&EPA
United States
Environmental Protection
Agency
Beneficial Use Compendium:
A Collection of Resources and Tools to
Support Beneficial Use Evaluations
Office of Resource Conservation and Recovery
Office of Land and Emergency Management
Washington, DC 20460
EPA 530-R-16-009
June 2016
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Beneficial Use Compendium Front Matter
Disclaimer
This document ("the beneficial use compendium" or "the compendium") was prepared by the United States
Environmental Protection Agency ("EPA" or "the Agency") Office of Land and Emergency Management.
The beneficial use compendium and the methodology it references are intended to be useful to those "who
conduct or review beneficial use evaluations, as well as other interested stakeholders, including states,
local governments, tribal authorities, regulated communities, and the general public. The information
contained in the compendium is based on the Agency's current understanding of the range of issues and
circumstances involved "with the beneficial use of industrial non-hazardous secondary materials
("secondary materials"). It is not intended to address the combustion of non-hazardous secondary materials
for energy, the use/reuse of municipal solid "waste, or the regulation of hazardous waste. Use of the
beneficial use compendium is voluntary and does not change or substitute for any federal or state statutory
or regulatory provisions or requirements. The compendium does not preclude the use of any other
available approaches. Nothing in the compendium is intended to establish binding requirements on EPA
or any other entity. Accordingly, EPA may revise or depart from the approach outlined in the beneficial
use compendium and the methodology it references at any time, "without prior notice. Any reference to
specific commercial products, process or service by trade name, trademark, manufacturer or otherwise
does not constitute or imply its endorsement, recommendation or favoring by the United States
government. Such references are provided for informational purposes only.
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Beneficial Use Compendium
Front Matter
Acknowledgements
The beneficial use compendium was developed by the U.S. Environmental Protection Agency (EPA)
Office of Land and Emergency Response (OLEM). Contributing authors include Jason Mills, Timothy
Taylor, and Donald Wilbur.
EPA Contributors and Reviewers
Office of Land and Emergency Management
Brandon Bass
Chris Carusiello
Rita Chow
Gregory Helms
Colette Hodes
Lee Hofmann
Ksenija Janjic
Kim Kirkland
Kathleen Raffaele
Taetaye Shimeles
Nicole Villamizar
Office of the Administrator
Keith Chanon
Sharon Cooperstein
Robin Jenkins
Office of Air and Radiation
Robert Burchard
Office of Research and Development
Jace Cuje
Susan Thorneloe
Regional Offices
Jui Yu Hsieh (Region 1)
Yigal Bar-Av (Region 2)
Dale Carpenter (Region 2)
Mary Hunt (Region 3)
Mary Beth VanPelt (Region 4)
Jerri-Anne Garl (Region 5)
Julie Gevrenov (Region 5)
Susan Mooney (Region 5)
Paul Ruesch (Region 5)
David Flora (Region 7)
Dave Christenson (Region 8)
Carl Daly (Region 8)
Kendra Morrison (Region 8)
Mary Rogers (Region 8)
Lynda Deschambault (Region 9)
Other Federal Contributors and Reviewers
U.S. Army Corps of Engineers
Mark Dortch
U.S. Department of Agriculture
Rufus Chaney
U.S. Department of Transportation
Jason Harrington
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Beneficial Use Compendium
Front Matter
State Contributors and Reviewers
Connecticut
Department of Environmental Protection
Carey Hurlburt
Delaware
Department of Natural Resources and
Environmental Control
Robert Underwood
Florida
Department of Environmental Protection
Stephen Roberts
Richard Tedder
Georgia
Environmental Protection Division
Jim McNamara
Charles Williams
Iowa
Department of Natural Resources
Matt McDonald
Indiana
Department of Environmental Management
Theresa Bordenkecher
Lori Freeman
Massachusetts
Department of Environmental Protection
Thomas Adamczyk
Michigan
Department of Environmental Quality
Kay Fritz
Duane Roskoskey
Minnesota
Pollution Control Agency
Geoffrey Strack
Missouri
Division of Environmental Quality
Eric Gramlich
New Jersey
Department of Environmental Protection
Zafar Billah
New York State
Department of Environmental Conservation
Thomas Lynch
North Dakota
Department of Health
Steve Tillotson
Ohio
Environmental Protection Agency
Jacob Howdyshell
Pennsylvania
Department of Environmental Protection
Michael Forbeck
Texas
Commission on Environmental Quality
Scott Green
Utah
Division of Solid and Hazardous Waste
Ralph Bohn
Virginia
Department of Environmental Quality
Donald Brunson
Rebecca Dietrich
Washington State
Department of Ecology
Chuck Matthews
Wisconsin
Department of Natural Resources
Bizhan Zia Sheikholeslami
Wyoming
Department of Environmental Quality
Bob Doctor
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Beneficial Use Compendium Front Matter
Table of Contents
Section 1. Introduction 1-1
1.1. Purpose and Scope 1-2
1.2. Benficial Use Compendium Organization 1-2
I: Planning and Scoping
Section 2. Planning and Scoping 1-0
2.1. Evaluation Scope 2-1
2.1.1. What Are the Relevant Stages of the Lifecycle? 2-1
2.1.2. What Is the Chemical and Physical Composition of the Secondary Material and
Beneficial Use? 2-2
2.1.3. What Might Be Released into the Environment? 2-3
2.1.4. What Happens to Stressors Released into the Environment? 2-4
2.1.5. What Exposures May Result from Releases? 2-5
2.1.6. What Adverse Impacts May Result from Exposures? 2-6
2.1.7. What Are the Applicable Risk Management Criteria? 2-6
2.2. Conceptual Model 2-7
2.3. Analysis Plan 2-8
2.3.1. Analytical Steps and Approaches 2-8
2.3.2. Accounting for Uncertainty 2-8
2.4. Summary 2-9
II: Impact Analysis
Section 3. Existing Evaluations 3-1
3.1. Identification Stage 3-1
3.2. Review Stage 3-2
3.2.1. Applicability and Utility 3-2
3.2.2. Clarity and Completeness 3-3
3.2.3. Soundness 3-3
3.2.4. Variability and Uncertainty 3-4
3.2.5. Evaluation and Review 3-4
3.3. Application Stage 3-5
3.4. Potential Sources of Uncertainty 3-5
3.5. Summary 3-6
Section 4. Comparison with Analogous Product 4-1
4.1. Considerations for Designing the Comparison 4-1
4.2. Considerations for Conducting the Comparison 4-3
4.3. Potential Sources of Uncertainties 4-5
4.4. Summary 4-6
IV
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Beneficial Use Compendium Front Matter
Section 5. Screening Analysis 5-1
5.1. Selection of Screening Benchmarks 5-1
5.2. Comparison at Point of Release 5-3
5.3. Comparison at Point of Exposure 5-4
5.4. Potential Sources of Uncertainty 5-6
5.5. Summary 5-7
Section 6. Risk Modeling 6-1
6.1. Model Selection 6-1
6.1.1. Model Assumptions 6-2
6.1.2. Deterministic and Probabilistic Models 6-2
6.1.3. Lumped- and Distributed-Parameter Models 6-4
6.2. Calculation of Risk 6-4
6.3. Potential Sources of Uncertainty 6-6
6.3.1. Data Uncertainty 6-7
6.3.2. Model Uncertainty 6-9
6.4. Summary 6-9
Phase III: Final Characterization
Section 7. Final Characterization 7-1
7.1. Summary of Analytical Results 7-1
7.2. Characterization of Uncertainties 7-2
7.3. Characterization of Potential for Adverse Impacts 7-3
Glossary
References
Appendix
Section A-1. Planning and Scoping A-6
Section A-2. Stressor Identification A-11
Section A-3. Environmental Releases A-15
Section A-4. Data Quality A-20
Section A-5. Statistical Methods A-22
Section A-6. Screening Benchmarks A-24
Section A-7. Toxicity Values A-31
Section A-8. Exposure Factors A-36
Section A-9. Fate and Transport Models A-38
Section A-10. Risk Calculations A-50
Section A-11. Final Characterization . ..A-54
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Beneficial Use Compendium Front Matter
List of Figures
Figure 1. Summary flowchart for the organization of the beneficial use compendium 1-3
Figure 2. Common lifecycle stages for a secondary material 2-2
Figure 3. Two different approaches to depicting the same conceptual model 2-7
Figure 4. Mass balance of stressors in a home 5-4
Figure 5. Relationship between probabilistic/deterministic inputs and outputs 6-2
Figure 6. Example of deterministic lumped and distributed inputs for a watershed 6-4
List of Tables
Table 1. Considerations for Applicability and Utility 3-2
Table 2. Considerations for Clarity and Completeness 3-3
Table 3. Considerations for Soundness 3-3
Table 4. Considerations for Variability and Uncertainty 3-4
Table 5. Considerations for Evaluation and Review 3-4
Table 6. Considerations for Screening Benchmarks 5-2
Table 7. Examples of Additional Factors Relevant to Risk Calculations 6-6
Table 8. Considerations for Discussing Conclusions 7-3
VI
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Beneficial Use Compendium
Front Matter
List of Abbreviations
AASHTO
AERMOD
AERSCREEN
AMS
ASTM
ASTSWMO
ATSDR
AWQC
BSAF
American Association of State Highway and Transportation Officials
American Meteorological Society/EPA Regulatory Model
American Meteorological Society/EPA Regulatory Screening Model
American Meteorological Society
American Society for Testing and Materials
Association of State and Territorial Solid Waste Management Officials
Agency for Toxic Substances and Disease Registry
ambient water quality criteria
biota-sediment accumulation factor
CalEPA California Environmental Protection Agency
CalTOX California Total Exposure Model
C&D construction and demolition
CDD/F chlorinated dibenzo-p-dioxins and chlorodibenzofuran
CERCLA Comprehensive Environmental Response, Compensation, and Liability Act
CFR Code of Federal Regulations
CPSC Consumer Product Safety Commission
CPV cancer potency value
CSF cancer slope factor
DAF dilution and attenuation factor
DOT Department of Transportation
DQA data quality assessment
Eco-SSL ecological soil screening level
EPA Environmental Protection Agency
EPACMTP EPA Composite Model for Leachate Migration with Transformation
Products
EPI Estimation Program Interface
FHWA Federal Highway Administration
FIFRA Federal Insecticide, Fungicide, and Rodenticide Act
HEAST Health Effects Assessment Summary Tables
HEI highly exposed individual
IEUBK Integrated Exposure Uptake Biokinetic Model
IRC Industrial Resource Council
IRIS Integrated Risk Information System
VII
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Beneficial Use Compendium
Front Matter
IWAIR Industrial Waste Air Model
IWEM Industrial Waste Management Evaluation Model
L/S liquid-to-solid
LANL Los Alamos National Laboratory
MCLG maximum contaminant level goal
MCL maximum contaminant level
MINTEQA2 Metal Speciation Equilibrium for Surface and Ground Water Model
MRL minimum risk level
MT3DMS Modular Three-Dimensional Transport Multi-Species Model
NAAQS National Ambient Air Quality Standards
NAPL non-aqueous phase liquid
NAS The National Academy Of Sciences
NEWMOA Northeast Waste Management Officials' Association
NJDEP New Jersey Department of Environmental Protection
NOAA National Ocean And Atmospheric Administration
NOAEL no observed adverse effect level
NPDWR National Primary Drinking Water Regulation
NRWQC National Recommended Water Quality Criteria
OEHHA Office of Environmental Health and Hazard Assessment
ORD Office of Research and Development
OLEM Office of Land and Emergency Response
ORNL Oak Ridge National Laboratory
OSWER Office of Solid Waste and Emergency Response
PCB polychlorinated biphenyl
PCDD/F Polychlorinated Dibenzo-P-Dioxin And Chlorodibenzofurans
PM particulate matter
PPRTV provisional peer-reviewed toxicity value
PRG preliminary remediation goal
QA quality assurance
QC quality control
RAGS Risk Assessment Guidance for Superfund
RCRA Resource Conservation and Recovery Act
REL reference exposure level
RfC reference concentration
RfD reference dose
VIM
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Beneficial Use Compendium
Front Matter
RMRC
RSL
SMCL
SQuiRT
SSL
SVOC
TEF
TRIM
TSCA
Recycled Materials Resource Center
regional screening level
secondary maximum contaminant level
screening quick reference table
soil screening level
semi-volatile organic compound
toxicity equivalency factor
Total Risk Integrated Methodology Model
Toxic Substances Control Act
U.S.
URF
USDA
VISL
VOC
United States
unit risk factor
U.S. Department of Agriculture
vapor intrusion screening level
Volatile Organic Compound
IX
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Beneficial Use Compendium
Section 1. Introduction
Industrial non-hazardous secondary materials
("secondary materials") are any materials that What Does "Non-Hazardous" Mean?
are not the primary product of manufacturing
and other industrial sectors. Examples can
• , , , -, , c , .. federal law, non-hazardous wastes are those
include scrap and residuals from production
that are not either explicitly listed as hazardous
processes and products recovered at the end of . ... „„ „„. 0 . . ., . .
F F under 40 CFR 261, Subpart D, and are not
classified as ignitable, corrosive, reactive or toxic
under 40 CFR 261, Subpart C, or are specifically
excluded from regulation as hazardous waste.
their useful life. Virtually all industrial sectors
generate some form of secondary material
during the course of normal operations. Some
of these secondary materials can be generated
"Non-hazardous" is a legal definition and is not
equivalent to "harmless" or "benign." Under
in large quantities. In the United States alone, several billion tons of secondary materials are
generated each year (U.S. EPA, 1987). Some examples include:
• Steam electric utilities generated nearly 130 million tons of coal combustion residuals
during the 2014 calendar year (ACAA, 2014).
• The metal casting sector generates approximately 9.4 million tons of spent foundry sands
each year (AFS, 2007).
• The construction and demolition sector generated approximately 530 million tons of
building-related construction and demolition materials in 2013 (U.S. EPA, 2015).
Once generated, secondary materials are often sent directly for disposal, but some have the
potential to be used beneficially instead. Beneficial use involves the substitution of these
secondary materials, either as generated or following additional processing, for some or all of
the virgin, raw materials in a natural or commercial product (an "analogous product") in a way
that provides a functional benefit, meets product specifications, and does not pose concerns to
human health or the environment.
Many opportunities exist to beneficially use these secondary materials (e.g., coal fly ash as a
replacement for cement in concrete, spent foundry sands as road subbase). Some of the
potential benefits associated with the use of secondary materials include preservation of
natural virgin resources, reduced air and water pollution from extraction activities, reduced
greenhouse gas emissions, reduced production costs, and avoided use of landfill space. Because
of the potential for numerous environmental, economic and performance benefits, the
appropriate beneficial use of secondary materials can advance the goals of EPA's Sustainable
Materials Management program, which emphasizes a materials management approach that
aims to reduce impacts to human health and the environment associated with materials over
their entire life cycle (e.g., extraction, manufacture, distribution, use, disposal).
1-1
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Beneficial Use Compendium Section 1. Introduction
1.1. Purpose and Scope
State, tribal and territorial regulatory bodies make the determinations whether to allow a given
beneficial use under a wide variety of programs, some that are dedicated specifically to
beneficial use and some that are handled under the purview of broader waste regulatory
programs. A survey of these beneficial use programs conducted by the Association of State and
Territorial Solid Waste Management Officials in 2006 found that, although the number of
requests for determinations is increasing, "insufficient information to determine human or
ecological impacts of use rather than disposal" has been a major barrier for states when
reviewing proposed beneficial uses (ASTSWMO, 2007). The United States Environmental
Protection Agency ("EPA" or "the Agency") Office of Land and Emergency Management
developed this document ("the beneficial use compendium" or "the compendium") to help
address this barrier.
EPA developed the Methodology for Evaluating the Beneficial Use of Industrial Non-
Hazardous Secondary Materials (U.S. EPA, 2016) to help determine whether the potential for
adverse impacts to human health and the environment from a proposed beneficial use is
comparable to or lower than from an analogous product, or at or below relevant health-based
and regulatory benchmarks. The methodology is intentionally broad in order to present a
balanced discussion of the different aspects of the methodology. The beneficial use compendium
is intended to provide a more detailed discussion of some specific considerations that may arise
in particular evaluations, as well as a list of existing resources and tools that can assist with
these evaluations.
The recommendations in the compendium are intended to be broad and flexible to allow
integration within any existing evaluation programs; however, those that use the compendium
are free to consider and incorporate other technically sound approaches. Use of both the
methodology and the compendium is voluntary and does not change or substitute for existing
laws, regulations, or any beneficial use determinations that govern the management of
individual wastes on either a federal or state level. EPA encourages those individuals or entities
who use both the methodology and the compendium to consult with relevant regulatory
bodies to ensure that the application of both these documents are scientifically sound and
accounts for any additional considerations required by these regulatory bodies. While
protection of human health and the environment is a critical component of beneficial use
determinations, EPA recognizes that additional considerations (e.g., existing state and federal
requirements, public opinion, the existence of a market) may also factor into the final
determination for a particular use.
1.2. Beneficial Use Compendium Organization
The compendium is divided into separate sections that mirror the phases and steps of the
beneficial use methodology. Each beneficial use evaluation conducted with this methodology
will progress through these three phases, but there is flexibility in which analytical steps are
1-2
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Beneficial Use Compendium
Section 1. Introduction
used and the specific methods used to implement a particular step. The compendium is
organized into multiple sections, each of which is intended to address one of these overarching
phases or analytical steps. A summary flowchart that maps each phase and step to the
corresponding section of the text where discussion can be found is presented in Figure 1.
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beneficial use evaluation and the information required to answer them. Data that will be used to
answer these questions can be assembled from the literature or generated for the evaluation. Further
data collection can also be conducted in the next phase if it is found that available data are
insufficient to support conclusions.
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Integrate the key findings,
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Figure 1. Summary flowchart for the organization of the beneficial use compendium.
1-3
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Beneficial Use Compendium Section 1. Introduction
For additional reference, a glossary and references are provided at the end of the compendium.
The glossary presents a list of common terms that may be encountered when conducting or
reviewing a beneficial use evaluation. The definitions presented may not be the only possible
definitions and some terms may have different meanings in other contexts. The references
provide a listing of all the references cited within the main text of the beneficial use
compendium. Further information about these and additional resources can be found in the
Appendix.
The appendix to the Beneficial Use Compendium is a library of additional resources that
supplement and expand on the discussion in the main text of the beneficial use compendium.
These resources provide information and tools that may aid in the development and execution
of beneficial use evaluations. The resources provided in this appendix are from publicly
available guidance documents, data sources, software programs and related informational
materials.
1-4
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Beneficial Use Compendium
Phase I:
Planning and Scoping
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Beneficial Use Compendium Section 2. Planning and Scoping
Section 2. Planning and Scoping
Planning and scoping is the first step of any beneficial use evaluation conducted with this
methodology. During planning and scoping, the purpose, level of detail, and initial analysis
plan for the beneficial use evaluation are established. Careful planning will ensure that the
objectives of the evaluation are well-defined, are realistic and form a sound basis for a
beneficial use determination. In addition, this preliminary work can help to determine future
resource needs, scheduling requirements, and any outside parties that may be useful to consult
during the evaluation process. This section builds on previous discussions in Risk
Characterization Handbook (U.S. EPA, 2000b), Framework for Human Health Risk
Assessment to Inform Decision Making (U.S. EPA, 2014), Science and Decisions: Advancing
Risk Assessment (NRG, 2009) and other documents presented in Sections 1, 2, 3 and 4 of the
Appendix to demonstrate specific considerations relevant to the evaluation of beneficial uses.
2.1. Evaluation Scope
The first part of planning and scoping is to identify the questions to be answered by the
evaluation. The following text explores several key questions pertinent to all beneficial use
evaluations. While this discussion can help establish a strong foundation for an evaluation, it
is not intended to provide an exhaustive list of the potential questions or considerations that
may arise. |
Key Questions to Ask
The type and amount of information
1 What are the relevant stages of the lifecycle?
required to answer each question
m What is the chemical and physical composition of the
posed during planning and scoping
secondary material and beneficial use?
will vary depending on the beneficial
• What might be released to the environment?
use and the methods that will be relied
What happens to releases in the environment?
What exposures may result from releases?
What adverse impacts may result from exposures?
What are the applicable risk management criteria?
upon to carry out the evaluation. It is
unlikely that all of the information
needed to completely answer these
questions will be available at the start
of this stage. However, establishing a
list of questions upfront can help identify areas where additional information is needed as the
evaluation progresses. Additional resources that may be useful during planning and scoping
are presented in Section 1 of the Appendix.
2.1.1. What Are the Relevant Stages of the Lifecycle?
There are often multiple stages in the lifecycle of a beneficially used secondary material. Some
common stages include generation, transport, storage, use and/or end of life management.
However, not all materials will have the same lifecycle stages. For example, a secondary
material that does not require additional processing after generation to be beneficially used
may not have a distinct processing stage (e.g., fly ash used as a replacement for cement in
concrete). Similarly, a beneficial use that is left in place at the end of its useful life will not
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Beneficial Use Compendium
Section 2. Planning and Scoping
have a distinct disposal stage (e.g., spent foundry sand used as soil amendment). Environmental
releases may be possible at any stage of the lifecycle, based on how the material is handled and
the degree of contact with environmental media. The type and magnitude of releases can vary
among the stages as the composition of the material and the environmental setting change.
Therefore, it is important to define which stages of the lifecycle may result in environmental
releases that warrant consideration in the beneficial use evaluation. Figure 1 depicts examples
of common lifecycle stages.
Generation
Design &
Manufacturing
Storage
Beneficial
Use
Management at
End of Useful Life
Emissions to Air, Water, and Land
Figure 2. Common lifecycle stages for a secondary material.
2.1.2. What Is the Chemical and Physical Composition of the Secondary Material
and Beneficial Use?
The chemical and physical composition of both the generated secondary material and the final
beneficial use provide information on how these materials may interact with the environment
during the different stages of the lifecycle. It is important to be aware that the composition of
the beneficial use may not be exactly the same as that of the secondary material. While some
secondary materials can be beneficially used as generated, others require additional processing
prior to use. This processing can alter the chemical and physical composition of the materials.
The chemical composition of a beneficial use is all the different chemical constituents present
in that material, regardless of source. Some may be introduced by the secondary material or
by other raw materials. Some may be generated during the manufacturing process. Others may
arise after the beneficial use is put in place, through processes such as chemical degradation.
Although the secondary material may not be the source of every constituent, it may still
interact with the other raw materials, resulting in higher constituent releases than would
otherwise be expected. For example, the substitution of a virgin material with a secondary
material may alter the pH or the reduction-oxidation (redox) potential in the resulting
beneficial use, which might cause certain constituents to become more mobile. Therefore, it is
important to understand both the identity and amounts of each chemical constituent
associated with the beneficial use.
2-2
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Beneficial Use Compendium Section 2. Planning and Scoping
Consideration: Chemical Composition
• What are the raw materials used in the manufacturing process (e.g., ores, metals, acids, solvents)?
- Any chemicals present in the raw materials may be incorporated into the beneficial use.
— If raw materials are extracted directly from the ground, then any chemical constituents that occur
naturally in the environment may be present.
• How are the raw materials handled before incorporation into the beneficial use?
- Some processes, such as combustion, refinement or distillation, may act to reduce or concentrate
the chemical constituents present in the raw materials.
• What chemical reactions take place during the manufacturing process?
- Incomplete reactions or reactions with impurities may result in unplanned contaminants.
* Are high temperatures present at any point during the manufacturing process?
- High-temperature processes, such as combustion, may create new chemical constituents
(e.g., polycyclic aromatic hydrocarbons, dioxins/furans)
The physical composition of a beneficial use includes both its macroscopic and microscopic
structure. This structure influences the amount of contact between the external and internal
surface area of the beneficial use and the surrounding environmental media. On a macroscopic
scale, a beneficial use will typically be either a liquid or solid. If it is a solid, it may also be
monolithic or granular. On a microscopic scale, a monolithic solid may have internal pore
spaces of varying size and interconnectivity, while a granular solid may be composed of a range
of different particle sizes. However, this physical structure can change over time. A liquid may
evaporate, leaving behind previously dissolved solids. A monolithic solid may be worn away
into smaller pieces from chemical and/or physical erosion. Conversely, a monolithic solid may
increase in density over time, reducing the internal porosity. Failure to account for these and
other changes to the beneficial use may result in a mischaracterization of potential impacts to
human health and the environment.
2.1.3. What Might Be Released into the Environment?
A stressor is any agent that can result in abnormal, harmful or undesirable impacts to human
health or the environment. Stressors associated with the beneficial use of secondary materials
are typically chemical (e.g., arsenic, lead) or physical (e.g., particulate matter) in nature. When
environmental media come in contact with the beneficial use, stressors can be released. Water-
soluble stressors can leach into storm/ground/surface water that passes over the beneficial use,
while stressors with a sufficiently high vapor pressure can volatilize into the surrounding air.
Even when the beneficial use is a monolithic solid, water and air can pass through interstitial
pores or cracks and transport stressors into the surrounding environment. In some instances,
the beneficial use itself may be transported through the environment. For example, one that
is liquid can infiltrate into the ground or flow overland. One that is a granular solid, or one
that can erode into a granular solid, may be blown by the wind or washed away overland by
runoff.
2-3
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Beneficial Use Compendium Section 2. Planning and Scoping
Environmental media can play an active role in the release of stressors. These media can
contain a variable mixture of organic and inorganic compounds, as well as an array of microbial
life, which can interact with the beneficial use and accelerate releases by eroding the physical
matrix of the beneficial use or altering the mobility of stressors (e.g., through prevailing redox
conditions). Environmental media can also alter releases through changes in concentration,
temperature, pressure, and other gradients. In extreme cases, the medium itself may physically
erode the beneficial use through abrasion. Thus, it is important to understand not only which
stressors are available to be released into surrounding environmental media, but also how the
surrounding media may influence the release of these stressors.
Example: Effect of Sulfate Attack on Releases from Concrete
Sulfates [SO/2] are ubiquitous in the environment and can come in contact with concrete through several
routes that include contact with saltwater, acid rain, bacterial reduction of hydrogen sulfide gas, and the
raw materials incorporated into the concrete. Sulfates chemically react with the cement matrix of the
concrete, altering and weakening its physical structure. Sulfates inside the concrete may also crystalize,
placing additional internal stress on the concrete matrix. The net result is a loss of strength that can cause
cracks in the concrete (TxDOT, 2011). These cracks allow greater contact with environmental media and
may result in the increased releases of industrial materials incorporated in the concrete into the
surrounding environment.
The timeframe over which releases occur will depend on the amount of a beneficial use that
is applied in a given area, as well as how long the beneficial use remains at that location.
Releases may continue until the total available mass of stressors is depleted or the beneficial
use is removed. But, if the beneficial use is later replaced or reapplied, then releases may
continue beyond that point. The total mass of stressors present can be estimated from the
chemical composition and amount of a beneficial use applied in a location. However, it is
important to be aware that the presence of a stressor in the beneficial use does not mean that
it is available to be released into surrounding media (e.g., soluble). In some instances, some or
all of a stressor may be bound within the physical matrix of the beneficial use to such a degree
that no appreciable quantities can escape under standard environmental conditions. The extent
to which stressors are present and available to be released from a beneficial use can vary as a
result of heterogeneity of the raw materials and differences in design specifications. In the
absence of detailed information on the availability of a stressor, the assumption that the total
mass is available provides a protective, upper-bound on potential releases.
2.1.4. What Happens to Stressors Released into the Environment?
Once released into the environment, stressors may be transported between different media
and across great distances. During transport, the stressor levels in the environment will not
remain constant. Stressor levels may be diluted as the release mixes with surrounding
environmental media. Stressors may also become bound to media and unavailable for further
transport or effectively eliminated through chemical or biological degradation. The rates at
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which these and other fate and transport processes occur are governed by the properties of the
stressor, as well as the physical, chemical and biological characteristics of each medium.
Consideration: Transport Between Media
Stressors can partition between two environmental
media that come into contact. It is possible that a
single stressor will pass through multiple media
before reaching a downgradient receptor.
For example, a stressor released to ground water
may flow downgradient and discharge to surface
water, where it accumulates in the tissue of a fish
before that fish is caught and eaten by a fisher and
their family.
While stressor properties (e.g., degradation
rate) can often be approximated as constant
during transport, the properties of a media
(e.g., hydraulic conductivity) that stressors
migrate through can change markedly, both
spatially and temporally. Knowledge of the
different locations a beneficial use might be
applied will help to define the variability of
these properties for each medium. If the
beneficial use will be located within a
limited geographic area, then collection of site-specific environmental data may be feasible.
However, if the beneficial use will be located across a wide geographic area, then collection of
site-specific data will quickly increase in difficulty. Instead, the evaluation may rely on existing
regional or national data sources to help define media characteristics.
2.1.5. What Exposures May Result from Releases?
Exposures occur when a receptor comes in contact with a stressor. The various ways in which
a receptor can come in contact with a stressor are called exposure routes. The most common
exposure routes are ingestion, dermal contact and inhalation. A single receptor may be exposed
through one or more routes simultaneously or at different times. The magnitude, frequency
and duration of these exposures is influenced by the different physiological and behavioral
characteristics of individual receptors. These characteristics can vary widely among the entire
exposed population. Therefore, it
is important to carefully identify
the relevant types of receptors.
Consideration: Types of Exposure
Some relevant exposure routes may not be immediately
obvious. While many exposures result from direct intake of
environmental media, such as inhalation of ambient air, others
may result from indirect intake, such as ingestion of trace
amounts of soil that have adhered to skin or produce. Even
though the rate of these incidental exposures may be small,
they can still account for a non-negligible fraction of overall
exposures.
Receptors are typically divided
into two broad groups: human
and ecological. Human receptors
can be further subdivided based
on the location of exposure
(e.g., office, residence) and the
age of the receptor (e.g., adult,
child). Ecological receptors can be further subdivided based on taxonomic grouping
(e.g., mammal, fish, plant), its position in the food chain (e.g., primary or secondary tropic
level) and habitat (e.g., aquatic, terrestrial). These divisions can be used to identify any
sensitive subpopulations and/or life stages in order to define the relevant range of receptor
characteristics. The relevant receptors are not limited to those present on-site at the time the
beneficial use is first applied. Exposures may occur at some point in the future, after a release
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from the beneficial use has migrated some distance through the environment or after the local
land use has changed.
2.1.6. What Adverse Impacts May Result from Exposures?
Adverse impact is a broad term for any abnormal, harmful or undesirable change that results
from exposure to a stressor. The level of a stressor required to cause such a change and the
severity of that change are dependent on the stressor properties, the route and magnitude of
exposure, and the receptor characteristics. Because of the variable rates at which receptors are
exposed and react to stressors, it is rarely possible to predict the exact extent to which adverse
impacts will occur. Even when a receptor is exposed to high stressor levels, some adverse
impacts may not occur or become apparent until years after the initial exposure. As a result,
these adverse impacts are typically discussed based on the potential for occurrence. This
potential might be estimated indirectly (e.g., through comparison with screening benchmarks)
or directly (e.g., through the calculation of risks).
