

5 2 0.5 1

1–14 1–5 0–2 0.7–1.4

7.3.4

Comparison of Driving Forces

The effect of different driving forces, stack effect, wind, and exhaust ventilation on radon activity

Figure 7.5. Indoor radon activity concentration and wind speed over a 3-week period (Riley et al., 1996).

119


Including the effect of wind on ground-surface pressures reduces the predicted radon entry rate relative to a calm, low wind situation by as much as a factor of 3 at a permeability of 10211 m2 (fine sand) to 1000 at a permeability of 1028 m2 (medium coarse gravel). The predicted indoor radon activity concentrations differ by about the same factor. The pressure field created by wind reduces soil gas radon activity concentration by pushing and mixing radon-free air beneath the house foundation. The observations indicate that the flushing effect of wind is an important factor affecting hourly, diurnal, and weekly variations in radon activity concentrations. Seasonal variations in monthly average wind speeds are often rather limited, the average wind speeds being generally 3–4 m s21. Therefore, the effect on seasonal variation is not as high as on shorter-term variation. The variations of indoor radon activity concentrations due to wind may differ greatly from house to house. Permeability of building site, varying permeability in horizontal soil layers at different depths, use of gravel as sub-slab filling material, ground surface profiles, and sensitivity to wind can cause large variations. The flushing effect will be emphasized in hilly areas where the forces of wind pressure pushing or sucking air from house subsoil are highest (see Chapter 7.3.6). In houses with crawl space, the variation depends on the interaction of wind speed, direction, and ventilation in crawl space (Miles, 2001).

travel time from surface to the basement, from hours to months, depending on soil permeability, and (2) the time required to reach a radioactive steady-state, typically several days. Figure 7.5 shows an example of wind-induced variations. In a test house in open terrain with no wind protection and with an eaves-height of 3 m, the indoor depressurizations caused by wind speed of 3.6 and 8.3 m s21 were 2–11 Pa (Riley et al., 1996). The real pressurization depends on wind direction, house structure, and air-tightness and shielding effect of the house surroundings. In the case of low indoor–outdoor temperature difference and an average wind speed of 3 m s21, the wind-induced pressure difference may be comparable to, or greater than, the temperatureinduced pressure differences. The effect of wind-induced ground surface pressures on the radon entry rate may be very marked. In the absence of wind-induced ground-surface pressures, the radon entry rate and hence indoor radon activity concentration may increase by an order of magnitude as the soil permeability increases from 10211 to 1028 m2.


concentration is illustrated in Table 7.4 (Sherman, 1992). The effect of wind on soil gas radon concentration (Section 7.3.3) is not included. The radon activity concentration from each driving force scales in a similar fashion with soil activity concentration and total envelope and entry leakage, but differently with leakage distribution and pressure. Combining these two effects allows a comparison of the induced radon activity concentrations for conditions representative of normal housing. Table 7.4 displays the indoor radon activity concentration normalized to the soil activity concentration and total leakages. The results indicate that the highest activity concentrations occur during stack-dominated periods. The stack effect (Section 7.3.1) causes the highest variation in houses with basements due to differences in height. For example, in the case of houses with basements, the stack effect increases the normalized reference radon activity concentration at the annual average outdoor temperature by a factor of 5 and during cold winter weather by a factor of 14. The lowest activity concentrations occur during wind-dominated periods, during warm periods, and windy weather. The effect of exhaust ventilation is generally lower than the stack effect because the increased air exchange is compensated by an increased pressure difference. In new very air-tight, low-energy construction practices, the role of pressure difference caused by mechanical ventilation can be higher, therefore increasing radon activity concentration (Arvela et al., 2014). High air-tightness of the base floor is required in order to avoid elevated radon activity concentrations.

7.3.5

Seasonal Correction Factors

A seasonal correction factor (SCF) is a multiplying factor applied to a measurement with a duration of one or more months in order to derive a meaningful annual average radon activity concentration. The calculations generally assume periodic annual, typically sinusoidal, variation (Pinel et al., 1995). In the UK, SCFs were initially derived from two consecutive 6-month measurements carried out in 2300 homes and having start dates in all seasons. Figure 7.6 shows the distribution of uncorrected season/annual average ratios in 91 UK houses measured in 3 months periods during 2 years (Miles et al., 2012). The modified UK correction factors based on these data are presented in Figure 7.7 together with the original correction factors (Pinel et al., 1995). In the British approach, the correction factor is given for all months. An alternative approach is to use only one average correction factor for heating season measurements. This has been found practical in the Nordic countries where only heating season measurements are recommended. For practical reasons, many SCFs are given in the form of normalized radon activity concentration, i.e., ratio of the measured 1–3 months radon activity concentration to the annual average. A seasonal correction factor actually should be a multiplicative factor which gives the annual average on the basis of a short-term measurement. The dominant observation in the current SCFs is a higher indoor radon activity concentration in wintertime when compared with summertime. The 120


Figure 7.6. Distribution of uncorrected seasonal/annual average ratios in 91 UK houses measured in three months periods over 2 years.


current British (Pinel et al., 1995) and Irish (Burke et al., 2010) correction factors are approximately 0.7 for the coldest winter months and 1.3 for midsummer. Finnish studies in 3000 randomly chosen dwellings, with two subsequent 6 months measurements, show an average wintertime/annual correction factor of 0.85 (Arvela, 1995). As a practical rule based on many studies, the summer activity concentration is 50% of the winter activity concentration. Analysis of British and Irish indoor radon measurements shows that there is a clear regional variation in seasonality of radon levels (Burke and Murphy, 2011; Denman et al., 2007). The Irish analysis presents the

Figure 7.7. Sinusoidal fit of monthly geometric mean radon activity concentrations for the new UK study (solid line) (Miles et al., 2012) and those presented by Pinel et al. (1995), normalized to the same geometric mean radon activity concentration (dashed line). Note the values for Miles et al. (2012) refer to the middle of each month, whereas the Pinel et al. (1995) data refer to the first day of each month.

7.3.6

Atypical Seasonal Variations

Atypical seasonal and diurnal variations have been observed in areas of hilly permeable terrains. In the

Figure 7.8. Monthly average radon activity concentrations in two homes during 4 years, individual annual variation and average over the whole investigation period with 95% confidence intervals (Denman et al., 2007).

121


seasonal correction factor for 3 months radon measurements for five regions. These results show a normalized radon activity concentration of 0.87–1.21 in these regions in January, while the recommended nationwide factor is 1.14. Figure 7.8 shows the seasonal variation during 4 years in two dwellings (Denman et al., 2007). Although SCFs illustrate the collective variation of radon, the value of applying such corrections to individual radon measurements is limited because of the wide variation from the national average correction factors. Gillmore et al. (2005) emphasizes the effect of the complexity of underlying geology and considerable variations in permeability of underlying materials as a reason for a significant number of occurrences where the application of a seasonal correction factor may give rise to over-estimated or under-estimated radon levels. Variation in soil moisture is a potential reason for the observed marked year-to-year variations in indoor radon activity concentrations (see Section 7.3.2). Increasing the length of measurement period when calculating SCFs increases the accuracy. In the Canadian study, two consecutive 6-month measurements in 4508 homes were used (Krewski et al., 2005a; 2005b). Observed and predicted annual average radon activity concentrations were in reasonable agreement. Roughly 15–30% of the predicted annual average radon activity concentrations were within 10% of the observed values. Based on the latest UK results (Miles et al., 2012), presented in Table 7.5, spring and autumn measurements give a better estimate of the annual average radon activity concentrations than the best seasonal correction factors applied to all season measurements.


In a Norwegian study (Sundal et al., 2008), instantaneous changes in soil air flow directions and in soil air radon activity concentration were recorded when the outdoor temperature reached the annual average outdoor temperature which is close to the deep soil temperature. The observations of the effect of wind in the anomalous areas described above can be applied to houses in normal hillside areas, with no elevated subterranean air flows, when the subsoil is permeable. Wind direction is a potential reason for strong diurnal variations and depending on the seasonal variation in wind speed and direction also for seasonal variations.

Table 7.5. Effects of different types of correction on the accuracy of estimates of annual mean radon activity concentrations (Miles et al., 2012) Percentage of all corrected 3-month results that are within 30% of the 2-year mean activity concentration for the home

No correction Seasonal correction based on Howarth and Miles (2008) Temperature correction based on Miles (1998) Seasonal correction based on Miles et al. (2012) Use only spring or autumn results with no correction

74% 71% 76% 79% 85%

7.3.7

Long-Term Variation in Annual Average Radon Activity Concentrations

The annual average temporal radon behavior was studied at 196 sites in 98 Minnesota houses (Steck, 2009). Seventeen hundred year-long indoor radon measurements were made from 1983 to 2000 to determine year-to-year radon fluctuations and long-term temporal trends. Ten year-long measurements over a span of 13 years were made at a typical site. The median radon activity concentration was 120 Bq m23. The median radon activity concentration of the group of houses showed little year-to-year variation and no persistent temporal trends. However, at individual sites, year-to-year variations ranged from 3 to 110%. The median variation was 26%. Climate, exposure to wind, and radon activity concentration affected year-to-year variation, while house age, construction, or measurement floor did not. Variation in soil moisture is another potential reason for the observed marked year-to-year variations in indoor radon activity concentrations (see Section 7.3.2). Some individual sites showed significantly larger radon changes when modifications were made to the house structure and heating-ventilation systems. An annual average study in Iowa analyzed year-to-year radon variation over spans up to 7 years (Zhang et al., 2007). In the 61 houses with 3-yr-long measurements over a 7-yr span, the COV had a mean of 24%, a median of 19%, and a range of 0–110%. These statistics are similar to those of the Steck study (2009) reviewed above, which has a larger sample size and longer study span. Hunter et al. (2005) examined 96 houses with moderately elevated radon to track for 6 years with 3-month-long measurements in each year. After extensive analysis that included building factors, they concluded that the year-to-year variation was of the order of 40%. Only 15% of the variation was explained by the building factors. Measurements conducted over 17 years in a new Jersey home showed averages and standard errors

karst terrains of Huntsville, Alabama (Wilson et al., 1991) elevated radon levels were observed during summertime. Abrupt day-to-day changes were also observed. Similar observations have been made in hilly eskers of coarse glacial permeable gravel in Finland (Arvela et al., 1994), in a volcanic region in Spain (Moreno et al., 2008), and in a permeable ice glacial sediment in Norway (Sundal et al., 2008). Another example of atypical seasonal variations is a house in Minnesota with maximum radon activity concentrations during the summer months (Steck, 2005) as shown in Figure 6.3b (Section 6.4.2). In a Finnish esker study, the difference in temperature between the soil air inside the esker and the outdoor air compels the subterranean soil air to stream between the upper and lower esker areas. In winter, the radon activity concentrations are amplified in the esker top area. In summer, activity concentrations are amplified in certain lower slope areas, while in winter, radon-free outdoor air is flowing into the esker and into subfoundation soil. Winter/summer concentration ratios were typically in the range of 3 – 20 in areas with amplified winter activity concentration, and 0.1 – 0.5 in areas with amplified summer activity concentrations. In a Spanish study, the average winter/summer ratio was 1.7 on non-volcanic subsoils and 0.5 in volcanic areas. In comparison, as a rule of thumb in normal terrains, the winter/summer ratio is close to 2. Indeed, Harley and Terilli (1990) showed that over a 3-year measurement period, the seasonal change in radon activity concentration varied by a factor of 2 (summer to winter). Parallel with temperature variations, the abrupt day-to-day changes in these areas are caused by variations in wind speed and direction. When hitting the slope of a hill, wind is pushing outdoor air to the soil masses below the buildings. 122


Type of correction applied to 3-month results to obtain estimate of annual mean activity concentration


of means for basement, first floor, and second floor of 26 + 18%, 13 + 11%, and 13 + 8% Bq m23, respectively (Harley et al., 2011). In conclusion, based on the studies above, the reported values of year-to-year variation as expressed as the COV are in the range of 25–40%.

7.4

Thoron Interference on Radon Detection Systems

7.4.1

Figure 7.9. Relationship between the ratios of thoron to radon activity concentrations, TnC/RnC, and computed radon activity concentrations RnC.

To take into account the thoron interference on radon measurements, the observed activity concentration (Cob) with a single passive radon detector can be expressed as follows:

Time-Integrating Devices

7.4.1.1 Alpha-Track Detector. Passive radon (222Rn) detectors, in particular track detectors, are commonly used for national radon surveys and epidemiological studies. Therefore, several major alphatrack detectors were examined with respect to their thoron interference. Tokonami (2010) summarized the thoron interference on radon measurements from the viewpoint of relative thoron sensitivity of radon detectors. For the interference testing, detectors made in Canada, Germany, Italy, UK, and USA were selected. The German detector had the highest sensitivity for thoron, followed by one from the USA. Special attention must be paid to these results because these two detectors were used in major epidemiological surveys (Krewski et al., 2006; Wichmann et al., 2005). Since the thoron sensitivities were 0.7–0.8 times of those for radon, careful consideration will have to be taken for their practical use. The other investigated detectors exhibited only very small thoron sensitivities, with relative sensitivities of about 0.05. It should be noted, however, that the thoron interference may be much larger if the detectors are placed near the walls, even in the case of low thoron sensitivity.

Cob ¼ RnC þ (STn=Rn ) TnC

ð7:5Þ

Where RnC and TnC are the mean activity concentrations of radon and thoron during the exposure period in Bq m23; and STn/Rn is the relative sensitivity. The values of STn/Rn were estimated to be 0.025 for the short-term electrets and 0.033 for the longterm electrets. Figure 7.9 shows the relationship between the ratios of thoron to radon and “apparent” radon activity concentrations. For values of the ratio, TnC/RnC above 10 on the abscissa in Figure 7.9, the computed radon activity concentrations for both electrets increased rapidly. There is the possibility that thoron activity concentrations are 10 times higher than radon activity concentrations. Thus, there may be problems related to thoron interference on radon measurements with the electret systems when extremely high thoron activity concentrations are encountered. 7.4.2

Continuous Devices

7.4.2.1 Ionization Chamber. Several types of PIC ( pulse ionization chamber) detectors are commercially available. Although the most common PIC monitor operates as a current ionization chamber for very high activity concentrations of radon, it could be considered as a PIC detector for the measurements of environmental radon (Ishikawa, 2004). It is widely used for measurements of environmental

7.4.1.2 Electret detector. It is known that radon measurements with electret monitors may be affected by environmental parameters, e.g., temperature, relative humidity (RH), the presence of ions in the room, air drafts, gamma radiation, thoron in the air, and external dust. Therefore, two types of electrets were examined for their thoron interference on radon measurements. 123


In most indoor environments, thoron (220Rn) is present as well as radon (222Rn). In general, the thoron activity concentration is negligible compared with that of radon. This is not always the case as recent studies have occasionally shown high thoron activity concentrations in some areas (Nuccetelli and Bochicchio, 1998; Wiegaud et al., 2000). Although most radon detectors are designed to minimize the entry of thoron, there are a few reports on the thoron contribution to the detector response (Tokonami, 2010; Tokonami et al., 2001).


Table 7.6 Radon and thoron activity concentrations measured with the two types of detector Exposure conditions

Thoron with background radon (1)

Thoron with background radon (2)

Mixture of radon and thoron

Elapsed time (h)

Radon/thoron monitor

PIC monitor

Radon activity concentration (Bq m23)

Thoron activity concentration (Bq m23)

0–1

3 (0 – 34)

634 + 132

91 + 18

14 + 6

1–2 2–3 Average

5 (0 – 34) 37 (0– 34) 15 (0– 34)

765 + 144 711 + 140 703 + 80

105 + 17 104 + 15 100 + 10

13 + 6 9+7 12 + 4

0–1 1–2 Average

3 (0 – 34) 40 (0– 34) 21 (0– 34)

710 + 139 604 + 130 657 + 95

84 + 16 115 + 19 100 + 12

11 + 5 12 + 8 12 + 5

0 – 0.5 0.5– 1 1 – 0.5 1.5– 2 2 – 2.5 Average

594 + 124 600 + 125 632 + 128 605 + 125 621 + 129 610 + 56

587 + 187 747 + 208 627 + 194 638 + 195 548 + 183 629 + 87

637 + 26 669 + 28 627 + 29 680 + 31 656 + 30 654 + 13

7 (0–34) 9 (0–34) 0 (0–34) 12 (0 –34) 6 (0–34) 7 (0–34)

124

Radon activity concentration (Bq m23)

Relative sensitivity for thoron (%)


exposure condition of a mixture of radon and thoron, calculated standard deviations were relatively large, e.g., 7.3–21.7. In this case, the value is shown to be 7 (0–29) Bq m23 in Table 7.6. From the estimated sensitivities for thoron, it could be concluded that the relative sensitivity to thoron of the PIC detector was about 10% on average. It indicated that the radon activity concentration (Bq m23) measured in a mixture of radon and thoron was approximately the sum of the actual radon activity concentration (Bq m23) and 10% of the thoron activity concentration (Bq m23). The overestimation of radon (i.e., 10% of thoron activity concentration) due to the presence of thoron is negligible for general environments. However, care should be taken in thoron-enhanced areas. For example, Wiegand et al. (2000) reported that the median values of indoor radon and thoron activity concentrations were 92 and 215 Bq m23, respectively, for cave dwellings in the region of Yan’an (China). If a PIC monitor were used in this environment, radon activity concentrations would be overestimated by approximately 20% on average. Such overestimation is also possible in other environments when the monitor is placed near thoron exhalation sources such as thorium-rich building materials. A method to ascertain the presence of thoron using a PIC detector is to measure air sucked with a pump. Operating this way, only a small fraction of thoron would decay. Consequently, the thoron sensitivity can be increased compared with that in the diffusion mode. If there is no significant difference in measured activity concentrations between pumping and diffusion modes, it indicates that the presence of thoron is negligible.

radon (Franco-Marina et al., 2001; Huber et al., 2001; Ramola et al., 2000). The PIC detector has some sensitivity to thoron and since this detector type is a very common device for environmental radon measurements, it is important to investigate the effect of thoron on the detector response. Radon and thoron activity concentrations measured with the radon/thoron discriminative detector (see Figure 5.11) and the PIC detector in a reference chamber are shown in Table 7.6. The second column in Table 7.6 indicates the time elapsed since starting the comparison measurements of the two detectors for each exposure condition. The detectors were started well in advance of the comparison measurements so that they could have a stable response. The radon activity concentrations measured with the radon/thoron discriminative monitor shown in Table 7.6 exhibit a wide range. The radon/thoron discriminative monitor uses 218Po counts to estimate the radon activity concentration. With a background level of radon, 218Po counts are very small and the radon activity concentration has a large uncertainty. Thus, it seems that the radon activity concentrations indicated by the monitor can be lower than 0, for example, 2.7 + 31.8. In this case, the activity concentration is shown as 3 (0–34) Bq m23 in Table 7.6. The relative sensitivity to thoron ranged from 9 to 14% (average: 12%) for the exposure condition of thoron with background radon. For a mixture of radon and thoron in the approximate ratio of 1:1, the relative sensitivity ranged from 0 to 12% (average: 7%). Standard deviations for the relative sensitivity were calculated using the usual least squares error propagation equations. For the


7.4.3

A computational method for the analysis of the results of the exposure of nuclear track detectors to a mixture of radon and thoron atmospheres and the determination of the decision threshold and the detection limit are presented in Appendix B (D. Schrammel, KIT, private communication, 2013).

