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ASSESSING COMPLIANCE
INTRODUCTION
in the preceding chapter, we described our conclusion that the form
of a Yucca Mountain standard should be based on limiting individual risk
as measured by the average risk to individuals in a critical group. This
group is defined as being composed of persons likely to be at highest risk
from radionuclides released from the repository. Our judgment is that
limiting individual risk in this way is also likely to provide adequate
radiological protection for all relevant populations that might be exposed
to radiation from radionuclides released from the proposed repository at
Yucca Mountain (see Chapter 2~. The period over which this level of
protection should be assessed should extend over the period of duration of
hazard potential of the repository, that is, until the time at which the highest
critical group risk is calculated to occur, within the limits imposed by the
long-term stability of the geologic environment at Yucca Mountain, which
is on the order of 1 o6 years.
In this chapter, we discuss the analyses that must be undertaken to
judge compliance with such a standard. Important questions to be answered
are:
Whether the scientific understanding of the relevant events
and processes potentially leading to releases is sufficient to
allow a quantitative estimate of future repository behaviors.
Whether adequate analytical methods and numerical tools
exist to incorporate this understanding into quantitative
assessments of compliance.
Whether the current scientific understanding and analytic
methods are sufficient to evaluate performance with
sufficient confidence to assess compliance over the long time
periods required.
4. Whether the results of the analyses required to assess
repository performance can be combined into an estimated
67
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YUCCA MOUNTAIN STANDARDS
risk for comparison with the standards in the licensing
process. In particular, the estimated risk is defineti as the
mean risk of members in the critical group. Risk is defined
as the expected value of the probabilistic distribution of
health effects experiences! by an individual member of the
critical group.
The main too! used to assess compliance is quantitative
performance assessment, which relies upon mathematical modeling. We
have evaluated the degree of confidence that can be placer! today in such
assessments. We have also made a systematic analysis of the application
of this methodology to the Yucca Mountain site. Based on these analyses,
we conclude that:
For those aspects of repository and waste behavior that
depend on physical and geologic properties and processes,
enough of the important aspects can be known within
reasonable limits of uncertainty, and these properties and
processes are sufficiently understood} and stable over the
long time scales of interest to make calculations possible and
meaningful. These properties and processes include the
raclionuclide content of the waste (which changes over time
clue to radioactive decay), the influx of water through the site
and its effect on waste package integrity and other
engineered barriers, the migration of wastes to ground} water
after waste packages have lost their integrity, anti the
subsequent dispersion and migration of wastes in ground
water. While these factors cannot be calculated precisely,
we believe that there is a substantial scientific basis for
making such calculations, taking uncertainties and natural
variabilities into account, to estimate, for example, the
concentration of wastes in ground water at different locations
and the times of gaseous releases.
One critical gap in our understanding is with respect to
future human behavior. Since there is no scientific basis for
predicting human behavior, we recommend that policy
decisions be made to specify default (or reference) scenarios
.
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69
to be user} to incorporate assumed future human behavior
into compliance assessment calculations.
Available mathematical and numerical tools are neither
perfect nor complete. Nevertheless, the currently available
tools plus additional tools that we believe can be developed
as part of the stanciarci-setting and compliance assessment
efforts, or through other research, should be adequate for the
analyses requires] to evaluate repository performance.
So long as the geologic regime remains relatively stable, it
should be possible to assess the maximum risks with
reasonable assurance. The time scales of long term geologic
processes at Yucca Mountain are on the order of 1 oh years.
Other processes that operate on short time scales, such as
seismic activity, can also be accommodates] in performance
assessment if the maximum risks associateci with these
processes depend] more on whether an event is likely to occur
(at any time) than on the specific timing of the event.
4. Established procedures of risk analysis should enable the
combination of the results of all repository system
simulations into a single estimated risk to be compared with
the standard. (Human intrusion is excluded from such a
combination. See Chapter 4.) An element of judgment is
contained in many of the conceptual assumptions to be
macle, and those assumptions, methods, and the reference
data will have to be specified. Similarly, reference exposure
scenarios must be established clearly. This transparency in
the use of assumptions is critical to evaluating the calculated
risk.
Because some readers might be unfamiliar with the technical
aspects of a repository performance assessment, it is appropriate to provide
an overview of the methodology, as we Rio in Part I of this chapter. We
then consider the scientific basis for making an assessment of Yucca
Mountain. We have found it useful to separate this evaluation into two
parts, one dealing with the physical properties and geologic processes
relevant to the behavior of the wastes and the other with those aspects of
performance assessment that deal with assumptions about where ant] how
people live, how they might be exposer] through the foot} en cl water they
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YUCCA MOUNTAIN STANDARDS
consume, and other factors that conic! affect exposures to radioactive
wastes. We shall refer to this latter collection of factors that must be
considered! as exposure scenarios. The reason for separating these two
elements of performance assessment is that the nature of calculations in
each is substantially different. We discuss these in Parts I] anti III.
