ecological risk assessment technical workgroup ... · state of oregon department of environmental...

Oregon Department of Environmental Quality

Ecological Risk Assessment Technical Workgroup Recommendation Report

Prepared for:

Oregon Department of Environmental Quality, Environmental Cleanup Program

May 18, 2017

Environmental Cleanup Program

700 NE Multnomah St. Suite 600

Portland, OR 97232

Phone: 503-229-5696 800-452-4011

Fax: 503-229-5850

Contact: Tiffany Johnson

www.oregon.gov/DEQ

DEQ is a leader in

restoring, maintaining and

enhancing the quality of Oregon’s air, land and

water.

State of Oregon Department of Environmental Quality

Oregon Department of Environmental Quality

700 NE Multnomah Street, Suite 600

Portland, OR 97232

1-800-452-4011

www.oregon.gov/deq

Contact:

DEQ Tiffany Johnson

503-229-6258

Documents can be provided upon request in an alternate format for individuals with disabilities or in a

language other than English for people with limited English skills. To request a document in another

format or language, call DEQ in Portland at 503-229-5696, or toll-free in Oregon at 1-800-452-4011,

ext. 5696; or email [email protected].

http://www.oregon.gov/deq

mailto:[email protected]


About the Workgroup

In 2014, the Oregon Department of Environmental Quality convened a technical ecological risk

assessment workgroup, compromised of risk assessors and technical experts, to provide input aimed at

improving the ERA process in Oregon. Workgroup members included experts from the U.S. Fish and

Wildlife Service – Oregon Office, U.S. Environmental Protection Agency – Region 10, Washington

Department of Ecology, Brunelle Environmental Consulting LLC, Formation Environmental, Maul

Foster and Alongi, SLR Consulting, Windward Environmental LLC, Oregon DEQ, CH2M Hill and Hart

Crowser. However, workgroup members from CH2M Hill and Hart Crowser were unable to continue

participation after meeting four and eight, respectively.

DEQ employees served as ex-officio workgroup members, serving mainly as subject matter experts to

inform the external workgroup members as they developed recommendations. DEQ workgroup

members participated in workgroup meetings and commented on the workgroup’s recommendations, but

did not participate in external technical subgroup meetings with the exception of the DEQ project

manager and sponsor.

The workgroup was tasked with providing input to the Cleanup Program to improve DEQ’s ERA

process by providing clear criteria for decision-making so the process could be more timely, user-

friendly and effective at removing sites from further ERA review where significant ecological risks are

unlikely. Specifically, the workgroup was tasked with developing recommendations that:

Refine the Level I Scoping, Level II Screening, and Level III Baseline risk assessments process

for terrestrial and aquatic habitats.

Consider the implications of adopting elements of the Washington Department of Ecology’s

sediment standards for use in Oregon.

Consider whether DEQ should integrate the Regional Sediment Team’s Sediment Evaluation

Framework, which was designed for dredging projects.

Evaluate if any rule changes should be considered to more effectively implement ERAs.

All of these efforts were not fully achieved.

Disclaimer The workgroup charter established the goal of decision-making by consensus. The charter indicated that

the workgroup would strive to reach consensus on all workgroup recommendations. The workgroup

initially agreed to participate in about eight meetings to develop recommendations. However, due to the

complexity of the issues and differing opinions, the workgroup extended the duration to 14 meetings in

effort to reach consensus and develop comprehensive recommendations. Nevertheless, the workgroup

was unable to reach full consensus.

As such, this report does not represent the opinions held by every workgroup member or their respective

organizations. Various workgroup members’ opinions are reflected in the meeting summaries and the

administrative record. External workgroup members’ formal dissents are provided under section 3.3.


This report is intended to summarize the various high-level recommendations and examples provided by

the external workgroup members’ for DEQ to consider. This report is not intended to be guidance. The

workgroup makes no warranties, either expressed or implied, as to whether the recommendations can be

applied consistent with statute and rule. Any updates to guidance must be consistent with statute and

rule.

DEQ will consider the workgroup’s final recommendations contained in this report, as well as the

administrative record, in developing new policies or guidance for ERAs, and evaluating whether there is

a need for rule changes. Any rulemaking will be conducted with public input.


Table of Contents About the Workgroup ................................................................................................................... iii

Disclaimer ..................................................................................................................................... iii

Abbreviations ................................................................................................................................. 8

Definitions.................................................................................................................................... 10

Executive Summary ..................................................................................................................... 14

Background ........................................................................................................................................... 14

Terrestrial Habitat Recommendations................................................................................................... 14

Aquatic Habitat Recommendations....................................................................................................... 16

1. Introduction .......................................................................................................................... 18

1.1 Background................................................................................................................................ 18

1.2 Workgroup Members ................................................................................................................. 21

1.3 Oregon Law ............................................................................................................................... 22

2. Terrestrial Habitat Recommendations ................................................................................. 25

2.1 Key Recommendations .............................................................................................................. 26

2.1.1 Target Response Actions ................................................................................................................. 26

2.1.2 Toxicity Reference Values and Ecological Benchmark Values ...................................................... 27

2.2 Stage 1 Scoping ......................................................................................................................... 28

2.3 Stage 2 Systematic Planning and Screening .............................................................................. 29

2.3.1 Conceptual Site Model, Sampling and Analysis Plan with Data Quality Objectives ...................... 30

2.3.2 Decision Units ................................................................................................................................. 30

2.3.3 Screening Thresholds ...................................................................................................................... 30

2.4 Stage 3 Risk Assessment ........................................................................................................... 30

2.4.1 Site-Specific Conceptual Site Model ............................................................................................... 31

2.4.2 Local Population Area ..................................................................................................................... 31

2.5 Net Environmental Benefit Analysis ......................................................................................... 32

2.6 Rule Revision Recommendations .............................................................................................. 33

Revise the Definition of Assessment “Population” (OAR 340-122-0115(40)) ................................................ 33

Revise the Definition of “Acceptable Risk Level for Populations of Ecological Receptors (OAR

340-122-0115(6)) ............................................................................................................................................. 33

Revise the Definition of “Ecological Benchmark Value” (OAR 340-122-0115(21)) ...................................... 34

Incorporate Net Environmental Benefit Analysis ............................................................................................ 34

3. Aquatic Habitat Recommendations ..................................................................................... 34

3.1 Stage 1 Scoping ......................................................................................................................... 35

3.1.1 Initial Aquatic Habitat Assessment ................................................................................................. 35


3.1.2 Detailed Aquatic Habitat and Ecological Receptor Surveys ........................................................... 35

3.1.3 Conceptual Site Model .................................................................................................................... 35

3.1.4 No Further Action ............................................................................................................................ 36

3.2 Stage 2 Systematic Planning ..................................................................................................... 37

3.2.1 Decision Units ................................................................................................................................. 37

3.2.2 Conceptual Site Model, Sampling and Analysis Plan with Data Quality Objectives ...................... 38

3.3 Dissents ..................................................................................................................................... 40

3.3.1 Washington State Department of Ecology ....................................................................................... 40

3.3.2 U.S. Environmental Protection Agency, Region 10 ........................................................................ 45

4. References ............................................................................................................................ 46

Appendix A: Stage 1 (Scoping), Stage 2 (Systematic Planning/Screening), and Stage 3

(Risk Assessment) Process Charts ............................................................................................... 49

Appendix B.1: Stage 2 Soil Sampling Approach for Deriving Exposure Concentrations

and Screening Environmental Risk at Cleanup Sites ................................................................... 68

Exhibit A, A Note on Exposure Estimates and Site Screening ............................................................. 73

Exhibit B, Technical Issue Paper – Recommendations for Sampling Approaches for Deriving Surface Soil

Exposure Estimates within Habitat Decision Units at Cleanup Sites ................................................... 74

Appendix B.2: Stage 2 Soil Sampling and Ecological Screening Approach ............................... 84

Appendix B.3: Stage 2 Approach for Conducting Site Screening and Representing a

Local Assessment Population Area ............................................................................................. 88

Stage 2 Systematic Planning/Screening Approach ............................................................................... 88

Appendix C: Selection of Toxicity Reference Values and Development of Ecological

Benchmark Values ..................................................................................................................... 104

Appendix D: Assessment Population......................................................................................... 112

Appendix E: Using Net Environmental Benefit Analysis in Stage 3 (Risk Assessment) of

the Recommended 3-Stage Oregon ........................................................................................... 117


State of Oregon Department of Environmental Quality 8

Abbreviations

ASG Aquatic ecological risk assessment subgroup

AVS/SEM Acid Volatile Sulfide / Simultaneously Extracted Metals

BKD background

BLM Biotic Ligand Model

BRA baseline risk assessment

BW body weight

COC chemicals of concern

COI chemicals of interest

COPC chemicals of potential concern

CPEC contaminants of potential ecological concern

CSL cleanup screening level

CSM conceptual site model

DEQ Department of Environmental Quality

DQO data quality objectives

DU decision unit

EBV ecological benchmark value

EBVd ecological benchmark value dose

ECx effect concentration

EDx effect dose

EEC ecological effect concentration

EPA U.S. Environmental Protection Agency

EPC exposure point concentration

EqP Equilibrium Partitioning

ERA ecological risk assessment

ESL ecological screening level

HDU habitat decision unit

ISM Incremental Sampling Methodology

ITRC Interstate Technology and Regulatory Council

LAPA Local Assessment Population Area

LC50 median lethal concentration

LD50 median lethal dose

LHR large home range receptors

LOAEL lowest-observed-adverse-effect-level

LOF locality of facility

MNR monitored natural recovery

MVP minimum viable population

Nc census size

Ne effective population size

NEBA Net Environmental Benefit Analysis



NFA no-further-action

NOAEL no-observed-adverse-effect-level

OARs Oregon Administrative Rules

PAUF population area use factor

PCBs polychlorinated biphenyl

PCL protective concentration levels

PQL practical quantification limit

QA/QC quality assurance/quality control

RBC risk based concentration

RP responsible party

RSET Regional Sediment Evaluation Team

SAP Sampling and Analysis Plan

SCebv soil concentration associated with EBV dose

SCO Sediment Cleanup Objective

SCUM II Sediment Cleanup User’s Manual II

SDU source decision unit

SEF Sediment Evaluation Framework

SHR small home range receptor

SIR soil ingestion rate

SL screening level

SLV screening level value

SMS Sediment Management Standards

SSL soil screening level

T&E threatened and endangered

TMDP technical/management decision point

TRA targeted response action

TRV toxicity reference value

UCL upper confidence limit



Definitions Acceptable risk level for populations of ecological receptors: as defined in OAR 340-122-0115(6)

means a 10 percent chance, or less, that more than 20 percent of the total local population will be

exposed to an exposure point value greater than the ecological benchmark value for each contaminant of

concern and no other observed significant adverse effects on the health or viability of the local

population.

Assessment endpoint: as defined in OAR 340-122-0115(7) means an explicit expression of a specific

ecological receptor and an associated function or quality that is to be maintained or protected.

Assessment endpoints represent ecological receptors directly or as their surrogates for the purposes of an

ERA.

Decision unit (DU): as defined by ITRC (2012) means the smallest volume of soil (or other media)

targeted for which a decision will be made. A decision unit may consist of one or more sampling units.

Ecological benchmark value (EBV): as defined in OAR 340-122-0115(21), means the highest no-

observed-adverse-effect-level (NOAEL) for individual ecological receptors considering effects on

reproductive success, or the median lethal dose or concentration (LD50 or LC50) for populations of

ecological receptors. If a NOAEL, LD50 or LC50, as applicable, is not available for ecological receptors

considered in the risk assessment, the ecological benchmark value may be derived from other

toxicological endpoints for those receptors or appropriate surrogates for those receptors, adjusted with

uncertainty factors to equate to a NOAEL, LD50 or LC50. The ecological benchmark value shall be

based, to the extent practicable, on studies whose routes of exposure and duration of exposure were

commensurate with the expected routes and duration of exposure for ecological receptors considered in

the risk assessment, or appropriate surrogates for those receptors.

Ecological Screening Levels (ESLs): are equivalent to screening level values (SLVs) defined by DEQ

(1998) as exposure concentrations that are deemed acceptable for ecological receptors, and used to

compare against an EPC to evaluate risk. They are intended for purposes of screening and are generally

not appropriate for use as site-specific cleanup levels.

Exposure Point Concentration (EPC): as defined by EPA (2002) means the value, based on either a

statistical derivation of measured data or modeled data, that represents an estimate of a contaminant

concentration available from a particular medium (such as soil) or route of exposure.

Exposure unit (or exposure area): as defined by EPA (2002) means the area throughout which a

potential receptor may be exposed to a contaminant. “The receptor is assumed to move randomly across

the area, being exposed equally to all parts of the area. The assumption of equal exposure to any and all

parts of the exposure area is a reasonable approach [EPA 1992a] that allows a spatially averaged soil

concentration to be used to estimate the true average concentration contacted over time.” EPA (1992a)

further states “While an individual may not actually exhibit a truly random pattern of movement across

an exposure area, the assumption of equal time spent in different parts of the area is a simple but

reasonable approach.”



Grid sampling: as defined by EPA (2002) means a method for determining the location of samples

where sample material is collected at the nodes of a geometrical grid pattern (for example, square,

rectangle, triangle, hexagon). Sampling can occur at equally-spaced intervals on the nodes or within the

grid cells (systematic grid sampling or systematic random sampling) or randomly within grid cells

(stratified random sampling or random sampling within grids).

Habitat decision unit (HDU): as defined by the Ecological Risk Assessment Technical Workgroup

means a type of exposure unit sampled under a structured protocol and for which a management

decision can be made based on the sampling results. The HDU is designated to evaluate the exposure

area of a receptor, and represents the area where a risk decision will be determined. The sampling unit

within a HDU should consist of relatively uniform materials and not contain material from different

habitat types (e.g., grassland and forestland) or blend habitat and non-habitat areas. In this approach the

minimum size of a terrestrial HDU is representative of small home range receptors, and is set at 0.5

acres based on the mean home range (0.55 acres) for 18 female vagrant shrews (Sorex vagrans) sampled

during the breeding season in British Columbia (Hawes 1977).

Incremental sampling methodology (ISM): as defined by ITRC (2012) means a structured composite

sampling and processing protocol based on statistical theory that reduces data variability and provides a

reasonably unbiased estimate of mean contaminant concentrations in a DU. Representative sampling is

achieved by collecting an increment (a portion of the sampling unit of a specified mass collected with a

single operation of a sampling device) and combining the increment with other increments (typically

30–100) each of equivalent mass collected within the same DU to form a single incremental sample.

This incremental sample is then processed and sub-sampled under specific protocols, and analyzed to

estimate the mean concentration in the DU. Proponents of ISM indicate that “…the sampling density

afforded by collecting many increments, together with the disciplined processing and sub-sampling of

the combined increments, in most cases yields more consistent and reproducible results than those

obtained by more traditional (i.e., discrete) sampling approaches.”

Judgmental sampling: as defined by EPA (2002) refers to the selection of sample locations based on

professional judgment alone, without any type of randomization. Judgmental sampling is useful when

there is reliable historical and physical knowledge about a relatively small feature or condition, and can

be helpful to perform a screening phase of a small-scale problem and whether further investigation is

warranted that could include a probabilistic design. Judgmental sampling is distinguished from

probability-based sampling in that inferences are based on professional judgment, not statistical

scientific theory. When using judgmental sampling, statistical analysis cannot be used to draw

conclusions about the target population. Conclusions can only be drawn on the basis of professional

judgment. The usefulness of judgmental sampling will depend on the study objectives, the study size

and scope, and the degree of professional judgment available. When judgmental sampling is used,

quantitative statements about the level of confidence in an estimate (such as confidence intervals) cannot

be made. Evaluation of data based on judgmental sampling is limited to qualitative conclusions, and

decisions are subject to dispute based on conflicting opinions about the magnitude and significance of

unquantified uncertainties.



