Draft White Paper 

Strategies to Investigate Allegations of 

Corrupt Bioassay Monitoring at Fernald 

Contract Number 200-2009-28555 

Prepared by 

S. Cohen & Associates 

1608 Spring Hill Road, Suite 400 

Vienna, Virginia 22182 

Saliant, Inc. 

5579 Catholic Church Road 

Jefferson, Maryland 21755 

June 2010 

Disclaimer 

This document is made available in accordance with the unanimous desire of the Advisory Board on 

Radiation and Worker Health (ABRWH) to maintain all possible openness in its deliberations. However, 

the ABRWH and its contractor, SC&A, caution the reader that at the time of its release, this report is predecisional and has not been reviewed by the Board for factual accuracy or applicability within the 

requirements of 42 CFR 82. This implies that once reviewed by the ABRWH, the Board’s position may 

differ from the report’s conclusions. Thus, the reader should be cautioned that this report is for 

information only and that premature interpretations regarding its conclusions are unwarranted.
TABLE OF CONTENTS 

Introduction......................................................................................................................................3 

1.0

................................................................................................................................4 

Strategy 1: Comparison of Urinalysis and In-Vivo Monitoring Data for Selected 

Workers

1.1 Theory and Approach ..............................................................................................4 

1.2 Feasibility/Proof of Concept....................................................................................4 

1.3 Benefits and Limitations of the Strategy .................................................................5 

2.0 Strategy 2: Consistency and Reliability of Urinalysis Results for Selected Workers ........7 

2.1 Theory and Approach ..............................................................................................7 

2.2 Feasibility/Proof of Concept....................................................................................7 

2.3 Benefits and Limitations of the Strategy .................................................................9 

3.0

......................................................10 

Strategy 3: Comparison of Daily Weighted Exposure Data to Urinalysis Records 

for Known Plant Areas, Job Types, and Time Periods

3.1 Theory and Approach ............................................................................................10 

3.2 Feasibility/Proof of Concept..................................................................................10 

3.3 Benefits and Limitations of the Strategy ...............................................................12 

Attachment 1: Technical Limitations of Urinalysis and In Vivo Methods in Determining 

Uranium Exposures............................................................................................................13 

Attachment 2: Example of Strategy 3 Analysis for the Pilot Plant in 1957 Using Claimant 

Data....................................................................................................................................15 

Attachment 3: Example of Strategy 3 Analysis for Plant 1 in 1967 Using DWE Urinalysis 

Data....................................................................................................................................17 

Draft White Paper – Fernald Monitoring 2 June 15, 2010 

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However, this report is pre-decisional and has not been reviewed by the Advisory Board on Radiation and Worker 

Health for factual accuracy or applicability within the requirements of 42 CFR 82. 
INTRODUCTION 

During the Fernald Work Group meeting on January 29, 2010, the concern was raised by 

petitioner [redacted] and others as to the integrity of the Fernald Feed Materials Production 

Center (FMPC) bioassay program; specifically, whether the data entered onto log sheets and 

other hardcopy records reflected the actual uranium sample results, or whether these data were 

systematically manipulated to avoid recording high internal exposures. SC&A was charged with 

developing strategies to investigate and analyze the issue, and provide information as to the 

feasibility and value of each approach. To this end, SC&A has developed three possible 

strategies to investigate the potential issue of data integrity related to the bioassay program at 

FMPC. 

The three strategies can be summarized as follows: 

(1) For a select group of workers, compare the urinalysis results to in-vivo count data to see 

if large increases in whole-body count results are reflected in the urinalysis records, or if 

they may have systematically under-reported uranium bioassay results. 

(2) For a select group of workers, perform biokinetic analysis of urinalysis records using 

Integrated Modules for Bioassay Analysis (IMBA) to see if implausibly large decreases 

in urine concentrations are a common occurrence after a high sample result. 

(3) Examine the available Daily Weighted Exposure (DWE) reports to identify the higher 

risk job titles, plant locations, and years for comparison with bioassay sampling for a 

group of claimants that can be identified by job title and plant locations by year. 

Further descriptions of each of these strategies are included in the following sections, and 

include the benefits and limitations, feasibility of the strategy, and an example implementation of 

the strategy (proof of concept). 

