NUREG-1720

Re-evaluation of the Indoor

Resuspension Factor for the

Screening Analysis of the 

Building Occupancy Scenario for

NRC’s License Termination Rule

Draft Report for Comment

U.S. Nuclear Regulatory Commission

Office of Nuclear Material Safety and Safeguards

Washington, DC 20555-0001
NUREG-1720

Re-evaluation of the Indoor Resuspension

Factor for the Screening Analysis of the

Building Occupancy Scenario for NRC’s

License Termination Rule 

Draft Report for Comment

Manuscript Completed: April 2002

Date Published: June 2002

Prepared by:

R.M. Abu-Eid, R. B. Codell, N. A. Eisenberg* 

T. E. Harris, S. McGuire** 

Division of Waste Management

Office of Nuclear Material Safety and Safeguards

U.S. Nuclear Regulatory Commission

Washington, DC 20555-0001

* 1208 Harding Lane, Silver Spring, MD, 20905

** Incident Response Office, U.S. Nuclear Regulatory Commission 

 
COMMENTS ON DRAFT REPORT

Any interested party may submit comments on this report for consideration by the NRC staff. 

Comments may be accompanied by additional relevant information or supporting data. Please

specify the report number NUREG-1720, in your comments, and send them to:

Chief, Rules and Directives Branch

Division of Administration Services,

Office of Administration, Mail Stop T-6D59

U.S. Nuclear Regulatory Commission

Washington, DC 20555-0001

You may also provide comments at the NRC Web site, http://www.nrc.gov . See the link under

“Technical Reports in the NUREG Series” on the “Reference Library” page. Instructions for

sending comments electronically are included with the document, NUREG-1720, at the web site.

For any questions about the material in this report, please contact:

Rateb (Boby) Abu-Eid

Mail Stop T-7 J-8 

U.S. Nuclear Regulatory Commission

Washington, DC 20555-0001

Phone: (301) 415-5811 

E-mail: BAE@NRC.GOV
iii

ABSTRACT

The purpose of this study was to re-evaluate the resuspension factor (RF) parameter used in

the screening analysis for demonstration of compliance, using the building occupancy scenario,

with the radiological criteria in the license termination rule in 10 CFR 20, Subpart E. The RF is a

highly sensitive parameter impacting the inhalation dose calculation. An RF parameter value of

1.42 x 10-4 m-1 was established for screening analysis (Beyeler et al, 1999). Assuming a 

10 percent fraction of loose (removable) contamination, NRC staff selected a default RF value of

1.42 x 10-5 m-1 for use in the inhalation dose calculation. Based on this RF value, and using the

DandD code, the derived default concentration or surface activity screening limits for most

radionuclides, particularly the alpha-emitters, were at background levels or far below the

corresponding detection limits. In this study, NRC staff analyzed further literature data

considering more realistic assumptions of the average member of the critical group in the

building occupancy scenario and accounting for more recent actual RF field data collected for

two facilities undergoing decommissioning. Based on the current analysis and re-evaluation,

staff recommends using an RF value of 10-6 m-1 in the screening analysis of the inhalation dose

calculation for the building occupancy scenario. The staff believes that the newly proposed RF

default value is more realistic than the current value in DandD code, and sufficiently conservative

for screening analysis. 
v

CONTENTS

Page

Abstract ......................................................................................................... iii

Contents......................................................................................................... v

List of Figures ............................................................................................... vii

List of Tables ................................................................................................. viii

Executive Summary ....................................................................................... ix

Foreword .......................................................................................................... xi

Acknowledgments........................................................................................... xii

1.0 Introduction ........................................................................................1

2.0 Inhalation Dose Calculations and Factors Affecting the Indoor RF...2

2.1 The NUREG/CR-5512 and the DandD Inhalation Dose Model .. 2

2.2 Factors Affecting the RF ......................................................... 2

2.2.1 Driving Forces ............................................................. 3

2.2.2 Removal Mechanisms ................................................ 3

2.2.3 Characteristics of the Surface Activity ....................... 4

2.2.4 Particle Size Effects .................................................... 5

2.3 Using the Wipe Tests to Assess Removable Fraction ............ 5

3.0 Previous Determinations of the RF ..................................................... 6

3.1 Basis for Deriving the Indoor RF in 

 NUREG/CR-5512, Volume 1 .............................................. 6

3.2 Development of the RF in DandD Code Version 1.0 ............6

4.0 Review and Evaluation of the Measured Data for the Indoor RF ......7

4.1 Breslin, 1966, Data .................................................................. 10

4.2 Eisenbud, 1954, Data ............................................................... 11

4.3 Fish, 1967, Data ....................................................................... 11

4.4 Ikezawa, 1980, Data ................................................................. 12

4.5 Jones, 1967 Data ..................................................................... 12

4.6 Nardi, 1999, Data ...................................................................... 13
vi

CONTENTS (cont’d)

Page

4.7 Ruhter and Zurliene, 1988 Data ............................................... 15

4.8 Spangler, 1998, Data .................................................................. 15

4.9 Summary of Data Used for Revising the RF .............................. 16

5.0 Development of an Alternate Estimate for RF ...................................... 17

5.1 Correction Factor for Time Variation of Airborne

Concentration ............................................................................ 18

5.2 Statistical Analysis of the RF ................................................... 22

5.2.1 Adjustments to Data ...................................................... 22

5.2.2 Statistical Analysis of Site Mean Results ..................... 24

6.0 Summary, Conclusions, and Recommendations .................................. 24

6.1 Summary .................................................................................. 24

6.2 Conclusions .............................................................................. 25

6.3 Recommendations .................................................................... 27

7.0 References ............................................................................................ 28

8.0 Appendix A ........................................................................................... 30
vii

LIST OF FIGURES

Figure Page

1 Cumulative Probability Function for RF Developed for 

DandD Code by SNL (Beyeler, et al.1999)).......................................8

2 Analysis of Breslin (1966) Data Showing the Variation With Time 

of the Concentration Measured at Different sampling Locations........ 19

3 Beta Air Activity Sample Results for Westinghouse

Active/Inactive Decommissioning Facilities......................................... 20 

4 Predicted Dust Load for Nardi, (1999) Data........................................ 21 

5 Predicted Variation of Dust Concentration (gm/cm3

) Using

Breslin Data (1966) .............................................................................. 21

6 Cumulative Probability Distribution (Normal & Lognormal) 

Of the RF Using Site Mean Values of Five Facilities.......................... 23

 
viii

LIST OF TABLES

Table Page

1 Summary of Representativeness of RF Data .................................... 9

2 Results of Jones, 1967, Study ........................................................... 13

3 Summary of RF Data Applicability ..................................................... 17

4 Mean Values of RF for Each Site ........................................................ 22

5 Parameters for Normal and Lognormal “Maximum Likelihood” 

Models of RF Data ............................................................................... 27

A-1 Summary of RF Values Based on Breslin et. al., (1966) Data ............. 30
ix

EXECUTIVE SUMMARY

This study was conducted to re-evaluate and establish a more realistic and representative

resuspension factor (RF) for use in screening dose analysis. Based on a study conducted by

Sandia National Laboratory, (SNL) (Beyeler et al, 1999), NRC staff adopted a default RF value of

1.42 x 10-5 m-1 for use in DandD screening code to derive default concentrations or surface

activity screening limits (NUREG-1727, 2000). Due to the highly conservative value of the RF,

the derived surface activity levels for most alpha-emitting radionuclides were unrealistically low

at or near background levels or below the corresponding detection limits. For example, the

screening concentrations equivalent to 0.25 mSv/y (25 mrem/y) for Th-232, U-238, and Am-241

were derived at 0.12, 1.68, and 0.45 Bq/100 cm2 (7.3, 101, and 27 dpm/100 cm2 ) respectively. 

In this study, the staff evaluated the main factors affecting the RF value such as the driving

forces, the removal mechanisms, the characteristics of surface activity (e.g., bound or loose),

and the particle size. Staff assessed these factors considering the building occupancy scenario

as defined in NUREG/CR-5512, Volume 1 (NRC, 1992); NUREG-1496, (NRC, 1997); and 

NUREG-1549, (NRC, 1998). In addition, staff assessed current tests used to determine

removable (loose) fraction using the “wipe” or “smear” tests. Further, the staff critically

evaluated the basis for deriving the indoor RF in NUREG/CR-5512, Volume. 1, and SNL

approach (Beyeler, et al, 1999) for development of the RF default value in DandD code Versions

1.0 and 2.1. The study also evaluated published RF data applicable to the building occupancy

scenario in consideration of the representativeness of such data to decommissioning sites

conditions particularly regarding the driving forces, ventilation, and surface activity adhesion

conditions. More importantly, staff analyzed and evaluated measurements of surface activity

and airborne activity concentration for facilities undergoing decommissioning. 

Using published literature data and extensive field measurements at two decommissioning

facilities, the staff used statistical analysis to evaluate time variation of airborne concentration,

conducted tests of independence of data from different locations, assessed partitioning of data,

and evaluated tolerance limits. As a result of the staff’s re-valuation of the RF data, an improved

basis to estimate indoor RF has been established. Finally, the staff conducted statistical

analysis of RF mean values for five sites (e.g., five data points) deemed applicable to the

building occupancy scenario as well as to decommissioning site conditions. The staff believes

that the available data and information on these sites are not perfect, but they provide the best

insight available at the present time to estimate the probability density function (PDF) for the RF. 

Overall, the authors of this report believe these data provide an overestimate of the distribution of

RF likely to exist at decommissioned facilities. We deemed it appropriate to base the PDF for

RF on the 5 data points representing the site means, adjusted for worker occupancy, because:

(1) workers may move around a facility and be exposed to a variety of air concentrations; and (2)

the regulation is written to protect the average member of the critical group. We fitted the five

site data to a normal and a lognormal distribution. Since there were only five data points, we felt

that it was appropriate to use the “maximum likelihood” approach (Benjamin and Cornell, 1970)

to estimate the distribution rather than a statistical 

(i.e., “unbiased”) approach. The difference between the two approaches is that the estimated

standard deviation in the maximum likelihood approach is smaller by the ratio (N&1)/N. This

smaller standard deviation will lead to a slightly smaller value for the 90th percentile of the

distribution, which is used as the suggested regulatory criterion for RF. The parameters of the

normal and lognormal distributions for the maximum likelihood fits are given below:
x

Parameters for Normal and Lognormal “Maximum Likelihood” Models of RF Data

Statistical Model Sample Mean Sample Standard

Deviation 90th Percentile RF

Normal Fit to 5 site

mean RF’s

4.74 x 10-7 m-1 3.11 x 10-7 m-1 8.7 x 10-7 m-1

Lognormal Fit to 5

site mean RF’s

log10 = -6.433 log10 = 0.3247 9.6 x 10-7 m-1

Although both the normal and lognormal distributions are reasonable fits to the data, the normal

distribution has the disadvantage of allowing negative values of RF, which is not physically

possible. In addition, the lognormal fit is more conservative choice at the 90th percentile RF. 

