Strontium-90 contamination in vegetation from radioactive waste ...

P
,

ORNL/TM- 10453
Strontium-90 Contamination in Vegetation from Radioactive Waste
Seepage Areas at ORNL, and Theoretical Calculatlons of 9oSr
Accumulation by Deer
C. T. Garten, Jr., and R. D. Lomax
Environmental Sciences Division
Publication No. 2924
Date Pub1 ished June 1 987
Prepared by the
OAK RIDGE NATIONAL LABORATORY
Oak Ridge, Tennessee 3783 1
operated by
MART IN MAR1 ETT A ENERGY SYSTEMS, I NC.
for the
US. DEPARTMENT OF ENERGY
3 La45b 0263200 b

1 .
2 .
3
CONTENTS
Paae
LIST W FIGURES ...................................................................................................................... v
LIST OF TABLES .................................................................................................................... vi1
ACKNOWLEDGMENTS .............................................................................................................. ix
ABSTRACT ................................................................................................................................ xi
INTRODUCTION ................................................................................................................... 1
METHODS .............................................................................................................................. 2
2.1 SITE SELECTION ......................................................................................................... 2
2.2 GROUND-LEVEL GM SURVEYS ................................................................................ 2
2.3 VEGETATION SAMPLING .......................................................................................... 5
2.4 STRONTIUM-90 ANALYSIS ..................................................................................... 5
RESULTS ............................................................................................................................... 6
3 . t QUAL I TY ASSURANCE .............................................................................................. 6
3.2 SITE CHARACTERIZATION AND GROUND-LEVEL SURVEYS ........................ 6
3.3 STRONTIW-90 LEVELS IN P t M SAMPLES ................................................ 14
4 . FOOD CHAIN PIOOEL ........................................................................................................ 16
4 . 1 STEADY-STATE CALCULATIONS ........................................................................ 16
4.2 NON-STEADY-STATE CALCULATIONS ............................................................. t0
4.3 MOOEL PARAMETERS .............................................................................................. 18
4.3. 1 Ingestion Rate (r) ........................................................................................ 18
4.3.2 Fractional Assimilation (a) .................................................................... 19
iii
..

.......................................................................... 19
................................................................................... 19
................................................................................... 20
................................................. 26
......................................................................... “27
AT IONS ................................................................. 32
........................................................................... 36
APPENDIX A - Strontium- Concentrations in Plant Samples .................. 39
APPENDIX E3 . - Strontium-W C~ncentration~ in Soils and Vegetation
from the White Oak Creek Floodplain ........................................ 4
CES ....................................................................................................................
iv

Fiaure
1
2
3
4
5
6
LIST OF F I W S
rn
Distributlm of %r In mi1 south of SWSA-4. This figure was
originally published in Melroy et al. (ref. 3) acrd later reprinted
in Davis artd shoun (ref. 1 4) .................................................................................... 3
Location of groundwater seeps on the perimeter of SWSA-5 as
Ickntlfled by Doguld (ref. 1 ) .................................................................................... 4
Correlation between %r concentrations in plants determined
by Cerenkov ccnrmttng (Environmental Sciences Division) and by
radiochemical methods (Analytical Chemistry Division I.......................... 7
Map of the study area at seep S- 1 1, adjacent to SWSA-5,
showlng ground-?evel GH survey meter readings In thousands of
counts per mtnute at vartous statlons on the sampling grid.
Circled GM survey meter readings show where plant samples
were collected in Wmber t ......................................................................... 8
Map of tlw study area at sew S-5, adjacent to SWA-5, showing
the ground-level GM w e y meter readings in thousands of
cmts per minute at various stations on the sampling grid.
Circled GH survey meter readlngs Snow whm plant samples
were collected in ~overntw t 986 ........................................................................ 9
Map of the study area associated with the “bathtub seeps’ on
SWSA-4 showing ground-level GM swvey meter madings In
thousands of counts per minute at various stations on the
sampling grid. Circled 661 survey meter readings show where
plant samples were taken in November 1986 ............................................... 12
V

7
8
I)
10
11
Paae
November 1 986 ........................................................................................................... 13
Sr c ~ ~ c in plant ~ ~ ~ ~ ~ t ~
samples from the four study areas (see Appendix A for a
complete 1 isting of data) ....................................................................................... 15
Relationship between gro~nd-l~~e~ GH survey meter readings and
~ ~ ~ e s p ~ ~ ~ l n ~
Combinations OF usage fact
result in calculated steady
plant 9%r concentratlans for the seepage areas ......... I 7
d plant 9oSr concentration that
e 9*~r levels in deer bone more
than (above the line) or less than (below the line) 30 pCi/g.
n the line correspond to plant concentrations at the
as and the usage f ~ necessary ~ ~ to result r in a
callculated 903- concentration in bone of 3Q pCibg,. ................................. 24
Combinattons of usage factor and plant 90Sr concentratlon that
result in calculated 9%- ievels in deer bone m8re than (above
the line) or less than (below the line) 30 pWg after 0 week of
food chatn exp~s~r%, Paints on the line correspond to plant
concentrations at the study areas and the usage factor
to result in a calculated 9@r concentration in bone
of 30 pCi/g ................................................................................................................. 25
Vi

Table
1
2
3
4
LIST OF TABLES
m
Example steady-state ca~culation of %r concentration in
8eef bone ................................................................................................................. 21
Mean plant cmmtratlon and calculated concentration
in deer bones after dffferent Intervals of food chain
exposure ................................................................................................................. .22
Strontium-9Q plantsoil concentration ratios reported f m
studies done in the White Oa& Greek Watershed ................................... 28
comparison of Wir in seep water and seepage area
vegetat Ion ............................................................................................................... 31
vii

ACKNOWLEMjMENTS
We wtsh to thank the following persons for their asslstance with
varlous aspects of this work: J. S. Baldwln, E. A. Bondietti, 1. W. Burwinkle,
J. W. Evans, R. E. Norman, T. G. Scott, B. P. Spatding, and R. I. Van Hook.
ix

ABSTRACT
This report describes data obtained during a preliminary
characterization of levels in browse vegetation from the vfcinity of
seclQs adjacent to ORNB, solid waste storage areas (SWSA) where deer
( ~c#/’/eus viqinims ) were suspected to accumulate 9*Sr through the
food chain. The highest strontium concentrations in plant samples were
found at seeps associated with SWSA-5. Strontium-90 concentrations in
honeysuckle and/or blackberry shoots from two seeps in SWSA-5 averaged
39 and 19 nCi/g dry weight (OW), respectively. The maximum concentration
observed was 90 nCi/g DW. Strontium-90 concentrations in honeysuckle
and blackberry shoots averaged 7.4 nCi/g DW in a study area south of
SWSA-4, and averaged 1.0 nCi/g QW in fescue grass from a seepage area
located on SWSA-4. A simple made1 (based on metabolic data for mule
deer) has been used to describe the theoretical accumulation of 9%r in
bone of whitetai1 deer following ingestion of contaminated vegetation.
Based on an assumed 1% usage factor and measured mean
concentrations of WSr in browse piants from the four seepage areas
studied, the calculated 90Sr level in deer bone can easily exceed the
confiscation limit of 30 pCi/g for a 45-kg buck that browses contaminated
vegetation an a regular basis. The time required to attain a steaw-state
concentration is expected to be relatively long (more than 2 years).
However, calculations, again based on an assumed 1 X usage factor and mean
plant mSr levels, indicate that a &-kg buck could attain 90%
concentrations in bone >30 pCi/g after browsing times of 1 week ta 1 year.
xi

est that if 30 pCj
level for retaining deer kille
Sr/g deer bone is to be
ulid be considered as a possible action
level in making decisions a need for remedial measures, because
unrestricted access and Full utilization of vegetation contaminated with (5
results in calculated stea -state ~ ~ ~ x i r9Qr n u bone ~ ~
s ob