Given that each strategy requires some interpretation of urinalysis data (and in one strategy, the 

comparison with in-vivo data), technical considerations for these monitoring types must be 

considered. Because these technical issues are applicable to all three strategies, they are 

discussed in detail in Attachment 1 and only briefly summarized in each respective strategy 

description. 

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Health for factual accuracy or applicability within the requirements of 42 CFR 82. 
1.0 STRATEGY 1: COMPARISON OF URINALYSIS AND IN-VIVO 

MONITORING DATA FOR SELECTED WORKERS 

1.1 THEORY AND APPROACH 

This strategy involves a direct comparison of worker records for individuals involved in both the 

urinalysis and in-vivo counting programs. It is assumed that significant intakes of uranium 

would be reflected in both the urinalysis and in-vivo records for an individual. Therefore, it 

follows that increases in the magnitude of in-vivo samples would likewise be seen as an increase 

in urine concentration. A significant increase in the in-vivo monitoring results without a 

comparative increase in urine concentration might indicate the intentional under-reporting of 

urinalysis data. 

1.2 FEASIBILITY/PROOF OF CONCEPT 

Strategy 1 is dependent on the number of workers that can be identified who have a significant 

number of monitoring records for both the in-vivo and urinalysis monitoring programs. SC&A 

has identified 53 workers who had at least 10 samples in each monitoring category. An example 

comparison of in-vivo and urinalysis records for two of these workers is shown in Figures 1-1 

and 1-2. 

-10

0

10

20

1969 1970 1971 1972 1973 1974 1975 1976

Year

Monitoring Result

In Vivo Result (mg)

Bioassay Result (ug/l)

Figure 1-1. Comparison of In-Vivo (mg U Total) and Bioassay Results (ug/l U Total) 

for a Select Worker 

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Health for factual accuracy or applicability within the requirements of 42 CFR 82. 
-20

-10

0

10

20

30

40

50

60

70

80

1967 1969 1971 1973 1975 1977 1979 1981 1983

Year

Monitoring Result

In Vivo Result (mg)

Bioassay Result (ug/l)

Figure 1-2. Comparison of In-Vivo (mg U Total) and Bioassay Results (ug/l U Total) 

for a Select Worker 

1.3 BENEFITS AND LIMITATIONS OF THE STRATEGY 

Benefits: 

 Provides a direct comparison of individual worker records to identify any suspect 

urinalysis results based on the separate in-vivo monitoring program. 

 Workers who were targeted for both the urinalysis and in-vivo programs were likely 

believed to have the highest internal exposure potential for uranium. Because of the high 

potential for uranium intake, they would also be the likely targets for any under-reporting 

of urinalysis data. 

Limitations: 

 Urinalysis sampling and in-vivo monitoring were not carried out on the same days, so 

peaks and valleys on the magnitude of each monitoring method will not match up exactly 

on a time scale. 

 In-vivo monitoring was not performed at FMPC until 1968, so any comparisons can only 

be made from this year onward. 

Draft White Paper – Fernald Monitoring 5 June 15, 2010 

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However, this report is pre-decisional and has not been reviewed by the Advisory Board on Radiation and Worker 

Health for factual accuracy or applicability within the requirements of 42 CFR 82. 
Draft White Paper – Fernald Monitoring 6 June 15, 2010 

 This report has been reviewed for Privacy Act information and has been cleared for distribution. 

However, this report is pre-decisional and has not been reviewed by the Advisory Board on Radiation and Worker 

Health for factual accuracy or applicability within the requirements of 42 CFR 82. 

NOTICE:

 Comparisons are restricted to those workers who were monitored via both urinalysis and 

in-vivo counting. Workers who were only monitored via urinalysis may also have had 

their results under-reported, but would not be identified by this strategy. 

 Uranium solubility type has a significant effect on the rate of passage of uranium from 

the lungs into the blood and subsequently the excretion rate observed in urinalysis data. 

Furthermore, interpretation of in-vivo monitoring requires accurate knowledge of 

detection methods and procedures, as well as the relative abundance of individual 

uranium isotopes and daughter products. Without specific knowledge of these aspects, an 

accurate and reliable comparison of in-vivo results to urinalysis data may be difficult. 

