
Interactions are violent, we assume that the material released Into air
would be distributed uniformly throughout the troposphere. Radionuclldes
released to air will affect people differently depending on whether the
nuclides are in the inhalation zone over land or in the air over the ocean
and on whether they deposit on land or in the ocean. We account for this
by splitting the inventory released to the air into two parts: that over
oceans and that over land, using the respective^surface areas of the
oceans and the land surface of the earth. This division of the airborne
material is for calculational convenience in developing the mathematical
equations for the environmental dose commitment analyses. Each curie of
radionuclide which is released is divided between that quantity released
directly to the land surface (f_L)» that released to air above land
(fAL), and that released to air above oceans (fAW)« We assume that
airborne material above land remains over land and that airborne material
above water remains over water.
3.4.2 Releases Directly to Land Surface
3.4.2.1 General Considerations
The radionuclides released directly to the land surface are
conservatively assumed to be distributed in a small area around the
release point. The methods used to determine vertical distribution and
resuspension at the source, dispersion in the environment, and resulting
ERC to the affected population are the same as those devised for the land
335

surface pathway (Section 3.3). The equations used for releases directly
to the land surface will be listed, for the sake of completeness, in the
following sections.
3.4.2.2 Food Ingestion
Food Crops (p=25)
Milk (p=26)
Beef (p=27)
FHE.
 >Tn(ttv)
• '
LL
(3.4.2,21)
where f., is the fraction of the radionuclides released to the
environment which go directly to land and ty is the time after placement
of radioactive material in the repository that material is released to the
environment.
3.4.2.3 Inhalation of Resuspended Material (p=24)
0.0622
np
=PDp RF IB
LL
1  e
^Tn(tty)
xDn xSn
+ XSn)(ttv)]
(3.4.2.31)
3.4.2.4 External Risk CommitmentGround Contamination (p=28)
FHE.
np PDp FCFnp SQF fll GCnp
1 —• 15
' {x
.
1  e
Dn
xDn * xSn
,
1
(3.4.2.41)
336

3.4,2.5 External Risk CommitmentAir Submersion (p=23)
FHE.
(np
= SOF FCF PD RF f
LL
0.0622
*Tn
[l
Dn Sn
 e
(3.4.2.51)
3.4.3 Releases to AirOverLand
3.4.3.1 General Considerations
The radionuclides released to the air over land surfaces are assumed
to be distributed uniformly In a volume determined by multiplying the
land surface area of the earth by the average height of the troposphere.
With the material distributed in this manner a two compartment model is
established, as depicted in Fig. 33, to predict radionuclide movement
between the air and the soil for use in computing the ERC for the various
pathways. The upper compartment in Fig. 33 is the tropospheric volume
above the earth's land surface and the lower compartment is the available
land layer, i.e., the layer of land containing the soil surface as an
upper boundary and including the root zone or plow layer of soil. It is
assumed that radionuclides enter the upper compartment at the instant a
volcano or meteorite Interaction releases radioactivity from the
repository. No further radionuclides are introduced into the system
after the initial input at t'= 0.
Radionuclides leave the upper compartment by radioactive decay (*Qn)
and by transfer from air to soil (vgn.AL/V,_) and they reenter the
337

Initial Input
To Air
(Initial Condition)
Radioactive
Decay
Radioactive
Decay
Tropespheric
Air Over Land
(Volume VL)
1) » quantity of material
in upper compartment, Ci
Transfer to soil
resuspenslon
to air
Available Land Layer
) = quantity of material
in lower compartment, Ci
nn
Removal from
available soil
F1g. 33. Compartment model for air over land,
volcano/meteorite release mode
338

upper compartment due to resuspension (XR). The assumptions controlling
our resuspension calculations are the same as discussed In sections 3.1
and 3.3. When radionuclides are deposited to the ground surface, we
assume that they quickly mix in the soil root zone (15 cm vertical depth)
and that only the radionuclides in the top 1 cm of soil are subject to
resuspension. Radionuclides enter the lower compartment by deposition
from air (VanAi/V ) and are removed from the lower compartment by
transfer to the unavailable soil layer USn), radioactive decay (xDn).
and resuspension from the top 1 cm of soil layer to air (XR). The.
radionuclide balance equations which can be written for this two
compartment system are discussed in the next section.
3.4.3.2 AirAboveLand: Two Compartment Model
To obtain the concentration of radionuclide n in the upper (air)
compartment, the quantity of n in the upper compartment, Pin^')* must
be predicted as a function of time and divided by the volume, V^, of the
upper air compartment. Similarly, to obtain the soil root zone inventory
of radionuclide n for the lower compartment, ^Tn^'^* tne 1uant'i'ty of n
in the lower compartment, Qcr/t'K must &e predicted as a function of
time and divided by the surface area, A. , for the lower compartment. To
obtain Qin(t') and Qcn(t')» a system of two coupled differential
equations, based on the nuclide balance shown in Fig. 33, is written and
solved. These equations are:
'Ln
dt
lDn vLn
«Sn'15
(3.4.3.21)
339

and
dQ vnn A.
(3.4.3.22)
and the Initial conditions for our model are
and
= fAL 'np
= 0
at t1 = 0 .
After a transformation of variables, these coupled differential equations
may be solved to yield QLn and QSn as follows:
^^'^' +<>»"M6nt ^.4.3.23)
15 f
AL
where
I5n
U6n = '
B4n   (a
 a5n)
XR/15)
•4n
5n
I5n
vinxR
M5n= !*L
4C
4n
M
6n
 4C
4n
i 6n 1
e J
(3.4.3.24)
340

Now, using equations 3.4.3.23 and 3.4.3.24, the air and ground
concentrations of radionuclides as a function of time can be calculated.
To compute the air concentration in the upper compartment as a
function of time, equation 3.4.3.23 is divided by the volume of the upper
compartment, which is V. = A. .h., to yield
AL . Qn
_
V
e °n + e
(3.4.3.25)
The soil root zone inventory for the lower compartment as a function
of time is obtained by dividing equation 3.4.3.24 by the surface area,
A,, of the lower compartment to yield
. np 5n 5n 6n 5n
^R(M6n  M5n' AL
i 6n 1
e J
(3.4.3.26)
' The equations generated above are used for the ERC pathway models
discussed below.
3.4.3.3. Food Ingestion
Food crops (p=19)
Milk (p=20)
Beef (p=21)
Methods similar to those discussed in sections 3.1 and 3.3 are
employed in calculating the ERC due to food ingestlon. The derivation of
the values for RI for food crops is discussed in detail in Appendix
C. The deposition to the ground surface due to the radioactive material
originally distributed in the air above the land surface (neglecting
341

resuspension) 1s calculated and applied 1n conjunction with the values of
RI . Since the RI values were determined without considering
resuspension, we must compute the radfonucllde flux to ground as a
function of time for the radionuclides originally dispersed into the air
at t'=0. Referring to Fig. 33, the flux of nuclide n to ground as a
function of time, F1 (t1), can be calculated as
rn(t')
gn
(3.4.3.31)
where, for these three pathways, QLn(t') is determined using
equation 3.4.3.23 with XR set equal to 0. Setting xR=0 will yield
QLn(t') based only on material originally dispersed in the air and
neglects resuspension altogether. To obtain Fn(t'), the quantity of
radlonuclide n deposited per unit area from the time material was
originally dispersed into the air (t'=0) to time t1, we integrate as
follows:
/• t>
F"(t")dt"=/
"en*" '
. a,J e bn +(ar  MCJ e
I6n U5n
I5n "5n
After Integrating, the result is
f.i • Q • v
F ftM ,AL "P. 9"
n tM MJ '
I5n
'6n
(3.4.3.32)
"
6"
(3.4.3.33)
342

which has units of Ci deposited per m . The ERC for these pathways is
derived in a manner similar to the methods applied 1n Section 3.1.4 and may be
computed using the following equation:
fp RInp FCFnp CPp AL
(3.4.3.34)
After substituting equation 3.4.3.33 for F"n{t'), normalizing by the
original total release, Q , substituting V,=A. .h., and making the
substitution t'=tty, we have
FHEnp_ fAL "gn FCFnp RInp fp CPp
"V ^
(M6na5n
TWW "5n
:a5n V
^/CI %/lI
I (M  Mr )
on on 5n
) r M, (tt ) i
*** 1 **C**V»w.»i I
n i *^n w i
" p 3tl v 11
^RTjlc . l\
(3.4.3.35)
or, defining COML as:
COML =
(Mc a )
6n 5n
n M5n(M6n'
M6n6n5n
FHE.
AL
FCFnp RInp fp CPp COMLn
'np
(3.4.3.36)
(3.4.3.37)
We make the conservative assumption that all farm land is used to
produce edible food crops; in fact, some would be used to raise nonfood
crops. Conversely, there will be some food crops whose roots extend below
the assumed 15 cm root zone such that they can take up radioactivity from
the soil below this depth. For these cases, our use of a xSn based on a
15 cm soil root zone is not conservative.
343

3.4.3.4 Inhalation of Dispersed and Resuspended Material (p=17)
In considering the ERC due to Inhalation of dispersed and resuspended
material an equation similar to the one derived In Section 3,1.5 was used,
which is
FHE.
np
t1
=[/ Vf
>BFCFnpPDpAL
(3.4.3.41)
Since the equation for Xn(t') has already been described in
equation 3.4.3.25, it can be substituted into equation 3.4.3.41. After
performing the indicated integration, normalizing by the release of
radionuclide n at t'=0 and replacing t1 by tty, we have
PD
(3.4.3;42)
3.4.3.5 External Risk CommitmentGround Contamination (p=22j
The equation to use in deriving an expression for the ERC for
contaminated ground is
t1
FHE
np
'in'*"1 dt"] FCFnp PDp AL SOF GCnP .
Equation 3.4.3.26 is used to express *In(t'). After the equation for
FHE 1s Integrated and normalized by the Initial release from the
np 9
repository, Q . and t1 is redefined as tty, the ERC equation becomes
344

FHE
[e
1]
(3.4.3.52)
3.4.3.6 External Risk CommitmentAir Submersion (p=18)
For air submersion external risk commitments, the ERC equation is
written as
FHE
'np
x ft") dt"
FCFnp PDp AL SOF
(3,4.3.61)
Equation 3.4.3.25 can be substituted for X (t1). After the
equation for FHE is integrated and normalized by the initial release
from the repository, Q , and t1 is redefined as tty, the ERC
equation becomes
FHEnp fAL FCFnp PDp SOF COMLn
F£
(3.4.3.62)
3.4.4 Releases to AirOverOceans
3.4.4.1 General Considerations
The radionuclides released to the air over the oceans are assumed to
be distributed uniformly in a volume determined by multiplying the earth's
ocean area by the average height of the troposphere. With the material
distributed in this manner a three compartment model is established, as
345

shown in Fig. 34, to describe radionuclide movement between the air and
the two ocean compartments. Using this model, concentrations of
radionuclldes can be determined as a function of time in the air and in
each of the two ocean compartments. These concentrations can be used in
estimating the ERC for the pathways considered in this section.
The upper compartment (Compartment 1) in Fig. 34 is the tropospheric
volume above the earth's oceans. The middle compartment (Compartment 2)
is the top compartment of the ocean and the lower compartment (Compartment
3) is the bottom compartment of the ocean.
We assume that radionuclides enter the air (Compartment 1) at the
instant a volcano or meteorite interaction releases radioactivity from the
repository and that no additional radioactivity is injected into the
system after that. Radionuclides leave the air compartment by radioactive
decay (XD ) and by deposition into the ocean (v Ay/V^). Radionuclides
enter Compartment 2 by deposition from the air (Vg^/V^) and by transfer
from Compartment 3 (TO) Radionuclides leave Compartment 2 by radioactive
decay (XD ) and by diffusion transfer (YJ) and sedimentation transfer
(SF, ) to Compartment 3. Radionuclides enter Compartment 3 by diffusion
transfer (YI) and sedimentation transfer (SFln) from the upper ocean
compartment and leave this compartment by radioactive decay (*n,n).
sedimentation to the ocean floor (SF2n), and transfer to the upper ocean
compartment (Y2K The differential equations which can be solved for
radionuclide inventory in this three compartment system are discussed in
the next section.
346

Initial Input
to Air
(Initial Conditions)
Radioactive
Decay
quantity of radionuclides
in Compartment 1 (Ci)
Transfer to Ocean
Radioactive
Decay
Compartment 1
Air
Volume =
Surface Area
Compartment 2
Ocean
(Upper compartment)
Volume = \
Qln(t') = quantity of radionuclide
in Compartment 2 {Ci)
Transfer to
Lower Layer
Sedimentation
from upper layer
SFln.Qln(t'>
Transfer to upper
layer
Compartment 3
Ocean
(Lower compartment)
Volume = \
Radioactive Decay
= quantity of radionuclides
In Compartment 3 (Ci)
,
Sedimentation from lower layer
Fig. 34. Compartment model for airoverocean,
volcano/meteorite release mode
347

3.4.4.2 AirAboveWater: Three Compartment Model
The ERC pathways considered for airoveroceans are consumption of
ocean fish and shellfish. Since the assumption is made that all edible
fish and shellfish are harvested in the upper ocean layer, it will be
necessary to obtain the quantity of each nuclide, Qln(t'K In the middle
compartment (upper ocean layer). This quantity can be divided by the
volume of the middle compartment, Vj, to yield the concentration in the
zone where edible fish and shellfish are produced. The differential
equations which describe the transfer of radionuclldes between
compartments In Fig. 34 and which are used to obtain the quantities of
radionuclides In the three compartments are
LDn
v A
wn Wx
~~
(3.4.4.21)
dt
and
ln
SF
2n
(3.4.4.23)
The initial conditions for this model are
QAn = fAW V
and
at t1 = 0
The procedure used to solve these differential equations Is to integrate
equation 3.4.4.21 directly and then use the resulting equation for QAn '
348

the solution of equations 3.4.4.22 and 3.4.4.23, which are coupled
differential equations. The resulting equations for QAn and Qln are
2n
Qln(t>)z (M, M,J
2n "In
(3.4.4.24)
'vV'v'V
(3.4.4.25)
where
v f n
wn AW vnp
'2n
and aln, b2n, B3n, C3n, Mln and M2f) are as defined in Section
3.2.2. Qonft') is not needed in this analysis, .so the equation for
Q2 (t1) is not presented.
The concentration of radionuclides in the upper compartment of the
ocean as a function of time can be computed by dividing equation 3.4.4.25
by V,, the volume of the upper ocean compartment, which yields
V ft')
xln(t >
(a
ln
(3.4.4.26)
349

3.4.4.3 Seafood Ingestion Ocean Fish (p=29)
Ocean Shellfish fp=30)
The equation used to calculate ERC for these pathways is:
f
^^M
f
(3.4.4.31)
where Q^n is described by equation 3.4.4.25. After performing the
integration, normalizing by the total release, Q , and making the
substitution t'=tt , we have
FHEnp _ CFnp
%P
where
Pp FCFnp vwn fAW
hAVl
COMO.
(3.4.4.32)
COMO =
n
(alnM2n)[ e
1]
("snMln)Mln
M(ttJ
(usnM2n)twsnMln)usn
(3.4.4.33)
3.5 Special Calculations for C14 Environmental Risk Commitment
The pathway models described in Sections 3.1 through 3.4 are used for
all pathway ERC calculations for all nuclides except carbon14. Unlike
the other radionuclides considered in these analyses, stable carbon
constitutes a significant fraction of the elemental composition of the
human body and man's diet. Transport processes through the different
350

environmental pathways and within plants, animals, and man, that apply to
trace quantities of radionuclides do not necessarily apply to
radionuclides, such as C14, where the corresponding stable elements are
present in such quantities that saturation effects are significant
(Mo79). Atmospheric releases of C14 as carbon dioxide can be evaluated
using a diffusiontype model of the carbon cycle developed by Killough
(Ki77). It seems clear that this model is the correct calculational
procedure to use for releases for the volcano/meteorite release mode where
it is assumed that hightemperatures would cause carbon releases to be
oxidized to carbon dioxide. To our knowledge, models are not available to
explicitly treat the ERC calculations for C14 released to water, land
surfaces, or air in a chemical form other than carbon dioxide. We
performed some preliminary calculations using various plausible models and
assumptions. Our literature review indicated that the chemical form of
C14 released in the water and land surface release modes was not well
known. Also, the rate of oxidation to carbon dioxide of other chemical
forms of C14 over the extensive integration period is not known for these
release modes. Considering all these uncertainties, we concluded that the
most prudent course was to use the Killough carbon dioxide model for all
four release modes, realizing that this probably leads to conservative
estimates of the ERC for the water and land release modes.
The environmental risk commitment for C14 is obtained by calculating
the total body environmental dose commitment (EDC) and multiplying by a
fatal cancer risk conversion factor. Values of the total bocty environmental
dose commitment per curie of C14 released to the atmosphere have been
351

calculated by Fowler (Fo79) using the K11lough model (K177). It Is
estimated that the Ingestlon pathway contributes 99 percent of the carbon14
environmental dose commitment (Fo76); however, we assume that the Ingestlon
pathways contribute 100 percent for purposes of computational convenience.
For estimating the environmental dose commitment, a cubic spline was fit to
Fowler's curve of worldwide EDC to the total bocjy per curie release versus
time after release. This cubic spline procedure yields the following
equations for worldwide total body EDC vs time after C14 placement 1n a
repository:
for 10

for 10,000_ 100,000 yr:
DTB14 = 537.0
(3.510)
(3.511)
The environmental risk commitment is obtained by multiplying the
total bocty environmental dose commitment, as obtained from equations 3.55
through 3.511, by the fatal cancer risk factor of 1.46E4 fatal cancers
per total bocty manrem* as given by Fowler (Fo79). The equation is
FHE
np = CARCAN •
(3.512)
'np
This equation expresses the total environmental risk commitment for all
pathways within a release mode and is not applied separately for each
pathway. Equation 3.512 can be multiplied by fLL, fAL, and fAW to
estimate the C14 ERC for the volcano/meteorite release mode for releases
directly to land, releases to air over land, and releases to air over
water.
*This C14 fatal cancer risk factor is less than would be used for
most other radionuclides because a significant percentage of the total
body dose from C14 is to adipose tissue and is not effective in producing
cancer (Fo79).
353

The C14 dosimetry and risk Information upon which our analysis is
based (Fo79), estimates C14fatal cancer risks using total body
environmental doseequivalent commitment and a fatal cancer risk per unit
total body doseequivalent conversion factor. If we were to revise
Fowler's analysis, we would use our latest RADRJSK data (not available
when Fowler performed his analysis) and compute an effectiveenvironmental
doseequivalent commitment and apply a fatal cancer risk per unit
effective doseequivalent conversion factor. We estimate that if our
newer data had been applied, the fatal cancer risk per curie of C14
released to the accessible environment would have increased by a factor of
approximately 1.5. However, due to the rounding of the calculated
radionuclide release limits in preparing Table 1 of 40 CFR 191 (EPA85c),
the Table 1, C14 release limit would not change.
354

Chapter 4: METHODS FOR DERIVATION OF FATAL CANCER RISK CONVERSION FACTORS*
Fatal cancer risk conversion factors are applied in each of the
pathway equations discussed in Chapter 3. In some cases, risk conversion
factors for daughter products are added to those for the parent** as an
approximate method to account for ingrowth of daughter products during
environmentaltransport. The methods used to obtain the risk conversion
factors and to account for daughter ingrowth during environmental
transport are discussed in this section.
4.1 Fatal Cancers Risk Conversion Factors
For each of the 30 pathways, either internal doses occur due to
inhalation or ingestion of radionuclides or external doses are delivered
due to ground contamination or air submersion and fatal cancer risk
conversion factors are needed to use with the equations developed in
Chapter 3. The computer code used by EPA to calculate dose and risk
conversion factors is RADRISK (Du84, Su81, Du80). RADRISK calculates the
radiation dose and risk resulting from an annual unit intake of a given
radionuclide or the risk resulting from external exposure to a unit
concentration of radionuclide in air or on the ground surface. Since both
dose and risk models are linear, the unit dose and risk results can then
be scaled to reflect the exposure associated with a specific source.
*The variables used in this chapter are defined in the "Nomenclature"
section, p. Nl ff.
**In these instances, the sum of the risk factors is reported for the
parent.
41

Internal exposures occur when radioact1ve.mater1al 1s Inhaled or
Ingested. The RADRISK code Implements contemporary dosimetric models to
estimate the dose rates at various times to specified reference organs in
the body from inhaled or ingested radionuclides. The dosimetric methods
in RADRISK are adapted from those of the INREM II code (Ki78b), based
primarily on models recommended by the International Commission on
Radiological Protection (ICRP79) and the National Radiation Protection
Board (Ad78). In some instances, input parameter values have been
adjusted to be more representative of the U.S. population as a whole
rather than an occupationally exposed group (Su81). The principal
qualitative difference is that RADRISK computes dose rates to specified
organs separately for high and low linear energy transfer (LET)
radiations, whereas INREM II calculated the committed dose equivalent to
specified organs.
Dose rates to organs of an Individual Immersed in contaminated air or
standing on a contaminated ground surface are computed by the DOSFACTER
computer code of Kocher (KoSlc). These calculations assume that the
radionuclide concentration 1s uniform throughout an infinite volume of air
or area of ground surface, and that the exposed individual is standing on
the ground surface. Since only photons penetrate the bo

3 (NAS80). The dose response functions applied in this report are linear
for both low and highLET risk estimates*. To project the number of
fatalities due to leukemia and bone cancer the Agency uses an absolute
risk model, a minimum induction period of two years, and a 25 year
expression period. To estimate the number of fatalities due to other
cancers, the Agency uses the arithmetic average of absolute and relative
risk projection models. For these cancers, we assume a 10year minimum
induction period and lifetime expression of radiation induced cancer. For
highLET risk estimates, we consider the risk from highLET (alpha
particle) radiation to be eight times that for lowLET radiation to the
same tissue except for bone cancer, where the highLET risk coefficient is
twenty times the lowLET value. A fuller discussion is included in
Appendix G, Section G.3.
An important feature of our methodology is the use of actuarial life
tables to account for the time dependence of the radiation insult and to
allow for competing risks of death in the estimation of risk due to
radiation exposure. A life table consists of data describing agespecific
mortality rates from all causes of death for a given population. This
information is derived from data obtained on actual mortality rates in a
real population; mortality data for the U.S. population during the years
19691971 are used throughout this study.
*We have applied the BEIRIII (NAS80) linear dose response function
in computing the risk factors listed in Table 42 and in computing the
fatal cancers per curie release to the accessible environment listed in
Chapter 6. However, in Appendix G, we have included discussions of both
the BEIRIII linear and the linear quadratic dose response functions for
cancer induction from lowLET radiation. This has been done to show a
comparison between the results obtained using the two models.
43

The use of life tables 1n studies of risk.due to lowlevel radiation
exposure 1s Important because of the time delay Inherent 1n radiation
risk. After a radiation dose 1s received, there Is a minimum induction
period (latency period) of several years before a cancer is clinically
observed. Following the latency period, the probability of occurrence of
a cancer during a given year 1s assumed to be constant for a specified
period, called a plateau period. The length of both the latency and
plateau periods depends upon the type of cancer.
During or after radiation exposure, a potential cancer victim may
experience years of life In which he or she Is continually exposed to risk
of death from causes other than incremental radiation exposure. Hence,
some individuals will be lost from the population due to competing causes
of death, and are not victims of Incremental radiationinduced cancer.
We assume that each member of the hypothetical cohort 1s exposed to a
specified activity of a given radionucllde. In the analysis, each member
of the cohort annually Inhales or Ingests 1 pC1 of the nucllde, or 1s
exposed to a constant external concentration of 1 pCi/cc 1n air or
2
1 pCi/cm on ground surfaces. Since the models used in RADRISK are
linear, these results may be scaled to evaluate other exposure
conditions. The cohort consists of an initial population of 100,000
persons, all of whom are simultaneously liveborn. In the scenario
employed, the radiation exposure 1s assumed to begin at birth and continue
throughout the entire lifetime of each Individual.
44

No member of the cohort lives more than 110 years. The span from 0
to 110 years 1s divided Into nine age Intervals, and dose rates to
specified organs at the midpoints of the age Intervals are used as
estimates of the annual dose during the age interval. For a given organ,
the Incremental probability of death due to radiationinduced cancer is
estimated for each year using radiation risk factors and the estimated
doses during that year and relevant preceding years. The incremental
probabilities of death are used in conjunction with the actuarial life
tables to estimate the incremental number of radiationinduced deaths each
year for each organ. The number of incremental deaths for the cohort for
each organ is obtained by summing the deaths each year over 110 years.
The total number of incremental deaths for the cohort is then obtained by
summing the total deaths for each organ over all organs.
In addition to providing an estimate of the incremental number of
deaths, the life table methodology can be used to estimate the total
number of years of life lost to those dying of radiationinduced cancer,
the average number of years of life lost per incremental mortality, and
the decrease in the population's life expectancy. An example summary
table of output from the RADRISK computer code, for inhalation of Ra226,
Is shown in Table 41.
Risk estimates for chronic irradiation of the cohort may also be
applied to a stationary population having the same agespecific mortality
rates as the 1970 U.S. population. That is, since the stationary
population is formed by superposition of all age groups in the. cohort,
45

TABLE 41:
Summary table from RADRISK computer code for Ra226 Inhalation
TOTAL COHORT (l.OE+5 PERSONS) CANCER FATALITIES FROM LIFETIME RA226
AMAD = 1.00, RESP CLEARANCE CLASS =U, Fl = 0.200E+00
FOR 1.0 PCI/YR INTAKE
INHALATION
[122883]
CANCER
LEUKEMIA
BONE
THYROID
BREAST
LUNG
STOMACH
BOWEL
LIVER
PANCREAS
URINARY
OTHER
ADULT
LATENCY
PERIOD
(YEARS)
2
5
2
15
10
15
15
15
15
15
15
ADULT
PLATEAU
PERIOD
(YEARS)
25
30
45
110
110
110
110
no
110
110
no
RISK
ABS
ABS
ABS
ABS
ABS
ABS
ABS
ABS
ABS
ABS
ABS
LET
LOW
HIGH
LOU
HIGH
LOU
HIGH
LOU
HIGH
LOW
HIGH
LOU
HIGH
LOU
HIGH
LOU
HIGH
LOU
HIGH
LOU
HIGH
LOU
HIGH
ADULT
DEATH
RATE (DTHS/
1E6/MRAD/YR)
2.17E+00
1.74E+OI
4.47E02
8.94E01
9.25E01
7.40E+00
1.49E+00
1.19E+01
2.03E+00
1.63E+01
9.61E01
7.69E+00
4.47E01
3.57E+00
9.77E01
7.81E+00
6.72E01
5.16E+00
2.84E01
2.27E+00
1.30E+00
1.04E+01
SUMMARY TABLE
NUMBER OF
70 YEAR
DOSE RATE
(MRAD/YR)
6.83E05
1.34E04
9.75E05
1.52E03
2.68E06
3.03E05
3.41E06
3.03E05
7.01E06
4.80E03
2.14E06
3.03E05
1.29E05
3.41E05
2.40E06
2.13E05
3.33E06
3.03E05
4.63E06
3.94E05
3.33E06
3.03E05
PREMATURE
DEATHS
IN COHORT
1.47E05
2.44E04
4.48E07
1.41E04
4.14E07
4.57E05
6.16E07
5.90E05
2.53E06
1.58E02
2.68E07
3.81E05
9.38E07
2.01E05
2.90E07
2.67E05
2.74E07
2.56E05
1.82E07
1.48E05
5.31E07
5.18E05
AVERAGE
YEARS OF
LIFE LOST
(YEARS)
2.64E+01
2.72E+01
2.44E+01
2.45E+01
2.59E+01
2.75E+01
1.99E+01
2.10E+01
•2.24E+01
2.30E+01
2.02E+01
2.10E+01
2.12E+01
2.11E+01
1.99E+01
2.09E+01
1.99E+01
2.10E+01
2.05E+01
2.11E+01
1.99E+01
2.10E+01
TOTAL
YEARS OF
LIFE LOST
(YEARS)
3.88E04
6.64E03
1.10E05
3.46E03
1.07E05
1.26E03
1.22E05
1.24E03
5.66E05
3.64E01
5.42E06
8.02E04
1.99E05
4.24E04
5.79E06
5.57E04
5.44E06
5.39E04
3.74E06
3.13E04
1.06E05
1.09E03
DECREASE
IN LIFE
EXPECTANCY
(YEARS)
3.88E09
6.64E.08
1.10E10
3.46E08
1.07E10
1;26E08
1.22E10
1.24E08
5.66E10
3.64E06
5.42E11
8.02E09
1.99E10
4.24E09
5.79E11
5.57E09
5.44E11
5.39E09
3.74E11
3.13E09
1.06E10
1.09E08
70YEAR
DOSE EQUIV
ALENT RATE
(MREM/YR)
2.75E03
3.06E02
6.09E04
6.10E04
9.59E02
6.08E04
. 6.95E04
4.28E04
6.09E04
7.94E04
6.09E04
RISK
EQUIVALENT
FACTOR
8.39E04
2.06E02
2.35E04
2.31E04
3.84E02
2.30E04
2.71E04
1.59E04
2.23E04
3.05E04
2.32E04
TOTAL (SOMATIC)
30YEAR GENETIC DOSE COMMITMENTS (MRAD):
1.65E02 2.31E+01 3.80E01 3.80E06
2.08E02
LET
LOW
HIGH
TESTES
5.59E05
8.52E04
OVARIES
7.44E05
8.52E04
AVERAGE
6.51E05
8.52E04
8.31E03

each age group corresponds to a segment of thestationary population with
the total population equal to the sum of all the age groups. Thus, the
number of excess fatal cancers calculated for lifetime exposure of the
cohort at a constant dose rate would be numerically equal to that
calculated for the stationary population receiving a population dose of
the same magnitude. This equivalence was used in deriving the risk
.factors for the environmental pathways analysis described in this report.
More detailed discussions of the methodology used by EPA to compute fatal
cancer risk estimates are included in Appendices F through H, and in
several of the references (Du84, Du80, Su81) for those readers who desire
more details than are presented in this section.
In our highlevel waste environmental pathway calculations, we have
calculated fatal cancer risk commitment factors using the RADRISK data to
convert from lifetime radionuclide intake for the inhalation and ingestion
pathways and from lifetime external exposure for the air submersion and
ground surface pathways directly to fatal cancer risk without calculating
dose commitments or dose rates*. As an example, the derivation of an
inhalation risk commitment factor will be described in the following
paragraphs.
Using the summary tables from the RADRISK computer code output
(example in Table 41), column 8, total (somatic), gives the total number
of premature fatal cancers in a cohort of 100,000 persons born
47

simultaneously and Inhaling 1 pCi/y continuously throughout their
lifetime. The average lifetime for the persons comprising the cohort is
70.756 years. Thus, the deaths tabulated in column 8 are the result of
the collective lifetime intake by the cohort of
(1E+5 personsMl pCi H70.756 yr)(!E12 Ci ) = 7.076E6 Ci
yrperson pCT
Then, for a constant lifetime rate of intake', a fatal cancer risk
commitment factor can be calculated using the equation
FCF
np
deaths committed
Ci inhaled
premature deaths in cohort
(col. 8, Total Somatic, Table 41)
7.076E6 Ci inhaled
(4.11)
This equation is applicable to a stable population (i.e., a population in
which equal numbers of persons are born and die in each year) which has
the same age distribution and age specific mortality ratio as used for the
cohort. The factors derived using this equation are not applicable for
computation of fatal cancer risks to an individual for an acute intake of
radioactivity.
For Ra226 particulates having AMAD s 1.0 micron and respiratory
clearance class W, the total number of premature fatal cancers in a cohort
of 100,000 persons is 1.65E2 (Table 41, column 8, total (somatic)).
Then, applying equation 4.11, the fatal cancer risk conversion factor
is calculated to be 2,332 deaths committed .
Ci inhaled
48

This illustration shows the methodology for deriving the fatal cancer
risk conversion factors for inhalation pathways. The procedures used to
obtain the factors for the ingestion, air submersion, and ground surface
exposure pathways are very similar to those presented above*.
4.2 Analytical Treatment of Daughter Product Buildup During
Environmental Transport
Daughter product buildup during environmental transport was not
addressed rigorously in the 30 pathway equations discussed in Section 3.
An examination of the decay schemes for the nuclides revealed that, in
general, the nuclides either (a) had stable daughters, (b) had daughters
that were very shortlived compared to the,parent, or (c) had moderately
to very longlived first or second daughters. The following techniques
were applied as an approximate method of handling daughter product
ingrowth during environmental transport.
For case (a), no action to account for daughter product buildup was
required.
In case (b), we assumed that the daughter was in secular equilibrium
with the parent, i.e., that the activity of the daughter was equal to that
of the parent, at all locations of the parent in the environment.
*Those wishing to compare their fatal cancer risk assessment
methodology to that used by EPA should multiply their dosimetry and fatal
cancer risk factors for each organ at risk, sum these products, and
compare their sums to the EPA risk factors listed in Table 42.
49

Obviously this is a simplifying assumption, since daughter products may
behave differently than the parents in the environment. The risk factors
for daughters were added to the risk factors for the parent in cases where
the daughters were dosimetrically significant. An example of case (b) is
Zr93. Zr93 has a half life of 1.53E+6yr and an ingestion fatal cancer
risk factor of 8.46E2 fatal cancers per curie intake. The only
radioactive daughter of Zr93 is Nb93m, which has a half life of 14.6yr
and an ingestion fatal cancer risk factor of 4.21E2. This is clearly a
case where Nb93m is in secular equilibrium with the Zr93 parent in the
environment and we have added the risk factors to obtain the reported risk
factor for Zr93 of 1.27E1 fatal cancers/Ci ingested (see Appendix B,
Table Bl). The rationale is that for each curie of Zr93 ingested a
curie of Nb93m is present and 1s also ingested.
In case (c), we performed simple calculations to determine whether a
significant buildup of the longlived daughters would occur during the
residence time of the parent 1n the accessible environment. The
accessible environment 1s that portion of the environment where the
material would be available to man. For example, radionuclides present
within the root zone of the soil would be 1n the accessible environment,
but radionuclides that have moved below the root zone would have left the
accessible environment. Since we believe that the soil root zone is an
environmental medium which will have one of the longest retention times
for radionuclides 1n the accessible environment, we calculated the mean
lifetime in soil of radionuclides 1n category (c). The mean lifetime was
410

taken as the reciprocal of the leaching removal rate constant, xs , for
the 15 cm soil root zone. Using standard Bateman equations (Ev55)t we
evaluated the maximum activity of the significant daughter products which
could build up during the mean lifetime of the parent and compared this
activity to the original activity of the parent. For daughters where the
maximum activity exceeded 1 percent of the original parent activity, we
added the product of the ingrowth fraction and the daughter risk factor to
the parent risk factor. We neglected the contribution of those daughters
which built up to less than 1 percent of the original parent activity.
Any shortlived daughters in the decay chain between the parent and the
first moderate to longlived daughter are assumed to be in secular
equilibrium as described for case (b) above. The specific treatment of
daughter products, for each parent nuclide in this analysis is specified in
Appendix A.
4.3 Application of Risk Factors for Environmental Pathway Calculations
For the inhalation and ingestion pathways two categories of fatal
cancer risk factors were calculated which were designated Inhalation 1,
Inhalation 2, Ingestion 1 and Ingestion 2. The category 1 factors were
used when we believed radionuclides will be present in the accessible
environment in a reasonably insoluble chemical form. The category 2
factors were used when we believed the nuclides are in a more soluble
chemical form. Class Y risk factors were used for the Inhalation 1
category for all nuclides where they were available and Class W risk
411

factors were used for the Inhalation 2 categorywhere they were
available. However, for some radionuclides, only Class D or Class D and
Class W inhalation risk factors were available. In these cases, the
factors for the least soluble clearance class available were applied. For
example, if inhalation risk factors were available for Class D and Class W
but not for Class Y, the Class W factors were listed 1n both the
Inhalation 1 and Inhalation 2 categories. For the Ingestion 1 and
Ingestion 2 categories, risk factors were used which were derived using
the same absorption fraction from guttoblood, (f«), as was used for
the Inhalation 1 and Inhalation 2 categories, respectively.
For the volcano/meteorite release mode, the Inhalation 1 and
Ingestion 1 risk factors were used and for the other three release modes
(releases to rivers, releases to oceans, and releases to land surfaces)
the Inhalation 2 and Ingestion 2 risk factors were used. This procedure
was followed because we believe that the radionuclides released in the
volcano/meteorite release mode will be 1n a less soluble chemical form
than the radionuclides released in the other three release modes.
The risk factors used in our analysis are tabulated 1n Table 42.
Included 1n Appendix B is a tabulation of the risk factors for the parent
radionuclides, and the daughter radionuclides where the risk factor was of
sufficient magnitude to be added to the risk factors for the parent.
412

iatai uancer KISK conversion razors
/fatal cancers committed
Nuclide
C14
Ni59
Sr90
Zr93
Tc99
Sn126
1129
Cs135
Cs137
Sm151
Pb210
Ra226
Ra228
Ac 227
Th229
Th230
(fatal
Inhalation 1
3.05E3
4.76E1
4.52E+2
2.72E+1
6.12E+0
5.72E+1
1.61E+1
1.27E+0
8.49E+0
5.27E+0
2.27E+4
4.38E+4
7.98E+4
6.97E+4
6.45E+4
6.89E+4
cancers committed per Ci intake)
Inhalation 2 Ingestion 1 Ingestion 2
3.05E3
4.76E1
5.19E+1
6.60E+0
6.12E+0
5.72E+1
1.61E+1
1.27E+0
8.49E+0
5.27E+0
2.99E+3
5.33E*3
1.58E+4
3.74E+4
2.82E+4
2.05E+4
4.32E1
3.76E2
2.29E+0
1.27E1
5.37E1
2.04E+0
2.41E+1
1.82E+0
1.24E+1
3.46E2
4.13E+2
4.91E*2
9.71E+1
2.85E+2
8.55E+1
5.13E+2
4.32E1
3.76E2
2.85E+1
1.27E1
5.37E1
2.04E+0
2.41E+1
1.82E+0
1.24E+1
3.46E2
4.13E+2
4.91E*2
9.71E+1
2.85E+2
8.55E+1
5.13E+2
Ciy/m3
Air Submersion
0
4.10E2
0
1.23E1
5.97E4
2.54E+3
7.57E+0
0
7.18E+2
8.15E4
1.34E+0
2.35E*3
3.43E*3
4.81E+2
3.30E*2
2.35E+3
H fatal cancers committed \
CiW '
Ground Contamination
0
8.87E3
0
1.89E2
1.41E5
5.11E+1
3.98E1
0
1.43E+1
9.43E5
6.09E2
4.20E+1
5.88E+1
1.05E+1
7.46E+0
4.20E*1
*The fatal cancer risk conversion factors in this table are the sum of the risk factors for the listed
nuclide plus any significant daughter products which can grow in during the residence time of the nuclide in
the accessible environment. For a more complete discussion, see section 4.2 and Appendices A and B.

TABLE 42 Continued:
Fatal Cancer Risk Conversion Factors
/fatal cancers committed^ /fatal cancers committed \
Nucllde
Th232
Pa231
U233
U234
U235
U236
U238
Np237
Pu238
Pu239
Pu240
Pu241
Pu242
Am241
Am243
Cm245
Cm246
(fatal
Inhalation 1
1.05E+5
1.03E+5
2.42E+4
2.07E+4
2.03E+4
1.96E+4
1.86E+4
2.89E+4
V
3.13E+4
3.09E+4
3.09E+4
1.19E+3
2.94E+4
3.27EH
3.19E+4
6.54E+4
3.26E+4
cancers comnltted per C1 Intake)
Inhalation 2 Ingestlon 1 Ingestion 2
2.94E+4
6.19E+4
3.70E+3
2.26E+3
2.72E*3
2.14E+3
2.04E+3
2.46E+4
2.49E+4
2.65E+4
2.65E+4
1.23E+3
2.52E+4
2.75E+4
2.73E+4
5.58E+4
2.78E+4
1.17E+2
4.67E+2
5.21E+0
9.38E1
5.8.6E+0
8.86E1
1.99E+0
1.86E+2
1.86E+2
2.04E+1
2.04E+1
9.57E+0
1.94E+1
2.07E*2
2.06E+2
4.21E+2
2.10E+2
1.17E+2
4.67E+2
5.07E+1
4.61E+1
5.02E+1
4.35E+1
4.84E+1
1.86E+2
1.86E+2
2.00E+2
1.99E+2
9.57E*0
1.90E+2
2.07E+2
2.06E+2
4.21E+2
2.10E+2
ClW 'l
Air Submersion
3.43E+3
5.17E+2
1.68E+1
1.63E1
2.01+2
1.27E1
2.36E+1
2.83E+2
8.80E2
9.06E2
8.63E2
5.98E1
7.36E2
1.99E+1
2.55E+2
1.02E+2
6.81E2
Cly/m*2 '
Ground Contamination
5.88E*1
1.14E+1
3.84E1
1.63E2
4.60E+0
1.48E2
5.17E1
6.39E+0
1.68E2
7.64E3
1.61E2
1.87E2
1.34E2
6.24E1
5.95E+0
2.58E>0
1.41E2

4.4 Risk Conversion Factors for Np237
Neptunium237 deserves special mention in this document. In ICRP
Report 30 (ICRP80) the value for absorption through the gut (f.) is
n A
10" . This is a 100fold increase over the previous value of 10
recommended 1n ICRP Report 2 (ICRP60). According to Cohen, this increase
in fj plus the high cancer risk factor for the liver quoted in BEIR III
have caused Np237 to become a principal nuclide of concern in various
assessments of the health effects from disposing of highlevel radioactive
waste (Co82). In ICRP30, it is mentioned that a value for f, of 10
may be more appropriate for trace quantities of the element or for
neptunium incorporated in food. Information published subsequent to the
publication of ICRP30 (Th82a, Th82b) suggests that 10 is probably the
most appropriate value for f, for neptunium for low environmental
levels. The internal dose conversion factors for Np237 utilized by EPA
3
in this report are based on an f, of 10 ; EPA believes, based on
current information, that this is the best value to use 1n these
calculations. EPA is aware that ICRP Committee 2 has a task group to
recommend the most appropriate values of f, for actinides and that the
NCRP has established a task group on neptunium. EPA will consider the
recommendations, when they become available, of both of these committees
in future analyses concerning the disposal of highlevel radioactive waste,
415


Chapter 5: DISCUSSION OF VALUES F0R PARAMETERS*
Some of the parameters used in these calculations appear in several
of the 30 pathway equations. For this reason, we decided to discuss
parameter values in a separate chapter rather than in the chapters
describing the pathway ERC equations. For many parameters, a range of
values will be found in the literature. A list of the estimated range of
possible values for these parameters is in Appendix C, Section C.9, Table
C10. The parameter values listed in this chapter are used for the fatal
cancer risk calculations summarized in Chapter 6 and discussed in more
detail in EPA's analysis of the population risks from geologic
repositories (EPA85a).
The parameter *Ln is the rate at which radionuclides are leached
from the waste into the groundwater in the repository and is assumed to be
the same for all nuclides. A range of values from 1.0 E2 yr to
1.0 E6 yr" was examined in the EPA analysis (EPA85a) based on
information furnished by the Arthur D. Little Company (L177b). The value
applied in computing fatal cancers per Ci release is 1.0 E4 yr" .
The parameter t is the time after placement in a repository that
leaching from the repository begins and usually corresponds to failure of
the waste canister. Canister lifetimes ranging between 100 and 5000 years
were considered in EPA's analysis of geologic repositories (EPA85a). We
assume t_ is the same for all radionuclides.
er
*The variables used in this chapter are defined in the "Nomenclature"
section, p. Nl ff.
51

The parameter tran 1s the time required foj radlonuclldes to travel
from the repository to an aquifer. This time varies depending upon the
situation being addressed 1n EPA's analysis of geologic repositories, but
the time Is usually on the order of a few years.
The parameter tfirn 1s the time required for material to travel from
the aquifer to the river. The value chosen for t 1s 760 R yr
arn n
where R 1s the retardation factor for the nuclide being considered.
Rp varies between 1 and 10,000 depending on the radionuclide and the
situation being considered. Values for R are discussed in the A. D.
Little report (Li77c) and in EPA's risk assessment report (EPA85a).
The parameter tR is the time after placement in a repository that
radionucliden enters the river or ocean and is the sum of t , t
er ran
and tarn For these calculations, tRn is set equal to zero. This 1s
permissible since we are computing the health effects per curie released
to the environment. Appropriate nonzero values for t^w, t^aw and
er* ran
tarn must be selected when computing the total release quantity of
radionuclides from a repository.
The parameter QQn Is the initial activity of nuclide n in the
repository at time t=0. The value for QQn remains constant for various
scenarios and is discussed in the risk assessment report (EPA85a).
The parameter xQn is the radioactive decay constant for nuclide n.
The values for >Dn are calculated using halflife information from
Lederer (Le67) and Kocher (KoSla) (see Table 51).
52

TABLE 51:
Radionuclide decay constants
Nucllde
C14
Ni59
Sr90
Zr93
Tc99
Sn126
1129
Cs135
Cs137
Sro151
Pb210
Ra226
Ra228
Ac227
Th229
Th230
Th232
Pa231
U233
U234
U235
U236
U238
Np237
Pu238
Pu239
Pu240
Pu241
Pu242
Am241
Am243
Cm245
Cm246
n
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
28
29
30
31
32
33
^Dnb"""1)
1.21 E4
8.66 E6
2.47 E2
4.62 E7
3.27 E6
6.93 E6
4.08 E8
2.31 E7
2.31 E2
7.97 E3
3.11 E2
4.33 E4
1.21 El
3.18 E2
9.44 E5
9.00 E6
4.93 Ell
2.12 E5
4.35 E6
2.81 E6
9.85 E10
2.96 E8
1.55 E10
3.24 E7
8.06 E3
2.84 E5
1.05 E4
4.81 E2
1.83 E6
1.51 E3
8.72 E5
8.15 E5
1.46 E4
53

The parameters f,. , f., , and fAW are the fractions of the total
release for a volcano/meteorite event which are released to the land
surface, the airaboveland, and the airabovewater, respectively. The
values used for these parameters are f,, = 0.500, f., = 0.150, and
f... = 0.350.
AW
The parameter PR 1s the number of people who drink water from the
river and R is the river flow rate. The ratio PR/R is needed in several
equations, and it can be determined for the purpose of this generic
evaluation without obtaining site specific data. Utilizing data from
Annex D of the 1977 UNSCEAR Report (UN77), the annual flow rate of the
rivers of the world is 3 E+16 liters/yr. If one assumes a constant world
10 *
population of 10 persons, the ratio PR/R is 3.3 E7
personyr/liter. This value forthe ratio PR/R 1s within the range of
values found for various river basins In the United States. These values
ranged from a high for PR/R of 5.73 E7 for the Lower Colorado WRC**
region to a low of 2.39 E8 for the Pacific Northwest WRC region based on
1975 river flow and population estimates (see Appendix C, Section C.7).
The parameter I Is the per capita annual consumption of drinking
W
water and waterbased drinks. The reference adult man drinking rate of
water and waterbased drinks 1s 1.65 liters/d (ICRP75), which yields a
*The current world population 1s about 3.8 E9. However, an estimate
of average world population during the time period involved 1n this
calculation 1s 10*0 people (UN77).
**WRC  Water Resources Council.
54

value of Iw of 603 liters/yr. Note that the fraction of the global
flowing water drunk by the world population 1s approximately 2 E4.
The parameter Ppp is the population eating freshwater fish from the
river and 1^ is the per capita annual freshwater fish consumption rate.
The ratio of the population fish consumption rate (PrF If) to the
river flow rate (R) is needed for the calculation. The UNSCEAR freshwater
fish consumption rate for the world is 3.8 E9 mankg/yr (UN77). We assume
that fish consumption will increase proportionately as the population
increases from the present level of 3.8 E9 people. For an eventual world
population of 10 people, this yields an annual freshwater fish
consumption rate of 10 mankg/yr. Considering the average flow rate
of the rivers of the world, the ratio of the population freshwater fish
consumption rate to the river flow rate is 10 /3 E16 = 3.3 E7
mankg/liter.
The parameter CF is the bioaccumulation factor for fish or
shaJIflsh for nuclide n and pathway p. The primary reference used for
CF for freshwater fish, ocean fish, and ocean shellfish is UCRL50564,
Rev.l (Th72). The values of the bioaccumulation factors are listed in
Table 52. The references for the bioacculumation factors not taken from
UCRL50564, Rev. 1 are noted in Table 52.
The parameter RI is the symbol for the terrestrial food pathway
factors discussed in Chapter 3. The values used for these factors are
listed in Table 53. The methodology used to derive these factors is
similar to that applied in the AIRDOSEPA computer code (Mo79) and is
55

TABLE 52:
Bioaccumulation factors for freshwater fish and seafood
Nuclide
C14
Ni59
Sr90
Zr93
Tc99
Sn126
1129
Cs135
Cs137
Sm151
Pb210
Ra226
Ra228
Ac227
Th229
Th230
Th232
Pa231
U233
U234
U235
U236
U238
Np237
Pu238
Pu239
Pu240
Pu241
Pu242
Am241
Am243
Cm245
Cm246
n
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
28
29 .
30
31
32
33
CFnp (Ci/kg per d/liter)
Freshwater Ocean Ocean
Fish Fish Shellfish
NA
l.OOE+2
1.10E+1 (Ho79)
3.33E+0
4.30E+1 (B182a)
3.00E+3
3.30E+1 (Ho79)
1.30E+3 (Ho79)
1.30E+3 (Ho79)
2.50E+1
l.OOE+2
5.00E+1
5.00E+1
2.50E+1
3.00E+1
3.00E+1
3.00E+1
1.10E+1
l.OOE+1
l.OOE+1
l.OOE+1
l.OOE+1
l.OOE+1
5.00E+2 (Sc83)
8.00E+0 (Ri83)
8.00E+0 (R183)
8.00E+0 (R183)
8.00E+0 (Ri83)
8.00E+0 (R183)
8.10E+1 (R183)
8.10E+1 (R183)
2.50E+1
2.50E+1
NA
l.OOE+2
2.00E+0
2.00E+2
l.OOE+1
3.00E+3
l.OOE+1
4.00E+1
4.00E+1
2.50E+1
3.00E+2
5.00E+1
5.00E+1
2.50E+1
l.OOE+3 (Ng84)
l.OOE+3 (Ng84)
l.OOE+3 (Ng84)
l.OOE+1
l.OOE+1
l.OOE+1
l.OOE+1
l.OOE+1
l.OOE+1
l.OOE+2 (Sc83)
3.00E+0
3.00E+0
3.00E+0
3.00E+0
3.00E+0
2.50E+1
2.50E+1
2.50E+1
2.50E+1
NA
2.50E+2
2.00E+1
8.00E+1
5.00E+1
l.OOE+3
5.00E+1
2.50E+1
2.50E+1
l.OOE+3
l.OOE+3
l.OOE+2
l.OOE+2
l.OOE+3
2.00E+3
2.00E+3
2.00E+3
l.OOE+1
l.OOE+1
l.OOE+1
l.OOE+1
l.OOE+1
l.OOE+1
l.OOE+2 (Sc83)
2.00E+2
2.00E+2
2.00E+2
2.00E+2
2.00E+2
l.OOE+3
l.OOE+3
l.OOE+3
l.OOE+3 .
NA  Not Applicable,
56