Locality of the facility: as defined in OAR 340-122-0115(35) means any point where a human or an

ecological receptor contacts, or is reasonably likely to come into contact with, facility-related hazardous

substances, considering:

(a) The chemical and physical characteristics of the hazardous substances;

(b) Physical, meteorological, hydrogeological, and ecological characteristics that govern the

tendency for hazardous substances to migrate through environmental media or to move and

accumulate through food webs;

(c) Any human activities and biological processes that govern the tendency for hazardous substances

to move into and through environmental media or to move and accumulate through food webs;

and

(d) The time required for contaminant migration to occur based on the factors described in

subsections (35)(a) through (c) of this rule.

Population and Local population: as defined in OAR 340-122-0115(40) means a group of individual

plants, animals, or other organisms of the same species that live together and interbreed within a given

habitat, including any portion of a population of a transient or migratory species that uses habitat in the

locality of the facility for only a portion of the year or for a portion of their lifecycle.

Probabilistic sampling: as defined by EPA (2002) refers to a method of sampling whereby sampling

errors can be calculated and for which the biases of selection and estimation are virtually eliminated or

contained within known limits (i.e., all constituent elements of a population have an equal chance of

being taken into the sample). Probabilistic sampling applies statistical theory, involves random selection

of sampling units, allows for statistical inferences to be made about a sampled population, and provides

reproducible results within uncertainty limits. With probabilistic sampling, a data quality or usability

assessment can be conducted and a statistical report produced.

Sample support: as defined by EPA (2002) means the portion of the sampling unit, such as an area,

volume, mass, or other quantity, that is extracted in the field and subjected to the measurement protocol

(e.g., if a sample unit is 10 grams of soil from a point location, the sample support might be 1 gram of

soil after homogenization).

Sampling design: as defined by EPA (2002) specifies the number, type, and exact location (spatial

and/or temporal) of sampling units to be selected for measurement.

Sampling unit: as defined by EPA (2002) refers to members of a population that may be selected for

sampling or, for Incremental Sampling Methodology (ITRC 2002), the volume of soil from which

increments are collected to determine an estimate of the mean concentration for that volume.

Screening Level Values (SLVs): as defined by DEQ (1998) means exposure concentrations that are

deemed acceptable for ecological receptors, and used to compare against an EPC to evaluate risk. They

are intended for purposes of screening and are generally not appropriate for use as site-specific cleanup

levels.

Source decision unit (SDU): as defined by the Ecological Risk Assessment Technical Workgroup refers

to a type of DUs that is specifically designated to identify contaminant sources that can be targeted for a



remedial action (a remedy DU) or to characterize the pathway of contaminants moving away from a

source (nature and extent of contamination or N&E DU). SDUs can be any size.

Spatial boundary: as defined by EPA (2002) specifies the area and volume and the spatial and temporal

conditions, along with the practical constraints, under which environmental data are collected.

Targeted Response Action (TRA): is comparable to a technical/management decision point in the current

guidance, where the Cleanup Program Manager may allow the RP to undertake a targeted source

control, removal action, or monitored natural recovery (MNR) in lieu of conducting further ERA, with

the result of completing the TRA being a no-further-action (NFA) decision for ecological risks. MNR

may occur with or without compensatory habitat improvements, to offset potential risk while MNR

occurs. The TRA could be a technology-based solution rather than a risk-based solution.



Executive Summary

Background

Oregon's environmental cleanup program is 30 years old. It has been nearly 20 years since

comprehensive revisions were adopted in the state's environmental cleanup statutes and rules to

incorporate a risk-based Cleanup Program and the Department of Environmental Quality (DEQ) adopted

corresponding ERA guidance.

In 2014, DEQ convened a technical ecological risk assessment (ERA) workgroup, compromised of risk

assessors and technical experts, to provide input aimed at improving the ERA process in Oregon. This

report contains the workgroup’s final recommendations, and is intended to summarize the various high-

level recommendations and examples provided by the external workgroup members’ for DEQ to

consider. This report is not intended to be guidance.

The workgroup recommended a revised ERA framework for evaluating terrestrial and aquatic habitats.

The core of the recommendations provide a framework for evaluating terrestrial and aquatic habitats

under the current Oregon Revised Statutes and Oregon Administrative Rules (OARs). The workgroup’s

recommendations for rule revisions are provided under section 2.6 of this report.

DEQ will consider the workgroup’s final recommendations contained in this report, as well as the

administrative record, in developing new policies or guidance for ERAs, and evaluating whether there is

a need for rule changes. Any updates to guidance must be consistent with statute and rule. Any

rulemaking will be conducted with public input.

Terrestrial Habitat Recommendations

The workgroup developed recommendations for a 3-staged ERA framework for evaluating terrestrial

habitat, which is described in the following subsections. The workgroup highly recommends that the

following three concepts be incorporated into DEQ’s ERA guidance update: 1) improved sampling

efficiency and representation of exposure within decision units; 2) the early incorporation of targeted

response actions (TRAs); and 3) improved toxicity reference values (TRVs) and ecological benchmark

values (EBVs). The workgroup noted that two critical aspects of determining ecological risks are

collecting representative samples for calculating exposure point concentrations (EPCs), and having

reliable TRVs to compare EPCs to. Additionally, incorporating TRAs early in the process provides

responsible parties (RPs) incentives to remediate sites earlier and with lower assessment costs. The

workgroup recommends the refined decisions points to help facilitate decision-making by obtaining high

quality data to support decisions.

DEQ has advised the workgroup that it does not have resources to research and maintain an update-to-

date TRVs and EBVs inventory. Nonetheless, the workgroup recommends that the ERA process allow

and encourage RPs to take this on and create the expectation that their results, once successfully peer-

reviewed by an external group of experts, will be adopted into guidance in a timely manner. The

workgroup encourages DEQ to update its ERA guidance in a manner that allows for TRVs and EBVs to



be incorporated as new ecotoxicology and environmental chemistry data become available. The

workgroup recommended the use of improved TRVs and EBVs to allow RPs with an alternative to

being regulated based on assumptions that, at the time of the assessment, are no longer consistent with

the state of the science.

The workgroup recommends a 7-step data quality objectives process in the Stage 2 Systematic Planning

and Screening step to reduce uncertainties in decision-making. The proposed recommendations limit the

flexibility in approach during the initial 2-stages, with the intent to provide for more timely and decisive

action, whether it be a TRA or proceeding to the next stage in the ecological risk evaluation.

The Stage 1 Scoping Process considers current and reasonably likely future land uses and habitat size to

assess potential ecological risks. Local land use designations that do not require conservation of habitat

areas are excluded from further ERA. Stage 1 includes a land use evaluation that is primarily conducted

to identify areas zoned for future development, such as brownfields sites or exclusive current or future

commercial, residential, or industrial use where it is likely that habitat, if present, will be removed

within a reasonable time frame. Because these areas may take years to develop and may provide habitat

during the interim, habitat should not be excluded unless the zoning designation is current and there is a

reasonable likelihood of development. Terrestrial habitat areas smaller than 0.5-acre would have little

value to warrant conducting an ecological risk assessment for small home range receptors. Neither the

land use nor size threshold for exclusion from further ERA applies where threatened and endangered

species or critical habitat is present on-site.

The Stage 2 Systematic Planning and Screening framework includes the following key elements:

• Conceptual Site Model, Sampling and Analysis Plan with a 7-Step DQO Process,

• Criteria for local population area definition,

• Habitat Decision Units,

• Source Decision Units,

• TRAs “off-ramps”, and

• Screening Thresholds.

The Stage 3 Risk Assessment framework includes:

• Site-Specific Conceptual Site Model,

• Approaches for defining a local population assessment area, and

• Incorporation of Net Environmental Benefit Analysis (NEBA).

NEBA is the procedure of weighing the advantages of active cleanup (remediation) versus the impact

that cleanup might have on potentially valuable ecological habitat. Ecology (2012c).The workgroup

recommends NEBA be incorporated at the front end of Stage 3 to encourage formulation of remedial

action alternatives that are designed to simultaneously reduce risk and improve the gains in

environmental services or other ecological properties. NEBA would be used to weigh remedial action

alternatives and evaluate whether a remedial action alternative would do more harm than good.

Additionally, the workgroup recommends the following key recommended rule revisions.

Revise the definition of “population” and “local population”, under OAR 340-122-0115(40), to

clarify what constitutes an assessment population for non-threatened and endangered species.



Revise the definition of “acceptable risk level for populations of ecological receptors”, under

OAR 340-122-0115(6). Key recommendations include removing the “10 percent chance or less”

element of the rule, and adding alternative acceptable risk levels based on population-level

effects, which would allow parties more opportunities to use conventional population models or

studies to assess exposure/response relationships. The definition should also be revised to allow

DEQ to accept site-specific definitions of acceptable risk for Stage 3 risk assessments.

Revise the definition of “ecological benchmark value”, under OAR 340-122-0115(21), to add an

effect concentration (ECx) as criterion for evaluating reproductive effects.

Revise the rule to specifically allow for the use of NEBA in ERAs. Incorporate NEBA

components into rule. Clearly allow for offsetting risk with actions that result in a “net benefit”

to a population of ecological species.

Aquatic Habitat Recommendations

The workgroup defines aquatic habitat as, “rivers, streams, ponds, lakes and reservoirs, and nearshore

marine and intertidal zones” for purposes of aquatic ERAs. Anthropogenic aquatic features, such as

drainage/irrigation ditches, treatment ponds/lagoons, and stormwater diversion features, require periodic

sediment management and do not represent a habitat quality similar to that of natural features.

Furthermore, frequently maintained dredging channels or berths where contaminants are evaluated and

managed through a dredging framework should be excluded (source control evaluations would be

performed on sites that represent important sources of contamination after dredging). Aquatic habitats

typically contain water year-round; wetlands may dry out through the season and should be evaluated

separately. If no aquatic habitat is present, then the process ends with a no-further-action decision for

ecological risk.

The workgroup developed recommendations for a 2-staged ERA framework for evaluating aquatic

habitat: 1) Stage 1 Scoping and 2) Stage 2 Systematic Planning, which is described in the following

subsections. The Stage 1 Scoping framework includes an:

• Initial Aquatic Habitat Assessment,

• Detailed Aquatic Habitat and Ecological Receptor Surveys, and

• Ecological Conceptual Site Model.

The Stage 2 Systematic Planning framework introduces:

• Habitat Decision Units,

• Source Decision Units, and

• 7-Step DQO Process.

The workgroup also recommended a sediment triad approach, which uses three lines of evidence to

determine potential for risk within HDU(s).

The Washington State Department of Ecology (Washington) and U.S. Environmental Protection Agency

(EPA) Region 10 provided dissents to the workgroup’s aquatic recommendations. Washington dissented

based on three main concerns 1) whether DEQ should adopt sediment standards similar to Washington;

2) whether DEQ should integrate the Regional Sediment Team’s (RSET) Sediment Evaluation



Framework (SEF) for dredging; and 3) whether there is value in using bulk sediment chemistry in

ERAs. EPA dissented, to the above characterization of aquatic habitat, stating that berths and channels

should be considered habitat and assessed as such with the understanding that the habitat may be

disturbed at a certain frequency; however, dredged areas will recolonize and provide habitat that may be

impacted by contamination. Additionally, the RSET and the Portland Sediment Evaluation (SEF) Team

consider it habitat as part of their CSM for evaluating dredge materials (as described in the SEF).



1. Introduction

1.1 Background

Oregon's environmental cleanup program is 30 years old in 2017. It has been nearly 20 years since

comprehensive revisions were adopted in the state's environmental cleanup statutes to incorporate a risk-

based Cleanup Program and the Department of Environmental Quality (DEQ) adopted corresponding

ecological risk assessment guidance (ERA). DEQ’s current ERA guidance was initially issued in 1998

and last updated in 2001.

In 2002, DEQ published more comprehensive draft guidance for sediment cleanup. That guidance

document was not finalized due to critical public comments from stakeholders. DEQ did, however,

finalize bioaccumulation guidance for sediment in 2007, which remains in use.

In 2010, DEQ considered adopting draft sediment toxicity values in development for the sediment

dredging program for federal Environmental Protection Agency Region 10 states (including Oregon,

Washington, Idaho, Alaska, and Hawaii). DEQ chose to defer this decision until standards had been

fully vetted during the state of Washington’s rule adoption process.

In 2016, DEQ signed the Regional Sediment Team’s (RSET) Sediment Evaluation Framework (SEF),

which provides a framework for assessing and characterizing sediment to determine the suitability of

dredged material for unconfined, aquatic disposal; determine the suitability of post-dredge surfaces; and

predict effects on water quality during dredging. The SEF was not designed to apply to cleanup projects.

The SEF does not provide guidance for characterizing a contaminated site in order to make decisions

regarding how the site will be managed. The SEF stated “[a]ll sediment evaluations for cleanup actions

are to be coordinated through the appropriate state and federal cleanup programs.” DEQ will consider

whether to adopt SEF principles for the purposes of conducting ERAs. DEQ requested the workgroup

consider whether to incorporate aspects of the SEF into ERAs in Oregon, as well as whether DEQ

should adopt sediment standards similar to Washington.

DEQ’s current ERA guidance provides a four-tiered risk assessment process: scoping, screening,

baseline, and field baseline. The Level I Scoping process in the current guidance includes a qualitative

technical/management decision point (TMDP) for determination whether there is any reason to believe

that ecological receptors or exposure pathways are present or potentially present at or in the locality of

the facility. Scoping is intended to identify sites that are obviously devoid of ecological important

species or habitats and/or where exposure pathways are obviously incomplete.

The Level II Screening process in the current guidance includes screening level values (SLVs) for

plants, invertebrates, and vertebrates for soil, sediment, and water. The SLVs are based on a no-

observed-adverse-effect-level (NOAEL) for individual threatened and endangered species, and a lowest-

observed-adverse-effect-level (LOAEL) for a population of non-threatened and endangered species.

These SLVs were intended for use in screening for potential risk under Level II and were not intended

for use as cleanup levels.



In 2013, DEQ commissioned Formation Environmental to develop updated SLVs on behalf of DEQ. In

2014, Formation Environmental provided DEQ with a table/workbook of updated SLVs (also referred to

as Risk Based Concentrations or RBCs). This version of the table/workbook was not intended to be the

final version, as some tasks remained to be completed. DEQ will consider whether it should complete

the table/workbook update, after deciding what criteria to include in the guidance update and whether

the table/workbook update is still warranted. The recommended SLVs were largely based on EPA’s

ecological soil SLVs. DEQ has not adopted or released these SLVs for general use. The workgroup

considered whether to incorporate the 2014 SLVs into the recommended revised ERA process.

Level III includes a methodology for deriving ecological benchmark values (EBVs) from generic

multipliers applied to NOAELs and LOAELs. See Level III, Table 2 in the current guidance.

The Level III Risk Assessment process in the current guidance involves conducting a baseline risk

assessment consistent with OAR 340-122-0084(3).The purposes of a baseline assessment are to

determine:

(a) If significant ecological effects are occurring at a site,

(b) The probable causes of these effects,

(c) The source of causal agents, and

(d) The consequences of not implementing a remedial action.

The Level III assessment provides the basis for determining the need for remediation and provides

information necessary for the development of protective remedial alternatives.

Several issues have been identified with DEQ’s application of current ERA guidance. In nearly all cases,

ERAs were limited to Level I and Level II scoping and screening procedures. In the past 30 years, less

than ten sites had employed the Level III baseline assessment where the evaluation uses a probability of

exposure to an ecological benchmark value as specified in rule.

The guidance has been challenging to implement because it lacks clear criteria to direct consistent

decision-making based on the information collected in each stage of the process. At times, the

information collected following the current guidance does not provide risk assessors enough confidence

to make risk assessment determinations. The guidance has outdated SLVs for a number of hazardous

substances and lacks bioaccumulation SLVs, resulting in site-specific decisions on the use of SLVs and

methods that result in inconsistencies between projects. As noted above, DEQ has adopted

bioaccumulation guidance (2007) for sediment sites. DEQ risk assessors commonly use SLVs and risk

assessment methods that are not contained in the current guidance or officially approved by DEQ.