7.5

Variation of Aerosol Parameter Values for Radon Progeny

In order to calculate doses from inhaled radon progeny, the activity size distribution of the radon progeny is required. As described in Section 4.6, the aerosol is created in two steps: After decay of the radon gas, the freshly formed radionuclides react rapidly (,1 s) with trace gases and vapors and grow by cluster formation to form particles around 1– 3 nm in size. These unattached progeny may also attach to existing aerosol particles in the atmosphere. The attached progeny may have a tri-modal activity size distribution, which can be approximated by a combination of three lognormal distributions (Porstendo¨rfer, 2001). These consist of the nucleation mode with activity median diameters (AMD) between 10 and 100 nm, the accumulation mode with AMD values of 100 – 450 nm and a coarse mode with an AMD . 1 mm. Generally, the greatest fraction of the potential alpha energy (PAE) is in the accumulation mode. If radon (222Rn) gas measurements are made, then the equilibrium factor, F, is required for dose calculations to determine the potential alpha energy (PAE) exposure. ICRP uses representative F values of 0.4 for indoors (ICRP, 1993a) and 0.78 for outdoors (ICRP, 1987). In its 2000 report, UNSCEAR assumes similar F values of 0.4 for indoor exposures and 0.6 for outdoor exposures (UNSCEAR, 2000). For a measured radon activity concentration, the F value dominates the contribution of radon progeny to lung doses and thus has to be determined for an accurate dose assessment. The following sections discuss the variation of aerosol parameter values due to different exposure conditions. 7.5.1

Equilibrium Factor, F, and Unattached Fraction, fp, for 222Rn

The value of F depends mainly on the ventilation rate with F decreasing with increasing ventilation. As the ventilation rate increases, there is less time for the radon gas to decay (i.e., for the radon progeny to 125


grow-in) and therefore F is lower. The indoor ventilation rate and hence the value of F depends on the opening/shutting of windows, use of electric fans, air conditioners, and dehumidifiers (Chen et al., 1998; Iimoto, 2000; Iimoto et al., 2001; Iyogi et al., 2003). For example, measurements of F in hospitals in Taiwan showed that F was reduced from a value of about 0.7 to about 0.1 when a dehumidifier was in operation. In comparison, the hospital central air conditioner only reduced F by about 20% (Chen et al., 1998). Also measurements of F made over 4–8 d at the end of each month for a year in a typical Japanese apartment showed that the monthly values were lower in the summer. In summer, when the windows were open or the air conditioner was in operation, F decreased to about 0.2–0.3 compared with the winter months value of 0.6–0.7 (Iimoto, 2000). The filtration effect of the air conditioner reduces the radon progeny activity concentration and therefore reduces F (Iimoto, 2000; Tokonami et al., 1996). In dwellings and indoor workplaces, the mean values of F published in the literature vary between 0.2 and 0.7 (Tables 7.7 and 7.8). As described in Section 4.6.1, the fp value depends inversely on the ambient particle concentration. This depends on ventilation rate and whether additional aerosol sources are present, such as those due to technical processes, combustion, and human activities. The mean values of fp measured in dwellings range between 4% and 20% with some values greater than 40% (Table 7.7) (Chen et al., 1998; El-Hussein, 2005; Guo et al., 2012; Hopke et al., 1995; Huet et al., 2001a; Kojima and Abe, 1988; Kranrod et al., 2009; Mohamed, 2005; Reineking and Porstendo¨rfer, 1990; Tokonami et al., 1996b; Vargas et al., 2000; Yu et al., 1996). Similar values have also been measured in indoor workplaces (Table 7.8). In tourist caves with no additional ventilation and high humidity, the particle concentration can be low (, 4 103 cm23) with the result that fp is greater than about 10% (Table 7.9). For example, values of fp measured in a natural tourist cave, Postojna, Slovenia, by Butterweck et al. (1992) ranged from 6% to 16% with a mean of 10%. These values are similar to the ones measured in a limestone cave, Australia; fp ¼ 11–18% (Solomon et al., 1992). However, further measurements carried out in the Postojna cave gave higher values: the mean values of fp were about 60% in the summer and about 12% in the winter (Vaupoticˇ, 2008b). These are comparable with those measured in the Carlsbad Caverns, in Southern New Mexico, in summer, which ranged from 25% to 60% with a mean of 44% (Cheng et al., 1997). In addition, particle concentration measurements carried out in two tourist caves located in North Spain, indicated fp values of 26% and 86% (Sainz et al., 2007). A much lower value of fp has been measured in a Bozkov

Mathematical Analysis of Radon/ Thoron Atmospheres using Nuclear Track Detectors

MEASUREMENT AND REPORTING OF RADON EXPOSURES Table 7.7. Published values of unattached fraction, fp, and equilibrium factor, F, obtained from measurements in dwellings Place

Keller and Folkers (1984) Kojima and Abe (1988) Wrixon et al. (1988) Reineking and Portendofer (1990)

Huet et al. (2001a) Clouvas et al. (2003) Lopez and Canoba (2003) Misdaq (2003) Abumurad and Al Tamimi (2005) El-Hussien (2005) Mohamed, A. (2005) Ramola (2005) Sohrabi and Babapouran (2005) Clouvas et al. (2003) Kranrod et al. (2009)c Jilek et al. (2010)

Germany Japan. Detached two-story concrete house UK Aged aerosol, Germany Closed rooms Rooms with open windows India Bangladesh Swaziland, Traditional Modern Apartment (ground floor) Bombay, India USA and Canada Japan. Second floor Hong Kong, ACb Natural ventilation Electricfans Urban dwellings of Kaohsiung, Taiwan. Mexico City, Mexico Osijek, East Croatia Hong Kong, ACb Natural ventilation Electricians Aged aerosol, Argentina India, Lucknow Kanpur Aigarh Tokyo, Japan. Typical apartment, 3rd floor. Spain Detached house Three-story farmhouse Three-story house India, Punjab China, Control area. High background area France, aged aerosol Thessaloniki, Greece Argentina Morocco Soum region, Jordan El-Minia City, Egypt El-Minia City, Egypt Himalayas, India. Stone and mud houses Ramsar, Iran Thessaloniki, Greece Okinawa, Japan Czech Republic, Town Village

Chen and Marro (2011) Guo et al. (2012) Harley et al. (2012a)

Canada China Ottawa, Canada, Basement

Subba Ramu et al. (1990) Farid (1993) Nsibande et al. (1994)

Ramachanran and SubbaRamu (1994) Hopke et al. (1995) Tokonami et al. (1996b) Yu et al. (1996)

Chen et al. (1998) Martinez et al. (1998) Planinic et al. (1999) Yu et al. (1999)

Canoba and Lopez (2000) Khan (2000)

Iimoto (2000) Vargas et al. (2000)

Virk et al. (2000) Yuan et al. (2000)

fp

F

0.043 (0.031–0.064) — 0.096 (0.016–0.25) 0.062 (0.019–0.223)

0.34 (0.07–0.90) — 0.4 0.30 (0.15–0.49) 0.24 (0.11–0.3)

—

0.047 + 0.032 0.08 0.09 + 0.04 0.14 + 0.13 0.15 + 0.10 0.055 (0.014–0.13)

0.09–0.29

— 0.24 (0.12–0.4) 0.43 (0.14–0.7) 0.14 (0.05–0.3)

0.31 (0.08–0.67)

0.09 (0.02–0.22) 0.11 (0.04–0.21)

0.19 (0.05–0.21) 0.095 (0.04–0.25) 0.11 (0.05–0.23)

0.39 (0.33–0.50)a 0.4 (0.33–0.5)a 0.33 0.34 0.34 0.54 (0.15–0.97) 0.41 + 0.03 0.34 0.22 + 0.11 0.22 + 0.13 0.19 + 0.11 0.49 (0.24–0.79) 0.41 + 0.17 0.44 (0.12–0.89) 0.32 + 0.15 0.22 + 0.11 0.17 + 0.17 0.11–0.33 0.35 + 0.19 0.38 + 0.26 0.42 + 0.28 0.43 (0.18–0.73) 0.17 (0.12–0.22) 0.06 (0.03–0.12) 0.39 (0.15–0.6) 0.29 0.58 + 0.05 0.43 + 0.16 0.16 (0.04–0.45) 0.47 + 0.09 (0.2–0.7) 0.34 (0.1–0.8) 0.51 (0.40–0.56) 0.4 (0.36–0.42) 0.31 (0.11–0.61) 0.35 (0.19-0.62) 0.26 (0.02–0.9) 0.5 (0.39–0.73) 0.49 + 0.10 (0.2–0.7) 0.14 + 0.01 0.41 (0.26–0.63) 0.33 (0.19–0.55) 0.54 (0.20–0.82)

0.093–0.17 0.72 (0.59–0.86)

a

Range of mean values. “AC” represents dwellings with air conditioning. Measurements were also carried out with an air cleaner in operation, and the results were fp ¼ 0.52 (0.3120.71) and F ¼ 0.04 + 0.01.

b

that because of this negative correlation, radon gas measurements are a more robust indicator of dose than the PAEC under a range of aerosol conditions normally encountered in dwellings and indoor workplaces (Sections 4.5–4.7).

dolomite cave, Czech Republic with values between 1% and 3% (Rovenska´ et al., 2008). In conditions where the ventilation rate is not high, it has been shown that fp is negatively correlated with F (Section 4.6.2). Again, it is emphasized 126


Reference

Interpretation of Measurements Table 7.8. Published values of unattached fraction, fp and equilibrium factor, F for 222Rn progeny obtained from measurements in indoor workplaces Place

fp

Kindergardens, Slovenia Schools, Slovenia Schools, Kuwait Schools, Tunisia Spas, Lesvos Island, Greece Spas, Lesvos Island, Greece Spas, LoutraEdipsou, Greece Spas, Slovenia Spa, Badgastein, Austria Water supply facility, Germany

0.15 (0.03–0.24) 0.13 (0.03–0.19)

0.06–0.11c 0.038–0.13c 0.042–0.25c

Reference

0.2–0.3

Iimoto et al. (2001) Porstendo¨rfer (2001) Iyogi et al. (2003)

0.43 (0.35–0.52)c 0.39 (0.35–0.44)c 0.26 (0.19–0.32)c 0.45 (0.40–0.53) 0.55 0.06 0.3 + 0.1 0.43 + 0.29 0.38 + 0.13 0.44 (0.3–0.5) 0.39 (0.24–0.5) 0.44 (0.36–0.6) 0.36 (0.13–0.55) 0.13 (0.01–0.29) 0.42 (0.20–0.61) 0.49 (0.27–0.78) 0.6 + 0.2 0.49 (0.4–0.55)c 0.21–0.44c 0.19–0.31c 0.14–0.57c 0.21–0.45c

0.05 (0.03–0.09)

Misdaq and Flata (2003) Misdaq and Amghur (2005) Chen et al. (1998) Hattori and Ishida (1994) Yu et al. (1998) Yu et al. (2000) Hattori et al. (1995) Tokonami et al. (1996a) Tokonami et al. (2003) Guo et al. (2012) Hafez et al. (2003) Vaupoticˇ (2007) Vaupoticˇ and Kobal (2006) Maged (2006) Labidi et al. (2010) Vogiannis et al. (2004a) Vogiannis et al. (2004b) Vaupoticˇ and Kobal (2001) Lettner et al. (1996) Porstendo¨rfer and Reineking (1999)

a

“AC” represents buildings with air conditioning. Types of workplace include public office, hospital, school, manufacturing plants, and wholesale/retail buildings. c Range of mean values. b

water vapor, trace gases, and the electrical charge distribution of the radionuclides in the air. Porstendo¨rfer (2001) and Reineking et al. (1994) measured the unattached size distribution with single screens and screen diffusion batteries. They found that under “normal” conditions of humidity and radon activity concentration, the activity size distribution of the unattached progeny can be approximated with three lognormal distributions. The activity median thermodynamic diameter (AMTD) values measured were 0.6, 0.85, and 1.3 nm with geometric standard deviations (GSD) of about 1.2. In places with high radon activity concentration, the fraction with the greatest AMTD value (1.3 nm) was not observed. The neutralization rate of the unattached clusters increases with radon activity concentration and so it is likely that modes below 1 nm are mainly associated with neutral clusters, whereas modes above 1 nm are charged clusters (Porstendo¨rfer et al., 2005). However, other workers have only measured a uni-modal distribution with AMDs in the range 0.7– 1.7 nm and with GSD values between 1.1 and 1.8 (Cheng et al., 1997; El-Hussein, 2005; El-Hussein

In mines, the particle concentration and the fp value depend on the use of diesel or electricpowered equipment, the ventilation rate and the type of heating used during the winter months. If diesel engines are used, the mine aerosol is dominated by diesel particles, resulting in a low unattached fraction of about 1% or less (Butterweck et al., 1992; Solomon et al., 1994). However, in a high-grade uranium ore mine in Canada, which used dieselpowered equipment, the ventilation rate was very high (about one air change per 3 min). This resulted in a low value of F and a higher fp value than the expected value based on particle concentration. Measurements carried out in the summer of 1996 showed that the average values of fp and F were about 6% and 0.08, respectively (Cavallo et al., 1999).

7.5.2

Particle Size Distributions

7.5.2.1 Unattached 222Rn Progeny. The relative activity size distribution of unattached radon progeny clusters depends on the concentration of 127


Buildings with ACa; museums, universities and hotels. Taiwan Buildings with no additional aerosol sources. Germany 0.05 (0.02–0.14) Aomori Prefecture, Japanb Reinforced concrete buildings Wooden buildings with steel frame Reinforced concrete buildings with ACa Cafe´ with smokers, Morocco Factory (marble), Morocco Hospitals with dehumidifier, Taiwan Nuclear power plants, Japan 0.065 (0.02–0.26) Offices, Hong Kong 0.13 + 0.17 Offices, Hong Kong Offices, Tokyo, Japan 0.026 (0.017–0.035) Offices, Tokyo, Japan 0.06 (0.04–0.1) 0.11 (0.08–0.16) Offices, Tokyo, Japan Offices, China Pyramid, Egypt: entrance inside

F

MEASUREMENT AND REPORTING OF RADON EXPOSURES Table 7.9 Published values of unattached fraction, fp, and equilibrium factor, F, for 222Rn progeny obtained from measurements in tourist caves and underground wineries Reference

Butterweck et al. (1992) Solomon et al. (1992) Cheng et al. (1997) Misdaq and Ouguidi (2008) Rovenska´ et al. (2008) Vaupoticˇ (2008a)

a b

Tourist Caves Postojna, Slovenia Royal Cave, Victoria, Australia Carlsbad Caverns, New Mexico Karst Caves, Morocco Bozkov Dolomite cave, CzechRepublic Postojna, Slovenia Winter 1999a: Summer 2001a: Summer 2001b: Underground wineries Four wineries, Solovenia

fp

F

0.1 (0.056–0.16) 0.14 (0.11–0.18) 0.44 (0.25–0.59)

0.36 (0.29–0.47) 0.19–0.52 0.43 (0.36–0.48) 0.6 (0.57–0.63)

0.01–0.03 0.14 + 0.08 0.64 + 0.12 0.17 + 0.06

0.58 + 0.13 0.32 + 0.08 0.58 + 0.13

0.08 + 0.02 0.09 + 0.02 0.12 + 0.04 0.20 + 0.06

0.63 + 0.16 0.48 + 0.06 0.49 + 0.14 0.25 + 0.08

Measurements made at the lowest point of the cave. Measurements made at the railway station in the cave.

et al., 1998; Huet et al., 2001b; Mohammed, 1999). As an example, Figure 7.10 gives the activity size distribution of unattached 214Pb measured with a granular bed diffusion battery in a dwelling situated in Brittany, France (Huet et al., 2001b). The result for 218 Po was similar with an AMTD of 0.85 nm and a GSD of 1.25.

nucleation and accumulation modes with the fraction of the attached PAEC in the nucleation mode (fpn) being about 0.2 (Reineking et al., 1994). Measurements of the activity size distribution of the attached progeny in a dwelling in Okinawa, Japan, also showed a nucleation mode with an activity fraction of 0.14 (Kranrod et al., 2009). Porstendo¨rfer (2001) noted that in low ventilated rooms without additional aerosol sources, the coarse mode is insignificant because of the greater plate-out rate of large aerosol particles on room surfaces (Figure 7.11). Typically, in places with one dominant aerosol source, e.g., cigarette smoking, the activity size distribution of the attached radon progeny can be approximated by a single lognormal distribution. Porstendo¨rfer (2001) measured an AMD of about 270 nm for attached radon progeny in room air containing a high particle concentration from cigarette smoke (Figure 7.12). The contributions of the PAEC in the size ranges of nucleation particles and coarse particles were negligible. Only a few activity size measurements have been carried out in workplaces other than mines. Reichelt et al. (2000) carried out activity size measurements of 222Rn progeny at several workplaces, including offices, workshops, factories, kitchens, agricultural facilities, and public buildings, such as schools, hospitals, and art galleries. Porstendo¨rfer (2001) summarized their results and suggested dividing workplaces into three categories regarding activity size distribution and particle concentration:

7.5.2.2 Attached 222Rn Progeny. The activity size distribution of the attached radon progeny depends upon the exposure scenario and the type of aerosol sources. Activity size measurements have been carried out in underground mines, caves, dwellings, and indoor workplaces. Results of experimental studies show that the differences between the activity size distributions of the individual decay products attached on aerosol particles are negligible (Huet et al., 2001b; Porstendo¨rfer, 1996). Therefore, for simplicity and for dosimetry purposes, the aerosol distribution of each of the short-lived 222Rn progeny (i.e., of 218 Po, 214Pb, and 214Bi) is assumed to be the same. Some activity size distributions of attached 222Rn progeny are given in Table 7.10 for dwellings and workplaces other than mines. The results for dwellings without additional aerosols (i.e., for aged aerosols) show that the nucleation mode is not always observed but can be measured when additional aerosols are produced, for example, by cooking, candle burning, tile stove heating, fumigating sticks, and gas combustion (Huet et al., 2001b; Marsh et al., 2002; NA/NRC, 1991). For an aged aerosol, Huet et al. (2001b) found that the attached size distribution consisted only of the accumulation mode. However, intercomparison measurements performed in a house in Germany, without additional aerosols, showed

† Workplaces in rooms without coarse particles. † Workplaces with coarse particles generated by human activities and dispersion processes (Figure 7.13). 128


Vaupoticˇ (2008b; 2008c)

Place


Table 7.10. Measurement results of activity size distributionsa of attached 222Rn progeny inside dwellings without additional aerosols (i.e., for aged aerosols) and inside workplaces other than mines. Mean measurement values are given and the extreme values are given in parentheses Reference

Tu et al. (1991) Tokonami et al. (1997) El-Hussein et al. (1998) Mohammed (1999) Huet et al. (2001b) Porstendo¨rfer (2001) Kranrod et al. (2009)

Butterweck et al. (1992) Solomon et al. (1992) Porstendo¨rfer and Reineking (1999) Porstendo¨rfer (2001)

Place

Mode, i fpi

Dwellings (aged aerosol) Rural Urban Tokyo Egypt Egypt France Germany Japan

a a a a a a na nac

Workplaces Tourist cave Tourist cave Water supply facility

a a na

Indoors: Without coarse modeb n a With coarse modec nac

AMD (nm)

248 (221–274) 118 (86–150) 100 208 –222 320 –340 190 (180–200) 0.3 (0–0.4) 0.7 (0.6–1.0) 20 –40 210 (120–350) 0.14 (0.09–0.21) 29 (23 –42) 0.81 (0.73–0.86) 267 (234–308) 0.05 (0.05–0.07) 1860–2520

0.16 0.84 0.3 (0.2–0.5) 0.7 (0.5–0.8) 0.3 0.6 0.1

228 (119 –289) 170 50 300 15 –40 300 (150–450) 15 –40 300 (150–450) 5000 (3000–8000)

GSD

1.8 (1.3–2.2) 3.4 2.4–2.5 2.7 1.6 1.7–2.1 2.2 (1.6–3.0) 1.6 (1.5–1.7) 1.7 (1.6–1.9) 1.4–1.6 2.2 (1.3–6.0) 1.5 1.8 1.6–2.2 2.2 (1.6–3.0) 1.6–2.2 2.2 (1.6–3.0) 1.8 (1.1–2.8)

a

Indices i ¼ n, a and c represent the nucleation, accumulation and coarse modes, respectively. fpi, fraction of attached potential alpha energy concentration (PAEC) associated with mode i. GSDi, geometric standard deviation of mode i. b An fp value of 0.05 (0.02– 0.14) was assumed for indoor workplaces without coarse particles (Porstendo¨rfer, 2001). c An fp value of 0.01 (0.007– 0.02) was assumed for indoor workplaces with coarse particles (Porstendo¨rfer, 2001).