TABLE 53:
Radionuclide intake factors
Nuclide
RI
np
(Ci intake per Ci/m^ deposited)
Food Crops Milk
Meat
C14
Ni59
Sr90
Zr93
Tc99
Sn126
1129
Cs135
Cs137
Sin 151
Pb210
Ra226
Ra228
Ac227
Th229
Th230
Th232
Pa231
U233
U234
U235
U236
U238
Np237
Pu238
Pu239
Pu240
Pu241
Pu242
Aro241
Am243
Cm245
Cm246
NA
4.38E+0
2.57E+0.
4.21E+0
1.57E+0
1.10E+0
1.17E+1
1.40E+1
8.51E1
5.47E1
4.98E1
6.62E1
3.95E1
3.95E1
7.33E1
2.77E+0
6.73E+0
6.92E1
1.19E+0
1.19E+0
1.19E+0
1.19E+0
1.19E+0
5.42E1
3.92E1
4.77E1
4.53E1
3.90E1
4.89E1
4.35E1
4.87E1
4.10E1
4.08E1
NA
3.22E1
1.07E+0
8.18E2
4.00E+0
3.04E1
1.03E+1
8.04E+0
1.74E+0
4.54E3
5.75E2
1.26E1
9.81E2
4.36E3
1.49E3
3.87E3
8.51E3
1.43E3
1.57E1
1.57E1
1.57E1
1.57E1
1.57E1
2.52E3
2.17E5
2.37E5
2.32E5
2.17E5
2.40E5
9.45E5
1.03E4
4.67E3
4.63E3
NA
2.48E1
8.20E2
2.10E+1
1.31E+0
9.36E+0
2.78E+0
8.84E+0
1.91E+0
4.37E1
2.66E2
6.26E2
4.53E2
2.10E3
6.87E4
1.79E3
3.93E3
1.10E3
2.01E2
2.01E2
2.01E2
2.01E2
2.01E2
1.94E2
1.67E4
1.83E4
1.79E4
1.67E4
1.85E4
3.18E4
3.48E4
3.14E4
3.12E4
NA  Not Applicable,
57

discussed, along with input parameter values, mpre fully in Appendix C.
Those readers Interested in the details of the derivation of these RI
factors should refer to Appendix C, Section C.I.
np
The fraction of land used for various food crops is f . For the
river pathway, irrigation water provides the source of radionuclides to
land, so irrigated farmland is the only land of concern. We assume that
50 percent of the irrigated land is used for growing food crops; 25
percent for grazing milk cows; and 25 percent for grazing beef cov/s. For
the nonriver release modes, radionuclides reach the land surface via
dispersion in air so that the values for the fraction, f_, must include
the portion of U.S. land surface used for farming. It was found that 45
percent of the U.S. land surface was used for farming in 1974 (Wo79). To
obtain a value for f for the nonriver release modes, 45 percent of the .
value of f applied for the river release mode was used. Thus, for the
nonriver release mode, 1t was assumed that 23 percent of the land 1s used
for growing food crops; 11 percent for grazing milk cows; and 11 percent
for grazing beef cows. The values selected for f are upper limits
since for all release modes part of the agricultural land will be used for
nonfood crops (e.g., cotton, etc.).
The fraction of the river flow used for Irrigation, fR, was set
equal to 0.1. This number represents the average fraction of total
surface water flow used for irrigation for the U.S. and 1s taken from USGS
Circular 765 (Mu77). Data from other publications generally support the
choice of 0.1 for a U.S. average (WRC78, WIC70). The value for fR
58

varies for various regions of the U.S. from a Toy of zero for the Ohio and
Tennessee regions to a value of almost one for the Lower Colorado region,
as shown In Appendix C, Section C.3.
The parameter CP Is the population that can be fed by raising
crop p on a unit area of land. The quantity is obtained by dividing the
2
agricultural productivity (kg/m y) of land on which crops are raised by
the annual consumption rate of an individual consuming the crop
(kg/yperson). Values for CP were obtained from information in two
references (Sh82, Ba84) and were derived taking into consideration the
types of crops consumed by humans and by milk and beef producing animals,
In this analysis, the value of CP for food crops is 4.79E3 persons
2 2
fed/nr; for milk, 1.56E3 persons fed/m ; and for beef, 7.85E5
2
persons fed/m . The details of the derivation of these numbers are
discussed in Appendix C, Section C.2.
The parameter PD is the population density for pathway p. The
2
value used for PD is 6.67 E5 person/m , which is the world average
population density and was obtained by dividing the assumed world
population of 10 persons by the land surface area of the earth of 1.5
o
E14 m (Wo79). This value is within the range of population densities
for various regions of the U.S. (Wo79), as shown in Appendix C, Section
C.4.
The parameter RF is the resuspension factor for material resuspending
from the ground surface to the air. It is defined as the ratio of air
concentration to ground concentration, X ft' )/jzf (t1), which is equal
59

to *D/vQn where XR 1s a rate constant for resuspension of
radlonuclides from ground to air and vQn 1s the deposition velocity from
air to land surface. The value of XR chosen for this analysis 1s
10" sec" , which should be representative of weathered material
2
(Ne78); and the value used for v is 10 m/sec. The resulting value
9 «1
of RF is 10 m and this value agrees well with the longterm
average value suggested by Bennett (Be76). Actually, XR and RF are
functions of time, but the time dependent relationships were not known and
constant values were used to represent the average values over the
calculation interval. The value selected for XR is appropriate to dry
land resuspension, so the dose due to resuspension from wet irrigated land
(the river release mode) may be conservatively high.
The parameter !„ is the standard man breathing rate. Based
on
Information contained In ICRP Report 23 (ICRP75), a value of 8400 m /yr
has been chosen for this parameter.
The parameter SOF 1s a factor that accounts for the reduction in
external dose due to household shielding and occupancy. A conservative
value of 1.0 has been chosen for this analysis for all release modes
except the river release mode. For the river release mode, the area where
external dose could be received is irrigated farm land. After considering
the fraction of time a person might spend around irrigated land, we
decided to assign a value of 0.33 to SOF for the river release mode.
510

The rate constant for transfer of nuclides.from available
to unavailable soil is xs . The value for x is nuclide dependent
and is determined using a method (Ba79a) and data (Ba84) described by
Baes. The values used for xs in this analysis are given in Table 54.
Baes models the loss of radionuclides from the soil root zone due to water
TABLE 54:
Leaching coefficients for radionuclides in soil
Element
Leaching Coefficient U$n)
(yr1)
C
N1
Sr
Zr
Tc
Sn
I
Cs
Sm (Rare Earth)
Pb
Ra
Ac
Th
Pa
U
Np
Pu
Am
Cm
NA
5.40E3
2.31E2
2.70E4
4.90E1
3.24E3
1.57E3
8.10E4
1.25E3
9.00E4
1.80E3
5.40E4
5.40E6
3.24E4
1.80E3
2.69E2
1.80E4
1.16E3
4.05E4
NA  Not Applicable.
511

leaching but does not consider erosion of soil Jand radionuclides) as a
removal mechanism. For long time periods, erosion may be a significant
removal mechanism which would make the Baes model conservative for this
application.
The risk conversion factors used for radionuclides deposited to the
ground were derived using the assumption that the material remains on the
surface. Over the long time periods involved in these calculations, the
radionuclides will move vertically downward into the soil. The gamma
radiation emitted from these nuclides is partially shielded by the soil
such that the dose equivalent per unit deposition is less than given by
the surface dose conversion factors. We derived correction factors for
each nuclide by assuming that the radioactivity was uniformly distributed
vertically within the soil root zone {see the discussion in Section
3.1.6). These correction factors are listed in Table 55 and were derived
using the methodology discussed in Appendix C, Section C.5.
The parameter fw is the fraction of a radionuclide which passes
through a drinking water treatment plant and remains in potable water. We
conservatively assumed a value of 1.0 for all radionuclides. However,
values In the literature will range from 0.2 to 1.0 for the radionuclides
considered in this analysis (F171, De75, NRC78).
512

TABLE 55:
Ground surface radionuclide correction factors (GCnp)
Nuclide
GCnp
(Dimensionless)
C14
Ni59
Sr90
Zr93
Tc99
Sn126
1129
Cs135
Cs137
Sm151
Pb210
Ra226
Ra228
Ac227
Tn229
Th230
Th232
Pa231
U233
U234
U235
U236
U238
Np237
Pu238
Pu239
Pu240
Pu241
Pu242
Am241
Am243
Cm245
Cm246
Beta emitter
8.8E5
Beta emitter
1.3E3
Beta emitter
2.2E1
l.OE2
Beta emitter
2.4E1
Beta emitter
2.3E2
2.4E1
1.8E1
1.5E1
9.7E2
2.4E1
1.8E1
1.3E1
7.5E2
2.9E2
7.3E2
2.5E4
4.3E2
9.2E2
3.8E4
4.1E4
4.0E4
1.2E2
4.0E4
1.2E2
6.9E2
3.3E2
4.0E4
513

The parameter f 'Is the fraction of drinking water which 1s
sw "
supplied by surface water. State average values varied from a high of
0.90 for Maryland to a low of 0.08 for Idaho with the U.S. average being
~ 0.65 (Mu77). We used the U.S. average value in these calculations.
The transfer rate coefficients used in the ocean model are y^ and
Y2. That for movement of water from the lower to the upper ocean
compartment is Y2 and the value of it used for this analysis is 6.25 E4
yr (Ma73). For movement of water from the upper to the lower ocean
compartment, the transfer rate coefficient 1s Yl, and the value applied
for this analysis is 3.3 E2 yr" , which is derived using the
methodology discussed in Appendix C, Section (MO.
The parameters SFln and SF2n are the sedimentation coefficients
from the upper layer and the lower layer of the ocean, respectively, for
nuclide n. The treatment of sedimentation 1s taken from a report of the
working group of the International Nuclear Fuel Cycle Evaluation
(INFCE78), and the methodology used to derive nuclide specific values for
SF. and SF2n Is discussed in Appendix C, Section C.10. The values we
used for these two parameters are listed 1n Table 56.
The ratio of the population seafood consumption rate (P I ) to
the ocean upper compartment volume
1s needed In these
calculations. P is the population eating seafood and I 1s the per
514

TABLE 56:
Values for ocean sedimentation
Element
C
N1
Sr
Zr
Tc
Sn
I
Cs
Sm (Rare Earth)
Pb
Ra
Ac
Th
Pa
U
Np
Pu
Am
Cm
coefficients
Sedimentation
SFm
0
5.33E6
2.6717
2.67E4
0
0
0
2.67E6
4.00E5
2.67E4
1.33E6
6.67E5
2.00E3
2.67E4
4.00E5
1.33E7
2.67E4
1.33E4
4.00E5
(SFin and SF2n)
Coefficients (yr'M
SF2n
0
1.02E7
5.10E9
5.10E6
0
0
0
5.10E8
7.64E7
5.10E6
2.55E8
1.27E6
3.82E5
5.10E6
7.64E7
2.55E9
5.10E6
2.55E6
7.64E7
515

capita seafood annual consumplon rate for pathway p (p = 9 for fish
ingestion and p « 10 for shellfish Ingestion). Vj Is the volume of the
upper compartment of the ocean where 1t is assumed that the edible fish
are harvested. For this generic analysis, average values for the world
are used. For ocean fish, the projected average population consumption
rate 1s 6 kg/yr'1010 persons = 6 ElO kgpersons/yr and for ocean
shellfish it is 1 kg/yr*1010 persons = 1 ElO kgpersons/yr (UN77).
The volume of the upper compartment of the ocean is obtained by
2
multiplying the world ocean surface area of 3.6 E14 m (CRC75) by the
assumed depth of the upper compartment of the ocean of 75 m. The
resulting volume is 2.7 E16 m3 or 2.7 E19 liters. Thus the ratio
P .1 /V, is 2.2 E9 kgpeople/literyr for ocean fish and
p p 1
3.7 E10 kgpeople/literyr for ocean shellfish.
The terms t. and ty represent the times after placement in a
repository that radioactive material is transmitted to the land surface or
into air for the land surface and the volcano/meteorite pathways,
respectively. The values for tL and ty change with various scenarios
and discussion of the values chosen for these parameters for various
scenarios is Included in the risk assessment report (EPA85a). However,
for this analysis, where we are calculating the fatal cancers per C1
released to the available environment, we have set tL and ty equal to
zero.
516

The average height of the troposphere 1s h_A. Tropospheric height
ranges from 25000 ft (7600 m) to 60,000 ft (18,000 m) (Wo79). An average
value of 13,000 m was selected for these calculations.
The deposition velocity from air to oceans is v.,n. In this
wn
analysis, a value of 2 cm/sec was used for all nuclides, which was derived
from general deposition velocity information contained in Meteorology and
Atomic Energy, 1968 (AEC68).
The rate constant for deposition from air to ocean is x , which is
wn
equal to vwn/h.. Thus, the value calculated for this analysis is
48.7 yr"1.
517

Chapter 6: HEALTH EFFECTS PER CURIE "RELEASE RESULTS*
6.1 Fatal Cancers per Curie Release to the Accessible Environment
In this section, we list the fatal cancers in the first 10,000 years
per curie release to the accessible environment for all nuclides
considered in the EPA environmental transport pathway analysis. These
fatal cancer estimates have been computed using the methodology and
algorithms presented in Chapters 2 and 3 and the parameter values
discussed and listed in Chapters 4 and 5. These fatal cancer estimates
have been used to develop the radionuclide release limits in Table 1 of
EPA's environmental standards for highlevel and transuranic radioactive
waste disposal 40CFR191 (EPA85c). Fatal cancer estimates for each of the
four release modes, for each radionuclide, are shown in Table 61.
Tables 62, 63, and 64 show the contributions of the various
environmental pathways to the fatal cancers per curie values for the
river, ocean, and land surface release modes. As mentioned previously, a
period of 10,000 years was used for the integration time. A value of .
10"4 parts per year was used for the waste leach rate ULn). although
these fatal cancers per curie parameters have only a very slight
dependence on the value chosen for xLn.
For the fatal cancer estimates listed in Tables 61 through 65, the
dose response functions applied are linear for both low and highLET
*The variables used in this chapter are defined in the "Nomenclature"
section, p. Nl ff.
61

radiation. For lowLET radiation, EPA considers plausible two of the dose
response functions discussed in the BEIRIII report (NAS80). They are the
linear model and the linearquadratic model; with the linear model being
more conservative. In Appendix G, where we have discussed the methodology
employed in estimating the risk of fatal cancers resulting from
radionuclide releases, we have presented information on both the linear
and the linearquadratic model for lowLET radiation so that the reader
can compare the magnitude of the risk estimates obtained for given doses
using both models. The use of the linear model for both low and highLET
radiation in our calculation has been thoroughly reviewed and accepted by
the Highlevel Radioactive Waste Disposal Subcommittee of the EPA Science
Advisory Board (EPA84a).
62

TABLE 61:
Fatal cancers per curie released to the accessible environment for
different release modes
Nuclide
C  14
Ni 59
Sr 90
Zr 93
Tc 99
Sn126
I 129
Cs135
Cs137
Sm151
Pb210
Ra226
Ra228
Ac227
Th229
Th230
Th232
Pa231
U 233
U 234
U 235
U 236
U 238
Np237
Pu238
Pu239
Pu240
Pu241
Pu242
Am241
Am243
Cm245
Cm246
Releases to
a River
5.83E02
' 4.61E05
2.25E02
1.51E04
3.65E04
1.05E02
8.07E02
7.73E03
1.07E02
9.38E06
1.18E01
1.63E01
2.41E02
6.67E02
3.49E02
5.38E01
3.40E01
1.48E01
2.15E02
1.96E02
2.17E02
1.85E02
2.06E02
7.95E02
4.23E02
4.97E02
4.84E02
2.17E03
4.79E02
5.42E02
5.72E02
1.01E01
4.99E02
Releases due
Releases to Releases to to Violent
an Ocean Land Surface Interactions*
5.83E02
1.70E06
6.14E06
8.59E06
3.17E06
2.07E03
1.43E04
2.61E05
2.28E05
4.01E07
6.80E03
5.40E03
1.07E04
1.94E03
2.71E02
1.87E01
4.32E02
1.67E03
1.90E04
1.73E04
1.89E04
1.64E04
1.83E04
7.03E03
4.06E04
2.19E03
1.91E03
9.24E06
2.18E03
3.74E03
1.09E02
2.29E02
1.01E02
5.83E02
6.79E07
3.76E05
2.26E05
5.65E08
1.38E03
3.96E03
5.75E04
2.19E05
6.71E08
1.52E04
5.62E03
1.57E05
1.24E04
1.90E02
3.86E01
3.76E01
2.36E02
7.51E04
6.54E04
8.42E04
6.18E04
6.90E04
1.21E04
3.10E04
6.23E03
5.22E03
2.50E06
6.34E03
1.05E03
2.45E03
8.08E03
3.54E03
5.83E02
2.89E05
1.16E03
1.22E04
1.99E04
2.73E02
5.57E02
4.91E03
3.39E03
4.72E06
4.31E02
7.20E02
2.78E02
3.82E02
5.06E02
1.26E+00
3.73E01
1.28E01
7.75E03
5.94E03
8.27E03
5.62E03
5.67E03
2.83E02
2.07E02
1.20E02
1.15E02
9.36E04
1.09E02
2.54E02
3.40E02
6.09E02
2.89E02
*For example, interactions of a metorite or a volcanic eruption with a
repository.
63

en
Fatal cancers per curie
Nuclide
C  14
Ni 59
Sr 90
Zr 93
Tc 99
Sn126
I 129
Cs135
Cs137
Sm151
Pb210
Ra226
Ra228
Ac227
Th229
Th230
Th232
Pa231
U 233
U 234
U 235
U 236
U 238
Np237
Pu238
Pu239
Pu240
Pu241
Pu242
Am241
Am243
Cm245
Cm246
^
TOTAL
5.83E02
4.61E05
2.25E02
1.51E04
3.65E04
1.05E02
8.07E02
7.73E03
1.07E02
9.38E06
1.18E01
1.63E01
2.41E02
6.67E02
3.49E02
5.38E01
3.40E01
1.48E01
2.15E02
1.96E02
2.17E02
1.85E02
2.06E02
7.95E02
4.23E02
4.97E02
4.84E02
2.17E03
4.79E02
5.42E02
5.72E02
1.01E01
4.99E02
released to
Drinking
Water
Ingestion
(p = 1)
N/A
4.91E06
3.72E03
1.66E05
7.02E05
2.67E04
3.15E03
2.38E04
1.62E03
4.52E06
5.40E02
6.41E02
1.27E02
3.72E02
1.12E02
6.70E02
1.53E02
6.10E02
6.62E03
6.02E03
6.56E03
5.68E03
6.32E03
2.43E02
2.43E02
2.61E02
2.60E02
U25E03
2.48E02
2.70E02
2.69E02
5.50E02
2.74E02
the accessible environment for releases to a river
Freshwater
Fish
Ingestion
(p = 2)
N/A
1.25E06
1.04E04
1.41E07
7.70E06
2.04E03
2.65E04
7.89E04
5.37E03
2.88E07
1.38E02
8.18E03
1.62E03
2.37E03
8.55E04
5.13E03
1.17E03
1.71E03
1.69E04
1.54E04
1.67E04
1.45E04
1.61E04
3.10E02
4.96E04
5.33E04
5.31E04
2.55E05
5.07E04
5.59E03
5.56E03
3.51E03
I.75E03
Above
Surface
Crops
Ingestion
(p = 3)
N/A
3.94E05
1.75E02
1.28E04
2.02E04
5.37E04
6.75E02
6.10E03
2.53E03
4.53E06
4.93E02
7.78E02
9.19E03
2.70E02
1.50E02
3.40E01
1.89E01
7.74E02
1.44E02
1.31E02
1.43E02
1.24E02
1.38E02
2.41E02
1.75E02
2.28E02
2.16E02
8.94E04
2.23E02
2.16E02
2.40E02
4.13E02
2.05E02
Milk
Ingestion
(p = 4)
N/A
4.72E07
1.19E03
4.05E07
8.38E05
2.42E05
9.68E03
'5.71E04
8.42E04
6.13E09
9.26E04
2.41E03
3.71E04
4.85E05
4.97E06
7.74E05
3.88E05
2.60E05
3.10E04
2.82E04
3.07E04
2.66E04
2.96E04
1.83E05
1.57E07
1.85E07
1.80E07
8.10E09
1.78E07
7.63E07
8.28E07
7.67E05
3.79E05
Beef
Ingestion
(p = 5)
N/A
1.83E08
4.59E06
5.23E06
1.38E06
3.75E05
1.31E04
3.1J5E05
4.65E05
2.97E08
2.16E05
6.03E05
8.63E06
1.17E06
1.15E07
1.80E06
9.02E07
1.01E06
2.00E06
1.82E06
1.98E06
1.72E06
1.91E06
7.08E06
6.10E08
7.18E08
6.99E08
3.14E09
6.90E08
1.29E07
1.41E07
2.59E07
1.29E07
Inhalation
of
Resuspended
Material
(p = 6)
N/A
3.25E10
4.05E09
6.58E08
4.67E11
6.47E08
3.68E08
5.38E09
1.33E09
2.14E09
3.45E07
8.91E06
5.61E07
4.29E06
4.85E04
4.29E04
6.27E04
5.33E04
7.41E06
4.53E06
5.46E06
4.29E06
4.09E06
3.40E06
1.14E05
3.14E04
2.75E04
8.73E08
3.13E04
3.85E05
7.92E05
3.85E04
1.75E04
External
Dose 
Ground
Contam.
(p = 7)
N/A
3.17E10
O.OOE+00
1.45E07
O.OOE+00
7.55E03
5.41E06
O.OOE+00
3.19E04
O.OOE+00
9.60E08
l.OOE02
2.23E04
1.07E04
7.39E03
1.25E01
1.34E01
7.58E03
3.43E05
5.63E07
4.00E04
4.41E09
2.65E05
4.83E05
1.74E09
2.21E08
3.97E08
9.46E09
3.95E08
6.22E06
7.08E04
3.49E04
2.11E08
External
Dose 
Air
Submersion
(p = 8}
N/A
1.11E15
O.OOE+00
4.86E14
1.80E19
1.14E10
6.86E13
O.OOE+00
4.45E12
1.31E17
6.13E15
1.56E10
4.83E12
2.18E12
2.25E10
1.95E09
2.90^09
1.76E10
1.33E12
1.29E14
1.60E11
1.01E14
1.88E12
1.55E,12
1.60E15
4.26E14
3.55E14
1.68E15
3.62E14
1.10E12
2.93E11
2.79E11
1.70E14

TABLE 63:
Fatal cancers per curie released to the accessible environment for
releases to an ocean
Nuclide
C  14
141 59
Sr 90
Zr 93
Tc 99
Sn126
I 129
Cs135
Cs137
Sm151
Pb210
Ra226
Ra228
Ac227
Th229
Th230
Th232
Pa231
U 233
U 234
U 235
U 236
U 238
Np237
Pu238
Pu239
Pu240
Pu241
Pu242
Am241
Am243
Cm245
Cm246
TOTAL
5.83E02
1.70E06
6.14E06
8.59E06
3.17E06
2.07E03
1.43E04
2.61E05
2.28Er05
4.01E07
6.80E03
5.40E03
1.07E04
1.94E03
2.71E02
1.87E01
4.32E02
1.67E03
1.90E04
1.73E04
1.89E04
1.64E04
1.83E04
7.03E03
4.06E04
2.19E03
1.91E03
9.24E06
2.18E03
3.74E03
1.09E02
2.29E02
1.01E02
Ocean
Fish
Ingesti on
(p = 9)
N/A
1.20E06
2.30E06
8.05E06
1.73E06
1.96E03
7.82E05
2.36E05
2.07E05
5.23E08
4.42E03
4.05E03
8.02E05
2.53E04
2.03E02
1.40E01
3.24E02
1.43E03
1.63E04
1.48E04
1.62E04
1.41E04
1.57E04
6.03E03
3.35E05
1.81E04
1.57E04
7.63E07
1.80E04
4.88E04
1.42E03
2.98E03
1.31E03
Ocean
Shellfish
Ingestion
(p = 10)
N/A
5.00E07
3.84E06
5.37E07
1.44E06
1.09E04
6.51E05
2.46E06
2.15E06
3.49E07
2.46E03
1.35E03
2.67E05
1.69E03
6.76E03
4.67E02
1.08E02
2.38E04
2.71E05
2.47E05
2.70E05
2.34E05
2.61E05
l.OOE03
3.73E04
2.01E03
1.75E03
8.48E06
2.00E03
3.25E03
9.44E03
1.99E02
8.75E03
65

en
t
Nuclide
C  14
Ni 59
Sr 90
Zr~ 93
Tc 99
Sn126
I 129
Cs135
Cs137
Sm151
Pb210
Ra226
Ra228
Ac 227
Th229
Th230
Th232
Pa231
U 233
U 234
U 235
U 236
U 238
Np237
Pu238
Pu239
Pu240
Pu241
Pu242
Am241
Am243
Cm245
Cm246
srb per iune
TOTAL
5.83E02
6.79E07
3.76E05
V2.26E05
5.65E08
1.38E03
3.96E03
5.75E04
2.19E05
6.71E08
1.52E04
5.62E03
1.57E05
1.24E04
1.90E02
3.86E01
3.76E01
2.36E02
7.51E04
6.54E04
8.42E04
6.18E04
6.90E04
1.21E04
3.10E04
6.23E03
5.22E03
2.50E06
6.34E03
1.05E03
2.45E03
8.08E03
3.54E03
Above
Surface
Crops
Ingestion
(p = 13)
N/A
6.68E07
3.53E05
2.11E05
3.99E08
1.46E05
3.47E03
5.25E04
1.01E05
4.61E08
1.46E04
2.96E03
8.44E06
7.94E05
3.44E03
9.63E02
5.46E02
1.13E02 [
6.61E04 ]
6.01E04
6.56E04
5.68E04
6.32E04
8.57E05
2.00E04
4.20E03
3.47E03
1.64E06
4.30E03
7.00E04
1.49E03
5.04E03
2.29E03
Milk
Ingestion
(p = 14)
N/A
7.65E09
2.29E06
6.39E08
1.58E08
6.30E07
4.76E04
4.70E05
3.22E06
5.96E11
2.63E06
8.78E05
3.26E07
1.36E07
1.09E06
2.10E05
1.08E05
3.65E06
1.36E05
1.24E05
1.35E05
1.17E05
1.30E05
6.21E08
1.73E09
3.25E08
2.77E08
1.42E11
3.29E08
2.37E08
4.91E08
8.93E06
4.06E06
Beef
Ingestion
(p = 15)
• N/A
2.96E10
8.83E09
8.25E07
2.61E10
9.76E07
6.47E06
2.60E06
1.78E07
2.89E10
6.11E08
2.19E06
7.58E09
3.31E09
2.53E08
4.88E07
2.50E07
1.41E07
8.75E08
7.96E08
8.68E08
7.52E08
8.37E08
2.40E08
6.68E10
1.26E08
1.08E08
5.49E12
1.28E08
4.01E09
8.35E09
3.02E08
1.38E08
Inhalation
of
Resuspended
Material
(p = 12)
N/A
3.11E09
4.02E08
4.47E07
4.66E10
6.03E07
3.23E07
4.32E08
1.31E08
2.07E08
3.41E06
7.88E05
5.59E06
4.24E05
2.77E03
2.56E03
3.76E03
3.69E03
6.59E05 '
4.03E05
4.85E05
3.82E05
3.64E05
3.36E05
1.10E04
2.03E03
1.75E03
8.66E07
2.04E03
3.46E04
6.63E04
2.73E03
1.24E03
External
Dose 
Ground
• Contam.
(p  16)
N/A
3.54E11
O.OOE+00
1.91E07
O.OOE+00
1.37E03
1.89E06
O.OOE+00
8.33E06
O.OOE+00
1.86E09
2.49E03
1.34E06
2.06E06
1.27E02
2.87E01
3.18E01
8.53E03
1.06E05
1.74E07
1.24E04
1.37E09
8.21E06
1.12E06
1.30E10
3.21E08
4.71E08
1.13E10
6.23E08
1.32E06
2.96E04
3.07E04
1.64E08
External
Dose 
Air
Submersion
(p = 11)
N/A
3.19E14
O.OOE+00
9.92E13
5.41E18
3.19E09
1.81E11
O.OOE+00
1.32E10
3.81E16
1.82E13
4.13E09
1.44E10
6.49E11
3.85E09
3.49E08
5.23E08
3.66E09
3.56E11
3.46E13
4.27E10
2.70E13
5.01E11
4.61E11
4.63E14
8.25E13
6.78E13
5.01E14
7.09E13
2.98E11
7.37E10
5.94E10
3.62E13

6.2 Comparison of Fatal Cancers and Serious Genetic Effects (All
Generations) per Curie Release to the Accessible Environment
The curie release limits for 40CFR191 are based on fatal cancer
risks. The estimated fatal cancers per curie of various radionuclides
released to the accessible environment are summarized, for the four
release modes we considered, in Table 61.
We also computed estimates of the serious genetic, effects to all
future generations per curie release to the accessible environment. The
mechanics of computing the estimates of serious genetic effects is the
same as is described in this report for fatal cancer risks except that
genetic effects risk factors are applied in place of the fatal cancer risk
factors (FCF ). The genetic effects risk factors are derived using the
genetic risk estimates from BEIR3 (NAS80) and using the dose received
before age 30. The BEIR3 estimates are "indirect" estimates and are
calculated using the normal prevalence of genetic defects and the dose
that is considered to double this risk. The MAS estimates used by EPA are
based on a doubling dose range, with a lower bound of 50 rem and an upper
boundof 250 rem. To express the range as a single estimate, the
geometric mean of the range 1s used, a method first recommended by UHSCEAR
(UN58) for purposes of calculating genetic risk. A factor of three
increase in risk for high dose rate, lowLET radiation is also used. We
apply an RBE of 20 to estimate the genetic risks for all highLET
radiations.
67

In developing the average mutation rate for the two sexes used in the
calculation of the relative mutation risk, the BEIR3 committee postulated
that the induced nutation rate in females was about 40 percent of that in
males (NAS30). Recent studies by Dobson et al. (Do83a, Do83b, Do84a,
Do84b) suggest that the assumption was invalid and that human oocytes
should have a risk equivalent to that of human spermatogonia. Use of the
results of the Dobson studies in place of the BEIR3 postulation would
increase our genetic risk estimates by a factor of 1.43.
A discussion of radiationinduced health effects other than fatal
cancer is included in section G.5 of Appendix G. Specifically a more
detailed discussion of the basis for the EPA genetic risk estimates is
incorporated in section G.5.5.
In Table 65, we have listed our estimates for both the fatal cancers
and the serious genetic effects to all generations so that the reader can
compare the relative magnitude of these two health effects. In reviewing
Table 65, we note that the genetic effects are about 50 percent of the
fatal cancers for 126Sn, 135Cs, 137Cs, 228Ra, and 232Th and 25 to 50 percent
for 59Ni, 226Ra, 227Ac, 229Th, 230Th, and 231Pa. The genetic effectsr
210 237
are between 15 and 25 percent of the fatal cancers for Pb, Np
and all Pu, Am, and Cm isotopes. For the other radionuclides, the genetic
effects are less than 15 percent of the fatal cancer estimates. Our curie
release limits for 40 CFR 191 were based only on consideration of fatal
cancers because we believe that the consideration of genetic and other
effects, along with the fatal cancers, would not significantly effect the
results.
68

curfe
to
envtron.ent for
Nuclide
~ • i ••
C  14
Ni 59
Sr 90
Zr 93
Tc 99
Sn126
I 129
Cs135
Cs137
Sm151
Pb210
Ra226
Ra228
Ac227
Th229
Th230
Th232
Pa231
U 233
U 234
U 235
U 236
U 238
Np237
Pu238
Pu239
Pu240
Pu241
Pu242
Am241
Am243
Cm245
Cm246
•••
Release to a River
Fatal . A .
Cancers Genetic
— — : — . — _
5.83E02
4.61E05
2.25E02
1.51E04
3.65E04
1.05E02
8.07E02
7.73E03
1.07E02
9.38E06
1.18E01
1.63E01
2.41E02
6.67E02
3.49E02
5.38E01
3.40E01
1.48E01
2.15E02
1.96E02
2.17E02
1.85E02
2.06E02
7.95E02
4.23E02
4.97E02
4.84E02
2.17E03
4.79E02
5.42EU2
5.72E02
1.01E01
4.99E02
3.03E02
1.55E05
4.40E04
9.36E06
1.74E05
4.22E03
1.82E04
3.19E03
4.13E03
1.24E09 i
1.91E02
3.54E02
1.11E02
1.57E02
8.31E03
1.35E01
1.36E01
2.33E02
2.03E03
1.66E03
2.06E03
1.57E03
1.50E03
1.29E02
7.23E03
8.05E03
7.85E03
3.20E04
7.71E03
8.89E03
9.45E03
1.64E02
8.08E03
— _ ...
Release to an Ocean
Fatal _ _
Cancers Genetic
5.83E02
1.70E06
6.14E06
8.59E06
3.17E06
2.07E03
1.43E04
2.61E05
2.28E05
4.01E07
6.80E03
5.40E03
1.07E04
1.94E03
2.71E02
1.87E01
4.32EQ2
1.67E03
1.90E04
1.73E04
1.89E04
1.64E04
1.83E04
7.03E03
4.06E04
2.19E03
1.91E03
9.24E06
2.18E03
3.74E03
1.09E02
2.29E02
1.01E02
3.03E02
5.74E07
1.20E07
5.31E07
1.51E07
6.57E04
3.19E07
1.07E05
8.77E06.
5.28E11
1.11E03
1.10E03
4.91E05
4.53E04
5.09E03
3.64E02
1.65E02
2.38E04
1.77E05
1.46E05
1.68E05
1.39E05
1.32E05
1.14E03
6.94E05
3.54E04
3.10E04
1.36E06
3.52E04
6.13E04
1.75E03
3.69E03
1.63E03
Dft, . . J ^ ^ Releases due to Violent
Release to Land Surface Interactions*
/atal Genetic Fata1 r +
Cancers tenenc Cancers Genet7c
5.83E02
6.79E07
3.76E05
2.26E05
5.65E08
1.38E03
3.96E03
5.75E04
2.19E05
6.71E08
1.52E04
5.62E03
1.57E05
1.24E04
1.90E02
3.86E01
3.76E01
2.36E02
7.51E04
6.54E04
8.42E04
6.18E04
6.90E04
1.21E04
3.10E04
6.23E03
5.22E03
2.50E06
6.34E03
1.05E03
2.45E03
8.08E03
3.54E03
—
3.03E02
2.29E07
7.34E07
1.44E06
2.66E09
6.01E04
9.79E06
2.37E04
8.83E06
' 6.45E12
2.42E05
1.69E03
4.70E06
2.61E05
6.13E03
1.42E01
1.57E01
5.57E03
6.79E05
5.19E05
1.11E04
4.91E05
5.02E05
1.93E05
5.12E05
9.76E04
8.21E04
3.61E07
9.92E04
1.67E04
4.62E04
1.35E03
5.55E04
5.83E02
2.89E05
1.16E03
1.22E04
1.99E04
2.73E02
5.57E02
4.91E03
3.39E03
4.72E06
4.31E02
7.20E02
2.78E02
3.82E02
5.06E02
1.26E+00
3.73E01
1.28E01
7.75E03
8.*27E03
5.67E03
2.83E02
2.07E02
1.20E02
1.15E02
9.36E04
1.09E02
2.54E02
3.40E02
6.09E02
2.89E02
3.03E02
9.73E06
8.40E06
7.23E06
9.37E06
1.17E02
1.34E04
2.02E03
1.36E03
4.59E10
6.01E03
1.26E02
3.08E03
5.13E03
7.26E03
4.32E01
1.37E01
2.38E02
1.81E04
9.10E06
7.47E04
8.08E06
4.98E05
3.63E03
2.42E03
7.08E04
6.73E04
1.06E04
6.50E04
3.06E03
5.04E03
7.56E03
3.54E03
*For example, interactions of a metorite or a volcanic eruption with a repository.

Chapter 7: UNCERTAINTY ANALYSIS*
Environmental pathway dosimetry and risk models generally employ
environmental transport methodology consisting of multiplicative chain
algorithms incorporating several variables. In performing regulatory
analyses, there is a tendency to choose conservative values for these
variables due to the inherent uncertainty in the parameters. The
multiplicative nature of the models means that conservatisms in chosen
values for individual parameters can lead to larger conservatism in the
result. This becomes an issue of contention between the regulators and
those being regulated in virtually every rulemaking action where
regulatory decisions will be made based on the results of the application
of multiplicative chain models. Since the protection of public health is
at stake, regulators believe that they must choose conservative values to
"insure" that the public is protected. The problem with this approach is
that multiple conservatisms can lead to extremely conservative and
sometimes unrealistic results. Those being regulated generally experience
escalating project costs as regulatory requirements become more stringent
so that there is strong incentive to encourage the use of less
conservative parameter values.
*In addition to the discussions of uncertainty included in this
chapter, uncertainty 1s discussed in Appendices F and G. In Section F.5
of Appendix F, uncertainty analysis related to radiation dosimetry
calculations is addressed. The uncertainties 1n risk estimates for
radiogenic cancer are discussed in Section G.4 of Appendix G.
71

The consideration of uncertainty 1n Individual parameter values used
1n environmental pathway models has been a subject of discussion in the
technical community for more than a decade (Ba79a, Ba79b, Ho79, M179,
Ru79, Sh79). However, the comprehensive consideration of overall
uncertainty in environmental pathway, dosimetry and health impact analyses
has begun to be addressed only recently (R183, Ru83).
When considering the uncertainty in the input parameters associated
with environmental pathway calculations, the most common procedure has
been to qualitatively consider the range of reported parameter values and
to use judgement to select the "best" value to use for a particular
application. More recently, there has been a tendency to statistically
analyze the distribution of data for individual parameters and to choose a
mean or median as the "best" value.
It appears that the most systematic mechanism for considering
uncertainty in multiplicative chain models would be to include a
probability distribution representing current uncertainty about parameter
values in the input data and to run a sufficient number of cases (with
parameter values for each case chosen by a suitable sampling procedure)
such that the distribution of results can be evaluated. The results of
this type of analysis could be considered in choosing an appropriate set
of singlevalued parameters to apply for regulatory calculations.
Alternately, a decision might be made to perform the regulatory
calculations probabilistically, then choose limits for a standard
72

(or to perform calculations to see if a limit is met) at a specified
confidence level. We believe the subject needs additional study to
determine the most appropriate use of uncertainty analysis for standards
setting applications;'however, it is clear to us that a quantitative
analysis of the uncertainties is most useful for focusing on important
uncertainties for more intensive consideration.
EPA is presently involved in a reevaluation of the methodology we
apply in risk assessment calculations. In a speech at Princeton
University on February 18, 1984, EPA Administrator William Ruckelshaus
stated (Ru84), in proposing some principles for more reasonable
discussions about risk, "First, we must insist on risk calculations being
expressed as distributions of estimates and not as magic numbers that can
be manipulated without regard to what they really mean. We must try to
display more realistic estimates of risk to show a range of
probabilities. To help do this we need new tools for quantifying and
ordering sources of uncertainty and for putting them in perspective."
Thus, at the highest level, EPA management is calling for an upgrading
of our risk assessment methodology so that risk estimates can be more
realistically expressed and the range of uncertainty in risk estimates
more thoroughly quantified.
Most of the technical analyses discussed in this report were
performed prior to the increase in emphasis on uncertainty in risk
assessment calculations. The results presented in Chapter 6 were
73

determined using point values for each parameter. In most cases, these
point values were chosen after review of the range of values reported 1n
the literature and were chosen to be near the mean or median value to
avoid obtaining unrealistically conservative results. There are certain
cases where conservative assumptions have been made, and these are
discussed in the sections of the report describing the algorithms used in
the computations (Chapter 3). Baes (Ba84) has published a very complete
review and analysis of parameters used to predict the transport of
radionuclides through agricultural pathways. For most radionuclides we
considered, the river release mode was dominant and the agricultural
pathways either dominated or were major pathways in determining the fatal
cancers calculated for the river release mode. Default values from Baes
report were used for many critical food pathway parameters and Baes states
that these default values were chosen to be realistic rather than highly
conservative. Since we were able to use default values based on Baes
recent and extensive review of the. literature, we believe that this
significantly strengthens the analysis and causes it to be more realistic
than would be the case if other sources of data were used.
The Envirosphere Company, a Division of Ebasco Services Incorporated,
has recently completed a significant project (Ri83, ENV85) where they
performed an uncertainty analysis for the input parameters of the river
release mode algorithms. These are the algorithms used to derive the
radionuclide release limits for Table 1 of 40CFR191 (EPA85c). Envirosphere
74

reviewed the EPA river pathway models and identified the key uncertain
input parameters for each river pathway. The key uncertain parameters
were:
soiltoplant bioaccumulation factor (B. . and B, „'
soil sink removal rate constant (\~)
5n
fish reconcentration factor (CF )
resuspension factor (RF)
sedimentation removal fraction*
irrigation fraction (fR)
watertreatment removal fraction
cowtomilk transfer factor (F )
mn
(a)
(a)
r
cowtobeef transfer factor
effective decay constant from vegetation
dose conversion factors**
risk conversion factors**
(a)
The uncertainties in these parameters were characterized by probability
distributions which were propagated through the pathway models using a
simulation technique which produced uncertainty distributions in the
estimates of fatal cancers per unit radionuclide release to a river. The
*These factors were set equal to 1.0 in the EPA calculations but were
assigned a range of values for the Envirosphere calculations.
**These factors were combined in the EPA analysis into the fatal
cancer risk factor (FCFnp).
factors are used in calculating the term RInp in the EPA
algorithms. They are defined and their application in the calculation of
RInp values is discussed in Section C.I of Appendix C.
75

purpose of this work was to estimate the uncertainty associated with the EPA
river release mode pathways to firstorder and to identify the important
uncertain parameters so that the values chosen for these parameters could be
carefully reevaluated. Preliminary Envirosphere analyses were presented to
expert reviewers (Ri83) whose comments were used to improve some of the
model input parameter uncertainty distributions for the final analysis, to
better reflect the current state of knowledge about those factors.
An example of the results of the Envirosphere uncertainty analysis is
shown in Figure 71, which shows uncertainty distributions for the fatal
cancers risk for Am243 releases to a river*. Figure 71 shows a probability
plot of the fatal cancers per 10,000 years per curie of Am243 released to a
river. The plots are generated by propagating the uncertainty distributions
for the parameters listed above through the eight river pathway algorithms
using stochastic simulation and a Latin Hypercube sampling technique. The
details of the analysis are presented in the Envirosphere reports (R183,
ENV85). Figure 71 indicates a 70 percent probability, considering parameter
uncertainties, that the fatal cancers over 10,000 years per curie of Am243
released to a river will be 5.72E2, as calculated by EPA (Table 62), or
less.
Similar calculations were performed for several other radionuclides
listed in Table 1 of 40CFR191 and these calculations and the results are
discussed in detail in the Envirosphere reports (R183, ENV85). The results
*The 40CFR191 release limit for Am243 1s 100 C1/10,000 yr/1000 MTHM.
76


indicated, for all radionuclides analyzed except Np237, a probability of
50 percent or more that the fatal cancers over 10,000 years per curie
released to a river will be the number calculated by EPA or less. The
exception was Np237, which showed a 10 percent probability in the
Envirosphere calculations. However, we believe there are equally
supportable differences of expert opinion as to the appropriate shape of
the parameter uncertainty distributions for the plant uptake factor
(Biy) and the fish concentration factor (CF ). We requested that
Envirosphere provide us an additional analysis for Np237, using the
alternate parameter uncertainty distributions for B. and CF^. This
* iv np
analysis yielded a probability of about 50 percent for the EPA Np237
fatal cancers per curie released to the accessible environment.
The Envirosphere project also included a number of model sensitivity
analyses which are not discussed here but which are discussed in detail in
their report. In addition, the Envirosphere reports discuss the following.
subject areas:
a. quantitative comparisons of important differences in expert
1 opinion regarding how to characterize key uncertainties,
b. an examination of the sensitivity of dose and risk uncertainty
results to the simulation technique used to propagate uncertainties,
type of parameter uncertainty distributions used (e.g., uniform vs.
log normal) and possible parameters correlation effects,
c. the relative importance of model parameter uncertainties with
respect to the overall uncertainties in dose and risk estimates.
78

We used these results, along with suggestions by the EPA Science Advisory
Board (SAB) Subcommittee (EPA84a), to identify those radionuclide release
limits that warranted further consideration regarding the selection of
appropriate values for important uncertain model parameters. Based upon
this reevaluation, some revisions were made to our input parameters in
order to better reflect the current state of understanding regarding these
parameters.
The Envirosphere report summarized a number of findings and
conclusions which are quoted below. In some cases, we have added
explanatory notes. We gave careful consideration to these findings and
conclusions in the final analysis used as a basis for the 40CFR191
(Table 1) release limits.
Envirosphere Findings (Ri83)
1. "Uncertainty about the EPA model dose and risk outputs can span
over nine orders of magnitude, depending on the radionuclide being
analyzed."
2. "Most of the model's dose output uncertainty is attributable to
uncertainties about the ingestion dose conversion factor, the
soiltoplant concentration factor (B1yl and B1v2), the soil
root zone removal rate constant (x$ ) and the fraction of river
flow used for irrigation. These pathway factors are all
associated with the crop ingestion pathway, which is the largest
dose contributing pathway of the eight included."
79

3. "Environmental pathway factor uncertainties are at least as
significant as dose conversion factor uncertainty and risk
coefficient uncertainty. In fact, many pathway factor
uncertainties are larger contributors to effects uncertainty than
are risk coefficient uncertainties in the EPA model, especially
for high LET alpha emitters."
4. "Uncertainties about external dose conversion factors, transfer
coefficients for forage to milk and forage to meat (Fmn and
Ffn), the plant surface removal coefficient UEn) and the
fraction of radionuclide removed by municipal water treatment are
not important contributors to EPA model output uncertainty for
this application."
5. "Soil resuspension factor uncertainty is only important for
Plutonium in this application of the EPA model, because plutonium
is the only radionuclide specified in 40CFR191 which has a
significant inhalation pathway dose contribution." (EPA Note: the
air resuspension model has been modified, based on suggestions by
the SAB subcommittee, and does not now contribute in a major way
to the total dose and risk values for plutonium.)
6. "Several expert reviewers expressed dissatisfaction with the
manner in which the EPA treated the removal of radioactivity from
the soil root zone and resuspension of radioactive soil. In
addition, removal of radionuclides by sedimentation processes in
the river was considered to be important, especially for
radionuclides with high binding coefficients, yet the EPA did not
include sedimentation in their model. The treatment of these
710

processes in the EPA river pathways modeling warrants further
consideration." (EPA Note: EPA is not aware of expert reviewer
dissatisfaction with the model used to remove radioactivity
from the soil root zone. Calculations were performed (see
Appendix C, Section C.8) to show that recycling from the soil
below the root zone into the river and back to the soil root zone
was not significant for fR values in the range applied by EPA
(fR = 0.1). Also, distribution coefficients (K^'s) have
been revised to generally agree with those suggested by Baes
(Ba84). As mentioned above, the resuspension model used by EPA
has been revised in accordance with suggestions provided by the
Science Advisory Board subcommittee. Several reviewers did
suggest that EPA add sedimentation removal to our river model.
There is no question that certain radionuclides deposit into
sediments in slowly flowing rivers and lakes and, during the
shortterm, sedimentation lowers river water concentrations.
However, in the long time period considered in these calculations,
massive floods (100 and 1000 year floods, etc.), may occur so that
much of the deposited activity may be resuspended from the
sediment and distributed on farm land. For this reason and
because of the difficulty involved in modelling sedimentation and
subsequent resuspension during floods, we chose what we consider
to be a conservation position and did not model radionuclide loss
from river water due to sedimentation.)
7. "Possible correlations among model parameters can have a
significant effect on uncertainty analysis results. Correlation
711

effects can increase or reduce model output uncertainties
depending on the extent of correlation and the structure of the
model. A lack of sufficient understanding about the processes
which might result in parameters being correlated permits only a
limited treatment of correlation effects."
8. "Identifying a specific repository site would considerably reduce
model dose and effects output uncertainties since many key
uncertainties are for siterelated pathway factors; however, there
would still be significant uncertainty contributions from dose
conversion factors and the risk coefficient. Much of the overall
uncertainty in dose estimation is contributed by site related
pathway parameters, and, assuming time can be "frozen" in the
assessment, once a specific site is identified measurements and
data can be collected for these parameters. The time invarient
assumption is necessary because to do otherwise eliminates the
ability to make reasonably based quantitative judgments about
model uncertainties. Also, the uncertainty characterization
developed provides a structure for updating the analysis as the
state of knowledge evolves and as changes occur."
Envirosphere Conclusions (R183)
Envlrosphere stated the following conclusions concerning the use of
probabilistic techniques for examining uncertainties In risk assessments:
1, "It 1s important to assure high quality 1n the Input parameter
uncertainty distributions used in an uncertainty analysis. The
712

validity of the results depends directly on the quality of the
input uncertainty characterizations and the results are quite
sensitive to the type of distribution assumed. Careful
consideration must be given to the implications of using a
particular probability distribution to represent a state of
•knowledge. Where valid differences of opinion exist, the
sensitivity of model results to those alternative formulations
should be tested."
2. "The type of analysis presented in this (Envirosphere) report
focuses on important technical issues of the problem, provides a
structure for updating the assessment as new information and
understanding evolves and provides a basis for defensible and
consistent standardsetting."
3. "The value of performing an analysis of uncertainties depends on
the costs associated with being wrong about a risk management
decision. These costs might include: (1) unexpected or unforeseen
negative consequences; (2) misplaced or practically irreversible
commitments of time, funds, manpower and capital; (3) adopting
policies which are difficult to alter at a later date when new
information becomes available, or (4) licensing, regulatory or
legal complications and delays. For risk management applications
an analysis of risk assessment uncertainties is, in effect, an
analysis of investment uncertainties, and as such the uncertainty
analysis should be coupled with a costbenefit analysis. For the
application examined inthis stu

limits and the degree of certainty thatthose limits will achieve
an acceptable level of population protection."
In summary, EPA is placing new emphasis on analyzing and discussing
the uncertainty in our risk assessments. The basic calculations presented
in this report were completed before the new emphasis was Implemented. We
have used point parameter values to calculate fatal cancers per unit
radionuclide release and have generally used what we believe are realistic
parameter values in the calculations, refined by the insights gained from
the Envirosphere analysis and by suggestions by the SAB subcommittee.
Taking into account the uncertainty analysis performed by Envirosphere
helps to provide reasonable assurances that the EPA goal of 10 deaths in
10,000 years per 1000 MTHM is reflected by the release limits in Table 1
of 40CFR191.
714

Ad78
AEC68
AEC73
Ba79a
Ba79b
Ba83a
Ba83b
Ba84
Be 76
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Ma73 Machta L., 1973, "Prediction of C02 in the Atmosphere", in
Carbon and the Biosphere (Edited by G.M. Woodwell and E.V.
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2131, (Springfield, VA: NTIS).
Ml79 Miller C.W., 1979, "The Interception Fraction", in: A
Statistical Analysis of Selected Parameters for Predicting Food
Chain Transport and Internal Doses of Radlonuclides Udlted by
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Hoffman F.O., Pleasant J.C. and Miller C.W., 1979, "AIRDOS 
EPA: A Computerized Methodology for Estimating Environmental
Concentrations and Dose to Man from Airborne Releases of
Radionuclides", USEPA Rep. EPA 520/179009, Oak Ridge National
Laboratory, (Washington, DC: USEPA).
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the United States in 1975", USGS Rep. Circular 765, USDOI,
(Arlington, VA: USGS).
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Ne78 Nelson C.B., Davis R. and Fowler T.W., 1978, "A Model to Assess
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Elements in the General Environment", USEPA Technical Note
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Ne84 Personal Communication, C.B. Nelson  U.S. Environmental
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Agency, December 19, 1984.
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"Transfer Coefficients for the Prediction of the Dose to Man Via
the Forage  Cow  Milk Pathway from Radionuclides Released to
the Biosphere", USDOE Rep. UCRL51939, Lawrence Livermore
Laboratory, (Springfield, VA: NTIS).
R7

Ng82a Ng Y.C., Colsher C.S. and Thompson S.E., 1982, "Transfer
Coefficients for Assessing the Dose from Radionuclides 1n Meat
and Eggs", USNRC Rep. NUREG/CR2976, Lawrence Livermore National
Laboratory, (Springfield, VA: NTIS).
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Plant Concentration Factors for Radiological Assessments", USNRC
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(Springfield, VA: NTIS).
Ng82c Ng Y.C., 1982, "A Review of Transfer Factors for Assessing the
Dose from Radionuclides in Agricultural Products", Nuclear
Safety, Vol. 23, No. 1, JanuaryFebruary 1982, pp. 5771.
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Laboratory to J.M. Smith  U.S. Environmental Protection
Agency, January 9, 1984.
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Doses to Man from Routine Releases of Reactor Effluents for the
Purpose of Evaluating Compliance with 10 CFR Part 50, Appendix
I", USNRC Regulatory Guide 1.109, revision 1, (Washington, DC:
USNRC).
NRC78 U.S. Nuclear Regulatory Commission, 1978, "Liquid Pathway
Generic Stutfy", USNRC Rep. NUREG0440, (Springfield, VA: NTIS).
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Laboratory to C.B. Nelson  U.S. Environmental Protection
Agency, November 1978.
Pe83 Peterson, H.T., 1983, "Terrestrial and Aquatic Food Chain
Pathways", in: Radiological Assessment: A Textbook on
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VA: NTIS).
Ri83 i Rish W.R., Schaffer S.A. and Mauro J.J., 1983, "Uncertainty and
Sensitivity Analysis of the Exposure Pathways Model Used as the
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Predicting Food Chain Transport and Internal Doses of
Radlonuclldes (Edited by P.O. Hoffman and C.F. Baes III) USNRC
Rep. ORNL/NUREG/TM282, pp. 109132, USNRC (Springfield, VA:
NTIS).
R8

Ru83
Ru84
Sc83
Sh79
Sh82
Sm82
Su81
Th72
Th82a
Th82b
Runkle G.E., 1983, "Calculation of Health Effects per Curie
Release for Comparison with the EPA Standard", in: Technical
Assistance for Regulatory Development: Review and Evaluation of
Draft EPA Standard 40CFR191 for Disposal of HighLevel
the
Waste,
7CTTST.
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Vol. 10, No. 3, April 1984, pp. 1215.
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Division of Ebasco Services Incorporated to J.M. Smith  U.S.
Environmental Protection Agency, September 21, 1983.
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Qp", in: A Statistical Analysis of Selected Parameters for
Predicting Food Chain Transport and Internal Doses oT
Radionuclides (Edited by F.O. Hoffman and C.F. Baes III) USNRC
Rep. ORNL/NUREG/TM282, pp. 5158, USNRC (Springfield, VA:
NTIS).
Shor R.W., Baes C.F. Ill and Sharp R.D., 1982, "Agricultural
Production in the United States by County: A Compilation of
Information from the 1974 Census of Agriculture for Use in
Terrestrial Food  Chain Transport and Assessment Models", USDOE
Rep. ORNL5768, Oak Ridge National Laboratory, (Springfield,
VA: NTIS).
Smith C.B., Egan D.J., Williams W.A., Gruhlke J.M., Hung C.Y.
and Serini B.L., 1982, "Population Risks from Disposal of
HighLevel Radioactive Wastes in Geologic Repositories', USEPA
Rep. EPA 520/380006, (Washington, DC: USEPA).
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Leggett R.W., Yalcintas M.G. and Eckerman K.F., 1981, "Estimates
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Review of the Biological and Environmental Literature",
Radiation Research, Vol. 90, No. 1, April 1982, pp. 132.
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December 1982, pp. 620621.
R9