During the last 3 months of 11986, the Tennessee Wildlife Resources
Agency and the Wpartrnent of Energy condarcted a second year of organized
deer hunts on the Oak Ridge Wildlife Management Area for the purpose of
controlling deer numbers and mitigating the likelihood of deer-vehicle
accidents. Each deer taken by hunters from tfw Wildltfe Management Area
was monitored at a checking station for radioactive contmlnation.
Strontium-90 concentration 5n bone was measured with a scintillation
detector applfed to a bone sample from the fareleg of each animal. Durlng
the 1986 hunt, 29 of 660 deer killed (4.499) exceeded confiscation limits
corresponding to approximately 30 pCI WSr/g bone. This compares with 7
of 926 deer killed (0.8%) during 1985 hunts that exceeded such limits.
This report describes data obtained during a preliminary
characterization of 96r levels in browse vegetation from the vicinity of
seeps adjacent to ORM, solid waste storage area where deer were
suspected to accumulate strontium through ingestion of contaminated
vegetation. A simple model has been used to describe the theoretical
accumulation of 9% in deer foilowing ingestion of contaminated
vegetation. Appendices to this report swnmarlze previously collected or
published data ora WSr contamination in soil and vegetation from the White
Oak Creek Watershed. Collectively, this information is intended to help in
planning remedial actions that will reduce the frequency of contaminated
deer Wen in future hunts.

2. II SITE SELECT10
2.
2
aata relating to 90% contamination in seepage
eys. Two sites were
a ISWSA) 4 one located ora SWA-
ed "bathtub seeps"
ehes allows them to 1111 wlth water durlng rainy
s of the year), and a seco ed south of SWSA-4 on a f?
e from the bu
d (Fig. 1). Two sites 6 -1
of SWSA-5 (Fig. 2) at seepage
ldentlf led by ~ ~ ~ ~hese ~ four ~ dsites l were . selected for lmmedlate study,
the first deer h of 1986. A grld was established at
each slte to faciittate und-level radlaticrn surveys wtth an
end-w indow Geiger-Mcrli
2.2
meter, and vegetation sampli
Snute (cw) readings were made with an ~ - w ~ GM n ~ w
1986. The, end-
ic bag to prevent instrument
water) was of interest.

3: *)@O 9
n
3

4
ORWL GRID COORDINATE-NQWTW
0 60 120 180 244l
0 WELL I. I 1 I J
kr SEEP
MET E R S
ORML DWG 74-960%

2.3 VEGETATION SAMPLING
5
Plant samples (cmprlsed of leaves and stems) were obtained from
each site on two dlfterent oCCaSiMS: ( 1 ) In early November, t 986, during
site visits prior to GM ground surveys, and (2) in mid-Mvember, 1986,
during 6l-l gMwnd surveys. Grab samples taken during the first slte vlstt
were composfted for several dlfferent types of fresh vegetatton. Followlng
(IrooMJi-level GPl surveys, samples were selected on the basis of count-per-
minute readings at each intersection on the gr9d. Because of the season of
the year, most vegetatlan was not in tollage. Honeysuckle and/or
blxkberrgc, both alive in November, were the prevalent browse plants at
sites sther than the "bathtub seeps" site on SMA-4. Fescue grass was the
dominant vegetation type at the "bathtub seeps.".
2.4 STRONTIW-90 ANALYSIS
Plant samples were cut with scissors into small pieces, mixed, and -1
g (fresh weight) was put into a tared crucible. Samples were dried
overnight at 100 'C, weighed to obtain the sample dry weight (PW), and
shed in a muffle furnace at 500 'C for 48 h. The ash was dissolved in 1 mL
of concentrated nitric acid, the solution was brought to a volume of 10 ml
with distilled water, and 4 ml, was transferred to a plastic scintillation
vial containing 15 mL of distilled water. Vials were analyzed for 90Sr by
Cerenkov radiation counting? A %r standard was made to determine
counting efficiency. Concentrations were originally expressed as
disintegrations per minute (clpm) and later converted to Curies ( 1 Ci = 2.22
x 1012 dpm). Eight samples (after ashing and dissolution in acid) were

E
A paired t-test of t t split samgl wed a statistically
sign 1 f jcant dj f r erewe between 90% Inations by Cerenkov co
ernleal analysis (t = 294, df = 7, P (0.05). Despite a very strong
led radlon~~~~d~~ that we rated from
us and by the QRM
1, ~ e counting ~ tended @ to ~ ~ ~
of 8.9% (SD =
to the presence of other
~ t showed ~ that the ~ ~ d
Sr on QUP ~ ~ ~ p was ~ e n t
A-5 (Fig. 5). Seep 3-1 1 lies
)a Access
to the

1 E+06
1 E+05
1 E+04
1 E+03
1 E+02
1
7
Y = -646 + 0.92 (X)
r = 1.00
ORNL-DWG 87-1 1058
1 E+02 1 E+03 1 E+04 1 E+05 1 E+06
Cerenkov Counting Strontium-90 (dprnlg DW)
Ftg. 3. Correlation between %r concentrations in plants determiw by
Cerenkov cmt ing (Environmental Sciences Division) and by
md#ochernical methods (Analytical Chemistry Dlvision).

Thistle
We11 TI 17-1
_ _ _ _ _ _ _ _ _ _ L _ _ _ _ _ - _ - - - - - -
Ground Level GM Survey Meter Readings
in Thousands of Counts per Minute
1
Fig. 4. f the study area at se
d-level GM survey me
jacent to SWSA-5, *owing
in t h ~ sf ~ counts ~ per ~ d ~
minute at various stations on the ~~~1~~~ grid. Circled
meter readings show where plant samples were collected in
November 1986.

A B C D E F
........................................................................................
in Thousands of Counts per Minute
ORNL-DWG 87-1 1060
-
fig. 5. Map of the study area at seep S-5, adjacent to SWSA-5, showing the
ground-level GM survey meter readings in thousands of cmts per
minute at various stations on the sampling grid. Circled GM survey
meter readings Snow where plant samples were collected In
November 1986.
.