Within DEQ, this lack of clear guidance results in decision-making inconsistencies amongst project

managers and regions, strains limited DEQ resources, and leads to increased review time, project delays

and costs. Externally, it may strain relationships with responsible parties (RPs) and their consultants,

who at times view DEQ’s ERA as confusing, unpredictable and burdensome. Consequently, DEQ is

considering updating its ERA guidance.

In 2014, DEQ’s Cleanup Program convened a workgroup comprised of external risk assessor

practitioners to evaluate its ERA process and identify ways to improve the process. The workgroup was

tasked with providing input to the Cleanup Program to improve DEQ’s ERA process by providing clear



criteria for decision-making so the process will be more timely, user-friendly, and effective at removing

sites from further ERA review where significant ecological risks are unlikely. Specifically, the

workgroup was tasked with developing recommendations that:

Refine the Level I scoping, Level II screening, and Level III baseline risk assessments process for

terrestrial and aquatic habitats.

Consider the implications of adopting elements of the Washington Department of Ecology’s sediment

standards for use in Oregon.

Consider whether DEQ should integrate the RSET’s SEF, which was designed for dredging projects.

Evaluate if any rule changes should be considered to more effectively implement ERAs.

The workgroup did not provide recommendations for all of these issues.

The workgroup considered approaches for improving TMDPs throughout the recommended ERA

process. The workgroup also considered what lines of evidence should be used to show observed effects

to constitute unacceptable risk to a population as required by OAR 340-122-0115(6); however, the

workgroup did not provide formal recommendations on this issue because it is a policy issue for DEQ to

decide.

With respect to terrestrial habitat scoping (Level I/Stage1), the workgroup considered adding land use

and habitat size exclusions to remove sites where ecological risks are unlikely. With respect to terrestrial

habitat screening and systematic planning (Level II/Stage 2), the workgroup considered the following:

(1) Approaches for improving how conceptual site models (CSMs) are defined, including an

improved data quality objective process;

(2) Criteria for defining a local population area;

(3) Approaches for incorporating decisions units (DUs) into the decision-making process to improve

systematic planning by defining assessment areas based on the home range size of ecological

receptors; and

(4) Approaches for updating screening thresholds. The workgroup considered whether NOAELs and

LOAELs should continue to be used as the primary screening tool and whether to apply generic

EBVs to screen sites similar to methodology used for deriving generic EBVs in Level III, Table

2 of the current guidance.

With respect to terrestrial habitat baseline risk assessments (Level III/Stage 3), the workgroup focused

on developing criteria to improve how local populations are defined. The workgroup also considered

approaches for improving site-specific CSMs and the incorporation of Net Environmental Benefit

Analysis (NEBA).

For aquatic habitat, the workgroup considered a general framework for conduct scoping and

screening/systematic planning for aquatic ERAs. Similar to the recommended terrestrial habitat ERA

process, the workgroup considered approaches for improving CSMs, including an improved data quality

objective process, and the incorporation of DUs into the Stage 2 Screening/Systematic Planning process.

This report provides the workgroup’s formal recommendations for improving DEQ’s ERA process.

DEQ directed the workgroup to clearly state whether their recommendations are consistent with DEQ’s

current rules or whether rulemaking would be needed to improve the process. The terrestrial and aquatic



habitat recommendations were constructed so that rule revisions would not be needed. Additionally, the

workgroup provided alternative recommendations for rule revisions and provided sample approaches

and examples for DEQ to consider. See subsection 2.6, and Appendices B.1 – E.

DEQ will consider the workgroup’s formal recommendations in developing new policies or guidance for

ERAs, and in evaluating whether there is a need for rule changes. Any rulemaking will be conducted

with public input separate from this workgroup.

1.2 Workgroup Members

In convening this workgroup, DEQ selected external technical experts that reflect the range of entities

both directly and indirectly affected by ERAs conducted under Cleanup Program rules. DEQ workgroup

members include a senior level toxicologist, cleanup project manager, and air toxics science/policy

analyst. Additional DEQ employees were involved in managing and supporting the workgroup during

and between meetings.

DEQ Sponsoring Manager

Bruce Gilles, DEQ Cleanup and Emergency Response Program Manager

Workgroup Members

Heather Brunelle, Brunelle Environmental Consulting LLC, joined after meeting 4

Arthur Buchan, Washington State Department of Ecology

Jeremy Buck, U.S. Fish & Wildlife Service, Oregon Fish and Wildlife Office

Joe Goulet, U.S. Environmental Protection Agency, Region 10

Dan Hafley, DEQ

Bruce Hope, CH2M Hill, served on the workgroup during meetings 1 – 4

Mark Lewis PhD, Formation Environmental

Susan MacMillan, DEQ, served on the workgroup during meetings 1 – 8

Madi Novak, Maul Foster and Alongi

Jeff Peterson, PhD, SLR Consulting

Jennifer Peterson, PhD, DEQ

John Toll, PhD, Windward Environmental LLC

Facilitator

Julie Wilson, PhD, Hart Crowser, served as the facilitator during meetings 1 – 8

Bruce Gilles, DEQ, facilitated the workgroup meetings meeting 9– 13

Tiffany Johnson, JD, DEQ, facilitated meeting 14

Project Manager

Annette Dietz, PhD, served as the workgroup project manager for the first six meetings

Tiffany Johnson, JD, DEQ, served as the workgroup project manager since meeting 10



Other Participants

David Anderson, provided a Cleanup Program manager perspective at meetings as reflected in

the meeting summaries

Sarah Apodaca, administrative support

Liz Bolden, administrative support

Don Hanson, provided a Cleanup Program manager perspective at meetings as reflected in the

meeting summaries

Keith Johnson, provided a Cleanup Program manager perspective at meetings as reflected in the

meeting summaries

Mike Kucinski, provided a Cleanup Program manager perspective at meetings as reflected in the

meeting summaries

Russ McMillan, Washington State Department of Ecology, participated at meeting as reflected in

the meeting summaries, and worked with Arthur Buchan in preparing Ecology’s

recommendations and dissent

Kevin Parrett, PhD, provided a Cleanup Program manager perspective at meetings as reflected in

the meeting summaries

Michael Poulsen, provided a toxicologist perspective at meetings as reflected in the meeting

summaries

Paul Seidel, provided a toxicologist perspective at meetings as reflected in the meeting

summaries

Susan Turnblom, provided a toxicologist perspective at meetings as reflected in the meeting

summaries

Phil Wiescher, Maul Foster and Alongi, participated at meeting as reflected in the meeting

summaries

1.3 Oregon Law

Oregon’s current environmental cleanup laws for Removal and Remedial Actions, Oregon Revised

Statute (ORS) 465.200- 465.325, provide for a risk-based approach for assessing and managing

environmental contamination. These statutes and the Oregon Administrative Rules (OAR) adopted to

implement the statute (OAR 340-122-0090 and 340-122-0115) require that environmental cleanup

actions be based on the results of risk assessment. Under OAR, humans and threatened or endangered

species risks are evaluated on an individual level and non-threatened or endangered species risks are

evaluated on a population level.

In risk assessment and other aspects of environmental cleanup, there is a hierarchy of authority amongst

the statutes, administrative rules and DEQ guidance or policy. The language of statute controls over the

language of OAR and DEQ guidance. Similarly, the language of an adopted administrative rule controls

over the language in DEQ guidance documents or policy statements.

ORS 465.315 is the foundation authority for risk assessments. This statute defines the acceptable risk

level for ecological receptors and instructs the Environmental Quality Commission (EQC) to adopt rules



that establish protocols, consistent with the statute, for conducting population-level ERA. The relevant

sections of the statute are given below.

ORS 465.315(1)(b)(A) establishes the acceptable risk level for ecological exposures to hazardous

substances as follows:

For protection of ecological receptors, if a release of hazardous substances causes or is

reasonably likely to cause significant adverse impacts to the health or viability of a species

listed as threatened or endangered pursuant to 16 U.S.C. 1531 et seq. or ORS 496.172, or

a population of plants or animals in the locality of the facility, the acceptable risk level

shall be the point before such significant adverse impacts occur.

OAR Division 340, Chapter 122, defines acceptable risk and establishes the standards and procedures to

investigate releases of hazardous substances and determine remedial actions necessary to protect human

health and the environment. These rules represent DEQ’s interpretation of statutes and they implement

the statutes.

OAR 340-122-0084(1)(h)(B) interprets ORS 465.315(1)(b)(A) to mean that the acceptable risk level for

threatened and endangered species is protection of an individual organism and for non-threatened and

endangered species protection is on a population level. Presumably, the protection at an individual

organism level is justified because injury to a single individual could potentially represent a “significant

adverse impact to the health or viability of a species listed as threatened or endangered.” Protection of

individual organisms of threatened and endangered species is also consistent with requirements of the

Endangered Species Act.

For non-threatened or endangered species, ORS 465.315(1)(b)(A) requires the protection of populations

of plants or animals in the locality of the facility. The locality of the facility is not defined in statute, but

the “facility” is defined in ORS 465.200(13) as follows:

Facility means any building, structure, installation, equipment, pipe or pipeline including

any pipe into a sewer or publicly owned treatment works, well, pit, pond, lagoon,

impoundment, ditch, landfill, storage container, above ground tank, underground storage

tank, motor vehicle, rolling stock, aircraft, or any site or area where a hazardous substance

has been deposited, stored, disposed of, or placed, or otherwise come to be located and

where a release has occurred or where there is a threat of a release, but does not include

any consumer product in consumer use or any vessel.

OAR 340-122-0084 includes the following provisions on how to conduct population-level risk

assessment:

(1) General requirements for risk assessments include:

(a) Risks assessments shall consider existing and reasonably likely future human

exposures and significant adverse effects to ecological receptors in the locality of the

facility.

(h) The use of population risk estimates in addition to individual risk estimates is

provided for as follows:



(B) For ERAs, risk estimates shall be made:

(i) At the level of the individual for species present in the locality of the facility

if the species is listed as threatened or endangered species pursuant to 16 U.S.C.

1531 et seq. or ORS 496.172; or

(ii) At the level of the population for all other plants or animals in the locality

of the facility.

(3) Baseline ERAs shall include, but are not limited to, the following information:

(a) Problem formulation to include identification of contaminants of ecological interest,

potential ecological effects, ecological receptors, relevant exposure pathways, initial

definition of assessment and measurement endpoints, all with respect to current and

reasonably likely future land and water uses, and described in a conceptual site model;

(f) As appropriate, the potential for significant adverse effects on the health or viability

of individual ecological receptors or local populations may be evaluated with a weight-

of-evidence analysis or population viability analysis, respectively. These analyses may

utilize field studies, laboratory investigations, appropriate population models, or any

combination of these or other methods acceptable to the Department;

OAR 340-122-0115 defines some of the above terms, and these definitions are important for

understanding the ERA protocols. The most relevant definitions for population-level risk assessment are

as follows:

(6) Acceptable risk level for populations of ecological receptors means a 10 percent chance, or

less, that more than 20 percent of the total local population will be exposed to an exposure

point value greater than the ecological benchmark value for each contaminant of concern and

no other observed significant adverse effects on the health or viability of the local population.

(7) Assessment endpoint means an explicit expression of a specific ecological receptor and an

associated function or quality that is to be maintained or protected. Assessment endpoints

represent ecological receptors directly or as their surrogates for the purposes of an ERA.

(21) Ecological benchmark value means the highest no-observed-adverse-effect-level

(NOAEL) for individual ecological receptors considering effects on reproductive success or

the median lethal dose or concentration (LD50 or LC50) for populations of ecological

receptors. If a NOAEL, LD50 or LC50, as applicable, is not available for ecological receptors

considered in the risk assessment, the ecological benchmark value may be derived from other

toxicological endpoints for those receptors or appropriate surrogates for those receptors,

adjusted with uncertainty factors to equate to a NOAEL, LD50 or LC50. The ecological

benchmark value shall be based, to the extent practicable, on studies whose routes of exposure

and duration of exposure were commensurate with the expected routes and duration of

exposure for ecological receptors considered in the risk assessment, or appropriate surrogates

for those receptors.



(25) Exposure point value means the concentration or dose of a hazardous substance occurring

at a location of potential contact between a human receptor and the hazardous substance, or

between an ecological receptor and the hazardous substance.

(35) Any point where a human or an ecological receptor contacts, or is reasonably likely to

come into contact with, facility-related hazardous substances, considering:

(a) The chemical and physical characteristics of the hazardous substances;

(b) Physical, meteorological, hydrogeological, and ecological characteristics that govern the

tendency for hazardous substances to migrate through environmental media or to move and

accumulate through food webs;

(c) Any human activities and biological processes that govern the tendency for hazardous

substances to move into and through environmental media or to move and accumulate

through food webs; and

(d) The time required for contaminant migration to occur based on the factors described in

subsections (35)(a) through (c) of this rule.

(36) Measurement endpoints for ecological receptors are quantitative expressions of an

observed or measured response in ecological receptors exposed to hazardous substances.

(40) Population and Local population, for purposes of evaluating ecological receptors, means

a group of individual plants, animals, or other organisms of the same species that live together

and interbreed within a given habitat, including any portion of a population of a transient or

migratory species that uses habitat in the locality of the facility for only a portion of the year

or for a portion of their lifecycle.

2. Terrestrial Habitat Recommendations The workgroup developed recommendations for a 3-staged ERA (ERA) framework for evaluating

terrestrial habitat, which is described in the following subsections. Appendix A: Stage 1 (Scoping),

Stage 2 (Systematic Planning and Screening), and Stage 3 (Risk Assessment) Process Charts, illustrates

the workgroup’s recommended ERA process under current rules. The following appendices were

prepared by the terrestrial subgroup, aquatic subgroup, or individual workgroup members to provide

additional information and examples of different approaches for DEQ to consider.

• Appendix B.1: Stage 2 Soil Sampling Approach for Deriving Exposure Concentrations and

Screening Environmental Risk at Cleanup Sites (provided as alternative example approaches)

• Appendix B.2: Stage 2 Soil Sampling and Ecological Screening Approach (provided as

alternative example approaches)

• Appendix B.3: Stage 2 Approach for Conducting Site Screening and Representing a Local

Assessment Population Area

• Appendix C: Selection of Toxicity Reference Values and Development of Ecological Benchmark

Values

• Appendix D: Assessment Population



• Appendix E: Using Net Environmental Benefit Analysis in Stage 3 (Risk Assessment) of the

Recommended 3-Stage Oregon ERA Process

The terrestrial habitat recommendations were constructed so that rule revisions would not be needed.

Subsection 2.6 provides the workgroup’s recommendations for rule revisions.

A more streamlined and transparent staged process is required to allow for early exit ramps to exclude

sites unlikely to have potential ecological risks requiring cleanup actions. The proposed

recommendations limit the flexibility in approach during the initial 2-stages, with the intent to provide

for more streamlined decision making on whether to proceed to a cleanup action or the next stage in the

ecological risk evaluation.

2.1 Key Recommendations

The workgroup highly recommends that the following three concepts be incorporated into DEQ’s ERA

guidance update: 1) improved sampling efficiency and representation of exposure within decision units

(DUs); 2) the early incorporation of targeted response actions (TRAs); and 3) improved toxicity

reference values (TRVs) and ecological benchmark values (EBVs). The workgroup noted that two

critical aspects of determining ecological risks are collecting representative samples for calculating

exposure point concentrations (EPCs), and having reliable TRVs to compare EPCs to. Additionally, the

workgroup recommends incorporating TRAs early in the process provides responsible parties (RPs)

incentives to remediate sites earlier and with lower assessment costs. The workgroup recommends the

refined decisions points to help facilitate decision-making by obtaining high quality data to support

decisions.