† Workplaces with one dominant aerosol source such as combustion aerosols, resulting in a uni-modal distribution for the attached progeny (Figure 7.12). For the first two categories, the nucleation mode represents about 30% of the attached PAEC (Table 7.10). Coarse particles produced by re-suspension may occur

when ventilation conditions vary considerably and when the ventilation rate is above 0.5 h21 (Reichelt, 2002). The relative size distribution of the aerosol attached 214 Pb activity concentration measured in a cabinet maker’s workshop is given in Figure 7.13 (Reichelt 129


Figure 7.10. Typical example of activity size distribution (dA/AdlogD) of unattached 214Pb plotted as a function of particle diameter D (mm). Taken from Huet et al. (2001b). EVE and Twomey are the algorithms that were used to derive the size distribution from the data.


Figure 7.12. Relative activity size distribution of the potential alpha energy concentration (Cp) of the attached radon progeny aerosol in air containing a high particle concentration of combustion aerosol from diesel engines and cigarette smoke. Continuous line: Mine air (working þ diesel engine), AMDa ¼ 200 nm. Dashed line: Room air þ cigarette smoke, AMDa ¼ 270 nm. Taken from Porstendo¨rfer (2001).

Aerosol measurements in mines were mainly carried out in the 1980s and 1990s. Butterweck et al. (1992) carried out activity size measurements of radon progeny in mines in Germany with a lowpressure cascade impactor and a high volume impactor. Their results showed that for a diesel-powered mine, the diesel aerosol dominates the mine aerosol resulting in a uni-modal distribution with an AMD of about 200 nm with a GSD of about 2.0 (Figure 7.12). During non-working hours, the AMD increased to about 350 nm with a GSD of about 2.0. Measurements have also been carried out in a uranium mine at the Olympic Dam, South Australia, with a serial graded screen array and a diffusion battery (Solomon et al., 1994). In areas of the mine where there were large diesel-powered vehicles, the AMD of the accumulation mode ranged from 200 to 300 nm with a mean value of 250 nm and a GSD of about 2.5. In the areas of the mine where there were no vehicles or the ventilation intakes were close by, the AMD values were smaller, in the range 90– 200 nm with a mean of 150 nm. A few activity size measurements of 222Rn progeny have also been carried out in a diesel-powered uranium mine in northern Saskatchewan, Canada (Cavallo, 2000; Cavallo et al., 1999; Wu-Tu et al.,

et al., 2000). The measurements were carried out with a low-pressure cascade impactor. A tube diffusion battery was connected to the front of the impactor to remove the unattached activities. If this is not done, then the unattached progeny collected in the upper stages of the impactor may be misinterpreted as the coarse mode (Gru¨ndel et al., 2005). To characterize the aerosol distribution in underground mines is difficult because of the highly variable conditions and because of the different types of mining conditions such as diesel or electric-powered equipment, different ventilation rates, and the type of heating used during the winter months (Cavallo, 2000; Marsh et al., 2008). Aerosol particle size distribution measurements were made in 27 areas in four uranium mines near Grants, NM (George et al., 1975). Mining activities included drilling, blasting, slushing, ore hauling, and equipment maintenance. All mines were ventilated by downdraft main fans and smaller auxiliary fans at stopes. Measurements were made with four compact diffusion batteries and a jet cascade impactor. The AMD ranged from 90 to 300 nm with a mean value of 170 nm (GSD ¼ 2.7). The unattached fraction, fp, ranged from 0.001 to 0.04 with a mean of 0.01. 130


Figure 7.11. Relative activity size distribution of the potential alpha energy concentration (Cp) of the attached radon progeny in a moderately ventilated room (,0.5 h21), without additional aerosol sources. This was measured with a low-pressure cascade impactor in a house in Northern Bavaria, Germany (Reineking et al., 1994). The measured size distribution (solid line) consists of the nucleation mode (broken line) and the accumulation mode (dot-dash line). Adopted from Porstendo¨rfer (2001).


Figure 7.13. Relative size distribution of aerosol-attached 214Pb activity measurement in a cabinet maker’s workshop. The two curves represent the distribution measured by the low-pressure impactor (step-like curve) and the fitted size distribution (smooth curve). Taken from Reichelt et al. (2000).

1997). Because of the exceptionally high grade ore, the mine ventilation rate was very high, about 3.6 104 m3 min21, which was estimated to be about one air change per 3 min. Measurements were carried out with an impactor during the winter of 1995 and the summer of 1996. During the winter months, the mine was heated to 58C by burning propane gas to heat the ventilation air. As a result, the mine aerosol consisted of particles from the combustion of propane gas as well as diesel particles. Wintertime measurements carried out at a stope and a drilling area where miners were working showed predominately a bi-modal distribution for the attached progeny. The mean values of the fraction of the attached PAEC associated with the nucleation and accumulation modes were about 65%, and 35%. The corresponding AMD values were about 60 and 330 nm, respectively. The summertime measurements showed that throughout the mine, the AMD values ranged from 50 to 120 nm with a mean value of 85 nm and GSD of about 2.0. It is acknowledged that the exposure conditions in mines today are significantly different from those 10– 20 years ago and that further measurements are required to characterize current mine aerosols.

7.5.2.4 Particle Density. Particle density is required when assessing the aerodynamic median diameter from measurements of the thermodynamic diameter. The first measurements of the density of airborne radioactivity were in settled dust on mine rafters in three mines in the Uravan region of the Colorado mining area. They were measured as having a range of 2.4–2.7 g cm23. This indicated silica as the primary component (HASL, 1960). Aerosol particle numbers or mass concentrations have been reported in some locations, but aerosol density is rarely measured (Kumara et al., 2012). Aerosol composition has been measured in New York State and is mainly road dust (51%), carbonaceous dust (21%), and compounds derived from fossil fuel emission such as sulphates. Measurements of mass in an industrial area in Poland using X-ray photoelectron spectroscopy (XPS)

Thoron 7.5.2.3 Thoron (220Rn) Progeny. ( Rn) decays into the short-lived progeny of 216Po, 212 Pb, and 212Bi, and it is the inhalation of these progeny that gives rise to a lung dose. However, the PAE per unit activity of 212Pb is about 105 and 10 times as great as that of 216Po and 212Bi, respectively. As a consequence, ICRP Publication 65 (ICRP, 1993a) states that “For protection against thoron, it is usually sufficient to control the intake of the decay product, lead-212, which has a half-life of 10.6 hours.” However, doses per unit PAE exposure to thoron progeny have been calculated by some authors by considering intakes of 212Pb and 212Bi (Kendall and 220

131


Phipps, 2007). The activity size distribution of 212Bi attached on aerosols is assumed to be the same as that for 212Pb. Published data on the activity size distributions of the thoron decay product 212Pb are relatively sparse. Measurement results for attached 212Pb are given in Table 7.11 for dwellings and mines. Activity size measurements performed by Kahn et al. (1987) in mines showed that the aerosol size of attached 212Pb was larger compared with that of 222 Rn progeny. The authors suggested that this may be due to the longer radioactive half-life of 212Pb, which allows 212Pb atoms to spend more time in the vicinity of aerosols, leading to increased coagulation of aerosols and thus larger particle sizes. However, measurements performed by other workers have shown that the AMD of the accumulation mode for 212 Pb and the 222Rn decay product, 214Pb are similar at least for “typical” indoor air (Becker et al., 1984; Reineking et al., 1992a; 1992b). Butterweck et al. (1992) using impactors carried out activity size measurements of 212Pb and 214 Pb/214Bi in mines. The size distributions of the attached progeny were uni-modal and the AMD values for 212Pb were similar to those of 222Rn progeny 214Pb/214Bi. During mining activities, the mean values of AMD for 212Pb ranged from 150 to 290 nm with a GSD of about 2–3, whereas during non-working hours, the mean AMD values of 300 nm and 400 nm were measured (Table 7.11). Measurements of the activity size distribution of unattached 212Pb showed that for indoor and mining environments, the unattached 212Pb were mostly neutral clusters with particle sizes of approximately 1 nm (Chen et al., 1997). Further, measurements carried out in a radon test chamber, as part of an intercomparison exercise, showed median diameters less than 1 nm for unattached 212Pb (Cheng et al., 2000).

MEASUREMENT AND REPORTING OF RADON EXPOSURES Table 7.11. Measurements of activity size distributionsa of attached given and the extreme values are given in parentheses. Reference

Becker et al. (1984) Reineking et al. (1992a; 1992b), Porstendo¨rfer (2001) Zhang et al. (2010)

Kahn et al. (1987) Butterweck et al. (1992)

Place

Mode, i

Dwellings Germany, Rural Urban Germany

a a na

Pb inside dwellings and mines. Mean measurement values are

fpi

0.14 (0.06–0.2) 0.86 (0.8–0.94)

China a City, Beijing a a Suburb, Beijing Countryside a Brick houses Cave dwellings Mines Canadian diesel-powered uranium mine. Measurements at exhaust ventilation areab Two Canadian minesb,c: Diesel Electrical German mines: Uraniummine, Gross-Schloppend Iron mine, Salzgitterd Baritemine, Lauterbergd With mining activityd Without mining activity Slate Mine, Fredeburg. Without mining activity

AMD (nm)

GSD

190 (120–240 230 (140–290) 30 –50 220 (175–270) 150 –160 110 (90–130) 80 (50 –130) 50 (40 –60)

3.0 (2.1–5.3) 2.6 (2.1–3.2) 1.9–2.1 1.8 (1.5–2.1) 1.7–2.2 2.5 (2.3–2.7) 2.9 (2.5–3.3) 3.1 (2.1–3.6)

88

2.3

100 70 190 146 (113 –171) 290 (280–300) 400 303

— — 3.1 2.0 (1.7–2.8) 2.2 (1.9–2.5) 1.6 2.4

a

Indices i ¼ n and a represent the nucleation and accumulation modes respectively. fpi, fraction of attached potential alpha energy concentration (PAEC) associated with mode i. GSDi ¼ geometric standard deviation of mode i. b Measurement carried out with diffusion batteries but resolution was poor. c Measurements carried out during winter. d Measurements carried out during working hours with mining activity.

7.6

showed that for all particle sizes, including , 1 mm, elemental carbon accounted for 80% of the mass and is the major surface element. For a diesel-powered mine, it is generally assumed that the aerosol is mainly dominated by the diesel aerosol. Several workers have calculated the effective density of diesel exhaust particles from measurements of the thermodynamic diameter (dth) and aerodynamic diameter (dae) of the exhaust particles (Olfert et al., 2007; Park et al., 2003). The effective density is the ratio of the particle density (r) and shape factor (x). Results indicate that the effective density decreases with increasing dth in the size range from 50 to 300 nm. This mainly occurs because particles become more highly agglomerated as size increases. The smaller particles are more compact than the larger particles and therefore have a higher effective density. Typically, the effective density varies from 1.2 to about 0.3 g cm23 depending on size and fuel composition; higher effective densities are observed for high sulphur fuel. For dosimetry purposes, Marsh et al. (2011) assumed an effective density of 0.6 g cm23 for radon progeny attached to diesel exhaust particles in a mine.

Estimation of Missing Exposure Data and Uncertainties Involved

As a consequence of the spatial and temporal variations of radon and radon progeny atmospheres, the a posteriori estimation of missing exposure data is only possible with great uncertainties. This is particularly important for epidemiological studies, where measurement errors and missing radon measurements contribute to major uncertainties of individual exposures. Inclusion of measurement data in residential epidemiological studies of radon and lung cancer usually requires detailed retrospective information about residences over 15–30 years. In many epidemiological studies, retrospective exposure measurements were not possible in a fraction of the study population. When radon measurements are not available for a specific lung cancer case, indirect methods have been constructed based on measurements in the control population in the same study. For example, in one individual study, radon exposure was imputed using models from prior area measurements (Raaschou-Nielson et al., 2008). In a pooling study of 13 European studies, the missing 132


Busigin et al. (1981)

212


value was estimated from either the arithmetic mean of all controls or from area-specific control means (Darby et al., 2005). In the European collaborative study, Darby et al. (2005; 2006) calculated a mean “usual” activity concentration (or true longterm average value), taking account of the uncertainties in the radon measurements. In other

words, the “usual” activity concentration was the measured activity concentration corrected for dilution by random uncertainties in measuring radon and year-to-year variability. The “usual” activity concentration was estimated as one half of the measured activity concentration for the high exposure group.


133




8. Variabilities and Uncertainties of Radon and Radon Progeny Exposure and Dosimetry 8.1

Introduction

8.1.1

The Meaning of Uncertainty in Metrology

The formal definition of the term “uncertainty of measurement” is given by GUM (ISO, 1995) and in the VIM (JCGM, 2012) as follows: Uncertainty (of measurement): a parameter, associated with the result of a measurement, that characterizes the dispersion of the values that could reasonably be attributed to the measurand. This means that the parameter may be, for example, a standard deviation (or a given multiple of it), or the half-width of an interval having a stated level of confidence. Uncertainty of measurement comprises, in general, many components. Some of these components can be evaluated from the statistical distribution of the results of a series of measurements and can be characterized by experimental standard deviations. Other components, which also can be characterized by

8.1.2

Variability of Long-term Average Radon Gas Exposures

As discussed above, the measurement uncertainty includes any uncertainty of the calibration along the traceability chain as well as other sources of uncertainty associated with the field measurement. However, in the case of radon, the true activity concentration varies with time or exhibits a trend due to other contributing factors that cannot always be monitored. In this case, the measurement of the true activity concentration at a given time cannot be repeated even if the same measurement conditions are put in place (e.g., the same instrument, the same place of measurement, and the same time of day). For radiation protection purposes, an estimate of the annual average radon activity concentration is often required. The radon levels in a house exhibit temporal and spatial variability. The temporal variability, is diurnal, monthly, seasonal, and annual (for details, see Section 7.2). The spatial variability is the variability inside a particular house. Short-term measurements have



This section considers the uncertainties associated with calibration and field measurements of 222 Rn and 220Rn exposures, radon progeny measurements, and derived quantities such as the equilibrium factor. The sources of uncertainty associated with the determination of the long-term average radon activity concentration inferred from a measurement in a single year are described. Examples of measurements and uncertainty evaluations are given for illustrative purposes with particular attention to measurements carried out with etched-track detectors (see also Appendix C). The sources of uncertainty associated with dosimetric calculations are also described. Note that this section deals only with random uncertainties and not with systematic uncertainties. The underlying concept here is “uncertainty.” An uncertainty is an intrinsic part of every measurement, the quality of the measurement device will only influence the value of the uncertainty not its existence itself.

standard deviations, are evaluated from assumed probability distributions based on experience or other information. This definition gives the state-of-the-art in dealing with all kind of measurements. Thus, all values that are derived from a measurement have to have an assigned uncertainty according to ISO (1995). The publication of incomplete uncertainties, like statistical uncertainty only, or statistical variations is not considered a sound basis for scientific work. The central task of a national metrology institute (NMI), holding a primary standard, is to realize, to maintain, and to disseminate the legal units in compliance with the International System of Units (SI). A calibration certificate issued by the NMI documents a calibration traceable to national measurement standards, thus providing secondary standards. An example for a possible traceability chain is given in Figure 8.1.


greater variability, which increases the uncertainty in radon exposure assessment. Long-term measurements, which have smaller variability, are usually preferred to short-term measurements for estimating the annual radon activity concentration. It is the estimated average annual radon activity concentration that is compared with reference levels for radiation protection purposes (ICRP, 2007). Meteorological factors can influence the amount of radon-bearing soil air flowing from the soil into the house. For example, the analysis of Miles (2001) showed that four different houses had a very different response to outdoor temperature, wind speed, and direction. Variation caused by these factors has been reviewed in Section 7.3. Outdoor temperature affects both the soil air entry rate and the air exchange within the house. Meteorological factors affect not only the transport of soil air into the house but also the radon activity concentration in soil air. The effect of wind has been considered in Section 7.3.3. Permeability directly affects the flow rate of soil air into living spaces and the typical soil type-dependent variation covers many orders of magnitude. Section 7.3.2 gives examples of subterranean air flows which strongly affect soil air radon activity concentration. Soil permeability has been considered in Section 7.3.2 and in

Figure 7.4. Rainfall may affect radon entry, for example, through variation in the soil air radon activity concentration caused by variations in radon emanation from solid mineral grains. In most case –control residential studies, measurements have been carried out in the living room and the bedroom and an average value weighted by the relative occupancy of the two rooms is calculated, although ignoring differences in breathing rates (Section 7.1.2). The exposure period of the detectors is typically 3 months or a year for each house in the study. If it is less than a year, then a seasonal correction factor is sometimes applied to obtain the annual average radon activity concentration (Section 7.3.5). To obtain a quantity that is a measure of the long-term average radon exposure over 25–30 years for a given individual, a quantity such as the time-weighted mean (TWM) activity concentration is calculated (Darby et al., 2005; 2006; Heid et al., 2004). The TWM activity concentration is the mean radon activity concentration across all homes inhabited by an individual during the 25 or 30 year period weighted by their relative residency time. Thus, for each house, the estimated annual average radon concentration is assumed to be an indication of the long-term average during the residency time, which may be over many years. 136


Figure 8.1. Traceability chain for the determination of an exposure to 222Rn activity concentration at the time of issuing this report. The basic units (s, m, mol) are realized by an NMI (PTB). The derived units (Bq, m3) may be realized by an NMI but have to be at least traceable to an NMI. The length of the traceability chain will influence the total uncertainty.

