Page 1 of 81

DOE Review Release 04/12/2021

Breathing Zone to General Area Air

Concentration Ratios in Small Workrooms

ORAUT-RPRT-0097 Rev. 00

Effective Date: 03/29/2021

Supersedes: None

Subject Expert(s): Brian P. Gleckler and Thomas R. LaBone

Document Owner 

Approval: Signature on File

Brian P. Gleckler, Document Owner

Approval Date: 03/24/2021

Concurrence: Pat McCloskey Signature on File for

Michael S. Kubiak, Objective 4 Manager

Concurrence Date: 03/24/2021

Concurrence: Vickie S. Short Signature on File for

Kate Kimpan, Project Director

Concurrence Date: 03/29/2021

Approval: Signature on File

Timothy D. Taulbee, Associate Director for Science

Approval Date: 03/29/2021

FOR DOCUMENTS MARKED AS A TOTAL REWRITE, REVISION, OR PAGE CHANGE, REPLACE THE PRIOR 

REVISION AND DISCARD / DESTROY ALL COPIES OF THE PRIOR REVISION.

New Total Rewrite Revision Page Change
Document No. ORAUT-RPRT-0097 Revision No. 00 Effective Date: 03/29/2021 Page 2 of 81

PUBLICATION RECORD

EFFECTIVE

DATE

REVISION

NUMBER DESCRIPTION

03/29/2021 00 New document initiated to evaluate the data from several air 

sampling studies performed in small workrooms. The air sample 

data were evaluated in terms of breathing zone air concentrations 

and air concentrations measured from general area air samplers. A 

statistical evaluation of the potential ratios of the breathing zone air 

concentrations and the general area air concentrations is presented 

in this document. Incorporates formal internal and NIOSH review 

comments. Training required: As determined by the Objective 

Manager. Initiated by Brian P. Gleckler.
Document No. ORAUT-RPRT-0097 Revision No. 00 Effective Date: 03/29/2021 Page 3 of 81

TABLE OF CONTENTS

SECTION TITLE PAGE

Acronyms and Abbreviations ............................................................................................................... 7

1.0 Purpose and Scope.................................................................................................................. 8

2.0 Introduction .............................................................................................................................. 8

2.1 Parameters Affecting Level of Mixing............................................................................ 8

2.1.1 Size of the Room............................................................................................ 9

2.1.2 Particle Size Distribution of the Aerosol.......................................................... 9

2.1.3 Ventilation Rate............................................................................................ 10

2.1.4 Room Complexity......................................................................................... 10

2.2 Parameters Only Affecting BZ:GA Ratios ................................................................... 10

2.2.1 Sampler and Release Locations................................................................... 11

2.2.2 Low Number Concentrations of Dominant Aerosol Particles ........................ 11

3.0 Studies Evaluated .................................................................................................................. 12

4.0 Gonzales et al. Study............................................................................................................. 15

4.1 Experiment Description............................................................................................... 15

4.2 Reported Results and Conclusions............................................................................. 16

4.3 Reevaluation of Gonzales et al. Study Data................................................................ 18

4.3.1 Bases and Assumptions for the Reevaluation .............................................. 18

4.3.2 Probabilities for Hypothetical BZ Locations and GA Sampling 

Locations ..................................................................................................... 20

4.3.3 Statistical Evaluation of the Data.................................................................. 22

4.3.3.1 Scenario 1 Results: Colocated Worker and Release Point ........ 26

4.3.3.2 Scenario 2 Results: Variable Worker Location Relative to 

the Release Point...................................................................... 27

4.3.3.3 Summary of Scenario 1 and Scenario 2 Results........................ 29

5.0 Charuau Study....................................................................................................................... 29

5.1 Contamination Transfer Study Description and Results.............................................. 29

5.2 Evaluation of the Charuau Study Data........................................................................ 30

5.2.1 Scenario 1 Evaluation: Colocated Worker and Release Point ...................... 31

5.2.2 Scenario 2 Evaluation: Variable Worker Location Relative to the 

Release Point............................................................................................... 33

5.2.3 Summary of Scenario 1 and Scenario 2 Results .......................................... 35

5.2.4 Combined Scenario 1 and 2 Results for Aerosols ........................................ 35

6.0 Munyon and Lee Study .......................................................................................................... 37

6.1 Description of the Study.............................................................................................. 37

6.2 Evaluation of the Munyon and Lee Study Data........................................................... 41

6.2.1 Statistical Evaluation of the Data.................................................................. 41

7.0 Scripsick et al. Study.............................................................................................................. 42

7.1 Description of the Study.............................................................................................. 42

7.2 Evaluation of the Scripsick et al. Study Data............................................................... 44

7.2.1 Statistical Evaluation of the Data.................................................................. 46

7.2.1.1 Scenario 1 Results: Colocated Worker and Release Point ........ 46
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7.2.1.2 Scenario 2 Results: Variable Worker Location Relative to 

the Release Point...................................................................... 47

7.2.1.3 Summary of Scenario 1 and Scenario 2 Results........................ 49

8.0 Whicker and Moxley Study..................................................................................................... 49

8.1 Description of the Study.............................................................................................. 49

8.2 Evaluation of the Whicker and Moxley Study Data...................................................... 51

8.2.1 Statistical Evaluation of the Data.................................................................. 52

8.2.1.1 Scenario 1 Results: Colocated Worker and Release Point ........ 52

8.2.1.2 Scenario 2 Results: Variable Worker Location Relative to 

the Release Point...................................................................... 53

8.2.1.3 Summary of Scenario 1 and Scenario 2 Results........................ 54

9.0 Discussion ............................................................................................................................. 54

9.1 Combined Ratio Distributions ..................................................................................... 54

9.1.1 Evaluations for Scenario 1 ........................................................................... 55

9.1.2 Evaluations for Scenario 2 ........................................................................... 57

9.2 Other Observations .................................................................................................... 58

9.2.1 Ventilation Rate............................................................................................ 58

9.2.2 Room Complexity......................................................................................... 61

10.0 Conclusions ........................................................................................................................... 61

11.0 Anticipated Use of the BZ:GA Ratio Data............................................................................... 61

References ........................................................................................................................................ 65

ATTACHMENT A GRAPHS FROM GONZALES ET AL. ............................................................. 67

ATTACHMENT B REGION AREA FRACTIONS FROM ORAUT (2019c).................................... 77

LIST OF TABLES

TABLE TITLE PAGE

3-1 Room sizes for the evaluated studies..................................................................................... 13

3-2 Summary of the particle size distributions for each study ....................................................... 13

4-1 Defining air concentration regions for iso-concentration graphs ............................................. 21

4-2 Adjusted air concentration ranges for probability calculations ................................................ 22

4-3 Gonzales et al. (1974) figures used to evaluate each ventilation scheme............................... 25

4-4 Summary of the Scenario 1 BZ:GA ratio distributions for Gonzales et al. (1974).................... 29

4-5 Summary of the Scenario 2 BZ:GA ratio distributions for Gonzales et al. (1974).................... 29

5-1 Summary of Charuau (1987) BZ:GA ratio distributions for Scenario 1.................................... 35

5-2 Summary of Charuau (1987) BZ:GA ratio distributions for Scenario 2.................................... 35

5-3 Summary of the combined BZ:GA ratio distributions for aerosols........................................... 37

7-1 Average BDs by release location ........................................................................................... 45

7-2 Summary of the BZ:GA ratio distributions for Scripsick et al. (1979a, 1979b)......................... 49

8-1 9-min average air concentrations by release location............................................................. 52

8-2 Summary of the BZ:GA ratio distributions for Whicker and Moxley (2001) ............................. 54

9-1 Summary of BZ:GA ratio distributions for Scenario 1 ............................................................. 55

9-2 Summary of BZ:GA ratio distributions when workroom is open in the middle ......................... 56

9-3 Summary of BZ:GA ratio distributions when workroom has obstructions in the middle........... 56
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9-4 Summary of BZ:GA ratio distributions for Scenario 2 ............................................................. 57

9-5 Summary of uncombined BZ:GA ratio distributions for Scenario 1 ......................................... 59

9-6 Summary of uncombined BZ:GA ratio distributions for Scenario 2 ......................................... 60

10-1 Summary of the combined BZ:GA ratio distributions .............................................................. 61

LIST OF FIGURES

FIGURE TITLE PAGE

4-1 Coordinate system used for positioning sampling probe ........................................................ 16

4-2 Example iso-concentration graph from Gonzales et al. (1974) ............................................... 17

4-3 Sampler exclusion area for hypothetical GA air sampler locations for Scenario B.................. 19

4-4 Illustration of area fraction calculations................................................................................... 21

4-5 Scatter plot of all 36 results from Gonzales et al. (1974) ........................................................ 23

4-6 Scatter plot of Scenario 1 results from Gonzales et al. (1974)................................................ 24

4-7 Scatter plot of Scenario 2 results from Gonzales et al. (1974)................................................ 24

4-8 Model for Scenario 1 with 0° airflow direction......................................................................... 26

4-9 Model for Scenario 1 with 90° airflow direction....................................................................... 26

4-10 Model for Scenario 1 with 180° airflow direction..................................................................... 27

4-11 Model for Scenario 2 with 0° airflow direction......................................................................... 27

4-12 Model for Scenario 2 with 90° airflow direction....................................................................... 28

4-13 Model for Scenario 2 with 180° airflow direction..................................................................... 28

5-1 Plutonium laboratory and transfer study results...................................................................... 30

5-2 Model for Scenario 1 for gas .................................................................................................. 31

5-3 Model for Scenario 1 for 2.3-μm aerosols............................................................................... 32

5-4 Model for Scenario 1 for 10.5-μm aerosols............................................................................. 32

5-5 Model for Scenario 2 for gas .................................................................................................. 33

5-6 Model for Scenario 2 for 2.3-μm aerosols............................................................................... 34

5-7 Model for Scenario 2 for 10.5-μm aerosols............................................................................. 34

5-8 Combined model for Scenario 1 for aerosols.......................................................................... 36

5-9 Combined model for Scenario 2 for aerosols.......................................................................... 36

6-1 Containment enclosure floorplan............................................................................................ 38

6-2 Exterior view of containment enclosure.................................................................................. 38

6-3 Interior view of workroom for containment enclosure.............................................................. 39

6-4 Relative performance between the BZ (PAS) and GA (SAS) air samplers ............................. 40

6-5 Normalized cumulative response functions for SAS data by SAS location ............................. 40

6-6 Normalized cumulative response functions for PAS versus SAS data.................................... 41

6-7 Model for Scenario 2..............................................................................................................42

7-1 Workroom floorplan with ventilation system components and air sampler locations ............... 43

7-2 Numbered release locations used in the study....................................................................... 43

7-3 Model for Scenario 1..............................................................................................................47

7-4 Intermediate model for Scenario 2 ......................................................................................... 48

7-5 Model for Scenario 2..............................................................................................................49

8-1 C-Lab floorplan with air sampler locations and release locations depicted ............................. 50

8-2 Model for Scenario 1..............................................................................................................53

8-3 Model for Scenario 2..............................................................................................................54

9-1 Combined model for all Scenario 1 models ............................................................................ 55

9-2 Combined model for Scenario 1 models that were for open workspaces................................ 56

9-3 Combined model for all Scenario 1 models that were for obstructed work spaces ................. 57

9-4 Combined model for all Scenario 2 models ............................................................................ 58

9-5 Scatter plot of uncombined BZ:GA ratio distributions for Scenario 1 ...................................... 59

9-6 Scatter plot of uncombined BZ:GA ratio distributions for Scenario 2 ...................................... 60
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A-1 Graphs of iso-concentration curves for a 0° angle air direction and 6 AC/hr........................... 69

A-2 Graphs of iso-concentration curves for a 0° angle air direction and 9 AC/hr........................... 70

A-3 Graphs of iso-concentration curves for a 0° angle air direction and 12 AC/hr......................... 71

A-4 Graphs of iso-concentration curves for a 90° angle air direction and 6 AC/hr......................... 72

A-5 Graphs of iso-concentration curves for a 90° angle air direction and 9 AC/hr......................... 73

A-6 Graphs of iso-concentration curves for a 90° angle air direction and 12 AC/hr....................... 74

A-7 Graphs of iso-concentration curves for a 180° angle air direction and 6 AC/hr....................... 75

A-8 Graphs of iso-concentration curves for a 180° angle air direction and 12 AC/hr..................... 76

B-1 Calculated region area fractions for Scenario 1A ................................................................... 78

B-2 Calculated region area fractions for Scenario 1B ................................................................... 79

B-3 Calculated region area fractions for Scenario 2A ................................................................... 80

B-4 Calculated region area fractions for Scenario 2B ................................................................... 81
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ACRONYMS AND ABBREVIATIONS 

AC air change

AMAD activity median aerodynamic diameter

AWE atomic weapons employer

BD breathing zone dilution factor

BZ breathing zone

CAM continuous air monitor

CEA Commissariat à l’Énergie Atomique

cfm cubic feet per minute

cm centimeter

CMAD count median aerodynamic diameter

DOE U.S. Department of Energy

ft foot

g gram

GA general area

GM geometric mean

GSD geometric standard deviation

hr hour

in. inch

kg kilogram

LANL Los Alamos National Laboratory

LPC laser particle counter

m meter

min minute

mm millimeter

MMAD mass median aerodynamic diameter

NIOSH National Institute for Occupational Safety and Health

ORAU Oak Ridge Associated Universities

PAS personal air sampler

ROS regression on order statistics 

s second

SAS stationary air sampler

SRDB Ref ID Site Research Database Reference Identification (number)

SRS Savannah River Site

μCi microcurie

μg microgram

μm micrometer
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1.0 PURPOSE AND SCOPE

The purpose of this report is to evaluate the relationship between the general area (GA) and breathing 

zone (BZ) air concentrations for small workrooms and to determine if adjustments to the GA air 

concentrations are necessary to make them equivalent to the BZ air concentrations in a small 

workroom. Therefore, the scope of the report is limited to small workrooms. Air concentrations that 

are representative of the air breathed by the workers (i.e., BZ air concentrations) are needed to 

assess inhalation intakes of those workers when bioassay data are not available. Application of the 

BZ:GA ratio information within this report should be justified on a case-by-case basis, as discussed in 

Sections 2.0 and 11.0. 

In this report, the term “workroom” refers to a work location having a single discernable airspace. 

Similarly, the term “test room” refers to a mockup of a real or hypothetical work location having a 

single discernable airspace. As used in this report, the term “significant” means “practically 

significant” as opposed to “statistically significant.” In other words, in this report “significant” means 

that the difference (effect size) is large enough to influence how a parameter is used or treated in 

practice. In addition, the relationships between BZ and GA air concentrations were evaluated in terms 

of BZ:GA air concentration ratios, which are abbreviated as BZ:GA ratios throughout the remainder of 

this report.

2.0 INTRODUCTION

In any workroom where there is complete air mixing, the concentration of respirable airborne 

radioactive material would be homogeneous throughout the airspace. In such a room, the air 

concentration measured at any location within the room would be the same, and there would be no 

significant difference between the BZ air concentration and the GA air concentration. However, 

complete air mixing is rarely possible or practical, for a number of reasons, which results in 

differences between the air concentrations measured at various locations throughout the room. When 

the mixing of the air in the room becomes less and less complete, the variability between air 

concentrations throughout the room increases, resulting in a distribution of BZ:GA ratios. As mixing 

becomes less complete, the central tendency of this distribution (the median) can shift away from 1 

and the spread of the distribution (the geometric standard deviation [GSD]) can increase. When the 

median of the BZ:GA ratio distribution becomes significantly greater than 1 or the GSD becomes 

large, the GA air concentration should be adjusted to account for the increased uncertainty in the BZ 

air concentration. 

As indicated in Section 1.0, the use of the BZ:GA ratio information in this report is intended to be 

justified on a case-by-case basis. Because there are so many potential parameters and scenarios 

that could have a significant effect on the BZ and GA air concentrations for a given workroom, it is 

important for the user of this BZ:GA ratio information to justify its use for their specific application.

The subsections below identify the key parameters that were considered when evaluating the 

relationship between the GA and BZ air concentrations for this report. Those parameters could be 

grouped into two groups: (1) ones that affect the level of mixing of an aerosol and (2) ones that only 

affect the BZ:GA ratio. Section 3.0 and the sections discussing the evaluated studies provide the 

details about how these parameters were addressed for the purposes of this report.

2.1 PARAMETERS AFFECTING LEVEL OF MIXING

The parameters that affect the level of mixing are important because less mixing tends to lead to 

larger air concentration gradients, which have a significant and direct effect on BZ:GA ratios and the 

GA air concentrations in a workroom. When looking to apply BZ:GA ratios to GA air concentrations to 

make them equivalent to BZ air concentrations, the analysis should consider the parameters that 
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affected the level of mixing in both the source of the BZ:GA ratios and for the room where the GA air 

samples were collected. Ideally, the parameters affecting the level of mixing for the source of the 

BZ:GA ratios would be comparable to the location where the GA air samples were collected. 

