EPA 402-R-93-076

ESTIMATING RADIOGENIC CANCER RISKS

June 1994

U.S. Environmental Protection Agency

401 M Street S.W.

Washington, DC 20460
ii

The scientific basis for this report has been reviewed formally by the Radiation

Advisory Committee (RAC) of the EPA Science Advisory Board (SAB). The

following paragraph is a synopsis of that review.

On January 10, 1992, Margo T. Oge, Director, Office of Radiation Programs

(now the Office of Radiation and Indoor Air or ORIA) requested that the RAC

review an issues paper comparing health risk estimates due to low level

exposures of low-LET radiation based on models recently published by the

Radiation Effects Research Foundation, the United Nations, the National

Radiological Protection Board of the UK, the National Academy of Sciences,

the US Nuclear Regulatory Commission, and the International Commission on

Radiation Protection. Following discussions on February 12, 1992 with the

RAC, ORIA staff prepared a document titled "Proposed Methodology for

Estimating Radiogenic Cancer Risk" and forwarded it to the RAC for their

review on May 1, 1992. In their letter to the EPA Administrator dated

December 9, 1992, Dr. Raymond C. Loehr, Chairman, SAB Executive

Committee, and Dr. Oddvar E. Nygaard, Chairman, SAB Radiation Advisory

Committee, provided the Committee's evaluation of the proposed ORIA

methodology for estimating radiogenic cancer risks. They concluded that,

"Although no single data set and model for predicting radiogenic cancer risk is

ideal, the method of analysis chosen by EPA is adequately supported by

present evidence." They also offered some comments and suggestions for

future consideration. In her letter of April 19, 1993, Carol M. Browner,

Administrator, EPA, provided responses to those comments and suggestions.

This report, which was prepared by EPA staff members Jerome S. Puskin and

Christopher B. Nelson, Office of Radiation and Indoor Air, Criteria and

Standards Division, presents radiation risks calculated with the models

proposed to the RAC. It also includes risks due to radionuclide intakes and

external exposures calculated with those models.

The authors gratefully acknowledge constructive reviews by Charles E. Land,

National Cancer Institute; Donald A. Cool and Shlomo S. Yaniv, Nuclear

Regulatory Commission; and Harold T. Peterson, Jr., Department of Energy.

The mailing address for the authors is: 

U.S. Environmental Protection Agency

Office of Radiation and Indoor Air (6602J)

Washington, DC 20460
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ABSTRACT

This document presents a revised methodology for EPA's estimation of cancer risks

due to low-LET radiation exposures developed in light of information that has become

available since the publication of BEIR III, especially new information on the Japanese

atomic bomb survivors. For most cancer sites, the risk model is one in which the age-specific

relative risk coefficients are obtained by taking the geometric mean of coefficients derived

from the atomic bomb survivor data employing two different methods for transporting risks

from Japan to the U.S. (multiplicative and NIH projection methods). Using 1980 U.S. vital

statistics, the risk models are applied to estimate organ-specific risks, per unit dose, for a

stationary population. With the exception of breast cancer, low-LET radiogenic cancer risks

are assumed to be reduced by a dose and dose rate effectiveness factor (DDREF) of 2 at low

doses and dose rates compared to risks at high acute dose exposure conditions. The DDREF

assumed for breast cancer is 1. For low dose (or dose rate) conditions, the calculated risk of a

premature cancer death attributable to uniform, whole-body, low-LET irradiation is about

5.1×10 Gy . The corresponding incidence risk (neglecting nonfatal skin cancers) is about -2 -1

7.6×10 Gy . High-LET (alpha particle) risks are presumed to increase linearly with dose -2 -1

and to be independent of dose rate. Except for leukemia and breast cancer, a relative

biological effectiveness (RBE) factor of 20 is adopted for the risk of high-LET radiation

relative to that for low-LET radiation at low dose or low dose rate conditions. For leukemia,

an effective high-LET RBE of 1 is used; for breast cancer, the high-LET RBE is 10. Using

the revised methodology, lifetime cancer risks associated with constant exposure rate

conditions are estimated for over 300 radionuclides.
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CONTENTS

Section Page

ABSTRACT ............................................................. iii

LIST OF TABLES ........................................................ vii

I. Introduction ............................................................. 1

II. Scientific Basis for Risk Estimates .......................................... 1

A. Epidemiological Data ............................................... 1

B. Modeling the Epidemiological Data ................................... 2

Age and Temporal Dependence ................................... 2

Transport of Risk Estimates Across Populations ...................... 3

Dose Response Function and Dependence on Dose Rate ................ 3

C. Risk from Alpha Particles ........................................... 6

III. Comparison of Alternative Risk Models ..................................... 8

A. Model Descriptions ................................................ 8

B. Comparison of Risk Projections ...................................... 12

C. Extrapolation to Low Doses and Dose Rates ............................ 16

D. High-LET Risk Estimates (RBE) ..................................... 17

IV. Methodology for Estimating Radiogenic Cancer Risks ......................... 17

A. Selection of Risk Models ........................................... 17

B. Transport of Risk Estimates from Japan ............................... 18

C. Adjustments to Models ............................................ 21

D. Other Cancer Sites ................................................ 22

E. Summary of Site Specific Cancer Mortality Risk Estimates ................ 24

F. Incidence Risk Estimates ........................................... 24

G. Dose and Dose Rate Effectiveness Factor (DDREF) ...................... 26

H. Alpha Particle RBE ............................................... 27

I. Summary of Revisions in EPA Low Dose Risk Estimates .................. 28

References .............................................................. 31

Appendix A: Calculational Methods .......................................... 35

A. Introduction ..................................................... 35

B. Risk Model Formulation ........................................... 36

C. Revised Methodology Risk Models ................................... 36

D. Risk Calculations ................................................. 39

E. Baseline Force of Mortality Calculations ............................... 44

F. Radionuclide Risk Coefficients ...................................... 45

References for Appendix A ........................................... 58
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vii

LIST OF TABLES

Table Title Page

1 Low-LET U.S. population fatal cancer risk (deaths per 10 person-Gy) for five 4

models. ..................................................... 13

1a Low-LET U.S. population risks (deaths per 10 person-Gy) of stomach and 4

colon cancer mortality for two ICRP Publication 60 models. ............ 15

2 Comparison of fatal cancer risks (deaths per 10 person-Gy) for the geometric 4

mean coefficient (GMC) projection model with Land & Sinclair (ICRP)

and NUREG/CR-4214 models. ................................... 20

3 Residual site mortality risk coefficients for the additive and multiplicative

projections of Land and Sinclair (1991). ............................ 21

4 Site specific mortality risk estimates (per 10 Gy) for proposed EPA model 4

compared with those for ICRP and NUREG/CR-4214 models (male and

female combined, DDREF=1). ................................... 25

5 Lethality data for adult cancers by site. .................................. 26

6 EPA low dose, low dose rate cancer mortality risks (10 per Gy). ............. 29 -4

A.1 Coefficients for the Revised Methodology mortality risk model (male and

female by age group). .......................................... 37

A.2 Dose regions associated with cancer types in the Revised Methodology risk

models. ..................................................... 43

A.3 ICD codes used to define cancer types. .................................. 47

A.4a Revised Methodology radionuclide mortality risk coefficients. ................ 49

A.4b Revised Methodology radionuclide incidence risk coefficients. ............... 53

A.5 Default inhalation clearance class and ingestion f1 values by element. .......... 57
viii
I. Introduction

Since 1984, EPA's estimates of risk from low-LET radiation have been based on the

1980 National Academy of Sciences' (NAS) BEIR III Report (NAS 1980, EPA 1984, EPA

1989). Subsequently, important new data have become available, especially revised

dosimetry and further epidemiological follow-up on the Japanese atomic bomb survivors. 

Risk estimates derived in light of the new data have now been presented in several recent

reports (Shimizu et al. 1988, 1990; UNSCEAR 1988; Stather et al. 1988; NAS 1990; ICRP

1991; Land and Sinclair 1991; Gilbert 1991). We critically examine here the information in

those reports, and some ancillary information, with the aim of developing a revised

methodology for EPA's calculations of radiogenic cancer risks. Radiogenic benign neoplasm

risks are not considered in this report.

In Section II, the main scientific issues are outlined and discussed. Section III

compares the assumptions and numerical projections of risk pertaining to alternative models

found in the above reports. Section IV presents EPA's revised methodology for estimating

radiogenic cancer risks at low doses and dose rates. The Appendix discusses calculational

methods and includes risk estimates for individual radionuclides.

Calculated values in this report are typically shown to three significant figures or one

decimal place. This practice is intended to facilitate comparisons and to simplify tabulations

only. The number of significant figures should not be considered to indicate the level of

certainty in the tabulated values.

II. Scientific Basis for Risk Estimates

 A. Epidemiological Data

By far the most important source of data upon which to base estimates of risk from

low-LET ionizing radiation is the Atomic Bomb Survivor Study (ABSS). Noteworthy

features of this study include: a large, relatively healthy population at the time of exposure; all

ages and both sexes; a wide range of doses, believed to be well estimated on an individual

basis, to all organs of the body; existence of a good control group, consisting of people who

were present in Hiroshima or Nagasaki at the time of bombing but who received only small

doses of radiation; detailed, long-term (40 y) epidemiological follow-up. A statistically

significant excess cancer mortality associated with radiation has been found among the bomb

survivors for the following types of cancer: leukemia, esophagus, stomach, colon, liver, lung,

breast, ovary, urinary tract, and multiple myeloma.

There is an extensive body of epidemiological data on radiation-exposed populations,

apart from the A-bomb survivors. Most important from the standpoint of developing

quantitative estimates of risk from low-LET radiation are the studies of medical exposures of

the thyroid and breast. For two other sites, bone and liver, low-LET risk estimates are

commonly determined from epidemiological studies of cohorts exposed to alpha particle

irradiation, extrapolating a value of RBE from animal studies. Cohorts ingesting or injected 
2

radiogenic liver cancer consists of patients receiving Thorotrast (ThO2) injections. There are

additional important epidemiological studies of persons exposed to low-LET radiation, most

notably, perhaps, the ankylosing spondylitis and cervical cancer patients. Currently, however,

the main value of these studies is for comparison to the A-bomb survivors; none of the major

recent efforts at radiation risk estimation (see below) make direct use of these studies in

developing quantitative estimates of risk.

 B. Modeling the Epidemiological Data

There are many different ways one could organize and model the ABSS data. Choices

can be made regarding: the grouping of cancer sites and age groups, the mathematical form of

the dose-response, and the general form of the age and temporal dependence. These choices

are generally made after exploratory analyses of the data, which indicate what parameters are

most useful to incorporate into the models. By breaking down the data into smaller subgroups,

interesting features may be revealed, but, at some point, the concomitant increase in statistical

variability precludes any meaningful improvement in the model. This constraint may lead to

certain trade-offs; e.g., to obtain a more detailed analysis of the effects of age and temporal

factors on risk, the BEIR V Committee combined all types of GI cancers into a single

category, even though a single model cannot adequately describe the risk for the different GI

cancers. 

Age and Temporal Dependence 

Information on the variation of risk of site specific radiogenic cancers among the

atomic bomb survivors with age and time is limited by sampling uncertainties and by the

incomplete period of epidemiological follow-up. For a given age at time of the bomb (ATB),

the excess solid tumor mortality has generally been found to increase with the age at death

(ATD), roughly in proportion to the age-specific baseline rate for the site of interest.

Consequently, models for these tumors are now generally framed in terms of relative risk.

For the period of epidemiological follow-up, the highest relative risks are found in the

youngest exposure categories. But the lifetime risks of solid tumors due to exposures before

age 20 remain highly uncertain. Individuals exposed as children are only now entering the

years of life where the risk of cancer is concentrated. While this group has exhibited a high

relative risk per unit dose, thus far, the observed excess represents a small number of cancer

deaths. Hence, the sampling error for most types of cancers is large for the younger age

cohorts. It is, moreover, unclear to what extent the observed high relative risks will persist. 

Theoretical considerations, arising from carcinogenesis modeling, would suggest that the

relative risks will decrease over time (Little and Charles 1991). In addition, there is some

epidemiological evidence suggestive of such a temporal fall-off in groups irradiated as

children (UNSCEAR 1988, Little et al. 1991).
3

Conclusions. For cancers other than leukemia, there is strong evidence of an

increasing risk with age at expression, roughly in proportion to the increase with age of

baseline cancer mortality. The data are generally consistent with a constant relative risk

model in which the risk coefficients decrease with age at exposure. There is some suggestive

evidence of a fall-off in relative risk with time after exposure, especially for childhood

exposures (NAS 1990), but further epidemiological surveillance will be necessary to clarify

the pattern of the temporal change (Shimizu et al. 1988).

Transport of Risk Estimates Across Populations

 Baseline rates for specific cancer types vary from population to population, as well as

over time, within a population. For example, stomach cancer rates are substantially higher in

Japan than in the U.S., while the reverse is true for lung, colon, and breast cancer; moreover,

the incidence rates for lung and breast cancer, particularly, have been increasing in both

populations during recent years. Despite the observed rough proportionality between radiation

risk and baseline cancer rates by age, one cannot necessarily infer that the radiation risk will

vary in proportion to the baseline rate as one goes from one population to another.

Information on how to "transport" risk estimates across populations is limited by the

quality of data available on irradiated populations other than the bomb survivors. Two cancer

types for which comparison data exist are thyroid and breast: data on the former suggest that

the risk does increase with the baseline rate (NAS 1990), but it would appear that the opposite

may be true for the latter (Preston 1991). Some insight into the problem might be gained by

looking at subgroups of an irradiated population. For example, lung cancer rates in Japanese

males are several times higher than in Japanese females, presumably due in part to the higher

smoking rate in males. Nevertheless, the excess absolute risk for lung cancer attributable to

radiation does not differ significantly between the male and female bomb survivors. This

would suggest that, for lung cancer, absolute risk may be more transportable than relative

risk.

Conclusions. Information on how to transport risk estimates between populations is

very limited; what information there is suggests that the answer is likely to be cancer site

specific.

Dose Response Function and Dependence on Dose Rate

A major issue in radiation risk assessment is how best to quantify the risks and to

characterize their uncertainties for small incremental doses above natural background. A

comprehensive examination of this question was contained in NCRP Report 64 (NCRP 1980).

Based primarily on laboratory studies of cells, plants and animals, the report advocated a

linear-quadratic dose response for acute doses up to about 2.5-4 Gy, above which the dose

response begins to turn over due to cell killing effects. At low doses, the quadratic term is

negligible in comparison to the linear term. The NCRP committee defined the low dose region

as 0-0.20 Gy, since significant deviations from linearity are found in Tradescantia
4

experiments and in life shortening in mice above this range. Evidence was also cited to the

effect that the D term in the dose response function vanishes when the radiation is delivered 2

at low dose rates, even for total doses above 0.2 Gy.

A theoretical framework for the linear-quadratic dose response model has been

developed by Kellerer and Rossi (1972), utilizing concepts originally put forth by Lea (1962). 

In this theory of "dual radiation action," events leading to "lesions" (i.e., permanent changes)

in cellular DNA require the formation of interacting pairs of "sublesions." The interacting

pairs can be produced by a single traversing particle, or track, or by two tracks, giving rise,

respectively, to a linear and a quadratic term in the dose response relationship. According to

the theory, a sublesion may be repaired before it can interact to form a lesion, the probability

of such repair increasing with time. Consequently, as the dose rate is reduced, the formation

of lesions from sublesions caused by separate tracks becomes less important, and the

magnitude of the D term decreases. Hence, the theory predicts that at sufficiently low doses 2

or dose rates, the response should be linear and, in either limit, should have the same slope.

Results of animal tumorigenesis studies are, in general, qualitatively consistent with

the theory: low-LET radiation seems to have reduced effectiveness per unit dose at low dose

rates (NCRP 1980). However, it is usually not possible from the data to verify that the dose

response curve has the linear-quadratic form. Another success of the dual action theory has

been in explaining observed differences between the effects of low- and high-LET radiations. 

In this view, the densely ionizing nature of the latter results in a much greater production of

interacting pairs of sublesions by single tracks, leading to a higher biological effectiveness at

low doses and a linear dose response relationship (except for deviations at high doses

attributable to cell-killing effects).

The dual action theory has nevertheless been challenged on experimental grounds, and

observed variations in response with dose, dose rate, and LET can also be explained by other

mechanisms, e.g., a theory involving only single lesions and a "saturable" repair mechanism

that decreases in effectiveness at high dose rates on the microscopic scale (Goodhead 1982). 

One property of such a theory is that, in principle, the effectiveness of repair - and therefore

the shape of the dose response curve - can vary widely with cell type and species. Hence,

results obtained on laboratory animals might not be entirely applicable to humans.

According to either the dual action theory or the saturable repair theory, the dose

response should be linear at low doses or low dose rates, and with equal slopes. At higher

doses and dose rates, multiple track events become important, and the dose response should

bend upward. As a result, the response per unit dose at low doses and dose rates will be

overestimated if one extrapolates linearly from observations made at high doses, acutely

delivered (NCRP 1980). The degree of overestimation is commonly expressed in terms of a

dose and dose rate effectiveness factor (DDREF): e.g., a DDREF of 3 means the risk per unit

dose observed at high acute doses should be divided by 3 before being applied to low dose

(dose rate) conditions. 
5

Current mechanistic explanations for a DDREF involve DNA repair. The linearity of

the dose response at low doses suggests that DNA repair is maximal and independent of dose

rate for doses below about 0.2 Gy. Repair of radiation-induced DNA damage is found to be

largely complete within a few hours of an acute exposure (Wheeler and Wierowski 1983,

Ullrich et al. 1987). Consequently, protracting the dose beyond this time span should have

little or no effect on the risk of cancer induction. It is expected, therefore, that repair will be

maximal so long as no doses above 0.2 Gy are delivered within a few hours.

When the BEIR III Committee attempted to fit the ABSS data to a linear-quadratic

model, the results were not very satisfactory (NAS 1980). Depending on whether one

analyzed solid tumors or leukemia, and depending on which city the data were drawn from,

the shape of the fitted dose response changed markedly; in some cases no reasonable fit could

be obtained. Some of the discrepancy was resolved by attributing a substantial fraction of the

excess cancers in Hiroshima to neutrons, but serious problems remained, and the ultimate

choice of dose response function seemed to be strongly influenced by supporting laboratory

data.

With the revised "DS86" dosimetry, these curve-fitting problems are largely removed

(Shimizu et al. 1990, NAS 1990). The data from the two cities are now in reasonable

agreement. The combined leukemia data can be fit by a linear-quadratic dose response

function; the slope of the function at low doses is about half that obtained by a linear fit to the

data. A statistical analysis of the solid tumor data, on the other hand, indicates no departure

from linearity in the dose response over the entire range from 10 to 400 rad. Using a linearquadratic model to fit the data reduces the linear term by, at most, a factor of 2 compared to a

simple linear model. Viewing these results through the paradigm adopted by NCRP 64 would

indicate that: a best estimate of the DDREF is about 2 for leukemia while, for solid tumors, a

DDREF of 2 represents an upper bound, and the best estimate is about 1. 

The conclusions in the preceding paragraph, however, appear to require some

modification in light of a subsequent analysis by Pierce and Vaeth (1991). These authors

show that errors in dose estimation will introduce a negative bias in the dose-squared

dependence of the response. Assuming dosimetry errors of 30-40%, this has a relatively

minor effect on the best estimate of the DDREF, but the upper bound is increased to about 3. 

Also pertinent to the issue of what DDREF is applicable to human cancer induction are

clinical studies of radiation-induced breast and thyroid cancer, which have shown little or no

reduction in risk with dose fractionation (Shore et al. 1984, Davis et al. 1989, Howe 1992). 