Variabilities and Uncertainties

8.1.3

Classification of Uncertainties in Exposure Assessment for Epidemiological Studies

For epidemiological studies, it is important to identify and assess the sources of uncertainty associated with the estimated long-term average radon activity concentration, distinguishing between the two types of error models, namely the “classical” and the “Berkson” models (Berkson, 1950; Heid et al., 2004). Classical type errors arise when a quantity is measured by some device and repeated measurements vary around the true value. The additive classical error model for a single source of uncertainty is: Measured value ¼ true value þ measurement error where the measurement error is a random variable with a mean of zero and is independent of the true value. Berkson type errors are involved, for example, when the average value of a group is taken as the “measured value” for an individual. The additive Berkson error model for a single source of uncertainty is:

8.2 Uncertainty Evaluations: From the Realization of the Unit to the Field Measurement

True value ¼ “measured value” þ individual peculiarity where the individual peculiarity is a random variable with a mean of zero and is independent of the “measured value.” In residential radon case–control studies, Berkson type errors occur when estimates are made for missing radon measurements based on indirect methods. For example, Darby et al. (2006) used average values in the control population as estimates

Carrying out a residential radon epidemiological study with radon activity concentration measurements obtained in dwellings (field measurements) is a complex task. A calibrated device is required to make field measurements (Figure 8.2). Such a device has assigned uncertainties from its use in field measurements and from its former

Figure 8.2. Potential resources to rely on for a radon study: While a measurement and its result (quantity with assigned uncertainty) can be expressed in a straightforward fashion according to GUM, the long-term average radon activity concentration, or dosimetric quantities and their associated uncertainty requires further evaluation (STAR is an acronym for “Systems for Test Atmosphere with Radon”).

137


for missing data (Section 7.5.3). Berkson type errors also occur when “group-matched” correction factors for radon measurements are applied to all individuals with certain characteristics in common, e.g., use of seasonal correction factors (Heid et al., 2004). Examples of classical type errors include measurement uncertainties and the uncertainty due to the year-to-year variability associated with estimates of the long-term average radon gas activity concentration based on measurements made in a single year (Darby et al., 2006; Heid et al., 2004). Heid et al. (2004) describe the sources of uncertainties associated with estimates of the long-term average radon activity concentration and classify them into errors of classical or Berkson type. The uncertainties associated with internal dosimetry can be considered as Berkson type errors (Schafer and Gilbert, 2006). The individual peculiarities represent the inability of the dosimetric model to predict the individual’s true dose for a given exposure.


device are required before starting a measurement campaign:

calibration (realization of the unit). In other words, the measured average radon activity concentration over the detector exposure period has a combined uncertainty according to GUM covering both the calibration measurement and the field measurement. Further sources of uncertainty occur in the estimation of the long-term average radon activity concentration and these are described in Section 8.3.

8.2.1

-

traceability, uncertainty, detection limit, and range of application.

Radon Gas Activity Concentration

Before a field measurement is performed, the device to be used should have been calibrated. In principle, a calibration after a field measurement is also possible, but the time between calibration and measurement should not be too long and the calibration has to be carried out in the range of activity concentration that is expected to occur. A calibration at 10 kBq m23 is not suitable for a measurement at 100 Bq m23. Although this seems to be obvious, it frequently occurs, in part due to a lack of knowledge, but sometimes due to the idea that a calibration at higher radon levels gives a better statistical significance and thus a smaller uncertainty for the calibration factor. In most cases, this is not a valid assumption since it ignores the question of linearity. Unfortunately, the devices for radon gas measurement on the market are not necessarily reliable and their determination of the value is rarely correct within the uncertainty stated by the manufacturer. A certification produced by a manufacturer is only valid if the manufacturer is properly accredited for that. However, no manufacturer meets this criterion at the moment. For example, tests performed at the PhysikalischTechnische Bundesanstalt (PTB) on two measurement devices of the same type (produced by the same manufacturer) for the measurement of 220Rn showed the following results: one differed by a factor of 1.9 and the other by a factor of 3.6 from the conventionally true value. Deviations for other devices were as high as a factor of 4 (PTB, 2011). With a correct calibration factor, all measurements performed with these devices would provide reliable data, without a correct calibration, a study based on these values will be of questionable value. To realize the unit, a calibration has to be performed to establish traceability. The uncertainty of the calibration will be an intrinsic part of each measurement later in the field. Therefore, the calibration procedures should be chosen with the same care as the device itself. In Section 5.1 and Appendix A, the general aspects are summarized as to how a field measurement should be prepared. For example, the following physical characteristics of the measuring

8.2.1.1 Rn-220 Calibration. Two typical procedures for the calibration of monitors for the activity concentration of 220Rn are used worldwide: (1) a primary calibration in a constant atmosphere based on a thorium emanation source, and (2) a secondary method based on calibration via a reference monitor enclosed in the same atmosphere as the system under test. Both methods provide valid calibration factors. In the case of the first approach, achievable relative combined uncertainties are 2–4% for k ¼ 2.1 In the case of the second approach, the relative combined uncertainties can greatly vary. Realistic uncertainties are 4–8% for k ¼ 2.1 8.2.1.2 Rn-222 Calibration. Three procedures for the calibration of monitors for the activity concentration of 222Rn are used: (1) a primary method based on a reference activity concentration realized by a primary radon gas standard and a calibration volume (both values are traceable to national standards), (2) a secondary method based on calibration via a reference monitor enclosed in the same atmosphere as the system under test, and (3) a primary/secondary calibration in a constant atmosphere based on a radium emanation source. This method is primary or secondary with respect to the components used. 1

The uncertainty stated is the expanded measurement uncertainty obtained by multiplying the standard measurement uncertainty by the coverage factor k ¼ 2. It has been determined in accordance with the “Guide to the Expression of Uncertainty in Measurement (GUM)”. The value of the measurand normally lies, with a probability of approximately 95%, within the attributed coverage interval.

138


Because the methodology of calibration differs for radon and thoron, these are described separately in the following text. However, for both radon and thoron, the calibration involves the determination of the background activity concentration of the instrument, which can be the main source of uncertainty when measuring low levels of radon or thoron. Because, the background typically increases during the service life of a radon monitor, regular systematic checks are necessary.


8.2.1.3 Determination of an Average Activity Concentration in a Room. The following example is a simple illustration of a measurement of the 220 Rn activity concentration in a room for 10 h with a direct reading instrument. That is with an active measurement device that provides continuous measurement values (quasi online) with a defined time resolution. The aim of this measurement is to determine the mean activity concentration and to obtain the corresponding uncertainty. At the start of the measurement, the device is tested for its characteristic properties, such as the background. The reading of the device might include internal calibration factors, but for the determination of a correct calibration factor, it will be taken as is. Thus, it is possible to obtain a “true” calibration factor independent of the calibration provided by the manufacturer. This procedure is comparable to the one explained in Appendix A, Equation (A1). A final advice to the user: Subtract the background from the reading of the device and multiply this value with the calibration factor to obtain the true activity concentration. This calibration is only valid if the internal calibration factors are not changed. The detection limit of the device is 5 Bq m23, its actual background reading was determined to be (10 + 1) Bq m23, and the calibration factor is 139


k ¼ 2.5 + 0.1 in the corresponding activity concentration level. The device is operated in the same geometry as in calibration, thus no further corrections for the sampling are necessary. An ab initio calculation of the uncertainty corresponding to a single measurement based on the detector parameters, such as response, measurement geometry, and counting statistics, is seldom possible because this information is not provided by the manufacturer. However, the manufacturer could have provided data for error or uncertainty but of unclear origin and an unclear mathematical base. Therefore, it is best to avoid problems caused by this situation by carrying out the following procedure. The statistical fluctuation of the device in response to a constant atmosphere is used to determine the type of uncertainty, the method of evaluation of uncertainty by the statistical analysis of a series of observations, for the given conditions. This approach is easily implemented in calibration, which can produce a calibration coefficient including this uncertainty. Thus, an instrument with low statistical power (for example, of low efficiency) will yield larger standard deviations responding to a reference atmosphere than an instrument with a high statistical power. This is independent of the quality of the reference atmosphere itself. In field measurements, the situation is more complex. Although the same effect of statistical variation caused by the instrument exists, the model of analysis is much more unspecific. For example, is the measurement a reading of a constant or changing atmosphere? To illustrate this, Figure 8.3 shows the results of measurements of the thoron activity concentration in a room over 10 h. The reading of the instrument is Cm(t) and by applying the calibration factor k and the correction of the background reading, Cm,bg the “true” activity concentration C(t) is calculated: C(t) ¼ (Cm2Cm,bg)k. The rather dramatic shift of the absolute values here is typical for many thoron measurement devices. Under the assumption that the calculation of an m ¼ average activity concentration is reasonable, C 23 (231 + 23) Bq m is determined. With the knowledge of the calibration equation for the mean activity m;bg Þ k, a simple uncer ¼ ðC m C concentration C tainty budget can be created (Table 8.1). Assuming all quantities are uncorrelated and the corresponding statistics is normal, then the combined uncertainty can easily be calculated using the law of propagation of uncertainty (ISO, 1995). This is a simple but reasonable approach to gain information about the thoron situation in a room as well as to gain information about the quality of this information. Since the dominating uncertainty in this measurement is the fluctuation of the measured activity concentration, the uncertainty associated

All facilities utilizing one or more of these methods have to be traceable to one of the facilities listed in the Calibration and Measurement Capabilities of the BIPM or in the BIPM key comparison database (http://kcdb.bipm.org/). All methods provide valid calibration coefficients. In the case of approaches 1 and 3, achievable relative combined uncertainties are 2 – 4% for k ¼ 2. In the case of the second approach, the relative combined uncertainties can vary widely, but realistic values are 4 – 6% for k ¼ 2. A calibration factor for the radon monitor under test is related to an activity concentration at a specified time C(t). This activity concentration is either given by a reference atmosphere or determined by a reference radon monitor. For statistical reasons, a measuring interval of 24 h for the extrapolation of C(t) from the reference activity concentration Cr(t,l ), by taking account of radioactive decay, is usually sufficient for activity concentration levels above 1 kBq m23. For a sealed radon gas standard, applying the radioactive decay constant l is always valid. In the case of low level radon activity concentrations (below 1 kBq m23), a calibration in a constant atmosphere is preferable to obtain small uncertainties (approach 3).


by a measurement of the activity concentration of Table 8.1. Example for the determination of the mean activity concentration C over 10 h

220

Rn

Quantity

Value

Standard uncertainty

Indexa

m C m;bg C k b C

231 Bq m23 10 Bq m23 2.5 553 Bq m23

23 Bq m23 1 Bq m23 0.1 62 Bq m23

87.0% 0.2% 12.8%

Result: Quantity

Value

Expanded uncertainty

Coverage factor

Probability in the given coverage interval

C

0.55 kBq m23

0.12 kBq m23

2.00

95% (Normal distribution)

a

The index gives the amount of influence of a single uncertainty to the combined uncertainty. m C m;bg Þk, where C m and C m;bg are the mean measured activity concentration and the mean background activity concentration, C ¼ ðC respectively, and k is the calibration factor.

b

with the mean average activity concentration is rela ¼ (0.55 + 0.12) kBq m23. As the untively large: C certainty associated with the calibration factor is smaller, this system shows much less variation in response to a constant reference atmosphere. Thus, it can be concluded that the room shows fluctuations in the thoron activity concentration around a value with the assigned uncertainty. of C This example shows that though the influence of the calibration uncertainty of the result is small, its absolute value changes the entire result. Moreover, the rather small uncertainty of the calibration will give better quality in field measurements.

8.2.2 Radon and Thoron Gas Exposures After a calibration of a thoron gas measuring device has been performed, this system is available as a secondary standard for the measurement of activity concentration, and in combination with a time measurement, also available for exposure determination (see Section 8.2.1). Determining the exposure (with k ¼ 2) from the example given in Figure 8.3 would yield an exposure P of : Dt ¼ ð5:5 + 1:2Þ kBq m3 h P¼C 140

ð8:1Þ


Figure 8.3. A measured thoron activity concentration Cm(t) (lower curve) as a function of time t and the calculated thoron activity m ¼ (231 + concentration C(t) (upper curve) obtained by applying the calibration factor and the background correction. The mean values C ¼ (553 + 62) Bq m23 with the standard variation are represented by the horizontal lines. 23) Bq m23 and C

Variabilities and Uncertainties Table 8.2. Example for the determination of the exposure P by a measurement of the activity concentration of 220Rn over 10 h Quantity

Value

Standarduncertainty

Distribution

Indexa

m C m;bg C K b C Dt Pc

231 Bq m23 10 Bq m23 2.50 553 Bq m23 10.0 h 5.525 kBq .h m23

23 Bq m23 1 Bq m23 0.05 62 Bq m23 0.0981 h 0.589 kBq .h m23

Normal Normal Normal

95.4% 0.2% 3.5%

Rectangular

0.8%

a

The index gives the amount of influence of a single uncertainty to the combined uncertainty. m C m;bg Þ k, where C m and C m;bg are the mean measured activity concentration and the mean background activity concentration, C ¼ ðC respectively, and k is the calibration factor. c is the calculated mean activity concentration and Dt is the exposure time (10 h). Exposure P ¼ CDt, where C b

8.2.2.2 Non-direct Reading Devices: Rn-222 Exposure Calibration. There is one procedure available for the calibration of non-direct reading devices for 222Rn exposure. In analogy to the 220Rn exposure calibration discussed in the previous section, it is a secondary method based on calibration via a stable reference atmosphere. There are quite a number of facilities, so-called radon chambers or STAR (System for Test Atmospheres with Radon) available worldwide. These facilities have to be traceable to one of the facilities listed in the Calibration and Measurement Capabilities of the BIPM (http://kcdb.bipm.org/). As described earlier, there are different non-direct reading devices for the measurement of 222Rn available. Since etched-track detectors are very popular in radon studies, it is worthwhile to take a closer look at these systems. The following list provides information on subjects which an ab initio approach for the calculation of the combined uncertainty in calibration and field measurements must take into account.

8.2.2.1 Non-direct Reading Devices: Rn-220 Exposure Calibration. There is one procedure available for the calibration of non-direct reading devices for 220Rn exposure. It is a secondary method based on calibration via a stable reference atmosphere. The devices to be calibrated are enclosed in the same atmosphere as the reference devices. The

† Variations of the etched-track material Track etch materials are commercially available with the quality of material varying from supplier to supplier and from manufacturing batch to manufacturing batch. Hanley et al. (2008) calculated a 141


irradiations (220Rn and/or 222Rn) are applied over a period of several hours to days in a constant atmosphere. The exposures are calculated from the mean values of the measured values of the reference standard and the irradiation time. They have to be corrected for background effects. Appendix B gives an example of how a mixed exposure (220Rn and 222Rn) calibration can be analyzed and applied to field measurements using matrix algebra. In this example, both types of detectors (radon and thoron) are exposed to a series of 220Rn exposures, and some of these detectors are additionally exposed to one 222Rn level.

with an exposure time, Dt of 10 h, and an assumed time resolution of 10 min. Thus, the uncertainty of the time measurement is less than 1% of the combined uncertainty (Table 8.2). This approach to determine exposure is for shortterm measurements with direct reading instruments and is therefore not used for epidemiological studies, but is appropriate for the determination of workplace exposures. The following sections describe the calibration of non-direct reading devices for long-term exposure measurements of 220Rn and 222Rn. So-called nondirect reading devices are time-integrating sampling devices (Section 5.2, especially SSNTD in Table 5.1 as well as thoron PADC given in Figure 5.11). The ab initio calculation of measurement uncertainty is difficult and requires the identification of all sources of uncertainty. Because etched-track detectors are commonly used in radon studies, the sources of uncertainty associated with measurements of 222Rn with etched-track detectors were considered by many studies (e.g., Hanley et al., 2008; Hardcastle and Miles, 1996; Miles, 1994; Miles et al., 2004). The results provide a basis for an ab initio approach in some special cases (see Section 8.2.2.2), but the implementation of this approach has to be done with great care: missing a source of uncertainty, choosing an improper probability function, or overestimating the influence of a quantity can lead to incorrect results. So before relying on an ab initio approach, the uncertainty model and its probability functions should be checked by exposure calibration. These checks can be implemented in the quality assurance system in the same way as the direct reading devices.


† Uncertainties due to variation in the etching process Variations in etching conditions can alter track sizes. Therefore, the etching parameters such as temperature, etch time, and chemical composition and concentration of etchant, should be monitored and kept the same (Ibrahimi et al., 2009; Miles, 1994; Miles et al., 2004). The uncertainties associated with the etching process can be measured using a control sample of detectors each exposed to the same amount of alpha radiation. An alpha-emitting source such as 241Am can be used to expose the detector. † Uncertainties of the automatic track counting system Inconsistent focusing and reading of the etch track detectors can lead to misinterpretation of the etch track characteristics. Illumination may vary, the focus of the counting system may drift, the track recognition may change, and the scratches or the surface defects may deteriorate the signal-to-background ratio, increasing the measurement error. The relative standard uncertainty of the automatic track counting system is estimated to be 5.6% (Hanley et al., 2008).

† Response to other radiation sources, e.g., thoron and thoron progeny The set-up of the etch track material inside a detector housing will influence its response to radiation. Since there is not only one source of radiation, all potential sources of interference should be checked and excluded. This is by nature not possible with 220Rn. Therefore, the response to 220 Rn has to be determined before using the detectors in the field. A calculation of diffusion times or lengths is not enough to prove insensitivity to 220 Rn, since diffusion is not necessarily the fastest path of gas transportation inside the detector housing. So if the transport of radon is not governed by diffusion, the assumption of insensitivity to 220Rn is not valid. The measurement of the 222Rn exposure in the field will in most cases be influenced by thoron. This is not an uncertainty to be taken into account but an error to be corrected—but this correction has an uncertainty. Figure 8.4 shows the response of a closed etched-track detector to a thoron activity concentration in the PTB thoron chamber. This detector was used to measure 222Rn exposure only and its response to thoron needs to be considered.

† Uncertainty in the linearity of response Detectors may be exposed to a wide range of radon activity concentrations. For example, in the UK, the mean annual radon activity concentration in a home is 20 Bq m23, but activity concentrations above 10 000 Bq m23 have been measured. At higher exposures, i.e., higher numbers of alpha particles, the probability that a new track will overlap a previous track is higher. When the tracks start to overlap, the calibration curve becomes non-linear and a correction factor must be considered. The point at which the calibration line ceases to remain linear and the degree of linearity correction required both depend on the size of the etched tracks (Ibrahimi et al., 2009). Therefore, consistent etched-track size is required for accurate determination across the expected exposure range. At high radon exposures, where track counting becomes unreliable, a calibration in terms of total area of tracks can be considered (Miles et al., 2004). Again a linear correction can be applied to allow for the areas of track overlapping.