Adverse biological impacts to human health and ecological communities are typically divided
into two main categories: carcinogenic and noncarcinogenic effects. Carcinogenic effects are
those that result in the development of cancer. Noncarcinogenic effects are those that result
in outcomes other than cancer. Some stressors are known to cause both carcinogenic and
noncarcinogenic effects, depending on the route through which the receptor is exposed and
the magnitude of the exposure. However, not all adverse impacts result in direct harm to the
health of a living organism. Instead, an adverse impact may be an undesired change to the
environment, such as the discoloration of a water body, the presence of an unpleasant odor, or
the proliferation of a nuisance species. While these impacts may not result in direct harm, they
may lead to public complaints and economic damages.
2.1.7. What Are the Applicable Risk Management Criteria?
Risk management criteria are used to define a point below which a proposed beneficial use can
be concluded to not pose concerns to human health or the environment. These criteria may
incorporate a range of pertinent risk-based, political, social, economic, legal and technological
considerations. Some examples might be a risk level that result from exposures, a stressor level
in media to which receptors could be exposed, or a stressor level associated with a natural or
commercial product that would have otherwise been used. The absence of concentrations or
exposures above these criteria is not always the same as the total absence of risk. Thus, before
selecting criteria for use in a beneficial use evaluation, it is important to understand the
considerations that are built into each. Some address specific, sensitive segments of the
population that may or may not be relevant to the proposed beneficial use. Some are
recommendations developed by various organizations, while others represent legally
enforceable standards. However, all risk management criteria will be based on a level of
acceptable risk, which is a fundamental policy decision. Individuals or entities that conduct
beneficial use evaluations should engage with relevant regulatory organizations to ensure that
the criteria selected are consistent with relevant state beneficial use requirements.
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Section 2. Planning and Scoping
2.2. Conceptual Model
Preparation of the initial conceptual model is another aspect of planning and scoping. A
conceptual model incorporates all the data gathered in response to the questions posed during
planning and scoping into a graphical representation of the complete exposure pathways that
will be evaluated for the beneficial use. These pathways consist of the source of stressors
(i.e., the beneficial use), the routes through which released stressors can migrate through the
environment, and the receptors that can be exposed. Conceptual models are useful tools to
organize, visualize and communicate the scope of the evaluation. There is no standardized
format for conceptual models; they can vary widely in terms of both layout and level of detail.
A conceptual model provides general information on the major categories of stressors and
receptors. Depicting every single stressor and receptor combination would quickly become
unwieldly. Figure 3 shows some of the different approaches that can be used to communicate
the same information.
SOURCE
RELEASE
MECHANISM
MED|A
^
Road Base
EXPOSURE ROUTES
Direct Cont;
Fish Ingestion -
Direct Contact -
Ingestion of
Biota
RECEPTORS
Aquatic Ecological
tors
•> Adult/Child Fisher
Infiltration
Ground Water
Ground Water
Ingestion
Benthic Ecological
Receptors
Adult/Child Resident
- Direct Contact
-Ingestion of Biota
-Adult/Child Resident
-Adult/Child Fisher
- Aquatic and Benthic
Ecological Receptors
Figure 3. Two different approaches to depicting the same conceptual model.
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2.3. Analysis Plan
Development of an analysis plan is another important aspect of planning and scoping. This
plan identifies the general analytical steps that will be used to characterize the potential for
adverse impacts from the proposed beneficial use and the specific approaches that will be used
to implement these steps. For any given step, there may be multiple approaches available. The
primary aim of drafting an analysis plan at this phase of the evaluation is to identify the steps
and approaches that make the best use of available resources, to minimize the potential for
unforeseen setbacks, and to foster agreement when multiple parties are involved in scoping
the evaluation. Additional resources that may be useful during development of the analysis
plan are presented in Sections 2, 3 and 4 of the Appendix.
2.3.1. Analytical Steps and Approaches
If all of the data that will be relied upon in the beneficial use evaluation are available during
this phase, then careful review can reveal which analytical steps and approaches the data can
support. However, if no data collection has yet taken place, or if additional rounds of data
collection are anticipated, it can be more difficult to identify the most suitable methods. When
additional data are needed, a decision can be made to either review the literature for existing
data or to generate the necessary data. The benefit of generating new data is that it allows the
quality and quantity of data to be tailored to the specific needs of the evaluation. Yet the
planning, sampling and analysis necessary to generate new data can be resource intensive.
Therefore, this option can also be reserved until a later stage of the evaluation, if it is found
that data drawn from the literature are insufficient to reach well-substantiated conclusions.
The analysis plan is not static and may change as new information becomes available.
Because of the substantial variability in the types of secondary materials generated, the
potential beneficial uses for each material, and the amount and quality of data available to
characterize each, there is no single analysis plan structure best suited for every evaluation.
Therefore, the next phase of this document highlights several broad steps built around similar
analytical methods, as well as the considerations and potential pitfalls associated with each.
The methods discussed are broad so as to remain applicable to any beneficial use evaluation.
There are no limitations on which or how many different methods can be used within an
evaluation, so long as the application of each is rooted in sound science. The benefit of multiple
methods is the ability to systematically eliminate individual stressors or entire exposure
pathways that can be shown to pose no concern before investing in increasingly complex and
resource-intensive methods. However, there is the potential for these simpler methods to be
too general or too likely to overestimate the potential for adverse impacts to effectively
streamline an evaluation. It can be helpful to seek input from experts in the field of risk
assessment to identify which specific steps and approaches make the best use of available data.
2.3.2. Accounting for Uncertainty
Uncertainties are gaps in the understanding of a system and will exist to some degree in any
beneficial use evaluation. Uncertainty can bias results and lead to incorrect conclusions if it is
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not considered and accounted for during the evaluation. Therefore, it is important to identify
and, to the extent possible, mitigate the potential sources of uncertainty as the evaluation
progresses. The National Research Council has identified three main categories of uncertainty
(NRG, 2013):
• Variability and heterogeneity introduce uncertainty when the available data are not
sufficient to characterize the relevant properties of stressors, media, receptors and other
components of the conceptual model. Variability and heterogeneity are natural parts
of environmental systems and cannot be eliminated through further study. However,
the associated uncertainties can be minimized through collection of additional data to
better define the range and distribution of key variables.
• Models introduce uncertainty through the simplifying assumptions used to
approximate real-world conditions, processes and relationships. These assumptions are
necessary to allow solutions to mathematical equations and fill gaps in available
knowledge. However, the simplification of complex systems may misrepresent real-
world conditions to an unknown degree. The associated uncertainty can be minimized
by identifying the most suitable model and, where possible, replacing default
assumptions with data that are more representative of the proposed beneficial use.
• Limitations of the current scientific knowledge may introduce uncertainty through a
lack of consensus about, or a fundamental ignorance of, particular aspects of the system
under evaluation. This can be the most difficult type of uncertainty to identify and
address. Neither the collection nor the analysis of additional data is likely to reduce this
type of uncertainty before a decision must be made.
Both the direction and magnitude of the uncertainties are important. The direction of an
uncertainty is the tendency for that uncertainty to push a predicted value higher or lower than
the true value. The magnitude of an uncertainty is the extent to which that uncertainty may
cause the predicted value to deviate from the true value. It is often impossible to quantify both
the direction and magnitude of an uncertainty due to the very data limitations that cause the
uncertainty. Still, identifying potential sources of uncertainty upfront can inform the selection
of analytical steps and approaches that make the best use of available data. In addition,
knowledge of the different sources of uncertainty can focus any further data collection efforts
on areas that will provide the greatest returns.
2.4. Summary
Planning and scoping is the initial step of any beneficial use evaluation, conducted before the
start of any analysis. This step helps to avoid unforeseen setbacks and to build early consensus
when multiple parties are involved in the evaluation. Documentation of any conceptual
models or decision trees that are developed is encouraged to increase the clarity and
transparency of the evaluation. The subsequent sections of this document highlight individual
steps that can be used to characterize the potential for adverse impacts to human health and
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the environment, as well as the considerations and potential pitfalls associated with each.
Those individuals or entities who use the beneficial methodology are encouraged to become
familiar with all of the phases and analytical steps, as well as the specific considerations
associated with each, before deciding which to incorporate into a beneficial use evaluation.
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Phase II:
Impact Analysis
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Beneficial Use Compendium Section 3. Historical Evaluations
Section 3. Existing Evaluations
Existing evaluations consist of the identification, review and application of the findings made
in the available literature that are relevant to the beneficial use. This step can be separated into
three sequential stages. In the first stage, all potentially relevant evaluations of the specific
beneficial use are identified from the existing literature. In the second stage, the quality of the
data and analyses contained in these evaluations is reviewed to determine whether the findings
are of sufficient quality to draw conclusions about the beneficial use. In the third and final
stage, the findings determined to be of adequate quality are applied to the ongoing beneficial
use evaluation and used to determine which of the potential exposures warrant further
consideration through other analytical steps. This section builds on documents and tools
presented in Section 3 of the Appendix.
3.1. Identification Stage
Existing evaluations are those that present findings germane to the proposed beneficial use.
These existing evaluations may include previous beneficial use evaluations, peer-reviewed
studies or technical reports published by government agencies, academic institutions, trade
associations and other sources. The identification and systematic review of these existing
evaluations is the same as for any other type of literature search and can easily be conducted
in parallel with other data collection efforts.
There are many potential sources of existing evaluations and it is important not to prematurely
exclude any data source from consideration. Published journals and monographs can be
accessed through public libraries and online literature databases. Carefully selected search
terms can help to maximize search results. Other potential sources are technical reports
authored by public authorities, academic institutions, and non-governmental organizations,
such as trade associations and public interest groups. These technical reports may exist as grey
literature that are not publicly catalogued and may require contacting the authors to obtain a
copy. Literature reviews are a useful place to begin, as they can provide an overview of the
findings from multiple evaluations, identify trends and relationships among different
evaluations, or highlight sources of uncertainty or disagreement in the current science. At a
minimum, these literature reviews can provide a list of additional references that will facilitate
further data collection efforts.
A major hurdle to the identification of applicable existing evaluations is access. Even when an
evaluation has been located, it may not be available for free. Costs may range from relatively
small amounts for a single journal article to large sums for a single technical report. Even when
the cost of each individual evaluation is small, the cumulative costs of a literature search can
compound quickly. Unnecessary expenditure of funds can be minimized through a review of
publicly available abstracts. It is often possible to glean enough information from these
abstracts to determine whether an existing evaluation is germane to the proposed beneficial
in
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Section 3. Historical Evaluations
use. Yet, while it is possible to gauge the relevance of an evaluation based on abstracts alone,
it can be much more difficult to determine whether the quality of the data and analyses
contained in the existing evaluation are sufficient without reviewing the full documentation.
3.2. Review Stage
As each existing evaluation is identified, it is important to review the underlying data and
analyses to determine whether the reported findings are of adequate quality to form the basis
for conclusions about the beneficial use. The goal of this review is to ensure that the
uncertainties introduced through the use of these existing evaluations are not too great. Each
beneficial use evaluation will be able to tolerate different types and amounts of uncertainty
and still reach well-substantiated conclusions. For example, an evaluation that finds all
estimated exposures to be far below relevant benchmarks will be able to tolerate a greater
magnitude of uncertainty about the range of possible releases and exposures than an evaluation
with estimated exposures near benchmarks. One example might be the ability of an evaluation
to tolerate non-detects with high detection limits in the dataset. As a result, what constitutes
adequate data quality can vary and will require professional judgment. The following text
details the five data quality assessment factors that EPA considers when reviewing external
data sources (U.S. EPA, 2003a). Additional resources that may be helpful when considering
data quality are presented in Section 4 of the Appendix.
3.2.1. Applicability and Utility
Applicability and utility is the extent to which the findings of an existing evaluation are
relevant for the intended use. This means that the data, analyses and findings presented in the
existing evaluation support a similar set of conclusions when applied to the conceptual model
for the proposed beneficial use. Table 1 presents example questions that may be helpful to
consider when reviewing the applicability and utility of an existing evaluation.
Table 1. Considerations for Applicability and Utility
Does the existing evaluation
capture the current
properties of the beneficial
use?
It is important to ensure that the existing evaluation reflects the current
secondary material and proposed beneficial use. The properties of both may
change over time from unintended changes during use (e.g., erosion) or
intended changes to the processes by which the secondary material or
beneficial use are generated (e.g., updated pollution control technologies). In
addition, the beneficial use may be exposed to environmental conditions
different from those considered in the existing evaluation (e.g., annual rainfall)
or may be used differently (e.g., greater mass applied, greater percentage of
virgin materials replaced).
Are the findings applicable
to the beneficial use?
An existing evaluation may not have the same scope as the beneficial use
evaluation and certain aspects, such as the simplifying assumptions, may not
be the same between the two evaluations. If the beneficial use is shown to
pose no concern under a more stringent existing evaluation, then the findings
may still be applicable to the ongoing beneficial use evaluation. However, if
the existing evaluation is less stringent than agreed upon for the beneficial use
evaluation, then further analysis may be warranted.
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Section 3. Historical Evaluations
3.2.2. Clarity and Completeness
Clarity and completeness are the degree to which an existing evaluation transparently
documents its assumptions, analytical methods, quality assurance protocols and other key
information. An evaluation that is both clear and complete provides enough detail that an
outside party with access to the proper tools can replicate the analyses. Table 2 presents
example questions that may be helpful to consider when reviewing the clarity and
completeness of an existing evaluation.
Table 2. Considerations for Clarity and Completeness
Are all of the raw data
available for review?
Authors may choose to present only summary statistics in the publicly
available documents for any number of reasons, such as space limitations in
some scientific journals. However, it may still be possible to obtain the
underlying raw data by contacting the authors.
Are all key assumptions
and methods discussed in
the text?
Assumptions made in an existing evaluation may be valid in the context of that
evaluation, but may not hold true for the ongoing beneficial use evaluation.
Therefore, it is important to understand the analytical methods and key
assumptions that underpin the findings. A critical review of the documentation
for the existing evaluation is important because authors may not recognize or
explicitly discuss some assumptions implicit in the analyses conducted. In
addition, authors may rely on citations to other literature sources to detail more
common methods and assumptions.
3.2.3. Soundness
Soundness is the extent to which the methods employed by an existing evaluation are
reasonable and consistent with the intended application. This means that any methods used to
collect and measure data have demonstrated the technical ability to reliably and repeatedly
achieve desired levels of accuracy and precision, and that any methods used to analyze and
interpret data; such as equations, models and simplifying assumptions; are adequately justified
and based on accepted scientific principles. Table 3 presents example questions that may be
helpful to consider when reviewing the soundness of an existing evaluation.
Table 3. Considerations for Soundness
What quality assurance and
quality control (QA/QC) has
been conducted?
QA/QC is undertaken to demonstrate both the accuracy and the precision
of reported data. Proper QA/QC procedures provide confidence that
reported values are not the result of contamination or other artifacts
introduced during sample collection, preparation or analysis.
Are the detection limits used
sufficiently low?
Non-detect data do not necessarily indicate the absence of a stressor, only
that the levels fall somewhere between the specified detection limit and
zero. This information may still be useful. However, if there is the potential
for adverse impacts at levels below the detection limit, then reliance on
these non-detects may introduce an unacceptably large amount of
uncertainty into the ongoing beneficial use evaluation.
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Section 3. Historical Evaluations
3.2.4. Variability and Uncertainty
Variability and uncertainty is the extent to which the existing evaluations effectively
characterize how the data and assumptions relied upon, the laboratory methods used, and the
interpretation of results affect the evaluation. Effective characterization of the major sources
of variability and uncertainty provides greater confidence that there are no unaddressed data
gaps and that the basis for the reported findings is sound. Table 4 presents some questions that
may be helpful to consider when reviewing the variability and uncertainty of an existing
evaluation.
Table 4. Considerations for Variability and Uncertainty
Do the data capture the
environmental
conditions that could be
present at each relevant
stage of the lifecycle?
An existing evaluation may consider environmental conditions (e.g., extreme pH)
that cannot or will not exist outside a laboratory setting. These extreme conditions
may bound the range of theoretically possible releases. However, the highest
releases for every stressor do not always occur at one extreme (e.g., acidic).
Instead, higher releases may occur under more typical conditions (e.g., neutral) or
closer to the other extreme (e.g., basic). It is important to be aware of how the
different environmental conditions affect releases and whether the conditions
considered in the existing evaluation reflect the range relevant to the proposed
beneficial use.
3.2.5. Evaluation and Review
Evaluation and review is the extent to which an existing evaluation underwent independent
verification, validation and peer review. An independent review is one conducted by objective
(i.e., free of any real or perceived conflicts of interest) technical experts who were not
associated with the generation of the work under review, either directly or indirectly, through
substantial contribution or consultation during its development, and who do not stand to
benefit from the review. Independent reviews are intended to identify any errors or bias
present in how data are collected, handled or interpreted and to ensure that the findings are
accurate, reliable and unbiased. Table 5 presents example questions that may be helpful to
consider when reviewing the level of review that an existing evaluation has undergone.
Table 5. Considerations for Evaluation and Review
Have the models used
undergone independent
validation/verification?
Models and the underlying mathematical expressions are simplifications of
reality that are used to approximate real-world conditions, processes and
relationships. Model validation and verification determine whether the model
executes as intended and whether the model accurately represents the
environmental system. These reviews provide confidence that the model used
in the existing evaluation operates as intended.
Where did the funding
for this study originate?
Are reviewers free from
conflicts of interest?
In some cases, a generator, beneficial user or other party with a financial stake
may perform or commission an evaluation of beneficial uses. These evaluations
can be good sources of information, but there is the potential for either a real or
perceived conflict of interest. However, an independent external peer review of
these evaluations can help to alleviate some of these concerns.
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3.3. Application Stage
Once the existing evaluations have been identified and determined to be of adequate quality,
the findings can form the basis for conclusions about the proposed beneficial use. The findings
might support the conclusion that some or all of the potential exposures do not pose concern
and do not warrant further evaluation. Conversely, the findings might support the conclusion
that some or all of the potential exposures warrant further evaluation or are so great that there
is adequate confidence the beneficial use is inappropriate as proposed.
The aim of this step is to avoid additional, substantial analyses beyond those presented in the
existing evaluations. The use of data to conduct further analyses is addressed through other
steps discussed in this document. However, there are some instances where it may be possible
to discuss the findings of an existing evaluation in the context of some additional, supporting
information to allow conclusions about the beneficial use as a whole. Supporting information
is also drawn from the existing literature, and is used to reinforce the existing evaluation by
providing greater certainty that the findings are applicable to the full range of relevant
environmental conditions, exposure scenarios, or other sources of variability. If the findings
of an existing evaluation, together with any supporting information, are adequate to demonstrate
that the potential for adverse impacts is comparable to or lower than from an analogous
product, or at or below relevant regulatory and health-based benchmarks, then no further
evaluation would be necessary.
Example: Supporting Information
A hypothetical historical evaluation analyzed the potential release and migration of an organic chemical
from a secondary material placed outdoors on the ground surface. This evaluation found that leaching
from the secondary material results in exposures below levels of concern, based on relevant risk
management criteria. These findings alone would not be applicable to a beneficial use of the secondary
material that mixes it with other raw materials because the properties of the beneficial use may result in
higher releases than the secondary material alone.
A separate supporting study is identified that analyzed the leaching from the actual beneficial use. It is
determined that this study did not sufficiently capture the variability of the beneficial use enough to stand
as the sole basis for conclusions. However, the study found that leaching from the beneficial use is
consistently lower than from the secondary material by itself. When considered in the context of the
supporting study, the findings of the historical evaluation may be sufficient to eliminate leaching of this
chemical from further consideration, assuming that there are no confounding factors that warrant further
consideration, such as the potential for releases from the beneficial use to increase over time as it ages.
3.4. Potential Sources of Uncertainty
Because this step relies on findings drawn from existing evaluations, it also introduces all of
the sources of uncertainty associated with those findings into the beneficial use evaluation.
While supporting information can help to minimize these uncertainties, they may also contain
and contribute additional sources of uncertainty. Documentation of the magnitude and
ITS
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Beneficial Use Compendium Section 3. Historical Evaluations
direction of the major sources of uncertainty in the existing evaluations can help demonstrate
that reliance on these findings does not introduce an unacceptable amount of uncertainty into
the beneficial use evaluation.
3.5. Summary
The benefit of reviewing existing evaluations is the potential to save resources by preventing
a duplication of effort. This step can be especially useful when a literature search has already
been planned as part of data collection efforts. If existing evaluations are identified that are of
adequate quality and demonstrate that the potential for adverse impacts from the proposed
beneficial use is below levels of concern, based on the selected risk management criteria, then
no further evaluation is warranted for that those specific releases or exposures. However, if
after review and application of all identified existing evaluations, there remain exposures that
require further consideration, then the data from these existing evaluations can be assembled
with those from other literature sources for use in subsequent analytical steps.
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Beneficial Use Compendium
Section 4. Comparison with Analogous Product
This step is a comparison of the beneficial use to a product already available on the market that
the beneficial use replaces (an "analogous product"). The secondary material substitutes for
some or all of the virgin materials found in the analogous products to create the beneficial use.
A single beneficial use may be able to substitute for more than one analogous product. The
purpose of this comparison is to determine whether the potential for adverse impacts to human
health and the environment from the beneficial use is comparable to or lower than from an
analogous product. This section discusses some of the considerations involved in the design
and implementation of these comparisons. This section builds on documents and tools
presented in Section 5 of the Appendix.
4.1. Considerations when Planning the Comparison
The industrial processes that generate secondary materials can introduce chemical constituents
and other stressors that are not found in any of the analogous products. As a result, there is the
potential that stressors in a beneficial use are wholly absent from all analogous products. When
the secondary material introduces stressors into the beneficial use that are not found in any
analogous product, this would be sufficient information to demonstrate that the beneficial use
is not comparable and that further evaluation for these stressors is warranted. Conversely, if
there are stressors associated with the analogous product that are wholly absent from the
beneficial use, then this is sufficient information to demonstrate that exposures to these
stressors would be lower with the beneficial use and do not warrant further comparison.
This comparison assumes the same receptors will be present, regardless of whether a beneficial
use or an analogous product is selected, and that the characteristics, behavior, and sensitivity
of these receptors are unchanged. Thus, any differences in exposures and subsequent adverse
impacts are driven only by changes in the stressor levels present in the environmental media.
A direct comparison of stressor levels at the point of exposure may involve some amount of
fate and transport modeling if field measurements are not available, which can greatly increase
the complexity of this step. However, it is often possible to use a surrogate in place of measured
stressor levels to reduce the computational burden. For the purposes of this step, a surrogate is
data on one variable (e.g., constituent release rate) that can be used to reliably approximate the
magnitude of another (e.g., stressor levels at point of exposure) and, as a result, can substitute
for the other in the comparison. It is important that a clear and consistent proportional
relationship can be demonstrated between these two variables. The stronger the relationship,
the greater confidence that comparison results are accurate.
One potential surrogate is the rate at which stressors are released into environmental media.
Because many stressors are released in trace concentrations, it can often be assumed that
surrounding environmental conditions will dictate the fate and transport of these constituents,
regardless of the source. The same constituent released at the same rate would be anticipated
to result in the same stressor levels in downgradient environmental media. However, this
assumption may not be valid when a beneficial use markedly changes the ambient pH, ionic
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strength, or other environmental conditions that could affect fate and transport. Such a
scenario is most likely to occur when a fine, granular beneficial use is applied in large quantities
relative to the surrounding environmental media.
Another possible surrogate is the bulk concentration of stressors, if it can be shown that both
releases and resulting stressor levels at the point of exposure are directly and consistently
proportional to these concentrations. This is easiest to demonstrate when receptors are exposed
directly to the beneficial use. However, this assumption may not be valid when there are
multiple factors that control the release rate. For example, changes to the level of organic
carbon, soluble salts, and other chemical components (some of which may not be identified as
potential stressors) may inhibit or facilitate the release of stressors in ways that cannot be
predicted based solely on bulk concentration. Changes to the physical composition can also
affect releases by altering the size and connectivity of internal pore spaces that allow stressors
to escape into surrounding media. These changes can result in different release rates, even
when bulk concentrations are identical.
Example: Surrogates
A hypothetical secondary material is proposed for use as generated. The secondary material is a fine
powder that can be beneficially used by mixing small amounts with soils to improve structure and promote
drainage. The analogous product it replaces is a virgin material of similar composition that must be
transported from a mine located a considerable distance away. There are multiple inorganic chemical
constituents that are known to be present in both the beneficial use and the analogous product.
For exposures through direct ingestion of the beneficial use or analogous product that are mixed with the
soil, the bulk concentration of chemical constituents might be used as a surrogate. Because the stressors
are directly ingested, the concentration at the point of exposure is directly proportional to the bulk
concentration in the beneficial use and analogous product. However, such a comparison presumes that
the bioavailability of stressors within the beneficial use is comparable to those in the analogous product.
For exposures through ingestion of impacted groundwater, bulk concentration is often a poor indicator of
actual release rates and, thus, a poor surrogate for stressor levels at the point of exposure (U.S. EPA,
2009). However, it may be possible to use measured release rates instead. Because both the beneficial
use and analogous product are used in small amounts relative to the surrounding soil, and because all of
the constituents are released in trace levels, it can often be assumed that the chemical constituents
released behave similarly once mixed with environmental media where ambient conditions dictate fate
and transport.
The secondary material may be only one of several raw materials used in the manufacture of
a beneficial use. The mixing of these raw materials can cause changes to the physical or
chemical composition of the materials and result in substantially different releases and
resulting stressor levels in downgradient environmental media than would be predicted based
on knowledge of the individual raw materials. If it can be shown that neither the secondary
material nor the replaced virgin material interact with the other raw materials in a way that
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would change either the physical or chemical composition of these or other raw materials, it
may be possible to directly compare these two raw materials. Otherwise, it is better to compare
the final beneficial use and analogous product, rather than any individual raw material.
However, in such a comparison, it is important to account for the natural variability of each
raw material to ensure that the effects of substituting the secondary material are not obscured
by the variability of other raw materials.
Example: Cement vs Aggregate in Concrete
The portland cement used in standard concrete mixes undergoes extremely complex chemical reactions
when mixed with water, transforming it from a granular powder into a monolithic solid with a complex
matrix of internal pores. The size and interconnectivity of these pores influences the rate that stressors
can be released from inside the concrete. Substituting a secondary material for some or all of the cement
can alter the density of the concrete by changing the size and connectivity of the pores. Because of the
changes to the chemical and physical composition of the raw cementitious materials, it is unlikely that a
direct comparison of the raw materials will provide an accurate estimate of the comparability of the
beneficial use and analogous product.
The large stone aggregate used in standard concrete mixes is effectively inert and does not react with
the cementitious matrix that surrounds it. If the secondary material that replaces this aggregate is also
inert and does not result in changes to the physical composition, such as the size of internal pores, then
it may be reasonable to compare the secondary material directly to the aggregate it replaces under the
environmental conditions relevant to the concrete matrix. Releases from the two materials into the internal
pores would be subjected to the same conditions before escaping into surrounding environmental media.
4.2. Considerations when Conducting the Comparison
Once the exposure pathways and any relevant surrogates that will be compared have been
identified, a review of the available data will help determine the comparison approaches that
are best suited for the beneficial use evaluation. During this review, it is important to identify
the different sources of variability within the available dataset to ensure that these sources do
not obscure actual differences or, conversely, cause the appearance of differences that do not
exist. There may be several sources of variability beyond the natural heterogeneity of
individual raw materials incorporated into the beneficial use and analogous product. Two
common examples are differences in the design of the beneficial use and analogous product
and differences in sample measurement:
• Variability in design arises when the beneficial use and analogous product do not have a
fixed design specifications. In these cases, varying amounts of each raw material are used
to meet the specific needs of a project. Altering the ratio of raw materials directly affects
both the chemical and physical composition of the beneficial use and analogous product,
which, in turn, can alter the magnitude of releases and the resulting stressor levels in
downgradient environmental media.
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• Variability in sample measurement arises when there are differences in how samples are
collected and analyzed. One common example is differences in the laboratory conditions
under which samples are analyzed. These conditions may be specified by the test methods
(e.g., pH) to mimic environmental conditions that may be present in the field or may
simply reflect the ambient laboratory conditions at the time the tests are performed
(e.g., temperature).
When data are compiled from the literature, there is a greater chance for these types of
variability to be present and go unrecognized in the resulting dataset. If a particular source of
variability is not the focus of a study, it may not be controlled for in the experimental design
or even discussed in the text. This information can sometimes be reliably inferred from
information reported or obtained by contacting the authors. But, if key information is
unknown, the data may introduce an unacceptable amount of uncertainty into the beneficial
use evaluation. Some ways that these sources of variability might be controlled for is ensuring
the full range of variability is equally well represented or by subdividing the samples into
related categories for separate comparisons.
Example: Variability in Leachate Data as a Function of pH
Multiple leaching tests have been developed by EPA and other organizations to address different
environmental conditions (more detail provided in Section 3 of Appendix A). If the comparison relies on
data drawn from the existing literature, it is likely that the available dataset will contain samples collected
with more than one of these leaching tests. Some of these tests specify the initial pH of the sample, while
others specify the final equilibrium pH. This can result in an uneven distribution of data over the entire pH
scale, only a portion of which may be relevant to the beneficial use evaluation. Data within the relevant
pH range may be clustered around a single pH value, resulting in disproportionate representation of this
pH in a comparison of the full dataset. If there is not even representation over the relevant pH range, it
may still be possible to group data into smaller pH brackets and compare these brackets. However, if
data are too sparse to conduct a comparison over part of the relevant pH range, it may not be appropriate
to draw final conclusions because the leaching behavior of different materials can differ markedly with
changes in pH.
Whether comparing stressor levels at the point of exposure or some surrogate, it is critical that
comparisons consider the entire distribution of potential values, rather than individual data
points. This ensures that both the magnitude and frequency of possible values are reflected in
the comparison. While an analogous dataset may contain one or a few data points that are
higher than any in the beneficial use dataset, such a limited comparison would not provide
enough context for these data points. These high values may be valid measurements, but may
also be statistical outliers within the larger dataset. And while this may indicate that higher
exposures could result from the analogous product, the beneficial use will not always substitute
for this relatively small subset of the analogous product. Thus, there remains the possibility
that the beneficial use will result in higher exposures in a majority of cases. A comparison of
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full distributions, including any extreme values that are valid data, provides a greater
confidence in the final conclusion whether the proposed beneficial use and analogous product
are comparable or not.
The most suitable methods for comparing data will depend in part on the magnitude of any
differences that exist between the distributions for the beneficial use and analogous product.
When differences are so great that there is little or no overlap between distributions, then a
simple graphical or tabular presentation of the distributions or relevant summary statistics may
suffice to demonstrate that differences exist. But, as the extent of overlap increases, more
sophisticated methods may be necessary to demonstrate whether apparent differences in the
available data reflect two separate distributions. Statistical tests are one of the most common
and powerful methods available to compare distributions. A great deal has previously been
written about the use of statistical tests to compare constituent concentrations in
environmental media (U.S. EPA 1974; 2013). Additional resources that may aid in the selection
and application of statistical tests and other methods are presented in Section 5 of the
Appendix.
4.3. Potential Sources of Uncertainties
Some uncertainty may be introduced into the evaluation because the comparison provides an
indirect estimate of the potential for adverse impacts from the beneficial use, and only
demonstrates whether this potential is comparable to or lower than that from the analogous
product. The analogous product selected for comparison acts as the risk management criteria
in this step. It is intended to represent an alternative scenario that is not anticipated to pose
concerns to human health or the environment. This presumption can often made because
analogous products are composed of virgin materials, have broad public acceptance, and
already have limitations placed on appropriate use as a result of years on the market. Yet, the
analogous product is later found to be inappropriate for a particular use, this may warrant a
reevaluation of any stressors eliminated through the comparison to determine whether the
beneficial use poses similar concerns.