10
road. Vegetatlon Is pr~n~~pal~y he~aceou~ with few trees.
which containe
metal bridge.
high as 33,000 cfm immediately swth of sew S-11 (Fig. 4). The area of
hlghest 90% cont
water in ~ v e m 1986, ~ r is crossed by a narrow
s wlth the end-window survey meter we
'Inatlsn (preliminarily defined by the gro
was c200 m2, LOW level Wjr contamtnattan may exlst on the floodplain
south of the set
from the migation of seepage water toward
Branch. Other notable features at the S- 1 1 site included: 1) a deer
o~pin~s in a dense blackberry thicket at grid marker C-5,
tall, dead thtstle plant Imrnedlately south of the road gave surface beta-
gamma readings of -7 mR/h (21,000 cprn).
Seep S-5. swth of SWSA-5, was also characterized by high
level count-per-minute readlngs (Fig. 5). Contamination at site 3-5 is
confined to a narrow ditch that Is surrounded by steep embankments. There
are many large trees on the site with little herbaceous understory. Seepage
water was not present in the northernmost portion of the ditch In Nwemkr
; however, stmdlng water was present behlnd a weir In the s
portion of the ditch Wore it mptles Into Plelton Branch. The hlgnest
-level, co~t-~r-m~~te readlngs were ~ ~ ~ along o the steep ~ t ~ ~ ~
center course of the
to its ~ ~ ~ ~ ) wt u e ~ c e
tered at the "Bathtu

encountered at seeps associated with SWSA-5 [readings near grlid rnarlcers
0-2 and 8-22 were 25,000 and 20,000 cgm, respectively (Fig. 611. ' Both
seeps had some Surface water discolored by iron. The vegetation at this
site is low grass and weeds. A well casing identified as 180-A is located
near grid marker 8-4, and a ditch, which drains to an area south of SWSA-4,
crossed the study site in an approximated NW-SE orientation (compass
readings w m erratic, pwhaps because of buried iron). The ditch
intercepts a downslope flow from the seeps, and appears to have prevented
migration of contamination from its south side (Fig. 6). The estimated
level of 90Sr contamination in surface soil in the general vicinity of the
"bathtub seeps" is between loo0 and 4000 Wi/g (Fig. 1). Deer have been
observed grating in this area of the burial ground.
Strontium-80 contamination in soil from the seepage area south of
SWSA-4 has been previously mapped3 (Fig. 1 ). Our survey south of SWSA-4
transected two areas of high surface %r activity (Fig 7): the %r
concentration in soil at grid marker 0-9 was -50,000 pCi/g, and the
surface wit concentration at marker 0-4 was 40,oOO pCi/g. The
westmost portion of the survey area included two trench-like
depressions (orre between 0-2 and 0-3, and one between €04 and 0-4) that
contained standing water in November 1986. The eastern portion of the
survey area, centered about marker D-9, was drier. The pund-level GM
survey meter readings at this site were lower than at any other seepage
area suweyed; a maximum reading of 26UO cpm was encountered (Fig. 7).
Higher ground-level readings encountered at the 'bathtub seeps" were
attributed to radionuclides other than %r. The "bathtub seeps" area is

12
I G F E D C B A
ORNL-DWG 87-1 lo61
DRAINAGE DITCH
Ground Level GM Survey Meter Readings
in fhousands of Caunts per Minute
.... 0.7 .........
Fig. 6 Map of the study area associated with the "bathtub seeps" on SWSA-4
showing growIcf-leve1 GM swvey meter readings In thousands of
counts per minute at various stations on the sampling grid. Clrcled
GM survey meter readings show where plant samples were taken In
November 1986.

ORNL
N
3 4 5 6
13
ORNL-DWG 87-1 1062
Ground Level GM Survey Meter Readings
in Thousands of Counts per Minute
Fig. 7. Map of the study area w th of SWSA-4 showing gsound-level fiM
survey meter readings in thousands of counts per minute at various
stations on the study area grid. Cfrcted Gfil swvey meter reiadrngs
show where piant samples were taken in November 1986.
1
I
I

14
known to contaln elevated levels of 1 Ws in soil.
There was evidence of deer browsing in vegetation from the st
south of SWSA-4. Dew bedding and evidence of digs were mount
nearby seepage area located amidst heavy RNL swveyed
grid point W 390- 120 (Fig. 1). The latter se area is one of several
other identified seeps associated with SWA-4 (Fig. 1) that were not
studied; however, ground-level GM survey meter readings in the vicinity of
the ORNL swveyed grid point W 390-S 120 were GOO cpm.
3.3 STRONTIUN-90 LEVELS IN RANT SAMPLES
The highest CQnCe~~ratIons of fn plant samples were f
seepage areas assoctated wlth SWSA-5 (Flg. 8). Strontlwn-90
concentrations In honeysuckle and/or blackberry shoots from seeps 5-11
and S-5 averaged 39 and I9 nCf/ DW, respectlvely. The ax^^^
concentration observed was 90 nCi/g OW tn ysuckle collected south of
seep S-? ? (Ap9endlx A).
cmentratlons In honeysuckle and blackberry shoots
collected swth of SWSA-4 averaged 7.4 nCl/g DW (fig. 8). Cmentratfm
ranged between 9 and 21 nCVg DW on the western portion of the transect
survey meter readtrqs wer
sol) isosr cmentrations were estimated to be
area, except In the st
ation coefficient was 6.82 (df = 6). This coprelati
tered In fescue
area assoctated wlth seep S-9 1 where

Plant
Strontium-90
(nCi/g DW)
100
10
I
0.1
0.01
I .
' I ,
ORNL-DWG 87-1 1063
Maximum
0 Mean
lm Minimum
"Bathtub South of Seep S-5 Seep S-11
Seeps" SWSA-4
Fig. 8. Maximum, mean, and minimum WSr concentratlons in plant samples
from the four study areas (see Appendix A fw a complete listing of
data).

16
signiflcmt because of three dtscrete groups of data (Fig. 9). Fig. 9 shows
that wer the sites examlined, -level readings wlth the GM survey
P C0.W t 1.
weakly correlated with %r concentrations in plants (r = 0.65,
4. FOOD CHAIN MOlXL
A simple mode) ob 9%r accumulation In deer was derlved rrom data for
tim metabollsrn In mule deer ~~~~~
In
age from 8 to 36 m
Whitetall deer we simtlar to mule deer In body size and habtts, except that
whitetail deer prefer forest habitats.
4.1 STEADY-STATE CALCULATIONS
he steacty-state skeletal concentration of %r in deer from
continuous ingestion of contaminated vegetation can be estlmated from the
following equation:
WtW@
S = skeletal cmcantsatl
I = daily ingestion (pCi/d),
a = fractional arsslmilatiorr fnwn t
constant (per
rn = skeletal mass (9 OW).
This equation assumes that, followtrq ingestion absorption into t
, This is a

