United States
Environmental Protection
Agency
Air and Radiation
(6603J)
93550-61
EPA 540-R-96-004
PB96-963303
January 1996
Three Multimedia Models
Used at Hazardous and
Radioactive Waste Sites
*****
Printed on Recycled Paper
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THREE MULTIMEDIA MODELS USED AT HAZARDOUS
AND RADIOACTIVE WASTE SITES
A Cooperative Effort by
Office of Radiation and Indoor Air
Office of Solid Waste and Emergency Response
U.S. Environmental Protection Agency
Washington, D.C 20460
Office of Environmental Restoration
U.S. Department of Energy
Washington, D.C. 20585
Office of Nuclear Material Safety and Safeguards
Nuclear Regulatory Commission
Washington, D.C. 20555
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FOREWORD
This report was produced by the Interagency Environmental Pathway Modeling Working Group.
The Working Group includes representatives of the U.S. Environmental Protection Agency - Offices of
Radiation and Indoor Air, and Solid Waste and Emergency Response, the U.S. Department of Energy -
Office of Environmental Restoration, and the U.S. Nuclear Regulatory Commission - Office of Nuclear
Material Safety and Safeguards. The purpose of the Working Group is to promote the appropriate and
consistent use of mathematical models in the remediation and restoration process at sites containing - or
contaminated with - radioactive and/or mixed waste materials. This report provides an approach for
evaluating and critically reviewing the capabilities of three specific multimedia models: MEPAS Version
3.0, MMSOILS Version 2.2, and PRESTO-EPA-CPG Version 2.0. These models are being used by the
sponsoring Offices to support cleanup decision-making at various waste sites, and are of technical
interest to them. The approach for model review advocated in this report is intended to assist technical
staff responsible for identifying and implementing multimedia models in support of cleanup decisions at
radioactive and hazardous waste sites. It is hoped that information in this report will enhance the
understanding of these three models within the context of specific media components, human exposure
and dose, and how they report uncertainty.
This document is one of several being developed by the Working Group to bring a uniform
approach to solving environmental modeling problems common to all Federal agencies. The following
are other reports prepared by this Interagency Working Group:
• Computer Models Used to Support Cleanup Decision-Making at Hazardous and Radioactive
Waste Sites, EPA 402-R-93-005, March 1993.
• Environmental Characteristics of EPA, NRC, and DOE Sites Contaminated with Radioactive
Substances, EPA 402-R-93-011, March 1993.
• Environmental Pathway Models - Ground Water Modeling in Support of Remedial Decision-
Making at Sites Contaminated with Radioactive Material, EPA 402-R-93-009, March 1993.
• A Technical Guide to Ground Water Model Selection at Sites Contaminated with Radioactive
Substances, EPA402-R-94-012, June 1994.
• Evaluating Technical Capabilities of Ground Water Models Used to Support the Cleanup of Low-
Level Radioactive Waste Sites: A Critique of Three Representative Models, Draft, March 1994
• Documenting Ground Water Modeling at Sites Contaminated with Radioactive Substances, EPA
540-R-96-003. January 1996.
The project Officers of the Interagency Working Group (Beverly Itla - EPA, Paul Beam - DOE.
Sam Nalluswami - NRC) acknowledge the cooperation and insight of many staff in preparing this
document from organizations including EPA/Environmental Research Laboratory, Athens Georgia. EPA
Office of Radiation and Indoor Air Criteria and Standards Division, Washington, D.C ; and Batelle/Pacific
Northwest Laboratories, Richland Washington. We would also like to thank all those from EPA Regions
II, III. IV, V, VI, and VIII; EPA Office of Emergency and Remedial Response; EPA Office of Radiation
Programs/Las Vegas; EPA National Air and Radiation Environmental Laboratory; DOE Office of
Environmental Restoration, and NRC Office of Material Safety and Safeguards, who graciously agreed
to provide review and comment. We also thank their managers who permitted them the time to provide
us with valuable input.
This report was prepared under IAG DW89934985, Paul Moskowitz, Project Officer, Brookhaven
National Laboratory.
iii
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KEY ABBREVIATIONS USED IN THIS REPORT
Ci Curie
cm centimeter
d day
g gram
kg kilogram
km kilometer
L liter
m meter
mg milligram
min minute
pCi pico-Curie
s sec
SI System Internationale
Sv Sieved
yr year
IV
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EXECUTIVE SUMMARY
Purpose
Multimedia models are used commonly in the initial phases of the remediation
process where technical interest is focused on determining the relative importance of
various exposure pathways. This report provides an approach for evaluating and
critically reviewing the capabilities of multimedia models. This study focused on three
specific models: MEPAS Version 3.0, MMSOILS Version 2.2, and PRESTO-EPA-CPG
Version 2.0. These models evaluate the transport and fate of contaminants from
source to receptor through more than a single pathway. They have been used to
support cleanup decision-making at various sites and are of technical interest to the
sponsoring organizations. The approach to model review advocated in this study is
directed to technical staff responsible for identifying, selecting and applying multimedia
models for use at sites containing radioactive and hazardous materials The presence
of radioactive and mixed wastes at a site poses special problems. Hence, in this
report, restrictions associated with the selection and application of multimedia models
for sites contaminated with radioactive and mixed wastes are highlighted It is hoped
that information in this report will enhance the understanding of these three models
within the context of specific media components, human exposure and dose, and how
they report uncertainty.
Report Structure
This report begins with a brief introduction to the concept of multimedia
modeling, followed by an overview of the three models. The remaining chapters
present more technical discussions of the issues associated with each compartment
and their direct application to the specific models. In these analyses, the following
components are discussed:
• Source Term
• Air Transport
• Ground Water Transport
• Overland Flow, Runoff, and Surface Water Transport
• Food Chain Modeling
• Exposure Assessment
• Dosimetry/Risk Assessment
• Uncertainty
• Default Parameters
The report concludes with a description of evolving updates to the model: these
descriptions were provided by the model developers.
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Model Selection
There are many multimedia models in use for simulating the transport, fate and
effects of contaminants present at waste sites. All of these models could not be
reviewed as part of this effort. Thus, the sponsoring agencies requested that MEPAS,
MMSOILS, and PRESTO-EPA-CPG be reviewed because of their technical interest in
these specific models. This should not be interpreted to mean that any of the agencies
endorse any of these models or the specific findings presented in this report
MEPAS, whose development was sponsored by the DOE, has a broad coverage
of pathways and scenarios for radioactive and chemical hazardous materials.
MMSOILS and PRESTO-EPA-CPG were developed by the EPA MMSOILS is meant to
be used for the screening and comparison of hazardous sites contaminated with toxic
chemicals that are released from underground storage tanks, impoundments, waste
piles, landfills, and injection wells. PRESTO-EPA-CPG was designed specifically to
provide annual committed dose equivalent estimates from the release of radionuclides
from low-level radioactive waste sites.
Model Components
Source Term
MEPAS is the most versatile of the three models, with the greatest ability to
handle a variety of different types of source terms. Although the PRESTO-EPA-CPG
model handles source terms only from near-surface trenches, its family of models can
handle a variety of source terms, including contaminated soil, waste piles, deep-well
injection, and underground tanks. MMSOILS is the only one of the three models
reviewed here that performs a mass balance for the air and ground water pathways
separately, relative to the initial source term. The generation of leachate into the
ground water is estimated by different, but similar, means in all three models.
Atmospheric Pathway
A sector-averaged Gaussian plume algorithm is used by all three models to
simulate the atmospheric transport of contaminants. The PRESTO-EPA-CPG model
includes the effects of wet deposition and radioactive decay. The current version of the
model does not include a volatile source term generation from a storage lagoon or lake.
While the overall modeling capabilities of MMSOILS are similar to those of MEPAS,
MMSOILS is less sophisticated in modeling the atmospheric pathway It does not
describe complex terrain, calms, depletion of the plume by wet deposition, and
contaminant decay. MMSOILS cannot model releases from vents or stacks. However,
this option is required only for modeling emissions from waste cleanup facilities, not
from hazardous waste sites The paniculate emission models which are included in
both MEPAS and MMSOILS are particles from wind erosion, vehicle traffic, and soil-
vi
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spreading operations. MMSOILS has a model of loading and unloading operations, but
MEPAS does not. Finally, MEPAS has some capabilities which none of the other
models have, namely, air sources (i.e., defining a source by ambient concentrations),
calm meteorological conditions, and complex terrain.
Ground Water
Overall, MMSOILS has the most complex ground water pathway, since it alone
uses a finite-element model for the unsaturated zone that incorporates layered
heterogeneity. Unfortunately, there are two problems with simulating radioactive
contaminants: (i) MMSOILS assumes that the contaminant does not decay while it is
sorbed onto soil, and (ii) MMSOILS only models nonradioactive substances and does
not explicitly simulate the ingrowth of progeny. Conceivably, the first problem could be
overcome by entering a radioactive decay rate that is multiplied by the K^. The second
problem cannot be avoided easily, especially for short-lived contaminants. The
PRESTO-EPA model employs a simple, one-dimensional model. MEPAS simulates
ground water transport using a 3-D algorithm, but assumes that radioactive progeny
have the same Kd as the parent. This can introduce error into the source and down-
gradient concentration estimations.
Surface Water Transport
All three models take a rather similar, simplistic approach to modeling the
surface water pathway. Both MEPAS and MMSOILS link ground water and surface
water media by converting the ground water flux feeding into the surface water into an
input flux to the surface water medium. The PRESTO-EPA-CPG model uses system
equations representing the surface water, subsurface water, and atmospheric diffusion
systems to calculate the rate of deep ground infiltration flow, overland flow, and the rate
of evapotranspiration. If conditions allow, the overland flow may combine with the
overflowing leachate. Then, this combined flow (with or without leachate overflow)
interacts with the contaminated soil. The combined overland flow is programmed also
to simulate the leaching of the contaminant out of the soil and transport into the nearby
surface water to be pumped for human drinking, irrigation, and cattle feed. All three
models employ the Universal Soil Loss Equation to estimate soil erosion across a site.
Food Chain Modeling
MEPAS includes food chains as an integral part of its exposure-dose
component Food chains are considered separately in MMSOILS and in PRESTO-
EPA-CPG as agricultural data supporting exposure estimates. Although MEPAS can
be used to model acute toxic atmospheric releases, all three models were designed
primarily to handle long-term, chronic exposures. Each of the three models employ
comparable, standard methods for estimating exposure to environmental contaminants
through the food chain and other pathways. Therefore, the same limitations that exist
for all exposure and risk assessments exist for these models. For example, food intake
is subject to behavioral variations. Both the quantity and type of foods eaten vary from
vii
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(Table S.1 cont'd. Summary of model features. I
Bio-accumulation
Animals
Terrestrial plants
Foliar deposition
Aquatic organisms
Spatial definition
Site Data Required
Contaminant Selection
Hazardous chemical waste
Radioactive waste
Intakes from Ingestion of
Drinking Water
Shower Water
Swimming Water
Leafy Vegetables
Other Produce
Meat
Milk
Finfish
Shellfish
Special Food
Shoreline Sediment
Soil
Intakes from Inhalation
While Showering
Of Air
Of Re-suspended Soil
Intakes from Contact
While Showering
While Swimming
With Shoreline Sediment
With Soil
With Volatiles in Air
External Exposures.
While Swimming
While Boating
From Air
With Soil
With Shoreline Sediment
From Direct Radiation.
MEPAS
yes
yes
yes
yes
2-D
Extensive
yes
yes
yes
yes
yes,,
yes;1
yes'3
yes
yes
yes
yes
yes
yes
yes
yes
yes
yes
yes
yes
yes
yes4
yes
yes
yes
yes
yes
yes
yes
MMSOILS
yes
yes
yes
yes
2-D
Moderate
yes
no
yes
no
yes
yes
no
yes
yes
yes
no
no
no
yes
no
yes
yes
no
no
no
yes
no
no
no
no
no
no
no
PRESTO-EPA-CPG
yes
yes
yes
no
2-D
Moderate
no
yes
yes
no
no
yes
yes
yes
yes
yes
yes
eggs
yes
yes
no
yes
yes6
no
no
no
no
no
no
no
yes
yes
no
no
1 This component not available in 1993 version.
2 From air deposition on crops.
3 From irrigation of crops.
4 Estimations based on either measured concentrations or on calculated accumulations
in soil after atmospheric deposition.
5 In the version modified for cleanup scenarios.
6 On-site scenario only
7 MMSOILS only considers ground surface roughness in wind erosion of particulates.
XII
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CONTENTS
FOREWORD iii
EXECUTIVE SUMMARY v
1. INTRODUCTION 1
2. MULTIMEDIA PATHWAY ANALYSIS 3
3 MODEL OVERVIEW 9
4. SOURCE TERM 17
5. AIRTRANSPORT 25
6 GROUND WATER TRANSPORT 33
7 RUNOFF, EROSION, AND SURFACE WATER TRANSPORT 43
8. FOOD CHAIN MODELING 49
9 EXPOSURE ASSESSMENT 53
10 DOSIMETRY/RISK ASSESSMENT 57
11 UNCERTAINTY ANALYSIS 63
12 PARAMETER ESTIMATION AND DEFAULT PARAMETERS 65
13 DISCUSSION/CONCLUSIONS 71
14. REFERENCES 77
X1H
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TABLES
S.1 Summary of model features xi
2 1 Typical exposure pathways by medium for residential
and commercial land uses 7
2.2 Summary of major intermedia transport routes 7
3.1 Some other representative multimedia models 12
3.2 Examples of model usage of other models 13
3.3 Evaluations of some other representative multimedia models 15
4.1 Model source term capabilities 17
42 Source term of volatilization scenarios 20
5.1 Atmospheric pathway. Comparison of capabilities 29
6.1 Ground water pathway: Comparison of capabilities 36
6.2 Data requirements for MMSOILS 40
6.3 Data requirements for MEPAS 41
64 Data requirements for PRESTO-EPA-CPG 42
7.1 Surface water pathway: Comparison of capabilities 45
7.2 Data input requirements of the surface water pathway 48
8.1 Summary of food chain features in models 50
82 Details of food chain levels in the models 51
9.1 Summary of exposure features in models 54
12.1 Input parameters for arsenic 68
12.2 Input parameters for benzene 69
13.1 Summary of model features 75
FIGURES
2.1 General air pathways to humans 6
22 General liquid pathways to humans 6
23 Relative relationships between input-data quality, output uncertainty,
and types of problems addressed by each level of assessment 8
5 1 Simplified pathways between radioactive materials released to
atmosphere and humans 25
5.2 Diagram of pathway interactions 26
6.1 Conceptual diagram of the ground water pathway 34
7.1 Pathways for surface water exposure 43
8.1 Basic food chains as depicted in risk assessments 49
XIV
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1. INTRODUCTION
Significant efforts are being made to remediate waste sites containing
radioactive materials and hazardous wastes. The remediation goals may be based on
reducing potential chemical or radiation doses to the public from all significant
scenarios, media, and exposure pathways. Remediation strategies are typically based
on an assessment founded on the use of computer models because of the complexities
of sites and of the characteristics of the contaminants. These computer models use
sets of mathematical equations incorporating many factors that cause or affect the
movement of contaminants and radionuclides through various media including their
intake by humans. Computer models are used now routinely by the U.S Environmental
Protection Agency (EPA) and others [e.g., Nuclear Regulatory Commission (NRC)] for
setting standards and regulations, and by the U.S. Department of Energy (DOE) and
others for determining the priorities and benefits of alternative cleanup options.
The EPA Office of Radiation and Indoor Air and Office of Solid Waste and
Emergency Response, and the DOE Office of Environmental Restoration are
attempting to develop a uniform approach to solving their common problems in
environmental modeling for site remediation and restoration. As part of this effort, this
report reviews in detail three multimedia models used by these agencies - MEPAS
version 3.0, MMSOILS version 2.2, and PRESTO-EPA-CPG version 20
The results of the analyses reported here are not intended as an endorsement
of any of the models reviewed. Rather, the intention is to provide the reader with both
an approach for evaluating mathematical models as well as an evaluation of each
model's capabilities and limitations.
This report begins with a brief introduction to the concept of multimedia
modeling, followed by an overview of the three models. The remaining chapters
present more technical reviews of the sub-components of the models. Each chapter
discusses first briefly the specific media component, then how each model handles
radionuclide transport within that compartment, and finally describes evolving updates
to the model.
In these analyses, the following pathway and risk assessment components are
discussed:
• Source Term
• Air Transport
• Ground Water Transport
• Surface Water Transport
• Food Chain Modeling
• Exposure Assessment
• Dosimetry/Risk Assessment
• Uncertainty
• Default Parameters
i
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The reviews are based on the following sources of information.
• Documentation from model developers, including Users' and Methods Manuals,
Guides, Appendices, Revisions, and Addenda which explain or clarify the use or
basis for each model.
• Reviews of models contained in the peer-reviewed literature and the results of
formal review programs.
• Personal interviews with the models' developers to answer specific questions
about features that are not discussed in the documentation, and to learn of
proposed or expected developments for new versions of the models.
• Computer databases and expert systems, like the Integrated Model Evaluation
System (USEPA, 1993b) and Exposure Models Library (USEPA, 1994a), that
were developed to aid in selecting models appropriate for different applications.
The documentation available does not always describe upgrades or planned
modifications because model building is an ongoing process To this end, the
developers of each model reviewed in this report were contacted and asked to provide
a letter-report to update information contained in the model documentation.
Improvements were summarized in the individual chapters.