This study resulted in a recommendation of using an RF value of 10-6 m-1 for screening dose

analysis as an alternate to the current default value 1.42 x 10-5 m-1 used in the NRC’s DandD

code Version 2.1. This recommendation was based on rounding the nominal 90th percentile of

the PDF RF value (e.g., 9.6 x 10-7 m-1) using a lognormal fit. 

 

FOREWORD

This report is a product of the staff’s continuing efforts to establish more realistic and

representative default values for use in screening performance assessment or dose analysis
xi

approaches. The current study was specifically conducted to re-evaluate the default screening

value of the resuspension factor (RF) parameter used in decommissioning screening analysis. 

The RF is a highly sensitive physical parameter that impacts the calculated inhalation dose and

subsequently the derived dose limit used for demonstration of compliance with NRC’s license

termination rule for decommissioning (10CFR20, Subpart E). The RF parameter is difficult to

determine in a realistic and reliable fashion because it requires extensive and costly

measurements over a long time period. Therefore, the staff attempted to critically evaluate

published RF data, deemed applicable to the building occupancy scenario, and use more recent

empirical field data collected over 1-3 years at two facilities owned by Westinghouse Electric

Company and BWX Technologies, Inc. Based on the staff’s current analysis and evaluation, the

RF default screening value for the building occupancy scenario may be reduced by an order of

magnitude. 

This draft NUREG report is not a substitute for NRC regulations and compliance with it is not

required. The approaches and/or methods presented in this NUREG are provided for

information only. The report is intended to solicit comments and feedback on staff analysis and

approaches, and to explore availability of more recent field or experimental indoor RF data that

may be used to optimize the current default RF value. Publication of this report does not

necessarily constitute NRC approval or agreement with the information contained herein. Use of

product or trade names is for identification purpose only and does not constitute endorsement by

the NRC. 

Sandra L. Wastler, Acting Chief

Environmental and Performance Assessment

 Branch

Division of Waste Management

Office of Nuclear Material Safety and Safeguards 

 
xii

ACKNOWLEDGMENTS

The authors wish to express their thanks to several people who helped in the development of

this report. Joseph Nardi of Westinghouse Electric Company and David Spangler of BWX

Technologies, Inc., provided significant field monitoring data on resuspension factor, in response

to discussions held at the U.S. Nuclear Regulatory Commission’s public workshops during 1999

-2000. Lee Abramson, Office of Nuclear Regulatory Research, NRC, provided invaluable help in

the statistical interpretation of the sparse data on resuspension. Duane Schmidt, Office of

Nuclear Material Safety and Safeguards, NRC, and James Weldy, Center for Nuclear Waste

Regulatory Analyses, conducted reviews and provided valuable comments that helped improve

early draft of this report. 
1

1 1.0 INTRODUCTION

2 The U.S. Nuclear Regulatory Commission’s (NRC’s) “Final Rule on Radiological Criteria for

3 License Termination” (NRC, 1997) requires that, in order to terminate a license, the dose to the

4 average member of the critical group from residual radioactivity distinguishable from background

5 must be no greater than 0.25 mSv per year (25 mrem/yr). In addition, this rule requires that the

6 residual radioactivity has been reduced to levels that are as low as is reasonably achievable

7 (ALARA).

8 For residual radioactivity on building surfaces, the concentration that would result in a dose of

9 0.25 mSv per year (25 mrem/yr) to the average member of the critical group may be calculated

10 using the screening building occupancy scenario described in NUREG/CR-5512, Volume 1

11 (Kennedy and Strenge, 1992, Section 3.2). The building occupancy scenario for screening

12 assumes that light industrial activities will take place in the decommissioned building (NRC,

13 1998 and NRC, 2001). The building occupancy scenario assumes three pathways by which a

14 future occupant of the building can be exposed to radiation. These pathways include: direct

15 external radiation; inhalation of residual radioactivity resuspended from surfaces, because of

16 activities of occupants; and ingestion of the residual radioactivity wiped off the surfaces and

17 subsequently ingested by occupants. The NRC is currently using the computer code DandD,

18 version 2.1, to perform screening analyses (NRC, 2001).

19 In evaluating the generic screening values, using DandD for the building occupancy scenario, it

20 was apparent that the values for alpha-emitters were very low, in many cases below detection

21 levels. Consistent with Commission direction for NRC staff to evaluate excessive conservatism

22 in the DandD code, we evaluated the causes for these very low values and whether there was

23 excessive conservatism. Based on our evaluation, we determined that the indoor resuspension

24 factor (RF) was one aspect of the methodology where excessive conservatism may have

25 contributed to the very low screening values.

26 For many nuclides, in particular the important alpha-emitters such as uranium and thorium, the

27 inhalation pathway is typically the predominant exposure pathway. The RF is the most sensitive

28 parameter affecting the inhalation dose. In the inhalation pathway model incorporated into the

29 DandD, the RF is the only factor treated as a random variable during selection of the default

30 parameter values. 

31 In Section 2, this report discusses how the RF is used in the inhalation dose calculation and the

32 factors affecting the RF. Section 3 discusses how the default values were selected for

33 NUREG/CR-5512 and the DandD code. Section 4 provides a summary and evaluation of

34 studies of the RF. Section 5 discusses the development of an alternate RF for

35 decommissioning cases. Section 6 presents conclusions and recommendations of this report

36 regarding selection of a screening value for RF.
2

Dinh ' DCFinh × B × t × RF × Csurf (1)

1 2.0 INHALATION DOSE CALCULATIONS AND FACTORS AFFECTING THE INDOOR

2 RF 

3 2.1 The NUREG/CR-5512 and the DandD Inhalation Dose Model

4

5 The DandD computer code uses the same equation as presented in NUREG/CR-5512, 

6 Volume 1 (Kennedy and Strenge, 1992, Volume 1) to calculate the inhalation dose for the

7 building occupancy scenario. That is, the dose from inhalation can be calculated by:

Dinh 8 is the committed effective dose equivalent rate from inhalation, mSv/y (mrem/yr), 

DCFinh 9 is the dose conversion factor for the radionuclide inhaled, mSv/Bq (mrem/pCi), 

B is the breathing rate, m3/hr (ft3 10 /hr),

11 t is the annual occupancy time, hr/yr, 

RF is the indoor RF relating airborne concentration to surface concentration, m-1 (ft-1 12 ), and 

Csurf is the surface concentration, becquerel per meter square, Bq/m2 (pCi/m2 13 )

14 The DCF is a fixed value from Federal Guidance Report No. 11 (U.S. Environmental Protection

15 Agency, 1988). The breathing rate and annual occupancy time are metabolic and behavioral

16 parameters that are fixed based on assumptions made in developing the critical group and

17 default scenario. The surface concentration is a measured site specific parameter. The RF

18 value is a variable dependent on several factors. The RF is considered to be a random variable

19 whose distribution represents the range of conditions (both physical conditions of the

20 contamination and the behavior conditions leading to resuspension) that might be found at sites

21 that have undergone decontamination. Unlike other dose models in DandD, the indoor

22 inhalation-dose model for building occupancy scenario generally allows only one random

23 variable, RF, that affects dose.

24 2.2 Factors Affecting the RF

25 The RF is the ratio of the airborne concentration of contamination to the surface concentration of

26 contamination. The RF is affected by a number of physical factors that include: type of

27 disturbance, intensity of disturbance, time since deposition, nature of the surface, particle size

28 distribution, climatic conditions, type of deposition, chemical properties of the contaminant,

29 surface chemistry, and building geometry and physical characteristics. A general discussion of

30 these factors is provided in NUREG/CR-5512, Volume 3 (Beyeler, et al., 1999).

31 In the simplest terms, the RF is determined considering the nature of contamination on the

32 surface (e.g., how tightly bound to the surface it is), and balancing the driving forces that cause

33 the material on the surface to become airborne, and the mechanisms that remove the material

34 from the air. Particle-size effects also play an important role in the airborne concentration of

35 contaminates, and thus the RF. In assessing these factors, one must consider the

36 circumstances under which the RF will apply (i.e., activities, physical conditions, and structures

37 associated with the building occupancy scenario). Clearly, the concept of RF applies to

38 particulate solids and does not apply to gases. 
3

1 2.2.1 Driving Forces

2 The primary driving force that will resuspend particles in the building-occupancy scenario can be

3 expected to be mechanical forces associated with rubbing and abrasion of surfaces. These

4 forces are typically caused by the activities or movements of the occupants like walking and

5 moving carts (Corn and Stein, 1967; Morton, 1999). In buildings, air currents caused by normal

6 room ventilation or by vibrations are not expected to be a major cause of resuspension of

7 particles (Walker et al., 1967; Hinds, 1982). Moreover, RFs determined from mechanical

8 disturbance can be one order of magnitude higher than RFs determined with air currents only

9 (Beyeler et al., 1999). Higher RFs were measured when driving forces were increased and

10 when the surface contamination was loose or easily removable. Several studies of RF,

11 including Fish, et al. (1967), observed a power-law relationship between air velocity and RF. 

12 Fish, et al. (1967) also reported a difference in the RF of greater than an order of magnitude due

13 to the type of driving forces. Jones and Pond (1967) also reported variations in the RF from

14 different walking speeds. Therefore, it is important to assess the types and intensity of the

15 applied driving forces to evaluate the corresponding RF measurements, to determine if they are

16 reasonably representative of the building-occupancy scenario.

17 For the building-occupancy scenario, driving forces (worker activities/movements) should

18 simulate normal workplace activities that would occur over an entire average working year. This

19 can best be accomplished if measurements are made while normal activities are being

20 conducted or if actual worker activities/movements are observed and reproduced faithfully. The

21 RF measurements of activities done for only brief periods should not be assumed to be

22 representative of RF measurements made over long periods of time.

23 2.2.2 Removal Mechanisms

24 In assessing studies that are representative of the building occupancy scenario, consideration

25 must be given to room ventilation. Although ventilation does not cause significant resuspension,

26 it will cause removal of already suspended particles by two mechanisms. The first removal

27 mechanism is by outflow of air from the room. The second removal mechanism is turbulent

28 inertial impaction caused by the change in direction of air streams as the air goes around the

29 obstacles in the room or in the ventilation system. These removal mechanisms are important

30 because they will reduce the airborne concentration and thus the RF. 