This again suggests a DDREF of about 1 (ICRP 1991). On the other hand, while studies of

tuberculosis patients, who had undergone repeated fluoroscopic examinations, clearly show

an elevated risk of breast cancer from fractionated doses of x-rays, they show no indication of

an excess lung cancer risk (Davis et al. 1989, Howe 1992). When compared with observed

lung cancer risks in the atomic bomb survivors, the results of these studies suggest that the

DDREF may be quite large for lung cancer induction, although the possibility of confounding

by the underlying disease process cannot be ruled out.
6

The results on human solid tumors appear to differ from those obtained through

laboratory studies, including studies of radiation-induced tumorigenesis in mice and rats. For

the most part, the laboratory studies suggest a DDREF of about 2 or 3, and sometimes higher,

depending on end point; on the other hand, the preponderance of the evidence on humans

suggests a lower DDREF, possibly about 1 for most sites. One can resolve this apparent

conflict in different ways, with significantly different implications for radiation risk estimation

at low doses and dose rates.

If one retains the linear-quadratic model in NCRP 64 and the connection it implies

between the shape of the dose response and the effect of dose rate on the response, the

Japanese data would seem to dictate an average DDREF no higher than 1 to 3 for radiationinduced carcinogenesis in humans. It could then be argued that, in light of the extensive

laboratory data suggesting a DDREF of at least 2, a DDREF of 2-3 should be applied in

estimating risks to humans. On the other hand, it could be argued that animal data are an

unreliable guide to the response in humans and that a DDREF of 1, an approximate best

estimate from the human data, should be used in estimating the risk of solid tumors at low

doses and dose rates.

There are experimental data suggesting a difference in DDREF between humans and

rodents. Grosovsky and Little (1985) measured x-ray induced mutations in human

lymphoblast cells and found a linear dose response over the range 0.05-2 Gy, which was

independent of dose rate. Similar experiments performed on rodent cells have shown a

curvilinear dose response and a decrease in the response with decreasing dose rate. 

Alternatively, one might reconcile the human and laboratory data by abandoning the

linear-quadratic model of radiation-induced carcinogenesis and its implied connection

between the shape of the dose response for acute doses and the effect of protracting the dose

over time. For example, one could envision having a linear response over the dose range

accessible to epidemiological observation (above about 0.1 Gy) but a substantial reduction in

risk at lower doses, or if these doses are fractionated or delivered chronically. 

Studies indicate that repair of radiation-induced DNA damage is completed within a

few hours after it is incurred (Wheeler and Wierowski 1983, Ullrich et al. 1987). Hence, for

multitrack events to be biologically important, it would appear that at least two tracks would

have to pass through a cell nucleus within this time period. For low-LET doses of about 1

mGy, only one track, on average, traverses each cell nucleus. From these considerations, it is

expected that the same amount of unrepaired DNA damage per unit dose should occur so long

as the dose delivered over a few hours is below about 1 mGy. Such conditions define a

region in which the response is expected to be linear with dose and independent of any further

fractionation or reduction in dose rate.

Conclusions. Taken together, current scientific data are generally indicative of a

DDREF between 1 and 3 for human cancer induction. However, there is an indication that a

higher DDREF may apply to the lung.
7

 C. Risk from Alpha Particles

Radiobiological data indicate that high-LET alpha radiation has a larger biological

effect than an equal absorbed dose of low-LET radiation. The subject has recently been

reviewed in: the BEIR IV Report (NAS 1988); NCRP Report No. 104 (NCRP 1990); and

ICRP Publication 60 (ICRP 1991). The radiobiological results, including those for tumor

induction, are generally suggestive of a linear nonthreshold dose response for high-LET

radiation, except for a possible fall-off in effectiveness at high doses. In contrast to low-LET

radiation, the effects of high-LET radiation often increase with fractionation or with a

decrease in dose rate.

A number of cohorts exposed occupationally or medically to internally deposited alpha

emitters have shown an excess of cancer at heavily irradiated sites. Most important is the

observed induction of: (1) lung cancer in miners inhaling radon progeny; (2) bone sarcomas

in patients injected with Ra-224; (3) bone sarcomas and head carcinomas in dial painters

ingesting mixtures of Ra-226 and Ra-228; and (4) liver cancers in patients injected with

Thorotrast, an x-ray contrast medium containing isotopes of Th. Although other organs of the

body received doses of alpha radiation in these populations, excess cancers were generally not

observed at sites other than those mentioned. As a result, only upper bounds to the risk for

these other organs can be estimated from studies of humans exposed to alpha irradiation. 

Site specific cancer risk estimates for high-LET radiation (neutrons or alpha particles)

are often calculated utilizing human epidemiological data on low-LET radiation (e.g., from

the ABSS) and laboratory data on the relative biological effectiveness (RBE) of the high-LET

radiation compared to a reference low-LET radiation (NCRP 1990). Since the dose response

relationship obtained for low-LET radiation is typically linear or concave upward while that

for high-LET radiation is linear or concave downward, the RBE is dose dependent. EPA is

primarily concerned with risks at low doses and dose rates, where the acute high dose risk for

low-LET radiation is reduced by the DDREF. Under these conditions, the dose responses for

both low and high LET radiations are thought to be linear, and the RBE takes on a constant

(maximum) value: RBEM. 

Ranges of estimated values for neutron and alpha particle RBEM are wide, depending

on both the biological system and the observed end-point; the uncertainty in the RBEM

estimate from an individual study is also usually large, primarily due to the uncertainty in

extrapolation of low-LET data to low doses. The effectiveness of alpha emitters has been

found to be 15 to 50 times that of beta emitters for the induction of bone sarcomas, liver

chromosome aberrations, and lung cancers (NCRP 1990). Since the LET of secondary

protons produced by fission neutrons in living tissue is comparable to that for alpha particles,

data on the RBEs of fission neutrons provides ancillary information relevant to the estimation

of alpha particle RBE. Where the dose response data on carcinogenic end-points are adequate
8

to derive an estimate, fission neutrons have been found to have an RBEM between 6 and 60

times that of low dose gamma rays (NCRP 1990). 

III. Comparison of Alternative Risk Models

 A. Model Descriptions

This section provides a qualitative description of 6 sets of risk models, all based

largely on ABSS data collected through 1985 and incorporating DS86 dosimetry.

RERF. A detailed description of the RERF's data on the atomic bomb survivors is

contained in two publications by Shimizu, Kato, and Schull (1988, 1990). The data on solid

tumors were analyzed using constant absolute and relative risk models, where the risk

coefficients were, however, allowed to vary with the age ATB. From this analysis, the

authors concluded that the relative, but not the absolute, risk model is consistent with the

observed temporal dependence of excess mortality due to solid tumors. 

Most of the major qualitative conclusions that can be drawn from the analysis have

been discussed above. These include: (1) a statistically significant increase in cancer at

various sites, positively associated with radiation dose; (2) for solid tumors, an increase in risk

with age ATD, roughly in proportion to the increase in baseline cancer mortality with age; (3)

a substantially higher observed relative risk in those below age 20 ATB; (4) essentially a

linear dose response for solid tumors, but with evidence of a relatively small quadratic

contribution in the dose response for leukemia.

Age-specific risk coefficients are given for these sites: leukemia, stomach, breast, lung,

colon, and nonleukemia. In the Life Span Report, these are tabulated both for an assumed

neutron RBE of 1 and 10 (Shimizu et al. 1988). 

UNSCEAR 88. The lifetime risks in UNSCEAR (1988) were calculated (for the

Japanese population) using coefficients from the RERF Life Span Study Report 11 (Shimizu

et al. 1990). Estimates for leukemia and all other malignancies are derived for age-specific,

absolute and relative risk projection models. The UNSCEAR report also provides risk

estimates for an expanded set of cancer sites, calculated using an "age-averaged" relative risk

model. In this model, the observed differences in relative risk with age ATB are ignored, and

a single, average risk coefficient is adopted for each site. This approach generally yields

somewhat lower estimates of the risk for constant lifetime exposures. While we would reject

the age-averaged model, as being less reflective of the epidemiological data collected so far, if

the high relative risks observed in the younger exposure groups decrease appreciably over

time, the age-averaged model may turn out to provide a better numerical estimate of the

lifetime risk than the age-specific model derived from these data.
9

NRPB. The NRPB report (Stather et al. 1988) represents a further elaboration of the

information contained in Life Span Study Report 11 and in UNSCEAR 88. Although other

model estimates are developed, the favored approach for solid tumors seems to the agespecific, constant relative risk projection model, while an absolute risk model with a 2-40 y

expression period is adopted for leukemia.

The NRPB model incorporates some modifications from the model originally derived

from the Japanese data. First, it was noted that the data indicate a much higher risk

coefficient for childhood irradiation of the colon compared to that for adults, but that the data

on childhood exposures are, in this case, sketchy. To avoid the problem this poses (a

relatively large contribution from colon cancer with very little observational support), the

authors arbitrarily assigned the coefficient obtained for ages 20-29 ATB to the age cohort 0-

19. Second, risk estimates were given for several cancer sites (breast, liver, thyroid, and

bone) derived from epidemiological data collected on populations other than the bomb

survivors. 

In the case of breast cancer, the authors argued that data on North American women

would be more relevant for the population of interest to them (women of the U.K.). 

Accordingly, they adopted a risk model published in the Nuclear Regulatory Commission's

(NRC) Health Effects Model Document (Evans et al. 1985). This breast cancer model was

largely based on studies of women from the U.S. and Canada who received diagnostic or

therapeutic doses of x-rays. For thyroid cancer, the NRPB adopted a model contained in the

same NRC report, as well as in an NCRP report on thyroid cancer risks (NCRP 1985). For

liver and bone cancer, no actual age-specific models are given, but lifetime risk estimates are

developed on the basis of Thorotrast and radium exposed populations, respectively, assuming

an RBE of 20 for alpha particles. 

No model is presented for calculating the risk at sites other than those listed. A risk

estimate for the "remainder" sites is calculated by taking the difference between the estimate

for total solid tumors and the estimated sum for listed solid tumors. This procedure only

makes sense in the context of uniform, whole-body irradiation.

ICRP. As support for its recommendations in Publication 60 (ICRP 1991), the ICRP

has made use of risk calculations performed by Land and Sinclair (1991). For the most part,

these calculations make direct use of the age- and sex-specific relative risk coefficients listed

in Table 5A of RERF Report 11, Part 2 (neutron RBE=10) (Shimizu et al. 1988). The age at

exposure groups are 0-9, 10-19, 20-29, 30-39, and 40+ years. Land and Sinclair also use the

information in the RERF report to incorporate three additional sites into their model:

esophagus, ovary, and bladder. Age-specific risk coefficients for "residual" cancers are

obtained by subtraction of specified cancers from the total for the period of follow-up.

The risks are calculated for 5 reference populations: Japan, U.S., Puerto Rico, U.K.,

and China. Three methods are used to transport risk estimates from the study population of

bomb survivors to each of the 5 reference populations. The first (additive) involves a direct
10

transport of age- and sex-specific absolute risk coefficients. The second (multiplicative)

involves a direct transport of relative risk coefficients. The third (NIH) is a hybrid of the

additive and multiplicative methods. For solid tumors, the total excess risk after the minimal

latency period is projected for the period of epidemiological follow-up (i.e., 10-40 y for the

RERF data) using the absolute risk coefficients of the additive model. However, it is

considered to be distributed over time after exposure as a multiple of the baseline rate. The

NIH model relative risk coefficient yields the same risk over the follow-up period as the

absolute risk model.This coefficient is then used to project lifetime risk in the same way as for

the multiplicative model. With the NIH method, the excess risk varies with age, in proportion

to the baseline rates in the population of interest, but only weakly reflects differences between

these baseline rates and those in Japan.

A peculiarity of the NIH projection model is that it can artificially introduce agedependent variability where none can be discerned from the data. For example, in view of the

very limited data on lung and colon cancer mortality among the atomic bomb survivors

exposed as children, authors have assigned equal risk coefficients for these cancers to the 0-9

y and the 10-19 y age groups, for both the additive and multiplicative models (Shimizu et al.

1990, Land and Sinclair 1991). However, if these age groupings are maintained, the derived

NIH projection model will contain significantly higher risk coefficients for the 0-9 group, and

a likely inflation of the risk estimates associated with childhood exposures. To avoid this

problem, the NIH risk coefficients for lung and colon are calculated on the basis of treating

the 0-19 y age group as a single group. The result is a decrease in the estimated risk for these

sites compared to previous calculations (ORP 1992). 

In discussing the appropriateness of the three models, the authors note that the

multiplicative but not the additive model provides a reasonable approximation to the

epidemiological data. On the other hand, they also point out that little information is available

pertaining to the transfer of risk across populations. Hence, in developing organ-weighting

factors, they advocate an average of the multiplicative and NIH model projections.

BEIR V. The National Academy of Sciences BEIR V Committee conducted an

independent analysis of the ABSS data, supplemented by data on breast cancer induced by

medical irradiation (NAS 1990). The Committee developed several age- and sex-specific

relative risk models for calculating excess mortality due to these types of radiogenic cancers:

leukemia, respiratory, digestive, breast, and other; breast cancer incidence was also modeled

separately from breast cancer mortality. In each case, a preferred model was designated. 

Unlike all the other reports discussed here, BEIR V incorporated time-since-exposure

dependence into its modeling. In transporting risk estimates from Japan to the U.S., BEIR V

assumes a multiplicative model: i.e., it assumes that the same risk models and coefficients

derived from a statistical fit to the atomic bomb survivor data can be applied to the U.S.

population with its own baseline cancer rates.
11

For acute doses of 0.1 Gy or more, BEIR V derives a linear-quadratic model for

leukemia but a linear model for all other cancers. This finding is consistent with earlier

conclusions by the RERF group (Shimizu et al. 1988, 1990).

A number of problems can be identified pertaining to the preferred models and

estimates in BEIR V:

First, the definition of "excess" risk adopted in the report excludes radiogenic cancers

in individuals projected to die of cancer in the absence of the irradiation - this not only

understates the predicted health impact of the radiation, it creates disturbing anomalies such

as organ-specific risks that are negative or dependent on doses to other organs (C. Nelson,

unpublished results).

Second, in projecting radiogenic leukemia risk from the ABSS to the U.S. population,

chronic lymphocytic leukemias were erroneously included in the U.S. baseline rate although

this type of leukemia does not appear to be radiogenic (Gilbert 1991). This results in an

inflation of the leukemia risk estimate for the U.S.

Third, the BEIR V committee employed a multiplicative projection of breast cancer

risk from the Japanese to the U.S. Given the higher breast cancer rates in the latter, this

implies a higher radiogenic risk also. In fact, epidemiological data indicate the radiogenic

risks are similar in the two populations (Preston 1991).

Fourth, a sharp fall-off in risk with time after exposure is incorporated into the

respiratory cancer model. Although the model was developed from a statistical fit to the

ABSS data, the existence of such a fall-off is not strongly supported by the ABSS data

collected so far (NAS 1990). The main evidence for a temporal fall-off comes from the

ankylosing spondylitis study (Darby et al. 1987) for which good dosimetry is lacking and for

which there is a question of potential confounding by the disease. A striking consequence of

the model's fall-off is that the projected risk of irradiating the respiratory tract of children is

very low compared to adults. It is noteworthy that the irradiated spondylitic patients were all

at least 15 y old.

Fifth, BEIR V models digestive cancers from the ABSS as a single category. An

obvious disadvantage of this approach is that no guidance is provided on how to partition the

risk among the digestive organs - most importantly, between stomach and colon. By

combining the ABSS data in this way, BEIR V was able to obtain a more accurate and robust

statistical modeling of sex, age, and time dependencies. To some degree, the gain may be

illusory, however, since there is no guarantee that the various digestive organ risks should

vary in the same way with these model parameters. Additional error may be introduced in

transporting digestive cancer risks from Japan, where stomach cancer rates are high and colon

cancer rates are relatively low, to the U.S., where the reverse is true. 
12

Sixth, BEIR V fails to deal effectively with the issue of projecting risk estimates into

the domain of low doses and dose rates. On the one hand, a linear dose response for solid

tumors is advocated. On the other, it is suggested that at low dose rates risk estimates should

be reduced "by a factor of two to ten." Taken together, these two recommendations appear to

be at odds with basic radiobiological principles, which would seem to imply no dose rate

dependence at low doses (see Section II).

NUREG/CR-4214. Recently, the Nuclear Regulatory Commission has published a

revision to NUREG/CR-4214 (Abrahamson et al. 1991), that updates its health effects models

and their scientific bases. The estimation of radiogenic cancers due to low-LET radiation is

discussed in a chapter by Dr. Ethel Gilbert (1991). 

While adhering to the general framework laid out in the previous report (Abrahamson

et al. 1989), revised models are developed in light of subsequent information, including the

new Japanese data and the analyses performed by the BEIR V, UNSCEAR 88, and ICRP 60

committees. Risk models are given for application to the general population for these cancer

sites: breast, lung, GI, thyroid, bone, skin, and other. In addition, models are given for in

utero cancer induction and benign thyroid tumor risks. Guidance is also included as to how to

partition the GI cancer risk among organs and how to separately calculate organ specific risks

for males and females. 

Age-specific, constant relative risk models are recommended for all sites except

leukemia, bone, thyroid, and skin, for which additive risk models are proposed. The risk

coefficients do not generally represent statistical "best estimates" obtained from an analysis of

the epidemiological data. Compared to the other models discussed here, the

NUREG/CR-4214 models more explicitly incorporate expert judgment. Broadly speaking,

the models are designed to be as simple as possible, but to yield estimates of the risk on an

age and organ specific basis, which are reasonably central in view of the scientific

uncertainties outlined in Section II.

 B. Comparison of Risk Projections

Three sets of models described above are quite similar: RERF, UNSCEAR 88, and the

ICRP (multiplicative model). For simplicity, we will eliminate the first two of these from

consideration. 

Table 1 compares the site-specific projections of lifetime risks for a stationary U.S.

population, calculated using these five alternative sets of models: NRPB, BEIR V,

NUREG/CR-4214, ICRP (multiplicative), and ICRP (NIH). For purposes of this comparison,

the DDREF in each case is 1. (The choice of a DDREF will be discussed below.) The values

in the table are risk of cancer attributable to radiation, not just the "excess" risk calculated in

the BEIR V report. The cancer risks have been calculated for each model using 1980

decennial U.S. life table and force of mortality data. Hence,the model comparisons are not
13

confounded by the effects of different sets of vital statistics or of using the specific age

distribution for a population in a particular year. As a consequence, the calculated risks differ

slightly from those in the referenced reports.

Leukemia. The numerical estimates of lifetime risk are quite similar, except for

BEIR V, which is about a factor of 2 higher. In part, this is due to the fact that BEIR V fails

to exclude chronic lymphocytic leukemias, which have not been shown to be radiogenic.

The NRC and NRPB recommend simple absolute risk models, which distribute the

risk evenly over a 25 or 38 y time period, respectively. In contrast, both ICRP's NIH model

and the BEIR V model for leukemia represent statistical fits to the temporal dependence in the

Japanese data. The NIH model, for example, predicts a lognormal temporal response, with a

shape dependent on age at exposure. The ICRP multiplicative model is least satisfactory in 

Table 1. Low-LET U.S. population fatal cancer risk (deaths per 10 person-Gy) 4

for five models.