Comparisons can be complicated by the fact that a beneficial use is not always applied in the
same way as the analogous product it replaces. For example, the advantage of a beneficial use
may be cost savings from smaller or less frequent applications than the analogous product. In
this example, the beneficial use might result in reduced releases to the soil, even when the
bulk stressor concentrations in the beneficial use are somewhat higher. It can be difficult to
integrate this additional source of variability into the comparison because, among other things,
it requires information on the range of application rates for both the beneficial use and the
analogous product. Actual use rates can be influenced by economic considerations, public
perception, and other factors that make precise estimates difficult and add further uncertainty
into the comparison. In this specific example, where the analogous product is used at a higher
quantity or frequency, it may still be possible to compare it with the beneficial use under the
assumption that both are used in the same way. Because this assumption overestimates the
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mass loading from the beneficial use, there will be greater confidence that these results are
protective if the comparison finds a lower potential for adverse impacts from the beneficial
use.
Regardless of the level of sophistication, quantitative comparisons will only be as reliable as
the available data allow. The presence of natural heterogeneity among and within samples,
matrix interference, high detection limits, and other sources of uncertainty can obscure the
true distributions and result in erroneous conclusions when the magnitude of uncertainties are
greater than the actual differences. Some sources of uncertainty, such as natural heterogeneity,
might be reduced through the collection of additional data. Yet others, such as the sensitivity
of available laboratory equipment, are unlikely to be resolved in a timeframe relevant to the
beneficial use evaluation. One way to mitigate these remaining uncertainties is to provide
supplementary information to corroborate the results of the initial comparison. Some examples
might include quantitative comparison of additional surrogates or qualitative discussion drawn
from the literature about stressor behavior under similar environmental conditions. Although
there are likely to be uncertainties associated with the supplementary sources of information,
the more evidence that can be provided to support the initial comparison, the more confidence
there will be in the results.
4.4. Summary
The purpose of this step is to determine whether the potential for adverse impacts to human
health and the environment from the proposed beneficial use is comparable to or lower than
from an analogous product. The substitution of a secondary material for a virgin material can
change the chemical and physical composition of the original analogous product in a number
of ways that can affect releases and subsequent exposures. It is critical that these and other
differences are identified and accounted for to ensure that the comparisons are valid for the
range of relevant circumstances. If the potential for exposures from the beneficial use that are
higher than from the analogous product, or unique to the beneficial use, then these additional
exposures warrant further evaluation in another analytical step.
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Sections. Screening Analysis
Screening analysis is a streamlined step that minimizes the amount of data and computation
required to reach well-substantiated conclusions. A screening can be conducted in several
ways, but the type and amount of available data will often dictate which approaches are most
suitable. Many of these screening methods aim to reduce the complexity of the modeled system
by using a combination of high-end data and simplifying assumptions, which result in
exposure estimates that are anywhere from a reasonable upper bound to unrealistically
extreme. If an exposure is found to be below levels of concern based on these methods, it can
be eliminated from further consideration with a high degree of confidence. This section
discusses the selection of screening benchmarks and some methods available to conduct a
screening. This section builds on documents and tools presented in Sections 6, 7 and 8 of the
Appendix.
5.1. Selection of Screening Benchmarks
A screening benchmark is a discrete value, typically a concentration in environmental media
(e.g., soil, ground water), set at a level below which exposures are not anticipated to pose
concern. These benchmarks are compared with high-end stressor levels that may occur in
environmental media to identify individual stressors or entire exposure pathways that do not
warrant further evaluation. However, given that the exposures estimated in the screening are
biased high, an exceedance of screening benchmarks at this step does not necessarily mean
that the beneficial use poses concern, only that further evaluation may be warranted.
The specific screening benchmarks relevant to a particular beneficial use evaluation will be
determined by the relevant stressors, exposure pathways and receptors. Relevant screening
benchmarks may have already been developed by federal, state and non-governmental
organizations. If an evaluation relies on these existing benchmarks, it is important to consider
how well each aligns with the conceptual model. Existing screening benchmarks may also
consider technological, economic and other factors (e.g., background concentrations) that are
not relevant to the ongoing beneficial use evaluation. Even if a benchmark does not perfectly
align with the conceptual model, it may still be useful. A screening benchmark that differs
from the conceptual model (e.g., based on sensitive receptors that are not present) might still
be useful if it can be used to demonstrate that an exposure does not pose concern for the
receptors that are present.
Alternatively, evaluation-specific benchmarks can be derived. This allows the benchmarks to
incorporate a set of risk management criteria or to capture considerations specific to that
evaluation. The development of benchmarks requires integration of information on the
stressors released, the environmental media impacted, the receptors exposed and the risk
management criteria selected. Table 6 presents a discussion of some potentially relevant
considerations. More information on how to calculate screening benchmarks, as well as links
to some existing benchmarks, is presented in Section 6 of the Appendix.
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Table 6. Considerations for Screening Benchmarks
Dose-
Response
Relationship
These relationships describe the likelihood and severity of health effects that may result from
exposure to a stressor ("the response") as a function of the magnitude and route of exposure
("the dose"), and are developed through the analysis of data from the scientific literature. The
shape of these relationships (e.g., linear) depends on the properties of the stressor, the type of
response that may occur (e.g., tumor, incidence of disease), and the susceptibility of the
exposed receptor (U.S. EPA, 1989). Screening benchmarks rely on a point estimate of these
relationships, expressed as a single toxicity value, to capture the potential for health effects.
Further information can be found in Section 7 of the Appendix.
Exposure
Factors
Exposure factors are the physiological, behavioral and sociological attributes of a receptor that
determine the magnitude of potential exposures. Relevant examples might include age, body
weight, ingestion rate of water or produce, and life expectancy. For each factor, there can be a
great deal of variability among the individuals in a population (U.S. EPA, 2011). Screening
benchmarks rely on a point estimate of these factors, often specific to a sensitive subpopulation
(e.g., children), to capture the magnitude of potential exposures. Further information can be
found in Section 8 of the Appendix.
Exposure
Duration
Exposure duration is the amount of time that a receptor is exposed to a stressor. Acute values
are developed for exposures that occur over a short period of time. Chronic values are
developed for prolonged or repeated exposures, which can last for many years (U.S. EPA,
2011). Other values may be developed for intermediate (i.e., subchronic) lengths of time.
Screening benchmarks generally focus on chronic exposures because associated health
effects often occur at lower exposure levels. However, it is important to be aware that some
acute health effects, such as developmental toxicity, can occur at even lower levels. Further
information can be found in Section 8 of the Appendix.
Risk
Management
Criteria
Screening benchmarks typically represent high-end (e.g., reasonable maximum) or bounding
(e.g., worst-case) exposures, which are higher than those expected to occur for the majority of
the population. The decision of how extreme to make these values represents a risk
management decision. The use of stressor levels and screening benchmarks in this step that
approach a worst-case scenario or even more extreme values may provide greater confidence
in the decision to remove stressors from further evaluation, but it can also negate the
usefulness of the screening by causing the appearance that all stressors pose concern.
There are instances where a single benchmark has been developed for a group of structurally
similar stressors (e.g., PCB toxicity equivalence factors) or for cumulative exposures across
multiple media (e.g., blood lead levels), but these are uncommon. As a result, a beneficial use
evaluation is likely to need multiple screening benchmarks to address the different stressors
and exposure routes contained in the conceptual model. It is generally not necessary to identify
screening benchmarks for every single receptor that may be exposed, as benchmarks developed
for the highly exposed individuals (HEIs) within a population will also be protective of other
individuals with lower exposures. Yet it is important to be aware that the HEI may not be the
same for all exposure pathways.
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For some stressors, there may be no screening benchmarks available and insufficient data to
allow the calculation of values. This is often due to insufficient data on the dose-response
relationship for a stressor, as other data gaps are easier to fill with generic, protective
assumptions. The absence of this type of data does not necessarily mean that there is no
potential for adverse impacts. In the absence of quantitative benchmarks for comparison, a
qualitative discussion of these stressors can still be provided. Information such as the tendency
of a chemical stressor to bioaccumulate, the stressor fate and transport, or the behavior and
toxicity of similar stressors might be drawn upon to better characterize the potential for
adverse impacts. However, even when a suitable surrogate is available, there will be some
uncertainty associated with physical and chemical data that cannot be quantified.
5.2. Comparison at Point of Release
A comparison of stressor concentrations at the point of release to screening benchmarks
assumes negligible dilution or attenuation occurs after release into the environment in order
to capture the highest theoretically possible exposures. For some exposure pathways, such as
ingestion of ground water, this assumption may greatly overestimate potential exposures. For
other exposure pathways, such a direct hand-to-mouth ingestion of the beneficial use, this
assumption may be more realistic. If exposures at the point of release are found to be below all
levels of concern as defined by the selected screening benchmarks, then no further evaluation
is warranted for that particular exposure route. However, when employing these methods, it
is important to be aware that some stressors may not be present at the point of release. Some
may be formed as the result of complexation, transformation or degradation processes and
occur at higher levels downgradient from the beneficial use (e.g., transformation of elemental
mercury into methyl-mercury; U.S. EPA, 1997b). Therefore, consideration of exposures
beyond the point of release may still be warranted.
The available data on releases may be reported as a rate, rather than a concentration. In these
cases, some additional calculation and potentially some additional data will be needed to
convert these rates into concentrations in environmental media before a comparison to
screening benchmarks is possible. For releases that can be approximated as constant over time,
assumption of steady state conditions may allow a relatively straightforward calculation.
Steady state is the point at which stressor levels released from the beneficial use equilibrate
with a defined volume of media in contact with the beneficial use, and the stressor levels
within that volume are effectively constant. When there are appreciable losses of the stressor
from the media, whether through stressor degradation, transport of impacted media away from
the beneficial use, or other processes that affect equilibrium, steady state can be calculated
through a mass balance of the stressor levels released into and lost from the media. When losses
from the media are minimal compared to releases, steady state can be defined by gradients
present between the beneficial use and the media (e.g., concentration, pressure). The
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Section 5. Screening Analysis
calculated steady state levels represent the highest sustained concentrations a receptor could
be exposed to and provide an upper bound on potential chronic exposures.
Example: Steady State
A hypothetical beneficial use is proposed as a building material, but it has the potential to emit volatile
chemicals into the air at low rates. Habitable structures are generally required to maintain a certain air
exchange rate with the outdoors, resulting in non-negligible losses from the transport of air between the
building interior and the outdoors. Thus, at a minimum, calculation of a steady state concentration will
require a balance between the emission of volatiles into the building and the loss of volatiles along with
air to the outdoors. Losses to the outdoors will not be constant, as the air exchange rate will fluctuate
based on temperature, barometric pressure, the presence of open doors/windows, and other factors.
But a single low-end value can be selected under the assumption that environmental conditions present
will minimize air exchange and that all doors/windows remain closed. In addition to air exchange, other
considerations may be important on a case-by-case basis, including chemical degradation and
adsorption/desorption from household surfaces (e.g., carpet, furniture). An example of a mass balance
for stressors in indoor air is shown in Figure 5.
Air flow out .*.
Outdoor ambient
air concentration
Airflow in
Figure 4. Mass balance of stressors in a home
5.3. Comparison at Point of Exposure
Often, stressors will migrate some distance through the environment before reaching a
receptor. During transport, stressor levels can be diminished through dilution, dispersion,
degradation, precipitation and other processes. They may also be increased through the
complexation, transformation or degradation of other stressors. Comparisons at the point of
exposure account for the change in stressor concentrations that result from these processes
before estimation of exposure levels. These approaches are more realistic than a comparison at
the point of release, but are still intended to remain protective through the use of data and
assumptions that bias the calculated exposures higher than are likely to occur during use.
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The potential magnitude of reduction in stressor levels can be quickly estimated by applying
previously developed dilution and attenuation factors (DAFs), which are ratios of initial
stressor levels at the point of release and final stressor levels at the point of exposure. The
development of these ratios can require a great deal of complex modeling. Therefore, at this
stage of the evaluation, the aim is to identify existing DAFs that provide an effective bound on
the environmental conditions relevant to the beneficial use. Because DAFs are dependent on
the properties of the stressor and a given medium, rather than the stressor source, these ratios
may still be applicable to a beneficial use evaluation even when the source of the stressors is
different. However, stressors can interact with media in ways that are non-linear with respect
to concentration, temperature and other factors. In addition, interactions between different
stressors have the potential to affect fate and transport. As a result, it is important to understand
and discuss the basis for a DAF to demonstrate that the magnitude of reduction identified is
applicable to the beneficial use evaluation.
Example: Ground Water Dilution-Attenuation Factors from New Jersey
In 2012, the New Jersey Department of Environmental Protection (NJDEP) established a committee to
review and update guidance for developing site-specific soil remediation standards based on potential
impacts to ground water. Drawing from previous EPA guidance (U.S. EPA, 1996), the NJDEP identified
a single, default DAF for all stressors and discusses how to modify this default to account for site-specific
considerations. Although this guidance was originally developed for cleanups, the DAFs may also be
relevant to beneficial uses mixed with soil or otherwise applied to the land. Further information on this
DAF can be found in Development of a Dilution-Attenuation Factor for the Impact to Ground Water
Pathway (NJDEP, 2Q13).
Dilution and attenuation can also be estimated through fate and transport models, which
combine mathematical equations and user-provided data to estimate the difference in stressor
levels present at the point of release and point of exposure. These models vary widely in
complexity, but some have been developed specifically for screening-level evaluations. These
screening models deliberately reduce the complexity of the modeled system with simplifying
assumptions in order to provide a protective estimate of exposures. Consequently, screening
models typically require fewer user-defined inputs than other models. The inputs required by
specific screening models will vary, but are typically point estimates of stressor concentrations
at the point of release and some of the more-sensitive environmental variables. As a result,
screening models require a risk management decision on how to calculate these point values.
In some instances, models may provide default inputs for some variables that a beneficial use
evaluation may choose to rely on, provided these defaults can be shown to provide an upper
bound for the scenario under evaluation. Additional resources that may be helpful during
selection of screening and other models are presented in Section 8 of the Appendix.
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5.4. Potential Sources of Uncertainty
The screening analysis can be relatively quick to carry out because it replaces variability with
point estimates and fills data gaps with simplifying assumptions. As a result, quantitative
estimates of exposure levels and the screening benchmarks used for comparison will contain
high levels of uncertainty. The magnitude of these uncertainties may not be quantifiable, but
the direction should, on the whole, be toward an overestimation of potential exposures. This
results in an analysis that is biased toward the retention of some stressors that do not actually
pose concern. Yet this approach also affords a high degree of confidence in the decision to
screen out stressors found to be below screening benchmarks.
Each different screening approach provides a single, quantitative estimate of potential stressor
levels in a medium that is then compared to individual screening benchmarks. This comparison
requires collapsing the variability associated with stressor release rates, fate and transport
mechanics, and receptor characteristics down to point values. This is not the same as
eliminating or completely ignoring variability, because variability is an inherent part of natural
systems that can never be eliminated. The selection of point values requires an understanding
of variability to determine what constitutes a high-end value. To ensure that a screening
remains protective of sensitive receptors within the population, enough variables are set to a
high-end value to ensure that the screening does not underestimate the potential for adverse
impacts. A beneficial use evaluation may set every last variable to a high-end value; however,
this may reduce the efficacy of the screening analysis and retain more stressors for further
evaluation than is necessary. Reducing the selected value for some variables does not
necessarily make a screening less protective, as the calculated exposures might still reflect or
exceed the upper bound of realistic exposures. Yet, without incorporation of variability into
the evaluation, it is not possible to know where the calculated exposures fall relative to the
true distribution of possible exposures.
Consideration: Selecting High-End Values
In instances where both the range and distribution of a variable are well known, either a maximum or an
upper percentile value might be used, based on the needs of the particular evaluation. Where the
distribution is poorly characterized, a maximum value may still be useful. However, as the amount of data
decreases there will be greater uncertainty that the maximum reported value falls near the true maximum,
or is even representative of the high-end for that variable. Depending on the amount of available data, it
may still be possible to use statistical analysis to calculate an upper confidence limit for data (U.S. EPA,
2002). Even in the worst-case scenario where there is great uncertainty surrounding both the range and
distribution of data, it may still be possible to use a bounding estimate that is known to fall outside the true
range, so long as justification is provided for the selected value. There is no "bright line" available to
determine which approach for deriving a point value is best suited for a given evaluation. Therefore,
professional judgment is critical.
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5.5. Summary
A number of approaches are available to implement a screening analysis. Depending on the
needs of an evaluation, the use of more than one step may be helpful. These screening methods
typically incorporate uncertainty into the evaluation in a precautionary manner, and are
neither designed nor intended to provide a precise quantification of exposures or the potential
for adverse impacts. The benefit of this step is the reduced need for more resource-intensive
analytical methods. While this step may provide sufficient information to prioritize resources
and rule out exposures for further evaluation, the calculated exposure levels may not be
meaningful beyond the limited context of the screening. Therefore, any exposures found to be
above screening levels should be retained for further evaluation. However, if more refined
analyses cannot be performed and other sources of information are not available, this may
indicate that uncertainties are too great to demonstrate whether the beneficial use is
appropriate as proposed.
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Section 6. Risk Modeling
Risk modeling consists of a refined, quantitative and qualitative characterization of the
potential for adverse impacts from the proposed beneficial use. This is accomplished with more
realistic data and models that are used to calculate risks. These calculated risks represent
quantitative estimates of the probability that adverse impacts will occur. The objective of this
step is to reduce the source of uncertainty remaining in the evaluation enough to allow
conclusions about potential risks associated with the proposed beneficial use. Simply
calculating risks for the exposures estimated from screening-level analyses will not provide
much additional information for decision-makers. Because of the more rigorous data
requirements, risk modeling is the most complex analytical step discussed in this document.
As a result, it may be worthwhile to first review the results obtained from previous steps to
determine whether they can be further refined. The remainder of this section details some
considerations involved in identifying the most suitable model or models. This section builds
on documents and tools presented in Sections 9 and 10 of the Appendix.
6.1. Model Selection
There are numerous models available to address different components of an exposure pathway.
Individual models may quantify stressor releases ("source term models"), transport of stressors
in environmental media ("fate and transport models"), receptor uptake ("exposure models"),
likelihood and severity of health effects ("dose-response models"), or a combination thereof.
The following text focuses on the selection of fate and transport models because these are the
type most likely to be encountered as part of beneficial use evaluations.
All models have strengths and limitations, so it is important to weigh the pros and cons of each
carefully. The most complex models will not always be those best suited for an evaluation.
Complex models require increasingly precise datasets, which may not be feasible to collect as
the geographic scale of the evaluation increases. And running models with insufficient data
can actually result in greater uncertainty associated with model results. Even when enough
data are available, the added specificity in these models may not add value to the evaluation
when less complex models are sufficient to reach a definitive conclusion. Conversely, use of
less complex models will involve greater reliance on simplifying assumptions and high-end
estimates to ensure that the evaluation remains protective. Some evaluations may not be able
to tolerate this additional level of uncertainty and still be able to reach final conclusions. Given
these complexities, it may be useful to consult experts knowledgeable in the fields of risk
assessment and environmental fate and transport modeling during the selection process.
Further discussion of some considerations involved in model selection can be found in Risk-
Based Corrective Action Fate and Transport Models: Compendium and Selection Guidance
(ASTM, 1998); specific state agencies may have more tailored guidance available. Examples of
other readily available fate and transport models are presented in Section 9 of the Appendix.
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Chapter 6. Risk Modeling
6.1.1. Model Assumptions
As a result of the extremely complex nature of environmental systems, the mathematical
equations needed to account for all the chemical or physical processes that might affect stressor
fate and transport may not be known, may not have known solutions, or may require a
prohibitive amount of time and resources to solve. To address this issue, models often rely on
simplifying assumptions to reduce the number and/or complexity of the equations that must
be solved. Other models avoid solving these equations altogether by developing empirical
relationships identified through field or laboratory experiments. Both means of addressing
environmental complexity can place limitations on the types of stressors, environmental
conditions, or chemical and physical processes a given model can consider. While the model
may still run and return results outside of these limits, the results may not be meaningful.
Therefore, it is important to read the supporting documentation for each model to understand
the major assumptions and to ensure that the models are valid for the proposed beneficial use.
6.1.2. Deterministic and Probabilistic Models
Inputs are the data that the user provides the model in order for it to run. These inputs are
generally data on the characteristics of stressors (e.g., concentration), environmental media
(e.g., hydraulic conductivity), or potential receptors (e.g., distance from the source). Fate and
transport models can be divided into two broad categories based on the amount of data
required for each model input. Deterministic models treat each input as a constant that can be
characterized by a single value. The inputs provided by the user are used to conduct one model
run (or "iteration"), which in turn generates a single output representative of that unique
combination of inputs. Probabilistic models treat inputs as variables that require a distribution
of possible values. The inputs provided are used to conduct multiple model iterations, each
with a varied combination of inputs. All of the individual outputs from each model run are
compiled to generate a distribution of outputs based on probability of occurrence. The
relationship between probabilistic and deterministic inputs and outputs is shown in Figure 6.
Model Inputs Model Outputs
Model Formulas
x,, X2, x,)
Probabilistic Distribution
(Light Green)
I Deterministic Point Value
( Dark Green)
Figure 5. Relationship between probabilistic/deterministic inputs and outputs.
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Beneficial Use Compendium Chapter 6. Risk Modeling
Because the primary difference between deterministic and probabilistic models is the amount
of data required, some probabilistic models can be made deterministic by assigning only a
single value to each input and some deterministic models can be made probabilistic by running
varied inputs and aggregating the results. Yet, the use of a model counter to its intended
application is unlikely to be the most effective use of resources when other, more suitable
models are available. Furthermore, models are not required to be entirely deterministic or
probabilistic. Some may be designed to accept a combination of single values and distributions
as inputs, while others may have default values or distributions built into the model
framework. These hybridized models are an attempt to minimize computational intensity,
while maximizing the precision of the model by focusing heightened data requirements on the
most sensitive variables.
Consideration: The Monte Carlo Simulation
A Monte Carlo simulation is a specific type of probabilistic analysis characterized by random sampling of
probability distributions provided by the user for each input variable. In a Monte Carlo simulation, the
selected model is run deterministically many times, with a different set of values selected each time.
Repeating this process enough times produces a distribution of outputs. The greater number of model runs,
the more stable and well-defined the resulting distribution will be. Yet, due to the large number of model
runs required, a Monte Carlo simulation may take considerable time to complete for more complex models.
Monte Carlo simulations are useful because they reduce the potential for human error and bias when
accounting for numerous variables. In addition, the extensive number of simulations provides a great deal
of data that can be used to identify correlations between variables and the sensitivity of a model to changes
in the different variables. However, the results of a Monte Carlo simulation will only be as accurate as the
model and data provided allow. Additional discussion about Monte Carlo simulations can be found in
Guiding Principles for Monte Carlo Analysis (U.S. EPA, 1997a).
The benefit of more deterministic modeling is the comparatively small amount of data
required. When deterministic modeling is sufficient to support final conclusions about a given
beneficial use, there may not be the need for more complex modeling. However, when there
is potential for risks above the selected risk management criteria it can be difficult to draw
conclusions because deterministic models do not provide information on the likelihood that
the combination of inputs modeled will actually occur. In this scenario, it may be more
practical to use a probabilistic model. The benefit of more probabilistic modeling is increased
precision from accounting for the variability of inputs and the ability to tie individual outputs
to a probability of occurrence. This provides greater context for model outputs. However, even
with large datasets, there will likely be some uncertainty that results from natural variability.
Additional discussion of the advantages and disadvantages of probabilistic analysis is provided
in Risk Assessment Guidance for Superfund: Volume III—Part A (U.S. EPA, 2001), as well as
in other references presented in Section 10 of the Appendix.
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Chapter 6. Risk Modeling
6.1.3. Lumped- and Distributed-Parameter Models
Environmental media can be highly variable, both spatially and temporally. Some examples of
variability that may be pertinent to an evaluation are changes in the depth to water table, soil
composition and wind speed. Fate and transport models can be divided into two broad
categories based on how each accounts for these variations. Lumped-parameter models treat
environmental media as homogenous within the region of interest. Each medium is
characterized by a single set of input parameters (either individual values or distributions).
Distributed- parameter models divide the region of interest into a grid. Each cell in this grid is
assigned a separate set of input parameters. Figure 7 shows the different handling of a variable
(soil hydraulic conductivity) within a defined watershed for lumped and distributed models.
>x
^
'>
+•>
u
-D
c
3
as
High
I Low Lumped Distributed
Figure 6. Example of deterministic lumped and distributed inputs for a watershed.
The benefit of lumped-parameter modeling is the comparatively small amount of data
required. This type of model is most suitable for scenarios where variations in environmental
media can be ignored with respect to distance, time or both without introducing unacceptable
amounts of uncertainty into the evaluation. However, when the potential for unacceptable
risks is identified and there is the potential for significant variations in the media that could
impact fate and transport, it may be difficult to draw final conclusions. In this case, it may be
worthwhile to consider distributed-parameter modeling. The benefit of distributed-parameter
models is the greater precision provided. However, because of the amount of information
required, this type of model is better suited for site-specific or small-scale evaluations for
which well-characterized environmental data are obtainable.
6.2. Calculation of Risk
Calculated risks are quantitative estimates of the probability that adverse impacts will occur.
Fate and transport models typically output stressor levels in environmental media as a function
of time, distance from the point of release, or both. Additional steps are necessary to combine
these stressor levels with data on receptor characteristics and stressor toxicity to calculate risks.
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A standard way of calculating risk is with equations similar to those used to calculate screening
levels. However, instead of solving for a stressor level that corresponds to a specified risk level,
the equations are rearranged to solve for a risk level that corresponds to the modeled exposure
level. These calculations can be accomplished either manually or with the aid of a model.
Regardless of the approach used, it is important to understand the assumptions that underlie
these calculations.
Consideration: Discussion of Risk
The risk of adverse impacts to human health and ecological communities can be expressed in different
ways (U.S. EPA, 1989):
Carcinogenic effects are typically discussed only for human receptors because of limited available data
for ecological receptors. Risks are often expressed as an increase in probability of occurrence that results
from an increase in exposure. A 1 *10"6 risk is equivalent to one additional incidence of cancer for every
1,000,000 individuals exposed.
Noncarcinogenic effects are typically discussed for both human and ecological receptors. Risks are
expressed as a ratio (or "hazard quotient") of the stressor level present and the level below which no
effects are known or anticipated to occur. Ratios greater than one indicate an effect may occur, with a
higher ratio indicating greater potential for occurrence. However, this ratio does not directly correspond
to a probability of occurrence.
Similar to stressor levels in environmental media, risks can be calculated deterministically or
probabilistically. Deterministic risks are calculated using a single stressor level together with
point estimates for exposure factors and stressor toxicity. The selected stressor level may
represent the single output from a deterministic model or a single percentile from the
distribution output by a probabilistic model. Deterministic risk calculations generally aim to
combine high-end (e.g., ingestion rate) and mid-range (e.g., body weight) exposure factors to
estimate risks for highly-exposed individuals that are both protective and reasonable, rather
than worst-case scenarios. Additional estimates for more moderately exposed individuals are
also helpful to place the overall risks in better context (U.S. EPA, 1992). In cases where a
beneficial use is placed in a single location with minimal heterogeneity, this type of model
might generate a reasonable approximation of real-world conditions. However, when a
secondary material is planned for wide-scale beneficial use, deterministic models are best used
like screening models to evaluate a high-end exposure scenario.1
Alternatively, probabilistic risks may be calculated to capture variability. Probabilistic risks
incorporate the range of potential stressor levels generated by probabilistic models, as well as
the range of possible exposure factors to generate a more complete distribution of potential
1) Screening models like those discussed in Section 5 are often deterministic. However, these screening models
frequently contain simplifying assumptions that may result in uncertainties that are too great to permit final
conclusions about risks.
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Chapter 6. Risk Modeling
risks. However, toxicity values are typically left as point estimates. Yet, while probabilistic
risks incorporate the variability of exposure factors, it is important to note that certain
exposure factors have been studied and characterized for the United States population more
extensively than others. Even with the best available data, some level of uncertainty will likely
be introduced through the risk calculations.
There may be additional factors beyond total stressor levels present, receptor characteristics
and stressor-specific toxicity that impact actual risks. Failure to consider these additional
factors may result in an over- or underestimation of potential risks. The relative importance of
these factors will differ on a case-by-case basis as a result of different receptors, stressors and
environmental media involved in a given evaluation. The information necessary to conduct a
quantitative evaluation of these factors may not be available or feasible to collect. Instead, it
may only be possible to discuss these factors qualitatively and to indicate the potential to
change the calculated risks. Table 7 briefly discusses some of these considerations. Additional
resources that may be helpful during risk calculation, including those listed below, are
presented in Section 10 of the Appendix.
Table 7. Examples of Additional Factors Relevant to Risk Calculations
Bioavailability
Aggregate
Exposure
Bioavailability is the fraction of a stressor present in an environmental medium that
will be available for distribution to and interaction with tissues and organs. The actual
extent of bioavailability is determined by a host of different environmental factors
(e.g., particle size, moisture, redox potential) and receptor characteristics (e.g., age,
sex, nutritional state). Further discussion about bioavailability can be found online in
the Bioavailability of Contaminants in Soils and Sediments: Processes, Tools, and
Applications (NRC, 2003) and Incorporating Bioavailability Considerations into the
Evaluation of Contaminated Sediment Sites (ITRC, 2011).
Aggregate exposure is the combined exposure to a single stressor through multiple
exposure pathways (e.g., oral, inhalation) that share a potential health effect. These
aggregate exposures may be simultaneous or sequential, but all occur within the
critical window for the health effect. Further discussion about aggregate exposures
can be found in The Framework for Cumulative Risk Assessment (U.S. EPA, 2003b).
Cumulative
Exposure
Cumulative exposure is the combined exposure to multiple stressors that produce
the same health effect. These different stressors may interact with one another in
antagonistic or synergistic ways that serve to mitigate or exacerbate potential health
effects. The extent of these interactions may change based on the level of the
stressors present and the order of exposure. Further discussion about the concept
of cumulative exposure can be found in The Framework for Cumulative Risk
Assessment (U.S. EPA, 2003b).
6.3. Potential Sources of Uncertainty
A main focus of risk modeling is reducing uncertainty to the point where well-substantiated
conclusions can be made about the potential for adverse impacts to human health and the
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environment from the proposed beneficial use. This is typically accomplished by replacing the
assumptions and point estimates from the screening analysis with more realistic data. Such
assumptions can be retained where desired as a factor of safety, so long as it does not interfere
with the ability to draw conclusions from the model results. The following text discusses some
common sources of uncertainty associated with risk modeling. These sources may not be
unique to risk modeling, but are often more pronounced in this method.
6.3.1. Data Uncertainty
As empirical data replace the point estimates and simplifying assumptions from the screening
analysis, the magnitude and direction of uncertainties in the evaluation will shift. The extent
of this shift is determined by how well the available data capture the full variability of each
input variable. Because even large datasets are unlikely to perfectly capture the full extent of
real-world variability, some amount of uncertainty will be introduced through the data used.