Unfortunately, that is often impractical or impossible, unless the BZ:GA ratios were based on the 

same room and conditions that the GA air samples were collected in. However, using BZ:GA ratios 

that have a basis that encompasses the parameters for the room where the GA air samples were 

collected is one of the next best options. Proper determination and application of BZ:GA ratios 

supports good decision-making about potential inhalation intakes of workers and associated steps to 

protect worker health.

The level of mixing of an aerosol within a workroom is dependent on a large number of parameters. 

However, the following four parameters tend to affect the level of mixing the most: (1) the size of the 

room, (2) the particle size distribution of the aerosol, (3) the ventilation rate, and (4) room complexity. 

The following subsections address each of these potentially significant parameters in more detail. 

2.1.1 Size of the Room

Total workroom or air space volume is a key parameter that usually influences how much an aerosol 

can or cannot be dispersed. However, with the exception of rooms where elevated releases above 

the typical breathing zone can occur, a room’s height is usually less of a factor influencing the aerosol 

concentration than its other dimensions, because of gravitational settling. Therefore, in most 

instances room sizes can be compared in terms of area for determining applicability of the BZ:GA 

ratio information in this report to a specific room. For the purposes of this report, elevated releases 

are considered to be above the typical BZ elevations and can include releases originating at a lower 

elevation that are propelled above the typical BZ elevations (e.g., jet releases, over-pressurization 

releases, aerosol plumes lofted by heat source etc.). 

2.1.2 Particle Size Distribution of the Aerosol

Because only respirable size particles (i.e., those particles with aerodynamic diameters smaller than 

about 20 μm [ICRP 2015]) contribute to inhalation intakes, only the respirable fraction of an aerosol is 

of interest for assessing the inhalation intakes of workers. Therefore, the ideal air sample 

measurements for assessing a worker’s inhalation exposure would discriminate against collecting 

nonrespirable particles. However, most routine air sampling systems used at atomic weapons 

employer (AWE) and U.S. Department of Energy (DOE) sites (including the DOE predecessor 

agencies) did not include particle sizing or particle discrimination devices to eliminate the 

nonrespirable particles from being collected on the air sample. Because of that, most air samples 

collected at AWE and DOE sites included both the respirable and nonrespirable particles that were 

present. The presence of larger nonrespirable particles on any air sample being used to estimate a 

worker’s inhalation intake, whether it is a BZ or GA air sample, could result in an unreasonable 

overestimate of the worker’s intake. 

In addition, air samples collected closer to the release location are more likely to collect larger 

nonrespirable particles, because the larger particles do not travel with air currents as far as the 

smaller respirable particles. One of the major causes of that is the terminal settling velocity for 

different size particles because the terminal settling velocity increases rapidly with particle size. For 

particles of the same composition, the terminal settling velocity increases proportionally to the square 

of the particle diameter (Hinds 1982, p. 35). Based on that, a 10-μm diameter particle has a terminal 

settling velocity that is 100 times faster than a 1-μm diameter particle. A nonrespirable 100-μm 

particle would settle 10,000 times faster than a 1-μm diameter particle. Even though there can be a 

number of potential causes or contributing causes to the discrepancies between BZ and GA air 

concentrations, the presence of nonrespirable particles is often a cause of discrepancy between BZ 

and GA air concentrations. 
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2.1.3 Ventilation Rate

The ventilation rate in terms of air changes (ACs) per unit time, usually in units of AC/hr, is a removal 

constant for the aerosol within a workroom. This removal constant is directly related to the depletion 

of the aerosol from an acute, constant, or variable release of aerosol and can be used to estimate the 

average air concentration at different points in time when the release quantity (instantaneous/puff 

releases) or release rate (longer term releases) along with several other parameters are known. This 

can be done using linear first-order kinetics equations as described in Skrable (1974). However, 

those kinetics calculations are based on a simple model that does not account for factors encountered 

in more complex rooms (e.g., air streaming, dead air spaces, eddy currents, etc.). 

2.1.4 Room Complexity

Factors contributing to the complexity of a workroom include room layout, obstructions, heat sources, 

room ventilation inlet and outlet locations, local exhaust locations, and general flow directions. All of 

these affect the airflow patterns and level of mixing within a room. These things tend to cause air 

streaming, dead air spaces, eddy currents, etc. within a room, which result in larger air concentration 

gradients. The more complex a room is, the more likely one is to encounter larger air concentration 

gradients. 

In combination with air velocity, the direction of the incoming and outgoing air can have a significant 

effect on the level of mixing. In some situations, this can enhance the level of mixing; in other 

situations this can cause extreme air concentration gradients within a workroom. It should be noted 

that ventilation systems designed to minimize worker exposures often cause the largest air 

concentration gradients and vice versa. In most instances, only the flow rates are typically known 

when assessing past events and information about the room air vent sizes and orientations 

(directions) are often unknown. Therefore, it is often impossible to assess how these two aspects of 

the ventilation would have affected the BZ and GA air concentrations during past events. 

More recently, much more sophisticated computational fluid dynamics models have been used to 

model aerosol releases and the resulting air concentrations throughout a workroom over a period of 

interest. The computational fluid dynamics models can provide air concentration estimates in three 

dimensions. However, those more sophisticated models require a detailed knowledge of the room 

being evaluated. When reconstructing worker exposures that occurred in the past, many of the 

needed details on the rooms where exposures occurred are unknown, making it impossible to 

adequately model those areas to determine what the air concentration gradients were. Therefore, the 

use of BZ:GA ratios as a means for accounting for the differences between BZ and GA air 

concentrations is one of the next best options.

2.2 PARAMETERS ONLY AFFECTING BZ:GA RATIOS

The parameters discussed in this section do not have any effect on the level of mixing but can have a 

significant effect on the BZ:GA ratio distribution. As discussed in the following subsections, two 

parameters that could have the most impact on the BZ and GA samples and resulting BZ:GA ratio 

distribution are sampler and release locations and low number concentrations of dominant aerosol 

particles.

In addition to the parameters discussed in the sections below, there are numerous other parameters 

and factors that can affect the differences between the measured BZ and GA air concentrations, but 

most of them have to do with issues or errors associated with the collection and analysis of the 

individual air samples (e.g., not accounting for natural radioactivity, self-shielding of activity on a 

sample, sample contamination, sample flow rates, etc.). The subject of sample collection, sample 

analysis, and their potential measurement errors is a major subject and beyond the scope of this 
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report. Therefore, it is assumed that the user of this report is already familiar with that subject and no 

further details are provided here. When details about the collection and analysis of individual samples 

are available, those parameters should also be considered when evaluating the relationship between 

the GA and BZ air concentrations. However, in documented air sampling studies, such details about 

individual samples are usually not included in the reports on the studies. When those details are 

unavailable, it should be reasonable to assume that there were no significant and unresolved sample 

collection or analysis issues or errors with the reported air sample data.

2.2.1 Sampler and Release Locations

When mixing is not complete, which is often the case, the following three spatial parameters and their 

locations, in relation to each other and in relation to the location of workroom ventilation inlets and 

outlets and obstructions, can have a significant effect on the BZ:GA ratio distribution: (1) the location 

of the worker (i.e., the BZ location), (2) the GA air sampler location, and (3) the location of the release 

point for the radioactive material. Therefore, when evaluating the differences between BZ and GA air 

concentrations, consideration should be given to where these three things were located in relation to 

each other. It is also important to understand any work activities that may cause the worker to 

position their direct breathing zone much closer to a source than their BZ sampler, for example, within 

an equipment enclosure or local ventilation shroud during an inspection or maintenance operation. 

2.2.2 Low Number Concentrations of Dominant Aerosol Particles

Low numbers of airborne radioactive particles in a workroom are normally a good thing and a 

desirable condition for the workplace atmosphere. However, when those low-in-number radioactive 

particles have a relatively high specific activity and radiotoxicity (i.e., what will be referred to for the 

purposes of this report as “dominant particles”), that condition can become very problematic and have 

a very adverse effect on the ability to collect meaningful and reproducible air samples. When the 

numbers of the radioactive particles are too low, both BZ and GA air sampling becomes a stochastic 

process versus a deterministic process because there just are not enough radioactive particles to go 

around (Scott, Hoover, and Newton 1997; Scott and Fencl 1999; Scott et al. 2001; Aden and Scott 

2003). In a discussion about personal air samplers (PASs), Strong (1988) indicated that “the personal 

air sampler behaves as a statistical sampling device when operated in an environment having only a 

few to a few tens of particles per m3

.” Because this normally is not a significant issue of concern for 

lower specific activity and less radiotoxic particles, the following discussions are only relevant to 

situations when the low-in-number radioactive particles have a relatively high specific activity and 

radiotoxicity.

Discussions of the dominant particle phenomena have predominately been found in the reports for air 

sampling studies in the United Kingdom during the 1960s, such as in Sherwood (1966), and Lister 

(1967), and later in Jones et al. (1983). A few more recent references to these phenomena have 

been found in studies in the United States. Munyon and Lee (2002), a study evaluated for this report, 

includes a brief discussion on the “... dominant or single particle phenomena....” Other reports from 

the Lovelace Respiratory Research Institute address the difficulties of assessing the intakes and 

internal doses from the inhalation of dominant particles, which are referred to as the stochastic 

exposure paradigm and stochastic intake paradigm in those reports (Scott and Fencl 1999; Scott et al. 

2001; Aden and Scott 2003). The available literature also indicates that dominant particles have a 

relatively high specific activity and are relatively few in number in comparison with the other particles 

in the radioactive aerosol being dispersed (Sherwood 1966; Lister 1967; Scott et al. 2001; Munyon 

and Lee 2002; Aden and Scott 2003). Fortunately, there is nothing to indicate the dominant particle 

phenomena was widespread, and most of the known radiological workrooms that had air sampling 

issues attributable to the presence of dominant particles were in the United Kingdom. 
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The presence of dominant particles can normally only be confirmed by autoradiograph analysis of the 

air samples, which is not a routine type of analysis. At best, autoradiographs are sometimes 

performed as part of a special air sampling study. Therefore, it is unlikely that any dominant particle 

information will be available for a given workroom. 

The presence of dominant particles makes the following two scenarios likely, neither of which include 

an air sample that is representative of the air that was inhaled by the worker. Further, the more the 

low-in-number particles are dispersed from their point of origin in a workroom, the farther apart they 

are and the more likely these two scenarios become. An indication that these two scenarios might

have occurred at a facility is when there is a lack of correlation between the air sample results and the 

bioassay results from that facility, which was one of the observations reported in Jones et al. (1983).

1. A dominant particle was collected on the air sample when the worker did not inhale one (i.e., 

no intake occurred). When air sample results are being used to estimate worker intakes, this 

scenario results in significant intakes being assessed when none actually occurred. For 

particles of the same material, radionuclide composition, and specific activity, the scale of that 

overestimate is proportional to the difference in the volumes of the dominant particles. 

Therefore, the overestimation can increase dramatically as the size of the dominant particle 

increases. For example, a single 10-μm diameter dominant particle on an air sample will yield 

an intake overestimate that is 1,000 times greater than the overestimated intake from a single 

1-μm diameter dominant particle. 

2. The worker inhales a dominant particle but one was not collected on the air sample. When 

this scenario occurs, the air sample fails to detect a potentially significant intake and any 

intakes based on that air sample result are underestimated. 

Because of these two scenarios and because of the stochastic nature of sampling airborne 

radioactive particles that are low in number, air sample data from workrooms with dominant particles 

are very unreliable. If an air sample result from an area with dominant particles is needed to assess 

worker exposures, Scott and Fencl (1999) indicates that intake distributions can and should be 

calculated to account for the stochastic nature associated with sampling and inhaling those particles. 

However, based on that guidance, one would need to know many details about the dominant particles 

in a given room to perform the intake distribution calculations, and much of that information is often 

unavailable for performing retrospective dose reconstructions. Therefore, the Oak Ridge Associated 

Universities (ORAU) Team does not recommend using air sample data from workrooms known to 

have dominant particles for developing BZ:GA ratios. 

3.0 STUDIES EVALUATED

This report evaluates the air sample data from the five air sampling studies discussed in Sections 4.0

through 8.0. The rooms in each of those studies are considered to be small rooms. The room size 

information for the evaluated studies is provided in Table 3-1. The room sizes in the evaluated 

studies ranged from 17.6 m2 to 105 m2

 (190 ft2 to 1,130 ft2). 

As the workroom size increases beyond the sizes in Table 3-1, there is a point where it will no longer 

be appropriate to use the BZ:GA ratio information in this report. Conversely, as the workroom size 

decreases below the sizes in Table 3-1, there is likely a point where the BZ and GA air concentrations 

are equivalent and no adjustment to the GA air concentration is needed. It is beyond the scope of this 

report to determine where those points are. The more a workroom size exceeds the room sizes in the 

evaluated studies, the more difficult it will be to conclude that the BZ:GA ratio information in this report 

is applicable to that room. 
Document No. ORAUT-RPRT-0097 Revision No. 00 Effective Date: 03/29/2021 Page 13 of 81

Table 3-1. Room sizes for the evaluated studies.

Study

Room dimensionsa

(m, ft)

Room area

(m2, ft2)

Room volumeb

(m3, ft3)

Gonzales et al. (1974) 6.1 × 6.1 × 2.4,

20 × 20 × 8

37.2,

400

89.3,

3,200

Charuau (1987) 15 × 7 × 4.5,

49 × 23 × 15

105.0,

1,130

472.5,

16,686

Munyon and Lee (2002) 4.9 × 3.6 × 2.4,

16 × 12 × 8

17.6,

190

42.3,

1,495

Scripsick et al. (1979b) 9.0 × 6.3 × 4.1,

30 × 21 × 13

56.7,

610

232.5,

8,211

Whicker and Moxley (2001)c 6 × 4 × 3,

20 × 13 × 10

24.0,

258

72.0,

2,542

a. The dimensions are provided in terms of length × width × height.

b. This room volume is the overall room volume, and does not account for large obstructions in the 

room such as equipment and gloveboxes. Therefore, it might not represent the actual volume of the 

airspace.

c. Room dimensions for the Whicker and Moxley (2001) study were obtained from Whicker, Rodgers, 

and Moxley (2003).

In addition, because only respirable size particles contribute to inhalation intakes, only studies with 

documented aerosol sizes that are considered respirable were evaluated for this report. The 

presence of larger nonrespirable particles on any air sample being used to estimate a worker’s intake, 

whether it is a BZ or GA air sample, would result in a significant overestimate of the worker’s intake. 

Air samples collected closer to the release location are more likely to collect larger nonrespirable 

particles, because those particles do not travel as far as the smaller respirable particles. Even though 

there can be a number of potential causes or contributing causes to the discrepancies between BZ 

and GA air concentrations, the presence of nonrespirable particles is also often the cause of the 

discrepancies between BZ and GA air concentrations, which would influence the BZ:GA ratios. 

Therefore, the inclusion of studies with air sample data that potentially included particles of sizes 

much larger than the respirable size range could generate BZ:GA ratios that would cause an 

unreasonable overestimate of the workers’ intakes. Table 3-2 summarizes the particle size 

distributions associated with each of the evaluated studies.

Table 3-2. Summary of the particle size distributions for each study.a

Study Particle size distributions Reported units

Gonzales et al. (1974) GM 0.64 to 0.86 μm,

GSD 1.48 to 1.49

MMAD

Charuau (1987) Gas, 2.3 μm, and 10.5 μm MMAD

Munyon and Lee (2002) GM 3.0 μm, GSD 2.4 AMAD

Scripsick et al. (1979a, 1979b) GM 0.35 μm, GSD 2.1 CMADb

Whicker and Moxley (2001) GM 0.3 μm, GSD <2 Not provided

a. AMAD = activity median aerodynamic diameter; CMAD = count median aerodynamic diameter; 

GM = geometric mean; MMAD = mass median aerodynamic diameter.

b. Based on the Hatch-Choate conversion equations in Hinds (1982), a CMAD of 0.35 μm is 

equivalent to a MMAD of 1.83 μm, and shares the same GSD of 2.1.

With the exception of Whicker and Moxley (2001), all units for the particle sizes were reported in 

terms of aerodynamic diameter, which is an equivalent diameter versus an actual physical diameter. 