31 For the building occupancy scenario, it can be assumed that the ventilation for a light industrial

32 facility would meet national codes and standards (e.g., ASHRAE, 1989) as well as State and

33 local requirements. Thus, to be representative of the building-occupancy scenario,

34 measurements should be conducted with ventilation similar to those found at light industrial-use

35 facilities. Measurements taken with no room ventilation will likely overestimate the RF because

36 the primary mechanisms for removal of airborne particulates were not present. Similarly,

37 measurements taken with excessive room ventilation are likely to underestimate the RF.

38 2.2.3 Characteristics of the Surface Activity

39 The characteristics of how the surface activity is bound to the surface will have a major effect on

40 the RF. For particles to become resuspended, the bond between the particles and the surface
1ALARA requirements are further discussed in DG-4006 and in Section 7 of the Standard 

 Review Plan.

4

1 (e.g., floor) must be broken by the driving forces (i.e., mechanical or air forces). Particles that

2 are tightly bound to the surface are not easily resuspended whereas particles that are loosely

3 bound, like freshly deposited material, will be more easily resuspended.

4 The adhesion of particles has been studied extensively, and although it is a very complex

5 process, the general principles are well understood. Hinds (1982) related the main surface

6 adhesion forces to either van der Waals force, electrostatic force, and/or surface tension forces

7 of adsorbed liquid films. These forces are affected by the material type, shape, and size of the

8 particles. In addition, the material roughness, the relative humidity, temperature, duration of

9 contact, and initial contact velocity are important factors affecting surface adhesion. The most

10 important adhesion forces are the London-van der Waals forces, the long range attractive forces

11 that exist between molecules. In general, adhesive forces are inversely proportional to the

diameter of particles “d” while removal forces are proportional to d3 12 for vibration and centrifugal

force or to d2 13 for air currents. This suggests that as the size of particles decreases, it becomes

14 increasingly difficult to remove them from the surfaces. For example, the adhesive forces on

15 particles of less than 10 μm are much greater than other forces that such particle experience. 

16 All small particles generally adhere to and are bound to the surface, and no particles are really

17 “loose.” Therefore, particles are removed from surfaces almost entirely by applying a

18 mechanical force to the particle sufficient to break the adhesive bond. Particles that are loosely

19 bound to the surface will be easily removed and resuspended. Particles that are tightly bound

20 require greater mechanical force to break the bonds and become resuspended. If the bond is

21 not broken, then the particle will not become resuspended. Therefore, the nature of the

22 contamination on the surface will have a important effect on the RF. For the same amount of

23 total surface activity, surfaces with a large portion of loosely bound particles would be expected

24 to have a larger RF, and surfaces where almost all the particles are tightly bound would be

25 expected to have a smaller RF. The amount of loosely bound particles could change as the

26 surface degrades over time with application of mechanical forces.

27 NUREG/CR-5512, Volume 3 (Beyeler, 1999) reported that “several studies model variations of

28 resuspension factor with time, including Kathren (1968), Langham (1969), NRC (1975), IAEA

29 (1982, 1986), Garland (1982), and Nair, et al., (1977)”. All of these models produced decrease in

30 RF with time, reflecting the experimentally observed decrease in contaminant air concentration

31 with time over contaminated areas. This trend also explained that contaminants become more

32 fixed with time and the contaminated source on surfaces becomes more depleted with time.

33 Consideration of the representativeness of the surface activity is important in selecting

34 measurements that are applicable to decommissioned facilities. We consider that good

35 housekeeping practices will be used in normal decommissioning as a minimum to meet the

ALARA requirements1 36 in 10 CFR 20.1402. It is assumed that surfaces will be cleaned or

37 washed during decommissioning. This will remove most of the loosely bound and some of the

38 more tightly bound particles. Following the above discussion, surfaces that have been cleaned

39 would be expected to have a smaller RF than surfaces that have not been cleaned, given the

40 same levels of surface contamination. 

41 2.2.4 Particle Size Effects
5

1 Particles are often classified by their activity mean aerodynamic diameter. This value provides

2 information about the particles aerodynamic behavior and how the particles will deposit in the

3 respiratory system. The particle diameter is typically expressed as the mean diameter. It is

4 common practice to consider respirable particles (i.e., particles able to reach the pulmonary

5 region of the lung) as having a mean diameter of 10 μm or less. It is therefore most important to

6 evaluate the activity of particles that are respirable. Larger particles typically do not reach the

7 pulmonary region of the lung and may be exhaled without contributing to inhalation dose, 

8 ingested, or otherwise absorbed, leading to doses other than to the lung (Cember, 1996).

9 Fish, et al., (1967) reports a strong correlation of RF with particle diameter. As discussed in 

10 NUREG/CR-5512, Volume 3, resuspension is greatest for smaller diameter particles. The RF

11 decreases with particle diameters in the range of 1 to 5 μm. As discussed above, this also

12 corresponds to the particle- diameter range that provides the most significant dose. In addition,

13 the distribution of particle sizes may change over time as mechanical forces are applied.

14 Although larger-diameter particles may be resuspended, gravitational settling removes them

15 from the air more rapidly than smaller particles. Nevertheless, larger particles can be important

16 because they can be measured as “removable” by a wipe test, leading to the conclusion that a

17 higher fraction of resuspendable particles may be present than can actually contribute to dose. 

18 In the context of this report, which is the estimation of RF’s representative of decommissioned

19 buildings, significant removable activity as larger particles may cause the RF to be under20 estimated. Since RF is a ratio, the numerator is set equal to the measured air concentration,

21 whereas the denominator is set equal to the measured surface activity.

22 Information about the mean airborne particle size is usually not provided in studies presenting

23 resuspension data. However where information is provided on particle-size distributions 

24 (e.g., on the air samplers or surface samplers), it is important to weigh the effect on the

25 estimated RF. 

26 2.3 Using the Wipe Tests to Assess Removable Fraction

27 Particles on surfaces are sometimes described as being of two types: (1) “fixed,” “bound” or

28 “non-removable” particles; and (2) “loose,” “unbound,” or “removable” particles. The “smear” or

29 “wipe” measurement is often taken to be a measurement of the particles that are “loose.” In

30 reality, this distinction is not exact, but it can be useful with proper understanding of the

31 underlying process.

32 The wipe test provides information about the fraction of the particles that projects high enough

33 above the surface to be subjected to the mechanical forces of the wipe. Basically almost all

34 particles physically touched by the surface of the wipe will have their bonds broken because the

35 force used for the rubbing will be far greater than the particle bond strength. A wipe will break

36 the bonds of many of the particles that are on the microscopic peaks on the surface profile, but

37 will affect few particles in the valleys and depressions in the surface. After the bonds are

38 broken, the particles can then either re-attach themselves to the surface at another location, re39 attach to the wipe material, or become airborne. This latter event requires that the particles have

40 sufficient kinetic energy to overcome the van der Waals and electrostatic forces and that they

41 have a free pathway for escape. Hence, a wipe measurement usually includes more than

42 “loose” activity. Considering this analogy, a wipe test may not adequately represent the fraction

43 of particles that would be resuspended by walking.
6

1 3.0 PREVIOUS DETERMINATIONS OF THE RF

2

3 3.1 Basis for Deriving the Indoor RF in NUREG/CR-5512, Volume 1

4 NUREG/CR-5512 Volume 1 (Kennedy and Strenge, 1992), recommended a specific value for

each of the parameters in equation 1. The recommended value for the indoor RF was 10-6 m-1 5 . 

6 However, there was no detailed explanation of how the value was determined. William Kennedy,

7 the principal author of Volume 1, revealed (Kennedy, 1999) indicated that the authors relied, in

8 part, on Brodsky (Brodsky, 1980), who concluded that, although vigorous disturbances could

produce RFs higher than 10-6 m-1 9 , normal activities averaged over long periods of time would

have RFS of less than 10-6 m-1 10 . The Volume 1 authors also relied on their own experience and

background knowledge in leading them to conclude that 10-6 m-1 11 is an upper bounding limit under

12 ordinary conditions that would be expected at a decommissioned facility.

13 3.2 Development of the RF in DandD Code Version 1.0

14 Unlike the deterministic value used in NUREG/CR-5512, Volume 1, the RF was treated

15 probabilistically in establishing the default parameters for the DandD code, version 1.0. The

16 approach used to develop the default RF parameter in DandD code is documented in Volume 3

17 (Beyeler, et al., 1999). A distribution describing the variability of the RF (i.e., a probability density

18 function (PDF)) was established. 

19 As described in NUREG/CR-5512, Volume 3, Sandia National Laboratories (SNL) reviewed a

20 number of studies published between 1964 and 1997, and determined that only a small number

21 of studies provided numerical results pertinent to indoor resuspension for the buildingoccupancy scenario. Reported RF values from all these studies ranged from 2 × 10−8 22 to

4 × 10−2 m−1 23 . Some of these studies were deemed inapplicable, for the following reasons: 

24 (1) the study did not provide results that could be converted to an RF; (2) the study conditions

25 included sources of airborne contamination other than resuspension; (3) the contaminated

26 surface in the study (e.g., clothing) was not representative of building surfaces; or (4) the

27 mechanical stresses on the contaminated surfaces were not representative of the conditions in

28 the building occupancy scenario. 

29 NUREG/CR-5512, Volume 3, concluded that two RF studies (Jones and Pond, 1967; Fish, 

30 et al., 1967) were applicable. For both of these studies, the surface contamination was freshly

31 deposited (by the researchers). Based on the assumption that, in these studies, essentially all

32 the contamination was removable, SNL expressed the RF for a decommissioned facility as the

33 product of the RF for loose, or removable, contamination and the fraction of the total

34 contamination that was removable. 

35 The data for RF were categorized by similarity of the nature (air flow and mechanical

36 disturbance) and intensity (low or high air flow, absence or presence of mechanical disturbance)

37 of the surface disturbance. Three categories were used: (A) low air flow and no mechanical

38 disturbance; (B) low air flow with mechanical disturbance; and (C) high air flow with mechanical

39 disturbance. Data from the two studies were grouped into these categories, and ranges

40 (minimum and maximum) of the RF were described for each category. Values from Category

41 “C” were adjusted to an effective value to account for the source depletion that would occur at a

42 high RF and high ventilation rate (high air flow). 
7

1 SNL acknowledged that the RF values from these studies represented pessimistic estimates,

2 and the spread of data would likely overestimate the uncertainty in an annual average RF. 