100
80
20
ORNL-DWG 87-1 1064
Bathtub Seeps
0 South Of SWSA-4
Seep S-11
0
0 10 20 30 40
Ground Survey (kcpm)
Fig. 9. Relationship between ground-level GM survey meter readiys and
corresponding plant 90~r concentrations for the seepage areas.
Seep S-5 I L
J
,

seeking radlmlide.
where
cmwaflve assumption since is known to be a
Dally dypstlor\ or can be estimated from the following equation:
c = piant concentration (pCl/g DW),
r = ingestion rate (9 DW/d),
e factor, or the fraction of diet from seepage areas.
4.2 NOM-STEADY-STATE CALCULATIONS
he skeletal concentratton or In deer bone, after a given time
interval of feedlng on contaminated veptation, can be estimated from the
f ol lowing equation:
where
si F the 9Qsr concentration in deer bone after time t,
I "C*cy*Cu,
t = the number of days that the contamlnated diet is utillzed.
4.3 L PMMTERS
4.3.1 /hgestr'cvr /b;ite (P)
The, amount ob ve is a functlm or weight, sex,
. In modeis of accmul at i on mule deer, Sc
Whicker4 used a d~~~~ lngestlm rate of 16.5 g DW vegetatlon/kg bo

19
wel@t for WS, and between -18 d 22 9 vegetation/kg body weiwt for
does. For the present calculatians, we can assume an average ingestion
rate of 17 g DW vegetatim/kg body wei@t/day in whitetail deer; the
ingestion rate is multiplied by deer body weight (kg) to obtain qms dry
weight ingested per day.
4.3.2 Fractiml AssjmhWim (a)
Schreckhlse and Whicker4 found that the fractional assimilation of
strontium from the 61 tract varles between bucks (a = 0.128) and does (a =
0.0377). Gender differences and seam1 variation in assimilation are
apparently related to changing mineral requirements doring antler
develment.
4.3.3 EWnjnatim Cmtmt (€1
For bucks and does, the elimination constant for strontium in mule deer is
0.003~~ and 0.0~401 per day, respectively4. AI average elimination
constant of 0.0038, corresponding to a biological half-life of 182 d, was
assumed for the purpose of the present model. Sdreckhise and Whicked,
report that there is evidently a large mount of skeletal bone mobilized
during antler development in males. AI-I alternative twnover rate for goSr
in deer bone of 0.00026 pef day (7.3 year biological half-life) suggested by
~arris5 does not appear to be realfstic in view of mode1 validation work
presented by Schreckhlse and Whicker?
43.4 SXee/etal&w (m)
A value of 0.103 was used as the skeleton to total deer body weight ratio,
or 10.3% of the total body weight was skeletal mass?

4 4
Table 1 Snows an ~ x ~ cakullatlm p ~ e fw the ste
lrOnn if 45-Q f 108-1B) Wf. TM CakUlati
W#/g (the werage for
ss than that in males
effect of lactatlort and atkr variables m
the model parameters Is unknown. 8y cmpwlm, parmeter values for
males are based
tions of %r in plants
studied, calculations indicate that the
in bucks after vwyln
scation ilmlt of

. -
.
21
Table 1. Example steady-state calculation of %I' concentration in deer
bone
Item
SymlDOl Qr
Equation Units Male Female
Plant concentratiMla C pcwl 39,000 39,000
Deer body weight 8W kg 45.3 45.3
Daily ingestiw i g/kg BW/d 17 17
Ingestion rate r=W*i g/d 770 770
Usage factor U Ig 1 1
Estimated intake I = c * r * u pCi/d 300,339 300,339
Assim i lat ion fraction 8 0.120 0.038
Elimination constant
Skeletal massbody weight
E
ratio
perday
x
0.0038
10.3
0.0038
10.3
Skeletal mass M 9 4,666 4,666
Steady state
8m concentration S = ((I * a)/E]l/m pCVg 2,168 644
a dry weight basis.

Tale 2. Mean plant %s cmentration and calculated concentration In deer
bones after different intervals of food chain expaswe
Ite
After 1 week
After 2 weeks
After 1 month
After 3 months
After 6 months
After 1 year
Steady-state cmn.
Bathtub South Seeps-5 S
seeps SMA-4 SWSA-5 SWSA-5
1
3
6
16
28
42
56
11
21
44
120
206
so9
18,800
27
54
113
306
524
784
1,045
* Calculation far a 45-kg 100-1b) buck, assuming 1% of the diet is
tamtnated vegetati
39,l
57
113
234
635
1,089
1,630
2,168

23
food chain exposure, is also presented in Table 2. For seeps S- 1 1 and S-5,
calculated %r concentratlons in deer bone can exceed 30 pCiPg after 2
weeks of food chain exgosure. For the seepage area south of SWSA-4, -1
month of food chain exgowe was requlred &@fore calculated bone
concentratlons exceeded the conf1xatim limlt.
The usage factor in the model has a proportionate influence on
calculations of bone 9% in deer bone (i.e., a doubling of the usage factor
will double the calculated concentration). A usage factor of 1% has been
assumed in prior calculations, but the validity of this assumption is
unknown because the extent to which deer utilize the seepage areas for
food has not been determined. Assuming maximum usage (lQO%),
calculations show that a 90% concentration of (5 pCi/g OW in vegetation
results in calculated steady-state concentrations of

Plant
Strontium-90
(nCi/g DW)
100-
0-
1-
I .I..
......... C...*3C...- .............................. C-..
\m ..... seep S-1 1 ;.:.:-;: ........... .........................
L , I,..
.............. : r ..........
\:
-...*-.... ..................................
I . : :::::: :
.............. . ,:..+seeD S-5 .......... ....... ---.,...,..,..+.,.
.......... :
....... L...-L..A..L.~.~-.
I I.. I I.
.......
..
I,.
ORNL-DWG 87-1 1065
. . . . . . I ,
I -c IC
I.
, : : : : : Above the line -7.:
I * I . .
I. - -r .C
. . : . : . : . : : . Bone>30pCi/g i i
, - -r -e
I , I . . I.
........ .......
........ .......
. . .
..... 2 .... :...&.&.:.&&: ....
I I . . * I .
....... . I . . I . . . I . . I . .
..... . I . . I . . .......
Below the line ....... ...... L...I..A-..-a.I-.
Bone e30 pCi/g
................ .. .. ... .. ..... ...
........
. I
I .
.
I..
0.1 -
0.01 0.1 1
Usage Factor (%)
Fig. 18. Combdnations of usage factor and plant 9% concentr
result in calculated steadystate 90% levels in deer bone more
than (above the line) or less thm (below the line) 30 p
on the 11w correspond to plant concentrations at the s
and the usage factor necessary to result in a calculate
concentration in bone of 30 pCi/g.
-. . -. .c ... -c -c
.......
13
b