Because most aerosol particles are not spherical, particle diameters are typically reported in 

equivalent diameters, based on one or more properties of the particle. Aerodynamic diameter is 

defined as the diameter of a unit density (ρp = 1 g/cm3

) sphere that has the same settling velocity as 

the particle (Hinds 1982). Particles with the same aerodynamic diameter are aerodynamically 

indistinguishable from other particles of different size, shape, and density (Hinds 1982). Note that the 

particle size units were not provided for the Whicker and Moxley (2001) study, and the study does not

indicate how the particle size distribution was measured. Given that the aerosol was a nontoxic oil 
Document No. ORAUT-RPRT-0097 Revision No. 00 Effective Date: 03/29/2021 Page 14 of 81

(dioctyl sebacate) (Whicker and Moxley 2001), the particles were likely close to being spherical in 

shape. That combined with the density of dioctyl sebacate, which is 0.9 g/cm3

, would indicate that the 

reported particle size in Whicker and Moxley (2001) was likely equivalent to an aerodynamic diameter. 

As indicated Section 2.2.2, air sample data from rooms with dominant particles was very unreliable 

and should not be used to assess worker exposures or for developing BZ:GA ratios. Because the 

dominant particle issue is only applicable to radioactive particles, this issue is not applicable to studies 

that only involved nonradioactive aerosols. Of the five evaluated studies, Munyon and Lee (2002) 

was the only one that involved radioactive aerosols. It was therefore the only evaluated study 

potentially affected by the dominant particle issue. However, Munyon and Lee (2002, p. 7) indicated 

that autoradiographs were performed on some of the air samples, and that “none of them exhibited a 

dominant or single particle phenomena.” Therefore, dominant particles were not considered to be an 

issue for any of the five studies that were evaluated for this report. 

The approaches taken for the evaluations in this report do not rely on a specific definition for the 

location of the BZ. With the exception of the Munyon and Lee (2002) study, the BZ locations were 

designated by the authors of this report, since no actual workers were present during the other 

evaluated studies. In Munyon and Lee, the BZ sampling locations were the lapel samplers on the 

workers who were present during the radiological work activity. In the broadest definition, the BZ can 

be defined as any location within a volume of air that has a concentration that is representative of the 

air being inhaled by a worker. Usually, the BZ is limited to the air volume that is in close proximity to a 

worker’s head or face. For the studies with no workers present, the BZ locations were designated 

based on sampling height and potential worker locations with air sample data. More information 

regarding the designation of BZ locations is provided in the following paragraphs and in the sections 

for each specific study.

Because the location of the worker, GA air sampler, and release point are often unknown and can 

have a significant effect on the BZ:GA ratio distributions, a method was devised to eliminate the need 

to know those exact locations. It was decided that there were only two main worker location 

scenarios that needed to be evaluated, which were in terms of where the worker was in relation to the 

release point. For those scenarios, the possible GA sampler locations could be anywhere in the room 

but were usually limited to the GA sampling locations in the evaluated studies. 

Worker Location Scenarios

• Scenario 1. Assumes the worker (BZ location) was always located at the same X,Y

coordinates in the room as the release point (i.e., colocated worker and release point).

• Scenario 2. Assumes the worker (BZ location) was not necessarily located at the same X,Y

coordinates in the room as the release point (i.e., variable worker location relative to the 

release point).

Scenario 1 represents what is typically the worst-case scenario because it normally yields the highest 

BZ:GA ratios. In most instances, this scenario only applies to acute exposures because the workers 

often move around and are not always located at the release point.

Scenario 2 was created because most radiological processing areas have multiple workstations and 

multiple workers moving around in each room rather than one worker being at a single stationary 

location for an entire work shift. For Scenario 2, it was assumed that the potential BZ locations had 

the same probability of being anywhere in the room.

Evaluations based on Scenarios 1 and 2 represent a wide variety of the possible BZ and GA location 

combinations for these two scenarios, thereby eliminating the need to know the worker location in 
Document No. ORAUT-RPRT-0097 Revision No. 00 Effective Date: 03/29/2021 Page 15 of 81

relation to the GA location. To adjust the site-specific GA air concentrations to make them equivalent 

to BZ air concentrations, the analysis need only decide which of the two scenarios best represents the 

worker’s location relative to the release point for a given exposure scenario. 

When possible, the two BZ location scenarios above were evaluated for each study. The Munyon and 

Lee (2002) study was the only one in which both scenarios could not be evaluated because that study 

was based on a real work activity and personal air samples from real workers versus being based on 

a simulated study.

4.0 GONZALES ET AL. STUDY 

Gonzales et al. (1974), Relationship Between Air Sampling Data from Glove Box Work Areas and 

Inhalation Risk to the Worker, was performed by Los Alamos National Laboratory (LANL). This study 

was an experiment to evaluate aerosol dispersal patterns from a simulated glovebox leak in a mockup 

of a plutonium work area.

4.1 EXPERIMENT DESCRIPTION

In Gonzales et al. (1974), plutonium releases were simulated using a nonradioactive tracer aerosol in 

a 20- by 20- by 8-ft tall (6.10- by 6.10- by 2.4-m tall) test room with a single glovebox at one end of the 

room. To produce submicron tracer aerosol, an air-operated dioctyl phthalate aerosol generator with 

a single jet impactor was placed inside the glovebox. The generated aerosol particle sizes ranged 

from a mass median aerodynamic diameter (MMAD) of 0.640 to 0.86 μm, with a GSD of 1.48 to 1.49. 

The release point was created by covering one glove port with an aluminum plate with a 1/8-in. 

(3.2-mm) hole drilled into the center, allowing the aerosol to escape from the glovebox into the room 

(Gonzales et al).

A three-dimensional Cartesian coordinate system was established to define air sampling locations 

relative to the aerosol release point (i.e., the aerosol release point is the point of origin for the 

coordinate system). The test room and the coordinate system for the experiment are depicted in 

Figure 4-1. In Figure 4-1, the three axes are depicted as “horizontal (H),” “longitudinal (L),” and 

“vertical (V)” axes, which are equivalent to the more commonly used X, Y, and Z axes. For 

descriptive purposes, when facing the glovebox, the wall behind it is considered to be the back wall. 

Therefore, the glovebox is considered to be in the back of the room and against the back wall. Based 

on the scale in Figure 4-1, the aerosol release point was approximately 3.75 ft (1.143 m) above the 

floor and 1.5 ft (0.457 m) from the back wall, because the glovebox has a longitudinal depth of 

approximately 1.5 ft (0.457 m) (ORAUT 2019a). Room aerosol concentrations were measured with a 

light-scattering photometer at several locations during each test to determine the aerosol dispersal 

patterns from a given test scheme (Gonzales et al. 1974). It should also be noted that nothing was 

placed in the room to simulate any obstructions, such as those that would be caused by workers or 

equipment in the room (i.e., the room was empty except for the glovebox and air sampler).
Document No. ORAUT-RPRT-0097 Revision No. 00 Effective Date: 03/29/2021 Page 16 of 81

Figure 4-1. Coordinate system used for positioning sampling 

probe (Gonzales et al. 1974, p. 6). 

The test schemes were defined under the following ventilation conditions: 6, 9, and 12 room air 

changes per hour (AC/hr) for each of three different airflow directions (0°, 90°, and 180°) relative to 

the aerosol leak flow direction. For the 0° orientation, room air entered from behind the glovebox and 

flowed in the same direction as the aerosol leak. For the 90° orientation, room air entered from one 

side of the room perpendicular to the leak flow direction. For the 180° orientation, room air entered 

from the wall opposite the glovebox and flowed in the opposite direction from the leak flow. The room 

was designed to have room air enter and exit the room via inlet and outlet plenums. The plenums 

covered the entire width of each wall. From the inlet plenum, the entering air was uniformly 

distributed across the entire wall through 1/8-in. (3.2-mm) holes spaced 1 in. (2.54 cm) apart. The 

outlet plenum was similarly constructed (Gonzales et al. 1974).

4.2 REPORTED RESULTS AND CONCLUSIONS

Approximately 640 air concentration measurements were taken for this study, and those 

measurements were used to generate 44 graphs depicting iso-concentration curves, but only 18 of 

those were presented in Gonzales et al. (1974). However, Gonzales et al. indicated that the 18

selected graphs were representative of data and conclusions drawn from all of the graphs. For the 

purposes of this report, the 18 graphs in Figures 2 through 19 of Gonzales et al. have been 

reorganized and provided in Attachment A as Figures A-1 through A-8. The concentrations in the isoconcentration graphs are presented as a percentage of the air concentrations measured at the 

aerosol release point.

In relation to Figures 2 through 19 from Gonzales et al. (1974), it should be noted that those figures 

do not depict the entire area of the test room depicted in Figure 4-1 above. The dimensions of the 

test room were 20- by 20-ft (6.10- by 6.10-m), but Figures 2 through 19 only depict a 16- by 14-ft 

(4.88- by 4.27-m) area in that room. In addition, Figures 2 through 19 only provide iso-concentration 

data for a 10- by 14-ft (3.05- by 4.27-m) area (the monitored area) in the depicted area. To illustrate 

that, Figure 4-2 is an example of one of the iso-concentration graphs, specifically Figure 4 from 

Gonzales et al., with an added red box to depict the monitored area. Figure 4-2 contains another 

added notation to point out the release location for all of the tests.

The Discussion Section in Gonzales et al. (1974, p. 13) reported that “under all conditions of 

ventilation, aerosol concentrations ranging up to 4.0% occurred in the probable breathing zones”, 

which were defined as an elevation of leak-level to 1 ft (0.30 m) above leak-level (i.e., approximately 
Document No. ORAUT-RPRT-0097 Revision No. 00 Effective Date: 03/29/2021 Page 17 of 81

3.75 to 4.75 ft [1.143 to 1.448 m] above the floor [ORAUT 2019a]) and distances 4 to 10 ft (1.22 to 

3.05 m) from the leak source. However, Figures 4 and 17 in Gonzales et al., which are redisplayed in 

Attachment A (see Figures A-1 and A-7), contradict that statement, because the 4.1% to 10% aerosol 

concentration range extends into the longitudinal distance range of 4 to 10 ft (1.22 to 3.05 m). 

Contrary to what was indicated in Gonzales et al., the ORAU Team does not consider the leak-level to 

be a good representation of a probable BZ elevation in a process area, because the worker would 

have needed to be bent over or sitting for the majority of their time in the process area. The ORAU 

Team considers the 1- and 2-ft above leak-level elevations to be better representations of the 

probable BZ elevations, which are equivalent to approximately 4.75 and 5.75 ft (1.448 and 1.753 m) 

above the floor. All of the available iso-concentration graphs in Gonzales et al. are redisplayed in 

Attachment A. Because the graphs indicate that the aerosol concentrations decline as the elevation 

in the test room increases, it can also be concluded that the aerosol concentrations for the entire room 

were 4.0% or less for elevations of 1-ft above leak-level and higher. That is equivalent to 4.75 ft 

(1.448 m) above the floor and higher, and it represents the upper 3.25 ft (1.143 m) of the entire room 

volume. 

Figure 4-2. Example iso-concentration graph from Gonzales 

et al. (1974, p. 9).
Document No. ORAUT-RPRT-0097 Revision No. 00 Effective Date: 03/29/2021 Page 18 of 81

Gonzales et al. (1974) also reported that the BZ air concentrations ranged from 0.11% to 10.0%, that 

the fixed room air sampler concentrations ranged from 0.04% to 0.6%, and that these data 

represented a maximum potential ratio of BZ to fixed room air concentrations of 250:1 (10.0% to 

0.04%). However, the reported BZ:GA ratio of 250:1 is highly unlikely for the following reasons:

1. For a glovebox work station, the BZ would normally be higher than the leak-level (i.e., higher 

than 3.75 ft [1.143 m] above the floor), and the leak-level should not be considered as being in 

the BZ;

2. The ratio is based on the extremes of multiple graphs (i.e., different test schemes) versus the 

ranges in a single graph; and

3. The air concentrations in the graphs are reported in ranges, and the ratios are based on only 

the highest BZ result and the lowest fixed sampler result for a given range.

Because of this, the ORAU Team has reevaluated the air sampling data reported in Gonzales et al. 

(1974).

4.3 REEVALUATION OF GONZALES ET AL. STUDY DATA

The ORAU Team has reevaluated the graphical air sampling data in the Gonzales et al. (1974) study 

using four different scenarios. Those four scenarios were created from a combination of the two 

different worker location scenarios (Scenarios 1 and 2, described above) and two different sampler 

location scenarios, which are described below and identified as Scenarios A and B. This reevaluation 

depicts the differences between potential BZ and GA air concentrations in terms of BZ:GA air 

concentration ratios.

4.3.1 Bases and Assumptions for the Reevaluation

For most radiological processing areas, the majority of the processing work took place on bench tops, 

in hoods, and in gloveboxes. Radiological work involving kneeling or significant bending was probably 

limited to activities that only accounted for a small fraction of a worker’s time in the processing areas. 

Therefore, the BZ elevation for most radiological processing areas would have been predominantly 

above the leak-level elevation in the Gonzales et al. (1974) study. Therefore, this reevaluation only 

used the nine iso-concentration graphs for the 1- and 2-ft (0.30- and 0.61-m) above leak-level 

elevations (i.e., elevations of 4.75 and 5.75 ft [1.448 and 1.753 m] above the floor). In addition, 

comparisons of the potential BZ air concentrations to the GA air concentrations were performed for 

the same elevation and the same test scenario (i.e., same AC rate and air direction).

For the other studies that were evaluated in this report, the GA air sampler locations were based on 

actual measurement locations. Unlike those studies, the iso-concentration graphs in Gonzales et al. 

(1974) made the air concentrations within any point of the monitored area of the test room known, 

which theoretically allowed for an infinite number of potential GA and BZ air sampler locations to be 

evaluated. As a result, any location within the monitored area in the test room could be designated as 

a potential GA air sampler location, which allowed for the evaluation of some additional scenarios for 

the GA sampler locations. Three potential GA sampler location scenarios are defined below. 

However, as discussed below, it was not feasible to evaluate the third scenario (Scenario C). 

Therefore, only Scenarios A and B were actually used to evaluate the data from Gonzales et al. 
Document No. ORAUT-RPRT-0097 Revision No. 00 Effective Date: 03/29/2021 Page 19 of 81

Sampler Location Scenarios

• Scenario A. Assumes the hypothetical GA air samplers had an equal probability of being 

located anywhere in the test room.

• Scenario B. Assumes the hypothetical GA air samplers were potentially located anywhere in 

the test room with the exception of the middle of the test room. The exclusion area for the 

hypothetical GA air sampler locations was defined as a 4- by 6-ft (1.2- by 1.8-m) area in the 

middle of the test room, which is depicted in Figure 4-3.

• Scenario C. Assumes the hypothetical GA air samplers were always located downstream of 

the release point and near the outlet plenum for the ventilation. 

Figure 4-3. Sampler exclusion area for hypothetical GA air 

sampler locations for Scenario B (ORAUT 2019b).

Scenario A represents the potential GA sampler locations when there were no restrictions on where 

the sampler could be located. 

Scenario B was created to evaluate another plausible scenario for the GA air sampler locations. 

Because the middle of a radiological processing area is often an unlikely location for a GA air sampler 

and because the highest air concentrations in the Gonzales et al. (1974) study tended to occur in the 

middle of the test room, there was concern that the assumptions used for the worker location 

Scenario 1 (i.e., colocated worker and release point) could underestimate the potential BZ:GA ratios. 

Therefore, a second scenario was evaluated and its results were compared to the results from the first 

scenario. GA air samplers are often located along the perimeters of the radiological processing areas 
Document No. ORAUT-RPRT-0097 Revision No. 00 Effective Date: 03/29/2021 Page 20 of 81

for the following reasons: (1) the locations for power outlets are normally along the outer walls, (2) the 

length of the power cord on the air samplers, and (3) keeping the GA air samplers out of primary 

traffic areas, which are often the middle of the room.

Scenario C was intended to evaluate a common placement scenario for GA air samplers. Often GA 

air samplers are placed downstream of where the radiological work is being performed, which helps to 

ensure that a release event is detected. Unfortunately, limitations in the iso-concentration graphs 

from Gonzales et al. (1974) prevented Scenario C from being evaluated. As discussed above and as 

shown in Attachment A, the iso-concentration graphs do not go all the way to the front and back walls 

of the test room. Additionally, the only thing that is known about the outlet plenum configurations for 

the ventilation were that they extended across the entire width of the wall. No information regarding 

the vertical aspects of those configurations was provided. As a result, determining the downstream 

air concentrations near the outlet plenum for the 0° and 180° orientations was not feasible. For the 

test room in Gonzales et al., the 180° orientation would have been the most likely airflow direction in a 

properly designed radiological workroom (i.e., where the radiological source term is between the 

workers and the workroom's ventilation outlet, such that the potentially contaminated air would be 

pulled away from the worker locations). 

Combining the hypothetical BZ location and hypothetical GA air sampler location scenarios above 

resulted in a total of four scenarios being evaluated for Gonzales et al. (1974) (i.e., Scenarios 1A, 1B, 

2A, and 2B). The following are the combined scenario definitions:

• Scenario 1A. Assumes the worker (BZ location) was always at the same X,Y coordinates in 

the test room as the release point, and assumes the GA air samplers had an equal probability 

of being located anywhere in the room.