3 However, SNL pointed out that with such a limited number of studies, the existing data were not

4 likely to describe the full range of potential RF values. SNL concluded that these two effects

5 tend to counteract each other, and that correction for the effects was not reasonable with a

6 limited pool of data. SNL adopted the pessimistic values as estimates of the annual average RF

7 values.

8 To combine results from the categories to form a PDF, NUREG/CR-5512,Volume 3, estimated

9 the fraction of light industrial structures that would fit the conditions for the categories. This

10 weighting was determined to be 0 percent for Category A (because the lack of mechanical

11 disturbance was seen as inconsistent with light industrial use); 90.2 percent for Category B, and

12 9.8 percent for Category C. Loguniform distributions were assumed for the RF for categories B

(with minimum 9.1 × 10−6 m−1 and maximum 1.9 × 10−4 m−1) and C (with minimum 7.1 × 10−6 13

m−1 and maximum 1.4 × 10−4 m−1 14 ). Based on these distributions, and the category weighting,

15 the resultant PDF for the RF for removable contamination was developed as shown in Figure 1. 

This resultant PDF ranges from 9.1 × 10−6 m−1 to 1.9 × 10−4 m−1, with median value 5.0 × 10−4 16

m−1 and default value for the DandD code (90th percentile) of 1.42 × 10−4 m−1 17 .

18 Finally, to calculate the RF for decommissioned sites, the fraction of total contamination that is

19 loose (removable) must be addressed. In this respect, NRC staff has assumed that a

20 reasonable value for screening purposes is 0.1. This removable fraction value has been used to

develop a DandD default parameter value of 1.42 × 10−5 m−1 21 applicable for all surface

22 contamination types (e.g., removable and non-removable) of decommissioned sites. 

23 4.0 REVIEW AND EVALUATION OF MEASURED DATA FOR THE INDOOR RF

24 This section reviews measurement studies of the indoor RF. If one considers all the

25 possibilities, the RF will have a value ranging from zero (when there is no driving force to disturb

26 the surface) to very large values (if there is a vigorous mechanical force such as scraping or

27 grinding applied on the surface). However, if we consider only those measurements

28 representative of long-term activities that represent the building-occupancy scenario, then the

29 range of the indoor RF distribution may be greatly narrowed. Furthermore, although some

30 vigorous activities may result in peaks of air concentration, what is of interest is the annual dose

31 which is related to the average conditions for a year. In selecting experiments to determine the

32 RF for the building- occupancy scenario, it is necessary to use measurements that are

33 representative of the building- occupancy scenario. This means that the driving force, the

34 ventilation (removal mechanism), particle size, and the degree to which the material is bound to

35 the surface should all be appropriate and compatible with the scenario. 
8

Figure 1. Cumulative Probability Function for RF Developed for DandD

Code by SNL (Beyeler, et al. (1999)) 

1 We present below a brief description and our conclusions regarding applicability and compatibility

2 of each study to decommissioned facilities. We also address factors that might tend to

3 overestimate or underestimate the RF value applicable to a building-occupancy scenario. In this

4 regard, there are three major criteria that need to be considered when assessing

5 representativeness of the RF data for decommissioned sites:

6

7 a) The RF data should have been derived using a driving force representative, to the extent

8 practicable, of the decommissioning facilities (e.g., similar to activities of the light-industry

9 scenario which is the critical group for the building-occupancy scenario); 
9

1 b) The RF data should have been generated for facilities with ventilation conditions as similar

2 as practicable to the light industry scenario described above. Thus, data generated under

3 forced or abnormal ventilation conditions (e.g., directing fans or hair dryers towards loose

4 contamination on the floor) or under no ventilation or air flow were rejected; and

5 c) The surface activity should be assumed to adhere to the surface to some extent or

6 assumed to occur on surfaces that went through cleaning or washing processes. These

7 assumptions are used because ALARA requires cleaning or washing of contaminated

8 surfaces for facilities undergoing decommissioning. 

9 Table 1 summarizes the representativeness for different studies of the driving forces, the room

10 ventilation conditions, and surface activity adhesion as applicable to the building-occupancy

11 scenario. The representativeness of the surface activity to decommissioned sites (i.e., cleaned

12 with a small percentage of loosely bound contamination) is presented. In Table 1, a “+” is used to

13 indicate conditions that are representative of decommissioned facilities, and a “-“ is used to

14 indicate conditions that are not representative. An “0" is used to indicate that either the conditions

15 are mixed or not sufficiently documented to assess. 

16 Table 1: Summary of Representativeness of RF Data

17 Study

Representativeness of:

Driving

Forces

Room

Ventilation

Surface

Activity

Adhesion

18 Breslin, 1966 + + 0

19 Eisenbud, 1954 + + 0

20 Fish, 1967 0 - -

21 Jones, 1967 0 + -

22 Ikezawa, 1980 + + -

23 Nardi, 1999 + + +

24 Ruhter, 1988 + 0 +

25 Spangler, 1998 + + +

26 + conditions representative of decommissioned facility.

27 - conditions not representative of decommissioned facility.

28 0 conditions are mixed or not sufficiently documented to assess.

29 Another factor that could be considered in evaluating the studies is the improvements in

30 measurement instruments and calibration techniques over time. Calibrations of alpha activity

31 measurements of surface activity, conducted during the early studies (e.g., 1954 - 1967), under32 estimate the total surface activity by about a factor of two (Abelquist, et al., 1998). Thus, it is likely
10

1 that the RF value is significantly over-estimated for the early studies. In addition, modern survey

2 instruments are more sensitive and will more accurately measure activity. However, we will not

3 use this factor of two to adjust downward any of the RF estimates from the early studies.

4 4.1 Breslin, 1966, Data

5

6 4.1.1 Description

7 RF data were collected at an operating uranium processing plant over a weekend while

8 operations were not being conducted. However, the surrogate workers attempted to duplicate

9 normal working activities and movements that they had observed during operation. These data

10 represent three different operational areas designated as: the “Assistant Press Operator” area,

11 the “Rod Puller” work area, and the “Uranium Extrusion” area. Operational activities at the

12 uranium processing plant introduced a significant amount of airborne activity. For each area,

13 there were four measurements taken relative to operations: (a) no operational impacts 

14 (i.e., airborne contamination introduced by operations had settled out of the air); (b) post15 operation transient conditions (i.e., airborne contamination introduced by operations had not

16 completely settled out of the air); (c) initial operating transient conditions (i.e., operations had

17 begun to introduce airborne contamination but had not yet reached equilibrium); and 

18 (d) operational conditions (i.e., equilibrium of airborne contamination introduced from operations

19 had been reached). Two data points, representing moving and work practices of two different

20 workers, were reported under each of these conditions, for each of the three facilities for a total of

21 24 data points. In addition, the study reported one data point at each of the four conditions for

22 each work area for a total of 12 data points. The averages of surface activities for the three

facilities were measured at 3.0 x 104 Bq/m2 (1.8 x 106 dpm/m2 23 )for the Assistant Press Operator

facility and 8.3 x 104 Bq/m2 (5 x 106 dpm/m2 24 ) for each of the other two areas. A summary of the

25 data is provided in Appendix A.

26 4.1.2 Evaluation

27 In assessing the RF data relative to decommissioning sites, we considered that data under

28 Condition (a) were representative of decommissioned sites. Some of the data listed under

29 Condition (b) may correspond to decommissioned conditions. The remaining data show

30 significant interferences arising from airborne contamination introduced by operations and were

31 not considered to be representative of decommissioned facilities. The average RF values

32 corresponding to Condition (a), for each of the three areas and for each of the three air samplers

33 for a total of nine values, were used in the evaluation of RF. 

34 We note that some of the data were collected by lapel (Breathing Zone) samplers worn by two

35 different workers, and some of the data were collected using a two-stage sampling instruments

36 at a fixed location within the facility. There was clearly a difference between the lapel samplers

37 and the fixed samplers, with the former being significantly higher ( an average of approximately

38 28 percent for the data used).

39 Several factors will cause the data from this study to potentially overestimate the RF at

40 decommissioning sites. First, workers’ activities and movements during the experiment were

41 conducted in an exaggerated active manner to maximize resuspension to determine an upper

42 bound on resuspension. Second, more loose residual radioactivity was present than would be

43 anticipated at a decommissioned facility, making the observed resuspension larger than the
11

1 resuspension at a decommissioned facility, as demonstrated by the observation of the fall-off of

2 airborne concentrations with time (this is discussed further in Section 5.1.1). Therefore, the data

3 should be used with the understanding that the RFS are overestimated by some factor that

4 cannot be precisely quantified.

5 4.2 Eisenbud, 1954, Data

6 4.2.1 Description

7 Airborne radioactivity concentrations during plant operations were compared with different 

8 surface radioactivity concentrations at several operating uranium and radium processing

9 facilities. The purpose of the study was to estimate the importance of surface activity for causing

10 airborne activity. The Eisenbud, et al., (1954) study concluded that airborne concentration is

11 attributable mainly to operational activities rather than resuspension from surface activity.

12 Several areas within the uranium and radium processing facilities were studied. As with the

13 Breslin (1966) study, operations at these facilities introduced a significant amount of airborne

14 contamination. In addition, most of the areas had very low surface activity. Therefore, the

15 airborne contamination is attributed to operational effects. However, one area (Plant J) did have a

16 high surface activity and low operational airborne contamination. 

17 4.2.2 Evaluation

18 We consider that data from Plant J are marginally representative of decommissioned facilities. 

19 The remaining data show significant interferences arising from airborne contamination caused by

20 operations and were not considered to be representative of decommissioned facilities. For plant

J, three RF values were reported: 0.1 x; 0.32 x; and 0.50 x 10-6 m-1 21 . 

22 The assumption that all airborne activity at this site is derived from resuspension will tend to

23 overestimate the RF because particulate activity is largely influenced by ongoing operations. 

24 Also, there had not been much cleaning of surfaces so that there is likely to be more

25 resuspension than would occur from a cleaned surface. However, this study suggests that the

average value of 0.3 x 10-6 m-1 26 could perhaps be near the high end of the RF distribution for the

27 building- occupancy scenario. 

28 4.3 Fish, 1967, Data

29 4.3.1 Description

RF values were developed from experimental conditions. Zinc sulfide (ZnS2 30 ) and cupric oxide

31 (CuO) particles were freshly dispersed in a test room with painted drywall walls and asphalt tile

32 floors. There were four sets of measurements:

33 1. Ten minutes of vigorous activity, including sweeping with no exhaust or fans. The

estimated RF for was 190 x 10-6 m-1 34 .