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NTIS).
R10

NOMENCLATURE
SUBSCRIPTS.:
Unless specifically stated otherwise, these subscripts refer to the
following:
a aquifer
aquifertoriver
air
airoverland
airoverwater
breathing
radionuclide C14
radioactive decay
repository breaching event
freshwater fish
air to ground
leaching (except refers to land surface
pathway when used with variable t)
directly to land
land surface
nuclide
organ
pathway
repositorytoaquifer
river (except refers to resuspension when
used with variable x)
soil
surface water
ar
A
AL
AW
B
c, 14, and C14
D
er
f and FF
9
L
LL
LS
n
o
P
ra
R
s
sw
Nl

SUBSCRIPTS (continued):
v
w
VI
0
1
2
SYMBOLS:
A
AL
CARCAN
CF
np
CP
D'(t)
volcano/meteorite event
water or ocean
water
initial condition
upper ocean compartment
lower ocean compartment
area of land irrigated (m2)
land surface area for earth (m2)
land area on which resuspended material is
deposited (m2)
ocean surface area for earth (m2)
Initial release rate of radionuclides Into the ocean from
the river (C1/y)
risk factor to convert total bocty environmental dose
commitment to environmental risk commitment for C14
(fatal cancers/total body man rem)
bloaccumulatlon factor for fish or shellfish for
nuclide n and pathway p (C1/kg per Ci/liter)
the number of persons who can be fed from the quantity of
crops (pathway p) raised annually on a unit area of land
(man fed/m2)
dose commitment rate as a function of time (rem/yr)
total bo^y EDC as a function of Integration time for C14
releases (man rem/C1 released)
fraction of total release for the volcano/meteorite
release mode which goes into air (dimensionless)
N2

SYMBOLS (continued):
fAL
fAW
fL
fwt
Fn(f>
FHE,
fraction of total release which goes to air over land
(dimensionless)
fraction of total release which goes to air over water
(dimensionless)
fraction of repository which is being leached
(dimensionless)
fraction of total release which goes directly onto land
(dimensionless)
fraction of the repository contents which is released to
the land surface (dimensionless)
fraction of land used for various food crops for
pathway p (dimensionless)
fraction of river flow used for irrigation (dimensionless)
fraction of drinking water which is supplied from surface
water sources (dimensionless)
fraction of nuclide which passes through a water
treatment plant and remains in potable water
(dimensionless)
quantity of radionuclide n deposited to ground per unit
area integrated to time t' (Ci/mz)
flux of nuclide n to ground as a function of time
(Ci/mzyr)
fatal cancer risk factor for nuclide n and pathway p: for
inhalation and ingestion (fatal cancers committed/Ci
intake); for external air submersion (fatal cancers
committed per Ciy/m3 integrated air concentration);
for external ground contamination (fatal cancers
committed per Ciy/m2 integrated ground concentration)
environmental risk commitment to the population for
nuclide n, integrated to time t, for the release mode
under consideration (fatal cancers committed)
N3

SYMBOLS (continued):
FHE
np
FHE
np
GC
np
hA
If
N(D',t)
PFF
PFP
PP
PR
PD
environmental risk commitment to the population for
nuclide n and pathway P» integrated to time t (fatal
cancers committed)
risk commitment rate to the population for nuclide n and
pathway p (fatal cancers committed/yr)
radionuclide specific factor used to correct ground
surface fatal cancer risk factors to account for uniform
distribution of radionuclides within the 15 cm soil root
zone (dimensionless).
height of troposphere (m)
standard man breathing rate (nrVyr)
freshwater fish annual consumption rate (kg/yrperson)
seafood annual consumption rate for pathway p (kg/yr)
annual individual water ingestion rate Oiters/yrperson)
size of the population exposed to dose commitment rate
D'(t) at time t (persons)
population subjected to inhalation of radionuclides for
pathway p (persons)
population eating freshwater fish from the river (persons)
population eating food included in pathway p (persons)
population eating seafood for pathway p (persons)
population drinking water from river (persons)
i
population density for pathway p (man/m^)
quantity of radionuclide n In the upper compartment of
the ocean for releases to ocean from rivers (Ci)
quantity of radionuclide n in the lower compartment of
the ocean for releases to ocean from rivers (Ci)
source term from ground to air at time t1 (Ci/yr)
N4

SYMBOLS (continued):
Q'anp(t)
Q'D
np
Qn
Q'np(t)
Qon
R
RF
quantity of radionuclide n 1n the airoverocean
compartment (Ci)
rate of entry of radionuclide n to an aquifer for
pathway p (Ci/yr)
source term from ground to air at time t1 corrected for
depletion (Ci/yr)
quantity of radionuclide n in the airoverland
compartment (Ci)
total release of radionuclide n to the accessible
environment into pathway p (Ci). For the land surface
and air release mode, the release is instantaneous; for
the river and ocean release mode, the release is
integrated from time of placement in the repository out
to time t.
total release of radionuclide n to the accessible
environment for the release mode under consideration (Ci)
Note: Qn = Qpp since the releases considered for the
different pathways within a release mode are all equal.
rate of entry of radionuclide n into the river or ocean
(Ci/y)
initial inventory of radionuclide n in the repository (Ci)
quantity of radionuclide n in the soil root zone (Ci)
quantity of radionuclide n in the upper compartment of
the ocean for releases to ocean from air (Ci)
quantity of radionuclide n in the lower compartment of
the ocean for releases to ocean from air (Ci)
radial distance from source of radionuclide to point of
Interest (m)
an empirical expression which is given in equation 3.3.24
river flow rate (liters/yr)
resuspension factor (nr*)
N5

SYMBOLS (continued):
RI
np
RIE
np
RIV
np
SOF
t
t1
t"
an
Intake of nucllde n by an individual for the crop
represented by pathway p and for a unit acute deposition
to the surface (C1 intake per C1/m2 deposited on soil
surface)
radionuclide intake or exposure for pathway p: for
inhalation and ingestion (Ci intake); for external air
submersion (Ciy/m^ exposure); for external ground
contamination (C1y/m2 exposure)
annual risk commitment to an individual for nuclide n and
pathway p (fatal cancers committed/yr)
sedimentation coefficient from upper layer of ocean for
radionuclide n (yr~*)
sedimentation coefficient from lower layer of ocean for
radionuclide n (yr"M
shielding and occupancy factor (dimensionless)
time after placement 1n repository at which ERC is
calculated (yr)
time after release of radionuclides to the environment at
which ERC is calculated (yr)
dummy variable used for integration {yr)
time for radionuclide n to travel from aquifer to river
(yr)
time after placement in repository that radioactive
material leaves the repository (yr)
time after placement in repository that the material
. comes to the surface for the land surface release mode
(yr)
time for radionuclide n to travel from repository to
aquifer (yr)
N6

SYMBOLS (continued):
tRn
tv
Tl/2
VAW
vgn
VL
vwn
vl
W
xln
(X/Q1
xRn
time after placement in repository that radionuclide n
enters the river or ocean (yr)
time after placement in the repository that the material
enters into the land and air environment as the result of
a volcano or meteorite {yr)
radiological half life (yr)
volume of tropospheric airoverwater (m3)
deposition velocity from air to land surface (m/yr)
volume of tropospheric air over land (m3)
deposition velocity from air to ocean (m/yr)
volume of compartment 1 (upper compartment) of ocean
(liters)
irrigation rate (Iiters/m2yr)
concentration of radionuclide n in the upper compartment
of the ocean for releases to the ocean from air (Ci/liter)
air concentration at point r and time t1 due to
resuspension at initial source (Ci/m3)
air concentration of radionuclide n due to resuspension
from the ground surface at the location of interest and
due to resuspension at the initial source and subsequent
dispersion to the location of interest (Ci/m3)
atmospheric dispersion factor at the reference
distance rn (sec/m3)
air concentration of radionuclide n at the center of a
uniformly contaminated area having a surface
concentration *5n(t) due to resuspension of
radionuclides from the ground surface (Ci/m3)
"fitting" exponent in empirical equation for Xfn (r,t')
transfer rate coefficient from upper to lower ocean
(yr1)
transfer rate coefficient from lower to upper ocean
(yr1)
N7

SYMBOLS (continued):
radioactive decay constant for nuclide n (yr"1)
rate constant for deposition from air to ground (yr"1)
leaching rate constant from repository (yr"1)
rate constant for resuspension of nuclides from soil to
air (yr"1)
rate constant for transfer of nuclides from available to
unavailable soil for nuclide n (yr*1)
O'n
rate constant for deposition from air to ocean (yr"1)
rate of change with time of inventory of radionuclide n
within the 15 cm root zone, expressed per unit surface
area of soil (Ci/m2y).
inventory of radionuclide n within the 15 cm root zone,
expressed per unit surface area of soil (Ci/m2)
rate of change with time of ground surface concentration
(material within top 1 cm) for radionuclide n (Ci/mzy)
ground surface concentration (material within top 1 cm)
of radionuclide n as a function of time (C1/m2)
N8

APPENDIX A: METHODS FOR CONSIDERATION OF DAUGHTER PRODUCT INGROWTH
For each parent radionuclide discussed in this report, the method for
considering daughter product ingrowth is given in this Appendix (also see
the discussion in section 4.2).
Radionuclide
Method for Consideration of Daughter Product Ingrowth
C14 stable daughter  no action required
(T1/2 = 5730 yr)
Ni59
(T1/2 = 8 E4 yr)
stable daughter  no action required
Sr90
assume Y90 (Tj/2 = 64 hr) is in secular
= 28.1 yr) equilibrium and add Y90 risk factors to those for
Sr90.
Zr93 assume Nb93m (Tj/2  ^.6 yr) is in secular
(Ti/2= 1.5 E6 yr) equilibrium and add Nb93m risk factors to those
for Zr93.
Tc99
(T1/2 = 2.1 E5 yr)
stable daughter  no action required.
Sn126
(Ti/2 = 1 E5 yr)
use the decay scheme given by Kocher (Ko81a) for
Sn126. Assume Sb126m and Sb126 are in secular
equilibrium with Sn126. Then, using Kocher's
decay scheme, add Sb126m risk factors and
0.14Sb126 risk factors to those for Sn126.
1129
(T1/2 = 1.7 E7 yr)
stable daughter  no action required.
Cs135
(T1/2 = 3 E6 yr)
stable daughter  no action required.
Al

Radlonuclide
Methods for Consideration of Daughter Product Ingrowth
Cs137
(Tj/2 = 30 yr)
decays to Ba137m 94.6 percent of the time. Assume
that Ba137m (Ti/2 = 2.55 nin) is in secular
equilibrium with Cs137 and add 94.6 percent of
dose factors for Ba137m to the dose factors for
Cs137.
Sm151
(Ti/2 = 87
stable daughter  no action required.
Pb210
(Ti/2 = 22.3 yr)
assume Bi210 (Ti/2 = 5.01 d) and Po210
(Ti/2 = 138.4 d) are in secular equilibrium and
add the risk factors for these two nuclides to
those for Pb210.
Ra226
(Ti/2  1602 yr)
assume that all daughters of Ra226 are in
secular equilibrium and add their risk factors to
the factors for Ra226. The daughters assumed
to be in secular equilibrium are Rn222
(Tw2 = 3.82 d), Po218 (T1/2 = 3.05 m),
Pb214 (Ti/2 = 26.8 m), Bi2I4 (T1/2 = 19.9 m),
Po214 (Ti/2 = 163.7 Ms), Pb210 (Ti/2 = 22.26 y),
Bi210 (T1/2 = 5.01 d)( and Po210 (Ti/2 = 138.4 d).
Ra228
(Ti/2 = 5.75 yr)
assume that all daughters of Ra228 are in secular
equilibrium and add their risk factors to the factors
for Ra228. The daughters assumed to be in secular
equilibrium are Ac228 (Ti/2 = 6.13 hr),
Th228 (Ti/2 = 1.91 yr), Ra224 (T1/2 = 3.62 d),
Rn220 (Ti/2 = 55.6 s), Po216 (Ti/2 = 0.15 s),
Pb212 (T1/2 = 10.64 hr), Bi212 (Ti/2 = 60.6 m),
0.64 Po212 (Ti/2 = 0.298 Ms), 0.36 Tl208
(T1/2 = 3.05m).
Ac227
(Ti/2  21.77 yr)
assume that all daughters of Ac227 are in secular
equilibrium and add their risk factors to the factors
for Ac227. The daughters assumed to be in secular
equilibrium are Th227 (Ti/2 = 18.7 d),
Ra223 (T1/2 = 11.4 d), Rn219 m/2 = 3.96 s),
Po215 (Ti/2 = 1.78 ms), Pb211 (Ti/2 = 36.1 m),
Bi211 (Ti/2 = 2.13 m), and Tl207 ft1/2 = 4.77 m).
A2

Radionuclide
Methods for Consideration of Daughter Product Ingrowth
Th229
(T1/2 = 7.34E3 yr)
assume that all daughters of Th229 are In secular
equilibrium and add their risk factors to the
factors for Th229. The daughters assumed to be in
secular equilibrium are Ra225 (Tj/g = 148 d),
Ac225 (T1/2 = 10.Od), Fr221 (T1/2 = 4.8m),
At217 (Ti/2 = 32.3ms), Bi213 (T1/2 = 45.65m),
Po213 (Tj/g =. 4.2Ms), and Pb209 (T1/2 = 3.25h).
Th230
(T1/2 = 7.7E4 yr)
the mean residence time of Th230 in the soil root
zone (l/xs), based on removal by leaching, is
185,200 yr. The first daughter is Ra226
(Ti/2 = 1600 yr). We calculated that the Ra226
concentration would peak at 0.92 of the initial
Th230 concentration so we assumed that all
daughters of Th230 are in secular equilibrium and
add their risk factors to the factors for Th230.
The daughters assumed to be in secular equilibrium
are Ra226 {Ti/2 = 1600 yr), Rn222
(Ti/2 = 3.82 d), Po218 (T1/2 = 3.05 m), Pb214
(T1/2 = 26.8 m), Bi214 (Ti/2 = 19.9 m), Po214
(T1/2 = 163.7 us), Pb210 lT1/2 =22.26 yr),
Bi210 (Ti/2 = 5.01 d), and Po210
(Ti/2 = 138.4 d).
Th232 assume that all daughters of Th232 are in secular
(Ti/2 = 1.405E10 yr) equilibrium and add their risk factors to the
factors for Th232. The daughters assumed to be in
secular equilibrium are Ra228 (T]y2 = 5.75yr),
Ac228 (T1/2 = 6.13 h), Th228
(T1/2 = 1.91 yr), Ra224 {T1/2 = 3.62 d),
Rn220 (T1/2 = 55.61 s), Po216
(T1/2 = 0.146 s), Pb212 (T1/2 = 10.64 hr),
Bi212 (T1/2 = 60.55 m), 0.64 Po212
(T1/2 = 0.298 us), and 0.36 Tl208
(Ti/2 = 3.05 m).
Pa231 assume that all daughters of Pa231 are in secular
(Ti/2 * 3.276E4 yr) equilibrium and add their risk factors to the
factors for Pa231. The daughters assumed to be in
secular equilibrium are Ac227 (Ti/2 = 21.Syr),
Th227 (T1/2 = 18.7 d), Ra223 (T1/2 = 11.4 d),
Rn219 (Ti/2 = 3.96 s), Po215
(Tl/2 = 1.78 ms), Pb211 (Ti/2 = 36.1 m),
Bi211 (Ti/2 = 2.13 m), and Tl207
(Ti/2 = 4.77 m).
A3

Radionuclide
Methods for Consideration of Daughter Product Ingrowth
U233 the mean residence time of U233 in the soil root
(Ti/2 = 1.592E5 yr) zone (l/xs), based on removal by Teaching, is
556 yr. The first daughter is Th229
(Tj/2 = 7.34E3 yr). We calculated that the
Th229 concentration would peak at 0.05 of the
initial U233 concentration so we assume that all
daughters of U233 attain 5 percent of secular
equilibrium and add 0.05 times their risk factors
to the factors for U233. The daughters assumed to
reach 5 percent of secular equilibrium are Th229
(Ti/2 = 7.34E3 yr), Ra225 (T1/2 = 14.8 d),
Ac225 (T1/2 = 10.0 d), Fr221 (Ti/2 = 4.8 m),
At217 (T1/2 = 32.3 ms), Bi213
(Ti/2 = 45.65 m), Po213 (Ti/2 = 4.2 Ms), and
Pb209 (T1/2 = 3.25 h).
U234 the mean residence time of U234 in the soil root
(Ti/2 = 2.5E5 yr) zone (l/xs), based on removal by leaching, is
555 yr. The first daughter is Th230
(Jl/2 = 8E 4 yr' We calculated that no
significant levels of Th230 would build up within
the mean lifetime of U234 in the soil root zone.
Thus, there were ££ additions to the U234 risk
factors.
U235
(Tl/2
= 7.038E8 yr)
assume Th231 (Tw2 = 25.52 hr) is in secular
equilibrium with 0235. The mean residence time
of U235 in the soil root zone (l/xs)» based on
removal by leaching, is 556 yr. The second
daughter is Pa231 (T1/2 = 3.276E4 yr). We
calculated that the Pa231 concentration would peak
at 0.01 of the initial U235 concentration so we
assumed that Pa231 and the remaining daughters
attain 1 percent of secular equilibrium. Thus,
we added 100 percent of the Th231 risk factors
and 1 percent of the remaining daughter risk
factors to the factors for U235. The daughters
for which the additions were made are
1.0 Th231 (Ti/2 = 25.5 h), 0.01 Pa231
* 3.276 E4yr), 0.01 Ac227
= 18.7 d),
•219
(T1/2 = 3.96 sV.'O.Ol Po215 (T^ * 1.78 ms),
0.01 Pb211 (Ti/2 = 36.1 m), 0.01 Bi211
(Tl/2 = 2'13 m), and 0.01 Tl207 (4.77 m).
(Ti/2 * 3.276 E4 yr), 0.01 Ac227
(Ti/o = 21.77 yr), 0.01 Th227 (Ti/2 =
O.Ol Ra223 (T1/2 = 11.4 d), 0.01 Rn21
(Ti/o = 3.96 s), 0.01 Po215 (T1/2 = 1.
A4

Radionuclide
Methods for Consideration of Daughter Product Ingrowth
U236
the mean residence time of U236 in the soil root
= 2.3415E7 yr) zone (l/xs), based on removal by leaching, is
556 yr. The first daughter is Th232
(T!/? = l405E10yr). We calculated that no
significant levels of Th232 would build up within
the mean lifetime of U236 in the soil root zone.
There were no additions to the risk factors.
U238
= 4.468E9 yr)
the mean residence time of U238 in the soil root
zone UAc), based on removal by leaching, is
556 yr. The first and second daughters are Th234
(Tj/2 = 24.1 d), and Pa234m (Tj/2 = 1.17 m)
which are assumed to be in secular equilibrium with
U238. The third daughter is U234
(TI/£ = 2.445E5yr). We calculated that no
significant levels of U234 would build up within
the mean lifetime of U238 in the soil root zone.
Thus, only the risk factors for Th234 and Pa234m
were added to those for U238.
Np237
(Ti/2= 2.14 E6 yr)
assume Pa233 (Tjy? = 27d) is in secular
equilibrium and ada Pa233 dose factors to those
for Np237. The mean residence time of Np237 in
the soil root zone (l/xs), based on removal by
leaching, is 37 yr. The first longlived daughter
is U233 (T1/2 = 1.62E5 yr). We calculated that
no significant levels of U233 (and the daughters
beyond) would build up within the mean lifetime of
Np237 in the soil root zone. Thus, there were no
additions to Np237 risk factors for U233 and th"e
daughters beyond U233.
Pu238
(T1/2 = 86 y)
the mean residence time of Pu238 in the soil root
zone (l/xs), based on physical removal by
leaching, is 5560 yr. The first daughter is U234
(Tjy2 = 2.5E5yr). We calculated that no
significant levels of U234 (and the daughters
beyond) would build up in the soil root zone due to
the decay of Pu238. There were no_ additions to
the Pu238 risk factors.
A5

Radionuclide
Methods for Consideration of Daughter Product Ingrowth
Pu239
(T1/2 = 2.4 E4 yr)
The mean residence time of Pu239 in the soil root
zone (1/>S), based on removal by leaching, is
5560 yr. The first daughter is U235
(fl/? = 7.1E8yr). We calculated that no
significant levels of U235 would build up within
the mean lifetime of Pu239 in the soil root zone.
There were no additions to the Pu239 risk factors
Pu240
(T1/2 = 6580 yr)
The mean residence time of Pu240 in the soil root
zone (l/xs), based on removal by leaching, is
5560 yr. The first daughter is U236
(TI/£ = 2.4E7yr). We calculated that no
significant levels of U236 would build up within
the mean lifetime of Pu240 in the soil root zone.
There were no additions to the Pu240 risk factors
Pu241
(1*1/2 «
The mean residence time of Pu in the soil root
zone (l/xs), based on removal by leaching, is
5556 yr. This is far longer than it would take the
Pu241 to disappear due to radioactive decay. The
first daughter is Am241 (Ti/2 = 432.2 yr). We
calculated that the Am241 concentration would peak
at 0.03 of the initial Pu241 concentration.
Np237 (Ti/g  2.14E6 yr) is the second daughter
and there would be no significant buildup in the
soil root zone. The Pu241 risk factors were
augmented by the addition of 0.03 times the risk
factors for Am241.
Pu242
(T1/2 = 3,8 E5 yr)
The mean residence time of Pu242 in the soil root
zone (l/xs), based on removal by leaching, is
5560 yr. The first daughter is U238
(Tj/2 • 4.5E9yr). We calculated that no
significant levels of U238 would build up within
the mean lifetime of Pu242 in the soil root zone.
There were no additions to the Pu242 risk factors.
Am241
(T1/2 = 458 yr)
The mean residence time of Am241 in the soil root
zone (1/Xe), based on removal by leaching, is
862 yr. The first daughter is Np237
(Tj/g = 2.1E6yr). We calculated that no
significant levels of Np237 would build up within
the mean lifetime .of Am241 .in'.the soil root zone.
There were no additions to the Am241 risk factors.
A6

Radionuclide
Methods for Consideration of Daughter Product Ingrowth
Am243
(Ti/2 = 7950 yr)
Assume Np239 (Tj/g = 2.3 d) is in secular
equilibrium and add Np239 risk factors to those
for Am243, The mean residence time of Am243 in
the soil root zone (l/xs), based on removal by
leaching, is 862 yr. The first longlived daughter
is Pu239 (Tj/2 = 24E4 *r) We calculated that
no significant levels of Pu239 would build up
within the mean lifetime of Am243 in the soil root
zone. There were n£ additions to the Am243 risk
factors for Pu239 and the daughters beyond Pu239.
Cm245
(T1/2 = 8.5E3 yr)
The mean residence time of Cm245 in the soil root
zone (l/xs), based on removal by leaching, is
2470 yr. The first and second daughters are Pu241
(Ti/2 = 14.4 yr) and Am241 (Tj/e = 432.2 yr)
whicn are assumed to be in secular equilibrium with
Cm245. The third daughter is Np237
(Ti/2 = 2.14E6 yr). We calculated that no
significant levels of Np237 would build up within
the mean lifetime of Cm245 in the soil root zone.
Thus, only the risk factors for Pu24i and Am241
were added to those for Cm245.
Cm246
(Ti/2 = 4.75E3 yr)
The mean residence time of Cm246 in the soil root
zone (l/xs), based on removal by leaching, is
2470 yr. The first daughter is Pu242
(Ti/2 = 3.758E5 yr). We calculated that no
significant levels of Pu242 would build up within
the mean lifetime of Cm246 in the soil root zone.
There were no additions to the Cm246 risk factors,
A7


APPENDIX B: FATAL CANCER RISK FACTORS
The fatal cancer risk factors which were applied in these analyses
are listed in Table Bl. Table Bl lists the risk factors for the parent
radionuclide and for daughter radionuclides which can grow in (and be
inhaled, ingested, or cause external exposure in addition to the parent)
during the mean lifetime of the parent in the soil root zone. For
inhalation and ingestion, all risk factors listed in Table Bl incorporate
the ingrowth and ctynamics of daughters in the body after intake of a
radionuclide.
The radionuclides shown in Table Bl have risk factors whose
magnitude exceeds 1 percent of the maximum risk factor for any nuclide in
the decay chain which could grow in during the mean lifetime of the parent
in the soil root zone. Included in Table Bl is the clearance class and
value for the guttoblood transfer fraction, fj, as applicable. The
source of these risk factors is a run of the EPA RADRISK computer code
using the V8401BD version of the input data file (Ne84).
An explanation of the methodology used to derive these risk factors
is given in Chapter 4*. For the inhalation and ingestion pathways two
categories of fatal cancer risk factors were calculated which were
designated Inhalation 1, Inhalation 2, Ingestion 1, and Ingestion 2.
Class Y risk factors were used for the Inhalation 1 category for all
*The technical basis for the EPA RADRISK computer code and data base
in discussed in detail in Appendices F, G and H.
Bl

nuclides where they were available and Class W risk factors were used for
the Inhalation 2 category where they were available. However, for some
radionuclides, only Class D or Class D and Class W Inhalation risk factors
were available. In these cases, the factors for the least soluble
clearance class available were applied. For example, if inhalation risk
factors were available for Class D and Class W but not for Class Y, the
Class W factors were listed In both the Inhalation 1 and Inhalation 2
categories. For the Ingestion 1 and Ingestion 2 categories, risk .factors
were used which were derived using the same absorption fraction from
guttoblood (f,) as was used for the Inhalation 1 and Inhalation 2
categories, respectively.
B2

TABLE Bl
Inhalation 1: Fatal cancer risk conversion factors for parent and significant* daughters
********************************* Daughters *******************************
Nuclide, Clearance Class, fj**
Parent R*sk factor
C14, , ,
3.053E3
N159, W, 5E2
4.761E1
Sr90, Y, 1E2
4.479E2
Zr93, Y, 2E3 Nb93m, Y, 1E2
1.269E1 1.449E1
Tc99, W, 8E1
6.120EO
Sn126, W, 2E2 (.14)Sb126, W, 1E2
5.637E1 8.310E1
1129, D, 9.5E1
1.605E+1
Cs135, D, 9.5E1
1.266EO
Parent *
Daughters
3.05E3
. 4.76E1
4.52E2
2.72E1
6.12EO
5.72E1
1.61E1
1.27EO
* Daughters for which the risk factor exceeds 1 percent of the maximum risk factor for any nuclide in the decay chain
which can grow in while the parent exists in the accessible environment.
** For each nuclide listed for inhalation pathways, the first line includes the nuclide symbol and the clearance class and
value for f used to derive the risk factor. The second line lists the risk factor.

TABLE Bl (Continued) .
Inhalation 1: Fatal cancer risk conversion factors for parent and significant* daughters
{fatal cancers committed per Ci intake)
********************************* Daughters *******************************
Parent
Cs137, D, 9.5E1
8.486EO
Sm151, W, 3E4
5.271EO
Pb210, Y, 2E1
1.715E4
Ra226, Y, 2E1
2.116E4
Ra228, Y, 2E1
1.841E4
Ac227, Y, 1E3
6.339E4
Th229, Y, 2E4
6.138E4
Th230, Y, 2E4
2.510E4
B1210, Y, 5E2
1.910E2
Pb210, Y, 2E1
1.715E4
Th228, Y, 2E4
6.030E4
Th227, Y, 2E4
3.826E3
Ra225, W, 2E1
1.211E3
Ra226, Y, 2E1
2.116E4
Nuclide, Clearance Class, fj
Risk Factor
Po210, Y, 1E1
5.311E3
Po210, Y, 1E1
5.311E3
Ra224, Y, 2E1
9.901E2
Ra223, W, 2E1
2.443E3
Ac225, Y, 1E3
1.883E3
Pb210, Y, 2E1 Po210, Y, 1E1
1.715E4 5.311E3
Parent +
Daughters
.8.49EO
5.27EO
2.27E4
4.38E4
7.98E4
6.97E4
6.45E4
6.89E4
* Daughters for which the risk factor exceeds 1 percent of the maximum risk factor for any nuclide in the decay chain
which can grow in while the parent exists in the accessible environment.

TABLE Bl
Inhalation
Parent
Th232, Y,
2.475E4
Pa231, Y,
3.287E4
U233, Y,
2.095E4
U234, Y,
2.070E4
U235, Y,
1.922E4
U236, Y,
1.959E4
U238, Y,
1.854E4
Np237, Y,
2.888E4
(Continued)
1: Fatal cancer risk conversion factors for parent and significant* daughters
(fatal cancers committed per Ci intake)
2E4
1E3
2E3
2E3
2E3
2E3
2E3
1E3
********************************* Daughters *******************************
Nuclide, Clearance Class, fi
Risk Factor
Ra228, Y, 2E1 Th228, Y, 2E4 Ra224, Y, 2E1
1.841E4 6.030E4 9.901E2
Ac227, Y, 1E3 Th227, Y, 2E4 Ra223, W, 2E1
6.399E4 3.826E3 2.443E3
(.05)Th229, Y, 2E4
3.069E3
{.01)Pa231, Y, 1E3 (.Ol)Ac227, Y, 1E3
3.287E2 6.339E2
Parent +
Daughters
1.05E5
1.03E5
2.42E4
2.07E4
2.03E4
1.96E4
1.85E4
2.89E4
* Daughters for which the risk factor exceeds 1 percent of the maximum risk factor for any nuclide in the decay chain
which can grow in while the parent exists in the accessible environment.

TABLE Bl (Continued)
Inhalation 1: Fatal cancer risk conversion factors for parent and significant* daughters
(fatal cancers committed per Ci intake)
********************************* Daughters *******************************
Nuclide, Clearance Class, fi
Parent Risk Factor
Pu238, Y, 1E3
3.134E4
Pu239, Y, 1E4
3.093E4
Pu240, Y, 1E4
3.092E4
Pu241, Y, 1E3 (.03)Am241, Y, 1E3
2.073E2 9.798E2
Pu242, Y, 1E4
2.936E4
Am241, Y, 1E3
3.266E4
Am243, Y, 1E3
3.193E4
Cm245, Y, 1E3 Am241, Y, 1E3
3.249E4 3.266E4
Cm246, Y, 1E3
3.263E4
Parent *
Daughters
3.13E4
3.09E4
3.09E4
1.19E3
2.94E4
3.27E4
3.19E4
6.54E4
3.26E4
* Daughters for which the risk factor exceeds 1 percent of the maximum risk factor for any nuclide in the decay chain
which can grow in while the parent exists in the accessible environment.

TABLE Bl (Continued)
Inhalation 2: Fatal cancer risk conversion factors for parent and significant* daughters
(fatal cancers committed per Ci intake)
********************************* Daughters *******************************
Nucllde, Clearance Class, fi
Parent Risk Factor
C14, , 
3.053E3
Ni59, W, 5E2
4.761E1
Sr90, D, 3E1 Y90, W, 1E4
4.833E1 3.556EO
Zr93, W, 2E3 Nb93m, W, 1E2
4.819EO 1.776EO
Parent +
Daughters
3.05E3
4.76E1
5.19E1
6.60EO
Tc99, W, 8E1
6.120EO
Sn126, W, 2E2
5.637E1
1129, D, 9.5E1
1.605E1
Cs135, D, 9.5E1
1.266EO
(0.14)Sb126, W, 1E2
8.310E1
5.72E1
1.61E1
1.27EO
* Daughters for which the risk factor exceeds 1 percent of the maximum risk factor for any nuclide in the decay chain
which can grow in while the parent exists in the accessible environment.

TABLE Bl (Continued)
Inhalation 2: Fatal cancer risk conversion factors for parent and significant* daughters
(fatal cancers committed per Ci intake)
Parent
Cs137, D, 9.5E1
8.486EO
Sm151, W, 3E4
5.271EO
Pb210, W, 2E1
' 9.961E2
Ra226, W, 2E1
2.331E3
Ra228, W, 2E1
4.754E2
Ac227, W, 1E3
3.232E4
Th229, W, 2E4
2.528E4
Th230, W, 2E4
1.514E4
********************************* Daughters *******************************
Nuclide, Clearance Class, fj Parent *
•Risk Factor , Daughters
Bi210, W, 5E2
6.182E1
Pb210, W, 2E1
9.961E2
Th228, W, 2E4
1.434E4
Th227, W, 2E4
2.667E3
Ra225, W, 2E1
1.2UE3
Ra226, W, 2E1
2.331E3
Po210, W, 1E1
1.930E3
Bi210, W, 5E2 Po210, W, 1E1
6.182E1 1.930E3
Ra224, W, 2E1
9.443E2
Ra223, W, 2E1
2.443E3
Ac225, W, 1E3
1.715E3
Pb210, W, 2E1 Po210, W, 1E1
9.961E2 1.930E3
8.49EO
5.27EO
2.99E3
5.33E3
1.58E4
3.74E4
2.82E4
2.05E4
* Daughters for which the risk factor exceeds 1 percent of the maximum risk factor for any nuclide in the decay chain
which can grow in while the parent exists in the accessible environment.

TABLE Bl (Continued)
Inhalation 2: Fatal cancer risk conversion factors for parent and significant* daughters
(fatal cancers committed per Ci intake)
********************************* Daughters *******************************
Parent
Th232, W, 2E4
1.358E4
Pa231, W, 1E3
2.442E4
U233, W, 2E1
O 9Q1 C"*
Ra228, W, 2E1
4.754E2
Ac227, W, 1E3
3.232E4
(.05)Th229, W, 2E4
i 9fiAr*
Nuclide, Clearance Class, f^
Risk Factor
Th228, W, 2E4 Ra224, W, 2E1
1.434E4 9.443E2
Th227, W, 2E4 Ra223, W, 2E1
2.667E3 2.443E3
(,05)Ra225, W, 2E1 (.05)Ac225, W, 1E3
fi.fWBFl 8.575F1
Parent +
Daughters
2.94E4
6.19E4
3.70E3
U234, W, 2E1
2.263E3
U235, W, 2E1
2.104E3
U236, W, 2E1
2.141E3
U238, W, 2E1
2.026E3
Np237, W, 1E3
2.464E4
(.01}Pa231. W, 1E3 (.01)Ac227, W, 1E3 (,01)Th227, W, 2E4 (,01)Ra223, W, 2E1
2.442E2 3.232E2 2.667E1 2.443E1
2.26E3
•2.72E3
2.14E3
2.04E3
2.46E4
Daughters for which the risk factor exceeds 1 percent of the maximum risk factor for any nuclide in the decay chain
which can grow in while the parent exists in the accessible environment.

TABLE Bl (Continued) _
Inhalation 2: Fatal cancer risk conversion factors for parent and significant* daughters
(fatal cancers committed per Ci intake)
********************************* Daughters *******************************
Nuclide, Clearance Class, fi
Parent R*sk Factor
Pu238, W, 1E3
2.491E4
Pu239, W, 1E3
2.648E4
Pu240, W, 1E3
2.645E4
Pu241. W, 1E3 (,03)Am241, W, 1E3
4.071E2 8.247E2
Pu242, W, 1E3
2.515E4
Am241, W, 1E3
2.749E4
Am243, W, 1E3
2.727E4
Cm245, W, 1E3 Pu241, W, 1E3 Am241, W, 1E3
2.794E4 4.071E2 2.749E4
Cm246, W, 1E3
2.782E4
Parent +
Daughters
2.49E4
2.65E4
2.65E4
1.23E3
'2.52E4
2.75E4
2.73E4
5.58E4
2.78E4
* Daughters for which the risk factor exceeds 1 percent of the maximum risk factor for any nuclfde in the decay chain
which can grow in while the parent exists in the accessible environment.

TABLE Bl (Continued) ^ j
Ingestlon 1: Fatal cancer risk conversion factors for parent and significant* daughters.
(fatal cancers committed per Ci intake)
******************************** Daughters *******************************
Nuclide, fj**
Parent R*sk Factor
C14, 
4.321E1
Ni59, 5E2
3.761E2
Sr90, 1E2 Y90, 1E4
w 1.452EO 8.391E1
 Zr93, 2E3 Nb93m, 1E2
8.459E2 4.213E2
Tc99, 8E1
5.374E1
Sn126, 2E2 Sb126m, 1E2 (.14)Sb126, 1E2
1.895EO 2.859E2 1.182E1
1129, 9.5E1
2.407E1
Cs135, 9.5E1
1.819EO
Parent +
Daughters
4.32E1
3.76E2
2.29EO
1.27E1
, 5.37E1
2.04EO
2.41E1
1.82EO
* Daughters for which the risk factor exceeds 1 percent of the maximum risk factor for any nuclide in the decay chain
which can grow in while the parent exists in the accessible environment.
** For each nuclide listed for ingestion pathways, the first line includes the nuclide symbol and the value for fx used
to derive the risk factor. The second line lists the risk factor.

TABLE Bl (Continued)
Ingestion 1: Fatal cancer ri
sk conversion factors for parent and significant* daughters
(fatal cancers committed per Ci intake)
********************************* Daughters *******************************
Parent
Cs137, 9.5E1
1.241E+1
Sm151, 3E4
3.461E2
Pb210, 2E1
3.409E2
Ra226, 2E1
7.783E1
Ra228, 2E1
5.474E1
Ac227, 1E3
2.335E2
Th229, 2E4
3.526E1
Th230, 2E4
2.198E1
Po210,
7.181E1
Pb210,
3.409E2
Th228,
1.053E1
Ra223,
4.938E1
Ra225,
4.419E1
Ra226,
7.783E1
Nuclide, fj
Risk Factor
1E1
2E1 Po210, 1E1
7.181E1
2E4 Ra224, 2E1 Pb212, 2E1
2.828E1 3.265EO
2E1
2E1 Ac225, 1E3
5.883EO
2E1 Pb210, 2E1 Po210, 1E1
3.409E2 7.181E1
Parent *
Daughters
1.24E1
3.46E2
4.13E2
4.91E2
•9.71E1
2.85E2
8.55E1
5.13E2
* Daughters for which the risk factor exceeds 1 percent of the maximum risk factor for any nuclide in the decay chain
which can grow in while the parent exists in the accessible environment.

TABLE Bl (Continued)
Ingestion 1: Fatal cancer risk conversion factors for parent and significant* daughters
(fatal cancers committed per Ci intake)
********************************* Daughters *******************************
Parent
Th232, 2E4
1.985E1
Pa231, 1E3
1.827E2
U233, 2E3
3 9.387E1
U234, 2E3
9.382E1
U235, 2E3
1.081EO
U236, 2E3
8.864E1
U238, 2E3
9.361E1
Np237, 1E3
1.860E2
Ra228, 2E1
5.474E1
Ac227, 1E3
2.335E2
(.05)Th229, 2E4
1.763EO
Th231, 2E4
1.083E1
Th234, 2E4
1.049EO
Nuclide, fi Parent +
Risk Factor Daughters
Th228, 2E4 Ra224, 2E1 Pb212, 2E1
1.053E1 2.828E1 3.265EO 1.17E2
Ra223, 2E1
4.938E1 4.67E2
(.05)Ra225, 2E1 (,05)Ac225,lE3
2.210EO 2.942E1 5.21EO
9.38E1
(.01)Pa231, 1E3 (.Ol)Ac227, 1E3 (0.01)Ra223, 2E1
1.827EO 2.335EO 4.938E1 '5.86EO
8.86E1
1.99EO
1.86E2
* Daughters for which the risk factor exceeds 1 percent of the maximum risk factor for any nuclide in the decay chain
which can grow in while the parent exists in the accessible environment.

TABLE Bl (Continued)
Ingestion 1: Fatal cancer risk conversion factors for parent and significant* daughters
(fatal cancers committed per Ci intake)
********************************* Daughters *******************************
Muclide, fi
Parent Risk Factor
Pu238, 1E3
1.856E2
Pu239, 1E4
2.043E1
Pu240, 1E4
2.041E1
Pu241, 1E3 (,03)Am241, 1E3
3.361EO 6.207EO
Pu242, 1E4
1.941E1
Am241, 1E3
2.069E2
Am243, 1E3
2.059E2
Cm245, 1E3 Pu241, 1E3 Am241, 1E3
2.111E2 3.361EO 2.069E2
Cm246, 1E3
2.098E2
Parent *
Daughters
1.86E2
2.04E1
2.04E1
9.57EO
1.94E1
2.07E2
2.06E2
4.21E2
2.10E2
* Daughters for which the risk factor exceeds 1 percent of the maximum risk factor for any nuclide in the decay chain
which can grow in while the parent exists in the accessible environment.

TABLE Bl (Continued)
Ingestion 2: Fatal cancer risk conversion factors for parent and significant* daughters
(fatal cancers committed per Ci intake)
********************************* Daughters *******************************
Nuclide, fj
parent Rl*sk Factor
C14, 
4.321E1
Ni59, 5E2
3.761E2
Sr90, 3E1 Y90, 1E4
2.762E1 8.391E1
Zr93, 2E3 Nb93m, 1E2
8.459E2 4.213E2
Tc99, 8E1
5.374E1
Sn126, 2E2 Sb126m, 1E2 (.14)Sb126, 1E2
1.895EO 2.859E2 1.182E1
1129, 9.5E1
2.407E+1
Cs135, 9.5E1
1.819EO
Parent *
Daughters
4.32E1
3.76E2
2.85E1
1.27E1
S.37E1
2.04EO
2.41E*1
1.82EO
* Daughters for which the risk factor exceeds 1 percent of the maximum risk factor for any nuclide in the decay chain
which can grow in while the parent exists in the accessible environment.

TABLE Bl (Continued)
Ingestion 2: Fatal cancer risk conversion factors for parent and significant* daughters
(fatal cancers committed per Ci intake)
********************************* Daughters *******************************
Parent
Cs137, 9.5E1
1.241E1
Sm151, 3E4
3.461E2
Pb210, 2E1
3.409E2
Ra226, 2E1
7.783E1
Ra228, 2E1
5.474E1
Ac227, 1E3
2.335E2
Th229, 2E4
3.526E1
Th230, 2E4
2.198E1
Nuclide, fi
Risk Factor
Po210, 1E1
7.181E1
Pb210, 2E1 Po210, 1E1
3.409E2 7.181E1
Th228, 2E4 Ra224, 2E1 Pb212, 2E1
1.053E1 2.828E1 3.265EO
Ra223, 2E1
4.938E1
Ra225, 2E1 Ac225, 1E3
4.419E1 5.883EO
Ra226, 2E1 Pb210, 2E1 Po210, 1E1
7.783E1 3.409E2 7.181E1
Parent *
Daughters
1.24E1
3.46E2
4.13E2
4.91E2
9.71E1
2.85E2
8.55E1
5.13E2
* Daughters for which the risk factor exceeds 1 percent of the maximum risk factor for any nuclide in the decay chain
which can grow in while the parent exists in the accessible environment.

TABLE Bl (Continued)
Ingestion 2: Fatal cancer risk conversion factors for parent and significant* daughters
(fatal cancers committed per Ci intake)
Parent
Th232, 2E4
1.985E1
Pa231, 1E3
1.827E2
U233, 2E1
4.646E1
U234, 2E1
4.605E1
U235, 2E1
4.546E1
U236, 2E1
4.353E1
U238, 2E1
4.735E1
Np237, 1E3
1.860E2
********************************* Daughters *******************************
Nuclide, fi
Risk Factor
Ra228, 2E1 Th228, 2E4 Ra224, 2E1 Pb212, 2E1
5.474E1 1.053E1 2.828E1 3.265EO
Ac227, 1E3 Ra223, 2E1
2.335E2 4.938E1
(.05)Th229, 2E4 (.05)Ra225, 2E1
1.763EO 2.210EO
(.01)Pa231, 1E3 (.Ol)Ac227, 1E3 (.01)Ra223, 2E1
1.827EO 2.335EO 4.938E1
Th234, 2E4
1.049EO
Parent *
Daughters
1.17E2
4.67E2
5.07E1
4.61E1
5.02E1
4.35E1
4.84E1
1.86E2
* Daughters for which the risk factor exceeds 1 percent of the maximum risk factor for any nuclide in the decay chain
which can grow in while the parent exists in the accessible environment.

TABLE Bl (Continued)
Ingestion 2: Fatal cancer risk conversion factors for parent and significant* daughters
(fatal cancers committed per Ci intake)
********************************* Daughters *******************************
Nucllde, fi
Parent Risk Factor
Pu238, 1E3
1.856E2
Pu239, 1E3
1.997E2
Pu240, 1E3
1.994E2
Pu241, 1E3 (.03)Am241, 1E3
3.361EO 6.207EO
Pu242, 1E3
1.897E2
Am241, 1E3
2.069E2
Am243, 1E3
2.059E2
Cm245, 1E3 Pu241, 1E3 Am241, 1E3
2.111E2 3.361EO 2.069E2
Cm246, 1E3
2.098E2
Parent *
Daughters
1.86E2
2.00E2
1.99E2
9.57EO
1.90E2
2.07E2
2.06E2
4.21E2
2.10E2
* Daughters for which the risk factor exceeds 1 percent of the maximum risk factor for any nuclide in the decay chain
which can grow in while the parent exists in the accessible environment.

TABLE Bl (Continued)
Air Submersion: Fatal cancer risk conversion factors for parent and significant* daughters
3
(fatal cancers committed per Ciy/m exposure) .
******************************* Daughters *********************************
Nuclide**
Parent Risk Factor
Parent
Daughters
C14
0
Ni59
4.100E2
Sr90
0
Zr93
0
Tc99
5.974E4
Sn126
5.395E1
1129
7.572EO
Cs135
0
Nb93m
1.232E1
Sb126m
1.993E3
M4)Sb126
4.913E2
0
4.10E2
0
1.23EI
' 5.97E4
2.54E3
7.57EO
0
* Daughters for which the risk factor exceeds 1 percent of the maximum risk factor for any nuclide in the decay chain
which can grow in while the parent exists in the accessible environment.
** For each nuclide listed for air submersion and for ground deposition, the first line includes the nuclide symbol and the
second line lists the risk factor.

TABLE Bl (Continued)
Air Submersion: Fatal cancer risk conversion factors for parent and significant* daughters
3
(fatal cancers committed per Ciy/ra exposure)
******************************* Daughters *********************************
Parent
Cs137
0
Sm151
8.148E4
Pb210
1.332EO
Ra226
8.183EO
Ra228
6.814E9
Ac227
1.445E1
Th229
9.923E1
Th230
4.350E1
(.946)Ba137m
7.179E2
Pb214
3.033E2
Ac228
1.202E3
Th227
1.258E2
Ra225
6.457EO
Pb214
3.033E2
Nuclide
Risk Factor
Bi214
2.032E3
Pb212 Bi212
1.763E2 2.392E2
Ra223 Rn219
1.589E2 7.019E1
Ac225 Fr221
1.574E1 3.748E1
Bi214
2.032E3
Parent *
Daughters
7.18E2
8.15E4
1.33EO
2.35E3
(.36)11208
1.793E3 ' 3.43E3
Pb211 Bi211
6.464E1 5.786E1 4.81E2
Bi213
1.711E2 3.30E2
2.35E3
* Daughters for which the risk factor exceeds 1 percent of the maximum risk factor for any nuclide in the decay chain
which can grow in while the parent exists in the accessible environment.

TABLE Bl (Continued)
Air Submersion: Fatal cancer risk conversion factors for parent and significant* daughters •
3
(fatal cancers committed per Ciy/m exposure)
******************************* Daughters *********************************
Parent
Th232
2.019E1
Pa231
3.629E1
U233
2.734E1
U234
1.631E1
U235
1.833E2
U236
1.269E1
U238
1.085E1
Np237
2.581E1
AC228
1.202E3
Th227
1.258E2
(.05)Th229
4.962EO
Th231
1.285E1
Th234
8.635EO
Pa233
2.575E2
Nuclide Parent +
Risk Factor Daughters
Pb212 Bi212 (.36)11208
1.763E2 2.392E2 1.793E3 3.43E3
Ra223 Rn219 Pb211 Bi211
1.589E2 7.019E1 6.464E1 5.786E1 5.17E2
(.05)Ra225 (.05)Ac225 (.05)Fr221 (.05)Bi213 .
3.229E1 7.870E1 1.874EO 8.555EO 1.68E1
1.63E1
2.01E2
1.27E1
Pa234m
1.485E1 2.36E1
2.83E2
* Daughters for which the risk factor exceeds 1 percent of the maximum risk factor for any nuclide in the decay chain
which can grow in while the parent exists in the accessible environment.

TABLE Bl (Continued)
Air Submersion: Fatal cancer risk conversion factors for parent and significant* daughters
(fatal cancers committed per Ciy/m3 exposure)
******************************* Daughters *********************************
Nuclide
Parent Risk Factor
Pu238
8.802E2
Pu239
9.058E2
Pu240
8.634E2
Pu241 (.03)Am241
0 5.982E1
Pu242
7.362E2
Am241
1.994E1
Am243 Np239
5.592E1 1.986E2
Cm245 Am241
8.242E1 1.994E1
Cm246
6.805E2
Parent +
Daughters
8.80E2
9.06E2
8.63E2
5.98E1
7.36E2
1.99E1
2.55E2
1.02E2
6.81E2
* Daughters for which the risk factor exceeds 1 percent of the maximum risk factor for any nuclide in the decay chain
which can grow in while the parent exists in the accessible environment.

TABLE Bl (Continued)
Ground Deposition: Fatal cancer risk conversion factors for parent and significant* daughters
(fatal cancers committed per Ciy/m exposure)
********************************* Daughters *******************************
Nuclide
Parent Risk Factor
C14
0
Ni59
8.871E3
Sr90
0
Zr93 Nb93m
0 1.885E2
Tc99
1.409E5
Sn126 Sb126m (.14)Sb126
1.354EO 4.001E1 9.769EO
1129
3.977E1
Cs135
0
Parent +
Daughters
0
8.87E3
0
1.89E2
1.41E5
5.11E1
3.98E1
0
* Daughters for which the risk factor exceeds 1 percent of the maximum risk factor for any nuclide in the decay chain
which can grow in while the parent exists in the accessible environment.

TABLE Bl (Continued)
Ground Deposition: Fatal cancer risk conversion factors for parent and significant* daughters
(fatal cancers committed per Ciy/m exposure)
Parent
Cs137
0
Sm151
9.425E5
Pb210
6.067E2
Ra226
1.811E1
Ra228
1.427E8
Ac227
4.661E3
Th229
2.390EO
Th230
1.928E2
********************************* Daughters *******************************
Nuclide Parent +
Risk Factor Daughters
(,946)Ba137m
1.432E1
Pb214
6.528EO
Ac228
2.264E1
Th227
2.825EO
Ra225
2.873E1
Pb214
6.528EO
Bi214
3.521E1
Ra224
2.670E1
Ra223
3.583EO
Ac225
3.806E1
Bi214
3.521E1
1.43E1
9.43E5
6.09E2
4.20E1
Pb212 Bi212 (.36)T1208 .
3.927EO 4.436EO 2.745E1 5.88E1
Rn219 Pb211 Bi211
1.509EO 1.293EO 1.242EO 1.05E1
Fr221 Bi213
8.267E1 3.577EO 7.46EO
4.20E1
* Daughters for which the risk factor exceeds 1 percent of the maximum risk factor for any nuclide in the decay chain
which can grow in while the parent exists in the accessible environment.

TABLE Bl (Continued)
Ground Deposition: Fatal cancer risk conversion factors for parent and significant* daughters
(fatal cancers committed per Ciy/m exposure)
********************************* Dau g hte r s *******************************
Parent
Th232
1.383E2
Pa231
8.488E1
U233
1.076E2
U234
1.634E2
U235
4.080EO
U236
1.476E2
U238
1.300E2
Np237
7.105E1
Ac228
2.264E1
Th227
2.825EO
(.05)Th229
1.195E1
Th231
4.089E1
Th234
2.225E1
Pa233
5.681EO
Nuclide
Risk Factor
Ra224 Pb212
2.670E1 3.927EO
Ra223 Rn219
3.583EO 1.509EO
{.05)Ra225 (.05)Ac225
1.437E2 1.903E2
(.01)Ra223
3.583E2
Pa234m
2.815E1
Parent *
Daughters
Bi212 (.36)11208
4.436EO 2.745E1 5.88E1
Pb211 Bi211
1.293EO 1.242EO 1.14E1
(,05)Fr221 (,05)Bi213
4.134E2 1.789E1 3.84E1
1.63E2
4.60EO
1.48E2
5.17E1
6.39EO
* Daughters for which the risk factor exceeds 1 percent of the maximum risk factor for any nuclide in the decay chain
which can grow in while the parent exists in the accessible environment.