• Scenario 1B. Assumes the worker (BZ location) was always at the same X,Y coordinates in 

the test room as the release point, and assumes the potential GA air samplers were potentially 

located anywhere in the room with the exception of the middle of the room. The exclusion 

area for the potential GA sampler locations was defined as a 4- by 6-ft (1.2- by 1.8-m) area in 

the middle of the room.

• Scenario 2A. Assumes the worker (BZ location) was not necessarily located at the same X,Y

coordinates in the test room as the release point, and assumes GA air samplers had an equal 

probability of being located anywhere in the room.

• Scenario 2B. Assumes the worker (BZ location) was not necessarily located at the same X,Y

coordinates in the test room as the release point, and assumes the potential GA air samplers 

were potentially located anywhere in the room with the exception of the middle of the room. 

The exclusion area for the potential GA sampler locations was defined as a 4- by 6-ft (1.2- by 

1.8-m) area in the middle of the room.

Each of the nine iso-concentration graphs for the 1- and 2-ft (0.30- and 0.61-m) above leak-level 

elevations was evaluated for the four scenarios above. This resulted in a total of 36 BZ:GA ratio 

distributions being generated for the Gonzales et al. (1974) study. 

4.3.2 Probabilities for Hypothetical BZ Locations and GA Sampling Locations

By dividing the areas for each potential air concentration region by the total monitored area in the test 

room, the resulting region area fractions are equivalent to the probability that a randomly located 

worker (i.e., BZ location) or GA air sampler was in a given air concentration region. Because the 

location of the worker and the GA air sampler can be treated as two independent events, the 

probability of a given BZ location and GA air sampler location combination would be the product of the 
Document No. ORAUT-RPRT-0097 Revision No. 00 Effective Date: 03/29/2021 Page 21 of 81

probabilities for each location. Using Figure 4-4 to illustrate this, the probability of the worker being in 

concentration region 3 (R3) while the GA air sampler was in concentration region 2 (R2) would be 

0.1870 × 0.2548 = 0.0476. The areas for each concentration region in each iso-concentration graph 

were measured using the Measurement Log feature in Adobe Photoshop CC 20.00 Release (ORAUT 

2019c). Because those areas were being used only to calculate unitless area fractions, the units for 

the area measurements were done in terms of pixels. Using this approach, probabilities for a BZ:GA 

air concentration ratio for every potential BZ location and GA air sampler location combination could 

be calculated and evaluated.

Figure 4-4. Illustration of area fraction calculations 

(ORAUT 2019d).

For this reevaluation, the air concentration regions in the iso-concentration graphs have been defined 

in Table 4-1. 

Table 4-1. Defining air concentration 

regions for iso-concentration graphs.

Concentration 

region

Concentration 

range

R1 0.01–0.10

R2 0.11–0.50

R3 0.60–1.00

R4 1.10–2.00

R5 2.10–4.00
Document No. ORAUT-RPRT-0097 Revision No. 00 Effective Date: 03/29/2021 Page 22 of 81

In Attachment B, Figures B-1 through B-4 provide summaries of the calculated area fractions for 

Scenarios 1A, 1B, 2A, and 2B. As indicated in Attachment B, the details regarding how the area 

fractions were calculated are provided in ORAUT (2019c).

4.3.3 Statistical Evaluation of the Data

The area fractions for the concentration regions presented in Section 4.3.2 were used to calculate the 

probabilities for each potential BZ:GA ratio combination. Because the air concentration regions are 

represented by a range of potential air concentration values, values within each air concentration 

range were randomly generated using a Monte Carlo simulation and a uniform distribution with limits 

equal to the lower and upper limits of the range (ORAUT 2020). To facilitate those calculations, the 

concentration ranges for the five concentration regions given in Table 4-1 were adjusted to make the 

lower limit of each range equal to the upper limit of the previous range as shown in Table 4-2.

Table 4-2. Adjusted air 

concentration ranges for probability 

calculations.

Concentration 

region

Concentration 

range

R1 0.01–0.10

R2 0.10–0.50

R3 0.50–1.00

R4 1.00–2.00

R5 2.00–4.00

As indicated in Section 4.3.1, four scenarios (i.e., Scenarios 1A, 1B, 2A, and 2B) were evaluated 

based on the data from the 9 iso-concentration graphs for the 1- and 2-ft (0.30- and 0.61-m) above

leak-level elevations. This resulted in a total of 36 BZ:GA ratio distributions being generated for the 

Gonzales et al. (1974) study. In Figure 4-5, all 36 BZ:GA ratio distributions are presented in a scatter 

plot. The data point colors in Figure 4-5 represent the three ventilation airflow directions (i.e., red = 

0o

, blue = 90o, and black =180o). The data point shapes represent the four scenarios that were 

evaluated (i.e., solid square = Scenario 1A, open square = Scenario 1B, solid circle = Scenario 2A, 

and open circle = Scenario 2B) (ORAUT 2020).
Document No. ORAUT-RPRT-0097 Revision No. 00 Effective Date: 03/29/2021 Page 23 of 81

Figure 4-5. Scatter plot of all 36 results from Gonzales et al. (1974) (ORAUT 

2020).

The solid and open squares, representing Scenarios 1A and 1B, at the far right of Figure 4-5 appear 

to be outliers in the dataset. Both data points are associated with Figure 5 in Gonzales et al. (1974). 

A review of the area fractions for those figures (see Figures B-1 and B-2 in Attachment B) indicates 

that Figure 5 in Gonzales et al. has a significantly larger GA area fraction for concentration region R1 

than the other figures in Gonzales et al. That coupled with the fixed BZ location that was used for 

Scenarios 1A and 1B appears to be the cause for the higher geometric means (GMs) for those data 

points.

Figure 4-6 presents just the 18 data points associated with Scenario 1 (i.e., both Scenarios 1A and 

1B), which was when the worker was always at the same X,Y coordinates as the release point. 

Figure 4-7 presents just the 18 data points associated with Scenario 2 (i.e., both Scenarios 2A and 

2B), which is when the worker was not necessarily at the same X,Y coordinates as the release point. 

In these two figures, the data point colors and shapes represent the same things as in Figure 4-5.

The scatter plots indicate that the uncertainties for the 90o ventilation airflow direction are generally 

higher than the other directions, with the 180o ventilation airflow direction generally having the lowest 

uncertainties. That relationship is even more noticeable for Scenario 2 (see Figure 4-7). For 

Scenario 1, when one ignores the outliers at the far right, the GMs even appear to have a similar 

relationship to the uncertainties in regards to ventilation airflow direction.

The scatter plots also indicate that the differences between Scenarios A and B are generally just a 

slightly higher GM for Scenario B. As indicated in Section 4.3.1, there was a concern that Scenario A 

could underestimate the potential BZ:GA ratios when Scenario B would be a more realistic scenario 

for the test room in Gonzales et al. (1974). Though that appears to be true, the underestimate is 

considered to be too small to justify evaluating and developing separate BZ:GA ratios for Scenarios A 

and B. Therefore, Scenarios A and B were grouped together, to help minimize the number of BZ:GA 

ratio models being evaluated in this report. Because Scenarios A and B are both plausible GA 
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sampler location scenarios, it was decided to include both scenarios in the evaluation of the Gonzales 

et al. study versus just using Scenario B.

Figure 4-6. Scatter plot of Scenario 1 results from Gonzales et al. (1974) (ORAUT 

2020).

Figure 4-7. Scatter plot of Scenario 2 results from Gonzales et al. (1974) (ORAUT 

2020).
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Because the data generated from Gonzales et al. (1974) was much more substantial than the other 

studies being evaluated and because it was the only study that evaluated different ventilation airflow

directions, it was decided to weight the Gonzales et al. data more heavily by generating separate 

BZ:GA ratio models for each ventilation airflow direction (ventilation scheme). That resulted in a total 

of six models to represent the Gonzales et al. study (i.e., three Scenario 1 models and three

Scenario 2 models). It should be noted that the generation of separate BZ:GA ratio models for each 

ventilation scheme is only being done as a weighting mechanism. The ORAU Team does not plan to 

develop any BZ:GA ratios to be applied to specific ventilation airflow directions, because the airflow

direction observations made for this data may only be applicable to simple workrooms with simple 

ventilation flow patterns. In addition, needed details about the ventilation system and airflow patterns 

are often unknown for workrooms at other sites, which means there would be few scenarios where 

BZ:GA ratios for specific ventilation airflow directions could be used. It is also desirable to keep the 

final number of BZ:GA ratio models to a minimum. 

As indicated above, the 18 Scenario 1A and 1B models were combined into three Scenario 1 models, 

one for each ventilation scheme. Similarly, the 18 Scenario 2A and 2B models were combined into 

three Scenario 2 models, one for each ventilation scheme. Table 4-3 identifies the figures in 

Gonzales et al. (1974) that were used to generate the datasets for evaluating Scenario 1 and 

Scenario 2 for each ventilation scheme. All of those figures are redisplayed in Attachment A. Then a 

lognormal model was fit to each dataset using regression on order statistics (ROS), generating a GM 

and GSD for each model. The six combined models were used to represent the Gonzales et al. study 

for the combined evaluations in Section 9.0. In the quantile-quantile plots below, the quantiles are 

from the fitted lognormal distribution, and the horizontal lines are the 50th, 84th, and 95th percentiles 

for the plotted data (ORAUT 2020). The plots for the Scenario 1 results are presented below in 

Section 4.3.3.1 (Figures 4-8 to 4-10), and the plots for the Scenario 2 results are presented below in 

Section 4.3.3.2 (Figures 4-11 to 4-13). 

Table 4-3. Gonzales et al. (1974) 

figures used to evaluate each 

ventilation scheme.

Ventilation

scheme

Figures

used

0o 5, 6, 7, and 8

90o 12, 13, and 14

180o 18 and 19
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4.3.3.1 Scenario 1 Results: Colocated Worker and Release Point

Figure 4-8. Model for Scenario 1 with 0° airflow direction (ORAUT 2020).

Figure 4-9. Model for Scenario 1 with 90° airflow direction (ORAUT 2020).
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Figure 4-10. Model for Scenario 1 with 180° airflow direction (ORAUT 2020).

4.3.3.2 Scenario 2 Results: Variable Worker Location Relative to the Release Point

Figure 4-11. Model for Scenario 2 with 0° airflow direction (ORAUT 2020).
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Figure 4-12. Model for Scenario 2 with 90° airflow direction (ORAUT 2020).

Figure 4-13. Model for Scenario 2 with 180° airflow direction (ORAUT 2020).
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4.3.3.3 Summary of Scenario 1 and Scenario 2 Results

Table 4-4 summarizes the results from Section 4.3.3.1 for Scenario 1.

Table 4-4. Summary of the Scenario 1 BZ:GA ratio distributions 

for Gonzales et al. (1974). 

Scenario

BZ:GA ratio 

GM

BZ:GA ratio 

GSD

Scenario 1 with 0° airflow direction 1.35 3.37

Scenario 1 with 90° airflow direction 1.59 4.13

Scenario 1 with 180° airflow direction 0.852 2.00

Table 4-5 summarizes the results from Section 4.3.3.2 for Scenario 2.

Table 4-5. Summary of the Scenario 2 BZ:GA ratio distributions 

for Gonzales et al. (1974). 

Scenario

BZ:GA ratio 

GM

BZ:GA ratio 

GSD

Scenario 2 with 0° airflow direction 1.06 3.86

Scenario 2 with 90° airflow direction 1.04 6.80

Scenario 2 with 180° airflow direction 1.08 2.28

5.0 CHARUAU STUDY

The results of a French study (Charuau 1987), which was presented at the DOE Workshop on 

Workplace Aerosol Sampling in October 1985, were published as part of the proceedings for that 

workshop. The purpose of that study, which was performed by the Commissariat à l’Énergie 

Atomique (CEA), was to design and assess a personal monitor to optimize the occupational 

monitoring in plutonium laboratories. However, the part involving a contamination transfer study was 

of interest for this evaluation. 

Charuau (1987) only provides the results for one contamination transfer study; however, it indicates 

that CEA specialists had completed several other ventilation and transfer studies. Therefore, 

information from other similar CEA studies might be available elsewhere but any such information was 

not found during the preparation of this report. 

5.1 CONTAMINATION TRANSFER STUDY DESCRIPTION AND RESULTS

In Charuau (1987), plutonium releases were simulated using nonradioactive tracer gas and tracer 

aerosol (helium gas and a fluorescent aerosol) in a 15- by 7- by 4.5-m tall (49- by 23- by 15-ft tall) 

laboratory with multiple gloveboxes and workstations. Figure 5-1 provides a diagram of this 

laboratory, the inlet and outlet locations for the ventilation system, and the results from the study. 

During the study, the average ventilation rate was 10 AC/hr. Filtered air was blown into the workroom

by three different diffusers arranged along the ceiling, and air was extracted from the room through 

10 vents low on the walls (Charuau 1987). In Figure 5-1, the diffusers are the circular features with 

the outward pointing arrows, and the exhaust vents are the openings in the top and bottom walls with 

arrows pointing at them. The arrows represent the airflow direction. The room was reported to have 

no great ventilation dissymmetry and no dead zones (Charuau 1987).
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Figure 5-1. Plutonium laboratory and transfer study results (Charuau 1987, 

p. 174).

The generated aerosols consisted of two particle size groups, one with MMAD of 2.3 μm and the other 

with MMAD of 10.5 μm. The testing appears to have been conducted in multiple stages with a 

continuous emission of helium and then a continuous emission of each aerosol group (i.e., the 2.3-μm

group and the 10.5-μm group) (Charuau 1987). Because the study did not include discussion about a 

sampling device with particle sizing capabilities and referred to “aerosols” in the plural form, it was

assumed that the 2.3- and 10.5-μm particles were generated separately in two different parts of the 

study. 

Air concentrations were measured at 10 locations in the workroom identified as D1 through D10 in 

Figure 5-1. The location of the gas and aerosol release point is identified as “Source: S”. The release 

point and sampling locations were all at an elevation of 1.5 m (4.9 ft) above the floor (Charuau 1987).

The results for this study were reported in terms of transfer coefficient TC in s/m3

. The transfer 

coefficient is the ratio of the locally measured concentration of gas (m3

/m3) or aerosols (kg/m3) to the 

emission flux from the source of gas (m3

/s) or aerosols (kg/s) (Charuau 1987).

5.2 EVALUATION OF THE CHARUAU STUDY DATA

The two BZ location scenarios described at the end of Section 3.0 were used to evaluate the potential 

differences between the BZ and GA air concentrations in the Charuau (1987) study. The following 

describes how Scenario 1 and Scenario 2 were evaluated using the data from Figure 5-1. For each 

scenario, a lognormal model was fit to the dataset for that scenario using ROS, generating a GM and 

GSD for each model. 
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5.2.1 Scenario 1 Evaluation: Colocated Worker and Release Point

As indicated above, air sampler location D1 was designated as the only BZ location to evaluate the 

BZ location scenario for Scenario 1 because it was the only sampling location near the release point. 

Then each of the 10 air sampling locations (D1 through D10) were evaluated as potential GA air 

sampler locations to generate a single BZ:GA ratio data point for each of the three types of tracer gas 

or aerosol used in Charuau (1987). This resulted in three separate datasets for Scenario 1 (i.e., one 

for gas, one for the 2.3-μm aerosol, and one for the 10.5-μm aerosol). Each of the three datasets

would have contained nine BZ:GA ratio data points, but there were no data for the 2.3-μm aerosol at 

location D8 (see Figure 5-1). Therefore, only eight BZ:GA ratio data points could be generated for the 

2.3-μm aerosol dataset. A lognormal model fit was then performed on each of the resulting three 

datasets, using ROS (ORAUT 2020).

Figures 5-2 through 5-4 present each of the three datasets for Scenario 1 in the form of a quantilequantile plot. In the quantile-quantile plots below, the quantiles are from the fitted lognormal 

distribution, and the horizontal lines are the 50th, 84th, and 95th percentiles for the plotted data

(ORAUT 2020). 

Figure 5-2. Model for Scenario 1 for gas (ORAUT 2020).
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Figure 5-3. Model for Scenario 1 for 2.3-μm aerosols (ORAUT 2020).

Figure 5-4. Model for Scenario 1 for 10.5-μm aerosols (ORAUT 2020).
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5.2.2 Scenario 2 Evaluation: Variable Worker Location Relative to the Release Point

Air sampler locations D1 through D10 were each designated in turn as the BZ location to evaluate the 

BZ location scenario for Scenario 2. Then, for each BZ location designation, each of the 10 air 

sampling locations was evaluated as potential GA sampler locations to generate a single BZ:GA ratio 

dataset for each of the three types of tracer gas or aerosol used in Charuau (1987). This would have 

generated 30 BZ:GA ratio datasets for Scenario 2, but there were no data for the 2.3-μm aerosol at 

location D8 (see Figure 5-1). Therefore, only 29 BZ:GA ratio datasets could be generated for 

Scenario 2. A lognormal model fit was then performed on each of the 29 BZ:GA ratio datasets using 

ROS (ORAUT 2020). 