2. Twenty minutes of vigorous walking. The estimated RF was 39 x 10-6 m-1 35 .

3. Forty minutes of light work activity. The estimated RF was 9.4 x 10-6 m-1 36 .
12

1 4. Ninety minutes of some light sweeping and some other light activity with no

2 exhaust ventilation, but with fans for circulation. The estimated RF was 

710 x 10-6 m-1 3 .

4

5 We consider that the driving forces for measurements 1 and 4 are not representative of a light

6 industrial facility. In addition, the fourth measurement appears to be an outlier with respect to the

7 other measurements reported in the study and with respect to the other studies described in this

8 report. 

9 

10 4.3.2 Evaluation

11 We do not consider this study to be representative of decommissioned sites for the following

12 reasons: 1) There was no ventilation to reduce the airborne concentrations; 2) The surfaces had

13 not been washed or otherwise treated to remove the easily removable particles; 3) The densities

of ZnS2 14 and CuO are lower than most radionuclides of interest, particularly uranium and

15 transuranics; and 4) Driving forces and measurement techniques were not always representative

16 (for example, certain data were obtained with air samplers located near the floor and extreme air

17 circulation was produced by fans aimed at the floor). These factors will cause the measured RF

18 to be overestimated, for the purposes of decommissioned facilities. However, the magnitude of

19 the difference cannot be determined. 

20 4.4 Ikezawa, 1980, Data

21 4.4.1 Description

22 The Ikezawa data were generated to assess the procedure of decontamination and cleanup

23 levels immediately after an accidental break of negative pressure in a plutonium (Pu) hot-cell

24 glove box. Airborne concentrations were measured by personal air samplers on two workers

25 who engaged in cleanup work. The measurements were conducted before any cleanup or

26 remedial actions. The released aerosol particulates were easily suspended due to this

27 instantaneous and fresh release of contaminants.

This study reported a mean RF of 180 x 10-6 m-1 28 for decontamination activities of floors and walls. 

A mean RF value of 2.3 x 10-6 m-1 29 was reported when no work was being performed. A range of

RF values (4 to 20 x 10-6 m-1 30 ) was also reported for decontamination activities of a hot cell. 

31 4.4.2 Evaluation 

32 This study is not considered to be representative of decommissioned facilities. The surface

33 activity was freshly deposited powder, which is not representative of cleaned decommissioned

34 facilities. As discussed in Section 2.2.4, the large amount of readily removable activity will likely

35 cause the RF to be greatly overestimated. 

36 4.5 Jones, 1967, Data 

37 4.5.1 Description 

38 Jones studied the resuspension of plutonium oxide and plutonium nitrate from floors. These

39 materials were deposited on the floors as a water suspension that was subsequently left to dry. 

40 The floor materials used in the experiment included: wax paper, PVC sheet, waxed linoleum, and

41 unwaxed linoleum. The investigators made no attempt to wash loose activity from the floors. Air

42 samples were taken with lapel samplers and a series of fixed samplers, located either near the

43 floor (at 15 cm above the floor surface) or far above the floor at heights reaching 175 cm above

44 the floor surface. Walking on the surface was done at 14 steps/minute, 36 steps/minute, and 100
13

1 steps/minute while blowing air with a hair dryer directed at the floor. Jones, 1967, results are

2 summarized in Table 2 below.

3 Table 2 - Results of Jones, 1967, Study

4 Condition Min RF, 

10-6 m-1

Max RF, 

10-6 m-1

Median RF

10-6 m-1

5 Pu Oxide, 14 steps per minute 0.6 20 1.27

6 Pu Oxide, 36 steps per minute 1 177 16.2 

7 Pu Nitrate, 14 steps per minute 0.3 1.33 0.64

8 Pu Nitrate, 36 steps per minute 1 16.2 3.02

9 4.5.2 Evaluation

10 The fixed air sampler results were reported as the average for 15 individual samples taken at

11 heights from 15 to 175 cm above the floor. Using values that were determined near the floor

12 where airborne concentration is higher than the breathing zone will tend to overestimate the RF

13 for decommissioned sites. Personal air sampler results, where available, averaged 36 percent of

14 the room air samples. The results of this experiment are not sufficiently representative of the

15 building occupancy scenario for a decommissioned facility because they were done with freshly

16 deposited solution and loose particles on smooth surfaces. This will cause the measured RF to

17 be overestimated for the building occupancy scenario, which assume cleaned surfaces. 

18 4.6 Nardi, 1999, Data

19 4.6.1 Description

20 Since the issue of dose estimates for the contamination in a building-occupancy scenario and the

21 related issue of data for resuspension factor estimates had been raised at a series of public

22 workshops, the NRC staff requested contributions of additional data on RF. In response, 

23 A. Joseph Nardi, a supervisory engineer with Westinghouse Electric Company, presented

24 significant resuspension data at the NRC’s public Workshop on Decommissioning, held on

25 March 18-19, 1999. Mr. Nardi also provided the NRC on October 28, 1999, (Letter from A.J.

26 Nardi, Westinghouse Electric Company, to N. Eisenberg, then NRC staff, now retired) with

27 supplemental information on the data presented at NRC’s workshop.

28 In Nardi’s study, measurements of total surface activity were compared with airborne activity at a

29 “Pump Repair” facility undergoing decommissioning. The facility consists of the main building,

30 which is an open high-bay area 49. 6 m long x 12.2 m wide x 9.1 m high (142.5 ft. long x 40.0 ft.

31 wide x 30 ft. high) and a tank room 14.6 m long x 3.7 m wide x 5.5 m high (48 ft. long x 12 ft. wide

32 x 18 ft. high).

33 There was no forced air circulation within the building, and the only ventilation came through open

34 doors and convection from space heaters. HEPA filters were used locally on the equipment

35 during the shot-blasting operation of the floors when dust levels from rigorous cleaning activities

36 were locally high. The filters were placed locally on the equipment by the manufacturers 

37 because of OSHA requirements for the protection of personnel. They were never used as part of

38 the facility ventilation system and no local HEPA filters were used during other decommissioning

39 operations (e.g., other than shot-blasting). Furthermore, the filters placed on the shot-blasting
14

1 equipment were characterized by very low air-flow rate and intended to reduce scattering of

2 particles from the floor caused by the shot-blasting process as required by OSHA. The impact of

3 the filters on the overall RF within the facility is minimal because it is localized and the air-flow

4 through the filter is rather small compared with the air-flow of the facility. 

5 The radionuclides of primary interest for this facility included Co-60 and Cs-137. Air sampling

6 was conducted using 13 fixed-head air sample stations. The air sampling change frequency was

7 1-7 days depending on operational considerations. A typical flow rate of air samplers was

approximately 17000 cm3/minute (0.6 ft3 8 /minute). 

9 The data included 377 air samples, representing two data sets. A total of 247 samples were

10 collected for the first data set and 130 samples were collected for the second data set. The first

11 data set was generated using measurements taken before and during the initial decontamination

12 activities. Although there were no plant operations being performed in the period prior to

13 decommissioning, there was sufficient human activity at the site in the vicinity of the air samplers

14 to warrant inclusion of the data collected. Three different activities were performed while taking

15 these measurements during the decommissioning period; the removal of equipment from the

16 room, a one-pass shot-blasting of the floor, and waste packaging. The first data set samples

17 were collected from 13 different stations within the facility. The average air concentration of the

247 data points was 4.66 x10-8 Bq/ml (1.26 x 10-12 18 μCi/ml). The total surface activity

measurements under similar conditions were reported to be 26.7 Bq/100 cm2 (1.6 x 105 19 dpm/100

cm2). Thus, the nominal RF value before and during decommissioning activities is 1.7 x 10 -7 m-1 20 .

21 The data also included surface contamination measurements from 29 locations, both before and

22 after floor contamination.

23 The second data set was generated using measurements taken after decommissioning while the

24 facility was essentially in a shutdown mode with minimal physical activities taking place. The

25 samplers for the second data set were located at the same 13 stations. The average RF value

corresponding to these condition are 4.2 x 10-8 m-1 26 . 

27 4.6.2 Evaluation

28 The first data set represents typical facilities that are undergoing decontamination. However, the

29 conditions of driving forces causing resuspension were more aggressive than those conditions

30 representing a typical light-industry scenario. In addition, ventilation was minimal. Therefore,

31 depletion of the source-term were ineffective leading to more airborne concentrations and

32 consequently RF values, for the measured facility, higher than would be anticipated for a

33 decommissioned facility. On the other hand, the second data set represented less aggressive

34 driving conditions for resuspension than expected for the light industry scenario. However,

35 ventilation was nearly static which causes a lesser depletion of the source-term and

36 subsequently increase in resuspension. Therefore, the data for the second set may lead to an

37 underestimate of the RF corresponding to the building occupancy scenario, and were therefore

38 not used. The average RF derived from data taken during the post-decommissioning phase may

39 underestimate the mean value for a light industrial scenario.

40 4.7 Ruhter and Zurliene, 1988, Data
15

1 4.7.1 Description

2 This study presented a brief discussion of airborne concentrations relative to surface

3 contamination in the Three Mile Island, Unit 2 (TMI-2) auxiliary building during cleanup activities

4 about 6 months after the accident. The principal source of airborne particulate radioactivity was

5 resuspension of radioactive contamination which had been deposited on the surfaces. The

6 report did not provide much data that can be broken down into subsets of measurements

7 representing different facilities or various occupancy conditions. A maximum particulate

concentration of 220 Bq/m3 (5.94 x 103 pCi/m3 8 ) was reported. Contamination levels on the floors

were reported as high as 2000 - 4000 Mbq/m2 (54 - 108 mCi/m2 9 ). These values correspond to

RF values in the range of 0.055 x 10-6 to 0.11 x 10-6 m-1 10 . However, both the surface and airborne

11 values reported were maximums, so the resulting RF could be in error. The authors stated that

“...a resuspension factor on the order of 10-8 cm-1 (i.e., 1x10-6 m-1 12 ) would be expected from

13 undisturbed surfaces, and would result in airborne concentrations similar to those observed...”,

14 but provided no additional information to support their affirmation.

15 4.7.2 Evaluation

16 Building surfaces had not been cleaned; thus, the test conditions could lead to an estimate of the

17 RF higher than expected for decommissioned facilities. There are no specific measurements

18 available for breaking the above data range into individual measurements representing different

19 conditions.