PART I: OVERVIEW OF PERFORMANCE ASSESSMENT
Any standard to protect inclividuals ant] the public after the
proposed repository is closecl wouIcl require assessments of performance
at times so far in the future that a direct evaluation of compliance (for
example by physical monitoring of system behavior) is out of the question.
The only way to evaluate the risks of adverse health effects and to compare
them with the standard} is to assess the estimated potential future behavior
of the entire repository system anti its potential impact on humans. This
procedure, involving modeling of processes and events that might Bali to
releases and exposures, is called performance assessment. It involves
computer calculations using quantitative models of physical, chemical,
geologic, anti biological processes, taking uncertainties into account.
Modeling repository performance is a challenging task because the
rates of geochemical transformation and transport of the radionuclides are
generally very slow and the times at which points distant from the
repository become significantly affected by ra(iionuclide releases will be
in the far future. Thus, to assess these effects requires projection of
geochemical, hydrodynamic, and other processes over long time periods
within rock masses whose properties are imperfectly known. Factors
describing how humans can be exposed to radionuclides from the wastes
are even more imperfectly known and these factors, inclucling the future
state of technology and medicine, might be more changeable over time
than are the physical processes.
Reasonable Confidence
One possible response to these difficulties is to conclude that they
render any assessments of the ultimate fate of the waste materials too
uncertain to be useful. However, we believe that such analyses do provide
information for judging the quality of a disposal site. Even if the
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71
uncertainties involves! are large, some options for the disposition of the
wastes can clearly be shown to result in worse consequences than other
options would] produce.
The results of compliance analysis should not, however, be
interpreted as accurate predictions of the expecter} behavior of a geologic
repository. No analysis of compliance will ever constitute an absolute
proof; the objective instead! is a reasonable level of confidence in analyses
that inclicates whether limits establisher! by the standard will be exceeded.
Both the USNRC ant! EPA have explicitly recognized this objective. For
example, EPA states in 40 CFR 191 that "unequivocal numeric proof of
compliance is neither necessary nor likely to be obtained." In regulation
10 CFR 60, USNRC acknowledges that "it is not expected that complete
assurance that "performance objectives] will be met can be presented." The
USNRC requires instead} "reasonable assurance, making allowances for the
time period, hazards, and uncertainties involved." EPA's required level of
proof in 40 CFR 191 is "reasonable expectation."
Time scale
One commonly expressed concern regarding the performance
assessment mo~ieling is that it requires simulating performance at such
distant times in the future that no condolence can be placed in the results.
Of course, the level of confidence for some predictions might decrease
with time. This argument has been used to support the concept of a 10,000
year cutoff (DOE, 19921. We cio not, however, believe that there is a
scientific basis for limiting the analysis in this way.
One of the major reasons for selecting geologic disposal was to
place the wastes in as stable an environment as many scientists consider
possible. The deep subsurface fulfills this condition very well (NRC,
19571. In comparison with many other fields of science, earth scientists are
accustomed to dealing with physical phenomena over long time scales. In
this perspective even the longest times considered for repository
performance models are not excessive. Furthermore, even changes in
climate at the surface would probably have little effect on repository
performance deep below the ground. We recommend calculation of the
maximum risks of radiation releases whenever they occur as long as the
geologic characteristics of the repository environment do not change
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YUCCA MOUNTAIN STANDARDS
significantly. The time scale for long-term geologic processes at Yucca
Mountain is on the order of approximately one million years. After the
geologic environment has changed, of course, the scientific basis for
performance assessment is substantially eroded and little useful
information can be cievelopect.
Because there is a continuing increase in uncertainty about most
of the parameters describing the repository system farther in the distant
future, it might be expected that compliance of the repository in the near
term could be assesses] with more confidence. This is not necessarily true.
Many of the uncertainties in parameters describing the geologic system are
clue not to temporal extrapolation but rather to difficulties in spatial
interpolation of site characteristics. These spatial cliff~culties will be
present at all times. Accordingly, even in the initial phase of the repository
lifetime, a compliance decision must be baser! on a reasonable level of
confidence in the predicteci behavior rather than any absolute proof. Under
some circumstances, use of a shorter period for analysis court! in fact
introduce additional uncertainties into the calculation. For example,
uncertainties in waste canister lifetimes might have a more significant
effect on assessing performance in the initial 10,000 years than in
performance in the range of 100,000 years.