'p
.t-w
. . .. .
0
r
F
25

26
exposure) show that more than 4% us of vegetation from the three more
highly contaminated seepage areas 6 - 1 1 , S-5, and south of §MA-4)
results in calculated bone concentrations exceeding 30 pCi/g (Fig. 1 1).
5. SOIL-TO-PLANT TRANSFER OF STRONTlW-90
In the late 195 's, 903- was recognlzed as a potential accumulator in
terrestrlal ecosystem eom onents of the ite QaR Lake bed. Mean
concentrations in grasses, forbs, and woody plants occupying the lake bed
from 1456 to 196 were 0.31, 0.77, and 0.56 Ki/g DW, respectivelyd.
Strontium-90 concentratlons were higher in leaves than In stems arrd
higher in forbs and woody plants than In herbaceous plants. DeSelm and
Shanks6 esttmated that approximately 7% and 29% of the soll strontium was
removed by lake bed willows and herbaceous vegetation, respectively. Much
of this removal was recycled back onto the topsoil as accumulated lltter.
Baes et al.7 reviewed existing literature on the plant:soll concentration
ratios or vartous radi(3nuclides. The range or reference mean values ror the
plant:soll concentration ratio of WSr was 0.077 to 17, with a geometric
mean of 2.7. Variability In the ratio arises from regional variation in soil
parameters affecting 9% upt e by plants. The foremost soil property
affecting uptake by plants IS the status or exchangeable caletum in SOH.
Plant cmentrations decrease w lth increasing exchangeable soil calcium.
Other soil properties, like e, and organic matter, can become
important in determining W ~P uptake by piants in neutral or alkaline soils
or in sails where more t
78% of the exchange capacity Is calcl
saturated$. Tncl relatlonshlp between 9%- levels In soil and plants Is
clfie conditions.

27
There is little empirical data from which to derive representative
plantsoil concentration ratios for 9% in the White Oak Creek Watershed.
Surface soils of the Tennessee ridge and valley province are typically
acidic (pH between 5.5 and 6.51, and in general, the plant uptake of %r is
greater from acid soils (pH

Table 3. Strontium-90 p1ant:soil concentration ratios reported from
studies done in the i te Qak Creek Wateixhed
28
P1ant:Soli
90% soil concentration
P1 ant type (Wi/g DW) ratio Notes Reference
Sudan Grass 0.255 1.9 a 1
sp. 1
Corn 0.3 10 1.3 b 2
( Zea mays)
Herbaceous species 0.36 3.3 C 3
Uniden t i f ied 0.175 0.9- 1.6 d This report
grasses (Appendix 8)
a) From White Oak Lake be agricultural plot, soil l;bH = 7.1.
b) Concentrations in leaves from White Oak Lake bed agricultural plot.
Bi&n$ €qpatwim# and dmcm
c) Includes followfng plants: pa
d) From Whfte Oak Creek floodplain, soil pH = 7.5.
References:
1. Auerbach, S. I., et a\. 1959. Ecological research. pp. 18-54. IN Health
Physics Division epwt, July 3 1 , 1959. ORNL-2806.
Oak Ridge Natdonal Laboratory, Oak Ridge, Tennessee.
2. Auerbaich, S. f ., et al. 1858. Ecological research. pp. 27-52. IN Health
Physics Dlvision Annual Progress Report, July 3 1, 1958. ORNL-25W.
Oak Rldge National Laboratory, Oak Ridge, Tennessee.
3. Crossley, D., A., Jr.> and H. F. Howden. 1961. Insect-vegetation
relationships In an area contaminated by radioactive wastes. Ecology
42: 302-317.

that govern 9%r uptake and retention by female mute deer are not well
quantified, and the extent to which parameters vary between mule deer and
whitetail deer is unknown. To avoid uncertainties and to normalize
comparisons between seepage areas, the calculations presented here have
been made for a "standard" deer (45-kg, male). Despite these limitations,
the calculations are useful as first approximations for guidance in planning
remedial actions to prevent the food chain transport of 90Sr to QRM deer.
The accumulation of WSr in deer depends even more strongly on the
extent to which deer actually utilize vegetation from the seepage areas in
their diet. Utifization of the seepage areas depends on elements of animal
behavior that cannot be adequately represented in the food chain model used
in this report However, calculations indicate that a food chain exposure of
7 d duration and more than 49% utilization of vegetation from seep areas S-
1 1, S-5, or the area south of SWSA-4 can produce calculated concentrations
of 90% in deer bone in excess of 30 pci/g (Fig. t 1).
Calculations also indicate that even the modest (-10%) inclusion in the
deer diet of vegetation contaminated with relatively low levels (-100
pCi/g) of 909 can result in steady-state concentrations of this isotope in
deer bone exceeding 30 pC?/g. The time required to attain a steady-state
concentration is expected to be relatively long (more than 2 years assumfng
a biological half-life of 182 d); however, given sufficient time, long-term
low-level exposure can result in a degree of 90Sr accumulation by deer that
might necessitate confiscation. Back calculations, for a 45-kg buck, show
that 100% usage of browse vegetation containing a 9% level of -5 pCi/g
OW is the maximum plant concentration that will not result in steadystate

‘)osr concentrations in bone >SO pci/g.
Research is needed on land m
modification or soil treatments, th
from contaminated areas or reducl
30
too ex~ns~v@ or difficult to remove eontaminati
nt practices, such as habitat
be effective in deterring deer
ant uptake of g%r, because it
or to exclude
deer by fencing larger (nonpoint-source) areas of low-level contamination,
For example, superphosphate fertilizer treatments have been shown to
reduce the 9%- uptake by Sor grown on the upper White Oak Lake
bedlo. Various other treatments that are known to affect. the cation-
exchange capacity of the soil, can also alter the 9oSr uptake by plant@,
thereby reducing or increasing its food chain transport. The
soil treatments as a remedial action measwe must be carefully researched,
because the effectiveness of soil amendments depends upon soil acidity and
base saturation?
The possibility of habitat modification as a remedial action measure,
such as the progressive reduction of forest coverage throughout
contaminated portions of the watershed, should be evaluated in the context
of an overall long-term land management plan for White Oak Creek
Watershed.
The use of seeps for drinking water is another potential source of 90Sr
available to deer aside from seepage area vegetation. Conce
9%- in seep water and plant samples for three of the four sites exa
are compared In Table 4. The data are more than 10 years apart, but mean
concentrations in vegetation during 1986 exceed the reported
concentrations in seep water at each site in 1995. The maxim

31
Table 4. Comparison of 90%- concentrations in seep water and seepage area
vegetation.
90% concentration
Vegetation
Seep wafefl Meanb Vegetation:water
Location Seep (dpm/mt) (dpm/g DW) ratio
South of SWSA-4 5-2 45 1 16,440 36
SWSA-5 5-5 340 41,730 120
S-1 f 23 86,802 3,774
8 Data from Duguid, J. 0. 1975. Status report on radioactivity movement
from burial grounds in Me1 ton and Bethel valleys. OWL-50 I 7. Oak Ridge
Natlonal Laboratory, Oak Ridge, Tennessee.
b Data from 1986.