20 4.8 Spangler, 1998, Data

21 4.8.1 Description

22 David Spangler, of the BWX Technologies, Navy Nuclear Fuel Division, presented resuspension

23 data at the NRC’s public Workshop on Decommissioning, held on December 1, 1998. These

24 data were later amended in a written communication (Olsen, 2000). The RF was measured in a

25 uranium storage area, the central storage vault, during handling of containers of uranium at an

26 operating uranium fuel fabrication plant. Surface residual radioactivity concentrations were

27 measured for both floors and uranium containers, both of which could contribute airborne activity

28 from resuspension. Fixed air samplers collected approximately 

29 1000 airborne radioactivity samples for the storage area of the fabrication plant. Approximately

30 4000 wipe test samples were also collected for the same facility. The data were generated over

31 12 months, during 1995. It appears that the facility meets the definition of a light-industry

scenario. The three-year average RF values were: 4.25 x 10-7 m-1, 7.79 x 10-6 and 8.97 x 10-7 32 for

33 fixed-air measurements, breathing-zone (BZ)measurements for averages < 6 hours, and BZ

34 measurements for averages $ 6 hours, respectively. 

35 4.8.2 Evaluation

36 These data could represent a decommissioned facility, in terms of the expected driving forces of

37 a light-industry scenario. However, the airborne concentration may be exaggerated, because of

38 the resuspension from contaminated surfaces of containers and movement of such containers. 

39 This is especially true with the BZ measurements, which tend to overemphasize the intake of

40 particles that were created by the mechanical operations such as opening or moving containers. 

41 The third value reported above is for measurements with at least a 6 hour averaging time, and are

42 much lower than the peak BZ values of RF. The data also show that fixed contamination varies
2The post-decommissioning Nardi data would qualify, but were not included in the final 

 assessment of RF.

16

over a relatively a small range 3.4 ± 2.7 x 102 Bq/100cm2 (2.04 ± 1.6 x 104 dpm/100cm2 1 ) whereas

2 airborne concentration varies by approximately a factor of 6. As with the other data used in the

3 present study, the 12 monthly values reported may be combined into a single annual average RF

4 for this site. 

5 There was surface activity, on the containers being moved, that would not be present in the

6 building occupancy scenario. This could cause the RF from this study to overestimate the RF at

7 decommissioned sites. Therefore, we will include only the RF values based on fixed air

8 samplers, and ignore the BZ data. Overall, the data appear to be representative of the building9 occupancy scenario and can be used for estimating the RF.

10 4.9 Summary of Data Used for Revising the RF

11 Although we have performed an extensive literature search, the number of measurements of

12 indoor RF is limited. Furthermore, the few measurements that are reasonably representative of

13 the building-occupancy scenario contain factors that will likely lead to an overestimate of RF. 

14 There is currently not enough information to estimate the magnitude of this likely over-estimation. 

15 Therefore, we must use our judgment to develop a distribution that we believe appropriately

16 reflects conditions for the building-occupancy scenario.

17 Table 3 shows ranges of RF values reported for two main types of particles or surface

18 contaminants. As can be seen in Table 3, the RF is significantly dependent on whether or not the

19 particles were freshly deposited on the surface. The studies involving freshly deposited

20 contamination have a high fraction of loosely bound particles; whereas the studies involving

21 operating facilities or those undergoing decommissioning have a significantly lower fraction of

22 loosely bound particles. None of the sites in the first category represent decommissioned

facilities in the respect that the surfaces had been decontaminated2 23 . We anticipate that most

24 owners of facilities undergoing decommissioning will wash or otherwise clean contaminated

25 surfaces to comply with ALARA requirements of 20 CFR 20.1402. The approach used in

26 NUREG/CR Volume 3 (Beyeler, et al., 1999) was based on data from Fish, et al., (1967) and

27 Jones and Pond (1967), involving freshly deposited material. This approach assumed that the

28 RF would be proportional to the “loose” fraction as measured by a wipe measurement. This

29 proportionality was assumed to hold even if the fraction of “loose” particles was as low as a

30 couple of tenths of a percent, as would be typical at a decommissioned facility that had been

31 washed. Rather than basing the RF on a study using freshly deposited material and

32 proportionally reducing the RF by an assumed factor accounting for the fraction of loose particles

33 likely to be present at decommissioned facilities, as was done previously 

34 (Beyeler, et al., 1999), the approach in this paper is to use data more directly applicable to

35 decommissioned facilities.

36 Three sets of data (Breslin, 1966; Nardi, 1999; and Spangler, 1998) appear to be most applicable

37 to estimating RF for decommissioned facilities. The measurements of Eisenbud, 1954, and

38 Ruhter, 1988, appear to be less applicable, but still usable. Data from these five studies were

39 used in this paper to develop an alternate distribution for RF.

40 5.0 DEVELOPMENT OF AN ALTERNATE ESTIMATE FOR RF 
17

1 This section describes the statistical methods used to: (1) analyze the data described in 

2 Section 4; (2) develop an alternate RF PDF; and (3) select an appropriate default value for RF, for

3 certain circumstances.

4 The approach used was a statistical analysis of all available data to evaluate the two empirical

5 distributions (normal and log-normal) of the mean value of RF for each facility considered

applicable. From the distribution, we report the 90th 6 percentile value of the RF. Because of the

7 sparsity of data, we also considered (but ultimately did not use) a tolerance limit to calculate the

90th percentile PDF value, with a 95th 8 percentile confidence. In addition, an analysis of the time9 dependance of the airborne concentration was performed for the Breslin and Nardi data sets to

10 correct the RF values for worker occupancy times.

11 Table 3: Summary of RF Data Applicability

12 Study Range of Resuspension

Factor Values (m-1)

13 Freshly Deposited Contamination

14 Fish, 1967 9.4 to 710 x 10-6

15 Ikezawa, 1980 2.3 to 180 x 10-6

16 Jones, 1967 0.3 to 177 x 10-6

17 Cleaned or Aged Contamination

18 Breslin, 1966 0.33 to2.08 x 10-6

19 Eisenbud, 1954 0.1 to 0.5 x 10-6

20 Nardi, 1999 0.067 to 0.227 x 10-6

21 Ruhter, 1988 0.055 to 0.11 x 10-6

22 Spangler, 1999 0.425 x 10-6
18

1 5.1 Correction Factor for Time Variation of Airborne Concentration

2 One consideration in the use of available data on airborne concentrations at indoor facilities is

3 that the filters used to collect these data are generally in operation all the time, but workers are

4 exposed only during the time they are there. These data need to be corrected to estimate RF

5 because invariably the airborne dust load would be smaller when there was no activity within the

6 buildings. The worst case would be that the airborne dust load falls to zero concentration after

7 the workers leave for the day. In this case, the RF should be adjusted upward by a factor of 4.2,

8 for a 40-hour work week; i.e., the ratio of 168 hours to 40 hours. However, the dust levels do not

9 fall to zero after workers leave because the finest particles settle slowly, and there are other

10 factors such as ventilation and natural convection that lead to a continual suspension of part of

11 the dust. 

Consider that the facility can be represented by a well-mixed room of volume V m3 12 . During

13 worker activities, dust is generated in the room at a rate W(t) grams/hour. Dust is removed from

14 the room at a rate ?CV grams/hour where ? is a first-order removal rate describing all removal

15 mechanisms, including purging by ventilation and settling. The concentration C of dust in the

16 room can be described by the first order ordinary differential equation:

17 (2) dC

dt

'

W(t)

V

& C?

18 This equation can be solved to calculate the concentration, and therefore the exposure rate in the

19 room. The correction factor for worker duty cycle, DS, can then be calculated as the ratio of the

20 average concentration during the time that the workers are present to the average concentration

21 for the entire 168 hour week.

22 The Breslin (1966) data show the concentration of radioactivity versus time for nine samplers. 

23 Figure 2 shows the calculated RF values at 9 stations within the plant at four separate times. 

24 These times represent different periods around operational activities and show how airborne

25 concentrations increase by these activities and decrease when they stop. The lines connecting

26 the time points should be considered to be visual aids only, rather than an indication of the

27 behavior between measurement times. 

28 Analysis of the Breslin data indicate rather clearly that the airborne concentrations persist for

29 considerable periods of time, and that the higher concentrations change at a faster rate than the

30 lower concentrations. The most likely explanation for this observation is that the higher

31 concentrations represent larger-sized particles, that must have been generated or suspended by

32 more energetic processes than the finer particles. This observation is relevant to the choice of

33 the RF value to be used for three reasons: (1) particles in the small-sized category are more

34 likely to be the type generated in a light-industrial scenario, (2) small particles are more

35 respirable, and (3) small particles are more likely to persist between work shifts in the building.

36 The observed persistence of airborne concentration diminishes, but does not eliminate, the

37 importance of daily activities in elevating the airborne concentration. 
19

Figure 2. Analysis of Breslin (1966) Data Showing the

Variation With Time of the Concentration Measured

at Different Sampling Locations.

An average decay rate from the first part of the Breslin data is ? = 0.029 hr-1. 1 If the average value

2 applied, concentration would fall roughly to half the highest value by the start of the next morning

3 (assuming a single 8-hour work shift). Excluding the two highest measurement stations leads to

4 a much smaller removal rate of 0.00946/hour. An alternative estimate of 

? = 0.022 to 0.054 hr-1 with an average value of ? = 0.0378 hr-1 5 can be based on the assumption

6 that the airborne concentrations in the Breslin facility are cyclical, but do not vary from week to

7 week. 
20

Figure 3. Beta Air Activity Sample Results for

Westinghouse Active/Inactive

Decommissioning Facilities

1 Figure 3 shows air sampling results for the Nardi site. These data are less descriptive than the

2 Breslin data, and it was not possible to estimate the decay rate a priori. Instead the model 

3 represented by Equation 2 was run for different values of ?, and the concentrations as measured

4 by the air filters calculated under the assumption that filters were changed at 

5 8:00 a.m. on Monday and 5:00 p.m. on Thursday. There were, therefore, two assumed periods of

6 averaging; 1) the 82 hours during which there was worker and decommissioning activity, and

7 2) the 86 hours of minimal activity after workers left for the week. A qualitative comparison of the

8 measured (Figure 3) and predicted (Figure 4) average concentrations indicated that a value of ? =

0.05 hr-1 9 was most appropriate for the conditions at this site.
21

Figure 5. Predicted Variation of Dust Concentration (gm/cm3

)

Using Breslin Data (1966) 

Figure 4. Predicted Dust Load for Nardi, (1999) Data
22

1 We estimated the correction factor for worker occupancy by numerically integrating Equation 2,

2 and calculating the ratio of the average concentration during worker exposure to the weekly

3 average, after the initial transient response for the system has died away. For the Breslin site,

4 the dust source term, W(t) was represented as a square wave input that was 1.0 gram/hour for 8

5 hours a day, and 0 grams/hour for the next 16 hours, repeated for 5 days, followed by an input of

6 0 grams/hour for the 48 hour weekend.