Careful management of the available data can minimize the impact of this uncertainty on the
evaluation.
The most conspicuous source of uncertainty is the amount of data available to define each
variable. The less data available for a given variable, the less confidence that the distribution
for that variable is well-defined. Yet, while collection of more data will result in some increase
in overall confidence, the resulting reduction in uncertainty will not be the same for each
variable. This is because each variable has a different amount of natural variability and models
may have different sensitivities to incremental changes in a variable based on the underlying
equations. As a result, collecting greater amounts of data on variables that are known to be
highly variable or that have a greater impact on model results will do more to reduce
uncertainty. Some models already identify and address these influential variables through
heightened input requirements or through discussion in the associated documentation. When
it is unknown which variables exert the greatest influence on model outputs, sensitivity
analyses can be conducted.
Consideration: Sensitivity Analyses
Sensitivity analysis is a broad set of tools that can provide insights about the relative importance of different
model inputs. There are many possible methods for these analyses. Some involve something as simple as
varying one or a few model inputs, usually from "low" to "high" values, while holding other variables
constant and observing the changes in model outputs. Others require more complex correlation and
regression analyses. This information can inform whether to conduct additional analyses or prioritize
resource allocations for additional data collection efforts. However, sensitivity analyses offer no additional
insight about the likelihood of a certain combination of inputs occurring. Further discussion of this topic can
be found in Appendix A of the Risk Assessment Guidance for Superfund: Volume III—Part -4 (U.S. EPA,
2001).
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Another major source of uncertainty is any data processing that is conducted to aggregate and
prepare the collected data for use in the selected model. Uncertainty can be introduced in this
process when additional calculations are used to transform data into a form that differs from
what was explicitly measured, such as the conversion of measured precipitation rates into
infiltration rates or the conversion of measured non-detect data to approximated
concentrations. These uncertainties can be compounded when the data are drawn from
multiple sources. Discrepancies in how the data are collected between sources can contribute
different types and magnitudes of uncertainty to the larger dataset. As a result, the data from
each source may need to be handled differently to properly account for these discrepancies.
Even when the data have been successfully aggregated, the sum of all these individual data
points is unlikely to provide a complete, continuous distribution for any given variable. This
can result in further uncertainty about how well the data points capture the full distribution.
Additional steps can be taken to approximate a more complete distribution from the available
data. This can be an effective way to ensure that the extreme tails of a distribution are captured,
but not over-represented.
Considerations: Developing Probability Distributions
The most straightforward approach to developing a data distribution is to use the measured data as an
empirical distribution, where the probability of occurrence is tied only to the frequency at which a value
appears in the dataset. However, this approach can introduce a great deal of uncertainty when the available
data are not well characterized or are heavily censored (i.e., when there is a large percentage of non-
detects). It may be possible to better characterize the distribution by fitting available data to a known
parametric distribution (e.g., lognormal, gamma, Weibul). But some datasets will not fit well into a known
distribution, making it difficult to consider the potential for values more extreme than those present in the
dataset. When too few data are available to support fitting the data to a distribution, it may still be feasible
to use available summary statistics (e.g., minimum, maximum, median) as constraints to generate a
distribution that minimizes the assumptions built into the distribution (sometimes referred to as a maximum
entropy distribution). However, there is often no "bright line" available to determine which of these or other
methods is best suited for a given evaluation. Therefore, some amount of professional judgment will be
necessary. Some additional discussion about these concepts can be found in Options for Development of
Parametric Probability Distributions for Exposure Factors (U.S. EPA, 2000a).
When preparing probability distributions, it is important to be aware that the different
variables do not exist in a vacuum. There can be strong correlation between certain variables,
such as pH and leachate concentration or age cohorts and body weight. Treating every variable
as independent has the potential to skew modeled risks through the use of input combinations
that rarely occur in the real world. A careful review of the literature can help identify the
various correlations that exist within natural systems, to the extent that these correlations have
been previously characterized. Where data are sufficient, these correlations can be captured
quantitatively in the beneficial use evaluation by linking variables together. This may involve
the development of multiple, separate distributions for certain variables that capture trends in
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Beneficial Use Compendium Chapter 6. Risk Modeling
one variable as a function of changes in another. Where correlations are known or suspected,
but sufficient data are not available to link the variables, this source of uncertainty can still be
explored qualitatively as discussed in Section 7 (Final Characterization).
6.3.2. Model Uncertainty
Models and the underlying mathematical expressions are inevitably a simplification of real-
world conditions, processes and relationships. Model uncertainty results from the inability to
exactly replicate all of the individual minutiae involved in environmental fate and transport.
However, careful review of the available models can minimize the uncertainty by ensuring
that the selected model captures major environmental processes relevant to the beneficial use
evaluation.
Review of the available verification and validation that has been conducted for the model is
one way to determine the accuracy of model results for the environmental conditions relevant
to the proposed beneficial use. Model verification helps determine whether the model code
executes as intended. During this process, the model is reviewed to identify and fix any errors
that could cause it to crash or improperly implement the computer code. This is accomplished
through a combination of peer review and beta testing. Independent peer review identifies
any errors in the conceptual framework and mathematical expressions relied on in the model,
while beta testing involves running the model under a range of conditions to identify errors
that may occur. When a model has undergone this level of review, there is greater confidence
that both model code and the underlying mathematical formulas are sound.
Even if the mathematical formulations are theoretically sound, the necessary simplifications
can ignore real-world heterogeneity (e.g., aquifer discontinuity) or neglect environmental
processes (e.g., colloidal transport) that can impact fate and transport. Model validation helps
to determine whether a model accurately represents the environmental system in question.
Validation studies evaluate the accuracy and precision of a given model by comparing stressor
levels predicted by the model to actual levels measured in either the field or laboratory. If a
model is shown to perform well for the environmental conditions relevant to the beneficial
use evaluation, then there is much greater confidence that the simplifying assumptions
included in the model do not add appreciable uncertainty to the evaluation.
6.4. Summary
Risk modeling is the most complex of the analytical methods discussed in this document. It
relies on more realistic data and models that refine the estimates of release, fate, transport and
exposure that are used to provide a more realistic estimate the actual risks to receptors than a
screening analysis. The primary goal of this step is to minimize the uncertainty present in the
evaluation to the extent necessary to reach final conclusions that can support a beneficial use
determination. However, it is important to emphasize that attempts to make the evaluation
more realistic will not necessarily result in a reduction in the overall amount of uncertainty.
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Beneficial Use Compendium Chapter 6. Risk Modeling
This is because empirical data can introduce additional types of uncertainty that arise from
imperfect knowledge about the system under evaluation. The direction and magnitude of these
new uncertainties may not be as obvious as those associated with high-end or worst-case
assumptions. However, such assumptions can be retained where desired as a factor of safety,
so long as they do not interfere with the ability to draw conclusions from model results.
Regardless, it is important to ensure that any data used are of adequate quantity, quality and
specificity for the model selected. Even the most accurate model will not generate meaningful
results if the underlying data are of poor quality.
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Phase III:
Final Characterization
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Beneficial Use Compendium Section 7. Final Characterization
Section 7. Final Characterization
Final characterization is the third and final phase of a beneficial use evaluation. The goal is to
integrate the key findings, assumptions, limitations and uncertainties identified throughout
the evaluation into a final conclusion about the potential for adverse impacts to human health
and the environment from the proposed beneficial use. While this may involve some further
quantitative and qualitative analysis of the data, the emphasis is on providing context for the
results of the beneficial use evaluation in as transparent, clear, consistent and reasonable a
manner as possible to inform decision-makers and the general public. This section builds on
previous discussions in Risk Characterization Handbook (U.S. EPA, 2000b), Framework for
Human Health Risk Assessment to Inform Decision Making (U.S. EPA, 2014), Science and
Decisions: Advancing Risk Assessment (NRG, 2009) and other documents presented in
Section 11 of the Appendix.
7.1. Summary of Analytical Results
It is useful to provide a concise summary of the analyses conducted and the results obtained.
While it is important to have this information documented in greater detail elsewhere to foster
transparency and reproducibility, some readers may not have the technical background to
parse this more comprehensive discussion. A concise summary that is free of excessive
technical jargon helps a wider audience follow the progression of logic through the evaluation
and understand how the individual analyses helped answer the questions posed in planning
and scoping. This streamlined summary becomes increasingly important as the evaluation
grows in complexity because the greater variety and quantity of model inputs and outputs can
obscure the variables that exert the greatest influence on calculated risks. The summary can
be used to highlight key variables and assumptions that drive these risks. For example:
• Summary of stressors found to pose concern for receptors, including:
- Sensitive subpopulations that may be more susceptible to adverse impacts than the
general population.
- Environmental conditions that result in higher potential for adverse impacts.
• Description of major decisions that form the basis for the evaluation:
- Basis for excluding any stressors, exposure pathways or receptors from analysis.
- Rationale for selection of analytical methods and any alternatives considered.
- Key assumptions, policy decisions and risk management considerations that factored
into decisions.
- Use of extrapolation or other handling of raw data.
• Known strengths and weaknesses of the assessment:
- Existence of any major data gaps.
- Known limitations of any models used.
- Potential for calculated risks to change over time.
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7.2. Characterization of Uncertainties
As stated in the discussion of planning and scoping in Section 2, the presence of uncertainty
can bias analytical results and lead to incorrect conclusions if it is not accounted for during the
evaluation. During planning and scoping, there is an opportunity to manage uncertainty
through the selection of methods that either minimize it or deliberately bias it in a known,
protective direction. Yet some sources of uncertainty will inevitably remain in the evaluation.
The aim in this phase of the evaluation is to document the remaining sources and, to the extent
practicable, discuss the potential for evaluation results to change if these uncertainties could
be fully addressed. There is currently no single recognized guidance on how to characterize
uncertainties (U.S. EPA, 2000b). Thus, professional judgment will be required to determine
how to characterize the various uncertainties and how to present this information.
Quantitative characterization can be the most informative way to discuss uncertainty. The aim
is to use available data to provide numerical estimates of the extent that uncertainties may alter
reported results. This typically involves varying the models, inputs and assumptions used in
previous analyses and detailing how the resulting results differ from previous best estimates.
The quantification of uncertainties can only be conducted where data is available, and will still
be subject to any uncertainties associated with the data and models used. As a result, this type
of characterization can give the misleading appearance of greater certainty than actually exists.
This problem can be minimized with an accompanying discussion that acknowledges the
limitations of quantitative characterization and places the calculations in proper context.
When data are insufficient to express uncertainties numerically, qualitative characterization
can provide additional useful information. The aim is to review available lines of evidence and
to summarize the potential for uncertainties to alter results through narrative descriptors, such
as "low" or "high." This qualitative interpretation of evidence is subjective and may suffer from
ambiguity due to a lack of standardized criteria to define the descriptors used. Therefore, it is
essential that a clear and transparent rationale is provided for any conclusions that result from
this type of characterization.
There may be many sources of uncertainty within a single evaluation. While it is critical to
acknowledge each of these sources, it can be counterproductive to devote extensive discussion
to those unlikely to alter evaluation results. For example, discussion focused on uncertainties
surrounding stressors that screened out based on a worst-case scenario is unlikely to raise any
doubts about the conclusion that these stressors will not pose concern. Sensitivity analyses can
help identify the individual variables that exert the greatest influence on the evaluation results
and help to focus the discussion of uncertainties. It is common to discuss each uncertainty
separately, but it is important to keep in mind that these different sources can compound and
exert a greater influence on analytical results together than separately. Unfortunately,
information on the relationship between different uncertainties can be sparse, so this type of
discussion is often qualitative by necessity.
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Section 7. Final Characterization
7.3. Characterization of Potential for Adverse Impacts
The final part of a beneficial use evaluation is consideration of analytical results, together with
information on uncertainties, to draw conclusions about the potential for adverse impacts from
the proposed beneficial use. These conclusions are intended to communicate a clear picture of
potential for adverse impacts, as well as the overall confidence in these conclusions. Decision-
makers will use the conclusions presented along with other pertinent considerations
(e.g., existing state and federal requirements, public opinion, the existence of a market) to
determine whether to allow a use, either as proposed or with some additional conditions.
Therefore, it is critical to emphasize any considerations that may influence this determination.
Table 8 presents questions that may be helpful to consider when developing these
conclusions.
Table 8. Considerations for Discussing Conclusions
What is the overall
picture based on
analytical results?
It is important to provide sufficient context for the any numerical results presented in the
conclusion. This often means breaking out results in multiple ways to capture variations
both between and within different receptor cohorts. Different subpopulations (e.g., children,
asthmatics) can vary considerably from the general population. Even within a given
exposure cohort, the potential for adverse impacts are not constant because of differences
in the behavior, physiology and sensitivity between individual receptors. Presenting a range
of possible results can capture the extent to which results may change between highly
exposed individuals and more typical members of the population.
Can the potential for
adverse impacts be
reduced through
management?
Sensitivity analyses may reveal that any concerns identified are driven by a specific subset
of possible uses. Identifying these subsets can help decision-makers define limits on the
beneficial use. For example, a proposed beneficial use may still be appropriate so long as
additional conditions are met, such as:
• The secondary material substitutes for less than a certain percentage of the virgin
materials.
• The concentrations of a constituent in the secondary material used are below
specified levels.
• The use is not exposed to extreme conditions (e.g., flooding, high temperatures).
• The use is restricted based on certain features (e.g., greater than a certain distance
from water bodies).
It may be possible to incorporate variability and uncertainty into these conclusions to
delineate between the subsets of possible uses where there is: 1) high confidence that a
beneficial use is appropriate, 2) enough uncertainty that additional consideration is
warranted on a case-specific basis, or 3) high confidence that a beneficial use is not
appropriate.
Do uncertainties place
limitations on the
conclusions?
Data may not be available to characterize the behavior of a beneficial use for all possible
variations in beneficial use design or environmental conditions to which the use may be
exposed. Such data gaps can make it difficult to draw unqualified conclusions about the
beneficial use, but it may still be possible to draw conclusions about the aspects for which
data are available.
It is important to highlight the distinction between major sources of uncertainty that may
be reduced through additional data collection (e.g., variability) and those that are unlikely
to be resolved in the immediate future (e.g., limitations of available models). This can help
decision-makers weigh the potential benefits of further data collection and analysis prior
to a beneficial use determination.
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Glossary
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Beneficial Use Compendium Glossary
This glossary lists common terms that may be encountered in a beneficial use evaluation and
may contain terms beyond those introduced in this document. The definitions presented may
not be the only possible definitions and some terms may have different meanings in other
contexts. These definitions do not constitute the Agency's official use of terms and phrases for
regulatory purposes, and should not be used to alter or supplant those found in any other
federal document. Official terminology can be found in the laws and related regulations as
published in such sources as the Congressional Recordand Federal Register.
Abiotic - Neither alive nor derived from living organisms.
Absorption - The process by which a liquid or gas is drawn into and fills the empty voids of a
porous material.
Accuracy - The degree to which a measurement reflects the true quantitative value of a
variable.
Acidic - An aqueous solution with a pH below 7.
Acute Health Effect - A health effect in which symptoms develop rapidly. These symptoms
may subside after the exposure stops.
Acute Exposure - Occurring over a short timeframe, typically under 24 hours in duration.
Adsorption - The physical adherence or bonding of ions and molecules onto the surface of
another molecule.
Advection - Transport driven by the bulk flow of a liquid or gas.
Adverse Impact - Any abnormal, harmful or undesirable change that results from being
exposed to stressors in the environment.
Aerobic - Occurring in the presence of oxygen (e.g., 02).
Aerosol - A suspension of fine liquid and/or solid particles in air.
Agent - See: Stressor.
Aggregate - Material formed from the loosely compacted mass of granular material.
Aggregate Exposure - The combined exposure to a single stressor through multiple exposure
pathways (e.g., oral, inhalation) that share a potential health effect.
Air - The mixture of gases present at the earth surface; typically composed of 79.0% N2, 20.9%
O2, and less than 0.1% a mixture of CO2, Ar, He, and hundreds of other gases originating from
both natural and artificial sources.
Air Exchange Rate - The rate at which outside air replaces indoor air in a space. Expressed
in one of two ways: 1) the number of changes of outside air per unit of time (e.g., air changes
G-l
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Beneficial Use Compendium Glossary
per hour; ACH) and 2) the rate at which a volume of outside air enters per unit of time (e.g.,
cubic feet per minute; cfm).
Albedo - The proportion of the incident light or radiation that is reflected by a surface.
Alkalinity - A measure of the capacity of water to neutralize acid without significant pH
change. It is often associated with the presence of hydroxyl (OH~), carbonate (COJ2), and/or
bicarbonate (HCO^) radicals in the water.
Anaerobic - Occurring in the absence of both free oxygen (e.g., 02) and bound oxygen
(e.g., N02) in a given medium.
Analogous Product - A natural or commercial product available on the market that is
replaced by a beneficial use.
Anion - An ion with a negative charge.
Anisotropic - Having properties that change as a function of direction.
Anoxic - Occurring in the absence of free oxygen (e.g., 02). Bound oxygen (e.g., N02) may
still be present.
Antagonistic Effect - A biologic response to exposure to multiple substances that is less than
would be expected if the known effects of the individual substances were summed together.
Anthropogenic - Of human origin.
Aquiclude - A saturated geological formation with insufficient porosity to support any
significant water removal or to contribute to the overall ground water regime.
Aquifer - An underground geological formation, or group of formations, that is saturated and
sufficiently permeable to yield economically significant quantities of water to wells or springs.
Aquitard - A saturated geologic formation that is permeable enough to contribute to regional
ground water flow, but not permeable enough to supply water for economic use.
Attenuation - The process in which contaminant concentrations diminish in a medium due
to filtration, biodegradation, dilution, sorption, volatilization and other processes.
B
Background - The concentration of a chemical substance in the environment not due to the
site or activity under consideration. Background levels may be naturally occurring
(i.e., ambient concentrations of substances present in the environment without human
influence) or anthropogenic (i.e., concentrations of substances present in the environment due
to human-made, but non-site, sources).
Base Flow - The part of the stream flow that is not attributable to direct runoff from
precipitation or snowmelt, usually sustained by ground water upwelling.
Basic - An aqueous solution with a pH above 7.
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Beneficial Use Compendium Glossary
Bedrock - A layer of solid rock that underlies the soil; can be permeable or non-permeable.
Benthic - Pertaining to the bottom zones of water bodies, where oxygen levels are typically
low.
Bias - A systematic error, or deviation from the truth, in results or inferences. Bias can exist
between test results and the true value (absolute bias, or lack of accuracy) or between results
from different sources (relative bias). If different laboratories analyze a sample for which the
true value is known, the absolute bias from the true value would be the difference between
that value and the value measured by a laboratory. If different laboratories analyze the same
sample, the relative biases among the laboratories would be the differences among the results
from the different laboratories.
Bioaccumillation - A general term for the net accumulation of substances in the tissue of an
organism at levels higher than those that occur in the surrounding environment.
Bioassay - A standardized procedure for determining the effects of an environmental variable
or a substance on a living organism.
Bioavailable - A measure of the fraction of a substance present in a medium that is available
to interact with and affect an exposed receptor.
Bioconcentration - The net accumulation of a chemical directly from an environmental
medium into an organism.
Bioconcentration Factor (BCF) - The ratio of a contaminant concentration in biota to its
concentration in the surrounding medium.
Biodegradation - The decomposition of a chemical that is mediated by a biotic organism, such
as bacteria or fungi.
Biodiversity - A measure of the numbers of different species of plants and animals found in a
natural environment. Used as an indicator of the overall health of an ecosystem.
Biomagnification - The cumulative increase in the concentration of a substance in
successively higher levels of the food chain due to predation.
Biota - All species of animal, plant and other life forms.
Biotic - Relating to, or resulting from, living things.
Biotransformation - The conversion of one substance into another within the body.
Biotransformation Factor (BTF) - An empirical ratio relating the chemical concentration
in biota; such as produce, livestock or animal products (such as eggs); to the amount of chemical
to which the plant or animal is exposed in soil, feed or other media.
Bounding Estimate - A point value estimate for a distribution that is above the highest (upper
bound) or below the lowest values (lower bound) that may realistically occur.
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Beneficial Use Compendium Glossary
Buffer (Chemical) - A material in a solution that adds resistance to changes in pH when the
solution is diluted or mixed with acids or bases.
Cancer - A disease of heritable, somatic mutations affecting cell growth and differentiation,
characterized by an abnormal, uncontrolled growth of cells.
Cancer Slope Factor - An upper bound, approximating a 95% confidence limit, on the
increased cancer risk from a lifetime exposure to a stressor.
Carcinogen - An agent that can cause or contribute to cancer.
Cation - An ion with a positive charge.
Chemical - Any organic or inorganic substance with a defined molecular structure.
Chemical Abstract Service (CAS) Number - A number assigned by the CAS to identify a
chemical based on the molecular structure. Individual chemicals can have many multiple
common names, but each chemical is assigned a single CAS number.
Chemical Mixture - Any combination of two or more chemicals that retain distinct identities
when placed together.
Chronic Health Effect - A health effect that occurs as a result of repeated or long-term
exposures.
Chronic Exposure - Occurring constantly or intermittently over a long duration, ranging
from several weeks to a lifetime.
Cohort - A group of people within a population who are assumed to have similar
characteristics (e.g., age, location, occupation, exposure) during a specified period.
Colloid - A fine particle ranging in size from 1 to 500 nanometers in diameter. Due to the
small size, these particles tend to remain suspended in water and can be a major source of
turbidity.
Concentration - The total mass of a substance present in a defined volume of a media.
Confined Aquifer - An aquifer bounded above and below by impermeable beds (e.g., bedrock)
or by beds of distinctly lower permeability than that of the aquifer itself (e.g., clay).
Consolidation - The densification of soil or other granular material by gravity or mechanical
force, which may result in the expulsion of excess water from pore spaces.
Contaminant - Any physical or chemical stressor present in a given medium with the
potential to pose a threat to human health or the environment. See also: Pollutant.
Control - In an experiment, a control is the baseline group that receives no treatment or a
neutral treatment. This group is used to assess the effects of a treatment by comparing the
treatment group to the control group.
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Correlation - An estimate of the degree to which two sets of variables vary together, with no
distinction between dependent and independent variables.
Corrosive - Liquid or aqueous substances that will destroy and damage other materials with
which it comes into contact. EPA regulates corrosive wastes with a pH less than or equal to
2.0 or greater or equal to 12.5, as well as those that corrode steel at rates of 6.35 mm or more
per year (determined by the National Association of Corrosion Engineers), as characteristic
hazardous wastes. These and other hazardous wastes fall outside the scope of this document.
Cumulative Distribution Function (CDF) - An equation that defines the likelihood (or
probability) that a variable will be less than or equal to a specified value.
Cumulative Exposure - The combined exposure to multiple stressors that produce the same
adverse effect.
Data Quality - All features and characteristics of data that bear on its ability to meet the stated
or implied needs and expectations of the user.
Data Quality Objective (DQO) - Qualitative and quantitative statements of the overall level
of uncertainty that a decision-maker is willing to accept in results or decisions derived from
environmental data. DQOs provide the statistical framework for planning and managing
environmental data operations consistent with the data user's needs.
Degradation - The process of breaking down a chemical through natural or anthropogenic
processes.
Deposition - The settling out of sediment, dust, gas, aerosols or other materials that have been
entrained by wind or water.
Desorption - The removal of a chemical from a solid to which it is attached or a liquid in
which it is dissolved.
Detection Limit - The lowest concentration of a chemical that can be distinguished reliably
from zero by a given analytical method.
Diffusion - Transport driven by the presence of a concentration gradient.
Dilute - To make less concentrated by mixing with additional materials.
Dispersion - Mixing that occurs during advective transport caused by variations in velocity
on a microscopic level.
Disposal - The final placement or destruction of wastes.
Distribution Coefficient (K
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Beneficial Use Compendium Glossary
Downgradient - The direction in which stressor transport will occur as a result of gradients
within environmental media.
Duplicate - Two measurements made concurrently and in the same location, or side-by-side.
Used to evaluate the precision of the measurement method.
Ecological - Pertaining to the interactions among living organisms and their physical
surroundings.
Element - A pure substance that cannot be further decomposed by chemical means.
Eluate - The leachate produced from exposing a material to eluent.
Eluent - A solvent intended to test the extent of leaching from a solid material.
Endangered Species - A species in danger of extinction throughout all or a significant
portion of its range/habitat.
Endpoint (Health Effect) - An observable or measurable biological change or chemical
concentration (e.g., metabolite concentration in a target tissue) that is used as an indicator of
a health effect.
Ephemeral Stream - A stream that goes dry during long periods without rain.
Equilibrium - Stable conditions in which relevant properties remain more or less constant
over a period and there is little or no inherent tendency for change.
Eutrophication - The enrichment of water bodies by nutrients (e.g., phosphorus, nitrogen).
Elevated nutrient levels can cause unwanted growth of algae, which in turn can result in
depleted oxygen levels in the water when the algae die and decay.
Evapotranspiration - The combined loss of water from a given area by evaporation from the
land and transpiration from plants.
Exposure - Contact between a receptor and a stressor.
Exposure Factor - Data on human behavior and physiological characteristics that can be used
to estimate the magnitude of potential exposures to stressors present in environmental media.
Exposure Pathway - The physical course that a chemical or pollutant takes from the source
to the exposed receptor.
Exposure Route - The way that a stressor passes into an organism after contact
(e.g., ingestion, inhalation, dermal absorption).
Extrapolation - The estimation of new data points outside the bounds of a discrete set of
known data points.
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Fate - The final disposition of a particular stressor in the environment as a result of adsorption,
degradation or transformation.
Flood plain - A relatively flat expanse of land bordering a river that experiences flooding
during periods of high discharge; often defined based on the frequency with which the
flooding occurs (e.g., 100-year floodplain).
Flux - The rate of mass transfer through or between environmental media.
Friable - Easily broken apart with the force exerted by an unassisted human hand.
G
Geological - Referring to the history and structure of the solid portion of the earth (e.g., rocks,
soils, minerals).
Gradient - Variations in a property (e.g., concentration) over a specified distance.
Granular - Consisting of small grains or particles.
Greenhouse Gas - Any gas that affects the overall heat-retaining properties of the Earth's
atmosphere (e.g., methane, nitrous oxide, ammonia, sulfur dioxide, carbon dioxide and certain
chlorinated hydrocarbons).
Grey Literature - Literature produced by government, academics, business and industry in
print and electronic formats outside of the traditional commercial or academic publishing and
distribution channels
Ground Water - Any water present underground between the porous spaces of soil and rock.
H
Half-Life - The time required for half of the mass of a substance to be degraded, transformed
or destroyed within a given medium.
Hazard - The potential for danger, harm or irreversible adverse health effects to occur.
Hazard Identification - The process of determining whether a stressor has the potential to
cause an increase in the incidence or severity of a particular adverse health effect.
Hazard Index (HI) - The sum of more than one hazard quotient for multiple substances and/or
multiple exposure pathways to estimate aggregate risk.
Hazard Quotient (HQ) - A ratio of the estimated exposure level to a substance and a toxicity
value at which no adverse health effects are known or anticipated to occur.
Heavy Metals - A group of metals with high molecular weights (e.g., arsenic, chromium,
copper, lead, mercury, silver, zinc).
Heterogeneous - Having properties that differ across the region of interest.
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Beneficial Use Compendium Glossary
High-End Estimate - A point value estimate for a distribution that is typically at or above the
90th percentile, but not higher than the highest value that may realistically occur.
Homogeneous - Material properties are identical across the area of interest.
Hydraulic Conductivity - The rate at which water can move through an aquifer or other
permeable medium.
Hydraulic Head - The force exerted by a column of liquid expressed by the height of the
liquid above the reference point at which the pressure is measured (e.g., sea level).
Hydrocarbon - An organic compound containing only hydrogen and carbon atoms.
Hydrolysis - A degradation process in which a chemical is broken into smaller parts through
reaction with water molecules.
Hydrophilic - The property of attracting and mixing well with water molecules; characteristic
of polar or charged molecules.
Hydrophobic - The property of dissolving readily in organic solvents, but not in water;
resisting wetting; and not containing polar groups or sub-groups.
I
Ignitable - Liable to undergo strongly exothermic decomposition due to high heat or readily
combustible materials that can cause fire through friction. EPA regulates substances classified
as ignitable as characteristic hazardous wastes. These and other hazardous wastes fall outside
the scope of this document.
Impervious - Having such low permeability as to effectively prevent any fluids or gases from
infiltrating into or passing through the material.
Indirect Impact - An impact where a stressor acts on supporting components of the ecosystem
(such as food availability), which in turn has an adverse impact on ecological receptors.
Industrial Non-hazardous Secondary Material - Any materials that are not the primary
products from industrial, manufacturing and commercial sectors. Examples can include scrap
and residuals from production processes and products that have been salvaged at the end of
their useful life.
Initial Abstraction - The amount of water from a precipitation event that is sequestered by
vegetation, evaporation and infiltration before overland runoff begins.
Infiltration - The downward entry of water into a soil or rock surface.
Inert - Stable and unreactive under the specified set of environmental conditions.
In Situ - Refers to testing or action conducted in the field or under natural conditions, rather
than replicated in a laboratory setting (literally, "in place").
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Interface - The contact zone between two materials of different chemical or physical
composition.
In Vitro - Refers to testing or action conducted outside a living organism (e.g., inside a test
tube or culture dish; literally, "in glass").
In Vivo - Refers to testing or action conducted inside a living organism (literally, "in life").
Instrument Detection Limit (IDL) - A quantitative limit on the detection capabilities of a
given piece of analytical equipment, set at a concentration equal to three times the standard
deviation (3a) of a series of 10 replicate measurements.
Interception - The process by which precipitation is captured on the surfaces of vegetation
and other impervious surfaces and evaporates before it reaches the land surface.
Interpolation - The estimation of new data points within the bounds of a discrete set of
known data points.
Ion - An atom that has lost or gained one or more electrons, becoming an electrically charged
particle.
Isotherm (Adsorption) - A mathematical relationship that describes, for a constant
temperature, the equilibrium of the adsorption of a material at a surface as a function of
concentration.
Isotope - Atoms of the same atomic number but having different atomic weight due to a
variation in the number of neutrons.
Isotropic - Uniform in all directions.
L
Latency Period - The time between the first exposure to a stressor and the manifestation or
detection of an adverse impact.
Leach ate - Any liquid, together with any substances dissolved or suspended in the liquid, that
has percolated through or drained from a solid material.
Leaching - The process by which chemicals or contaminants are dissolved into and
transported away by a liquid.
Lifecycle - All the different stages a material may undergo, including material acquisition,
manufacture, use/reuse/maintenance, and ultimate disposition.
Lifestage - A distinguishable time frame in a person's life characterized by unique and
relatively stable behavioral and/or physiological characteristics that are associated with
development and growth. EPA guidance recommends consideration of the following
childhood age groups.
• Age groups less than 12 months old: birth to <1 month, 1 to <3 months, 3 to <6 months,
and 6 to <12 months.
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Beneficial Use Compendium Glossary
• Age groups greater than 12 months old: 1 to <2 years, 2 to <3 years, 3 to <6 years, 6 to
<11 years, 11 to < 16 years, and 16 to <21 years.
Some other lifestages that may be important to consider when assessing human exposure are
pregnancy, nursing and old age.