32
Concentrations in vegetation at each site exceed those in seep water by
factors between 100 and mwater ratio und~u~te~ly
varies, depending on the the time of collection;
therefore the importance o of 9QSr to deer is
difficult to assess bec ances of expo
However, for the seeps
contaminated vegetation e important source
of 9QSr.
7. CONCLUSIONS AN
1. The two seeps south of SWSA-5, S- 1 1 and S-5, are a hi
for remedial action than the seeps associated with SWSA-4. The areas of
high-level (> 1000 pCi/g DW) 90Sr contamination in vegetati
S-5 are relatively small (

33
seepage areas adjacent to SWSA-5. However, in terms of priority for
remedial action, the seeps associated with SWSA-4 (both the "bathtub"
seeps and those south of SWSA-4) are only slightly less important than
seeps adjacent to SWSA-5, because then! is apparently heavy use of SWSA-
4 by deer. This evidence includes frequent sightings of deer on SWSA-4 as
well as the presence of deer beds and digs in brushy areas adjacent to the
burial gramd. Assuming a 1% usage factor, calculations show that a food
chain exposure of -1 month in areas south of SWSA-4 results in calculated
90Sr levels in deer bone of >30 pCi/g.
3. Additional areas of environmental 9% contamination in the White
Oak Creek Watershed should be identified and surveyed for %r
contamination. Prior reports on the areal distribution of %r activity in
streambed gravels from the watershed1Zs13 and from seeps associated with
SWSA-4 and SWSA-51 1 J4J5 indicate that these areas fall into the
following broad categories:
seeps associated with solid waste disposal areas that have been
previously identified and are suspected of known sources of 90%
contamination to the environment,
e the exposed shoreline and sediments of White Oak Lake, particularly
secluded areas that are attractive to deer and where, based on historical
data16, WSr contamination in native vegetation is expected to range
between 100 and 1000 pCi/g,
floodplains adjacent to White Oak Creek and Melton Brarich where
environmental 9% contamination is suspected to exist because of prior
events in the history of OWL, or WSr migration away from seeps

34
associated with solid waste storage areas.
To aid this identificatlotn process, lished data on 90Sr
concentrations In surface soil and grass area of low-level
ination bordering White Oak Creek are wesented in Appendix 8.
Research is needed to empirically determine the plmt:soil c~centrat~on
ratios for 90Sr in a varlety of vegetation types from the White Oak Creek
Watershed, so that sites requiring remedial actions can be confide
the basis of 90% levels In soils when plants are not present.
calculations sug st that if 30 i of 90~r per gram of deer
bone 1% to be the accepted screening level for retaining deer killed on the
ation, then 5 pCi of 9oSr per gr dry weight vegetation should be
c ~ n § ~ as d a $ possible ~ ~ ~ action level in rnakfn decisions about the need for
remedial measures. This level is -25 times the background 90%
~ ~ ~ cin plants e ~ that t originates ~ ~ ~ from i we- ~ ~ 6 testing fallout.
Theoretical calculations show that unrestricted access and 100
utilization of vegetation contaminated with (5 pei of %r per gram
weight (by a 45-kg buck) results in calculated steadystate (maximum)
~ ~ ~ c of

35
Research is needed on land management practices, such as habitat
modification or soil treatments, that might be effective in deterring deer
from contaminated areas or reducing the plant uptake of %r; it may be too
expensive or difficult to remove contamination or to exclude deer by
fencing larger (nonpoint-source) areas of low-level contamination.

36
REFERENCES
1. Duguid, J. 0, 1975. Status report o radioact ivty movement fro
burial grounds in Melton and Bethel valleys. ORNL-50 17. Oak Ridge
~at~o~al ~aborato~y~ Oak Ridge, Tennessee.
2. Larsen, I. L. 198 1. Strontium-90 deter ination by Cerenkov radiation
counting for well ~ ~ n ~ at Oak ~ o idge ~ National i ~ g Laboratory.
ORNL/TM-7760. 0 k Ridge Natlonal Laboratory, Oak Ridge, Tennessee.
3. Melroy, L. A., D. 0. Huff, and N. D. Faro . 1986. Characterization of the
near-surface radionuclide Contamination associated with the bathtub
effect at Solid Waste Storage Area 4, Oak Ridge National Laboratory,
Tennessee. ORNL/TM- 10043. Oak Ridge National Laboratory, Oak Ridge,
Tennessee.
4. Schreckhise, R. G., and F. W. Whicker. 1976. A model for predicting
strontium-90 levels in mule deer. pp. 148- 156. IN C. E. Cushlng, Jr. ed.,
Radioecology and Energy Resources. Dowde , Hutchinson, and Ross, Inc.,
Stroudsburg, Pennsylvania.
5. Farris, G. C. 1967. Factors influencing the accumulation of %r,
stable strontium, and calcium in mule deer. Ph.0. dissertation.
Colorado State University, Ft. Collins.

6. DeSelm, H. R., and R. E. Shanks. 1963. Accumulation and cycling of
37
organic matter and chemical constituents during early vegetational
succession on a radioactlve waste disposal area, pp. 83-96. IN V.
Schultz and A. W. Klement, Jr. eds. , Radioecology, Proc. First National
Symposium, Reinhold Publishing Cow., New Yo&, and AISS, Washington,
0. C.
7. Bas, C. F., 111, R. 0. Sharp, A L. Sjoreen, and R. W. Shor. 1984. A review
and analysis of parametem for assessing transport of environmentally
released radionuclides through agriculture. OM-5786. Oak Ridge
National Laboratory, Oak Ridge, Tennessee.
8. Francis, C. W. 1978. Radiostrontium movement in soils and uptake by
plants. T6D-27564. National Technical Information Service,
Springfield, Virginia.
9. Goldman, M., W. M. Longhurst, R. J. Della Rosa, N. F. Baker, and R. 0.
Barnes. 1%5. The comparative metabolism of strontium, calcium, and
cesium in deer and sheep. Health Phys. 1 1: 141 5- t 422.
10. Auerbach, S. I., et al. 1961. White Oak Lake bed studies. pp. 81 - 105.
IN Health Physics Division Annual Progress Report, July 3 I , 196 1.
ORNL-3 189. Oak Ridge National Laboratory, Oak Ridge, Tennessee.
1 I . Spalding, B. I?, and I . L. Munro. 1984. Determination of the areal
distribution of 90% in groundwater via single-use boreholes,
ORNL/TM-899 1. Oak Ridge National Laboratory, Oak Ridge, Tennessee.
12. Cerling, T. E., and 8. P. Spalding. 1981. Areal distribution of f&o,
137Cs, and 90% in streambed gravels of White Oak Creek Watershed,
Oak Ridge, Tennessee. ORWTM-73 i 8. Oak Ridge National Laboratory,

Oak Ridge, Tennessee.
13. Spalding, 8. P., and T. E. Cerling. 1979. Association of radionuclides
38
with streambed sediments in White Oak Greek Watershed. ORNL/TM-
6895. Oak Ridge National Laboratory, Oak Ridge, Tennessee.
14. Davis, E. C., and R. R. Shoun. 1986. Environmental data package for
ORNL solid waste storage area four, the adjacent intermediate-level
liquid waste transfer line, and the liquid waste pilot pit area.
ORNL/TM- 10 155. Oak Ridge National Laboratory, Oak Ridge, Tennessee.
15. Stueber, A. M., 0. E. Edgar, A F. McFadden, and T. G. Scott. 1978.
Preiiminary investigation of %r in White Oak Creek between
monitoring stations 2 and 3, Oak Ridge National Laboratory. ORNUTM-
65 10. Oak Ridge National Laboratory, Oak Ridge, Tennessee.
16. Auerbach, S. I., and D. A. Crossley, Jr. 1958. Strontium-90 and cesium-
137 uptake by vegetation under natural conditions, pp. 494-499. IN
Proc. Second United Nations Geneva Conference on Peaceful Uses of
Atomic Energy, Vol. 18. Pergamon Press, London.