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2. MULTIMEDIA PATHWAY ANALYSIS
2.1 Media-Based Analyses
Multimedia modeling begins with a source of contamination and ends with a
calculation of risk for the final assessment. Ideally, such a model would evaluate every
possible pathway by which a contaminant is carried through every potential media from
source to humans. Given a known or assumed concentration of a contaminant at a
source and, from that, computing a risk is an extremely complex procedure. As stated
by Seigneur et al. (1992):
"A comprehensive treatment of all these processes would require a
multimedia transport model with fine spatial and temporal resolutions in all
media, two-way inter-media transport, treatment of population dynamics
with resolution of population cohorts according to activity patterns, age
groups and physiological status: description of population exposure in a
variety of micro-environments; and the development of accurate dose-
response relationships "
Multimedia models may neither consider every potential pathway with the same
thoroughness, nor every pathway between media. Even when some inter-media
pathways are included, a model may not account accurately for the fate of material
transported from one media to another However, as Ryan (1993) pointed out, people
may be exposed to contaminants indirectly through inter-media transport, as well as
directly.
Several documents incorporating pathway analyses including estimating
radiation dose in the environment were prepared for a variety of well-defined
conditions. The Environmental Impact Statement (EIS) in support of licensing
requirements for shallow land burial of low-level radioactive waste (10 CFR 61) is one
example Regulatory Guide 1.109 issued by the Nuclear Regulatory Commission is
designed to be used for any release to the environment from effluent streams for any
nuclear power plant. This document recommends how a generalized pathway analysis
can be structured for a given effluent medium (air, water) in a particular environmental
setting.
Figures 2.1 and 2.2 adapted from Dugan et al. (1990) illustrate simplified
pathways for the release of radioactive and hazardous materials to the atmosphere and
water, and their routes of exposure to humans. In these suggested transport models,
air is contaminated by re-suspension and volatilization of radionuclides and chemicals.
The roots of the plants take up the material They are contaminated externally by the
deposition of suspended particles. Herbivores take in radionuclides from the ingestion
of soil, by grazing on contaminated vegetation, by drinking water, and by inhaling dust.
The maximally exposed person is someone who lives in. and obtains their food from,
the contaminated area, inhales contaminated air, drinks contaminated water, and
ingests contaminated vegetation, meat, and dairy products from animals raised there
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People can be exposed to radioactive and hazardous contaminants present in
the soil at National Priority List (NPL) and other sites through four basic environmental
media (i) the atmosphere (ii) surface water, (iii) soil and ground water; and (iv) biota
The exposure pathways shown in Table 2.1 are considered by EPA to be typical of
those to be included in any evaluation of human health conducted at a SUPERFUND
site (Office of Emergency and Remedial Response, 1991).
Among these different media, a variety of inter-media transport mechanisms
exist (Table 2.2). Choosing among the ones that should be included in any model
requires balancing several competing concepts: modeling objectives,
simplicity/complexity of the model; scenario/site complexity; data availability; and. the
value of the information provided
22 Level of Analysis
Practically, three levels of multimedia analysis can be identified (Whelan, et al ,
1994).
• Screening-level (ranking)
• Analytical (prioritization and preliminary assessments)
• Numerical (detailed)
Early in the process, screening models are used to identify environmental
concerns These models are based often on a structured-value approach They are
designed to be used with regional/representative information. Models such as the EPA
Hazard Ranking System (MRS) (USEPA, 1988b; USEPA, 1990b) divide the site and
release characteristics into pre-determined categories that are assigned a point value
based on answers to questions. The score from such systems is useful to determine if
a situation is a problem, but not to provide a risk-based relative ranking of problems
Detailed analyses require a highly specialized assessment of potential impacts
Methodologies such as the Chemical Migration Risk Assessment (CMRA) are
composite-coupled approaches that use numerically based models that are not
physically linked and represent single-medium models, implemented independently in
series This approach is reserved usually for the most complex models, is data-
intensive, and relies on the expertise of the analyst. These detailed models are used to
determine the levels of risk associated with relatively well-defined, complex problems,
and tend to focus on special sets of problems and special types of situations. Although
such tools are appropriate for their intended application, extension beyond site-specific
applications is often either difficult or cost-prohibitive.
Analytical/Semi-Analytical/Empirical-Based multimedia models (designated as
analytical models) can be used for prioritization or preliminary assessments Most
often, they are employed between initial screening and highly specialized numerical
models These models are the most versatile as they do not have the data constraints
4
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of the numerical models, but are physics-based, unlike the structured-value models.
The analytical models may contain some numerical computations (hence the semi-
analytical designation). The analytical models provide environmental evaluations
through a wide range of applications. These models are fully coupled approaches that
use analytically, numerically, and empirically based algorithms that are combined into a
single code to describe each environmental medium.
Figure 2.3 illustrates the value of analytical models in the waste-site evaluation
process. They can be used in a detailed (i.e., numerical) or an initial-screening (i.e.,
ranking/prioritization) assessment, where data and circumstances warrant Figure 2.3
illustrates also the relative relationships between input-data quality, output uncertainty,
and types of problems at each level of assessment. The computational requirements
tend to be less at the earlier stages of an assessment when there are fewer available
data and, correspondingly, the uncertainty with the output results tends to be greater.
As the assessment progresses, improved site-characterization data and
conceptualization of the problem increase, thereby reducing the overall uncertainty in
risk estimates.
The analytical multimedia models integrate standard approaches into a
consistent, yet powerful, tool. The multimedia models incorporate medium-specific,
transport-pathway, and exposure-route codes that are based on standard, well-
accepted algorithms. For example, these multimedia models employ analytical
solutions to the advective-dispersive equations that describe transport in the ground
water environment. When coupled, the models allow the analyst to immediately assess
the entire process of contaminant release, transport, exposure, and risk at one sitting.
Some models give the user the freedom to by-pass the transport components and use
only the exposure/risk components. The value of a coupled model is exemplified by an
order-of-magnitude reduction in assessment time, as compared to an uncoupled model
Multimedia models assess concurrently multiple waste sites with multiple
constituents to include baseline (at time = 0 yrs), no action (at time > 0 yrs), during-
remediation, and residual (post-remediation) assessments, including changing land-
use patterns (e.g., agricultural, residential, recreational, and industrial). The
multimedia models can describe the environmental concentrations within each medium
at locations surrounding the waste. Spatially distributed, three-dimensional,
concentration isopleths can be constructed detailing the level of contamination within
each environment. Three-dimensional risk isopleths can be developed by coupling
land-use patterns with the environmental concentrations.
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Human*
Figure 2.1 General air pathways to humans (after Dugan et al., 1990)
Radioactive
Materials
ijt :j •-.••.. v
:: v.. ^•:-..-•. V.....
Aquatic
Plants & Animals
Ground Water
Humans
Figure 2.2 General liquid pathways to humans (after Dugan et al.. 1990)
6
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I Table 2.1. Typical ex
MEDIUM
Ground Water
Surface Water
Soil
posure pathways by medium for residential and commercial land uses.
Exposure Pathways, Assuming
RESIDENTIAL/RECREATIONAL LAND
USE
Ingestion from drinking
Inhalation of volatiles
Dermal absorption from bathing
Immersion-external
Ingestion from drinking
Inhalation of volatiles
Ingestion during swimming
Ingestion of contaminated fish
Immersion - external
Ingestion
Inhalation of volatiles & particles
Direct external exposure
Ingestion via plant uptake
Ingestion of meat, milk and other animal
products
Dermal absorption from gardening
COMMERCIAL/INDUSTRIAL LAND
USE
Ingestion from drinking
Inhalation of volatiles
Dermal absorption
Irrigation
Ingestion from drinking
Inhalation of volatiles
Irrigation
Ingestion
Inhalation of volatiles & particles
Direct external exposure
Table 2.2. Summary of major intermedia transport routes.
Transport from the Atmosphere to Land and Water
Dry deposition of particulate and reactive gaseous pollutants
Precipitation scavenging of gases and aerosols
Adsorption onto particulate matter and subsequent dry and wet deposition
Transport from Water to Atmosphere, Sediments, and Organisms
Volatilization
Aerosol formation at the air/water interface
Sorption by sediment and suspended solids
Sedimentation and re-suspension of solids
Uptake and release by biota
Transport from Soil to Water, Sediment, Atmosphere, or Biota
Dissolution in rain water
Adsorption on soil particles and transport by runoff or wind erosion
Volatilization from soil and vegetation
Leaching into ground water
Re-suspension of contaminated soil particles by wind
Uptake by microorganisms, plants and animals.
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•LEVEL OF ANALYSIS.
numerical
representative
regional
site-specific
least-
•INPUT DATA QUALITY
Figure 2.3. Relative relationships between input-data quality, output uncertainty, and
types of problems addressed by each level of assessment (after Whelan et at., 1994.)
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3. MODEL OVERVIEW
3.1 Introduction
A principal objective of modeling by the EPA, DOE. and NRC is to characterize
the risks to human health presented by soil contamination present at sites containing
radioactive materials, and the benefits to health derived from their cleanup. Estimates
of the time-varying and time averaged radionuclide concentrations in air, surface water,
ground water, soil and food items, intake of these materials by humans, and
subsequent health risk are needed to fulfill this objective.
In the context of the exposure pathways identified in Chapter 2, the following
end-points and processes are of particular importance.
• Individual and population doses and risks as a function of time
• External radiation exposures to radionuclides on the ground and in the air
• Radioactive decay and daughter ingrowth
• Indoor radon exposures
Through analysis of survey data (Moskowitz et al. 1993, Mills and Vogt, 1983,
Case et al 1989, USEPA 1989, USEPA 1990a), application of the EPA Integrated
Model Evaluation System and the Environmental Models Library (USEPA 1993), review
of scientific and vendor literature, and discussions with project staff, a list of models
was identified that have been or could be used in a multimedia radiological risk
assessment project. In developing this list, there was no attempt to determine initially
whether these (Table 3.1) models could be appropriately applied to sites contaminated
with radioactive substances.
Tables 3.2 and 3.3 give a brief description of representative ways in which each
of the listed models has been used. The sponsoring Agencies requested that MEPAS,
MMSOILS, and PRESTO-EPA-CPG be reviewed in greater detail. Each of these
models was developed primarily for screening-type use or for comparisons between
sites conducted for the purpose of ranking relative risk. These models were never
intended for non-screening uses such as remedial design, etc. In addition to being
designed primarily for screening, the three models are generic models; i.e., they are
meant to be used at a wide variety of sites.
32 MEPAS
MEPAS (the Multimedia Environmental Pollutant Assessment System) is an
analytical model designed by Pacific Northwest Laboratories, which was developed for,
but is not limited to, use at CERCLA, Clean Air Act and Clean Water Act sites (Droppo
et al., 1989, Volume 1). MEPAS is an enhancement of the Remedial Action Priority
9
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System (RAPS, Whelan et al., 1987), using the same mathematical formulations and
algorithms plus new additions to the methodology (Droppo, Whelan, et al., 1989).
MEPAS was developed for DOE applications, but its development was specifically
designed to address general problems at any hazardous waste site
MEPAS develops an integrated, site-specific, multimedia environmental
assessment. It can simulate the transport and distribution of contaminants (chemical
and radiological) over time and space within air, water, soil, and food chain pathways
It estimates long-term health effects at receptor locations, from exposures over 70
years, as well as normalized maximum hourly concentrations for determining acute
effects. Contaminated media and exposure pathways include air, ground water wells,
water intakes from surface waters, recreation parks along surface water, on-site soil
ingestion, and direct radiation Receptors are evaluated as members of population and
agriculture centers within an 80 km radius of the release unit Currently, the model's
database contains 576 referenced organic and inorganic chemicals and radionuclides.
The database is updated and expanded continually A "user-friendly" shell is provided
with MEPAS which aids the user in defining the problem, entering input data, and
executing the model run
3.3 MMSOILS
MMSOILS (the Multimedia Contaminant Fate, Transport, and Exposure Model)
was developed by the EPA Office of Research and Development as a "screening tool"
for the "relative comparison" of hazardous waste (especially RCRA) sites (U.S. EPA,
1989a). It was designed specifically to simulate the release of toxic chemicals from
underground storage tanks, surface impoundments, waste piles, and landfills It can
model the fate and transport of chemicals only, and calculates human exposure and
health risk, as well as concentration in all important media. MMSOILS has a database
for 240 chemicals Like MEPAS, MMSOILS is provided with a "user-friendly" shell that
aids the user in defining the problem, executing the model, and evaluating the output
34 PRESTO-EPA-CPG
PRESTO-EPA-CPG (CPG for Critical Population Groups) belongs to a family of
EPA exposure-assessment models which includes PRESTO-EPA-POP, PRESTO-EPA-
DEEP, PRESTO-EPA-BRC, and PATHRAE-EPA (U.S. EPA, 1987) The PRESTO-EPA
family of analytical models was designed specifically for radionuclide transport via
natural processes, a consideration that dominates the overall structure and operation of
their codes. PRESTO-EPA-POP (PRESTO for regional Populations) was the first in
the series, and is the basis for each of the other models. PRESTO-EPA-CPG is
designed to calculate the annual committed dose equivalent to members of a critical
population group resulting from the disposal of low-level radioactive wastes (LLW) by a
near-surface disposal method. The model identifies also the maximum effective dose
equivalent and year of occurrence. POP models incidental, fatal, and genetic health
effects to local and regional populations stemming from LLW deposited in shallow land
burial sites also This model can handle several different wasteforms within those
10
-------
shallow-land disposal facilities, absorbing materials, activated metals, trash, solidified
waste, and incinerated waste. It incorporates a database of 40 radionuclides. The
PRESTO-EPA models are being modified currently to assess the health effects from a
cleanup site by adding contamination scenarios not already included, namely: radon
emission, soil and fish ingestion, and farming on site without protective cover
11
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Table 3.1. some otner representative multimedia models.
MODEL NAME
ARCL
DECHEM
DITTY
DOSES
DOSTOMAN
GENII
CEOTOX
GWSCREEN
HHEM
HRS-1
IMPACTS (PART 61)
MEPAS
MILDOS
MILDOS-AREA
MMSOILS
MULTMED
NUREG5512
NUTRAN
ONSITE/MAXI1
PATH1
PATHRAE (-EPA)
PC GEMS
PRESTO-EPA
PRESTO-EPA-BRC
PRESTO-EPA-CPG
PRESTO-E PA-POP
PRESTO-EPA-DEEP
PRESTO-II
RESRAD
RISKPRO
SARAH2
UDAD
UTM-TOX
PRIMARY REFERENCE
Napier and Piepel, 1988
Radiological Assessments
Corporation
Napier etai., 1986
Oak Ridge National
Laboratory
Root, 1 981; King etal., 1985
Napier etal., 1988
McKoneetal., 1983
Root 1991
USEPA, 1991
Stenner et al., 1986
Oztunali and Roles, 1986;
Oztunali et al., 1986
Doctor etal., I990a,b,c;
Droppo et al., 1989; Whelan
etal., 1987
Strenge and Bander, 1981
Yuan etal, 1989
USEPA, 1992
Salhorta et al., 1990
Kennedy and Strenge, 1992
Ross etal., 1980
Napier et al., 1984; Kennedy
etal, 1986; Kennedy etal,
1987
Helton and Kaestner, 1981;
Campbell etal. , 1981
Rogers and Hung, 19873
General Sciences
Corporation, 1982
USEPA 1983
Rogers and Hung, I987b
Rogers and Hung, I987d
Fields etal, 19873, 1987b
Rogers and Hung, 1987C
Fields etal, 1986
Gilbert, 1988
General Sciences Corp, 1992
vandergrift and Ambrose,
1988
Momeni etal, 1979
Browmanetal, 1982
SPONSORING
AGENCY
DOE
DOE
DOE
ORNL
DOE
DOE/NRC
DOE
EPA
DOE
NRC
DOE
NRC
DOE
EPA
EPA
NRC
Atomic Energy
of Canada, Ltd.
NRC
NRC
EPA
EPA
EPA
EPA
EPA
EPA
EPA
DOE
EPA
EPA
NRC
HARDWARE
PLATFORM
MSDOS-PC
MSDOS-PC
MSDOS-PC
Not yet
implemented
MSDOS-PC
MSDOS-PC
MSDOS-PC
MSDOS-PC
MSDOS-PC
MSDOS-PC
Not Yet
Available
IBM Main
Frame
MSDOS-PC
MSDOS-PC
MSDOS-PC
MSDOS-PC
MSDOS-PC
MSDOS-PC
MSDOS-PC
MSDOS-PC
MSDOS-PC
12
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Table 3.2 - Examples of usage of other models.
MODEL NAME
ARCL
DECHEM
DITTY
DOSES
GENII
GEOTOX
GWSCREEN
HHEM
HRS-1
IMPACTS
(PART 61)
MEPAS
MILDOS
MILDOS-AREA
MMSOILS
MULTIMED
NUREG 0707
NUREG 5512
NUTRAN
ONSITE/MAXI1
PATH
PATH1
PATHRAE (-EPA)
PC GEMS
DESCRIPTION OF REPRESENTATIVE USAGE
Evaluate decommissioning alternatives by using a site-specific
radiation scenario/exposure pathway analysis to determine the
acceptable levels of residual radioactive contaminants that remain.
Determine acceptable levels of chemicals in soil after clean-up of
Uranium Mill Tailings Remedial Action Project Sites.
Determine the collective dose from long term nuclear waste disposal
sites resulting from ground water pathways.
Estimates of long-term dose to man from buried waste.
Internal dosimetry from chronic and acute radiation exposure.
Evaluated health risks presented from the presence of TNT, RDX and
benzene present in military explosives residuals.
Developed for assessment of ground water pathway from leaching of
radioactive and nonradioactive substances from surface or buried
sources.
Assist RPMs to develop preliminary remediation goals at CERCLA
sites.
Hazard ranking for SUPERFUND site assessment.
Estimates radiological impacts for a given combination of waste
streams and processing options, disposal technology alternatives, and
disposal site environmental settings. Used during the development of
10CFR Part 61 rule.
A risk computation system developed for hazard ranking applications.
Computes environmental radiation doses from uranium recovery
operations
The MILDOS-AREA code provides improved capability for handling
large area sources and updates the dosimetry calculations
Multimedia landfill model.
EPA Toxicity Characteristic Final Rule.
Estimates site-specific limits for allowable residual contamination
Provides generic and site-specific guidance of radiation doses for
exposures to residual radioactive contamination after the
decommissioning of facilities licensed by the NRC.