A detailed example of the procedures to calculate the combined standard uncertainty of a calibration coefficient for etched-track detectors is given in Annex C. This example does not try to calculate the 142


† Uncertainties due to chemical change of the etch track material Etch track material is subject to many changes and variations with time. Hardcastle and Miles (1996) showed that the polymer sensitivity of CR-39 to alpha radiation damage decreased over time due to aging and fading, which may lead to an underestimation of the radon activity concentration. Aging refers to the detector losing its sensitivity to record alpha tracks over time when stored in air, possibly due to increases in crosslinking of the polymer. Fading is the loss of alpha tracks already recorded on a detector over time when stored in air, possibly due to the partial repair of damaged trails over time. As detectors are commonly placed for a minimum of 3 months during a measurement, they are subject to both aging and fading effects. The estimated relative standard uncertainties due to aging and fading given by Hanley et al. (2008) are 4.5 and 4.4%, respectively. The effect of aging (before exposure) and fading (after exposure) can be significantly minimized if the plastic is stored either below 08C or in pure nitrogen gas at room temperature and pressure.

relative standard uncertainty of 2.1% for the typical between-sheet variability for their detectors. The processing laboratory should therefore implement rigorous Quality Assurance controls in order to identify the variation in the material.


Figure 8.4. Number of tracks as a function of exposure to 220Rn for closed nuclear track detectors designed to measure the exposure of 222Rn.

uncertainty ab initio, because the complete data for that were not available. The annex also describes the procedure to calculate the uncertainty associated with a measurement in the field together with the decision threshold and detection limit. The examples are consistent with ISO (1995) and are based on measurements carried at the PTB, Germany. The reader is also referred to the ISO 11665–4 (ISO, 2012c), which describes procedures for the calculation of uncertainty associated with field measurements using passive detectors.

8.3.2

Annual average radon activity concentration in living spaces has become the standard concept when determining the exposure to radon. For practical reasons, normally shorter measurement periods than a full year are used. Section 6.4.2 considers the variation in the estimates of the annual average radon activity concentration based on short-term measurements. The coefficient of variation of the 1-month long radon measurements for the annual average radon level was typically 40% (Table 6.1). The variation of half-year or 3 months averages (15–30%) is low enough to provide good substitutes for the annual average in most applications. The coefficient of variation for a measurement with duration of 3 months was about 25%. Shorter-term (2 or 3 d) measurements are very poor predictors of the annual average. In some countries, the annual radon activity concentration was calculated from short-term measurements by applying seasonal correction factors (Section 7.3.5). The seasonal factors in one country are different from the seasonal corrections factors in another country. Therefore, every country should develop its own correction factors to extrapolate the results obtained for several months to the annual result if a correction factor is to be used.

8.3 Other Sources of Uncertainties in Assessment of the Annual Average Radon Activity Concentration 8.3.1

Uncertainties in Extrapolating a Short-term Measurement to an Annual Average

Uncertainties due to Spatial Variation of Indoor Radon Activity Concentration in Dwellings

Variation in radon activity concentration between different rooms of a dwelling increases the overall uncertainty of the estimated radon exposure to residents when only one or two rooms have been measured. Radon monitors are placed usually in two inhabited rooms, labeled as “living room” and “bedroom.” The average radon activity concentration for the house is usually calculated as an average between these two rooms weighted by their relative occupancy. In the UK, for example, the relative occupancy of the bedroom is assumed to be 0.55 based on results of a national survey (Wrixon et al., 1988). The relative occupancy of the “living room” is taken as 120.55 ¼ 0.45. The uncertainties arise from the fact that the radon activity concentrations in the rooms without measurements may differ from the radon activity concentration in the living room/bedroom, which is used as a substitute for the activity concentrations in the other rooms.

8.3.3

Uncertainties due to Long-term Variation in Annual Average Radon Activity Concentration

Section 7.3.7 deals with year-to-year radon variations. Typical values of year-to-year variation expressed as the coefficient of variation in the annual 143


Section 7.1.2 deals with the spatial variation of radon activity concentrations within houses. The activity concentration differences are, typically, higher between different floors compared with rooms on the same floor. To summarize Section 7.1.2, the COV of 30% (Heid et al., 2004) is considered as the “best estimate” and a conservative estimate of the uncertainty in exposure estimates due to variations of radon activity concentrations between rooms. This estimate represents the variation between rooms both on the same floor and on different levels above the basement. For the determination of the individual exposure to radon, the additional exposure at the workplace, with a daily occupancy factor of 0.333, equivalent to 8 hours per working day (ICRP, 1994) and in outdoor air, with a daily occupancy factor of 0.2 (UNSCEAR, 2000) must also be considered.


average radon activity concentration in the studies reviewed were in the range of 25–40%. The collaborative radon risk analysis in EU countries found a country-specific coefficient of variation of 17–62%. These estimates were based on repeated measurements of radon activity concentrations in the same dwelling in different years (Darby et al., 2006). In some countries, the measurement period was for 1 year, while for others, it was for 2–3 months. 8.3.4

8.3.5 Uncertainties Associated with the Estimate of Individual Exposure Obtained with Areal Measurements

Combined Uncertainty in the Estimation of Long-term Average Radon Activity Concentration

The combined uncertainty of the long-term average radon activity concentration can roughly be estimated on the basis of the reviews of the effect of short-term radon measurements, spatial variation within the dwelling, and the variation over years. Table 8.3 summarizes the uncertainties in the longterm average radon activity concentration based on measurements made in a single year with a measurement period of 3 months (Table 6.1) (Miles et al., 2012; Steck, 2005). The uncertainties due to different sources have been combined using the law of propagation of uncertainty (ISO, 1995) assuming these quantities are multiplicative and independent. The estimate of the combined uncertainty of 49% can be compared with the detailed error analysis of the German epidemiological analysis (Heid et al., 2004). In the German study, year-long measurements were used, in bedroom and living room. In addition, the year-by-year variability was studied using results of repeated 1 year measurements in a given house. According to Heid et al. (2004), the resulting total error size estimate of 0.55 corresponds to a coefficient of variation of 60%. The uncertainties listed in Table 8.3 do not take into account of different breathing patterns of individuals in different rooms and that the 3-month measurements carried out in these rooms may not be representative of the individual exposure.

where CRni , Oi , and Bi are the average radon activity concentration, occupancy, and average breathing rate of the individual in room i, respectively. The occupancy, Oi , represents the fraction of the time spent in room i as a fraction of the time spent at home. The long-term radon gas measurements in dwellings with passive detectors are continuous with no timeresolved information. Uncertainties, therefore arise if CRn is not representative of the radon activity concentration in the room while it is occupied. For example, the ventilation of the bedroom (due to opening or closing windows) may be different at night while it is occupied compared with during the day when it is not being used. The dwelling may only be occupied for part of the day or the week, but the passive detectors record continuously. Furthermore, the behavior of the inhabitants may change during the monitoring period by increasing or decreasing the ventilation. Measurements of the radon activity concentration in homes may be not be a good proxy for individual exposure because of the above reasons and because it does not take account of the individual’s exposure spent outside their homes, e.g., outdoors, workplace, or in other buildings (Section 6.6).

Table 8.3. Example summary of sources of uncertainty, and the estimated combined uncertainty, in the long-term average radon activity concentration, in the same house without modifications. A measurement period of 3 months has been used Source of uncertainty

Coefficient of variation (%)

Three months versus 1 year long measurement Spatial variation within the house Variation over years

25% 30% 30%

Combined

49%

8.4

Uncertainties of Radon Progeny Measurements

The general aspects of the uncertainty of the calibration and the preparation of field measurements 144


For a given activity concentration of radon progeny in air, the intake is directly proportional to the breathing rate. Therefore, lung doses are not only determined by the radon progeny activity concentration but also by the individual breathing pattern, which depends upon the physical activity of the individual. The breathing rate for an individual asleep in the bedroom is lower than that for an individual awake in the living room. For example, for dosimetric modeling, the recommended values of daily breathing rates for an adult male at home are 0.45 m3 h21 for sleep and 1.18 m3 h21 while awake (1/3 sitting and 2/ 3 light exercise) (ICRP, 1994). An improved estimate of the residential annual exposure to radon can be made by taking account of both the occupancy and the average breathing rate in the monitored rooms. One possible approach is to calculate a weighted average radon activity concentration, CRn as follows: P i CRni Oi Bi CRn ¼ P ð8:2Þ i Oi B i


8.4.1

Measurand and Derived Quantities

The measurement of a progeny activity concentration, potential alpha energy concentration, an equilibrium factor, or an unattached fraction requires a number of simultaneous measurements (for example, an a-spectrum, the volume flow of the sample, times for sampling and measurement). The measurands are the number of counts in a special region of interest, the volume flow, and time. With these measurands, the determination of an activity concentration as a derived quantity is possible. This is achieved by mathematical equations with nuclear data which have uncertainties as well. The easiest way to implement traceability to the derived value would be to calibrate the device in a reference atmosphere. This implies using the assigned uncertainties in calibration and assessing the uncertainties in field measurements separately as described in Section 8.2. Whether this approach can be used for a derived quantity depends on the quantity, the individual device and its range of application. A calibration is only possible if for a quantity (measurand or derived quantity), a stable response in a range of parameters is achieved. Thus, different reference atmospheres are necessary to assure that a calibration is feasible for the scope of application.

8.4.1.2 Reference fields for 222Rn progeny concentrations. There is one procedure available for the calibration of 222Rn progeny devices. It is a secondary method based on calibration via a stable reference atmosphere. The devices to be calibrated are enclosed in the same atmosphere as the reference devices. The irradiations are applied over a period of several hours to days in a constant atmosphere. There are quite a number of facilities (so-called radon chambers or STAR) available worldwide. Some of these facilities can be operated for 222Rn progeny calibrations. These facilities have to be traceable to one of the facilities listed in the Calibration and Measurement Capabilities of the BIPM (http://kcdb. bipm.org/).

8.4.1.1 Reference fields for 220Rn progeny concentrations. There is one procedure available for the calibration of 220Rn progeny devices. It is a secondary method based on calibration via a stable reference atmosphere. The devices to be calibrated are enclosed in the same atmosphere as the reference devices and exposed over a period of several hours to days in a constant atmosphere. For the calibration of the activity concentration of radon, thoron, and their progenies, a reference atmosphere has been established at PTB, Germany (BfS, 2006; 2007; BMU, 2009). This field consists of an airconditioned walk-in testing chamber of 6 m3 volume, in which the environmental parameters temperature, air humidity, and aerosol content can be adjusted and controlled. The range of temperature is from 08C to 708C, while the relative humidity can be controlled from 10% to 95%. A defined air movement is established by two fans on the roof of the chamber with an adjustable output from 30% to 100%. The aerosol

8.4.2

An Example for the Determination of Derived Quantities

Derived quantities are values calculated from one or more measurands (e.g., uncorrelated or correlated count rates) in combination with some constants (e.g., calibration factors, nuclear data and correction factors). The quantity radon activity concentration is a simple derived quantity with only one measurand (alpha counts), while the equilibrium equivalent 145


content is controlled by an aerosol generator based on Carnauba wax and a High Efficiency-Particulate Air (HEPA) filter system. The activity concentrations of thoron and thoron progeny are adjusted by means of 10 open exhalation sources with 228Th, which are distributed inside the chamber. For the addition of 222Rn, an external source is available. Homogeneity of the environmental parameters and of the activity concentrations of thoron and its progeny in the chamber is ensured by a special ventilation system. With this system, a compromise has been made between high circulation rates due to the short half-life of thoron, on the one hand, and low flow velocities to avoid entrainment of aerosol particles from the chamber surfaces, on the other hand. Exposure parameters for calibration purposes are (i) environmental parameters (temperature, humidity, air pressure, aerosol size distribution), (ii) radon gas activity concentration (220Rn and/or 222 Rn), and (iii) radon progeny activity concentration (216Po,218Po, 212,214Pb, 212,214Bi, 212,214Po). The environmental parameters temperature and humidity are controlled by the climate control of the air-conditioned chamber. The atmospheric parameters temperature, humidity, and pressure are measured also by a sensor system distributed inside the chamber. This system is traceable to national standards.

are the same as described in Section 8.2.1 for radon gas activity concentrations. Because the determination of the activity concentration of progeny is much more dependent on the sampling process than on the measurement itself, this has to be reflected in the uncertainty budget.


¼ ð Ceq;m Ceq;bg Þkeq F Rn;m CRn;bg ÞkRn ðC

Table 8.4. The uncertainty budget for F assuming either (a) the exposure conditions are stable so that the actual value of F is constant during the measurement period or (b) that the exposure conditions are variable so that F fluctuates with time

ð8:3Þ

Quantity

Rn;m and C eq;m are the mean radon activity where, C concentration and the mean equilibrium equivalent activity concentration. Table 8.4 gives the uncertainty budget for F assuming either (a) the exposure conditions are stable so that the actual value of F is constant during the measurement period or (b) that the exposure

(a) eq;m C Ceq,bg keq Rn;m C CRn,bg kRn c F (b) eq;m C Ceq,bg keq Rn;m C CRn,,bg kRn F a

Value


Indexa

705 Bq m23 5 Bq m23 0.88 1572 Bq m23 15 Bq m23 1.06 0.37

29 Bq m23b 2 Bq m23 0.05 39 Bq m23b 5 Bq m23 0.03 0.03

26.2% 0.1% 50.8% 10.0% 0.2% 12.6%

705 Bq m23 5 Bq m23 0.88 1572 Bq m23 15 Bq m23 1.06 0.37

140 Bq m23d 2 Bq m23 0.05 192 Bq m23d 5 Bq m23 0.03 0.09

67.0% 0.0% 5.4% 26.3% 0.0% 1.3%

The index gives the amount of influence of a single uncertainty to the combined uncertainty. b The standard uncertainty is set equal to the standard error pffiffiffi ¼ sðCÞ= n, where s(C) is the standard deviation given in Table 8.3b and n is the number of measurements, 24 in this example. c Rn;m CRn;bg ÞkRn , where, C Rn;m and eq;m Ceq;bg Þkeq =ðC F ¼ ðC Ceq;m are the mean radon activity concentration and the mean equilibrium equivalent concentration. The respective background readings and calibration factors are CRn,bg, Ceq,bg, kRn, and keq. d The standard uncertainty is set equal to the standard deviation, s(C).

Figure 8.5. Results of 24 h field measurements of the radon activity concentration CRn,m and the equilibrium equivalent activity concentration Ceq,m in a room. No corrections for calibration or for the background readings have been made. The equilibrium factor Fm ¼ Ceq,m / CRn,m is also given at the y-axis to the right.

146


conditions are variable so that F fluctuates with time. The calculations are based on the 24 individual measurement results given in Figure 8.5. Assuming stable exposure conditions, the standard so that its error of the mean is calculated for pffiffiffiffiffiC ffi standard uncertainty u(C) ¼ sðCÞ= 24 (Table 8.4a). However, if the exposure conditions are assumed to ¼ sðCÞ, where sðCÞ is the be variable then u(C) standard deviation of C (Table 8.4b). For stable exposure conditions, the determined ¼ (0.37 + 0.06) with mean equilibrium factor is F k ¼ 2 and the dominating uncertainty is the calibration of the two devices (Table 8.4a), whereas for un ¼ (0.37 + stable exposure conditions, the result is F 0.18) with k ¼ 2 (Table 8.4b). The mean value is the same, but the difference in the uncertainty is large. In the given example, the assumption of a constant atmosphere is not sustainable within the uncertainty of Table 8.4a. Nevertheless, the overall uncertainty given in Table 8.4b can be considered as too large in the case of quasi-stable situations in the room’s atmosphere. If the data set is split at 14 h as shown by the broken line in Figure 8.5, it means that the decrease in the radon activity concentration after

activity concentration Ceq includes three measurands (counts for 218Po, 214Pb,214Bi) or alternatively two correlated measurement series (alpha counts of 218 Po and 214Po as a function of time). The following simplified example shows a 24 h field measurement with a time resolution of 1 h to obtain the equilibrium factor in a room. Two independent measuring devices were used to determine the radon activity concentration CRn,m and the equilibrium equivalent concentration Ceq,m. The symbols CRn,m and Ceq,m denote the readings from these devices without applying corrections for calibration or for the background readings. Figure 8.5 shows the measurement results for both CRn,m and Ceq,m as well as the calculated equilibrium factor, Fm ¼ Ceq,m/ CRn,m. Although the functions CRn,m and Ceq,m seem to run rather parallel as a function of time, their quotient shows large fluctuations. To analyze the data further, the background readings and the calibration factors of the devices are required together with their uncertainties. In this example, the calibration factors are kRn ¼ (1.06 + 0.03) and keq ¼ (0.88 + 0.05) and their respective background readings are CRn,bg ¼ (15 + 5) Bq m23 and Ceq,bg ¼ (5 + 2) Bq m23. The mean equilibrium is given by: factor, F,


A comparison of dose-exposure conversion coefficients obtained by different lung dosimetry models for uranium mining exposure conditions, shown in Table 3.15, indicates a range of dose values from 4.2 to 12.7 mSv WLM21, with an average value of 7.9 mSv WLM21. It should be noted, however, that exposure conditions varied among the different model calculations and thus may overestimate the differences between the various model predictions. Indeed, recent calculations for three different models, the compartmental HRTM model (ICRP, 1994), a deterministic airway generation model (Winkler-Heil et al., 2002), and the stochastic airway generation model IDEAL-DOSE (Hofmann et al., 2010) using the same mining exposure conditions produced relatively similar results, ranging from 8.3 to 11.8 mSv WLM21 (2.3 to 3.3 mSv per mJ h m23). This suggests that the application of current radon lung dosimetry models will produce dosimetric uncertainties of the order of about 30%.

(a) the basis of their measurement (traceability) and (b) the model of uncertainty analysis in which all sources of uncertainty are included in the assigned uncertainty of the derived quantity.

8.5

8.5.2

Currently, a variety of uncertainties of physical and biological parameter values affect lung dosimetry. These include the relative contributions of sensitive basal and secretory cells to lung cancer risk (Section 8.5.2.1), the size distributions of attached and unattached fractions (Section 8.5.2.2), the apportionment factors for bronchial, bronchiolar, and alveolar–interstitial regions for the calculation of average lung doses (Section 8.5.2.3), and the correct value of the radiation weighting factor for radon progeny alpha particles (Section 8.5.2.4).

Uncertainties of Dosimetric Results

The primary sources of the uncertainty of dosimetric results are (1) the application of different dosimetric models, which vary with respect to lung anatomy, deposition equations, clearance velocities, location of target cells, and the application of different mathematical modeling techniques, (2) still existing uncertainties of relevant parameters, such as the relative contribution of sensitive target cells, apportionment factors, and the radiation weighting factor for alpha particles, and (3) the inter-subject variability of lung anatomy, particle deposition, particle clearance, and cellular dosimetry (Sections 3.4 – 3.8).

8.5.1

Uncertainties of Model Parameter Values used in Dose Calculations

8.5.2.1 Sensitive Target Cells. At present, basal and secretory cells are considered to be the primary target cells in bronchial epithelium (ICRP, 1994). Because of lack of more pertinent information, it is further assumed that both cell types have the same volumetric density of cell nuclei across the epithelium and the same radiosensitivity, i.e., the same relative contribution to tumor induction. Hence bronchial doses are commonly expressed as the average of 50% basal and 50% secretory cell doses, except for the IDEAL-DOSE model, where basal and secretory doses are weighted by their relative nuclear volumetric densities (Winkler-Heil and Hofmann, 2005). Thus different assumptions about the relative contributions of basal and secretory cells will affect bronchial dose estimates. For example, calculations for mining exposure conditions revealed that the choice of different target cells or any combination thereof leads to bronchial doses ranging from 1.85 to 6.23 mGy WLM21 (see Table 3.16), i.e., varying by a factor of about 3.