Littoral - Dealing with the shallow area of a water body where sunlight penetrates easily and
oxygen levels are typically high.
Lowest Observed Adverse Effect Level (LOAEL) - The lowest dose or exposure level at
which there is a statistically or biologically significant increase in the frequency or severity of
an adverse health effect in the exposed population as compared with an appropriate, unexposed
control group.
Lysimeter - A device for measuring percolation and leaching losses from a column of soil
under controlled conditions.
M
Matrix (Environmental) - The solid framework of a porous environmental medium.
Media (Environmental) - Specific environmental compartments with distinct properties,
such as air, water and soil.
Metabolite - Any substance produced by metabolism or a metabolic process.
Method Detection Limit (MDL) - A quantitative limit on the detection capabilities of a given
analytical method performed by a given laboratory, set at the minimum concentration of a
substance that can be reliably determined to be greater than zero with at least 99% confidence.
Migration - The transport of a stressor through environmental media.
Mobility - The ability of a chemical, element or pollutant to move into and through the
environment.
Model - A mathematical representation of a natural system that is intended to mimic the
behavior of the real system, allowing description of empirical data and predictions about
untested states of the system. Use of models is usually facilitated by computer programming of
the mathematics and construction of a convenient input and output format.
Monolithic - Having a large, cohesive structure that cannot be broken apart without
considerable effort.
Monte Carlo - A method of probabilistic analysis that uses repeated random sampling from
the distribution of values for each of the variables in a calculation (e.g., lifetime average daily
exposure) to derive a distribution of estimates (of exposures) in the population.
Municipal Waste - Waste generated within homes, offices, and commercial or institutional
establishments (such as stores and hospitals). Industrial office and lunchroom waste is also
classified as municipal waste.
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Beneficial Use Compendium Glossary
Mutagenicity - The potential for a chemical to increase the frequency of mutations by directly
or indirectly modifying the structure of DNA or its expression.
N
Natural Resource - Land, fish, wildlife, biota, air, soil, water, ground water, and other
materials or energy supplied by nature and its processes independent of anthropogenic
refinement.
Non-aqueous Phase Liquid (NAPL) - A liquid which may be either denser (DNAPL) or
lighter (LNAPL) than water and that does not easily mix or dissolve in water, remaining as a
separate phase.
Nonpoint Source - Pollution sources that are diffuse, without a single identifiable point of
origin.
No Observed Adverse Effect Level (NOAEL) - An exposure level at which there are no
statistically or biologically significant increases in the frequency or severity of adverse effects
between the exposed population and its appropriate control; some effects may be produced at
this level, but they are not considered to be adverse or precursors to adverse effects.
No Observed Effect Level (NOEL) - An exposure level at which there are no statistically or
biologically significant increases in the frequency or severity of any effects between the
exposed population and its appropriate control.
Order of Magnitude - A difference in values by a factor often.
Organic - Relating to, or derived from living matter.
Organic Soil - Soil composed of predominantly organic material rather than mineral material.
Overland Flow - Water from precipitation, irrigation or other sources that flows over the
ground surface, rather than soaking into it, and eventually enters into a body of surface water.
Oxidation - The loss of electrons in a chemical reaction.
P
Parameters - An input in a mathematical equation or model.
Partial Pressure - The portion of total vapor pressure in a system due to one or more
constituents in the vapor mixture.
Partition Coefficient (Kd) - See Distribution Coefficient.
Percolation - The slow movement of water through the pores in soil or permeable rock.
Permeability - The relative ease with which rock, soil or sediment will transmit a liquid or
gas.
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Beneficial Use Compendium Glossary
Persistent - Describes chemicals that do not break down, or that degrade very slowly, and
remain in the environment for an extended period of time.
pH - A measure of how acidic or basic an aqueous solution is. Defined as the negative logarithm
of the hydrogen ion concentration.
Photolysis - A degradation process in which a chemical is broken into smaller parts by
ultraviolet light.
Piezometer - A non-pumping well, generally of small diameter, that is used to measure to
elevation of the water table or potentiometric surface.
Point Estimate - A single value used to define an input variable (e.g., concentration).
Typically a mean, median or upper percentile based on the full range of observed values.
Point Source - Pollution sources that are discharges from a single, identifiable point of origin
(e.g., pipe, smokestack).
Point Value - A single, constant value used to characterize a variable.
Pollutant - Any agent that can render water, soil, air or another natural resource unfit for a
given use.
Pore Space - The empty, interstitial spaces within a soil, sediment or other solid material.
Pore Water - Water occupying space between sediment or soil particles.
Potable - Suitable for human consumption.
Practical Quantisation Limit (PQL) - The lowest concentration that can be reliably
measured under routine operating conditions in a given laboratory based on the specified
limits of precision and accuracy.
Precipitation (Chemistry) - The formation of a solid phase substance within a liquid mixture
through chemical reactions, adsorption or other means that can be physically separated from
the liquid.
Precipitation (Meteorology) - Water that falls to the ground as rain, snow, sleet or hail.
Precision - A measure of the closeness, or agreement, among individual measurements.
Probability Density Function (PDF) - An equation that defines the likelihood (probability)
that a variable will be a specified value.
Quality Assurance (QA) - A system of management activities intended to ensure that a
product will be of the type and quality needed by the user. QA deals with setting policy and
implementing an administrative system of management controls that cover planning,
implementation and review of data collection activities.
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Beneficial Use Compendium Glossary
Quality Control (QC) - Scientific precautions, such as calibrations and duplications, that are
necessary to identify any defects in the actual products produced.
Radical - An atom, molecule or ion with unpaired valence electrons, causing it to be highly
reactive.
Reactive - Refers to materials with the capability to explode or undergo violent chemical
change when exposed to certain conditions, such as mixture with water, exposure to pressure
or heat, or exposure to acidic conditions. EPA regulates substances classified as reactive as
characteristic hazardous wastes. These and other hazardous wastes are outside the scope of this
document.
Reasonable Maximum Exposure (RME) - The highest exposure that is reasonably likely to
occur, often defined somewhere within the range of the 90th and 99.9th percentiles of all
possible exposures.
Recalcitrant - Resistant to degradation in the environment through natural processes.
Receptor - A living entity exposed to a stressor.
Recharge - The process of adding uncontaminated water to the saturated zone through the
infiltration of precipitation.
Reduction - The loss of oxygen or the gain of electrons in a chemical reaction.
Reference Concentration (RfC) - An estimate of a continuous inhalation exposure to the
human population (including sensitive subgroups) that is likely to be without an appreciable
risk of deleterious noncancer effects during a lifetime.
Reference Dose (RfD) - An estimate of a daily exposure to the human population (including
sensitive subgroups) that is likely to be without an appreciable risk of deleterious noncancer
effects during a lifetime.
Refractory - Resistant to biological degradation.
Release - Any spilling, leaking, pumping, pouring, emitting, emptying, discharging, injecting,
escaping, leaching, dumping or otherwise disposing of potential stressors into the
environment.
Replicate - Duplicate analysis of an individual sample. Used for quality control to evaluate
the precision of the measurement method.
Representativeness - The degree to which a sample is characteristic of the whole medium,
exposure or dose for which the samples are being used to make inferences.
Risk - The expected frequency or probability of adverse impacts resulting from exposure to
stressors.
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Beneficial Use Compendium Glossary
Risk Assessment - Qualitative or quantitative evaluation of the risks posed to human health
and/or the environment by the actual or potential presence or release of hazardous substances,
pollutants or contaminants.
Risk Management - The process of evaluating and selecting between alternative responses to
risk, which may also include consideration of political, legal, economic and behavioral factors.
Runoff - See Overland Flow.
s
Sample - A fragment of some larger material (e.g., soil) that is collected to be tested or
analyzed.
Saturation - The state in which no more of a fluid can be absorbed by a porous material.
Sediment - Soil and other small, granular material settled at the bottom of, or entrained in
the flow of, a water body.
Seep - A place where water flows or ponds due to the intersection of an aquifer with the Earth
surface.
Sensitivity (Model) - The variation in output of a model with respect to changes in the values
of the model's input(s).
Sensitivity (Receptor) - Differences in response to a stressor that can arise due to numerous
biological factors such as lifestage (windows of enhanced sensitivity), genetic polymorphisms,
gender, disease status, nutritional status, etc.
Soil - Unconsolidated materials that compose the superficial geologic strata (material overlying
bedrock) consisting of some combination of clay, silt, sand or gravel-sized particles, as classified
by the U.S. Natural Resources Conservation Service.
Solubility - The ability or tendency of one substance to dissolve into another at a specified
temperature and pressure; generally expressed in terms of the amount of solute that will
dissolve in a given amount of solvent to produce a saturated solution.
Solute - A substance dissolved in a solution.
Solvent - A substance in which a solute is dissolved to form a mixture.
Sorption - A generic term that refers to both the processes of absorption and adsorption.
Source - An entity or action that releases stressors to the environment.
Species (Chemical) - A specific form of an element that is defined by the isotopic
composition, electronic or oxidation state, and complex or molecular structure. Changes in this
form may alter mobility in the environment and toxicity to receptors.
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Beneficial Use Compendium Glossary
Species (Receptors) - A group of organisms that actually or potentially interbreed and are
reproductively isolated from all other such groups; a taxonomic grouping of morphologically
similar individuals.
Spring - See Seep.
Steady State - The state in which fluxes of a substance between environmental media has
reached a balance and the concentrations within each are effectively constant.
Stressor - Any biological, chemical or physical entity that can cause or induce an adverse
response in receptors.
Subpopulation - Some subset of the full, exposed population.
Surface Water - Water that is naturally open to the atmosphere, such as rivers, lakes,
reservoirs, streams and seas.
Surficial Aquifer - The geologic formation nearest the natural ground surface that is an
aquifer, as well as lower aquifers that are hydraulically interconnected with this aquifer.
Surrogate Data - Substitute data or measurements on one substance used to estimate
analogous or corresponding values of another substance.
Susceptibility - Differences in potential risks resulting from variation in both toxicity
response (sensitivity) and exposure rate (as a result of gender, life stage, and behavior).
Synergistic Effect - A biologic response to exposure to multiple substances that is greater
than would be expected if the known effects of the individual substances were summed
together.
Target Organ - The biological organ(s) affected by a stressor.
Teratogen - A substance that may cause birth defects.
Threatened Species - A vulnerable species that is likely to become endangered in the near
future.
Threshold - A dose or exposure below which a specified, measureable effect is not observed.
Topography - The changes in surface elevation associated with geographic features, such as
hills, valleys and plains, that shape the surface of the Earth.
Total Dissolved Solids (TDS) - The total mass of dissolved constituent particles that will pass
through a filter with pores around 2 microns (0.002 centimeters) in size.
Total Suspended Solids (TSS) - The total mass of constituent particles that will be filtered
out with pores around 2 microns (0.002 centimeters) in size.
Toxic - A generic term for substances that are harmful or fatal when ingested or absorbed.
EPA regulates certain toxic substances that may be released above specified levels, as defined
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Beneficial Use Compendium Glossary
by the Toxicity Characteristic Leaching Procedure (TCLP), as characteristic hazardous wastes.
These and other hazardous wastes are outside the scope of this document.
Toxicity - Deleterious or adverse biological effects elicited by a chemical, physical or
biological agent.
Toxicity Value - A numerical estimate of the dose-response curve for a stressor that is used
to quantify the probability of adverse impacts.
Transformation - A change in a chemical or physical state of a stressor.
Transmissivity - The rate at which a liquid moves through an aquifer. This is a function of
the liquid, the aquifer media, and the thickness of the aquifer.
Transpiration - The process by which water vapor escapes from living plants, generally
through the leaves, and enters the atmosphere.
Transport - The conveyance of a substance within an environmental medium or between
media.
Trophic Level - A feeding relationship within an ecosystem (e.g., predation) that determines
the route of energy flow and the pattern of chemical cycling.
Turbidity - Cloudiness in water caused by suspended materials.
u
Uncertainty - Imperfect knowledge concerning the present or future state of a system under
evaluation.
Uncertainty Factor (UF) - One of several, generally 10-fold, default factors used in deriving
toxicity values from experimental data. The factors are intended to account for 1) variation in
susceptibility among the members of the human population, 2) uncertainty in extrapolating
animal data to humans (i.e., interspecies uncertainty), 3) uncertainty in extrapolating from
data obtained in a study with less-than-lifetime exposure (i.e., extrapolating from subchronic
to chronic exposure), 4) uncertainty in extrapolating from a LOAEL rather than from a
NOAEL, and 5) uncertainty associated with extrapolation when the database is incomplete.
Unconfined Aquifer - An aquifer that has a free water table.
Unit Risk - The upper-bound excess lifetime cancer risk estimated to result from continuous
exposure to an agent at a concentration of 1 microgram per liter ([Jg/L) in water, or 1
microgram per cubic meter ([ag/m3) in air.
Upgradient - The direction away from which stressor transport will occur as a result of
gradients within environmental media. Environmental media upgradient from a source are
typically assumed to be free of contamination.
Uptake - The processes by which stressors are transferred from environmental media and into
a receptor.
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Beneficial Use Compendium Glossary
Upwelling - The flow or ponding of water due to the intersection of an aquifer with the Earth
surface.
Useful Life - The period over which a product or beneficial use is used for the purpose it was
acquired. This may or may not be the same as the physical life or economic life.
V
Vadose Zone - The subsurface soils and partially saturated pore spaces above the water table.
Vapor - The gaseous phase of any substance that is liquid or solid at atmospheric temperatures
and pressures.
Vapor Pressure - A measure of a substance's volatility, or its propensity to partition to the
vapor (gaseous) phase from its condensed phase (solid or liquid).
Variability - A quantitative description of the range or spread of possible values for a variable.
Variable - Elements in an equation or model that may change in value.
Void - See Pore Space.
Volatile - The property of having a high vapor pressure, readily converting from a liquid or
solid state into a gaseous vapor under atmospheric temperatures and pressures.
w
Waste Water - Used water from an individual home, a community, a farm or an industry that
contains dissolved or suspended matter.
Watershed - An area of land where all of the water that flows through or over it or drains off
to the same stream, river, lake or other water body.
Water Table - The upper surface of the zone of saturation, defined as the point where the
water pressure is equal to the atmospheric pressure.
Well - Any shaft or pit that is dug or bored into the earth, generally cylindrical in form and
often walled with bricks or tubing to prevent the earth from caving in around it.
Worst-Case Exposure - The maximum possible exposure that can conceivably occur,
regardless of whether this exposure actually occurs within the exposed population.
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Beneficial Use Compendium
References
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Beneficial Use Compendium References
ASTM (American Society for Testing and Materials). 1998. RBCA Fate and Transport Models:
Compendium and Selection Guidance. Funded by the U.S. EPA under agreement
#X 825708-01. Prepared for ASTM by Foster Wheeler Environmental Corporation.
ASTSWMO (Association of State and Territorial Solid Waste Management Officials). 2007.
ASTSWMO 2006 Beneficial Use Survey Report. Washington, DC. November.
Interstate Technical and Regulatory Council (ITRC). 2011. Incorporating Bioavailability
Considerations into the Evaluation of Contaminated Sediment Sites. CS-1. Interstate
Technology and Regulatory Council, Contaminated Sediments Team. Washington, DC.
February.
NJDEP (New Jersey Department of Environmental Protection). 2013. Development of a
Dilution-Attenuation Factor for the Impact to Ground Water Pathway. Trenton, NJ.
November.
NRC. 2003. Bioavailability in Soils and Sediments: Processes, Tools, and Applications. National
Academies Press. Washington, DC.
NRC. 2009. Science and Decisions: Advancing Risk Assessment. National Academies Press.
Washington, DC.
NRC. 2013. Environmental Decisions in the Face of Uncertainty. National Academies Press.
Washington, DC.
TxDOT (Texas Department of Transportation). 2011. Laboratory and Field Evaluations of
External Sulfate Attack in Concrete (FHWA/TX-11/0-4889-1). Prepared for TxDOT by T.
Drimalas, J.C. Clement, K.J. Folliard, R. Dhole, and M.D.A Thomas of The University of
Texas at Austin.
U.S. EPA (United States Environmental Protection Agency). 1974. Basic Environmental Statistics
Notebook (EPA-43Q/1-74-QQ4). Water Programs Operations. Washington, DC. May.
U.S. EPA. 1987. Screening Survey of Industrial Subtitle D Establishments. Prepared for EPA
by K. Shroeder, R. Clickner, and E. Miller of Westat, Inc., under EPA Contract 68-01-7359.
December.
U.S. EPA. 1989. Risk Assessment Guidance for Superfund: Volume I - Part A (EPA/540/1-
89/002). Office of Solid Waste and Emergency Management. December.
U.S. EPA. 1992a. Guidelines for Exposure Assessment (EPA/600/Z-92/001). Risk Assessment
Forum. Washington DC. May.
U.S. EPA. 1992b. Guidance on Risk Characterization for Risk Managers and Risk Assessors.
Office of the Administrator. Washington, DC. May.
U.S. EPA. 1996. Soil Screening Guidance: Technical Background Document (EPA/540/R-
95/128). Office of Solid Waste and Emergency Response. Washington, DC. May.
U.S. EPA. 1997a. Guiding Principles for Monte Carlo Analysis (EPA/630/R-97/001). Risk
Assessment Forum. Washington, DC. March.
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Beneficial Use Compendium References
U.S. EPA. 1997b. Mercury Study Report to Congress (EPA/452/R-97/003). Office of Air
Quality Planning and Standards and Office of Research and Development. Washington,
DC. December.
U.S. EPA. 2000a. Options for Development of Parametric Probability Distributions for
Exposure Factors (EPA/600/R-00/058). Office of Research and Development. Washington,
DC. July.
U.S. EPA. 2000b. Risk Characterization Handbook (EPA/100/B-00/002). Office of Research
and Development. December.
U.S. EPA. 2001. Risk Assessment Guidance for Superfund: Volume III - Part A, Process for
Conducting Probabilistic Risk Assessment (EPA/540/R-02/002). Office of Solid Waste and
Emergency Management. December.
U.S. EPA. 2002. Calculating Upper Confidence Limits for Exposure Point Concentration at
Hazardous Waste Sites (OSWER 9285.6-10). Office of Emergency and Remedial Response.
Washington, DC. December.
U.S. EPA. 2003a. A Summary of General Assessment Factors for Evaluating the Quality of
Scientific and Technical Information (EPA/100/B-03/001). Science Policy Council.
Washington, DC. June.
U.S. EPA. 2003b. The Framework for Cumulative Risk Assessment (EPA/630/P-02/001F). Risk
Assessment Forum. Washington, DC. May.
U.S. EPA. 2009. Characterization of Coal Combustion Residues from Electric Utilities -
Leaching and Characterization Data (EPA-600/R-09/151). Office of Research and
Development, National Risk Management Research Laboratory, Research Triangle Park,
NC. December.
U.S. EPA. 2010b. Risk Characterization Handbook (EPA/100/B-00/002). Office of Research
and Development. Washington, DC. December.
U.S. EPA. 2011. Exposure Factors Handbook: 2011 Edition (EPA/600/R-090/052F). Office of
Research and Development. Washington, DC.
U.S. EPA. 2013. ProUCL Version 5.0.00 Technical Guide: Statistical Software for Environmental
Applications for Data Sets with and without Nondetect Observations (EPA/600/R-07/041).
Office of Research and Development. Washington, DC. September.
U.S. EPA. 2014. Framework for Human Health Risk Assessment to Inform Decision Making
(EPA/100/R-14/001). Office of Science Advisor. Washington, DC. April
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Appendix
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Beneficial Use Compendium Appendix
Disclaimer
This document ("the beneficial use compendium" or "the compendium") "was prepared by the
United States Environmental Protection Agency ("EPA" or "the Agency") Office of Land and
Emergency Management. The beneficial use compendium and the methodology it references are
intended to be useful to those "who conduct or review beneficial use evaluations, as "well as other
interested stakeholders, including states, local governments, tribal authorities, regulated
communities, and the general public. The information contained in the compendium is based on
the Agency's current understanding of the range of issues and circumstances involved "with the
beneficial use of industrial non-hazardous secondary materials ("secondary materials"). It is not
intended to address the combustion of non-hazardous secondary materials for energy, the
use/reuse of municipal solid waste, or the regulation of hazardous waste. Use of the beneficial use
compendium is voluntary and does not change or substitute for any federal or state statutory or
regulatory provisions or requirements. The compendium does not preclude the use of any other
available approaches. Nothing in the compendium is intended to establish binding requirements
on EPA or any other entity. Accordingly, EPA may revise or depart from the approach outlined in
the beneficial use compendium and the methodology it references at any time, "without prior
notice. Any reference to specific commercial products, process or service by trade name,
trademark, manufacturer or otherwise does not constitute or imply its endorsement,
recommendation or favoring by the United States government. Such references are provided for
informational purposes only.
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Beneficial Use Compendium Appendix
Table of Contents
Introduction A-5
A. 1 Planning And Scoping A-6
A. 1.1 General Resources A-6
A. 1.2 Specific Points of Contact A-8
American Association of State Highway and Transportation Officials (AASHTO) A-8
Association of State and Territorial Solid Waste Management Officials (ASTSWMO) A-8
Industrial Resource Council (IRC) A-8
Interstate Technology and Regulatory Council (ITRC) A-9
National Center for Manufacturing Sciences (NCMS) A-9
Northeast Waste Management Officials' Association (NEWMOA) A-9
Recycled Materials Resource Center (RMRC) A-9
U.S. Army Corp of Engineers A-10
U.S. Department of Agriculture (USDA) A-10
U.S. Department of Transportation (U.S. DOT) A-10
U.S. Environmental Protection Agency (U.S. EPA) A-10
A.2 Stressor Characterization A-11
A.2.1 General Resources A-11
A.2.2 Specific Stressor Categories A-12
Asbestos A-12
Chlorinated Dibenzo-p-Dioxins and Chlorodibenzofurans (CDD/Fs) A-12
Metals A-12
Particulate Matter A-13
Pesticides A-13
Radionuclides A-13
Semi-Volatile Organic Compounds (SVOCs) A-14
Volatile Organic Compounds (VOCs) A-14
A.3 Environmental Releases A-15
A.3.1 General Resources A-15
A.3.2 Specific Analytical Methods A-16
ASTM Method D3987-06: Shake Extraction of Solid Waste with Water A-16
EPA Method 1311: Toxicity Characteristic Leaching Potential (TCLP) A-16
EPA Method 1312: Synthetic Precipitation Leaching Procedure (SPLP) A-17
EPA Method 1313: Liquid-Solid Partitioning as a Function of Eluate pH for Constituents in
Solid Materials Using a Parallel Batch Extraction Procedure A-17
EPA Method 1314: Liquid-Solid Partitioning as a Function of Liquid-to-Solid Ratio for
Constituents in Solid Materials Using an Up-flow Percolation Column Procedure A-18
EPA Method 1315: Mass Transport Rates of Constituents in Monolithic or Compacted
Granular Materials Using a Semi-dynamic Tank Leaching Procedure A-18
EPA Method 1316: Liquid-Solid Partitioning as a Function of Liquid-to-solid Ratio for
Constituents in Solid Materials Using a Parallel Batch Extraction Procedure A-19
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Beneficial Use Compendium Appendix
A.4 Data Quality A-20
A.4.1 General Resources A-20
A.5 Statistical Methods A-22
A.5.1 General Resources A-22
A.6 Screening Benchmarks A-24
A.6.1 General Resources A-24
A.6.2 Specific Human Health Benchmarks A-24
Maximum Contaminant Levels (MCLs) A-25
National Ambient Air Quality Standards (NAAQs) A-25
National Recommended Water Quality Criteria (NRWQC) A-26
Preliminary Remediation Goals (PRGs) for Radionuclides A-26
Regional Screening Levels (RSLs) A-27
Secondary Maximum Contaminant Levels (SMCLs) A-27
A.6.3 Specific Ecological Benchmarks A-28
Ecological Soil Screening Levels (Eco-SSLs) A-28
ECORISK Database A-28
Great Lakes Initiative Clearinghouse A-29
National Recommended Water Quality Criteria (NRWQC) A-29
Risk Assessment Information System Database A-30
Screening Quick Reference Tables (SQuiRTs) A-30
A.7 Toxicity Values A-31
A.7.1 General Resources A-31
A.7.2 Specific Human Health Toxicity Values A-33
California Environmental Protection Agency (CalEPA) A-33
Health Effects Assessment Summary Tables (HEAST) A-33
Integrated Risk Information System (IRIS) A-34
Provisional Peer-Reviewed Toxicity Values (PPRTVs) A-34
Minimum Risk Levels (MRLs) A-34
A.7.3 Specific Ecological Toxicity Data A-35
Ecological Toxicology (ECOTOX) Database A-35
ECORISK Database A-35
Great Lakes Initiative Clearinghouse A-35
A.8 Exposure Factors A-36
A.8.1 General Resources for Human Exposure A-36
A.8.2 General Resources for Ecological Exposure A-37
A.9 Fate And Transport Models A-38
A.9.1 General Resources A-38
A.9.2 Specific Fate and Transport Models A-39
American Meteorological Society/EPA Regulatory Model (AERMOD) A-39
American Meteorological Society/EPA Regulatory Model Screen (AERSCREEN) A-40
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Beneficial Use Compendium Appendix
California Total Exposure (CalTOX) Model A-41
EPA Composite Model for Leachate Migration with Transformation Products (EPACMTP) A-42
HYDRUS-1D A-43
Industrial Waste Air (IWAIR) Model A-44
Industrial Waste Management Evaluation Model (IWEM) A-45
Metal Speciation Equilibrium for Surface and Ground Water (MINTEQA2) A-46
Modular Three-Dimensional Transport Multi-Species (MT3DMS) Model A-47
Total Risk Integrated Methodology (TRIM); TRIM.FaTE Module A-48
WiscLeach A-49
A. 10 Risk Calculation A-50
A. 10.1 General Resources A-50
A. 11 Final Characterization A-54
A.11.1 General Resources A-54
A-4
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Beneficial Use Compendium Appendix
Introduction
This appendix is intended to be a library of resources that can aid in the development and
review of beneficial use evaluations. These resources represent publicly available guidance
documents, data sources, software programs and other materials compiled from EPA, federal
and state agencies, academic institutions and private organizations. The primary aim of this
appendix is to make these disparate resources more accessible by assembling them all in one
location. All of the citations and external weblinks presented in this appendix are current as
of the publication of this document.
The resources presented in this appendix were selected for their general applicability. EPA
recognizes that many of these resources were originally developed specifically to address
Superfund and other contaminated waste sites; however, many aspects of these resources are
also germane to the evaluation of environmental impacts that may result from the beneficial
use of secondary materials. More tailored resources may be available from specific regions or
states.
To help place these resources into context, this appendix is structured to loosely parallel the
discussion in the main document. Each section addresses a single, general topic and provides
some available resources relevant to that topic. EPA has made no attempt to rank the different
resources based on potential relevance, as the scope of different beneficial use evaluations can
vary considerably. Instead, to aid in navigation, each resource has been categorized as either
general or specific:
• General resources provide a broad discussion or guidance for a given topic. These
resources are typically finalized documents that will not be subject to change. Therefore,
they are organized by the date of publication. Where older documents have been
updated, each of the editions are provided for historical context.
• Specific resources are existing tools that can be used directly in a beneficial use evaluation
with little or no modification. These resources are more likely to be updated periodically.
Therefore, these resources are organized alphabetically.
A given section may present one or both type of resource, based on what was available at the
time this appendix was compiled. These resources are provided for informational purposes
only. Inclusion in this appendix does not impose an obligation to consider or rely upon any
of the resources listed here, nor does it indicate that any of these materials are the most
appropriate or most applicable for any given evaluation. Professional judgment should be
used when reviewing and incorporating the information in these resources, as some of their
conclusions may be based on subjective interpretation of available data. Different conclusions
may be appropriate for a given beneficial use evaluation based on policy, precedent,
evaluation-specific considerations or other pertinent factors.
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Appendix
A.I Planning and Scoping
The following compilation of resources supplements the discussion of planning and scoping
provided in Section 2 of this document. The resources contain recommendations on how to
define the scope and analytical framework for a risk assessment. These principles can also be
applied to beneficial use evaluations to define the conceptual model, potential data needs, a
realistic schedule for completion, and outside parties that may be able to provide assistance.
A.I.I General Resources
Date:
Title:
Author:
Details:
September 1986
Standard Scenarios for Estimating Exposure to Chemical Substances During Use of
Consumer Products
U.S. EPA/Office of Toxic Substances
This document provides standard scenarios that can be used to derive exposure
estimates for chemical substances in consumer products. It presents values for some
parameters required to estimate exposure drawn from available, published sources of
information.
Date:
Title:
Author:
Details:
May 1998
Guidelines for Ecological Risk Assessment, Chapter 2: Planning the Risk Assessment
and Chapter 3: Problem Formulation Phase
U.S. EPA/Office of the Science Advisor
These chapters describe the basic structure and starting principles for evaluating
scientific information on the adverse effects of stressors on the environment to
improve the quality and consistency of ecological risk assessments.
Date:
Title:
Author:
Details:
Date:
Title:
Author:
Details:
December 2001
Risk Assessment Guidance for Superfund (RAGS) Volume I — Part D, Chapter 3:
Risk Assessment Data Needs and Tasks During the Remedial Investigation
U.S. EPA/Office of Solid Waste and Emergency Response (OSWER)
This chapter describes EPA guidance on the data requirements for conducting human
health risk assessments at Superfund sites. It discusses the different planning tables
that have been developed to encourage clear and consistent documentation of
important data, calculations and conclusions during planning and scoping.
December 2000
Risk Characterization Handbook, Chapter 2: Preparing for a Risk Assessment and its
Risk Characterization — Planning and Scoping
U.S. EPA/Science Policy Council
This chapter explains the goals and principles of risk characterization, the importance
of planning and scoping for a risk assessment, the essential elements to address in a
risk characterization, the factors that risk managers consider in decision-making, and
the forms the risk characterization takes for different audiences.
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Appendix
;
Date: January 2002
Title: Lessons Learned on Planning and Scoping for Environmental Risk Assessments
Author: U.S. EPA/Science Policy Council
Details: Intended to encourage formal planning and scoping practices to improve
environmental risk assessments, this document provides lessons learned from case
studies following the release of the 1997 document Guidance on Cumulative Risk
Assessment—Part 1: Planning and Scoping.
Date:
Title:
Author:
Details:
Date:
Title:
Author:
Details:
September 2006
A Framework for Assessing Health Risk of Environmental Exposures to Children,
Chapter 3: Lifestage-Specific Problem Formulation
U.S. EPA/Office of Research and Development (ORD)
This document provides an overarching framework for a more complete assessment
of children's exposure to environmental agents and the resulting potential health risks
within the EPA risk assessment paradigm. This chapter includes information on
planning and scoping to help characterize exposures and outcomes during all
developmental life stages, creating a conceptual model, and preparing an analysis plan.
2009
Science and Decisions: Advancing Risk Assessment, Chapter 3: The Design of Risk
Assessments
National Research Council
This chapter discusses planning, scoping and problem formulation. Elements of scope
to consider during planning and scoping, methodology considerations in problem
formulation, and major elements of an analysis plan are presented in this chapter.
Date: April 2014
Title: Framework for Human Health Risk Assessment to Inform Decision Making, Chapter
2: Initiation of the Risk Assessment Process and Chapter 3: Public, Stakeholder and
Community Involvement.