The 29 lognormal models were then grouped by tracer gas or aerosol type, resulting in 9 lognormal 

models in the 2.3-μm aerosol group and 10 lognormal models in the other two groups. Each of the 

three groups of lognormal models were then combined using Monte Carlo simulation to create a 

single Scenario 2 dataset for each type of tracer gas or aerosol (i.e., one for gas, one for the 2.3-μm 

aerosol, and one for the 10.5-μm aerosol). A lognormal model fit was then performed on each of the 

resulting three datasets using ROS (ORAUT 2020). 

Figures 5-5 through 5-7 present each of the combined datasets for Scenario 2 in the form of a 

quantile-quantile plot. In the quantile-quantile plots below, the horizontal lines are the 50th, 84th, and 

95th percentiles for the plotted data (ORAUT 2020). 

Figure 5-5. Model for Scenario 2 for gas (ORAUT 2020).
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Figure 5-6. Model for Scenario 2 for 2.3-μm aerosols (ORAUT 2020). 

Figure 5-7. Model for Scenario 2 for 10.5-μm aerosols (ORAUT 2020).
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5.2.3 Summary of Scenario 1 and Scenario 2 Results

Table 5-1 summarizes the results for Scenario 1, and Table 5-2 summarizes the results for 

Scenario 2.

Table 5-1. Summary of Charuau (1987) BZ:GA ratio 

distributions for Scenario 1.

Gas/aerosol

BZ:GA ratio 

GM

BZ:GA ratio 

GSD

Gas (helium) 1.97 1.37

2.3-μm aerosol 3.02 1.88

10.5-μm aerosol 7.79 2.54

Table 5-2. Summary of Charuau (1987) BZ:GA ratio 

distributions for Scenario 2.

Gas/aerosol

BZ:GA ratio 

GM

BZ:GA ratio 

GSD

Gas (helium) 0.995 1.60

2.3-μm aerosol 1.02 2.32

10.5-μm aerosol 1.01 3.67

The Charuau (1987) study was the only identified study that had data for different particle sizes. The 

data in Tables 5-1 and 5-2 show that particle size has a significant effect on the BZ:GA ratios even 

within the respirable particle size range. It is generally understood that larger particles do not travel 

as far as smaller size particles. The data for Scenario 1 (Table 5-1) provide a good demonstration of 

that. It also illustrates the importance of knowing the particle sizes when evaluating the differences 

between BZ and GA air concentrations for Scenario 1 (i.e., when the BZ is near the release location). 

For Scenario 2, the effect particle size has on the BZ:GA ratio is more complicated but less significant, 

because the BZ location is not always closer to the release point than the GA location. At this time, 

the ORAU Team has no recommendations regarding the use of particle size specific BZ:GA ratios 

and does not intend to use the particle size specific information in this section.

5.2.4 Combined Scenario 1 and 2 Results for Aerosols

For comparing the Charuau study to the other studies, only the aerosol datasets for the 2.3-μm and 

10.5-μm aerosols were of interest. Therefore, the lognormal models for the 2.3-μm and 10.5-μm 

aerosols were combined, to create a single lognormal model for each scenario (i.e., one for 

Scenario 1 and one for Scenario 2). Monte Carlo simulation was used to create the combined aerosol 

datasets. A lognormal model fit was then performed on each of the resulting aerosol datasets using 

ROS (ORAUT 2020). 

For Scenario 1 (colocated worker and release point), the two lognormal models for the 2.3-μm and 

10.5-μm aerosols were combined using Monte Carlo simulation to create a single Scenario 1 dataset. 

A lognormal model fit was then performed on the new Scenario 1 dataset using ROS (ORAUT 2020). 

The combined Scenario 1 aerosol plot is provided as Figure 5-8. 

For Scenario 2 (variable worker location relative to the release point), the 9 lognormal models for the 

2.3-μm aerosols and the 10 lognormal models for 10.5-μm aerosols were combined using Monte 

Carlo simulation to create a single Scenario 2 dataset. A lognormal model fit was then performed on 

the new Scenario 2 dataset using ROS (ORAUT 2020). The combined Scenario 2 aerosol plot is 

provided as Figure 5-9. 

Table 5-3 summarizes the combined BZ:GA ratio distributions for the aerosols, which will be 

compared to the other evaluated studies.
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Figure 5-8. Combined model for Scenario 1 for aerosols (ORAUT 2020).

Figure 5-9. Combined model for Scenario 2 for aerosols (ORAUT 2020).
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Table 5-3. Summary of the combined BZ:GA ratio 

distributions for aerosols. 

Scenario

BZ:GA ratio 

GM

BZ:GA ratio 

GSD

Scenario 1 for aerosols 4.92 2.50

Scenario 2 for aerosols 1.00 2.94

6.0 MUNYON AND LEE STUDY

Workplace air sampling was performed during the decommissioning of a previously active plutonium 

glovebox facility at Argonne National Laboratory-East. Approximately 60 gloveboxes were included in 

the scope of the decommissioning project (Munyon and Lee 2002). The primary purposes of the 

study included (1) describing the relative response between the stationary air samplers (SASs) and 

PASs, (2) reporting on the results from a set of aerosol particle sizing measurements, and 

(3) summarizing some general observations about the spatial distribution of radioactive particles that 

were collected on air sampling filters and the degree to which gross alpha measurements were 

affected by alpha particle absorption phenomena. The portion of this study addressing the relative 

response between the SASs and PASs was the primary interest for this report.

6.1 DESCRIPTION OF THE STUDY

The decommissioning operations were performed in an 8.5- by 3.6- by 2.4-m tall (28- by 12- by 8-ft 

tall) enclosure of prefabricated stainless-steel panels. A drawing of the containment enclosure 

floorplan, consisting of a workroom and airlock area, is provided in Figure 6-1. The workroom portion 

of that enclosure had dimensions of 4.9- by 3.6- by 2.4-m tall (16- by 12- by 8-ft tall), which 

corresponds to a room air volume of 42.34 m3 (1,495 ft3

). Four air exhaust vents were installed in the 

workroom; two along the west wall and two moveable aerosol capture hoods that were suspended 

from the ceiling. The workroom exhaust rate was reported to be approximately 64 m3

/min (2,260 cfm) 

and was reported to have an AC rate of 90 AC/hr (Munyon and Lee 2002). A portable vacuum 

system with high-efficiency particulate air filters was used in close proximity to the cutting operations 

to minimize the dispersal of aerosols. A photograph of the exterior of the enclosure, as viewed from 

the personnel and equipment entrance side of the enclosure (i.e., the east side), is provided in 

Figure 6-2. Figure 6-3 is a photograph of the interior of the enclosure’s workroom, which shows the 

two movable aerosol capture hoods along with the west and north SASs (Munyon and Lee 2002).

PASs were used to measure BZ activity concentrations of workers engaged in size-reducing work on 

the contaminated gloveboxes. SASs were used to measure the work area activity concentrations and 

test their application in providing representative sampling of BZ activity concentrations (Munyon and 

Lee 2002). Based on Figures 6-2 and 6-3, the sampling heads for the SASs appear to be positioned 

at an elevation of 4.5 ft above the floor, which is within the typical BZ elevation. Both the SAS and 

PAS air filters were removed after each 4-hour work-shift and counted 24 hours later using a gas-flow 

proportional counter. The air samples were recounted 1 week later, which allowed for the decay of 

short-lived radon progeny. The contribution of the radon progeny to the initial gross alpha count rate 

was quite small, typically less than 10% (Munyon and Lee 2002).
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Figure 6-1. Containment enclosure floorplan (Munyon and Lee 2002, p. 3). 

Figure 6-2. Exterior view of containment enclosure (Munyon and Lee 2002, p. 3).
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Figure 6-3. Interior view of workroom for containment enclosure (Munyon and Lee 2002, p. 3). 

Independent of the other air samplers, a 10-stage cascade impactor was used to determine the 

particle size distribution of workplace aerosols during seven measurement periods. The cascade 

impactor samples were collected adjacent to the north wall SAS, which is depicted in Figure 6-1. 

Aerosols were separated on the basis of aerodynamic diameter over a range of 0.08 to 28 μm. The 

average activity median aerodynamic diameter for the set of seven measurements was 3.0 μm with a 

corresponding average GSD of 2.4 (Munyon and Lee 2002). 

Figure 6-4 depicts the four histograms from Munyon and Lee (2002) that summarize the relative 

performance between the SASs and PASs. The cumulative response of workplace air samplers 

throughout the duration of the decontamination and decommissioning project is shown in Figures 6-5 

and 6-6. These curves illustrate how well the samplers performed relative to one another. In each 

case the daily activity concentration was summed over the entire sampling period and then plotted on 

the basis of the fractional cumulative concentration for each sampler. The relative performance 

between each of the SAS locations is shown in Figure 6-5. It is interesting to note the general 

similarity in response between the north and west wall samplers as shown in Figure 6-5. The relative 

performance between the PASs and SASs is shown in Figure 6-6. Overall, the summed response of 

the three SASs agrees very well with that of the three corresponding PASs. The plotted data illustrate 

that the SASs, which were positioned a couple of meters away from the work crew, were indeed 

sensitive to changes in the activity concentration as measured by the SASs (Munyon and Lee 2002).
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Figure 6-4. Relative performance between the BZ (PAS) and GA (SAS) air samplers 

(Munyon and Lee 2002, p. 5). 

Figure 6-5. Normalized cumulative response functions for SAS data by SAS location 

(Munyon and Lee 2002, p. 6).
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Figure 6-6. Normalized cumulative response functions for PAS versus SAS data (Munyon 

and Lee 2002, p. 6). 

6.2 EVALUATION OF THE MUNYON AND LEE STUDY DATA

In Figure 6-4, Histogram A (i.e., the histogram labelled “All SAS”) was thought to represent the sum of 

Histograms B to D, but an evaluation of the data determined that was not the case. Because Munyon 

and Lee (2002) only indicate that Histogram A depicts the PAS:SAS ratios with no further details, it 

could not be determined what Histogram A actually represented. Therefore, the data from Histograms 

B to D were retabulated to create a combined histogram and dataset for this evaluation.

Unlike the other studies evaluated in this report, Munyon and Lee (2002) is based on an actual work 

activity and the PAS data from actual workers rather than a simulated scenario. Because the workers 

likely moved around in the workroom, the data from this study are only representative of the BZ 

location in Scenario 2.

6.2.1 Statistical Evaluation of the Data

The data were presented in the original paper as a histogram of the frequencies of specified BZ:GA

ratios. The data in each bin of the histogram were assigned a value equal to the midpoint of the 

respective bin. For example, there were five occurrences of a BZ:GA ratio in the bin with a midpoint 

of 0.1, which is represented in the dataset as {0.1, 0.1, 0.1, 0.1, 0.1}. Then a lognormal model was fit 

to the dataset using ROS, generating the GM and GSD shown in Figure 6-7. In the quantile-quantile 

plot below, the quantiles are from the fitted lognormal distribution, and the horizontal lines are the 

50th, 84th, and 95th percentiles for the plotted data (ORAUT 2020). 

Based on Figure 6-7, the BZ:GA ratio distribution for Scenario 2 (variable worker location relative to 

the release point) has a GM of 1.08 and a GSD of 5.40. 
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Figure 6-7. Model for Scenario 2 (ORAUT 2020). 

7.0 SCRIPSICK ET AL. STUDY

In June 1978, the results of a study at the LANL were presented at the International Atomic Energy 

Agency Symposium on Advances in Radiation Protection Monitoring, and in August 1979 the paper 

for that presentation was published as part of the proceedings for that symposium (Scripsick et al. 

1979a). Additional details about the LANL study are documented in Section I.A of LANL progress 

report LA-8153-PR (Scripsick et al. 1979b). The purpose of that study was to measure the dilution of 

contaminants between worker BZ and GA air concentrations. 

7.1 DESCRIPTION OF THE STUDY

In Scripsick et al. (1979a, 1979b), releases were simulated from 20 potential release locations in a 

typical workroom inside a plutonium-handling facility. Facility operations involved research and 

development with various forms of plutonium, and all work was performed in gloveboxes.

The workroom dimensions were 9.0- by 6.3- by 4.1-m tall (30- by 21- by 13-ft tall), and the room 

layout was typical of workrooms dealing with toxic materials. Figure 7-1 provides a diagram of this 

workroom and depicts the fixed aerosol sampling locations along with the ventilation inlets and 

outlets. In Figure 7-1, the letters A through H identify the fixed air sampler locations. The asterisks in 

Figure 7-1 identify the two continuous air monitors (CAMs) locations for the room (locations NEC and 

SEC) and the locations of two additional air samplers that were used for the study (locations NEX and 

SEX). The ventilation inlet was near the ceiling, and the ventilation exhausts were on the floor at the 

opposite end of the room from the inlet. The ventilation rate for the room was approximately 12 AC/hr 

(Scripsick et al. 1979a, 1979b). Figure 7-2 provides a diagram of the workroom depicting the 

20 release locations for this study.
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Figure 7-1. Workroom floorplan with ventilation system components and 

air sampler locations (Scripsick et al. 1979a, p. 319). 

Figure 7-2. Numbered release locations used in the study (Scripsick et al. 

1979a, p. 319). 

The test aerosol was generated from a solution of fluorescein in NH4OH, which was detectable at an 

air concentration of 0.1 μg/m3 during this study. The generated aerosol had a count median 

aerodynamic diameter of 0.35 μm with a GSD of 2.1. The aerosol releases were made 1.3 m (4.3 ft) 

above the floor. Aerosol was generated during the first 15 minutes of each test. Collection of air 

samples was initiated when the aerosol generation started and continued for 15 minutes after the 

aerosol generation was stopped. Another test was started after the workroom was allowed to clear for 

15 minutes (i.e., after 3 AC), and clean air sampling filters were placed on all samplers. Six releases 
Document No. ORAUT-RPRT-0097 Revision No. 00 Effective Date: 03/29/2021 Page 44 of 81

were made at each of the 20 locations in Figure 7-2 (Scripsick et al. 1979a, 1979b). Red dots were 

added to Figure 7-2 to depict the sampler locations from Figure 7-1 in relation to the release locations.

The study used a variable BZ location that was always 0.4 m (1.3 ft) above the release location 

(i.e., 1.7 m [5.6 ft] above the floor). Area samplers along the glovebox faces (Samplers A through H) 

were reported as being “~2 m above the floor,” which is likely the same height of the BZ sampler 

rounded to the nearest meter. The CAMs at locations NEC and SEX were located at 1 m (3.2 ft) 

above the floor. The two additional air samplers at locations NEX and SEX were located immediately 

above each workroom ventilation exhaust, which was interpreted as being near floor level.

In Scripsick et al. (1979a, 1979b), BZ dilution factors (BDs) were calculated for each release location 

and sampler location combination by dividing the BZ air concentration at the release by the air 

concentration at the sampler, which makes the BD values in this study equivalent to BZ:GA ratios. As 

indicated above, six releases were made at each of the 20 release locations. For each release 

location and sampler location combination, the average BD value and standard deviation was 

calculated from the six releases and measurements made for that release location. The results of 

those measurements and average BD calculations were provided in Table I of Scripsick et al. (1979a, 

1979b) and are represented in Table 7-1. 

7.2 EVALUATION OF THE SCRIPSICK ET AL. STUDY DATA

To evaluate potential differences between BZ and GA air concentrations, the ORAU Team used the 

Scripsick et al. (1979a, 1979b) data to evaluate the two BZ location scenarios described at the end of 

Section 3.0. To evaluate the BZ location in Scenario 1, the data from Table 7-1 was used “as is” 

because the average BDs in that figure were equivalent to BZ:GA ratios for Scenario 1 (i.e., the BZ 

location was always at the release point for this study).

Because the actual BZ locations in Scripsick et al. (1979a, 1979b) were fixed for a given release 

location, the ratio of the BDs (i.e., BZ:GA ratios) in Table 7-1 could be used to generate additional 

sets of data to evaluate Scenario 2 for this study. By taking the ratio of two different samplers (i.e., 

two different rows) for the same release location (i.e., the same column) from Table 7-1, the original 

BZ result in the BDs will cancel out, resulting in the ratio of the concentrations at the two samplers. 

This can be used to produce a new set of BZ:GA ratios that can be used to evaluate Scenario 2. The 

following equations are being used to illustrate how the original BZ air concentration from the study 

can be cancelled out to produce a new BZ:GA ratio.

For release locations j = {1, 2,...,20}, and GA sampler locations i = {A, B,...,H, NEC, SEC, NEX, SEX}. 