2.1.1 Target Response Actions

A TRAs is comparable to a TMDP in the current guidance, where the Cleanup Program Manager may

allow the RP to undertake a targeted source control, removal action, or monitored natural recovery

(MNR) in lieu of conducting further ERA, with the result of completing the TRA being a no-further-

action (NFA) decision for ecological risks. MNR may occur with or without compensatory habitat

improvements, to offset potential risk while MNR occurs. The TRA could be a technology-based

solution rather than a risk-based solution.

There is a need for RPs to have the option to conduct TRAs to allocate resources towards early cleanup

actions rather than toward more refined risk evaluations. If the TRA option is taken at Stage 1 then the

TRA is likely to be more conservative because site data are limited. The recommended ERA process

includes later opportunities to opt for a TRA, either at the end of the Stage 2 Systematic Planning and

Screening process or during the Stage 3 risk assessment process.

The ERA process for the targeted area or specific DU is suspended when a TRA agreement is reached,

and ends (for that target area or DU) when the TRA has been completed. Post-TRA monitoring may be

required to confirm that the TRA achieved specific performance metrics. TRAs may be selected by

mutual agreement of the authorizing parties, and would be governed by a formal agreement between

DEQ and the RP.



2.1.2 Toxicity Reference Values and Ecological Benchmark Values

TRVs for wildlife species are typically doses of environmental contaminants that represent exposure that

are not expected to result in ecologically adverse effects on the target species. TRVs are used during the

ERA process to evaluate whether site-specific exposure may represent unacceptable risk to wildlife

receptors.

The workgroup recommends using TRVs to develop soil SLVs and EBVs for the Stage 2 analysis, and

the TRVs be used to allow direct comparison of data on contaminant concentrations in site media to

evaluate risk. See Appendices B.3 and C for details on how TRVs could be used in the recommended

ERA process.

The workgroup considered whether to screen sites based on EBVs derived from applying generic

multipliers to NOAELs and LOAELs, which is similar to methodology for deriving EBVs that is

included in Level III, Table 2 of the current guidance. The workgroup recommends using EBVs based

on toxicological data, to the extent such data is available, and not using EBVs derived from generic

EBVs. Any uncertainty factors incorporated into an assessment should be scientifically supported, and

generic uncertainty factors (such as those based on ten-fold reductions) should not be used.

Reliable TRVs and EBVs are critical to ecological risk decision-making. Reliable values are essential in

the derivation of generic screening levels and also for use in site-specific, baseline ERAs. The ERA

guidance should be updated with an efficient process for continually updating TRVs and EBVs with

newly available science, and to provide updated TRVs and EBVs to all interested parties. The effort to

continuously update TRVs and EBVs may require an increase allocation of DEQ staffing resources

above current levels. Key recommendations for updating TRVs and EBVs include:

1. Incorporate improved methodology, including evaluating effective concentration or dose

(ECx or EDx) values for survival, reproduction, or growth endpoints to replace to use of

NOAELs and LOAELs.

2. Gradually develop a database of EBVs and use in place of ESLs as EBVs are developed.

When an EBV is used, then additional evaluations must be conducted to show how the

analysis meets the acceptable level of risk for populations of ecological receptors as defined

in rule.

3. Utilize an external panel of experts for assistance in the review of TRV and EBV updates.

4. Provide more incentives for RPs to allocate resources for TRV and EBV improvements.

5. Initially focus on those contaminants identified as risk drivers in past ERAs.

6. Maintain a database of TRVs and EBVs that can be built upon as new information develops.

This database would be maintained by DEQ and provided to interested parties.

The workgroup recommends the use of EBVs, if available, to evaluate mortality (i.e., LD50 or LC50)

and the use of ECx or EDx to evaluate survival, reproduction, or growth. Appendix C provides

additional recommendations regarding development of TRVs and EBVs.

DEQ has advised the workgroup that it does not have resources to research and maintain an update-to-

date TRVs and EBVs inventory. Nonetheless, the workgroup recommends that the ERA process allow

and encourage RPs to take this on and create the expectation that their results, once successfully peer-

reviewed by an external group of experts, will be adopted into guidance in a timely manner. The



workgroup encourages DEQ to update its ERA guidance in a manner that allows for TRVs and EBVs to

be incorporated as new ecotoxicology and environmental chemistry data become available. The

workgroup recommended the use of improved TRVs and EBVs to allow RPs with an alternative to

being regulated based on assumptions that, at the time of the assessment, are no longer consistent with

the state of the science.

2.2 Stage 1 Scoping

A shortcoming of the current Level 1 Scoping process is that it lacks criteria for identifying sites that are

sufficiently unlikely to pose significant ecological risks, and withdraw them from the ERA process.

Consequently, the current process triggers unnecessary ERAs. A more streamlined and transparent

staged process is required to allow for early exit ramps to exclude sites unlikely to have potential

ecological risks requiring cleanup actions.

The recommended Stage 1 Scoping process is intended to be completed at the beginning stages of a

project, prior to delineation of the nature and extent of contamination. The workgroup recommends that

the scoping process include two new considerations to better identify sites that warrant additional ERA:

1) Determine current and reasonably likely future land uses and exclude sites that are unlikely to

represent important ecological habitat over the long-term and

2) Exclude sites that are too small to pose significant ecological risks.

The Stage 1 Scoping Process considers current and reasonably likely future land uses and habitat size to

assess potential ecological risks. Local land use designations that do not require conservation of habitat

areas may be excluded from further ERA. Stage 1 includes a land use evaluation that is primarily

conducted to identify areas zoned for future development, such as brownfields sites or exclusive current

or future commercial, residential, or industrial use where it is likely that habitat, if present, will be

removed within a reasonable timeframe. Because these zoned areas may take years to develop and may

provide habitat during the interim, habitat should not be excluded unless the zoning designation is

current and there is a reasonable likelihood of development. The land use exclusion is not considered for

areas with a green overlay (an area within a property that is set aside for environmental protection).

The workgroup recommended a habitat size threshold to exclude small sites from further ERA. The

habitat size threshold excludes terrestrial habitat under 0.5-acre from further ecological investigation,

unless the site includes presence of threatened or endangered species, or designated critical habitat for

threatened and endangered species, or aquatic habitat is present on-site. The 0.5-acre terrestrial habitat

threshold is considered to represent an area below which an ERA would have little or no value. The 0.5-

acre minimum size is based on the average home range of a breeding female vagrant shrew (Sorex

vagrans).

The Stage 1 process requires an initial qualitative habitat and ecological receptor survey for all sites to

determine whether insufficient “acceptable habitat” is present to warrant an ERA. The workgroup

defined “acceptable habitat” as habitat that provides distinct food and cover benefits for ecological

receptors. The workgroup expects that new guidance will have to be developed to define the terms

“acceptable habitat” and “anthropogenic habitat” in a manner that satisfies the intent of the workgroup’s

recommendation.



The Stage 1 Scoping process is described in greater detail in Appendix A, Stage 1 Scoping Flowchart,

provided as an example of conducting a scoping evaluation for the ERA. The Stage 1 Scoping process,

illustrated in Appendix A, includes land use and habitat thresholds, identification of the initial

geographic scope of the study area, criteria for conducting habitat and ecological receptor surveys and

assessments, and TRAs.

2.3 Stage 2 Systematic Planning and Screening

The Stage 2 Systematic Planning and Screening process for terrestrial habitat involves a planning step to

identify critical data needs, and a risk-based screening step to better focus detailed ERA on sites that

have a reasonable potential to pose unacceptable ecological risks.

The purpose of Stage 2 is threefold:

1) Obtain appropriate data for determining whether or not an ERA should be conducted for the site

2) Decide whether or not an ERA should be conducted for the site

3) If an ERA is not going to be conducted for the site, then decide which is needed to manage

ecological risk: a TRA or NFA determination. Sites that meet Stage 2 site screening criteria

automatically qualify for NFA for ecological risks. Sites that do not meet Stage 2 site screening

criteria can be managed by completing a TRA or by completing a Stage 3 ERA and taking

subsequent actions as determined by the Stage 3 ERA outcome.

The first goal of Stage 2 is to ensure that exposure estimates and toxicity thresholds used for making

Stage 2 decisions are based on appropriate data so environmental decisions can be made cost-effectively

without delays that are often associated with too much uncertainty and insufficient data. The process

provides more opportunities for sites to screen out or undergo TRAs early in the process compared to

the current risk assessment approach, and therefore more sites are expected to be cost-effectively closed

while still maintaining environmental protection.

The second goal of Stage 2 Systematic Planning and Screening is to expeditiously and cost-effectively

identify sites that can be addressed with NFA or a TRA, without the need for proceeding to Stage 3 of

the ERA process. The workgroup expects that if the proposed changes to the ERA process are adopted, a

substantial fraction of sites will be expeditiously and cost-effectively closed without the need for a Stage

3 ERA.

The recommended Stage 2 process is illustrated in Appendix A, Stage 2 Systematic Planning/Screening

Flowchart, which is provided as an example of how to conduct a planning and screening evaluation.

Appendices B.1, B.2, and B.3 offer different examples of how a Stage 2 screening assessment and

systematic planning can be performed for terrestrial ecological receptors, including approaches for

designing a soil sampling and analysis plan, conducting site screening, deriving exposure

concentrations, and defining a local assessment population area. These examples illustrate different

approaches that are intended to better utilize incremental sampling methodology (ISM) where most

appropriate. Key elements of the recommended terrestrial Stage 2 process are described below.



2.3.1 Conceptual Site Model, Sampling and Analysis Plan with Data Quality Objectives

Stage 2 starts with a technical planning meeting with experts that are knowledgeable about the site or

have expertise in specific disciplines needed to refine the conceptual site model (CSM), identify the

primary study question, define the spatial scale and populations of interest, and establish the decision-

making process and level of certainty needed to make decisions.

The products of the Stage 2 process are the revised CSM, a sampling and analysis plan which includes

the data quality objectives (DQOs) and decisions made during the planning meeting, along with a report

identifying the sampling results, identification of contaminants of potential ecological concern, and a

determination about whether the site will be designated for NFA, TRA, or an ERA (the third stage of the

ERA process).

2.3.2 Decision Units

To help standardize sampling plans, the workgroup recommends using habitat decision units (HDUs) of

a designated size to define the area to evaluate small home range receptors (SHRs). The recommended

minimum size of the HDUs is 0.5 acres, which roughly estimates the home range of a SHR. The HDU

will serve as the exposure areas to represent SHRs. Larger DUs can be used if necessary to evaluate

larger receptors or local population areas (determined a priori during the planning stage). In addition to

HDU, source decision units (SDUs) can be designated as any size and are specifically used to address

contaminant sources at a site, and to better manage areas where TRAs could occur. See Appendices B.1,

B.2, and B.3 for additional details on how DUs can be used in the ERA process.

2.3.3 Screening Thresholds

To standardize the screening of site data, the workgroup recommends use of generic SLVs (also referred

to as ecological screening level (ESLs) values) as screening thresholds during Stage 2 with the following

considerations:

Screening thresholds be derived for both soil and prey tissue. Standard equations should be

provided in guidance for translating screening thresholds between concentration-based and dose-

based measurement units. Screening thresholds should be derived based on best available

science, and that they be revised as new ecotoxicology and environmental chemistry data

become available.

Screening thresholds should be based on best available science to account for chemical

bioavailability and other factors that can improve reliability of thresholds.

Screening thresholds should rely less on NOAEL and LOAEL values and instead be based on

ECx or EDx values for survival, reproduction, or growth endpoints. The value of x should be

specified in guidance.

EBVs should be developed for key chemicals. The values can be included in a database of that is

regularly updated as parties develop new EBVs that are approved by the agency.

2.4 Stage 3 Risk Assessment

A terrestrial habitat Stage 3 risk assessment requires more ecological information than is used to screen

sites against toxicity thresholds in Stage 2. Information about life history characteristics (e.g., home



range, population density) and habitat preferences can be obtained from the literature. Information about

habitat conditions within and near the locality of facility (LOF) can only be obtained by site visits and

field surveys. Obtaining and interpreting this additional information is necessary to yield ecologically

relevant and reasonable estimates of risk.

The workgroup recommends that a clear process be developed for performing population-level risk

assessments using EBVs and the acceptable risk level rule as defined in current guidance. Appendix D

provides an example of how population-level risk assessment can be performed consistent with current

rules using the EBV.

In general, the ecological risks for sites that pass through Stage 2 and into Stage 3 will be lower than

what one would conclude based on the information used in Stage 2 to make the decision to conduct a

Stage 3 ERA. This is because the risk assessment process provides a margin of safety that can be

reduced, without loss of protectiveness, by gathering more information about the conditions occurring at

the specific site in question.

It is cost-effective to obtain more site-specific information in Stage 3 at a point that allows DEQ to make

risk management decisions that are equally or more protective than the decision that could be made

based on a Stage 2 assessment, while costing less for the parties paying for the remedial investigation

and response action. In other words, a Stage 3 assessment can in some cases produce both net economic

and environmental benefits.

It is important though to understand that the net environmental benefit of a Stage 3 assessment is

contingent on the expertise of the risk assessment team conducting the assessment, and the ability of the

oversight team to accept creative solutions. The workgroup recommends that a peer-review team that

includes scientists and other practitioners outside of DEQ be developed to evaluate, as necessary, Stage

3 risk assessments. A database of innovative Stage 3 risk assessment approved by DEQ should be

assembled and regularly updated.

An overarching recommendation of the workgroup is that Stage 3 be less prescriptive than Stages 1 and

2 because of the need to tailor the ERA approach to meet the field conditions and other circumstances

specific to each particular site. The Stage 3 process is illustrated in Appendix A, Stage 3 Risk

Assessment Flowchart, provided as an example of conducting a Stage 3 assessment.

Recommendations on specific elements of the terrestrial Stage 3 process are described below.

2.4.1 Site-Specific Conceptual Site Model

The workgroup recommends that each Stage 3 assessment begins by producing a revised CSM

describing the hypothesized causal links between the presence of contaminants and adverse population-

level effects (individual organism level effects if a T&E species is present). The approved CSM should

serve as the basis for developing a more detailed problem formulation and site-specific work plan.

2.4.2 Local Population Area

The workgroup recommends that guidance clearly define the local population to be assessed in a Stage

3 ERA. Appendices B.3 and D provide examples of different concepts for defining the assessment

population. The local population area identifies the boundary around habitat patches that will be



considered in the risk assessment in relation to the contaminated area. The local population area is best

defined using geographic and anthropogenic features (physical boundaries). When these boundaries are

not sufficient to limit an area, then the local population area for terrestrial environments will differ

depending on the receptors being evaluated.

2.5 Net Environmental Benefit Analysis

A Net Environmental Benefit Analysis (NEBA) has been described as “the procedure of weighing the

advantages of active cleanup (remediation) versus the impact that cleanup might have on potentially

valuable ecological habitat.” Ecology (2012c). NEBA is also described as:

“A methodology for identifying and comparing net environmental benefits of alternative

management options, usually applied to contaminated sites.” Net environmental benefits

are describes as, “the gains in environmental services or other ecological properties

attained by remediation or ecological restoration, minus the environmental injuries

caused by those actions. Efroymson et al. (2003).1

NEBA has the long-term potential to reduce the costs, increase the ecological benefits, and increase the

pace of environmental cleanups.

OARs implicitly allow for the use of NEBA to weigh remedial action alternatives as an element of risk

management. OAR 340-122-0084(4) requires a residual risk assessment be conducted, for candidate

remedial action alternatives, prior to the selection or approval of a remedial action. Residual risk

assessments must include:

a) A quantitative assessment of the risk resulting from concentrations of untreated waste or

treatment residuals remaining at the facility at the conclusion of any treatment or excavation and

offsite disposal activities taking into consideration current and reasonably likely future land and

water use scenarios and the exposure assumptions used in the baseline risk assessment; and

b) A qualitative or quantitative assessment of the adequacy and reliability of any institutional or

engineering controls to be used for management of treatment residuals and untreated hazardous

substances remaining at the facility.

c) The combination of (a) and (b) constitute a residual risk assessment that must demonstrate to the

Department that acceptable levels of risk as defined by OAR 340-122-0115 would be attained in

the locality of the facility.