Calculates the consequences of ground water releases of radioactivity
from a waste repository.
NRC review of license applications for onsite disposal of radioactive
wastes.
Used to implement residual radioactive material guidelines during
decommissioning.
Models the physical and biological processes that result in the
transport of radionuclides through the Earth's surface environment
and eventual human exposure to these radionuclides.
Maximum annual effective dose equivalent to a critical population
group and to offsite populations at risk from the land disposal of
radioactive wastes.
Used to evaluate the spread of toxic chemicals released to air, soil,
surface water and ground water.
13
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Table 3.2 cont'd - Examples of model usage.
PRESTO-EPA
PRESTO-EPA-
BRC
PRESTO-EPA-
CPG
PRESTO-EPA-
POP
PRESTO-EPA-DEEP
PRESTO-II
RESRAD
RISKPRO
SARAH2
UDAD
UTM-TOX
Simulates transport of low-level radioactive waste material from a
shallow trench site and assesses human risks associated with such
transport. This model was modified and added to create the PRESTO
family of models.
This is a modified version of PRESTO-EPA-POP. Additions to this
model include estimation of radionuclide transport and exposure to
workers and visitors, population exposures from incinerator releases,
worker and visitor gamma exposures, and onsite farming.
Maximum whole body dose to critical population groups from land
disposal of low-level radioactive waste by shallow and deep methods.
Cumulative population health effects to local and regional basin
populations from low-level waste disposal by shallow land methods.
Cum. population health effects to local and regional populations from
land disposal of low-level radioactive wastes by deep methods.
Evaluation of possible health effects from shallow-land and waste
disposal trenches.
An analytical methodology recommended by the Department of
Energy in its guidelines for allowable concentrations of residual
radioactive material in soil encompassed by the Formerly Utilized
Sites Remedial Action Program (FUSRAP) and Surplus Facilities
Management Program.
Used to evaluate the spread of toxic chemicals released to air, soil,
surface water and ground water. RISKPRO was adapted from
PCGEMS.
Core equations were developed in support of the EPA Land Disposal
Banning Rule."
UDAD provides estimates of potential radiation exposure to
individuals and to the general population in the vicinity of a uranium
processing facility.
A multimedia model which links an atmospheric transport model with
a surface water model.
14
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Table 3.3 Evaluations of some other representative multimedia models.
Model Name
DECHEM
GENII
GWSCREEN
MEPAS
MMSOILS
MULTIMED
NUREG 5512
ONSITE/MAXI1
PATHRAE
PRESTO-EPA-BRC
PRESTO-EPA-CPG
PRESTO-EPA-POP
PRESTO-II
RESRAD
RISKRPO
SARAH2
Exposure Pathways
External
Exposure
X
X
X
X
X
X
X
X
X
X
X
Soil
Ingestion
X
X
X
X
X
X
Plant,
Meat, Milk
Ingestion
X
X
X
X
X
X
X
X
X
X
X
X
Inhalation
Particulates
X
X
X
X
X
X
X
X
X
X
X
X
X
Radon
X
X
X
X
X
X
Ground
Water
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
Administrative Issues
Current/
Planned
Use
X
X
X
X
X
X
X
X
X
Validated/
Peer-
Reviewed
X
X
X
X
X
X
X
X
Site Data
Required
Moderate
Extensive
X
Moderate
Moderate
Moderate
Moderate
Moderate
Moderate
Available
Computer
Code
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
15
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4. SOURCE TERM
4.1 Introduction
This chapter deals with the identification and estimation of the source term. The
source of emissions and its physical characteristics must be identified before using any
model. Source term estimates are provided either by the user, calculated by the model,
or back-calculated from measured concentrations at the receptor Source term
conservation entails mass balance calculations to ensure that mass is conserved
among multiple release pathways.
4.2 Model Comparisons
4.2.1 Source type
Table 4.1 summarizes possible source types MEPAS has the most varied
selection of source terms, including simulation of injection wells, underground tanks,
landfills, lagoons, direct subsurface injection of wastes from tanks or wells, and
trenches with caps. Furthermore, MEPAS is the only one of the three models reviewed
that allows the user to specify any mass-flux, time-varying distribution of the source
term MMSOILS has a variety of source terms also, but not surface impoundments,
direct injection to wells, or trenches with caps. PRESTO-EPA-CPG has the capability of
modeling a variety of source terms including waste burial in capped trenches,
contaminated soil with and without cover, landfill, and waste piles None of these
models account adequately for the presence of free phase or residually-saturated
material in the source terms. Neither do any of these models have the ability to
consider facilitated transport, an especially important factor in the transport of
radioactive species.
TABLE 4.1 Source term capabilities of the models.
Contaminant Source
contaminated soil
injection well
landfill
surface impoundment
trench with cap
underground storage tank
waste pile
MEPAS
yes
yes
yes
yes
yes
yes
yes
Capability
MMSOILS
yes
no
yes
yes
no
yes
yes
PRESTO
yes
yes"
yes
no
yes
no
yes
1. PRESTO-EPA-PILCPG considers a source term in a pile
2. PRESTO-EPA-DEEP
4.22 Estimation of the source term
Estimates of the source term are provided either by the user, or are calculated
internally by the computer. For example, the release rate of a contaminant spilled on
the ground is calculated from the contaminant's vapor pressure, soil/vapor partitioning.
17
-------
and molecular diffusion in air. The PRESTO-EPA-CPG model does not consider the
vaporization of radionuclides, and assumes that all contaminants will be transported
either through atmospheric pathways in absorbed form or through water pathways in
dissolved form. The fate of release through water pathways is calculated internally
from the mass-balance equation using the inventory and leaching/solubility
characteristics of the given radionuclide and the internally calculated stream flow In
applications to radioactive waste disposal, this approach will give conservative results
for health risk assessments always, especially when the chemical forms of the
contaminant are unknown.
For the atmospheric component only, MEPAS has the option of back-calculating
release rates from measured concentrations at the receptor. This requires data on (i)
air concentration, (ii) soil concentration, or (iii) both This option is not available in the
other two models
4.2.3 Conservation of the source term
Since the individual pathway models in MEPAS, MMSOILS, and PRESTO-EPA-
CPG are linked implicitly, verifications of mass conservation are needed to prevent
multiple accounting of the same mass of contaminant in different media. MEPAS
accounts for depletion of the source via a link between the source's inventory and
release rate and duration that ensures that a release is over. This option addresses
the theoretical need for mass conservation, but is useful only when the inventory of the
source is known. Sometimes there is more certainty about the duration of the release
and the inventory than about the rate of release. When the inventory of waste is
uncertain, great care is needed in using the source depletion option properly,
especially for long-term simulations (Peer Review Committee report, 1994).
MMSOILS includes calculations of mass balance annually to ensure that mass is
conserved in waste management units that have multiple release pathways. These
calculations compute the accumulation and depletion in landfills, impoundments, and
waste piles. For each unit, the mass that is removed from each pathway is accounted
for annually, to satisfy overall mass conservation.
PRESTO-EPA-CPG includes mass-balance calculations also to insure that mass
is conserved in waste management units. This equation calculates the rate of release
and the mass remaining in the waste units. Then, the radionuclide mass is adjusted for
the radioactive decay at the end of each year
4.2.4 Air pathway
42.4.1 Air source
MEPAS has an option allowing the user to specify a uniform ambient
concentration of the contaminant as a source term when there are measurements of the
ambient concentration of the contaminant at a waste site A similar option is provided
18
-------
in PRESTO models. A user-assigned strength of background radionuclide
concentration in the atmosphere above the contaminated area can be added to the re-
suspended radionuclide concentration for assessing the combined health effects.
MMSOILS does not have this option.
4.2.4.2 Radioactive and chemical decay
MEPAS can handle both first-order radioactive and chemical decay, while
MMSOILS is limited to chemical decay. Progeny formation is not calculated in
MMSOILS. MEPAS handles progeny formation in ground water, surface water, surface
soil, and deposited contaminants from wet and dry deposition, but not while the
contaminant is moving in the air; it handles it after the contaminant has been deposited.
The PRESTO-EPA-CPG model calculates radiological effects for the progeny produced
by up to a four-member decay chain.
4.2.4.3 Volatilization from soil or spill
In both MEPAS and MMSOILS, volatilization is calculated by either steady-state
or transient equations, depending on the scenario of release (Table 4.2). Steady state
equations are used in scenarios of landfill release and sediment-controlled emissions,
whereas time-averaged solutions of transient diffusion equations are used for releases
from spills, contaminated soil, and land treatment facilities. The steady-state equations
assume a very large source, so that emission does not deplete the source during the
time considered
In the MEPAS scenarios of releases from spills and land treatment facilities, the
volatilization flux is calculated by accounting for the decrease over time of the
concentration of the chemical in the soil. A dry-out period is computed, after which
emissions stop. MMSOILS does not define explicitly a similar mechanism of tracking
and depletion.
PRESTO-EPA-CPG assumes that all volatile radionuclides are released in a
water-soluble form and contribute to the ground water and surface water pathways.
PRESTO-EPA-CPG was designed primarily for use at low-level radioactive waste
disposal sites, and assumes that the health effects due to the volatile radionuclides
(primarily 14C and 3H) are negligibly small. PRESTO-EPA-CPG is not included in Table
4.2. for this reason.
19
-------
Table 4.2 Source term of volatilization scenarios.
No
1
2
3
4
5
6
Submodel1
Description
Landfill, without
gas generation/
(Farmer's Equation
Covered Sites)
Landfill,
with gas generation
(Municipal Waste)
New spill
Old spill
(Covered Sites.
Adsorbed Phase)
Soil Contaminated up to
the Surface/
(Uncovered Sites,
Adsorbed Phase)
Contaminated Soil
covered with a layer of
Clean Soil/
(Covered Sites,
Adsorbed Phase)
Assumptions
MEPAS
•Steady state
•Very large source (emission does not deplete
source during time frame considered)
•Steady state
•Very large source (emission does not deplete
source during time considered)
•Time-averaged form of transient solution,
emission rates decrease with time
•Emissions occur from liquid above spilled
surface
•A dry-out period is computed, after which
emissions stop
•Time-averaged form of transient solution;
emission rate decreases with time
•Contaminant concentration in cover soil initially
is zero; uniform concentration underneath
cover to finite depth
•Vapor concentration at soil surface is
maintained at zero
•Release rate controlled by soil/vapor
partitioning and molecular diffusion in air
•A dry-out period is computed, after which
emissions stop.
•Time-averaged form of transient solution;
emission rate decreases with increasing time
•Release rate controlled by soil/vapor
partitioning and molecular diffusion in air
•Same assumptions and equations as submodel
4 above
MMSOILS
Same as MEPAS, but
steady-state flux is limited
by mass inventory
NA
NA
•Release rate controlled
by soil/vapor partitioning
and molecular diffusion
in soil gas
(i.e.. controlled by
diffusion of vapor in a
porous medium, which is
1-2 orders of magnitude
less than diffusion in air.
Same as MEPAS
Same as MEPAS
1 Submodel descriptions in /fa//cs refer to MMSOILS.
20
-------
Table 4.2 cont'd Source term of volatilization scenarios.
Submodel
Assumptions
No
Description
MEPAS
MMSOILS
Land Treatment
Facilities/
(Landfarming Equation)
•Time-dependent release rate
•Release rate controlled by liquid-phase
concentration of contaminant in soil
•Contaminant concentration is constant until all
its mass vaporizes from liquid-phase
Same as MEPAS
(slightly different equation
for release rate)
Sediment-Controlled
Emissions
•Steady state
•Includes both sediment-to-water and water-to-
air transfer; mass transfer coefficients control
diffusion in the two media
Same as MEPAS
Surface impoundments,
e.g. ponds, lagoons,
small lakes./
(Volatilization from a
Contaminated Water
Body)
•Two-layer resistance model; a gas and a liquid
film across the air-water interface form the
dominant resistance to mass transfer
Same as MEPAS (model
not yet in code)'
General
•Emission rates of low-volatility contaminants
are constant during time considered
•Emission rates of highly volatile contaminants
decrease significantly with time; thus, ambient
concentrations are computed mainly as a
function of total amount of released material
rather than emission rate. User determination of
contaminant's total inventory is crucial for highly
volatile materials
1. Submodel descriptions in italics refer to MMSOILS.
2. A model of volatilization from contaminated water is described in MMSOILS manual, but is not
included in the 1993 computer code. See Model Developer's Comments - Section 4.3.2.
4.2.4.4 Air-borne depletion due to deposition
All models account for airborne contaminant depletion via dry deposition. Wet
deposition and the associated source depletion is included in MEPAS and PRESTO-
EPA-CPG, but not in MMSOILS.
4.2.5 Ground Water Pathway
4.2.5.1 Generation of leachate
Contaminants are introduced into the ground water pathway from leachate
originating in a waste management unit. Leachate migrates vertically through the
unsaturated zone and discharges finally into the saturated ground water system. The
way in which leachate is generated is similar in the three models.
21
-------
MEPAS contains the most sophisticated source term for leachate of the three
codes. MEPAS was set up specifically to permit the user to define the source term if it
is known. The user specifies the total inventory of waste in the unit and the leaching
rate. The code has a mass-balance check to see that there is enough inventory to
match the amount of material leached from the source.
If the user cannot define the source term, MEPAS will calculate it based on a
combination of: (i) solubility limit on concentration, (ii) equilibrium partitioning with
contaminated soils, (iii) steady-state concentration of leachate supplied by user, and
(iv) transient or time-varying releases as specified by user.
MEPAS provides the user with three source term options:
Option 1: the user supplies the source term concentration, the
code supplies the rate of deep-drainage percolation; then, the code
calculates the time-varying mass-flux rate. This information can be
supplied for a point source, line source (accounts for both the x
and y directions), or area source The source can be a ponded site
or a contaminated-soil site. The movement of the contaminant can
be released directly to the vadose zone and then, to the saturated
zone, or it can be released directly to the saturated zone
Operational releases and non-operational releases (i.e., past-
practice sites) are considered.
Option 2: the user supplies time varying mass-flux rate from the
source and the rate of deep-drainage percolation; then the code
calculates the initial source term concentration. This information
can be supplied for a point source, line source (accounts for both
the x and y directions), or area source. The source can be a
ponded site or a contaminated-soil site. The movement of the
contaminant can be released directly to the vadose zone and then,
to the saturated zone, or it can be released directly to the saturated
zone. This includes direct discharge (e.g., injection well, pipe to a
river) also. Operational releases and non-operational releases
(i.e., past-practice sites) are considered.
Option 3: a combination of Options 1 and 2.
MMSOILS was designed specifically to address leaching from landfills and
waste piles. The leachate can be generated from soil, landfills, waste piles, surface
impoundments, and underground storage tanks (USTs). In the first three, the
contaminants are dissolved in infiltrating recharge water derived from precipitation. By
definition, surface impoundments contain pre-mixed leachate that infiltrates into the
unsaturated zone. MMSOILS uses a continuously mixed reactor model for this source
type.
22
-------
Like MEPAS, MMSOILS has several different options for generating leachate for
landfills and waste piles: (i) solubility limit on concentration of leachate, (ii) equilibrium
partitioning with contaminated soil, (Hi) completely mixed reactor, and (iv) steady-state
concentration of leachate specified by the user Thus, the user can choose from a
variety of options, depending upon how much data are available for the site. If the data
are limited, the steady-state option allows the user to specify a concentration of
leachate.
PRESTO-EPA-CPG can model leachate source terms from ground surface
contaminated soil, waste trenches with cover, and waste piles It has similar options for
generating leachate to those of MMSOILS: (i) solubility limit on the concentration of
leachate, (ii) equilibrium partitioning with contaminated waste mixed with soil, and (iii)
release fraction The latter is similar to the steady-state option of MMSOILS.
Since landfill leachate is known to contain high concentrations of colloids that
are likely to facilitate the transport of radionuclides. it is especially significant that none
of these models can consider such facilitated transport.
4.2.5.2 Other source terms
MEPAS and another version of PRESTO-EPA (-DEEP) have additional source
terms for ground water in the form of injection wells. The user specifies both the
concentration of contaminant in the injected water and the flow rate MMSOILS does
not have this source term.
4.2.6 Surface Water Pathway
4.26.1 Soil erosion
MMSOILS and MEPAS allow erosion of the contaminated soil from the waste
unit. Then the soil is transported into the surface water where it continues to act as a
source of dissolved contaminants. The contaminants are dissolved into surface water
using an equilibrium partitioning approach. In the scenario of the source term in
shallow trenches with cover, the PRESTO-EPA-CPG model assumes that the cover is
constructed with clean soil. Therefore, the eroded soil will not contain contaminants as
long as the cover remains effective {i.e., as soon as the cover is eroded) the
contaminants would begin to dissolve into the surface runoff water and be transported
away from the contaminated unit When there is no cover, the PRESTO-EPA-CPG
model assumes that the contaminants will be transported into the surface water body
as soon as erosion begins. Thus, the surface water body will be contaminated from the
beginning of the simulation An equilibrium partitioning model using a linear sorption-
desorption relationship is used also in calculating the rate of transport of contaminants.
-------
4.2.6.2 Runoff
All three codes allow rainfall to leave the unit as runoff. They assume that the
runoff water is in chemical equilibrium with the contaminated soil, using a simple
partitioning model The assumption that runoff water will be in chemical equilibrium is
an oversimplification The degree to which runoff water achieves equilibrium will rely
on the partitioning coefficients and the residence time of surface water in contact with
the contaminated surface soils. In most scenarios, there is likely to be far less time
than is required to achieve chemical equilibrium As such, this assumption will be
overly conservative
4263 Ground water inflow
All three codes allow the interception of the contaminated ground water by a
surface stream A complete mix (also called a "completely mixed") model is assumed
by MMSOILS and PRESTO-EPA-CPG as the ground water enters the surface MEPAS
does not assume a completely stirred tank reactor (a CSTR, operationally the same as
a complete mix model), but uses a plug-flow with dispersion model (i.e., a solution to
the advective-dispersive equation) Such a model accounts for plume migration in the
lateral direction from the bank where the source enters the stream.