Application of Different Dosimetric Models

Over the last decades, a considerable number of dosimetric models for inhaled radon progeny has been published in the open literature (see Section 3.9.1). These models utilize different anatomical models of the human lung, apply different deposition equations, assume different mucociliary clearance velocities, and use different geometric models of the bronchial epithelium. Furthermore, they are based on different conceptual modeling philosophies and computational methods, ranging from semiempirical compartment models to airway geneneration models and from analytical to stochastic modeling techniques. 147


14 h can be considered separately. Thus, results for F h , t , 14 hÞ ¼ (0.39 + 0.09) can be expressed as: Fð0 with k ¼ 2 and Fð14 h , t , 24 hÞ ¼ (0.35 + 0.15) with k ¼ 2. These results overlap in the assigned uncertainties. Splitting a data set has to be done with great care. It should never be done to provide small uncertainties in results. If there is evidence of a change of exposure conditions, for example, a change in the ventilation, then it may be reasonable. However, for radiation protection purposes, long-term measurements are generally required to estimate an annual average quantity. Summarizing the discussion of uncertainties in measurements, it is indispensable to provide clear information about


an average lung dose of 2.36 mGy WLM21. For comparison, the application of non-uniform apportionment factors (ABB:Abb:AAI ¼ 0.80:0.15:0.05), based on the relative cancer sensitivity of the three regions of the lung (Porstendo¨rfer, 2002), results in an average lung dose of 4.07 mGy WLM21. Thus, calculated average lung doses may vary by nearly a factor of 2 depending on the assumed apportionment factors. 8.5.2.4 Radiation Weighting Factor. ICRP currently uses a radiation weighting factor of 20 for alpha particles to convert the absorbed dose (in gray) to an organ/tissue to an equivalent dose (in sieverts). This value was chosen for radiation protection purposes only and is based on the observed relative biological effectiveness (RBE) of alpha particles for many types of radiation effects (ICRP, 2007). The RBE values for alpha particles were derived primarily from animal experiments, but values obtained from human data were also considered (Harrison and Muirhead, 2003). However, RBE values for in vitro oncogenic transformation in different immortalized cell lines irradiated by alpha particles (with varying LET and dose) range from 2.4 to 20, with an average value of about 7 (Hofmann et al., 2004). Although the application of in vitro transformation data to in vivo carcinogenesis in bronchial tissue requires several extrapolations, these smaller values are consistent with the reported range of RBE values from 4–8 for lung cancer incidence in rats exposed to radon progeny (Cross and Monchaux, 1999). In conclusion, the actual radiation weighting factor for bronchial carcinomas caused by radon progeny alpha particles may be smaller than 20 by about a factor of 2 or even 3 (Hofmann et al., 2004).

8.5.2.3 Apportionment Factors. In radiation protection, lung cancer risk is commonly related to an average lung dose. Depending on the weighting procedure applied to basal and secretory cells, doses to the large bronchi (BB) are about a factor of 2 higher than those to the bronchiolar (bb) region (Table 3.16). Moreover, doses to the alveolar–interstitial region are between one and two orders magnitude smaller than those to the bronchial and bronchiolar regions (Table 3.3). Thus, for the assessment of an average lung dose, an additional weighting procedure has been introduced through apportionment factors for the BB, bb, and AI regions. In contrast to uniform dose distributions in the case of external exposure to gamma radiation or neutrons, the dose distribution produced by inhaled radon progeny is distinctly nonuniform. Assuming that the epithelium in each region is equally sensitive to cancer induction, this then raises the question whether each region of the human lung should contribute equally to lung cancer risk in the case of radon progeny exposure or whether the contribution of each region should be based on their relative dose. Moreover, the distribution of lung cancers among bronchial and bronchiolar airways observed in pathological examinations may be used as an additional weighting procedure. ICRP (1994) currently uses a tissue weighting factor, wT, of 0.12 for the whole lung, consisting of BB, bb, and AI regions. The apportionment of the lung tissue weighting factor to each of the three regions of the lung (BB, bb, and AI) assumed by ICRP (1994) is ABB:Abb:AAI ¼ 0.333:0.333:0.333. Based on the dose estimates listed in Table 3.16 and assuming equal weighting of basal and secretory cells and equal weighting of regional doses leads to

8.5.3

Inter-subject Variability

The primary biological parameters contributing to inter-subject variability of bronchial doses are the variability of the extrathoracic airways, the bronchial and alveolar airway structure and airway dimensions, random variations of breathing parameters, individual mucociliary clearance velocities, and variation of the thickness of the bronchial epithelium and related depths of target cells (see Section 3.8.2). Calculations of inter-subject variability indicated that the asymmetry and variability of the airway geometry is the most important factor, followed by the filtering efficiency of the nasal passages and by the diameter-related thickness of the bronchial epithelium (Hofmann et al., 2010). Several results of variability or uncertainty calculations have been published in recent years, in which the obtained dose distributions were represented by lognormal distributions. For example, the uncertainty analysis performed by NCRP (2009) 148


8.5.2.2 Radon Progeny Size Distributions. As shown in Tables 3.13 and 3.14, lung doses predicted by different dosimetric lung models can vary by more than a factor of 2, depending mainly upon aerosol particle size, unattached fraction, and target cell depth. Marsh and Birchall (2000) found that the unattached fraction and the activity median diameter of the attached fraction are the aerosol parameters that most affected the equivalent dose per WLM. For example, it is well published that the attached fraction of aerosol particle size can change from 100 to 400 nm, and the unattached fraction from 0.05 to 6 nm. A change from 100 to 400 nm for the attached fraction reduces the effective dose per WLM by about a factor 2 due to the less efficient diffusion deposition. On the other hand, the change of the size of the unattached fraction from 0.05 to 6 nm increases the effective dose per WLM by about a factor 3 due to the less efficient filtration in the nasal or oral region (see Figure 3.3).


8.5.4

of an exposure–effect relationship, where lung cancer risk is related to measured average radon activity concentrations. However, this approach neglects the fact that lung cancer is caused by the inhalation of the short-lived radon progeny and not by the inhaled radon. Alternatively, lung cancer risk can also be expressed in terms of a dose–effect relationship, where lung doses are determined by the application of dosimetric models, which consider the effect of inhaled radon progeny. In both approaches, uncertainties of either radon exposure levels or lung doses affect the estimation of lung cancer risk in epidemiological studies by assigning error bars on the x-axis. Note that the lung cancer risk plotted on the y-axis is also associated with error bars, which are particularly large at low radon levels. (1) The uncertainty of exposure levels in current epidemiological studies is dominated by the retrospective reconstruction of past exposures from a limited number of measurement sites, a limited number of passive detectors, and an exposure time which represents only a small fraction of time during which the initiation of lung cancer could occur. Indeed, a recent study (H. Paretzke: personal communication) demonstrated that the individual exposures of 23 test persons, determined by a personal exposure meter (Karinda et al., 2008), were on average a factor of 2 greater than those estimated on the basis of indoor measurements with passive devices. (2) Moreover, breathing rates depending on individual physical activities, and hence bronchial dose, were not known or were not recorded. For typical indoor exposure, a breathing rate of 0.78 m3 h21 is commonly assumed, consisting of 55% resting (sleeping), 15% sitting awake, and 30% light exercise. Since the breathing rate for sleeping, sitting, and light exercise varies from 0.625 to 1.25 l for adult men, and from 0.444 to 0.992 l for adult women (ICRP, 1994), any other combination of activity patterns will lead to different breathing rates and thus radon inhalation rates.

Summary of Uncertainties of Dose Calculations

The above discussion of uncertainties of dosimetric results suggests that the primary sources of uncertainties are the role of sensitive target cells, the definition of the radon progeny size distributions, particularly the unattached fraction, the choice of regional apportionment factors, and the appropriate value of the radiation weighting factor for radon progeny alpha particles in the bronchial region. However, despite their significance, defined values of these factors are currently adopted in international radiation protection regulations. Uncertainty of parameter values as well as intersubject variations of anatomical and physiological parameters lead to lognormal dose distributions with GSDs of the order of 1.5, while the additional consideration of intra-subject variability yields GSDs of the order of 2.5 (Hofmann et al., 2010). Although different dosimetry models have produced significant differences in dosimetric results in the past, recent model predictions suggest that the uncertainties caused by the application of different radon lung dosimetry models will not introduce uncertainties of dose estimates greater than 30 or 40%.

Since radon gas measurements do not account for the fact that doses to bronchial target cells are caused by the short-lived radon progeny, an equilibrium factor has been applied to relate measured radon gas activity concentrations to the potential alpha energy concentration (PAEC) of the progeny, because this may be a better indicator of dose. Measured equilibrium factors in different indoor environments range 0.2 –0.9, with mean values between 0.3 and 0.4, depending primarily on ventilation conditions (Porstendo¨rfer, 1994). Thus, for individual exposure conditions, the corresponding

8.6 Effect of These Uncertainties on the Analysis of Epidemiological Studies Lung cancer risk due to radon exposure in epidemiological studies is commonly reported in terms 149


resulted in a geometric mean of 9 mSv WLM21, with a geometric standard deviation (GSD) of 1.6. Marsh et al. (2002) carried out a parameter uncertainty analysis with the HRTM (ICRP, 1994) to calculate the probability distribution of the weighted equivalent dose to the lung per unit exposure to radon progeny in the home. The resulting dose distribution was approximated by a lognormal distribution with a geometric mean of 14 mSv WLM21 and a GSD of 1.5. Similar results were obtained by Birchall and James (1994) for the exposure to radon progeny in a mine. These results suggest that a GSD of about 1.5 is representative for the weighted equivalent dose to the whole lung. The analysis of the effect of intra- as well as intersubject variability on bronchial and bronchiolar doses indicated much wider lognormal dose distributions (Hofmann et al., 2010): BB: median ¼ 3.2 mGy WLM21, GSD ¼ 2.3; bb: median ¼ 2.3 mGy WLM21, GSD ¼ 4. Note that consideration of intra-subject variability which is an inherent feature of the stochastic dosimetry model, produces wider dose distributions than deterministic dosimetry models, where each individual is characterized by a single dose value.


equilibrium factor can deviate from the average value by a factor of 2. However, measurements have shown that the equilibrium factor (F) is negatively correlated with the unattached fraction (fp) for conditions where the ventilation rate is relatively low. Taking account of this negative correlation between F and fp, it has been shown that for indoor air, the radon gas activity concentration is a more robust indicator of dose than the PAEC under a range of aerosol conditions normally encountered.

In conclusion, radon levels reported in epidemiological studies are associated with significant uncertainty bars, which are largest at the lowest exposure levels, thereby affecting the statistical uncertainty of derived lung cancer risk estimates at low radon levels. However, it is in the low exposure region where the most reliable estimates of lung cancer risk are needed in order to derive statistically significant radon exposure limits for homes and workplaces.


150



9. Recommendations

Measurement objectives Radon gas or radon progeny are measured for diverse purposes, such as the determination of: † Individual exposure or remedial action decisions † Post-remediation testing to test effectiveness of mitigation systems † Average population exposure in a region or country † Distribution of exposure in a population † Demonstration of compliance with reference levels and dose limits † Airborne progeny properties for lung dose calculations or for other purposes such as: † Input for risk estimates from exposure distributions

† Ancillary measurements for retrospective exposure estimates † Evaluation of population exposure or dose guidelines † Legal purposes † Research

9.1

Good Practice Recommendations

Each assessment of the radon and thoron situation in an area of interest is based on the measurements of the respective activity concentrations. Since a measurement is the basis of all further evaluations, it is of fundamental importance to follow the rules of metrology to obtain reliable measurements. The uncertainties in measurements drive the uncertainties in risk assessment. Strict adherence to the rules will broadly affect risk assessment capability. Following these rules requires the correct usage of an international vocabulary of metrology in general and the specific vocabulary of radon in particular (Glossary and Section 8). The usage of quantities and units according to international standards is fundamental, as well as following the basic requirements of quality assurance. In order to obtain accurate results, measurements have to be performed with a traceable calibrated instrument and a measure of uncertainty has to be assigned to each measured value. Performing a measurement that is able to meet scientific or legal criteria implies that the measurement should be suited to the purpose with regard to: (1) its appropriateness (e. g., measured quantity, sampling type, long- or short-term measurement), and (2) its properties (e. g., traceability, uncertainty, detection limit, range of application). Good practice recommendations comprise good practice in recording and reporting, the use of appropriate nomenclature, e.g., SI units, and quality assurance for data validation. It must be emphasized that although performance criteria are in place, it is up to individuals to carry out the practices. Change in staff, location, budget,



This section provides recommendations regarding the optimum measurement strategies, i.e., best practices, choice of measurement techniques, appropriate recording of measurements, and reporting format of measurement results depending on the objectives. Target audiences are (i) authorities who are planning radon surveys, (ii) those carrying out measurements, (iii) those conducting epidemiological studies, and (iv) those reviewing and evaluating past (historical) studies. Due to the importance of reliable measurements of radon activity concentrations, one of the past developments in international metrology addressed two basic needs: (1) the harmonization of metrology within the scope of the Mutual Recognition Arrangement (MRA), an arrangement drawn up by the International Committee of Weights and Measures for the mutual recognition of national standards and of calibrations issued by national metrology institutes and (2) the increased demands of the European Atomic Energy Community (EURATOM) and the International Atomic Energy Agency (IAEA) directives, transferred into national radiation protection regulations with regard to natural radioactivity and its quality-assured measurements (Section 8).

MEASUREMENTS AND REPORTING OF RADON EXPOSURES

etc. can impact on usual practices. Therefore, it is important that all aspects of the data acquisition process be subject to ongoing evaluation. The combination of a reliable measurement and a well-designed and conducted survey is required for a study to be scientifically valid. The above-listed aspects of the measurements together with the following points for a survey should be considered.

9.2.1

Recommendations Regarding Measurement Strategies

Indoor radon measurements are required because it is not possible to predict with accuracy and precision the indoor radon levels in an individual building, including a dwelling or an indoor workplace. For radiation protection purposes, the appropriate measurement result should be compared with the relevant reference level. If mitigation is carried out to reduce radon exposure, then repeat measurements should be made to confirm the effectiveness of the mitigation system and records of the measurements should be kept. Remediated premises should be re-measured periodically to ensure that radon levels remain low. Measurements should also be repeated after any significant building work or changes to an operational cycle affecting exposure conditions such as changes to the heating, ventilation, and air-conditioning operation.

9.2.2

Regional Indoor Radon Mapping

Radon surveys form an essential initial step in the establishment of a national or regional radon program aiming to reduce the population risk. The principal objective of a regional survey usually is to obtain the population distribution of annual average radon activity concentrations. In the surveys of exposure of the population to indoor radon either random sample surveys or stratified sampling is recommended. The distribution of indoor radon exposure of the population of a country or region indicates the areas where action may be required to comply with national or regional reference levels 152


In dwellings, it is recommended that radon activity concentrations be measured in at least two specified rooms. High occupancy rooms are more meaningful, such as the main living room and the bedroom, than less inhabited rooms. As most of the indoor radon in a dwelling comes from the ground subjacent to the building, the lowest inhabited level of the building is preferred as one of the measurement locations (Section 6.3). In individual dwellings, long-term measurements are to be preferred and measurements over a period of 1 year are advisable. However, if for practical reasons this is not feasible, then a period as long as possible should be chosen, but not shorter than 3 months. On the other hand, in some cases, e.g., for radon screening in houses, short-term measurements represent a reasonable alternative. There is a considerable seasonal variation of radon activity concentrations. Seasonal correction factors specific for a given climate have to be applied, i.e., specific seasonal correction factors have to be determined for a given region. National or regional studies should therefore be undertaken to determine if there is an observable and reliable seasonal variation. Spring and autumn measurements may give a better estimate of the annual average radon activity concentration than the best seasonal correction factors applied to all measurements over all seasons. An alternative approach is to use only one average correction factor for heating season measurements. This has been found practical in Nordic countries where only heating season measurements are recommended. Typical values of year-to-year variation in the annual average radon activity concentration in dwellings can be expressed by a coefficient of variation. Such coefficients of variation typically range from 25% to 40%. Ongoing measurements should evaluate best estimates of the coefficient of variation as this has major impact on uncertainties in risk assessment (Section 7.3.5).

† Specifying the objectives † Target population, parameters to be estimated (e.g., population densities, construction of dwellings) † Inventory of resources, budget, staffing levels required, detectors, data processing † Choice of detector, installation, and collection of detectors † Requirements as to time schedule and accuracy required † Sampling design, sample selection mechanism, and sample size determination † Data collection method † Information security and confidentiality (i.e., implementation of guidelines on data protection) † Data processing methods, including imputation and editing † Specification of formulas for statistical quantities and measures of precision † Training of personnel and organization of field work † Allocation of resources to different survey operations † Allocation of resources to control and evaluation † Questionnaire design (if required)

9.2

Individual Dwellings

Recommendations

If a dose assessment is required for radiation protection purposes, then consideration of the actual parameters of the exposure situation should be taken into account. These may include, for example, occupancy times of the measured rooms (or in locations) and equilibrium factor (or radon progeny activity concentrations). The assessment should also take into account of any regular (i.e., diurnal) variations in radon levels, in which case time-resolved measurements may be required. In such cases, monitoring devices with 1 h time resolution are recommended. However, care must be taken to assess the full range of occupancy of the workplaces, taking into account of workers who might have non-typical occupancy. 9.2.4

9.2.3

Workplaces

Residential Epidemiological Studies

Epidemiological studies of radon risk as a function of exposure rely on measurements or estimates of radon or radon progeny exposure over long time periods. Exposures from 2 to 3 month measurements are often imputed to even 30 year exposures with amendments or assumptions, such as seasonal and annual correction factors. In some cases, long-term measurements exist or are made retrospectively with detectors that have accumulated radon progeny over long periods of time. Long-term measurements provide the best uncertainty estimates for risk assessment compared with short-term measurements (Section 6.4). For reliable dose assessments, however, individual time-resolved monitoring is needed. But for residential epidemiology studies, personal monitoring is currently not a practical option, especially for long-term measurements (Section 6.6). Although the radon progeny deliver the relevant lung dose, i.e., to bronchial epithelium, their use for residential exposure assessment is limited by the short time duration of measurement and the requirement of air sampling equipment. Exposure assessment, especially for purposes of risk estimation, requires long-term data including evaluation of retrospective exposure. Passive alpha track detectors that monitor residential radon gas atmospheres for up to 1 year have generally replaced short-term measurements. Emerging research indicates that alpha track detectors can use progeny surface deposition to measure individual, time-resolved radon progeny exposures (Section 6.6.2). A major uncertainty affecting the accuracy of exposure estimates is the diurnal, weekly, monthly, seasonal, and annual variability of radon levels in residences. If, for practical reasons, this may not be feasible, then a period as long as possible should be chosen, but at least a period of 3 months. The annual variability of the estimates of average radon

In indoor workplaces and in mixed-use buildings, which are used both by members of the public and workers (e.g., schools, libraries, hospitals, residential homes, shops, and cinemas), areal radon measurements with passive detectors are recommended to demonstrate compliance with national reference levels. In general, measurements over a period of 1 year are advisable. However, if for practical reasons, this is not feasible, then a period as long as possible should be chosen, but not shorter than 3 months. If appropriate, seasonal correction factors can be applied to obtain the annual average radon activity concentration as discussed above. Regulatory requirements apply in workplaces where the exposure to radon is considered as occupational. In such workplaces, individual exposure or dose assessment are required to demonstrate compliance with reference levels and dose limits. Depending upon exposure conditions, individual as well as area monitoring may be applied (Sections 6.5.2 and 6.6.1). If the spatial and temporal conditions are very variable or if the individual frequently changes exposure sites with different exposure conditions, then individual monitoring is generally recommended, if appropriate. For example, personal monitors are used in many underground workplaces, such as mines, where the exposure conditions are variable. On the other hand, if spatial and temporal variations can be neglected and occupancy times are known, individual exposures may reasonably be approximated by areal measurements. In such cases, individual occupancy times of the person at the workplace (or at the measured locations) should be recorded. Radon progeny measurements are recommended at workplaces where the equilibrium factor varies significantly because of variation in the ventilation or fluctuations in aerosol particle concentration. 153


(Section 6.3.2). In other words, information from radon maps can be used to support decisions to carry out radon measurements in homes and indoor workplaces. For example, if an indoor workplace is in a radon-prone area then radon measurements are usually recommended. To obtain a reasonable population-weighted average radon activity concentration for a given area, the selection of houses should be based on population densities. Other population-dependent criteria are the structure of the houses, such as single family houses or multi-story town buildings, and the construction material used, such as brick, concrete, or wood. For the measurements in the selected houses, the same recommendations apply as discussed above for individual dwellings.