Author: U.S. EPA / Risk Assessment Forum
Details: This document is intended to provide information on the overarching process for
conducting human health risk assessments. These chapters includes information on
how to conduct planning and scoping, problem formulation and stakeholder
engagement.
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Appendix
A.I.2 Specific Points of Contact
These tables list some federal, state and nongovernmental organizations that have experience
with the beneficial use of secondary materials. It may be useful to seek input from these or
other parties during planning and scoping. These organizations may be able to share data or
other pertinent information on a proposed beneficial use, similar beneficial uses, or the
secondary materials incorporated into these uses.
American Association of State Highway and Transportation Officials (AASHTO)
Overview:
AASHTO is a nonprofit, nonpartisan association representing highway and
transportation departments in the 50 states, the District of Columbia and Puerto
Rico. It represents all five transportation modes: air, highways, public
transportation, rail and water. Its primary goal is to foster the development,
operation and maintenance of an integrated national transportation system. The
AASHTO Center for Environmental Excellence offers products and programs for
technical assistance, training, information exchange, partnership-building
opportunities and quick access to environmental tools.
Website:
environment.transportation.org/environmental issues/waste manage reeve/
Association of State and Territorial Solid Waste Management Officials (ASTSWMO)
The ASTSWMO Solid Waste Subcommittee established a Beneficial Use Task Force
to study how different states manage requests to allow the beneficial use of non-
Overview: hazardous, secondary materials. The task force's primary goal is to collect and
share information that will assist U.S. states and territories in developing or
improving programs and processes to handle these requests.
Website:
www.astswmo.org/main/mmp pubs.html
Industrial Resource Council (IRC)
Overview:
The IRC is a collaboration of nonprofit industry associations working together to
promote the appropriate use of materials generated by key national
manufacturing sectors. The IRC partners with the U.S. EPA, the Federal Highway
Administration, AASHTO and the Recycled Materials Resource Center in
supporting the appropriate use of secondary materials in transportation,
construction and other applications. These efforts include the development of
codes, standards and regulatory guidance, the documentation of field projects
involving secondary materials.
Website:
www.industrialresourcescouncil.org/
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Beneficial Use Compendium Appendix
Interstate Technology and Regulatory Council (ITRC)
The ITRC is a public-private coalition working to reduce barriers to the use of
innovative environmental technologies that reduce compliance costs and
Overview: maximize cleanup efficacy. ITRC produces documents and training intended to
broaden and deepen technical knowledge and expedite quality regulatory
decision making while protecting human health and the environment.
Website: www.itrcweb.org
National Center for Manufacturing Sciences (NCMS)
NCMS is a nonprofit, membership-based consortium. Membership is limited to
organizations which have a substantial manufacturing presence in North
_ . America. The organization developed and maintains a site that identifies state
Overview:
regulations and programs related to the beneficial use of secondary materials.
Searches can be done by either state or secondary material. In addition, provides
links to potential points of contact in each state, and in other organizations.
Website: www.beneficialuseportal.org
Northeast Waste Management Officials' Association (NEWMOA)
NEWMOA is an inter-state association consisting of Connecticut, Maine,
Massachusetts, New Hampshire, New Jersey, New York, Rhode Island and
Vermont. The organization was established to coordinate the inter-state handling
Overview: of hazardous and solid waste, pollution prevention, and waste site cleanup
activities. Part of the organization's stated mission is to implement
environmentally sound solutions for proper reuse and recycling discarded
materials that have value.
Website: www.newmoa.org
Recycled Materials Resource Center (RMRC)
The mission of the RMRC is to test, evaluate and develop guidelines for recycled
materials and to provide outreach to reduce barriers to the use of recycled
. _ materials in highways. The advisory board includes representatives from United
States Department of Transportation (DOT) Federal Highway Administration
(FHWA), U.S. EPA, New Hampshire DOT, AASHTO, ASTSWMO, industry, and
highway trade associations.
Website: rmrc.wisc.edu
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Beneficial Use Compendium Appendix
U.S. Army Corp of Engineers
The Army Corps of Engineers works to develop and maintain the navigable waters
. _ of the Unites States. The agency has experience with the beneficial use of dredged
sediment and secondary materials in infrastructure and habitat restoration
projects.
Website: www.usace.armv.mil
U.S. Department of Agriculture (USDA)
The USDA Cooperative State Research, Education, and Extension Service
maintains offices that may be able to provide useful information on the beneficial
Overview: use of secondary materials in agriculture. These offices are located in a network
of local or regional offices, as well as in the land-grant universities of each state
and territory.
Website: www.csrees.usda.gov/Extension
U.S. Department of Transportation (U.S. DOT)
The Federal Highway Administration (FHWA) is an agency within the U.S. DOT
that supports state and local governments in the design, construction, and
. _ maintenance of the Nation's highway system (Federal Aid Highway Program)
and various federally and tribal owned lands (Federal Lands Highway Program).
The FHWA has established policy for the recycling of aggregates and other
highway construction materials in roadway construction.
Website: www.fhwa.dot.gov/pavement/recvcling/index.cfm
U.S. Environmental Protection Agency (U.S. EPA)
The U.S. EPA Sustainable Materials Management (SMM) Program was
established to support the productive and sustainable use/reuse of resources
_ . _ throughout all stages of their life cycles, from resource acquisition through
disposal. The SMM Program seeks to avoid or minimize impacts to the
environment while also accounting for economic efficiency and social
considerations.
Website: www.epa.gov/smm/sustainable-management-industrial-byproducts
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Beneficial Use Compendium
Appendix
A.2 Stressor Characterization
The following compilation of resources supplements the discussion of stressor characterization
provided in Section 2. These resources describe the sources, the physical and chemical
properties, and the environmental behavior of various stressors. This information can be used
during planning and scoping to help identify the types of stressors associated with an secondary
material or beneficial use and the routes through which these stressors may be released into
the surrounding environment.
A.2.1 General Resources
Date:
Title:
Author:
Details:
February 2009
Biota-Sediment Accumulation Factor (BSAF) Dataset
U.S. EPA/ORD
This dataset includes approximately 20,000 BSAFs for non-ionic, organic chemicals
(e.g., polyaromatic hydrocarbons) collected from 20 different locations. Data are
available for species such as lobster, crayfish and benthic invertebrates in
freshwater, tidal and marine ecosystems. The purpose of the dataset is to provide
tools to: 1) evaluate the reasonableness of BSAFs measured from other locations; 2)
build a BSAF dataset for other locations; 3) conduct a bounding assessment of risks
for locations where limited or no bioaccumulation data are available; 4) identify
underlying relationships and dependences of BSAFs on ecosystem conditions and
parameters; and 5) compare polychlorinated biphenyl, polychlorinated dibenzo-p-
dioxin and polychlorinated dibenzofuran residues to residue-effects data.
Date: November 2012 (Version 4.11)
Title: Estimation Program Interface (EPI) Suite Software
Author: U.S. EPA/Office of Pollution Prevention and Toxics and Syracuse Research Corp.
Details: This software provides users with screening-level estimates of the physical, chemical
and environmental fate properties of over 40,000 chemicals. The suite is composed
of 17 individual models that provide information on specific chemical properties.
The only input required to run each model is the chemical structure of the stressor.
This chemical structure can be identified through a Chemical Abstract Service
number or using the name lookup function.
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Appendix
A.2.2 Specific Stressor Categories
The following tables briefly describe some general categories of stressors that are most likely
to be associated with secondary materials. This list is provided as a reference and is not
intended to be comprehensive. There may be many individual stressors grouped under each
category, based on similar chemical structures or other commonalities. However, the mobility
and toxicity of the different stressors within a category can vary greatly. Thus, while an
understanding of the general categories of stressors that may be present can provide valuable
information during planning and scoping, it is important to also identify and characterize each
of the specific stressors.
Asbestos
Overview:
Asbestos is the name given to a group of naturally occurring silicate minerals
that are resistant to heat and corrosion. Asbestos has historically been used in
a number of products, such as insulation for pipes (e.g., steam lines), floor tiles
and other building materials. As a result, asbestos is most likely to be
associated with construction and demolition debris. The asbestos contained
in these materials is referred to as friable if it can be crumbled, pulverized or
reduced to a powder by the pressure of an ordinary human hand. The most
likely exposure route for asbestos is the inhalation of airborne particulates.
Further
Information:
cfpub.epa.gov/ncea/iris/iris documents/documents /toxreviews/1 02 6tr.pdf
www.atsdr.cdc.gov/asbestos/
Chlorinated Dibenzo-p-Dioxins and Chlorodibenzofurans (CDD/Fs)
Overview:
CDD/Fs are a family of chlorinated organic compounds that have either a
dioxin or furan as the central ring, and are sometimes referred to simply as
"dioxins" and "furans." The largest source of CDD/Fs in the environment is as
an unintentional byproduct from industrial processes. Some examples of the
processes that may produce these compounds are the manufacture of certain
pesticides, preservatives, disinfectants and paper products, as well as the low-
temperature combustion of chemical products, plastic, paper and wood. The
most likely exposure routes for CDD/Fs are through the ingestion of
contaminated water, food and dust/soil, although exposures through
inhalation of particulate matter and dermal contact may also occur.
Further
Information:
www.epa.gov/expobox/exposure-assessment-tools-chemical-classes-other-
organics
www.atsdr.cdc.gov/substances/toxchemicallisting.asp?svsid=29
Metals
Overview:
Metals are a broad category of naturally occurring, inorganic elements that are
found throughout the environment. Specific examples include arsenic, lead,
mercury and selenium. Metals cannot be created or destroyed through
biological or chemical processes. However, these processes can alter the
speciation of the metal and complex it into different inorganic or organic
compounds. These changes have the potential to affect both mobility in the
environment and toxicity to receptors. Although metals are often discussed as
isolated elements, few metals are found alone in the environment. Common
sources of elevated metal levels are combustion, refinement, distillation or
other procedures that concentrate metals naturally present in the raw
materials (e.g., rocks, ore). The most frequent exposure routes for metals are
through the ingestion of contaminated water, food and dust/soil; the
inhalation of vapor (e.g., elemental mercury) or particulate matter; and dermal
contact.
Further
Information:
www.epa.gov/expobox/exposure-assessment-tools-chemical-classes-
inorganics-and-fibers
www.atsdr.cdc.gov/substances/toxchemicallisting.asp?svsid=37
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Paniculate Matter
Particulate matter is a complex mixture of extremely small solid particles
and/or liquid droplets. These particles may be composed of a number of
different substances, such as acids (e.g., nitrates and sulfates), organic
chemicals, metals and/or soil particles. Particulate matter may be associated
with any granular solid or liquid that can become suspended in the air. Of
Overview: particular concern is the size of the particulate matter, specifically the amount
of the material less than 10 micrometers ("inhalable coarse particulates" or
"PMio") and 2.5 micrometers ("fine particulates" or "PIVh.s") in diameter. These
are the particulates that can pass through the throat and nose and enter into
the lungs. The most likely exposure route for PMio and PIVh.s is the inhalation
of airborne particulates.
Further
Information:
www.epa.gov/pm/
Pesticides
Overview:
A pesticide is any substance used to kill, repel or control certain forms of plant
or animal life that are considered to be pests. They often have a complex
chemical structure and may be either organic or inorganic in nature.
Pesticides used for their intended purpose are often applied to building
materials. As a result, pesticide residues may be associated with construction
and demolition debris. The most frequent exposure routes for pesticides are
through the ingestion of contaminated water, food and dust/soil, the
inhalation of particulate matter, and exposure through dermal contact.
Further
Information:
www.epa.gov/expobox/exposure-assessment-tools-chemical-classes-
pesticides
www.atsdr.cdc.gov/substances/toxchemicallisting.asp?svsid=31
Radionuclides
Radionuclides are a specific subset of metals that have unstable atomic nuclei.
All radionuclides eventually undergo a process called radioactive decay,
wherein the atomic structure of the element changes, often accompanied by
the release of ionizing radiation (e.g., alpha particles, gamma rays). Like other
inorganics, most radionuclides in the environment are found complexed with
inorganic or organic compounds. However, this complexation does not affect
Overview: the rate or risk of radioactive decay for an atom. Common sources of elevated
radionuclide levels are combustion, refinement, distillation or other
procedures that concentrate metals naturally present in the raw materials
(e.g., rocks, ore). The most frequent exposure routes for radionuclides are
through the ingestion of contaminated water, food and dust/soil, the
inhalation of gas (e.g., radon) or particulate matter, exposure through dermal
contact, and direct exposure to external radiation.
Further
Information:
www.epa.gov/radiation
www.atsdr.cdc.gov/substances/toxchemicallisting.asp?svsid=27
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Semi-Volatile Organic Compounds (SVOCs)
Overview:
SVOCs are any organic compounds that have boiling points in the vicinity of
240 to 400°C. Examples of some broad classes of SVOCs include polyaromatic
hydrocarbons (PAHs), phenols and phthalates. Some examples of the
processes that can produce these compounds are primary aluminum and coke
production, products containing plasticizers, petrochemical refinement,
rubber tire and cement manufacturing, bitumen and asphalt industries, wood
preservation, and the low-temperature combustion of chemical products,
plastic, paper and wood. The most frequent exposure routes for SVOCs are
through the ingestion of contaminated water, food and dust/soil, the
inhalation of particulate matter, and exposure through dermal contact.
Further
Information:
www.epa.gov/expobox/exposure-assessment-tools-chemical-classes-other-
organics
PAHs: www.atsdr.cdc.gov/substances/toxsubstance.asp?toxid=25
Phthalates: www.atsdr.cdc.gov/substances/toxchemicallisting.asp?svsid=41
Volatile Organic Compounds (VOCs)
Overview:
VOCs are organic compounds that will readily evaporate around normal
indoor atmospheric conditions. Examples of common VOCs include benzene,
trichloroethane, trichloroethylene and xylene. Some examples of the
processes that produce these compounds are the production and use of
adhesives, solvents, paints, resins, varnish, lithography and printing, vinyl
coating and asphalt. The most frequent exposure routes for VOCs are through
the ingestion of contaminated water, food and dust/soil, the inhalation of
vapor or particulate matter, and exposure through dermal contact.
Further
Information:
www.epa.gov/expobox/exposure-assessment-tools-chemical-classes-other-
organics
www.atsdr.cdc.gov/substances/toxchemicallisting.asp?svsid=7
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A.3 Environmental Releases
The following compilation of resources supplements the discussion of stressor identification
and characterization in Section 2. These resources detail methods that can be used to estimate
the stressor levels present in an secondary material or beneficial use and the rate at which
these stressors may be released into surrounding media based on the prevailing environmental
conditions. These references can be used to help determine which methods will generate data
best suited for a particular evaluation or, when an evaluation relies solely on published data,
an understanding of the assumptions built into the procedures for these and similar methods
can help determine whether the data generated are representative of the beneficial use under
evaluation.
A.3.1 General Resources
Date: February 2014
Title: Methods for Evaluating Solid Waste, Physical/Chemical Methods (SW-846)
Author: U.S. EPA/OSWER
Details: This manual provides test procedures and guidance approved by EPA, which are
recommended for use in conducting the evaluations and measurements needed to
comply with the RCRA. This manual presents the state-of-the-art in routine
analytical tests adapted for the RCRA program. Contains procedures for field and
laboratory quality control, sampling, determining hazardous constituents in
wastes, determining the hazardous characteristics of wastes, and for determining
physical properties of wastes. It also contains guidance on how to select
appropriate methods. The methods presented have been validated for the specific
set of environmental media and constituents listed for each method. However, a
given method may be relevant to additional media and constituents, provided the
user can demonstrate the appropriateness of the intended application.
Date: December 2014
Title: LeachXS Lite (version 2.0.38)
Author: U.S. EPA/ORD
Details: LeachXS Lite™ is a data management and visualization tool and an essential part of
the Leaching Environmental Assessment Framework (LEAF). The tool allows users
to evaluate and characterize the release of material constituents based on
comparisons derived from leaching test results for a wide range of materials and
waste types (e.g., secondary or recycled materials, stabilized waste and construction
materials). Users that want to work with leaching test results (e.g., EPA Methods
1313 through 1316) of their own can use Microsoft Excel® templates for uploading
data into LeachXS database.
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A.3.2 Specific Analytical Methods
The following tables detail several methods developed by EPA and other organizations that
can simulate the release of stressors from secondary materials and beneficial uses. These tables
provide a general description of each method and highlight the specifications for sample
preparation and release simulation that determine how well these releases reflect the range of
conditions a beneficial use may be exposed to in the real world.
ASTM Method D3987-06: Shake Extraction of Solid Waste with Water
Overview:
This method is a batch leaching test designed to estimate releases of
inorganics and non-volatile organics from granular solid materials.
Leachate is produced by mixing the solid sample with unbuffered water and
agitating the mixture continuously for around 18 hours. The water is then
filtered and analyzed for constituent concentrations. The method is
intended to provide equilibrium liquid-solid partitioning at the natural pH
of the material.
Release Type:
Solid
Liquid
Gas
Specifications:
Assumes that there is enough contact time to achieve equilibrium
between the liquid and solid phases. This may overestimate releases if
liquid passes through or over the material quickly.
The material is finely ground before sampling. May overestimate
releases if the material is monolithic.
The leachant is unbuffered, distilled water (pH « 7.0). Sample will tend
to reflect the natural pH conditions of the material in isolation. However,
these conditions may overestimate or underestimate actual releases if
the prevailing conditions driven by the surrounding media are different.
The liquid to solid (L/S) ratio is 20:1. This is a point estimate of releases
and does not provide information on how releases may change as the
cumulative L/S ratio increases.
Website:
www.astm.org/Standards/D3987.htm
EPA Method 1311: Toxicity Characteristic Leaching Potential (TCLP)
Overview:
Method 1311 is a batch leaching test designed to estimate releases of
inorganic and organic compounds from solids and liquids. Leachate is
produced by mixing solid test samples with water buffered to a pH around 2.9
and agitating the mixture continuously for around 18 hours. This leachate or
any liquid samples are then filtered and analyzed for constituent
concentrations. The method is intended to provide equilibrium liquid-solid
partitioning under typical conditions found in a municipal solid waste landfill.
Release Type:
Solid
Liquid
Gas
Considerations:
Assumes that there is enough contact time to achieve equilibrium between
the liquid and solid phases. May overestimate releases if liquid passes
through or over the beneficial use quickly.
The material is finely ground before sampling. May overestimate releases if
the beneficial use is monolithic.
Leachant pH is buffered to be acidic (pH « 2.9). These conditions may
overestimate or underestimate actual releases if the prevailing conditions
driven by the surrounding environmental media are different.
The L/S ratio is 20:1. This is a point estimate of releases and does not
provide information on how releases change as the cumulative L/S ratio
increases.
Website:
www.epa.gov/hw-sw846/sw-846-test-method-1311-toxicity-characteristic-
leaching-procedure
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EPA Method 1312: Synthetic Precipitation Leaching Procedure (SPLP)
Overview:
Release Type:
Considerations:
Website:
Method 1312 is a batch leaching test designed to estimate releases of
inorganic and organic compounds from solids and liquids. Leachate is
produced by mixing solid test samples with water buffered to a pH around 4.2
and agitating the mixture continuously for around 18 hours. This leachate or
any liquid samples are then filtered and analyzed for constituent
concentrations. The method is intended to provide equilibrium liquid-solid
partitioning under the conditions that mimic acidic rain.
Solid
•/ Liquid
Gas
• Assumes that there is enough contact time to achieve equilibrium between
the liquid and solid phases. May overestimate releases if liquid passes
through or over the beneficial use quickly.
• The material is finely ground before sampling. May overestimate releases if
the beneficial use is monolithic.
• Leachant pH is buffered to be acidic (pH « 4.2). These conditions may
overestimate or underestimate actual releases if the prevailing conditions
driven by the surrounding environmental media are different.
• The L/S ratio is 20:1. This is a point estimate of releases and does not
provide information on how releases change as the cumulative L/S ratio
increases.
www.epa.gov/hw-sw846/sw-846-test-method-1312-svnthetic-
precipitation-leaching-procedure
EPA Method 1313: Liquid-Solid Partitioning as a Function of Eluate pH for Constituents
in Solid Materials Using a Parallel Batch Extraction Procedure
Overview:
Release Type:
Considerations:
Website:
Method 1313 is a batch leaching test designed to estimate releases of
inorganics and non-volatile organics from granular solid materials. A total of
nine leachate samples are produced by mixing solid test samples with water
buffered to one of nine pH values between 2 and 13. The mixtures are then
agitated continuously for between 24 and 74 hours, based on particle size.
This leachate is then filtered and analyzed for constituent concentrations. The
method is intended to provide equilibrium liquid-solid partitioning under the
range of plausible field pH values.
Solid •/ Liquid
Gas
• Assumes that there is enough contact time to achieve equilibrium between
the liquid and solid phases. May overestimate releases if liquid passes
through or over the beneficial use quickly.
• Material is finely ground before sampling to facilitate equilibrium
conditions. May overestimate releases if the beneficial use is monolithic.
• Leachant pH is buffered to nine different levels between 2 and 13 in
different samples to capture the effect of pH on releases.
• The L/S ratio is 10:1. This is a point estimate of releases and does not
provide information on how releases may change as the cumulative L/S
ratio increases.
www.epa.gov/hw-sw846/validated-test-method-1313-liauid-solid-
partitioning-function-extract-ph-using-parallel
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EPA Method 1314: Liquid-Solid Partitioning as a Function of Liquid-to-Solid Ratio for
Constituents in Solid Materials Using an Up-flow Percolation Column Procedure
Overview:
Release Type:
Considerations:
««Tl^-.
Website:
Method 1314 is an up-flow column leaching extraction procedure designed to
estimate releases of inorganics and non-volatile organics from granular solid
materials. Leachate samples are produced by pumping water at a low flow
rate over the material.
This resulting leachate is collected at specified
cumulative L/S ratios, filtered and analyzed for constituent concentrations.
The method is intended
the cumulative L/S ratio
to provide leachate concentrations as a function of
which can be related to a time scale when data on
mean infiltration rate, density and column height are available. The data may
also provide insight into the impact of organic carbon release and the
influence of dissolved
constituents.
Solid
organic carbon on the partitioning of inorganic
•/ Liquid
Gas
• Assumes that there is enough contact time to achieve equilibrium between
the liquid and solid phases. May overestimate releases if liquid passes
through or over the beneficial use quickly.
• Material is finely ground prior to sampling to facilitate equilibrium
conditions. May overestimate releases if the beneficial use is monolithic.
• The leachant is unbuffered, distilled water (pH « 7.0). Sample will reflect
the natural pH conditions of the material in isolation. However, these
conditions may overestimate or underestimate actual releases if the
prevailing conditions driven by the surrounding environmental media are
different.
• Samples are collected at specific cumulative L/S ratios between 0.2:1 and
10:1 to capture the effect of increasing cumulative L/S ratio on releases.
www.epa.gov/hw-sw846/validated-test-method-1314-liquid-solid-
partitioning-function-liquid-solid-ratio
EPA Method 1315: Mass Transport Rates of Constituents in Monolithic or Compacted
Granular Materials Using a Semi-dynamic Tank Leaching Procedure
Overview:
Release Type:
Considerations:
Website:
This
method is a batch leaching test designed to measure releases of inorganics
from monolithic or compacted granular materials. Leachate samples are
produced by placing the test sample in a tank filled with unbuffered water for
a specified time period, at which point the sample is moved to a new tank of
water. This process is repeated nine times. The leachate from each tank is then
filtered and analyzed for constituent concentrations. The method is intended
to provide diffusion-controlled mass transfer rates (release rates). Diffusivity
and tortuosity can be estimated through analysis of the resulting leaching data.
Solid y
Liquid
Gas
• Assumes that there is enough contact time to achieve equilibrium between
the liquid and solid phases. May overestimate releases if liquid passes
through or over the beneficial use quickly.
• The material is either monolithic or compacted into a mold before sampling.
May underestimate releases if the beneficial use is an uncompacted granular
material
• The leachant is unbuffered, distilled water (pH « 7.0). Sample will reflect the
natural pH conditions of the material in isolation. However, these conditions
may overestimate or underestimate actual releases
if the prevailing
conditions driven by the surrounding environmental media are different.
• Samples are collected at five
times at a liquid to surface area ratio of 10:1 to
capture releases over time.
www.eDa.eov/hw-sw846/validated-test-method-1315-mass-transfer-rates-
constituents-monolithic-or-compacted
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EPA Method 1316: Liquid-Solid Partitioning as a Function of Liquid-to-Solid Ratio for
Constituents in Solid Materials Using a Parallel Batch Extraction Procedure
Release Type:
Solid
y
Liquid
Gas
Overview:
Considerations:
This method is a parallel batch leaching test to estimate releases of inorganics
and non-volatile organics from granular solid material. Leachate samples are
produced by placing the test sample in five different tanks filled with unbuffered
water and different L/S ratios, ranging between 0.5:1 and 10:1. The mixtures are
then agitated continuously for between 24 and 74 hours, based on particle size.
The resulting leachate is then filtered and analyzed for constituent
concentrations. The method is intended to provide leachate concentrations as a
function of the L/S ratio. The method also allows identification of the mode of
leaching for constituents (washout or solubility-limited).
Assumes that there is sufficient contact time to achieve equilibrium between
the liquid and solid phases. May overestimate releases if liquid passes through
or over the beneficial use quickly.
Material is finely ground prior to sampling to facilitate equilibrium conditions.
May overestimate releases if the beneficial use is monolithic.
The leachant is unbuffered, distilled water (pH « 7.0). Sample will reflect the
natural pH conditions of the material in isolation. However, these conditions
may overestimate or underestimate actual releases if the prevailing conditions
driven by the surrounding environmental media are different.
Samples are collected at five cumulative L/S ratios between 0.5:1 and 10:1 to
capture the effect of increasing cumulative L/S ratio on releases.
Website:
www.epa.gov/hw-sw846/validated-test-method-1316-liquid-solid-
partitioning-function-liquid-solid-ratio-solid
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Appendix
A.4 Data Quality
The following compilation of resources supplements the discussion of data quality in Section
3 of this document. These resources detail the various factors that can affect data quality, as
well as the available quality assurance/quality control measures that increase confidence in
collected data. This information can help to ensure that primary and secondary data are of
sufficient quality to support defensible conclusions about a beneficial use.
A.4.1
General Resources
Date:
Title:
Author:
Details:
December 1989
RAGS Volume I—Part A, Chapter 5: Data Evaluation
U.S. EPA/OSWER
Describes the process of data evaluation in risk assessments. The outcome of this
evaluation is the identification of a set of chemicals that are likely to be site-related
and reported concentrations of acceptable quality for use in the risk assessment.
Date: May 1992
Title: Guidance for Data Usability in Risk Assessment: Parts A and B
Author: U.S. EPA/OSWER
Details: These documents are designed to provide a consistent basis for making decisions
about the minimum quality and quantity of environmental analytical data
sufficient to support decisions at Superfund sites. Addresses how to design sampling
and analytical activities to meet data quantity and quality needs, procedures for
assessing the quality of data, and options for combining data of varying quality from
different sources.
November 2002
Guidance on Environmental Data Verification and Data Validation
U.S. EPA/Office of Environmental Information
This guidance explains how to implement data verification and data validation in
the context of EPA's Quality System, and provides practical advice and references.
This guidance describes an array of data verification and data validation practices
to promote common understanding and effective communication among
environmental laboratories, field samplers, data validators and data users. This
guidance also describes the related subjects of data integrity (how to help detect
possible falsification of data) and data suitability (how to anticipate and support
decisions about the usability of the data).
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Appendix
Date:
Title:
Author:
Details:
:
June 2003
Summary of General Assessment Factors for Evaluating the Quality of Scientific
and Technical Information
U.S. EPA/Science Policy Council
This document provides information on the considerations that EPA takes into
account when evaluating the quality of scientific and technical information that is
submitted to the Agency, or that is gathered or generated by EPA, for various
Date: February 2006
Title: Data Quality Assessment: A Reviewer's Guide
Author: U.S. EPA/Science Policy Council
Details: This guide provides general guidance to organizations on assessing data quality
criteria and performance specifications for decision-making. EPA has developed a
process for performing the data quality assessment (DQA) process for project
managers and planners to determine whether data are of the type, quantity and
quality needed to support Agency decisions.
Date: February 2006
Title: Data Quality Assessment: Statistical Methods for Practitioners
Author: U.S. EPA/Science Policy Council
Details: This document describes the different statistical methods that can be used in DQAs
when evaluating environmental data sets. A DQA is the scientific and statistical
evaluation of environmental data to determine if they meet the planning objectives
of the project, and are of the right type, quality and quantity to support their
intended use.
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A.5 Statistical Methods
The following compilation of resources supplements the discussion of statistical methods
provided in Section 4 of this document. The resources contain recommendations on how to
select and apply different statistical tests to the comparison of environmental media. These
principles can also be applied to beneficial use evaluations to compare stressor levels present
in or released from a beneficial use and analogous product.
A.5.1 General Resources
May 1974
Basic Environmental Statistics Notebook
U.S. EPA/Water Program Operations
This document introduces the a number of concepts and applications of statistics to
environmentally-oriented studies. Emphasis is placed on parametric tests of
significance and sampling from normally distributed data.
September 2002
Title: Guidance for Comparing Background and Chemical Concentrations in Soil for
CERCLA Sites
Author: U.S. EPA/OSWER
Details: This document is intended to assist with the evaluation of back-ground
concentrations at CERCLA sites. This document recommends statistical methods
for characterizing reliable representation of background concentrations of
chemicals in soil.
Date: September 2002
Title: Statistical Methods in Water Resources
Author: U.S. Department of the Interior/U.S. Geological Survey
Details: This document presents statistical methods likely to be of greatest usefulness to
water resources scientists. Yet all topics can be directly applied to many other types
of environmental data. The document emphasizes topics not always found in
introductory statistics textbooks, and often not adequately covered in statistical
textbooks for scientists and engineers.
Date: March 2009
Title: Statistical Analysis of Ground Water Monitoring Data at RCRA Facilities: Unified
Guidance
Author: U.S. EPA/ ORCR
Details: This documents provides a suggested framework and recommendations for
the statistical analysis of groundwater monitoring data at RCRA facility units
to determine whether ground water has been impacted by a hazardous constituent
release. This document provides examples and background information that will
aid in successfully conducting statistical analyses.
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Date: September 2013
Title: ProUCL Version 5.0.00 User Guide: Statistical Software for Environmental
Applications for Data Sets with and without Nondetect Observations
Author: U.S. EPA/ORD
Details: ProUCL is a tool that provides numerous and varied statistical methods and
graphical tools to address many environmental sampling and statistical issues. It
can be run on environmental data sets with and without nondetect data samples.
Calculating upper statistical limits is a primary function of the software and the
graphical analyses offered includes probability plots, histograms, box plots, and
line/trend plots.
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A.6 Screening Benchmarks
The following compilation of resources supplements the discussion of screening benchmarks
provided in Section 5 of this document. These resources address the development and
application of benchmarks to identify the stressors that do not warrant further evaluation. The
general resources listed below provide models and guidance that can be used to calculate
benchmarks, while the specific resources provide some sources of pre-developed benchmarks.