43 Developer Updates - Source Term
4.3.1 MEPAS
Droppo (1994) reports that MEPAS Version 3.0 has the capability of direct input
of waterborne monitoring data in computing risk values. A module to include
geochemistry in the environmental release component of MEPAS is being developed
also The new source term code for MEPAS will provide a coupled contaminant source
term that is partitioned to the different environmental media for transport and exposure.
Two- and three-dimensional, spatially-varied concentrations for any designated period
will be implemented in MEPAS. Thus, MEPAS will be able to calculate the contribution
(o downgradient sites from multiple waste sites.
432 MMSOILS
The most recent version of MMSOILS contains a two-layer resistance model for
air-water interface transfer (see item 9 Table 4.2).
433 PRESTO-EPA-CPG
Future versions of PRESTO-EPA-CPG will contain an improved infiltration
submodel for handling uncovered contaminated soil (Hung, 1994).
24
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5. AIRTRANSPORT
5.1
Introduction
The air-transport pathway is one of the principal pathways whereby
radionuclides released from waste sites may reach living organisms Radionuclides
may be discharged to the atmosphere through particulate suspension, venting from
containers, and volatilization from contaminated water and soil Once airborne, they
will disperse downwind and deposit on ground surfaces in a pattern dependent on the
local meteorology, the location of the point of release, the nature of the terrain
downwind of the release, and the physical and chemical characteristics of the emission
Exposure to humans can occur via direct radiation, inhalation, or consumption of
contaminated water, crops, and animals (Figure 5.1).
Direct Radiation
RADIOACTIVE
MATERIALS
HUMANS
Figure 5.1. Simplified pathways between radioactive materials released to atmosphere
and humans (after ICRP, 1979).
The objective of atmospheric transport modeling is to predict the concentration of
radionuclides at specific locations surrounding the source. The basic types of data
required to run these models include the release rate of each radionuclide, physical
characteristics of the source (e.g., stack height, area, or release), and meteorological
data (e.g., stability class, wind speed, precipitation) For environmental radiological
assessments, models should be able to simulate plumes from point sources (e.g.,
containment leaks) and area sources (e.g., contaminated ponds), for several minutes
up to several years, and up to about 80 km from the source. Also, these models should
25
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include volatilization from soil and water, and particulate emissions from wind erosion
and mechanical operations As the plume travels downwind, it disperses in the air and
is depleted also by deposition to ground surfaces, radioactive decay, and chemical
decay Such depletion processes are important for radiological health assessment.
The outputs from these models include the concentration of air and surface
contaminants which can be used in assessing the inhalation and ingestion components
of the exposure The surface contaminant levels are used also as input to the overland
transport pathways Figure 5.2 shows these interactions.
(Wind ^Md w* tfrvdton,
ctmMpftwtc ftoMty;
umpmfcn, «to.)
MrttmkMnto, wrta
MMT. TttJflhMM. MC.)
SUSPENSitWEMISSMN
•F CONTAMINANTS
Surf»c*V»nl
Sur«K*/V*nt
Onttmttirt
EmtattonftMM
_ ATMSSPHEWCinANSPtflT !
AN» MSreftSMW I
Ptum*
L
il
ThSufen
Figure 52 Diagram of pathway interactions (after Droppo et al., 1993)
5.2 Comparisons of models
The same sector-averaged Gaussian plume equation for air transport is used in all
three models Most of the volatilization algorithms in MEPAS and MMSOILS are also
the same However, MMSOILS and PRESTO-EPA-CPG do not describe complex
26
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terrain effects, calms, wet deposition, and contaminant decay. In addition, PRESTO-
EPA-CPG does not include several components such as area releases and
volatilization from lagoons, lakes, ponds, and rivers, and the suspension of particles
due to loading and unloading operations.
5.2.1 Radioactive and chemical decay
Depletion of radionuclides in the plume by radioactive decay may be significant
when the decay is fast (e.g., emissions of cesium, iodine, manganese, radon, and
ruthenium) and transport is slow. This option is available in PRESTO-EPA-CPG, but
not in the current version of MEPAS or MMSOILS. MMSOILS can model first-order
chemical decay once the contaminant is deposited on soil, but not radionuclides
explicitly. None of these models describes the creation of progeny within the air
pathway.
5.2.2 Wet deposition
Ground deposition can result from wet and dry processes, and for many
locations the magnitude of these processes in depleting airborne radionuclides is
roughly the same. Wet deposition is caused by rain scavenging the contaminant and
by deposition of cloud droplets which have absorbed the contaminant. Dry deposition
is the direct deposition of the airborne contaminant onto a surface by gravitational
settling, or impacting. Ground deposition is necessary for linking the air-pathway
models with the water and food chain models. Wet deposition is included by MEPAS
and PRESTO-EPA-CPG, but not by MMSOILS. Therefore, MMSOILS will
underestimate ground concentrations and overestimate air concentrations, with the
error increasing with the distance from the source.
5.2.3 Air source
Chapter 4, section 4.2.3.1 discusses the air source term for the three models.
5.2.4 Calm conditions
Calm conditions can be extremely important in assessing health impacts to
populations near the source (e.g., up to 10 km). In some locations, the prevailing winds
blow from one direction, and calms (e.g., wind speeds <1m/s) from another direction. If
calms occur often, they can cause much higher concentrations at near-field receptors
than predicted by the wind-rose data. The effect of calm conditions is more important
in determining acute effects than long-term ones as such conditions may change over
long periods. MEPAS can distribute calms as a function of direction, and models them
with a wind speed of 0.5 m/s. Calm conditions are not described by the other two
codes.
27
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5 2.5 Complex terrain
The atmospheric pathway in MEPAS takes into account local site influences in a
highly simplified manner and describes complex terrain characteristics such as
channeling in a valley, and intersection with hills around a release. PRESTO-EPA-
CPG and MMSOILS account only for different roughness of a flat terrain. In general,
complex terrain adjustments have more effect on maximum individual exposures than
on average population exposures. However, in sites where the flow of contaminants
towards surrounding receptors is either interrupted or concentrated by hills or valleys,
these topographical features can affect average population exposures significantly.
526 Acute effects
MEPAS calculates maximum (hourly) air concentration and its location in each
direction to determine acute effects; the other two models do not. All three atmospheric
pathway models use annual averages, and predict annual average concentrations and
subsequent exposures. Average annual exposures might not represent adequately
strongly seasonal (e.g., calm conditions) or event-driven (e.g., large storms)
environmental transport. MEPAS includes equations necessary to describe such
variations, but its present structure is limited to the calculation of annual estimates.
The features of these models and their fundamental assumptions are further
described in Table 5.1.
53 Developer Updates - Air Transport
As reported by Droppo (1994), a planned update of MEPAS will compute a
single mass budget for airborne-waterborne releases rather than separate mass
budgets
28
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Table 5.1 . Atmospheric pathway: Comparison of capabilities.
No
1
2
3
Submodel
Description
Point Releases
Ground
Elevated
Plume rise
Area Releases
Soil
Landfills
Lagoons
Lakes, ponds, rivers
Multi-point regional
Suspension of particles
Wind speed
Surface roughness (z)
Mechanical disturbance
Loading & Unloading
Soil spreading operations
Availability & Fundamental Assumptions
MEPAS
yes
Sector-averaged Gaussian
Sector-averaged Gaussian
Briggs, 1975
Approximation with point source
at virtual distance and sector
averaged Gaussian plume
yes
yes
yes
yes
no
Sehmel, 1976; Cowherd et al,
1989
yes
0.1
-------
32
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6. GROUND WATER TRANSPORT
6.1 Introduction
Often, ground water is an important pathway for wastes found below the land
surface. Contaminants leach from the waste, move downward through the unsaturated
zone to the water table, and then migrate in the saturated ground water system. The
contaminants may discharge ultimately either to a drinking water well or to a surface
stream (Figure 6.1) Humans are exposed to radioactive and other contaminants by
using well water or surface water, and by eating organisms living in the surface
streams
The ground water component of multimedia models predicts the concentration
over time at wells and surface discharge areas. Usually, these calculations are broken
down into three linked sub-pathways: (i) leaching of contaminants from the waste unit,
(ii) vertical movement of the dissolved contaminant downward to the water table
through the unsaturated zone, and (iii) migration of the contaminant in saturated
ground water to the receptor point. Separate models simulate these three processes,
with the preceding model supplying a source of contaminated water to the next one.
Thus, the leachate generation model supplies a source of contaminated water to the
unsaturated zone model, which passes the contaminated water subsequently to the
saturated ground water model at the water table.
Ideally, these models would be three-dimensional, capable of incorporating all
our knowledge of the subsurface, and of simulating the complex chemical reactions that
occur as the contaminant migrates through the soil and aquifer materials.
Unfortunately, even the most sophisticated ground water models cannot address all
these issues. Since multimedia models are used often as screening tools or for
comparing different sites, each pathway is simplified to incorporate only the most basic
features. Furthermore, these features must be described with limited data. For the
ground water pathway, most multimedia models simplify the unsaturated zone to a one-
dimensional (1D) model which assumes that the contaminant migrates only vertically
from the waste source to the underlying water table. In most cases, this is a valid
assumption because the scale of transport in the unsaturated zone tends to be orders
of magnitude smaller than that in saturated ground water.
Further simplifications are made for the saturated ground water model. The
most common assumptions are that ground water moves at a uniform rate and is
unaffected by pumping wells, changes in recharge, or other systems stresses These
assumptions are much less realistic than the simplifications made to the unsaturated
zone models, but for screening they are adequate as long as the user understands the
degree of uncertainty in the model's results. The following disclaimer from the
MMSOILS manual is a good synopsis of the problems inherent in this approach:
33
-------
"It is important to be cognizant of the uncertainty inherent in this type of
model Often the most basic parameters, such as contaminant
concentration in soil, vary significantly over a given site and the distribution
may be poorly understood. These uncertainties, coupled with
approximations that were used to streamline the modeling process lead to
results that may differ from reality by orders of magnitude. As such, the
user is cautioned to examine the input and output of the model closely and
consider a sensitivity study to evaluate the impact of varying input
parameters on the calculated results."
62 Comparisons of Models
Table 6.1 outlines a range of capabilities for modeling the ground water
pathways. The approach to modeling the ground water pathway in MEPAS (Whelan et
al. 1987) and MMSOILS (US. EPA, 1992) is similar. However, PRESTO-EPA-CPG
(U.S. EPA 1987) differs from the other two codes in many ways which are enumerated
below.
Figure 6.1. Conceptual diagram of the ground water pathway (Whelan et al. 1987).
34
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6.2 1 Radioactive decay/progeny ingrowth
Each model incorporates a first-order decay coefficient to simulate decay. While
MMSOILS is not specifically designed to consider radioactive decay, it does
incorporate a decay term for non-radioactive chemicals However. MMSOILS limits the
decay to dissolved chemical contaminants; which when adsorbed onto the soil material
do not undergo decay. While this is a conservative assumption which would lead to
persistence of the chemical contaminant in the environment, it is overly conservative
since many radionuclides are strongly sorbed onto most soils.
Only MEPAS and PRESTO-EPA-CPG simulate ingrowth of progeny during
decay; this may be important if travel times in ground water approach the half-life of the
contaminant, or if the progenies are particularly toxic, or if the progeny is in a different
physical state (e.g., radium to radon).
MEPAS assumes that the progenies have the same distribution coefficient (Kd)
as the parent. This is seldom the case and should be considered when reviewing the
output from MEPAS for scenarios where progeny ingrowth is important This drawback
is only significant when the parent nuclide has a short half-life or when the travel time is
long relative to the parent's half-life. The NRC NUREG-0868 states that - the
assumption of equal transport speeds makes a relatively small difference to the
calculation of concentrations of the most important components, and is conservative "
The user always has the option of modeling the decay products as parents instead of,
or in addition to, the actual parent radionuclides, thereby bounding the problem without
making any assumption about
There are two versions of PRESTO-EPA-CPG available for simulating progeny
ingrowth: a research model and a screening model. The screening version assumes
that progeny have the same K
-------
Table 6.1 Ground water pathway: Comparison of capabilities.
Capability
Unsaturated Zone
Miscible Transport
Model Type
Advection
Dispersion
Diffusion
Physical/Chemical Processes
Decay
Progeny Ingrowth
Sorption
Other Chemical Reactions
Immiscible Transport
Vapor Transport
Saturated Zone
Miscible Transport
Model Type
Advection
Dispersion
Diffusion
Physical/Chemical Processes
Decay
Progeny Ingrowth
Sorption
Other Chemical Reactions
Immiscible Transport
Density-Dependent Flow
Fractured Zone
MEPAS
yes
1 D semi-
analytical
yes
yes
yes
yes
yes'
linear
no
yesj
yes
3D semi-
analytical
1D
3D
3D
yes
yes'
linear
no
no
no
no
MMSOILS
yes
1D finite-
element
yes
yes
no
yes1
no
linear
no
no
yes
3D semi-
analytical
1D
3D
no
yes1
no
linear
no
no
no
no
PRESTO
yes
1D
analytical
yes
no
no
yes
yes
linear
no
no
yes
1D
analytical
1D
2D
no
yes
yes
linear
no
no
no
no
1. No decay occurs while contaminant is sorted onto soil.
2. Progenies have the same adsorption coefficients (K
-------
same model (VADOFT) as that used in Rustic (USEPA, 1989). a more complex
subsurface simulator.
MEPAS uses a one-dimensional, semi-analytical transport model that assumes a
constant vertical velocity for each layer in the vadose zone. The user may describe the
vadose zone with multiple layers. Therefore, the user can account for heterogeneity in
the vadose zone by modeling multiple vadose-zone layers with velocity variability
between layers, and infiltration rates that change with time. MMSOILS. with its layered
finite-element model computes a non-uniform vertical velocity based upon changing
soil properties.
PRESTO-EPA-CPG uses an empirical formula developed by Clapp and
Hornberger (1978) to calculate the average degree of saturation which then is used to
obtain the unsaturated water velocity and retardation factor. Then, the rate of
radionuclide transport is calculated from a steady-state, one-dimensional transport
equation.
6.2.3 Saturated Zone Model
MMSOILS and MEPAS take similar approaches to simulating transport of
contaminants in the saturated ground water flow, using a three-dimensional, semi-
analytical transport model. The three-dimensional adjective is somewhat misleading.
however, because only dispersion is considered in three dimensions Ground water
velocities are assumed to be uniform and horizontal, and thus one-dimensional The
codes used in these semi-analytical transport models are similar to the AT123D code
(Yeh, 1981).
Both the MEPAS and MMSOILS mathematical formulations employ a
convolution integral that distributes a transient release from the source to the receptor.
thereby avoiding problems with convergence and instability since each time step is
calculated independently of its predecessor. Short (i.e., 1 year) or long (i.e.. 10 million
year) simulations are possible without the risk of problems of instability or convergence
because the user-defined time steps are independent. A potential problem may occur
with this integration scheme if the upper and lower bounds and limits of integration are
not properly selected.
The PRESTO-EPA-CPG model employs a simple one-dimensional model (Hung.
1986) to achieve the goal of analyzing the annual rate of radionuclide transport for
10,000 years. Although an analytical model, PRESTO-EPA-CPG can adopt any form
of boundary conditions and can consider lateral and longitudinal effects It is designed
as a screening-type model, aiming at an accurate health-effects evaluation with a
minimum of numerical calculations. To achieve these goals, a correction factor called
Hung's correction factor compensates for the rate of radionuclide transport obtained
from the analytical model without lateral dispersion effects (Hung, 1986) Since Hung's
correction factor is derived by matching the total mass of radionuclides passing through
a particular layer, theoretically, the estimated cumulative health effects should agree
37
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with the results obtained from a numerical approach As to the maximum dose
analysis, the solution using Hung's model and that using a numerical approach are
fairly close, in general, to each other as long as the transport number is less than 4 and
the Peclet number is greater than 2 (Hung 1986). In a general waste disposal site risk
assessment application, the transport number and the Peclet number are usually within
the domain described above Therefore the PRESTO-EPA-CPG model can calculate
the maximum individual dose with minimum error compared to the exact solution
obtained from a one-dimensional model
6.2.4 Mixing-zone calculations
The results of the unsaturated zone model are a flux of contaminants that serve
as a source term for the saturated zone model The volume of aquifer over which the
contaminant flux is diluted when it first enters the aquifer is called the mixing zone
Each model treats the mixing zone differently The least conservative approach is to
mix the contaminants over the entire saturated thickness of the aquifer, as is done in
PRESTO-EPA-CPG. That approach causes maximum dilution, resulting in the lowest
possible concentration of contaminants in the saturated zone beneath the source
However, the unsaturated zone concentration can be concentrated rather than diluted.
as occurs when the water flow from the unsaturated zone into the aquifer exceeds the
ground water flow out of the source
MMSOILS computes the vertical dispersion coefficient and a mixing depth,
called the depth of penetration, using the ratio of the horizontal rate of ground water
flow to the vertical flow-rate of water from the unsaturated zone As the amount of
vertical flow and the vertical dispersivity increase, the thickness of the mixing zone
increases
MEPAS assumes that the flux of contaminants occurs at the water table and the
depth of mixing depends directly upon the vertical dispersivity value.