BZj j

i,j i ,j

GAi i

C BZ

BD BZ:GA

C GA = = = (7-1)

where

BDi,j = is the BD for GA sampler location i and release location j

CBZj = breathing zone air concentration at release location j, which is also notated as BZj

CGAi = GA air concentration at GA air sampler location i, which is also notated as GAi

BZ:GAi,j = is the BZ:GA ratio when the GA sampler is at location i and the BZ is at release 

location j
 

Document No. ORAUT-RPRT-0097 Revision No. 00 Effective Date: 03/29/2021 Page 45 of 81

Table 7-1. Average BDs by release location.

a 

Samplers123456789 10

A 5.7 ±0.3

b 7.1 ±2.1 7.5 ±2.3 16 ±5.8 40 ±11 151 ±55 13 ±5.2 2.6 ±0.3 7.3 ±3.6 26 ±11

B 6.0 ±0.7 9.4 ±3.9 6.5 ±0.3 10 ±3.6 28 ±5.5 132 ±89 22 ±0.9 15 ±3.3 9.4 ±1.3 15 ±4.6 C 8.0 ±0.3 11 ±2.3 5.1 ±0.4 8.5 ±1.2 33 ±9.0 45 ±15 29 ±2.7 28 ±4.5 24 ±5.7 32 ±4.4 D 7.4 ±4 15 ±7.6 6.3 ±1.0 6.9 ±0.8 25 ±5.6 54 ±25 18 ±4.0 17 ±5.6 11 ±2.3 18 ±2.9 E 6.6 ±0.2 7.4 ±1.3 19 ±12 12 ±2.3 22 ±0.6 23 ±23 35 ±8.7 41 ±3.9 38 ±7.0 41 ±8.6 F 6.0 ±0.6 6.4 ±1.1 34 ±14 15 ±3.8 34 ±30 338 ±128 40 ±9.2 49 ±2.8 43 ±2.7 48 ±10 G 4.9 ±0.1 5.9 ±0.8 6.0 ±0.7 15 ±6.3 71 ±46 466 ±190 36 ±13 50 ±6.6 44 ±2.2 49 ±12 H 2.6 ±0.9 2.9 ±1.3 5.7 ±1.1 20 ±8.7 119 ±54 1079 ±384 44 ±26 96 ±11 79 ±34 102 ±23

NEC 11 ±0.5 13 ±5.0 11 ±2.3 18 ±2.6 32 ±10 23 ±6.1 43 ±11 54. ±7.4 53 ±4.1 48 ±15

SEC 11 ±2.1 12 ±3.7 11 ±4.0 19 ±3.0 3.9 ±8.7 31 ±7.2 55 ±8.0 5.4 ±4.1 64 ±40 57 ±15

NEX 9.8 ±0.7 10 ±1.7 8.6 ±2.4 36 ±33 43 ±13 25 ±11 36 ±36 51 ±34 64 ±40 57 ±15

SEX 11 ±1.0 13 ±5.6 15 ±5.4 25 ±6.4 69 ±36 365 ±456 60 ±20 89 ±19 69 ±22 61 ±8.3

Samplers 11 12 13 14 15 16 17 18 19 20 A 68 ±39 168 ±64 148 ±60 102 ±49 41 ±24 46 ±21 63 ±15 8.6 ±2.5 19 ±10 68 ±20 B 33 ±8.2 78 ±31 55 ±18 46 ±25 24 ±13 31 ±10 1 ±0.2 8.4 ±1.4 1.3 ±3.2 50 ±21 C 31 ±13 38 ±5.2 104 ±142 32 ±16 23 ±8.1 41 ±4.7 28 ±4.6 8.9 ±0.7 6.4 ±0.6 24 ±7.1 D 13 ±2.0 1.6 ±2.0 6.3 ±19 23 ±9.2 11 ±2.4 13 ±2.0 24 ±3.3 9.0 ±1.3 6.2 ±0.4 22 ±10 E 63 ±26 150 ±25 215 ±18 62 ±18 61 ±22 66 ±12 59 ±11 15 ±2.7 12 ±1.7 23 ±0.7 F 83 ±32 194 ±36 236 ±25 76 ±21 72 ±20 83 ±41 68 ±13 16 ±1.0 13 ±1.2 26 ±7.0 G 118 ±45 240 ±51 256 ±45 110 ±38 86 ±22 79 ±16 73 ±13 12 ±2.1 12 ±1.4 46 ±18 H 224 ±83 469 ±114 546 ±125 194 ±90 196 ±39 165 ±34 124 ±37 6.7 ±1.9 10 ±0.7 61 ±33

NEC 58 ±27 41 ±34 87 ±61 85 ±25 42 ±28 84 ±29 9.6 ±1.4 14 ±2.1 11 ±1.1 8.5 ±1.9

SEC 84 ±41 217 ±43 268 ±98 80 ±25 92 ±35 90 ±23 88 ±19 54 ±78 18 ±2.2 20 ±7.2

NEX 45 ±49 66 ±73 47 ±30 28 ±8.9 23 ±9.6 21 ±6.9 11 ±3.5 13 ±4.6 8.5 ±3.7 23 ±12

SEX 200 ±252 208 ±46 356 ±128 83 ±25 86 ±18 162 ±166 143 ±146 17 ±1.8 12 ±1.3 18 ±12

a. Sources: Scripsick et al. (1979a, 1979b).

b. Standard deviation estimate over six releases.
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For new BZ location x, which is a selected GA sampler location: 

:

:

:

j

i,j i x

i ,x

x,j j i

x

BZ

BZ GA GA GA BZ GA

BZ GA BZ GA

GA

      = = =      

(7-2)

Using the data for Release Location 1 as an example, the original BZ location was at Release 

Location 1, which is not depicted as an air sampler location in Figure 7-1. To redesignate GA sampler 

location A as the new BZ location and produce a new BZ:GA ratio from that data, one just needs to 

take the following ratio: 

1

,1

,

,1 1

:

:

NEC NEC A

NEC A

A NEC

A

BZ

BZ GA GA GA BZ : GA

BZ GA BZ GA

GA

      = = =      

(7-3)

7.2.1 Statistical Evaluation of the Data

The two BZ location scenarios described at the end of Section 3.0 were used to evaluate the potential 

differences between the BZ and GA air concentrations in the Scripsick et al. (1979a, 1979b) study. 

The following describes how Scenario 1 and Scenario 2 were evaluated using the data from 

Table 7-1. For each scenario, a lognormal model was fit to each dataset using ROS, generating a 

GM and GSD for each model. In the quantile-quantile plots below, the quantiles are from the fitted 

lognormal distribution, and the horizontal lines are the 50th, 84th, and 95th percentiles for the plotted 

data (ORAUT 2020). 

7.2.1.1 Scenario 1 Results: Colocated Worker and Release Point

As indicated above, the raw data in Table 7-1 are BDs, which are equivalent to BZ:GA ratios when the 

BZ is always at the release location. Therefore, the BDs in Table 7-1 were used as is for evaluating 

Scenario 1. In Table 7-1, a BD is given for 10 retrospective samplers and 2 CAMs at each of the 20 

release points. A lognormal model was fit to the 240 BZ:GA ratios in Table 7-1, which is shown in 

Figure 7-3 (ORAUT 2020). 
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Figure 7-3. Model for Scenario 1 (ORAUT 2020). 

7.2.1.2 Scenario 2 Results: Variable Worker Location Relative to the Release Point

For the Scenario 2 evaluation, additional BZ:GA ratio combinations were calculated from the 

Table 7-1 data using Equations 7-1 and 7-2. To produce the additional BZ:GA ratio combinations for 

the Scenario 2 evaluation, air sampler locations A through H were evaluated as other potential BZ 

locations. These additional BZ locations are in addition to the ones used for Scenario 1 (i.e., when 

the BZ location was always at the release location). Because the air samplers at locations NEC, 

SEC, NEX, and SEX were only 1 m (3.2 ft) above the floor or less, they were excluded as potential BZ 

locations for this evaluation. For each of the eight new BZ locations, all 12 air sampler locations were 

each designated in turn as the GA locations for all 20 release locations. For example, when the 

location A air sampler was designated as the BZ location (BZ-A), a BZ:GA ratio was calculated for 

each of the 12 potential GA locations and 20 release locations. This created a single BZ:GA ratio 

dataset consisting of 240 data points for the BZ-A location. Then a lognormal model fit was 

performed on the new dataset for the BZ-A location using ROS (ORAUT 2020). This process was 

then repeated for each of the remaining new BZ location designations until a new lognormal model 

was created for all eight of the new BZ locations (ORAUT 2020). 

Because the GMs for the eight new lognormal models were significantly lower than the GM for the 

lognormal model for Scenario 1, the eight new lognormal models were combined to evaluate how well 

they fit a single lognormal distribution by themselves. The eight new lognormal models were 

combined using Monte Carlo simulation to create a single dataset for when the BZ location was at air 

sampler locations A through H. A lognormal model fit was then performed on the new dataset using 

ROS (ORAUT 2020). Figure 7-4 provides the results of this intermediate evaluation for Scenario 2. 

Based on Figure 7-4, the combination of the eight new lognormal models fit a single lognormal 

distribution reasonably well. 
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Figure 7-4. Intermediate model for Scenario 2 (ORAUT 2020). 

For the Scenario 2 evaluation, the eight new lognormal models were combined with the lognormal 

model for Scenario 1 using Monte Carlo simulation to create a single dataset for Scenario 2. A 

lognormal model fit was then performed on the new dataset using ROS (ORAUT 2020). Figure 7-5 

provides the results for the Scenario 2 evaluation. As indicated by Figure 7-5, this combination of 

lognormal models no longer fits a single lognormal distribution very well. Based on Figures 7-3, 7-4, 

and 7-5, the complete Scenario 2 dataset is clearly the product of two significantly different lognormal 

distributions. The lack of fit between the Scenario 1 model and the other eight models was tolerated 

for this report because it represents only one of nine different models that were combined to generate 

the Scenario 2 model. Fitting the Scenario 2 dataset to a different distribution other than a lognormal 

distribution was not considered, because it would have been impractical for this report and its 

intended uses. For practical reasons, the final models need to be lognormal distributions. 

Consideration was given to excluding the Scenario 1 model from this Scenario 2 evaluation. 

However, it was decided that it would be more appropriate to include it for the following reasons: (1) 

the scenario when the BZ location is at the release locations is a plausible scenario that should be 

included in the Scenario 2 evaluation, (2) the GM and GSD values would be lower if the Scenario 1 

model was excluded, and (3) excluding the Scenario 1 model would make this Scenario 2 evaluation 

inconsistent with the Scenario 2 evaluations performed on the other studies that were evaluated in 

this report. 
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Figure 7-5. Model for Scenario 2 (ORAUT 2020). 

7.2.1.3 Summary of Scenario 1 and Scenario 2 Results

Table 7-2 summarizes the results from Sections 7.2.1.1 and 7.2.1.2 for Scenarios 1 and 2.

Table 7-2. Summary of the BZ:GA ratio 

distributions for Scripsick et al. (1979a, 1979b). 

Scenario

BZ:GA ratio 

GM

BZ:GA ratio 

GSD

Scenario 1 30.5 3.31

Scenario 2 1.43 3.64

8.0 WHICKER AND MOXLEY STUDY

In 2001, the results of a study that was performed by LANL personnel at the Savannah River Site 

(SRS) C-Lab were documented as LA-UR-01-4933 (Whicker and Moxley 2001). Additional details 

about the study were also documented in a 2003 Health Physics journal article (Whicker, Rodgers, 

and Moxley 2003). The specific goals of the Whicker and Moxley study were to measure fundamental

airflow characteristics (velocity, turbulence), aerosol lag times, dilution, and potential dose savings 

given various arrangements of CAMs. From those measurements an evaluation of the adequacy of 

the then-current CAM sampling location was performed, and the study also evaluated other possible 

sampling locations to determine the optimal number of and placement of CAMs. 

8.1 DESCRIPTION OF THE STUDY

In Whicker and Moxley (2001), releases were simulated from six potential release locations in the 

C-Lab. At the time of the study, the SRS C-Lab was being used as a low-level plutonium chemistry 

laboratory that contained multiple workstations, hoods, and gloveboxes. The laboratory dimensions 

were approximately 6- by 4- by 3- m tall (20- by 13- by 10-ft tall). Figure 8-1 provides a diagram of the 
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C-Lab and depicts the release locations and air sampling locations. In Figure 8-1, the boxes with R1

to R6 in them identify the six release locations, and the numbers identify the fixed air sampler and 

CAM locations. Sampler location 8 is not depicted in Figure 8-1 because it represents the variable 

location of the BZ sample. The supply air for the workroom was introduced through a series of 

diffusers along a ceiling strip that ran through the middle of the room, and the room air was exhausted 

through the chemical hoods. The ventilation rate for the room was approximately 15 AC/hr.

Figure 8-1. C-Lab floorplan with air sampler locations and release locations depicted (Whicker and 

Moxley 2001, p. 16).

The six different release locations used in the study were based on input from the C-Lab operations 

personnel, who indicated those six locations were the most probable locations for real releases. The 

simulated releases were in the form of 60-second “puff-type” releases at each of the six release 

locations in the workroom. Three separate releases were performed at each of the six locations to 

measure the variability of the aerosol dispersion, which resulted in a total of 18 simulated releases. 

To simulate a radioactive aerosol release, a nontoxic oil (dioctyl sebacate) aerosol was released from 

an aerosol generator. The generated particles were polydispersable with a size range of 0.01 to 

2 μm. The distribution of the particle size range had a GM of about 0.3 μm and a GSD of less than 2. 

Tracer releases at glovebox workstations (release locations R2 through R4) were conducted about 

30 cm (~1 ft) in front of the glovebox face and at the height of the gloves, to simulate the breach of a 

glove. Tracer releases at chemical hood workstations (release locations R1, R5, and R6) were 

conducted in front of the hood and near the floor to simulate a dropped sample that breaks on the 
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floor and disperses the material into the air (Whicker and Moxley 2001; Whicker, Rodgers, and 

Moxley 2003).

Sixteen laser particle counters (LPCs), which were coupled to a multiplexer, were used to measure 

the concentrations at all of the sampling locations. The 16 LPCs were set up to provide concentration 

measurements in 10-second intervals to measure the aerosol migration through time and space. For 

this ORAU Team report, only the 9-minute average concentration data for each release location and 

sampler location combination were used. In Whicker, Rodgers, and Moxley (2003), the 9-minute 

average concentration was defined as the tracer aerosol concentration measurements averaged over 

a 9-minute interval.

For the simulated releases, it was assumed the cause of release was the result of a worker’s action 

and not a random event (i.e., the worker was always next to the aerosol release). To do that, the 

study used a variable BZ location designated as location 8. The BZ LPC was always positioned about 

30 cm (~1 ft) over and behind the aerosol generator’s release point (Whicker and Moxley 2001; 

Whicker, Rodgers, and Moxley 2003). For the chemical hood release locations, this put the BZ 

location only 30 cm (~1 ft) or so above the floor, which is an unlikely BZ location. One would also 

expect a release and BZ location combination that close to the floor to significantly bias the BZ air 

concentrations for release locations R2 through R4 high. However, a comparison of the measured 

concentrations for location 8 and the nearest fixed sampler that was closest to the BZ location 

indicates that was not the case. The fact that chemical hoods were the room’s air exhaust points 

might have mitigated the potential bias. The LPC at location 15 was placed about 30 cm (~1 ft) 

directly below the existing CAM intake tube for evaluation and comparison with other CAM placement 

locations (Whicker and Moxley 2001). For LPC locations 1 through 7, 9 through 14, and 16, no 

sampling elevation was provided in the documentation. For this ORAUT Team report, it was assumed 

the sampling elevation for LPC locations 1 through 7, 9 through 14, and 16 was 1.7 m (5.6 ft), which 

was the sampler elevation in other LANL studies.

8.2 EVALUATION OF THE WHICKER AND MOXLEY STUDY DATA

As indicated above, only the 9-minute average concentration data generated for each release location 

and sampler location combination were used for this report. The 9-minute average concentration data 

are redepicted in Table 8-1. 
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Table 8-1. 9-min average air concentrations by release location (particles/ft3) (Whicker and Moxley 

2001). 

Measurement 

location R1 R2 R3 R4 R5 R6

1 14,406 423,751 828,070 929,484 60,554 74,831

2 75,033 450,019 559,933 547,856 62,260 411,195

3 No data 345,591 494,387 542,140 38,438 107,993

4 62,693 156,404 355,190 496,388 7,545 227,033

5 171,816 98,778 144,317 190,359 3,300 461,537

6 244,397 93,188 53,089 93,091 2,000 624,272

7 268,213 77,182 32,609 52,222 478 423,681

8a 350,699 205,203 504,657 544,960 42,109 485,956

9 200,578 89,125 43,691 75,236 454 435,768

10 147,222 70,434 92,680 118,969 1,525 388,079

11 215,446 437,992 261,424 289,824 6,039 458,991

12 34,089 151,648 320,713 358,358 7,874 183,370

13 10,678 276,646 470,217 494,661 29,715 69,539

14 10,385 291,385 549,856 594,946 42,683 65,453

15 128,326 198,547 371,092 421,902 15,141 333,763

16 22,348 592,443 968,702 989,134 56,281 107,379

a. Measurement location 8 was a variable location that represented the BZ location that was used in the C-Lab study.