Cancer NRPB BEIR V NUREG/ ICRP 

Site CR-4214

Mult. NIH

Nonleukemia 966 —— —— 966 773 1

Digestive 179 263 297 457 434 2 3 3

 Esophagus —— —— 14.9 6.2 21.3 4

 Stomach 29.3 —— 74.3 29.3 274 4

 Colon 120 —— 149 381 109 4

 Liver 30 30 29.7 30 30 5 5 4 5 5

Respiratory —— 187 —— —— ——

 Lung 265 —— 149 265 78.7

Bone 10 14 8.1 9.3 9.3 6 7 8 8

Skin 3.0 —— 1.8 2.0 2.0 9 9

Breast 78.0 33.5 46.2 116 32.7

Ovary —— —— 32.2 47.5 25.0 10

Bladder —— —— 49.6 64.0 38.9 10

Thyroid 6.3 6.4 11 22.5 7.5 7.5

Leukemia 81.7 164 89.9 110 97.9 12

Remainder 424 329 248 374 276 13
14

Totals:

 Solid tumors14 —— 812 754 1293 855

 All sites15 —— 977 845 1403 953

 Nonleukemia + —— ——

 leukemia16

1048 1076 871

Notes for Table 1.

General: All risks are calculated for a stationary population using 1980 decennial U.S. vital

(see Appendix A.) The DDREF is one. Risks not in italics are calculated directly

from the models given in the references. Those in italics are sums of sites or make use

of supplementary information.

Notes for Table 1. (Cont.)

 1. NRPB and ICRP provide explicit models for all solid tumor (nonleukemia) mortality

risk. These nonleukemia models presume a uniform dose to all tissues.

 2. Sum of stomach, colon, and liver risks.

 3. Sum of esophagus, stomach, colon, and liver risks.

 4. NUREG/CR-4214 esophagus, stomach, colon, and liver risks are 0.05, 0.25, 0.50, and

0.10 times the digestive risk, respectively.

 5. NRPB, BEIR V, and ICRP liver risks are the corresponding alpha dose risks divided

by an RBE of 10.

 6. NRPB alpha dose bone risk divided by an RBE of 10.

 7. BEIR V incidence value multiplied by a lethality factor of 0.7 for comparability.

 8. ICRP alpha dose bone risk divided by an RBE of 10.

 9. ICRP also recommends this value for the low-dose, low-dose-rate region.

 10. NUREG/CR-4214 ovary and bladder risks are 0.13 and 0.20 times the remainder risk,

respectively.

 11. Except for BEIR V, all thyroid risks are based on NCRP Report 80 (NCRP 1985). 

 12. The linear coefficient of the BEIR V linear-quadratic model for leukemia has been

doubled for comparability with the other model estimates.
15

 13. NRPB remainder risk is calculated as the nonleukemia risk less the sum of the

stomach, colon, liver, lung, bone, breast, and thyroid values.

 14. Sum of site specific risks for each model as follows:

BEIR V: Digestive, respiratory, breast, and remainder.

NUREG/CR-4214: Digestive, lung, bone, breast, thyroid, and remainder.

ICRP: Esophagus, stomach, colon, lung, breast, ovary, bladder, and remainder.

 15. Sum of all solid tumor and leukemia risks (BEIR V, NUREG/CR-4214, and ICRP,

only).

 16. Sum of nonleukemia and leukemia risks (NRPB and ICRP, only).
16

describing the temporal response, concentrating the excess risk at the end of the expression

period, opposite to what is actually observed.

 

Breast. A major issue with respect to breast cancer is in the transport of risk from Japan

to the U.S., where the baseline rates are much higher. For example, the ICRP multiplicative and

NIH projections of breast cancer risk for the U.S. differ by almost a factor of 4 (Land and Sinclair

1991). The NRPB and NUREG/CR-4214 models do not have this problem since they are based

on North American data. These model projections agree fairly well with ICRP's NIH projection

but are substantially lower than the projection made with ICRP's multiplicative model.

Lung. Lung cancer risks are highly uncertain due to uncertainties in age and temporal

dependencies, and in transporting risk from Japan to the U.S., where the baseline lung cancer

rates are considerably higher. The NRPB relative risk and ICRP multiplicative models are

identical and project the highest risks; these models both presume that the age-specific constant

relative risk coefficients derived from the Japanese data apply to other populations. The BEIR V

respiratory model yields a lower estimate because of its temporal fall-off. ICRP's NIH projection

is lower because of the difference between Japanese and U.S. lung cancer rates. The

NUREG/CR-4214 model produces a higher estimate of risk for childhood exposures but a

lifetime risk projection similar to that from BEIR V or an average of the two ICRP model

projections.

Digestive. All of the stomach and colon cancer risk models are constant relative risk

models derived from the ABSS data, each incorporating a substantially higher coefficient for the

younger age-at-exposure groups. Nevertheless there are important differences among them. For

example, as shown below from a comparison of Land and Sinclair's multiplicative and NIH

projections (1991), the results for stomach and colon are very sensitive to how one transports the

risk from Japan to the U.S.

Table 1a. Low-LET U.S. population risks (deaths per 10 person-Gy) of stomach and 4

colon cancer for two ICRP Publication 60 projection models.

Transport model

Cancer type Multiplicative NIH

Male Female Male Female

Stomach 32 45 221 333

Colon 223 602 178 143

These results highlight the large colon cancer contribution in the multiplicative model -

especially for females. As noted previously, the NRPB reduced its colon cancer risk estimate by

decreasing the risk coefficient for childhood exposures. It is also instructive to compare

estimates of total digestive cancers made with the BEIR V model and the ICRP multiplicative

model. (See Table 1.) Although both are age-specific constant relative risk models, which
17

transport relative risk coefficients directly from the bomb survivors to the U.S. population, the

former projects only about 65% of the digestive cancer risk. This seems to be largely a

consequence of BEIR V's modeling digestive cancers as a single group, coupled with the

differences in baseline stomach and colon cancer rates between Japan and the U.S. The same

concern would probably apply to Gilbert's estimate of digestive cancer risk.

Other/Remainder. Since the sites for which risk estimates are developed differ, the sites

included in the remainder category differ among the sets of models considered here. The NRPB

does not develop a risk model for this category; instead the projection is obtained as a difference

between the model projection for total (nonleukemia) cancers and for modeled (nonleukemia)

sites. This approach yields a higher estimate for the remainder sites than obtained by modeling

the risk for these sites directly. The lack of an explicit model and the assignment of about 40% of

the total risk to this category might be regarded as weaknesses of the NRPB approach.

Miscellaneous Specific Organs. Each of the reports cites high-LET Thorotrast data as the

basis for its liver cancer risk estimate. Assuming an RBE of 10, for the purpose of this

comparison, all the models yield a liver cancer risk estimate of 30 per 10 Gy. The reports 4

recommend bone cancer risk estimates derived from Ra-224 studies. Based again on an assumed

RBE of 10 and a bone cancer lethality of 0.7, the estimates are in reasonably good agreement

with one another.

ICRP 60 recommends a risk estimate for skin cancer incidence of 980 per 10 Gy; 0.2% of 4

these cancers are assumed to be fatal. The NRC bases its skin cancer model on ICRP 60 and,

therefore, projects essentially the same risk. (The two reports differ on the risk at low dose rates;

the ICRP makes no adjustment in extrapolating from high dose rates, whereas the NRC applies a

DDREF of 2.) The NRPB employs an older ICRP model, which projects about 30% of the

incidence but 150% of the mortality as ICRP 60.

The NRC, NRPB, and ICRP 60 all calculate thyroid cancer using the absolute risk model

recommended in NCRP 80 (NCRP 1985). From the Israeli Tinea Capitis data (Ron and Modan

1984), BEIR V develops its own (relative risk) model, which projects about 3 times higher risk

than the NCRP model. 

 

The ICRP estimates risk for the bladder and ovary, using the age-average relative risk

coefficients derived from the ABSS data. None of the reports provides an estimate for kidney,

which receives a relatively high dose from certain radionuclides, especially uranium. The ABSS

shows a non-statistically-significant elevation in kidney cancer associated with radiation. The

existence of a radiogenic risk for this site seems to be confirmed by the cervical cancer study

(NAS 1990). The estimate of kidney cancer risk here is based on the ABSS kidney data. An

alternative would be to calculate the risk using a model developed for remainder sites. A

preliminary examination indicates this approach would yield roughly similar results.

 C. Extrapolation to Low Doses and Dose Rates
18

As discussed in Section I.B, it is widely assumed that the risks of low-LET radiation are

reduced by a DDREF at low doses and dose rates. For leukemia, BEIR V advocates a linearquadratic model, consistent with a DDREF of 2. For other sites, the report recommends no

reduction in risk for low, acute doses but suggests that a reduction by a factor of 2 or more may

be appropriate at low dose rates. ICRP 60 contains a fairly detailed discussion of the issue [ICRP

1991: pp. 108-112] and recommends that a DDREF of 2 be used for radiation protection purposes

at this time. The NRC concurs with the ICRP recommendation, except in the case of breast or

thyroid, for which a DDREF of 1 is adopted. The NRPB recommends a DDREF of 1, 2, and 3,

respectively, for thyroid, breast, and all other sites. 

 D. High-LET Risk Estimates (RBE)

The ICRP (1991) assumes that alpha radiation produces 20 times the risk, per unit

absorbed dose (Gy or rad), as low-LET radiation. This relationship is meant to hold in the limit

of low doses and dose rates. Thus, it already takes into account the assumed DDREF of 2 for

low-LET radiation; at high acute doses, the RBE would be 10. This must be kept in mind both

when calculating alpha particle risks using models derived from low-LET epidemiological data

and when estimating low-LET risks (for bone and liver) based on high-LET studies. The NRC

and NRPB reports also assume that at low doses the risk per Gy from alpha particles is 20 times

that from gamma rays. 

IV. Methodology for Estimating Radiogenic Cancer Risks

 A. Selection of Risk Models

In our opinion, the models developed by Gilbert for the NRC, and by Land and Sinclair

for the ICRP, are preferable for EPA's needs to the others considered here. BEIR V reveals novel

features of the Japanese data, but for reasons outlined above, was not deemed to provide a good

basis for EPA's nominal "best estimates" of radiogenic cancer risk. The NRPB models are very

similar to the ICRP multiplicative models, but the NRPB makes a somewhat arbitrary adjustment

to its colon cancer model for childhood exposures and appears deficient in its handling of the

"remainder" category. It could also be argued that, in view of the uncertainties, weight should be

given to an "additive transport" of risk estimates, where the radiogenic risk is assumed to be

insensitive to differences in baseline cancer rates between populations. An additive type of

transport (such as that provided by ICRP's NIH projection) leads to somewhat lower estimates of

risk for most radionuclides, especially for those retained in the lung. (See Table 1.)

To a large extent, the ICRP approach reflects a well defined, predetermined procedure in

which the excess cancer mortality observed in the A-bomb survivors, by site, age, and sex, are

used to calculate risk in the U.S. population. However, Land and Sinclair express no preference

between the multiplicative and NIH methods of projecting risk from one population to another,

and the ICRP ended up adopting an arithmetic average of the two methods for each site. The

NRC approach, on the other hand, rests to a degree on judgments, reached after an examination of
19

all the epidemiological data and a consideration of alternative modeling approaches, on a site

specific basis.

Land and Sinclair's models involve more detailed age and site specific information. For

example, Gilbert does not provide age and sex-specific risk coefficients for individual types of

digestive cancers. Instead she develops a model for uniform irradiation of the digestive organs

and then indicates what fraction of the total risk should be assigned to each. Since the age and

sex dependencies differ among the various digestive organs, considerable manipulation is

required to obtain organ-specific relative risk coefficients that will result in calculated lifetime

risks partitioned as Gilbert describes. Some might prefer Gilbert's approach, however, since it

points up the sketchiness of the organ-specific epidemiological data. The BEIR V Committee,

for this reason, also chose to model digestive cancers together as a single class.

Similar considerations apply with respect to the dependence of risk on age at exposure,

where the ICRP incorporates a more detailed breakdown. Due probably in large part to sampling

errors, the ICRP models display some anomalous variations in risk with age at exposure. Such

variations are smoothed out in the NUREG/CR-4214 models, but significant real features of the

age dependence may be lost in the process. 

Gilbert's breast cancer model has the advantage of being derived from North American

data; however, Land and Sinclair's NIH projection of lifetime risk for breast cancer is comparable

to Gilbert's and, qualitatively, exhibits the same sharp decrease in risk with age at exposure. 

Conclusions. Having reviewed the scientific information and models outlined here, we

have chosen to base the risk estimates for most organs on Land and Sinclair's models. (A notable

exception is breast cancer where Gilbert's model is adopted.) In view of the uncertainty over the

transport of risk estimates from Japan to the U.S., we have adopted a methodology, described

below, which yields risk estimates intermediate between the multiplicative and NIH projections

of Land and Sinclair. This methodology has been reviewed and judged acceptable by EPA's

Radiation Advisory Committee (Loehr and Nygaard 1992). 

 B. Transport of Risk Estimates from Japan

Land and Sinclair present two models for calculating risk in a population, differing in

how risk estimates are to be transported from the Japanese atomic bomb survivor study (ABSS)

population. Both models assume a constant excess relative risk coefficient beginning 10 years

after an exposure and continuing throughout the rest of life for each cancer site (except for

leukemia). One model (multiplicative) assumes that the relative risk coefficient is the same

across populations. The other (NIH) assumes that the relative risk coefficients for the target

population should yield the same risks as those calculated with the additive risk coefficients from

the original population over the period of epidemiological follow-up (excluding the minimal

latency period.) These excess relative risk coefficients are then used to project the risk over the

remaining years of life. Projections made for the U.S. using the NIH model are much less

sensitive to differences in site specific baseline rates between Japan and the U.S. than are those

using the multiplicative model.
20

Data on North American women irradiated for medical purposes indicate a similar

attributable risk for breast cancer induction as the ABSS study data, despite the substantially

higher breast cancer rates found in the U.S. or Canada, compared to Japan. For breast cancer,

therefore, the NIH model projection agrees with observation better than the multiplicative model

projection. Comparative data on other radiation-induced cancers, however, are generally lacking

or are too weak to draw any conclusions regarding the transportation of risk estimates from the

ABSS population to the U.S. 

Both transportation models have a degree of biological plausibility. For example, the

multiplicative model is consistent with the hypothesis that radiation acts as an initiator while the

factors responsible for differences in baseline rates act as promoters. Alternatively, if both

radiation and these factors act independently, but at the same stage in the carcinogenesis process,

their effects should be additive, and radiation risks should be similar between populations despite

differences in baseline rates. In actuality, the situation is likely to be more complex than either of

these alternatives, leading to an interaction that is intermediate between multiplicative and

additive. In this case, the radiation risk for the U.S. population may lie between the

multiplicative and NIH projections from the ABSS.

Given the uncertainty in the transportation of risk across populations, we adopt here a

model in which most age and site specific risk coefficients are taken to be geometric means of the

corresponding coefficients from the multiplicative and NIH models of Land and Sinclair. Our

choice of a geometric mean coefficient (GMC) model reflects a judgment regarding the

distribution of uncertainty associated with the transportation of risk. We believe this approach

provides a reasonable central estimate of the risk, by organ and by age at irradiation. While

giving weight to both the multiplicative and NIH approaches, it tends to deemphasize extreme

values (e.g., the multiplicative projection for colon cancer) which may reflect large extrapolations

based on a few excess cancers observed among those exposed as children. (Note: since the risk

coefficients for the respective models are age and sex specific, the average lifetime risks

calculated with the GMC model are, in general, not the same as the geometric means of the

average lifetime risks calculated with the multiplicative and NIH models.)

Risk estimates for esophagus, stomach, colon, lung, ovary, bladder, leukemia, and

residual, derived using the multiplicative, NIH, and geometric mean projection models are given

in Table 2. Shown for comparison are the estimates derived using Gilbert's models for these

same organs. Gilbert's models were, as discussed previously, developed primarily from the same

epidemiological data, but incorporate the author's judgment as to what constitutes a reasonable

central estimate of the risk in light of all available information and uncertainties. As can be seen

from Table 2, the GMC model yields lifetime risks that agree well with those calculated using

Gilbert’s models.
21

Table 2. Comparison of fatal cancer risks (deaths per 10 person-Gy) for the 4

geometric mean coefficient (GMC) projection model with Land & Sinclair

(ICRP) and NUREG/CR-4214 models.

Cancer NUREG/

type CR-4214

 Land & Sinclair 

 GMC

 Mult NIH

Esophagus 16.2 21.3 18.1 14.9

Stomach 29.3 274 88.7 74.3

Colon 381 109 196 149

Lung 265 78.7 143 149

Breast 116 32.7 60.8 46.2

Ovary 47.5 25.0 33.2 32.2

Bladder 64.0 38.9 49.7 49.6

Leukemia 110 97.9 99.1 89.9

Residual 374 276 297 238

 Total 1403 953 986 844

Notes for Table 2.

Model risks are calculated with 1980 U.S. vital statistics for a DDREF of one.

Values in roman type are calculated directly from the models given in the references.

Those in italic type are sums of sites or make use of supplementary information.

The sex and age at exposure specific risk model coefficients for the GMC model are

the geometric means of the corresponding coefficients for the Land and Sinclair (1991)

multiplicative and NIH risk transportation models (see text). Note that since the risk model

coefficients are age and sex specific, the average lifetime risks for the GMC model are not

simply equal to the geometric mean of the risks for the corresponding multiplicative and NIH

models.

The residual risk shown for the NUREG/CR-4214 model (Gilbert 1991) includes the

balance of the digestive site risk.
22

Table 3. Residual site mortality risk coefficients for the additive and

multiplicative projections of Land and Sinclair (1991).

Age group

(y)

Additive Multiplicative

(10 per Gy-y) (per Gy) -4

Male Female Male Female

0-9 0.096 1.73 0.091 2.370

10-19 2.28 1.60 0.762 0.876

20-29 5.42 4.98 0.682 0.969

30-39 4.18 4.16 0.246 0.403

40+ 2.09 2.96 0.052 0.151

 C. Adjustments to Models

For all sites except leukemia, the same temporal response was employed by Land and

Sinclair in both the multiplicative and NIH models; i.e., a constant relative risk with a 10 y

minimal latency period. For leukemia, the temporal dependencies are different. The

multiplicative model presumes a constant relative risk over an expression period extending

from 2 y to 40 y after exposure; the NIH model, on the other hand, presumes a lognormal

variation in relative risk with a width dependent on the age at exposure (National Institutes of

Health 1985). Averaging the risk coefficients corresponding to these two different temporal

models is nonsensical. Before taking the geometric mean of the model coefficients, therefore,

we first adjusted the multiplicative model so that it would exhibit the same form of temporal

response as the NIH model, holding constant the lifetime risk for a given age at exposure. 

The NIH temporal response was chosen over that of the multiplicative model because it

conforms better to the epidemiological data. [The BEIR V Committee preferred a model

incorporating two steps, with the temporal width of the steps dependent on age at irradiation

(NAS 1990)].

In view of the statistical limitations in the data, analysts have assumed a constant ratio

of male to female risk coefficients across ages for all specific cancer sites (Shimizu et al.

1988, Land and Sinclair 1991). Land and Sinclair did not, however, constrain their models

for "residual" cancers in this way. As shown in Table 3, this leads to apparent anomalies in

the risk coefficients for the 0-9 y age group. Due probably to large sampling errors in this

group, the estimated risk coefficient appears to be low for males but high for females. 