Both MMSOILS and MEPAS assume that the pumping of a well does not affect
the background flow of ground water This assumption is applicable only when the
unit-width flow strength is much greater than the pumping rate However, a waste
disposal or cleanup site may be situated in a region of low or moderate ground water
flow, a situation that would disqualify this assumption. In such a region, a well screen
would be set near the bottom of the aquifer and pumped with several times higher
capacity than the daily demand In most cases, this would create a free surface draw-
down in the vicinity of the well, so that the contaminant plume will be pulled down and
mixed with the bottom layer of clean water Although this mixing may occur only in the
vicinity of the well, the quality of water being pumped out would be close to complete
mixing. For these reasons, the assumptions of the PRESTO-EPA-CPG model may be
reasonable
-------
6.2.5 Adsorption of contaminants
All three models assume a linear, fully reversible, adsorption model in both the
unsaturated and saturated zones. The only difference between them is that MMSOILS
assumes that contaminants do not decay while sorbed to the soil matrix
626 Complex processes
None of the models simulate complex transport processes, such as vapor phase
transport, fracture flow, or immiscible phase transport. At a particular site, these
processes may be important. For example, transport of radon in soil gas may be
important for exposure assessments, if radium is one of the contaminants of concern
627 Requirements for data input
The requirements for data input in MMSOILS (Table 6.2). MEPAS (Table 6.3).
and PRESTO-EPA-CPG (Table 6.4) differ significantly. MEPAS requires the most data,
especially for the soil and unsaturated zones. A data-input guide is provided that
explains each parameter and gives suggestions on selecting a value for a parameter
One problem with this guide is that metric and English units are mixed For example,
hydraulic conductivity is entered in units of ft/d, while bulk density is expressed in
g/cm3. According to the developers, the default units employed by MEPAS were
chosen to conform with those most likely to be found in data source documents The
data-input shell of MEPAS can be redefined to employ any units (consistent or
otherwise) desired by the user, since this model can convert any set of units used
Modeling the unsaturated zone within MMSOILS could require significantly more
data input than the other two models, if numerous soil layers are incorporated in the
model (10 data elements are entered for each soil layer). System International (SI)
units are used consistently throughout MMSOILS except for time units which are
expressed in years for the decay coefficient, and hours for hydraulic conductivity
PRESTO-EPA-CPG requires very little data for the ground water pathway
consistent with its low sophistication in the subsurface transport models The units are
internally consistent in PRESTO unlike MMSOILS and MEPAS.
6.3 Developer Updates - Ground water Transport
Improved capabilities for ground water transport of light, non-aqueous phase
liquids (LNAPLS) and dense, non-aqueous phase liquids (DNAPLS) are planned for
future versions of MEPAS according to Droppo (1994). Version 30 of MEPAS includes
also an improved calculation for waterborne transport that incorporates double-
precision mathematical routines to address problems that would
-------
arise because of round-off errors. New versions of MEPAS will account for curvilinear
flow in the saturated zone also.
Table 6.2 Data requirements for MMSOILS.
Unsaturated Zone
Climatic Data
pan factor for converting pan evaporation to potential evapotranspirat
latitude of site
precipitation data (12 months)
number of days with precip. (12 months)
average temperature (12 months)
pan evaporation (12 months)
starting and ending month for growing season
Soil Property Data
curve number of surface soil
Held capacity of soil
wilting point of soil
depth of root zone (cm)
number of soil layers (entering the following for each layer)
saturated hydraulic conductivity (cm/hr)
saturated water content
bulk density (gm/cm3)
exponent "b" for moisture curve
percent organic matter
percent clay
percent silt
percent sand
ratio of first-order decay (1/yr)
thickness of layer (cm)
Saturated Zone
hydraulic gradient (dimensionless)
hydraulic conductivity (m/yr)
porosity (dimensionless)
bulk density of aquifer material (gm/cm1)
fraction of organic carbon in aquifer
dispersivity (x, y, and z-directions) (m)
aquifer thickness (m)
1st order decay rate (yr1)
time (yr)
x,y,z locations (meters)
40
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Table 6.3 Data requirements for MEPAS.
Unsaturated Zone
depth of waste site in unsaturated zone (ft)
length of site (ft)
width of site (ft)
waste liquid infiltration rate (ft/d)
Top Soil Data
moisture content of soil
bulk density of soil (g/cm3)
soil textural classification
percent sand, silt, and clay
percent organic content
percent iron and aluminum
pH
percent vegetative cover
water capacity
SCS curve number
Partially Saturated Zone Data
soil textural classification
percent sand, silt, and clay
percent organic matter
percent iron and aluminum
PH
thickness of partially saturated zone (ft)
bulk density (g/cm3)
total porosity
field capacity
dispersivity (ft)
saturated hydraulic conductivity (fVd)
Saturated Zone
soil textural classification
percent sand, silt, and clay
percent organic matter
percent iron and aluminum
pH of pore water
total porosity
effective porosity
contaminant velocity (ft/d)
thickness of saturated zone (ft)
bulk density of saturated zone (g/cm3)
travel distance in saturated zone
longitudinal, transverse, and vertical dispersivity (ft)
41
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Table 6.4 Data requirements for PRESTO-EPA-CPG.
Unsaturated Zone
length of contaminated zone (m)
average slope of contaminated zone
component of porosity for gravity water
component of porosity for pedicular water
thickness of the top layer (m)
equivalent diffusivity (m2/hr)
maximum day length for each month (hr)
mean daily temperature (*C)
hourly rainfall (0.1 mm/hr)
percentage of top layer failure
annual infiltration rate (m/yr)*
fraction of residual saturation
distance from bottom of trench to nominal depth of aquifer (m)
porosity
hydraulic conductivity (m/yr)
bulk density (g/m3)
Saturated Zone
distance between well and stream (m)
distance from trench to well (m)
ground water velocity (m/yr)
thickness of aquifer (m)
dispersion angle (radians)
bulk density (g/rrn
longitudinal dispersivity (m)
porosity
• internally calculated, output from transient zone calculation.
42
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7. RUNOFF, EROSION, AND SURFACE WATER TRANSPORT
7.1 Introduction
Surface water may be an important pathway by which contaminants are
transported from a waste disposal site; such pathways include lakes, streams, rivers,
and the rainfall-runoff process. Contaminants present on the surface of a waste site
may become entrained or dissolved in surface runoff and be transported to adjacent
bodies of surface water. Contaminated soil particles detached by the impact of rain
drops or eroded by surface runoff may be transported to surface bodies also. Exposure
to humans can occur then through drinking and using contaminated surface water, or
by eating organisms living in these water bodies (Figure 7.1)
Figure 7.1 Pathways for surface water exposure.
The pathways for surface water from a contaminant source to drinking water (or
immersion exposure) can be sub-divided into three major components:
• Infiltration into the subsurface and eventual discharge of ground water into
surface water bodies
• Runoff across the land surface transporting dissolved, suspended, and bed
load as overland flow
• Mixing of the contaminated surface or infiltrating ground water with a surface
water body.
The magnitude of each of these components can be predicted using empirical or
physically-based equations that model the transport of contaminants through overland
and ground water flow to a surface water body. These equations need to consider the
following classes of variables:
43
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• The quantity and intensity of precipitation
• The physical characteristics of the soil that control the soil's ability to absorb
and transport water and contaminants, including antecedent moisture
conditions
• The nature of vegetative cover
• Topographic features of the landscape, such as slope and the presence of
depressions
• The physical characteristics of the surface water body into which runoff flows
and ground water infiltrates
The mechanisms by which different radionuclides are transported to surface
water bodies usually vary with their respective geochemical properties Radioactive
metals in solution tend to bind to soil components, leaving only a small fraction in
solution Conversely, some radioactive constituents such as tritium tend to remain in
solution with only a small fraction binding to soil materials. Consequently, radioactive
metals in streams are related to surface runoff (event water) and soil erodibility
generally, while more soluble constituents may be related more to infiltration,
dissolution, and ground water discharge. It is essential to model processes (flow
pathways), in addition to flow amounts, in order to analyze behavior of these and other
contaminants in natural systems. This conclusion would imply that physically-based
models should produce more accurate predictions for the surface water components
than empirically-based models.
Methods for simulating surface water transport fall into two broad categories -
empirically and physically based Two examples of these are the Morton and the
variable-source-area (VSA) theories Morton developed his theory for the infiltration
process in the early 1930s. The Morton model (and several later variations) are based
on the concept of the soil's surface as a barrier to vertical flow The VSA theory was
presented first by Hewlett (1961) and by Hewlett and Hibbert (1967) in response to
phenomena unexplained by traditional hydrologic theories.
7.2 Model Comparisons
MEPAS, MMSOILS, and PRESTO-EPA-CPG each take slightly different
approaches to simulating overland flow and the surface water pathway However, their
difference may not significantly affect constituent concentrations at points-of-concern.
Each model incorporates a surface contaminant source term, a runoff model, an
erosion model, and a surface water mixing component. Table 71 compares the
capability of the models
7.2.1 Rainfall-runoff
A significant percentage of the water associated with rainfall-runoff is present in
the subsurface flow system before a storm begins (antecedent moisture) In addition,
simple hydrologic abstractions based upon conditions at the soil surface cannot predict
these contributions, nor their origin within a watershed, even though proper application
44
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of these techniques will quantify rainfall-runoff accurately. The complexity of the
rainfall-runoff process, the importance of surface-subsurface interactions, and the
modeling of surface water flow pathways are not fully implemented into MEPAS,
MMSOILS, or PRESTO-EPA-CPG; no subsurface contributions to surface water bodies
are implemented into their rainfall-runoff components. Subsurface contributions to
surface water bodies are computed solely by the ground water submodel. PRESTO-
EPA-CPG uses a physically-based approach to estimate runoff by evaluating the
vertical movement of water in the vadose zone beneath the site. Modifying this
procedure to evaluate vadose and water table conditions throughout the catchment
would generate runoff computations consistent with VSA theory. However, MMSOILS
and MEPAS (both of which are based upon an Hortonian approach to the rainfall-runoff
process) cannot simulate rainfall-runoff flow pathways.
Table 7.1 Surface water pathway: Comparison of capabilities.
Runoff Calculations
Erosion
Transport
Miscible
Adsorbed on Soil
Stream Mixing
MEPAS
SCS-CN'
MUSLE4
yes
yes
coupled,
2D, steady-state
advection-dispersion
MMSOILS
SCS-CN1
USLE2
yes
yes
uncoupled,
1D
complete mix
PRESTO-EPA-CPG
Physically Based
Deterministic Approach
USLE: 3
yes
no
uncoupled
2D, steady-state
advection-dispersion
1. Soil Conservation Service Curve Number method
2. Universal Soil Loss Equation
3. Eroded material is removed from the model and not transported off-site
4. MEPAS uses the Modified USLE - MUSLE (Onstad and Foster 1975; Onstad et al . 1976;
Mitchell and Bubenzer, 1980; Novotny and Chesters, 1981)
yes or note = option is available
no = option is not available
The U.S. Soil Conservation Service Curve Number (SCS-CN) method (a variant
of the Morton method) is used to compute runoff in the MMSOILS and MEPAS models
This empirically-based procedure was designed to be used on a storm-by-storm basis
The SCS-CN method employs a series of curves that relate runoff volume (Q) to
precipitation (P) and watershed storage (S):
Q = (P-0.2S)2
P + 0.8S
45
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This approach is used widely, and accurately predicts runoff volumes on the scale of a
watershed. MMSOILS modified the interpretation of a storm in implementing the SCS-
CN procedure. The total monthly depth of precipitation is broken into individual storms
of equal magnitude by dividing the monthly value by the total number of days per month
with precipitation The antecedent moisture conditions are estimated from the number
of days it rained in a particular month The authors of MMSOILS recognized that these
assumptions would give an approximation of runoff volumes using the SCS-CN method,
but that this procedure was consistent with the available data.
The rainfall-runoff component in MEPAS uses the same procedure and is based
upon the same assumptions as made in MMSOILS. In the rainfall-runoff module in
PRESTO-EPA-CPG, overland flow is modeled using a modification of the one-
dimensional momentum and continuity equations, and infiltration rates are based upon
subsurface conditions The equation for surface water, soil moisture, and evaporation
each is solved on the time-scale of minutes and hours over the course of an individual
storm However, a peer review subcommittee (USEPA, 1984) that evaluated the
rainfall-runoff sub model of PRESTO-EPA-CPG was concerned that: •• (i) the rate of
infiltration is insensitive to variation in the slope of the trench cap: and (ii) the results
are highly dependent on the initial water storage value which can not be initialized by
the user" Hydrologists have recognized for a long time that these two factors are
important for estimating runoff. Nevertheless, since the solution of the equations
employed by PRESTO-EPA-CPG is an initial value problem, the error in the assumed
initial value can be eliminated by ignoring the initial period of analysis. Based on the
extensive trial runs that EPA performed, the maximum length of simulation has never
exceeded 5 years, and normally was 3 years, before the initial water storage value
reaches equilibrium Since the PRESTO-EPA-CPG model has had this adjustment to
the initial water-storage value built-in to the model, the difficulty of initializing the
storage value is virtually solved. As to the insensitivity of the rate of infiltration to the
slope of trench cap, this is caused by the relatively large numerical error. This error
can be suppressed by selecting smaller space and time steps.
Input Data requirements for the three models are summarized in Table 7.2.
PRESTO-EPA-CPG has extensive requirements for climatological data, and hourly
precipitation data are required for each day of the year to run this model Rainfall-
runoff and the associated erosion and transport of contamination are short-term
transient phenomena controlled by individual storms. A single, short-duration high-
intensity thunderstorm will cause more erosion and transport of constituents than a
long-duration, low-intensity storm of equal volume Detailed climatological data are
required to simulate these processes.
7 2.2 Erosion and transport components
All three models use the universal soil loss equation (USLE) to approximate soil
erosion across the site (Wischmeier and Smith, 1978) This equation is based on a
number of empirical relationships (factors) that followed from the analysis of years of
accumulated rainfall and erosion data The equation that embodies this approach is:
46
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A=R.K»SL«V«P
where the average soil loss (A) is the product of the rainfall (R). soil credibility (K),
slope (SL), vegetation (V), and management/conservation practice (P) factors
Representative values for these factors for areas within the 48 contiguous states are
given in Wischmeier and Smith (1978).
MEPAS uses a modified form of the USLE (MUSLE) recommended by Foster
(1976) for use at sites where storm events are to be analyzed In MMSOILS and
MEPAS contaminant transport is linked with erosion. These two models have
components that simulate constituents in the runoff which are in solution and sorbed
onto the soil being eroded off the site. PRESTO-EPA-CPG accounts for the erosion of
the cap at a site, but does not transport the eroded material and associated
contaminants; it is simply removed from the system. This is because the standardized
PRESTO-EPA-CPG model assumes that the material used for trench-cap construction
is clean soil. The eroded soil would not contain contaminants as long as the protective
cover is functioning effectively. However, when the protective cover is totally eroded
away, the soil would begin to contain contaminants. However, PRESTO-EPA-CPG
simulates the transport of dissolved constituents in surface runoff Contaminants
adsorbed onto soils exposed to precipitation and runoff are partitioned off, and
considered to be in equilibrium with constituent concentrations in the water. These
transport components in each of the models represent distributed source terms (non-
point sources) to down-slope surface water bodies.
7.2.3 Surface water mixing
MEPAS, MMSOILS, and PRESTO-EPA-CPG use a similar approach to assess
radionuclide impacts within surface water bodies. Constituents may be delivered via
the rainfall-runoff process, seepage through the movement of ground water, or as direct
discharge from the waste site. MEPAS uses a plug-flow-with-dispersion approach for
the surface waterborne component (Whelan et al., 1987). MMSOILS uses a simple.
complete-mix model for assessing impacts MMSOILS includes stream and surface
water body (lake or pond) submodels, while MEPAS includes a stream and a wetlands
component. The wetlands component in MEPAS has sufficient flexibility to simulate a
surface water body also. The stream component is a one-dimensional approximation in
MMSOILS, while MEPAS includes a two-dimensional, vertically averaged stream-flow
model with unidirectional advection in the flow direction and dispersion in the
transverse direction (Whelan et al., 1987). PRESTO-EPA-CPG considers flow within
surface water bodies to be one-dimensional. However, transport is evaluated using a
two-dimensional (lateral and transverse) steady-state approximation Additional
surface water pathway components can be incorporated also into the PRESTO-EPA-
CPG and MMSOILS models because within these two models the surface water
components are uncoupled from the other submodels.
47
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Table 7.2 Data input requirements of the surface water pathway.
Climatological Data
Precipitation
Storms
Site Parameters
Vegetative Cover
Land surface Slope
Antecedent
Moisture
Waste
Concentrations
Soil Parameters
Bulk density
Porosity
MEPAS
MMSOILS
PRESTO
Monthly Summary
Index on storm type
Monthly Summary
Average Number of
Storms/Month
Hourly Data
—
yes
yes
SCS curve number
yes
yes
yes
Estimated from storm
frequency
yes
yes
yes
Computed from soil
conditions in the
vadose zone
yes
yes
Calculated from
specific weight and
bulk density
yes
yes
yes
yes
7.3 Developer Updates - Surface Water Pathway
7.3.1 MEPAS
Droppo (1994) reports that efforts are underway to add to MEPAS specific
environmental transport capabilities for wetlands, lakes, estuaries, and river sediment
interactions.
732 PRESTO-EPA-CPG
The modified version of the PRESTO-EPA-CPG model (designed for cleanup
scenarios) will be able to simulate contaminants in the surface runoff from the
beginning of a simulation, if the scenario of contaminated soil without soil cover is
selected.
48
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8. FOOD CHAIN MODELING
8.1 Introduction
Food chains are biospheric pathways through which humans are exposed to
environmental contaminants. They are represented by bioaccumulations of
contaminants in the edible portions of animals and plants that are affected by the
facility. Food chains consist of one or more trophic levels (steps) between the physical
environment and human intake of contaminants (Figure 8.1).