TABLE Bl (Continued) . ^^ J u^ •
Ground Deposition: Fatal cancer risk conversion factors for parent and significant* daughters
(fatal cancers committed per Ciy/m exposure)
********************************* Daughters *******************************
Nuclide
Parent R*sk Factor
Pu238
1.681E2
Pu239
7.642E3
Pu240
1.610E2
Pu241 (,03)Am241
0 1.871E2
Pu242
1.337E2
Am241
6.236E1
Am243 Np239
1.437EO 4.511EO
Cm245 Ara241
1.959EO 6.236E1
Cm246
1.411E2
Parent *
Daughters
1.68E2
7.64E3
1.61E2
1.87E2
1.34E2
6.24E1
5.95EO
2.58EO
1.41E2
* Daughters for which the risk factor exceeds 1 percent of the maximum risk factor for any nuclide In the decay chain
which can grow In while the parent exists in the accessible environment.

APPENDIX C: COMPUTATIONAL .DETAILS
In this appendix, we will provide the details of the derivation of
the values used for several parameters which were discussed in Chapter 5.
A subsection of this appendix has been set aside for each parameter to be
discussed.
C.I Curie Intake per Unit Area Deposition (RInp)
The parameter, RInD» expresses the individual intake of a
radionuclide (n) per unit acute deposition to the soil surface for a food
crop (p). The associated units attached to this parameter are Ci intake
o
per Ci/m deposited to the soil. The algorithms used to compute values
for RI were similar to those given in the AIRDOSEPA"computer code
np
manual (Mo79) and those applied by NRC in Regulatory Guide 1.109(NRC77).
The computational techniques can be traced back to the HERMES computer
code (F171) which was prepared by the Pacific Northwest Laboratories in
the early 1970's.
For food crops consumed directly by humans, we can express RI
using the rate of consumption of vegetation by a human (Up and U ),
the concentration of radionuclides in the vegetation (Cp and
CL), and the deposition rate of radionuclides to the ground (dn) as
RI
np
n
(Cl)
where
Up and UL =
quantity of vegetation consumed by a human
receptor per unit time for produce (kg wet/yr)
and leafy vegetables (kg dry/yr), respectively,
Cl

CLn
concentration of nuclide n 1n and on vegetation
for produce (Ci/kg wet) and leafy vegetables
(C1/kg dry), respectively,
the deposition rate of nuclide n onto the
2
ground (Ci/m yr).
Note that the dimensions for RI from equation Cl are
2
C1 intake/yr per Ci deposited/m yr whereas the dimensions we desire are
2
Ci Intake over all time per Ci deposited (total)/m . It can be shown
that the ratio of the equilibrium intake rate to a continuous deposition
2
rate (C1 intake/yr per Ci deposited/m yr) is numerically equal to the
ratio of the total integrated intake to the acute surface deposition
2 •
(C1 intake per Ci deposited/m ). Thus, if we apply equation Cl for
equilibrium conditions (long buildup times), 1t Is appropriate to use the
equation to compute values of RI for our analysis. The expressions
for C^ and Cj: are basically the same as given in equation 49,
page 40, of AIRDOSEPA (Mo79) modified to account for removal of
radlonuclides from the plant root zone to a soil sink Usn)« The
equations are
r«>ifcp[i. *•>] ,
B1 v2 E l  e ^ ] "
vpxEn *xDn x$ir
e"XDnthp
and
(C2)
DDI fcL [ 1  e' En eL ] B.vl [ 1  e'
+XcJt,
V^T
.^DnV
(C3)
C2

where
DDI =
fraction of nuclide retained on plant foliage
which remains after washing (dimensionless),
f and f ,
cp cL
fraction of deposited nuclide retained on
edible portions of produce and leafy
vegetables, respectively (dimensionless),
lEn
the effective removal rate constant for nuclide
n from crops (yr~ ),
t and t .
ep eL
Yvp and V
time period that crops are exposed to
contamination during growing season for produce
and leafy vegetables, respectively (yr),
agricultural productivity (yield) of the edible
2
portion of produce (kg wet/m ) and leafy
2
vegetables (kg dry/m },
Biv2 and Bivl
the concentration factor for uptake of
radionuclide n from soil by edible parts of
crops for produce (Ci/kg wet plant per Ci/kg
dry soil) and leafy vegetables (Ci/kg dry plant
per Ci/kg dry soil), respectively,
lDn
radioactive decay constant for nuclide n
(yr'1),
removal rate constant for transfer of nuclide n
from the root zone to the soil below the root
zone {yr ),
C3

t. = period of longterm buildup of activity 1n soil
(yr).
P = effective density of the root zone (top 15 cm of
soil) (kg dry soil/square meter), and
a holdup time that represents the time interval
between harvest and consumption of produce and
leafy vegetables (yr).
An implicit assumption in equations C2 and C3 is that irrigation water
deposits radionuclides on the ground surface continuously. This 1s a
conservative assumption since Irrigation would actually take place for
less than the full year in many locations within the U.S.
As mentioned above, a significant change was made in equations C2
and C3 that is not included in the models 1n the AIRDOSEPA program
manual. The loss of radionuclides from the soil root zone due to leaching
of radionuclides to the soil below the root zone was accounted for by
adding the x term to the equation. This loss mechanism can be
important for longlived radionuclides and this is the reason for
including the modification 1n the equations. The addition of this loss
mechanism causes the majority of the total intake of radionuclides from
deposition on crop land to occur over a shorter time period after
deposition of radioactivity in the environment than would be the case if
radioactive decay were the only mechanism for removal from the soil root
zone. Substituting equations C2 and C3 Into Cl yields
C4

(x*x)t
RI
np
"DDI f
, [ 1  e '
Yvp xEn
•n ep ] B.
•*• ,
f . '"On "Sn'b 1 
V2 ~ ' J
p (xDn + xsn' J
e'*Dnthp
DDI fcL [ 1 
] Biyl[.le'(XDn+Xsn)tb]
vL En
."XDnthL
(C4)
The methods used to derive algorithms for.Rl for milk and beef
are similar to those used to derive equation Cl. For milk, we may write
where
quantity of milk consumed by a human receptor
per unit time (liters/yr).
rm
Ln =
concentration of nuclide n in milk (Ci/liters),
and d is as defined previously. The
algorithm for cJJ is obtained using the
methodology discussed on pages 42 and 43 of
AIRDOSEPA (Mo79) and can be written as
X t
n = m ^m
<
rf r_e Wen]
Yvf xEn
_ f 1 + \ ^ t .
r ™\"r^«* **^>*J*'l* •
. n I i Dn Sn D I
^ivll16 J
P(X + X« ) J
\ l Dn Sn' '
X
)e
Dnthff]d
(C6)
C5

where
•fm a
cf =
'em
vf =
'hsf
average fraction of a cow's daily intake of
radionuclide n which appears in each liter of
milk (Ci/liter per Ci/day intake),
amount of feed consumed by the cow (kg dry/day),
average transport time of the activity from the
feed into the milk and to the receptor (yr),
fraction of the deposited radionuclides
retained on edible portions of animal feed
crops (dimensionless),
time period that milk cow feed crops are
exposed to contamination during the growing
season (yr),
agricultural productivity (yield) of the edible
2
portion of animal feed crops (kg dry/m ),
fraction of year that animals graze on pasture
{dimenslonless),
fraction of feed that Is pasture grass when the
animals graze on pasture (dimensionless),
the time interval between harvest and
consumption for stored animal feed (yr),
and the other terms are as defined previously. Substituting equation C6
Into equation C5 yields
C6

"
„
E"H
Yvf xEn
For beef, RInp is determined by
RI
np
) e
"xDnthsf
(C7)
(C8)
where
\y = quantity of meat consumed by a human receptor
per unit time (kg/yr)
C = concentration of radionuclide n in meat (Ci/kg)
and d is as defined previously. The algorithm used to determine
values for C^ is obtained as described on pages 43 and 44 of
AIRDOSEPA (Mo79) and is
 , Ff Qf e
f F A t rl

where
Q* =
t. =
'ef
average fraction of a cow's daily intake of
radionuclide n which appears in each kilogram
of meat (Ci/kg per Ci/day Intake),
amount of feed consumed by the cow (kg dry/day),
average time from slaughter to consumption (yr),
time period that meat animal feed crops are
exposed to contamination during the growing.
season (yr),
and the other terms are as defined previously. Substituting equation C9
into equation C8 yields
RIlipUFf«f
tnVl
vf
B1vllle
x
Dn
Dnthsfl
(C10)
The parameter values chosen for this analysis are discussed below and
the references used to derive these values are listed.
For Vegetative Food Crops
Up = 176 kg wet vegetation/yr (Mo79)
C8

DD1 = 1.0 (conservative assumption)
f = 0.052 (Ba84)
cp
XE = 18.4 yr""1 (all nuclides except I) (Mo79)
This is based on a weathering half time of 13.75 d,
x£n = 31.6 yr'1 (I isotopes) (Ba84)
This is based on a weathering half time of 8 d.
t = te_ = 100 d = 0.274 yr (Ba83a)
Y = 1.6 kg wet/m* (Ba84)
The parameters xDn and \Sn are discussed in Chapter 5 and values
for various radionuclides are given in Tables 51 and 54. Values for
x,. are also repeated in Table Cl of this appendix. As discussed
Sn
earlier, equation C4, C7, and C10 must be evaluated at equilibrium so
the term e~*xDn + xSn'tb must drop out of the equation and a value
for tt. is not needed.
P = 215 kg dry soil/m2 (Mo79)
th = *hL = 336 hr
(produce and leafy vegetables)
C9

For all radionuclldes considered, the half I1fe.s are long enough such that
e"xDnthp and e"xDnthl are 1.0 so that these terms can be set
equal to 1 for our analysis.
UL = 1.2 kg dry veg./yr (Mo79, Ba83a)
fcL = 0.15 (Ba84)
Yv_ = 0.12 kg dry veg./rrf (Ba84)
The values for B^vl and Bjv2 are radionuclide specific and are
listed in Table Cl. The values are based on information provided by Baes
(Ba84) except where'noted in the table.
For Milk
,m
IT = 112 liters milk/yr (Mo79)
F values are specific to each radionuclide and are listed in
m r
Table Cl. The values are based on information provided by Baes (Ba84)
except where noted otherwise In the table.
Qm = 18.1 kg dry veg./day (Sh82)
tfm = 4 days = 0.011 yr (Mo79)
C10

Nucl i de
C
Ni
Sr
Zr
Tc
Sn
1
Cs
Sm
Pb
Ra
Ac
Th
Pa
U
Np
Pu
Am
Cm
* Value
** Val ue
*** Value
a Value
aa Value
+ See S«
B1vl
pCi/kg dry plant
pCi'Ag dry soil
NA
6.00 E2
2.50 EO
7.20 E2**
9.50 EO
3.00 E2
1.50 El
8.00 E2
1.00 E2
4.50 E2
1.50 E2
3.50 E3
8.50 E4
2.50 E3
8.50 E3
1.00 El
4.50 E4
5.50 E3
8.50 E4
B1v2
pCi/kg wet plant x$n
pCi/kg dry sol I (yr1)
NA NA
2.60 E2 5.40 E3
1.10 El 2.31 E2
7.70 E4** 2.70 E4
6.40 El 4.90 El
2.60 E3 3.24 E3
2.10 E2 1.57 E3
1.30 E2 8.10 E4
1.70 E3 1.25 E3
3.90 E3 9,00 E4
6.40 E4 1.80 E3
1.50 E4 5.40 E4
3.60 E5 5.40 E6
1.10 E4 3.24 E4
1.70 E3 1.80 E3
4.30 E3 2.69 E2
1.90 E5 1.80 E4
1.10 E4 1.16 E3
6.40 E6 4.05 E4
Fm
pCi/1
pCi /day Intake
NA
1.00 E3
1.50 E3
3.00 E5
1.00 E2
1.00 E3
1.00 E2
7.00 E3
2.00 E5
2.50 E4
4.50 E4
2.00 E5
5.00 E6
5.00 E6
6.00 E4
1.00 E5°
1.00 E7
4.00 E7
2.00 E5
is arithmetic average of values given by Baes (Ba84) and Ng (Ng82a).
is based on data suggested by Ng (Ng82b).
is based on data suggested by Ng (Ng82a).
based on data suggested by Schaffer (Sc83).
based on judgement after reviewing data from Baes (Ba84), Ng (Ng82a)
jction C.6 of this appendix for explanation of methodology used to co
Ff
pCi/kg
pCi/day intake
NA
2.00 E3***
3.00 E4
2.00 E2***
8.50 E3
8.00 E2
7.00 E3
2.00 E2
5.00 E3
3.00 E4
5.80 E4*
2.50 E5
6.00 E6
1.00 E5
2.00 E4
2.00 E400
2.00 E6***
3.50 E6
3.50 E6
, and Schaffer
impute xcn.
mT/g
NA
150
35
3,000
1.5
250
10
1,000
650
900
450
1,500
150,000 '
2,500
450
30
4,500
700
2,000
(Sc83).

fcf = 0.57 (Mo79, Ba83a)
tem = 65 days = 0.178 yr {Ba83a, Sh82)
Yyf = 0.28 kg dry veg./m'
= 90 days = 0.246 yr (Mo79) (stored feed)
For the radionuclides in this analysis, the half llfes are long enough
such that e~ Dn hsf are "1. This makes 1t unnecessary to select
values for f and f since they drop out of the equation. Values for
the other parameters in equation C7 are the same as those used for the
vegetative food crops.
For Meat
UF = 94 kg meat/yr (Mo79)
Ff values are specific to each radionuclide and are listed in Table
Cl. The values are based on information provided by Baes (Ba84) except
where noted.
Qf = 8.3 kg dry veg./day (Sh82)
ts = 20 days = 0.055 yr (Mo79)
t f = 65 days = 0.178 yr (Ba83a, Sh82)
C12

Values for the other parameters 1n equation C10 are the same as those
used for the milk pathway.
Using the algorithms and parameter values discussed in this section,
the values for RI for vegetative food crops, milk and meat can be
derived. These values are listed in Table 53.
C.2 Persons Fed per Unit Area (CPp)
The parameter CP_ expresses the number of persons who can be fed
per unit area of land for the vegetative food crops, milk and meat
pathways. The deviation of this parameter for the various foods will be
discussed in this section.
Vegetative Food Crops
Shor (Sh82) gives agricultural productivity for four different
categories of vegetative food crops. In a recent report, Baes (Ba84)
lists estimates of the relative importance of these categories in the
human diet. This data is recorded in Table C2.
TABLE C2: Productivity and relative importance of vegetative human
food crops
Crop Category
Leafy vegetables
Exposed produce
Protected produce
Grains
Productivity
kg wet/m^
2.44
1.65
0.91
0.23
Percent of Vegetative
Human Food
5.8
20.0
42.2
32.0
C13

We have assumed that one food crop per year is .raised and that each person
consumes 194 kg wet of vegetative food crops per year (Mo79) so that CP
(veg) may be calculated as
CPp (veg) =
kg wet
2.44(.Q58) + 1.65(.2Q) + 0.91(.422) + 0.23(.32) m2yr
Kg wet
yrperson
CP (veg) = 4.79 E3 persons fed/m*
Milk
Shor (Sh82) gives agricultural productivity and area! yield data for
four categories of cattle feed crops. She also discussed the fraction of
total cattle diet furnished by each feed crop. This data is listed in
Table C3.
TABLE C3: Area!
Crop Category
Pasture
Grain
Hay
Silage
yield and fraction of diet for cattle
Areal Yield
(kg dry/m^yr)
0.09
0.31*
0.46
0.66*
feed crops
Fraction of
Cattle Feed
0.55
0.17
0.21
0.07
* Productivity (kg dry/m2); assume 1 crop/yr to obtain area! yield.
C14

Shor (Sh82) also provides the following data:
Milk
Cow
Feed
Rate
= Qm = 18.1 kg dry veg./day consumed by milk cows
Milk Production = 12.9 liters
daycow
From the AIRDOSEPA computer code manual (Mo79)
Milk consumption by man = 112 liters
yrman
Then, using the data from Table C3 and the above listed values,
CP (milk) = L.09(.55)+.31(.17)+{
kg dry veg]
.46)(.21)+.66(.07) yrm2 J
«9 p liters milk 1
day cow j
18.1
kg dry veg
daycow
112
liters milk
yman
roan
*n i JIL\ i cc r o
CPn(milk) = 1.56 E3  «
P m
Meat
The data on area! yield and percentage of cattle feed listed in Table
C3 were utilized 1n deriving CPp for the meat pathway. Other data
listed by Shor (Sh82) which were used are:
Q = 8.3 kg dry feed
T ff^y
Slaughter factor = 0.34/yr
Live weight at slaughter = 477 kg
animal
C15

dressed weight = 0.56
live weignt
Therefore,
Neat production = [477 kg live
arnma
0.56 kg meat
kg 1i ve
0.34
= 90.8 kg meat = 0.25 kg meat
,
animal yr
,
animal day
From the AIRDOSEPA computer program manual, human annual meat consumption
is 94 kg meat/yr. Using this data, we can derive the CP for meat as
CPp(meat) =
.09(.55) + .
kg dry yeg
yrm .
n ?5
meat
am ma i day
8.3
kg dry veg
daycow
94
kg meat \
ypersonj
CPJmeat) = 7.85 E5
m
In summary, the values used for CP_ in our analysis are listed in Table
C4.
TABLE C4: Values for persons fed per unit area of land (CPp)
Food
CP,
person fed/m2
Vegetative Food Crops
M1lk
Meat
4.79 E3
1.56 E3
7.85 E5
C16

C.3 Fraction of River Flow Used for Irrigation.(fR)
The fraction of the river flow used for irrigation, fR, was set
equal to 0.1 in this analysis. This number is representative of the
average fraction of total surface water flow used for irrigation for the
U.S. The reader may obtain a feel for the variation in fR for various
regions of the U.S. by referring to the data in Table C5.
TABLE C5: Fraction of river flow used for irrigation (fp) by Water
Resources Council region for 1975 (Mu77)
Water Resources
Council Region
New England
MidAtlantic
South AtlanticGulf
Great Lakes
Ohio
Tennessee
Upper Mississippi
Lower Mississippi
SourisRedRainy
Missouri Basin
ArkansasWhitened
TexasGulf
Rio Grande
Upper Colorado
Lower Colorado
Great Basin
Pacific Northwest
California
U.S. (conterminous)
0.001
0.001
0.009
0.001
0
0
0.001
0.020
0.003
0.370
0.029
0.031
0.580
0.285
0.969
0.667
0.114
0.307
0.070
C17

For the conterminous U.S., the fR values was rounded from 0.07 to
0.1. The data for the conterminous U.S. from the above table have been
compared to data from other references which generally support the fR
value of 0.1 (WIC70, WRC78).
C.4 Population Density (PD )
o
The value used for population density is 6.67 E5 persons/m . This
value is the world average population density and was obtained by dividing
the assumed population of 10 persons* by the land surface area of the
earth of 1.5 E14 m2 (Wo79). A review of the data listed in Table C6
will show that the PD used is within the range of current values for
various regions of the U.S. As the world population increases, the U.S.
population would also increase.
TABLE C6: U.S. regional values for population density (PDp) ( USDC83)
Region
Population Density
for 1982 (persons/m2)
U.S. Average
New England
Middle Atlantic
East North Central
West North Central
South Atlantic
East South Central
West South Central
Mountain
Pacific
2.51 E5
7.65 E5
1.43 E4
6.57 E5
1.31 E5
5.52 E5
3.21 E5
2.28 E5
5.41 E6
1.43 E5
*The current world population Is about 3.8 E9. However, an estimate
of average world population during the time period Involved in this
calculation is 1010 people (UN77K
C18

C.5 Correction Factor for the Ground Surface Risk Factors (GC )
The risk conversion factors used for radionuclides deposited on the
ground were derived using the assumption that the material remains on the
surface. Over the long time periods involved in these calculations, the
radionuclides will move vertically downward into the soil. The gamma
radiation emitted from these nuclides is partially shielded by the soil
such that the dose equivalent per unit deposition is less than given by
the surface dose conversion factors. We derived correction factors for
each nuclide by assuming that the radioactivity was uniformly distributed
vertically within the soil root zone (see the discussion in Section
3.1.6). The algorithm used for calculating the correction factor is
GC.
np
where
[15 DiplW]
(Cll)
GC
np
Dis1(r)
= radionuclide specific factor used to correct ground
surface fatal cancer risk factors to account for uniform
distribution of radionuclides within the 15 cm soil root
zone (dimensionless),
4i~tc—
= gamma intensity for the i— gamma (gammas
emitted/disintegration),
= dose rate in air due to 1 Bq/cm ground volume
concentration within the 15 cm soil root zone for gamma
energy 1 (Sv/y),
2
= dose rate in air due to 1 Bq/cm ground surface
/
concentration for gamma energy i (Sv/y).
C19

The summations are for all gammas emitted by the parent radionuclide and
the daughter radionuclides which were Included 1n deriving the risk
conversion factors. The multiplier, 15, in the denominator of the
equation is to adjust the radionuclide content of the soil surface to
equal that of the 15 cm slab representing the soil root zone. Values for
D^sl(r) and D^ J(Y), as a function of gamma energy, were furnished by
Kocher (Ko83b). D J(T) and 15 0^ {Y) are plotted as a function of '.
gamma energy in Figure Cl. Using the algorithm given above, the gamma
energy intensity information for the parents and significant daughters
given by Kocher (KoSla) and the data plotted in Figure Cl, the
radionuclide specific correction factors listed in Table C7 were
computed. These factors were multiplied by the RADRISK risk conversion
factors (derived assuming surface deposition) to obtain risk conversion
•factors for uniform distribution of radionuclides within the 15 cm soil
root zone.
C20

ours
L'ose t'6 i^'b 'i n a "• r 3i i \\^\.i:r s L'Gvo yround 1 or
infinite uniform plane source and an infinite
uniform slab source
> ID
uo
o>
res
i
V)
o
o
t
03
QJ
QJ
C
ro
O.
i—i
ID
The infinite plane source is
located at ground level and
has an area concentration of
15 Bq/cm2. _
The infinite slab source has
the top surface at ground level
and the bottom surface at a
depth of 15 cm and has a volume
concentration of 1 Bq/cm3.
QJ
•M
(O
s
QJ
trt
O
o
ID
10
7
0.01
0.10 1.0
gamma energy, (MeV)
10.0

TABLE C7:
Ground surface radionucllde correction factors (GCnp)
Nuclide
GCnp
(Dimensionless)
C14
Ni59
Sr90
Zr93
Tc99
Sn126
1129
Cs135
Cs137
Sm151
Pb210
Ra226
Ra228
Ac227
Th229
Th230
Th232
Pa231
U233
U234
U235
U236
U238
Np237
Pu238
Pu239
Pu240
Pu241
Pu242
Am241
Am243
Cm245
Cm246
Beta emitter
8.8E5
Beta emitter
1.3E3
Beta emitter
2.2E1
l.OE2
Beta emitter
2.4E1
Beta emitter
2.3E2
2.4E1
1.8E1
1.5E1
9.7E2
2.4E1
1.8E1
1.3E1
7.5E2
2.9E2
7.3E2
2.5E4
4.3E2
9.2E2
3.8E4
4.1E4
4.0E4
1.2E2
4.0E4
1.2E2
6.9E2
3.3E2
4.0E4
C22

C.6 Leaching Removal Rate Constant for Soil (x$n)
The leaching rate constant for transfer of nuclides from available to
unavailable soil is x . The value for x. is nuclide dependent and
is determined by a method described by Baes (Ba79a). The algorithm is
w
where
I1*
(C12)
leaching removal rate constant from soil root zone
(yr'1),
w
velocity of vertical water percolation (cm/yr),
depth of soil root zone (cm), 
3
soil bulk density (g/cm )
3
soil water content (ml/cm )
equilibrium distribution coefficient of the nuclide
species between soil and water (ml/g)
C23

Parameter values for these generic calculations were chosen after
discussion with C.F. Baes III of Oak Ridge National Laboratory. The
parameter values and references are listed below:
Vw and p  used median value from Table 3.19, NUREG/CR1004 (Ba79a)
W
Vw = 74 cm/yr
p e 1.4 g/cnT
d = 15 cm (assumed soil root zone depth)
o  used average of median field capacity volumetric water content
and median wilting point volumetric water content for all soils
from Table 2 of Baes and Sharp 1983 article In the Journal of
• Environmental Quality (Ba83b)
e = 0.23 ml
cm
K.  values used are the default values recommended by Baes in
ORNL5786 (Ba84)
Kd values are nucllde specific and are listed in Table Cl.
C24

Using the above listed parameter values, the values for ASn listed
in Table Cl were computed, except for 1129. For 1129, data from
Kocher's dynamic model of the global iodine cycle {KoSlb, Ko83b) were
applied to determine AS . Kocher has a surface soil region with a depth
of 100 cm in his model. Dr. Kocher recommended that we consider transfer
from his surface soil region to the ocean mixed layer, the shallow land
subsurface region and the deep land subsurface region in determining a
value for A . The rate constants listed by Kocher for transfer from
his 100 cm deep surface soil region to the other three regionsare listed
in Table C8. We linearly scaled these rate constants to obtain rate
constants for our 15 cm soil root zone (Table C8), The summation of
these three rate constants gives a value for ASP for 1129 of
1.57 E3 yr1.
TABLE C8:
Determination of A$n for 1129
Transfer from Surface
Soil Region to
Rate Constant,
(yr1)
100 cm depth
15 cm depth
Ocean Mixed Layer
Shallow Subsurface Region
Deep Subsurface Region
2.0 E4
3.5 E5
7.0 E7
1.3 E3
2.3 E4
4.7 E6
= 1.57 E3 yr1
C25

C.7 Ratio of Persons Drinking Water and Eating F1sh to River Flow Rate
PR 1s the number of people who drink water and/or eat fish from a
river and R is the river flow rate. The ratio PR/R is needed in several
equations, and it can be determined for the purpose of this generic
evaluation without obtaining site specific data. Utilizing data from
Annex D of the 1977 UNSCEAR Report (UN77), the annual flow rate of the
rivers of the world is 3E+16 liters/yr. If one assumes a constant world
population of 10 persons*, the ratio PR/R is 3.3E7 personyr/liter.
This value for the ratio PR/R 1s midrange of values found for various
river basins in the United States. These values ranged from a high of
5.73E7 for the Lower Colorado Water Resources Council region to a low of
2.39E8 for the Pacific Northwest Water Resources Council region, based on
1975 river flow and population estimates. Table C9 lists these ratios
for the various Water Resources Council regions.
C.8 Total Fraction of Initial River Inventory Deposited to Cropland for
Radionuclides Rapidly Transferred Through Soil (Radionuclide Recycle)
The algorithms used to compute environmental risk commitment from
Irrigated food crop consumption do not Include the consideration of
recycle of radionuclides deposited on the cropland back to the river and a
*The current world population is about 3.8E9. However, an estimate
of average world population during the time, period Involved in this
calculation 1s 10*0 people (UN77).
C26

TABLE C9: Ratio of persons drinking water and eating fish to river
flow rate by Water Resources Council region (Mu77, USDC83)
Water Resources
Council Region
(Personyr/liter)
New England
MidAtlantic
South AtlanticGulf
Great Lakes
Ohio
Tennessee
Upper Mississippi
Lower Mississippi
SourisRedRainy
Missouri Basin
ArkansasWhiteRed
TexasGulf
Rio Grande
Upper Colorado
Lower Colorado
Great Basin
Pacific Northwest
California
1.32E7
2.88E7
1.03E7
2.02E7
1.50E7
5.62E8
2.00E7
6.27E8
1.78E7
1.19E7
9.24E8
1.90E7
4.40E7
8.76E8
5.73E7
1.09E7
2.39E8
2.52E7
U.S. (conterminous)
1.30E7
C27

redeposltlon of this material back to the cropland via Irrigation. We
assume that when the radionuclides are removed from the soil root zone (by
leaching) they are no longer available for uptake by foodcrops. For
radionuclides which leach rapidly through the soil, 1t 1s of interest to
consider the effects of recycling. Of the radionuclides we consider, the
one most subject to this phenomenon Is Tc99.
Dr. Kocher (Ko83a) has suggested a bounding calculation to determine
the Importance of recycle 1n making material available for plant uptake
from soil. The computation 1s shown below.
River
Irrigated
Cropland
0.85 returns
to river
0.15 Is not available
for recycle.
Assumptions:
Neglect radioactive decay as a removal mechanism.
85 percent of radionucllde deposited on cropland Immediately
recycles back to the river (Xcn 1s very large).
15 percent of radionuclide deposited on cropland Is permanently
fixed within the soil below the plantrootzone and Is no longer
available for uptake or recycle.
C28

Then let
fraction of river flow used for irrigation.
initial inventory in river (Ci).
I,
final inventory on cropland (Ci}.
We may write
= fR To * (0'85fRIo>fR + (0.85f*I0)(0.85)(fR)
3
[(0.85) fj I0](0.85)(fRK{0.85) f IQ](0.85)(fR)+
Then
If » fR + (0.85fR)fR + (0.85fR)2fR + (0.85fR)3fR + (0.85fR)4fR+ . .
"£
The above series is a geometric progression where the square of the common
ratio (0.85fR) Is less than one. For this case, the value of If/^0
for an infinite summation is
If
I.
(6u48)
(C14)
10.85f
R
The ratio If/IQ represents the total fraction of the initial inventory
in the river which is deposited on cropland' due to infinite recycling of
radionuclides. For our chosen value of fR of 0.10, we have
0.10
= 0.11.
I0 10.85(0.10)
C29

Since this ratio is very close to our chosen vajlue of fR of 0.10, the
effects of recycling are not significant in our calculations.
C.9 Tabulation of Estimated Range of Parameter Values
A specific request of the Science Advisory Board Highlevel
Radioactive Waste Disposal Subcommittee was that we include, In the final
pathways report, a listing of parameter values used in the analysis and an
estimate, where possible, of the range of values for the parameters. This
information is included in Table C10. In addition to listing the
estimated range of parameter values, the values used for our analyses,
which are also listed in other sections of this report, are restated in
the table. The parameters which are essentially invarient (such as earth
land area) are not listed 1n the table.
For some parameters, a range of values was not given in the
references we consulted and only the default value which we used is
given. For others, intuition dictates that the range given appears to be
too narrow (for example, the range of Kd for Sm, 600650 ml/g). If more
data were available, 1t is probable that the range would be larger. In
some cases, we applied a parameter value for our analysis which was near
an extreme of the range rather than one near the midpoint. This 1s ah
indication that the bulk of the data had values near this extreme and/or
that we had more confidence 1n the data near this extreme.
C30

TABLE C10:
Listing of parameter value ranges
Parameter
PD/R and Prjr/R
Estimated Range
of Values
10'6 to ID'2 per yr
2.4E8 to 5.7E7
Value
Used
104/yr
3.3E7
Notes
Estimated range
for USA based on 1975
o
I
OJ
(Pacific Northwest)(Lower Colorado)
320 to 712
603 1/y
(Ref. man value)
data (Mu77, USOC83). Value used is
world average number for a stable
world population which is about 2.6
times the current population (UN77).
Range is measured data. Ref. man
value is set higher than most
measured values. See pages 358 and
360 of ICRP No. 23 (ICRP75).
4.4 to 13.9 (Supplies of fish)
1.0 kg/y Range is per caput. Data from page
(fresh water fish) 349, ICRP No. 23 (ICRP75). Values
used from UNSCEAR (UN77).
6.0 kg/y
(Ocean fish)
1.0 kg/y
(Ocean shellfish)
Values could vary from 0 to 1.0 0.50
(food crops)
0.25
(Milk)
Value used column lists the fraction
of crop land used for the various
food crops.
0 to 0.97
0.25
(Meat)
0.10
Value used is U.S. average (See
Table C5).

o
UJ
ro
TABLE C10 (Continued):
Parameter
CPp
PDP
RF

IB
Estimated Range
of Values
5.1E5 to 9.3E2
2.1E5 to 1.4E1
1.1E6 to l.OE2
5.4E6 to 1.4E4
(Mountain) (Hid Atlantic)
1E10 to 1E8
See Note
750 to 14,600
Value
Used
d.79F_3 man fed
(Food crops) m*
l.SfiF.3 ««" fed
(Milk) m*
7.85F5 man fed
(Meat) m^
6.67E5 Persons
m2
lEftlT1
lEllsec1
3
8400 m
y
Notes
(Ba79b, Ho82b, USDA82, Ba84)
Estimated range for USA based on 1982
data (USDC83). Value used is world
average number for a stable world
population which is about 2.6 times
the current population (UN77, Wo79).
Weathered material. (Ri83, Be76).
Calculated from range of RF using the
equation RF=Xp/vg with vg=0.0l
m/sec .
(ICRP75) Minimum is for 1 yr old rest
24 hr/day. Maximum is for adult man
fwt
0.2 to 1.0
1.0
doing heavy work 10 hr/day, light
activity 6 hr/day and resting 8 hr/
day. Value used is for Reference Man
(Adult man).
Estimated range is for various
nuclides. Data from (NRC78, F171,
De75).

TABLE C10 (Continued):
Parameter
Estimated Range
of Values
Value
Used
Notes
o
I
to
HA
vgn
0.10 to 0.90
7,600m to 18,000m
0.0004 to 0.09
0.009 to 0.057
0.65
13,000m
0.01
0.02
48.7y
1
Value used Is U.S. average. Range
represents variation within U.S.
(Mu77).
Value used is mean of estimated
range. Estimated range from (Wo79).
Estimated range is from data in
Meteorology and Atomic Energy, 1968
(AEC68).
Estimated range is from data in
Meteorology and Atomic Energy, 1968
(AEC68). There is not nearly so much
data for vwn as for Vgn* The
available data suggests that vwn is
at least twice vgn.
Value calculated from vwn and fy*

TABLE C10 (Continued):
Parameter
Estimated Range
of Values
Value
Used
Notes
o
I
(A)
CFnp*
(Freshwater Fish)
C
Ni
Sr
Zr
Tc
Sn
I
Cs
Sm
Pb
Ra
Ac
Th
Pa
U
Np
Pu
45505000
100
7.0E1 to 2,
3.3
11 to 75
10010,000
10132
4014,000
25
100300
3750
25
3080
11
220
1010,000
0.150,000
OE2
4550
100
11
3.3
43
3000
33
1300
25
100
50
25
30
11
10
500
8
(Th72)
(Th72)
(B1825, R183)
(Th72)
(B182a)
(Ri83, Th72)
(Ho79)
(Pe83, Bl82b, Ho79)
(Th72)
(Th72)
(B182b, Pe83, Th72)
(Th72)
(Th72, Pe83, Th72)
(Th72)
(Th72, B182b, Th72)
(Th72, Ri83) Value of 10,000 was
top of range used by Envlrosphere Co.
This was not a measured value.
(B182b, Ri83) Value of 50,000 appears
to be an outlier. Most reported
values are between 3.5 and 50.
Am
Cm
15 to 452
25
81
25
(R183)
(Th72)
*CFnp data for ocean fish and ocean shellfish not Included In this tabulation because of minor significance
of these pathways.

o
I
to
on
TABLE C10 (Continued):
Parameter
Parameters used in
vw
if
p
0
K(j values (ml/g)
C
Ni
Sr
Zr
Tc
Sn
I
Cs
Sm
Pb
Ra
Ac
Th
Pa
U
Np
Pu
Am
Cm
Estimated Range
of Values
calculating \$n (See equation C12).
36.5376
0.931.84
0.030.40
NA
80150
0.153,300*
20003000
0.00291.5*
250
010
1052,000*
600650
4.57640*
100450
10001500
2000510,000*
25004000
10.5.4400*
0.16929*
11300,000*
1.047,230*
99.351,900*
Value
Used Notes
74 cm/y (Ba79a)
1.4 g/cm3 (Ba79a)
0.23 ml/cm3 (Ba79a)
15 cm (Ba79a)
NA
150
35
3000
1.5
250
10
1000
650
900
450
1500
150,000
2500
450
30
4500
700
2000
*Range as listed in Table 2.13 (Ba84). Range estimates without * are based on default value in (Ba84) and
value listed in Table C3 of (Li77c). Values used are the default values In (Ba84).

o
I
to
en
TABLE C10 (Continued):
Parameter
UP
DD1
fcp
xw
tep
Yyp
P
UL
DD1
fcL
teL
YVL
*hL
Estimated Range
of Values
0 to 540
01.0
0.027 to 0.073
1.7128.0
60180d
l.OE2 to 5.6
100300
84336
0 to 3.7
01.0
0.061.0
40120d
0.024 to 0.35
84336
Value
Used
Parameters used in calculating RInp
i?fi Kg wet
y
1.0
0.052
18.4/y
lOOd
1 Tfi kg wet
?15 kg dry
336 hr
1.2 kg dry/yr
1.0
0.15
lOOd
n.1? kg dry
336 hr
Notes
(Ho82b,
(Ba84)
(Ho82b,
(Ho82b,
(Ba79b,
(Ho82b,
(B177,
(Ho82b,
(Mi79f
(Ho82b,
(Ba79b,
(B177,
Mo79)
Ho79)
Ba84)
Ba84)
Ho79)
Mo79)
Ba84)
Ba84)
Ba84)
Ba84)
Mo79)

I
CO
TABLE C10 (Continued):
Parameter
um
Qm
tfm
fcf
fcem
Yvf
thsf
uf
Qf
ts
W
Estimated Range
of Values
0 to 600
4 to 25
34d
0.02 to 0.82
15200d
0.03 to 1.7
0 to 300
1.618
1220d
15200d
Value
Used
112 1/yr
ift.l kg dry
d
4d
0.57
65d
n_?8 kg dry
90d
94 kg/yr
8.3 kg dry/d
20d
65d
Notes
(Ho82b, Ho79)
(Ho82b, Sh82)
(8177, Mo79)
(M179, Mo79)
(Ho82b, Ba84)
(Ba79b, Mo79)
(Mo79)
(Ho82b, Ho79)
(Ho82b, Sh82)
(B177, Mo79)
(Ho82b, Ba84)

to
oo
TABLE
C10 (Continued):
Estimated Range
Parameter of Values
Blvl
Ni
Sr
Zr
Tc
Sn
I
Cs
Sm
Pb
Ra
Ac
Th
Pa
U
Np
Pu
Am
Cm
(pCl/kg dry crop per pCI/kg dry soil)
5.7E3 to 5.5E1
4.3E2 to 2.3E1
7.2E3 to 2.5E1
1.4 to 4.4E+1
1.3E2 to 3.0E2
1.5E2 to 2.0
3.8E3 to 5.7E1
l.OE2
1.3E2 to 9.0E1
2.4E3 to 7.1E1
3.5E3 to l.OE2
8.5E4 to 2.7E3
2.5E3 to l.OE2
8.5E3
4.8E3 to 3,5
106 to ID'2
1.7E3 to 5.5E3
3.0E5 to 8.5E4
Value
Used*
6.0E2
2.5
7.0E2
9.5
3.0E2
1.5E1
8.0E2
l.OE2
4.5E2
1.5E2
3.5E3 *
8.5E4
2.5E3
8.5E3
l.OE1
4.5E4
5.5E3
8.5E4
Notes**
(Ng82b)
(Ba84, Ng82b)
(Pe83, Ba84)
(Ho80)
(Ba84)
(Ng82b, Ba84)
(Ng82b)
(Ba84)
(Ba84)
(Ba84)
(Ba84, Mo79)
(Ba84, Mo79)
(Ba84, Mo79)
(Ba84)
(Pe83, Ng82b)
(Ba84)
(Pe83, Ba84)
(Pe83, Ba84)
*Va1ues used are default values given by Baest et. al (Ba84) except for Zr which was taken from Ng, et. al
(Ng82b).
**Notes indicate references used to estimate range of values.

I
CO
TABLE
C10 (Continued): x
Estimated Range
Parameter of Values
Biv2
Ni
Sr
Zr
Tc
Sn
I
Cs
Sm
Pb
Ra
Ac
Th
Pa
U
Np
Pu
Am
Cm
(pCi/kg wet crop per pCI/kg dry soil)
3.0E4 to 1.5E1
8.6E5 to 1.1E1
3.4E6 to 1.8E2
9.6E2 to 3.00***
l.OE3 to 1.0E2
2.0E4 to 1.5
1.5E5 to 6.8E1
1.7E3 to 7.0E3
3.0E4 to 7.3E2
7.0E5 to 7.5E1
1.5E4 to 2.5E3
. 3.0E5 to 8.6E3
1.1E4 to 2.5E3
3.0E5 to 8.6E3
5.7E6 to 1.3E1
3.8E8 to 4.0E2
2.3E7 to 5.0E3
1.1E6 to 1.2E5
Value
Used*
2.6E2
1.1E1
7.7E4
6.4E1
2.6E3
2.1E2
1.3E2
1.7E3
3.9E3
6.4E4
1.5E4
3.6E5
1.1E4
1.7E3
4.3E3
1.9E5
1.1E4
6.4E6
Notes**
(Ba84, Ng82b)
(Ba84)
(Ng82b)
(Ba84)
(Ri83)
(Ng82b, Ng82c)
(Ng82b, Ng82c)
(Ba84)
(Ng82c)
(Ng82c)
(Ba84, Mo79)
(Pe83, Ba84)
(Ba84, Mo79)
(Pe83, Ba84)
(Pe83, Ng82b)
(Ng82c)
(Ng82c)
(Pe83)
*Values used are default values given by Baes, et. al (Ba84) except for Zr which was taken from Ng, et. al
(Ng82b).
**Notes indicate references used to estimate range of values.
***Range estimated from Bfvl range in Ho80 and BfV2/BiVl ratio given in Ba84.

o
i
TABLE C10 (Continued):
Parameter
Fm (day/liter)
Mi
Sr
Zr
Tc
Sn
I
Cs
Sm
Pb
Ra
Ac
rl\*
Th
Pa
u
Np
•r
Pu
Am
Cm
Estimated Range
of Values
l.OE3 to l.OE2
3.5E4 to 3.8E3
3.0E5 to 8.0E2
2.0E3 to 4.3E2
l.OE4 to l.OE1
1.4E3 to 5.4E2
1.3E3 to 3.7E2
2.0E5
9.1E6 to 7.7E4
9.0E5 to 7.0E4
2.0E5
3.0E6 to 5.0E6
5.0E6
7.3E5 to 6.1E4
l.OE7 to l.OE3
2.7E9 to l.OE7
4.0E7 to 2.0E5
2.0E5
Value
Used*
l.OE3
1.5E3
3.0E5
l.OE2
l.OE3
l.OE2
7.0E3
2.0E5
2.5E4
4.5E4
2.0E5
5.0E6
5.0E6
6.0E4
l.OE5
l.OE7
4.0E7
2.0E5
Notes**
(Ba84, Pe83)
(Ng82c)
(Ba84, Pe83)
(Ri83)
(Ri83)
(Ng82c, Ng77)
(R183)
(Ba84)
(Ng77)
(Ng77)
(Ba84)
(Ng77, Ba84)
(Ba84)
(Ng77)
(R183)
(Ng77)
(Ba84, Ng77)
(Ba84)
*Values used are default values given by Baes, et. al (Ba84) except for Np which was taken from Rish, et. al
(R183).
**Notes indicate references used to estimate range of values.

TABLE C10 (Continued):
Parameter
Estimated Range
of Values ***
Value
Used*
Notes**
o
I
Ff (day/kg)
N1
Sr
Zr
Tc
Sn
I
Cs
Sm
Pb
Ra
Ac
Th
Pa
U
Np
Pu
Am
Cm
3.4E4 to 1.1E2
2.0E6 to 8.0E2
5.5E3 to 2.0E2
l.OE3 to 2.0E1
l.OE4 to l.OE1
1.8E4 to 2.0E1
2.9E3 to 4.5
5.0E3
l.OE4 to 2.0E3
2.5E4 to 2.0E3
1.6E6 to 2.5E5
1.6E6 to 2.0E4
1.6E6 to l.OE5
1.6E6 to 1.2
l.OE6 to 5.0E3
5.0E9 to 1.6E4
3.5E6 to 1.8E4
3.5E6
2.0E3
3.0E4
2.0E2
8.5E3
8.0E2
7.0E3
2.0E2
5.0E3
3.0E4
5.8E4
2.5E5
6.0E6
l.OE5
2.0E4
2.0E4
2.0E6
3.5E6
3.5E6
(Ng82e)
(R183, Ng82c)
(Ba84, Ng82a)
(R183, Ng82a)
(R183)
(Ng82a, Ng82c)
(R183, Mg82c)
(Ba84)
(Ng82a, Ng82c)
(Ba84, Ng82c)
(Mo79, Ba84)
(Mo79, Pe83)
(Mo79, Ba84) '
(Mo79, Ng82a)
(R183)
(Ng82c, Ng82a)
(Ba84, Ng82a)
(Ba84)
*Va1ues used are default values given by Baes, et. al (Ba84) except for HI, Zr, Ra, Np, and Pu. Values of Ff
for these five elements were discussed with C.F. Baes, III (ORNL) and S.A. Schaffer (Envlrosphere) and the
concensus was:
N1, Zr, and Pu  use values given by Ng, et. al (Ng82a);
Ra  average the values given by Baes, et. al (Ba84) and Ng, et. al (Ng82a);
Np  values given by Baes, et. al (Ba84) and Ng, et. al (Ng82a) are based on an Injection study where gut
uptake was not considered. The value should be Increased to account for gut uptake.
**Notes Indicate references used to estimate range of values.
***For several elements, values of Ff given by Ng, et. al (Ng82a, Ng82c) Include data for chicken. Ff for
chicken Is generally substantially higher than for beef and pork. The "values used" are more representative of
beef values. However, for several elements, the upper limit of the "estimated range of values" 1s for chicken.
This Is the reason that the "value used" 1s nearer the lower limit for several elements (see U; for example).