Bathtub
saeps
southof
WSA-4
seeps-1 1
(SWSh-5)
seep s-5
(SWSA-5)
39
Appendix A
Strontium-90 Concentrations in Plant Samples
131
02
03
04
DS
06
07
08
03
04
DS
F4
A4
08
09
Dl0
F9
A9
86
cb
D6
E6
84
05
c7
07
A1
81
C1
01
M
02
D3
F5
0.38
0.32
0.44
0.47
0.43
0.41
0.43
0.52
0.34
0.17
0.40
0.36
0.35
0.27
0.39
0.48
0.42
0.33
OS8
OS4
0.20
0.38
0.42
0.5 1
0.5 1
0.38
0.40
0.4 1
0.35
0.36
0.39
0.37
0.24
0.35
0.80
1.43
t .79
1 .%
8.8 I
0.68
0.47
0.03
2.07
0.6s
1.70
7.1 1
3.24
9.17
12.6 1
20.70
11.62
5.17
17.58
63.92
51.17
63.24
5.98
90.07
8.97
12.13
20.82
7 I .60
3 1 .05
6.24
3.80
4.07
2.40
10.40
0.5
14.0
9.0
15.0
18.0
14.0
1 .2
0.2
2.0
2.2
1 .o
0.9
2.2
2.2
2.6
2.2
2.5
2.3
2.7
20.0
20.0
19.0
11.0
35.0
18.0
7.0
15.0
18.0
31.0
8.0
12.0
4.0
2.0
23.0

Appendix B
Strontium-90 Concentrations in Soils and Vegetation from
the White Oak Creek Floodplain
The White Oak Creek floodplain lies to the east of SWSA-4 (Fig. B. 1)
and borders an abandoned channel of White Oak Creek. A 30 x 30-m grid
has been surveyed on the the floodptain, in conjunction with prior
radioecology investigationsl, to study radionuclide migration from SWSA-
4. The site, -0.5 krn downstream from ORNL, received effluents containing
fission products when in service as a temporary settling basin during 6
months in 1944. The soil profile is azonal because of periodic erosion and
deposition of sediments related to flooding. The soil texture is a loamy
clay, and the soil is slightly alkaline (pH 7.1 to 7.6) because of alkaline
treatment of the waste effluents in 1944. More detailed descriptions of
this site, including maps of 137Cs and 239Pu contamination, can be found in
references 1 through 3.
Paired samples of surface sol1 (0 - 7 cm) and plants were collected on
the floodplain at 27 stations (Fig. 6.2) in 1983. The mean surface soil
9oSr concentration was 388 dpm/g DW. Plant samples, collected in June
and August, were comprised principally of unidentified grasses
honeysuckle. The mean plant 90% concentration was 608 and 375 dpm/g
DW in June and August, respectively. Mean 9oSr concentrations in plants
were approximately equal to or 1.5 times greater than the mean
concentration in surface soil (Table 6. I 1. Two properties of the site that
probably help to diminish the plant uptake of 9*Sr are the high ("1%) silt

41
content of the soil and the high soil pH. Nonetheless, 9% concentrations
in plants, over the -9000-rn2 area surveyed in 1983, ranged from 129 to
1672 @m/g DW (58 to 753 pCi/g OW) (Table B. 1 1.

.
E uxn BASIN
4 A13 OgSERVATION WELL AND NUMBER
t . 681 PROPOSED OBSERVATION WELL AND NUMBER
0 cn3 CORE HOLE AND NUMBER
A CR3 CREEK WIlGUfflCi POINT AND NUMBER
0 FLOW OCIUGING STATION
__ SWSA 8 BOUNDARY (APPROXYATE) - ROAD _-- STREAM - U((OEROROUND WISE TRANSFER *
___.__
UNDLROROUND SURFACE DRAINAGE LINE - A-LT UNED DRAINAGL
0 HIGH LEVEL WASTE
0 TRENCHES COVERED WITH SWLE
TRENCHES COVERED WmC CONCRETE
A - 1 PROPOSED WATU MIALITV WEU AND NUMBER
FLOW GAUGW
STATON 12A
Fig. 8.1. Map of SWSA-4 showing site features and locatlon of the 38-m
grid system superimposed on the White Oak Creek floodplain east
of SWSA-4.
+
b

S 210
43
Toward SWSA-4 rsgO-P
0 Survey Point
e Sampling
Station
S 240
S 270
S 300
1
104 .9
S 180
I aii I
0
m
ti2
3
e13
Y a14
0 e15
ct)
16
+30 m -b
17 b
0
ORNL-DWG 87-1 1092
Toward Old
Creek Channel
Fig. 8.2. Sampling stations and grid swvey points on the White Oak Creek
f Imdplaln east of SWSA-4.

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
Minimum
Maximum
M
C.V!
766
258
272
319
rn
644
230
302
452
256
269
274
282
329
350
m
443
279
308
246
550
366
632
431
505
607
230
644
3
0.37
438
330
210
42
444
420
895
326
524
446
448
47 1
551
437
959
7081
454
915
#I8
233
194
743
3%6
712
lbsl
754
1 672
194
1672
6
0.60
44
7m
230
178
437
269
433
314
152
226
298
297
129
302
272
349
278
305
445
24
257
219
1412
414
3%
326
506
129
1412
375
0.67
i3 Plmt mples included mostly unidentiflad
Refer to Fig 8.2 for sample laxdim 011
2.22dpm = 1 pCi.
d C. V. = coefficient of variation = mean / starderd de~iatim.
0 57
1.28
0.77
1 .os
1.99
1.08
1.39
1.41
1.74
0.99
1.75
1.75
2.0 1
1%
2.92
2.02
1.34
2.06
221
0 -78
0.79
1.35
1.06
1.13
3.83
1.49
2.75
0.57
3.83
1 .58
0.46
1 .oo
0.89
0.65
1 .oo
0.84
1.1 1
0.49
0b6
0.711
0b6
1.16
0.
1.10
0 .%
1 .a
0.79
1.05
1 .oo
0.88
O M
0.89
257
1.13
0.63
0.76
1.01
1 .w
0.48
2.57
8.94
0.40
with m e mlm iracluslon le.