OAR 340-122-0090(1) requires DEQ to select or approve a remedial action that is:

a) Is protective of present and future public health, safety and welfare and of the

environment, as specified in OAR 340-122-0040;

1Efroymson, R. A., J. P. Nicolette, and G. W. Suter II. 2003. A framework for net environmental benefit analysis for remediation or restoration of petroleum-contaminated sites. ORNL/TM-2003/17. Oak Ridge National Laboratory, Oak Ridge, Tennessee.



b) Is based on balancing of remedy selection factors, as specified in section (3) of this rule;

and

c) Satisfies the requirements for hot spots of contamination, as specified in section (4) of

this rule.

OAR 340-122-0090(3)(e) requires that all candidate remedial action alternatives be assessed for the

reasonableness of the cost of the remedial action, by considering, among other things, the “degree to

which the costs of the remedial action are proportionate to the benefits to human health and the

environment created through risk reduction or risk management, as well as any other information

relevant to cost-reasonableness.”

Taken together, residual risk and cost-reasonableness assessments required by OARs can be used to

identify and compare the net environmental benefits of alternative risk management options.

The workgroup recognizes the importance of identifying and comparing the net environmental benefits

of alternative risk management options, and recommends that steps be taken to facilitate, through

updates to its ERA rules and guidance, the use of NEBA in Oregon ERAs. The workgroup has the

following key recommendations about the use of NEBA in Oregon ERAs, under existing rules:

• NEBA should be incorporated at the front end of Stage 3 to encourage formulation of remedial

action alternatives that are designed to simultaneously reduce risk and improve the gains in

environmental services or other ecological properties. This will require that preliminary remedial

action alternatives be defined early in Stage 3.

• NEBA methodology should be left flexible in guidance. NEBA requirements will vary from site

to site, depending on a) the nature and extent of candidate remedial action alternatives and b) the

variance and uncertainty in the residual risks and costs of those alternatives.

2.6 Rule Revision Recommendations

The workgroup recommends that DEQ consider revising some OARs regarding ecological risk

assessment, especially population-level risk assessment. Suggested rule revisions four key rule changes:

1) redefine “population”, 2) redefine “acceptable risk level for populations of ecological receptors”, 3)

redefine “ecological benchmark value”, and 4) explicitly incorporate NEBA into rule.

Revise the Definition of Assessment “Population” (OAR 340-122-0115(40))

The workgroup recommends DEQ provide a better rule description or clarification of the assessment

population for non-threatened and endangered species. For example, better describe the area over which

the assessment population resides, and consider removing aspects of the current definition that may be

unnecessary such as the requirement that individuals in a population interbreed.

Revise the Definition of “Acceptable Risk Level for Populations of Ecological Receptors

(OAR 340-122-0115(6))

The workgroup recommends DEQ consider adding on population-level effects. The current definition

focuses on exposure. By adding alternative acceptable risk levels based on population-level effects,

parties will have more opportunities to use conventional population models or studies to assess



exposure/response relationships. OAR 340-122-0084(3)(f) currently describes a number of population

assessment methods, but most of these methods are difficult to implement using an acceptable risk level

based only on exposure. Examples of additional acceptable risk level definitions consistent with OAR

340-122-0084(3)(f) include the following:

No more than X% reduction in population size (average number of individuals) due to exposure

to a chemical.

No more than X% reduction in population growth rate due to exposure to a chemical.

No more than X% reduction in population persistence time due to exposure to a chemical.

No more than X% increase in the probability of population extirpation due to exposure to a

chemical.

Consider dropping the “10 percent chance or less” term, as this is the hardest part of the rule to measure,

and assessing a “10 percent chance” adds a large component of uncertainty to the risk evaluation. The

remaining part of the acceptable risk definition, which relies on evaluation a 20 percent effect (or which

could be changed to a lower X percent effect), is more reliably measured and is likely nearly as

protective or at least associated with less uncertainty.

For Stage 3, DEQ could accept proposals defining acceptable risk that are specific to a particular

contaminated site. DEQ can review and accept these proposals to ensure they meet sufficient conditions.

It is expected that these site-specific definitions would be reserved for a small fraction of sites and could

include something other than an exposure-based evaluation.

Revise the Definition of “Ecological Benchmark Value” (OAR 340-122-0115(21))

The workgroup recommends DEQ consider adding an effect concentration (ECx) for reproduction in the

ecological benchmark value definition. Some chemicals can cause adverse effects on populations by

reducing reproductive rates at exposure levels well below those that cause mortality.

Incorporate Net Environmental Benefit Analysis

Rules changes should be considered to establish boundaries and expectations on parties opting to use

NEBA to evaluate remedial alternatives in an ERA. The workgroup recommends DEQ revise rule to

specifically call out NEBA as a permissible consideration in ERA risk management decisions. The rule

could be revised to reflect NEBA components and clearly allow for offsetting risk with actions that

result in a “net benefit” to the population.

3. Aquatic Habitat Recommendations The workgroup developed recommendations for a 2-staged ERA framework for evaluating aquatic

habitat: 1) Stage 1 Scoping and 2) Stage 2 Systematic Planning, which is described in the following

subsections.

Appendix A incorporates TMDPs for aquatic habitat ERAs. Elements specific to aquatic habitat include:

Initial Aquatic Habitat Assessment,

Quantitative Aquatic Habitat and Ecological Receptor Surveys, and



Conceptual Site Model (CSM), Sampling and Analysis Plan with Data Quality Objectives.

Unlike the recommended Stage 1 scoping process for terrestrial habitat, there is no minimum acreage

requirement for aquatic habitat.

3.1 Stage 1 Scoping

The Stage 1 Scoping framework for an aquatic habitat is provided as part of the ERA flowchart.

Elements specific to an aquatic habitat include:

Initial Aquatic Habitat Assessment

Detailed Aquatic Habitat and Ecological Receptor Surveys

Conceptual Site Model

3.1.1 Initial Aquatic Habitat Assessment

The first step is to determine if aquatic habitat is present within the Geographic Scope of Study Area.

The initial aquatic habitat assessment can be based on a desktop mapping exercise or a site visit made by

the project manager or designee. Aquatic habitats include rivers, streams, ponds, lakes and reservoirs,

and nearshore marine and intertidal zones. Anthropogenic aquatic features require periodic sediment

management and do not represent a habitat quality similar to that of natural features, such as

drainage/irrigation ditches, treatment ponds/lagoons, and stormwater diversion features. Furthermore,

frequently maintained dredging channels or berths where contaminants are evaluated and managed

through a dredging framework may be excluded from ERAs. Nonetheless, source control evaluations

would be performed on aquatic sites that represent important sources of contamination after dredging.

Aquatic habitats typically contain water year-round; wetlands may dry out through the season and

should be evaluated separately. If no aquatic habitat is present, then the process is ended.

3.1.2 Detailed Aquatic Habitat and Ecological Receptor Surveys

If results of the initial habitat assessment indicate that a chemical release may have contaminated aquatic

habitats, a more detailed habitat evaluation is recommended. This step includes aquatic habitat and

ecological receptor evaluations, conducted by a qualified ecologist(s) with support as needed from other

technical experts to inform the aquatic ecological CSM. Species listed as threatened and endangered

must be identified and their use of the habitat characterized. It also includes an initial assessment of the

feasibility and effectiveness of controlling sources in source decision units.

3.1.3 Conceptual Site Model

The CSM is a tool to organize and summarize available information about a site and determine data gaps

that need to be filled in order to determine potential for unacceptable risk. A CSM should be developed

based on existing information, including information from detailed habitat and ecological receptor

surveys, that summarizes: physical and aquatic habitat features at the site, including water uses; sources

of contaminants, historical and ongoing; transport pathways and transformation/partitioning processes;

available data on distributions of contaminants and/or toxicity; potential and currently exposed

ecological receptors; and relevant exposure scenarios, including appropriate spatial scale. Benthic

organisms are expected to be present at all sediment sites. Many sites will have some form of exposure



to fish, as well as to higher trophic levels. The degree to which ecological exposures exist is important,

and the trophic levels that are most representative of the site should be identified based on the quality,

size, and types of habitat present at the site. Representative species of various trophic levels expected to

be present at the site should be described, such as: bottom fish, pelagic fish, shorebirds, aquatic birds,

higher trophic-level piscivorous birds (e.g., heron, eagle, osprey), and aquatic mammals. Any species

expected to use the site that are listed as threatened or endangered under the Endangered Species Act

should be noted, along with the manner in which they are expected to use the site and any seasonal or

habitat limitations on that use.

Chemicals of interest (COIs) should be identified based on knowledge of historical or ongoing sources,

complete and significant transport pathways, and available data. COIs are defined as chemicals detected

at the site which have not been screened, while those that have been screened-in should be designated as

Chemicals of Potential Concern (COPCs) (also referred to as Contaminants of Potential Ecological

Concern or CPEC). Following the baseline risk assessment, chemicals that do not meet acceptable risk

levels should be designated as Chemicals of Concern (COCs). COIs are typically screened on the basis

of background concentrations, and chemical concentrations relative to screening levels to determine

whether COIs should be retained as COPCs to be carried forward in the risk assessment. COIs for

freshwater habitats are those with concentrations in sediment that are above ambient levels due to a site-

related release that also exceed either a freshwater SEF SL1 criteria (SEF 2016), or a DEQ (2007)

bioaccumulation guidance default criteria over an area of at least 0.5 acres. Similar COI identification

would be used for marine or estuarine systems, although the subgroup has not identified sediment

screening levels for marine/estuarine systems.

Bulk sediment concentrations exceeding these criteria indicate potential risk to benthos and would

trigger additional assessment to evaluate risk or consideration of a target response action protective of

all exposure pathways. They are useful for identifying the COIs that can be carried into Stage 2 of the

ERA process.

3.1.4 No Further Action

With respect to aquatic habitat, NFA is recommended if:

No aquatic habitat is identified.

No COIs are identified. The DEQ may determine sufficient data that account for

known/suspected site-related sources, identified in the CSM, which are available to evaluate for

the presence of COIs.

Human health bioaccumulation pathway is established as the risk driver, unless the

corresponding remedy would not be protective of ecological receptors. Potential risks associated

with a chemical may be greater for human health than for ecological receptors. In such cases,

addressing potential risk to human health may also account for ecological risks. PCBs are an

example of a chemical where human-health associated risks (due to fish ingestion) are typically

higher than for ecological receptors. Other bioaccumulative chemicals (e.g., DDx or TBT) might,

in some instances, have greater potential for posing risk to ecological receptors than to human

health. In these cases, if a complete and significant exposure pathway has been established to



occur, identifying the bioaccumulative chemical as a COI and proceeding to Stage 2 might be

warranted.

TRA for ecological risks is completed. The ERA process for the targeted area or specific DU is

suspended when a TRA agreement is reached, and ends (for that target area or DU) when the

TRA has been completed. Post-TRA monitoring may be required to confirm that the TRA

achieved specific performance metrics. TRAs may be selected by mutual agreement of the

authorizing parties, and would be governed by a formal agreement between DEQ and the RP.

3.2 Stage 2 Systematic Planning

The Stage 2 Systematic Planning framework is provided as part of the ERA flowchart. See Appendix A.

Elements specific to aquatic habitat include:

Habitat Decision Units

Source Decision Units

7-Step DQO Process

3.2.1 Decision Units

Define decision units (DUs) to be used for systematic planning. In general, a decision unit (DU) is the

smallest area/volume of soil or sediment for which a decision will be made. Contaminant concentrations

in all media are heterogeneous on some scale. Therefore, the determination of the sampling scale and the

related sample density is very important in all sampling situations. If a finer resolution of contaminant

variability is needed to address the objectives of the investigation, then the scale of the DU is too large.

On the other hand, excessively small DUs are impractical at some point. Determining the size, shape,

location, depth, and number of DUs is a critical component of the systematic planning process. DU

selection should be consistent with the site understanding reflected in the CSM. An individual DU

should be selected based on materials that are relatively uniform and within similar habitat types. During

the Planning Meeting, sampling design should be developed at the DU scale and targeted to the specific

(DQOs) that the DU was defined to fulfill.

Habitat decision units

Classify each DU as a “habitat decision unit” (HDU), “source decision unit” (SDU), or both. Different

types of DUs may be defined based on sampling objectives. DUs may be based on features of the site

that define habitat areas for receptors (to characterize exposure potential). DUs may also be applied to

refine understanding of the contaminant distributions, for example, in and around source areas (to

inform risk management/cleanup design decisions).

HDUs are the area/volume where receptors derive the majority of exposure at an appropriate spatial

scale for risk characterization. This DU type is central to informing ERA and should be based on the

CSM. A HDU represents the horizontal and vertical extent of the area to be sampled, should be defined

for areas with uniform or similar characteristics (substrate, water depth, proximity to shore, etc.), and



account for natural boundaries that influence receptor use. HDUs will typically account for significant

changes in associated receptor uses (e.g., semi-aquatics use of primarily nearshore areas versus channel

areas). The HDU should not be larger than the smallest exposure area associated with an assessment

endpoint (as defined in CSM). Note that the area encompassed by multiple HDUs may represent an

exposure area for larger/more mobile assessment endpoints (e.g., piscivorous bird populations); in these

cases, the individual HDUs might represent a particular piece of critical habitat or a territory for an

individual member of the population. The vertical extent of HDU will typically be the vertical extent of

contamination that substantially influences contaminant concentrations and physical characteristics of

the biologically active horizon, such as 0–10 cm bml. Note that since multiple receptors may be

considered and many have very small or large population boundaries/home ranges, it is not always

possible for HDU scale to exactly correspond to scales that reflect exposure areas for all receptors.

HDUs should not blend habitat and non-habitat areas.

Source decision units

A source decision unit (SDU) will inform a decision about cleanup, not exposure. The SDU may

represent different source areas (e.g., transformer release versus sandblast area), or it could be a high

concentration area outside of the source area. A SDU could be part of the aquatic habitat, features not

defined as aquatic habitat (e.g., drainage ditches), or upland habitat (see terrestrial ERA process). The

SDU may be smaller than or coincide with HDUs. The SDUs should consider expected contaminant

distribution (e.g., smaller for contaminants with high small-scale variability (e.g., lead shot). The vertical

extent of SDU would be informed by CSM, contaminant type, and release history. For example, if a

historical release and significant subsequent deposition has occurred, surface (e.g., 0–10 cm) and

subsurface SDUs may be appropriate. SDUs are investigated to determine whether source

removal/control is warranted.

3.2.2 Conceptual Site Model, Sampling and Analysis Plan with Data Quality Objectives

The Sampling and Analysis Plan (SAP) provides the sampling design and analysis process. The SAP

should follow DQOs, which describe: Problem Statement, Decision (Principal Study Questions,

Alternative actions), Inputs, Boundaries (spatial and temporal), Decision Rule (identify criteria), Error

Tolerance, Optimizing Sample Design. The process is further described within ERA framework. SAP

elements should include, but are not limited to, identifying the DUs, sampling media and methodology,

chemical lists and analysis procedures (e.g., reporting limits), and identify appropriate assessment tools

for evaluating risk to ecological receptors as needed and based on the CSM evaluating 1) benthic

community, 2) fish, and 3) bioaccumulation pathway:

Benthic community assessment tools

The sediment triad approach is recommended as it utilizes three lines of evidence to determine potential

for risk within HDU(s). However, not all three lines of evidence would necessarily be required to

evaluate risk. The risk assessment would include one or more of the following assessment tools:

Chemistry. The following methods are recommended to assess potential risks to benthos. Pore

water representing freely dissolved/bioavailable chemical concentrations in the HDU. Pore water



may be measured using direct (e.g., passive sampling) or indirect (centrifugation or other

extraction) methods. Pore water concentrations may also be measured/modeled (e.g., EqP,

AVS/SEM, BLM) using bulk sediment samples that represent the HDU (e.g., ISM samples). For

example, Acid Volatile Sulfide/Simultaneously Extracted Metals (AVS/SEM) and the metals

mixtures biotic ligand model should be employed to measure the bioavailable fraction of metals.