C.10 Determination of Values for the Parameters YI, ^g, SFjn and
Used for the Ocean Release Mode
In this section, we will show the methodology used to determine
parameter values which are applied in the algorithms for the ocean release
mode. These algorithms are discussed in Chapter 3, sections 3.2 and 3.4.4,
The transfer rate coefficients used in the ocean model are y^ and
Yg (see Figures 31 and 34). That for movement of water from the lower
to the upper ocean compartment is ^ an(* tne value of it used for this
analysis is 6.25 E4 yr" (Ma73). For movement of water from the upper
to the lower ocean compartment, the transfer rate coefficient is Yl, and
the value applied for this analysis 1s 3.3 E2 yr" , which 1s derived
from the expression TI « Y2 (3925/75) where 3925 m is the assumed
depth of the ocean lower compartment and 75 m is the assumed depth of the
ocean upper compartment.
The relationship between Y^ and ^ 1s derived by assuming that
interchange of water between the upper and lower layers of the ocean
results 1n no net transfer from one layer to the other, I.e., the mass of
each layer remains the same. If we further assume that the density of
water In the upper and lower layer is equal close to the boundary between
the layers, we can derive a value for YI using the value for Yg and
using conservation of mass.* The volume of water transport upward per
*For equal densities close to the boundaries of the two ocean layers,
conservation of mass will also result in conservation of volume.
C42

year 1s equal to

The Kn_ values that we used are more conservative than those 1n
INFCE78 to allow for expected competition for adsorption sites by the sea
water ions, especially Mg and Ca. In the absence of detailed experimental
work on sorption, anionic ions were assigned KDn values of zero; major
sea water ions were given KD values of 1; and neptunium was also given
a KD of 1. The effect of the sea water ions on divalent ions and on
cesium was approximated by reducing the desert soil KDn values given by
Arthur D. Little (L177c) by a factor of 10. Since the monovalent and
divalent sea water cations would be expected to have a smaller effect on
the adsorption of polyvalent cations, the Arthur D. Little KQn values
were reduced by a factor of 2 for trivalent ions and unchanged for
tetravalent ions. The values of KDn used in this report are listed in
Table Cll. Using these values and equations C16 and C17, the values
for SF, and SF0« listed In Table 56 were computed.
in in
C44

TABLE Cli:
Distribution coefficients for radionuclides on sediment
Element KQnCnvMI iliters/g)
C
Ni
Sr
Zr
Tc
Sn
I
Cs
Sm (Rare Earth)
Pb
Ra
AC
Th
Pa
U
Np
Pu
Am
Cm
0
40
2
2000
0
0
0
20
300
2000
10
500
15,000
2000
300
1
2000
1000
300
C45


APPENDIX D: SAMPLE DERIVATION OF AN ENVIRONMENTAL PATHWAY EQUATION AND
CALCULATION OF POPULATION FATAL CANCERS
A derivation of an environmental risk commitment equation and the
application of representative data in the equation to compute population
health effects for an environmental pathway will serve to illustrate the
application of the methodology described in this report. The
environmental pathway chosen for demonstration is ingestion of food crops
for radionuclide releases to a river (pathway number 3). Terms that are
explained in the "Nomenclature" section are not defined again in this
Appendix.
An expression for environmental risk commitment must be derived and
is the same as is described in section 3.1.4. The starting point is the
annual risk commitment to an individual.
The annual risk commitment is given by the concentration of
radionuclides in the river water (Q'nD/R)» the irrigation rate (W), a
conversion factor to .express the radionuclide intake by an individual per
unit deposition to the ground surface (RInD), and the risk conversion
factor (FCF ) as
RIV
RInp FCFnP
np
(Dl)
The annual population risk commitment can be expressed as the
individual risk commitment multiplied by the number of persons being fed a
particular food crop raised on irrigated land. The number of persons fed
can be determined using an estimate of the number of persons who can be
fed by raising the food crop on a unit area of land (CP ), the area of
Dl

land irrigated (A), and a weighting factor to express the fraction of
irrigated land used for a particular crop (f ) as
FP
A f
A f
(D2)
Then the annual population risk commitment is
Q' W RIM FCFnn CPn A f,
FHEnp  RIV'np PFp
np
np np ' p p
R
(D3)
By integrating this expression over time, we obtain an equation for
environmental risk commitment as
FHE
Qnp W RInp FCFnp CPp A fp
np
(D4)
Some rearrangement of terms is desirable in equation D4 since it is
to be used for generic rather than site specific analyses. We can write
the relationship
W A = f R R
which yields
W fR
* = R .
If equation D6 is substituted into equation D4, we obtain
(D5)
(D6)
FHE
np
fR fp
CPp FCFnp
Implicit in equation D7 is the assumption that all river water used
for irrigation contains radlonuclides and, consequently, that all land
irrigated by river water receives radlonuclides released from the waste
repository.
D2

Our food pathway calculation will be performed for Tc99. Parameter
values from Chapters 4 and 5 will be used in the sample calculation.
A leachingratelimited.sourceterm equation will be used for this
Illustrative calculation. Figure Dl shows the predicted travel of
radionuclides from the waste repository to the river. An expression for
the rate of entry of radionuclide n to the river can be developed after
examination of Figure Dl. The inventory of material at time, ter, when
leaching begins Is
W'er' = Qon e
(D8)
where
Q (ter) = inventory of radionuclide n in the repository at the
time leaching begins (C1) .
At any time t, (t,xt ) the rate of exit of radionuclide n from
the repository Is
it }
rnp(tlj
Ln
(D9)
where
Q'
.
rnp
rate of exit of radionuclide n from the repository at
time t. (where t1 _> t ) (Ci/yr) .
Now, assuming that radioactive decay is the only mechanism of loss of
radionuclide n during travel from the repository to the aquifer
,^,
ran
D3

REPOSITORY;
Initial Inventory=Qon
Time between placement
of nuclides and initi
ation of 1eaching=ter
t=o at time radioactive
material 1s placed 1n
repository
Travel time from
repository to
aquifer=tran
* leaching coeff.
from repository
AQUIFER
Travel time in
aquifer to
river = tarn
RIVER
F1g. Dl. Radionucllde travel from repository to river
D4

and travel from the aquifer to the river (tarn)* the equation for
release rate to the river at any time t is
W'ran'tarn'
for t > t + t * t
er ran arn
and
=0 for t £ ter + t_ + t
The relationship between t and t, is
or
an
1 = ran " arn .
D10)
(Dll)
(D12)
Substituting equations D8 and D9 into equation D10 yields
Q'n (t)  xLf Oon
(D13)
or
and substituting equation D12 into D14 gives
(D14)
n /tl , n /XDn(ter+trannarn)
Q np(t) = xLnQone e
(D15)
*0ther removal mechanisms will be operative during groundwater
transport of radionuclides from the respository to a river. However,
since our objective is to determine the fatal cancers per Ci released
to a river, this simplified transport model is acceptable for these
calculations.
D5

or
(016)
Now, assuming that only a fraction, f, , of the contents of the
repository are subject to leaching, we can write the final expression for
the release rate of radlonuclide n to the river as
fL Qon
and
Q (t) . 0
for t > t + t + t
er ran arn
for t < t + t + t
— er ran arn .
(D17)
To obtain the total (Integrated) amount of radionuclide n that has
entered the river up to time t, we Integrate equation D17 and get
Vtl / Q1np(t">dt"
0
Using equation D17 and the relationship
Rn = er ran arn
(D18)
(D19)
we obtain
°ww" r DnRneLnl
for t > t
Rn .
and
= 0
for t < t
Rn .
(D20)
D6

To determine the total release of Tc99 we will use the following
data:
Q = 1000 curies of Tc99
1
1
fL = 0.01
xLn " ^^ E"4 yr
\Dn = 3.27 E6 yr
ter = 100 yrs ,
ran
;arn = 76° Rn yrs' where Rn
= 760 (1) = 760 yrs.
= 1 (Li77c), therefore
Now, from equation C23
*Rn  ler + Van + 'arn
76°  861
Let the tine, t, for computation of the health effects commitment be
t = 10,000 yrs. Then, using equation D20 we have
and
\n fl Qon f ^Dn^ „ \n\n /'WW
—i^ r—. ie  e e
 (3.27E6)(861)
1
[(1.00E4)(861)(3.27E6+1.00E4)(10,000)]
 e
Q(IO.OOO) = (9.683) (0.997  0.388)
Q(10,000) = 5.90 curies of Tc99 released over 10,000 yrs.
To compute a value for RI , we have the following equation (from
Appendix C, Equation C4).
D7

% = "" I DDI '^P116
*r_ t.
vp
+ u'
• f 1  e
P
hL
The parameter values used in this equation are given 1n Appendix C (with
the references). They are listed again here for completeness.
IT = 176 kg wet/yr
f_ = 0.052
DDI = i.O
'En
"1
"1
'1
+ *w = 3.26 E6 yr" + 18.41 yr" = 18.41 yr', where
x = time constant for loss from vegatation due to weathering, yr"1
'ep
'ivl
teL = 0.274 yrs
q s Ci/kg dry crop
Ci/kg dry soil
Yyp . 1.6 kg wet/m'
= 3.26 E6 y
1
B  0 64 C1/kg wet crop
B1v2 ' °'M Ci/kg dry soil
xsn = 0.49 yr'
/kg dry
1
hp
= 1 E15 yrs*
*hL = 3'83 E'
P . 215 kg dry soll/m1
UL = 1.2 kg dry/yr
YyL = 0*12 kg dry/m'
fcL = 0.15
*The large value of
for RInp 1s computed.
is used to assure that an equilibrium value
D8

Using these values, the value of RI can be computed as
RI
np
176
(1M.052)
[le18'41(274>] M.64)[l]
U.6M18.4T)
M2HT8.W
215(3.26E6 + .49)
9.5E1]
215(3.26E6 +
(3.26E6M.0383
{3.26E6)(.C383
RI = 176 [1.754 E3 + 6.075 E3] 1.0 + 1.2[6.746 E2 + 9.018 E2]1.0
RI.1.57 Ci intake ^ ^
np Ci/m deposited
The remaining parameter values for use in equation D7 to compute
environmental dose commitment are
fR = o.:*
f = 0.5
2*
CP = 4.8 E3 man/m .
FCFnp = 5.4E1 fatal cancers/CI Intake (Appendix B)
The expression for computation of environmental dose commitment Is
equation D7, i.e.
FHE
np
fR fp RInp CPP FCFnp
(D7)
Substituting the parameter values discussed above into equation D7 yields
FHE = (5.90)(0.1)(0.5)(1.57)(0.0048) (0.54) = 1.19E3 fatal cancers
Thus, for 5.90 Ci of Tc99 released to the river, the number of fatal
cancers in 10,000 yrs to the affected population from consumption of food
crops irrigated by contaminated river water is estimated to be 0.00119.
*See more detailed discussion in Appendix C.
D9

The fatal cancers per curie released to the accessible environment for
this sample calculation are 0.0012/5.90 « 2.02 E4. The fatal cancers per
curie release to the accessible environment for the other nuclldes and
pathways discussed 1n this report are determined in a similar manner and
are presented in Chapter 6.
D10

APPENDIX E: FORTRAN SOURCE LISTING OF PROGRAM WESPDOSE2:
WESP POPULATION ENVIRONMENTAL RISK COMMITMENT CODE
J. M. SMITH
EPA/EERF
P. 0. BOX 3009
MONTGOMERY,AL 36193
INCLUDE COMMON FILE
INCLUDE 'DRO:WESPCOM2.FTN/LIST'
BYTE DIMENSION FOR FILE
BYTE FILE(30)
'DIMENSION STATEMENT FOR DUMMY VARIABLES FOR PRINTING ALL PATHWAY
HEALTH EFFECTS INFORMATION
DIMENSION PRINTF(MAXP),PRINTG{MAXP)
DATA WHICH RARELY OR NEVER CHANGES IS CONTAINED IN BLOCK DATA
SUBPROGRAM. READ IN OTHER DATA.
PROMPT AND TERMINAL READ
' WRITE(5,900)
READ(5,903)IPRINT,(XLABEL{J),J=1,30KLTH,FILE
ASSIGN 30TH BYTE IN FILE TO BE ZERO
FILE(LTH+1)=0
OPEN FILE AND READ MISC. INPUT DATA AND CLOSE FILE
OPEN(UNIT=lfNAME=FILE,TYPE='OLD',SHARED,READONLY,ERR=2)
READ(1,906)NN,NCARB,FRASUR,{WATER(P),POP(P),
1USEFR(P),GENVAR(P),PD(P),SOF(P),P=1,MAXP)
CLOSE(UNIT=1)
OPEN ALL OUTPUT FILES
OPEN(UNIT=1,NAME='DRO:POPDOSE.SUMI,TYPE=:INEW1}
OPEN(UNIT=2,NAME='DRO:POPHEF.SUM1JYPE'NEW1)
OPEN(UNIT=3,NW^E='DRO:POPHEG.SUMI,TYPE=1NEW1)
OPEN(UNIT^4,NAME='DRO:DILHEF.SUM',TYPE=INEW)
OPEN(UNIT=6,NAME=IDRO:DILHEG.SUMI,TYPE=INEW)
OPEN(UNIT=7,NAME='DRO:INOUT1.DATI,TYPE='NEWI)
OPEN{UNI%8,NAME='DRO:INOUT2.DATIJYPE='NEWI)
OPEN{UNIT=11,NAME=IDRO:EGANHEF.SUB',TYPE=INEW')
OPEN(UNIT=12,NAME='DRO:EGANHEG.SUBIJYPE=1NEW')
IF(IPRINT.EQ.2)OPEN(UNIT=9,NAME=IDRO:POPHE.SUBIJYPE='NEW')
WRITE OUT APPROPRIATE INPUT DATA AND HEADINGS.
El

MRITElT^OgjIPRINT.FILE.IW.IB.NN.MAXO.MAXP.MAXSUM.NWLBOD,
INCARB.OVARIE.TESTES.FRASUR.CARCAN.CARGEN,
2(P,WATER(P),POP(P),USEFR(P),GENVAR(P),PD(P),
3INTAKE(P).F(P),CP(P),FRCARB(P},SOF(PMP1(P),IP2(P),IP3(P),P,
4IM.MAXP)
.
WR1TE(8,915)(JDUM,ODUM=1>MAXP2),(JDUM>JDUM=1IMAXP3)
WRITE(1,918)((HEAD1(IDUM,0),IDUM=1,2),0=1,MAXO)
WRITE(2,921)
WRITE(2,927)((HEAD2(IDUM,PDUM),IDUM=1,2),PDUM=1,MAXSUM)
WRITE(3,924)
WRITE(3l927)((HEAD2(IDUMtPDUM),IDUMsl,2),PDUM=l,MAXSUM)
WR!TE(4,928)(XLABEL(J),J=1,19)
WRITE(6,928)(XLABEL(0),J=1,19)
WRITE(11,970)
WRITE(ll,928)(XLABEL(J),J«lf19)
WRITE(12,975)
WRITE(12,928)(XLABEL(J),J.1,19)
IF(IPRINT.EQ.2)WRITE(9,930)
OPEN(UNlT=10,NAME=lDRO:WESP2NUC.DAT',TYPE='OLDl,SHARED,READONLYf
1ERR=2)
INITIATE LOOP TO CYCLE THROUGH NUCLIDES
DO 100 Nl.NN
PDUM=1
READ(10,940)(HEAD3(IDUM)>IDUM=1I2),DIALNU,(CF(J)>J=1,MAXP2),
KRI(J),J»l1MAXP3)tVGiVW,WTRTREtGNDCOR,
2((D(J,0)(0=lfMAXO),CHEFAC(J),GHEFAC{0),J=l,fWXPl)
WRITE(7,942)(HEAD3(IDUM),IDUM=1,2)(((HEAD4(IDUM)J),IDUM=1>2),
1{D(J,0),0=1,MAXO),CHEFAC(J),GHEFAC(J),J=1,MAXP1)
WRITE(8>944)(HEAD3(IDUM),IDUM=1,2),DIALNU,N,(CF{J),J=1,MAXP2),
KRI(J),J=1(MAXP3),VG,VW,WTRTRE.GNDCOR
INITIATE LOOP TO CYCLE THROUGH PATHWAYS
DO 70 P.l.MAXP
INITIATE LOOP TO CYCLE THROUGH ORGANS
DO 50 0=1,MAXO
DOS=DOSN(N,P,0)
IF(O.EQ.OVARIE.OR.O.EQ.TESTES)DOS=DOS/2.
E2

DOSSUM(0)=DOSSUM(0)+DOS
50 CONTINUE
C .
C CALCULATE FATAL CANCER INFORMATION
C
HEFN=HEF(N,P)
. HEFSUM(PDUM)*HEFSUM(PDUM)+HEFN
60
63
70
C
CALCULATE SERIOUS GENETIC EFFECTS INFORMATION
HEGN=HEG(N,P)
HEGSUM(PDUM)*HEGSUM(PDUM)+HEGN
PRINTF(P)*HEFN
PRINTG(P)=HEGN
IF(IPRINT.EQ.2)WRITE(9,950)(HEAD3{IDUMKIDUM=1,2),P,
1HEFN.HEGN
IF(P.NE.5.AND.P.NE.8.AND.P.NE.10.AND.P.NE.12.AND.P.NE.15.AND.P
1.NE.16.AND.P.NE.21.AND.P.NE.22.AND.P.NE.24.AND.P.NE.27.AND.P.NE.
228.AND.P.NE.30)GO TO 63
WRITE(1,953)(HEAD3('IDUM),IDUM=1>2),(HEAD2(IDUM,PDUM),IDUM=1,2),
1(DOSSUM(0),Q=1,MAXO)
DO 60 0*1,MAXO
DOSSUM{0)=0.
PDUM=PDUM+1
CONTINUE
CONTINUE
WRITE(2,956){HEAD3(IDUM},IDUM=l,2),{HEFSUM(PDUM},PDUH=lfHAXSUM)
WRITE{4,959)DIALNU,(HEFSUM(PDUM)>PDUM=i,MAXSUM)
WRITE(3,956)(HEAD3(IDUM),IDUM=1,2),(HEGSUM(PDUM),PDUM=1,MAXSUM)
WRITE(6,959)DIALNU,(HEGSUM(PDUM),PDUM=1,MAXSUM)
90
C
100
C
WRITE{12,977)DIALNU,(PRINTG(P)>P=1,MAXP)
WRITE(1,963)
IF(IPRINT.EQ,2)WRITE(9,963)
DO 90 PDUM=1,MAXSUM
HEFSUM(PDUM)=0.
HEGSUH(PDUM)=0.
CONTINUE
E3

900
903
906
909
912
915
918
921
924
927
928
FORMATr HEY: HEY: HEY: LET us GET STARTED: :VIH ,
TON FIRST LINE TYPE IN IPRINT AND THE LA&EL',
2' TO BE PUT ON EGANS FILES.'/1H 'ON SECOND LINE',
3' TYPE IN INPUT DATA FILE NAME.')
FORMAT(I3,30A4/Q,30A1)
FORMAT(I3,2X,I3,2X,E10.3/(6E10.3))
FORMAT(36X,'WESP ENVIRONMENTAL DOSE COMMITMENT ESTIMATES'///
155X,'INPUT DATAV//2X,'CALCULATION OPTIONtIPRINT) = ',I2.7X,'GENE',
2'RAL INPUT DATA FILE NAME IS '.30A1//2X,'IW=',
31PE10.3,1 L/Y IBMPE10.3,1 M**3/Y NN=',I3,4X,'MAXO*1,
4I3,3X,'MAXP='.I3,3X,'MAXSUM=',I3//2X/NWLBOD=',I3,5X,'NCARB=',
4I3,5X,'OVARIE=',I3I5XJ'TESTES=',I3,5X,'FRASUR=t,lPE10.3/
42X,'CARCAfJ=',lPE10.3,t FATAL CANCERS/T.B. MANREM',5X,
4'CARGEN=',1PE10.3/ SERIOUS GENETIC EFFECTS/T.B. MANREM'///
552X,'PATHWAY DEPENDENT INPUT DATA'//2X,'P WATER(P) POP(P)',
63X, 'USEFR(P) GENVAR(P) PD(P) INTAKE(P) F(P) CP(P)',
73X,'FRCARB(P) SOF(P) IP1 IP2 IPS P1/
776X,'PERSONS'/4X,'L/Y OR L',4X,
' MAN/M**2 KG/Y',14X,'FED/M**2'/(X>I2,
FORIlAT(52Xf'NUCLIDE DEPENDENT INPUT DATAV/41X, 'DOSE EQUIVALENT
1' FACTORS AND RISK CONVERSION FACTORS ' //4X, ' (DOSE UNITS: INHAL.
2' AND INGEST. =REM/CI INTAKE, AIR SUBMER.=REM PER CIY/M**3 ',
3'GROUND CONTAM.=REM PER CIY/M**2) '/4X, ' (RISK UNITS: INHAL. AND
4' INGEST. =EFFECTS/CI INTAKE, AIR SUBMER.=EFFECTS PER CIY/M**3,
5' GROUND CONTAM. ^EFFECTS PER CIY/M**2) V/124X, 'SERIOUS'/
6115X, 'FATAL GENETICV2X, 'NUCLIDE PATHWAY *****' ,38X, 'ORGAN1
739X, ****** CANCER EFFECTSl/20X,A5,A4,2A5,5(A5,A4) ,2A5,
82(A5,A4) ,5X, 'RISK RISKV116X, 'FACTOR FACTOR' )
FORMAT(//27X,'**********CF(N,IP2)********** *********RI(N,IP3)
1'**********'/34Xi'CI/KG PER CI/L CI INTAKE PER CI/M**2',
21 DEPOSITED VG(N) VW(N) WTRTRE(N) GNDCOR(N)1/
329X,IIP2=I,I2,4X,'IP2=',I2,4X,
3'IP2=l,I2,4X(IIP3=l,I2,4X,lIP3=1,I2,4X,IIP3=',I2,6XflM/Y',6X,
4'M/Y'/2X,INUCLIDE DIALNU(N) N1//}
FORMAT (/26X,1 SMITH FACTORS FOR POPULATION DOSE AS A FUNCTION OF
1' NUCLIDE AND ORGAN'//14X, 'SUB1 ,46X, 'ORGANV2X, 'NUCLIDE1 ,2X,
2'PATHWAYS'/12X, 'SUMMED', (X,2A5),3X,2(X,2A5)/)
FORMAT(/33X,' SMITH FACTORS FOR POPULATION FATAL CANCERS1,
1' AS A FUNCTION OF NUCLIDE1/)
FORMATC22X,1 SMITH FACTORS FOR POPULATION GENETIC EFFECTS TO ',
1'FIRST GENERATION AS A FUNCTION OF NUCLIDE'/)
FORMAT(/2X, 'NUCLIDE ********************',
1 ' *********************************SUBPATHWAYS SUMMED********** '
2 ' *************************************** ' /9X , ( 4X , 2A3 ) )
FORMATUH ,30A4)
E4

930 FORMATU7X, 'SMITH FACTORS FOR POPULATION HEALTH EFFECTS AS A1,
I1 FUNCTION OF NUCLIDE AND SUBPATHWAY'//13X,'SUB1,23X,
2'SERIOUS'/2X,1NUCLIDE PATHWAY FATAL',
3' CANCERS GENETIC EFFECTS1//)
940 FORMAT(A4,A3,2X,F8.3,3X,(E10.3)/
1(E10.3))
942 FORMAT(/2X,A4,A3f2X,2A4fX,lPE9.2,lPE10.2,lP5E9.2,lPE10.2,
11P2E9.2,2X,1P2E9.2/(11X,2A4,X,1PE9.2J1PE10.2,1P5E9.2,1PE10.2>
21P2E9.2.2X.1P2E9.2))
944 FORMAT(2X,A4,A3,3X,F8.3,2X,I2,2X>(1PE10.3))
950 FORMAT(2X,A4,A3,4X,I3,2(6X,1PE10.3))
953 FORMAT{2X,A4,A3,2X,2A3,X,(X,1PE10.3),3X,2(X,1PE10.3))
956 FORMAT(2X,A4,A3,2X,(1PE10.3))
959 FORMATUH .F8.3.1P6E10.3/1H ,1P6E10.3)
963 FORMAT(/)
970 FORMAT(IX,'FATAL CANCER SMITH FACTORS FOR EACH PATHWAY1)
975 FORMAT(1X,'GENETIC EFFECTSALL GENERATIONS SMITH FACTORS',
1' FOR EACH PATHWAY')
977 FORMATdH ,F8.3,1P6E10.3/(1H .1P6E10.3))
CLOSE(UNIT=1,DISP=ISAVE1)
CLOSE(UNIT=2,DISP='SAVE')
CLOSE(UNIT=3,DISP='SAVE')
CLOSE(UNIT=4,DISP='SAVEI)
CLOSE(UNIT=6,DISP='SAVEl)
CLOSE(UNIT=7,DISP='SAVE')
CLOSE(UNIT=8,DISP='SAVE')
IF (IPRINT.EQ.2)CLOSE(UNIT=9,DISP='SAVE')
CLOSEtUNIT^lO.DISPx'SAVE1)
CLOSE(UNIT=11,DISP='SAVE')
CLOSE(UNIT=12,DISP='SAVE')
STOP
END
C
BLOCK DATA
C THIS SUBPROGRAM CONTAINS ALL DATA STATEMENTS
C
C INCLUDE COMMON FILE
INCLUDE 'DRO:WESPCOM2.FTN/NOLIST'
C
C DATA STATEMENTS
DATA HEAD1/1 BO' ,'NE1, 'RED M','ARROW',' LU'.'NG1,' LIVVER1,
1' GI^/LLI1,1 THY'.'ROIDV KID1,'NEY','OTHER1,'ORGAN1,
2' OVAR'.'IES1,' TES'/TES'/
DATA HEAD2/1 I'.'S1,1 6','8',' 9l,'IO',' 11','12',' 13',
l'15',' I'.'e1,1 l?1,1^!',1 2','21,' 23','241/ 25','27',
DATA HEAD4/' INH'/ALl1,1 INH1,'AL21,' INGE','ST1', UNGE1,'ST2',
1'EXT ','AIR','EXT ','GND'/
E5

DATA DOSSUM/MAXO*0./
DATA HEFSUM/MAXSUM*0./
DATA HEGSUM/MAXSUM*0./
DATA IPl/4,4.4,4,4,2,6,5,4,4,5,2,4,4,4,6,1,5,3,3,3,6,5,1,3,3,3,
16,3,37
DATA IP2/0,1,0,0,0,0,0,0,2,3,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,
10,2,3/
DATA IP3/0,0,1,2,3,0,0,0,0,0,0,0,1,2,3,0,0,0,1,2,3,0,0,0,1,2,3,
10,0,0/
DATA FRCARB/0.,0.,1.,0.,0.,0.,0.,0.,1.,0.,0.,0.,1.,0.,0.,0.,
10.,0.,1.,0.,0.,0.,0.,0.,1.,0.,0.,0.,1.,0./
DATA NWLBOD,OVARIE,TESTES/8,9,10/
DATA IW,IB/603.,8401./
DATA F/0.,0.,.50,.25,.25,0.,0.,0.,0.,0.,0.,0.,.23,.11,.11,0.,0.,
10,,.23,.11,.11,0.,0.,0.,.23,,11,.11,0.,0.,0./
DATA CP/0.,0.,.00479,.00156,.0000785,0.,0.,0.,0.,0.,0.,0.,.00479,
1.00156,.0000785,0.,0.,0...00479,.00156,.0000785,0.,0.,0.,.00479,
2.00156,.0000785,O.,0.,0./
DATA INTAKE/0.,1.,0.,0.,0.,0.,0.,0.,6.,1.,0.,0.,0.,0.,0.,0.,0.,
10.,0.,0.,0.,0.,0.,0.,0.,0.,0.,0.,6.,1./
DATA CARCAN,CARGEN/1.46E04,7.60E05/
END
FUNCTION DOSN(N,P,0)
C THIS FUNCTION SUBPROGRAM SELECTS THE PROPER FUNCTION FOR CALCULATING
C DOSE MULTIPLIER FOR SUBPATHWAY P AND COMPUTES THE DOSE
C QUANTITY.
C
C INCLUDE COMMON FILE
INCLUDE 'DRO:WESPCOM2.FTN/NOLIST'
IF(N.EQ.NCARB)GO TO 9
GO TO (1,2,3,3,3,4,5,6,2,2,6,4,3,3,3,5,4,6,7,7,7,5,6,4,3,
13,3,5,8,8}P
30
C
DOSN=DOSNA(P)*D(IP1{P),0)
GO TO 40
2 DOSN=DOSNB(P)*D{IP1(P),0)
GO TO 40
3 DOSN=DOSNC(P)*D(IP1(P),0)
GO TO 40
4 DOSN=DOSND(P)*D(IP1(P),0)
GO TO 40
5 DOSN=DOSNE(P)*D(IP1(P),0)
GO TO 40
6 DOSN=DOSNF(P)*D(IP1(P),0)
GO TO 40
7 DOSN=DOSNG(P)*D(IP1(P),0)
E6

8
9
40
C
C
C
C
C
C
C
C
GO TO 40
DOSN=DOSNH{P)*D(IP1(P),0)
GO TO 40
DOSN=DOSNI(P,0)
RETURN
END
*************************
FUNCTION HEF(N.P)
THIS FUNCTION SUBPROGRAM SELECTS THE PROPER FUNCTION FOR CALCULATING
FATAL CANCER HEALTH EFFECTS MULTIPLIER FOR SUBPATHWAY P AND
COMPUTES THE FATAL CANCERS QUANTITY FOR EGAN'S CODE.
INCLUDE COMMON FILE
INCLUDE 'DROiWESPCOMZ.FTN/NOLIST1
IF(N.EQ.NCARB)GO TO 9
30 GO TO (1,2,3,3,3,4,5,6,2,2,6,4,3,3,3,5,4,6,7,7,7,5,6,4,3,
13,3,5,8,8)P
35
C
40
HEF=DOSNA(P)*CHEFAC(IP1(P))
GO TO 40
HEF=DOSNB(P)*CHEFAC(IP1(P))
GO TO 40
HEF=DOSNC(P)*CHEFAC(IP1(P))
GO TO 40
HEF=DOSND(P)*CHEFAC(IP1(P})
GO TO 40
HEF=DOSNE(P)*CHEFAC(IP1(P))
GO TO 40
HEF=DOSNF(P)*CHEFAC(IP1(P))
GO TO 40
HEF=DOSNG(P)*CHEFAC(IP1(P))
GO TO 40
HEF=DOSNH(P)*CHEFAC(IP1(P))
GO TO 40
EQUATION 9 HANDLES FATAL CANCER RISK CALCULATIONS FOR C14 FOR
PATHWAYS 1 THROUGH 30.
CONTINUE
IF(P.NE.3.AND.P.NE.9.AND.P.NE.13.AND.P.NE.19.
1AND.P.NE.25.AND.P.NE.29)GO TO 35
HEF=CARCAN
GO TO 40
HEF=0.
RETURN
END
E7

FUNCTION HEG(N,P)
C  '
C THIS FUNCTION SUBPROGRAM SELECTS THE PROPER FUNCTION FOR CALCULATING
C SERIOUS GENETIC EFFECTS TO ALL GENERATIONS MULTIPLIER FOR
C SUBPATHWAY P AND COMPUTES THE SERIOUS GENETIC EFFECTS QUANTITY
C FOR EGAN'S CODE.
C
C INCLUDE COMMON FILE
INCLUDE 'DRO:WESPCOM2.FTN/NOLISr
IF(N.EQ.NCARB)GO TO 9
30 GO. TO {1,2,3,3,3,4,5,6,2,2,6,4,3,3,3,5,4,6,7,7,7,5,6,4,3,
' 13,3,5,8,8)P
C
1 HEG=DOSNA(P)*GHEFAC{IP1(P))
GO TO 40
2 HEG=DOSNB(P)*GHEFAC(IP1(P)}
GO TO 40
3 HEG=DOSNC(P)*GHEFAC(IP1(P))
GO TO 40
4 HEG=DOSND(P)*GHEFAC(IP1(P))
GO TO 40
5 HEG=DOSNE(P)*GHEFAC(IP1(P)}
GO TO 40
6 HEG=DOSNF(P)*GHEFAC{IP1(P))
GO TO 40
7 HEG=DOSNG(P)*GHEFAC(IP1(P))
GO TO 40
8 HEG=DOSNH(P)*GHEFAC(IP1{P))
GO TO 40
C EQUATION 9 HANDLES SERIOUS GENETIC RISK CALCULATIONS FOR C14 FOR
C .P=l THROUGH 30.
C
9 CONTINUE
IF(P.NE.3.AND.P.NE.9.AND.P.NE.13.AND.P.NE.19.
1AND.P.NE.25.AND.P.NE.29)GO TO 35
HEG=CARGEN
GO TO 40
HEG=0.
RETURN
END
*************************
FUNCTION DOSNA(P)
DRINKING WATER SUBPATHWAY. P=l
INCLUDE COMMON FILE
INCLUDE IDRO:WESPCOM2.FTN/NOLIST1
35
C
40
C
C
C
C
C
E8

DOSNA=POP(P)*IW*WTRTRE*FRASUR/WATER(P)
RETURN
END
********************
FUNCTION DOSNB(P)
C FISH AND SHELLFISH INGESTIOM. P=2>9,10
C
C INCLUDE COMMON FILE
INCLUDE 'DRO:WESPCOM2.FTN/NOLI$r
C
DOSNB=CF(IP2(P))*POP(P)*INTAKE(P)/WATER(P)
C .
RETURN
END
Q ********************
C
FUNCTION DOSNC(P)
C ABOVE SURFACE CROPS, MILK, BEEF INGESTION. P=3, 4, 5, 13, 14, 15, 25, 26, 27
C
C
INCLUDE COMMON FILE
INCLUDE 1DRO:WESPCOM2.FTN/NOLIST1
DOSNC=USEFR(P)*F(P)*RI(IP3(P))*CP(P)
RETURN
END
********************
FUNCTION DOSND(P)
C INHALATION OF RESUSPENDED MATERIAL. P=6,12,17,24
C
C INCLUDE COMMON FILE
INCLUDE 'DRO:WESPCOM2.FTN/NOLIST'
C
DOSND=GENVAR(P)*PD(P)*IB*USEFR(P)
C
RETURN
END
£ ********************
C
FUNCTION DOSNE(P)
C EXTERNAL DOSE—GROUND CONTAMINATION. P=7,16,22,28
C
C INCLUDE COMMON FILE
INCLUDE 'DRO:WESPCOM2.FTN/NOLIST'
E9

DOSNE=US£FR(P)*PD(P)*GNDCOR*SOF(P)
RETURN
END
Q ********************
c
FUNCTION DOSNF(P)
C EXTERNAL DOSEAIR SUBMERSION. P=8,ll, 18,23
C
C
c
c
INCLUDE COMMON FILE
INCLUDE 'DRO:WESPCOM2.FTN/NOLIST'
DOSNF=GENVAR(P)*PD(P)*USEFR{P)*SOF(P)
RETURN
END
Q ********************
C
FUNCTION DOSNG(P)
C ABOVE SURFACE CROPS,MILK,BEEF INGESTION. P=19,20,21
INCLUDE COMMON FILE
INCLUDE 'DRO:WESPCOM2.FTN/NOLIST'
DOSNG=VG*RI(IP3(P))*F(P)*CP(P)*GENVAR(P)
RETURN
END
********************
FUNCTION DOSNH(P).
C OCEAN FISH AND SHELLFISH INGESTION. P=29,30
INCLUDE COMMON FILE
INCLUDE 'DRO:WESPCOM2.FTN/NOLIST'
DOSNH=CF(IP2(P))*INTAKE(P)*POP(P)*VW*
1GENVAR(P)/WATER(P)
RETURN
END
********************
FUNCTION DOSNI(P,0)
C HANDLES ALL DOSE CALCULATIONS FOR C14.
INCLUDE COMMON FILE
INCLUDE 'DRO:WESPCOM2.FTN/NOLIST'
E10

20
40
965
C
60
IF(D(IP1(P),NWLBOD).EQ.O..AND.D(IP1(P),0).NE.O.)GO TO 20
IF(D(IP1{P),NWLBOD).EQ.O..AND.D(IP1(P),OKEQ.O,)GO TO 40
DOSNI=FRCARB(P)*D{IP1(P),0)/D(IP1(P),NWLBOD)
GO TO 60
WRITE(7,965)
DOSNI=0.
FORMAT(/2X,'YOU IDIOT—YOU HAVE SET WHOLE BODY DOSE1,
1' FACTOR FOR CARBON TO ZERO WITHOUT SETTING'/2X,'OTHER ',
2' DOSF. FACTORS TO ZERO'/)
RETURN
END
********************
INFORMATION COMMON TO MAIN CODE AND ALL SUBPROGRAMS
C
C
C SET VALUES FOR PARAMETERS
C
PARAMETER MAXP=30>MAXN=19,MAXO=10,MAXSUM=12,MAXP1=6,MAXP2=3,
1MAXP3=3
DEFINE REAL AND INTEGER VARIABLES AND THEIR LENGTHS
INTEGER*2 PtO,PDUM,OVARIE,TESTES
REAL*4 IW.INTAKE.IB
REAL*8 HEAD1
COMMON STATEMENTS
COMMON/BLK1/HEAD1{2,MAXO),HEAD2(2,MAXSUM),HEAD3(2),HEAD4(2,MAXP1),
1DIALNU,NN,NWLBOD,NCARB,IPRINT,OVARIE,TESTES,XLABEL(30)
COMMON/BLK2/D(MAXP1>MAXO)IRI(MAXP3),CF(MAXP2),WATER(MAXP),
1POP(MAXP),USEFR(MAXP),GENVAR(MAXP),PD(MAXP),INTAKE(MAXP),
2F{MAXP),CP(MAXP)>FRCARB{MAXP),DOSSUM(MAXO),HEFSUM(MAXSUM),
3HEGSUM(MAXSUM),IPl{MAXP)fIP2(MAXP),IP3(MAXP),
4VG,VW,SOF(MAXP),IW,IB,CARCAN,CARGEN,CHEFAC(MAXP1),GHEFAC{MAXP15,
SWTRTRE^FRASUR.GNDCOR
Ell

NOTES PERTINENT TO APPENDICES F, G, AND H.
The Information contained 1n Appendices F, G, and H 1s adapted from
Chapters 7 and 8 and Addendums A and B of the EPA report entitled
"Radionuclides: Background Information Document, for Final Rules",
Volume 1 (EPA84b). These appendices contain their own list of references
and definition of symbols and do not utilize, the "REFERENCES" and
"NOMENCLATURE" sections, of the main report.
In our highlevel waste environmental pathway calculations, we have
used the RADRISK data to convert from radionuclide intake for the
inhalation and ingestion pathways and from external exposure for the air
submersion and ground surface pathways directly to fatal cancer risk,
without calculating dose commitments or dose rates. The methodology
applied to compute our fatal cancer risk factors is described in
Section 4.1 of Chapter 4. Since the RADRISK computer code utilizes
computed dose rates in calculating fatal cancer risks, we have included
Appendix F, which describes the radiation dosimetry techniques applied by
EPA in these RADRISK calculations.

APPENDIX F: RADIATION DOSIMETRY
F.I Introduction
Radlonuclides transported through the environment may eventually
reach people. This contact occurs through either external exposure to
radioactive air, water, and ground surfaces or internal exposure from
inhaling or ingesting radioactive air, water, or food. Individuals in the
population may absorb energy emitted by the decaying radionuclides.
The quantification of this absorbed energy is termed dosimetry. This
appendix describes the dosimetric models for Internal and external
exposures, the EPA procedure for implementing the dosimetric equations
associated with the models, and the uncertainties in dosimetric
calculations.
Mathematical models are used to calculate doses to specific human
body organs. The models account for the amount of radionuclides entering
the body, the movement of radionuclides through the body, and the energy
deposited in organs or tissues resulting from irradiation by the
radionuclides that reach the tissue. These models provide the basis for
the computer codes, RADRISK and DARTAB, which EPA uses to calculate doses
and dose rates. (See Appendix H.) .
Uncertainties in dosimetric calculations arise from assumptions of
uniform distribution of activity in external sources and source organs and
assumptions concerning the movement of the radionuclides 1n the body. The
uncertainties associated with dosimetric calculations are difficult to
quantify because the data available for determining distribution for the
parameters used in the models are usually insufficient. The major source
of uncertainty in dosimetry is the real variation in parameter values
among individuals in the general population while doses and dose rates are
calculated for a "typical" member of the general population. The three
sources of dosimetric uncertainty assessed by EPA are: individual
variation, age, and measurement errors. The effects of uncertainty are
discussed in greater detail in Section F.6 of this appendix and in
Chapter 7.
F.2 Definitions
F.2.1 Activity
Radioactive decay is a process whereby the nucleus of an atom emits
excess energy. The emission of this energy is referred to as radioactivity.
The "activity" of a radioactive material is characterized by the number of
atoms that emit energy, or disintegrate, in a given period of time. The
unit of activity used in this report is the picocurie (pCi), which equals
2.22 disintegrations per minute. The excess energy is normally emitted as
charged particles moving at high velocities and photons. Although there are
many types of emitted radiations, or particles, only three are commonly
encountered in radioactive material found in the general environment: alpha
radiation (nuclei of helium atoms), beta radiation (electrons), and gamma
radiation (photons).
Fl

The primary mechanism for radiation damage 1s the transfer of
kinetic energy from the moving alpha and beta particles and photons to
living tissue. This transfer leads to the rupture of cellular
constituents resulting 1n electrically charged fragments (ionlzatlon).
Although the amount of energy transferred is small in absolute terms, it
Is enough to disrupt the molecular structure of living tissue, and,
depending on the amount and location of the energy release, leads to the
risk of radiation damage.
F.2.2 Exposure and Dose
The term "exposure" denotes physical contact with the radioactive
material. The term "dose" refers to the amount of energy absorbed per
gram of absorbing tissue as a result of the exposure. An exposure, for
example, may be acute, I.e., occur over a.short period of time, while the
dose, for some internally deposited materials, may extend over a long
period of time.
The dose is a measure of the amount of energy deposited by the alpha
and beta particles or photons and their secondary radiations 1n the
organ. The only units of dose used in this chapter are the raddefined
as 100 erg (energy units) per gram (mass unit)and the millirad (mrad),
which Is one onethousandth of a rad. The rad represents the amount, on
average, of potentially disruptive energy transferred by ionizing
radiation to each gram of tissue. Because 1t is necessary to know the
yearly variation In dose for the calculations described in this report,
the quantity used will be the average annual dose (or dose rate) 1n rad
or millirad (per year).
F.2.3 External and Internal Exposures
Radiation doses may be caused by either external or internal
exposures. External exposures are those caused by radioactive materials
located outside the bocty, such as Irradiation of the body by radioactive
material lying on the ground or suspended In the air. Internal exposures
are caused by radioactive material that has entered the bocjy through the
Inhalation or consumption of radioactive material. Having once entered
the body, the contaminant may be transmitted to other Internal organs and
tissues.
The external exposures considered In this report are those resulting
from irradiation of the bocjy by gamma rays only. Gamma rays (high energy
photons) are the most penetrating of those radiations considered and
external gammas may normally contribute to the radiation dose affecting
all organs 1n the bocjy. Beta particles (electrons), which are far less
penetrating, normally deliver their dose to, or slightly below, the
unshielded surface of the skin and are not considered because their
Impact is small, particularly on clothed individuals. Alpha particles
(helium nuclei), which are of major Importance internally, will not
penetrate unbroken skin and so are also excluded from the external dose
calculations. The Internal exposures considered in this report originate
from all three types of radiation.
F2

F.2.4 Dose Equivalent
Different types of charged particles differ in the rate at which
their energy is transferred per unit of length traveled in tissue, a
parameter called the linear energy transfer (LET) of the particle. Beta
particles generally have a much lower LET than alpha particles. Alpha
particles are more damaging biologically, per rad, than gamma rays and
beta particles. In radiation protection, this difference is accounted
for by multiplying the absorbed dose by a modifying factor, Q, the
quality factor, to obtain a dose equivalent. The quality factor is
intended to correct for the difference in LET of the various particles.
At present, the International Commission on Radiological Protection
(ICRP77) recommends the values Q=l for gamma rays and beta particles and
Q=20 for alpha particles. The units for the dose equivalent, corre
sponding to the rad and millirad, are rem and millirem. Thus, dose
equivalents for gamma rays and beta particles are numerically equal to
the dose since the dose equivalent (mrem) = (Q=l) x dose (mrad) while
alpha dose equivalents are twenty times as large, dose equivalent (mrem)
= (Q=20) x dose (mrad).
F.3 Dosimetric Models
The radiation dose has been defined, in Section F.2.2, as the amount
of energy absorbed per unit mass of tissue. Calculation of the dose
requires the use of mathematical models such as that shown later in
Equation (F2). In this equation, the amount of activity ingested, I, is
multiplied by the fraction, fj, going to the blood, and the fraction,
f*2» going to a specific tissue. E is the amount of energy absorbed by
the tissue for each unit of activity so that the product of all these
factors divided by the mass of the tissue is, by definition, the
radiation dose per unit activity. The remaining term, [le"^]/x,
indicates how the activity deposited in the tissue changes with time.
All these factors together yield the dose rate. A more comprehensive
description of the equations used is given in Appendix H.
F.3.1 Internal Doses
Any effort at calculating dose and risk must, of necessity, involve
the use of models. In its simplest form, a model is a mathematical
representation of a physical or biological system. If, for example, the
amount of radioactive material in an organ is measured periodically,
a graph of the activity in the organ, such as that in Figure Fl, is
obtained. In the simplest case, analysis of these data may indicate that
the fraction of the initial activity, R, retained in the organ at any
time, t, is given by an equation of the form
R = e
(Fl)
F3

o;
o
o
•a:
TIME
Figure Fl. Typical pattern of decline of activity of a
radionuclide in an organ, assuming an initial activity
1n the organ and no additional uptake of radionuclide
by the organ (ORNL81)
F4

where x 1s the elimination rate constant. (More generally, It may
require the sum of two or more exponential functions to properly
approximate the decrease of radioactivity in the organ. This may be
interpreted physically as indicating the existence of two or more
"compartments" in the organ from which the radionuclide leaves at
different rates.)
The elimination rate constant, x, is the sum of two terms, which may
be measured experimentally, one proportional to the biological clearance
halflife and the other proportional to the radioactive halflife. The
effective halflife, twg, for these processes is the time required for
onehalf of the material originally present to be removed by biological
clearance and radioactive decay.
If radionuclides are generally found to follow this behavior, then
this equation may be used as a general model for the activity in an organ
following deposition of any initial activity. In general, the models
used by EPA are those recommended by the International Commission on
Radiological Protection (ICRP79) and are documented in detail in the
cited reference. A brief description of each model is given below as an
aid to understanding the material presented in the balance of this
chapter.
As mentioned earlier, all radiations—gamma, beta, and alpha—are
considered in assessing the doses resulting from internal exposure, that
is, exposure resulting from the inhalation or ingestion of contaminated
material. Portions of the material inhaled or ingested may not leave the
body for a considerable period of time (up to decades); therefore, dose
rates are calculated over a corresponding time interval.
The calculation of internal doses requires the use of several
models. The most important are the ICRP lung model, depicted in
Figure F2, and the gastrointestinal (GI) tract model shown in Figure
F3. The lung model is comprised of three regions, the nasopharyngial
(NP), the tracheobronchial (TB), and the pulmonary (P) regions. A
certain portion of the radioactive material inhaled is deposited in each
of the three lung regions (NP, TB, and P) indicated 1n Figure F2. The
material is then cleared (removed) from the lung to the blood and
gastrointestinal tract, as indicated by the arrows, according to the
specified clearance parameters for the clearance class of the inhaled
material.
Deposition and clearance of inhaled materials in the lung are
controlled by the particle size and clearance class of the material.
The particle size distribution of the airborne material is specified by
giving its Activity Median Aerodynamic Diameter (AMAD) in microns (one
micron equals 10"" meters). Where no AMAD is known, a value of 1.0
micron is assumed. Clearance classes are stated in terms of the time
required for the material to leave the lung, that is, Class D (days),
Class W (weeks), and Class Y (years).
F5

Compartment
NP
(D3 = 0
TB
(D4 = 0
P
(D5 = 0
L
.30)
.08)
.25)
a
b
c
d
e
f
9
h
1
Class
D
T
0.01
0.01
0.01
0.2
0.5
n.a.
n.a.
0.5
0.5
F
0.5
0.5
0.95
0.05
0.8
n.a.
n.a.
0.2
1.0
W
T
0.01
0.4
0.01
0.2
50
1.0
50
50
50
F
0.1
0.9
0.5
0.5
0.15
0.4
0.4
0.05
1.0
Y
T
0.01
0.4
0.01
0.2
500
1.0
500
500
1000
F
0.01
0.99
0.01
0.99
0.05
0.4
0.4
0.15
0.9
cr»
B
i
0
u
0
1
1
!»•
a
c
e
D
s
I),
D.
X
h
bs
v*^
'^
v^
K
v>

b
.
r
3
,'
1
. i
/
•
(
b
d
}
I.
T
R
A
r
T
Figure F2. The ICRP Task Group lung model for particulates
The columns labeled D, W, and Y correspond, respectively, to rapid, intermediate, and slow
clearance of the inspired material (in days, weeks, or years). The symbols T and F denote the
biological halftime (d^ys) and coefficient, respectively, of a term in the appropriate retention
function. The values shown for 03, 04, and 05 correspond to activity median aerodynamic
diameter AMAD = 1 Mm and represent the fraction of the inspired material depositing in the lung
regions.

INGESTION
RESPIRATORY
TRACT
xab
ASI
Xs = 24 day'
SI
ab
= 6 day'
ULI
ab
Ul
XULI = 1>85 day
1
LLI
LLI
day'
Figure F3. Schematic representation of radionuclide movement among
respiratory tract, gastrointestinal tract, and blood
S = stomach
SI = small Intestine
ULI = upper large intestine
LLI m lower large Intestine
x = elimination rate constant
F7

The gastrointestinal tract model consists ^of four compartments, the
stomach (S), small Intestine (SI), upper large "Intestine (ULI), and lower
large Intestine (LLI). However, It 1s only from the small Intestine (SI)
that absorption Into the blood Is considered to occur. The fraction of
material that 1s transferred Into blood 1s denoted by the symbol fj.
Radionuclides may be absorbed by the blood from either the lungs or
the GI tract. After absorption by the blood, the radlonuclide is
distributed among botty organs according to fractional uptake coefficients,
denoted by the symbol f£. Since the radioactive material may be
transported through the bocjy, dose rates are calculated for each organ or
tissue affected by using a model of the organ that mathematically
simulates the biological processes Involved. The ^general form of the
model for each organ Is relatively simple. It postulates that the
radioactive material which enters the organ 1s removed by both
radioactive decay and biological removal processes.
F.3.2 External Doses
The example just described for modeling the activity of a
radionuclide in an organ pertains to estimating doses from Internal
exposure. In contrast, the external immersion and surface doses are
calculated as follows. First, the number of photons reaching the body is
determined. The model used here is a set of equations governing the
travel of photons (gamma radiation) 1n air. The simplifying assumptions
used in these calculations are that the medium (air) Is an Infinite
halfspace and is the only material present. This makes the calculation
relatively straightforward. In the second portion of the calculation,
the photons reaching the body are followed through the body using a
"Monte Carlo*1 method. The "phantoms," I.e., the models of the body, are
those used by the Medical Internal Radiation Dose Committee (MIRD69).
The Monte Carlo method is a procedure 1n which the known properties of
the radiation and tissues are employed to trace (simulate) the paths of a
large number of photons In the bocly. The amount of energy released at
each Interaction of the radiation with bocy tissues Is recorded and,
thus, the dose to each organ or tissue 1s estimated by evaluating a large
number of photon paths.
F.3.3 Effects of Decay Products
In calculating doses from Internal and external exposures, the
occurrence of radioactive decay products (or daughters) must be
considered for some radionuclldes. When an atom undergoes radioactive
decay, the new atom created 1n the process may also be radioactive and
may contribute to the radiation dose. Although these decay products may
be treated as Independent radionuclldes 1n external exposures, the decay
products of each parent must be followed through the bodly 1n Internal
exposures. The decay product contributions to the dose rate are included
In the dose calculations, based on the metabolic properties of the
element and the organ In which they occur.
F8

F.3.4 Dose Rate Estimates
For each external and internal exposure, dose rates to each of the
organs listed in Table' Fl are calculated for each radioisotope. These
organ dose rates serve as input to the life table calculations described
in Appendix G.
TABLE Fl:
Organs for which dose rates are calculated
Red bone marrow
Bone
Lung
Breast
Stomach
Pancreas
Intestine
Thyroid
Liver
Urinary tract
(^Esophagus, lymphatic system, pharynx, larynx, salivary gland,
brain.
F.4 EPA Dose Calculation
F.4.1 Dose Rates
The models described in Section F.2 are used by EPA to calculate
radiation dose rates resulting from internal and external exposures to
radioactive materials. A more complete description of the methodology,
equations, and parameters used is given in Du84, ORNL80, and ORNL81. EPA
has adopted two refinements to the ICRPrecommended protocol for these
calculations. The first is to track the movement of internally produced
radioactive daughters by assuming that their movement is governed by
their own metabolic properties rather than those of the parent. Although
not enough information is available to allow a rigorously defensible
choice, this appears to be more accurate for most organs and
radionuclides than the ICRP assumption that daughters behave exactly as
the parent. In the second departure from ICRP recommenda
tions, agedependent values of the parameters governing the uptake of
transuranic radionuclides have been taken from two sources, deemed
appropriate to the .general population, the National Radiological
Protection Board (NRPB82) and the EPA transuranic guidance document
(EPA77).
The internal dose equations given by ICRP may be used to calculate.
either radiation doses (rad), i.e., the total dose over a given time
period, or radiation dose rates (rad/yr), i.e., the way in which the dose
F9

changes with time after intake. The integral of the dose rates 1s, of
course, the total dose. EPA calculates dose rates rather than doses,
because EPA considers age when assessing the effects of radiation on the
population.
External irradiation does not result in any residual internal
material. Therefore, external dose rates to a g'iven organ are constant
as long as the external radionuclide is present. That is, the dose rate
caused by a given amount of radionuclide present in air or on a ground
surface becomes zero when the radionuclide is removed.
The calculation of dose rates, rather than integrated doses, allows
the use of agedependent metabolic parameters more appropriate to the
general population to be taken into account. In the vast majority of
cases, however, there is not now sufficient Information available to make
such calculations. The effect of using agedependent metabolic
parameters 1s discussed in Section F.5.2 for some radionuclides for which
sufficient information 1s available.
F.4.2 Exposure and Usage
The ICRP dosimetrlc equations used by EPA are linear, i.e., an
intake of 10 picocuries will result in dose rates ten times as large as
those from an intake of 1 picocurie. In similar fashion, exposure to 10
times as large an air or ground surface concentration will increase the
external doses by a factor of 10. EPA uses this linearity to avoid
having to calculate radiation dose rates for a range of concentrations.
The standard EPA procedure Is to use unit Intakes of 1 pCi/yr and air and
ground surface concentrations of 1 pCTTcm3 and 1 pd/cmS respectively.
The doses for other intakes and concentrations may then be scaled up or
down as required.
In most cases, it is necessary to make certain assumptions regarding
the exposure conditions in order to perform an assessment. EPA calculates
dose rates for lifetime exposure to the unit Intakes and concentrations.
Appendix G describes the different ways 1n which these rates can be
applied. In addition, the exposure assessment will usually depend on
other usage conditions.assumed for the exposures.
F.5 Uncertainty Analysis
Uncertainty, in the dose, refers to the manner in which the
calculated dose changes when the parameters used in the calculation
(intakes, metabolic factors, organ sizes, etc.) are changed. The
uncertainty associated with the dosimetric calculations Is extremely
difficult to .quantify because the term "uncertainty analysis" implies a
knowledge of parameter distributions that is usually lacking. Internal
doses, for example, depend on the parameters used to characterize the
physiological and metabolic properties of an Individual, while external
doses must consider parameters such as organ size and geometry for a
particular individual. The data available for most of these parameters is
not sufficient to define the form of the parameter distribution.
F10

The major source of uncertainty in calculating the dose to a distinct
individual, however, in most Instances, does not result from errors in
measuring the parameters but from the real variation in parameter values
among individuals in the general population. Thus, a calculated dose is
thought to be representative of a "typical" member of the general
population and is probably reasonably precise for some large segment of
that population.
The basic physiological and metabolic data used by EPA in calcu
lating radiation doses are taken from the ICRP Report of the Task Group
on Reference Han (ICRP75) and from the ICRP Limits for Intakes for '.
RadTonuclTdes by Workers (ICRP79). The "Reference Han" report is the
most comprehensive compilation of data available on the intake,
metabolism, internal distribution, and retention of radioisotopes in the
human body. Its major purpose, however, is to "define Reference Man, in
the first instance, as a typical occupational individual," although
differences with respect to age and sex are indicated in some instances.
The limitations inherent in defining Reference Man, and 1n
estimating uncertainties due to variations in individuals in the general
population, are recognized by the Task Group (ICRP75):
"The Task Group agreed that it was not feasible to
define Reference Man as an "average1 or a 'median1
individual of a specified population group and that it was
not necessary that he be defined in any such precise
statistical sense. The available data certainly do not
represent a random sample of any specified population.
Whether the sample is truly representative of a particular
population group remains largely a matter of judgement which
cannot be supported on the basis of statistical tests of the
data since the sampling procedure is suspect. Thus the Task
Group has not always selected the 'average1, or the
'median', of the available measurements in making its
selection, nor has it attempted to limit the sample to some
national or regional group and then seek an average or
median value. However, the fact that Reference Man is not
closely related to an existing population is not believed to
be of any great importance. If one did have Reference Man
defined precisely as having for each attribute the median
value of a precisely defined age group in precisely limited
locality (e.g., males 1820 years of age in Paris, France,
on June 1, 1964), these median values may be expected to
change somewhat with time, and in a few years may no longer
be the median values for the specified population.
Moreover, the Reference Man so defined would not have this
relation to any other population group unless by
coincidence. To meet the needs for which Reference Man is
defined, this precise statistical relationship to a
particular population is not necessary. Only a very few
individuals of any population will have characteristics
which approximate closely those of Reference Man, however he
Fll

1s defined. The Importance of the Reference Man concept 1s
that his characteristics are defined rather precisely, and
thus If adjustments for individual differences are to be
made, there Is a known basis for the dose estimation
procedure and for the estimation of the adjustment factor
needed for a specified type of individual."
With respect to the dosimetric calculations performed by EPA to
assess the impact of radioactive pollutants on a general population,
three sources of uncertainty should be considered:
(1) that due to the variation In Individual parameters among
adults 1n the general population
(2) that due to the variation in individual parameters with age
(3) that due to experimental error 1n the determination of
specific parameters
Each of these sources of uncertainty Is discussed 1n this section.
As noted above, the data required to perform a rigorous uncertainty
analysis are lacking, and a form of uncertainty analysis called
sensitivity analysis is employed. The sensitivity analysis consists of
substituting known ranges 1n the parameters for the recommended value and
observing the resulting change in the calculated dose rate.
F.5.1 Dose Uncertainty Resulting from Individual Variation
This section discusses the uncertainty 1n calculated radiation
doses occasioned by differences In physical size and metabolism among
Individuals in the general population. In order to investigate the
effects of Individual differences in Intake, size, and metabolism, It Is
necessary to consider the form of the equation used to calculate
radiation dose rates. Equation F2 1s a simplified form of the one used
by EPA to represent the 1ngest1on of radioactive materials.
* c
f f
Tl T2
Tl
m x L1
.xt
(F2)
where D is the dose rate (mrem/yr)
I is the intake rate of radioactivity (pC1/yr)
fj 1s the fraction of I transferred to blood after Ingestion
i
f2 [ 1s the fraction'transferred to an organ from the blood
m is the mass of the organ (g)
x 1s the elimination constant, which denotes how rapidly
the activity 1s removed from the organ (yr1)
E is the energy absorbed by the organ for each radioactive
disintegration (ergs)
c 1s a proportionality constant.
F12