Probabilistic Analysis of Risk
To judge compliance against a risk-base(i standard of the type
proposed, a risk analysis including treatment of all scenarios that might
leac! to releases from the repository and to radiation exposures is, in
principle, required. To include them in a stanciarci risk analysis, all these
scenarios need to be quantified with respect to the probabilities of scenario
occurrence ant} the probability distribution of their consequences to
humans, such as health effects of radiation doses. In subsequent sections
we specifically note that for some events or processes either the probability
of occurrence or the estimates! consequences become very difficult to
specify with confidence. Events caused by human activity are usually of
this type. Incorporation of such events or processes into the formalized
risk analysis sometimes is not justified on a scientific basis. Instead, how
to deal with these events should be decided as a matter of policy.
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73
This approach implies a departure in part from common analytical
techniques to assess risks and the introduction of more pragmatic
procedures needed to provide an adequate decision basis. It is important,
therefore, that the "rules" for the compliance assessment be established in
advance of the licensing process; that is, that the scenarios that might be
excluder! from the integrated risk analysis be identified. Human intrusion
is an example of one scenario that we judge to be not amenable to
incorporation in the risk assessment framework; this is discusser] further
in Chapter 4.
We believe that performance assessment using numerical models
of physical anti chemical processes and quantitative estimates of
probabilities is the key approach to assessing compliance. However, the
confidence that can be placed in such analyses is also a key part of the
compliance issues. To some extent, this degree of confidence can be
quantified, for example, by performing rigorous uncertainty analyses that
propagate uncertainties in parameter values through the analysis to produce
estimates of uncertainties in estimated risks. Uncertainties due to modeling
approaches can also be assesses! by comparing the results of assessments
using various alternative models, or by comparing mocie! results with data
collected! in experiments or in observations. In other cases, less rigorous
but useful evidence of the adequacy of models or data can be obtained by,
for example, comparisons with relevant natural analog systems.
A final, important point to note is that performance assessments of
the type summarized above are not likely to be performed only on a single
occasion preparatory to licensing. Assessments will likely be performed
iteratively during system clesign, construction and operation of a geologic
repository, and finally at the time the repository is sealed, following
decades of experience in which additional data on the performance of
system components can be gatherer).
QUANTITATIVE CALCULATION OF REPOSITORY
PERFORMANCE
In this section, we summarize general aspects of performance
assessment modeling ant! sources of uncertainty in the modeling process
before moving in subsequent sections to issues more specific to Yucca
Mountain. The main thrust of performance assessment involves
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YUCCA MOUNTAIN STANDARDS
developing a quantitative understanding of system behavior, assembling a
sufficient database of parameters describing the system, and producing
simulations of possible future system behavior allowing as fully as possible
for uncertainties in understanding or in databases. Figure 3.1 schematically
illustrates the generic modeling process described in more detail below.
Figure 3.l The Basic Steps in Performance Assessment
Natural Observations
Laboratory and Field
Experiments
develop system understanding (conceptual model)
develop quantitative models (mathematical model)
numerical implementation (numerical analysis)
test models in relevant conditions
accumulate input data on repository
(in form of probability distributions)
1
run simulations
derive estimates of consequences and probabilities
derive risk estimate
Elements of Performance Assessment
Conceplual midge!
The conceptual mode} reflects the scientists' understanding of how
the important aspects of the system work. It answers questions such as:
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What are the limits of the system? What are the geometry and composition
of the system? What are the significant physical processes? It is the
conceptual mode] that dictates the selection of the mathematical
formalisms that enable quantitative calculations to be performed.
One special type of conceptual mocle! frequently employed in
performance assessment is the scenario. In this context, a scenario means
a description of how radionuclides might migrate from the repository and
affect humans. For example, "the wastes are dissolved in ground] water,
which is transported by natural processes to an agricultural area, where it
is pumped out of the ground en cl used to irrigate crops and ingested] by
humans" is a possible scenario for the Yucca Mountain repository.
Quantitative performance assessment baser] on this scenario wouIc! then
have to employ cletailec! conceptual models of release ant] transport
processes specifying, among other things, how and where the ground water
flows and exposure scenario mociels specifying where farmers live, what
technologies they use ant! their patterns of consumption of food and water.
The scenario thus constitutes a kind of master conceptual mocle! that
guicles the selection of more detailed and specific conceptual moclels for
each step of the process.
The conceptual models are potentially the source of the most
significant uncertainties regarding the outcome of the analysis. If the
nature of the system has not been properly assessed, or the most important
processes have not been included in the conceptual model, the
mathematical mocle] based on the conceptual mode} will not properly
simulate the behavior of the system regardless of how adequately the other
elements of the analysis might be quantif~ecI.
Inadequacies in conceptual models are a particularly worrisome
aspect of the performance assessment process because a major error couIc!
invalidate the entire exercise, yet be difficult or impossible to detect.