To evaluate potential differences between BZ and GA air concentrations from the Whicker and Moxley 

(2001) study, the ORAU Team used the data in Table 8-1 to evaluate the two BZ location scenarios 

described at the end of Section 3.0. 

8.2.1 Statistical Evaluation of the Data

The two BZ location scenarios described at the end of Section 3.0 were used to evaluate the potential 

differences between the BZ and GA air concentrations in the Whicker and Moxley (2001) study. The 

following describes how Scenario 1 and Scenario 2 were evaluated using the data from Table 8-1. 

For each scenario, a lognormal model was fit to the dataset for that scenario using ROS, generating a 

GM and GSD for each model. In the quantile-quantile plots below, the quantiles are from the fitted 

lognormal distribution, and the horizontal lines are the 50th, 84th, and 95th percentiles for the plotted 

data (ORAUT 2020). 

For the Scenario 1 and Scenario 2 evaluations, BZ:GA ratios were calculated for each potential BZ 

location from the air concentration data in Table 8-1. To produce those BZ:GA ratios, all 16 air 

sampler locations were evaluated as potential BZ locations. Then, for each of the 16 BZ locations, all 

16 air sampler locations were each designated in turn as the GA locations for all six release locations. 

For example, when the location 1 air sampler was designated as the BZ location (BZ-1), a BZ:GA 

ratio was calculated for each of the 16 potential GA locations and six release locations. This created 

a single BZ:GA ratio dataset consisting of 95 data points for the BZ-1 location. Because there was no 

air concentration result for the air sampler at location 3 for the first release location (R1), there were 

only 95 BZ:GA ratio combinations generated for each BZ location dataset. Then a lognormal model fit 

was performed on the new dataset for the BZ-1 location using ROS. This process was then repeated 

for each of the remaining BZ location designations until a new lognormal model was created for all 16 

of the BZ locations (ORAUT 2020).

8.2.1.1 Scenario 1 Results: Colocated Worker and Release Point

Only the lognormal model that was generated for BZ-8 location dataset was used for the Scenario 1 

evaluation. The location 8 air sampler represented the sampling location at each release point. As 
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indicated in Table 8-1, location 8 was a variable sampling location that was dependent on the location 

of the release point. The lognormal model for Scenario 1 is shown in Figure 8-2 (ORAUT 2020). 

Figure 8-2. Model for Scenario 1 (ORAUT 2020). 

8.2.1.2 Scenario 2 Results: Variable Worker Location Relative to the Release Point

For the Scenario 2 evaluation, the 16 lognormal models that were created for each BZ location 

designation were combined using Monte Carlo simulation to create a single dataset for Scenario 2. A 

lognormal model fit was then performed on the new dataset using ROS (ORAUT 2020). Figure 8-3 

provides the results for the Scenario 2 evaluation.
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Figure 8-3. Model for Scenario 2 (ORAUT 2020).

8.2.1.3 Summary of Scenario 1 and Scenario 2 Results

Table 8-2 summarizes the results from Sections 8.2.1.1 and 8.2.1.2 for Scenarios 1 and 2.

Table 8-2. Summary of the BZ:GA ratio distributions for Whicker 

and Moxley (2001).

Scenario

BZ:GA ratio 

GM

BZ:GA ratio 

GSD

Scenario 1 2.28 3.18

Scenario 2 1.02 4.31

9.0 DISCUSSION

As indicated in Section 1.0, the purpose and scope of this report is to evaluate the differences 

between the GA and BZ air concentrations for small workrooms and to determine if any adjustment to 

the GA air concentrations is necessary to make them equivalent to the BZ air concentrations in a 

small workroom. Based on the evaluations for this report, adjustments to GA air concentrations are 

warranted, and those adjustments can be made by applying the appropriate BZ:GA ratio distribution 

below. The appropriate BZ:GA ratio distribution is dependent on the worker’s exposure scenario and 

the type of workroom. 

9.1 COMBINED RATIO DISTRIBUTIONS

The datasets from each study were combined using Monte Carlo simulations to create a single 

dataset for each BZ location scenario (i.e., Scenarios 1 and 2) and for each evaluated ventilation 

scheme. With the exception of Gonzales et al. (1974), the studies evaluated only had one ventilation 

scheme. As explained in Section 4.3.3, three ventilation schemes were evaluated in Gonzales et al. 

for the same test room, and it was decided to weight that data more heavily by generating separate 

BZ:GA ratio models for each ventilation scheme. For each scenario, a lognormal model was fit to 

each dataset using ROS, generating a GM and GSD for each model. In the quantile-quantile plots 
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below, the quantiles are from the fitted lognormal distribution, and the horizontal lines are the 50th, 

84th, and 95th percentiles for the plotted data (ORAUT 2020). 

9.1.1 Evaluations for Scenario 1

As defined in Section 3.0, Scenario 1 assumes the worker (BZ location) was always located at the 

same X,Y coordinates in the room as the release point. Table 9-1 summarizes the BZ:GA ratio 

distributions for each of the evaluated datasets for Scenario 1.

Table 9-1. Summary of BZ:GA ratio distributions for Scenario 1.

Study

BZ:GA ratio 

GM

BZ:GA ratio 

GSD

Gonzales et al. (1974) – 0° ventilation direction 1.35 3.37

Gonzales et al. (1974) – 90° ventilation direction 1.59 4.13

Gonzales et al. (1974) – 180° ventilation direction 0.852 2.00

Charuau (1987) 4.92 2.50

Scripsick et al. (1979a, 1979b) 30.5 3.31

Whicker and Moxley (2001) 2.28 3.18

The BZ:GA ratio distributions for Scenario 1 in Table 9-1 were combined to generate a single 

distribution that is representative of all of the evaluated studies for Scenario 1. This resulted in a 

combined BZ:GA ratio distribution with a GM of 2.95 and a GSD of 5.03 for Scenario 1 (Figure 9-1)

(ORAUT 2020). 

Figure 9-1. Combined model for all Scenario 1 models (ORAUT 2020). 

The generated data for Scenario 1 also indicate there is a significant difference between the BZ:GA 

ratios when the workroom is generally open in the middle of the room rather than when the workroom 

has significant obstructions in the middle of the room. Because the data indicate the BZ:GA ratios 

can be significantly higher when the workroom has significant obstructions in the middle of the room, it 

might be more appropriate to use a BZ:GA ratio based only on the data from workrooms with 

obstructions in the middle of the room. Therefore, the BZ:GA ratio distributions in Table 9-1 were 
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divided into two groups and reevaluated. The grouping in Table 9-2 represents the scenario when the 

workroom is generally open in the middle of the room. The grouping in Table 9-3 represents the 

scenario when the workroom has significant obstructions in the middle of the room.

Table 9-2. Summary of BZ:GA ratio distributions when workroom is open in the 

middle.

Study

BZ:GA ratio

GM

BZ:GA ratio

GSD

Gonzales et al. (1974) – 0° ventilation direction 1.35 3.37

Gonzales et al. (1974) – 90° ventilation direction 1.59 4.13

Gonzales et al. (1974) – 180° ventilation direction 0.852 2.00

Whicker and Moxley (2001) 2.28 3.18

Table 9-3. Summary of BZ:GA ratio distributions when 

workroom has obstructions in the middle.

Study

BZ:GA ratio 

GM

BZ:GA ratio 

GSD

Charuau (1987) 4.92 2.50

Scripsick et al. (1979a, 1979b) 30.5 3.31

The same statistical process used to evaluate the Table 9-1 distributions was used to evaluate the 

Table 9-2 distributions for Scenario 1. Based on this process, the combined BZ:GA ratio has a GM of 

1.39 and a GSD of 3.27 for Scenario 1 when the workroom is open in the middle of the room 

(Figure 9-2) (ORAUT 2020).

Figure 9-2. Combined model for Scenario 1 models that were for open 

workspaces (ORAUT 2020). 

The same statistical process used to evaluate the Table 9-1 distributions was used to evaluate the 

Table 9-3 distributions for Scenario 1. Based on this process, the combined BZ:GA ratio has a GM of 

12.0 and a GSD of 4.11 for Scenario 1 when the workroom has significant obstructions in the middle 

of the room (Figure 9-3) (ORAUT 2020).
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Figure 9-3. Combined model for all Scenario 1 models that were for obstructed 

work spaces (ORAUT 2020). 

9.1.2 Evaluations for Scenario 2

As defined in Section 3.0, Scenario 2 assumes the worker (BZ location) was not necessarily at the 

same X,Y coordinates in the workroom as the release point. Table 9-4 summarizes the BZ:GA ratio 

distributions for each of the evaluated datasets for Scenario 2.

Table 9-4. Summary of BZ:GA ratio distributions for Scenario 2.

Study

BZ:GA ratio

GM

BZ:GA ratio

GSD

Gonzales et al. (1974) – 0° ventilation direction 1.06 3.86

Gonzales et al. (1974) – 90° ventilation direction 1.04 6.80

Gonzales et al. (1974) – 180° ventilation direction 1.08 2.28

Charuau (1987) 1.00 2.94

Munyon and Lee (2002) 1.08 5.40

Scripsick et al. (1979a, 1979b) 1.43 3.64

Whicker and Moxley (2001) 1.02 4.31

The BZ:GA ratio distributions for Scenario 2 in Table 9-4 were combined to generate a single 

distribution that is representative of all of the studies evaluated for Scenario 2. This resulted in a 

combined BZ:GA ratio distribution having GM of 1.08 and a GSD of 4.02 for Scenario 2 (Figure 9-4) 

(ORAUT 2020). 
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Figure 9-4. Combined model for all Scenario 2 models (ORAUT 2020). 

The generated data for Scenario 2 did not indicate a significant difference between the BZ:GA ratios 

when the workroom is generally open in the middle of the room versus when the room has a lot of 

obstructions in the middle of the room. Therefore, no special consideration is warranted for 

Scenario 2 when there are obstructions in the middle of the room. 

9.2 OTHER OBSERVATIONS

As indicated in Section 2.0, the ventilation rate and room complexity were two of the six parameters 

that were thought to affect the level of mixing the most. However, comparisons of the individual 

BZ:GA ratio distributions and the combined BZ:GA ratio distributions indicate that ventilation rate and 

room complexity had less of an effect on the level of mixing than expected. An indicator of the level of 

mixing in a room is the BZ:GA ratio distribution. Mixing is likely more complete, as the GM and GSD 

for that distribution both approach unity.

9.2.1 Ventilation Rate

As indicated in Section 2.1.3, the ventilation rate is usually only evaluated in terms of air change rate, 

specifically AC/hr. In the studies evaluated for this report, there were six different air change rates 

(i.e. 6, 9, 10, 12, 15, and 90 AC/hr). To determine if the air change rates affected the BZ:GA ratio 

distributions for a specific scenario (i.e., Scenario 1 and Scenario 2), each of the BZ:GA ratio 

distributions from the evaluated studies were graphed in a scatter plot for each scenario. Because the 

9- and 10-AC/hr air change rates are nearly equal and because there were not many data points for 

them, they were combined into a single air change rate to simplify the scatter plots. As discussed in 

Section 4.3, in addition to Scenarios 1 and 2, the Gonzales et al. (1974) study data were evaluated for 

the two additional scenarios (Scenarios A and B). Scatter plots of the results of those scenario 

evaluations are depicted in Figures 4-5 through 4-7. Those scatter plots indicate that the differences 

between the Scenario A and Scenario B results are typically limited to a slightly higher GM for 

Scenario B. Because of that and because Scenario A is an unrestricted scenario (i.e., the GA 
Document No. ORAUT-RPRT-0097 Revision No. 00 Effective Date: 03/29/2021 Page 59 of 81

 

sampler could be anywhere in the test room), only the Scenario A data were used in the scatter plots 

to compare the air changes rates. 

The uncombined BZ:GA ratio distributions for Scenario 1 were obtained from ORAUT (2020) and are 

presented in Table 9-5. Figure 9-5, is a scatter plot of the uncombined BZ:GA ratio distributions for 

Scenario 1.

Table 9-5. Summary of uncombined BZ:GA ratio distributions for Scenario 1.a

Studyb

Air change

rate (AC/hr)

BZ:GA ratio 

GM

BZ:GA ratio 

GSD

Gonzales et al. (1974) – 0° v.d., 1-ft elevation 6 0.869 2.88

Gonzales et al. (1974) – 90° v.d., 1-ft elevation 6 1.52 3.49

Gonzales et al. (1974) – 180° v.d., 1-ft elevation 6 0.952 1.57

Gonzales et al. (1974) – 0° v.d., 2-ft elevation 6 0.687 2.24

Gonzales et al. (1974) – 0° v.d., 2-ft elevation 9 1.27 2.77

Charuau (1987) – 2.3 μm aerosol 10 3.02 1.88

Charuau (1987) – 10.5 μm aerosol 10 7.79 2.54

Gonzales et al. (1974) – 0° v.d., 1-ft elevation 12 3.05 3.33

Gonzales et al. (1974) – 90° v.d., 1-ft elevation 12 1.38 4.51

Gonzales et al. (1974) – 180° v.d., 1-ft elevation 12 0.674 2.44

Gonzales et al. (1974) – 90° v.d., 2-ft elevation 12 1.44 4.21

Scripsick et al. (1979a, 1979b) 12 30.5 3.31

Whicker and Moxley (2001) 15 2.28 3.18

a. Values in this table were obtained from ORAUT (2020) and rounded to 3 significant figures.

b. v.d. = ventilation direction.

Figure 9-5. Scatter plot of uncombined BZ:GA ratio distributions for Scenario 1 

(ORAUT 2020). 
Document No. ORAUT-RPRT-0097 Revision No. 00 Effective Date: 03/29/2021 Page 60 of 81

 

The uncombined BZ:GA ratio distributions for Scenario 2 were obtained from ORAUT (2020) and are 

presented in Table 9-6. Figure 9-6 is a scatter plot of the uncombined BZ:GA ratio distributions for 

Scenario 2.

Table 9-6. Summary of uncombined BZ:GA ratio distributions for Scenario 2.a

Studyb

Air change

rate (AC/hr)

BZ:GA ratio 

GM

BZ:GA ratio 

GSD

Gonzales et al. (1974) – 0° v.d., 1-ft elevation 6 1.03 4.10

Gonzales et al. (1974) – 90° v.d., 1-ft elevation 6 1.01 5.26

Gonzales et al. (1974) – 180° v.d., 1-ft elevation 6 0.984 1.88

Gonzales et al. (1974) – 0° v.d., 2-ft elevation 6 0.997 2.74

Gonzales et al. (1974) – 0° v.d., 2-ft elevation 9 1.00 3.78

Charuau (1987) – 2.3 μm aerosol 10 1.02 2.32

Charuau (1987) – 10.5 μm aerosol 10 1.01 3.67

Gonzales et al. (1974) – 0° v.d., 1-ft elevation 12 1.00 4.78

Gonzales et al. (1974) – 90° v.d., 1-ft elevation 12 1.01 7.88

Gonzales et al. (1974) – 180° v.d., 1-ft elevation 12 1.02 2.98

Gonzales et al. (1974) – 90° v.d., 2-ft elevation 12 0.995 7.29

Scripsick et al. (1979a, 1979b) 12 1.43 3.64

Whicker and Moxley (2001) 15 1.02 4.31

Munyon and Lee (2002) 90 1.08 5.40

a. Values in this table were obtained from ORAUT (2020) and rounded to 3 significant figures.

b. v.d. = ventilation direction.

Figure 9-6. Scatter plot of uncombined BZ:GA ratio distributions for Scenario 2 

(ORAUT 2020). 

Based on the scatter plots in Figures 9-5 and 9-6, the different air change rates appear to have less of 

an effect on the BZ:GA ratio distribution than expected. In these plots, the different air change rates 

do not appear to have any noticeable effect on the BZ:GA ratio distributions. 
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9.2.2 Room Complexity

Because the level of complexity of a room cannot be readily quantified, a qualitative review of the 

BZ:GA ratios and their respective room complexities was performed. In regards to room complexity, 

the room in Charuau (1987) had the most complex room configuration and likely the most complex 

ventilation flow patterns of the evaluated studies. The room in Scripsick et al. (1979a, 1979b) had the 

next most complex room. As anticipated, the two most complex rooms in the evaluated studies 

generated significantly higher GM values for their BZ:GA ratio distributions for Scenario 1. However, 

for Scenario 2, the GM values for their BZ:GA ratio distributions were much closer to unity. Therefore, 

room complexity does not appear to have a significant effect on exposure scenarios similar to 

Scenario 2. 