ATMOSPHERIC DEPOSITION (wet or dry) » p|ants > Animal Products
Humans
irrigation
WATER (surface or ground) > Plants > Animal Products
> Humans
SOIL > Plants *• Animal Products
Humans
SURFACE WATER + Fin-or Shellfish * Humans
AQUATIC SEDIMENT > Fin-or Shellfish » Humans
Figure 8.1. Basic food chains as depicted in risk assessments
8.2 Comparisons of Models
Food chains are described as part of the exposure-dose models in
documentation for MEPAS (Whelan, 1993), separately in MMSOILS (USEPA. 1992).
and as agricultural data supporting exposure estimates in PRESTO-EPA-CPG
(USEPA, 1987). MEPAS documentation has detailed formulas to describe each aspect
of food chain modeling. As part of its equations for animal feeds, leafy vegetables.
and other produce, MEPAS separates descriptions by the origin of plant contamination
from wet or dry atmospheric deposition, irrigation, or accumulations in soil Both foliar
and root uptake are described Table 8.1 summarizes the descriptions of the food
chain in the models, and Table 82 gives more detailed descriptions of each level in the
food chain.
49
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MEPAS, MMSOILS, and PRESTO-EPA-CPG use inputs of time-weighted
average concentrations of contaminants. Equations are given for estimating the
average concentrations of contaminants at the location of exposure resulting from
transport in media and food chains. Measured concentrations can be used instead of
those calculated in MEPAS
Table 8.1 Summary of food chain features in models.
Selection of Contaminant
Hazardous Chemical Waste
Radioactive Waste
Transfer to Plants
From Air
From Irrigation
From Soil
Transfer to Animal Products
Meat and Milk
From Air Deposition or» Feed Crops
From Irrigation of Feed Crops"
From Soil Consumption
From Drinking Water
Finfish
Shellfish
MEPAS
yes
yes
yes
yes
yes
yes
yes
yes
no
yes
yes
yes
MMSOILS
yes
no
yes
yes
yes
yes1
yes
yes
yes
yes
yes
yes3
no
PRESTO-EPA-CPG
no
yes
yes
yes
yes
yes
yes
yes
yes4
yes
yes4
no
1 Combines intake from forage, soil and water.
2 Includes pasture grass, stored feed and leafy vegetables.
3. Calculations based on either water or sediment concentrations.
4. Included in the modified model adaptable to cleanup scenahos.
The irrigation pathway to food chain transport is not well described in MMSOILS,
and uptake into plants does not account for edible fractions. For vegetation, MMSOILS
uses a general food chain equation to describe atmospheric deposition and
bioconcentration from contaminated soil, with a specific description in root crops of the
bioconcentration of contaminants from soil. For plant materials, the use of measured
concentrations in the three models negates the need for such distinctions. MEPAS and
PRESTO-EPA-CPG distinguish leafy vegetables from other types of produce. The
number of days in a growing season that vegetable matter including pasture grass and
feed is exposed to radionuclides and the fraction of animal feed that is contaminated is
considered in PRESTO-EPA-CPG estimates. MEPAS includes the length of the
growing season in vegetable and feed-crop production also. All feed for milk cows is
assumed to be contaminated forage. All feed for meat animals is assumed to be grain-
type plants. If some of the feed is uncontaminated, then the user may modify the intake
rates of animal feed to reflect the proportion of contaminated intake.
50
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Table 8.2 Details of food chain levels in the models.
Plant
Meat
Milk and
Milk Products
Fish
MEPAS
Feed crops for
animals
Leafy vegetables
such as lettuce,
cabbage, and spinach
Other vegetables
including grains, root
crops, and food not
generally exposed to
depositional material
beef
pork
bovine, poultry
cow
freshwater finfish and
shellfish
MMSOILS
Pasture grass and hay
Above around
includes leafy (lettuce). and
silage (com), exposed
produce (non citrus fruits,
berries, field crops —
cucumber, tomato,
squash, eggplant)
Below around
root crops
beef
cow
freshwater finfish
PRESTO-EPA-CPG
Grass
Leafy vegetation
Produce
including grains and root crops
beef
goat
cow
goat
freshwater finfish and shellfish
A single formula in MMSOILS describes transfers to animal products (meat and
milk) by combining the chemical concentrations in, and the intake rates of, animal
feeds, soil, and drinking water. The transfer factors in MMSOILS either take into
account the fraction of food that is fat and bioconcentration in the organism, or use
partition coefficients for transfers from soil to meat and/or to milk. In MEPAS, transfers
to animal products account for direct transfers from media, and transfers from media to
forage plants and feed. At present, MMSOILS does and MEPAS does not describe
transfers to animal products from accumulations in ingested soil, but MEPAS includes
animal ingestion of contaminated water. PRESTO-EPA-CPG includes atmospheric,
irrigation, and drinking water sources of contamination of vegetation and animal
products.
Whole-body concentrations of chemical and radiological contaminants are
considered in both finfish and shellfish by MEPAS and PRESTO. MMSOILS describes
only chemical concentrations in "fish" (assumed from the documentation to be finfish),
but can base its calculations on concentrations in water and/or sediments. Bio-
concentration factors can be selected for fish in general, or for particular species. The
bioconcentration factors for contaminants in the water column are adjustable also for
the lipid content (%) of fish. MMSOILS uses a sediment-to-fish partition coefficient for
chemicals in sediments. MEPAS does not relate concentrations in aquatic animals to
those in the sediments.
8.3 Developer Updates Food Chain
None of the models plan future updates that would have any direct impact on
assessing transport and exposure via the food chain.
51
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9. EXPOSURE ASSESSMENT
9.1 Introduction
Often, exposures and doses are confused. Exposures are quantities of toxic or
carcinogenic agents that are potentially taken into the human body, or (as described by
Ruttenber, 1993a,b) "...the contact between an organism and its environment"
Exposures (e.g., mg, g, pCi) to a contaminant are estimated usually by multiplying the
intakes of environmental media or foods (e.g., L, m3, kg) by the respective
concentrations of the agent in the media and/or foods (e.g., mg per L, g per m3, pCi per
kg) and summing their products. Exposure rates include specified periods, such as mg
per d or pCi per yr. Exposures to chemicals are generally expressed in metric units of
mass, while exposures to radionuclides are expressed in standard units of picocuries
(pCi) or in System Internationale (SI) units of Becquerels (Bq)
Exposure pathways are the last stage of transport modeling, and include those
parts of the transport directly related to the behavior and characteristics of those at risk.
Exposure estimates are affected by uncertainties in pathway exposure factors (PEFs -
McKone, 1990). PEFs are terms that translate unit concentrations in media (e.g., pCi
per L) and food chain components into exposures per unit time (exposure rates). PEFs
use information on human physiology and behavior, and environmental transport for
specific media (McKone, 1990). These uncertainties arise from biological and
behavioral variations, as well as the accuracy and precision of the estimated values for
each parameter. Many characteristics important to personal exposure are constant, or
have a near-constant distribution nationwide (e.g., breathing rates). Others (such as
intake of local foods) can be significantly different, depending on local production and
exports.
9.2 Comparison of Models
The scope and complexity of the food chain and exposure calculations for
multimedia pathways vary with each of the three models. MEPAS covers a wide variety
of sources of movement in the food chain and human exposure to chemical and
radioactive contaminants (Table 9.1) This coverage includes on-site and off-site
pathways. MMSOILS analyzes on- and off-site exposures to chemicals buried in the
soil. PRESTO-EPA-CPG analyzes on-site and off-site food chain transport and human
exposures for buried, low-level radioactive wastes.
MEPAS, MMSOILS, and PRESTO-EPA-CPG use inputs of time-weighted
average concentrations of contaminants. The exposure modules provide users with
equations for estimating the average concentrations of contaminants at the location of
exposure resulting from transport in media and food chains. Measured concentrations
can be used instead of those that are calculated in MEPAS and PRESTO-EPA-CPG,
but not in MMSOILS.
-------
Table 9.1 Summary of exposure features in models.
Contaminant Selection
Hazardous Chemical Waste
Radioactive Waste
Intakes from Inqestion of
Drinking Water
Shower Water
Swimming Water
Leafy Vegetables
Other Produce
Meat
Milk
Finfish
Shellfish
Special Food
Shoreline Sediment
Soil
Intakes from Inhalation
While Showering
Of Air
Of Re-suspended Soil
Intakes from Contact
While Showering
While Swimming
With Shoreline Sediment
With Soil
With Volatiles in Air
External Exposures from Radiation: while
Swimming and Boating; in air, Soil and
Shoreline Sediment; or from
Measurements of Direct Radiation.
MEPAS
yes
yes
yes
yes
yes
yes' \
yes12
yes
yes
yes
yes
yes
yes
yes3
yes
yes
yes
yes
yes
yes
yes3
yes
yes
MMSOILS
yes
no
yes
no
no
yes
yes
yes
yes
yes
no
no
no
yes
no
yes
yes
yes
yes
no
yes
no
no
PRESTO-EPA-CPG
no
yes
yes
no
no
yes
yes
yes
yes
yes
yes
eggs
yes
yes4
no
yes
yes
no
no
no
no
no
air immersion, ground
surface
1 From air deposition on crops.
2 From irrigation of crops.
3 Estimations based on either measured concentrations or on calculated
accumulations in soil after atmospheric deposition.
4 Included in the modified model adaptable to cleanup scenarios.
5 Root crops.
MEPAS and MMSOILS (as described below) incorporate exposure rates in their
formulas for doses from chemical contaminants. Both MEPAS and PRESTO-EPA-CPG
use additional special algorithms for MC
analysis (see Chapter 10).
and H in vegetable and animal product
Although MEPAS and MMSOILS describe human exposures from ingesting
water during swimming, only MEPAS describes ingestion during showering In MEPAS.
exposure rates for ingestion of contaminants in vegetable matter, in animal products.
and in special foods are described separately for each transport medium
54
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MEPAS separately calculates the rates of ingestion of contaminants in shoreline
sediments and the soil contaminants. Soil contaminants can be described either by
measured concentrations, or by calculated accumulations from atmospheric deposition.
Similarly, uptakes from contact with shower water, swimming, shoreline sediments, and
soils are described separately.
MEPAS calculates exposure rates separately for inhaling contaminants in air,
showers, and re-suspended soil. Also, it is the only one of the three models that
distinguishes indoor from outdoor inhalation, which is an important procedure in
estimating exposures to volatile organic chemicals and radon
For radioactive materials, MEPAS models external exposure from irradiation by
radionuclides in air, soil, shoreline sediments, and from radionuclides in water during
swimming, and boating. Measurements of direct radiation can be used in the exposure
calculations also.
In MMSOILS, exposures to non-carcinogenic toxic chemicals are compared to
available Reference Dose (RfD) or Health Advisory (HA) values for comparable
intervals. Average daily intake rates (mg per kg per d) are time-weighted for 1 day, 10
days, longer periods, and for sub-chronic and chronic periods. HA values (exposure
rates in mg per day) are modified to RfD units (dose rates) by adjusting for body weight.
For radionuclide exposures, PRESTO-EPA-CPG estimates include the period of
the growing season that vegetable matter is exposed, and fractions of human intake of
water and animal products that are contaminated. Animal products are distinguished
as meat and milk from cattle and/or goats.
9.3 Developer Updates - Exposure Assessment
Future versions of MEPAS will include ingrowth of progeny in the exposure
assessment component of the model (Whelan, personal communication, 1994). No
updates are planned for MMSOILS and PRESTO-EPA-CPG that would have a direct
impact on the calculation of exposures for any of these models
55
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10. DOSIMETRY/RISK ASSESSMENT
10.1 Introduction
Dose-assessment codes integrate two components into the assessment of risk:
one component calculates the transport mechanism of the released contaminant, and
the other calculates the human uptake and dose associated with the exposure This
chapter explores how MEPAS, MMSOILS, and PRESTO-EPA-CPG translate exposures
from various sources into numerical estimates of dose and risk (e.g., the number of
excess fatal cancers). The estimation of radiation dose is discussed in some detail
below because dose estimation for radioisotopes must be treated differently than that
for chemicals.
In contrast to chemicals, the effect of radioactive contaminants on humans is a
function of the nature of the energy released during their radioactive decay Radiation
is emitted by a radioisotope when it transforms (disintegrates) into another isotope
(e.g., 226Ra to 222Rn). Each radioisotope is unique, and the decay rate, energy, and the
type of radiation differ. The term activity expresses the number of disintegrations of a
radioisotope per unit time. The fundamental unit of activity was the Curie (Ci, or 3.7 x
1010 disintegrations per second, equal to the activity of 1 g of 226Ra), but the current SI
unit is the Bq (i.e., 1 disintegration per second). The most common types of ionizing
radiation are alpha (a) and beta (B) particles, and gamma (g) rays (photons). Each of
these three types can be emitted over a range of energies, expressed commonly in
units of thousands of electron volts (KeV), or millions of electron volts (MeV) Each
radionuclide has its own characteristic radiation type or types and range of associated
energy levels. Alpha particles can travel only about 2 or 3 cm in air and no more than
about 0.01 mm in body tissue because they have mass. On the other hand, beta
particles can travel much further in air and tissue, yet have about the same kinetic
energy. A 1 MeV beta particle can travel approximately a meter in air and can likely
penetrate the thickness of human skin, but not much beyond that The minimum
energy required for skin penetration for alpha and beta radiations are 7.5 MeV and 70
KeV, respectively. External alpha radiation is not often of concern for the purpose of
radiation protection since few alpha decays achieve energies in that range. On the
other hand, a weightless 1 MeV gamma-ray can penetrate a sheet of paper or
aluminum foil easily, and could pass entirely through the human body. Therefore,
gamma radiation is the principal source of concern for external radiation exposures
Doses for chemicals are the amounts of toxic or carcinogenic agents (or their
metabolically activated products) that reach a tissue or organ within the body. Doses
are expressed in mass of agent accumulated per unit mass of organ or body weight.
Dose rates include specified periods in the expression (e.g., g per kg per d, pCi per kg
per d). Dose estimates are derived generally from exposure estimates by using dose
conversion factors, which usually represent the fraction of exposure that is delivered to
a target organ (or target organs), with adjustments for temporal factors, retention, and
conversions to active progeny. Dose factors have been defined extensively for
radionuclides, but there is a great deal of uncertainty for chemical doses. Therefore,
57
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risk factors are expressed often in reference to exposures because it is easier to
quantify exposures (e.g., EPA's HEAST and IRIS expressions of risks per unit ingested
or inhaled).
Radiation dose has been expressed in units of rads (radiation absorbed dose),
and rem (roentgen equivalent, man). The rad is a measure of the energy per unit mass
(100 erg/gm) delivered to any mass when a given amount of radiation is absorbed. The
rem is a special unit of dose equivalent and depends on the type of radiation absorbed
(ICRP, 1990) The dose equivalent rem is numerically equal to the product of an
absorbed dose in rads and a quality factor (also termed the radiation weighting factor
[ICRP, 1991]). For example, neutrons and alpha particles deliver energy in high
density packets, while X- and gamma rays deliver the same amount of energy at lower
density. Quality factors for radiation are represented usually by the term relative
biological effectiveness (RBE), which is a ratio of the magnitude of a particular
biological effect of one type of radiation to the magnitude of the same effect of another
type of radiation. The SI units for rad and rem are the Gray (Gy) and Seivert (Sv),
respectively. One Gy (1 Joule/kg) is equal to 100 rads, while one Sv is equal to 100
rem.
One of the key parameters in deriving the dose to an individual or population is
the dose conversion factor. This factor relates a given intake of radioactive material to
a radiation dose. In general, the dose conversion factors are derived from
recommendations made by the International Commission on Radiation Protection
(ICRP) The ICRP recommendations on dose limits are the primary guidance
documents used by international and national organizations for estimating effects of
ionizing radiation exposure on radiation workers and members of the public (ICRP,
1977, 1979, 1986, 1988, 1989, 1990). Within the United States, the methodology for
dose conversion is based on guidance from five different organizations: the ICRP, the
National Council on Radiation Protection and Measurement (NCRP, 1993), DOE (DOE,
1988a, 1988b), EPA (USEPA, 1988a, 1993), and NRC.
102 Review of Models
Outlined below are the methods used by PRESTO-EPA-CPG and MEPAS to
calculate doses from radiation exposures. MMSOILS does not calculate a radiation-
based dose; it provides comprehensive analyses of pathways and receptors for on- and
off-site exposure, and it is limited to the transport of non-radiogenic chemical materials.
Using MMSOILS to predict radiation dose from exposures requires additional health-
physics analyses to convert the intake dose and correct for decay. For this reason, we
discuss only chemical and not radiation dose for MMSOILS in the text that follows.
58
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10.2.1 Overall dose
10.2.1.1 Chemical Dose
Intakes of chemicals are referred to as administered doses (AD) to conform with
RfD values, and MMSOILS assumes that the absorbed fraction of intake is 100% in
humans ADs are calculated as mg per day for water and food ingestion (vegetable,
meat, milk and fish), and inhalation or mg per occurrence for soil ingestion The AD for
soil contact are expressed as mg per visit to the contaminated area, and the
calculations may require modifications to adjust for alterations of chemicals during
cutaneous transfer. Although MMSOILS does not specify ingestion of, nor contact with,
shoreline sediment, it is assumed that these exposures can be described by the
comparable equations for soil ingestion and contact
Carcinogenic chemical intakes, as 70-year lifetime average daily doses, are
compared to EPA's potency factors (now supplanted by slope factors — USEPA, 1989)
There is a marked inconsistency in the use of 75-year lifetimes for toxicity and 70-year
lifetimes for carcinogenicity.
10.2.12 Radiation Dose
The current version of PRESTO-EPA-CPG employs dose conversion factors
developed by Eckerman (USEPA, 1994) to calculate dose from internal and external
exposures (Rogers and Hung, 1987). The dose conversion factors are extracted from
the RADRISK data file (Dunning et al., 1980) and the weighting factors are consistent
with the definitions used in ICRP Publications 26 and 30 (ICRP, 1977 and 1979). The
effective dose equivalent is the weighted sum of the 50-year committed dose equivalent
to the specified and remainder organs. The cancer risk coefficients are calculated from
the radiation risk models based on 1980 U.S. vital statistics. On the other hand, the
radionuclide genetic risk coefficients for serious heritable disorders to all generations
are calculated from the product of the average absorbed dose to the ovaries and testes
up to age 30 per unit intake before that age. Genetic Risk Coefficients of 2 60 x 10~2
and 69 x 10~2 Gy"1 for low-LET and high-LET radiation are used to calculate the risk
conversion factors, respectively (USEPA, 1994b).