Although, it is important to realize that this limitation is an aspect of all
human problem-solving activities, it is particularly important for
radioactive waste repository performance assessment computations
because of their long-term considerations. The best way to guard against
errors of this nature is to provide for multiple, rigorous, independent
reviews of conceptual moclels that are clearly documentecI and widely
disseminated.
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Math etnatical mode'
YUCCA MOUNTAIN STANDARDS
By mathematical mocie} we mean the mathematical relationships
that are used to describe the physical system quantitatively. The system of
equations that is incorporated in the mathematical mocle! usually represents
a simplification of the selected conceptual model. Mathematical
simplification might be required because it is not possible to filch adequate
descriptions of all the phenomena consiclerec] important, or because
incorporation of all relevant equations would result in a mathematical
system too cumbersome to solve, or because the data available do not
justify the most complete description of the system that might be possible.
Mathematical simplifications reduce the realism of the outcome of the
moclel, but the degree to which the results are affecter! can be assessed by
means of mathematical techniques, such as sensitivity analyses of
numerical results.
Numerical analysis
Most mathematical models consist of sets of coupled differential
equations. For the cases of interest to performance assessment, it is often
difficult to solve such complex systems of equations analytically, or
exactly, in which case approximate numerical methods are employed.
Selection of appropriate numerical methods is important because more
efficient numerical techniques can permit more complex (and thus,
presumably, more realistic) physical models to be solved, ant! because
inappropriate numerical schemes can introduce significant errors into
results. However, numerical inaccuracies are rarely a major source of error
in properly conducted modeling because well-established methods exist for
assessing the accuracy of numerical schemes. Further, if one approach is
found to introduce unacceptable error, it can either be replaced or modified
to achieve the desired accuracy.
Model parameters
Physical ant] chemical models require the specification of the
physical properties of the system to be modelecl. These properties are
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77
referred to as parameters. The parameters are represented by numerical
functions or values in the mathematical models. Models of the type
commonly used in performance assessment describe the behavior of the
system as a function of both space and time. Spatially heterogeneous
models of systems incorporate the spatial variations of the parameters
throughout the physical domain that is being modeled. The neeci to provide
numerical values for parameters is another source of uncertainty in
mathematical modeling. It is a goal of geologic disposal of nuclear wastes
to emplace them in an environment that is deep, remote, and clifficult to
access. These same repository properties make it clifficult to obtain data
on the spatial variations of physical parameters in the system.
Furthermore, the very procedures necessary to collect the data, such as
drilling exploratory holes to extract samples of rock might compromise the
integrity of the geologic barriers.
Boundary conditions
Performance assessment models have both spatial and temporal
boundaries, that is, times of the beginning and ending of simulations. In
general, both mass and energy can flow across these boundaries. Thus, to
perform model calculations it is necessary to specify the conditions at the
spatial ant] temporal boundaries (the mode] calculates parameter values
within the mocle] domain). Specification of the "boundary conditions" is
subject to many of the same types of uncertainty that are involved in
specifying parameter values, and they are usually ciealt with in a similar
fashion.
In general, spatial boundary conditions of regional scale subsurface
flow models are considered to be constant over time. There is at least one
important exception to this generalization. The upper boundary to the
geologic environment around the repository is the atmosphere. The
average of atmospheric conditions is the climate, and it is well known that
climate can vary significantly over geologic periods of time. Although the
typical nature of past climate changes is well known, it is obviously
impossible to predict in detail either the nature or the timing of future
climate change. This fact adds to the uncertainty of the model predictions.
During the past 150,000 years, the climate has fluctuates} between
glacial and interglacial status. Although the range of climatic conditions
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YUCCA MOUNTAIN STANDARDS
Studies have been made of the possibility that a seismic event
could produce transient changes in the water table at Yucca Mountain
sufficient to bring ground water through the repository to the surface
(NRC, 19921. Results indicate a probable maximum transient rise on the
order of 20 m or less. In summary, although the timing of seismic events
is unpredictable, the consequences of these events are bounciable for the
purpose of assessing repository performance.
Volcanism
A volcanic intrusion into the proposer! repository could be
catastrophic, releasing a major part of the repository inventory directly into
the biosphere. However, the overall risk might be very low, because it is
also a very unlikely event. Like seismicity, volcanism is episodic. The
two phenomena cocci also be linked, in that some seismic activity can be
triggered during periods of volcanic activity. Unlike seismicity, volcanism
in the Yucca Mountain region involves intermittent concentrated activity
separated by long repose periods. Even so, like seismicity, estimates of
future volcanic activity can be based on analysis of the geologic record,
with the assumption that the same pattern of events will hold in the future.
The risk from volcanism at Yucca Mountain is being examined
using a probabilistic approach. According to Crowe et al. ~1994), current
studies are designed to establish three components of an overall probability
of magmatic disruption of a repository:
1.