7 Figure 5 shows the concentration buildup for Breslin (1966) data with time for a 6 week cycle

8 starting with zero concentration in the air. Workers are present and exposed only on the upward

9 segments of the “sawtooth”. The volume is immaterial for calculating the correction factor DS.

For ? = 0.0378 hr-1 10 , the correction factor DS = 1.2. For ? = 0.00946/hour, perhaps more

11 representative of respirable-sized particles, DS = 1.02. 

12 For the Nardi’s data, we made similar assumptions, but the workers were exposed for 4 ten-hour

days. Using a decay factor ? = 0.05 hr-1 13 leads to a correction factor DS = 1.5. Interestingly, the

14 correction factor is larger for the 4-day work week. Assuming 8 hour days, 

15 5 days a week led to a smaller correction factor DS = 1.28 for this site.

16 5.2 Statistical Analyses of the RF

17 5.2.1 Adjustments to Data

18 Data available for statistical analysis consist of the average RF values for the five sites (Nardi,

19 Breslin, Spangler, Ruhter and Eisenbud). Each of the average RF values was adjusted upward

20 by an “occupancy” factor. Occupancy correction factors were available only for the Breslin and

21 Nardi data. The average RF values for the Breslin and Nardi sites were adjusted by a factor of

22 DS = 1.2 and 1.5, respectively. The average RF values for the for the remaining three sites were

23 adjusted by a factor of 1.35, which is the average for the Breslin and Nardi corrections. We feel

24 that these correction factors are conservative, mainly because the filters that were used to collect

25 the airborne particles probably captured a significant fraction of larger particles, which settle

26 faster, and lead to the calculation of higher ?, and thus higher DS. This might be especially true

27 for the Nardi data, which included periods of high-energy operations such as shot-blasting of

28 surfaces.

29 The corrected RF data for the five sites is shown in Table 4. The cumulative probability for

30 normal and lognormal distributions of the RF using the mean values of five facilities is shown in

31 Figure 6. 

32 Table 4: Mean Values of RF for Each Site

33 Site Reference Mean RF, 10-7 m-1 Mean RF, 10-7 m-1,

Adjusted for Occupancy

34 Nardi (1999, Decommissioning) 1.71 2.565

35 Spangler (2000) 4.25 5.734

36 Ruhter and Zurliene (1988) 0.825 1.114

37 Breslin (1966) 8.44 10.13

38 Eisenbud (1954) 3.07 4.145
23

Figure 6. Cumulative Probability Distribution (Normal &Lognormal)

of the RF Using Mean Values of Five Facilities

1 5.2.1.1 Tolerance Limits

The statistical confidence in the estimated value of the 90th 2 percentile RF can be calculated for

3 the size of the sample under the assumption that RF (or its logarithm) is normally distributed. 

4 The confidence in the value of RF can be stated: “At least 90 percent of the values of RF would

5 be less than μ - k s with a confidence of 95 percent”, where μ is the sample mean of RF and s is

6 the sample standard deviation of RF. A similar statement would apply to the logarithm of RF. 

7 Tolerance is an issue because we are using a small amount of data to estimate the PDF

8 describing the variability of RF over the various NRC decommissioning sites. The variability

9 among various sites is an aleatory uncertainty, while the tolerance describes how certain we are

10 of the knowledge base, i.e. an epistemic uncertainty. If we had a large number of data, say

11 hundreds to thousands of samples, to estimate the PDF, the tolerance bands around the nominal

12 value would be small. However, with sparse data, the tolerance bands can be significant. The

methodology for obtaining the 90th 13 percentile of the dose distribution assumes that the PDF’s are

14 precise, i.e., (1) estimation error is not explicitly represented; and (2) the derived PDF’s do not

15 appear to take into account how much data are available (almost always sparse data) to make

16 the estimate. Since the rest of the methodology for obtaining screening values does not consider

17 the amount of data available to estimate the input variable PDF’s, it would be inconsistent to take

18 this into account for resuspension factor. Furthermore, because of the nature of the data used,

19 which we believe overestimates the value of RF, and because features of the model (e.g., no

20 depletion by ventilation) also tend to overestimate dose, use of the nominal value is deemed

21 appropriate. However, consideration of estimation error in dose modeling, (perhaps in risk
24

1 analysis in general) may be a topic that needs further study within the entire context of regulatory

2 decision-making.

3 5.2.1.2 Consideration of the Post-decommissioning Data from Nardi

4 The average value of RF calculated from the post-decommissioning Nardi data are about 1/4

5 those calculated from the decommissioning results. This result could be used to lower the

6 estimates presented from the other data by a similar factor. However, the post-decommissioning

7 data may be unrepresentative of a light-industrial scenario. Consequently, we decided that this

8 factor will not be used in the estimate of the RF distribution.

9 5.2.2 Statistical Analysis of Site Mean Results

10 Although some of the data indicate that there are likely to be significant variations in airborne

11 concentrations from place to place, one may wish to consider that there is an overall effective RF

12 for each site. Occupants of the buildings are likely to move around; therefore they are exposed to

13 a variety of potential resuspension conditions rather than one. Under these assumptions, it is

14 appropriate to use the site average of the RF’s as a sample representing the variability of RF

15 across the population of NRC licensees. 

16 6.0 SUMMARY, CONCLUSIONS, AND RECOMMENDATIONS

17 6.1 Summary

18 The authors of this report followed the following approach to reevaluate the PDF and nominal

19 value of the indoor resuspension factor for use in screening evaluations for the license

20 termination rule:

21 1. Modeling the building occupancy scenario for contamination with a-emitters resulted in

22 doses higher than those obtained with other standard codes; in some cases the indicated

23 cleanup levels were below detectable limits. 

24

25 2. Evaluation of the models used in the building occupancy scenario indicated that the

26 resuspension factor parameter, both the PDF and default value, was the primary cause of

27 this result.

28

29 3. Examination of the basis for the PDF used previously indicated the data were obtained

30 under conditions that did not match very well the conditions anticipated at

31 decommissioned facilities.

32 4. The technical literature was reviewed to obtain further data for indoor resuspension

33 factors.

34 5. Participants at NRC’s public workshops on implementation of the License Termination

35 Rule were asked to provide additional data on indoor resuspension factors. Additional

36 data were provided by D. Spangler of BWX Technologies, and A. Nardi, of Westinghouse

37 Power Corporation.

38 6. A total of eight sets of data were evaluated for applicability to decommissioned facilities. 
25

1 7. Five sets of data were deemed applicable enough to use to quantify the PDF for the

2 indoor resuspension factor.

3 8. Data were corrected to account for the fraction of the time workers occupy the site.

4 9. We performed several statistical analyses:

5 a. A determination of the PDF for mean values of RF from each of the five studies (5

6 separate estimates of RF).

7 b. Evaluation of different functional forms of the PDF (lognormal and normal).

c. Determination of the nominal value of the 90th 8 percentile of the PDF.

10. These analyses were evaluated and a preferred choice of PDF and the 90th 9 percentile of

10 that PDF were chosen.

11 6.2 Conclusions

12 The additional information, both in the literature and provided by two facilities, appears to be an

13 improved basis to estimate indoor resuspension factor. Nevertheless, these data have certain

14 limitations, most of which relate to the applicability to decommissioned facilities of the conditions

15 under which data were obtained. These limitations include:

16 1. Interference from Operations. An apparent elevation of air concentrations occurred in

17 some cases (Breslin, Eisenbud, and Nardi) when measurements were made in facilities

18 where operational activities introduced radioactive material directly into the air.

19 2. Different Resuspension Forces. In some cases, the resuspension forces were simulated

20 (Breslin); in other cases, the resuspension forces were absent, because the facility was

21 not in use at the time of measurement (Nardi). In the former case, the measured

22 resuspension factor could be higher or lower than that in a decommissioned facility,

23 depending on the nature of simulated activity; in the latter case, the measured

24 resuspension factor could be lower than that in a decommissioned facility.

25 3. Location of Measuring Instruments. There are several factors with the location and type of

26 measuring instruments. Data from fixed air samplers were preferred because they better

27 indicated levels of respirable dust than breathing zone, lapel samplers. Location is also

28 important. Lapel samplers are at the correct height, but tended to reflect contamination

29 levels from equipment operation rather than resuspension. Samples taken close to the

30 floor were considered inappropriate for data on respiration.

31 4. Condition of the Contamination. In a decommissioned facility, it is anticipated that the

32 contaminated surfaces will have been cleaned, so loose particulate matter harboring

33 contamination will have been removed. However, as surfaces are subject to wear and

34 other forces, some of this “fixed” contamination may become loosened. Alternatively,

35 maintenance activities such as waxing floors or painting surfaces, may more firmly fix

36 residual contamination. Some tests (Jones and Pond, 1967, Fish et al, 1967, Ikezawa, et

37 al., 1980) used freshly deposited material, which probably overestimates RF.
26

1 5. Other Conditions of Measurement. Other conditions existing during the time that

2 measurements were made may also influence the degree to which the data obtained

3 apply to a decommissioned facility. Ventilation at the contaminated sites was not well4 characterized, and it is difficult to determine how well ventilation expected in

5 decommissioned facilities corresponds to the data. Another possible example is the use

6 of HEPA filters during decommissioning operations. Nardi (1999) reports that such filters

7 were in use during some of the decommissioning operations, but only to protect workers

8 near the operating machinery. We decided that the use of the filters in this case did not

9 generally decrease the airborne dust load since they acted only on the operating

10 equipment producing the dust, and not on resuspended dust.

11 In summary, the available data are not perfect, but they do provide the best insight available at the

12 present time into an estimate of the PDF for resuspension factor. Overall, the authors of this

13 report believe these data provide an overestimate of the distribution of RF’s likely to exist at

14 decommissioned facilities.

15 The methodology used to develop default parameters for the DandD code presumed that the

16 PDF’s describing the variability of parameters among NRC-licensed facilities was precise, but

17 sparse. Even though this uncertainty may be significant, we conclude that the “best estimate” of

18 the PDF should be used for screening analyses. Two important reasons for choosing this

19 strategy are: (1) the exposure scenario, dose models, PDF’s for other parameters, and the data

20 supporting quantification of the PDF for RF are all believed to contain significant conservatisms,

21 which argue against using the extra measure of conservatism introduced by insisting on high

22 confidence in the results (i.e., using tolerance); and (2) the remainder of the DandD screening

23 analysis uses PDF’s that do not consider estimation uncertainty. Therefore, consideration of

24 tolerance for RF only would be inconsistent and would introduce more unnecessary

25 conservatism for radionuclides affected by resuspension.