Accordingly, we have replaced the 0-9 y values given by Land and Sinclair with those given

for the age group 10-19 y. The overall effect of this change on U.S. population risk estimates

is very slight: about 10% for the residual organ risk and about 2% for the uniform whole body

risk.
23

 D. Other Cancer Sites

For all the sites listed in Table 2, a statistically significant excess of cancer mortality

(at the 95% confidence level) has been observed in the ABSS (Shimizu et al. 1988). The

excess for breast cancer is also statistically significant, but it seems preferable to base the risk

estimate on the available North American data, bypassing the question of transporting risk

estimates across populations. For kidney, the ABSS data are suggestive of a risk but narrowly

miss statistical significance. The existence of a radiogenic kidney cancer risk is, however,

borne out by the cervical cancer study (NAS 1990; Boice et al. 1988). Given the importance

of the kidney as a possible target organ for uranium and some other radionuclides, we have

developed a risk estimate for this site based on the ABSS data. We also present risk estimates

for liver, bone, and thyroid. 

Breast. Using the multiplicative model projection from the Japanese data, a breast

cancer (mortality) risk of 116×10 Gy is calculated. The NIH projection is 32.7×10 Gy . 

-4 -1 -4 -1

Gilbert's model, based on the North American data, yields a lifetime risk of 46.2×10 Gy ,

-4 -1

much closer to the NIH projection. The geometric mean model projection (60.2×10 Gy )

-4 -1

also agrees reasonably well with Gilbert's model estimate.

 Kidney. The age- and sex-averaged excess relative risk (ERR) coefficient for kidney

cancer mortality from the ABSS is 0.5829 Gy , with a 90% confidence interval of (-0.09, -1

1.94). The corresponding absolute risk (AR) coefficient from Table 2B of Shimizu et al.

(1988) is 9×10 (Gy y) . However, these values are based on shielded kerma rather than on -6 -1

organ-absorbed dose as needed for the risk model. Risk coefficients based on kidneyabsorbed dose were calculated assuming that the ratio of the organ-absorbed dose ERR

coefficients to the shielded kerma values is the same as for the bladder. The bladder-absorbed

dose ERR from Table 1 of Land and Sinclair (1991) is 1.3395 Gy and the corresponding -1

shielded kerma value from Table 2-27 of Shimizu et al. (1988) is 1.1343 Gy . Accordingly, -1

the kidney-absorbed dose ERR and AR coefficients for kidney cancer are calculated to be

0.6883 Gy and 1.06×10 (Gy y) , respectively. Using this AR coefficient, the NIH model -1 -5 -1

ERR coefficient is calculated to be 0.2663 Gy . The geometric mean model ERR projection -1

(see Table 4) is 10.9 kidney cancer deaths per 10 Gy, about 20% of bladder cancer mortality. 4

Liver. Based on Thorotrast data, BEIR III and BEIR IV estimate the risk of fatal liver

cancer induction by alpha particle radiation to be 300×10 Gy (NAS 1980, 1988). -4 -1

Assuming an RBE of 10 for alpha particles (see below), a low-LET risk of 30×10 Gy is -4 -1

derived. For purposes of calculation, we have adopted a constant relative risk model

independent of age-at-exposure and sex. 

Bone. As a basis for estimating radiation-induced bone sarcomas, we adopt BEIR IV's

estimate of 2×10 Gy for alpha irradiation by Ra (NAS 1988), derived from the work of -2 -1 224

Mays and Speiss (1984). This estimate, however, refers to average skeletal dose rather than

endosteal cell dose (NAS 1980, 1988; Mays and Speiss 1984). Taking the endosteal dose to

be 7.5 times that of the whole skeleton, the alpha risk estimate is 2.7×10 cases per Gy; for -3
24

low-LET, the risk is again assumed to be 10 times lower (2.7×10 Gy ). About 70% of bone -4 -1

sarcomas are fatal (ICRP 1991); hence, for mortality, the low-LET risk estimate is 1.9×10-4

Gy . The ICRP 60 estimate of bone cancer risk is higher because it confuses endosteal and -1

average skeletal doses (ICRP 1991, Puskin et al. 1992); unfortunately, the NRC erroneously

adopted the ICRP estimate (Gilbert 1991). In a subsequent report (Gilbert 1993), the NRC

has addressed this error. Following BEIR III (NAS 1980), a constant absolute risk model was

selected for projecting risk, with an expression period extending from 2 to 27 years after

exposure.

Thyroid. Thyroid risk estimates are based on NCRP Report 80 (NCRP 1985). Both

the NRC and the ICRP have also adopted this approach (Gilbert 1991, ICRP 1991). The

estimated fatality risk is calculated to be 6.4×10 Gy , 1/10 the incidence risk. The estimated -4 -1

incidence and mortality risks are each reduced by a factor of 3 in the case of exposures to

iodine-125, -129, and -131. [This reduction includes the effect of lowered dose rate on the

risk, as well as possible other factors; hence, the DDREF of 2 applied to organ specific risk

estimates (see below) should not be applied in the case of these radioiodine exposures.]

In addition to thyroid cancers, radiation has been found to induce benign thyroid

nodules. Maxon et al. (1985) has estimated that: for external X or gamma rays, the risk of a

radiogenic thyroid nodule is about 3.7 times that of a radiogenic thyroid cancer; for iodine131, the nodule risk is about 2.1 times the cancer risk.

Skin. Estimates of skin cancer risks are highly uncertain, but the mortality risk is

known to be relatively low. For acute exposures, we have adopted the mortality risk estimate

in ICRP 60, 2×10 Gy ; however, in contrast to ICRP, we have applied a DDREF of 2 in -4 -1

estimating the skin cancer risk at low doses and dose rates (see below).

Radiation induced skin cancers are of two types: basal cell and squamous cell

carcinomas. The former are nearly all curable, perhaps about 99.99%, but about 1% of the

latter may be fatal (ICRP 1991, 1992). As an upper bound, the ICRP estimates that one of six

radiogenic skin cancers would be squamous cell. Based on these considerations, the ICRP

estimates that only 0.2% of all radiation-induced skin cancers are fatal (ICRP 1991, 1992).

The great majority of radiation induced skin cancers should be easily curable and

result in little trauma for the patient (ICRP 1992). However, left unattended, some of these

cancers, though still not fatal, may require more intensive medical treatment or be disfiguring. 

In the absence of data on the fraction of radiogenic skin cancer cases that might be regarded

as serious, we have excluded nonfatal radiogenic skin cancers from the estimates of risk.
25

 E. Summary of Site Specific Cancer Mortality Risk Estimates

Table 4 summarizes an extended set of organ risk estimates calculated using the

revised EPA set of models described above, and using the NUREG/CR-4214 and ICRP

models (Gilbert 1991, Land and Sinclair 1991, ICRP 1991). A detailed listing of age- and

site-specific risk coefficients for the EPA revised models is given in the Appendix. For most

sites, the ICRP estimates reflect the multiplicative and NIH projections of the ABSS estimates

to the U.S.; the basis for ICRP estimates of risk for liver, bone, thyroid, and skin are described

separately in ICRP 60 (ICRP 1991). For comparison purposes, a DDREF of 1 is again

assumed for all sites. The resulting whole body risk calculated using the revised EPA set of

models is 9.72×10 fatal cancers per person-Gy. -2

 F. Incidence Risk Estimates

To obtain estimates of radiation-induced cancer incidence, each site specific mortality

risk estimate is divided by its respective lethality fraction, i.e., the fraction of radiogenic

cancers at that site which are fatal. Aside from thyroid cancer, the lethality fraction is

generally assumed to be the same for radiogenic cancers as for the totality of other cancers at

that site. [An exception is sometimes made for thyroid cancer because the radiogenic cases

are confined to specific types, which have a somewhat lower than average lethality (NCRP

1985)]. 

Table 5 reproduces a list of lethality fractions recommended by ICRP 60. Two

limitations with respect to this list should be noted. First, the values reflect only cancers

appearing in adults. It appears that leukemia is now often curable in children. However, most

radiogenic leukemias in the atomic bomb survivors occurred before successful treatment

became available. Hence, the leukemia mortality risks derived from the Japanese may more

properly reflect incidence rather than mortality for children. Second, the values listed in

Table 5 are, in part, judgments, since there is no completely reliable way to determine long

term survival based on current (or future) treatment modalities. As in the case of childhood

leukemia, however, improved survival would imply an overestimation of mortality risks

rather than an underestimation of incidence.

Recognizing these limitations, we calculate site specific incidence using the ICRP 60

lethality fractions, except for skin, which is projected by this method to contribute most of the

nonfatal cancers induced by uniform whole body irradiation. At least 83% are basal cell

carcinomas ( 0.01% lethality) and the remainder squamous cell carcinomas ( 1% lethality). 

The incidence estimate employed here reflects only fatal cases and omits the much larger

number of nonfatal cases, most of which are easily treated (see Section D).
26

Table 4. Site specific mortality risk estimates (deaths per 10 person-Gy) for proposed 4

EPA model compared with those for ICRP and NUREG/CR-4214 models (male and

female combined, DDREF=1).

Cancer ICRP NUREG/

site Mult NIH CR-4214 EPA

 Esophagus 16.2 21.3 18.1 14.9

 Stomach 29.3 274 88.7 74.3

 Colon 381 109 196.4 149

 Liver 30 30 30.0 29.7

 Lung 265 78.7 143.2 149

 Bone 9.3 9.3 1.9 8.1

 Skin 2.0 2.0 2.0 1.8

 Breast 116 32.7 46.2 46.2

 Ovary 47.5 25.0 33.2 32.2

 Bladder 64.0 38.9 49.7 49.6

 Kidney —— —— 10.9 ——

 Thyroid 7.5 7.5 6.4 6.4

 Leukemia 110 97.9 99.1 89.9

 Residual 325 227 246.2 193

 Total 1403 953 972.0 844

Notes for Table 4

 The ICRP risk estimates for liver, bone, skin, and thyroid are general (rather than sexspecific) estimates from ICRP Publication 60 (ICRP 1991).

 For those sites above (other than breast) that are also shown in Table 1, the proposed EPA

risk model coefficients are the same as those for the geometric mean coefficient (GMC)

model. If the GMC model for the female breast had been used, the breast cancer risk would

be 118.5 and 60.2 per 10 Gy for the female and combined male and female populations, 4

respectively. The total risk estimates would change accordingly.

 The residual risk estimate is different from that in Table 1 because it does not include risks

for sites (viz., liver, bone, skin, kidney, and thyroid) that are specifically estimated.
27

Table 5. Lethality data for adult cancers by site.

Cancer site Lethality

fraction k

Esophagus 0.95

Stomach 0.90

Colon 0.55

Liver 0.95

Lung 0.95

Bone 0.70

Skin 0.002

Breast 0.50

Ovary 0.70

Bladder 0.50

Kidney 0.65

Thyroid 0.10

Leukemia (acute) 0.99

Residual 0.71

Notes for Table 5.

Lethality fractions (mortality:morbidity ratios) except for residual are from Table B-19

of ICRP Publication 60 (ICRP 1991). Residual lethality fraction is calculated from the

corresponding value of (2-k) in Table B-20 of the same document.

 G. Dose and Dose Rate Effectiveness Factor (DDREF)

The issue of DDREF was discussed in Section II.B. After reviewing the information

and arguments pertinent to the choice of a DDREF, we concluded that a value of 2.0 provides

a reasonable "best estimate." The Agency's Radiation Advisory Committee agreed "that this

choice is reasonable and ... consistent with current scientific judgment" (Loehr and Nygaard

1992). A DDREF of 2 has recently been adopted by the ICRP (1991), as well as by other

organizations (Gilbert 1991, CIRRPC 1992), and is expected to be widely applied for

purposes of risk assessment and radiation protection worldwide. The uncertainty in the

DDREF will be factored into EPA's assessments of uncertainty in radiation risk, however.
28

The DDREF will be applied to all organ-specific risks except for the breast. There is

epidemiological evidence that dose fractionation has little or no effect on risk to the breast

(NAS 1988); moreover, the risk model we have adopted is based mainly on fluoroscopy

studies in which the doses were in fact delivered as multiple small fractions (NAS 1990,

Gilbert 1991). Hence, we have adopted a DDREF of 1 for breast cancer. This choice

assumes that the risk (per unit dose) of highly fractionated exposures approximates the risk at

low doses and dose rates.

The conditions under which the DDREF should be applied remain to be defined. 

Although the biological mechanisms are not yet elucidated, according to current thinking: at

low doses, repair is maximal, and the unrepaired DNA damage reflects single track events; at

higher (acute) doses, repair decreases due to damage caused by multiple tracks passing

through the cell nucleus in close temporal proximity. It would appear that repair efficiency is

maximal for all doses below about 0.2 Gy (NCRP 1980). It also appears that DNA repair is

essentially completed within a few hours after radiation-induced damage (Wheeler and

Wierowski 1983, Ullrich et al. 1987). Consequently, maximum repair efficiency should occur

so long as the dose does not exceed 0.2 Gy over a few hours. In view of these considerations,

we have adopted UNSCEAR's recommendation that the DDREF should be applied whenever

the total dose is below 0.2 Gy or the dose rate is below 0.1 mGy/min (UNSCEAR 1993).

 H. Alpha Particle RBE

With the exception of radiation-induced breast cancer and leukemia, we have followed

the ICRP recommendation (ICRP 1991) and assumed that the RBE for alpha particles is 20, in

comparison to low-LET radiation at low doses and dose rates. Where the comparison is made

against acute high doses of low-LET radiation, however, a value of 10 will be assumed for the

alpha particle RBE. Thus the low-LET radiation DDREF of 2 we have used for these cancers

is implicitly incorporated into the RBE value for alpha radiation.

For breast cancer induction, a DDREF of 1 has been adopted (see above). Therefore,

the RBE will be independent of dose and dose rate. Since there is no DDREF correction of

the low-LET breast cancer risk estimates at low doses and dose rates, it is assumed that the

acute high dose RBE of 10 is also applicable to breast cancer at low doses and dose rates.

There is evidence that alpha particle leukemia risks estimated on the basis of an RBE

of 20 are too high (EPA 1991). For this reason, an alpha particle leukemia risk estimate of

5.0×10 Gy is employed, consistent with the available high-LET epidemiological data (NAS -3 -1

1988, EPA 1991). Quantitatively, this would correspond to an RBE of 1 for this site (relative

to low dose, low-LET radiation). This is not to imply that alpha radiation is no more

carcinogenic than low-LET radiation in inducing leukemia. At least in part, the lower than

expected leukemia risk produced by alpha emitters may result from a nonuniform distribution

of dose within the bone marrow (i.e., average doses to sensitive target cells may be

substantially lower than calculated average marrow doses). Thus the RBE of 1 should be
29

regarded as an "effective RBE," that reflects factors other than just the relative biological

sensitivity to high- and low-LET radiations. Finally, we recognize that since the spatial

distribution of the dose within the marrow will differ among alpha emitters, depending on the

distribution of the radionuclide within bone and the energies of the emitted alpha particles, the

effective RBE may be radionuclide dependent. However, this issue cannot be resolved with

current data.

Our radon decay product risk estimates will continue to be based directly on radon

epidemiological data. Currently, EPA's radon risk estimate is 2.2×10 fatal lung cancers per -4

working level month (EPA 1992, Puskin 1992).

 I. Summary of Revisions to EPA Low Dose Risk Estimates

Table 6 lists the revised EPA site specific cancer risk estimates (incidence and

mortality), applicable at low doses and dose rates. For comparison, the corresponding

estimates from EPA's 1989 Background Information Document for the Radionuclides

NESHAPS are shown (EPA 1989). These revised EPA site specific mortality risk estimates

are generally quite close to those in NUREG/CR-4214 (Gilbert 1991).

For low-LET radiation at low doses or dose rates, the lifetime fatal cancer risk estimate

associated with uniform, whole-body irradiation of the U.S. population has increased by 24%,

from 392 to 509 per 10 person-Gy. This value is similar to those determined by NRPB, 4

ICRP, and NRC, and BEIR V, assuming a DDREF of 2. It is estimated that about 70% of all

cancers induced by whole-body irradiation are fatal (nonfatal skin cancers excluded),

corresponding to an incidence risk estimate of 7.61×10 Gy . These increases occur despite -2 -1

the change from a DDREF of 1 in NESHAPS to a value of 2 here; without this change, the

risk estimates would have more than doubled.

It should be emphasized that EPA's previously published lifetime risk estimates for

chronic radionuclide exposures (EPA 1989) cannot be simply scaled by the ratio of wholebody risk estimates to arrive at risk estimates based on the revised models. In general, such

exposures produce a non-uniform dose distribution within the body, which may also be time

varying. As a result, estimation of revised radionuclide specific risks requires more detailed

calculations.
30

Table 6. EPA low dose, low dose rate cancer risks (10 per Gy). -4

Cancer Mortality Morbidity

site NESHAPs Revised NESHAPs Revised

Esophagus 9.1 9.0 9.1 9.5

Stomach 46.0 44.4 60.1 49.3

Colon 22.9 98.2 42.9 178.5

Liver 49.6 15.0 49.6 15.8

Lung 70.1 71.6 74.5 75.4

Bone 2.5 0.9 2.5 1.3

Skin —— 1.0 —— 1.0

Breast 55.4 46.2 142.0 92.5

Ovary —— 16.6 —— 23.7

Bladder 11.8 24.9 21.4 49.7

Kidney 5.9 5.5 21.4 8.4

Thyroid 6.4 3.2 64.3 32.1

Leukemia 44.8 49.6 44.8 50.1

Remainder 67.8 123.1 90.5 173.4

TOTAL 392.1 509.1 623.0 760.6

Notes for Table 6.

The Dose and Dose Rate Effectiveness Factor (DDREF) is 1 for breast and 2 for all

other sites. These risk coefficients are applicable to all doses less than 200 mGy and for total

doses greater than 200 mGy from dose rates less than 0.1 mGy/min. The revised model

morbidity estimate for skin shown is for fatalities only. The entire morbidity risk for skin

would be about 500 times greater. The thyroid morbidity risk includes only malignant

neoplasms and does not include benign tumors or nodules. For most cancer sites, high-LET

(alpha particle) risk estimates have increased by more than the corresponding low-LET

estimates, reflecting the change in RBE from 8 to 20, which comes from adopting a DDREF

correction at low doses of low-LET radiation (EPA 1989, NCRP 1990, ICRP 1991).

For occupational exposures, the mortality and incidence risk estimates are 3.94×10-2

Gy and 5.67×10 Gy , respectively. (Occupational risks were calculated assuming a -1 -2 -1

constant exposure rate for both sexes between the ages of 18 and 65.)
31
32

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36

Appendix A: Calculational Methods

A. Introduction

A radiogenic cancer risk model defines the relationship between radiation dose and the

subsequent force of mortality (or morbidity) attributable to that dose. As such, the model

provides the basis for calculating a time (or age) varying rate coefficient in a death or disease

process model. [General methods for structuring and solving the differential equations

representing such stochastic processes can be found in Chiang (1980).] Thus, to calculate

risks, the radiogenic risk model and other relevant quantities must be incorporated into a

suitable calculational procedure.

The risk calculations in this appendix are for attributable risk. Attributable risk can be

defined as the likelihood of death from (or development of) cancer that, according to the risk

model, is caused by a radiation exposure. By way of comparison, the excess risk calculated in

BEIR V (National Research Council 1990, Vaeth and Pierce 1989) excludes the fraction of

the attributable risk that represents deaths or cases among persons who would be expected to

die from (or to develop) cancer at a later age even if they had not been exposed.

The use of the attributable risk-per-unit-dose coefficients calculated here is limited to

the asymptotic case, i.e., these coefficients can only be used for applications where the

survival function is not significantly affected by the doses being assessed. When this is not

the case, risks must be calculated explicitly for the specific doses under consideration.

Male and female survival data (up to an age of 110 y) are from the U.S. Decennial life

Tables for 1979-1981 (National Center for Health Statistics 1985). These data were used to

calculate a combined life table for a male:female live birth ratio of 1.051. U.S. mortality data

were extracted from 1979-1981 Vital Statistics Mortality Data, Detail Tapes (National Center

for Health Statistics 1982, 1983, 1984). Deaths in these data files are classified according to

the 9th edition of the International Classification of Disease (ICD) codes (Public Health

Service 1980).