45
REFERENCES
1. Van Voris, P., and R. C. Dahliman. 1976. Floodplain data: ecosystem
characteristics and Cs-137 concentrations in biota and soil. ORML/TM-
5526. Oak Ridge National Laboratory, Oak Ridge, Tennessee.
2. Dahlrnan, R. C., and P. Van Voris. 1976. Cycling of Cs- 137 in soil and
vegetation of a flood plain 30 years after initial contamination. pp.
291 -298. IN C. E. Cushing, 3r. ed., Radioecology and Energy Resources.
Dowden, Hutchinson, and Ross, Inc., Stroudsburg, Pennsylvania.
3. Dahlman, R. C., C. T. Garten, Jr., and T. E. Hastonson. 1980. Comparative
distribution of plutonium in contaminated ecosystems at Oak Ridge,
Tennessee, and Los Alamos, New Mexico. pp. 37 1-380. IN W. C. Hanson
ed., Transuranic Elements in the Environment. ooE/TlC-22800.
National Technical information Service, Springfield, Virginia.

I. S. 1. Auerbach
2. 8. A. Bewen
3. E. A. 0ondietti
4. T. W. Burwinkle
5. C. Clark, Jr.
6. K. W. Cook
7. J. W. Evans
8. C. T. Garten, Jr.
9. 0. F. Mll
10. F. J. Human
I 1. J. R. Lawson
12. R. 0. Lomax
13. T. E. Myrick
14. R. E. Noman
15. 7. W. Oakes
47
1 NTERNAL D I STRI BUT I ON
16.
1 7.
i 8.
19.
20.
21.
22.
23.
24.
25.
26 - 40.
41 -42.
43.
44.
45.
EXTERNAL DlSTRlBUTfON
P. T. Owen
0. E. Reichie
P. S. Rohwer
T. f. Scanlan
B. P. Spalding
J. R. Trabalka
R. I. Van Hook
8. T. Wal ton
J. K. Wflliams
Central Research Library
ESD ti brary
Laboratory Records Department
Laboratory Records, RC
QRNL Patent Office
ORNL Y- 12 Technical Library
46. Tom Beasley, 9700 South Cass Avenue, Argonne National
Laboratory, Argonne, It 60439
47. Jack Blanchard, Office of Environmental and Health Affairs,
Department of State, Room 7820, Washington, M1 20520
48. Dewey L. Bunting, Graduate Program in Ecology, The University of
Tennessee, Knoxville, TN 37916
49. J. Thomas Callahan, Associate Director, Ecosystem Studies
Program, Room 336, 1800 G Street, NW, National Science
Foundation, Washington, DC 20550
50. J. 1. Cooley, Ecology Institute, University of Georgia, Athens, GA
30602
5 1. Colbert E. Cushing, Ecosystems Department, f3attelle Pacific
Northwest Laboratories, P.O. Box 999, Richtand, WA 99352

48
Process
52. G. J. Foley, Office of € ~ ~ i r o ~ ~ n t a ~
tal ~ ~ ~ A ~ e ~ 481 t M ~ iStreet, o ~ SW, RD- ~ ~ ,
Washington, DC 2046
53. C. R. Goldman, Professor of Limnology, Director of Tahoe Research
Group, Divlsion of En~iron~e~ta~ Studies, University of
~alifor~ia~ Da Is, CA 95616
54. J. W. Hucka~@@~ Manager, Ecalo cat1 Studies Program, Electric
Power Research Institute, 34 Hi 1 lview Aven e, P.O. Box 104 12,
Palo Alto, CA 94303
55. W. F. Harrts, National Science ~ o ~ n ~ 1800 a ~ G Street, t ~ ~ NW, ,
Room 336, Washington, DC 20550
56. George Y. Jordy, Director, Office of ~ r ~ ~ ralysis, a m Off ice of
Energy Research, ER-30,G-2226, US. Department of Energy,
Washington, DC 28545
57. C. J. Mankin, Director, Oklahoma Geo ical Survey, The University
of ~ ~ 830 Van ~ Vleet Oval, ~ R 163> ~ Norman, ~ OK 73019 ~ a ,
58. J. S. Mattice, Electric Power Research Institute, 3412 Hillview
Avenue, P.O. Box I04 i 2, Palo Alto, CA 94303
59. Helen McCarnrnon, Director, Ecological Research Division, Off ice
of Health and Environmental Research, Off ice of Energy Research,
MS-E2Q 1 , ER-75, Room E-233, Department of Energy, Washington,
DC 20545
60. J. Frank McComlck, The University of Tennessee, Knomi 1 le, TN
379 16
61. Robert 8. Min Research, US. Nuclear
Regulatory Commission, Was~~n~~~n, DC 20555
62. V. Nabholz, Office of Toxic Substances, ~ ~viron~~ntal Review
Division, U.S. E ~ ~ i r o ~ Protection ~ @ n t Agency, ~ ~ 40 1 M Street, NW,
was^^^^^^^, DC 20545
63. Christopher B. Nelson, Office of Radiation Programs, ANR-45
U.S. ~ ~v~ron~enta~ Protectio Agency, 401 M Street, SW,
Washington, DC 2

64.
65.
66.
67.
68.
69.
70.
71.
72.
73.
74.
75.
76.
49
Y. Ng, Environmental Sciences Divjsiun, Mal1 Code L-453, P.O. Box
5507, Lawrence hivermore National laboratory, hivermore, CA
94550
P. 6. Risser, Vice President for Research, The University of New
Mexico, Schoies Hall 108, Albuquerque, NM 87131
Warren K. Slnclalr, National Council on Radiation Protection and
Measurements, 79 10 Woodmont Avenue, Suite 10 16, Sethesda, MD
208 14
M. W. Smith, Savannah River Ecology Laboratory, Drawer E, Aiken,
SC 29601
R. J. Stem, Director, Office of Environmental Compliance, NS PE-
25, FORRESTAL, U.S. Department of Energy, 1000 Independence
Avenue, SW, Washington, DC 20585
W. L. Templeton, Battelle Pacific Northwest Laboratories, P.O. Box
999, Richland, WA 99352
Robert C. Watters, Ecological Research Division, Off ice of Health
and Environmental Research, Off ice of Energy Research, MS-E20 I ,
ER-75, Room F-226, US. Department of Energy, Washington, DC
20545
Leonard H. Weinstein, Program Director of Environmental Biology,
Cornel1 University, Boyce Thompson Institute for Plant Research,
Ithaca, NY 14853
F. W. Whlcker, Uepartrnent of Radiology and Radiation Biology,
Colorado State University, Fort Coil ins, CO 80523
R. Wildung, Battelie Pacific Northwest Laboratories, P.O. Box 999,
Richland, WA 99352
Raymond G. Wilhour, Chief, Air Pollution Effects Branch, CorvalIIis
Environmental Research Laboratory, U.S. Environmental Protect ion
Agency, 200 SW 35th Street, Cowailis, OR 97330
Frank J. Wobber, Divlsion of Ecological Research, Off Ice of Health
and Environmental Research, Off ice of Energy Research, MS-E20 1,
Department of Energy, Washington, DC 20545
M. Gordon Wolman, The Johns Hopkins University, Department of
Geography and Environmental Engineering, Baltimore, MD 2 12 I8

50
77. Office of Assistant Manager for Energy Research and Development,
Oak Ridge Operations, P. 0, Box E, Department of Energy, Oak
Ridge, TN 3783 1
78- 107. Technical Information Center, Oak Ridge, TN 3783 I