Further discussion of this issue is found in Attachment 1. 
2.0 STRATEGY 2: CONSISTENCY AND RELIABILITY OF 

URINALYSIS RESULTS FOR SELECTED WORKERS 

2.1 THEORY AND APPROACH 

This strategy assumes that while integrity issues may have existed, the practice of underreporting the worker’s urinalysis results was not so widespread as to encompass all of the 

individual’s records. Therefore, workers with significant uranium intakes who had a portion of 

their urinalysis samples under-reported would show implausibly large changes in uranium 

concentrations reported over time. For example, a worker may have a high urine sample that is a 

reflection of an actual intake accrued. If this large sample is then followed by implausibly low 

samples, which cannot be explained by established biokinetic models, then this may indicate that 

these low samples have been under-reported. 

2.2 FEASIBILITY/PROOF OF CONCEPT 

One requirement for selecting workers for this strategy is that they must have a reasonable 

number of urinalysis measurements over a given timeframe. The urinalysis data contained in the 

HIS-20 database were broken down by decade to determine the pool of workers with a 

significant number of data points, and the results of this query are shown in Table 2-1. Decades 

were chosen as the cutoff point for Table 2-1; however, any combination of timeframes could be 

used to sample the worker records, depending on the timeframes of interest. 

Table 2-1. Frequency of Worker Sampling by Decade 

Number of Workers with Listed Number 

of Records by Period 

Number of 

Records in 

Period 1950s 1960s 1970s 1980s 

1–10 2442 1342 933 3317 

11–20 741 516 263 428 

21–30 371 392 64 246 

31–40 242 472 40 122 

41–50 149 253 88 91 

>50 293 369 90 337 

Based on the results shown in Table 2-1, there certainly appears to be a sufficient pool of 

workers to develop a random sample to test via this strategy. An example of the analysis 

proposed for Strategy 2 is presented in Figures 3 and 4 for a selected worker. For these IMBA 

calculations, it is assumed the worker sustained an acute intake of enriched uranium 

approximately halfway between the high sample and the previous sample. 

As shown in Figure 2-1, the subsequent bioassay results agree well with the high sample if a 

Type F absorption is assumed. If Type M absorption is assumed, then there are a couple 

bioassay samples which do not agree with the high sample. Figure 2-2 shows that even if Type F 

is assumed, there is one data point that is too low to be compatible with the high sample (data 

point is highlighted in red). 

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Health for factual accuracy or applicability within the requirements of 42 CFR 82. 
0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

0.16

Oct-55 Nov-55 Jan-56 Mar-56 Apr-56 Jun-56 Aug-56 Sep-56 Nov-56 Jan-57

Date

Bioassay Result (mg/l)

Sample Worker Bioassay

Calculated Bioassay Type M

Calculated Bioassay Type F

Figure 2-1. IMBA Predicted Bioassay Results Based on First High Sample for 

Select Worker Compared to Actual Bioassay Results 

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

0.16

Oct-55 Nov-55 Jan-56 Mar-56 Apr-56 Jun-56 Aug-56 Sep-56 Nov-56 Jan-57

Date

Bioassay Result (mg/l)

Sample Worker Bioassay

Calculated Bioassay Type M

Calculated Bioassay Type F

Figure 2-2. IMBA Predicted Bioassay Results Based on Second High Sample for Select 

Worker Compared to Actual Bioassay Results 

Draft White Paper – Fernald Monitoring 8 June 15, 2010 

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However, this report is pre-decisional and has not been reviewed by the Advisory Board on Radiation and Worker 

Health for factual accuracy or applicability within the requirements of 42 CFR 82. 
Draft White Paper – Fernald Monitoring 9 June 15, 2010 

 This report has been reviewed for Privacy Act information and has been cleared for distribution. 

However, this report is pre-decisional and has not been reviewed by the Advisory Board on Radiation and Worker 

Health for factual accuracy or applicability within the requirements of 42 CFR 82. 

NOTICE:

2.3 BENEFITS AND LIMITATIONS OF THE STRATEGY 

Benefits: 

 Directly examines individual bioassay records to identify inconsistencies in reported 

values that may indicate the practice of under-reporting high samples. 

 Strategy is not restricted to any one period during the SEC. 

Limitations: 

 The strategy relies on workers with multiple urine samples taken frequently over a given 

time period, and would not detect under-reported sampling for workers with sparse 

monitoring. 