9.2.5

Miner Epidemiological Studies

Since mines are generally classified as occupational exposures, legally prescribed radiation protection practices have to be performed. Radon progeny measurements were the historical choice in most underground uranium mines. The reported units were in Working Level Months (WLM), a unit that described the total alpha energy concentration of progeny per liter of air multiplied by the working months spent at various locations. Occupational exposure assessment in underground mines still relies upon real-time equipment to measure progeny mainly because regulations are based on dose. Due to the dependence of lung doses on individual physical activities, and because exposure conditions are very variable, personal measurements should be carried out, although they may be supplemented by areal measurements. In the case of uranium miners, airborne radioactivity other than radon progeny, i.e., long-lived radionuclides in the uranium ore dust, and external gamma radiation also contribute to their exposure.

† Occupancy patterns (daily, yearly) † Radon data for previous homes, workplaces, and outdoors † Physical activities † Smoking status, also spousal smoking † Gender and age † Occupant work-related information Since the actual lung carcinogens are the radon progeny and risk-based studies would require dose estimates that build upon exposure data, the additional measurement parameters related to radon progeny exposure are:

9.2.6

Retrospective Measurements

For the estimation of the retrospective exposure to radon in residential epidemiological studies, radon activity concentrations can be derived from the measurement of the long-lived radon progeny with surface or volume trap detectors (Section 5.4). Examples of suitable surface traps are:

† Equilibrium factor † Unattached fraction of the PAEC † Activity size distributions of the attached and unattached radon progeny

† Glass in a picture or photograph frame † A wall mirror in a bedroom or living room † The outer vertical surfaces of glass in a display cabinet or vitrine † Glass in a door between rooms † The flat glass surface of a clock

The residential radon activity concentration is mainly measured by passive radon detectors. Although passive radon detectors are usually designed to detect radon efficiently and exclusively, several types (actually used in major epidemiological studies) can detect thoron together with radon. In this case, these detector readings may include both radon and thoron signals and lung cancer risk will be given as a biased estimate when epidemiological studies are carried out (Section 5.2.3). Information on doses derived from thoron progeny inhalation is much sparser than that from radon progeny. Indoor levels of thoron are generally much lower than radon levels unless the materials of the internal surfaces of the building have a high content of thorium. Considering the spatial distribution of the thoron activity concentration indoors, it is questionable to apply the equilibrium factor of thoron for the determination of thoron progeny activity concentrations. Therefore, direct measurements of thoron progeny ( particularly 212Pb) are recommended (Section 4.6).

Examples of suitable volume traps are: † Filling material of cushions † Mattresses Uncertainty estimates for retrospective measurements are not well established. This is an area for worthwhile research. 9.2.7

Outdoor Radon Mapping

Methods available for outdoor radon mapping are aerial gamma surveys, soil gas measurements, and measurements of ambient radon activity concentrations. The population density distribution and the variation in geology are valuable input parameters when designing radon maps and identifying high radon areas. Spatial and temporal variations are important factors to be considered. Spatial variations 154


activity concentrations should also be taken into account when estimating risks in residential epidemiology studies. Using seasonal correction factors, the radon activity concentrations determined for measurement periods between 3 months and 1 year can be converted into annual values. If a national survey is carried out in a phased fashion (say four sequential 3 month measurement periods or three 4 month periods), then, in principle, its results could be used to generate site-specific seasonal correction factors (Section 7.3). In principle, the same measurement strategies apply as for individual dwellings. In addition, the following aspects must be considered:

Recommendations Table 9.1. Recommended devices for radon (222Rn) gas areal measurements for indoor workplaces, mixed-use buildings, or dwellings

depend on the geology of the study area and hence determine the grid size of the measurement sites. Temporal variations are caused by variable weather conditions, such as snowfall, inversion, etc. For example, variation in outdoor radon activity concentrations observed in 10 km 10 km squares or in towns is typically described by a median coefficient of variation (COV) of 60% and by a geometric standard deviation (GSD) of 1.9, with a typical variation in the range of 1.7 – 2.2. In national radon surveys, the GSD is typically in the range of 1.8–2.7 (Sections 4.4 and 7.1).

Recommendations Regarding Measurement Techniques

At present, a wide variety of measurement methods and detectors are available for radon and radon progeny measurements. Depending on the objectives of the planned study, the first decision to be made is whether to measure radon or radon progeny. Although it is the radon progeny which cause lung cancer, the measurement of radon activity concentrations is a much simpler and cheaper alternative for exposure assessment purposes. The purpose of the measurements will usually prescribe the techniques. Table 9.1 recommends devices for indoor radon (222Rn) gas areal measurements. In the case of radon monitoring, either short-term or long-term, or active or passive, or areal or personal measurement methods can be applied. In addition, the selection of an appropriate measurement device depends on the required sensitivity and accuracy. Another consideration is the related cost/ benefit relationship. For example, passive, timeintegrating devices are recommended for long-term measurements of the radon activity concentration, either for areal or personal monitoring. To avoid the potential contribution of thoron to the measured radon signal, the sensitivity of the radon monitor to thoron must be known. In the case of suspected high thoron activities, it is recommended to use a separate thoron detector (Section 5.2). In the case of individual monitoring, the required time-resolution should be correlated with physical activity, i.e., personal breathing rates, depending on gender and age, and diurnal occupancy with respect to exposure conditions. The variation of the breathing rate is a source of uncertainty in estimates of “individual dose” or “individual exposure” in epidemiological studies (Sections 6.6 and 8.3.5). In contrast to time-integrating radon monitoring, radon progeny measurements are usually shortterm measurements with filter devices combined with alpha detectors. Their use for residential

Measurement type

Device

Assessment of exposure

Long-term sampling ( 3 months)

Determination of ratio of average working time to one week activity concentrationa Post remediation test to test effectivenessc

Short-term sampling (1 week)

Alpha track Low detectors Electret Medium ionization chambers Continuous High radon monitorsb

Short-term sampling (1 week)

Cost

High Continuous radon monitors Low/ Medium Passive detectors (Alpha track, electret, activated charcoal)

a

Annual average activity concentration during working hours can be estimated my multiplying the annual average activity concentration by the ratio of the average activity concentration during the working hours of a week to the average activity concentration during the whole week. b These are active monitors that have the ability to produce timeresolved measurements. c As well as long-term testing, short-term measurements (1 week) may be started at the same time.

exposure assessment is limited by the short duration of the measurement and the requirement of realtime air sampling equipment (Section 5.3). To explore the full potential of radon progeny measurements, determination of radon progeny activity concentrations should be combined with measurements of the size distributions of the attached (cascade impactors, diffusion batteries) and the unattached fraction (screen samplers, diffusion batteries) (Section 5.3.3). 9.4

Recommendations Regarding Recording and Reporting of Measurements

Key features in recording and reporting of the results of radon measurements depend on the specific purpose of the measurement. In the case of radon measurements aimed at the assessment of radon levels in homes or indoor workplaces rather than the assessment of exposures to specific individuals, such as national radon surveys, the following key parameters should be recorded and reported. Measurements: † Date, time, and duration of measurement 155


9.3

Purpose


† Persons carrying out the measurement † Location of measurement and placement of detectors † Sampling method † Instrumentation used (methods, detectors) † Uncertainty associated with the measurement, which should be taken into account when setting reference values to comply with the limits recommended by international directives or national legislation † Detection limit and decision level † Quality assurance for data validation † Meteorological conditions, e.g., temperature, humidity, rain, or snowfall

characterizing personal exposure conditions and concomitant exposures which may contribute to lung cancer risk, such as cigarette consumption, should be considered as well. Personal exposure conditions: † Occupancy parameters † Physical activities Confounding factors:

In the case of radon progeny measurements, the following key parameters should be recorded and reported:

Results: † Persons analyzing the data † Local and temporal distribution of results † Application of seasonal or annual correction factors, taking into account their high variability † Statistical parameters: arithmetic mean and standard deviation (or coefficient of variation) and/or geometric mean and geometric standard deviation † Percentage exceeding reference levels and identification of houses above action thresholds

† Equilibrium factor † Size distribution of attached and unattached radon progeny (activity median diameter, geometric standard deviation) † Unattached fraction of the PAEC In summary, the above recommendations regarding measurement strategies, measurement techniques, and recording and reporting of measurements provide a framework of practical advice to those who are planning, conducting and reporting radon measurements for a variety of purposes.

In the case of individual exposure assessments, such as radon measurements associated with epidemiological lung cancer studies, additional key parameters

156


† Smoking status (active, passive) † Additional carcinogenic factors † Occupational exposure



Appendix A Radon and Radon Progeny Metrology and Quality Assurance of Measurements A.1

Metrological Traceability

Primary standards In the case of 222Rn, the creation of a reference atmosphere based on the development of a radon gas standard (Dersch and Schotzig, 1998; Picolo, 1996) became a standard procedure worldwide (Paul et al., 2000). The use of this procedure for the calibration of commercial devices is limited to activity concentrations above 1 kBq m23, because below this level, the measurement uncertainty of the commercial devices is too large due to the limited statistics of counts in their active volumes. For reference atmospheres below 1000 Bq m23, a time constant has been generated to perform longterm calibrations (t 5 d) of commercial devices. With the development of the low-level radon reference chamber at PTB (Linzmaier, 2012), constant activity concentrations from 1900 Bq m23 down to 150 Bq m23 are available. For this purpose, several emanation sources have been manufactured. These emanation sources generate a constant reference atmosphere in the low-level radon reference chamber. The emanation coefficients of the sources are measured and analyzed according to the count rate approach of a gas-tight closed 222Rn emanating 226Ra source.

Secondary standards A device (e.g., system under test) that is exposed to a reference atmosphere can be calibrated, thus becoming a secondary standard. If this device is used for further calibrations of other devices, for example, in other parts of the world, it is referred to as a transfer standard. The CIPM MRA National metrology institutes work independently from each other but they cooperate as signatories of the Mutual Recognition Arrangement of the Committee International des Poids et Mesures (CIPM MRA), an “Arrangement on the mutual recognition of the equivalence of national standards and of calibration certificates issued by national metrology institutes.” This assures under certain conditions that a calibration certificate from one national metrology institute is accepted to be valid by the others. One central point of the arrangement is a regulation for worldwide comparison measurements in key



Metrological traceability is a property of a measurement result whereby the result can be related to a reference through a documented unbroken chain of calibrations, each contributing to the measurement uncertainty. Traceability of the unit, for radon and its progeny typically Bq m23 or J m23, means that the calibration of the device used in the measurement is linked to a chain of calibrations originating at a national or international metrology laboratory. At the origin, e.g., a national metrology institute, the unit is realized in the form of a primary method. For example, a radon activity gas standard (Bq) is transferred without loss to a known volume (m3), thus creating a homogeneous reference atmosphere (Bq m23). This reference atmosphere is a primary standard.

For the first time, the calibration of commercial radon devices is possible in constant reference atmospheres and therefore small uncertainties are achieved. The relative standard uncertainty for the radon activity concentration at approximately 360 Bq m23 is u(C) ¼ 1.1%. In the case of 220Rn, a reference atmosphere has been available since 2009. This primary standard is based on a certified activity standard of 228Th, a certified known volume, and measurement of the 220Rn emanation factor for the activity standard, which is determined online and continuously over the entire period of the calibration (Ro¨ttger et al., 2010). The 220 Rn gas emanating from the 228Th source is determined by online measurement g-ray spectrometry through the disequilibrium of the 228Th activity (measured via 224Ra) and the 212Pb activity. A primary standard has been available for 222Rn progeny since 1999 (Paul et al., 1999) and for 220Rn progeny since 2009 (Ro¨ttger et al., 2009).


areas, so-called key comparisons, to obtain information about the degree of equivalence of national measurement standards and calibration procedures. Under the MRA, the International Bureau of Weights and Measures (Bureau International des Poids et Mesures, BIPM) publishes the results of the key comparisons in a “key comparison database” which is accessible via the internet. The database contains the results of comparisons between national (and international) standards, expressed in terms of degrees of equivalence with respect to an agreed reference value, as well as statements about the measuring capabilities of the metrology institutes and the associated uncertainty budgets for calibrations. These capabilities are also supported by supplementary comparisons, which extend the reach of the key comparisons. This structure of key and supplementary comparisons is organized through the CIPM and its laboratory, the BIPM, as well as through a series of regional metrology organizations (ROMs). The CIPM MRA also requires that all national metrology institutes provide evidence of a suitable quality system, either by self-declaration and peer review or by certification by a third party (ISO/IEC 17025, 2005). Entries for “radon” can be found at http://kcdb. bipm.org/.

ISO 9001 and ISO/IEC 17025 ISO 9001 (ISO, 2008) is a generic management standard that can be applied to any business enterprise, public administration, or government department. Growth in the use of management systems generally has increased the need to ensure that laboratories can operate in a quality management system that is seen as compliant with ISO 9001 (ISO, 2008) as well as demonstrating technical competence. Therefore, ISO 17025 (ISO, 2005) was written to incorporate all the ISO 9001 (ISO, 2008) requirements that are relevant to the scope of testing and calibration services as well as specifying the technical requirements for technical competence. Testing and calibration laboratories that comply with ISO 17025 (ISO, 2005) will also operate in accordance with ISO 9001 (ISO, 2008). The ISO 17025 (ISO, 2005) standard itself comprises five elements: scope, normative references, terms and definitions, management requirements, and technical requirements. The last two elements contain the actual accreditation requirements. Accreditation requirements are divided into management requirements (quality system, document control, review of requests, tenders and contracts, subcontracting of tests and calibrations, purchasing services and supplies, service to client, complaints, control of nonconforming testing and/or calibration work, corrective action, preventive action, control of records, internal audits, management reviews), and technical requirements (general, personnel, accommodation and environmental conditions, test and calibration methods and method validation, equipment, measurement traceability, sampling, handling of test and calibration items, assuring the quality of test and calibration results, reporting the results).

Quality Assurance

Definition and Purpose Quality assurance (QA) includes all planned and systematic actions that are necessary to provide adequate confidence in the accuracy of measurements. A quality assurance program encompasses requirements on organization and management of the service and requirements on technical equipment and provisions for carrying out measurements. Quality assurance should include validation of methods and verification of results which in turn involves all the actions by which the adequacy of equipment, instruments, and procedures are assessed against specified requirements. It should ensure that equipment and instruments function correctly, procedures are correctly established and followed, quantifiable errors are within acceptable limits, and records are correctly and promptly maintained. The quality assurance program and the regular checks made for quality control shall be fully documented. General requirements for the competence of laboratories are set out by the international standard ISO/IEC 17025 (ISO, 2005) which should be adopted by radon services carrying out radon measurements. The competence of a radon service can be formally recognized by an authoritative body working under a national accreditation scheme.

Quality Control The radon service should maintain an appropriate monitoring system to prove that specified requirements are met and processes are under control. The modality of recording relevant process parameters shall ensure the repeatability of measurements. From an analysis of the measurement process, the relevant parameters should be deduced and monitored by control charts to reveal early trends and to prevent malfunctions of procedures and equipment. A QA Plan shall specify all activities, measurements, and documentations to be carried out. The activities can encompass regular calibrations, cross-checks of measurement results (interlaboratory comparison 158


A.2

Measurements for a scientific or legal purpose have to be in agreement with ISO/IEC 17025 (ISO, 2005). This standard covers all aspects of quality assurance.

Appendix

are used to calculate the calibration factor kt for the reading of the item being calibrated.

exercises), duplicates or collocated measurements, laboratory and field background measurements. The provision of objective evidences that specified requirements have been fulfilled, is an essential prerequisite to verify processes and to accomplish confidence in results.

kt ¼

C Ct;tc Ct;bg

ðA:1Þ

Validation of Methods Validation is the confirmation that requirements for a specific intended use have been fulfilled. Standard validation procedures are type tests of instruments, comparisons, and calibrations, and should be as extensive as necessary to meet the needs of a given application. Type Test of Radon Instruments By a type test, one or more radon instruments representative of the manufacturing production are checked for compliance with requirements specific to the intended use. It covers mechanical, electrical, and radiological examinations which can be carried out by the manufacturer or by an approved testing laboratory. Specific requirements for radon measuring instruments are laid down in the standard series IEC 61577(IEC, 2000; 2006; 2009; 2011).

A.4

Example of the Analysis of Uncertainties in an Interlaboratory Comparison

Passive radon devices consisting of a diffusion chamber with a solid-state detector inside are commonly used for long-term measurements to determine the average 222Rn activity concentration. In order to estimate the measurement uncertainty of this method, an analysis of the results of the annual intercomparisons conducted by the German Federal Office for Radiation Protection (BfS) has been undertaken (Beck et al., 2005; 2007; 2009). About 20 national and international radon services have participated in the intercomparison each year since 2003. Figure A.1 shows a summary of the results. The box plots illustrate the distribution of the single

A.3 Example of the Analysis of Uncertainties in a Calibration by a Primary Radon Activity Standard For the measurements, the calibration item (system under test) is placed into the radon reference chamber of known volume Vr. Then the calibration item is exposed to radon inside the closed chamber. The radon activity concentration C in the chamber results from the activity A0 of the radon gas standard at a reference date given in the certificate, the volume of the chamber Vr and the displaced volume of the measurement item Vt to C ¼ A0/(Vr 2Vt). The readings of the calibration item are recorded over a period of 1 – 3 d, at given intervals. During this time, the radon activity concentrations in the chamber decreases as a result of radioactive decay i.e. C ¼ A0 exp (2ltc). The instrument background Ct,bg of the calibration item caused by contamination of the measurement volume, in particular with 210Pb and its decay products, are determined over a period of 24 h by means of a measurement in radon-free air, and taken into account for the calibration. The readings of the calibration Ct,tc item are averaged over the respective interval. The mean value is corrected by the respective background. These data

Table A.1. A reduced uncertainty budget according to the “Guide to the Expression of Uncertainty in Measurement” (ISO, 1995) for a calibration of a 222Rn measuring device in a reference atmosphere (primary standard)

159

Quantity

Value


Index

C A0 Vr 2Vt Ct,tc Ct,bg kt

959.8 Bq m23 60.00 Bq 0.048600 m3 1000.0 Bq m23 10.00 Bq m23 0.960

16.7 Bq m23 1.00 Bq 243.1026 m3 10.0 Bq m23 2.00 Bq m23 0.0193

68.9% 6.2% 24.8% 0.0%


An example of a resulting uncertainty budget is given in Table A.1. The results for the ratio of the activity concentrations in the reference volume and the mean values of the readings of the calibration item is kt ¼ (0.96 + 0.4) for coverage factor k ¼ 2 (see Section 8.2.1 for the definition of the coverage factor). In the respective range of the activity concentration, the reading of the calibration item must be multiplied by the calibration factor kt after subtraction of the background. The uncertainty stated is the expanded measurement uncertainty obtained by multiplying the standard measurement uncertainty by the coverage factor k ¼ 2, which has been determined in accordance with the “Guide to the Expression of Uncertainty in Measurement (ISO, 1995).” The value of the measurand then normally lies, with a probability of 95%, within the attributed coverage interval.