The methods and basis shall be described. See SEF (2016) for recommendations.

Toxicity testing. Field and/or laboratory-based toxicity testing that represent the HDU. The

methods and basis, including test organisms, endpoints, performance standards, response

categories, shall be described. See SEF (2016) for recommendations. Bulk chemistry results may

be used to evaluate relationships between chemical concentrations in sediment and toxicity

measures, based on bioassay tests using bulk sediment.

Community composition. Community structure indices may be compared with applicable

reference conditions (site-specific or regional indices, as available) to determine community

impacts. Structure indices may also be compared over a gradient of contamination to determine

impacts. The methods and basis shall be described.

Fish

Pore water concentrations as derived for benthic community assessment (see above) and/or surface

water concentrations that represent the HDU(s). The methods and basis shall be described.

Bioaccumulation pathway

Site-related chemicals to be evaluated for bioaccumulation pathways are PCBs, dioxins, certain

organochlorine pesticides, mercury, and selenium. Bioaccumulation potential should be evaluated

according to a data hierarchy, wherein results from preferred data supersede other data. The following

data types are preferred, in order:

Tissue. Tissue data that represent the HDU may be collected via site samples and/or in-situ or

ex-situ bioaccumulation testing. Tissue concentrations of representative receptors collected from

sites provide direct measurements of contaminant transfer to biota. Laboratory organisms

exposed to site sediments reflect expected uptake to species closely associated with

sediments/pore water (although not necessarily with the site). Site conditions (e.g., availability of

organisms known to be closely associated with sediments) will help inform selection of tissue

data collection. The methods and basis shall be described. See SEF (2016) for recommendations.

Tissue data may be compared with acceptable tissue levels (ATLs) based on applicable, best-

available science. ATLs based on species sensitivity distributions (SSDs) or similar methods

(e.g., certain DEQ provided ATLs, sediment evaluation framework TRVs) likely more

accurately reflect risk than ATLs based on ambient water quality criteria and uncertain

bioconcentration factors (i.e., WQC*BCF approach [DEQ, 2007]). Procedures should be

identified in SAP.

Pore water. Pore water concentrations as derived for benthic community assessment (see above)

to estimate tissue concentrations. Pore water data can be used to estimate tissue concentrations



(e.g., using bioconcentration factor) or could be compared with applicable water quality criteria

protective of bioaccumulative effects. Procedures should be identified in SAP.

Bulk sediment. Bulk sediment data may not accurately reflect chemical bioavailability. If

available, representative data for HDUs might be used in a preliminary assessment consistent

with modeling procedures described in DEQ (2007), but the value of these procedures is

questionable. Use of DEQ (2007) bioaccumulative screening criteria tends to screen in most

organics (e.g., PCBs) even at very low concentrations and at sites without site-related PCB

issues, further underlining the importance of CSM development (i.e., not including PCBs when

PCBs are not associated with site operations), as well as background determination. Evaluating

the various types of carbon in sediment (e.g., black carbon) may improve bioavailability

assessment.

3.3 Dissents

3.3.1 Washington State Department of Ecology

The Washington State Department of Ecology submitted the following dissent to the workgroup’s

aquatic recommendations.

DEQ’s Cleanup Program charged the workgroup with three primary goals in 2014. The second of these

was, “Consider the implications of adopting elements of the Washington Department of Ecology’s

sediment standards for use in Oregon.” The following recommendations are provided by the

Washington State Department of Ecology, who were not members of the Aquatic ERA Subgroup. The

following sections first calls out an issue, then provides Ecology’s recommendation, and concludes with

a summary of specific elements of the Sediment Management Standards (SMS) for DEQ to consider

incorporating in the aquatic ERAs and cleanup process. (See Washington State Sediment Management

Standards at https://fortress.wa.gov/ecy/publications/SummaryPages/1309055.html.)

These were selected because they benefit the cleanup program by clarifying or enhancing cleanup

decision-making. Additional discussion regarding those benefits or functions follows. Where Ecology’s

recommendations differed from the ASG recommendations, those distinctions are included as Ecology’s

comments on ASG recommendations.

Ecology has developed and fine-tuned the elements crucial to an effective and comprehensive sediment

management program, both for cleanup and dredged material management. This program has resulted in

the SMS rule, the Sediment Cleanup User’s Manual II (SCUM II), the Dredged Material Management

Program User’s Manual, and the Regional Sediment Evaluation Team’s SEF. The SMS includes a clear

framework for identifying actionable contamination, clear and achievable criteria for protection of

human and ecological receptors, access to simpler methods to assess and manage risk, and off ramps for

a simplified risk assessment process and NFA determinations. See Washington State, Sediment Cleanup

Users Manual II (SCUM II) Guidance document at

https://fortress.wa.gov/ecy/publications/SummaryPages/1209057.html.)

https://fortress.wa.gov/ecy/publications/SummaryPages/1309055.html

https://fortress.wa.gov/ecy/publications/SummaryPages/1209057.html



The SCUM II guidance outlines mechanisms for working through complex determinations such as

integrating protection of benthic, upper trophic levels, and human health in establishing cleanup levels,

and for prioritizing goals when selecting among cleanup alternatives.

As recommendations for DEQ to consider, these elements are described below with the goal of aiding

DEQ in the process of developing a sediment management program that is effective, builds on the

success achieved in Washington and is compatible with the our joint navigation dredging management

program (SEF) and with implementation of sediment cleanup in waters shared between our states.

Framework for identifying actionable contaminant levels

Issue: Setting cleanup levels for sediments is complex due to multiple receptors and pathways and risk-

based protection levels that may be below background. A way to structure priorities and decisions in

developing the site cleanup levels is needed.

Recommendation: Adopting the SMS framework would provide the DEQ sediment cleanup program

with a clear path through an otherwise complex mix of risk management decisions. The SMS framework

integrates management of ecological risk from benthic toxicity to higher trophic levels and provides the

project manager with a clear mechanism for determining site specific cleanup levels.

Summary of SMS framework: The SMS framework provides 1) bounds within which site-specific

cleanup levels are set and 2) a clear method for developing cleanup levels. It serves to establish realistic

cleanup levels, defaulting to background or practical quantitation limit (PQL) when risk-based

concentrations would fall below these, making it unlikely to achieve or maintain cleanup at those levels.

Most importantly, this framework integrates management of ecological risk from benthic toxicity and

from risk to higher trophic levels (and to human health) and provides clear criteria for cleanup decision-

making.

The SMS framework for establishing site specific cleanup levels is two tiered. The lower tier is the

Sediment Cleanup Objective (SCO, equivalent to the RSET SL1) defined as no adverse effects level.

The upper tier is the Cleanup Screening Level (CSL, equivalent to the RSET SL2) which serves as the

upper limit allowed for effects to human health and the environment at a cleanup site. Cleanup levels for

a site will be set at the SCO, with allowance for upward adjustment up to the CSL if cleanup at SCO is

not technically possible, or carrying out active cleanup at that level will result in greater harm than

benefit.

The SCO is established as highest of a) a risk-based concentration, b) natural background or c) PQL (see

Figure 1). That risk-based concentration is established as the lowest of, a) the concentration protective of

human health, b) concentration or biological effects level protective of the marine or freshwater benthos

and, c) concentration or biological effects level that results in no adverse effects to higher trophic level

species.

The CSL is similarly defined as shown in Figure 1 (below).



Figure 1. SMS Framework for establishing site specific cleanup levels (WAC 173-204 Part V and

Chapter 7, SCUM II).

Freshwater sediment standards protective of benthos

Issue: Sediment bulk chemistry is discounted in the ASG recommendations as a tool for assessing

benthic toxicity in favor of pursuing multiple, costly exposure mechanisms tied to dissolved

contaminants in porewater. The stated goal is to determine “potential risk” but the approach lacks clear

actionable levels leaving the project manager without direction on what to do with the many test results.

The SMS benthic criteria for bulk sediment represent a reliable, accurate method for assessing benthic

toxicity and are also used in by RSET to manage navigation dredging in Oregon waters.

Recommendation: Adoption of the SMS chemical standards for freshwater sediment provides an

accurate, effective and cost-efficient tool for managing risks from sediment toxicity to benthos. Use of

the SMS chemical and biological standards in DEQ’s sediment cleanup program satisfies the goal of

compatibility with DEQ’s interstate dredging program (SEF) as well as compatibility in managing

sediment cleanup in waters shared between Oregon and Washington.

Summary of SMS benthic standards: The SMS chemical and biological benthic standards for freshwater

sediments represent a critical element of a comprehensive sediment risk assessment and management

program. These provide a risk assessment tool that is important for defining sediment cleanup

units/sediment management areas, and selecting among remedial action alternatives. The SMS chemical

standards accurately predict benthic toxicity and the suite of bioassays from which they are derived

represent the best available science using bioassays for assessing benthic toxicity.



The bedded sediment tests used in developing the benthic chemical standards address exposure through

all pathways (e.g., via respiration or contact with dissolved contaminants in porewater, direct contact

with sediments and sediment ingestion) resulting in chemical standards and interpretive criteria with a

proven, clear and achievable mechanism for project managers to assess benthic toxicity. The sediment

chemical criteria were developed to optimize accurate prediction of the presence or absence of toxicity

and met the rigorous development goal, correctly predicting presence or absence of toxicity eighty

percent of the time. This ensured that the criteria did not result in missing toxicity or in falsely

designating hits where sediments were not toxic to benthos. The biological standards target the

minimum level of effects that can be detected in the bioassays.

Another basis for adopting these chemical benthic standards is for consistency with navigation and

sediment cleanup programs in waters shared with Oregon. State and federal sediment experts from

Oregon, Washington and Idaho have spent a tremendous effort over the last 2 decades to develop a

program to manage sediments in shared waters. RSET has worked along with Ecology to establish

freshwater sediment bioassays and chemical criteria based on regional data for adoption into the SMS.

When Ecology adopted the biological and chemical standards for freshwater, RSET embraced their use

for evaluating and managing dredging activities in the northwest. This ensures that sediment cleanup

and navigation dredging programs work in accord with each other. Use of these chemical and biological

standards in Oregon’s sediment cleanup program would satisfy the goal of compatibility with DEQ’s

interstate navigation dredging program as well as managing sediment cleanup in waters shared between

Oregon and Washington.

Ecology comments on ASG recommendations for benthic toxicity: ASG recommendations focus only

on pathways looking at porewater representing freely dissolved contaminants and use of theoretical

approaches like EqP, AVS/SEM, BLM to measure the “bioavailable fraction” to assess potential risk to

benthos. While a great deal of research along these lines has been done to attempt to explain or

understand bioavailability, this work falls short of establishing effects levels that a project manager

could use in discerning when remediation is warranted. The ASG porewater focus would trigger a costly

myriad of tests to map pathways of exposure and identify “potential risk” from metals, polar and non-

polar organics, without a clear indication of what to do with the results. Also, looking only at pore water

disregards exposure from direct contact and sediment ingestion. This ignores the success RSET and

Ecology have achieved in developing the simpler and less costly bulk sediment chemistry criteria which

accurately predicts the presence or absence of toxicity to benthos and provide a clear determination

where remediation is warranted.

Bioaccumulative standards protective of upper trophic level species

Issue: The protection of ecological receptors from bioaccumulative chemicals is very site specific based

on COCs, pathways and receptors. Practical guidance is critical to allow a project manager to navigate

the complex issues of ERA.

Recommendation: Use Ecology’s SMS and SCUM II guidance when updating DEQ risk assessment

policies and guidance. These provide substantive guidance and helpful information for determining

when a risk assessment is appropriate, what COCs are of greatest concern, what species to consider and

what other pertinent data to gather.



Summary of SMS standards for protecting upper trophic level species: The SMS implementation

guidance for examining bioaccumulative risk to higher trophic levels starts with a 3-part screening, 1)

screen out COCs where human health will be the driver, 2) screen out and default to background for

chemicals where risk-based levels for tissue or sediments fall below background and, 3) identify

resources of special concern that warrant specialized field investigations, modeling or literature-based

assessments (Chapter 9, SCUM II). The guidance notes that only a handful of bioaccumulative

chemicals are likely to pose greater risk to ecological receptors than humans. These are Lead, Mercury,

Selenium, Tributyltin, Pentachlorophenol, Pyrene and Phenanthrene. Risk-based levels to protect HH for

other bioaccumulatives are typically lower than for ecological receptors. Also, in most cases, risk-based

dioxin/furan levels protective of higher trophic levels are likely to fall below background concentrations.

The SMS also provides direction on temporal, biological or population-level considerations for

assessing risk to higher trophic levels. (e.g., include species that are currently or historically present, or

potentially inhabit the area; consider effects to reproduction, growth or survival; take into account life

history, feeding, reproductive strategy, population numbers, home range, potential for recruitment or

immigration etc.) (WAC 173-204-564 and SCUM II Chapter 9).

Selection of remedy

Issue: Remedy selection brings together a wide array of differing requirements, priorities and

considerations into a process for choosing among cleanup actions for a site. A project manager is often

stymied in wrestling through and ordering these competing priorities if there is no guidance or direction

for a clear path forward.

Recommendation: The SMS remedy selection process provides a well-defined path, defining goals and

ordering priorities important to achieving a successful cleanup. The full process or elements can be

adopted or built into DEQ’s sediment cleanup program. The SMS remedy selection process is tailored to

the specific challenges of performing sediment cleanup in the aquatic environment. It is built on decades

of experience conducting large and small sediment cleanups and reflects the most recent and ongoing

updates through the implementation guidance in SCUM II.

Summary of SMS remedy selection: Cleanups will occur more quickly if the project manager has clear

direction on how to prioritize the different objectives, and requirements when selecting among the

alternatives for conducting a cleanup. The SMS remedy selection process is especially helpful in

working through these, sometimes competing, priorities and getting on to the actual cleanup itself. Basic

requirements or components of the remedy selection are summarized below and can be found in the

SMS (WAC 173-204-570) and in the guidance (Chapter 12, SCUM II);

Threshold criteria (similar to CERCLA or MTCA requirements)

o Protective of HH and environment

o Permanent to maximum extent practical

o Provide for reasonable timeframe (Mechanism exists for managing limited recovery

period of 10 years)

o If source control is part of remedy, prioritize prevention of sediment recontamination

o Preference for active (short term) remedies over passive (long term)



o Provide public review and comment

o Provide monitoring for effectiveness of remedy

o Comply with all applicable laws

Use of permanent solutions to the maximum extent practicable takes into account a

disproportionate cost analysis, evaluating and comparing each cleanup action alternative subject

to the following components in descending order;

o Source controls in combination with other cleanup technologies

o Beneficial reuse of sediments

o Treatment to immobilize, destroy, or detoxify contaminants

o Dredging and disposal in upland engineered facilities

o Dredging and disposal in a nearshore, in-water, confined aquatic disposal facility

o Containment of contaminated sediment in-place with an engineered cap

o Dredging and disposal at an open water disposal site

o Enhanced natural recovery

o Monitored natural recovery

o Institutional controls

Reasonable time frame: Bioaccumulatives drive cleanup levels really low, even when defaulting

to background or PQL. To address this, remedial alternatives including the process of natural

recovery are considered subject to the following requirements;

o A reasonable restoration time frame is achieved if cleanup standards are met within 10

years of completing active remedial measures

o Active cleanup is conducted to the maximum extent practicable, and;

Active cleanup for the entire site would likely result in a deficit of environmental

benefits

3.3.2 U.S. Environmental Protection Agency, Region 10

Joe Goulet, representing the U.S. Environmental Protection Agency Region 10, submitted a dissent to

the workgroup’s aquatic recommendations with respect to whether berths maintained through dredging

should be evaluated as part of aquatic ERAs. The recommended aquatic Stage 1 Scoping framework

states that frequently maintained dredging channels or berths where contaminants are evaluated and

managed through a dredging framework may be excluded as habitat.