 High urinalysis records may not have been the result of a significant uranium intake, but 

rather of alternate factors, such as the contamination of the sample. Therefore, 

subsequent records that show implausibly large drops in concentration may not be the 

result of under-reporting of the later samples, but rather the overestimation of the original 

high sample. 

 As mentioned in Strategy 1 and discussed in detail in Attachment 1, uranium solubility 

type has a significant effect on the excretion rate observed in urine. Without knowledge 

of the solubility type encountered by an individual worker, an accurate biokinetic 

assessment of urinalysis results becomes difficult. Further discussion of this issue is 

found in Attachment 1. 
3.0 STRATEGY 3: COMPARISON OF DAILY WEIGHTED EXPOSURE 

DATA TO URINALYSIS RECORDS FOR KNOWN PLANT AREAS, 

JOB TYPES, AND TIME PERIODS 

3.1 THEORY AND APPROACH 

Daily weighted exposure (DWE) reports are provided for various facilities, job types, and 

periods of exposure at FMPC. The DWE reports provide a comparison of the intake potential for 

various job types and plant areas. It is assumed that those job types and areas with the highest 

intake potential would also have a higher-than-average concentration of uranium in urine. Job 

title and work location data will be extracted from HIS-20 (when available) and compared with 

DWE reports to determine if there were consistently low bioassay results reported for workers 

with a high intake potential. If the higher-risk job titles consistently show below-average 

concentrations of uranium in urine, this might indicate that there was a systematic underreporting of high urine samples. 

3.2 FEASIBILITY/PROOF OF CONCEPT 

Table 3-1 provides a listing of DWE reports for FMPC by plant and year that SC&A was able to 

identify on the Site Research Database (SRDB). The identification of specific job titles is 

derived from the NIOSH DCAS Claims Tracking System (NOCTS), so only claimants can be 

used for comparison. Further restricting the pool of available workers is the fact that plant 

location is only reported in the HIS-20 database for select workers, and generally only from 

1953–1958 (and to a lesser extent, 1959–1961). 

Table 3-1. Availability of DWE Reports by Plant Area at Fernald 

Plant Area Identified DWE Reports 

Pilot Plant 1953, 1956–1957 

Plant 1 1955–1963, 1965–1967 

Plant 2 1955–1961 

Plant 2-3 1962, 1965–1968 

Plant 3 1956–1961 

Plant 4 1954–1965, 1967–1969 

Plant 5 1953–1963, 1965–1969 

Plant 6 1953–1959 

Plant 6 Inspection and 

Machining 1960–1968 

Plant 6 Rolling Mill 1960–1968 

Plant 7 1955–1956 

Plant 8 1955–1968 

Plant 9 1954–1955, 1957, 1959–1960, 1962–1966, 1968 

Table 3-2 shows the plants and years in which SC&A was able to identify a DWE report, as well 

as a group of claimants that are identified with that particular plant and year. One difficulty in 

matching up specific claimants to the DWE data is the fact that job titles listed in the DWE 

reports are much more specific than typically contained in NOCTS. The vast majority of 

Draft White Paper – Fernald Monitoring 10 June 15, 2010 

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Health for factual accuracy or applicability within the requirements of 42 CFR 82. 
claimants identified with specific plants have the rather generic job title of ‘operator’ or 

‘technician,’ whereas the DWE reports will specifically state what type of operator or technician 

is being examined (such as ‘medart straightener operator’ or ‘sample preparation technician’). 

Furthermore, the DWE report often contains multiple instances of a given job title with 

drastically different air sampling data. For example, the DWE report for Plant [redacted] in 

1961 shows [redacted] different DWE values for the ‘mill man.’ Depending on where in the 

plant the worker was stationed and what the specific duties were as a ‘mill man,’ the DWE 

values could range from 21 dpm/m3

 (~0.3 × MAC) to 1,750 dpm/m3 (~25 × MAC). 

However, one trend that holds true throughout nearly all of the DWE reports is that 

administrative personnel, such as clerks, recorders and foreman-type job titles, repeatedly had 

lower DWE air sample results than the various types of ‘operators,’ which consistently had a 

higher exposure potential. Therefore, in a general sense, the plant-specific urinalysis data can be 

examined to see if the operator job categories consistently have higher urinalysis results than the 

lower-risk jobs, such as the administrative categories. As an example analysis, the bioassay and 

DWE data are analyzed for the Pilot Plant in 1957 and provided in Attachment 2. 