2.
3.
Future recurrence rate of volcanic events, such as volcanic
centers or volcanic clusters;
The probability that a future event will intersect a specified
area, such as the repository or a controlled area beyond! the
repository;
The probability that an event occurring within the specified
area will release radionuclides into the biosphere.
The probability of occurrence of the second component depends
upon the probability of the first component, and the overall probability of
raclionuclide release due to volcanism in the Yucca Mountain region
tiepentis on the combined probability of all three components. Emphasis
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95
is being given to estimating the combination of the first ant! second!
components to determine the combiner] probability that a future event will
intersect a specifier! area. This analysis is baser! on extrapolations into the
future of volcanic activity from the historic record, and on assumptions
about the spatial distribution of future volcanic eruptions in the Yucca
Mountain region. Crowe suggests that a probability of ~ 0~~/yr, which is a
1 in 10,000 possibility of a disruption over 10,000 years or ~ in 1,000
possibility in 100,000 years ~ or less might be sufficiently low to constitute
a negligible risk. If the combined probability of the first two components
can be shown to be below this level, then it might not be necessary to
consider the third component.
Efforts are underway to refine the intrusion distribution models by
incorporating geologic structure constraints. It is noteci, for example, that
the volcanic eruptions in Crater Flat appear to be aligned in the northeast
direction of the extensional faulting (across the Yucca Mountain site). If
this constraint is confirmed and included in the distribution, the probability
of a future event intersecting the repository site might fall below ~ 0~8 per
year.
While acknowledging the complexity of estimating the release of
radionuclicles to the biosphere, it seems possible, given the knowledge of
material ejected} from various types of volcanic eruptions ant! study of the
circler cones in the region, to clevelop reasonable estimates of the health
consequences from radionuclides releaser] by a volcanic eruption through
a repository at Yucca Mountain. Thus, it is believer] that the radiological
health risk from volcanism can ant] should! be subject to the overall health
risk standard] to be requires] for a repository at Yucca Mountain.
PART III: EXPOSURE SCENARIOS IN PERFORMANCE
ASSESSMENT
As noted above, we believe that it is feasible to calculate, to within
reasonable limits of certainty, potential, defined as possible but not
necessarily probable concentrations of radionuclides in ground water and
air at different locations and times in the future. To proceed from the
calculation of ra~iionucli~ie concentrations to calculations of risks that
would result from a repository, many additional factors or assumptions
about the nature of the human society at or near the repository site must be
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YUCCA MOUNTAIN STANDERS
consiclered. These factors must be included in an exposure scenario that
specifies the pathways by which persons are exposer] to radionuclicles
releaser} from the repository.
As we note in Chapter 4 with regard to the feasibility of making
projections of future human intrusion into a repository, based on our
review of the literature we believe that no scientific basis exists to make
projections of the nature of future human societies to within reasonable
limits of certainty. Therefore, unlike our conclusion about the earth
science ant! geologic engineering factors described in Part lI of this
chapter, we believe that it is not possible to predict on the basis of
scientific analyses the societal factors that must be specified in a far-future
exposure scenario. There are an unlimited! number of possible human
futures, some of which would involve risks from a repository and others
that would not.
Although the nature of future societies cannot be preclicted, it is
possible, at least conceptually, to consider several characteristics of future
society that would indicate whether a repository is likely to pose a risk to
people. A repository wouicl be unlikely to pose significant risks to future
societies: if the area near the repository were not occupied, if future
societies do not use ground water from the contaminated region, or if future
societies routinely monitor ground-water quality ant] either treat or avoid
use of contaminated sources. Conversely, exposures would result if water
wells were drilled into the contaminateci areas and the water consumed by
people or used to irrigate crops. As far as we are able to determine, there
is no sound basis for quantifying the likelihood of future scenarios in which
exposures do or do not occur; about all that can be said is that both are
possible.
It is our view, however, that once exposure scenarios have been
adopted, performance assessment calculations can be carried out for the
specified scenarios with a degree of uncertainty comparable to the
uncertainty associated with geologic processes and engineered] systems.
The more difficult task is the specification of reasonable scenarios for
evaluation. Any particular scenario about the future of human society near
Yucca Mountain that might be adopted for purposes of calculation is likely
to be arbitrary, and should not be interpreter} as reflecting conditions that
eventually will occur. Although we recognize the burden on regulators to
avoid regulations that are arbitrary, we know of no scientific method for
identifying these scenarios.