EPA states that berths and channels should be considered habitat and assessed as such with the

understanding that the habitat may be disturbed at a certain frequency; however, dredged areas will

recolonize and provide habitat that may be impacted by contamination. Additionally, the RSET and the

Portland Sediment Evaluation Team consider it habitat as part of their CSM for evaluating dredge

materials (as described in the SEF).



4. References Allard P, Fairbrother A, Hope BK, Hull RN, Johnson MS, Kapustka LA, Mann G, McDonald B, Sample

B.E. 2009. Recommendations for the development and application of wildlife toxicity reference

values. Integr Environ Assess Manage 6(1):28-37.

Calder, W. H., III. 1984. Size, function, and life history. Harvard University Press, Cambridge,

Massachusetts

CH2M HILL, USR Corp. 2001. Coeur d'Alene Basin Remedial Investigation/Feasibility Study/

Feasibility Study. Ecological Risk Assessment - Final. Volume 1, 1 (Parts 1 and 7), 2, 5, 6, 7, 10.

For U.S. Environmental Protection Agency, Region 10, Seattle, WA.

Clapp, J.G., and J.L. Beck. 2015. Evaluating distributional shifts in home range estimates. Ecology and

Evolution 5:3,869-3,878.

Deming, W.E. 1950. Some theory of sampling. Dover publications, New York. 640 pp.

Franklin, I.R. 1980. Evolutionary change in small populations. In Conservation Biology: an

Evolutionary–Ecological Perspective (Soule´, M.E. and Wilcox, B.A., eds), pp. 135–150.

Hajduk, L.I. 2008. Space use and habitat selection of long-tailed weasels (Mustela frenata) in southern

Illinois. M.S. Thesis, Southern Illinois University at Carbondale. 50 pp.

Harestad, A. S., and F. L. Bunnell. 1979. Home range and body weight—a reevaluation. Ecology

60:389–402.

Hawes, M. L. 1977. Home range, territoriality, and ecological separation in sympatric shrews, Sorex

vagrans and Sorex obscurus. Journal of Mammalogy 58:354-367.

Hope, B.K., and J.A. Peterson. 2000. A procedure for performing population-level ecological risk

assessments. Environmental Management 25:281-289.

Interstate Technology & Regulatory Council. 2012. Incremental sampling methodology. Interstate

Technology & Regulatory Council, Incremental Sampling Methodology Team.

http://www.itrcweb.org/ism-1/.

Jamieson, I.G. and Allendorf, F.W. 2012. How does the 50/500 rule apply to MVPs? Trends Ecol. Evol.

27, 578–584.

Mayfield DB, Johnson MS, Burris JA, Fairbrother A. 2013. Furthering the derivation of predictive

wildlife toxicity reference values for use in soil cleanup decisions. Integr Environ Assess Manag

10(3):358-371.

Meyer, R. L., and T.G. Balgooyen. 1987. A study and implications of habitat separation by sex of

wintering American kestrels (Falco sparverius L.). Raptor Research 6:107-123.

Oregon Department of Environmental Quality. 1998 (updated 2001). Guidance for ecological risk

assessment: Levels I, II, III, IV. Oregon Department of Environmental Quality, Portland,

Oregon.

http://www.itrcweb.org/ism-1/



Oregon Department of Environmental Quality. 2000. Guidance for ecological risk assessment—Level

III baseline. Oregon Department of Environmental Quality. March.

Pauli BD, Perrault JA, Money SL. 2000. RATL: a database of reptile and amphibian toxicology

literature. National Wildlife Research Center, Canadian Wildlife Service, Hull, Quebec, Canada.

Peters, R. H. 1983. The ecological implications of body size. Cambridge University Press, Cambridge.

Petersen, L. 1979. Ecology of great horned owls and red-tailed hawks in southeastern Wisconsin.

Wisconsin Department Natural Resources Technical Bulletin Number 111. Madison, Wisconsin.

64 pp.

Ryti, R. T., J. Markwiese, R. Mirenda, and L. Soholt. 2004. Preliminary remediation goals for terrestrial

wildlife. Human and Ecological Risk Assessment 10:437-450.

Sample B.E., Opresko DM, Suter GW. 1996. Toxicological benchmarks for wildlife. 1996 revision.

ES/ERM-86/R3. Office of Environmental Management, US Department of Energy, Washington,

DC.

Sample, B. E., C. Schlekat, D. J. Spurgeon, C. Menzie, J. Rauscher, and B. Adams. 2013.

Recommendations to improve wildlife exposure estimation for development of soil screening

and cleanup values. Integrated Environmental Assessment and Management 10:372-387.

Samuel, M. D., D. J. Pierce, and E. O. Garton. 1985. Identifying areas of concentrated use within the

home range. Journal of Animal Ecology 54:711-719.

Santini, L., M. Di Marco, P. Visconti, D. Baisero, L. Boitani, and C. Rondinini. 2013. Ecological

correlates of dispersal distance in terrestrial mammals. Hystrix, the Italian Journal of

Mammalogy. 24:181-186.

Schoener, T. W. 1968. Sizes of feeding territories among birds. Ecology 49:123–140.

Shaffer, M.L. 1981. Minimum population sizes for species conservation. BioScience 31, 131–134.

Sparling DW, Linder G, Bishop CA, eds. 2000. Ecotoxicology of amphibians and reptiles. SETAC

Technical Publications Series, Ingersoll CG, ed. Society of Environmental Toxicology and

Chemistry (SETAC) Press, Pensacola, FL.

U.S. Environmental Protection Agency. 1991. Guidance for data usability in risk assessment (Part A).

Final Report EPA/540/R-92/003. Office of Research and Development, Washington, D.C.

U.S. Environmental Protection Agency. 1992a. Supplemental guidance to RAGS: Calculating the

concentration term. Final Report 9285.7-08I. Intermittent Bulletin Volume 1 Number 1. Office

of Solid Waste and Remedial Response, Washington, D.C.

U.S. Environmental Protection Agency. 1992b. Preparation of soil sampling protocols: sampling

techniques and strategies. Final Report EPA/600/R-92/128. Office of Research and

Development, Washington, D.C.

U.S. Environmental Protection Agency. 2000a. Guidance for the data quality objectives process. EPA

QA/G4. Final report EPA/600/R-96/055. Office of Environmental Information, Washington, DC.



U.S. Environmental Protection Agency. 2000b. Data quality objectives process for hazardous waste site

investigations. EPA QA/G-4HW. Final report EPA/600/R-00/007. Office of Environmental

Information, Washington, DC.

U.S. Environmental Protection Agency. 2000c. Guidance for data quality assessment: Practical methods

for data analysis. EPA QA/G-9, QA00 Update. Final Report EPA/600/R-96/084. Report

EPA/600/R-96/084.

U.S. Environmental Protection Agency. 2002. Guidance on choosing a sampling design for

environmental data collection for use in developing a quality assurance project plan. EPA QA/G-

5S. Final report EPA/240/R-02/005. Office of Environmental Information. Washington, DC. 166

pp.

U.S. Environmental Protection Agency. 2003. Generic ecological assessment endpoints (GEAEs) for

ecological risk assessment. Risk Assessment Forum, U.S. Environmental Protection Agency.

EPA/630/P-02/004F, October.

U.S. Environmental Protection Agency. 2005. Guidance for developing ecological soil screening levels

(Eco-SSLs). OSWER Directive 92857-55. Issued November 2003; revised October 2005

[online]. US Environmental Protection Agency, Washington, DC. Available from:

http://rais.ornl.gov/documents/ecossl.pdf.

U.S. Environmental Protection Agency. 2006. Guidance on systematic planning using the data quality

objectives process. EPA QA/G-4. Final report EPA/240/B-06/001. Office of Environmental

Information, Washington, DC. 111 pp.

U.S. Environmental Protection Agency. 2012. Benchmark dose technical guidance. EPA/100/R-12/001.

US Environmental Protection Agency, Washingon, DC.

Waser, P. M. 1987. A model predicting dispersal distance distributions. Pages 251–256 in B. D.

Chepko-Sade and Z. T. Halpin (eds.), Mammalian dispersal patterns. University of Chicago

Press, Chicago.

WashingtonState Department of Ecology. 2012c. Terrestrial Ecological Evaluations under the Model

Toxics Control Act. Draft. Internal Review. No Publication No.

Windward. 2013. Portland Harbor RI/FS, Final Remedial Investigation Report, Appendix G: Baseline

ecological risk assessment. Final. Prepared for the Lower Willamette Group. Windward

Environmental LLC, Seattle, WA.

Young, H. 1951. Territorial behavior in the eastern robin. Proceedings of the Linnaean Society of New

York. Number 58-62:1-37.



Appendix A: Stage 1 (Scoping), Stage 2

(Systematic Planning/Screening), and

Stage 3 (Risk Assessment) Process

Charts



STAGE 1 (SCOPING) FOOTNOTES

1 The Geographic Scope of Study Area includes the entire area initially determined by the project manager where contaminants released could become located over time, and incorporates the initial boundary for a defining a local population of potentially exposed receptors. The first approach is to review landscape conditions surrounding the suspected contaminated areas for topographic or anthropogenic features likely to represent dispersal barriers (e.g., cliff faces/escarpments, streams and rivers, highways) for small mammal receptors in case the evaluation moves forward into the Stage 2 process. The geographic scope should distinguish between areas that are on- or off-property (Note: the on-property area is the recorded legal description of the property where the release has occurred, although the on-property area could include multiple properties where the release occurred).

2 The Stage 1 Terrestrial and Aquatic Habitat Assessment within the Geographic Scope of Study Area is based on qualitative information. Acceptable habitat provides distinct food and cover benefits for ecological receptors and excludes anthropogenic “habitat” features that may have a small ecological function but are not necessary for receptor survival, such as row crop monoculture, landscaping, lawns, storage ponds, bioswales, berths maintained by dredging, etc. The initial qualitative habitat and receptor survey can be based on a desktop mapping exercise or a site visit made by the project manager or designee, but does not need to be as rigorous as the current Stage 1 Ecological Scoping Checklist at this stage. The survey includes an assessment to identify if threatened or endangered species or designated critical habitat may be present. A qualified biologist or ecologist should conduct the initial survey if threatened or endangered species are suspected to be present. Information on threatened or endangered species and critical habitat can be found at the following agency websites:• U.S. Fish and Wildlife Service

(http://www.fws.gov/oregonfwo/articles.cfm?id=149489416) • National Marine Fisheries Service

(http://www.westcoast.fisheries.noaa.gov/habitat/complying_with_the_esa.html)• Oregon Department of Fish and Wildlife

(http://www.dfw.state.or.us/wildlife/diversity/species/threatened_endangered_species.asp).

3 The Land Use Evaluation is primarily conducted to identify areas zoned for future development, such as Brownfields sites or exclusive current or future commercial, residential, or industrial use where it is likely that habitat will be removed within a reasonable timeframe and can be excluded from further analysis. Because these zoned areas may take years to develop and will provide habitat during the interim, habitat should not be excluded unless the zoning designation is current and there is a reasonable likelihood of development. The redevelopment exclusion is not considered for areas with a green overlay (an area within a property that is set aside for environmental protection). Habitat cannot be excluded from analysis if threatened or endangered species are present, or if the habitat has been designated as critical habitat for threatened and endangered species.

4 Contiguous habitat is physically adjacent or non-adjacent but directly connected by hydraulic releases or air emissions (including ground water, drainage or piping, construction activities or roadways, or other site specific release mechanisms). The Geographic Scope could encompass multiple contiguous habitat areas. The ½ acre habitat exclusion cannot be applied if threatened or endangered species are present, or if the habitat has been designated as critical habitat for threatened and endangered species.

5 Habitat and Eco-receptor Surveys- This step includes thorough quantitative aquatic and/or terrestrial habitat and eco-receptor surveys conducted by a qualified ecologist(s) with support as needed from other technical disciplines. This stage also requires a more thorough review or survey for species listed as threatened and endangered (including listed plants). Aquatic habitat will also be further delineated and may require additional evaluation (e.g., source control evaluation).

6 The Targeted Response Action (TRA) is comparable to a technical/management decision point in the current guidance, where the Cleanup Program Manager may allow the responsible party (RP) to undertake a targeted source control, removal action, or monitored natural recovery (MNR) in lieu of conducting further ERA, with the result of completing the TRA being a no-further-action (NFA) decision for ecological risks. MNR may occur with or without compensatory habitat improvements, to offset potential risk while MNR occurs. The TRA could be a technology-based solution rather than a risk-based solution. It would be governed by a formal agreement between DEQ and the RP.

go to Stage 2(Systematic

Planning/Screening)

Stage 1 (Scoping)

Targeted response

action (TRA)6? Yes

No

Conduct site visit:

Define the initial Geographic Scope of Study Area1

Identify Habitat Areas (Terrestrial and Aquatic Habitat Assessment2)Conduct Land Use Evaluation3 to identify current / future zoning

Identify potential Decision Units (see Stage 2) if coordinating with RI at this stage

Define Geographic Scope of Study Area1 & conduct initial Habitat

Assessment2 (On- and Off-property)

No

Conduct quantitative Habitat and Eco-receptor Surveys5?; (Complete Eco CSM)

Off-Property Assessment On-Property Assessment

Conduct Land Use Evaluation3 Is

habitat excluded?

> 1 complete pathway for contaminants to be transferred from

on-property to contiguous4 off-

property habitat?

Exclude on-property upland

acreage from EcoCSM

(off-property assessment still

required)

Yes

Is habitat on property (not

excluded by zoning) plus contiguous4

terrestrial habitat >1/2 acre, or consist of aquatic habitat of any

size?

NFA (Ecological)

Yes

NFA (Ecological)

Design TRA

Implement TRA?

No

Yes

Yes No

No

Appendix A: Stage 1 (Scoping), Stage 2 (Systematic Planning/Screening), and Stage 3 (Risk

Assessment)



This page intentionally left blank.



Stage 2(Systematic

Planning/Screening) a

Is the DU used by small home range (SHR) T&E species?

yes no

NOTES REGARDING TRANSITIONING FROM STAGE 2 (SYSTEMATIC PLANNING/SCREENING) TO STAGE 3 (RISK ASSESSMENT)

Ecological effect levels and ecological exposure levels are used for both Stage 2 (systematic planning/screening) and Stage 3 (risk assessment). At Stage 2, the ecological effect levels are termed ecological screening levels (ESLs) and the ecological exposure levels are termed exposure point concentrations (EPCs). Stage 2 ESLs should change over time as new ecotoxicological data of suitable quality become available. ESLs are appropriate for Stage 2 (systematic planning/screening) purposes only. They generally will not be appropriate for Stage 3 (risk assessment) because they do not correspond to site-specific, population-level assessment endpoints. The fundamental approach (comparing ecological effect concentrations to exposure levels) should not change between Stage 2 and Stage 3.

ESLs are conservative screening-level values that support decisions about whether to conduct a risk assessment or instead conduct a targeted response action. The quotient EPC/ESL, also known as a “hazard quotient” (HQ), can help DEQ and PRP risk managers roughly estimate the costs and benefits of these two conducting a risk assessment, versus conducting a targeted response action. Successful Stage 2 (systematic planning/screening) has to accomplish two goals:

1. Provide sufficient information to inform good decisions about whether to conduct a risk assessment, or a targeted response action2. Provide a detailed plan for the targeted response action if that option is pursued

Define decision units (DUs) b

from DQO process

Use lookup table to determine Stage 2

exposure estimation data needs d

Identify Contaminants of Interest (COIs) based on

terrestrial ecological Conceptual Site Model (CSM)c

Classify each DU as “habitat unit” (HDU), “source unit”

(SDU) or both

SDU?