Table 3-2. Plants and Years in which Claimant Urinalysis can be Matched 

and DWE Data Exists 

FEMP # of Claimants (# of Samples)* 

Location 1953 1954 1955 1956 1957 1958 1959 1960 1961 

Pilot Plant - - - 20 (184) 11 (53) - - - - 

Plant 1 - - 14 (42) 39 (140) 22 (49) - - - - 

Plant 2 - - 21 (85) 42 (127) 32 (67) 1 (1) - - - 

Plant 2-3 - - - - - - - - - 

Plant 3 - - 31 (93) 23 (43) 27 (64) 1 (1) - - 18 (18) 

Plant 4 - 5 (13) 16 (30) 26 (112) 27 (148) 4 (4) - - - 

Plant 5 8 (11) 5 (11) 48 (343) 61 (135) 69 (257) 9 (9) - - 1 (1) 

Plant 6 6 (6) 7 (21) 48 (167) 73 (444) 121 (822) 7 (7) - - - 

Plant 7 - - 42 (629) 25 (154) - - - - - 

Plant 8 - - 15 (66) 35 (197) 42 (387) 2 (2) - - - 

Plant 9 - - 5 (8) - 21 (58) - - - - 

* Dashes indicate that either no claimant samples could be identified or no DWE report is available for that plant 

and year. 

In addition, a handful of DWE reports contain an appendix that provides urinalysis data by job 

title. The benefit of this information is that the appendices use many of the same specific job 

titles as the DWE report; therefore, a much clearer connection can be made between the 

urinalysis and the DWE data. This additional urinalysis data can be checked for consistency 

with the exposure potential outlined in the given report. An example of this secondary approach 

is found in Attachment 3 for Plant 1 in 1967. 

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However, this report is pre-decisional and has not been reviewed by the Advisory Board on Radiation and Worker 

Health for factual accuracy or applicability within the requirements of 42 CFR 82. 

NOTICE:

3.3 BENEFITS AND LIMITATIONS OF THE STRATEGY 

Benefits: 

 Specifically investigates the highest risk jobs and plant locations, which would likely be 

the target of any purposeful under-reporting of urine concentrations. 

 A handful of DWE reports list average urine concentration results by job category for the 

given plant as an appendix. These data can be used to expand the pool of workers 

examined for that plant beyond available claimant data, and also provide a more direct 

comparison of the DWE and urinalysis data by job category. 

Limitations: 

 Daily weighted exposure reports identified are limited to the years and plants shown in 

Table 3-1. 

 Job title data for urinalysis sampling is limited to the claimant job categories on NOCTS. 

This pool is further restricted by the practice of reporting the plant location in the HIS-20 

records themselves (generally 1953–1958 and, to a lesser extent, 1959–1961). 

 Direct comparison of an individual worker’s urinalysis records to those workers analyzed 

in the DWE study is not possible, because of a lack of information on the specific 

workers sampled in the DWE study. This is further clouded by the same job title 

appearing multiple times in a given DWE report with drastically different air sampling 

results (i.e., the mill man in Plant [redacted], 1961). 

 It is not clear to what extent respiratory protection was used for high-risk jobs and 

specific workers. Therefore, even a worker who had the highest DWE assessment in a 

given plant and year may not have had significantly higher urine concentrations, due to 

the use of respirator or other personal protective equipment. 

 As stated in the previous strategies and further described in Attachment 1, uranium 

solubility type significantly affects the rate of passage of uranium into the urine. 

Therefore, if workers were exposed to a very insoluble form of uranium, it may not be 

reflected in the urinalysis records, even though that worker may have been subject to a 

high DWE to uranium. The inverse may also be true, in which a worker with a low DWE 

inhales a highly soluble form of uranium, which would result in a comparatively large 

urinalysis result. Further discussion of this issue is presented in Attachment 1. 
ATTACHMENT 1: TECHNICAL LIMITATIONS OF URINALYSIS AND 

IN VIVO METHODS IN DETERMINING URANIUM EXPOSURES 

This attachment describes the technical limitations of in-vivo and urinalysis monitoring methods 

in the context of their possible effect on the accuracy and conclusiveness of Strategies 1–3. 