Radiogenic risk calculations require integrating functions of the risk model and vital

statistics. The vital statistics are discrete data, typically tabulated at one or five year intervals. 

Radiogenic risk models are usually defined for several different age intervals and are

inherently discontinuous. Previously, such risk model calculations were implemented by

adapting actuarial methods developed for life table calculations, e.g., the CAIRD program

(Cook et al. 1978). The method used here is to fit a cubic spline to discrete data and then to

calculate interpolated values, derivatives, and integrals directly from the spline coefficients

(de Boor 1978, Fritsch and Butland 1982). This method admits almost any form of risk

model and eliminates most of the ad hoc approaches that were necessary with CAIRD. 
(x,xe

) (xe) (t,xe) (x)

(x,xe) (xe) (t,xe) (x)

37

B. Risk Model Formulation

There are two basic types of radiogenic cancer risk projection models: absolute risk

and relative risk. An absolute risk model presumes that the age-specific excess force of

mortality (or morbidity) due to a radiation dose is independent of cancer mortality or

morbidity rates in the population. It can be written as 

(1)

where (x,x ) is the excess force of mortality (or morbidity) (y Gy ) at age x due to a dose at e

-1 -1

age x (x > x ), e e

(x ), the absolute risk coefficient (y Gy ), is a function of age at exposure, x ,

e e

-1 -1

(t,xe), the time since exposure (t = x-xe) response function, can also be a function

of x ,

e

and (x) is the age at expression response function,

The radiogenic risk models for bone, skin, and thyroid cancer in the Revised Methodology are

all absolute risk models.

A relative risk model presumes that the age-specific excess force of mortality (or

morbidity) due to a radiation dose is the product of an exposure-age-specific relative risk

coefficient and baseline cancer mortality or morbidity rates in the population. The model can

be written as

(2)

where (x,x ) is the relative risk (Gy ) at age x due to a dose at age x (x > x ), e e e

-1

(x ), the relative risk coefficient (Gy ), is a function of age at exposure, x ,

e e

-1

(t,x ), the time since exposure (t=x-x ) response function, may also be a function of x ,

e e e

and (x) is the age at expression response function.

C. Revised Methodology Risk Models

Risk model coefficients

Risk coefficients for the Revised Methodology mortality risk models are shown in

Table A.1. Absolute risk models are used for bone, skin, and thyroid cancers. Relative risk

models are used for all other cancers.
38

Table A.1 Coefficients for the Revised Methodology mortality risk model (male and

female by age group).

Cancer Risk Age group

type model

type* 0-9 10-19 20-29 30-39 40+

Male:

Esophagus R 0.2239 0.2312 0.2517 0.2892 0.3258

Stomach R 1.2337 1.9165 1.9051 0.2881 0.2524

Colon R 2.1565 2.1565 0.2809 0.4275 0.0899

Liver R 1.3449 1.3449 1.3449 1.3449 1.3449

Lung R 0.4060 0.4060 0.0453 0.1342 0.1794

Bone A 0.0927 0.0927 0.0927 0.0927 0.0927

Skin A 0.0672 0.0672 0.0672 0.0672 0.0672

Breast R 0.0 0.0 0.0 0.0 0.0

Ovary R 0.0 0.0 0.0 0.0 0.0

Bladder R 1.2191 1.1609 1.0736 1.0544 0.9639

Kidney R 0.3911 0.3911 0.3911 0.3911 0.3911

Thyroid A 0.1667 0.1667 0.0833 0.0833 0.0833

Leukemia R 672.16 244.07 323.47 228.86 142.51

Residual R 0.7115 0.7140 0.1735 0.1754 0.1847

Female:

Esophagus R 1.0418 1.0896 1.2492 1.5831 2.0211

Stomach R 3.4469 4.2721 4.0533 0.5797 0.4887

Colon R 2.9680 2.9680 0.5755 0.8186 0.1870

Liver R 1.3449 1.2449 1.3449 1.3449 1.3449

Lung R 1.3753 1.3753 0.1921 0.5440 0.8048

Bone A 0.0927 0.0927 0.0927 0.0927 0.0927

Skin A 0.0672 0.0672 0.0672 0.0672 0.0672

Breast R 0.7000 0.7000 0.3000 0.3000 0.1000

Ovary R 1.3163 1.0382 0.8829 0.7678 0.6367

Bladder R 1.0115 0.9296 1.0124 1.1032 0.9792

Kidney R 0.3911 0.3911 0.3911 0.3911 0.3911

Thyroid A 0.3333 0.3333 0.1667 0.1667 0.1667

Leukemia R 761.07 225.81 281.76 153.12 154.28

Residual R 0.7119 0.7174 0.2932 0.2963 0.3031

*Notes:

Risk model type Coefficient units

Absolute (A) 10 (Gy y) -4 -1

Relative (R) Gy-1
(t) 0, t < 10

1, 10 t

(t) 0, t < 2

1, 2 t < 27

0, 27 t

(t) 0, t < 5

1, 5 t

(t,xe) 0, t < 2

(t, (xe),

2

), 2 t

(t, (xe),

2

)

exp 0.5(ln(t 2) (xe))

2

/

2

(t 2) 2

2

.

(t,xe) 0.32 (t,

cgl(xe

),

2

cgl) 0.68 (t,

al(xe

),

2

al) .

39

Time since exposure response function

The time since exposure (TSE) response function for all cancers except bone, thyroid, and

leukemia has a 10 y minimal latency period and a lifetime plateau, i.e.,

(3)

while for bone cancer,

(4)

and for thyroid cancer,

(5)

For leukemia, the TSE function developed by the NIH Working Group for the

Radioepidemiology Tables (National Institutes of Health 1985) is used. The Working Group

fitted lognormal response functions for time since exposure greater than a minimal latency of

2 years to A-bomb survivor data for both chronic granulocytic leukemia (CGL) and acute

leukemia (AL). These response functions can be expressed as follows:

(6)

where

(7)

The values of (xe

) and are 2.68 and 1.51, respectively, for CGL. For AL, they are the 2

value of the expression 1.61+0.151xe+0.0005xe and 0.65, respectively. The total leukemia 2

response function is a weighted mean of the CGL and AL response functions:

(8)

Since this TSE function has a maximum value that is much less than 1, the risk model

coefficients for leukemia in Table A.1 are much larger than those for other sites.

Age at expression function

The age at expression function, (x), is equal to one for all models in the Revised

Methodology.
e°(x)

1

S(x) x

S(u)du .

μ(x)

alli

μi(x) .

S(x) exp(

x

0

μ(u)du) .

S(x) exp(

x

0

(μ0(u) μi(u))du)

S0(x) Si(x) ,

S0(x) exp(

x

0

μ0(u)du) ,

Si(x) exp(

x

0

μi(u)du) .

40

D. Risk Calculations

Basic quantities

S(x), the survival function, is the fraction of live born individuals expected to survive

to age x. S(0)=1, and decreases monotonically for increasing values of x. S(x) is obtained by

fitting a cubic spline to the decennial life table values to provide a continuous function of x.

°e(x) is the expected lifetime (years) remaining for an individual who has attained age

x. It is given by

(9)

μ(x) is the force of mortality or hazard rate (y ) at age x. Without a subscript, it is -1

usually the total rate from all causes. A subscript is used (unless it is clear by context) to

indicate a specific cause, i.e.,

(10)

S(x) is directly dependent on μ(x) since

(11)

When the baseline force of mortality μ (x) is incremented by μ (x), S(x) becomes 0 i

(12)

where

(13)

and

(14)

For sufficiently small values of μ (x), S (x) approaches a value of 1 for all values of x, i.e., i i

S (x) and S(x) are essentially the same. For most environmental radiation risk assessment 0

cases of practical interest, the increment of risk due to radiation satisfies this condition.
r

i

(x)

1

S0(x) x

i

(u)S0(u)du .

r

i

(x)

1

S0(x) x

i

(u)μi(u)S0(u)du .

ei(x)

1

S0(x) x

i

(u)e°(u)S0(u)du .

ei(x)

1

S0(x) x

i

(u)μi(u)e°(u)S0(u)du .

r ̄

0

r(x)S(x)dx

0

S(x)dx

0

r(x)S(x)dx

e°

,

41

Attributable lifetime risk coefficient

The age-specific attributable lifetime risk (ALR) coefficient, r(x), is the risk per unit

dose of a subsequent cancer death (Gy ) due to radiation received at age x. For an absolute -1

risk model, the asymptotic ALR coefficient is

(15)

Similarly, for a relative risk model,

(16)

These age-specific coefficients are principally used to calculate age-averaged coefficients and

risks from radionuclide intakes or exposures.

Attributable lifetime loss coefficient

The attributable lifetime loss (ALL) coefficient e(x), at age x, is the expected lifetime

loss per unit dose (y Gy ) for a radiation dose a age x. For an absolute risk model, the -1

asymptotic ALL coefficient is

(17)

For a relative risk model,

(18)

Age-averaged coefficients

The lifetime age-averaged risk and life loss coefficients are

(19)

and
e ̄

0

e(x)S(x)dx

0

S(x)dx

0

e(x)S(x)dx

e°

,

Sc(x)

1.051 Sm(x) Sf(x)

2.051

,

e°c

1.051 e°me°f

2.051

.

μc(x)

1.051 Sm(x)μm(x) Sf(x)μf(x)

1.051 Sm(x) Sf(x)

.

r

c

(x)

1.051 Sm(x)rm(x) Sf(x)r

f

(x)

1.051 Sm(x) Sf(x)

,

42

(20)

respectively. Since the age distribution of a stationary population is proportional to S(x), the

stationary-population weighted average values are identical to the lifetime age-averaged ones. 

When the coefficients are averaged over a specific age interval, e.g., for assessing childhood

or occupational exposures, the limits of integration in both the numerators and the

denominators of these expressions are changed accordingly.

Sex-averaged coefficients

Since radiogenic cancer risk models are generally sex-specific, the resulting risk

coefficients must be averaged for use in assessing risk to a combined population. This is

accomplished by presuming a male:female sex ratio for live births of 1.051. Since S(x) is sexspecific, the sex ratio is a function of age. The combined (sex-averaged) survival function is

(21)

where the subscripts m, f, and c refer to the male, female, and combined values respectively. 

Similarly, the expected combined lifetime is

(22)

The combined age-specific force of mortality must reflect the age-specific contribution of

each sex. Hence,

(23)

Combined age-specific ALR and ALL coefficients are

(24)

and
ec

(x)

1.051 Sm(x)em(x) Sf(x)ef(x)

1.051 Sm(x) Sf(x)

.

r

c

1.051 e°mrme°fr

f

1.051 e°m

e°f

,

ec

1.051 e°meme°fef

1.051 e°me°f

.

43

(25)

respectively. Combined age averaged ALR and ALL values must reflect the expected lifetime

over the age interval. The lifetime average combined ALR and ALL coefficients are

(26)

and

(27)

Continuity considerations

While the integration of a smoothly varying function using a spline is straightforward,

the radiogenic cancer models are inherently discontinuous. For example, the time since

exposure function for most solid cancers typically has a value of zero for times since exposure

that are less than the 10 y minimal latency and a value of one for times equal to or greater

than the minimal latency. Suppose that the function to be integrated (the integrand) is fitted at

one year increments. For the Revised Methodology models, the function will change abruptly

from a value of zero for times since exposure less than 10 y to a generally smoothly varying

function of time for times equal to or greater than 10 years. However fitting a spline to the

integrand provides a continuous transition from the value at 9 y to the value at 10 y. If the

integral is evaluated on the basis of these spline coefficients, it will include an unintended

contribution from this interval.

One way to solve the problem is to integrate functions in piece-wise continuous

intervals. This method is exact and would work well for the simple example considered

above. In general, however, the value of the integrand at each discontinuity depends on the

interval of integration; the method becomes unwieldy for situations with many discontinuities. 

An alternative method for situations where the function is reasonably smooth on either side of

a discontinuity is to replace the value of the function at the discontinuity with the average of

the values immediately above and below it. For the case above, the value of the time since

exposure response function at 10 y is changed from 1 to (0+1)/2=0.5. The reduced excess in

the integral between 9 and 10 y is then compensated for by a comparable reduction in the 10

to 11 year interval. This discontinuity smoothing method was used to calculate the risks and

lifetime losses for this report.

Cancer type and dose location associations
44

The dose locations associated with each cancer type are shown in Table A.2. When

more than one dose location is shown in the table, risks are calculated for a weighted mean of

the doses at these locations using the weights shown in the table. The residual cancer

category represents a composite of primary and secondary cancers that are not otherwise

considered in the model. The dose location associated with these cancers, the pancreas, was

chosen to be generally representative of soft tissues; the pancreas is not considered the origin

of all these neoplasms.

Table A.2 Dose regions associated with cancer types in the Revised Methodology risk

models.

Cancer type Dose region Weighting

factor

Esophagus Esophagus 1.0

Stomach Stomach wall 1.0

Colon Upper Large Intestine wall 0.5

Lower Large Intestine wall 0.5

Liver Liver 1.0

Lung Tracheo-bronchial region 0.8

Pulmonary region 0.2

Bone Bone surface 1.0

Skin Dermis 1.0

Breast Female breast 1.0

Ovary Ovary 1.0

Bladder Urinary bladder wall 1.0

Kidney Kidney 1.0

Thyroid Thyroid 1.0

Leukemia Red bone marrow 1.0

Residual Pancreas 1.0
mi

x

i

x

i 1

μ(x)S(x)dx S(xi 1) S(xi) ,

mij

x

i

xi 1

μj(x)S(x)dx

nij mi

ni

nij

ni

[S(xi 1) S(xi)] .

45

Cancer morbidity calculations

While the calculational methodology outlined above could be used with incidence

models and force of morbidity data, the method used for the Revised Methodology is to

divide the mortality risk coefficient by a corresponding lethality factor, k, (see Section IV.F). 

An exception is made for skin; only mortality is considered for calculating skin cancer

morbidity, i.e., k is considered to be 1. The lifetime loss coefficient is not recalculated for

morbidity.

E. Baseline Force of Mortality Calculations

Age-specific mortality rates (force of mortality) were calculated at one year intervals

using U.S. death data for the period 1979-1981 (National Center for Health Statistics 1982,

1983, 1984). These calculations assume that the fraction of the recorded deaths in each age

group due to a given cause, e.g., a specific ICD code, is the same as the probability of death in

that age interval for a birth cohort with the corresponding age-specific death rate. In

summary,

let n be the number of deaths due to all causes between ages x and x ,

i i-1 i

n be the number of deaths due to cause j between ages x and x ,

ij i-1 i

m be the probability in a birth cohort of dying from all causes between ages x and x ,

i i-1 i

and m be the probability in a birth cohort of dying from cause j between ages x and x .

ij i-1 i

Then, given the age-specific forces of mortality, μ(x) and μ (x), and the survival function, j

S(x),

(28)

and

(29)

(For i=0, xi, ni, nij, mi, and mij are all equal to 0 as well.) Let 

 Mj

(xi) be the probability in a birth

cohort of dying from cause j by age x , i.e., i
Mj

(xi)

x

i

0

μj(x)S(x)dx

i

k 0

mkj .

dMj(x)

dx

μj(x)S(x) .

μj(x)

1

S(x)

dMj(x)

dx

.

r

a

(x

i

)

1

S(x

i

) x

i

d(x)r(x)S(x) dx ,

46

(30)

Differentiating the expression for M (x) with respect to x,

j

(31)

Solving for the force of mortality,

(32)

Hence, point estimates of μ (x) can be calculated by fitting a spline to M (x), calculating its j j

derivative with respect to x from the spline coefficients, and dividing the derivative by the

value of the survival function at x.

The ICD-9-CM codes for malignant neoplasms used to define each cancer type in the

model are listed in Table A.3. Even though baseline mortality rates are not necessary for

absolute risk model calculations, these definitions serve to clarify which ICD codes are

considered to comprise each cancer type.

F. Radionuclide Risk Coefficients

Age-specific radionuclide risk calculations

The age-specific cancer risk attributable to a unit intake of a radionuclide (Bq ) is -1

calculated from the absorbed dose rate due to a unit intake of activity and the age-specific risk

per unit dose coefficient. The calculation is specific for each cancer and associated absorbed

dose site in the risk model. The complete calculation may involve the sum of contributions

from more than one tissue (see Table A.2) and from both low- and high-LET absorbed doses. 

Except for leukemia, the Revised Methodology radiogenic cancer risk relative biological

effectiveness (RBE) for a high-LET absorbed dose from alpha radiation is 20 times that for a

low dose, low dose rate low-LET absorbed dose. For leukemia, the effective alpha dose RBE

is 1, as discussed in the main text. Each risk contribution is calculated as follows:

(33)

where r (x ) is the cancer risk coefficient (Bq ) for a unit intake of activity at age x , a i i

-1
r ̄a

0

r

a

(x)S(x)dx

e°

,

r

a

(xi)

1.051 rma(xi)Sm(xi) r

fa(xi

)Sf(xi)

1.051 Sm(xi) Sf(xi)

,

47

(35)

d(x) is the absorbed dose rate (Gy y ) at the site at age x due to a unit intake of activity -1

at age x ,

iii

r(x) is the cancer risk due to a unit absorbed dose (Gy ) at the site at age x,

-1

and S(x) is the survival function at age x.

Sex-averaged risk coefficient

Age-specific male and female risk coefficients are combined by calculating a weighted

mean:

(34)

where r (x) is the combined cancer risk coefficient (Bq ) for a unit intake of activity at age x , a i

-1

1.051 is the presumed sex ratio at birth (male:female),

rma(x) is the male risk per unit activity at age x ,

i

r (x) is the female risk per unit activity at age x ,

fa i

Sm(x ) is the male survival function at age x ,

i i

and S (x ) is the female survival function at age x .

f i i

This formulation weights each sex-specific risk coefficient by the proportion of that sex in a

stationary combined population at the desired age of intake.

Average lifetime risk coefficient

The average lifetime risk coefficient (Bq ) for a unit intake of a radionuclide is -1

calculated from the age-specific value, r (x), by the equation: a

where  ̄ra (Bq ) is the average lifetime risk per unit intake of activity -1

and °e is the expected lifetime at age 0.
r ̄a

1.051 r ̄ma e°mr ̄fa e°f

1.051 e°m

e°f

.

48

Table A.3 ICD codes used to define cancer types.

Cancer type ICD-9-CM codes

Esophagus 150.0-150.9

Stomach 151.0-151.9

Colon 153.0-153.9

Liver 155.0-155.2

Lung 162.0-162.9

Bone 170.0-170.9

Skin 173.0-173.9

except 172.0-172.9 (melanoma)

Breast 174.0-174.9 (female)

 and 175.0-175.9 (male)

Ovary 183.0

Bladder 188.0-188.9

Kidney 189.0-189.1

Thyroid 193.0-193.9

Leukemia 204.0-208.9

except 204.1 (chronic lymphoid)

EPA residual 140-208

except 181 (placenta), and all codes included

in the above definitions.

Equation (35) also provides the lifetime risk per unit intake for a lifetime intake at a constant

intake rate. For a stationary population, the expected incidence or mortality per unit activity

intake (cases per Bq or deaths per Bq) is also given by equation (35).

The sex-weighted average is given by

(36)

Radionuclide risk coefficients for external exposures

Lifetime risks for external radionuclide exposures are calculated in a similar manner to

those for radionuclide intakes. Since the organ and tissue doses occur at the same time as the

exposure and are not considered to be age dependent, the calculations are simpler. Given the

age specific cancer risk per unit dose, r(x), from equation (15) or (16) and the corresponding
r

e

(x) der(x)

r ̄eder ̄ .