10.0 CONCLUSIONS

As indicated in Section 2.0, when the median of the BZ:GA ratio distribution becomes significantly 

greater than 1 or the GSD becomes large, the GA air concentration should be adjusted to account for 

the increased uncertainty in the BZ air concentration. Based on that and the combined BZ:GA ratio 

distributions presented above, the GA air concentrations in most small workrooms should be adjusted 

to make them equivalent to BZ air concentrations. Table 10-1 summarizes the results from 

Sections 9.1.1 and 9.1.2 for Scenarios 1 and 2. For the scenarios in Table 10-1, the appropriate 

BZ:GA ratio distribution can be applied to the GA air concentrations to make them equivalent to BZ air 

concentrations. 

Table 10-1. Summary of the combined BZ:GA ratio distributions.

Scenario

BZ:GA ratio 

GM

BZ:GA ratio 

GSD

Scenario 1 2.95 5.03

Scenario 1 – open in the middle 1.39 3.27

Scenario 1 – obstructions in the middle 12.0 4.11

Scenario 2 1.08 4.02

For acute exposure scenarios, the decision to use the results from Scenario 1 or Scenario 2 will be 

dependent on whether or not the worker was present at the release locations. Because it is unlikely 

that a worker would be located at the release location for every release event, the results from 

Scenario 1 would normally just be applicable to acute exposure scenarios, such as when the worker 

was at the release location during a radiological accident or excursion. Therefore, the results from 

Scenario 2 would usually be the more appropriate BZ:GA ratio distribution to use for assessing 

chronic exposure scenarios. However, in the rare instances when a chronic exposure scenario is 

more consistent with the description for Scenario 1, the results from Scenario 1 should be used. 

For convenience, the Worker Location Scenario definitions from Section 3.0 are represented below: 

• Scenario 1. Assumes the worker (BZ location) was always located at the same X,Y

coordinates in the room as the release point (i.e., colocated worker and release point).

• Scenario 2. Assumes the worker (BZ location) was not necessarily located at the same X,Y

coordinates in the room as the release point (i.e., variable worker location relative to the 

release point).

11.0 ANTICIPATED USE OF THE BZ:GA RATIO DATA

The use of the BZ:GA ratio information in this report is primarily intended for radiological workrooms 

with relatively long-lived radionuclides. Because short-lived radionuclides (i.e., having half-lives of 
Document No. ORAUT-RPRT-0097 Revision No. 00 Effective Date: 03/29/2021 Page 62 of 81

 

only a few hours or less) can affect the BZ:GA ratios in a workroom, the BZ:GA ratio information in 

this report is not intended to be used with short-lived radionuclides. As indicated in Sections 1.0 and 

2.0, all uses of the BZ:GA ratio information in this report will need to be justified on a case-by-case 

basis. Because all potential uses of the data in this report cannot be foreseen, it will be the 

responsibility of the users of this report’s BZ:GA ratio information to justify the use of it and the 

appropriateness of how they choose to apply it. As indicated in Section 2.0, there are five potential 

key parameters that should be considered when justifying the application of the generic BZ:GA ratio 

distributions in Table 10-1 to site-specific GA air sample results. Those parameters include: (1) room 

size, (2) particle size distribution for the airborne radioactivity, (3) ventilation rate for the room, 

(4) room complexity, and (5) the presence of dominant particles. 

1. As indicated in Section 1.0, the BZ:GA ratio information in this report is intended to be 

applicable to small workrooms. However, “small workroom” is an undefined and potentially 

highly variable term. 

The room sizes in the evaluated studies ranged from 17.6 to 105.0 m2

 (190 to 1,130 ft2). The 

room sizes that the BZ:GA ratio information is being used for should be reasonably 

comparable to those room sizes, and should not be used for rooms that are significantly larger 

than 105.0 m2 (1,130 ft2

). As the workroom size increases beyond 105.0 m2 (1,130 ft2), it will 

become progressively more difficult to justify using the BZ:GA ratio information in this report 

for that workroom.

In addition, because the studies evaluated for this report did not include any elevated releases, 

the BZ:GA information in this report might not be applicable to scenarios with elevated 

releases. As indicated in Section 2.0, elevated releases are considered to be above the BZ 

elevation and can include releases originating at a lower elevation that are propelled above the 

BZ elevation (e.g., jet releases, over pressurization releases, aerosol plumes lofted by heat 

sources, etc.) for the purposes of this report.

2. In the rare event that the particle size distribution is known for the air being sampled by the GA 

air samplers, one should consider adjusting the workroom’s GA air sample results to exclude 

the nonrespirable fraction before applying a BZ:GA ratio.

3. The BZ:GA ratios in this report are based on the data from rooms with a wide range of 

ventilation rates, which were expressed in terms of room air change rates in the evaluated 

studies. Those air change rates included 6, 9, 10, 12, 15, and 90 AC/hr. Based on the results 

generated from the evaluated studies, the air change rate appears to have less of an effect on 

the BZ:GA ratio distribution than one would expect. Therefore, the BZ:GA ratio information in 

this report is considered applicable to rooms with all but the most extreme air change rates. 

4. The complexity of the rooms and ventilation flow patterns appear to have the largest effect on 

BZ:GA ratio distribution, but that is mostly limited to Scenario 1 when there are obstructions in 

the middle of the room. In terms of complexity, the room in Charuau (1987) has the most 

complex room configuration and likely the most complex ventilation flow patterns of the 

evaluated studies. For exposure scenarios similar to Scenario 2, the complexity of the rooms 

and ventilation flow patterns do not appear to have much of an effect on BZ:GA ratio 

distribution. When evaluating Scenario 2 types of exposures, the BZ:GA ratio data in this 

report is likely applicable to all small workrooms. 

5. As indicated in Section 2.2.2, air sample data from workrooms with dominant particles are very 

unreliable. Therefore, using that data to assess worker exposures should be avoided when 

possible. However, when that is not avoidable, intake distributions should be calculated 
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instead of point estimates to account for the stochastic nature associated with sampling and 

inhaling those particles (Scott and Fencl 1999).

After justifying the use of this BZ:GA ratio information for a workroom, the next step would be to select 

the most appropriate BZ:GA ratio distribution from Table 10-1 in Section 10.0, which will depend on 

whether the exposure scenario is best represented by Scenario 1 or Scenario 2. Section 10.0 also

provides some guidance that might help with choosing between Scenarios 1 and 2. If best 

represented by Scenario 1, the user will then need to decide and justify which of the three Scenario 1 

ratio options is most appropriate for the workroom for which the BZ:GA ratio distribution is being used. 

The following describes one of the anticipated ways to use the BZ:GA ratio information in this report. 

The initial anticipated use of the BZ:GA ratio information provided in Section 10.0 is to multiply the 

appropriate BZ:GA ratio distribution from Table 10-1 to the GA air sample results for a workroom to 

make the measured air concentrations equivalent to BZ air concentrations in that workroom.

To illustrate the application of BZ:GA ratio information in this document, this section uses Scenario 2 

as an example on how to use the various BZ:GA ratio distributions to convert GA air concentrations 

into BZ air concentrations. In Section 10.0, the Scenario 2 models for all five studies are combined 

into a single BZ:GA ratio distribution for the Scenario 2 model, which has a GMBZ:GA = 1.08 and 

GSDBZ:GA = 4.02. Three examples are described below, which represent the three types of GA air 

concentrations that might be encountered. 

Example 1

When the GA air concentration has a lognormal distribution with a GMGA and GSDGA, the BZ:GA ratio 

distribution can be used to make it equivalent to the probability distribution for the BZ air concentration 

by using the following equations: 

GMBZ = exp ln ln ( ( ) ( ) GMGA + GMBZ:GA ) (11-1)

( ( ) ( ) ) 2 2

BZ exp ln GA BZ:GA GSD = GSD +ln GSD (11-2)

where

GMBZ = GM of the BZ air concentration distribution

GSDBZ = GSD of the BZ air concentration distribution

GMBZ:GA = GM of the applicable BZ:GA ratio distribution

GSDBZ:GA = GSD of the applicable BZ:GA ratio distribution

GMGA = GM of the GA air concentration distribution

GSDGA = GSD of the GA air concentration distribution

Based on Equation 11-2, the GSD of the BZ air concentration distribution will always be larger than 

the GSD of the GA air concentration distribution. For example, if GMGA = 10 μCi/cm3 and GSDGA = 

4.0, the GMBZ and GSDBZ would equal the following: 

( ( ) ( )) 3 GMBZ = += exp ln 10 ln 1 08 11 . μCi/cm (11-3)

( ( ) ( ) ) = +=

2 2 GSDBZ exp ln 4 0. . . ln 4 02 7 1 (11-4)
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Example 2 

When the GA air concentration is a constant, the BZ:GA ratio distribution can be used to make it 

equivalent to the probability distribution for the BZ air concentration by using the following equations: 

GMBZ GA BZ:GA = × C GM (11-5)

GSD G BZ = SDBZ:GA (11-6)

where

CGA = is the GA air concentration

For example, if the GA air concentration is a constant with a value of 10 μCi/cm3

, the GMBZ and 

GSDBZ would equal the following: 

3 GMBZ =× = 10 1 08 11 . μCi/cm (11-7)

GSDBZ = 4 02 . (11-8)

Example 3 

When the GA air concentration is not a constant and has a distribution other than a lognormal 

distribution (e.g., a normal distribution with an arithmetic mean and standard deviation), the BZ:GA 

ratio distribution can be used to make it equivalent to the probability distribution for the BZ air 

concentration by multiplying the two distributions together using Monte Carlo techniques. 
Document No. ORAUT-RPRT-0097 Revision No. 00 Effective Date: 03/29/2021 Page 65 of 81

 

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in Gonzales et al. (1974),” Oak Ridge, Tennessee, December 6. [SRDB Ref ID: 178684]

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Protection at the U.S. Department of Energy,” Radiation Protection Journal, volume 83, 

number 3, pp. 221–232. [SRDB Ref ID: 179236]

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ATTACHMENT A 

GRAPHS FROM GONZALES ET AL.

LIST OF FIGURES

FIGURE TITLE PAGE

A-1 Graphs of iso-concentration curves for a 0° angle air direction and 6 AC/hr........................... 69

A-2 Graphs of iso-concentration curves for a 0° angle air direction and 9 AC/hr........................... 70

A-3 Graphs of iso-concentration curves for a 0° angle air direction and 12 AC/hr......................... 71

A-4 Graphs of iso-concentration curves for a 90° angle air direction and 6 AC/hr......................... 72

A-5 Graphs of iso-concentration curves for a 90° angle air direction and 9 AC/hr......................... 73

A-6 Graphs of iso-concentration curves for a 90° angle air direction and 12 AC/hr....................... 74

A-7 Graphs of iso-concentration curves for a 180° angle air direction and 6 AC/hr....................... 75

A-8 Graphs of iso-concentration curves for a 180° angle air direction and 12 AC/hr..................... 76
Document No. ORAUT-RPRT-0097 Revision No. 00 Effective Date: 03/29/2021 Page 68 of 81

ATTACHMENT A 

GRAPHS FROM GONZALES ET AL. (continued)

As indicated in Section 4.2, of the 44 graphs depicting iso-concentration curves for Gonzales et al. 

(1974), only the 18 most representative graphs were presented in that study. For the purposes of this 

ORAU Team report, those 18 graphs (Figures 5 through 19 of Gonzales et al.) have been reorganized 

and provided below as Figures A-1 through A-8. The concentrations in the graphs are presented as a 

percentage of the measured air concentrations at the aerosol release point.

In relation to these figures, it should be noted that they do not depict the entire area of the test room in 

Figure 4-1 above. The dimensions of the test room were 20- by 20-ft (6.10- by 6.10-m), but Figures 5 

through 19 only depict a 16- by 14-ft (4.88- by 4.27-m) area in that room. In addition, Figures 5 

through 19 only provide iso-concentration data for a 10- by 14-ft (3.05- by 4.27-m) area (the monitored 

area).
Document No. ORAUT-RPRT-0097 Revision No. 00 Effective Date: 03/29/2021 Page 69 of 81

ATTACHMENT A 

GRAPHS FROM GONZALES ET AL. (continued)

Figure A-1. Graphs of iso-concentration curves for a 0° angle air direction and 6 AC/hr (Gonzales et 

al. 1974, p. 9-10).
Document No. ORAUT-RPRT-0097 Revision No. 00 Effective Date: 03/29/2021 Page 70 of 81

ATTACHMENT A 

GRAPHS FROM GONZALES ET AL. (continued)

Figure A-2. Graphs of iso-concentration curves for a 0° angle air direction and 9 AC/hr (Gonzales et 

al. 1974, p. 9-10).
Document No. ORAUT-RPRT-0097 Revision No. 00 Effective Date: 03/29/2021 Page 71 of 81

ATTACHMENT A 

GRAPHS FROM GONZALES ET AL. (continued)

Figure A-3. Graphs of iso-concentration curves for a 0° angle air direction and 12 AC/hr (Gonzales et 

al. 1974, p. 8 and 10).
Document No. ORAUT-RPRT-0097 Revision No. 00 Effective Date: 03/29/2021 Page 72 of 81

ATTACHMENT A 

GRAPHS FROM GONZALES ET AL. (continued)

Figure A-4. Graphs of iso-concentration curves for a 90° angle air direction and 6 AC/hr (Gonzales et 

al. 1974, p. 11-12).
Document No. ORAUT-RPRT-0097 Revision No. 00 Effective Date: 03/29/2021 Page 73 of 81

ATTACHMENT A 

GRAPHS FROM GONZALES ET AL. (continued)

Figure A-5. Graphs of iso-concentration curves for a 90° angle air direction and 9 AC/hr (Gonzales et 

al. 1974, p. 11).
Document No. ORAUT-RPRT-0097 Revision No. 00 Effective Date: 03/29/2021 Page 74 of 81

ATTACHMENT A 

GRAPHS FROM GONZALES ET AL. (continued)

Figure A-6. Graphs of iso-concentration curves for a 90° angle air direction and 12 AC/hr (Gonzales 

et al. 1974, p. 11-13).
Document No. ORAUT-RPRT-0097 Revision No. 00 Effective Date: 03/29/2021 Page 75 of 81

ATTACHMENT A 

GRAPHS FROM GONZALES ET AL. (continued)

Figure A-7. Graphs of iso-concentration curves for a 180° angle air direction and 6 AC/hr (Gonzales 

et al. 1974, p. 14).
Document No. ORAUT-RPRT-0097 Revision No. 00 Effective Date: 03/29/2021 Page 76 of 81

ATTACHMENT A 

GRAPHS FROM GONZALES ET AL. (continued)

Figure A-8. Graphs of iso-concentration curves for a 180° angle air direction and 12 AC/hr (Gonzales 

et al. 1974, p. 13-14).
Document No. ORAUT-RPRT-0097 Revision No. 00 Effective Date: 03/29/2021 Page 77 of 81

 

ATTACHMENT B 

REGION AREA FRACTIONS FROM ORAUT (2019c) 

LIST OF FIGURES

FIGURE TITLE PAGE

B-1 Calculated region area fractions for Scenario 1A ................................................................... 78

B-2 Calculated region area fractions for Scenario 1B ................................................................... 79

B-3 Calculated region area fractions for Scenario 2A ................................................................... 80

B-4 Calculated region area fractions for Scenario 2B ................................................................... 81
Document No. ORAUT-RPRT-0097 Revision No. 00 Effective Date: 03/29/2021 Page 78 of 81

ATTACHMENT B 

REGION AREA FRACTIONS FROM ORAUT (2019c) (continued)

Figures B-1 through B-4 provide summaries of the calculated area fractions for Scenarios 1A, 1B, 2A, 

and 2B, which were calculated in ORAUT (2019c). 

Figure B-1. Calculated region area fractions for Scenario 1A (ORAUT 2019c). 
Document No. ORAUT-RPRT-0097 Revision No. 00 Effective Date: 03/29/2021 Page 79 of 81

ATTACHMENT B 

REGION AREA FRACTIONS FROM ORAUT (2019c) (continued)

Figure B-2. Calculated region area fractions for Scenario 1B (ORAUT 2019c). 
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ATTACHMENT B 

REGION AREA FRACTIONS FROM ORAUT (2019c) (continued)

Figure B-3. Calculated region area fractions for Scenario 2A (ORAUT 2019c). 
Document No. ORAUT-RPRT-0097 Revision No. 00 Effective Date: 03/29/2021 Page 81 of 81

ATTACHMENT B 

REGION AREA FRACTIONS FROM ORAUT (2019c) (continued)

Figure B-4. Calculated region area fractions for Scenario 2B (ORAUT 2019c).