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Selection of Exposure Scenarios for Performance Assessment
Calculations
97
Any approach to assessing compliance with the standard! must
make assumptions about the nature of the human activities and lifestyles
that provide pathways for exposure. For example, people could drink
water containing radionuclicies, irrigate crops with the water, eat these
crops, and bathe in the water. Quantification of the doses receiver} from
the various pathways requires detailed data on these pathways. For the
example above, the average amount of water-ingested per day (not
including other beverages constituted with uncontaminated water) should
be known, as should the type of crops grown, the amount eaten, ant! the
frequency of bathing. The set of circumstances that affects the dose
received, such as where people live, what they eat and drink, and other
lifestyle characteristics including the state of agricultural technology, are
part of what we refer to as the exposure scenario.
Unfortunately, many human behavior factors important to
assessing repository performance vary over periods that are short in
comparison with those that should be consiclered for a repository. The past
several centuries (or even decades) have seen radical changes in human
technology and behavior, many or most of which were not reasonably
pre(lictable. For example, within the past one hundred years, our society
has evolved from one in which drilling and pumping technology did not
exist for production of water from the depths of grounc! water at Yucca
Mountain to a level of technology where such production is feasible.
Within this same time period, we have seen U.S. (demographic patterns
shift from a time where a majority of U.S. residents were engages! in
farming and grew their own food to the present day in which only a few
percent of the work force is employee] in farming, ant! in which most
people's diet includes foot] producer! outside their local area.
Given this potential for rapic! change, it is unknowable what
patterns of human activity might exist 10,000 or 100,000 years from now.
Incleed, the perioc! during which repository performance might be relevant,
on the order of a million years, is sufficiently long that any number of
different societies might reside near the repository site. Several glacial
periods probably will have occurred, making estimates of human society
even more difficult. Given the unknowable nature of the state of future
human societies, it is tempting to seek to avoid the use of such assumptions
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in performance assessment calculations. In our view, however, it is not
possible for a reasonable stanciar~i for the protection of human health to
avoid use of some specified assumptions about future populations, patterns,
and lifestyles around a proposed repository site. Even regulatory standards
stated in terms of geologic and engineering factors are not inciependent of
assumptions about future exposure scenarios. For example, the
containment requirements of 40 CFR 191 were apparently developed based
on consideration of a global release scenario in which average doses to
large populations were considered.
The problem is how to pick an exposure scenario to be user! for
compliance assessment purposes. Given the lack of a scientific basis for
doing so, we believe that it is appropriate for the regulator to make this
policy decision. One specific recommendation we make is to avoid placing
the burden of postulating and defencling assumptions about exposure
scenarios on the applicant for a license. The regulator appears to be better
situates! than the applicant to carry the responsibility because of the
perception that any future scenario cievelopeci by the applicant could have
been chosen to give the desired outcome. On the other hand, the results of
calculations from a scenario specified by the regulator in an open process
designed to consider the views of all the interested! parties might be seen
as a fair test of the suitability of a site and design.
In addition, we recommend against an approach under which a
large number of future scenarios are specified for compliance assessment,
since such an approach could be seen as putting both the regulator and the
applicant in the indefensible position of claiming to have considered a
sufficient number of scenarios and that all reasonable future situations are
represented] in the analysis. The purpose of making exposure scenario
assumptions is not to iclentiiTy possible fixtures, but to provide a framework
for the analysis and evaluation of repository performance for the protection
of public health.2
2 Another argument for using a large number of scenarios is that iterative analysis
of repository performance will lead to the most cost-effective repository design.
This might be true, but we believe that the regulator must in the end assess
compliance with a single level of protection as defined in the standard.
Therefore, one (or at most a few) exposure scenarios must be specified for
compliance assessment purposes.
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Specification of the exposure scenario assumptions to be user} in
performance assessment at Yucca Mountain will greatly influence whether
the site and ciesign can comply or not. The selection of exposure scenarios
is perhaps the most challenging and contentious aspect of risk and
compliance assessment. For example, EPA guidlines for exposure
assessment reflect a philosophical disagreement over the question of when
and how to depart from the theoretical upper bounc] estimate of exposure
and to employ probabilistic techniques (Federal Register 57 fMay 29,
19921: 22888-229381. These questions, which are at the interface between
science anti policy judgment, are also acIdresseci in Science and Judgment
in Risk Assessment (NRC, 19941. For these reasons, we strongly
recommend that the decision be made through a public rulemaking process.
This process will provide a more complete analysis of the advantages and
iisadvantages of alternative scenarios than we have been able to perform,
and do so with the benefit of full public participation.3
As with other aspects of defining the standards and demonstrating
compliance that involve scientific knowlecige but must ultimately rest on
policy judgments, we considered what to suggest to EPA as a useful
starting point for rulemaking on exposure scenarios. Reflecting the
disagreement inherent in the literature, we have not reached complete
consensus on this question.