49

(37)

(38)

dose per unit exposure coefficient, de (e.g., Gy per Bq y/m to the thyroid from ground surface 2

exposure to Co), the lifetime risk is simply 60

for an exposure at age x. The average lifetime risk,  ̄r is just e

Equation (38) can also be used in the same manner as equation (35) to calculate lifetime risk

from lifetime exposure at a constant exposure rate or population risk from an external

exposure.

Radionuclide Risk Coefficient Tables

Average lifetime mortality and morbidity (incidence) risk coefficients for the 321

radionuclides in Tables A.4a and A.4b, respectively, were calculated with CRDARTAB

(Sjoreen 1994) using RADRISK dose rates and Revised Methodology risk coefficients. The

coefficients correspond to the sums of risks for all cancers using equations (35) or (38) for

intakes and external exposures, respectively. The default clearance class for inhalation and

the digestive tract to blood transfer factor, f1, for each element (or radionuclide when

necessary) are shown in Table A.5. These clearance class and f1 defaults were chosen

conservatively, i.e., among the standard values that might be appropriate for environmental

exposures, they yield the greatest risks.
50

Table A.4a Revised Methodology radionuclide mortality risk coefficients.))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) Internal External 

)))))))))))))))))))))) )))))))))))))))))))))))

Nuclide Ingestion Inhalation Submersion Gnd Surface (Bq ) (Bq ) (per (per -1 -1 Bq y/m ) Bq y/m ) 3 2)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))H-3 1.28E-12 1.73E-12 Be-7 1.38E-12 3.56E-12 2.83E-09 5.88E-11C-11 1.01E-12 8.36E-13 5.83E-08 1.20E-09C-14 1.93E-11 1.31E-13 C-15 1.58E-14 2.06E-14 2.68E-07 3.10E-09N-13 7.01E-13 6.36E-13 5.83E-08 1.20E-09O-15 2.23E-13 2.45E-13 5.83E-08 1.20E-09F-18 2.34E-12 1.56E-12 5.65E-08 1.17E-09Na-22 1.50E-10 8.95E-11 1.29E-07 2.42E-09Na-24 2.57E-11 1.52E-11 2.82E-07 4.20E-09Si-31 8.42E-12 8.09E-12 5.35E-11 9.35E-13P-32 1.14E-10 6.21E-11 P-33 1.42E-11 7.91E-12 S-35 6.92E-12 3.33E-12 Cl-36 4.02E-11 2.36E-11 3.27E-16 3.60E-17Cl-38 4.72E-12 4.06E-12 1.01E-07 1.57E-09Ar-41 1.05E-14 7.74E-08 1.35E-09K-40 2.28E-10 1.33E-10 9.49E-09 1.60E-10K-42 2.36E-11 1.65E-11 1.70E-08 2.83E-10Ca-45 3.84E-11 5.77E-11 5.92E-19 1.56E-19Ca-47 1.05E-10 1.04E-10 6.41E-08 1.13E-09Sc-46 8.87E-11 2.73E-10 1.22E-07 2.26E-09Sc-47 4.44E-11 3.83E-11 6.10E-09 1.35E-10Sc-48 1.03E-10 7.99E-11 2.04E-07 3.67E-09V-48 1.17E-10 1.32E-10 1.76E-07 3.21E-09Cr-51 2.16E-12 3.59E-12 1.77E-09 3.82E-11Mn-52 9.59E-11 8.34E-11 2.08E-07 3.81E-09Mn-54 3.32E-11 7.31E-11 5.05E-08 9.73E-10Mn-56 1.46E-11 1.26E-11 1.09E-07 1.88E-09Fe-55 6.24E-12 1.08E-11 8.87E-13 1.71E-13Fe-59 9.56E-11 1.37E-10 7.20E-08 1.28E-09Co-57 1.65E-11 6.47E-11 6.65E-09 1.50E-10Co-58 4.69E-11 1.07E-10 5.83E-08 1.14E-09Co-58m 1.49E-12 1.93E-12 1.33E-12 2.75E-13Co-60 3.36E-10 1.46E-09 1.51E-07 2.65E-09Ni-59 3.04E-12 8.00E-12 1.48E-12 3.22E-13Ni-63 8.85E-12 2.01E-11 Ni-65 9.51E-12 8.80E-12 3.34E-08 5.78E-10Cu-64 8.29E-12 9.33E-12 1.09E-08 2.22E-10Zn-65 1.78E-10 1.94E-10 3.52E-08 6.37E-10Zn-69 1.29E-12 2.67E-12 3.40E-13 7.16E-15)))))))))))))))))

))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) Internal External 

)))))))))))))))))))))) )))))))))))))))))))))))

Nuclide Ingestion Inhalation Submersion Gnd Surface (Bq ) (Bq ) (per (per -1 -1 Bq y/m ) Bq y/m ) 3 2)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))Zn-69m 2.36E-11 2.57E-11 2.36E-08 4.95E-10Ga-67 1.28E-11 9.81E-12 7.97E-09 1.77E-10Ga-72 7.38E-11 4.39E-11 1.77E-07 2.97E-09Ge-71 2.03E-13 1.45E-12 3.52E-12 9.03E-13As-73 1.28E-11 3.09E-11 1.97E-10 8.14E-12As-74 6.62E-11 9.71E-11 4.43E-08 9.00E-10As-76 1.01E-10 9.16E-11 2.55E-08 4.91E-10As-77 2.52E-11 2.40E-11 4.86E-10 1.04E-11Se-75 1.21E-10 9.46E-11 2.17E-08 4.73E-10Br-82 2.54E-11 1.45E-11 1.58E-07 3.00E-09Kr-83m 7.81E-16 3.41E-12 8.26E-13Kr-85 6.08E-15 1.28E-10 2.63E-12Kr-85m 5.93E-15 8.83E-09 1.95E-10Kr-87 2.68E-14 5.23E-08 8.65E-10Kr-88 4.60E-14 1.34E-07 2.08E-09Kr-89 3.68E-14 1.19E-07 1.95E-09Kr-90 3.86E-14 7.82E-08 1.39E-09Rb-82 2.51E-13 3.00E-13 6.29E-08 1.29E-09Rb-86 1.38E-10 8.28E-11 5.75E-09 1.05E-10Rb-87 7.27E-11 4.43E-11 Rb-88 3.47E-12 3.46E-12 4.22E-08 6.78E-10Rb-89 1.97E-12 1.73E-12 1.33E-07 2.23E-09Sr-82 4.06E-10 1.68E-10 1.20E-11 2.89E-12Sr-85 2.39E-11 2.07E-11 2.92E-08 6.04E-10Sr-85m 3.38E-13 1.51E-13 1.21E-08 2.64E-10Sr-89 1.63E-10 7.18E-11 8.32E-12 1.57E-13Sr-90 9.64E-10 1.51E-09 Sr-91 4.42E-11 1.46E-11 4.16E-08 7.85E-10Sr-92 3.14E-11 8.53E-12 8.09E-08 1.39E-09Y-90 2.25E-10 1.89E-10 Y-91 2.02E-10 4.05E-10 2.18E-10 3.86E-12Y-91m 6.76E-13 7.02E-13 3.06E-08 6.24E-10Y-92 3.15E-11 3.92E-11 1.53E-08 2.81E-10Y-93 8.76E-11 7.55E-11 5.60E-09 9.90E-11Zr-93 8.55E-12 1.29E-10 Zr-95 5.99E-11 1.33E-10 4.39E-08 8.62E-10Zr-97 1.57E-10 9.39E-11 1.09E-08 2.01E-10Nb-93m 1.00E-11 1.07E-10 4.42E-12 6.78E-13Nb-94 1.08E-10 1.79E-09 9.47E-08 1.84E-09Nb-95 3.50E-11 6.27E-11 4.59E-08 8.96E-10Nb-95m 4.60E-11 4.32E-11 3.34E-09 7.48E-11))))))))))))))))))
51

Table A.4a Revised Methodology radionuclide mortality risk coefficients. (cont.)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) Internal External 

)))))))))))))))))))))) )))))))))))))))))))))))

Nuclide Ingestion Inhalation Submersion Gnd Surface (Bq ) (Bq ) (per (per -1 -1 Bq y/m ) Bq y/m ) 3 2)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))Nb-97 3.34E-12 5.38E-12 3.92E-08 7.82E-10Nb-97m 6.41E-14 8.41E-14 4.36E-08 8.54E-10Mo-99 3.88E-11 8.60E-11 9.15E-09 1.82E-10Tc-95 1.22E-12 7.59E-13 4.72E-08 9.21E-10Tc-95m 2.22E-11 4.38E-11 3.91E-08 7.85E-10Tc-96 3.95E-11 3.86E-11 1.51E-07 2.90E-09Tc-96m 4.66E-13 4.83E-13 2.50E-09 4.90E-11Tc-97 2.83E-12 8.02E-12 3.05E-11 4.13E-12Tc-97m 2.10E-11 4.49E-11 4.33E-11 3.71E-12Tc-99 2.49E-11 6.75E-11 2.63E-14 6.22E-16Tc-99m 8.87E-13 7.66E-13 7.02E-09 1.56E-10Ru-97 9.18E-12 7.83E-12 1.28E-08 2.82E-10Ru-103 5.09E-11 9.66E-11 2.76E-08 5.70E-10Ru-105 1.83E-11 1.82E-11 4.62E-08 9.24E-10Ru-106 5.28E-10 2.75E-09 Rh-103m 1.66E-13 3.26E-13 6.59E-12 7.46E-13Rh-105 2.91E-11 2.38E-11 4.37E-09 9.40E-11Rh-105m 1.98E-14 2.11E-14 1.51E-09 3.66E-11Rh-106 8.78E-14 1.18E-13 1.21E-08 2.41E-10Pd-100 5.76E-11 6.71E-11 Pd-101 5.89E-12 4.82E-12 Pd-103 1.58E-11 2.23E-11 6.03E-11 6.62E-12Pd-107 3.14E-12 3.61E-11 Pd-109 5.05E-11 4.17E-11 3.94E-11 8.11E-13Ag-105 2.67E-11 4.75E-11 Ag-108 1.69E-13 2.42E-13 1.02E-09 2.07E-11Ag-108m 1.03E-10 1.49E-09 9.41E-08 1.90E-09Ag-109m 6.55E-15 8.87E-15 2.04E-10 7.24E-12Ag-110 5.94E-14 8.10E-14 1.80E-09 3.59E-11Ag-110m 1.43E-10 6.78E-10 1.65E-07 3.11E-09Ag-111 1.03E-10 1.01E-10 1.48E-09 3.19E-11Cd-109 1.38E-10 4.29E-10 7.25E-11 6.22E-12Cd-115 1.10E-10 9.45E-11 1.17E-08 2.40E-10Cd-115m 2.19E-10 3.64E-10 1.33E-09 2.44E-11In-113m 1.50E-12 1.43E-12 1.44E-08 3.07E-10In-114 1.10E-13 1.49E-13 1.85E-09 3.71E-11In-114m 3.18E-10 5.39E-10 5.15E-09 1.08E-10In-115 8.14E-10 5.00E-09 In-115m 5.46E-12 4.09E-12 8.92E-09 1.93E-10Sn-113 5.66E-11 1.46E-10 3.92E-10 1.26E-11Sn-121 1.84E-11 1.20E-11 )))))))))))))))))

))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) Internal External 

)))))))))))))))))))))) )))))))))))))))))))))))

Nuclide Ingestion Inhalation Submersion Gnd Surface (Bq ) (Bq ) (per (per -1 -1 Bq y/m ) Bq y/m ) 3 2)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))Sn-121m 3.08E-11 1.63E-10 1.23E-11 4.38E-13Sn-125 2.51E-10 2.32E-10 1.88E-08 3.39E-10Sn-126 3.26E-10 9.07E-10 2.36E-09 5.89E-11Sb-122 1.33E-10 1.04E-10 2.57E-08 5.21E-10Sb-124 1.65E-10 2.70E-10 1.16E-07 2.05E-09Sb-125 4.59E-11 1.10E-10 2.43E-08 5.01E-10Sb-126 1.51E-10 1.62E-10 1.63E-07 3.24E-09Sb-126m 1.60E-12 1.62E-12 9.22E-08 1.85E-09Sb-127 1.28E-10 1.16E-10 3.88E-08 7.78E-10Sb-129 2.92E-11 1.95E-11 8.69E-08 1.63E-09Te-125m 4.08E-11 6.14E-11 3.42E-10 1.48E-11Te-127 1.32E-11 9.46E-12 2.74E-10 5.79E-12Te-127m 1.02E-10 2.99E-10 1.12E-10 4.74E-12Te-129 2.90E-12 3.71E-12 3.08E-09 6.38E-11Te-129m 1.84E-10 2.87E-10 1.94E-09 4.02E-11Te-131 2.59E-12 2.67E-12 2.44E-08 4.91E-10Te-131m 8.77E-11 7.06E-11 8.59E-08 1.63E-09Te-132 1.66E-10 1.45E-10 1.19E-08 2.66E-10I-122 5.12E-13 5.69E-13 5.59E-08 1.14E-09I-123 2.24E-12 1.31E-12 8.58E-09 1.94E-10I-125 7.24E-11 4.78E-11 3.86E-10 1.71E-11I-126 1.38E-10 9.01E-11 2.65E-08 5.38E-10I-129 5.06E-10 3.35E-10 2.98E-10 1.56E-11I-130 2.04E-11 1.19E-11 1.26E-07 2.50E-09I-131 1.04E-10 6.72E-11 2.16E-08 4.55E-10I-132 6.30E-12 4.00E-12 1.37E-07 2.64E-09I-133 3.53E-11 2.11E-11 3.52E-08 7.06E-10I-134 3.87E-12 2.62E-12 1.60E-07 2.99E-09I-135 1.12E-11 6.80E-12 9.74E-08 1.69E-09Xe-122 5.60E-14 3.23E-09 7.54E-11Xe-123 1.39E-14 3.63E-08 7.08E-10Xe-125 1.93E-14 1.38E-08 3.01E-10Xe-127 7.37E-15 1.44E-08 3.21E-10Xe-129m 1.09E-14 1.01E-09 3.78E-11Xe-131m 7.86E-15 3.65E-10 1.42E-11Xe-133 7.87E-15 1.64E-09 4.58E-11Xe-133m 9.81E-15 1.54E-09 3.99E-11Xe-135 1.44E-14 1.39E-08 3.00E-10Xe-135m 3.81E-15 2.45E-08 5.05E-10Xe-137 3.17E-14 1.10E-08 2.16E-10Xe-138 4.21E-14 7.33E-08 1.23E-09)))))))))))))))))
52

Table A.4a Revised Methodology radionuclide mortality risk coefficients. (cont.)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) Internal External 

)))))))))))))))))))))) )))))))))))))))))))))))

Nuclide Ingestion Inhalation Submersion Gnd Surface (Bq ) (Bq ) (per (per -1 -1 Bq y/m ) Bq y/m ) 3 2)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))Cs-131 3.28E-12 1.91E-12 2.51E-10 1.39E-11Cs-134 8.49E-10 5.01E-10 9.22E-08 1.82E-09Cs-134m 9.17E-13 7.09E-13 1.04E-09 2.71E-11Cs-135 8.27E-11 4.78E-11 Cs-136 1.38E-10 8.10E-11 1.30E-07 2.47E-09Cs-137 5.71E-10 3.34E-10 Cs-138 3.96E-12 3.21E-12 1.49E-07 2.52E-09Ba-131 2.64E-11 8.35E-12 2.56E-08 5.46E-10Ba-133 4.53E-11 7.90E-11 2.02E-08 4.52E-10Ba-133m 4.17E-11 9.49E-12 3.03E-09 7.19E-11Ba-137m 5.35E-14 3.90E-14 3.52E-08 7.01E-10Ba-139 5.72E-12 3.59E-12 1.96E-09 4.19E-11Ba-140 1.78E-10 5.49E-11 1.07E-08 2.23E-10La-140 1.44E-10 9.75E-11 1.44E-07 2.49E-09Ce-141 5.86E-11 8.99E-11 4.07E-09 9.21E-11Ce-143 8.91E-11 7.48E-11 1.46E-08 3.14E-10Ce-144 4.42E-10 2.60E-09 9.32E-10 2.18E-11Pr-142 1.05E-10 8.44E-11 3.64E-09 6.02E-11Pr-143 9.88E-11 1.10E-10 5.33E-16 1.04E-17Pr-144 1.91E-12 3.37E-12 2.10E-09 3.49E-11Pr-144m 7.46E-13 1.44E-12 2.01E-10 7.63E-12Nd-147 8.82E-11 9.47E-11 7.23E-09 1.59E-10Nd-149 7.60E-12 9.89E-12 2.12E-08 4.53E-10Pm-147 2.12E-11 1.84E-10 1.91E-13 4.27E-15Pm-148 2.17E-10 2.00E-10 3.46E-08 6.24E-10Pm-148m 1.52E-10 6.26E-10 1.17E-07 2.33E-09Pm-149 8.27E-11 6.83E-11 6.59E-10 1.40E-11Sm-147 5.12E-10 1.69E-07 Sm-151 6.99E-12 1.15E-10 3.02E-14 3.48E-15Sm-153 6.04E-11 4.17E-11 2.45E-09 6.57E-11Eu-152 9.17E-11 1.69E-09 6.79E-08 1.28E-09Eu-154 1.47E-10 2.01E-09 7.51E-08 1.39E-09Eu-155 2.54E-11 2.23E-10 2.81E-09 6.94E-11Eu-156 1.65E-10 1.83E-10 8.59E-08 1.46E-09Gd-153 2.01E-11 7.03E-11 4.18E-09 1.15E-10Gd-159 3.93E-11 2.48E-11 2.04E-09 4.62E-11Tb-158 6.54E-11 1.53E-09 4.55E-08 8.62E-10Tb-160 1.16E-10 2.37E-10 6.48E-08 1.22E-09Dy-165 5.54E-12 5.54E-12 1.34E-09 2.93E-11Dy-166 1.40E-10 1.49E-10 1.48E-09 4.04E-11Ho-166 1.14E-10 7.92E-11 1.54E-09 3.04E-11)))))))))))))))))

))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) Internal External 

)))))))))))))))))))))) )))))))))))))))))))))))