This information can be used to select appropriate, existing benchmarks or to calculate
evaluation-specific benchmarks. However, the parties conducting the evaluation are
encouraged to engage with the appropriate regulatory bodies during the planning and scoping
process to identify any benchmarks required by state or federal law.
A.6.1 General Resources
Date: June 2009
Title: Integrated Exposure Uptake Bio kinetic (IEUBK) Model Version 1.1
Authors: U.S. EPA/OSWER
Details:
Link:
The IEUBK Model is used to predict the risk of elevated blood lead levels in children
(under the age of seven) that are exposed to environmental lead from many sources.
The model also predicts the risk that a typical child, exposed to specified media lead
concentrations, will have a blood lead level greater or equal to the level associated
with adverse health effects.
www.epa.gov/superfund/lead-superfund-sites-frequent-questions-risk-
assessors-integrated-exposure-uptake
Date: May 2014
Title: Vapor Intrusion Screening Level (VISL) Calculator
Authors: U.S. EPA/OSWER
Details:
Link:
VISL is a spreadsheet calculator that lists chemicals considered to be volatile and
toxic through the inhalation pathway and calculates human health screening levels
for ground water, soil gas and indoor air.
www.epa.gov/vaporintrusion
A.6.2 Specific Human Health Benchmarks
The following tables provide some specific screening benchmarks that have been developed
by EPA and other organizations. These tables provide a summary of each set of values and
highlight the relevant receptors, stressors and media to help determine how well each set of
benchmarks reflects the exposure scenarios anticipated for a given beneficial use evaluation.
The focus of these tables is on the information anticipated to be most pertinent to beneficial
uses, but a given set of benchmarks may include additional media, exposure routes, or stressors.
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Appendix
Maximum Contaminant Levels (MCLs)
Overview:
Media:
Exposures:
Stressors:
Basis:
Developer:
Website:
MCLs are regulatory standards that represent the maximum permissible level
of a contaminant in water delivered to any user of a public water system serving
25 people. They have been developed for approximately 90 constituents and
environmental indicators under the National Primary Drinking Water
Regulations ("NPDWRs" or "primary standards").
V
V
V
Soil
Sediment
Ingestion
Metals
V
V
V
Ground Water
Surface Water
Inhalation
VOCs
V
Air
Fish Tissue
Dermal
SVOCs
Other: Dioxins/Furans, Radionuclides
The development of maximum contaminant level goals (MCLGs) is the first step
in establishing MCLs. For most constituents, MCLGs are set at a level below
which there is no known or expected risk to human health and which allow an
adequate margin of safety. For known or probable human carcinogens, MCLGs
are set equal to zero. MCLs are set as close to MCLGs as practicable after
consideration of the cost and feasibility of available sampling, measurement
and removal technologies.
U.S. EPA/Office of Water
www.epa.gov/ground-water-and-drinking-water/table-regulated-drinking-
water-contaminants
National Ambient Air Quality Standards (NAAQs)
Overview:
Media:
Exposures:
Stressors:
Basis:
Developer:
Website:
NAAQs are regulatory standards established by EPA for six pollutants in
ambient air throughout the United States. Standards are set as a maximum
allowable concentration averaged over a given timeframe.
y
y
Soil
Sediment
Ingestion
Metals
y
Ground Water
Surface Water
Inhalation
VOCs
y
Air
Fish Tissue
Dermal
SVOCs
Other: Particulate Matter
Notes: Standards are available for carbon monoxide, lead, nitrogen dioxide,
ozone, particulate matter and sulfur dioxide.
NAAQS are based on comprehensive studies of available ambient air
monitoring data, health effects data, and material effects studies.
• Primary standards are designed to protect human health, with an adequate
margin of safety, including sensitive populations such as children, the
elderly and people suffering from respiratory diseases.
• Secondary standards are designed to protect public welfare from any
known or anticipated adverse effects of a pollutant (e.g., unacceptable
damage to crops and vegetation, buildings and property, and ecosystems).
U.S. EPA/Office of Air
www.epa.gov/criteria-air-pollutants/naaqs-table
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National Recommended Water Quality Criteria (NRWQC)
Overview:
Media:
Exposures:
Stressors:
Basis:
Developer:
Website:
NRWQC, also known as ambient water quality criteria (AWQC), are values
developed by EPA to protect human and ecological health from the harmful
effects of pollutants in surface water.
y
Soil
Sediment
Ingestion
y
y
Ground Water
Surface Water
Inhalation
y
Air
Fish Tissue
Dermal
Additional Notes: Ingestion benchmarks are developed for both for the
consumption of water and aquatic organisms (e.g., fish) together and for
consumption of organisms alone. Inhalation is considered together with
ingestion in non-cancer screening benchmarks.
y
y
Metals
y
VOCs
Other: Dioxin/Furan, pH, Suspended Solids,
y
SVOCs
Turbidity
• Human health benchmarks for carcinogens are based on a IxlO"6 excess
lifetime cancer risk.
• Human health benchmarks for non-carcinogens are based on an HQ of 1, the
threshold below which adverse effects are not known to occur.
U.S. EPA/Office of Water
www.epa.eov/wqc/national-recommended-water-qualitv-criteria
Preliminary Remediation Goals (PRGs) for Radionuclides
Overview:
Media:
Exposures:
Stressors:
Basis:
Developer:
Website:
PRGs are screening benchmarks for human health derived from equations
combining exposure assumptions with chemical-specific toxicity values. Users
may select from default screening benchmarks or may calculate their own using
the PRG Calculator.
y
y
y
y
y
Soil
Sediment
y
y
Ground Water
Surface Water
y
y
Air
Fish Tissue
Other: Produce, Two-Dimensional Surfaces, Three-Dimensional
Buildings
Ingestion
y
Inhalation
Dermal
Other: External Exposure
Notes: Default screening benchmarks are developed both for each individual
exposure route and for all exposure routes considered together.
y
Metals
VOCs
SVOCs
Other: Radionuclides
• Default PRGs for carcinogens are based on a IxlO"6 cancer risk.
• User-defined PRGs are generated by the calculator based on a cancer risk
selected by the user.
U.S. EPA/OSWER and Oak Ridg
Soil/ water/air PRGs:
Outdoors hard surface PRGs:
Indoor building PRGs:
;e National Laboratory (ORNL)
epa-prgs.ornl.gov/radionuclides/
epa-sprg.ornl.gov/
epa-bprg.ornl.gov/
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Appendix
Regional Screening Levels (RSLs)
Overview:
Media:
Exposures:
Stressors:
Basis:
Developer:
Website:
RSLs are benchmarks derived for multiple media from equations combining
exposure assumptions with chemical-specific toxicity values. Users may select
from default screening benchmarks or may calculate their own using the
calculator.
V
V
V
Soil
Sediment
Ingestion
V
V
V
Ground Water
Surface Water
Inhalation
V
V
V
Notes: Screening benchmarks are developed both for each
route and for all exposure routes considered together.
Air
Fish Tissue
Dermal
individual exposure
V
V
Metals
V
Other: Dioxin/Furan
VOCs
V
SVOCs
* Default values for carcinogens are based on a IxlO'6 cancer risk.
• Default values for non-carcinogens are based on a hazard quotients of 0.1 or
1.
• User-defined values are generated by the RSL calculator based on a cancer
risk or hazard quotient selected by the user.
U.S. EPA/Regions 3, 6 and 9, and ORNL
www.epa.gov/risk/regional-screening-levels-rsls
Secondary Maximum Contaminant Levels (SMCLs)
Overview:
Media:
Exposures:
Stressors:
Basis:
Developer:
Website:
SMCLs, also called National Secondary Drinking Water Regulations (NSDWRs),
set non-mandatory water quality standards. EPA does not enforce these
secondary levels. They are established only as guidelines to assist public water
systems in managing their drinking water for aesthetic considerations, such as
taste, color and odor. These Stressors are not considered to present a risk to
human health at the SMCL. At present, SMCLs have been developed for 15
Stressors.
y
y
y
Soil
Sediment
Ingestion
Metals
V
V
Ground Water
Surface Water
Inhalation
VOCs
Air
Fish Tissue
Dermal
SVOCs
Other: Color, Corrosivity, Odor, Foaming Agents, pH, Total Dissolved Solids
The lowest concentration at which these associated adverse effects are not
known or anticipated to occur under typical conditions found in public water
systems.
U.S. EPA/Office of Water
www.epa.gov/dwstandardsregulations/secondarv-drinking-water-standards-
guidance-nuisance-chemicals
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Appendix
A.6.3 Specific Ecological Benchmarks
The following tables provide some sources of ecological screening benchmarks that have been
developed by EPA and other organizations. These tables provide a summary of each set of
values and highlight the relevant receptors, stressors and media to help determine how well
each set of benchmarks reflects the exposure scenarios anticipated for a given beneficial use
evaluation. The focus of these tables is on the information anticipated to be most pertinent to
beneficial uses; however, a given set of benchmarks may include additional media, exposure
routes or stressors.
Ecological Soil Screening Levels (Eco-SSLs)
Overview:
Media:
Exposure
Route:
Stressors:
Basis:
Developer:
Website:
Eco-SSLs are soil concentrations for approximately 20 chemicals developed to
be protective of ecological receptors that commonly come into contact with soil
or ingest biota that live in or on soil.
V
V
Soil
Sediment
Ingestion
Ground Water
Surface Water v
Inhalation v
Air (Pore Gas)
f Biota
f Direct Contact
Notes: Ingestion of soil and biota considered for mammals, birds and
invertebrates. Direct contact also considered for plants and invertebrates.
V
Metals
V
VOCs v
f SVOCs
Notes: Benchmarks are available for 17 metals, pentachlorophenol, and total
polyaromatic hydrocarbons.
Derived from a review of the literature on the lowest concentration at which no
observed adverse effects levels (NOAELs) were observed for plants,
invertebrates, birds and/or mammals. A
U.S. EPA/OSWER
www.epa.gov/ecotox/ecossl
ECORISK Database
Overview:
Media:
Exposure
Route:
Stressors:
Basis:
Developer:
Website:
The ECORISK Database is a screening tool developed by the Los Alamos
National Laboratory to evaluate impacts from chemicals and radionuclides in
soil, water, sediment and air on the ecological receptors. Screening levels are
calculated for receptors in various functional feeding guilds (e.g., carnivores,
herbivores, insectivores) or drawn from the peer-reviewed literature.
y
y
y
y
y
Soil
Sediment
Ingestion
Metals
y
y
y
Ground Water
Surface Water
Inhalation
VOCs
V
y
y
Air (Pore Gas)
Biota
Direct Contact
SVOCs
Others: Dioxins/Furans, Pesticides, Radionuclides.
Dependent on individual benchmark source.
Los Alamos National Laboratory (LANL)
www.lanl.gov/communitv-environment/environmental-
stewardship/protection/eco-risk-assessment.php
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Appendix
Great Lakes Initiative Clearinghouse
Overview:
Media:
Exposures:
Stressors:
Basis:
Developer:
Website:
The Clearinghouse is a central access point for available data from State and
Tribal environmental agencies. It contains information on criteria, toxicity data,
exposure parameters and other supporting documents used in developing
water quality standards in the Great Lakes Watershed. It currently contains
data provided by Indiana, Minnesota, New York, Ohio, and Wisconsin.
y
y
y
Soil
Sediment
Ingestion
Metals
y
y
Ground Water
Surface Water
Inhalation
VOCs
V
y
Air (Pore Gas)
Biota
Direct Contact
SVOCs
Others: Pesticides, Dioxins/Furans
Dependent on individual benchmark source.
State and Tribal environmental agencies
www.epa.gov/gliclearinghouse/
National Recommended Water Quality Criteria (NRWQC)
Overview:
Media:
Exposures:
Stressors:
Basis:
Developer:
Website:
NRWQC, also known as ambient water quality criteria (AWQC), are values
developed by EPA to protect human and ecological health from the harmful
effects of pollutants in surface water.
y
y
y
Soil
Sediment
Ingestion
Metals
y
y
Ground Water
Surface Water
Inhalation
VOCs
V
V
Air (Pore Gas)
Biota
Direct Contact
SVOCs
Other: Dioxin/Furan
Ecological benchmarks based on a review of all available toxicological literature
for both acute and chronic effects. If warranted, criteria may also be a function
of different water quality criteria (e.g., pH, temperature, hardness).
U.S. EPA/Office of Water
www.epa.gov/wqc/national-recommended-water-qualitv-criteria
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Appendix
Risk Assessment Information System Database
Overview:
Media:
Exposures:
Stressors:
Basis:
Developer:
Website:
Oak Ridge National Laboratory developed and compiled a searchable
database of ecological screening benchmarks from a number of sources for a
range of aquatic organisms, soil invertebrates, and terrestrial plants.
y
y
y
y
y
Soil
Sediment
Ingestion
Metals
y
y
Ground Water
Surface Water
Inhalation
VOCs
y
y
y
Air (Pore Gas)
Biota
Direct Contact
SVOCs
Other: Pesticides
Dependent on individual benchmark source.
Oak Ridge National Laboratory (ORNL), University of Tennessee, and
Bechtel Jacobs Corp.
rais.ornl.gov/tools/eco search.php
Screening Quick Reference Tables (SQuiRTs)
Overview:
Media:
Exposures:
Stressors:
Basis:
Developer:
Website:
SQuiRTs is a compilation of ecological screening benchmarks developed by
EPA, other U.S. agencies, Canada, the Netherlands and the United Nations.
This reference tool was developed to help evaluate potential risks from
inorganic and organic contaminants in water, sediment and soil.
V
V
V
V
V
Soil
Sediment
V
Ingestion
Metals
V
Ground Water
Surface Water
Inhalation
VOCs
Other: Radionuclides, Pesticides
V
V
Air (Pore Gas)
Biota
Direct Contact
SVOCs
Dependent on individual benchmark source.
National Ocean and Atmospheric Administration (NOAA)
Benchmarks: resoonse.restoration.noaa.eov/sites /default/files /SOuiRTs.odf
FAQs
: response.restoration.noaa.gov/environmental-
restoration/environmental-assessment-tools/sauirt-cards-
faq.html
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Appendix
A.7 Toxicity Values
The following compilation of resources supplements the discussion of receptor exposure
factors provided in Section 5 and Section 6 of this document. These resources identify
different sources of toxicity values, detail how these values are derived, and provide
recommendations on how to select the most appropriate values when more than one are
available for a single exposure scenario. This information may be used in the beneficial use
evaluation to calculate screening values or risks.
A.7.1 General Resources
Date: December 1989
Title: RAGS Volume I—Part A: Human Health Evaluation Manual
Chapter 7: Toxicity Assessment
Author: U.S. EPA/OSWER
Details: Provides step-by-step guidance for locating EPA toxicity assessments and
accompanying values, and advises how to determine which values are most
appropriate when multiple values exist. Prior to this procedural discussion,
background information regarding EPA's methods for toxicity assessment is
provided to help the risk assessor understand the basis of the toxicity values and the
limitations of their use.
Date: December 2003
Title: Human Health Toxicity Values in Superfund Risk Assessments
Author: U.S. EPA/OSWER
Details: This document presents the OSWER technical and policy recommendations
regarding the use of human health toxicity values in risk assessments. A tiered
approach is provided to prioritize the selection of chemical toxicity data based on the
quality of the underlying toxicity database and the extent of peer review.
Date: April 2007
Title: Identification and Selection of Toxicity Values/Criteria for CERCLA and Hazardous
Waste Risk Assessments in the Absence of IRIS Values
Author: Environmental Council of the States (EGOS), Department of Defense
Details: This document provides recommendations from EGOS on identifying and selecting
toxicity values for those chemicals for which an IRIS toxicity value is not available.
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Date: December 2010
Title: Dioxin Toxicity Equivalency Factors (TEFs) for Human Health Risk Assessments of
2,3,7,8-Tetrachlorodibenzo-p-Dioxin and Dioxin-Like Compounds
Author: U.S. EPA/Risk Assessment Forum
Details: This document describes the updated EPA approach for evaluating the human
health risks from exposures to environmental media that contain dioxin-like
compounds. EPA recommends that the toxicity equivalence factor (TEF)
methodology, a component mixture method, be used to evaluate human health risks
posed by these mixtures, using 2,3,7,8-tetrachlorodibenzo-p-dioxin as the index
chemical.
Date: June 2012
Title: Ecological Structure Activity Relationships (ECOSAR)
Authors: U.S. EPA/Office of Pollution Prevention and Toxics
Details: ECOSAR is a computerized predictive system that estimates aquatic toxicity. The
program estimates a chemical's acute (short-term) toxicity and chronic (long-term
or delayed) toxicity to aquatic organisms such as fish, aquatic invertebrates, and
aquatic plants by using computerized structure activity relationships.
Date:
Title:
Author:
Details:
Date:
Title:
Author:
Details:
Constituent-Specific
ATSDR Toxicological Profiles
ATSDR/Division of Toxicology
Provides toxicological profiles for stressors found at National Priorities List and
other federal sites. Chemical names can be searched alphabetically. Each
toxicological profile contains a review of key studies and other data characterizing
the exposure-related health effects and pertinent characteristics and processes that
affect human exposures. Sections include other relevant information on releases to
the environment, environmental fate, levels monitored in the environment,
potential exposures, and analytical methods. Numerical toxicity values for many of
these chemicals are available through the ATSDR minimum risk levels (MRLs).
May 2013
Tier III Toxicity Value White Paper
U.S. EPA/Human Health Risk Assessment Forum
This paper articulates issues pertaining to the selection of toxicity values when
multiple Tier III values are available and provides recommendations on processes
that will improve the transparency and consistency of evaluating, selecting and
documenting these values.
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Appendix
A.7.2 Specific Human Health Toxicity Values
The tables below provide specific examples of human health toxicity values for chemical
stressors derived by EPA and other organizations. These tables contain a general description
of each set of values; highlight the relevant receptors, exposure timeframe and exposure route
that determine how well each set of values reflect the types of exposures anticipated for a given
beneficial use; and provide links to where the values can be found. Values are developed for
the specific timeframes and exposure routes listed in the tables only when sufficient data are
available for a given chemical.
California Environmental Protection Agency (CalEPA)
Overview:
CalEPA has developed two sets of toxicity values, cancer potency values (CPVs)
for carcinogens and reference exposure levels (RELs) for non-carcinogens, for
120 chemicals regulated under the California Hot Spots Air Toxics Program.
These values have undergone internal peer review by various California
agencies and have been the subject of public comment.
Timeframe:
y
Route:
y
Developer:
Chronic
Oral
y
Sub-chronic
Inhalation
State of California/Office of Environmental Health
(OEHHA) and Air Resources Board
Acute
and Hazard Assessment
Website:
www.arb.ca.gov/toxics/healthval/healthval.htm
Health Effects Assessment Summary Tables (HEAST)
Overview
HEAST is a listing of provisional human health toxicity values. EPA has
developed four sets of
unit risk factor (URF,
toxicity values, cancer slope factor (CSF, ingestion) and
inhalation) for carcinogens and reference dose (RfD,
ingestion) and reference concentration (RfC, inhalation) for noncarcinogens.
Although the toxicity values in HEAST have undergone review and have the
concurrence of individual EPA program offices, they have not been reviewed as
extensively as those in
IRIS. The HEAST tables for
chemical constituents are not
periodically updated at this time.
Timeframe:
y Chronic
Route:
y Oral
Developer:
y
Sub-chronic
Inhalation
Acute
U.S. EPA/OSWER
Website:
Chemicals: cfpub.epa.gov/ncea/cfm/recordisplav.cfm?deid=2877
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Integrated Risk Information System (IRIS)
Overview:
IRIS
is the EPA human health
assessment program that evaluates information on
the health effects of more than 550 chemical stressors.
EPA has developed four
sets of to xicity values, CSF (ingestion) and URF (inhalation) for carcinogens and
RfD
(ingestion) and RfC (inhalation) for noncarcinogens. Each chemical has
undergone multiple rounds of extensive internal and public review. The file for
each
stressor contains descriptive and quantitative information on the potential
health effects.
Timeframe:
y
Route:
y
Developer:
Chronic
Oral
y
Sub-chronic
Acute
Inhalation
U.S. EPA/ORD
Website:
www.epa.gov/IRIS/
Provisional Peer-Reviewed Toxicity Values (PPRTVs)
Overview:
PPRTVs provide information on the cancer and non-cancer effects of various
chemical stressors. EPA has developed four sets of toxicity values, CSF
(ingestion) and URF (inhalation) for carcinogens and RfD (ingestion) and RfC
(inhalation) for noncarcinogens. PPRTVs are derived after a review of the
relevant scientific literature using the methods, sources of data and guidance for
value derivation used by the EPA IRIS Program. All PPRTVs receive internal
review by EPA scientists and external peer review by independent scientific
experts.
Timeframe:
y
Route:
y
Developer:
Chronic
Oral
y
y
Sub-chronic
Inhalation
Acute
U.S. EPA/OSWERand ORNL
Website:
hhpprtv.ornl.gov
Minimum Risk Levels (MRLs)
Overview:
MRLs are substance-specific health guidance levels developed by ATSDR for only
the non-carcinogenic endpoints associated with each chemical. An MRL is an
estimate of the daily human exposure to a hazardous substance that is likely to
be without appreciable risk of adverse health effects over a specified duration of
exposure. MRLs are derived for acute, intermediate and chronic exposure
durations for oral and inhalation routes of exposure.
Timeframe:
y
Route:
y
Developer:
Chronic
Oral
y
V
Sub-chronic •/
Acute
Inhalation
ATSDR
Website:
www.atsdr.cdc.gov/mrls/index.asp
www.atsdr.cdc.gov/toxprofiles/index.asp
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Appendix
A.7.3 Specific Ecological Toxicity Data
The tables below provide specific sources of toxicity data for chemical stressors derived by
EPA and other organizations. These tables contain a general description of each data set and
provide links to where the values can be found. Each database may contain diverse types of
data on different chemicals, media, receptors, exposure durations and adverse effects that will
require careful handling and interpretation before use.
Ecological Toxicology (ECOTOX) Database
Overview:
ECOTOX is a database that provides information on adverse effects of a range of
single chemical stressors to ecologically relevant aquatic and terrestrial species.
The primary source of data included in this database is peer-reviewed literature.
Developer:
EPA/ORD
Website:
cfpub.epa.gov/ecotox/
ECORISK Database
Overview:
The ECORISK Database is a screening tool developed by the Los Alamos National
Laboratory to evaluate impacts from chemicals and radionuclides in soil, water,
sediment and air on the ecological receptors. This database includes toxicity data
for plants, worms, birds and mammals based on evaluation of peer-reviewed
toxicity study literature. The other data available for terrestrial and aquatic
receptors and for radionuclides come from the EPA, ORNL, the International
Atomic Energy Agency for radionuclides, and other sources.
Developer:
EPA/ORD
Website:
www.lanl.gov/environment/protection/eco-risk-assessment.php
Great Lakes Initiative Clearinghouse
Overview:
The Clearinghouse is a central access point for available data from State and
Tribal environmental agencies. It contains information on criteria, toxicity data,
exposure parameters and other supporting documents used in developing water
quality standards in the Great Lakes Watershed. It currently contains data
provided by Indiana, Minnesota, New York, Ohio, and Wisconsin.
Developer:
State and Tribal environmental agencies
Website:
www.epa.gov/gliclearinghouse/
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Appendix
A.8 Exposure Factors
The following compilation of resources supplements the discussion of receptor exposure
factors in Section 5 and Section 6 of this document. These resources identify and compile
data on physiological, behavioral and cultural factors that can influence human and ecological
exposures. This information can be used to characterize the magnitude, frequency and
duration of potential exposures. Some of the listed resources represent different editions of the
same document and are provided for the historical context and discussion contained therein.
A.8.1 General Resources for Human Exposure
Date: June 1991
Title: Risk Assessment Guidance for Superfimd Volume I: Human Health Evaluation
Manual, Supplemental Guidance: Standard Default Exposure Factors
Author: U.S. EPA/OSWER
Details: This guidance recommends exposure factors based on the data contained in the
original 1989 Exposure Factors Handbook. The exposure factors discussed are
defaults used in many historical OSWER risk assessments in the absence of site-
specific data.
Date: August 1997
Title: Exposure Factors Handbook
Author: U.S. EPA/ORD
Details: This handbook summarizes data on human behaviors and characteristics that affect
exposure to environmental contaminants and recommends values to characterize
these factors. It includes discussions of the issues assessors should consider in
deciding how to use these data and recommendations.
Date:
Title:
Author:
Details:
September 2006
Example Exposure Scenarios
U.S. EPA/ORD
Outlines scenarios for various exposure pathways and to demonstrate how data from
the 1997 Exposure Factors Handbook may be applied for estimating exposures. It
should be noted that the example scenarios presented here have been selected to best
demonstrate the use of the various key data sets in the Exposure Factors Handbook
and represent commonly encountered exposure pathways.
Date: September 2008 (Full Document)
October 2009 (Highlights)
Title: Child-Specific Exposure Factors Handbook
Author: U.S. EPA/ORD
Details: Focuses on various factors used in assessing exposure, specifically for children 0 to
< 21 years old. This handbook provides nonchemical-specific data on exposure
factors for the EPA-recommended set of childhood age groups.
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Date: September 2011 (Full Document)
October 2011 (Highlights)
Title: Exposure Factors Handbook: 2011 Edition
Author: U.S. EPA/ORD
Details: This handbook summarizes data on human behavioral and physiological
characteristics that affect exposure to environmental contaminants and provides
exposure/risk assessors with recommended values for these factors that can be used
to assess exposure among both adults and children. This handbook incorporates the
changes in risk assessment practices based on the need to consider life stages rather
than subpopulations.
Date: February 2014
Title: Human Health Evaluation Manual, Supplemental Guidance: Update of Standard
Default Exposure Factors
Author: U.S. EPA/OSWER
Details: Based on the recommendations from Exposure Factors Handbook: 2011 Edition,
several OSWER default exposure factors were identified that warranted updates.
This guidance presents the updated recommended values. This guidance
supplements the Risk Assessment Guidance for Superfund: Human Health
Evaluation Manual (RAGS), Part A through E. Where numerical values differ from
those presented in Part A or E, the factors presented in this guidance should be
considered updates to the older values.
A.8.2 General Resources for Ecological Exposure
Date: December 1993
Title: Wildlife Exposure Factors Handbook
Author: U.S. EPA/ORD
Details: This handbook provides data, references and guidance for conducting a screening-
level risk assessment of common wildlife species exposed to toxic chemicals in the
environment.
Date:
Title:
Author:
Details:
Species-Specific
Mammalian Species Series
American Society of Mammalogists
The American Society of Mammalogists has published these documents since 1969,
with 20 to 30 new accounts issued each year. Each account summarizes the current
understanding of the biology of a single species, including systematics, distribution,
fossil history, genetics, anatomy, physiology, behavior, ecology and conservation.
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A.9 Fate and Transport Models
The following compilation of resources supplements the discussion of fate and transport
models provided in Section 5 and Section 6 of this document. These resources detail some
models that can be used to predict the extent to which dilution and attenuation occurs as
stressors migrate through the environment. These models may be used to estimate stressor
levels at the point of exposure as part of either a conservative screening assessment or a more
realistic risk assessment. While the specific models discussed in some of the general resources
may no longer be the most relevant or current for beneficial use evaluations, the discussion
about fate and transport considerations and model selection may still be useful.
A.9.1
General Resources
Date:
Title:
Author:
Details:
March 1994
Evaluation of Unsaturated/Vadose Zone Models for Superfund Sites
U.S. EPA/ORD
This report summarizes research findings that address the sensitivity and
uncertainty of model output due to uncertain input parameters. The objective of the
research was to determine the sensitivity and uncertainty of travel time,
concentration, mass loading and pulse width of contaminants at the water table due
to uncertainty in soil, chemical, and site properties for four models: Regulatory and
Investigative Treatment Zone (RITZ), Vadose Zone Interactive Processes (VIP),
Chemical Movement in Layered Soils (CMLS) and HYDRUS.
November 1998
RBCA Fate and Transport Models: Compendium and Selection Guidance
American Society of Testing and Materials (ASTM)
This document catalogs and describes non-proprietary fate and transport models
that are readily available for risk-based corrective action (RBCA) at the time of
publication. It is meant to function as a compendium and resource guide, assisting
the user in the model selection process. It is not intended to be a comprehensive
review of every available fate and transport model or a comprehensive guidance on
the use of any single model. The guidance does not endorse models listed or attempt
to rank them or evaluate their performance or accuracy.
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A.9.2 Specific Fate and Transport Models
These tables summarize several publicly available models that have been developed by EPA
and other organizations to estimate the fate and transport of stressors through the
environment. The models listed are publicly available and nonproprietary. These models vary
widely in scope and complexity. Each table provides a general summary of a model; highlight
the different data requirements, outputs and limitations of the model; and provide a link to
where the model can be found.
American Meteorological Society/EPA Regulatory Model (AERMOD)
Overview:
AERMOD is a steady-state plume model that estimates the amount of
atmospheric dispersion and deposition during windblown transport of
stressors. The model has two pre-processors designed to handle
transport over variable terrain and account for inhomogeneity within the
air column. AERMOD may be appropriate to estimate exposures to
particulate matter, gases and vapors released from beneficial uses
exposed to outdoor air.
Model Type:
Deterministic
Probabilistic
Spatial Variability:
Lumped
Distributed
Media:
Soil
Ground Water
Sediment
Surface Water
Air
Food
Required Inputs:
Source type (e.g., single point, capped stack, horizontal stack,
rectangular area, circular area, flares, volume).
Source characteristics (e.g., emission rate, release height, dimensions).
Building characteristics (e.g., height, width, distance from source).
Hourly meteorology (e.g., temperature, wind speed/direction, cloud
cover).
Terrain (e.g., albedo, bowen ratio, roughness length, elevation).
Coordinate system (e.g., cartesian grid, polar grid, single discrete
point).
Receptor data (e.g., population size, distance from source,
urban/rural).
Model Outputs:
Time-averaged air concentration and land deposition rates as a
function of location (x-, y-, z-axis) for specified averaging time (e.g., 1-
hr, 3-hr, 24-hr).
Occurrences (time and location) of a stressor concentration exceeding
a user-specified threshold.
Major
Assumptions:
Constant, temporally averaged meteorological conditions are present
during each modeled hour.
Exposed receptors are less than 50 km away from the source.
In the stable boundary layer of the atmosphere, stressor
concentrations in both vertical and horizontal direction fit a normal
distribution.
Stressors are chemically inert.
Developer:
U.S. EPA/Office of Air and American Meteorological Society (AMS)
Website:
www3.epa.gov/scram001/dispersion prefrec.htm
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Appendix
American Meteorological Society/EPA Regulatory Model Screen (AERSCREEN)
Overview:
AERSCREEN is the screening version of AERMOD. This model is designed
to conservatively account for atmospheric dispersion during windblown
transport of stressors. AERSCREEN may be appropriate to estimate
exposures to particulate matter, gases and vapors released from beneficial
uses exposed to outdoor air.
Model Type:
Deterministic
Probabilistic
Spatial Variability:
Lumped
Distributed
Media:
Soil
Ground Water
Sediment
Surface Water
Air
Food
Required Inputs:
Source type (e.g., single point, capped stack, horizontal stack,
rectangular area, circular area, flares, volume).
Source characteristics (e.g., emission rate, release height, dimensions).
Building characteristics (e.g., height, width, distance from source).
Hourly meteorology (e.g., temperature, wind speed/direction, cloud
cover).