We do agree, however, that the exposure scenario user} to test
compliance should not be based on an inclividual dei ined by unreasonable
assumptions regarding habits and sensitivities affecting risk. It is essential
that the exposure scenario that is ultimately selected be consistent with the
critical-group concept that we advanced in Chapter 2. The purpose of
using a critical group is to avoid using the standard to protect a person with
unusual habits or sensitivities. The critical-group approach does this by
using the average risk in the group for testing compliance. To ensure that
this average risk nevertheless affords a high level of protection to most
persons, the group must contain the persons at highest risk within the group
and must be homogeneous in risk. An exposure scenario selected for
3 This rulemaking need not be done before the promulgation of an individual-risk
standard that we recommended in Chapter 2. Indeed, we would not want the
selection of that standard to be colored by foreknowledge of the assumptions
incorporated in the exposure scenario.
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YUCCA MOUNTAIN STANDARDS
compliance assessment should procluce a critical group with these
characteristics.
Aciditionally, we note that the {CRP (1985a) recommends that the
critical group be defined using present knowledge4 and cautious, but
reasonable, assumptions. Although this guidance was originally intended
for the regulation of dose limits, we believe that it is generally appropriate
in applying the critical-group concept to risk, as we have recommencied.
EPA should rely on this guiciance when choosing the assumptions for the
exposure scenario to be used for performance assessment.
Finally, we have considered the design of an exposure scenario that
EPA might propose when it initiates the rulemaking process. We have
considered} two illustrative approaches for this purpose. We describe the
two approaches in Appendixes C and D, and summarize their important
characteristics below.
A substantial majority of the committee considers that the
approach outliner! in Appendix C is more clearly consistent with the
foregoing criteria for selecting an exposure scenario than is the alternative
in Appendix D, and therefore believes that: EPA should propose an
approach along the lines of Appenclix C. Of course, other methods might
also meet these criteria, ant! some of the methods might be less complex
than the method illustrated in Appendix C.
Although the following discussion highlights differences between
the two approaches, we wish to stress that the approaches are similar in
many ways.
The approach in Appendix C makes use of information that can be
collected on the factors that influence human behavior in the present.
Assumptions about factors such as the source of foot! would! be based on
the source of food for today's population near the repository site. The
Appendix C approach bases the exposure scenario on a population
distribution rierived from observer! statistical associations between
environmental parameters and the population distribution of actual
population groups. For example, such parameters couic} inclucle depth to
4 We understand "present knowledge" to mean any knowledge that is available
today, and so should be read as an injunction against making assumptions about
knowledge that might exist in the future. For example, assuming that future
societies will have found a cure or prevention for cancer would not be present-
day knowledge.
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ASSESSING COMPLIANCE
101
water, soil type and depth, land slope, and growing season. This approach
uses statistical techniques to compute a critical group for each of a large
number of simulations of the contaminated ground-water plume and then
averages over these calculations to identify the average critical group for
compliance purposes.
Important characteristics of this approach include the following.
First, it extends the probabilistic methods that have been applied to
simulations of physical processes (such as transport of ground-water
contaminants) to analysis of the factors affecting exposure. Second,
although mathematically complex, the model is based on currently
observable data and does not require assumptions regarding specific values
of parameters, only ranges within which the parameters might fall. Third,
the degree to which conservatism is incorporated is determined not only by
the analyst in selecting the ranges of parameters that describe farming
lifestyles but also by the regulator when the standard is set. Fourth, it
requires that the probability that persons occupy specific parcels of land for
farming be determined statistically by the relevant characteristics of the
land, ground water, and technology that influence farming, avoiding the
potential that the standard could be influenced by a situation in which the
maximum dose occurred at a place that was uninhabitable or otherwise
unsuitable for farming.
The approach in Appendix D specifies a priori one or more
subsistence farmers as the critical group and makes assumptions designed
to define the farmer at maximum risk to be included in the critical group.
The subsistence farmer would be a person with eating habits and with
response to doses of radiation that are normal for present-day humans. All
food eaten over the lifetime of the subsistence farmer would be grown with
water drawn from an underground aquifer contaminated with radioactivity
from the repository. The water would be withdrawn at a location outside
the footprint of the repository and near that maximum potential
concentration of the most critical radioactive contaminant in the ground
water so that the scenario describes the maximum dose and risk. All of the
farmer's drinking water would come from that same source. For
compliance assessment purposes, it is assumed that the homogeneity
criterion (see the definition of critical group in Chapter 2) applies and that
the risk to the average member of the critical group is about one-third that
of the subsistence farmer.
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YUCCA MOUNTAIN STANDARDS
The important features ofthe subsistence-farmer mode! include the
following. First, it has been used extensively in radioactive waste
management programs in the United States ant! other countries, so a body
of experience with it exists on which to draw. Second, it is straightforward
en c! relatively simple to understand and calculate. Third, while it
incorporates a series of assumptions about the lifestyle of the hypothetical
farmer, any degree of conservatism can be built into the mode! by choices
among alternative assumptions, which can be based on current conditions
in the Amorgosa Valley; these assumptions need not be constrained by the
characteristics of the current population of the region. Fourth, it makes the
most conservative assumption that wherever en c} whenever the maximum
concentration of raclionuclides occurs in a ground water plume accessible
from the surface, a farmer will be there to access it.