Difficulties in Determining the Lung Content of Uranium from In-Vivo Monitoring Data: 

The uranium content in the lungs usually is estimated by in-vivo counting of 186 keV photon 

emissions from U-235. Depending on the sensitivity of the counting system, it may also be 

feasible to estimate the U-238 activity in the lungs by counting 63 keV and 93 keV emissions 

from the U-238 daughter Th-234, assuming Th-234 is in equilibrium with U-238. The accuracy 

of in-vivo lung measurements of uranium is limited by the weak photon energies (particularly 

from Th-234), the low yield of photon emissions, and uncertainty in the calibration associated 

with individual differences in chest wall thickness and location of internally deposited uranium 

in the chest. For Th-234 counting, an additional uncertainty is introduced by the assumption of 

its equilibrium with U-238. For the more common method of counting U-235 photon emissions, 

interpretation of the data depends on knowledge of the isotopic composition of the inhaled 

uranium. That is, one needs to know the relative amounts of U-234, U-235, and U-238 in the 

inhaled material in order to estimate the total uranium in the lungs. For example, the estimated 

total uranium content based on the U-235 content will be much different for depleted uranium, 

natural uranium, and uranium at various levels of U-235 enrichment, because of the large 

differences in the percentage of total mass represented by U-235. 

In evaluating the workability and relative merits of Strategy 1, it is important to assess the 

reliability of the in-vivo lung counting procedure at Fernald, including knowledge of the isotopic 

composition of the airborne uranium at times and locations of interest. Without specific 

knowledge of the counting procedure, methods, and types of uranium encountered, a comparison 

between in-vivo counting and urinalysis data may become difficult. 

Difficulties Arising from the Behavior of Inhaled and Absorbed Uranium: 

Inhaled uranium-containing materials show a wide range of dissolution properties in the lungs. 

The portion of inhaled uranium that is absorbed to blood shows a high level of urinary excretion 

soon after absorption. 

The more soluble uranium compounds show rapid removal from the lungs and rapid absorption 

to blood. Roughly two-thirds of the absorbed uranium is excreted in urine during the first 

24 hours. Thereafter, the urinary excretion rate declines rapidly. Only about 2% is excreted in 

urine during the next 24 hours, and the urinary excretion rate continues to decline thereafter. 

Since it is likely that relatively soluble uranium compounds were commonly handled at Fernald, 

large decreases in urinary uranium over a short period might be expected. This limits the 

usefulness of Strategy 2 for uranium workers at Fernald (i.e., a check for implausibly large 

decreases in urine concentrations after a high sample result). 

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NOTICE:

Urinary measurements generally are not a good way to monitor intake of relatively insoluble 

uranium compounds, such as uranium dioxide, because little of the inhaled activity reaches blood 

and hence little is excreted in urine. This would be a particular problem for Strategy 1, in that 

high in-vivo counts would not correspond to high urinary uranium, and perhaps not even to 

measurable urinary uranium in many cases. This would also be an issue for Strategy 3 if a 

worker with a high daily exposure was subject to an insoluble form of uranium. 

Given these considerations, reliable information about the uranium solubility type becomes very 

important. Although the HIS-20 database does provide a solubility type designation along with 

each urinalysis result, the origin and reliability of these solubility designations has not yet been 

established, so it is not clear to what extent they can be used for comparison with in-vivo counts 

(Strategy 1), biokinetic analysis (Strategy 2), or comparison with DWE reports. 
ATTACHMENT 2: EXAMPLE OF STRATEGY 3 ANALYSIS FOR THE 

PILOT PLANT IN 1957 USING CLAIMANT DATA 

The daily weighted exposure (DWE) data by job category for the Pilot Plant in 1957 is provided 

in Table A2-1. As one would expect, the higher DWE results are for the various types of 

operators, while the administrative job categories such as the supervisors were much lower. 