PRESTO-EPA-CPG employs the DARTAB submodel to estimate both exposure
and annual committed doses (mrem per y) for as many as 40 radionuclides, by adding
the weighted doses to each organ from all pathways of exposure. Exposures from
ingested intakes of radionuclides are expressed as person pCi per year External
irradiation exposures from air or contaminated ground surfaces are. expressed as
person-pCi per m3 (volume), and person-pCi per m2 (surface) respectively DARTAB
combines estimates of radionuclide exposure with dosimetric and health effects data to
generate predicted impacts.
MEPAS uses the methodology in Federal Guidance Report -11 (FGR-11
[USEPA, 1988]) to calculate dose from internally deposited radionuclides For external
59
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exposures, MEPAS obtains dose using the Eckerman (USEPA, 1994) dose conversion
factors. In contrast to PRESTO-EPA-CPG which calculates and reports a dose.
MEPAS calculates dose rate, as rem per unit time, but only reports fatal cancer risks
These risks (5.0 x 10"2 fata! cancers Sv"1) are consistent with the latest ICRP
recommendation (ICRP, Publication 60, 1991) for radiation workers. If MEPAS is used
to calculate risk for the whole population, the suggested risk factor is 7.3 x 10"2 fatal
cancers Sv"1 (NCRP, 1993); i.e.. the sum of the fatal cancer, non-fatal cancer, and
severe genetic effects. These cancer effects represent a stochastic outcome. MEPAS
does not calculate an equivalent dose for any single organ or tissue for evaluating
deterministic health effects like those associated with organ-seeking nuclides (e g ;
iodine for thyroid, and strontium for bone).
MEPAS and MMSOILS estimate doses (e.g., mg per kg per d; pCi per kg per d)
on the basis of average daily exposures. This may not determine risks accurately, for
example, when exposures vary widely in intensity and duration. PRESTO-EPA-CPG
uses annual exposures because it estimates maximum doses on a year-by-year basis
(up to 10,000 years) but, overall, this is similar to the assessment of radionuclides in
MEPAS. On the other hand, PRESTO-EPA-POP calculates the fatal cancer and
serious genetic risks for the local and downstream basin population However the
uncertainty of the overall risk assessment tends to increase with time because of the
increasing uncertainty of demographic predictions Since the PRESTO-EPA-CPG
model uses a hypothetical scenario in which the critical population resides in a user-
assigned location and calculates the dose for each person, the uncertainty in the
demographic distribution will not be the concern of this analysis. In PRESTO-EPA-
POP, the uncertainty in the demographic distribution will affect significantly the
uncertainty of the number of the fatal cancer and serious genetic effects - a situation
that applies to all models.
10.2.2 Inhalation dose
There is a significant relationship between particle size, lung retention, and dose
for estimating dose due to inhalation. The physical association of radioactivity with
micron size and sub-micron size particles is crucial for the inhalation pathway The
smaller particles penetrate deeper into the lung, are more efficiently deposited there.
and are cleared inefficiently as long as they are insoluble
All assumptions associated with the intake-dose constants of FGR-11 (USEPA,
1988) become default parameters within MEPAS. MEPAS uses a 1 micron particle size
for aerosols based on FGR-11. Furthermore, MEPAS uses the ICRP-30 dynamic lung
model and its compartment parameter values, the so-called D-W-Y lung clearance
class for chemical transportability (ICRP, 1979). In this case, D refers to those
materials that can be removed from the lung in days, W in weeks, and Y in years,
respectively. The PRESTO-EPA-CPG organ dose rates are calculated from pre-
calculated conversion factors, derived using the default value of 1 micron particle size
for aerosols and the lowest solubility D-W-Y lung class (class Y is used in most cases)
These default values are recommended by ICRP.
60
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10.2.3 Radon/Thoron progeny and long-lived fission products
The modified PRESTO-EPA-CPG version adaptable to cleanup scenarios
includes a radon inhalation pathway. MEPAS does not derive dose calculations for
natural radon/thoron progeny (RTP), but allows the user to specify a radon emission
rate from which atmospheric transport of radon and progeny is evaluated using "mock
radon" radionuclides. This representation allows an evaluation of dose from radon. It
includes an equilibrium amount of short-lived progeny and the maximum amount of
long-lived progeny, thus providing a conservative estimate of radiation risk. 222Rn, and
220Rn are a concern at sites contaminated with 226Ra or 224Ra, respectively. Since many
sites have high levels of Ra, failure to account for dose due to 222Rn,220Rn would be a
significant deficiency.
Long-lived fission products and nuclear materials cannot be neglected
necessarily because of their low specific activity, especially those that have been
classified as "most hazardous materials" such as neptunium (Np), plutonium (Pu), and
americium (Am). On the other hand, those radioisotopes with short half-lives (e.g.,
isotopes of Np, Pu, and Am other than 237Np, 239Pu, and 241Am) are of less concern to
any health risk assessment of long-term waste disposal. However, the release of
contamination that includes long-lived isotopes like those of 237Np, 241Am, and 239Pu is
of the utmost concern for any environmental safety and health study.
10.2.4 Period of exposure
PRESTO-EPA-CPG model calculates the rate of dose commitment (mrem/yr) by
multiplying the exposure rate (pCi/yr) with the dose-conversion coefficient (mrem/pCi).
A 50 year dose commitment factor is used for this calculation. The value of the dose
commitment factor is obtained from FGR-11 for each radionuclide. MEPAS bases its
dose analysis on intake for a user-defined exposure duration (70 year default).
10.2.5 Individual vs. population-based dose
MEPAS calculates the dose to an individual located at some place in time and
both individual and population risks. Early versions of MEPAS calculated a Hazard
Potential Index (HPI) which is based on the population exposure. Neither the MEPAS
or MMSOILS models calculate onsite exposures. The original version of PRESTO-
EPA-CPG model calculated the annual and maximum dose to the on-site farmers from
drinking, irrigation, and cattle-feed pathways. The estimation of the cumulative fatal
and genetic health effects does not include normally the effects to on-site farmers.
Since the PRESTO-EPA-CPG model calculates the total population health effects by
adding the local population health effects with downstream population health effects,
the user may combine the on-site farmers into the local population. The results of
analysis include the fatal and genetic effects from the on-site farmer and the
downstream population.
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10.3 Developer Updates - Dose/Risk Assessment
10.3.1 MEPAS
Planned updates for MEPAS include modules to calculate ecological risk, acute
human risk, and worker risk {Droppo. 1994).
MEPAS is being incorporated into the Remedial Action Assessment System
(RAAS), a screening tool for cleanup remedies. MEPAS' baseline risk assessment is
used by RAAS as a starting point for estimating residual risk to evaluate the
effectiveness of alternative remedies
1032 PRESTO-EPA-CPG
PRESTO-EPA-CPG is being modified to include dose from progeny nuclide
ingrowth and for the soil-ingestion pathway (Hung, 1994). Version 2.1 of PRESTO-
EPA-CPG contains also revised computational models, procedures, and data for dose
conversion to conform with ICRP 30. SI units are adopted also for radioactivity and
dose equivalent. The modified PRESTO-EPA-CPG model will improve the on-site
residence to cover all applicable scenarios that could be adapted to a cleanup
scenario.
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11. UNCERTAINTY ANALYSIS
11.1 Introduction
Uncertainties in risk assessment are important in making risk management
decisions. In a risk assessment, descriptions of uncertainties may indicate the quality
of information, range of knowledge, and level of confidence available. Extensive
sensitivity and uncertainty analyses were made to develop EPA's Low-Level Waste
Environmental Standards. Several factors contribute to these uncertainties, including:
limitations in the data that characterize sites and source terms, uncertainties in
scenarios and choices of parameters to fit different scenarios, uncertainties in
formulating the transport model and in physical parameters used as input to the models
(e.g., diffusion coefficients), exposure parameters, and dose-response relationships.
The word parameter is used in this document as a component (= property or variable)
that can be characterized either quantitatively or qualitatively. Some factors
contributing to the uncertainty in final risk estimates are more important than others.
Uncertainty arises from combinations of heterogeneity (variability), errors in
measurement, and lack of knowledge.
• Heterogeneity is the variability within a parameter, such as the
variability in the characteristics of a population. For example, it is
relatively easy to determine the amount of water that an individual
drinks daily, but the amount will vary from day to day and among
individuals in a population.
• Error in measurement arises from inadequacy of sampling,
sampling biases, errors in the measurements, and imprecision
• Lack of knowledge can involve parameters that are expressed
quantitatively and components of a risk assessment that do not have
numerical values. Major sources of uncertainty include inadequate
knowledge of physical processes, such as environmental transport
mechanisms, and gaps in qualitative knowledge, such as future land-
use scenarios. Parameters and their ranges of values can be affected
profoundly by choices among these components of a risk assessment,
in turn affecting the overall uncertainties of the risk estimates.
Most parameters used in risk assessments contain elements of heterogeneity,
errors in measurement, and lack of knowledge. For example, the amount of water that
is imbibed daily is heterogeneous across a population, but each sample is subject to
errors in measurement and sampling bias.
As part of a risk assessment, uncertainty analyses should be performed to
determine which parameters exert a significant influence on the overall risk estimates.
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Sensitivity analyses are used to assess which parameters are the most
important contributors to the magnitude of an overall risk estimate, and they frequently
are undertaken as part of a screening-level assessment. These analyses compare all
parameters in an assessment for the overall effects of a specific degree of change
(e g . a 20% variation) in each parameter (Morgan and Henrion, 1990)
Uncertainty analyses estimate the contribution of uncertainty associated with
each variable to the overall uncertainly of a risk estimate (Rish, 1988) A sensitivity
analysis can be performed as part of an uncertainty analysis to identify the parameters
that contribute the most to the variance of the final risk estimates. In other words, the
analysis quantifies the sensitivity of uncertainty of a risk estimate to a changed range or
assumed type of distribution of a single variable.
11 2 Comparison of Models
The three models use deterministic (single) values for parameters It is difficult
in such deterministic assessments to sort out the contributions of individual parameters
to the overall uncertainty of the risk estimates, because the calculations can combine
high (90th or 95th percentile) parameter values with lower (50th percentile or average)
values (Burmaster and Harris, 1993)
The accuracy of the value of the parameters in all three models is difficult to
verify Although such difficulties are balanced by the user's ability to input alternative
values, no specific instructions are provided for performing uncertainty analyses as a
way of estimating the adequacy and precision of assumptions The "Documentation
and Users Manual for MMSOILS" (USEPA, 1992) expresses the clearest concern
about the overall uncertainty of the risk estimates, and of specific parameters MEPAS
and MMSOILS suggest and allow input of site-specific and region-specific data to
reduce uncertainty for food chain and exposure parameters, and to provide alternative
choices for doing some calculations when the concentrations of contaminants have
been measured at specific sites. MEPAS also gives some regional data in its reference
tables MEPAS supplies a report, based on site-specific sensitivity analysis, that gives
the user information on sensitive parameters in each of the codes comprising the model
(Doctor et al., 1990). A second MEPAS report (Droppo et al., 1990) provides a system-
wide uncertainty analysis for representative sites and constituents.
113 Developer Updates - Uncertainty Analysis
An operational version of a sensitivity/uncertainty module for MEPAS is being
tested at several sites (Droppo, 1994). Besides user-input parameters, a version is
planned that will allow sensitivity analysis via Monte-Carlo analysis on the physical,
chemical, and toxicity parameters associated with health impacts from the MEPAS
database The addition of the capability to perform uncertainty analysis within the
existing PRESTO-EPA-CPG model is planned
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12. PARAMETER ESTIMATION AND DEFAULT VALUES
12.1 Introduction
Inaccurate values for input parameters can be a major source of error in health
risk assessments. Input data can be faulty because of poor judgment in estimating the
parameter and over-reliance upon default values which may not be applicable to a
given scenario. The data from which parameter values were derived may not be
relevant to the specific set of conditions to be addressed by the model. The
determination of a parameter value itself carries some inherent uncertainty since
processes within environmental models have a large natural variability in time and
space, and such values are based often on experimental data that refer to only a few
discrete points in time and space.
In this chapter, the three models are compared in terms of their data
requirements, availability of default values, and guidance to select or estimate
parameter values. This chapter assesses also the relative importance of different
parameters in the given models, based on information in the manuals and in previous
reviews. The parameters of greatest importance are the ones that have the greatest
potential impact on the outputs for the particular assessment (i.e., long-term
environmental and public health risks for environmental restoration and waste
management activities). In this context, four categories of model parameters are
considered following the approach outlined by IAEA (1989): (i) source parameters (e.g.,
rate, time, and duration of a release, nuclide speciation, source strength, chemical and
physical form of the release radionuclides), (ii) environmental transport parameters
(e.g., wind speed, precipitation height, porosity, sorption, partition coefficients, soil
hydrogeological properties), (iii) bioaccumulation parameters, and (iv) dose and
exposure parameters (e.g., living and consumption habits, health standards).
12.2 Comparison of Models
12.2.1 Description of the data input requirements for models and their default values
MEPAS has data on more than 576 chemicals and radionuclides in the chemical
and sorption Kd databases. The former includes information on a) physical properties,
b) environmental decay, c) environmental transfer, d) radiological dosimetry, and e)
chemical toxicity. The sorption K
-------
Sorption K^s for organic constituents are computed within MEPAS using
values, organic matter content, and the soil's proportion of sand, silt, and clay The
inorganic and organic Kd values determined by MEPAS are provided to the user as
suggested values for each constituent of the soil layer; as such they are not presented
as "correct" values Rather, they are meant to represent typical values that might be
found for the constituents of concern The user can take the suggested value or
replace it with site-specific information.
MMSOILS has a database with chemical, transport, decay, and chemical or
radiological dosimetry characteristics for 240 pollutants. The code requires several
pathway-specific pieces of information (e.g.. atmospheric pathway, surface water
pathway, ground water pathway, infiltration leaching and recharge, food chain
bioaccumulation pathway). One hundred and seventy-seven input values are required,
many of which are provided in tables or suggested in the users manual. The manual
gives guidance for selecting or estimating the parameter values, but that guidance is
not as detailed as that of MEPAS.
PRESTO-EPA-CPG requires input data on site-specific and radionuclide source
terms, hydrogeologic and meteorological conditions, radiological dosimetry, and health
effects The manual describes all the required parameters, but includes default values
and/or guidance to select/estimate values for only six of them Since the model
provided input data sets for the humid permeable, the humid impermeable, and the arid
permeable sites in the United States, it gives a wide spectrum of sites across the
United States. Furthermore, since each of the submodels within PRESTO-EPA-CPG
is designed to be as dynamic as possible, most of the required input parameters
represent system characteristics and are measurable. That is, the PRESTO-EPA-CPG
model uses less dependent variables that should be calculated, in theory, by the model
as user-assigned input parameters. Therefore, the model requires less guidance to
assign input parameters that would require extensive empirical data bases.
12 2.2 Comparison of values from MMSOILS and MEPAS databases
Table 12.1 compares the values from the databases of MEPAS and MMSOILS
for a relatively immobile chemical, arsenic. Table 12.2 shows the same data for
benzene, a relatively mobile chemical. PRESTO-EPA-CPG was excluded because (i) it
includes only radionuclides, not chemicals, and (ii) the documentation provides only a
few default values These comparison tables provide examples of the range in input
parameters that can exist between MEPAS and MMSOILS for two typical contaminants.
12.2.3 Source term parameters
Problems related to quantifying the parameters of the source term include
sparse or inaccurate information about identifying the types of wastes present,
determining the quantities of waste, and estimating waste distribution. Release and
solubility parameters define the mass of leachate to be released to the subsurface from
a waste management unit. Some site-specific parameters are difficult to ascertain, yet
66
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they can have a significant impact on the results. For example, one such parameter is
the rate of suspension of particles caused by vehicles disturbing the site. MEPAS
accounts for the silt content of the road, vehicle weight, length, frequency of
mechanical disturbances, and other such parameters. Different analysts could choose
easily different values of these parameters for the same site.
12.2.4 Environmental transport and decay parameters
An important parameter that defines the distribution of the source term among
different media is the Kd. K
-------
Although these comments may be correct for a specific problem that is being
assessed, they are not universally true. For example, if the problem is temporally far-
field, the rate of release has no effect on the results; only a change in the source term
inventory affects the results For a temporally near-field case, the rate of release
determines the risk. If the soil type is radically altered, then the risk will be influenced
substantially by this change.
Table 12.1 Input Parameters for Arsenic.