These approaches have many elements in common. Most
important, both rely on probabilistic methods of estimating the distribution
of raciionuclides in the environment. Both also incorporate knowledge of
the natural geologic features of the environment that influence the potential
for exposure and both are intended to incorporate cautious, but reasonable'
assumptions about lifestyles of the affected populations that the EPA might
propose in a rulemaking. For example, both assume eating habits and
response to radiation doses that are normal for present-day humans.
Despite these similarities between the approaches, two major
issues that differentiate them have emerged from our consideration. These
issues are summarized below:
Assumptions about the location and lifestyle of persons who
might be exposed to radionuclides released from the
repository are crucially important because they affect the
identification of the person at highest risk that must be
contained in the critical group. The two approaches differ in
their treatment of these assumptions. For example, the
approach in Appendix D specifies a priori that a person will
be present at the time and place of highest nuclide
concentrations in grounc} water and will have such habits as
to be exposed to the highest concentration of radiation in the
environment. This person is assumed to define the upper
limit of risk in the critical group. Appendix C treats the
distribution of potential farmers probabilistically based on
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ASSESSING COMPLIANCE
103
current technical understanding of farming in the region.
Because the person at highest risk might not be the same
uncler the two approaches, the critical group selected for
compliance assessment could be different.
The second difference involves the method of calculating the
average risk of the members of the critical group. Appendix
C uses detailed statistical analysis to clef~ne the critical
group. Specifically, it identifies a "critical subgroup" for
each of a large number of Monte CarIo realizations of the
contamination plume. The critical group risk is determiner}
by averaging over the average risks to each of these
subgroups. In contrast, the Appendix D approach
approximates the average critical group risk at about one-
thirc! of the risk faced by the person at highest risk, since the
requirement that the critical group be homogeneous in risk
implies that the overall range of risks in the critical group be
limited to about a factor of ten. If the distribution of risk
among members of the critical group is not relatively
uniform, these approaches could produce different averages.
As notes! earlier, we agree that unrealistic assumptions are
inappropriate. Our divergence of view is on the extent to which the
alternative sets of assumptions embodies} in Appendixes C ant} D are
cautious, but reasonable. The approach of Appendix C has the advantages
of explicitly accounting for how the physical characteristics of the site
might influence population distribution ant! of identifying the makeup of
the critical group probabilistically. Most of the committee regard these as
desirable features of exposure scenarios that are intended to be consistent
with the critical-group concept. We emphasize, however, that specification
of exposure-scenario assumptions is a matter for policy decision.
Exclusion Zone
The original standard, 40 CFR 191, contained a provision for an
exclusion zone in the immediate vicinity of the repository. The purpose
was to provide a boundary for calculating releases.
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YUCCA MOUNTAIN STANDARDS
In light of our conclusion in Chapter 4 that there is no scientific
basis for assuming that institutional controls can be maintained for more
than a few centuries, we also conclude that there is no scientific basis for
assuming that human activity can be prevented from occurring in an
exclusion zone or that defining such a zone will provide protection to
future generations from exposures in the vicinity of the repository.
The question remains whether an exclusion zone serves a useful
purpose for compliance assessment. In our analysis, we have assumed that
some human activities, such as drilling into or through the repository,
should be treated as special cases of human intrusion (see Chapter 4~. If,
as we recommencI, human intrusion is treater] separately from the
performance of an undisturbeci repository, it is reasonable in our view to
clefine a region in which human activities are to be regarded as intrusion
and to exclude that region from calculation of the undisturbed repository
performance. For example, if we assume that all drilling for water wells
is vertical, the area directly above the repository plan (or footprint) would
be consiclered an exclusion zone for purpose of calculating compliance
with that part of the standard that applies to undisturbed performance.
Drilling in that zone would be a case of human intrusion.
Beyond the repository footprint, however, there seems to be no
practical purpose for defining a larger exclusion zone for the form of the
standard we recommenct. Without either a release limit or a time limit for
the standard for undisturbed performance, an arbitrary boundary serves no
purpose. In the approach we recommend, an objective of performance
assessment calculations is to determine the time in the future when risks
from exposure to radionuclides released from the repository are greatest
ant] to base the regulatory judgment about compliance on a comparison of
the risks at that time to the standard. Furthermore, neither of the
alternatives for treating the critical group requires an exclusion zone larger
than the repository footprint.
Representative terms from entire chapter:
assessing compliance