For simplicity, we will assume that dose rates _at large times, t, are to
be studied so that the term in the bracket is approximately unity.
Although the actual equations used are considerably more complicated
because they must describe the lung model and the GI tract, and also
treat all radioactive progeny, the essential features of the uncertainty
in dose calculation are reflected in the terms of Equation (F2). The
sensitivity of the dose to each of the terms in the equation may be
studied by substituting observed ranges of the quantities for the single
value recommended by Reference Man. For some of these quantities, as
noted below, no range 1s cited because of insufficient data.
Intake, I
As an example, postulate that the ingestion mode to be calculated is
for fluid intakes. The average fluid intake is about 1900 ml, with an
adult range of 1000 to 2400 for "normal" conditions. Under higher
environmental temperatures, this range may be increased to 2840 to
3410 ml. Thus, a dose calculated as 1.9, for example, could range from
1.0 to 2.4.
Transfer Fraction, fj
The value of the transfer fraction to blood depends on the chemical
form of the element under stucly. One of the most common naturally
occurring radionuclides is uranium, which is used here as an example.
ICRP79 cites values of fj ranging from 0.005 to 0.05 for industrial
workers, but notes that a higher value of 0.2 is indicated by dietary
data from persons not occupationally exposed. EPA has used the 0.2 value
for the general population but, based on the ICRP range above, a
calculated dose determination could vary by a factor of 10.
Organ Mass, m
The range of organ masses depends primarily on the organ under
investigation. For example, reported values for the bloodless lungs
range from 461 to 676 grams. Liver weights ranged from 1400 to 2300
grams for adult males and 1200 to 1820 grams for females. Thus, because
the organ mass appears in the denominator, calculated lung doses might be
expected to vary by a factor of 1.5 and liver doses by a factor of
about 2.
Remaining Terms,
x, E
There are few reported data on the ranges in values to be expected
for the remaining variables. They are all quantities which are less
directly observable than I, fj, and m and their influence on the dose
calculation can only be estimated. The discussion In Section F.6 Is
intended to augment the uncertainty analysis by introducing the results
of some direct observations on segments of the general population.
F13

F.5.2 Dose Uncertainty Resulting from Age
The dose rates calculated by EPA are normally based on the metabo
lism and physical characteristics of Reference Man (ICRP75). These
properties may obviously be expected to depend on the age of an
Individual. Most particularly, for Infants and children such factors as
breathing rates, liquid and solid intakes, organ size and growth rates,
and boc(y geometry are known to vary considerably from adult values. The
effect of such changes on the radiation dose also depends on the
chemistry of the radioactive element under stu(Jy. For example, rapid
bone growth in children is of more Importance when a "bone seeker" such
as strontium 1s considered. Although the data available for most age and
chemical element combinations are insufficient to allow estimation of the
uncertainty 1n dose, some organ/element combinations, for which more
information Is available, are discussed below.
Iodine and the Thyroid
Iodine 1s rapidly and virtually completely absorbed into the blood
stream following Inhalation or ingestlon. From the blood, Iodine enters
the extracellular fluid and quickly becomes concentrated in the salivary,
gastric, and thyroid glands. It 1s rapidly secreted from the salivary
and gastric glands, but it 1s retained in the thyroid for relatively long
periods.
The Intake and metabolism of Iodine have been reviewed extensively
(ORNL84a) to develop an agedependentmodel for Iodine. In the model
used here, ingested iodine is assumed to be almost completely absorbed by
the blood. The remaining parameters are age dependent and are shown In
Table F2. The fluid intake varies from 0.72 liters per day for a
newborn to about 2.0 liters per day for an adult.
These agedependent parameters may then be used in Equation (F2) to
calculate the dose rate resulting from a constant concentration of iodine
1n water and air. The resulting curves for the dose rate as a function
of age are shown in Figures F4 and F5. These may be compared to the
dose rates obtained using Reference Man parameters at all ages, Indicated
by the dotted lines 1n the same figures. Thus, for this particular
combination of organ and Isotope, the total (70year) dose Is seen to
increase by about 30 percent for Ingestlon and 35 percent for Inhalation
when dependence on age is considered.
Strontium and Bone
Because of the chemical similarities of strontium and calcium,
strontium tends to follow the calcium pathways in the,body and deposits
to a large extent in the skeleton. In fact, the fraction of Ingested
strontium eventually reaching the skeleton at a given age depends largely
on the skeletal needs for calcium at that age, although the bocjy Is able
to discriminate somewhat against strontium In favor of calcium after the
first few weeks of life.
F14

Agedependent model
Adult model
0.0 10.0 20.0 30.0
40.0 50.0 60.0
AGE (YEARS)
70.0 80.0 90.0 100.0
Figure F4. Dose rate from chronic ingesUon of iodine131 in
water at a concentration of 1 pCi/1
F15

Agedependent mddel
Adult model
10.0 20.0 30.0
40.0 50.0 60.0 70.0
AGE (YEARS)
89.0 90.0 100.0
Figure F5. Dose rate from chronic inhalation of ^ocline131 in
air at a concentration of 1 yCi/m3
F16

TABLE F2:
Agedependent parameters for Iodine metabolism In the thyroid
Age Fractional uptake
i
(days) to thyroid, f«
Thyroid mass
(g)
Biological halftime
1n the thyroid
(days)
Newborn
100
365
1825
3650
5475
7300
0.5
0.40
0.3
0.3
0.3
0.3
0.3

1.78
3.45
7.93
12.40
20.00
15
20
30
40
50
65
80
The ICRP model for bone is more complicated than that for the
thyroid because It consists of more than one compartment. For purposes
of modeling the transport of strontium by the skeleton, it suffices to
view the mineralized skeleton as consisting of two main compartments:
trabecular (cancellous, porous, spongy) and cortical (compact) bone.
Two subcompartments, surface and volume, are considered within each of
these main compartments. The four subcompartments of mineralized
skeleton and the movement of strontium among these compartments are shown
schematically in Figure F6. The equations governing the age dependence
of the parameters are given in (ORNL84a). Dose rate curves for the
inhalation and ingestion of constant concentrations of strontium90 are
given in Figures F7 and F8 The comparable curves for Reference Man are
again indicated by dashed lines. Thus, for this element and organ
combination, the dose rate resulting from ingestion is somewhat higher,
while the dose rate resulting from inhalation exhibits only minor
perturbations, when the age dependence of the parameters is considered.
The lifetime (70year) dose resulting from ingestion is about 7 percent
greater and the inhalation dose less than 1 percent different when age
dependence is considered.
Plutonium and Lung and Red Bone Marrow
Apparently plutonium and iron bear sufficient chemical resemblance
that plutonium Is able to penetrate some iron transport and storage
systems. It has been shown that plutonium in blood serum complexes with
transferrin, the irontransport protein. Thus, plutonium will partially
F17

Figure F6. Compartments and pathways in model for
strontium in skeleton
TRABECULAR
SURFACE
TRABECULAR
VOLUME
BLOOD
CORTICAL
SURFACE
CORTICAL
 VOLUME
1
F18

o n
Agedependent model
Adult model
—i 1—
20.0 30.0
40.0 50.0 60.0
AGE (YEARS)
70.0 80.0 90.0 100.0
Figure F7. Dose rate from chronic. Ingestlon of^strontlum90
in water at a concentration of 1 vCi/1
F19

Agedependent model
Agedependent model
10.0 20.0
30.0 40.0 50.0 60.0 70.0
AGE (YEARS)
80.0 90.0 100.0
Figure F8. Dose rate from chronic"Inhalationof strontium90
in air at a concentration of 1 pC1/m3
F20

trace the Iron pathway, with the result that a .substantial fraction of
systemic plutonium is carried to the bone marrow and to the liver. In
the skeleton, plutonium may be released mainly at sites of developing red
cells. Plutonium that has reached the skeleton behaves very differently
from iron; its movement is governed by fairly complicated processes of
bone resorption and addition. Because the total metabolic behavior of
plutonium is not closely related to that of any essential element, any
retention model for plutonium as a function of age will involve much
larger uncertainties than the analogous model for strontium. Still,
there is enough information concerning the metabolism of plutonium by
mammals to justify an examination of potential differences with age in
doses to radiosensitive tissues following intake of this radioelement.
The effect of agedependent parameters on dose rate calculations is
most evident for the lung when the inhalation pathway is considered.
Figure F9 exhibits the variation in dose rate to the total and pulmonary
portions of the lung both for the adult and agedependent cases. The
increased dose rate from age 0 to about 20 is typically caused by
variations in the breathing ratelung mass ratio for infants and
juveniles. For this model, the agedependent pulmonary lung 70year dose
is about 9 percent greater than for the adult model.
To describe retention of plutonium in the skeleton, it is convenient
to view the skeleton as consisting of a cortical compartment and
trabecular compartment. Each of these is further divided into three
subcompartments: bone surface, bone volume, and a transfer compartment.
The transfer compartment, which includes the bone marrow, may receive
plutonium that Is removed from bone surface or volume; plutonium may
reside in this compartment temporarily before being returned either to
the bloodstream or to bone surfaces (Figure F10), Because of the large
amount of recycling of plutonium among the skeletal compartments, blood,
and other organs, recycling is considered explicitly in the model. The
agedependent features of the model are described in detail in (ORNL84a).
Red bone marrow dose rates for the agedependent model are shown in
Figure Fll, for ingestion, and in Figure F12, for inhalation. The
dashed curves are the dose rates using nonagedependent parameters. As
in the corresponding curves for strontium, the difference is more
pronounced for the ingestion pathway. Because of the long physical and
biological halflives of plutonium in the skeleton, the dose rate, for a
chronic intake, does not reach equilibrium within the one hundred year
time period of the figures. The total lifetime (70year) dose to the red
marrow 1s about 25 percent greater for ingestion, and nearly unchanged
for inhalation when the agedependent parameters are used.
In summary, it is difficult to make generalizations concerning
the uncertainty Involved in neglecting age dependence in the dose
calculations. Although the examples given indicate higher dose rates
for the ingestion pathway, with smaller changes for inhalation, when
using agedependent parameters, this results from the complex interaction
between parameters in the dose equation and depends on the element/organ
combination under consideration.
F21

dose
rates
and
rates
rates
Adult dose rates and,intake rate (pulmonary lung)
Adult dose rates and intake rate (total lung)
Q.O 10.0 20.0 30.0 40.0 50.0 60.0 70.0
AGE (YEARS)
80.0 90.0 100.0
Figure F9. Dose rate from chronic Inhalation of plutonium239
in air at a concentration of 1 pCi/m3
F22

Figure F10. Compartments and pathways in model
for plutonium in skeleton
TRABECULAR
SURFACE
TRABECULAR
VOLUME
TRABECULAR
MARROW
BLOOD
CORTICAL
SURFACE
CORTICAL
VOLUME
CORTICAL
MARROW
F23

o
o .,
O O
E UD ,
UJ r
o: •^
o:
<: o
Agedependent model
30.0 40.0 50.0
AGE (YEARS)
60.0
T 1 1 1
70.0 80.0 90.0 100.0
Figure Fll. Dose rate from chronic ingestion of pluton$um239
1n water at a concentration of 1 yd/1
F24

o
o
o
ID
> O
ca:
a o
^ o
E o
UJ IT)
or
3: o
o
CtL O
G: o

F.5.3 Dose Uncertainty Caused by Measurement Errors
The last potential source of uncertainty in the dose calculations 1s
the error Involved In making measurements of fixed quantities. The
radioactive halflife of an Isotope, for example, may be measured
independently of any biological system, but the measurement is subject to
some error. The organ mass of a given organ may also be measured with
only a small error. Repeated determinations of these quantities, in
addition, can reduce the error. Although this source of uncertainty may
be of importance in other aspects of an environmental assessment, it is
of little consequence in the dosimetry, because 1t 1s overwhelmed by the
magnitude of the uncertainties resulting from individual variations.
Although consideration of the factors described above implies large
uncertainties in calculated doses, the actual variation is expected to be
considerably smaller. The reason for this, and some supporting studies
on real populations, are presented in Section F.6.
F.6 Distribution of Doses in the General Population
Although the use of extreme parameter values in a sensitivity
analysis indicates that large uncertainties in calculated doses are
possible, this uncertainty is not usually reflected in the general
population. There are several reasons for this: the parameter values
chosen are intended to be typical of an individual in the population; it
is Improbable that the "worst case" parameters would be chosen for all
terms in the equation; and not all of the terms are mutually Independent,
e.g., an increased intake may be offset by more rapid excretion.
This smaller range of uncertainty in real populations Is demon
strated by studies performed on various human and animal populations. It
should be noted that there is always some variability In observed doses
that results primarily from differences 1n the characteristics of
individuals. The usual way of specifying the dose, or activity,
variability in an organ 1s in terms of the deviation from the average, or
mean, value. In the following studies, it should also be noted that, in
addition to the variability resulting from individual characteristics,
the exposure levels of Individuals may also have varied .appreciably  .
another factor tending to Increase the dose uncertainty.' The following
studies are representative of those carried out on real populations:
(1) An analysis of the thyroid from 133 jackrabblts 1n a nuclear
fallout area (Tu65) found that in only 2 did the iodine131 content
exceed three times the same mean.
(2) Measurements of the strontium90 content of adult whole
skeletons (Ku62) showed that only about 5 percent of the population would
exceed twice the average activity, with only about 0.1 percent exceeding
four times the average.
F26

(3) In another study, the cesium137 consent of 878 skeletal muscle
samples (E164a, E164b) was measured. This radioisotope 1s also the
result of nuclear tests so that the muscle content depends not only on
the variation In individual parameters but also on the pathways leading
to ingestion or inhalation of the isotope. Nevertheless, analyses of
these samples indicated that only 0.2 percent exceeded three times the
mean activity at a 95 percent confidence level.
(4) A stucty of the variability in organ deposition among individuals
exposed under relatively similar conditions to toxic substances has also
been performed (Cu79). In eleven exposure situations (Table F3), the
geometric standard deviation of the apparently lognormal organ doses
ranged from 1.3 to 3.4. This means that 68 percent of the bone doses
resulting from ingestion of strontium90 would lie between 0.56 and
1.8 times the average.
In all but two of the situations examined, there is the complicating
factor that there was probably a great deal of variation in the exposure
levels experienced by members of the population. The magnitude of
geometric standard deviations of the studies listed in Table F3 may be
the evidence of this variation since, except for the two beagle studies,
the exposure was not uniform. Despite these nonuniform exposures,
however, the organ dose is not greatly affected probably because of
differences in metabolic processes. For example, there is probably some
"selfadjustment" in the amount of strontium90 absorbed from the small
intestine to blood of different persons, since strontium90 tends to vary
with calcium in food; if a person has a low calcium intake, then he may
absorb a higher fraction of the calcium and strontium90 than a person
with a high calcium intake.
In the beagle studies, the geometric standard deviation is 1.8 for
inhaled metals in bone or liver, but is only 1.3 for ingested
strontium90 in bone. An important difference is that all dogs ingesting
strontium90 at a given level were administered the same amount, whereas,
in the inhalation studies, the exposure air concentrations were controlled
but the dogs inhaled variable amounts depending upon their individual
characteristic breathing patterns.
Thus, in real situations, the overall uncertainty in dose is seen to
be considerably smaller than would be expected solely on a basis of the
"worst case" sensitivity analyses.
F.7 Summary
This appendix presents an overview of the methods used by EPA to
estimate radiation doses. The appendix defines the basic quantities
reported by EPA and describes briefly the models employed. The appendix
also points out departures from the occupational parameters and
assumptions employed in the basic ICRP methodology and gives the reasons
for the deviations outlined.
F27

TABLE F3;
Distributions of organ doses'8' from Inhalation and 1ngest1on of metals
Population
Beagle
Humans
Humans
Humans
Humans
Beagles
Humans
Humans
(smokers)
Humans
(nonsmokers)
Humans
Humans
Exposure
Metals
Plutonium
(fallout)
Titanium
(soil)
Aluminum
(soil)
Vanadium
(fuel com
bustion)
Strontium90
Strontium90
(fallout)
Cadmium
Cadmi urn
Lead
Lead
Principal
exposure mode
Inhalation
Inhalation
Inhalation
Inhalation
Inhalation
Ingestion
Ingestion
Inhalation and
Ingestion
Inhalation and
Ingestion
Inhalation and
Ingestion
Inhalation
Geometric standard
Target deviation of
organ organ doses*8'
Bone or liver 1.8
Lung 3

Many of the physiological and metabolic parameters recommended 1n
methods for calculating radiation doses are based on a limited number of
observations, often on atypical humans or on other species. EPA has
attempted to bound the uncertainty associated with the ranges observed
for some of the more important parameters used. In fact, some empirical
data on population doses mentioned here indicate that actual dose
uncertainties are much less than is implied by this "worst case" analysis.
For the sources of uncertainty discussed, the large dose range$ possible
because of variation in individual characteristics must be modified by
consideration of the narrower ranges indicated by studies of real
populations; the dose range resulting from age dependence appears to be
small for lifetime exposures, and the range resulting from experimental
error 1s negligible by comparison. Based on these observations, 1t is
reasonable to estimate that EPA's calculated doses should b,e accurate
within a factor of 3 or 4. It should be emphasized that much of the
"uncertainty" in the dose calculation is not caused by parameter error
but reflects real differences in individual characteristics within the
general population. Therefore, the uncertainty in the dose estimates
cannot be dissociated from specification of the segment of the population
to be protected.
More complete derivations and explanations for the EPA methodology
are given in the references cited in the text, and a technical descrip
tion of the dose rate equations and their use 1n conjunction with the
life table risk evaluation is given in Appendix H.
F29

REFERENCES
Cu79 Cuddihy R. G., McClellan R. D., and Griffith W. C., Variability
in Target Organ Deposition among Individuals Exposed to Toxic
Substances, Toxicology and Applied Pharmacology 49, 179187,
1979. ~~
Du84 Dunning D. E. Jr., Leggett R. W., and Sullivan R. E., An
Assessment of Health Risk from Radiation Exposures, 1n Health
Physics 46 (5), 10351051, May 1984.
E164a Ellett W. H. and Brownell G. L., Caesium137 FallOut Body
Burdens, Time Variation and Frequency Distributions, Nature 203
(4940), 5355, July 1964.
E164b Ellett W. H. and Brownell G. L., The Time Analysis and
Frequency Distribution of Caesium137 FallOut in Muscle
Samples, IAEA Proceedings Series, STI/PUB/84, Assessment of
Radioactivity in Man, Vol. II, 155166, 1964.
EPA77 U.S. Environmental Protection Agency, Proposed Guidance on Dose
Limits for Persons Exposed to Transuranium Elements in the
General Environment, EPA 520/477016, 1977.
ICRP75 International Commission on Radiological Protection, Report of
the Task Group on Reference Man, ICRP Publication No. 23,
Pergamon Press, Oxford, 1975.
ICRP77 International Commission on Radiological Protection,
Recommendations of the International Commission on Radiological
Protection, ICRP Publication No. 26, Pergamon Press, Oxford,
1977.
ICRP79 International Commission on Radiological Protection, Limits for
Intakes of Radionuclides by Workers, ICRP Publication No. 30,
Pergamon Press, Oxford, 1979.
Ku62 Kulp J. L. and Schulert A. R., Stront1um90 in Man V, Science
136 (3516), May 1962.
MIRD69 Medical Internal Radiation Dose Committee, Estimates of
Absorbed Fractions for Monoenergenetic Photon Sources Uniformly
Distributed in Various Organs of a Heterogeneous Photon, MIRD
Supplement No. 3, Pamphlet 5, 1969.
NRPB82 National Radiological Protection Board, Gut Uptake Factors for
Plutonium, Amerldum, and Curium, NRPBR129, Her Majesty's
Stationery Office, 1982.
F30

ORNL80 Oak Ridge National Laboratory, A Combined Methodology for
Estimating Dose Rates and Health Effects for Exposure to
Radioactive Pollutants, ORNL/RM7105, Oak Ridge, Tennessee,
1980.
ORNL81 Oak Ridge National Laboratory, Estimates of Health Risk from
Exposure to Radioactive Pollutants, ORNL/RM7745, Oak Ridge,
Tennessee, 1981.
ORNL84a Oak Ridge National Laboratory, Age Dependent Estimation of
Radiation Dose, to be published,.
ORNL84b Oak Ridge National Laboratory, Reliability of the Internal
Dosimetric Models of ICRP30 and Prospects for Improved Models,
to be published.
Tu65 Turner F. B., Uptake of Fallout Radionuclides by Mammals and a
Stochastic Simulation of the Process, in Radioactive Fallout
from Nuclear Weapons Tests, U.S. AEC, Division of Technical
Information, November 1965.
F31


APPENDIX G: ESTIMATING THE RISK OF HEALTH EFFECTS
RESULTING FROM RADIONUCLIDE RELEASES
G.I Introduction
This appendix describes how EPA estimates the probability of fatal
cancer, serious genetic effects, and other detrimental health effects
caused by exposure to ionizing radiation. Such risk estimates are
complex and uncertain, even though much scientific effort has been
expended to increase the understanding of radiation effects.
Because the effects of radiation on human health are known more
quantitatively than for most other environmental pollutants, it is
possible to make numerical estimates of the risk from a particular
source of radioactivity. Such numbers may give an unwarranted aura of
certainty to estimated radiation risks. Compared to the baseline
incidence of cancer and genetic defects, radiogenic cancer and
radiationinduced genetic defects do not occur very frequently. Even
among heavily irradiated populations, the number of cancers and genetic
defects resulting from radiation is not known with either accuracy or
precision simply because of sampling variability. In addition, exposed
populations have not been followed for their full lifetime, so that
information on ultimate effects is limited. Moreover, when considered
in light of Information gained from experiments with animals and from
various theories of carcinogenesis and mutagenesis, the observational
data on the effects of human exposure are subject to a number of
interpretations. This in turn leads to differing estimates of
radiation risks by both individual radiation scientists and expert
groups. Readers should bear 1n mind that estimating radiation risks is
not a mature science and that the evaluation of radiation hazards will
change as additional information becomes available. In this appendix,
a number of simple mathematical models are presented that may describe
the main features of the human response to radiation. However, most
scientists would agree that the underlying reality is quite complicated
and largely unknown, so that such models should not be taken too
literally but rather as useful approximations that will someday be
obsolete.
EPA's estimates of cancer and genetic risks in this report are
based on the 1980 National Academy of Sciences BEIR3 report (NAS80).
This report was prepared for the purpose of assessing radiation risks
at the low exposure levels of interest in standard setting. As phrased
by the President of the Academy, "We believe that the report will be
helpful to the EPA and other agencies as they reassess radiation
protection standards. It provides the scientific bases upon which
standards may be decided after non scientific social values have been
taken into account."
In the sections below, we outline the various assumptions made in
calculating radiation risks based on the 1980 MAS report and compare
these risk estimates with those prepared by other scientific groups,
Gl

such as the 1972 NAS BEIR Committee (NAS72). the United Nations
Scientific Committee on the Effects of Atomic Radiation (UNSCEAR), and
the International Commission on Radiation Protection (ICRP). We
recognize that information on radiation risks is incomplete and do not
argue that the estimates made by the 1980 NAS BEIR Committee are highly
accurate. Rather, we discuss some of the deficiencies 1n the available
data base and point out possible sources of bias in current risk
estimates. Nevertheless, we believe the risk estimates made by EPA are
"stateoftheart."
In the sections below, we first consider the cancer risk resulting
from wholebody exposure to lowLET* radiation, i.e., lightly ionizing
radiation like the energetic electrons produced by Xrays or gamma
rays. Environmental contamination by radioactive materials also leads
to the ingestion or inhalation of the material and subsequent
concentration of the radioactivity 1n selected bocty organs. Therefore,
the cancer risk resulting from lowLET Irradiation of specific organs
is examined next. Organ doses can also result from highLET radiation,
such as that associated with alpha particles. The estimation of cancer
risks for situations where highLET radiation is distributed more or
less uniformly within a body organ Is the third situation considered,
Section G.3. In Section G.4, we review the causes of uncertainty in
the cancer risk estimates and the magnitude of this uncertainty so that
the public as well as EPA decision makers have a proper understanding
of the degree of confidence to place in them. In Section G.5, we
review and quantify the hazard of deleterious genetic effects from
radiation and the effects of exposure 1n utero on the developing
fetus. Finally, 1n Section G.6, we calculate cancer and genetic risks
from background radiation using the models described in this appendix.
G.2 Cancer Risk Estimates for LowLET Radiations
Most of the observations of radiationinduced carcinogenesls in
humans are on groups exposed to lowLET radiations. These groups
Include the Japanese Abomb survivors and medical patients treated with
Xrays for ankylosing sponcjylitis 1n England from 1935 to 1954 (Sm78).
The UNSCEAR (UNSCEAR77) and NAS Committee on the Biological Effects of
Ionizing Radiations (BEIR) (NAS80) have provided knowledgeable reviews
of these and other data on the carcinogenic effects of human exposures.
The most Important epidemiological data base on radiogenic cancer
1s the Abomb survivors. The Japanese Abomb survivors have been
studied for more than 38 years and most of them, the Life Span Stucty
Sample, have been followed in a carefully planned and monitored
epidemiological survey since 1950 (Ka82, Wa83). They were exposed to a
wide range of doses and are the largest group that has been studied.
*Linear Energy Transfer (LET) — the energy deposited per unit of
distance along the path of a charged particle.
G2

Therefore, they are virtually the only group providing information on
the response pattern at various levels of expos'ure to lowLET
radiation. Unfortunately, the doses received by various individuals In
the Life Span Study Sample are not yet known accurately. The 1980 BEIR
Committee's analysis of the Abomb survivor data was prepared before
bias in the dose estimates for the Abomb survivors (the tentative 1965
dose estimates, T65) became widely recognized (Lo81). It is now clear
that the T65 doses tended to be overestimated (Bo82, RERF83.84) so that
the BEIR Committee's estimates of the risk per unit dose are likely to
be too low. A detailed reevaluation of current risk estimates is
indicated when the Abomb survivor data have been reanalyzed on the
basis of new and better estimates of the dose to individual survivors.
Uncertainties in radiation risk estimates do not result just from
the uncertainties in the Japanese data base and in other epidemio
logical studies. Analyses of these data bases require a number of
assumptions that have a considerable effect on the estimated risk.
These assumptions are discussed below. The degree of uncertainty
introduced by choosing among these assumptions is probably greater than
the uncertainty of the estimated risk per unit dose among the Abomb
survivors or other sources of risk estimates for radiogenic cancer in
humans.
G.2.1 Assumptions Needed to Make Risk Estimates
A number of assumptions must be made about how observations at
high doses should be applied at low doses and low dose rates for
radiation of a given type (LET). These assumptions include the shape
of the dose response function and possible dose rate effects. A dose
response function expresses the relationship between dose and the
probability that a radiogenic cancer is induced. Observed excess
cancers have occurred, for the most part, following relatively high
doses of ionizing radiation compared to those likely to occur as a
result of the combination of background radiation and environmental
contamination from controllable sources of radiation. Therefore, a
dose response model provides a method of interpolating between the
number of radiogenic cancers observed at high doses and the number of
cancers resulting from all causes including background radiation.
The range of interpolation is not the same for all kinds of cancer
because it depends upon the radiosensitivity of a given tissue. For
example, the most probable radiogenic cancer for women is breast
cancer. As described below, with appropriate references, breast cancer
appears not to be reduced when the dose is delivered over a long period
of time. For example, the number of excess cancers per unit dose among
Japanese women, who received acute doses, is about the same per unit
dose as women exposed to small periodic doses of Xrays over many
years. If this is actually the case, background radiation is as
carcinogenic for breast tissue as the acute exposures from Abomb gamma
radiation. Moreover, the female Abomb survivors show an excess of
breast cancer at doses below 20 rad which is linearly proportional to
G3

that observed at several hundred rad (To84). Women In their 40's, the
youngest age group 1n which breast cancer 1s common, have received
about 4 rad of wholebody lowLET background radiation and usually some
additional dose Incurred for' diagnostic medical purposes. Therefore,
for this cancer, the difference between observed radiogenic cancer,
less than 20 rad, and the dose resulting from background radiation 1s
less than a factor of 5, not several orders of magnitude as 1s
sometimes claimed. However, it should be noted that breast tissue is a
comparatively sensitive tissue for cancer Induction and that for most
cancers, a statistically significant excess has not been observed at
doses below 100 rad, lowLET. Therefore, the range of. dose
Interpolation between observed and calculated risk 1s often large.
G.2.2 Dose Response Functions
The 1980 NAS report (NAS80) examined three dose response functions
in detail: (1) linear, in which effects are directly proportional to
dose at all doses; (2) linear quadratic, in which effects are very
nearly proportional to dose at very low doses and proportional to the
square of the dose at high doses; and (3) a quadratic dose response
function, where the risk varies as the square of the dose at all dose
levels.
We believe the first two of these functions are compatible with
most of the data on human cancer. Information which became available
only after the BEIR3 report was published indicates that a quadratic
response function is Inconsistent with the observed excess risk of
solid cancers at Nagasaki, where the estimated gammaray doses are not
seriously confounded by an assumed neutron dose component. The chance
that a quadratic response function underlies the excess cancer observed
In the Nagasaki incidence data has been reported as only 1 in 10,000
(Wa83). Although a quadratic response function 1s not incompatible
with the Life Span Stu<(y Sample data on leukemia incidence at Nagasaki,
Beebe and others (Be78, E177) have pointed out how unrepresentative
these data are of the total observed dose response for leukemia in that
city. There is no evidence that a quadratic response function provides
a better fit to the observed leukemia excess among all Abomb survivors
in the Life Span Study Sample than a simple linear model (NAS80).
Based on these considerations, we do not believe a quadratic response
can be used in a serious effort to estimate cancer risks due to
Ionizing radiation. EPA notes that neither the NCRP, the ICRP, nor
other authoritative scientific groups, e.g., NRPB and UNSCEAR, have
used a quadratic response function to estimate the risks due to
ionizing radiation.
The 1980 NAS BEIR Committee considered only the Japanese mortality
data in their analysis of possible dose response functions (NAS80).
Based on the T65 dose estimates, this Committee showed that the excess
Incidence of solid cancer and leukemia among the Abomb survivors Is
compatible with either a linear or linear quadratic dose response to
G4

the lowLET radiation component and a linear response to the highLET
neutron component (NAS80K Although the 1980 8EIR report indicated
lowLET risk estimates based on a linear quadratic response were
"preferred" by most of the scientists who prepared that report, opinion
was not unanimous, and we believe the subsequent reassessment of the
Abomb dose seriously weakens the Committee's conclusion. The
Committee's analysis of dose response functions was based on the
assumption that most of the observed excess leukemia and solid cancers
among Abomb survivors resulted from neutrons (NAS80). Current
evidence, however, is conclusive that neutrons were only a minor
component of the dose in both Hiroshima and Nagasaki (Bo82, RERF83.84).
Therefore, it is likely that the linear response attributed to neutrons
was caused by the gamma dose, not the dose from neutrons. This point
is discussed further in Section G.3.
Reanalysis of the Japanese experience after completion of the dose
reassessment may provide more definitive information on the dose
response of the Abomb survivors, but it is unlikely to provide a
consensus on the dose response at environmental levels, I.e., about 100
mrad per year. This is because at low enough doses there will always
be sampling variations in the observed risks so that observations are
compatible, in a statistical sense, with a variety of dose response
functions. In the absence of empirical evidence or a strong
theoretical basis, a choice between dose response functions must be
based on other considerations.
Although there is evidence for a nonlinear response to lowLET
radiations in some, but not all, studies of animal radiocarcinogenesis
(see below), we are not aware of any data on human cancers that are
incompatible with a simple linear model. In such a case, 1t may be
preferable to adopt the simplest hypothesis that adequately models the
observed radiation effect. Occams's razor is still a viable scientific
rule for separating necessary from ad hoc assumptions. Moreover, EPA
believes that risk estimates, for tfie" purpose of assessing radiation
impacts on public health, should be based on scientifically creditable
risk models that are unlikely to understate the risk. The linear model
fulfills this criteria. Given the current bias in the doses assigned
to Abomb survivors (see Section 7.5.1 below), such an approach seems
reasonable, as well as prudent. Therefore, in this appendix, EPA has
used the BEIR3 linear dose response model as one of two dose response
models for discussing the risk of radiogenic cancer due to lowLET
radiations.
For lowLET radiations, we have also Included in the appendix,
discussions of risk that are based on the BEIR3 linear quadratic dose
response model. While In the dose range of interest (environmental
levels) the dose squared term in this model Is Insignificant, the
linear term is about 2.5 times smaller than that In the BEIR3 linear
response model, NAS80. That Is, for the same dose, risk estimates
based on the BEIR3 linear quadratic dose response model are only 40
percent of those based on the BEIR3 linear model.
G5

Many of the risk estimates needed to evaluate the effect of
radlonucllde emission must be made on an organ "specific basis. The
BEIR3 report provides risk coefficients for Individual solid cancers
only for the linear model, Tables V14 and V15 1'n NAS80. We have
therefore divided BEIR3 organ risk estimates for a linear response by
a factor of 2.5 to obtain organ specific linear quadratic risk
coefficients.
The underlying basis for a linear quadratic response is thought to
be that repair of radiation damage mitigates the effect of small doses
of radiation or those which occur over a long time period, the reduced
linear term being Indicative of this repair. Use of a linear quadratic
dose response function, as formulated by the BEIR3 Committee, 1s
equivalent to the use of a dose rate effectiveness factor (DREF) of 2.5
(see below).
The discussions of both the linear and the linearquadratic dose
response models for lowLET radiations are Included in this appendix to
compare the risk estimates obtained for given doses using both models.
The more conservative of these two models is the linear model. We have
used this model for the calculation of the fatal cancers per curie
release to the accessible environment which are listed 1n Chapter 6.
This policy was thoroughly reviewed and accepted by the Highlevel
Radioactive Waste Disposal Subcommittee of the EPA Science Advisory
Board (EPA84).
G.2.3 The Possible Effects of Dose Rate on Radiocarcinogenesis
The BEIR3 Committee limited its risk estimates to a minimum dose
rate of 1 rem per year and stated that it "does not know 1f dose rates
of gamma rays and Xrays of about 100 mrad/y are detrimental to man."
At dose rates comparable to the annual dose that everyone receives for
naturallyoccurring radioactive materials, a considerable bocy of
scientific opinion holds that the effects of radiation are reduced.
NCRP Committee 40 has suggested that carcinogenic effects of lowLET
radiations may be a factor of from 2 to 10 times less for small doses
and dose rates than have been observed at high doses (NCRP80).
The low dose and low dose rate effectiveness factors developed by
NCRP Committee 40 are based on their analysis of a large bocjy of plant
and animal data that showed reduced effects at low doses for a number
of biological endpoints, Including radiogenic cancer In animals,
chiefly rodents. However, no data for cancer in humans confirm these
findings as yet. A few human studies contradict them. Highly
fractionated small doses to human breast tissue are apparently as
carcinogenic as large acute doses (NAS80, La80). Furthermore, small
acute (less than 10 rad) doses to the thyroid are as effective per rad
as much larger doses 1n Initiating thyroid cancer (UNSCEAR77, NAS80).
Moreover, the Increased breast cancer resulting from chronic low dose
occupational gamma ray exposures among British dial painters is
comparable to, or larger, than that expected on the basis of acute high
dose exposures (Ba81).
G6

While none of these examples is persuasive by itself, collectively
they indicate that it may not be prudent to assume that all kinds of
cancer are reduced at low dose rates and/or Tow doses. However, it may
be overly conservative to estimate the risk of all cancers on the basis
of the linearity observed for breast and thyroid cancer. The
International Commission on Radiation Protection and the United Nations
Scientific Committee on Atomic Radiations have used a dose rate
effectiveness factor of about 2.5 to estimate the risks from
occupational (ICRP263 and environmental exposures (UNSCEAR77). Their
choice of a DREF is fully consistent with and equivalent to the
reduction of risk at low doses obtained by substituting the BEIR3
linearquadratic response model for their linear model. Use of both a
DREF and a linear quadratic model for risk estimation is inappropriate
(NCRP80).
The difference between risk estimates obtained with the BEIR3
linear and linearquadratic dose response models is by no means the
full measure of the uncertainty in the estimates of the cancer risk
resulting from ionizing radiation (Section G.4 below summarizes
information on uncertainty). Using two models serves as a reminder
that there is more than one creditable dose response model for
estimating radiation risks and that it is not known if all radiogenic
cancers have the same dose response.
G.2.4 Risk Projection Models
None of the exposed groups have been observed long enough to
assess the full effects of their exposures, if, as currently thought,
most radiogenic cancers occur throughout an exposed person's lifetime
(NAS80). Therefore, another major decision that must be made 1n
assessing the lifetime cancer risk due to radiation is to select a risk
projection model to estimate the risk for a longer period of time than
currently available observation data will allow.
To estimate the risk of radiation exposure that is beyond the
years of observation, either a relative risk or an absolute risk
projection model (or suitable variations) may be used. These models
are described at length in Chapter 4 of the 1980 WAS report (NAS80). A
relative risk projection model projects the currently observed
percentage increase in cancer risk per unit dose into future years. An
absolute risk model projects the average observed number of excess
cancers per unit dose Into future years at risk.
Because the underlying risk of cancer increases rapidly with age,
the relative risk model predicts a larger probability of excess cancer
toward the end of a person's lifetime. In contrast, the absolute risk
model predicts a constant Incidence of excess cancer across time.
Therefore, given the incomplete data we have now, less than lifetime
followup, a relative risk model projects somewhat greater risk than
that projected using an absolute risk model.
G7

The National Acaderny of Sciences BEIR Committee and other
scientific groups, e.g., UNSCEAR, have not concluded which projection
model is the appropriate choice for most radiogenic cancers. However,.
evidence is accumulating which favors the relative risk projection
model for most solid cancers. As pointed out by the 1980 MAS BEIR
Committee,
"If the relativerisk model applies, then the age of the
exposed groups, both at the time of exposure and as they
move through life, becomes very important. There is now
considerable evidence in nearly all the adult human
populations studied that persons irradiated at higher
ages have, in general, a greater excess risk of cancer
than those irradiated at lower ages, or at least they
develop cancer sooner. Furthermore, if they are
Irradiated at a particular age, the excess risk tends to
rise pan' passu (at equal pace) with the risk of the
population at large. In other words, the relativerisk
model with respect to cancer susceptibility at least as
a function of age, evidently applies to some kinds of
cancer that have been observed to result from radiation
exposure." (NAS80, p.33)
This observation is confirmed by the Ninth Abomb Survivor Life
Span Study, published two years after the 1980 Academy report. This
latest report indicates that, for solid cancers, relative risks have
continued to remain constant in recent years while absolute risks have
increased substantially (Ka82). Smith and Doll (Sm78) have reached
similar conclusions on the trend in excess cancer with time among the
irradiated spondylitic patients.
Although we believe considerable weight should be given to the
relative risk model for most solid cancers (see below), the model does
not necessarily give an accurate projection of lifetime risk. The mix
of tumor types varies with age so that the relative frequency of some
common radiogenic tumors, such as thyroid cancer, decreases for older
ages. Land has pointed out that this may result 1n overestimates of
the lifetime risk when they are based on a projection' model using
summed sites, relative risks (La83). While this may turn out to be
true for estimates of cancer Incidence that Include cancers less likely
to be fatal, e.g., thyroid, 1t may not be too Important in estimating
the lifetime risk of fatal cancers since the incidence of most of the
common fatal cancers, e.g., breast and lung cancers, increases with age.
Leukemia and bone cancer are exceptions to the general validity of
a lifetime expression period for radiogenic cancers. Most, if not all,
of the leukemia risk has apparently alreac(y been expressed in both the
Abomb survivors and the sponctylitlcs (Ka82, Sm78). Similarly, bone
sarcoma from acute exposure appears to have a limited expression period
(NAS80, Ma83). For these diseases, the BEIR3 Committee believed that
an absolute risk projection model with a limited expression period is
appropriate for estimating lifetime risk (NAS80).
G8

Note that, unlike the MAS BEIR1 report (NAS72), the BEIR3
Committee's relative and absolute risk models are age dependent. That
is, the risk coefficient changes, depending on the age of the exposed
persons. Observation data on how cancer risk resulting from radiation
changes with age is sparse, particularly so in the case of childhood
exposures. Nevertheless, the explicit consideration of the variation
in radiosensitivity with age at exposure is a significant improvement
in methodology. It is important to differentiate between age
sensitivity at exposure and the age dependence of cancer expression.
In general, people are most sensitive to radiation when they are
young. In contrast most radiogenic cancers occur late in life, much
like cancers resulting from other causes. In this appendix we present
risk estimates for a lifetime exposure of equal annual doses. The
cancer risk estimated is lifetime risk from this exposure pattern.
However, agedependent analyses using BEIR3 r;sk coefficients indicate
that the risk from one year of exposure varies by a factor of at least
5, depending on the age of the recipient.
G.2.5 Effect of Various Assumptions on the Numerical Risk Estimates
Differences between risk estimates made by using various
combinations of the assumptions described above were examined in the
1980 WAS report. Table Gl below, taken from Table V25 (NAS80), shows
the range of cancer fatalities that are induced by a single 10rad dose
as estimated using linear, linear quadratic, and quadratic dose
response functions and two risk projection models, relative and
absolute (NAS80).
As illustrated in Table Gl, estimating the cancer risk for a
given risk projection model on the basis of a quadratic as compared to
a linear dose response reduces the estimated risk of fatal cancer by a
factor of nearly 20. Between the more credible linear and linear
quadratic response functions, the difference is less, a factor of about
2.5. For a given dose response model, results obtained with the two
projection models, for solid cancers, differ by about a factor of 3.
Even though the 1980 NAS analysis estimated lower risks for a
linear quadratic response, it should not be concluded that this
response function always provides smaller risk estimates. In contrast
to the 1980 NAS analysis where the proportion of risk due to the dose
squared term (e.g., Cj in equation c of Table Gl) was constrained to
positive values, the linear quadratic function (which agrees best with
Nagasaki cancer incidence data) has a negative coefficient for the
dosesquared term (Wa83). Although this negative coefficient is small
and indeed may not be significant, the computational result is a larger
linear term which leads to higher risk estimates at low doses than
would be estimated using a simple linear model (Wa83). Preliminarily,
the BEIR3 analyses of the mortality, which were not restricted to
positive coefficients of the dose squared terms, yielded similar
results.
G9

Differences in the estimated cancer risk introduced by the choice
of the risk projection model are also appreciable. As pointed out
above, the 1980 NAS analysis indicates that relative risk estimates
exceed absolute risk estimates by about a factor of 3, Table Gl.
However, relative risk estimates are quite sensitive to how the risk
resulting from exposure during childhood persists throughout life.
This question is addressed in the next section, where we compare risk
estimates made by the 1972 and 1980 NAS BEIR Committees with those of
the ICRP and UNSCEAR.
TABLE Gl:
Range of cancer fatalities induced by 10rad lowLET radiation
(Average value per rad per million persons exposed)
Dose response
functions
Lifetime risk projection model
Relative*3* Absolute
Linear(b)
(c)
Linear Quadratic
id]
Quadratic10'
501
226
28
167
77
10
(a)Relative risk projection for all solid cancers except
leukemia and bone cancer fatalities, which are projected by means of
the absolute risk model (NAS80).
^'Response R varies as a constant times the dose, I.e., R=
CiD
Source: NAS80, Table V25.
G2.6 Comparison of Cancer Risk Estimates for LowLET Radiation
A number of estimates of the risk of fatal cancer following
lifetime exposure are compared in Table G2. Although all of these
risk estimates assume a linear response function, they differ
considerably because of other assumptions. In contrast with absolute
risk estimates, which have increased since the first NAS report
(BEIR1) was prepared in 1972(NAS72), the 1980 NAS BEIR3 Committee's
estimates of the relative risk, as shown in Table G2, have decreased
relative to those in the BEIR1 report. This illustrates the
G10

sensitivity of risk projections to changes in modeling assumptions.
For the NAS80 report, the relative risk observed for ages 10 to 19 was
substituted for the considerably higher relative risk observed for
those exposed during childhood, ages 0 to 9. In addition, the relative
risk coefficients used in the BEIR3 analysis are based on excess
cancer in the Japanese Abomb survivors compared to U.S. population
cancer mortality rates. In the 1972 MAS report this excess was
compared to cancer mortality in Japan. Moreover, the difference
introduced by these two changes, particularly the former, is somewhat
greater than indicated in the 1980 MAS report. 'The relative risk
estimate attributed to the BEIR1 Committee in the NAS 1980 report is
incorrect. Therefore, two BEIR1 relative risk estimates are listed in
Table G2: the risk estimate^ in NAS80 attributed to the BEIR1
Committee and an estimate which is based on the risk coefficients in
NAS72. The NAS 1980 estimate did not use the relative risk coefficient
for childhood exposure given in the BEIR1 report, which for solid
cancers is a factor of 10 larger than adult values (p. 171 in NAS72),
but rather used the adult risk for all ages including children. The
estimate in Table G2 labeled NAS72 uses the relative risk coefficients
actually given in the BEIR1 report.
By comparing the three relative risk estimates in Table G2, it is
apparent that the relative risk estimates are fairly sensitive to the
assumptions made as to what extent the observed high relative risk of
cancer from childhood exposure continues throughout adult life. The
Life Span Study (Ka82) indicates that the highrisk adult cancer caused
by childhood exposures is continuing, although, perhaps, not to the
extent predicted by the NAS BEIR1 Committee in 1972.
The major reason the risk estimates in Table G2 differ is
because of the underlying assumption in each set of risk estimates.
The NAS BEIR estimates are for lifetime exposure and lifetime
expression of induced cancers (NAS72, 80). Neither the age
distribution of the population at risk nor the projection models (if
any) have been specified by either the UNSCEAR (UNSCEAR77) or the ICRP
(ICRP77). UNSCEAR apparently presumes the same age distributions as
occurred in the epidemiological studies they cited, mainly the Abomb
survivors, and a 40year period of cancer expression. The ICRP risk
estimates are for adult workers, presumably exposed between ages 18
and 65, and a similar expression period. These are essentially
ageindependent absolute risk models with less than lifetime expression
of induced cancer mortality. For these reasons alone, risks estimated
by ICRP and UNSCEAR are expected to be smaller than those made on the
basis of the BEIR3 report.
The last entry in Table G2 (Ch83) is of interest because it
specifically excludes the Abomb survivor data based on T65 dose
estimates. The authors reanalyzed the information on radiogenic cancer
in UNSCEAR77 so as to exclude all data based on the Japanese
experience. Their estimate of fatalities ranges from 100 to 440 per
Gll

TABLE G2:
A comparison of estimates of the risk of fatal cancer from a lifetime
exposure at 1 rad/year (lowLET radiation)
Source of
estimate
BEIR1 (NAS72)(a)
BEIR1 (NAS80) b , ,
BEIR3 (NASSOjtbMc)
BEIR3 (NAS80)td)
BEIR3 (NAS80)(b)
BEIR1 (NAS80)(b)
BEIR3 (NAS80)(d)
UNSCEAR (UNSCEAR77)(e)
UNSCEAR (UNSCEAR77)(e)
ICRP (ICRP77)
CLM (Ch83)
Cases per 106
person rad
667
568
403
169
158
115
67
200300
75175
125
100440
Projection model
Relative Risk
Relative Risk
Relative Risk
Relative Risk
Absolute Risk
Absolute Risk
Absolute Risk
Nonehigh dose > 100 rad
Nonelow dose/dose rate
Noneoccupational 
Tow dose/dose rate
UNSCEAR77 without Abomb
data
l relative risk model.
V4 1n NAS80, linear dose response.
lc'LL absolute risk model for bone cancer and leukemia; UT relative
risk model for all other cancer.
V4 in NAS80 linearquadratic dose response.
Paragraphs 317 and 318 in UNSCEAR77.
106 person rad for high doses and dose rates. As indicated 1n Table
G2, this is somewhat greater but comparable to the UNSCEAR estimate,
which includes the Abomb survivor data. The mean number of fatalities
given 1n Ch83 is 270 per 10° personrem, which is nearly identical to
the value EPA has used for a linear dose response model —280 fatalities
per 10° person rad (see below).
G.2.7 EPA Assumptions About Cancer Risks Resulting from LowLET
Radiation?
EPA's discussion of radiation risks in this appendix are based on
presumed linear and linear quadratic dose response functions. We believe
these are the most credible dose response functions for estimating risks
to exposed populations. Using the BEIR3 linear quadratic model Is
equivalent, at low dose, to using a dose rate effectiveness factor of
G12

2.5. As discussed in section G.2.2, we have used a linear dose
response function for lowLET radiation in competing the fatal cancers
per curie released to the accessible environment which are listed in
Tables 61 through 64.
Except for leukemia and bone cancer, where we use a 25year
expression period for radiogenic cancer, we use a lifetime expression
period, as was done in the NAS report (NAS80). Because the most recent
Life Span Stuc(y Report (Ka82) indicates absolute risks for solid
cancers are continuing to increase 33 years after exposure, the 1980
NAS Committee choice of a lifetime expression period appears to be well
founded'. We do not believe limiting cancer expression to 40 years {as
has been done by the ICRP and UNSCEAR) is compatible with the
continuing increase in solid cancers that has occurred among irradiated
populations (Ka82). Analyses of the spondylitic data have led others
to similar conclusions (Sm78).
To project the number of fatalities resulting from leukemia and
bone cancer, EPA uses an absolute risk model, a minimum induction
period of 2 years, and a 25year expression period. To estimate the
number of fatalities resulting from other cancers, EPA uses the
arithmetic average of absolute and relative risk projection models.
For these cancers, we assume a 10year minimum induction period and
expression of radiationinduced cancer for the balance of an exposed
person's lifetime after the minimum induction period.
G.2.8 Methodology for Assessing the Risk of Radiogenic Cancer
EPA uses a life table analysis to estimate the number of fatal
radiogenic cancers in an exposed population of 100,000 persons. This
analysis considers not only death due to radiogenic cancer, but also
the probabilities of other competing causes of death which are, of
course, much larger and vary considerably with age (Bu81, Co78).
Basically, it calculates for ages 0 to 110 the risk of death due to all
causes by applying the 1970 mortality data from the National Center for
Health Statistics (NCHS75) to a cohort of 100,000 persons. Additional
information on the details of the life table analysis is provided in
Appendix H. It should be noted that a life table analysis is required
to use the agedependent risk coefficients in the BEIR3 report. For
relative risk estimates, we use agespecific cancer mortality data also
provided by NCHS (NCHS73). The EPA computer program we use for the
life table analysis was furnished to the NAS BEIR3 Committee by EPA
and used by the Committee to prepare its risk estimates. Therefore, we
believe that the population base and calculational approach are similar
in both the NAS and EPA analyses.
To project the observed risks of most solid radiogenic cancers
beyond the period of current observation, we use both absolute and
relative risk models, but usually present an arithmetic average based
on these projections. Using a single estimate, instead of a range of
values, does not mean that our estimate is precise. As indicated in
G13
/

Table G2, the range of estimated fatal cancers resulting from the
choice of a particular projection model and Its" internal assumptions 1s
about a factor of 3. Although we think it is likely that the relative
risk model 1s the best projection model for most solid cancers, 1t has
been tested rigorously only for lung and breast cancer (La78). Until
it has more empirical support, we prefer to use an average risk based
on both projection models. A second reason for this choice is to avoid
overly conservative risk estimates caused by the compounding of
multiplicative conservative assumptions.
To estimate the cancer risk from lowLET, wholebo

G.2.9 Organ Risks
For most sources of environmental contamination, Inhalation and
1ngest1on of radioactivity are more common than direct exposure. In
many cases, depending on the chemical and physical characteristics of
the radioactive material, inhalation and Ingestion result in a
nonuniform distribution 'of radioactive materials within the body so
that some organ systems receive much higher doses than others. For
example, iodine isotopes concentrate in the thyroid gland, and the dose
to this organ can be orders of magnitude larger than the average dose
to the bocly.
Fatal Cancer at Specific Sites
To determine the probability that fatal cancer occurs at a
particular site, we have performed life table analyses for each cancer
type using the Information on cancer incidence and mortality in NAS80.
For cancer other than leukemia and bone cancer, we used NAS80 Table V14
(Age Weighted Cancer Incidence by Site Excluding Leukemia and Bone
Cancer) and NAS80 Table V15, which lists the BEIR Committee's
estimates of the ratio of cancer fatality to cancer incidence for these
various organs. The proportions of leukemia and fatal bone cancer
caused by lowLET radiation were estimated using the results given in
Tables V17 and V20 of NAS80. Normalized results, which give the
proportion of fatal cancer caused by radiogenic cancer at a particular
site, are listed in Table G3. As noted above, these proportions are
assumed to be the same for the BEIR3 linear quadratic dose response
model.
Information on the proportion of fatal cancers resulting from
cancer at a particular organ is not precise. One reason is that the
data In NAS80 (and Table 63} are based on wholeboc(y exposures, and it
is possible that the incidence of radiogenic cancer varies depending on
the number of exposed organs. Except for breast and thyroid cancer,
very little information is available on radiogenic cancer resulting
from exposure of only one region in the body. Another reason is that
most epidemiology studies use mortality data from death certificates,
which often provide questionable information on the site of the primary
cancer. Moreover, when the existing data are subdivided Into specific
cancer sites, the number of cases becomes small, and sampling
variability 1s increased. The net result of these factors is that
numerical estimates of the total cancer risk are more reliable than
those for most single sites.
The 1977 UNSCEAR Committee's estimated risks (UNSCEAR77) to
different organs are shown in Table G4. For all of the organs, except
the breast, a high and low estimate was made. This range varies by a
factor of 2 or more for most organs, Table G4. Other sitespecific
estimates show a similar degree of uncertainty (Ka82), and it is
clear that any system for allocating the risk of fatal cancer on an
G15