26 We deemed it appropriate to base the PDF for RF on the 5 data points representing the site

27 means, adjusted for worker occupancy, because: (1) workers may move around a facility and be

28 exposed to a variety of air concentrations; and (2) the regulation is written to protect the average

29 member of the critical group. We fitted the five site data to a normal and a lognormal distribution. 

30 Since there were only five data points, we felt that it was appropriate to use the “maximum

31 likelihood” approach (Benjamin and Cornell, 1970) to estimate the distribution rather than a

32 statistical (i.e., “unbiased”) approach. The difference between the two approaches is that the

33 estimated standard deviation in the maximum likelihood approach is smaller by the ratio 

. This smaller standard deviation will lead to a slightly smaller value for the 90th 34 (N&1)/N

35 percentile of the distribution, which is used as the suggested regulatory criterion for RF.

36 Parameters of the normal and lognormal distributions are given in Table 5 for the maximum

37 likelihood fits. Figure 6 shows the two distributions. Also shown in this figure are the original data

plotted as an empirical distribution, with the smallest value equal to the 10th 38 percentile and the

largest as the 90th 39 percentile. Although both the normal and lognormal distributions are

40 reasonable fits to the data, the normal distribution has the disadvantage of allowing negative

41 values of RF, which is not physically possible. In addition, the lognormal fit is the more

conservative choice at the 90th 42 percentile RF.

43 Table 5: Parameters for Normal and Lognormal “Maximum Likelihood” Models of RF

44 Data
27

1 Statistical Model Sample Mean Sample Standard

Deviation

90th Percentile RF

2 Normal Fit to 5 site

3 mean RF’s

4.74 x 10-7 m-1 3.11 x 10-7 m-1 8.7 x 10-7 m-1

4 Lognormal Fit to 5

5 site mean RF’s

log10 = -6.433 log10 = 0.3247 9.6 x 10-7 m-1

6 6.3 Recommendations

7 We make the following recommendations:

8 1. The PDF given in Section 6.2 should be implemented in the DandD code. For the building

9 occupancy scenario with the additional condition that the dose is dominated by inhalation

of a single radionuclide, the nominal 90th 10 percentile of the lognormal fit for

RF , (i.e. 9.6 x 10-7 m-1 11 ), may be used. For situations where other pathways (e.g., direct

12 exposure) are significant, this PDF must be processed through the DandD code

13 screening methodology.

14 2. Because of the paucity of data and the incompatibility of the conditions under which it was

15 obtained and conditions anticipated for decommissioned facilities, consideration should

16 be given to conducting research to obtain more data directly applicable and representative

17 of facilities whose licenses are to be terminated by NRC.

18 3. Sparse data for the estimation of the properties of a distribution can lead to significant

19 uncertainties in the properties of the distribution (e.g., the mean, the standard deviation,

the 90th 20 percentile). Consideration is usually not given to this type of uncertainty in the

21 PDF’s used for dose estimates, performance assessments, and probabilistic risk

22 analyses. The NRC staff should investigate the impact of estimation uncertainty and how

23 it may affect regulatory decisions in a risk-informed, performance-based regulatory

24 context.
28

1 7.0 REFERENCES

2 Abelquist, E. W, W. S. Brown, G. E. Powers, A. M. Huffert, “Minimum Detectable Concentrations

3 with Typical Radiation Survey Instruments for Various Contaminants and Field Conditions,”

4 NUREG-1507, 1998.

5 ASHRAE 89“Ventilation for Acceptable Indoor Air Quality,” ANSI/ASHRAE 62-1989, American

6 Society of Heating, Refrigerating and Air-Conditioning Engineers, Inc., Atlanta, 1989.

7 Benjamin, J.R., and C. A. Cornell, Probability, Statistics, and Decision for Civil Engineers,

8 McGraw-Hill, 1970

9 Beyeler, W.E., W.A. Hareland, F.A. Durán, T.J. Brown, E. Kalinina, D.P. Gallegos, and P.A.

10 Davis, Residual Radioactive Contamination from Decommissioning, Parameter Analysis. Draft

11 report for comment, NUREG/CR-5512, Vol. 3. U.S. Nuclear Regulatory Commission,

12 Washington, DC., 1999.

13 Beyeler, W. E. et al., “Review of Parameter Data for the NUREG/CR-5512 Building Occupancy

14 Scenario and Probability Distributions for the DandD Parameter Analysis,” Draft Letter Report

15 dated January 30, 1998.

16 Breslin A. J., A. C. George, and P. C. LeClare, “The Contribution of Uranium Surface

17 Contamination to Inhalation Exposures,” HASL-175, 1966.

18 Brodsky, A., “Resuspension Factors and Probabilities of Intake of Material in Process (Or ‘Is 

10-6 19 a Magic Number in Health Physics?’),” Health Physics, 39, 992.

20 Cember, H., 1996, Introduction To Health Physics, McGraw-Hill, New York, NY

21

22 Corn, M. and F. Stein, “Mechanisms of Dust Resuspension” in Surface Contamination:

23 Proceedings of a Symposium Held in Gatlinburg Tennessee, June 1964, B. R. Fish, ed., 

24 page 45, Pergamon Press, Oxford, 1967.

25 EPA 1988, Limiting Values of Radionuclide Intake and Air Concentration and Dose Conversion

26 Factors for Inhalation, Submersion, and Ingestion, Federal Guidance Report No. 11,

27 Environmental Protection Agency, Washington, D.C.

28 Eisenbud, M., Blatz H., and E.V. Barry, “How Important is Surface Contamination?” Nucleonics,

29 Vol. 12(8), 12, August, 1954.

30 Fish, B. R., R. L. Walker, G. W. Royster, Jr., and J. L. Thompson, “Resuspension of Settled

31 Particulates,” in Surface Contamination: Proceedings of a Symposium Held in Gatlinburg,

32 Tennessee, June 1964, B. R. Fish, ed., page 75, Pergamon Press, Oxford, 1967. 

33 Hinds, W.C., Aerosol Technology - Properties, Behavior, and Measurement of Airborne

34 Particles, John Wiley & Sons, New York, 1982. 
29

1 Ikezawa, Y., T. Okamoto, and A. Yabe, “Experiences in Monitoring Airborne Radioactive

2 Contamination in JAERI,” in Radiation Protection: A Systematic Approach to Safety - Proceedings

3 of the 5th International Radiation Protection Society, p 495, Pergamon Press, 1980.

4 Jones, I.S. and S. F. Pond, “Some Experiments to Determine the Resuspension Factor of

5 Plutonium from Various Surfaces,” in Surface Contamination: Proceedings of a Symposium Held

6 in Gatlinburg Tennessee, June 1964, B. R. Fish, Ed., page 83, Pergamon Press, Oxford, 1967. 

7 Kennedy, W.E., “Provate Communication Between S. McGuire and W.E. Kennedy,” 1999. 

8 Kennedy W.E. and D. L. Strenge, NUREG/CR-5512, Volume 1, “Residual Radioactive

9 Contamination from Decommissioning,” 1992

10 Morton, H., “Interpretation of the Relation of Building Interior Surface to Airborne Radioactivity,”

11 Submitted at NRC Public Workshop on Decommissioning, January 1999. 

12 Nardi, A.J., “Operational Measurements and Comments Regarding the Resuspension Factor,

13 Presentation at NRC Decommissioning Workshop, March 18, 1999 and associated transcript.

14 Nuclear Regulatory Commission, “Final Rule on Radiological Criteria for License Termination,”

15 July 21, 1997, 62 FR 39058.

16 Ruhter, P.E.and W.G. Zurliene, “Radiological Conditions and Experiences in the TMI- Auxiliary

17 Building,” CONF-881-24-9, 1988.

18 Spangler, D.L., “Re-Suspension Factor Determination and Comparison Using Data from an

19 Operating Licensed Facility,” BWX Technologies, Inc., presentation at NRC Decommissioning

20 Workshop, December 1, 1998 and associated transcript. 

21 Walker, R.L. and B. R. Fish, “Adhesion of Radioactive Glass Particles to Solid Surfaces” in

22 Surface Contamination: Proceedings of a Symposium Held in Gatlinburg Tennessee, June 1964,

23 B. R. Fish, ed., page 61, Pergamon Press, Oxford, 1967.
1

 The RF is the ratio of airborne concentration of radioactive contaminant to the average 

surface activity. The airborne concentration was measured for each of the three facilities

using two lapel samplers and one fixed air sampler. The surface activity values

measured for each facility were given in Section 4.1.1. These values were multiplied by

a factor of 2 because calibrations of alpha measurements of surface activity conducted

in early studies (1954 - 1967) underestimated the total surface activity by a factor of two

(Abelquist et. al., 1998). 

2

 Condition “a” corresponds to measurements taken on Sunday with no operational 

impacts (e.g., airborne contamination introduced by operations had settled out of the air). 

Condition “b” corresponds to measurements taken on Saturday representing postoperation transient condition. Condition “c” represents initial operating transient

conditions for measurements taken on Monday; and conditions “d” corresponds to

measurements taken on Thursday with typical operation of the concerned facility (see

Section 4.1.1 for details). 

30

1 8.0 APPENDIX A

2 Table A-1: SUMMARY OF RF VALUES BASED ON BRESLIN, et. al., (1966) DATA

3 Facility/Data Set

Calculated RF Values1, (m-1)Multiplied By 106, Under Different

Operational Conditions2

Condition “a” Condition “b” Condition “c” Condition “d”

4 Assistant

5 Press

6 Operator

7 Facility

Lapel Sampler

of Worker 1

0.22 0.36 0.86 3.40

Lapel Sampler

of Worker 2

0.19 0.39 1.03 3.40

Fixed Air

Sampler 

0.1 0.31 0.37 1.60

8 Rod

9 Puller

10 Facility

Lapel Sampler

of Worker 1

0.33 0.62 1.30 1.90

Lapel Sampler

of Worker 2

0.35 0.57 1.30 1.60

Fixed Air

Sampler 

0.26 0.27 1.20 1.80

11 Rod

12 Straight13 ener

14 Facility

Lapel Sampler

of Worker 1

0.75 1.60 3.10 1.70

Lapel Sampler

of Worker 2

1.04 3.2 2.05 3.00

Fixed Air

Sampler 

0.49 0.31 1.50 2.00

15 
31