Figure A.1. Summary of an interlaboratory comparison for instruments with solid state nuclear track detectors at BfS since 2003, box plots indicate the distribution of the single measurement results of the participating radon service for a given reference exposure to radon (boundary of the boxes indicates the 25th and the 75th percentile, a line within the boxes marks the median, whiskers indicate the 10th and the 90th percentiles, and points indicate the 5th and 95th percentile).

results around the corresponding reference value. Only radon services which could prove an acceptable

160


quality level have been involved in the analysis. Measurement services whose average results deviate by more than 10% from the reference level were excluded. From Figure A.1, the nominal measurement uncertainty of a single 222Rn measurement using radon diffusion chambers with solid-state detectors can be deduced. This nominal measurement uncertainty represents the characteristic uncertainty of the measurement method irrespective of the individual uncertainty of a particular radon service. From this figure, it is estimated that within a range from 500 to 1000 kBq h m23, the expanded uncertainty of the method is approximately 30% (expanded uncertainty: value of the measurand that normally lies within this interval with a probability of 95%). For exposures to 222Rn above 2000 kBq h m23, the expanded uncertainty is somewhat lower (about 20%) and below 300 kBq h m23 higher. All uncertainties relate to the measurement uncertainty (IEC, 2015) of a single 222Rn measurement with a statistical safety of 95%. The standard uncertainty in the exposure range from 500 to 1000 kBq h m23, which corresponds to an annual average 222Rn activity concentration of about 100 Bq m23, is thus approximately 15%.



Appendix B Analysis of Results of the Nuclear Track Detector Exposure at PTB in View of Cross Sensitivity to Radon/Thoron and the Determination of Decision Threshold and Detection Limit

This appendix describes a computational method for the analysis of the results of the exposure of nuclear track detectors at PTB to a mixture of radon and thoron activity concentrations. Both types of detectors (radon and thoron) were exposed to a series of 220Rn exposures (102, 500, 1500, 3000 kBq m23 h), some of these detectors were additionally exposed to one 222Rn level (1250 kBq m23 h). An additional background is assumed for all detectors: nR0 (for the radon detectors) and nT0 (for the thoron detectors). By using the formula Ay¼x

ðB:1Þ

with A being the exposure matrix, x the vector of result (mean value of the number of tracks of the respective group of nuclear track detectors), the result vector y can be calculated (Tables B.1 and B.2). The values in the vector y represent the result of solving Equation (B.1): T 1 1 y ¼ Uy AT U1 x x with Uy ¼ ðA Ux AÞ

ðB:2Þ

Since the mathematical operations are timeconsuming, the use of a qualified software tool is advisable: 2 3 2 3 2 3 2 3 0:0034 0:100 uðwR0 Þ wR0 6 7 6 7 6 7 6 7 yR ¼ 4wR25 ¼ 4 3:23 5 with 4uðwR2 Þ5 ¼ 4 0:017 5ðB:3Þ nR0 2:14 52:85 uðnR0 Þ 3 3 2 3 2 2 3 2 uðwT0 Þ 0:0046 0:135 wT0 yT ¼ 4 wT2 5 ¼ 4 2:69 5 with 4 uðwT2 Þ 5 ¼ 4 0:042 5: 5:08 71:28 uðnT0 Þ nT0 Example 1 If these radon detectors are exposed to 1000 kBq m23 h of thoron, and 2000 kBq m23 h of radon, the number of tracks will be: wR0 1000 þ wR2 2000 þ 52:85 ¼ 6617:

If these thoron detectors are exposed to 1000 kBq m23 h of thoron, and 2000 kBq m23 h of radon, the number of tracks will be: wT0 1000 þ wT2 2000 þ 71:28 ¼ 6797: Combining the detectors (that is using always a radon and a thoron detector together), the individual exposure to 222Rn and 220Rn can be determined. To cover this, an uncertainty for single track density is calculated leading to 2 3 2 3 3 mR mR0 1:10E2 6 6 7 6 7 7 ½uðni Þ ¼ A 4 mT 5 with 4 mR2 5 ¼ 4 3:27E2 5 b bR 8:34 2 3 2 3 mT0 2:75E1 6 7 6 7 or 4 mT2 5 ¼ 4 4:28E2 5 ðB:4Þ bT 5:42 2

while the uncertainty of a single number of tracks is supposed to be covered by Equation (B.5) in which uð nÞ is the uncertainty of a group of m nuclear track detectors: uðni Þ ¼

pffiffiffiffiffi Þ: m uðn

ðB:5Þ

The overall uncertainty of a measurement is given by the matrix Un covering the respective sum of uncertainties: background, results according to Equations (B.2) and (B.3), and the single track density according to Equation (B.5). Using

these results, an unknown exposure E220 can be determined by solving Equation (B.6): E222 "

nR

#

"

wR0 wR2

# "

E220

#

"

nR0

#

¼ þ ; nT wT0 wT2 E222 nT0 " # " #" # " # nR 0:10 3:23 E220 52:85 ¼ þ ; ðB:6Þ nT E222 1; 35 2:69 71:28



D. Schrammel, KIT ( private communication)

MEASUREMENT AND REPORTING OF RADON EXPOSURES Table B.1. Exposure matrix and the respective matrix of variances according to Equation (B1). The thoron detectors at the exposure level of 1500 kBq m23 h (thoron) and at 1250 kBq m23 h (radon) did not pass the linearity check and were therefore dismissed Exposure matrix A E(Rn-220) E(Rn-222) Ebg

Matrix of variances 2

u ð ni Þ 0 Ux ¼ 0 ...

Radon detectors

This yields: 2

E220 E222

Table B.2. Analysis of tracks according to the results of calibration in the PTB’s reference chambers. The corresponding matrices were calculated according to Equations (B.2 –B.8)

31

6w 7 6 R0 wR2 7 ¼6 7 4 wT0 wT2 5 |fflfflfflfflfflfflfflffl{zfflfflfflfflfflfflfflffl}

nR

nT

nR0 nT0

Q

Quantity

Value (kBq m23 h)

Standard uncertainty of the value (kBq m23 h)

220

571.8 430.1

145.4 10.7

; 222

0:696 Q¼ 0:330

0:789 ; 0:0243

ðB:7Þ It is obvious from this result that the crosscorrelation of the response of nuclear track detectors toward 222Rn or 220Rn, respectively, has to be considered with great care. For practical use of the combined system, the determination of the decision threshold and detection limit is needed. According to ISO 11929 (ISO, 2010), this can be done using the following equation:

The uncertainty of the exposure is the square root of the diagonal elements of the matrix UE given by U E ¼ Q U n QT :

Rn exposure Rn exposure

ðB:8Þ

The determination of U n has to be performed carefully (sum of all uncertainties, see statements above).

~ ¼ 0Þ ~ ðE decision threshold: E ¼ k1a u #

detection limit: E ¼ E þ k1b

Example 2 A set of detectors is exposed and the tracks analyzed to be:

ðB:9Þ

~ ¼ E# Þ ðB:10Þ ~ ðE u

The decision threshold and detection limit are defined by the respective uncertainties for special exposure conditions. Calculating the limit for one exposure (radon/thoron), the corresponding other exposure value (thoron/radon) is kept constant. The

number density in the thoron monitor: 2000 cm22 number density in the radon monitor: 1500 cm22 162


Thoron detectors

Appendix B

Quantity

Decision threshold (kBq m23 h)

Detection limit (kBq m23 h)

Exposure to 220Rn Exposure to 222Rn

47.4 10.4

133.6 21.1

uncertainties are calculated in the same way as for actual exposures. The exposure to 220Rn is represented for the decision ˜ Rn-220 ¼ 0; threshold with the exposure vector ½E ERn-222 ; 1 and for the detection limit with ˜ Rn-220 ¼ E# ½E Rn-220 ; ERn-222 ; 1. The exposure to 222Rn is represented for the decision threshold with the exposure vector

163


˜ Rn-222 ¼ 0; 1 and for the detection limit ½ERn-220 ; E ˜ Rn-222 ¼ E# with ½ERn-220 ; E Rn-222 ; 1. Solving Equations (B.9) and (B.10) can be tedious, so an iterative solution might be chosen instead. With the probability of the error of first and second order a ¼ b ¼ 5%, the results are given in Table B.3. This example shows the importance of welldefined calibration and exposure conditions. Although the analysis of data is time-consuming, the final result drastically improves the quality of results obtained in all subsequent measurements. All users of radon monitors, passive or active, should be aware of the problem of cross-sensitivity to 220Rn or 222Rn, respectively. Since this effect does influence the uncertainty of the measurement, it is fundamental for the determination of the decision threshold and detection limit as well.

Table B.3. Decision threshold and detection limit determined according to ISO 11929 for a pair of nuclear track detectors




Appendix C Measurement Method using Solid-State Nuclear Track Detectors and the Expression of Results where Cr is the measured activity concentration and Crbg is the specific background value obtained with the reference instrument and kr is the calibration factor for the instrument. The uncertainty budget for exposure P is given in Table C.1 and has been calculated according to ISO (1995). During this exposure, a number m of nuclear track detectors were exposed. The variation in the track density was used to determine the uncertainty . This is a simplified uð nÞ of the mean track density n example, for a special batch of track-etch detectors only. P ni

C.1 Realization of the Unit: Determination of a Calibration Coefficient for Nuclear Track Detectors

where f takes account of variation other than counting statistics. uncertainty, uð nÞ, is then calculated as: sffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi 1 ðC:4Þ uð nÞ ¼ f P 1 :

A simple example to illustrate the general principle for using the ISO (1995) procedures for the calibration of nuclear track detectors is presented in the following uncertainty budget. The calibration conditions are well known in terms of the exposure period, Dt ¼ (t2 t1 ) and radon activity concentration CRn-222 : This calibration is performed in the radon reference chamber starting at time t1 and ending at t2 . The exposure is determined with a secondary standard (i.e., with reference instrument) that has been calibrated using a primary standard (Sections 5.1 and A.1). The exposure P is given by P ¼ CRn-222 ðt2 t1 Þ with CRn-222 ¼ kr Cr Crbg

ðC:1Þ

¼P n

u2 ðni Þ ; 1 u2 ðni Þ

ðC:2Þ

where i is the index of a given track-etch detector. A statistical consistency check is carried out as follows: X ðni n Þ

; if M . x20:95;m1 then u2 ðni Þ rffiffiffiffiffiffiffiffiffiffiffiffiffi M ; else f ¼ 1 f ¼ m1

M¼

ðC:3Þ

u2 ðni Þ

To correlate the track density to the exposure, several exposures have to be performed and analyzed. However, for simplicity, only one exposure is considered in this example (Table C.2). Also for illustrative purposes, f ¼ 1 for the unexposed detectors, while for the exposed detectors f . 1, indicating that the variation in track densities is larger than expected. If a group of m nuclear detectors is exposed to different radon levels, a linearization can be performed and if the linear model passes the consistency check,



In the following example, a number of soild-state nuclear track detectors were calibrated in the radon reference chamber of the Physikalisch-Technische Bundesanstalt (PTB), Germany. For the reference exposure, each nuclear track detector and its housing positioned in a specific geometry were brought into the radon reference chamber, together with the active radon monitor calibrated as reference standard, and exposed to 222Rn. The irradiations extended over a period of several hours to days. The exposures are calculated from the mean values of the measured values of the reference standard and the irradiation time. They were corrected for background effects. The radon activity concentration was recorded in the radon reference chamber at intervals of 10 min. A number of the detectors were not exposed and were used to determine the background effects for each device. Tables C.1–C.3 give the results of the measurements, calculated quantities, and their associated uncertainties for the determination of a calibration coefficient starting with a traceable reference atmosphere. Table C.4 gives an example of how this calibration information can be used in field measurements.

MEASUREMENT AND REPORTING OF RADON EXPOSURES Table C.1. Uncertainty budget for the exposure P according to (ISO, 1995) based on Equation (C.1) Quantity

Value


CRn-222 kr Cr Crbg t2 t1 P

30.7 kBq m23 1.031 29.8 kBq m23 59 Bq m23 49.00 h 0.0 h 1500 kBq h m23

0.5 kBq m23 0.014 0.13 Bq m23 3 Bq m23 0.04 h 0.04 h 22 kBq h m23

Table C.3. Example of the analysis of an exposure of the nuclear track detectors at 1500 kBq m23 h and 12 detectors without exposure (background detectors) to obtain a calibration coefficient k, according to Equation (C.5)

Indexa

89.7% 9.9% 0.0% 0.2% 0.2%

The index gives the amount of influence of a single uncertainty to the combined uncertainty.

12 68.94 10 2026.78

8.46 19.68 477.17 16.92

uð nÞ (cm22)

1 5.57 7.28 155.77

P : bg Þ ð nn

Assigning Uncertainty to a Measurand in a Field Measurement

Following from Equation (C.5), an unknown exposure to a radon activity concentration (mean can be obtained by: value C) bg Þ k: P ¼ ð nn

ðC:6Þ

bg Þ k nn P ¼ ð C ¼ Dt Dt

ðC:7Þ

1500 kBq m23 h 2030 cm22 69 cm22 0.77 kBq m23 h cm2

22 kBq m23 h 160 cm22 6 cm22 0.06 kBq m23 h cm2

3.2% 96.5% 0.3%

Quantity

Value


Indexa

k n bg n P Dt C

0.77 kBq m23 h cm2 3290 cm22 50 cm22 2500 kBq m23 h 2000 h 1.25 kBq m23

0.06 kBq m23 h cm2 220 cm22 5 cm22 260 kBq m23 h 14 h 0.13 kBq m23

56.8% 43.2% 0.0% 0.4%

¼ (1.25 + 0.26) kBq m23 (with a coverage C factor k ¼ 2). These results show the expanded measurement uncertainty obtained by multiplying the standard measurement uncertainty by the coverage factor k ¼ 2. It is determined in accordance with the “Guide to the Expression of Uncertainty in Measurement (GUM).” The value of the measurand then normally lies, with a probability of 95%, within the attributed coverage interval. This method is strictly only valid, if the conditions and constraints set up by all equations for calibration are valid for the field measurements as well. A good example, where this may not be the case, is the presence of thoron (220Rn) in field measurements. The thoron activity concentration for the above example is assumed to be negligible in the calibration procedure and in the field measurement, or the nuclear track detectors are assumed to be insensitive to thoron. However, this cannot always be assumed. For example, all systematic investigations at the PTB thoron chamber showed a significant effect of the presence of 220Rn activity concentration on 222Rn measuring devices particularly for open detectors. For closed detectors, where the nuclear track detector is mounted in a closed container, the sensitivity to thoron (220Rn) is less (Section 7.4).

ðC:5Þ

The calculated value of k and its associated uncertainty is given in Table C.3 for this example.

C.2

P n bg n k

a The index gives the amount of influence ofa single uncertainty to the combined uncertainty.

the calibration coefficient, k, can be calculated as follows:

k¼

Indexa

Applying the law of propagation of uncertainty (ISO, 1995) to Equation (C.7), the uncertainty budget for C can be determined (Table C.4). The determined exposure (of a field measurement) is expressed in the form P ¼ (2.5 + 0.6) 103 kBq m23 h (with a coverage factor k ¼ 2) and the mean value for the radon activity concentration during the time of measurement (2000 h) is given by 166


0 1500


Table C.4. Example of the analysis of nuclear track detectors to obtain an exposure according to Equation (B.6)

Table C.2. Example of the analysis of the track density for an exposure of 10 nuclear track detectors at 1500 kBq m23 h and the track density for 12 detectors without exposure (background detectors)

x20:95;m1 f

Value

a The index gives the amount of influence of a single uncertainty to the combined uncertainty.

a

(cm22) M P (kBq m23 h) m n

Quantity

Appendix C

#: and the detection limit C

The decision threshold and detection limit can be calculated according to ISO 11929 (ISO, 2010). The decision threshold and detection limit are defined by the respective uncertainties for special exposure conditions. With the probability of the error of first- and second-order, typically a ¼ b ¼ 5%, the results can be : expressed by the decision threshold C e ¼ k1a u ¼ 0Þ ~ ðC C

e ¼C #Þ # ¼ C þ k1b u ~ ðC C

ðC:9Þ

# ¼ 15 ¼ 6 Bq m23 and C In the given example C Bq m23 is determined. Detailed and simple examples for the determination of the uncertainties for different detector types, their decision threshold, and detection limit can be found in ISO 11665-4 (ISO, 2012c).

ðC:8Þ


167




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Occupational and environmental exposures to radon: cancer risks.

Preface: radon-thoron instrumentation and measurement.

Radon measurement and mitigation activity in Finland.

Efficiency analysis and comparison of different radon progeny measurement methods.

Neisseria gonorrhoeae and Chlamydia trachomatis among women reporting extragenital exposures.

Measurement uncertainties in whole body counting and radon progeny.

Multi-parametric approach towards the assessment of radon and thoron progeny exposures.

Healthcare reform: quality outcomes measurement and reporting.

Radon measurement of natural gas using alpha scintillation cells.

Measurement of radon progenies using the Timepix detector.

Lung cancer risk due to residential radon exposures: estimation and prevention.

Radon Mitigation Approach in a Laboratory Measurement Room.

Study on peak shape fitting method in radon progeny measurement.

Reconstruction of national distribution of indoor radon concentration in Russia using results of regional indoor radon measurement programs.

Measurement of personal carbon monoxide exposures by mailed passive sampler.

The measurement of activity-weighted size distributions of radon progeny: methods and laboratory intercomparison studies.

The relationship between measurement uncertainty and reporting interval.

Analysis of problems and failures in the measurement of soil-gas radon concentration.

Radon in waterworks: dose assessment, analysis of influence parameters and improved methods of measurement.

Track counting and thickness measurement of LR115 radon detectors using a commercial image scanner.

thoron and its daughter nuclides in room air.

Reporting individual results for biomonitoring and environmental exposures: lessons learned from environmental communication case studies.

Radon daughter exposures at the Radium Hill uranium mine and lung cancer rates among former workers, 1952-87.

Revised coefficients for the measurement of radon-222 daughter concentrations in air.