TABLE G3:
Proportion of the total risk of fatal radiogenic cancer resulting from
cancer at a particular site
Site
Proportion of
total ri
Lung lh\
Breasttb)
Red bone marrow^0'
Thyroid
Bone
Liver
Stomach
Intestines
Pancreas
Kidneys and urinary tract
Other^J
0.21
0.13
0.16
0.099
0.009
0,085
0.084
0.039
0.058
0.025
0.11
ia'NAS80L1fetime exposure and cancer expression; results are
rounded to two figures.
^'Average for both sexes.
lc'Leukem1a.
risk for all other organs, Including the esophagus,
lymphatic system, pharynx, larynx, salivary gland, and brain.
organspecific basis is Inexact. Table G5 compares proportional risks
by the MAS BEIR3 Committee, UNSCEAR, and the ICRP. ICRP Report 26
provides organspecific weights for assessing combined genetic and
cancer risks from occupational exposure (ICRP77K In Table G5, we
have renormalized ICRP risks so that they pertain to cancer alone.
Considering that the cancer risk for a particular site is usually
uncertain by a factor of 2 or more, as indicated by the range of
UNSCEAR estimates in Table G4, we would not expect perfect agreement
in apportionment of total body risks. Table G5, however, does
indicate reasonable agreement among the three sets of estimates
considered here.
G16

TABLE G4:
UNSCEAR estimates of cancer risks at specified sites
Site
Fatalities Average
(per 106 person rad) (per 106 organ rad)
Proportion
of total risk
Lung
Breast*3'
Red bone marrow'0'
Thyroid
Bone
liver
Stomach
Intestines
Pancreas
Kidneys and urinary
tract
Otheric)
2550
25
1525
515
25
1015
1015
1423
25
25
410
37.5
25.0
20.0
10.0
3.5
12.5
12.5
18.5
3.5
3.5
7.0
0.24
0.16
0.13
0.065
0.23
0.081
0.081
0.12
0.023
0.023
0.046
laJAverage for both sexes.
}bLeukemia,
'^Includes esophagus and lymphatic tissues.
Source: UNSCEAR77.
The differences between the proportions of the total risk of fatal
cancer shown in Table G5 are, for the most part, small in comparison to
their uncertainty. We have used the BEIR3 organ risks in preference to
those made by other groups such as UNSCEAR or the ICRP for several
reasons. BEIR estimates of organ risk are based on a projection of
lifetime risk using agespecific risk coefficients, rather than just
observations to date. Moreover, the 1980 BEIR Committee considered cancer
incidence data as well as mortality data. This gives added confidence that
the diagnostic basis for their estimates is correct. And, finally, because
we apply these proportional organ risk estimates to the NAS80 cancer risk
estimates for wholebody exposures, we believe it is consistent to use a
single set of related risk estimates. The way we have used NAS80 to
estimate mortality resulting from cancer at a particular site is outlined
in the next section.
G17

TABLE G5:
Comparison of proportion of the total risk of radiogenic cancer fatalities
by bocty organ
Site
(a)
NAS80
UNSCEAR77
1CRP77
(b)
Lung
Breast
Red Marrow
Thyroid
Bone
Liver
Stomach
Intestine
Pancreas
Kidneys and
urinary tract
Other
.21
.13
.16
.099
.009
.085
.084
.039
.058
.025 %
.11(0)
.24
.16
.13
.065
.023
.081
.081
.12
.023
.023
.046
.16
.20
.16
.04
.04
( ,08)*c'
(.08)
(.08)
(.08)
(.08)
(^Lifetime exposure and cancer expression.
{^Normalized for risk of fatal cancer (see text).
(c'Five additional organs which have the highest dose are assigned
0.08 for a total of 0.4.
s include esophagus, lymphatic system, pharynx, larynx,
salivary gland, and brain.
G.2.10 Methodology for Calculating the Proportion of Mortality
Resulting from Leukemia
Application of NAS80 to particular problems is straightforward but
requires some familiarity with the details of that report. In this section
we provide sample calculations based on the BEIR3 linear dose response
model for the case of fatal leukemia resulting from irradiation of the bone
marrow throughout an average person's lifetime. We then compared this
number to the average number of all fatal radiogenic cancers to obtain the
proportion due to leukemia (Table G3).
The NAS80 estimates in Table G3 differ from the others in that they
include both a consideration of age at exposure and a full expression of
radiogenic cancer resulting from lifetime exposure. For example, Table
V17 in (NAS80) gives explicit age and sexdependent mortality
coefficients for leukemia and bone cancer together.
G18

The ratio of leukemia to bone cancer fatalities is given by the
coefficient in the dose response relationship listed in Table V17, i.e.,
2.24/0.05. For lifetime exposure at a dose rate of one rad per year, Table
V17 lists 3,568 leukemia (and bone) deaths per 106 males and 2,709
deaths per 106 females (NAS80). Using a malefemale birth ratio of 1.05
to 1.0,' this averages to 3,149 fatal cancers per million persons in the
general population. The total person rads causing these excess fatalities
is the product of one rad per year, 10^ persons, and 70,7 years (the
average age of this population at death). Dividing the total number of
fatalities by this product yields 44.5 fatalities per 106 person rad of
which about 43.5 are due to leukemia. As noted above, for total body
exposure, the average of the absolute and relative risk projection models
yielded 280 premature cancer deaths per 10° person rad.
Therefore, P, the proportion of the wholebody risk caused by the lifetime
risk of a leukemia death due to lifetime exposure of the red bone marrow,
is:
P = 43.5 = .16 (cf. with Table G3)
(Gl)
To obtain the proportional mortality for othercancers, we have used
the sitespecific, agedependent risk coefficients in Table V14
(NAS80) and the mortality ratios in Table V15 to calculate the risk of
fatal cancer from lifetime exposure at one rad per year (for each sex)
and proceeded as in the example for leukemia outlined above.
To apply the data shown in Table G3 to a particular organ, we
multiply the average of the relative and absolute lifetime risk
estimates for whole body lifetime exposure for a linear dose response,
280 fatalities per 106 person rad and 112 fatalities per 106 person
rad for a linear quadratic response by the proportional mortality for
that cancer. For example, using the linear model, a one rad dose
OowLET) to the kidney (urinary tract) resulting from lifetime
exposure is estimated to cause a lifetime probability of death caused
by radiogenic cancer that is equal to (.025) x (280xl06) or 7xlQ'6,
i.e., 7 chances in a million.
Iodine131 has been reported to be only 1/10 as effective as
Xrays or gamma rays in inducing thyroid cancer (NAS72, NCRP77). For
this cancer a linear dose response and a DREF of 10 is used in
calculating lifetime probability of death. For example, the risk from
a one rad dose to the thyroid from exposure to iodine131 or iodine129
is calculated as follows: (0,099) x (0.10) x (280xlO~6) or
2.8xl(H>f about 3 chances in a million.
G19
\

G.2.11 Cancer Risks Due to AgeDependent Doses
As noted 1n Appendix F, almost all of the dose models we have used
are based on ICRP "Reference Man." ICRP dosimetric models are
appropriate for adult workers and do not take into account differences
resulting from the changes 1n physiological parameters between children
and adults, e.g., intake rates, metabolism, and organ size. Although
it is difficult to generalize for all radionuclides, in some cases
these differences tend to counterbalance each other. For example, the
ratio of minute volume to lung mass is relatively constant with age,
i.e., within a factor of two, so that the ICRP adult model for
Insoluble materials provides a reasonably good estimate of the average
annual dose throughout life.
An exception is the thyroid where the very young have a relatively
high uptake of radloiodine into a gland which is much smaller than the
adult thyroid, as noted in Table Fl. This results in a larger
childhood dose and an increased risk which persists throughout life.
Since this is a worst case situation, we have examined it with some
care, using the agespecific risk coefficients for thyroid cancer in
Table V14 of the BEIR3 report (NAS80) and the agedependent dose
model in ORNL84. For iodine131 ingestlon, the estimated lifetime risk
is increased by a factor of 1.56 due to the 30 percent increase in
lifetime dose over that obtained with the ORNL adult model, c.f.
Appendix F. Results are about the same for inhalation of iodine131—
the estimated lifetime risk of fatal thyroid cancer is increased by a
factor of 1.63 for ORNL's agedependent dose estimate.
As noted in Appendix F, use of an agedependent dosimetry for
other radionuclides has yielded much smaller increased doses relative
to adult models and therefore has little effect on estimates of
lifetime risk. In particular, the lung dose and risk resulting from
the inhalation of insoluble alpha particle emitters is nearly
unchanged. The lifetime dose for an agedependent dose model is only
1.09 times greater than that calculated using an adult model
(Appendix F); the lifetime risk of lung cancer for this agedependent
model is a factor of 1.16 greater than we calculate for life exposure
with the adult only model.
G.3 Fatal Cancer Risk Resulting from HighLET Radiations
In this section we explain how EPA estimates the risk of fatal
cancer resulting from exposure to highLET radiations. In some cases,
ingestion and inhalation of alpha particle emitting radionuclides can
result in a relatively uniform exposure of specific body organs by
highLET radiations. Unlike exposures to Xrays and gamma rays where the
resultant charged particle flux results In linear energy transfers (LET)
of the order of 0.2 to 2 keV per micron In tissue, 5 MeV alpha particles
G20

result in energy deposition at a track average rate of more than 100 keV
per micron. HighLET radiations have a larger Biological effect per unit
dose (rad) than lowLET radiations. How much greater depends on the
particular biological endpoint being considered. For cell killing and
other readily observed endpoints, the relative biological effectiveness
(RBE) of highLET alpha radiations is often 10 or more times greater than
lowLET radiations.
G.3.1 Quality Factors for Alpha Particles
Charged particles have been assigned quality factors, Q, to account
for their efficiency in producing biological damage. Unlike an RBE
value, which is for a specific and welldefined endpoint, a quality
factor is based on an average overall assessment by radiation protection
experts of potential harm of a given radiation relative to X or gamma
radiation. In 1977, the ICRP assigned a quality factor of 20 to alpha
particle irradiation from radionuclides (ICRP77). The reasonableness of
this numerical factor for fatal radiogenic cancers at a particular site
is not well known, but it is probably conservative for all sites and
highly conservative for some.
The dose equivalent (in rem) is the dose, in rad, times the
appropriate quality factor for a specified kind of radiation. For the
case of internally deposited alpha particle emitters the dose equivalent
from a onerad dose is equal to 20 rem. It should be noted that prior to
ICRP Report 26 (ICRP79), the quality factor for alpha particle
irradiation was 10. That is, the biological effect from a given dose of
alpha particle radiation was estimated to be 10 times that from an acute
dose of lowLET Xrays or gamma rays of the same magnitude in rad. The
ICRP decision to increase this quality factor to 20 followed from their
decision to estimate the risk of lowLET radiations, in occupational
situations, on the assumption that biological effects were reduced at low
dose rates for lowLET radiation. There is general agreement that dose
rate effects do not occur for highLET (alpha) radiations. The new ICRP
quality factor for alpha particles of 20 largely compensates for the fact
that their lowLET risks are now based on an assumed dose rate reduction
factor of 2.5. This DREF has been addressed in preparing EPA estimates
of the risk per rad for alpha particle doses described below, in Section
G.3*3*
In 1980 the ICRP published a task group report "Biological Effects
of Inhaled Radionuclides" which compared the results of animal
experiments on radiocarcinogenesis following the inhalation of alpha
particle and beta particle emitters (ICRP80). The task group concluded
that "the experimental animal data tend to support the decision by the
ICRP to change the recommended quality factor from 10 to 20 for alpha
radiation."
G21

G.3.2 Dose Response Function
In the case of highLET radiation, a linear dose response 1s
commonly observed 1n both human and animal studies and the response £$
not reduced at low dose rates (NCRP80). Some data on human lung cancer
ThUicate that the carcinogenic response per unit dose of alpha
radiation is higher at low doses than higher ones (Ar81, Ho81, Wh83);
1n addition, some studies with animals show the same response pattern
(Ch81, U182). We agree with the MAS BEIR3 Committee that, "For
highLET radiation, such as from Internally deposited alphaemitting
radionuclides, the linear hypothesis 1s less likely to lead to
overestimates of the risk and may, 1n fact, lead to underestimates"
(NAS80). However, at low doses, departures from linearity are small
compared to the uncertainty 1n the human epidemiological data, and we
believe a linear response provides an adequate model for evaluating
risks in the general environment.
A possible exception to a linear response is provided by the data
for bone sarcoma (but not sinus carcinoma) among U.S. dial painters who
have ingested alphaemitting radium226 (NAS80). These data are
consistent with a dosesquared response (Ro78). Consequently, the MAS
BEIR3 Committee estimated bone cancer risk on the basis of both linear
and quadratic dose response functions. However, as pointed out 1n
NAS80, the number of U.S. dial painters at risk who received less than
1000 rad was so small that the absence of excess bone cancer at low
doses 1s not statistically significant. Therefore, the consistency of
this data with a quadratic (or threshold) response is not remarkable
and, perhaps, not relevant to evaluating risks at low doses. In
contrast to the dial painter data, the Incidence of bone cancer
following radium224 irradiation, observed In sponctyHtics by Mays and
Spiess (Ma83» NAS80), 1n a larger sample at much lower doses, is
consistent with a linear response. Therefore, for highLET radiations
EPA has used a linear response function to evaluate the risk of bone
cancer.
Closely related to the choice of a dose response function is what
effect the rate at which a dose of h1ghLET radiation is delivered has
on its carcinogenic potential. This Is a very active area of current
research. There Is good empirical evidence, from both human and animal
studies, that repeated exposures to radium224 alpha particles is 5
times more effective in Inducing bone sarcomas than a single exposure
which delivers the same dose (Ma83, NAS80). The 1980 MAS BEIR
Committee took this Into account In their estimates of bone cancer
fatalities which EPA is using. We do not know to what extent, if any,
a similar enhancement of carclnogenicity may occur for other cancers
resulting from internally deposited alpha particle emitters.
Nevertheless, we believe the ICRP quality factor of 20 1s conservative,
even at low dose rates.
G22

G.3.3 Assumptions Made by EPA for Evaluating the Dose from Alpha
Particle Emitters:
We have evaluated the risk to specific body organs by applying the
ICRP quality factor of 20 for alpha radiations to the risk estimates .
for low dose rate lowLET radiations as described above. For some
organs this quality factor may be too conservative. Several authors
have noted that estimates of leukemia based on a quality factor of 20
for bone marrow irradiation overpredicts the observed Incidence of
leukemia in persons receiving thorotrast (thorium oxides) (Mo79) and in
the U.S. radium dial painters (Sp83). Nevertheless, in view of the
paucity of applicable human data and the uncertainties discussed above,
the ICRP quality factor provides a reasonable and prudent way of
evaluating the risk due to alpha emitters deposited within body organs.
All of EPA risk estimates for highLET radiations are based on a
linear dose response function. For bone cancer and leukemia we use the
absolute risk projection model described in the previous section. For
other cancers we use the arithmetic average of relative and absolute
risk projections.
Table G6 indicates the Agency's estimates of the risk of fatal
cancer due to a uniform organ dose in various organs from internally
deposited alpha particles. These estimates are for lifetime doses at a
constant dose rate. It was prepared by multiplying the average risk
(based on the linear model for a uniformly distributed wholebody dose
of lowLET radiation and a dose rate effectiveness factor of 2.5) by a
quality factor of 20 and then apportioning this risk by organ, as
indicated in Table G6.
This procedure was not followed for bone cancer. As outlined
above, the risk estimate for this cancer in the BEIR3 report 1s based
on data for highLET (alpha) radiation and a direct estimation of the
effect of the alpha radiation per highLET rad. Some readers may note
that the risk estimate in Table G6, about 20 bone cancer fatalities
per 106 person rad, is less than the 27 fatalities listed in Table
A27 of (NAS80) for alpha particles. This is because the analysis in
Appendix A of NAS80, but not Chapter V of that report, assumes that in
addition to a 2year minimum induction period, 27 years are available
for cancer expression. This is usually not the case for doses received
beyond middle age. Hence, the estimated lifetime risk Is smaller when
it is based on a life table analysis that considers lifetime exposure
in conjunction with death from all causes.
G.4 Uncertainties in Risk Estimates for Radiogenic Cancer
As pointed out in the introduction of this appendix, numerical
estimates of risks due to radiation are neither extremely accurate nor
precise. A numerical evaluation of radiogenic cancer risks depends
both on epidemiological observations and a number of ad hoc assumptions
which are largely external to the observed data set. "These assumptions
G23

TABLE G6:
Estimated number of cancer fatalities from a lifetime exposure to
Internally deposited ALPHA particle emitters
Site
Proportional risk'3'
Fatalities per
106 person
Lung
Breast*0'
Red marrow(d)
Thyroid 
Bonefe)
Liver
Stomach
Intestine
Pancreas
Kidneys and
urinary tract
OtherSum (total)
.21
.13
.16
.099
.009
.085
.084
.039
.058
.025
.11
460
290
350
220
20
190
190
90
130
55
250
{^Proportion of whole body risk from Table G3.
JbJRounded to two figures.
}cjAverage for both sexes.
d Leukemia.

G.4.1' Uncertainty of the Dose Response Models Due to Bias In the
Abomb Dosimetry
Although the BEIR3 Committee's choice of a linearquadratic
response has gained considerable attention, it may not be generally
appreciated that the BEIR3 Committee's numerical evaluations of dose
response functions for cancer due to lowLET radiation were based
exclusively on the cancer mortality of the Abomb survivors.
Unfortunately, the dosimetry for Abomb survivors, on which the BEIR3
Committee relied, has since been shown to have large systematic errors
which serve to undermine the analyses made by the Committee. As
outlined below, the mathematical analyses made by the Committee were
"constrained" to meet certain a priori assumptions. These assumptions
have since been shown to be dotlbtful.
A careful stateoftheart evaluation of the dose to Abomb
survivors was carried out by investigators from Oak Ridge National
Laboratory in the early 1960's (Au67, Au77). The results of these
studies resulted in a "T65" dose being assigned to the dose (kerma) in
free air at the location of each survivor for both gamma rays and
neutrons. A major conclusion of the ORNL study was that the mix of
gamma ray and neutron radiations was quite different in the two cities
where Abombing occurred. These results indicated that at Hiroshima,
the neutron dose was more important than the gamma dose when the
greater biological efficiency of the highLET radiations produced by
neutrons was taken into account. Conversely, the neutron dose at
Nagasaki was shown to be negligible compared to the gamma dose for that
range of doses where there were a significant number of survivors.
Therefore, the 1980 BEIR Committee evaluated the cancer risks to the
survivors at Hiroshima on the assumption that the combined effects of
gamma rays and particularly neutrons caused the observed cancer
response.
Since the BEIR3 report was published, it has become evident that
the organ doses due to neutrons at Hiroshima were overestimated by
about an order of magnitude, at distances where most of the irradiated
persons survived bomb blast and yet received significant doses,
10001500 meters. In fact, the neutron doses at Hiroshima are quite
comparable to those previously assigned, at similar distances, to
Nagasaki survivors (KeSla, KeBlb, RERF83, RERF84). Moreover, there is
now grounds to believe the T65 estimates of gamma ray doses in both
cities are also incorrect .(RERF83, RERF84). While several factors need
further evaluation, reduction of the gamma dose to individual survivors
due to the local shielding provided by surrounding structures, is
significant. The important point, however, is that the overestimate of
the neutron dose to the Hiroshima survivors led to the BEIR3 Committee
attributing most of the risk to neutrons rather than gammarays.
Hence, they underestimated the risk for lowLET radiations by, as yet,
an unknown amount.
G25

For their analysis of the Abomb survivor data, the BEIR3.
Committee expanded the equations for lowLET ra'dlations listed 1n
Section G.2, Table Gl, to Include a linear dose response function for
neutrons:
1) P(d.D) = cid +
2) P(d,D) = c2d2
3) P(d.D) = c3d +
k2D
k3D
(G2)
(G3)
(G4)
where d is the gamma dose and D.is that part of dose due to highLET
radiations from neutron Interactions. Note that in equation G4 the
linearquadratic (LQ) response, has two linear terms, one for neutrons and
one for gamma radiation. In analyzing approximately linear data In terms
of equation G4, the decision as to how much of the observed linearity
should be assigned to the neutron or the gamma component, i.e, k3 and
c3, respectively, is crucial. As shown below, the BEIR3 Committee
attributed most of the observed radiogenic cancer to a linear response from
neutron doses which did not occur.
The BEIR3 Committee's general plan was to examine the dose response
for leukemia and for solid cancer separately to find statistically valid
estimates of the coefficients cj 04 and kj k3 by means of
regression analyses. The regressions were made after the data were
weighted in proportion to their statistical reliability; thus, Hiroshima
results dominate the analysis. The T65 neutron and gamma doses to
individual survivors are highly correlated since both are strongly
decreasing functions of distance. This makes accurate determination of the
coefficients in equation G4 by means of a regression analysis extremely
difficult. In addition, there is considerable sampling variation in the
Abomb survivor data due to small sample size which exacerbates the
regression problem. Herbert gives a rigorous discussion of these problems
for the case of the Abomb survivors (He83). Because of these and other
problems, agreement between the observed response for solid cancers and
that predicted by any of the dose response functions examined by the BEIR3
Committee is not impressive. For example, goodness of fit, based on Chi
square, ranges from 0.20 for equation G3 to 0.23 for equation G4, to 0.30
for equation G2 (Table Vll in NA.S80). For leukemia, the goodness of fit
between the observed data and that predicted by the regression analysis is
better, e.g., 0.49 for equations G2 and G3 (Table V8 in NAS80).
The Committee analyzed the Abomb survivor data in two separate sets,
I.e., first leukemia and then all cancer excluding leukemia (solid
cancers). Their treatment of these two cases was not equivalent. Unlike
the analysis of solid cancers, the Committee's analysis of leukemia
considered the Nagasaki and Hiroshima data separately. Their approach
G26

(p. 342 in NAS80) appears to be based on an unpublished paper by
Charles Land and a published report by Ishimaru et al. on estimating the
RBE of neutrons by comparing leukemia mortality TW "Hiroshima to that in
Nagasaki (Is79). Unlike the case for solid cancers, (see below), the
Committee's regression analysis of the leukemia mortality data did provide
stable values for all of the coefficients in equation G4, and therefore an
RBE for neutrons as a function of dose, as *ell as the ratio of the linear
to the dosesquared terms for leukemia induction due to gamma rays,
Estimating the linearquadratic response coefficients for solid
cancers proved to be less straightforward. When the BEIR3 analysis
attempted to fit the Abomb survivor data on sol id .cancers to a .
linearquadratic dose response function, they found that the linear
response coefficient, 03 in equation G4, varied from zero to 5.6
depending on the dose range considered. Moreover, their best estimate of
the coefficient for the dosesquared term in equation G4, I.e., 04, was
zero, i.e., the best fit yielded a linear response. Therefore, it was
decided that the observations on solid cancers were "not strong enough to
provide stable estimates of low dose, lowLET cancer risk when analyzed in
this fashion," (NAS80, p. 186).
As outlined in the BEIR3 Report, the Committee decided to use a
constrained regression analysis, that is, substitute some of the parameters
for equation G4 found in their analysis of leukemia deaths to the
regression analysis of the dose response for solid cancers. That is, both
the neutron RBE at low dose (the ratio of the coefficient ks to 03) and
the ratio of cj to 04, as estimated from the leukemia data, were
assumed to apply to the induction of fatal solid cancers. Regression
analyses that are constrained in this manner can yield much higher
estimates of precision than is warranted by the data, as discussed by Land
and Pierce (La83). They can also be very misleading. Herbert has
discussed this point in detail as it applies to the BEIR3 regression
analysis (He83). The BEIR3 Committee's substitution of the results of the
leukemia regression for the data on solid cancers allowed them to make
stable estimates of C3, C4, and k3. These estimates became the basis
for the "preferred" linear quadratic risk estimates for solid cancers
presented 1n NAS80, I.e., the LQL model, page 187. (The response models
for solid cancers that are based on the Committee's constrained regression
analysis are designated with a bar In their 1980 report, e.g., UPU and
L~L* )
Given the Information discussed above, 1t Is possible to see, at least
qualitatively, how the high bias 1n the estimated T65 neutron dose to the
Japanese survivors affects the 1980 BEIR Committee's "preferred" LQ
estimates of the risk coefficients for leukemia. The Committee's
ageadjusted risk coefficients for leukemia are listed In Table V8 (NAS80,
page 184). For the linearquadratic response, k3, the neutron risk
coefficient 1s 27.5. Tables All (NAS80, page 341) and V6 (NAS80, page
152) provide the estimates of neutron and gamma doses to the bone marrow of
G27

Hiroshima survivors that were used by the Committee. Substituting these
doses In their risk equations (Table V8) Indicates that about 70 percent
of the leukemia deaths were ascribed to the neutron dose component then
thought to be present at Hiroshima. As noted above, subsequent research
indicates that the highLET dose due to neutrons was actually much smaller
It is not possible to accurately quantify what effect the Committee's
use of these same coefficients had on their analysis of the dose response
for solid cancers. Equation V10 for solid cancers, p. 187 1n NAS80,
indicates about 60 percent of the solid tumor response was attributed to
the T65 neutron dose; but this Is a minimum estimate that Ignores the
effect of the assumed neutron doses on the value of k$ and the ratio of
€ to €.
The BEIR3 Committee's LQL model assumes an RBE of 27.8 at low
doses. In the Committee's LL linear response model, the assumed RBE 1s
11.3. Therefore, this linear model is considerably less sensitive to the
neutron dose component, assumed by the Committee, than their LQL model.
For either model, most of the Abomb survivors' radiogenic cancer was
ascribed to the T65 neutron doses at Hiroshima.
There 1s no simple way of adjusting the 1980 BEIR risk estimates to
account for the risk they attributed to neutrons. Adjustment of neutron
doses alone is clearly Inappropriate, since there is good reason to believe
that T65 estimates of the dose due to gamma rays are also subject to
considerable change. Moreover, not all of the individuals In a given T65
dose category will, necessarily, remain grouped together after new
estimates of neutron and gamma doses are obtained. Both the numerator and
denominator 1n the ratio of observed to expected cases are subject to
change and indeed could change 1n opposite directions, a fact not
considered In some preliminary (and premature) analyses (St81).
Nevertheless, it 1s reasonable to conclude that bias in the estimated
neutron doses at Hiroshima has led to considerable uncertainty in the
BEIR3 risk estimates and also to a systematic underestimation of the risk
due to lowLET radiations. For this reason we believe that estimates based
on the more conservative linear dose response should be given considerable
weight ^ll £ Xli tnose ma(*e using the BEIR3 linear quadratic models.
G.4.2 Sampling Variation
In addition to the systematic bias 1n the BEIR3 risk estimates for
lowLET radiation outlined above, the precision of the estimated linear and
quadratic risk coefficients in the BEIR3 report is poor due to statistical
fluctuations due to sample size. Recently, Land and Pierce have
reevaluated the precision of the BEIR3 linear quadratic risk estimates to
take Into account, at least partially, the Committee's use of a constrained
regression analysis (La83). This new analysis indicates that for the
BEIR3 LQL model for leukemia, the standard deviation of the linear term
Is nearly as large as the risk coefficient Itself (jK).9 compared to a risk
coefficient of 1). For the HPT model , solid cancer, the standard
deviation is +1.S compared to a risk coefficient of 1.6.
G28

It Is likely that at least part of the uncertainty attributed to
sampling variation in the BE3R3 risk estimates'ls not due to sample size
and other random factors but rather due to the use of Incorrect dose
estimate for the Abomb survivors. The correlation of neutron and
gammaray doses has been a major underlying cause of the uncertainty in
regression analysis using the T65 doses. Analyses of revised data with
much smaller neutron doses may result in better precision. At present, we
have concluded that the BEIR3 risk coefficients are uncertain by at least
a factor of 2, see below, as well as being biased low by an additional
factor of 2 or more.
G.4.3 Uncertainties Arising from Model Selection
In addition to a dose response model, a "transportation model" is
needed to apply the risks from an observed irradiated group to another
population having different demographic characteristics. A typical example
is the application of the Japanese data for Abomb survivors to western
people. Seymore Jablon, (Director of the Medical Followup Agency of the
National Research Council, NAS) has called this the "transportation
problem," a helpful designation because it is often confused with therisk
projection problem described below. However, there is more than a
geographic aspect to demographic characteristics. The "transportation
problem" includes estimating the risks for one sex based on data for
another and a consideration of habits influencing health status such as
differences between smokers and nonsmokers.
The BEIR3 Committee addressed this problem in their 1980 report and
concluded, based largely on the breast cancer evidence, that the
appropriate way to transport the Japanese risk to the U.S. population was
to assume that the absolute risk over a given observation period was
transferable but that relative risk was not. Therefore, the Committee
calculated what the relative risk would be if the same number of excess
cancer deaths were observed in a U.S. population having the same age
characteristics as the Abomb survivors. The base line cancer rates in the
U.S. and Japan are quite different for some specific cancers so this is a
reasonable approach. However, it contains the assumption that while the
cancer initiation process Is the same in the two countries, the actual
number of radiogenic cancers that actually occur 1s the result of cancer
promotion, the Tatter being a culturally dependent variable.
An alternative approach to solving the "transportation problem" is
that of the 1972 NAS BEIR1 Committee. This Committee assumed relative
risks would be the same In the United States and Japan and transferred the
observed percentage increase directly to the U.S. population. We have
compared estimates of the lifetime risk for these two treatments of the
"transportation problem" in order to find out how sensitive the BEIR3
Committee risk estimates are to their assumptions. To do this, we
calculated new relative risk estimates for solid cancers based on the
agespecific cancer mortality of the Japanese population rather than the
U.S. data used by the BEIR3 Committee. We found that this alternative
G29

approach did not have much effect on the estimated lifetime risk of solid
radiogenic cancer, I.e., a change of 3 percent Tor males, and 17 percent
for females. We have concluded that the amount of uncertainty Introduced
by transporting cancer risks observed 1n Japan to the U.S. population 1s
small compared to other sources of uncertainty 1n this risk assessment.
Baseline leukemia rates are about the same in the countries, so we believe
these risks are also "transportable."
The last of the models needed to estimate risk 1s a risk projection
model. As outlined in Section G.2, such models are used to project what
future risks will be as an exposed population ages. For leukemia and bone
cancer, where the expression time is not for a full lifetime but rather 25
years, absolute and relative risk projection models yield the same number
of radiogenic cancers, but would distribute them somewhat differently by
age. For solid cancers, other than bone, the BEIR3 Committee assumed that
radiogenic cancers would occur throughout the lifetime. This makes the
choice of projection model more critical, because the relative risk
projection yields estimated risks about three times larger than that
obtained with an absolute risk projection, as shown in Table G2. Because
we have used the average of these two projections for solid cancers, we
believe this reduces the uncertainty from the choice of model to about a
factor of 2 or perhaps less, depending on the age distribution of fatal
radiogenic cancer, as outlined in Section G.2 above.
Similarly, there 1s as yet insufficient Information on radiosensltivity
as a function of the age at exposure. The agedependent risk coefficients
we have used are those presented In the BEIR3 report. As yet, there is
little Information on the ultimate effects of exposure during childhood.
As the Abomb survivors' population ages, more information will become
available on the cancer mortality of persons irradiated when they were
young. Table G2 Indicates that the more conservative BEIR1 estimates for
the effect of childhood exposures would Increase BEIR3 risk estimates by
about 40 percent. As this is probably an upper limit, the lack of more
precise Information Is not a major source of uncertainty 1n estimates of
the risk caused by lifetime exposure. Similarly, the BEIR3 Committee did
not calculate population risks for radiogenic cancer that Included in utero
radiation because they felt the available data were unreliable. We have
deferred to their judgment in this regard. The BEIR1 report did Include
in utero.cancer risk. These had little effect, 1 to 10 percent, on the
TTfetime risk of cancer from lifetime exposure. An effect this small is
not significant relative to other sources of uncertainty 1n the risk
assessment.
Summary
We can only semiquantitatively estimate the overall uncertainty in
the risk per rad for lowLET radiations. We expect that more quantitative
estimates of the uncertainty will be possible only after the Abomb dose
reassessment is completed and the Abomb survivor data reanalyzed on the
basis of the new dose estimates. It should be noted, however, that even if
G30

all systematic bias is removed from the new dos* estimates, there will
still be considerable random error in the dose estimate for each survivor.
This random error biases the estimated slope of the dose response curve so
that it is smaller than the true dose response (Da72, Ma59). The amount of
bias introduced depends on the size of the random error in the dose
estimates and their distribution which are unknown quantities at this stage
of the dose reassessment.
The source of uncertainty in risk estimates for lowLET radiations can
be ranked as shown in Table G7.
TABLE G7:
A ranking of causes of uncertainty in estimates of the risk of cancer
Source of uncertainty
Degree of uncertainty
Choice of dose response model
Slope of dose response resulting
from sampling variation
Choice of an average risk
projection model
Choice of transportation model
Abomb T65 dosimetry
±250 percent^
^200 percent^)
+100 percent(c>
^20 percent
(d)
Plus only,
amount unknown
(a)For choices limited to BEIR3 linear and linear quadratic
models, see G.2.
^Estimate of 2 standard deviations for the BEIR3 OJ" model (La83).
jcjAverage of relative and absolute projection as described above.
*dJFor the total of all cancers, not specific cancers.
The estimates of uncertainty in Table G7 are not wholly comparable and
must be interpreted carefully. However, they do have some illustrative
value, particularly when ordered in this way. The uncertainty listed for
the slope of dose response is a nominal value for the BEIR3 linear
quadratic UJ" formulation (La83) 1n that it is only valid Insofar as the
Committee's assumptions are true. It is based on a two standard deviation
error so that the expectation that the error is less than indicated is 95
percent. We do not believe the uncertainty in the BEIR3 linear estimate,
is'significantly smaller, c.f. Tables V9 and Vll in NAS80.
G31

The other uncertainties listed 1n Table G7 are quite different, being
more 1n the nature of Informed judgments than the result of a statistical
analysis. It 1s doubtful that all radiogenic cancers have the same type of
response functions. However, 1f they were all linear, as breast cancer and
thyroid appear to be, the BEIR3 linear quadratic response model would
underestimate the response by 250 percent. If most cancers have a linear
quadratic response, or equivalently, a dose rate reduction factor equal to
the difference in slope at low doses between the BEIR3 linear and linear
quadratic models, the use of a linear model would overestimate the response
by a factor of 2.5. We believe that a factor of 250 percent is a
conservative estimate of the uncertainty introduced by the lack of data at
low dose rates.
As discussed above, the uncertainty due to the choice of an absolute
or a relative risk model is about a factor of 3. The use of the average
risk for these two models reduces the uncertainty in risk projection by
more than a factor of 2, since 1t 1s known that a relative risk projection
is high for some kinds of cancer and that an absolute risk projection 1s
low for others.
The uncertainties listed in Table G7 are largely independent of each
other and therefore unlikely to be correlated in sign. Their root mean
square sum is about 300 percent, indicating the expectation that calculated
risks would be within a factor of 3 or so of the true value. This result
is overly optimistic because it does not Include consideration of the
uncertainty introduced by the bias in the Abomb dosimetry or by the
constrained regression analysis used by the BEIR3 Committee.
G.5 Other RadiationInduced Health Effects
The earliest report of radiationinduced health effects was in 1896
(Mo67), and It dealt with acute effects In skin caused by xray exposures.
Within the sixyear period following, 170 radiationrelated skin damage
cases had been reported. Such Injury, like many other acute effects, Is
the result of exposure to hundreds or thousands of rad. Under normal
environmental exposure situations, however, such exposure conditions are
not possible and therefore will not be considered 1n assessing the risk to
the general population from radionuclide releases.
Although radiationinduced cardnogenesis was the first delayed health
effect reported, radiationInduced genetic changes were reported early
ToolIn 1927, H.J. Muller reported on xray Induced mutations In animals
and 1n 1928, L.J. Stadler reported a similar finding In plants (K162). At
about the same time, radiation effects on the developing embryo were
reported. Case reports In 1929 showed a high rate of microcephaly (small
head size) and central nervous system disturbance and one case of skeletal
defects 1n children Irradiated In utero (UNSCEAR69). These effects, at
unrecorded but high exposures, appeared to produce central nervous system
and eye defects similar to those reported In rats as early as 1922 _(Ru50).
G32

For purposes of assessing the risks of environmental exposure from
radionuclide releases, the genetic effects and in utero developmental
effects are the only health hazards other than cancer that are addressed in
this appendix.
G*5l Types of Genetic Harm and Duration of Expression
Genetic harm or the genetic effects of radiation exposure are those
effects induced in the germ cells (eggs or sperm) of exposed individuals,
which are transmitted to and expressed only in their progeny and future
generations.
Of the possible consequences of radiation exposure, the genetic risk is
more subtle than the somatic risk. Genetic risk is incurred by fertile
people when radiation damages the nucleus of the cells which become their
eggs or sperm. The damage, in the form of a mutation or a chromosome
aberration, is transmitted to, and may be expressed in, a child conceived
after the radiation exposure and in subsequent generations. However, the
damage may be expressed only after many generations, may.be lost by chance,
or, alternately, it may never be expressed because of failure to reproduce.
EPA treats genetic risk as independent of somatic risk because,
although somatic risk is expressed in the person exposed, genetic risk is
expressed only in progeny and, in general, over many subsequent generations.
.Moreover, the types of damage incurred often differ in kind from cancer and
cancer death. Historically, research on genetic effects and development of
risk estimates has proceeded independently of the research on
carcinogenesis. Neither the dose response models nor the risk estimates of
genetic harm are derived from data on studies of carcinogenesis.
Although genetic effects may vary greatly in severity, the genetic
risks considered by the Agency evaluating the hazard of radiation exposure
include only those "disorders and traits that cause a serious handicap at
some time during lifetime" (NAS80). Genetic risk may result from one of
several types of damage that ionizing radiation can cause in the DNA within
eggs and sperm. The types of damage usually considered are: dominant and
recessive mutations in autosomal chromosomes, mutations in sexlinked
(xlinked) chromosomes, chromosome aberrations (physical_rearrangement or
removal of part of the genetic message on the chromosome or abnormal
numbers of chromosomes), and irregularly inherited disorders (genetic
conditions with complex causes, constitutional and degenerative diseases,
etc.).
Estimates of the genetic risk per generation are based on a 30year
reproductive generation. That is, the median parental age for production
of children is age 30 (onehalf the children are produced by persons less
than age 30, the other half by persons over age 30). Thus, the radiation
dose accumulated up to age 30 is used to estimate the genetic risks. Using
this accumulated dose and the number of live births in the population along
G33

with the estimated genetic risk per unit dose, 1t 1s possible to estimate
the total number of genetic effects per year, tfiose 1n the first generation
and the total across all time. Most genetic risk analyses have provided
such data. EPA assessment of risks of genetic effects Includes both first
generation estimates and total genetic burden estimates.
Direct and Indirect Methods of Obtaining Risk Coefficients for Genetic
Effects
Genetic effects, as noted above, may occur in the offspring of the
exposed Individuals or they may be spread across all succeeding
generations. Two methods have been used to estimate the frequency of
mutations in the offspring of exposed persons, direct and indirect. In
either case, the starting point is data from animal studies, not data
obtained from studies of human populations.
For a direct estimate, the starting point is the frequency of a
mutation per unit exposure in some experimental animal study. The 1982
IMSCEAR (UNSCEAR82) report gave an example of the direct method for
estimating induction of balanced reciprocal translocatlons (a type of
chromosomal aberration) in males per rad of low level, lowLET radiation.
1) Rate of induction in rhesus monkey
Spermatogonia: cytogenetic data
2) Rate of induction that relates to
recoverable translocations in the FI
(1st filial generation) progeny [divide
. (1) by 4]
3) Rate after low dose rate Xrays:
based on mouse cytogenetic observations
[divide (2) by 2]
4)
5)
6)
Rate after chronic gammairradiation:
based on mouse cytogenetic observations
[divide (2) by 10]
Expected rate of unbalanced products:
[multiply (3) and (4) by 2] for (3)
for (4)
Induction rate/rad
0.86 x lO'4
0.215 x 104
0.1075 x 104
0,022 x ID'4
0.215 x 104
0.043 x ID'4
Expected frequency of congenital ly
malformed children in the Fjf assuming
that about 6 percent of unbalanced products
[item (5) above] contribute to this
for low dose rate Xrays 1.3 x 106
for chronic gamma radiation "0.3 x 10~6
G34

For humans, UNSCEAR estimates that as a consequence of Induction
of balanced reciprocal translations in exposed fathers, an estimated
0.3 to 1.3 congenital!,/ malformed children would occur in each 10°
live births for every rad of parental radiation exposure.
A complete direct estimate of genetic effects would include
estimates, derived in a manner similar to that shown above for each
type of genetic damage. These direct estimates can be used to
calculate the risk of genetic effects in the first generation (Fi)
children of exposed parents.
The indirect (or doubling dose) method of estimating genetic risk
also uses animal data but in a different way. The 1980 BEIR3 report
(NAS80) demonstrates how such estimates are obtained.
1) Average radiation inducedmutation per
gene for both sexes in mice [based on
12 locus data in male mice]: induction
rate per rad
2) Estimated human spontaneous mutation
rate per gene
3) Relative mutation risk in humans
[divide (1) by (2)]
4) Doubling dose: the exposure needed
to double the human mutation rate
0.25 x 107
0.5 x 10~6 to
0.5 x 105
0.005 to 0.05
200 to 20 rad
The doubling dose can then be used to estimate the equilibrium
genetic effects or the genetic burden in all future generations caused
by the exposure of parents. Since the genetic component of congenital
defects occurring in the population can be estimated by epidemiological
surveys, and this component is considered to be maintained at an
equilibrium level by mutations, a doubling dose of ionizing radiation
would double these genetic effects. Dividing the number of the various
genetic effects in 106 livebirths by the doubling dose yields the
estimate of genetic effects per rad. For example:
1) Autosomal dominant and x1inked
diseases, current incidence
2) Estimated doubling dose
3) Estimate of induced autosomal
dominant and x1inked diseases
10,000 per 106
live births
20 to 200 rad
50 to 500 per 106
live births per rad of
parental exposure.
G35
r

A doubling dose estimate assumes that the total population of both
sexes Is equally Irradiated, as occurs from background radiation, and
that the population exposed 1s large enough so that all genetic damage
can be expressed in future offspring. Although 1t is basically an
estimate of the total genetic burden across all future generations, 1t
can also provide an estimate of effects that occur in the first
generation. Usually a fraction of the total genetic burden for each
type of damage is assigned to the first generation using population
genetics data as a basis to determine the fraction. For example, the
BEIR3 committee geneticists estimated that onesixth of the total
genetic burden of xHnked mutations would be expressed 1n the first
generation, fivesixths across all future generations. EPA assessment
of risks of genetic effects includes both first generation estimates
and total genetic burden estimates.
G.5.2 Estimates of Genetic Harm Resulting from LowLET Radiations
One of the first estimates of genetic risk was made In 1956 by the
NAS Committee on the Biological Effects of Atomic Radiation (BEAR
Committee). Based on Drosophila (fruit fly) data and other
considerations, the BEAR Genetics Committee estimated that 10 Roentgens
(10 R*) per generation continued indefinitely would lead to about 5,000
new Instances of "tangible inherited defects" per 106 births, and
about onetenth of them would occur in the first generation after the
irradiation began (NAS72). The UNSCEAR addressed genetic risk in their
1958, 1962, and 1966 reports (UNSCEAR58, 62, 66). During this period,
they estimated one rad of lowLET radiation would cause a 1 percent to
10 percent increase in the spontaneous incidence of genetic effects.
In 1972, both the NAS BEIR Committee (NAS72) and UNSCEAR
(UNSCEAR72) reexamlned the question of genetic risks. Although there
were no definitive human data, additional Information was available on
the genetic effects of radiation on mammals and Insects. In 1977,
UNSCEAR Devaluated the 1972 genetics estimates (UNSCEAR77). Their new
estimates used recent Information on the current incidence of various
genetic conditions, along with additional data on radiation exposure of
mice and marmosets and other considerations.
In 1980, an ICRP Task Group (ICRPTG) summarized recommendations
that formed the basis for the genetic risk estimates published in ICRP
Report 26 (Of80). These risk estimates are based on data similar to
that used by the BEIR and UNSCEAR Committees, but with slightly
different assumptions and effect categories, Table G8.
*R is the symbol for Roentgen, a unit of measurement of xradiation,
equivalent to an absorbed dose in tissue of approximately 0.9 rad.
G36

Table G8. ICRP task group estimate of number of cases
of serious genetic ill health in liveborn from
parents Irradiated with 10° manrem in a
population of constant size9
(Assumed doubling dose = 100 rad)
Category of
genetic effect
First generation
Equilibrium
Unbalanced translocations:
risk of malformed liveborn 23
Trisomics and XO 30
Simple dominants and sex
linked mutations 20
Dominants of incomplete
penetrance and multifactorial
disease maintained by mutation 16
Multifactorial disease not
maintained by mutation 0
Recessive disease
Total 89
30
30
100
160
0
320
aThis 1s equivalent to effects per 10^ liveborn following an average
parental population exposure of 1 rem per 30year generation, as used
by BEIR and UNSCEAR.
Source: Of80.
The 1980 MAS BEIR Committee revised genetic risk estimates BEIR3
(NAS80). The revision considered much of the same material that was in
BEIR1 (NAS72), the newer material considered by UNSCEAR in 1977
(UNSCEAR77), and some additional data. Estimates for the first generation
are about a factor of 2 smaller than reported in the BEIR1 report. For
all generations, the new estimates are essentially the same, Table G9.
The most recent genetic risk estimate, in the 1982 UNSCEAR Report
(UN82), Includes some new data on cells in culture and the results of
genetic experiments using primates rather than rodents, Table G10.
Although all of the reports described above used somewhat different
sources of information, there is reasonable agreement in the estimates
(Table Gll). Most of the difference is caused by the newer information
G37

used In each report. Note that all estimates listed above are based on
the extrapolation of animal data to humans. Groups differ In their
Interpretation of how genetic experiments In animals might be expressed 1n
humans. While there are no comparable human data at present, Information
on hereditary defects among the children of Abomb survivors provides a
degree of confidence that the animal data do not lead to underestimates of
the genetic risk following exposure to humans. (See "Observations on
Human Populations" which follows.)
Table G9. BEIR3 estimates of genetic effects of an average
population exposure of 1 rem per 30year generation
Type of genetic
disorder
Current Incidence
per 106 Hveborn
Effects per 106 Hveborn
per rem per generation
Autosomal dominant
and x1 Inked
Irregularly Inherited
Recessive
Chromosomal aberrations
10,000
90,000
1,100
6,000
First Generation
565
(not estimated)
Very few
Fewer than 10
Equilibrium
40200
20900
Very slow
Increase
Increases
only
slightly
Total
107,100
575
601100
Source: NAS80.
G38
r

Table G10. UNSCEAR 1982 estimated effect of 1 rad per
generation of low dose or low dose rate, lowLET
radiation on a population of 10° liveborn
according to the doubling dose method
(Assumed doubling dose = 100 rad)
Disease classification Current incidence
Effect of 1 rad
per generation
Autosomal dominant and
xlinked diseases 10,000
Recessive diseases 2,500
Chromosomal diseases
Structural 400
Numerical 3,000
Congenital anomalies,
anomalies expressed later,
constitutional and
degenerative diseases 90,000
Total 105,900
First Generation Equilibrium
15 100
Slight slow increase
2.4
Probably very
small
4.5
22
45
149
Source: (UNSCEAR82).
G39

Table Gll. Summary of genetic risk estimates per 106 Hveborn for
an average population exposure of 1 rad of low dose or
low dose rate, lowLET radiation 1n a 30year generation
Source
Serious hereditary effects
First generation
Equilibrium
(all generations)
BEAR, 1956 (NAS72)
BEIRI, 1972 (NAS72)
UNSCEAR, 1972 (UNSCEAR72)
UNSCEAR, 1977 (UNSCEAR77)
ICRPTG, 1980 (Of80)
BEIR3, 1980 (NAS80)
UNSCEAR, 1982 (UNSCEAR82)
49a (12200)
9a (615)
63
89
19a (575)
22
500
300a (601500)
300
185
320
257a (601100)
149
Numbers In parentheses are the range of estimates.
aGeometr1c Mean 1s calculated by taking the square root of the product
of two numbers for which the mean is to be calculated. The cube root
of three numbers, etc. In general, It Is the Ntn root of the product
of N numbers for which the mean is to be calculated.
G40