Molecular Weight (g/mol)
Vapor Pressure (mm Hg)
Henry's Law Constant (atm mj/mol)
Solubility In Water (mg/L)
Organic Carbon Partition Coefficient (Koc) (mUg)
Octanol-Water Partition Coefficient (Kow) (mUg)
Partition Coefficient, Kd, (ml/gm) - at pH=
Kd for clay+organics <10% of total soil (mL/g)
Kd for clay+organics 10-30% of total soil (mUg)
Kd for clay+organics >30% of total soil (mL/g)
Kd for aquifer (VnL/g;
Environmental Half-Life In Air (days)
Environmental Half-Life In Water (days)
Environmental Half-Life In Soil (days)
Ground Water 15' Decay (1/yr)
Unsaturated Sediments 1ST Order Decay (1/yr)
Chemical Decay In The WMU ( 1/yr)
Chemical Decay Constant In Off-Site Field (1/yr)
1SI Order Decay In Stream (1/yr)
Fish Bio-Accumulation Factor (1/kg)
Bio-concentration In Fish (mg/kg fish)/(mg/L water)
Sediment/fish Partition Coef. (mg/kg fish)/(mg/ kg soil)
Shellfish Bio-Accumulation Factor (1/kg)
Soil-To-Plant Uptake
Soil-To-Meat Partition Coef. (mg/kg beef)/(mg/kg soil)
Feed-To-Meat Coefficient (d/kg)
Feed-to-Cow Milk Coefficient (g/L)
Transfer Factor For Cattle (kg/kg)
Transfer Factor For Milk (mg/kg milk)/(mg/kg intake)
Soil To Milk Partition Coef. (mg/kg milk)/(mg/kg so;/)
Uptake From Soil To Plant (mg/kg plant)/(mg/kg soil)
Soil Moist. To Root Factor (mg/kg root)/(mg//kg solute)
Water Purification Factor
Deposition Velocity (m/s)
Atmospheric Deposition Class
Inhalation Cancer Potency Factor (kg-d/mg)
Ingestion Cancer Potency Factor (d/mg)
MEPAS
75
0.0
NA
0.0
NA
0.0
>9 5-9 <5
0.6 5.86 5.86
2.0 19.4 19.2
2.0 19.4 21.5
NV.6.9E+07'
NV1, 6.9E+07'
NV\ 6.9E+07"
NA
NA
NA
NA
NA
100'. 1.0*
NA
NA
40
0.0015' 0.01
NA
0.002
0.002
NA
NA
NA
NA
NA
0.7
0.001
1
5.0E+01
1.5
MMSOILS
75
0.0001
1.E-08
100000
NV
NV
354
354
3.54
354
NA
NA
NA
0.0
0.0
0.0
0.0
0.0
NA
1.00
0.00
NA
NA
0.00
NA
NA
0.002
000006
0.00
0.04
0.00
NA
NA
NA
NA
NA
NV = no value is listed in electronic database NA = not applicable
1. = value in electronic database of MEPAS version 3.x
2. = value in manual (Chemical Databases; Strenge, Peterson, and Sager, 1989) Note that the
values in subsequent versions of the manual are continuously updated to conform
with the values in the electronic database.
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Table 122 Input Parameters for Benzene.
Molecular Weight (g/mol)
Vapor Pressure (mm Hg)
Henry's Law Constant (atm mj/mol)
Solubility In Water (mg/L)
Organic Carbon Partition Coefficient (Koc) (mUg)
Octanol-Water Partition Coefficient (Kow) (mUg)
Partition Coefficient (Kd) For Waste - at pH=
Kd for clay+organics <10% of total soil (mUg)
Kd for clay+organics 10-30% of total soil (mUg)
Kd for clay+organics >30% of total soil (mUg)
Kd for aquifer (mL/g)
Environmental Half-Life In Air (days)
Environmental Half-Life In Water (days)
Environmental Half-Life In Soil (days)
Ground Water 1st decay (1/yr)
Unsaturated Sediments 1&: Order Decay (1/yr)
Chemical Decay In The WMU (1/yr)
Chemical Decay Constant In Off-Site Field ( 1/yr)
1S1 Order Decay In Stream (1/yr)
Finfish Bio-Accumulation Factor (1/kg)
Bio-Concentration In Fish (mg/kg fish)/(mg/L water)
Shellfish Bio-Accumulation Factor (1/kg)
Sediment/Fish Partition Coef. (mg/kg fish)/(mg/ kg soil)
Soil-To-Edible Plant
Soil-To-Meat Partition Coef (mg/kg beef)/(mg/kg soil)
Beef Uptake (d/kg)
Feed-To-Cow Milk Coefficient (g/L)
Feed-To-Meat Coefficient (d/kg)
Milk Update (d/L)
Transfer Factor For Cattle (kg/kg)
Transfer Factor For Milk (mg/kg milk)/(mg/kg intake)
Soil To Milk Partition Coef. (mg/kg milk)/(mg/kg soil)
Uptake From Soil To Plant (mg/kg plant)/(mg/kg soil)
Soil Moist. To Root Factor (mg/kg root)/(mg//kg solute)
Water Purification Factor
Deposition Velocity (m/s)
Atmospheric Deposition
Inhalation Cancer Potency Factor (kg-d/mg)
Ingestion Cancer Potency Factor (d/mg)
MEPAS
78
95
5.6E-03
1750
83
1.32
computed
NV1, 6.9E+07-
NV\6.9E+07-
NV1, 6.9E+07'
NA
NA
NA
NA
NA
0\24'
NA
0\3.9'
NA
o'.o.ss-
NA
0',3.36E-06'
0.002
0.002
1 .05E-06
NA
NA
NA
NA
NA
1.00
1 .2E-06
1
2.9E-02
2.9E-02
MMSOILS
78.11
94.2
5.7E-03
1690
31
NA
0.0
0.0
0.0
0.0
NA
NA
NA
0.0
0.0
0.0
00
0.0
NA
24.48
NA
0.00
NA
0.00
NA
NA
NA
0002
0.00000107
0.00000000
14.5606
2.12987
NA
NV
NV
NV
NV
NV = no value is listed in electronic database NA = not applicable
1. = value in electronic database of MEPAS version 3.x
2. = value in manual (Chemical Databases; Strenge, Peterson, and Sager, 1989). Note that the
values in subsequent versions of the manual are continuously updated to conform
with the values in the electronic database
12.2.5 Parameters for bioaccumulation
MEPAS lists some different values of bioaccumulation in its electronic and paper
database For example, benzene's feed-to-meat coefficient has a zero value in the
69
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electronic database, and 3.36E-06 value in the paper database. The model user needs
to be aware that MEPAS' electronic database is constantly being updated, and the
paper database serves only as an example of representative values. In addition, the
electronic database of MEPAS contains zero values for those parameters (e.g., finfish
bioaccumulation parameter) that are evaluated at run time by MEPAS' exposure
assessment component using correlation relationships. Correlation analysis is not
used for non-zero values in the database.
1226 Parameters of dose and exposure
When source terms and estimates of contaminant flux along different exposure
pathways are determined, the next set of data required includes the more site-specific
parameters that determine exposure and dose.
In MMSOILS, the "action levels" for air-borne releases of several contaminants
are incorrect. For example, the action level for 1,1,2 trichloroethane is listed as 0.6
ng/m3, whereas the PEL (Permissible Exposure Level, based on 40 hour work-week) is
45 mg/m3. The action level for selenium is listed as 3.5 |ig/m3, whereas the PEL for
selenium is 0.2 mg/m3. A default value of 99.9 mg/m3 is assigned to several other
chemicals (e.g., mercury, acetone, dioxane), while their PELs range from 0.1-2400
mg/m3.
In addition, MEPAS Version 3.0 allows the user to input certain uptake and
exposure parameters. Documentation is provided for the inclusion of such parameters.
There are procedures for modifying MEPAS default parameter files contained in files
that can be edited, rather than the previously hard-wired versions.
123 Developer Updates - Default Parameters
The number of contaminants in the MEPAS database is under expansion to
include new parent radionuclides, and organic and inorganic chemicals (Droppo, 1994).
Radioactive decay chains are being expanded also. Whereas the current MEPAS
contains approximately 500 chemicals, the September 1994 release contains
approximately 700.
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13. DISCUSSION/CONCLUSIONS
13.1 Source Term
Hazardous waste sites may leak contaminants into the environment and pose a
threat to human health. At many sites, in addition to the general characteristics of the
site, the only fact that is known is that hazardous materials are being released The
specific cause of the release of contaminants from that site source may be undefined
In addition, the strength and nature of hazardous releases may vary with time, and the
impact may shift among the pathways affected by those releases. These uncertainties
challenge the multimedia modeler to arrive at some reasonable approximation for a
source term that will simulate closely the actual site release of hazardous waste.
The three models can simulate a variety of source terms; MEPAS has the most
varied capabilities for source term modeling of the three models reviewed. None of the
models can deal with the presence of free or residually-saturated, non-aqueous liquid,
within the source term. Each model bases leachate production on either a steady-state
value or on leachate solubility or equilibrium-partitioning.
13.2 Air Transport
Volatile hazardous waste components leaving a site through the atmospheric
pathway are subject to (he vagaries of weather at the surface of the earth Air-transport
modeling assumes commonly that transport through the atmosphere occurs as a more
or less weakly organized plume whose direction, dimensions, and contaminant
concentrations are controlled by the speed and direction of the wind, the rate and
quantity of precipitation, and the extent of fallout from that plume.
All three models use a standard, sector-averaged, Gaussian-plume approach for
air-transport and model annual-average concentrations and exposures. MEPAS and
MMSOILS use the same volatilization algorithm. Only PRESTO-EPA-CPG models
radioactive decay Only MEPAS can model atmospheric calm conditions with
accompanying channeling and complex terrain characteristics.
13.3 Ground Water Transport
The movement of ground water is most often very slow, and that movement
occurs over an area and volume that is often much larger than the area and volume of
the source. Once in the ground water, contaminants are isolated and difficult to
remove. As an essential human nutrient, almost every human being is exposed in
some way to contaminants that originate in ground water, some people much more than
others. All of these factors imply that the ground water pathway can pose a serious
threat to public health at hazardous waste sites.
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Therefore, perhaps the most serious limitation of screening-type models like
MEPAS, MMSOILS and PRESTO-EPA-CPG is the relative simplicity of their ground
water transport components. While each model includes a ground water component
that is capable of modeling both unsaturated and saturated transport, that component
is simulated using classical assumptions - uniform, linear flow in a homogeneous,
layered medium with equilibrium, and reversible adsorption of miscible contaminants.
The transport of materials through the ground water system is complex, both in terms of
the effect of non-uniform flow regimes and because of chemical reactions between
ground water and matrix. The properties of radioactive materials themselves pose
special problems Only MEPAS and PRESTO-EPA-CPG consider the fate and
transport of radioactive progeny: although both assume the same adsorption
characteristics for progeny as for parent. MMSOILS does not model the decay of
adsorbed contaminants.
134 Erosion, Overland Flow, Runoff and Surface Water Transport
Multimedia models are very often employed for use at sites where radioactive
contamination originates at or near the land's surface. Therefore, source materials
may be not only subject to atmospheric conditions or leached into the ground water, but
also possibly removed by surface transport processes.
As with the ground water component, MEPAS, MMSOILS and PRESTO-EPA-
CPG employ similar, simplistic models for runoff, erosion, and mixing within surface
water bodies These simplistic approaches are based, for the most part, on empirical
equations that may have little or no physical basis. The same limitations for simulating
the transport of radionuclides that exist for simple ground water models pertain to
simple surface water models: accurate flow paths can be very important when
modeling constituents that decay, and simple equilibrium partitioning between
dissolved contaminants and sediments within surface water bodies may not be
sufficient in environments where, for example, resuspension can be important. None of
these models considers volatilization from surface water bodies into the atmosphere.
MEPAS and MMSOILS have separate subroutines for modeling transport within
wetlands and lakes, respectively.
13.5 Food Chain Modeling and Exposure Assessment
The assessment of human health risk is the primary objective of most transport
and exposure assessment modeling. The penultimate step before the final calculation
of human exposure and risk is to estimate the concentration of contaminants in food
and drink to which humans will be exposed. MEPAS includes food chains as an
integral part of its exposure-dose component. Food chains are considered separately
in MMSOILS and in PRESTO-EPA-CPG as agricultural data supporting exposure
estimates Although MEPAS can be used to model acute toxic atmospheric releases,
all three models were designed primarily to handle long-term, chronic exposures
72
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Each of the three models employ comparable, standard methods for estimating
exposure to environmental contaminants through the food chain and other pathways
Therefore, the same limitations that exist for all exposure and risk assessments exist
for these models. For example, food intake is subject to behavioral variations Both
the quantity and type of foods eaten vary from location to location In addition, the poor
state of knowledge of the combined effects of radionuclides and toxic chemicals may
have additional implications for the accuracy of exposure calculations at mixed-waste
sites
136 Dosimetry/Risk Assessment
Human health risk is a function of the actual impact that an environmental
contaminant has on an individual or group. The quantity of a toxic substance that
produces an adverse response in an organism is known as a dose. Dose can refer to
individual organs or a whole body; it can be either internal or external: and it can be
either acute or chronic. In addition, the model may be designed to calculate either
individual or population dose on and/or off a contaminated site.
Only MEPAS and PRESTO-EPA-CPG can calculate human dose from
radionuclides. MMSOILS is designed to consider only toxic chemicals. Both MEPAS
and PRESTO-EPA-CPG use methods defined by Eckerman to calculate external dose.
The chronic dose calculated by MEPAS is based on a default lifetime exposure of 70
years, while PRESTO-EPA-CPG uses 50 years for its dose period. MEPAS calculates
individual dose and individual and population risk. Both MEPAS and MMSOILS were
designed for the estimation of off-site exposures and dose, while PRESTO-EPA-CPG
can calculate both on- and off-site dose by including the on-site population as part of
the local" population.
137 Uncertainty Analysis
The accuracy of a predicted outcome cannot be better than the accuracy of the
data input to the model. In addition, no matter how accurate the input data is, if the
algorithms used by the model do not closely mirror "real-world" processes, the output
generated by the simulation will be of little use. Not all input data and not every model
algorithm affect the accuracy of the outcome of the simulation equally. Uncertainty and
sensitivity analyses are procedures that the model user can follow in an attempt to
quantify the impact of parameter (input) and/or structural (algorithm) error
Uncertainty analyses can and should be performed with any model as long as
the user can vary input parameters and observe the results of the simulation The
capabilities for performing uncertainty analyses with the three models reviewed in this
report are a function of the number and diversity of input parameters In this way,
PRESTO-EPA-CPG has fewer environmental input parameters than either MEPAS or
MMSOILS. MEPAS and MMSOILS discuss methods for estimating more accurate
values for site-specific parameters when site-monitoring data are available.
73
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138 Parameter Estimation and Default Values
The three models use deterministic (single) values for parameters. It is difficult
in such deterministic assessments to sort out the contributions of individual parameters
to the overall uncertainty of the risk estimates, because the calculations can combine
high (90th or 95th percentile) parameter values with lower (50th percentile or average)
values The accuracy of the value of the parameters in all three models is difficult to
verify Although such difficulties are balanced by the user's ability to input alternative
values, no specific instructions are provided for performing uncertainty analyses as a
way of estimating the adequacy and precision of assumptions.
139 Overall Summary
Table 13.1 presents a summary of the features contained within each of the
three models For the purpose of simulating the transport, fate and effects of
radioactive contaminants through more than one pathway, both MEPAS and PRESTO-
EPA-CPG are adequate for screening studies; MMSOILS only handles nonradioactive
substances and must be modified before it can be used in these same applications Of
the three models, MEPAS is the most versatile, especially if the user needs to model
the transport fate and effects of hazardous and radioactive contaminants
74
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Table 13.1 Summary of model features.
Contaminant Selection
Hazardous chemical waste
Radioactive waste
Air Pathway
Gas/Vapor emissions
Paniculate emissions
Point/Area/Air sources
Volatilization
Plume rise
Plume reflections on
ground/lid
Calm conditions
Complex terrain
Ground roughness
Dry deposition
Wet deposition
Radioactive decay
Chemical decay
Re-suspension
Inhalation
Indoor exposure
Onsite exposure
Short time exposure
Spatial definition
Surface Water Pathway
Overland flow (runoff)
Overland sediment
Suspended solids
Sediment
Volatilization
Spatial definition
Ground Water Pathway
Spatial definition
Time dependence
Soil Pathway
Volatilization
Infiltration
Ground water loss
Degradation
Soil ingestion
Spatial definition
Time dependence
MEPAS
yes
yes
yes
yes
yes/yes/yes
yes
yes
yes
yes
yes
yes
yes
yes
yes
yes
yes
yes
yes1
yes
yes
2-D
yes
yes
yes
yes
yes
2-D
3-D
yes
yes
yes
yes
yes
yes
1-D
yes
MMSOILS
yes
no
yes
yes
no/yes/no
yes
no
no
no
no
no7
yes
no
no
no
yes
yes
no
yes
no
2-D
yes
yes
no
no
yes
1-D
3-D
yes
yes
yes
yes
yes
no
1-D
yes
PRESTO-EPA-CPG
no
yes
yes
yes
yes/yes/no
no
no
yes
no
no
yes
yes
no
yes
no
yes
yes
no
c.
yes"
yes
2-D
yes
yes
no
no
yes
1-D
1-D
yes
no
yes
yes
yes
yes
no
yes
75
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Table 13.1 cont'd. Summary of model features.
Bio-accumulation
Animals
Terrestrial plants
Foliar deposition
Aquatic organisms
Spatial definition
Site Data Required
Contaminant Selection
Hazardous chemical waste
Radioactive waste
Intakes from Ingestion of
Drinking Water
Shower Water
Swimming Water
Leafy Vegetables
Other Produce
Meat
Milk
Finfish
Shellfish
Special Food
Shoreline Sediment
Soil
Intakes from Inhalation
While Showering
Of Air
Of Re-suspended Soil
Intakes from Contact
While Showering
While Swimming
With Shoreline Sediment
With Soil
With Volatiles in Air
External Exposures:
While Swimming
While Boating
From Air
With Soil
With Shoreline Sediment
From Direct Radiation.
MEPAS
yes
yes
yes
yes
2-D
Extensive
yes
yes
yes
yes
yes
yes;'
yes23
yes
yes
yes
yes
yes
yes
yes
yes
yes
yes
yes
yes
yes
yes4
yes
yes
yes
yes
yes
yes
yes
MMSOILS
yes
yes
yes
yes
2-D
Moderate
yes
no
yes
no
yes
yes
yes
yes
yes
yes
no
no
no
yes
no
yes
yes
no
no
no
yes
no
no
no
no
no
no
no
PRESTO-EPA-CPG
yes
yes
yes
no
2-D
Moderate
no
yes
yes
no
no
yes
yes
yes
yes
yes
yes
eggs
yes
yes
no
yes
yes-
no
no
no
no
no
no
no
yes
yes
no
no
1 This component not available in 1993 version.
2. From air deposition on crops.
3. From irrigation of crops.
4. Estimations based on either measured concentrations or on calculated accumulations
in soil after atmospheric deposition.
5. In the version modified for cleanup scenarios.
6. On-site scenario only.
7. MMSOILS only considers ground surface roughness in wind erosion of participates
76
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