Nuclide Ingestion Inhalation Submersion Gnd Surface (Bq ) (Bq ) (per (per -1 -1 Bq y/m ) Bq y/m ) 3 2)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))Er-169 3.17E-11 2.93E-11 9.54E-14 4.33E-15Er-171 2.53E-11 1.65E-11 2.03E-08 4.46E-10Tm-170 1.12E-10 2.41E-10 2.18E-10 5.82E-12Tm-171 8.79E-12 4.23E-11 2.33E-11 6.94E-13Yb-169 5.21E-11 8.31E-11 1.45E-08 3.55E-10Yb-175 3.60E-11 3.19E-11 2.18E-09 4.71E-11Lu-177 4.42E-11 4.22E-11 1.87E-09 4.21E-11Hf-181 8.30E-11 1.26E-10 3.05E-08 6.45E-10Ta-182 1.07E-10 3.61E-10 7.70E-08 1.41E-09W-181 4.29E-12 1.47E-12 1.47E-09 4.17E-11W-185 3.07E-11 7.29E-12 1.46E-12 3.26E-14W-187 3.77E-11 9.25E-12 2.74E-08 5.59E-10Re-183 2.82E-11 5.77E-11 7.12E-09 1.76E-10Re-186 4.80E-11 5.47E-11 1.04E-09 2.44E-11Re-187 1.63E-13 4.41E-13 Re-188 4.69E-11 4.89E-11 3.31E-09 6.85E-11Os-185 2.86E-11 9.57E-11 4.08E-08 8.25E-10Os-191 4.58E-11 5.38E-11 3.44E-09 8.36E-11Os-191m 7.50E-12 6.88E-12 1.89E-10 5.45E-12Os-193 6.56E-11 5.26E-11 3.65E-09 7.95E-11Ir-190 7.68E-11 8.70E-11 7.98E-08 1.65E-09Ir-192 9.84E-11 2.42E-10 4.64E-08 9.80E-10Ir-194 1.06E-10 8.49E-11 5.28E-09 1.07E-10Pt-191 2.30E-11 7.09E-12 1.51E-08 3.37E-10Pt-193 2.43E-12 1.38E-12 1.70E-12 4.31E-13Pt-193m 3.76E-11 9.62E-12 4.56E-10 1.22E-11Pt-197 3.21E-11 7.82E-12 1.14E-09 2.74E-11Pt-197m 5.32E-12 2.07E-12 4.06E-09 9.42E-11Au-196 2.04E-11 2.00E-11 2.60E-08 5.65E-10Au-198 7.99E-11 7.02E-11 2.29E-08 4.83E-10Hg-197 1.79E-11 1.33E-11 2.99E-09 7.60E-11Hg-203 4.02E-11 6.10E-11 1.27E-08 2.77E-10Tl-202 1.83E-11 1.08E-11 2.58E-08 5.51E-10Tl-204 3.54E-11 2.10E-11 4.84E-11 1.23E-12Tl-207 2.61E-13 3.16E-13 1.32E-10 2.51E-12Tl-208 3.95E-13 3.42E-13 2.33E-07 3.56E-09Tl-209 3.08E-13 2.82E-13 1.28E-07 2.27E-09Pb-203 1.62E-11 5.66E-12 1.62E-08 3.61E-10Pb-209 3.45E-12 1.45E-12 Pb-210 1.46E-08 3.59E-08 5.49E-11 2.41E-12Pb-211 7.15E-12 2.61E-10 3.00E-09 5.99E-11)))))))))))))))))
53

Table A.4a Revised Methodology radionuclide mortality risk coefficients. (cont.)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) Internal External 

)))))))))))))))))))))) )))))))))))))))))))))))

Nuclide Ingestion Inhalation Submersion Gnd Surface (Bq ) (Bq ) (per (per -1 -1 Bq y/m ) Bq y/m ) 3 2)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))Pb-212 2.99E-10 8.68E-10 7.98E-09 1.77E-10Pb-214 6.02E-12 1.56E-10 1.39E-08 2.98E-10Bi-206 1.11E-10 9.61E-11 1.98E-07 3.72E-09Bi-207 7.82E-11 1.95E-10 9.16E-08 1.74E-09Bi-210 1.10E-10 1.28E-09 Bi-211 4.42E-13 4.48E-11 2.66E-09 5.69E-11Bi-212 1.22E-11 9.35E-10 1.11E-08 2.06E-10Bi-213 8.90E-12 7.92E-10 7.90E-09 1.65E-10Bi-214 4.45E-12 3.74E-10 9.48E-08 1.64E-09Po-210 5.88E-09 5.14E-08 5.13E-13 9.95E-15Po-212 1.10E-21 1.52E-19 Po-213 1.57E-20 2.00E-18 1.83E-12 3.57E-14Po-214 5.16E-19 7.12E-17 5.02E-12 9.74E-14Po-215 1.13E-17 1.15E-15 8.46E-12 1.77E-13Po-216 1.59E-15 7.56E-14 8.75E-13 1.69E-14Po-218 1.10E-12 9.44E-11 At-217 1.98E-16 1.32E-14 1.39E-11 2.80E-13Rn-219 1.74E-12 3.22E-09 6.91E-11Rn-220 4.42E-12 3.01E-11 6.16E-13Rn-222 3.21E-11 2.22E-11 4.59E-13Fr-221 3.04E-12 2.05E-10 1.70E-09 3.75E-11Fr-223 7.91E-12 1.17E-11 2.34E-09 5.85E-11Ra-223 3.91E-09 9.12E-08 7.18E-09 1.61E-10Ra-224 2.46E-09 5.70E-08 5.57E-10 1.21E-11Ra-225 2.88E-09 6.01E-08 2.63E-10 1.16E-11Ra-226 5.26E-09 6.62E-08 3.71E-10 8.21E-12Ra-228 4.48E-09 2.22E-08 2.48E-18 5.19E-19Ac-225 2.19E-09 1.06E-07 7.03E-10 1.68E-11Ac-227 8.17E-09 1.78E-06 6.41E-12 1.95E-13Ac-228 2.55E-11 8.33E-10 5.58E-08 1.05E-09Th-227 6.11E-10 1.10E-07 5.72E-09 1.28E-10Th-228 9.84E-10 2.41E-06 1.01E-10 2.69E-12Th-229 9.94E-10 1.91E-06 4.42E-09 1.05E-10Th-230 6.39E-10 4.22E-07 1.88E-11 7.72E-13Th-231 2.70E-11 2.18E-11 5.60E-10 1.71E-11Th-232 5.61E-10 4.73E-07 8.51E-12 5.31E-13Th-234 2.88E-10 3.89E-10 3.78E-10 9.65E-12Pa-231 2.86E-09 5.85E-07 1.65E-09 3.81E-11Pa-233 7.05E-11 1.01E-10 1.17E-08 2.58E-10Pa-234 3.37E-11 2.91E-11 1.17E-07 2.25E-09)))))))))))))))))

))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) Internal External 

)))))))))))))))))))))) )))))))))))))))))))))))

Nuclide Ingestion Inhalation Submersion Gnd Surface (Bq ) (Bq ) (per (per -1 -1 Bq y/m ) Bq y/m ) 3 2)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))Pa-234m 1.16E-13 1.61E-13 6.90E-10 1.31E-11U-232 1.40E-09 1.35E-06 1.23E-11 8.11E-13U-233 7.44E-10 3.63E-07 1.21E-11 4.38E-13U-234 7.38E-10 3.58E-07 6.72E-12 6.12E-13U-235 7.53E-10 3.33E-07 8.29E-09 1.84E-10U-236 6.99E-10 3.39E-07 5.12E-12 5.47E-13U-237 6.01E-11 5.99E-11 6.96E-09 1.65E-10U-238 7.31E-10 3.19E-07 4.36E-12 4.81E-13U-240 8.29E-11 6.98E-11 2.79E-11 2.90E-12Np-236 1.43E-11 8.96E-11 6.80E-09 1.61E-10Np-237 6.65E-09 8.04E-07 1.13E-09 3.05E-11Np-238 6.92E-11 9.80E-11 3.36E-08 6.24E-10Np-239 6.42E-11 4.61E-11 8.96E-09 2.03E-10Np-240 3.42E-12 3.26E-12 6.81E-08 1.34E-09Np-240m 5.76E-13 7.24E-13 1.94E-08 3.82E-10Pu-236 1.56E-09 3.39E-07 4.66E-12 7.14E-13Pu-238 6.64E-09 6.76E-07 3.32E-12 6.11E-13Pu-239 7.12E-09 6.82E-07 3.83E-12 2.89E-13Pu-240 7.11E-09 6.81E-07 3.26E-12 5.86E-13Pu-241 1.19E-10 6.55E-09 Pu-242 6.76E-09 6.47E-07 2.78E-12 4.86E-13Pu-243 5.80E-12 6.29E-12 1.16E-09 2.83E-11Pu-244 6.95E-09 6.53E-07 1.94E-12 4.11E-13Am-241 7.39E-09 8.96E-07 8.46E-10 2.61E-11Am-242 2.25E-11 2.52E-10 7.03E-10 1.78E-11Am-242m 6.74E-09 8.08E-07 2.01E-11 2.00E-12Am-243 7.36E-09 8.89E-07 2.43E-09 6.21E-11Cm-242 6.60E-10 7.81E-08 3.62E-12 6.51E-13Cm-243 5.58E-09 6.75E-07 6.82E-09 1.55E-10Cm-244 4.66E-09 5.70E-07 3.04E-12 5.80E-13Cm-245 7.54E-09 9.12E-07 3.69E-09 8.68E-11Cm-246 7.48E-09 9.08E-07 2.49E-12 5.10E-13Cm-247 6.93E-09 8.34E-07 1.79E-08 3.80E-10Cm-248 2.90E-08 3.39E-06 2.26E-12 4.11E-13Cf-252 3.50E-09 6.59E-07 2.79E-12 4.37E-13)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))
54

Table A.4b Revised Methodology radionuclide incidence risk coefficients.))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) Internal External 

)))))))))))))))))))))) )))))))))))))))))))))))

Nuclide Ingestion Inhalation Submersion Gnd Surface (Bq ) (Bq ) (per (per -1 -1 Bq y/m ) Bq y/m ) 3 2)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))H-3 1.93E-12 2.59E-12 Be-7 2.33E-12 4.81E-12 4.31E-09 8.94E-11C-11 1.21E-12 9.14E-13 8.87E-08 1.83E-09C-14 2.79E-11 1.89E-13 C-15 1.79E-14 2.18E-14 4.05E-07 4.69E-09N-13 8.25E-13 6.84E-13 8.87E-08 1.83E-09O-15 2.57E-13 2.60E-13 8.87E-08 1.83E-09F-18 2.94E-12 1.77E-12 8.59E-08 1.77E-09Na-22 2.17E-10 1.32E-10 1.96E-07 3.68E-09Na-24 3.74E-11 2.03E-11 4.28E-07 6.36E-09Si-31 1.36E-11 8.90E-12 8.13E-11 1.42E-12P-32 1.65E-10 7.92E-11 P-33 2.11E-11 1.07E-11 S-35 1.12E-11 5.01E-12 Cl-36 6.04E-11 3.51E-11 6.32E-16 6.95E-17Cl-38 5.58E-12 4.41E-12 1.54E-07 2.37E-09Ar-41 1.27E-14 1.17E-07 2.05E-09K-40 3.39E-10 2.02E-10 1.44E-08 2.43E-10K-42 3.48E-11 2.04E-11 2.57E-08 4.30E-10Ca-45 5.46E-11 6.79E-11 1.13E-18 2.98E-19Ca-47 1.80E-10 1.41E-10 9.74E-08 1.71E-09Sc-46 1.55E-10 3.53E-10 1.85E-07 3.43E-09Sc-47 7.97E-11 5.44E-11 9.42E-09 2.08E-10Sc-48 1.80E-10 1.13E-10 3.10E-07 5.58E-09V-48 2.04E-10 1.85E-10 2.67E-07 4.88E-09Cr-51 3.74E-12 4.70E-12 2.71E-09 5.83E-11Mn-52 1.62E-10 1.19E-10 3.16E-07 5.79E-09Mn-54 5.30E-11 9.98E-11 7.68E-08 1.48E-09Mn-56 2.32E-11 1.41E-11 1.65E-07 2.85E-09Fe-55 9.50E-12 1.51E-11 1.71E-12 3.30E-13Fe-59 1.59E-10 1.91E-10 1.09E-07 1.94E-09Co-57 2.62E-11 7.78E-11 1.03E-08 2.33E-10Co-58 7.62E-11 1.40E-10 8.85E-08 1.73E-09Co-58m 2.56E-12 2.41E-12 2.55E-12 5.31E-13Co-60 5.11E-10 1.86E-09 2.30E-07 4.03E-09Ni-59 5.00E-12 1.08E-11 2.85E-12 6.21E-13Ni-63 1.49E-11 2.74E-11 Ni-65 1.52E-11 9.71E-12 5.07E-08 8.78E-10Cu-64 1.42E-11 1.13E-11 1.65E-08 3.38E-10Zn-65 2.68E-10 2.70E-10 5.34E-08 9.68E-10Zn-69 1.67E-12 2.82E-12 5.18E-13 1.09E-14)))))))))))))))))

))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) Internal External 

)))))))))))))))))))))) )))))))))))))))))))))))

Nuclide Ingestion Inhalation Submersion Gnd Surface (Bq ) (Bq ) (per (per -1 -1 Bq y/m ) Bq y/m ) 3 2)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))Zn-69m 4.11E-11 3.16E-11 3.59E-08 7.54E-10Ga-67 2.26E-11 1.39E-11 1.23E-08 2.72E-10Ga-72 1.29E-10 5.87E-11 2.69E-07 4.51E-09Ge-71 3.19E-13 1.58E-12 6.79E-12 1.74E-12As-73 2.22E-11 3.69E-11 3.21E-10 1.39E-11As-74 1.14E-10 1.25E-10 6.74E-08 1.37E-09As-76 1.77E-10 1.17E-10 3.87E-08 7.46E-10As-77 4.46E-11 3.10E-11 7.43E-10 1.58E-11Se-75 1.77E-10 1.33E-10 3.33E-08 7.26E-10Br-82 3.83E-11 2.12E-11 2.41E-07 4.56E-09Kr-83m 9.40E-16 6.48E-12 1.58E-12Kr-85 7.75E-15 1.94E-10 3.99E-12Kr-85m 7.42E-15 1.36E-08 3.00E-10Kr-87 3.26E-14 7.93E-08 1.31E-09Kr-88 5.96E-14 2.03E-07 3.15E-09Kr-89 4.34E-14 1.81E-07 2.96E-09Kr-90 4.33E-14 1.19E-07 2.12E-09Rb-82 2.84E-13 3.17E-13 9.56E-08 1.95E-09Rb-86 1.92E-10 1.14E-10 8.74E-09 1.59E-10Rb-87 9.96E-11 6.12E-11 Rb-88 3.96E-12 3.69E-12 6.39E-08 1.03E-09Rb-89 2.34E-12 1.87E-12 2.02E-07 3.38E-09Sr-82 6.97E-10 2.40E-10 2.29E-11 5.51E-12Sr-85 3.78E-11 3.08E-11 4.44E-08 9.19E-10Sr-85m 4.87E-13 1.93E-13 1.85E-08 4.04E-10Sr-89 2.79E-10 9.94E-11 1.26E-11 2.39E-13Sr-90 1.10E-09 1.61E-09 Sr-91 7.62E-11 2.11E-11 6.32E-08 1.19E-09Sr-92 5.48E-11 1.27E-11 1.23E-07 2.12E-09Y-90 4.05E-10 2.68E-10 Y-91 3.64E-10 5.01E-10 3.32E-10 5.86E-12Y-91m 9.98E-13 8.09E-13 4.65E-08 9.49E-10Y-92 5.26E-11 4.36E-11 2.32E-08 4.27E-10Y-93 1.55E-10 9.40E-11 8.51E-09 1.50E-10Zr-93 1.41E-11 1.42E-10 Zr-95 1.06E-10 1.75E-10 6.68E-08 1.31E-09Zr-97 2.80E-10 1.28E-10 1.65E-08 3.05E-10Nb-93m 1.79E-11 1.17E-10 8.30E-12 1.27E-12Nb-94 1.87E-10 2.22E-09 1.44E-07 2.79E-09Nb-95 6.09E-11 8.40E-11 6.97E-08 1.36E-09Nb-95m 8.27E-11 6.08E-11 5.12E-09 1.15E-10))))))))))))))))))
55

Table A.4b Revised Methodology radionuclide incidence risk coefficients. (cont.)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) Internal External 

)))))))))))))))))))))) )))))))))))))))))))))))

Nuclide Ingestion Inhalation Submersion Gnd Surface (Bq ) (Bq ) (per (per -1 -1 Bq y/m ) Bq y/m ) 3 2)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))Nb-97 4.74E-12 5.75E-12 5.96E-08 1.19E-09Nb-97m 8.85E-14 9.03E-14 6.62E-08 1.30E-09Mo-99 6.13E-11 1.21E-10 1.39E-08 2.78E-10Tc-95 1.84E-12 9.13E-13 7.17E-08 1.40E-09Tc-95m 3.36E-11 5.67E-11 5.95E-08 1.20E-09Tc-96 6.17E-11 5.25E-11 2.29E-07 4.41E-09Tc-96m 7.05E-13 6.11E-13 3.81E-09 7.53E-11Tc-97 4.27E-12 9.31E-12 5.69E-11 7.72E-12Tc-97m 3.24E-11 5.30E-11 7.56E-11 6.78E-12Tc-99 3.79E-11 7.81E-11 4.14E-14 9.78E-16Tc-99m 1.51E-12 9.43E-13 1.09E-08 2.42E-10Ru-97 1.59E-11 1.10E-11 1.96E-08 4.34E-10Ru-103 8.98E-11 1.24E-10 4.20E-08 8.67E-10Ru-105 3.12E-11 2.17E-11 7.02E-08 1.40E-09Ru-106 9.32E-10 3.11E-09 Rh-103m 2.21E-13 3.45E-13 1.20E-11 1.37E-12Rh-105 5.22E-11 3.30E-11 6.66E-09 1.43E-10Rh-105m 2.92E-14 2.50E-14 2.34E-09 5.79E-11Rh-106 9.80E-14 1.25E-13 1.84E-08 3.66E-10Pd-100 1.01E-10 9.60E-11 Pd-101 1.01E-11 6.18E-12 Pd-103 2.85E-11 2.92E-11 1.09E-10 1.21E-11Pd-107 5.66E-12 3.94E-11 Pd-109 9.00E-11 5.37E-11 5.98E-11 1.23E-12Ag-105 4.41E-11 6.28E-11 Ag-108 1.88E-13 2.55E-13 1.55E-09 3.14E-11Ag-108m 1.64E-10 1.90E-09 1.43E-07 2.89E-09Ag-109m 7.32E-15 9.34E-15 3.31E-10 1.22E-11Ag-110 6.60E-14 8.53E-14 2.74E-09 5.45E-11Ag-110m 2.28E-10 8.69E-10 2.50E-07 4.72E-09Ag-111 1.85E-10 1.42E-10 2.26E-09 4.86E-11Cd-109 2.16E-10 5.00E-10 1.31E-10 1.13E-11Cd-115 1.97E-10 1.33E-10 1.77E-08 3.65E-10Cd-115m 3.84E-10 4.60E-10 2.02E-09 3.71E-11In-113m 2.24E-12 1.56E-12 2.20E-08 4.68E-10In-114 1.23E-13 1.57E-13 2.81E-09 5.64E-11In-114m 5.56E-10 6.83E-10 7.87E-09 1.66E-10In-115 9.43E-10 5.60E-09 In-115m 9.24E-12 4.74E-12 1.36E-08 2.96E-10Sn-113 1.01E-10 1.79E-10 6.29E-10 2.10E-11Sn-121 3.31E-11 1.66E-11 )))))))))))))))))

))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) Internal External 

)))))))))))))))))))))) )))))))))))))))))))))))