Table A2-1. Job Specific DWE Data Collected in December of 1957 

Job Title Area DWE Result 

(d/m/m3

) 

Remelt and Burnout Operators 3037 1,136.4 

Centrifugal Casting Operators 3037 942.5 

Reduction Operators 3037 346.3 

Chief Technicians 3037, 3620 313 

Roving Operators General Plant 210.8 

Saw Operators 3037 123.2 

All Personnel 3620 115.8 

Breakout Operators 3037 114.7 

General Operators 3013 71.7 

Chief Technicians 3013 66.2 

Superintendant, Administrative Assistant, Clerks Administrative 53.3 

Area Supervisor, Technologist 3037, 3620 46 

Area Supervisor 3013 27.5 

As was shown in Table 3-2, urinalysis data for 11 claimants (53 total samples) could be 

identified with the Pilot Plant in 1957. All but [redacted] of these 11 claimants had the job title 

of [redacted], while the [redacted] had the listed job titles of [redacted], which would clearly 

fall into that administrative category. By rank ordering the claimant data, it was found that this 

[redacted] bioassay sample fell at about the 16th percentile, which is in excellent agreement with 

the DWE data. 

In addition to this, the rank-ordered data for chemical operators were compared with the data for 

all workers (not just claimants) who could be identified with the Pilot Plant in 1957. The results 

can be seen in Figure A2-1, which shows that the uranium concentrations for chemical workers 

are very similar to the overall population of identified Pilot Plant workers for 1957. However, 

Figure A2-1 also shows that from the 20th percentile to approximately the 80th percentile, the 

uranium concentrations for chemical workers are just slightly higher than the Pilot Plant worker 

population as a whole. While the difference is not overly large, there is nothing that indicates 

that individuals in a seemingly higher-risk job category, such as the chemical workers, were 

having their urinalysis results systematically under-reported. 

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Health for factual accuracy or applicability within the requirements of 42 CFR 82. 

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

0 10 20 30 40 50 60 7

Uranium Bioassay Concentration (ug/l)

Rank Ordered Percentile

0

Chemical Operators

All Pilot Plant Workers

Figure A2-1. Rank-Ordered Plot of Chemical Operator Uranium Concentrations 

versus All Identifiable Pilot Plant Workers 

NOTICE:
ATTACHMENT 3: EXAMPLE OF STRATEGY 3 ANALYSIS FOR PLANT 

1 IN 1967 USING DWE URINALYSIS DATA 

Table A3-1 shows the DWE data for Plant 1 in 1967, as well as the plant average urine 

concentrations reported in an appendix to the DWE report. This table does not show very good 

agreement between the DWE assessments and plant average urine concentrations. For example, 

the job title of ‘Wheelabrator’ had by far the highest DWE; however, that job category had one 

of the lowest average urine concentrations. Meanwhile, the job title of ‘Williams Mill Operator’ 

had one of the highest average urine concentrations, yet had a comparatively low DWE. 

One possibility is that the jobs with the high DWEs all wore respiratory equipment during the 

highest risk activities. In fact, the DWE report does recommend that the ‘Wheelabrator 

Operator’ wear a dust-type respirator during the dustiest activity performed (operating the 

wheelabrator itself). However, the same recommendation is made for the ‘Williams Mill 

Operator’ during the dustiest activity for that job type (changing drums at the sampling station). 

So it is not clear why the DWE and urinalysis data for this plant and year do not seem to mirror 

each other. 

Table A3-1. Comparison of Job Specific DWE Data and 

Plant Average Urine Concentrations 

Job Title DWE Result 

(d/m/m3

) 

Plant Average Urine 

Concentration (mg/l) 

[Redacted] Operator 120 0.006 

[Redacted] Operator 50 0.012 

[Redacted] Technician 50 0.007 

[Redacted] Operator 50 0.005 

[Redacted] Foreman 20 0.003 

[Redacted] Clerk 20 0.003 

[Redacted] Operator 20 0.014 

[Redacted] 20 0.004 

[Redacted] Operator 20 0.021 

[Redacted] Operator 20 0.009 

[Redacted] Operator 20 0.006 

[Redacted] Clerk 10 Not Available 

[Redacted] Technician 10 0.002 

[Redacted] Operator 10 0.008 

[Redacted] Operator 10 0.011 

[Redacted] Operator 10 0.002 

[Redacted] 10 Not Available 

Draft White Paper – Fernald Monitoring 17 June 15, 2010 

NOTICE: This report has been reviewed for Privacy Act information and has been cleared for distribution. 

However, this report is pre-decisional and has not been reviewed by the Advisory Board on Radiation and Worker 

Health for factual accuracy or applicability within the requirements of 42 CFR 82.