It should be noted that the genetic risk estimates summarized in
Table Gll are for lowLET, low dose, and low dose rate Irradiation.
Much of the data were obtained from high dose rate studies, and most
authors have used a sexaveraged factor of 0.3 to correct for the change
from high dose rate, lowLET to low dose rate, lowLET exposure (NAS72,
80, UNSCEAR72, 77). However, factors of 0.5 to 0.1 have also been used
in estimates of specific types of genetic damage (UNSCEAR72,77,82).
G.5.3 Estimates of Genetic Harm for HighLET Radiations
Although genetic risk estimates are made for lowLET radiation, some
radioactive elements, deposited in the ovary or testis can irradiate the
germ cells with alpha particles. The ratio of the dose (rad) of lowLET
radiation to the dose of highLET radiation producing the same endpofnt
is called RBE and is a measure of the effectiveness of highLET compared
to lowLET radiation in causing the same specific endpoint.
Studies with the beta particle emitting isotopes carbon14 and
tritium yielded RBEs of 1.0 and 0.7 to about 2.0, respectively
{UNSCEAR82). At the present time, the RBE for genetic endpoints due to
beta particles is taken as one (UNSCEAR77.82).
Studies of the RBE for alphaemitting elements in germinal tissue
have used only plutonium239. Studies comparing cytogenetic endpoints
after chronic low dose rate gammma radiation exposure, or incorporation
of plutonium239 in the mouse testis, have yielded RBEs of 23 to 50 for
the type of genetic injury (reciprocal translocations) that might be
transmitted to liveborn offspring (NAS80, UNSCEAR77,82). However, an RBE
of 4 for plutonium239 compared to chronic lowLET radiation was reported
for specific locus mutations observed in neonate mice (NAS80). Neutron
RBE, determined from cytogenetic studies in mice, also ranges from about
4 to 50 (UNSCEAR82, Gr83a, Ga82). Most reports use an RBE of 20 to
convert risk estimates for low dose rate, lowLET radiation to risk
estimates for highLET radiation.
G.5.4 Uncertainty in Estimates of Radiogenetic Harm
Chromosomal damage and mutations have been demonstrated in cells In
culture, in plants, in insects, and 1n mammals (UNSCEAR72,77,82).
Chromosome studies in peripheral blood lymphocytes of persons exposed to
radiation have shown a doserelated increase in chromosome aberrations
(structural damage to chromosome) (UNSCEAR82). In a stucly of nuclear
dockyard workers exposed to external xradiation at rates of less than 5
rad per year, Evans, et al. (Ev79) found a significant increase in the
Incidence of chromosome aberrations. The increase appeared to have a
linear dependence on cumulative dose. In a stucjy of people working and
living in a high natural background area where there was both external
gammaradiation and internal alpharadiation, PohlRuling et al. (Po78)
G41

reported a complex dose response curve. For majnly gammaradiation
exposure (less than 10 percent alpha radiation)", they reported that the
increase in chromosome aberrations Increased linearly from 100 to 200
mrad per year then plateaued from 300 mrad to 2 rad per year. They
concluded:
"From these data, and data in the literature, it can be
concluded that the initial part of the doseeffect curve
for chromosome aberrations is not linear or sigmoid with
a threshold at the lowest dose, but rises sharply and
passes into a complex upward form with a kind of plateau
until it meets the linear curve of the high dose.
Although chromosomal damage in peripheral blood lymphocytes cannot
be used for predicting genetic risk in progeny of exposed persons, it
is believed by some to be a direct expression of the damage, analogous
to that Induced In germ cells, resulting from the radiation exposure.
It is at least evidence that chromosome damage can occur in vivo in
humans.
Although evidence from the genetic studies in Japan falls short of
providing statistically significant conclusions, all indicators support
the hypothesis that genetic damage resulted from the radiation exposure
(ScSJb, Sa82). While these data give rise to estimates of the doubling
dose (see below) and probabilities of mutation per locus per rad that
have large errors, there Is no reason to believe that they are biased,
and they are adequate to recommend the elimination of some previously
conjectured values. However, In the sources of numerical risk
estimates used in this document, human genetic risks following
radiation exposure are based on extrapolations from animal data. As
genetic studies proceeded, emphasis has shifted from Drosophlla (fruit
flies) to mammalian species in attempts to find an experimental system
which would reasonably project what might happen in humans.
For example, Van Buul (Va80) reported the slope (b) of the linear
regression, Y = a + bD, for Induction of reciprocal translations 1n
spermatogonia (one of the stages of sperm development) In various
species as follows:
~~~~: b x 104 + sd x 104
Rhesus monkey
Mouse
Rabbit
Guinea Pig
Marmoset
Human
0.86 + U.U4
1.29 + 0.02
1.48 ^0. 13
0.91 7 0.10
7.44 + 0.95
3.40 + 0.72
to 2.90 + 0.34
^~
These data indicate that animalbased estimates for this type of genetic
effect would be within a factor of 4 of the true human value. In this
case most of the animal results would underestimate the risk in humans.
G42

However, when risk estimates such as this are used in direct
estimation of risk for the first generation, the total uncertainty in the
estimate becomes indeterminate. Even if studies have been made in a
species which can predict the dose response and risk coefficient for a
specificradiation induced genetic damage, there is no certainty that it
predicts the response for all genetic damage of that type. In addition,
as shown in the example from the 1982 UNSCEAR report (UNSCEAR82) in
Section G.5.1, additional assumptions based on observations, usually in
other animal species, are used to adjust the risk coefficient to what is
expected for humans. The uncertainty in these extrapolations has not been
quantified.
A rough estimate of the uncertainty can be obtained by comparing
direct estimates of risk for the first generation with doublingdose
estimates in the 1977 UNSCEAR report (UNSCEAR77). The estimates differ by
a factor between 2 and 6 with the direct estimate usually smaller than the
doubling dose estimate.
A basic assumption in the doublingdose method of estimation is that
there is a proportionality between radiation induced and spontaneous
mutation rates. Some of the uncertainty was removed in the 1982 UNSCEAR
report with the observation that in two test systems (fruit flies and
bacteria), there is a proportionality between spontaneous and induced
mutation rates at a number of individual gene sites. There is still some
question as to whether the sites that have been examined are representa
tive of all sites and all gene loci or not. The doubling dose estimate
dose, however, seems better supported than the direct estimate.
While there is still some uncertainty as to what should be doubled,
future studies on genetic conditions and diseases can only increase the
total number of such conditions. Every report, from the 1972 BEIR and
1958 UNSCEAR reports to the most recent, has listed an increased number of
conditions and diseases which have a genetic component.
Observations on Human Populations
As noted earlier, the genetic risk estimates are based on interpreta
tion of animal experiments as applied to data on naturallyoccurring .
hereditary diseases and defects in man. A study of birth cohorts was
initiated in the Japanese Abomb survivors in mid1946. This resulted in
a detailed monograph by Neel and Schull (Ne56) which outlined the
background of the first study and made a detailed analysis of the findings
to January 1954 when the study terminated. The authors concluded "• • •
under circumstances where, on the basis of what is known concerning the
radiation genetics of mammals, it appears unlikely that conspicuous
genetic effects of the atomic bombs could be demonstrated, such effects
have in fact not been demonstrated. The present stucjy can in no way be
interpreted to mean that there were no mutations induced in the survivors
of the atomic blasts. Neither, on the other hand, is the reverse
interpretation  that of mutation production  permissible from this
series of observations • • •. We are left with inconclusive findings,
albeit findings which permit us to set confidence limits." (Ne56).
G43

Further, 1t appeared that 1t was improbable that human genes were so
sensitive that exposures as low as 3 R, or even 10 R, would double the
mutation rate. While this first stuc(y addressed a number of endpoints
such as : sex ratio, malformations, pre and perinatal mortality and
anthropometric data, subsequent studies have addressed these and other
endpoints. The most recent reports on this birth cohort of 70,082 persons
have attempted to estimate the minimum doubling dose for genetic effects
in humans (ScSla, Sa82).
Data on four endpoints have been reviewed for this birth cohort.
Frequency of stillbirths, major congenital defects, prenata1 death, and
frequency of death prior to age 17 have been examined in the entire
cohort. Frequency of cytogenetic aberrations (sex chromosome aneuploidy)
and frequency of biochemical variants (a variant enzyme or protein
electrophoresls pattern) have been measured on large subsets of this
cohort.
Although the updated data reported appear to suggest radiation
effects have occurred, the numbers are small and not statistically
significant. Overall, the estimated doubling dose for lowLET radiation
at high doses and dose rates for human genetic effects is about 156 rem
(ScSla) or 250 rem (Sa82). As noted above, animal studies indicate that
chronic exposures to lowLET radiation would be less hazardous by a factor
of 3 (NAS72, 80). This would increase the estimated doubling dose to 468
rem to 750 rem, respectively. These recent reports suggest the minimum
doubling dose for humans may be 4 to 7 times higher than those in Table
Gll (based on animal data). It would be premature to reach a firm
decision on the exact amount since these reports are based on the T65D
dosimetry in Japan (see Section G.2) which Is being revised. However, we
believe EPA estimates of genetic risks will prove to be very conservative
even when the dosimetry of Abomb survivors Is revised.
EPA is using the geometric mean of the BE1R3 range of doubling
doses, about 110 rad. The minimum doubling dose reported above 1s 4 to 7
times greater. It Is unlikely that dose estimates for Japanese survivors
will change by this much (RERF83, 84). Therefore, EPA believes the
estimate of a doubling of about 100 rad will continue to be a conservative
estimate.
Ranges of Estimates Provided by Various Models
EPA has continued to follow the recommendations of the 1980 BEIR3
committee and use a linear nonthreshold model for estimating genetic
effects. Although, as pointed out by the 1982 UNSCEAR committee, there
are a number of models other than linear (Y = c + ad), e.g., linear
quadratic (Y = c + bD + eDz), quadratic (Y = k + fD2), even power
function (Y = k + gDn)*. However, there are strong data to support the
*Y 1s yield of genetic effects; D is radiation dose; c, C, k, and K
are spontaneous incidence constants for genetic effects; and a, b, e, f,
g, and h are the rate constants for radiation induced genetic effects,
G44

hypothesis that mutations themselves are single, track events. That is,
the mutations follow a linear dose response function while the observed
mutation rate shows the influence of other factors, and may be nonlinear
(UNSCEAR82).
Most of the arguments for a nonlinear dose response have been based
on target theory (Le62) or microdosimetric site theory (Ke72). However,
other theories based on biology [e.g., enzyme inductionsaturation
(Go80,82), repairmisrepair (To80)] could also provide models that fit the
observed data. There is still much disagreement on which dose response
model is appropriate for estimating genetic effects in humans. Until
there is more consensus, the linear nonthreshold model appears to be a
prudent approach that will not underestimate the risks.
The agreement in estimates made on a linear nonthreshold model in
various reports is reasonably good. Even though the authors of the
reports used different animal models, interpreted them in different ways,
and had different estimates of the level of human genetic conditions in
the population, the range of risk coefficients is about an order of
magnitude (see Table Gll). For the most recent, more comparable
estimates, the range is a factor of 2 to 4 (see ICRPTG, BEIR3 and
UNSCEAR 1982 in Table Gll).
G.5.5 The EPA Genetic Risk Estimate
There is no compelling evidence for preferring any one set of the
genetic risk estimates listed in Table Gll. EPA has used the estimates
from BEIR3 (NAS80). These "indirect" estimates are calculated using the
normal prevalence of genetic defects and the dose that is considered to
double this risk. The WAS estimates which EPA uses are based on a
"doubling dose" range with a lower bound of 50 rem and an upper bound of
250 rem. We prefer these risk estimates to those made by the ICRP task
group (Of80), which used a "direct" estimate because the ICRPTG tabulation
combines "direct" estimates for some types of genetic damage with doubling
dose estimates for others. We also prefer the BEIR3 risk estimates to
the "direct" estimates of UNSCEAR 1982 which tabulates genetic risk
separately by the direct method and by the doubling dose method. The risk
estimated by the direct method does not include the same types of damage
estimated by doubling doses and was not considered further. Moreover, the
BEIR3 genetic risk estimates provide a better estimate of uncertainty
than the UNSCEAR 1982 and ICRPTG estimates because the BEIR3 Committee
assigned a range of uncertainty for multifactorial diseases (>5 percent to
<50 percent) which reflects the uncertainty in the numbers better than the
other estimates do (5 percent and 10 percent, respectively).
In developing the average mutation rate for the two sexes used in the
calculation of the relative mutation risk, the BEIR3 Committee postulated
that the induced mutation rate 1n females was about 40 percent of that in
males (NAS80). Recent studies by Dobson et al. suggest that the
assumption was invalid and that human oocytes should have a risk
equivalent to that of human spermatogonia. This would increase the risk
estimate obtained from doublingdose methods by a factor of 1.43 (Do83a,
Do83b, Do84a, Do84b).
G45

We recognize, however, that the use of the doublingdose concept does
assume that radiationInduced genetic damage' 1s 1n some way proportional
to "spontaneous" damage. As noted earlier, the recent evidence obtained
1n Insects (prosophila) and bacteria (E. coll) supports the hypothesis
that, with the exception of "hot spots'nr"for mutation, the radiation
induced mutation rate is proportional to the spontaneous rate (UNSCEAR82).
No proof that this is also true in mammals is available yet.
The BEIR3 estimates give a considerable range. To express the range
as a single estimate, the geometric mean of the range is used, a method
first recommended by UNSCEAR (UNSCEAR58) for purposes of calculating
genetic risk. The factor of 3 increase in risk for high dose rate,
lowLET radiation noted earlier is also used.
The question of RBE for highLET radiation 1s more difficult. As
noted above, estimated RBEs for plutonlum239 alphas versus chronic gamma
radiation for reciprocal translocations as determined by cytogenetic
analyses are between 23 and 50 (NAS80, UNSCEAR82). However, the observed
RBE for single locus mutations in developing offspring of male mice given
pluton1um239 compared to those given Xray irradiation is 4 (NAS80). The
average of RBEs for these reciprocal translocations for specific locus
mutations is 20.25. Since reported neutron RBEs are similar to those
listed above for plutonium239 alpha radiation, we use an RBE of 20 to
estimate genetic risks for all highLET radiations. This is consistent
with the RBE for highLET particles recommended for estimated genetic
risks associated with space flight (Gr83b).
Genetic risk estimates used by EPA for high and lowLET radiations
are listed 1n Table G12. As noted earlier, EPA uses the dose received
before age 30 in assessing genetic risks.
The EPA estimates in Table G12 are limited, like all other human
genetic risk estimates, by the lack of confirming evidence of genetic
effects in humans. These estimates depend on a presumed resemblance of
radiation effects in animals to those in humans. The magnitude of the
possible error is indeterminable. The study with the largest data base,
the Japanese Abomb survivors, appears, at best, to provide only an
estimate of the minimum doubling dose which calculates the maximum
estimate of genetic risk In man. However, doublingdose estimates are
also uncertain because the number of human disorders having a recognized
genetic component is constantly Increasing, and the type of genetic damage
implicated 1n a specific disorder may change. The combined uncertainties
in doubling dose estimates and the magnitude of genetic contributions to
various disorders probably introduce an overall uncertainty of about an
order of magnitude in the risk estimates. Moreover, the BEIR Committee in
deriving its estimate has assumed that almost all of the risk was due to
recessive mutations which would eventually be eliminated. To what extent
this occurs will depend on medical practices 1n the future. It 1s
possible, as our knowledge of medicine Improves, that recessive hereditary
defects will be carried on for many more generations than assumed by the
BEIR Committee.
G46

Table G12. Estimated frequency of genetic.disorders in a birth cohort
due to exposure of the parents to 1 rad per generation
Radiation
Serious Heritable Disorders
(Cases per 106 liveborn)
First Generation
low3 highb
All Generations
lowa high6
Low Dose Rate, LowLET
High Dose Rate, LowLET
HighLET
20
60
400
30
90
600
260
780
5200
370
1110
7400
aFemale sensitivity to induction of genetic effects is 40 percent as
great as that of males.
^Female sensitivity to induction of genetic effects is equal to that of
males.
The relative risk of highLET radiation compared to lowdoserate,
lowLET radiation (RBE) is also uncertain. The data are sparse, and
different studies often used different endpoints. In addition, the
microscopic dosimetry, i.e., the actual absorbed dose in the cells at
risk, is poorly known. However, the RBE estimate used by EPA should be
within a factor of 5 of the true RBE for highLET radiation.
G.5.6 Teratogenic Effects
Although human teratogenesis (congenital abnormalities or defects)
associated with xray exposure has a long history, the early literature
deals mostly with case reports. Stettner reported a case in 1921 (St21)
and Murphy and Goldstein studied a series of pregnancies in which 18 of
the children born to 76 irradiated mothers were microcephalic {Mu29,
Go29). However, the irradiation exposures were high.
In 1930, Murphy exposed some rats to Xrays at doses of 200 R to
1600 R. Thirtyfour of 120 exposed females had litters, and 5 of the
litters had animals with developmental defects (Mu30). He felt that this
stucly confirmed his clinical observations and earlier reports of animal
studies. Although there were additional studies of radiation induced
mammalian teratogenesis before 1950, the majority of the studies were
done/after that time (see Ru53 for a review), perhaps reflecting interest
in radiation hazards caused by the explosion of nuclear weapons in 1945
(Ja70).
G47

Much of the work done after World War II was done 1n mice (Ru50,
Ru54, Ru56) and rats (W154, H154). Early studfes, at relatively high
radiation exposures, 25 R and above, established sone dose response
relationships. More importantly, they established the time table of
sensitivity of the developing rodent embryo and fetus to radiation
effects (Ru54, Hi53, Se69, Hi66).
Rugh, in his review of radiation teratogenesls (Ru70) listed the
reported mammalian anomalies and the exposure causing them. The lowest
reported exposure was 12.5 R for structural defects and 1 R for
functional defects. He also suggested human exposure between ovulation
and about 7 weeks gestational age could lead to structural defects and
from about 6 weeks gestational age until birth could lead to functional
defects. In a later review (Ru71), he suggested structural defects in
the skeleton might be Induced as late as the 10th week of gestation and
functional defects as early as the 4th week. It should be noted that the
gestation period In mice is much shorter than that in humans and that
weeks of gestation referred to above are In terms of equivalent stages of
mousehuman development. Estimates of equivalent gestational age are not
very accurate.
In the reports of animal studies it appeared as if teratologic
effects, other than perhaps growth retardation, had a threshold for
induction of effects (Ru54, Ru53, W154). However, Ohzu (Oh65) showed
that doses as low as 5 R to preimplantation mouse embryos caused
Increased resorption of implanted embryos and structural abnormalities 1n
survivors. Then 1n 1970, Jacobsen (Ja70) reported a stucly In which mice
were exposed to 5, 20 or 100 R on the 8th day of pregnancy. He concluded
that the doseresponse function for Induction of skeletal effects was
linear, or nearly linear, with no observable threshold. This appears
consistent with a report by Russell (Ru57), which suggested a threshold
for some effects whereas others appeared linear.
Rugh (Ru71) suggested there may be no threshold for radiation
Induced congenital effects 1n the early human fetus. In the case of
microcephaly (small head size) and mental retardation, at least this may
be the case. For other teratogenic effects, the dose response 1n humans
1s unknown. In 1978, .Michel and FritzN1ggl1 (M178) reported Induction
of a significant Increase in growth retardation, eye and nervous system
abnormalities, and post implantation losses In mice exposed to 1 R. The
Increase was still greater 1f there was concurrent exposure to
radlosensitizing chemicals such as lodoacetlmide or tetracycllne (M178).
One of the problems with the teratologic studies 1n animals 1s the
difficulty of determining how dose response data should be interpreted.
Russell (Ru54) pointed out some aspects of the problem: 1) although
radiation Is absorbed throughout the embryo, It causes selective damage
which 1s consistently dependent on the stage of embryonic development at
G48

the time of irradiation, and 2) the damaged parts respond, in a consistent
manner, within a narrow time range. However, while low dose irradiation
at a certain stage of development produces changes only in components at
their peak sensitivity, higher doses may induce additional abnormalities
which have peak sensitivity at other stages of development, and may
further modify expression of the changes induced in parts of the embryo
at peak sensitivity during the time of irradiation. In the first case,
damage may be to primordial cells themselves, while in the second, the
damage may lead indirectly to the same or different endpoints.
The embry'o/fetus starts as a single fertilized egg and divides and
differentiates to produce the normal infant at term. (The embryonic
period, when organs develop, is the period from conception through 7
weeks gestational age. The fetal period, a time of in utero growth, is
the period from 8 weeks gestational age to birth.) THe different organ
and tissue primordia develop independently and at different rates.
However, they are in contact through chemical induction or evaporation
(Ar54). These chemical messages between cells are important in bringing
about orderly development and the correct timing and fitting together of
parts of organs or organisms. While radiation can disrupt this pattern,
interpretation of the response may be difficult. Since the cells in the
embryo/fetus differentiate, divide, and proliferate at different times
during gestation and at different rates, gestational times when cells of
specific organs or tissues reach maximum sensitivity to radiation are
different. Each embryo/fetus has a different timetable. In fact, each
half (left/right) of an embryo/fetus may have a slightly different
timetable.
In addition, there is a continuum of variation from the hypothetical
normal to the extreme deviant, which is obviously recognizable. There is
no logical place to draw a line of separation between normal and
abnormal. The distinction between minor variations of normal and frank
malformation, therefore, is an arbitrary one, and each investigator must
establish his own criteria and apply them to spontaneous and induced
abnormalities alike (HWC73). For example, some classify mental
retardation as IQ 80 or lower, some classify on ability to converse or
hold a job, some on the basis of the need to be institutionalized.
Because of the problems in interpretation listed above, it appears a
pragmatic approach is useful. The dose response should be given as the
simplest function that fits the data, often linear or linear with a
threshold. No attempt should be made to develop complex doseresponse
models unless the evidence is unequivocal.
The first report of congenital abnormalities in children exposed
in utero to radiation from atomic bombs was that of Plummer (P152). In
tFis selected group, twelve children with microcephaly of which 10 also
had mental retardation had been identified in Hiroshima in the in utero
exposed survivors. They were found as part of a program started in 1950
to stucjy children exposed in the first trimester of gestation. In 1955
the program was expanded to include all survivors exposed in utero.
G49

Studies initiated during the program have shown radiation related
1) growth retardation; 2) increased microcephaly; 3) increased mortality,
especially infant mortality; 4) temporary suppression of antibody
production against influenza; and 5) increased frequency of chromosomal
aberrations in peripheral lymphocytes (Ka73).
Although there have been a number of studies of Japanese Abomb
survivors, including one showing a dose and gestational age related
increase in postnatal mortality (Ka73), only incidence of microcephaly
and mental retardation have been investigated to any great extent. In
the most recent report, Otake and Schull (Ot83) showed that mental
retardation was associated with exposure between 8 and 15 weeks of
gestation (10 to 17 weeks of gestation if counted from the last menstrual
period). They further found a linear doseresponse relationship for
induction of mental retardation that had a slope yielding a tentative
estimate of doubling dose for mental retardation of about 2 rad, fetal
absorbed dose (Ot83). Classification as mentally retarded was based on
"unable to perform simple calculations, to care for himself or herself,
or 1f he or she was completely unmanageable or had been
institutionalized" (Ot83).
Estimates of the risk of mental retardation for a rad of
embryo/fetus exposure in the U.S. population can be derived by three
methods. The first and easiest method is to use the absolute risk
calculated by Otake and Schull for the Japanese survivors (Ot84). A
second method 1s to use the doubling dose calculated by Otake and Schull
(Ot83) times the incidence of mental retardation per 103 live births.
Unfortunately, a number of assumptions must be made to establish the
incidence of mental retardation per 103 live births. Mental
retardation may be classified as mild (IQ 5070), moderate (IQ 3549),
severe (IQ 2034) and profound (IQ <20) (WH075). However, some
investigators use only mild mental retardation (IQ 5070) and severe
mental retardation (IQ <50) as classes (Ha81, St84). Mental retardation
1s not usually diagnosed at birth but at some later time, often at school
age. Since the mental retardation may have been caused before or during
gestation, at the time of birth, or at some time after birth, that
fraction caused before or during gestation must be estimated. In like
manner since mental retardation caused before birth may be due to genetic
conditions, Infections, physiologic conditions, etc., the fraction
related to unknown causes during gestation must be estimated. This Is
the fraction that might possibly be doubled by radiation exposure.
A third method to estimate the risk Is Indirectly using the
relationship of microcephaly and mental retardation reported in the
Japanese survivors (Wo65, Ot83). If head size is assumed to be normally
G50

distributed, then the fraction of the population with a head size 2 or 3
standard deviations smaller than average can be "obtained from statistical
tables. The fraction of 103 liveborn with microcephaly multiplied by
the proportion of mental retardation associated with that head size
yields an estimate of the incidence of mental retardation per 10^ live
births, which can then be used with the doubling dose to estimate the
risk as described above.
Risk estimates for mental retardation are derived below for
comparison purposes using each of the three methods described above.
A.
Estimate of Incidence Per Rad Based on Direct Application of the
Slope of the Japanese Data " '•
Otake and Schull (Ot84) gave an estimate of 'The Relationship of
Mental Retardation to Absorbed Fetal Exposure in the "Sensitive" Period
When All "Controls" are Combined.1 The estimate of 0.416 cases of mental
retardation per 100 rad could be directly applicable to a U.S.
population. In this case the risk estimate would be about:
4 cases of mental retardation per rad per 1000 live births.
B Estimate of Incidence Per Rad Based on the Doubling Dose
The Otake and Schull report (Ot83) suggested the doubling dose for
mental retardation was about 2 rad fetal absorbed dose or about a 50
percent increase in mental retardation per rad. It would seem reasonable
that this doubling dose would apply only to ideopathic cases of mental
retardation caused during gestation. That is, those which have no known
genetic, viral, bacterial, etc., cause.
Data from studies of the prevalence of mental retardation in school
age populations in developed countries suggest a prevalence of
2.8 cases/1000 (Uppsala County, Sweden) to 7.4 cases/1000 (Amsterdam,
Holland) of severe mental retardation, with a mean of about 4.3 + 1.3
cases/1000 (St84). Where data are available for males and females
separately, the male rate is about 30 percent higher than the female rate
(St84). Historically, the prevalence of mild mental retardation has been
6 to 10 times greater than that of severe mental retardation. But in
recent Swedish studies, the rates of prevalence of mild and severe mental
retardation have been similar (St84). This was suggested to be due to a
decline in the "culturalfamilial syndrome." That is, improved
nutrition, decline in infection and diseases of childhood, increased
social and intellectual stimulation, etc., combined to reduce the
proportion of• nonorganic mental retardation and, therefore, the
prevalence of mild mental retardation (St84).
i
In studies of the causes of mental retardation, 23 percent to 42
percent of the mental retardation has no identified cause (Gu77, Ha81,
St84). It is this portion of the mental retardation which may be
651

susceptible to Increase from radiation exposure of the embryo/fetus.
In that case, the prevalence of Ideopathic mental retardation would.be
0.6 to 3.1 cases per 1000 of severe mental retardation and perhaps an
equal number of cases of mild mental retardation.
For purposes of estimating the effects of radiation exposure of the
embryo/fetus, a risk of spontaneous idoopathic mental retardation of 1 to
6 per 1000 will be used. If this spontaneous ideopathic mental
retardation can be increased by radiation the estimate would be:
(1 to 6 cases per 1000 live births){0.5 Increase per rad)
or about 0.5 to 3 cases of mental retardation per rad per 1000 live
births.
This estimate may be biased low because mental retardation induced
during gestation is often associated with high childhood death rate
(St84). If this is generally true for ideopathic causes of mental
retardation, It would cause an underestimation of the risk.
C. Estimate of Incidence Per Rad Based on Incidence of Microcephaly
1) Of live born children, 2.275 percent will have a head
circumference 2 standard deviations or more smaller than average, 0.621
percent will have a head circumference 2.5 standard deviations or more
smaller than average, and 0.135 percent will have a head circumference 3
standard deviations or more smaller than average (statistical estimate
based on a normal distribution).
2) There is evidence 1n a nonselected group of 9,379 children that
mental retardation can be estimated using incidence of microcephaly, even
though head circumference In the absence of other supporting data, e.g.,
height or proportion, Is an uncertain indicator of mental retardation.
Based on a study of 9,379 children, Nelson and Deutschberger (Ne70)
concluded that about half of the children with a head circumference 2.5
standard deviations or more smaller than average had IQs of 79 or lower.
Since 0.67 percent of those studied were in this group, the observed
number is about what would be expected based on the normal distribution
of head size in a population, 0.62 percent. The estimated incidence of
mental retardation per live birth in a population would be:
(6.7 cases of microcephaly per 1000 live births) x
0.5
cases of mental retardation
case of microcephaly
or about 3.4 cases of mental retardation per 1000 live births.
G52

3) A first approximation of risk of mental retardation might then be
(3.4 cases of mental retardation per 1000 live births)
(0.5 increase per rad)
or about 2 cases of mental retardation per 1000 live births per rad.
Both microcephaly and mental retardation were increased in Japanese
survivors (Wo65, Wo66). However, the relationship of mental retardation
to microcephaly in Japanese Abomb survivor data is not1 clear. Estimates
range from about half of those with head sizes 2 or more standard
deviations smaller than average having mental retardation (RERF78), a
result similar to that observed by Nelson and Deutschberger (Ne70), to
about ten percent of those with small head size having mental retardation
(Wo66). Therefore, the above estimate based on the incidence of
microcephaly in a population should be a reasonable estimate of the risk
from radiation.
Summary of the Calculated Risk of Mental Retardation
The risk of increased mental retardation per rad of embryo/fetus
exposure during the 8 to 15week gestational period estimated above
ranges from about 5 x 10~4 to 4 x 10~3 cases per live birth, the
largest being a direct estimate. The geometric mean of these estimates^is
1.4 x 10~3; the arithmetic mean is 2.4 x 10"3 cases per live birth.
All the estimates derived above by any of the three methods are in
the same range as an earlier UNSCEAR (UNSCEAR77) estimate of an increase
of 1 x 10'3 cases of mental retardation per rad per live birth. The
UNSCEAR estimate, however, did not consider gestational age at the time of
exposure. The Otake and Schull report (Ot83) did address gestational age
and estimated a higher risk, but a narrower window of susceptibility.
If the estimates are applicable, the 15 mrad of lowLET background
radiation delivered during the 8 to 15week gestational agesensitive
period could, induce a risk of 6 x 10'5 to 7.5 x 10'° cases of mental
retardation per live birth. This can be compared to an estimate of a
spontaneous occurrence of 1.5 x 10"z to 3.4 x 10~3 cases of mental
retardation per live birth.
Japanese Abomb survivors exposed in utero also showed a number of
structural abnormalities and, particularly in those who were
microcephalic, retarded growth (Wo65). No estimate has been made of the
radiationrelated incidence or doseresponse relationships for these
abnormalities. However, UNSCEAR (UNSCEAR77) made a very tentative
estimate based on animal studies that the increased Incidence of ;
structural abnormalities in animals may be 5 x 10~3 cases per R per live
born, but stated that projection to humans was unwarranted. In any event,
the available human data cannot show whether the risk estimates derived
from high dose animal data overestimates the risk in humans.
G53

It should be noted that all of the above estimates are based on high
dose rate lowLET exposure. UNSCEAR 1n 1977 also Investigated the
doserate question and stated:
"In conclusion, the majority of the data available for
most species indicate a decrease of the cellular and
malformature effects by lowering the dose rate or by
fractionating the dose. However, deviations from this
trend have been well documented in a few instances and
are not inconsistent with the knowledge about
mechanisms of the teratogenic effects. It is therefore
Impossible to assume that dose rate and fractlonatlon
factors have the same Influence on all teratological
effects." (UNSCEAR77).
From this analysis, EPA has concluded that a range of risk is
4 x 103 to 5 x 10"* cases of mental retardation per live birth per
rad of lowLET radiation delivered between weeks 8 and 15 of gestation
with no threshold Identified at this time.
No attempt can be made now to estimate total teratogenic effects.
However, It should be noted that the 1977 UNSCEAR estimate from animals
was 5 x 10~3 cases of structural abnormalities per R per live birth
(about the same number per rad of lowLET). This estimate must be viewed
as a minimum one since it Is based, to a large extent, on observation of
grossly visible malformations. Differences 1n criteria for identifying
malformations have compounded the problem, and questions of threshold and
species differences have made risk projection to humans unwarranted.
G.5.7 Nonstochastic Effects
Nonstochastlc effects, those effects that Increase 1n severity with
increasing dose and may have a threshold, have been reviewed in the 1982
UNSCEAR report (UNSCEAR82). In general, acute doses of 10 rad lowLET
radiation and higher are required to Induce these effects. It 1s
possible that some of the observed effects of ^ utero exposure are
nonstochastlc, e.g., the risk of embryonic loss, estimated to be 10'z
per R (UNSCEAR77), following radiation exposure soon after fertilization.
However, there are no data to address the question. Usually, no
nonstochastic effects of radiation are expected at environmental levels
of radiation exposure.
G.6 Radiation Risk  A Perspective
To provide a perspective on the risk of fatal radiogenic cancers and
the hereditary damage due to radiation, we have calculated the risk from
background radiation to the U.S. population using the risk coefficients
presented In this chapter and the computer codes described In Appendix H.
G54

The risk resulting from background radiation is
the risks caused by releases of radionuclides.
auto accidents, and other measures of common ri
from background radiation are neither voluntary
abuse. The risk caused by background radiation
unavoidable; therefore, it is a good benchmark
risks from radionuclide releases. Moreover, to
estimated risk of radionuclides is biased, the
risk estimates for background radiation.
a useful perspective for
"Unlike cigarette smoking,
sks, the risks resulting
nor the result of alcohol
is very largely
for judging the estimated
the degree that the
same bias is present in the
LowLET background radiation has three major components: cosmic
radiation, which averages to about 28 mrad per year in the U.S.:
terrestrial sources, such as radium in soil, which contributes an average
of 26 mrad per year (NCRP75); and the lowLET dose resulting from internal
emitters. The last differs between organs, to some extent, but for soft
tissues is about 24 mrad per year (NCRP75). Fallout from nuclear weapons
tests, naturally occurring radioactive materials in buildings, etc.,
contributes about another 10 mrem for a total lowLET wholebody dose of
about 90 mrad per year. The lung and bone receive somewhat larger doses
due to highLET radiations; see below. Although extremes do occur, the
distribution of this background annual dose to the U.S. population is
relatively narrow. A population weighted analysis indicates that 80
percent of the U.S. population would receive annual doses that are between
75 mrad per year and 115 millrad per year (EPA81).
As outlined in Section G.2, the BEIR3 linear models yield, for
lifetime exposure to lowLET radiation, an average lifetime risk of fatal
radiogenic cancer of 280 per 106 person rad. Note that this average is
for a group having the age and sexspecific mortality rates of the 1970
U.S. population. We can use this datum to calculate the average lifetime
risk due to lowLET background radiation as follows. The average duration
of exposure in this group is 70.7 years and at 9 x 10~2 rad per year, the
average lifetime dose is 6.36 rad.
this group is:
The risk of fatal cancer per person in
280 fatalities x 6.36 rem = 1.78 x 103
106 person rad ,
or about 0.18 percent of all deaths. The vital statistics we use in our
radiation risk analyses indicate that the probability of trying from
cancer in the United States from all causes is about 0.16, i.e.,
16 percent. Thus, the 0.18 percent result for the BEIR3 linear dose
response model indicates that about 1 percent of all U.S. cancer is due
to lowLET background radiation. The BEIR3 linear quadratic model
indicates that about 0.07 percent of all deaths are due to lowLET
background radiation or about 0.4 percent of all cancer deaths.
G55

Table G6 Indicates a risk of 460 fatalities per 106 organ rad for
alpha emitters 1n lung tissue. The lifetime cancer from this exposure is:
460 fatalities v 0,03 rad
— £  x  x
10° organ rad
, _ no 1A
.7years * 0.98 x 10
3
This is twice the risk due to lowLET background radiation calculated by
means of the BEIR3 linear quadratic model and more than half of the risk
calculated by means of the BEIR3 linear model.
The 1982 UNSCEAR report Indicates that the average annual dose to the
endosteal surfaces of bone due to naturallyoccurring highLET alpha
radiation is about 6 mrad per year or, for a quality factor 20, 120 mrem
per year (UNSCEAR82). Table G6 indicates that the lifetime risk of fatal
bone cancer due to this portion of the naturally occurring radiation
background is:
20 cases „ .0.006 rad
105 person rad *ear
x 70.7 years = 8.5 x 10
6
The spontaneous incidence of serious congenital and genetic
abnormalities has been estimated to be about 105,000 per 10° live
births, about 10.5 percent of live births {NAS80, UNSCEAR82). The lowLET
background radiation dose of about 90 mrad/year in soft tissue results 1n
a genetically significant dose of 2.7 rad during the 30year reproductive
generation. Since this dose would have occurred 1n a large number of
generations, the genetic effects of the radiation exposure are thought to
be an equilibrium level of expression. Since genetic risk estimates vary
by a factor of 20 or more, EPA uses a log mean of this range to obtain an
average value for estimating genetic risk. Based on this average value,
the background radiation causes 700 to 1000 genetic effects per 106 live
births, depending on whether or not the oocyte is as sensitive to
radiation as the spermatogonla (see Section G.5). This result Indicates
that about 0.67 percent to 0.95 percent of the current spontaneous
incidence of serious congenital and genetic abnormalities may be due to
the lowLET background radiation.
G56

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G66
.f

APPENDIX H: A DESCRIPTION OF THE RADRISK AND CAIRO COMPUTER CODES
USED BY EPA IN ASSESSING DOSES AND RISKS FROM RADIATION EXPOSURE
H.I Introduction
This appendix provides a brief overview of the RADRISK (Du80) and
CAIRD (Co78) computer codes used by the Environmental Protection Agency
to assess the health risk from radiation exposures. It describes how
the basic dose calculations are performed and describes the mechanics
of the life table implementation of the risk estimates derived 1n
Appendix G.
H.2 Overview of the EPA Analysis
RADRISK, the computer code used to calculate dose and risk (Du84,
Su81, Du80), calculates the radiation dose and risk resulting from an
annual unit intake of a given radionuclide or the risk resulting from
external exposure to a unit concentration of radionuclide 1n air or on
ground surface. Since both dose and risk models are linear, the unit
dose and risk results can then be scaled to reflect the exposure
associated with a specific source.
As outlined in Appendix F, estimates of the annual dose rate to
organs and tissues ,of interest are calculated by using, primarily,
models recommended by the International Commission on Radiological
Protection (ICRP79, ICRP80). Because EPA usually considers lifetime
exposures to a general population, these dose rates are used in
conjunction with a life table analysis of the increased risk of cancer
resulting from radiation (Co78). This analysis, described below, takes
account of competing risks and the age of the population at risk.
H.3 Dose Rates from Internal Exposures
Internal exposures occur when radioactive material 1s Inhaled or
Ingested. The RADRISK code Implements contemporary dosimetric models
to estimate the dose rates at various times to specified reference
organs in the botty from inhaled or Ingested radionuclides. The
dosimetric methods in RADRISK are adapted from those of the INREMII
code (K178) which is based on models recommended by the International
Commission on Radiological Protection UCRP79). The principal
qualitative difference is that RADRISK computes dose rates to specified
organs separately for high and low linear energy transfer (LET)
radiations, while INREMII calculates the committed dose equivalent to
specified organs. The timedependent dose rates are used in the life
table calculations of RADRISK.
Hl

In RADRISK, the direct Intake of each radionuclide 1s treated
separately. For decay chains, the Ingrowth an3 ctynamics of decay
products (daughters) 1n the bccty after Intake of a parent radtonucllde
are considered explicitly 1n the calculation of dose rate. The decay
product contributions to the dose rate are Included In the dose
calculations, based on the metabolic properties of the element and the
organ in which they occur.
The dose rate Df(X,t) to target organ X at time t due to
radionuclide 1 (l

experts. In almost all cases, doses to soft tissues calculated on this
basis differ only slightly, if at all, from ICRP80 dose estimates, but
the difference is large for some radlonuclides when the parent is
Incorporated into bone, as In lead210. For this radionuclide the
ICRP80 model has been used without any modifications.
A schematic representation of radioactivity movement in the boc[y
is shown in Appendix F. Except for radon daughters, which are
considered separately, inhaled activity is assumed to be originally
deposited in the lungs (distributed among the nasopharyngeal,
tracheobronchial, and pulmonary regions), and ingested activity is
originally deposited in the stomach. From the lungs, activity may be
absorbed by the bloodstream or migrate to the stomach. Activity in the
stomach may proceed through the small intestine, upper large intestine,
and lower large intestine; activity may be absorbed by the bloodstream
from any of these four segments, although only absorption from the
small intestine is considered in this stuoV
The activity, A^ft), of radionuclide i in organ k may be divided
among several "pools or "compartments," denoted here by the subscript p,
Each differential equation describing the rate of change of activity
within a compartment is a special case of the equation:
A,
ipk
11
£ Bu
pal,..., p^
(H3)
where
xipk
cipk
Pik
= activity of radionuclide i in compartment p of organ k,
= number of exponential terms in the retention function for
radionuclide i in organ k,
s branching ratio of radionuclide j to nuclide i,
« rate coefficient (time'M for radiological decay of
radionuclide i,
= rate coefficient (time'*) for biological removal of
radionuclide i from compartment p of organ k,
= fractional coefficient for radionuclide 1 in the pth
compartment of organ k,
= inflow rate of radionuclide i into organ k.
H3

If the Inflow rate P^ remains constant, the equations may be
solved explicitly for Aik(t) as described by Kfllough, Dunning, and
Pleasant (Ki78). In many cases the Inflow into a compartment will not
be a constant rate over a long period of time. To handle this problem,
the time interval over which solution of the activity equation 1s
desired (e.g., 110 years) is divided into 1year subintervals. The
inflow rate on each subintorval is then taken to be that constant value
which would yield the total activity flowing out of the preceding
compartment(s) during the same subinterval.
The model used in RADRISK for particulate deposition and retention
in the respiratory tract is the ICRP task group lung model (Mo66,
ICRP72). In this model, shown in Appendix F, there are four major
regions: the nasopharyngeal, tracheobronchial, pulmonary, and
lymphatic tissues. A fraction of the inhaled activity is Initially
deposited in each of the nasopharyngeal, tracheobronchial, and
pulmonary regions. The material is then cleared (removed) from the
lung to the blood and the gastrointestinal tract, also as shown in
Appendix F. Deposition and clearance of inspired partlculates in the
lung are controlled by the particle size and solubility classification.
The size distribution of the particles is specified by the activity
median aerocjynamic diameter (AMAD); where no AMAD is known, a value of
1.0 micron is assumed. The model employs three solubility classes,
based on the chemical properties of the radionuclide; classes D, W, and
Y correspond to rapid (days), intermediate (weeks), and slow (years)
clearance, respectively, of material deposited in the respiratory
passages. Inhaled nonreactive, I.e., noble, gases are handled as a
special case.
Movement of activity through the gastrointestinal (GI) tract is
simulated with a catenary model, consisting of four segments: stomach,
small intestine, upper large intestine, and lower large intestine.
Exponential outflow of activity from each segment into the next or out
of the system Is assumed. Outflow rate constants are calculated from
the transit times of Eve (Ev66). Although absorption may occur from
any combination of the four segments, only activity absorbed into the
blood.from the small Intestine is normally considered; the fractional
absorption from the small intestine into the blood is traditionally
denoted fj.
Activity absorbed by the blood from the GI or respiratory tract is
assumed to be distributed immediately to systemic organs. The
distribution of activity to these organs is specified by fractional
uptake coefficients. The list of organs 1n which activity 1s explicitly
H4

distributed (termed source organs) is elementdependent, and may
include such organs as bone or liver where sufficient metabolic data
are available. This 11st is complemented by an additional source
region denoted as OTHER, which accounts for that systemic activity not
distributed among the explicit source organs; uniform distribution of
this remaining activity within OTHER is assumed.
Radioactive material that enters an organ may be removed by both
radioactive decay and biological removal processes. For each source
organ, the fraction of the initial activity remaining at any time after
intake is described by a retention function consisting of one or more
exponentially decaying terms.
The metabolic models and parameters employed in the present stucty
have been described by Sullivan et al. (Su81). In most cases, the
models are similar or identical to those recently recommended by the
ICRP (ICRP79, ICRP80, 1CRP81). However, some differences in model
parameters do exist for some radionuclides (Su81). In particular,
parameter values that are thought to be more representative of
metabolism following lowlevel environmental exposures, rather than
occupational exposures, have been used In this analysis [e.g., fi=0.2
for uranium In the environment (ICRP79, NAS83)]. For transuranic
isotopes, metabolic parameters from EPA77, related comments from EPA78
and from the National Radiological Protection Board (Ha82),.have been
used rather than those from ICRP80. These parameters are listed In
Table Hl.
The EPA values were recommended by U.S. experts on transuranic
element metabolism at Battelle Pacific Northwest Laboratory (EPA78).
The recentlyadopted National Radiation Protection Board fj values
for transuranics in the general environment are closer to the values
proposed by EPA In 1977 than those currently advocated by ICRP for
occupational exposures. The larger f$ values will increase the
estimated dose and risk from ingestion of transuranic materials but
have little effect on doses following inhalation.
H.4 Dose Rates from External Exposures
Because of the penetrating nature of photons, radioactivity need
not be taken Into the body to deliver a dose to bocjy organs. Energy
absorbed from photons emitted by radionuclides in the air or on the
ground surface may also contribute to the overall risk. Natural
background radiation 1s an example of an important external exposure,
ordinarily contributing the largest component of dose to people.
H5

TABLE Hl:
Small intestine to blood
elements
Element
Isotope
Plutonium238 and 241
Oxide form
Nonoxide form
Bio. inc.*3)
Plutonium239 and 240
Oxide form
Nonoxide form
Bio. inc.
Americium
Oxide form
Nonoxide form
Bio. inc.
Curium
Oxide form
Nonoxide form
Bio. inc.
Neptunium
transfer
EPA
Child
012 mo
102
102
5x102
103
102
5x102
102
102
5x102
102
5x102

fractions,
Adult
>12 mo
lO3
103
5xlO3
104
103
5x103
lO3
ID'3
5x103
103
ID'3
5x103
ID'3
fit for
Adult
5x104
5x104
!05
5x104
5x104
5x104
5x104
5x104
5x104
5x104
5x104
103
transuranic
NRPB
Chil
012 mo
5x104
5x103
5x103
5x104
5x103
5x103
5x103
5x103
5x103
5x103
5x103
5x103
5x103
d
03 mo
102
102
103(b)
102
lO2
102
102
102
102
102
102
102
aBioiogically Incorporated form.
e form.
Source: EPA77, EPA78, Ha82.
NRPB: National Radiological Protection Board,
H6

Organ dose rates to an individual immersed in contaminated air or
standing 'on a contaminated ground surface are computed by Kocher's
DOSFACTER computer code (Ko81). These calculations assume that the
radionuclide concentration 1s uniform throughout an infinite volume of
air or area of ground surface, and that the exposed individual Is
standing on the ground surface. Only photons penetrate the body
sufficiently to deliver a significant dose to internal organs, and only
doses from photon radiation are considered in this analysis. Beta
radiation is far less penetrating and delivers a dose only to the bo

The photon dose rate factor Djz (X) to organ X of an Individual at
a distance z above a unit concentration contaminated ground surface may be
computed as:
0}z (X) = O.ScK £ fj Ej[(M/p)t]n
exp(uanr) dr[Can/(6anl)]
(H5)
where
K
pm
Man
z
= 1.0 s particlematerial correction factor,
s mass attenuation coefficient for the ntn discrete proton,
= height of reference position above ground surface (taken
to be 1 meter 1n this study).
c = unit conversion proportionality constant.
The coefficients Can and Dan are functions of the photon energy.
For detailed discussion of the derivation of these equations and a
tabulation of dose rate factors for various radionuclides, see Kocher
(Ko79, Ko81).
In the analysis here, the dose rate factors described by these
equations are scaled to achieve a continuous exposure of 1 pC1/cm3 for
air immersion and 1 pCi/cm* for ground surface exposure. Risk estimates
for these exposure pathways are based on continuous lifetime exposure to
these levels.
H.5 Life Table Analysis to Estimate the Risk of Excess Cancer
Radiation effects can be classified as stochastic or nonstochastic
(NAS80, ICRP77). For stochastic effects, the probability of occurrence
of the effect, as opposed to the severity, is a function of dose;
induction of cancer, for example, is considered a stochastic effect.
Nonstochastic effects are those health effects for which the severity
of the effect is a function of dose; examples of nonstochastic effects
Include cell killing, suppression of cell division, cataracts, and
nonmalignant skin damage.
H8

At the low levels of radiation exposure attributed to
radionuclldes 1n the environment, the principal health detriment 1s the
Induction of cancers (solid tumors and leukemia), and the expression,
in later generations, of genetic effects. In order to estimate these
effects, instantaneous dose rates for each organ at specified times are
sent to a subroutine adaptation of CAIRD (Co78) contained in the
RADRISK code. This subroutine uses annual doses derived from the
transmitted dose rates to estimate the number of incremental fatalities
in the cohort due to radiationinduced cancer in the reference organ.
The calculation of Incremental fatalities is based on estimated annual
incremental risks, computed from annual doses to the organ, together
with radiation risk factors such as those given in the 1980 MAS report
BEIR3 (NAS80). Derivation of the risk factors in current use is
discussed in Appendix G.
An important feature of this methodology is the use of actuarial
life tables to account for the time dependence of the radiation insult
and to allow for competing risks of death in the estimation of risk due
to radiation exposure. A life table consists of data describing
agespecific mortality rates from all causes of death for a given
population. This information is derived from data obtained on actual
mortality rates in a real population; mortality data for the U.S.
population during the years 19691971 (HEW75) are used throughout this
study.
The use of life tables in studies of risk due to lowlevel
radiation exposure is important because of the time delay inherent in
radiation risk. After a radiation dose is received, there is a minimum
Induction period of several years (latency period) before a cancer is
clinically observed. Following the latency period, the probability of
occurrence of a cancer during a given year 1s assumed to be constant
for a specified period, called a plateau period. The length of both
the latency and plateau periods depends upon the type of cancer.
During or after radiation exposure, a potential cancer victim may
experience years of life in which he is continually exposed to risk of
death from causes other than incremental radiation exposure. Hence,
some individuals in the population will die from competing causes of
death, and are not potential victims of incremental radiationinduced
cancer.
Each member of the hypothetical cohort is assumed to be exposed
to a specified activity of a given radionuclide. In this analysis
each member of the cohort annually inhales or ingests 1 pCi of the
radionuclide, or Is exposed to a constant external concentration of
in air or 1 pd/cm* on ground surfaces. Since the models
H9

used 1n RADRISK are linear, these results may be scaled to evaluate
other exposure conditions. The cohort consists" of an Initial
population of 100,000 persons, all of whom are simultaneously
llveborn. In the scenario employed here, the radiation exposure 1s
assumed to begin at birth and continue throughout the entire lifetime
of each Individual.
No member of the cohort lives more than 110 years. The span from
0 to 110 years is divided into nine age intervals, and dose rates to
specified organs at the midpoints of the age intervals are used as
estimates of the annual dose during the age Interval, For a given
organ, the incremental probability of death due to radiationinduced
cancer is estimated for each year using radiation risk factors and the
calculated doses during that year and relevant preceding years. The
incremental probabilities of death are used in conjunction with the
actuarial life tables to estimate the incremental number of radiation
induced deaths each year.
The estimation of the number of premature deaths proceeds in the
following manner. At the beginning of each year, m, there is a
probability PN of dying during that year from nonradiological causes,
as calculated from the life table data, and an estimated incremental
probability PK of dying during that year due to radiationinduced
cancer of the given organ. In general, for the mth year, the
calculations are:
= total number of deaths in cohort during year m,
= CPN(m) + pR(m)] x N(m)
= incremental number of deaths during year m due to
radiationinduced cancer of a given organ,
= PR(m) x
M(m)
Q(m)
N(m+l) = number of survivors at the beginning of year m + 1
= N(m)  M(m)
(NtlMOO.OOO).
PR Is assumed to be small relative to PN, an assumption which is
reasonable only for lowlevel exposures (Bu81), such as those
considered here. The total number of incremental deaths for the cohort
Is then obtained by summing Q(nO over all organs for 110 years.
In addition to providing an estimate of the incremental number of
deaths, the life table methodology can be used to estimate the total
number of years of life lost to those (tying of radiationinduced
cancer, the average number of years of life lost per Incremental
mortality, and the decrease In the population's life expectancy. The
total number of years of life lost to those (tying of radiationInduced
H10

cancer is .computed as the difference between the total number of years
of life lived by the cohort assuming no Incremental radiation risk, and
the total number of years of life lived by the same cohort assuming the
incremental risk from radiation. The decrease in the population's life
expectancy can be calculated as the total years of life lost divided by
the original cohort size (N(l)=100,000).
Either absolute or relative risk factors can be used. Absolute
risk factors, given in terms of deaths per unit dose, are based on the
assumption that there is some absolute number of deaths in a population
•exposed at a given age per unit of dose. Relative risk factors, the
percentage increase in the ambient cancer death rate per unit dose, are
based on the assumption that the annual rate of radiationinduced
excess cancer deaths, due to a spec.ific type of cancer, is proportional
to the ambient rate of occurrence of fatal cancers of that type.
Either the absolute or the relative risk factor is assumed to apply
uniformly during a plateau period, beginning at the end of the latent
period.
The estimates of incremental deaths in the cohort from chronic
exposure are identically those which are obtained if a corresponding
stationary population (i.e., a population in which equal numbers of
persons are born and die in each year) is subjected to an acute
radiation dose of the same magnitude. Since the total persons years
lived by the cohort in this stucty is approximately 7.07 million, the
estimates of incremental mortality in the cohort from chronic
irradiation also apply to a one year dose of the same magnitude to a
population of this size, age distribution, and agespecific mortality
rates. More precise life table estimates for a specific population can
be obtained by altering the structure of the cohort to reflect the age
distribution of a particular population at risk.
H.6 Risk Analysis Methodology
Risk estimates in current use at EPA are based on the 1980 report
(BEIR3) of the National Academy of Sciences Advisory Committee on the
Biological Effects of Ionizing Radiation (NAS80). The form of these
risk estimates is, to some extent, dictated by practical considerations,
e.g., a desire to limit the number of cases which must be processed for
each environmental analysis and a need to conform to limitations of the
computer codes in use. For example, rather than analyze male and
female populations separately, the risk estimates have been merged for
use with the general population; rather than perform both an absolute
and a relative risk calculation, average values have been used.
The derivation of the risk estimates from the BEIR3 report is
presented in Appendix G. A brief outline of the general procedure is
summarized below. Tables referenced from Chapter V of NAS80 are
designated by a V prefix.
Hll

(1) The total number of premature cancer fatalities from lifetime
exposure to 1 rad per year of lowLET radiation 1s constrained to be
equal to the arithmetic average (280 per million person rad) of the
absolute and relative risk values (158 and 403) given in Table V25 of
the BEIR3 report (NAS80) for the LL and FT models for leukemia and
solid cancers, respectively.
(2) For cancers other than leukemia and bone cancer, the age and
sexspecific Incidence estimates given 1n Table V14 were multiplied by
the mortality/incidence ratios of Table V15 and processed through the
life table code at constant, lifetime dose rates of 1 rad per year.
The resulting deaths are averaged, using the male/female birth ratio,
and proportioned for deaths due to cancer 1n a specific organ as
described in Appendix G. These proportional risks are then used to
allocate the organ risks among the (235.5) deaths per million person
rad remaining after the 44.5 leukemia and bone cancer fatalities
(Table V17) are subtracted from the arithmetic average of 280 given
in Table V25.
(3) The RADRISK code calculates dose rates for high and lowLET
radiations independently. A quality factor of 20 has been applied to
all alpha doses (ICRP77) to obtain the organ dose equivalent rates in
rem per year. The derivation of the proportional organ risks and
mortality coefficients for alpha particles are, however, based on the
dose in rad as described in Appendix G, Table G6.
A typical environmental analysis requires that a large number of
radionuclides and multiple exposure modes be considered. The RADRISK
code has been used to obtain estimates of cancer risk for intakes of
approximately 200 radionuclides and external exposures by approximately
500 radionuclides. For each radionucllde and exposure mode, we assume
that each member of a cohort of 100,000 persons 1s exposed to a
constant radionuclide Intake of 1 pCI/year, or a concentration of
1 pC1/ccyear for air Immersion, or of 1 pC1/cm2year from the ground
surface, until they die or are 110 years old, the maximum cohort. The
mean life span of the cohort population is 70.7 years, a result
obtained from 1970 agespecific mortality rates. The calculated dose
rates and mortality coefficients described in the preceding sections
are then processed through the life table subroutine of the RADRISK
code to obtain lifetime risk estimates. At the low levels of
contamination normally encountered in the environment, the life table
population 1s not appreciably perturbed by the excess radiation deaths
calculated and, since both the dose and risk models are linear, these
unit exposure results may be scaled to reflect excess cancers due to
the radionucllde concentrations predicted in the analysis of a specific
source.
H12

As noted in the discussion of the life table analysis, risk
estimates for chronic irradiation of the cohort" may also be applied to'
a stationary population having the same agespecific mortality rates as
the 1970 U.S. population. That is, since the stationary population is
formed by superposition of all age groups in the cohort, each age group
corresponds to a segment of the stationary population with the total
population equal to the sum of all the age groups. Therefore, the
number of excess fatal cancers calculated for lifetime exposure of the
cohort at a constant dose rate would be numerically equal to that
calculated for the stationary population exposed to an annual dose of
the same magnitude, Thus, the risk estimates may be reported as a
lifetime risk (the cohort interpretation) or as the risk ensuing from
an annual exposure to the stationary population. This equivalence is
particularly useful in analyzing acute population exposures. For
example, estimates for a stationary population exposed to annual doses
which vary from year to year may be obtained by summing the results of
a series of cohort calculations at various annual dose rates.
H13

Bu81
Co78
DuSO
Du84
EPA77
EPA78
Ev66
Ka82
HEW75
ICRP72
ICRP77
REFERENCES
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Cook J.R., Bunger B., and M.K. Barrlck, A Computer Code for
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Dunning, D.E. Jr., Leggett R.W., and M.G. Yaldntas, A
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H14

ICRP79 International Commission on Radiological Protection, Limits
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NAS83 National Academy of Sciences  National Research Council,
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H15

Sn74 Snyder W.S., Ford M.R., Warner G.G., and Watson S.B., A
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