Nuclide Ingestion Inhalation Submersion Gnd Surface (Bq ) (Bq ) (per (per -1 -1 Bq y/m ) Bq y/m ) 3 2)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))Sn-121m 5.40E-11 2.02E-10 2.08E-11 7.39E-13Sn-125 4.53E-10 3.23E-10 2.85E-08 5.14E-10Sn-126 5.73E-10 1.15E-09 3.74E-09 9.36E-11Sb-122 2.38E-10 1.47E-10 3.91E-08 7.91E-10Sb-124 2.91E-10 3.57E-10 1.76E-07 3.12E-09Sb-125 8.02E-11 1.41E-10 3.69E-08 7.64E-10Sb-126 2.63E-10 2.27E-10 2.47E-07 4.92E-09Sb-126m 1.97E-12 1.74E-12 1.40E-07 2.82E-09Sb-127 2.29E-10 1.63E-10 5.89E-08 1.18E-09Sb-129 5.02E-11 2.32E-11 1.32E-07 2.47E-09Te-125m 6.78E-11 7.70E-11 5.94E-10 2.57E-11Te-127 2.31E-11 1.17E-11 4.17E-10 8.81E-12Te-127m 1.62E-10 3.53E-10 1.94E-10 8.24E-12Te-129 4.00E-12 3.96E-12 4.70E-09 9.74E-11Te-129m 3.18E-10 3.60E-10 2.97E-09 6.18E-11Te-131 1.05E-11 6.71E-12 3.72E-08 7.49E-10Te-131m 2.38E-10 2.27E-10 1.31E-07 2.48E-09Te-132 3.29E-10 2.26E-10 1.83E-08 4.10E-10I-122 5.84E-13 6.05E-13 8.49E-08 1.73E-09I-123 1.47E-11 7.94E-12 1.33E-08 3.00E-10I-125 6.98E-10 4.62E-10 6.63E-10 2.94E-11I-126 1.30E-09 8.52E-10 3.97E-08 8.06E-10I-129 4.98E-09 3.30E-09 5.03E-10 2.64E-11I-130 1.31E-10 7.06E-11 1.91E-07 3.80E-09I-131 9.77E-10 6.31E-10 3.24E-08 6.82E-10I-132 1.79E-11 9.51E-12 2.09E-07 4.02E-09I-133 2.86E-10 1.63E-10 5.35E-08 1.07E-09I-134 6.25E-12 3.74E-12 2.43E-07 4.54E-09I-135 6.14E-11 3.19E-11 1.48E-07 2.56E-09Xe-122 8.34E-14 4.99E-09 1.18E-10Xe-123 2.41E-14 5.53E-08 1.08E-09Xe-125 3.25E-14 2.12E-08 4.65E-10Xe-127 1.10E-14 2.22E-08 4.94E-10Xe-129m 1.55E-14 1.65E-09 6.31E-11Xe-131m 1.12E-14 5.99E-10 2.39E-11Xe-133 1.12E-14 2.62E-09 7.38E-11Xe-133m 1.38E-14 2.39E-09 6.32E-11Xe-135 2.01E-14 2.12E-08 4.59E-10Xe-135m 5.09E-15 3.72E-08 7.68E-10Xe-137 3.76E-14 1.67E-08 3.29E-10Xe-138 5.58E-14 1.11E-07 1.87E-09))))))))))))))))))
56

Table A.4b Revised Methodology radionuclide incidence risk coefficients. (cont.)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) Internal External 

)))))))))))))))))))))) )))))))))))))))))))))))

Nuclide Ingestion Inhalation Submersion Gnd Surface (Bq ) (Bq ) (per (per -1 -1 Bq y/m ) Bq y/m ) 3 2)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))Cs-131 4.87E-12 2.87E-12 4.35E-10 2.42E-11Cs-134 1.28E-09 7.80E-10 1.40E-07 2.76E-09Cs-134m 1.23E-12 8.39E-13 1.63E-09 4.32E-11Cs-135 1.22E-10 7.33E-11 Cs-136 2.09E-10 1.26E-10 1.98E-07 3.76E-09Cs-137 8.54E-10 5.18E-10 Cs-138 4.75E-12 3.51E-12 2.26E-07 3.82E-09Ba-131 4.59E-11 1.30E-11 3.91E-08 8.38E-10Ba-133 7.29E-11 1.09E-10 3.09E-08 6.96E-10Ba-133m 7.47E-11 1.51E-11 4.68E-09 1.12E-10Ba-137m 6.58E-14 4.24E-14 5.34E-08 1.07E-09Ba-139 8.23E-12 4.13E-12 3.02E-09 6.46E-11Ba-140 3.18E-10 8.57E-11 1.62E-08 3.41E-10La-140 2.56E-10 1.38E-10 2.18E-07 3.78E-09Ce-141 1.06E-10 1.17E-10 6.31E-09 1.43E-10Ce-143 1.60E-10 1.04E-10 2.24E-08 4.81E-10Ce-144 7.99E-10 2.91E-09 1.46E-09 3.42E-11Pr-142 1.89E-10 1.12E-10 5.52E-09 9.14E-11Pr-143 1.78E-10 1.51E-10 8.09E-16 1.59E-17Pr-144 2.18E-12 3.55E-12 3.18E-09 5.29E-11Pr-144m 8.72E-13 1.52E-12 3.39E-10 1.29E-11Nd-147 1.59E-10 1.31E-10 1.11E-08 2.45E-10Nd-149 1.23E-11 1.14E-11 3.24E-08 6.94E-10Pm-147 3.82E-11 2.02E-10 2.96E-13 6.65E-15Pm-148 3.90E-10 2.83E-10 5.25E-08 9.47E-10Pm-148m 2.68E-10 7.96E-10 1.78E-07 3.54E-09Pm-149 1.49E-10 9.64E-11 1.01E-09 2.13E-11Sm-147 6.78E-10 1.87E-07 Sm-151 1.24E-11 1.25E-10 5.54E-14 6.42E-15Sm-153 1.09E-10 5.88E-11 3.88E-09 1.05E-10Eu-152 1.55E-10 2.14E-09 1.03E-07 1.94E-09Eu-154 2.53E-10 2.47E-09 1.14E-07 2.12E-09Eu-155 4.46E-11 2.59E-10 4.43E-09 1.10E-10Eu-156 2.95E-10 2.50E-10 1.30E-07 2.22E-09Gd-153 3.56E-11 8.66E-11 6.67E-09 1.85E-10Gd-159 7.03E-11 3.34E-11 3.14E-09 7.13E-11Tb-158 1.14E-10 1.90E-09 6.92E-08 1.31E-09Tb-160 2.06E-10 3.08E-10 9.85E-08 1.86E-09Dy-165 8.80E-12 6.06E-12 2.06E-09 4.53E-11Dy-166 2.55E-10 2.11E-10 2.36E-09 6.48E-11Ho-166 2.05E-10 1.10E-10 2.38E-09 4.70E-11)))))))))))))))))

))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) Internal External 

)))))))))))))))))))))) )))))))))))))))))))))))

Nuclide Ingestion Inhalation Submersion Gnd Surface (Bq ) (Bq ) (per (per -1 -1 Bq y/m ) Bq y/m ) 3 2)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))Er-169 5.73E-11 4.08E-11 1.52E-13 7.63E-15Er-171 4.41E-11 2.03E-11 3.12E-08 6.85E-10Tm-170 2.03E-10 2.96E-10 3.47E-10 9.29E-12Tm-171 1.58E-11 4.97E-11 3.75E-11 1.12E-12Yb-169 9.27E-11 1.08E-10 2.27E-08 5.57E-10Yb-175 6.49E-11 4.54E-11 3.33E-09 7.21E-11Lu-177 7.97E-11 5.94E-11 2.89E-09 6.51E-11Hf-181 1.48E-10 1.67E-10 4.65E-08 9.85E-10Ta-182 1.90E-10 4.47E-10 1.17E-07 2.14E-09W-181 7.36E-12 2.17E-12 2.37E-09 6.71E-11W-185 5.50E-11 1.15E-11 2.27E-12 5.07E-14W-187 6.65E-11 1.43E-11 4.17E-08 8.52E-10Re-183 4.26E-11 6.94E-11 1.12E-08 2.76E-10Re-186 8.12E-11 7.06E-11 1.63E-09 3.82E-11Re-187 2.47E-13 5.10E-13 Re-188 8.63E-11 6.25E-11 5.07E-09 1.05E-10Os-185 4.87E-11 1.25E-10 6.21E-08 1.26E-09Os-191 8.22E-11 7.30E-11 5.41E-09 1.32E-10Os-191m 1.34E-11 8.97E-12 3.03E-10 8.84E-12Os-193 1.18E-10 7.24E-11 5.59E-09 1.22E-10Ir-190 1.34E-10 1.21E-10 1.22E-07 2.52E-09Ir-192 1.74E-10 3.04E-10 7.06E-08 1.49E-09Ir-194 1.89E-10 1.13E-10 8.04E-09 1.62E-10Pt-191 4.05E-11 1.12E-11 2.32E-08 5.21E-10Pt-193 4.38E-12 2.13E-12 3.28E-12 8.32E-13Pt-193m 6.77E-11 1.56E-11 7.26E-10 1.96E-11Pt-197 5.74E-11 1.23E-11 1.79E-09 4.32E-11Pt-197m 8.79E-12 2.72E-12 6.28E-09 1.47E-10Au-196 3.52E-11 2.81E-11 3.97E-08 8.65E-10Au-198 1.43E-10 9.83E-11 3.49E-08 7.36E-10Hg-197 3.20E-11 1.88E-11 4.75E-09 1.21E-10Hg-203 7.15E-11 8.18E-11 1.94E-08 4.24E-10Tl-202 2.74E-11 1.64E-11 3.94E-08 8.43E-10Tl-204 5.33E-11 3.12E-11 7.68E-11 1.95E-12Tl-207 2.90E-13 3.34E-13 2.01E-10 3.81E-12Tl-208 4.73E-13 3.68E-13 3.54E-07 5.41E-09Tl-209 3.80E-13 3.04E-13 1.95E-07 3.45E-09Pb-203 2.79E-11 8.38E-12 2.50E-08 5.56E-10Pb-209 5.66E-12 1.85E-12 Pb-210 1.82E-08 4.51E-08 9.09E-11 4.16E-12Pb-211 9.13E-12 2.79E-10 4.56E-09 9.11E-11))))))))))))))))))
57

Table A.4b Revised Methodology radionuclide incidence risk coefficients. (cont.)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) Internal External 

)))))))))))))))))))))) )))))))))))))))))))))))

Nuclide Ingestion Inhalation Submersion Gnd Surface (Bq ) (Bq ) (per (per -1 -1 Bq y/m ) Bq y/m ) 3 2)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))Pb-212 4.87E-10 1.04E-09 1.23E-08 2.74E-10Pb-214 7.94E-12 1.68E-10 2.12E-08 4.56E-10Bi-206 1.92E-10 1.37E-10 3.01E-07 5.66E-09Bi-207 1.37E-10 2.54E-10 1.39E-07 2.65E-09Bi-210 1.97E-10 1.38E-09 Bi-211 4.93E-13 4.71E-11 4.05E-09 8.69E-11Bi-212 1.68E-11 9.88E-10 1.69E-08 3.13E-10Bi-213 1.19E-11 8.36E-10 1.20E-08 2.51E-10Bi-214 5.27E-12 3.94E-10 1.44E-07 2.49E-09Po-210 8.80E-09 5.79E-08 7.79E-13 1.51E-14Po-212 1.22E-21 1.60E-19 Po-213 1.81E-20 2.11E-18 2.79E-12 5.42E-14Po-214 5.74E-19 7.50E-17 7.63E-12 1.48E-13Po-215 1.35E-17 1.21E-15 1.29E-11 2.70E-13Po-216 2.38E-15 7.98E-14 1.33E-12 2.57E-14Po-218 1.37E-12 9.96E-11 At-217 2.43E-16 1.39E-14 2.11E-11 4.26E-13Rn-219 1.87E-12 4.91E-09 1.05E-10Rn-220 5.18E-12 4.58E-11 9.35E-13Rn-222 4.96E-11 3.38E-11 6.97E-13Fr-221 3.91E-12 2.17E-10 2.61E-09 5.76E-11Fr-223 1.21E-11 1.60E-11 3.66E-09 9.23E-11Ra-223 6.33E-09 9.74E-08 1.11E-08 2.50E-10Ra-224 4.04E-09 6.08E-08 8.54E-10 1.86E-11Ra-225 4.25E-09 6.44E-08 4.40E-10 1.96E-11Ra-226 7.98E-09 7.35E-08 5.72E-10 1.27E-11Ra-228 6.64E-09 2.60E-08 4.77E-18 9.99E-19Ac-225 3.85E-09 1.12E-07 1.10E-09 2.65E-11Ac-227 9.52E-09 1.91E-06 1.01E-11 3.24E-13Ac-228 4.38E-11 8.84E-10 8.49E-08 1.60E-09Th-227 1.09E-09 1.16E-07 8.78E-09 1.97E-10Th-228 1.70E-09 2.55E-06 1.58E-10 4.34E-12Th-229 1.53E-09 2.05E-06 6.90E-09 1.66E-10Th-230 1.01E-09 4.66E-07 3.00E-11 1.33E-12Th-231 4.85E-11 2.97E-11 8.91E-10 2.83E-11Th-232 8.85E-10 5.21E-07 1.39E-11 9.57E-13Th-234 5.20E-10 5.15E-10 5.98E-10 1.54E-11Pa-231 4.02E-09 6.54E-07 2.54E-09 5.92E-11Pa-233 1.27E-10 1.33E-10 1.80E-08 3.97E-10Pa-234 5.76E-11 3.51E-11 1.78E-07 3.42E-09)))))))))))))))))

))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) Internal External 

)))))))))))))))))))))) )))))))))))))))))))))))

Nuclide Ingestion Inhalation Submersion Gnd Surface (Bq ) (Bq ) (per (per -1 -1 Bq y/m ) Bq y/m ) 3 2)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))Pa-234m 1.29E-13 1.70E-13 1.05E-09 1.98E-11U-232 2.19E-09 1.43E-06 2.01E-11 1.47E-12U-233 1.21E-09 3.82E-07 1.91E-11 7.46E-13U-234 1.20E-09 3.77E-07 1.13E-11 1.13E-12U-235 1.22E-09 3.51E-07 1.28E-08 2.84E-10U-236 1.14E-09 3.57E-07 8.72E-12 1.02E-12U-237 1.08E-10 8.43E-11 1.08E-08 2.58E-10U-238 1.15E-09 3.36E-07 7.46E-12 8.97E-13U-240 1.48E-10 9.06E-11 4.84E-11 5.36E-12Np-236 2.52E-11 1.05E-10 1.06E-08 2.53E-10Np-237 7.98E-09 9.33E-07 1.79E-09 4.92E-11Np-238 1.23E-10 1.26E-10 5.11E-08 9.48E-10Np-239 1.15E-10 6.52E-11 1.38E-08 3.15E-10Np-240 4.79E-12 3.55E-12 1.04E-07 2.04E-09Np-240m 6.54E-13 7.64E-13 2.95E-08 5.80E-10Pu-236 2.08E-09 3.61E-07 8.30E-12 1.34E-12Pu-238 7.98E-09 7.42E-07 6.05E-12 1.16E-12Pu-239 8.53E-09 7.51E-07 6.29E-12 5.28E-13Pu-240 8.52E-09 7.51E-07 5.93E-12 1.11E-12Pu-241 1.40E-10 7.59E-09 Pu-242 8.11E-09 7.13E-07 5.04E-12 9.20E-13Pu-243 9.97E-12 7.22E-12 1.82E-09 4.46E-11Pu-244 8.46E-09 7.20E-07 3.63E-12 7.81E-13Am-241 8.87E-09 1.04E-06 1.36E-09 4.26E-11Am-242 3.96E-11 2.81E-10 1.10E-09 2.84E-11Am-242m 7.90E-09 9.43E-07 3.42E-11 3.69E-12Am-243 8.84E-09 1.03E-06 3.85E-09 9.92E-11Cm-242 1.03E-09 8.54E-08 6.63E-12 1.23E-12Cm-243 6.79E-09 7.81E-07 1.05E-08 2.40E-10Cm-244 5.69E-09 6.58E-07 5.60E-12 1.10E-12Cm-245 9.05E-09 1.06E-06 5.75E-09 1.36E-10Cm-246 8.97E-09 1.05E-06 4.65E-12 9.67E-13Cm-247 8.35E-09 9.68E-07 2.72E-08 5.78E-10Cm-248 3.54E-08 3.95E-06 4.13E-12 7.76E-13Cf-252 4.86E-09 7.01E-07 5.04E-12 8.22E-13))))))))))))))))))
58

))))))))))))))))))))))))))))))))))

 Inhalation Ingestion

Element clearance f1

 class

))))))))))))))))))))))))))))))))))

H V 1.0E+00

Be Y 5.0E-03

N D 9.5E-01

C D 9.5E-01 *

O D 9.5E-01

F D 9.5E-01

Na D 9.5E-01

Si W 1.0E-02

P D 8.0E-01

S D 8.0E-01

Cl D 9.5E-01

Ar *

K D 9.5E-01

Ca W 3.0E-01

Sc Y 1.0E-04

V W 1.0E-02

Cr Y 1.0E-01

Mn W 1.0E-01

Fe W 1.0E-01

Co Y 3.0E-01

Ni W 5.0E-02

Cu Y 5.0E-01

Zn Y 5.0E-01

Ga W 1.0E-03

Ge W 9.5E-01

As W 5.0E-01

Se W 8.0E-01

Br D 9.5E-01

Kr *

Rb D 9.5E-01

Sr D 3.0E-01

Y Y 1.0E-04

Zr W 2.0E-03

Nb Y 1.0E-02

Mo Y 8.0E-01

Tc W 8.0E-01

Ru Y 5.0E-02

Rh Y 5.0E-02

Pd Y 5.0E-03

Ag Y 5.0E-02

Cd Y 5.0E-02

In W 2.0E-02

Sn W 2.0E-02

Sb W 1.0E-01

Te W 2.0E-01

)))))))))))))

For C, clearance class is *, f is 1.0. * 14

1

))))))))))))))))))))))))))))))))))

 Inhalation Ingestion

Element clearance f1

 class

))))))))))))))))))))))))))))))))))

I D 9.5E-01

Xe *

Cs D 9.5E-01

Ba D 1.0E-01

La W 1.0E-03

Ce Y 3.0E-04

Pr Y 3.0E-04

Nd Y 3.0E-04

Pm Y 3.0E-04

Sm W 3.0E-04

Eu W 1.0E-03

Gd W 3.0E-04

Tb W 3.0E-04

Dy W 3.0E-04

Ho W 3.0E-04

Er W 3.0E-04

Tm W 3.0E-04

Yb Y 3.0E-04

Lu Y 3.0E-04

Hf W 2.0E-03

Ta Y 1.0E-03

W D 3.0E-01

Re W 8.0E-01

Os Y 1.0E-02

Ir Y 1.0E-02

Pt D 1.0E-02

Au Y 1.0E-01

Hg W 2.0E-02

Tl D 9.5E-01

Pb D 2.0E-01

Bi W 5.0E-02

Po W 1.0E-01

At D 9.5E-01

Rn *

Fr D 9.5E-01

Ra W 2.0E-01

Ac Y 1.0E-03

Th Y 2.0E-04

Pa Y 1.0E-03

U Y 5.0E-02

Np W 1.0E-03

Pu Y 1.0E-03

Am W 1.0E-03

Cm W 1.0E-03

Cf Y 1.0E-03

))))))))))))))))))))))))))))))))))

Table A.5 Default inhalation clearance class and ingestion f values by element. 1
59

References for Appendix A

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F.N. Fritsch and J. Butland, A Method for Constructing Local Monotone Piecewise Cubic

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National Center for Health Statistics, Vital Statistics Mortality Data, Detail, 1979, PB82-

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National Center for Health Statistics, Vital Statistics Mortality Data, Detail, 1980, PB83-

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United States Life Tables, (PHS) 85-1150-1, U.S. Department of Health and Human Services,

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1260, U.S. Department of Health and Human Services, Public Health Service—Health Care
60

Financing Administration, Superintendent of Documents, U.S. Government Printing Office,

Washington, DC, 1980.

A.L. Sjoreen, Reconstruction of the RADRISK Database, Oak Ridge National Laboratory,

Oak Ridge, TN, (to be published) 1994.

M. Vaeth and D.A. Pierce, Calculating Excess Lifetime Risk in Relative Risk Models, RERF

CR 3-89, Editorial Office, Radiation Effects Research Foundation, Hiroshima, Japan,

November 1989.