Terrain (e.g., albedo, bowen ratio, roughness length, elevation).
Receptor data (e.g., population size, distance from source,
urban/rural).
Model Outputs:
Worst-case 1-hr time-averaged air concentration at a given elevation
and distance.
Worst-case 3-hr, 8-hr, 24-hr and annual time-averaged concentrations
based on modeled 1-hr concentration.
Major
Assumptions:
Constant, temporally averaged meteorological conditions are present
during each modeled hour.
Exposed receptors are less than 50 km away from the source.
Receptors are located along the centerline of plume.
Stressors are inert and recalcitrant.
Deposition does not occur.
Developer:
U.S. EPA/Office of Air and AMS
Website:
www3.epa.gov/scram001/dispersion screening.htm
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Appendix
California Total Exposure (CalTOX] Model
Overview:
CalTOX is a spreadsheet-based model that simulates the fate and transport of
stressors through different environmental media originating from releases to
soil, air and/or water along with the magnitude of resulting exposures. CalTOX
can conduct uncertainty and variability analyses through Monte Carlo
simulations. This model may be applicable to outdoor beneficial uses that are
exposed to precipitation and wind.
y
Deterministic
y
Probabilistic
Model Type:
Note: The model can be run deterministically with single-value inputs, but all
model inputs for transport, transformation and exposure assessment can be
probabilistic.
Snatial
y
Lumped
Distributed
Variability:
Note: CalTOX is a compartmental model that does not account for the spatial
variations of a stressor within each media.
Media:
y
y
Soil
Sediment
y
y
Ground Water
Surface Water
y
y
Air
Food
Note: Food pathway includes produce, meat, dairy, eggs and fish.
Required
Inputs:
Stressor properties (e.g., partition coefficients, vapor pressure, degradation
rates, toxicity values).
Meteorology (e.g., wind speed, temperature, rainfall, deposition velocity).
Hydrogeology (e.g., bulk density, erosion rates, infiltration rate, ground
water recharge, root zone depth, porosity, runoff rate, surface water depth).
Exposure factors (e.g., ingestion rate, body weight, exposure duration).
Model
Outputs:
Media-specific human health exposure concentrations.
Probability or cumulative density function of environmental
concentrations.
Human health risks from exposure to different media.
Major
Assumptions:
Stressor concentrations are uniform within the media of interest.
Mass transport across different environmental media is one-dimensional.
Evaluation timescale is on the order of years.
Stressor transport and transformations across/within media are first-order
processes.
Ratio of dry land to surface water is large (> 90% dry land).
Stressor concentrations are treated either as constant with a continuous
source or as time-varying based on the initial concentrations in each soil
layer.
Stressors are not mixed polarity dissociating organics (e.g., surfactants),
volatile metals (e.g., mercury) or inorganic chemical with high vapor
pressure.
Developer:
State of California/Department of Toxic Substances Control
Website:
www.dtsc.ca.gov/AssessingRisk/caltox.cfm
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EPA Composite Model for Leachate Migration with Transformation Products (EPACMTP)
Overview:
Model Type:
EPACMTP simulates the fate and transport of leached stressors through
the subsurface environment. The model combines two separate modules
to account for advection, dispersion and diffusion through the unsaturated
and saturated zones. The model is designed to run either deterministically
or probabilistically. EPACMTP was originally designed to evaluate stressor
releases from land disposal units (e.g., landfills); however, the current
version can also be used to evaluate ground water impacts from the land
application of secondary materials.
•/ Deterministic •/
Spatial Variability:
y Lumped
Media:
Required Inputs:
Soil y
Sediment
Probabilistic
Distributed
Ground Water Air
Surface Water Food
• Source characteristics (e.g., geometry, depth below ground).
• Stressor properties (e.g., initial leachate concentration, MINTEQA2-
derived sorption isotherms, degradation rate).
• Meteorology (e.g., precipitation rate).
• Hydrogeology (e.g., temperature, depth to aquifer, hydraulic
conductivity, aquifer thickness).
• Receptor location (e.g., distance from source, depth of well, angle of well
off away from the plume centerline).
Model Outputs:
• Deterministic simulation outputs stressor concentrations at the top of
the water table or at a downgradient receptor well.
• Probabilistic simulation outputs the distribution of either peak or time-
averaged stressor concentrations at a downgradient receptor well as a
function of both distance (x-, y-, and z-axis) and time.
Major
Assumptions:
• Soil and aquifer media properties are homogenous.
• The modeled source is the only contributor of stressors to the
environment.
• Transformation (e.g., hydrolysis, oxidation, biodegradation) of stressors
follow first-order kinetics.
• The surficial aquifer is unconfined and has a constant saturated
thickness.
• Stressors are not non-aqueous phase liquids (NAPL) or volatiles.
• The stressor concentration entering the unsaturated soil is either
constant or depletes at a first-order rate.
Developer:
U.S. EPA/OSWER and HydroGeoLogic, Inc.
Website:
www.epa.gov/smm/epas-composite-model-leachate-migration-
transformation-products-epacmtp
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Appendix
HYDRUS-1D
Overview:
The HYDRUS models simulate the fate and transport of heat and chemical
solutes (as well as viruses, bacteria, colloids, and nanoparticles) through
variably-saturated (i.e., unsaturated, partially or fully saturated)
subsurface environments. This model accounts for advection, gaseous
and liquid diffusion, dispersion, sorption, and chemical transformation of
stressors within the variably saturated media. HYDRUS-1D is a one-
dimensional version of the model available in the public domain. This
model may be applicable to outdoor beneficial uses that are exposed to
precipitation.
Model Type:
Deterministic
Probabilistic
Spatial Variability:
Lumped
Distributed
Media:
Soil
Sediment
Ground Water
Surface Water
Air
Food
Required Inputs:
Stressor properties (e.g., dispersivity, diffusion coefficients, adsorption
isotherm coefficients, Henry's law constants, production and
degradation rates, attachment/detachment rates).
Hydrogeology (e.g., soil types and layers, depth of soil profile, hydraulic
conductivity, retention properties, soil bulk density, porosity, initial
water content, and initial pressure head).
Meteorology (e.g., time-dependent precipitation, evaporation rate,
transpiration rate, temperature, solar radiation).
Model Outputs:
Graphical representation of changes in stressor concentration, water
content, pressure head, and temperature as a function of time at user-
specified observational nodes within the soil profile.
Graphical representation of profiles of stressor concentration, water
content, pressure head, and temperature as a function of depth (z-axis)
at user-specified times).
Actual and cumulative water and solute fluxes, pressure head, and
water content at flow boundaries (i.e., at the surface or bottom of the
soil profile).
Major
Assumptions:
Stressors are not NAPL.
Stressor transport is limited to the vertical, horizontal or inclined
direction.
Transformation (e.g., degradation, volatilization, precipitation) follows
zero- or first-order kinetics.
Partitioning between liquid and gas phases are linear and in
equilibrium (but solid-liquid phase partitioning processes can be
nonlinear and non-equilibrium).
Developers:
University of California Riverside and PC-Progress Incorporated
Website:
http://www.pc-progress.com/en/Default.aspx7hvdrus-ld
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Appendix
Industrial Waste Air (IWAIR) Model
Overview:
IWAIR is composed of three modules that simulate the volatilization of
stressors from solid and liquid materials into the surrounding air, the
subsequent fate and transport downgradient, and the resulting risk to
receptors. This model may be applicable to outdoor beneficial uses that
passively emit gas or vapor.
Model Type:
Deterministic
Probabilistic
Spatial Variability:
Lumped
Distributed
Media:
Soil
Ground Water
Sediment
Surface Water
Air
Food
Required Inputs:
Source properties (e.g., area, depth, application rate, bulk density,
porosity, total stressor mass).
Stressor properties (e.g., vapor pressure, diffusivity in air and water,
soil biodegradation rate, hydrolysis constant, henry's law constant).
Dispersion modeling parameters (e.g., source type, height
aboveground of a WMU, wind speed, wind direction, mixing height,
air stability class, receptor type, distance to potential receptors).
Exposure factors (e.g., inhalation rate, body weight, exposure
duration).
Model Outputs:
Human health risks from inhalation of vapor-phase emission.
Allowable stressor concentration at source pre-calculated from
exposure level concentration without an appreciable adverse effect at
the receptor point.
Major
Assumptions:
No more than six stressors are present during a single model run.
The source and surrounding environmental media are in equilibrium.
Biodegradation, hydrolysis and adsorption processes are considered
for an impoundment waste containing low concentrations of organics
chemicals; however, these processes are not considered when the
waste is over saturated with organic chemicals.
Biodegradation is accounted for in emission modeling for landfills,
waste piles and land application units, but hydrolysis is not
considered.
Volatilization is the primary route through which stressors are
released; releases through sorption to windblown particulates is
negligible.
Any biodegradation or hydrolysis of stressors occurs through first-
order kinetics.
Both wet and dry depletion of vapors from the atmosphere is
negligible.
No emission control technologies are in place.
Developer:
U.S. EPA/OSWER
Website:
www.epa.gov/smm/industrial-waste-air-model-iwair
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Appendix
Industrial Waste Management Evaluation Model (IWEM)
Overview:
IWEM is a screening-level model that conservatively implements
EPACMTP to simulate the fate and transport of stressors leached into the
subsurface environment. The model accounts for advection, dispersion,
diffusion, and chemical transformation processes during transport
through unsaturated and saturated subsurface media. The model uses
predefined probability distributions for several input parameters to
capture potential national variability. The remaining user-defined inputs
are deterministic. The model also compares stressor levels at the point of
exposure to user-specified screening levels. The current version is
designed to consider releases from beneficial use in land application, road
construction, embankments and structural fill that are exposed to
precipitation.
Type:
Deterministic
Probabilistic
Spatial Variability:
Lumped
Distributed
Media:
Soil
Sediment
Ground Water
Surface Water
Air
Food
Inputs:
Source characteristics (e.g., geometry, density, hydraulic conductivity,
leachable mass of stressors).
Stressor properties (e.g., initial leachate concentration, partitioning
coefficient).
Overland flow characteristics (e.g., runoff rate, manning's number).
Soil data (e.g., soil type, infiltration rate into soil).
Hydrogeology (e.g., ground water depth, hydraulic conductivity, aquifer
thickness).
Meteorology (e.g., annual rainfall, evaporation rate).
Receptor location (e.g., distance from source, angle offset from plume
centerline).
Outputs:
90th percentile of maximum time-averaged stressor concentration at
the receptor location as a function of location (x-, y-, and z-axis).
Comparison of an exposure point stressor concentration with a pre-
calculated health-based concentration.
Major
Assumptions:
Source characteristics are constant.
Releases only occur through the dissolution of stressors into water
percolating through the source.
The rate of infiltration through the source and unsaturated zone is
constant on an annualized basis.
Until all available mass is depleted, the stressor concentration in
leachate from the source is either constant or decreasing over time
through first-order kinetics.
Stressor transport through the unsaturated soil is one-directional,
entirely downward toward underlying ground water.
The surficial aquifer is unconfined and has a constant saturated
thickness.
Both unsaturated and saturated soils are homogenous and isotropic.
Geochemical interactions between stressors and environmental media
are equilibrium sorption process.
All biochemical transformation (e.g., hydrolysis, oxidation,
biodegradation) follow first-order kinetics.
Stressors are not NAPLs or volatiles.
Developer:
U.S. EPA/OSWER
Website:
www.epa.gov/smm/industrial-waste-management-evaluation-model-
version-31
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Appendix
Metal Speciation EC
uilibrium for Surface and Ground Water (MINTEQA2)
Overview:
MINTEQA2 is a geochemical speciation model that simulates equilibrium
partitioning of total chemical mass among the dissolved species, adsorbed
species, gas phase species, precipitates, and soluble complexes with
organic and inorganic ligands under a variety of environmental conditions.
The outputs from MINTEQA2 can help identify the likely speciation and
partitioning coefficients of chemical stressors for use in other fate and
transport models.
Model Type:
Deterministic
Probabilistic
Spatial Variability:
Lumped
Distributed
Media:
Soil
Ground Water
Sediment
Surface Water
Air
Food
Inputs:
System chemistry (e.g., ionic strength, alkalinity, pH, redox potential,
temperature, initial concentration of major ions).
Simulation design (e.g., adsorption model options, precipitation options,
number of model iterations).
Outputs:
Equilibrium mass distribution of species in dissolved, precipitated,
adsorbed, and volatilized states.
Each time when solid precipitation occurs, the model outputs a pre-
equilibrium, or provisional mass distribution, of species in the dissolved,
precipitated, adsorbed and volatilized states.
Ionic strength, pH, pE, electrostatic surface potential, and charge at both
equilibrium and any provisional states.
Saturation indices of all database solids.
Major
Assumptions:
Temperature of the modeled system is below 100QC.
System is at chemical equilibrium, with no net flux of mass or energy.
Water is in contact with geologic materials for a sufficient time to allow
all chemical reactions to go to completion.
Gases present have constant partial pressure.
Developer:
U.S. EPA/ORD
Website:
www.epa.gov/exposure-assessment-models/minteqa2
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Appendix
Modular Three-Dimensional Transport Multi-Species (MT3DMS) Model
Overview:
MT3DMS is an extension of a USGS model (MODFLOW) that simulates the
fate and transport of chemical constituents leached to ground water.
Together, these models solve for three-dimensional transport in the
saturated zone. This model may be applicable to outdoor beneficial uses
exposed to precipitation, where transport through the unsaturated zone is
already known or can be neglected.
Model Type:
Deterministic
Probabilistic
Spatial Variability:
Lumped
Distributed
Media:
Soil
Sediment
Ground Water
Surface Water
Air
Food
Inputs:
Cell dimensions (e.g., number of columns, rows, and layers).
Cell boundary conditions (e.g., impermeable boundaries, hydraulic
head).
Hydrogeology of each cell (e.g., hydraulic conductivity, recharge rate,
porosity, dispersivity).
Meteorology (e.g., precipitation rate).
Stressor characteristics (e.g., initial concentration at water table,
distribution coefficient).
Outputs:
Stressor concentration as a function of distance (x-, y- and z- axis) and
time.
Graphical presentation of Stressor migration as a function of distance
and time.
Major
Assumptions:
Where ground water is intercepted by surface water, the Stressor
concentration in surface water is equal to the concentration in ground
water.
Non-equilibrium sorption and other biochemical reactions follow first-
order kinetics and are reversible (equilibrium-controlled sorption may
be linear or non-linear).
Chemical and hydrogeological parameters are uniform throughout each
cell.
Developer:
U.S. Army Corps of Engineers
Website:
hvdro.geo.ua.edu/mt3d/
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Total Risk Integrated Methodology (TRIM); TRIM.FaTE Module
Overview:
TRIM.FaTE is a compartmental mass-balanced model that describes the
movement and transformation of stressors over time through a user-defined,
bounded, spatially explicit topography that includes both abiotic (e.g., air, soil,
water) and biotic (aquatic food-web) compartments. It provides an inventory,
over time, of a stressor throughout the entire modeled system and predicts
stressor concentrations in multiple environmental media that can be used as
inputs to estimate human and ecological exposure and risk. TRIM.FaTE may be
applicable to outdoor beneficial uses affected by precipitation and wind.
Model Type:
Deterministic
Probabilistic
Spatial
Variability:
Lumped
Distributed
Note: TRIM is a compartmental model that does not account for the spatial
variations of a stressor within a given media.
Media:
Soil
Sediment
Ground Water
Surface Water
Air
Food
Note: Food pathway includes fish.
Required Inputs:
Source properties (e.g., location, height, stressor-specific emission rate).
Stressor properties (e.g., initial concentrations within each medium, stressor
boundary concentrations, degradation rate, partitioning coefficients,
stressor-specific physical properties).
Meteorology (e.g., wind direction and speed, ambient air temperature, air
mixing height, precipitation rate).
Environmental media properties (e.g., soil bulk density, sediment porosity,
lake residence time, fraction of precipitation that runs off).
Model Outputs:
Stressor concentration in each environmental medium as a function of time.
Major
Assumptions:
Stressor concentrations are homogenous within a compartment of interest.
The properties of each medium are homogenous and isotropic within a
compartment.
Advection, dispersion, diffusion, biochemical transformations and biotic
uptake follow first-order kinetics.
Chemical partitioning between phases assumes equilibrium.
Stressors are either recalcitrant or decay according to first-order kinetics.
Developer:
U.S. EPA/ORD and Office of Air and Radiation, Lawrence Berkeley National
Laboratory, ORNL, University of Tennessee, ICF Consulting, MCNC-North
Carolina Supercomputing
Website:
www.epa.gov/fera
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Appendix
WiscLeach
Overview:
WiscLeach is a Web-based model designed to simulate the fate and
transport of stressors leached to ground water from secondary
materials beneficially used in road stabilization and
embankment/structural fill, and may also be applicable to other land
applications. The model is based on three analytical solutions to the
advection-dispersion-reaction equation that describe transport in the
unsaturated and saturated zones and ground water. This model solves
for one- and two-dimensional stressor transport in the unsaturated and
saturated zones, respectively.
Model Type:
Deterministic
Probabilistic
Spatial Variability:
Lumped
Distributed
Media:
Soil
Ground Water
Sediment
Surface Water
Air
Food
Required Inputs:
Source characteristics (e.g., geometry, density, hydraulic conductivity,
depth to road stabilization layer, porosity, slope of embankments).
Stressor properties (e.g., leachate concentration, retardation factors in
road stabilization layer and subgrade, molecular diffusion coefficient).
Hydrogeological data (e.g., depth to ground water, aquifer porosity
and hydraulic conductivity, regional hydraulic gradient).
Meteorological data (e.g., annual precipitation rates).
Receptor location (e.g., distance to receptor or other point of
compliance, depth of well).
Model Outputs:
Stressor concentrations in unsaturated and saturated zones as function
of location (x-, y- and z-axis) and time.
Contour plots of the stressor plume within unsaturated and saturated
zones.
Major
Assumptions:
The characteristics of the stressor source and underlying
environmental media are homogenous and isotropic.
Mass loss through overland runoff and evapotranspiration are
negligible.
Transport through the source and unsaturated zone is constant and
downward (but transport through dispersion is three-dimensional.
Transport in ground water dominated by advection in the direction of
the downgradient receptor (but stressor transport through dispersion
is three-dimensional).
Stressor adsorption to media follows zero-order kinetics and is
reversible.
Stressors are inert and recalcitrant.
Stressors are neither volatile nor NAPL.
Developer:
Recycled Materials Resource Center (RMRC) at the University of
Wisconsin-Madison and Jackson State University,
Website:
wiscleach.engr.wisc.edu/index.html
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Appendix
A.10 Risk Calculation
The following compilation of resources supplements the discussion of risk calculation in
Section 6 of this document. These resources address approaches to estimate the magnitude of
receptor exposures, as well as some of the factors that may act to mitigate or exacerbate the
risk from these exposures. This information may help account for the variability in receptor
exposure and response when conducting a probabilistic risk assessment. However, it is
important to note that the relative importance of some of these topics will vary based on the
different receptors, stressors and environmental media associated with a particular beneficial
use. Some of the older listed resources have been further expanded upon in more recent
documents also included the list. These older documents may still contain useful information
and are provided for the historical context and discussion contained therein.
A.10.1 General Resources
September 1986
Guidelines for the Health Risk Assessment of Chemical Mixtures
Date:
Title:
Author:
Details:
U.S. EPA/OSWER
This guide provides a consistent approach for evaluating data on the chronic and
subchronic effects of chemical mixtures. A procedural guide, it emphasizes broad
underlying principles of various science disciplines (e.g., toxicology, pharmacology,
statistics) necessary for assessing health risk from chemical mixture exposure. It also
discusses approaches to analyze and evaluate the various data.
Date: December 1989
Title: Risk Assessment Guidance for Superfund Part A, Volume I: Human Health
Evaluation Manual Chapter 6: Exposure Assessment
Author: U.S. EPA/OSWER
Details: Chapter 6 of this document describes procedures for conducting an exposure
assessment as part of the baseline risk assessment process at Superfund sites. The
objective of the exposure assessment is to estimate the type and magnitude of
exposures to the chemicals of potential concern that are present at or migrating from
a site. The results of the exposure assessment are combined with chemical-specific
toxicity information to characterize potential risks.
Date: May 1992
Title: Supplemental Guidance to RAGS: Calculating the Concentration Term
Author: U.S. EPA/Risk Assessment Forum
Details: This bulletin explains the concentration term used in estimate exposures, discusses
basic concepts about the concentration term, generally describes how to calculate
the concentration term, presents examples to illustrate several important points, and
identifies where additional help can be found.
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Date: December 1992
Title: Guidelines for Exposure Assessment
Author: U.S. EPA/ORD
Details: This document addresses principles and procedures to guide risk assessments and to
inform decision-makers and the public about these procedures. In particular, the
guidelines standardize terminology used in exposure assessment and in many areas
outline the limits of sound scientific practice. They discuss and reference a number
of approaches and tools for exposure assessment, along with their appropriate use.
These guidelines are intended to convey the general principles of exposure
assessment, not to serve as a detailed instructional guide.
Date: March 1997
Title: Guiding Principles for Monte Carlo Analysis
Author: U.S. EPA/Risk Assessment Forum
Details: This document provides a general framework and broad set of principles important
for ensuring good scientific practices in the use of Monte Carlo analysis. Many of
the principles apply generally to the various techniques for conducting quantitative
analyses of variability and uncertainty, though they focus on Monte Carlo analysis.
These guiding principles are intended to serve as a minimum set of principles and
are not intended to prevent the use of new or innovative improvements where
scientifically defensible.
Date:
Title:
Author:
Details:
August 2000
Supplementary Guidance for Conducting Health Risk Assessment of Chemical
Mixtures
U.S. EPA/Office of the Science Advisor
This document updates the risk assessment paradigm for mixtures from the 1986
Guidelines for the Health Risk Assessment of Chemical Mixtures. The document is
organized according to the type of data available to the risk assessor, ranging from
data-rich to data-poor situations. Procedures are described for assessment using
data on the mixture of concern, data on a lexicologically similar mixture, and data
on the mixture component chemicals. No single approach is recommended in this
supplementary guidance. Instead, guidance is given for the use of several
approaches depending on the nature and quality of the data.
December 2001
RAGS Volume III—Part A: Process for Conducting Probabilistic Risk Assessment
U.S. EPA/OSWER
Date:
Title:
Author:
Details:
This document provides policies and guiding principles on the application of
probabilistic risk assessment (PRA) methods to human health and ecological risk
assessments. It focuses on Monte Carlo analysis as a method of quantifying
variability and uncertainty in risk. This document introduces a tiered approach to
PRA, beginning with a point estimate analysis and progressing to increasing levels
of complexity until the scope of the analysis satisfies decision-making needs.
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May 2003
Framework for Cumulative Risk Assessment
U.S. EPA/Office of the Science Advisor
This document discusses chemical risks to human health in the context of the
effects from a variety of stressors. The framework has two purposes, one immediate
and one longer-term. It immediately offers a basic structure and provides starting
principles for cumulative risk assessments. The process it describes provides wide
latitude for planning and conducting cumulative risk assessments in many diverse
situations, each based on common principles discussed in the report. The process
also will help foster a consistent approach for conducting and evaluating
cumulative risk assessments, for identifying key issues, and for providing
operational definitions for terms used in cumulative risk assessments. In the longer
term, the document offers the basic principles around which to organize a more
definitive set of cumulative risk assessment guidance.
July 2004
RAGS Volume I—Part E: Supplemental Guidance for Dermal Risk Assessment
U.S. EPA/OSWER
This document is supplemental guidance to RAGS Volume I and contains methods
for conducting dermal risk assessments. EPA has found these methods generally to
be appropriate. However, for each dermal risk assessment, users must decide whether
these methods, or others, are appropriate, depending on the facts.
March 2007
Framework for Metals Risk Assessment
U.S. EPA/Office of the Science Advisor
The document presents key guiding principles based on the unique attributes of
metals (as differentiated from organic and organo-metallic compounds) and
describes how these metals-specific attributes and principles may then be applied in
the context of risk assessment guidance and practices. There are unique properties,
issues and processes within these principles that risk assessors need to consider when
evaluating metal compounds.
Date: May 2007
Title: Guidance for Evaluating the Oral Bioavailability of Metals in Soils for Use
in Human Health Risk Assessment
Author: U.S. EPA/OSWER
Details: This document provides guidance on how to assess site-specific oral bioavailability
of metals in soils for use in human health risk assessments. Specifically, it provides:
1) a recommended process for deciding when to collect site-specific information
on the oral bioavailability of metals in soils; 2) a recommended process for
documenting the data collection, analysis and implementation of a validated
method that would support site-specific estimates of oral bioavailability; and 3)
general criteria that EPA would normally use to evaluate whether a specific
bioavailability method has been validated for regulatory risk assessment purposes.
This guidance focuses on media-specific relative bioavailability and does not
address adjustments to default absolute bioavailability values.
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February 2011
Incorporating Bioavailability Considerations into the Evaluation of
Contaminated Sediment Sites
Date:
Title:
Author:
Details:
Interstate Technology and Regulatory Council
This guidance is constructed to assist the user in identifying the most relevant places
within an exposure assessment that bioavailability can be assessed and which tools
and methods are most useful and appropriate. The document also provides case
studies that highlight the application of bioavailability assessment tools and
methodologies in contaminated sediment sites.
Date: December 2011
Title: RAGS Volume III—Part A: Process for Conducting Probabilistic Risk Assessment
Author: U.S. EPA/OSWER
Details: This document provides policies and guiding principles on the application of
probabilistic risk assessment methods to human and ecological risk assessment. It
focuses on Monte Carlo analysis as a method of quantifying variability and
uncertainty in risk. This is intended to be most accessible to those readers who are
familiar with risk assessment and basic statistical concepts. The guidance introduces
a tiered approach to probabilistic risk assessment, beginning with a point estimate
analysis and progressing to increasing levels of complexity until the scope of the
analysis satisfies decision-making needs.
Date: July 2014
Title: Risk Assessment Forum White Paper: Probabilistic Risk Assessment Methods and
Case Studies
Author: U.S. EPA/Office of the Science Advisor
Details: This document provides a general overview of the value of probabilistic analyses
and similar or related methods, as well as examples of current applications across the
Agency. The goal of this publication is not only to describe potential and actual uses
of these tools, but also to encourage their further implementation in human,
ecological and environmental risk analysis and related decision-making.
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A.ll Final Characterization
The following compilation of resources supplements the discussion of final characterization
provided in Section 7 of this document. These resources address the considerations related to
the evaluation of variability and uncertainty; the integration findings, assumptions, limitations
and uncertainties into final conclusions; and the presentation of information. This information
can be used to guide the documentation of information about the beneficial use evaluation to
ensure that it is transparent, clear, consistent and informative for both decision-makers and
other members of the audience. Some of the older listed resources have been further expanded
upon in more recent documents also included the list. These older documents may still contain
useful information and are provided for the historical context and discussion contained therein.
A.ll.l General Resources
Date:
Title:
Author:
Details:
December 1989
RAGS Volume I—Part A: Human Health Evaluation Manual, Chapter 8: Risk
Characterization
U.S. EPA/OSWER
This document describes the process of risk characterization and provides some
guidance on the interpretation, presentation and qualification of evaluation results.
Exhibits illustrate several ways to present the discussion of uncertainty and
variability.
Date:
Title:
Author:
Details:
February 1992
Guidance on Risk Characterization for Risk Managers and Risk Assessors
U.S. EPA/Risk Assessment Council
This guidance describes risk results in reports, presentations and decision packages.
It addresses problems that may affect public perception regarding the reliability of
scientific assessments and related regulatory decisions.
Date: 1994
Title: Science and Judgment in Risk Assessment
Author: National Academy of Sciences
Details: The first part of the report examines the background and current practices of risk
assessment. It discusses the historical, social, and regulatory contexts of quantitative
risk assessment, EPA's approach to applying risk assessment principles, and identifies
ways in which the process might be improved.
A-54
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Beneficial Use Compendium
Appendix
:
Date:
Title:
Author:
Details:
December 1994
An Introductory Guide to Uncertainty Analysis in Environmental and Health Risk
Assessment
DOE and ORNL
This document presents guidelines for evaluating uncertainty in mathematical
equations and computer models applied to assess human health and environmental
risk. Analytical and numerical methods for error propagation are presented, along
with methods for identifying the most important contributors to uncertainty. The
guide emphasizes the need for subjective judgment to quantify uncertainty when
relevant data are absent or inromnlete.
Date: February 1995
Title: Guidance for Risk Characterization
Author: U.S. EPA/Science Policy Council
Details: This guide is an update to the 1992 Guidance on Risk Characterization for Risk
Managers and Risk Assessors, and describes principles for developing and describing
EPA risk assessments, with a particular emphasis on risk characterization. This
guidance does not substantially revise the 1992 document, but it includes some
clarifications and changes to give more prominence to certain issues, such as the
need to explain the use of default assumptions.
Date: October 1996
Title: Risk Characterization for Ecological Risk Assessment of Contaminated Sites
Author: DOE and ORNL
Details: This document describes the approach for estimating risks based on individual lines
of evidence and then combining them through a process of weighing the evidence.
The lines of evidence are integrated independently so that the implications of each
are explicitly presented. This makes the logic of the assessment clear and allows
independent weighing of the evidence by risk managers and stakeholders.
Date: December 2000
Title: Risk Characterization Handbook
Author: U.S. EPA/Science Policy Council
Details: This guide is based on the 1995 Guidance for Risk Characterization, and is
designed to provide an understanding of the goals and principles of risk
characterization, the importance of planning and scoping for a risk assessment, the
essential elements to address in a risk characterization, the factors that are
considered in decision-making by risk managers, and the forms the risk
characterization takes for different audiences.
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Beneficial Use Compendium
Appendix
Date: 2003
Title: Bioavailability in Soils and Sediments: Processes, Tools, and Applications. National
Academies
Author: National Research Council
Details: This report assesses the current understanding of processes that affect the degree to
which chemical contaminants in soils and sediments are bioavailable to humans,
animals, microorganisms and plants. It seeks to address the most pressing issues and
to contribute toward developing common frameworks and language to build a
mechanistic-based perspective of bioavailability processes.
Date: 2009
Title: Science and Decisions: Advancing Risk Assessment, Chapter 4: Uncertainty and
Variability—The Recurring and Recalcitrant Elements of Risk Assessment
Author: National Research Council
Details: This chapter reviews approaches to address uncertainty and variability and
comments on whether and how the approaches have been applied to EPA risk
assessments. It also discusses how uncertainty and variability are applied to each of
the stages of the risk assessment process and defines key terminology related to
uncertainty and variability.
2013
Environmental Decisions in the Face of Uncertainty
National Research Council
This document provides guidance on approaches to managing risk in different
contexts when uncertainty is present. It also provides guidance on how information
on uncertainty should be presented to help risk managers make sound decisions and
to increase transparency in its communications with the public about those
decisions.
Date: April 2014
Title: Framework for Human Health Risk Assessment to Inform Decision Making, Chapter
4: Risk Assessment
Author: U.S. EPA / Risk Assessment Forum
Details: This document is intended to provide information on the overarching process for
conducting human health risk assessments. These chapters includes information on
how to conduct risk characterization.
A-56
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Beneficial Use Compendium
&EPA
United States
Environmental Protection
Agency
EPA530-R-16-009
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