For each DU

yes

HDU?

no SDU?

Identify source media(soil, sediment, ground water, surface water)

yes

Terrestrial or aquatic habitat?

STAGE 2 (SYSTEMATIC PLANNING/SCREENING) FOOTNOTES

a When Stage 1 results indicate additional contaminant data are needed, the Stage 2 Systematic Planning/Screening stage begins. Systematic Planning/Screening, described on the following pages and in guidance, starts with a planning meeting to establish the type, quantity, and quality of data to manage uncertainty and make defensible decisions.

b A decision unit (DU) is the defined volume (area and depth) of the sample media (such as soil) where a contaminant can be sampled and represented by a mean and compared to an action or screening level to make management decisions. Decision units should consist of relatively uniform materials and not contain material from different habitat types (e.g., grassland and forestland) or blend habitat and non-habitat areas. Habitat DUs (HDUs) are designated for risk assessment and are based on the range of ecological receptor. The mean representing the HDU (when sampled appropriately) is the exposure point concentration (EPC). The minimum allowable size for an HDU is 0.5 acres. Source DUs (SDUs) can be any size and are designated to specifically characterize a contaminant source that can be targeted for remedial action (a “remedy” DU), or for characterizing nature and extent of contamination (a N&E DU). Typically the objectives for a specific DU should not be mixed, but one or more SDUs can be identified within a HDU. The mean representing the SDU can be compared to an action level for decision making, but it does not represent an EPC (which is only represented by a HDU).

c Contaminants of Interest (COIs) are those chemicals elevated above natural (ambient) background levels due to a site release, and are based on existing data from the site and the conceptual site model (CSM).

d The revised ERA guidance document will contain a lookup table that provides risk-based screening values for comparison to EPCs.

e For sampling soil, various methods including probabilistic and incremental sampling methodology (ISM) will be specified. It is preferred that the calculation of EPCs be based on probabilistic methods (see brief description in the following pages). Any sampling design must be robust enough to quantitatively demonstrate that an EPC represents the HDU, and typically probabilistic sampling methods will be required to meet the criteria for representativeness. ISM is most often the preferred and cost effective approach. Prey item (tissue) sampling may be incorporated at Stage 2 stage, on a site-specific basis.

f EPC calculation procedures (individual DU and site-wide) will be specified in the revised ERA guidance document.

g Ecological Screening Levels (ESLs) for terrestrial HDUs will be based on the more sensitive of small mammal (typically shrew) and small bird (typically robin) invertivores (and may vary by COI). ESLs for aquatic TRVs will be chronic ambient water quality criteria for the protection of aquatic life, or the closest available equivalent for COIs that don’t have chronic ambient water quality criteria for the protection of aquatic life. EBVs should be developed to gradually replace ESLs. When an EBV is used, then additional evaluations must be conducted to show how the analysis meets the acceptable level of risk for populations of ecological receptors as defined in rule.

h TRA is comparable to a technical/management decision point in the current guidance, where the Cleanup Program Manager may allow the responsible party (RP) to undertake a targeted source control, removal action, or monitored natural recovery (MNR) in lieu of conducting further ERA, with the result of completing the TRA being a no-further-action (NFA) decision for ecological risks. MNR may occur with or without compensatory habitat improvements, to offset potential risk while MNR occurs. The TRA could be a technology-based solution rather than a risk-based solution. The ERA process for the targeted area or specific DU is suspended when a TRA agreement is reached, and ends (for that target area or DU) when the TRA has been completed. Post-TRA monitoring may be required to confirm that the TRA achieved specific performance metrics. TRAs may be selected by mutual agreement of the authorizing parties, and would be governed by a formal agreement between DEQ and the RP.

Use T&E SHR ESLs g Use standard SHR ESLs g

Data needs met?

yes

Produce sampling & analysis plan (SAP) following 7-step Data Quality

Objective (DQO) process for Stage 2e

Collect and analyze data

Calculate HDU Exposure Point Concentrations (EPCs) f

Calculate HQs Calculate HQs

Combined area of HDUs > area threshold for calculating

predator EPCs?

yes

HQs > 1?

Round HQs to the nearest integer

NFA (Ecological)yes

no

Design and Implement Targeted

response action (TRA)? h

go to Stage 3(Risk Assessment)

Determine whether source

removal/control is

warranted

no

no

Site-wide

Is the DU used by predator T&E

species?

no

Use T&E predator ESLs

Calculate site-wide

EPCs d

yes

Site-wide EPCs not needed

Use standard predator ESLs

Calculate HQs Calculate HQs

no

Terrestrial Aquatic

Proceed to

Aquatic Habitat -Stage 2 Process no

yes



Stage 3(Risk Assessment)

Summarize Available Information for CPECs Exposure Profiles and

Potential Effectsa

STAGE 3 (RISK ASSESSMENT) FOOTNOTESa First step in Stage 3 (Risk Assessment) involves the

following activities for the HDUs, CPECs, and complete exposure pathways retained from Stage 2 process:• Refine CPECs’ chemical fate and transport

information.• Identify assessment endpoints for receptor groups. • Summarize CPECs’ ecological effects information.

b Net-Environmental Benefits Analysis (NEBA) Planning Phase involves the following activities for HDUs retained for further ecological risk evaluation from the Stage 2 process:• Define ecological functions.• Define services and other ecological properties• Define comparative metrics (e.g., habitat

equivalency). • Identify potential reference state(s).

c Scoping considerations:• Measurement endpoints are site-specific and reflect

the ecological functions provided by HDUs identified during Stage 2 process.

• “Measurement endpoints used to characterize the existing ecological conditions for selected ecosystem services can also be used to evaluate restoration success.” (Kapustka et al. 2016).

• Stage 3 may include a multi-pathway exposure assessment.

d Identify Preliminary Remedial Alternative Actions, including following tasks:• Define preliminary remedial action objectives (RAOs)

based on risk questions.• Identify preliminary remedial alternative actions to

achieve preliminary RAOs.• Identify potential ecological hazards for each

preliminary remedial alternative action (e.g., physical destruction of habitat).

e Stage 3 Study Design will follow DQO process and involve the following activities:• Define risk assessment testing and sampling

requirements (e.g., toxicity testing, bioaccumulation testing, tissue data, geochemical data, field studies)

• Define sampling requirements to supplement evaluation of remedial alternatives (e.g., geochemical data)

• Characterize reference state(s) for NEBAf The fundamental approach (comparing ecological effect

levels to exposure levels) should not change between Stage 2 and Stage 3. Stage 3 ecological effect concentrations (EECs) will generally be different than ESLs because the risk assessment should by design provide additional information about population-level effects, resulting in EECs that differ from ESLs.

g Risk Management Summary will include the following components: • Residual risk reduction evaluation for each remedial

action alternative• Comparison of ecological impacts of management

alternatives (See Note 2). For example:• Lost ecological services• Recovery time

• Engineering evaluation of costs (e.g., disproportionate cost analysis)

Complete NEBA Planning Phaseb

Identify Preliminary Remedial Alternatives Actionsd

Complete Stage 3 Study Design Plan for Data Collectione

Refine Ecological CSM

Risk Assessment and NEBA Scoping: Identify Measurement Endpoints, Exposure Assumptions, Toxicity Reference Values

(TRVs), Risk Questions, and Management Goalsc

no

NOTES REGARDING STAGE 3 (RISK ASSESSMENT)

1. EPCs also could change at Stage 3 (risk assessment), from those calculated for Stage 2 (systematic planning/screening). If the decision is to proceed to Stage 3 (risk assessment), then a planning step in the risk assessment will be to produce a detailed plan (again following the 7-step DQO process) to collect additional site-specific data of suitable quality for better estimating exposure levels. These new data should allow risk assessors to replace Stage 2 assessment approaches (simple heuristics) with site-specific risk methods and values. The new data could include better measurements of exposure concentrations, better information about the behaviors of ecological receptors (e.g., habitat use), better information about chemical bioaccumulation in the food chain, and better information about population dynamics. This list is not necessarily inclusive of all the improvements that are possible between Stage 2 and Stage 3.

2. “A NEBA for chemically contaminated sites typically involves the comparison of the following management alternatives: (1) leaving contamination in place; (2) removing the contaminants through traditional remediation; (3) improving ecological value through onsite or offsite restoration that does not involve removing contaminants; or (4) a combination of those alternatives.” Source: Efroymson et al. 2003.

Complete Stage 3 Data Collection Activities

Calculate EELs and Complete Risk Characterizationf

Unacceptable Risk?Complete Risk Management

Summaryg

Remedial Action Alternative(s) Achieve Net

Ecological Benefit?

yes

Implement Remedial Action(s) NFA (Ecological)

yes

no

Implement MNR with or without compensatory habitat

improvements to offset potential unacceptable risk

while MNR occurs



STAGE 1: SCOPINGTasks:• Identify the initial site boundaries and areas to be investigated• Collect site history and process knowledge• Initiate habitat quality assessment to document the presence, extent, and quality of habitat on site

and adjacent property (and degree of habitat manipulation)• Initiate the Conceptual Site Model (CSM) which identifies generic pathways, aquatic/terrestrial land

use of site and surrounding area, preliminary identification of ecological receptors• Identify zoning on or nearby site and future use• Can be a desktop assessment if data are available using default screening values• Identify Contaminants of Interest (COIs) Product:• Scoping document: describes tasks conducted and conclusions, initial conceptual site model, COIs,

preliminary problem statement (and the info needed to complete problem statement), and identifies stakeholders

STAGE 2: SYSTEMATIC PLANNING/SCREENINGTasks:• Identify Planning Team, which includes parties responsible for risk assessment who have knowledge

about the site background and investigation goals, and may include individuals with expertise in fields such as chemistry, toxicology, geology, aquatic and terrestrial ecology, engineering, risk assessment, modeling, field sampling, and statistics.

• Conduct Planning Meeting with the Planning Team. The planning meeting identifies the primary study question, provides a framework for the data quality objectives (DQOs), resolves issues such as identifying the population of interest and potentially important uncertainties, defines spatial scale of interest, incorporates NRC–risk based decision making framework, and establishes the decision-making process and level of certainty needed to make decisions. The number of representatives and diversity of professions participating in the planning meeting will depend on size and complexity of the site.

• Complete the 7-step DQO process describing: Problem Statement, Decision (Principal Study Questions, Alternative actions), Inputs, Boundaries (spatial and temporal), Decision Rule (identify criteria), Error Tolerance, Optimizing Sample Design

• Revise CSM and COIs if needed • Produce Sampling Analysis Plan (SAP) which includes the DQOs, spatial boundaries, and decision units

as defined in the Planning Meeting• Sample and analyze data• Conduct data quality assessment and determine if data are acceptable • Make risk determination• Identify Contaminants of Potential Ecological Concern (CPECs)• Products:• CSM, DQO Plan, SAP, DQA, Risk Determination, CPECs

STAGE 3: RISK ASSESSMENTTasks:• Net environmental benefits identification • Incorporate and evaluate risk management options• Assessment of likely remedy• Field Studies/ site specific development of risk parameters

Product:Risk Management Summary



7 Step Data Quality Objective Process

1. Initiate Problem Statement:

Problem Statement Format (constrain within the CSM)

In order to [achieve/support/understand/confirm/prevent] (some issue or one of the objectives of the study) data regarding [pollutant/contaminant/physical-chemical-biological parameter (in/on/above/below) the medium are needed.

Example: In order to show that lead is contributing to the decrease in small mammal or avian populations in the upland habitat (or to individuals if listed species present), concentrations of lead in the soil, vegetation, and surface water are needed.

Develop principal study questions (PSGs) and alternative actions (AAs):

PSQs-identify key unknown conditions or unresolved issues that reveal solution to the Problem Statement.

Example: PSQ1: Does the concentration of lead in soil on the site exceed the screening level for shrews [or robins]?PSQ2: Does the concentration of lead in vegetation on the site exceed the screening level for shrews [or robins]?PSQ3: Does the concentration of lead in surface water on the site exceed the screening level for shrews [or robins]?

Develop AAs:PSQ1:AA1: if PSQ1=yes, then conduct Stage III assessment or targeted action on site or decision unitAA2: if PSQ1=no, then no further action

PSQ2:AA1: if PSQ2=yes, then conduct Stage III assessment or targeted action on site or decision unitAA2: if PSQ2=no, then no further action

PSQ2:AA1: if PSQ3=yes, then conduct Stage III assessment or targeted action on stormwater channels AA2: if PSQ3=no, then no further action

Document consequences of making a wrong decision for each AA and rate the severity of the decision as low, moderate, or severe.

PSQ, AA1: =incorrect yes decision, Stage III assessment made or targeted remediation on a site that is clean. Consequences: potential financial impacts, schedule issues. Severity = moderatePSQ,AA2: = incorrect no decision, Stage III assessment or targeted remediation not conducted on dirty site. Consequences: potential risk remains to the environment. Severity = moderate-severe.



This page intentionally left blank



2. Develop Decision Statement:Format: Determine whether [PSQ1] requires [AA1] or [AA2].

Example: Determine whether the lead concentrations in soil on site (or within decision unit) contributes to a decrease in small mammal/avian populations and requires Stage III assessment or targeted remediation; if not, no further action needed.

3. Identify Inputs:Identify information inputs that will be required to resolve the decision statements, and determine which require environmental measurements.

• Specify measurements and media (& identify what’s not required) and sources of info or parameters needed of modeling

• Evaluate usability of existing data• Do the data fall within the range expected based on the CSM?• Determine sample sizes, action levels (and basis for levels), detection limits required, and

control criteria; precision required (RSD) and accuracy required (percent recovery)

4. Specify Boundaries

Define spatial and temporal boundaries that data must represent to support decision statement.This is where professional judgment is used so that judgmental sampling is not.

Define population of interest (total universe of objects from which an estimate will be made within a spatial unit), such as:

• the top two inches of soil within the site perimeter• the universe of sediment samples (1kg) from the top 6 inches of lake bottom• all the soil particles less than 2 mm diameter• the oily black or sheened-area over there• this pile of waste

Define spatial boundaries of the decision statement and temporal boundary of the problem to ensure that data are representative of the population and where it resides (i.e., the geographical area or volume to which the decision statement applies), which can include:

• area (surface soil to a depth of 5 inches in the waste pit)• volume (soil to a depth of 20 feet within the area of the waste pit)• length (the pipeline)• or identifiable boundary (natural habitat range of an animal or plant)

and:

• define kind and size of sampling units • identify heterogeneous and more uniform areas• Separate heterogeneous areas into different decision units based on uniformity (e.g., do not mix

sediment and soil samples, separate grass habitats from wooded habitats) and stratify and randomize where samples should be taken (dividing the population into strata that have relatively uniform characteristics will reduce variability or complexity of the problem)



4. Specify Boundaries continued.

Describe timeframe the data will represent and when samples should be taken (may be very important especially with volatile compounds).

• determine when to collect and for how long data will reflect those conditions

Define scale of decision making (what size/level the decision pertains to). Define smallest, most appropriate subsets of the population or subpopulations for which decisions will be made, considering:

• Exposure Unit: Area/volume corresponding to the area/volume where receptors derive majority of exposure

• Remediation Unit: Area/volume which has been determined to be most cost-effective area/volume for remediation.

Identify constraints on data collection. Identify constraints or obstacles that could interfere with full implementation of data collection and sampling design, considering:

• seasonal conditions and weather• site access• personnel availability• sensitive or high use periods for fish and wildlife (e.g., nesting or migration staging)

5. Define Decision RulesCombines steps 1-4Includes:

• Parameter of interest• Unit of decision making• Null hypothesis• Action level• Alternative Actions

Example:

If the [true mean as estimated by the 90%UCL (or average if using ISM) calculated using the sample mean) lead concentration] within [the upland area exposure unit within the perimeter of the site] is ≥ [shrew ESL for population (or shrew ESL for individual if listed mammal species present)] then exposure unit requires Stage III risk assessment or targeted remediation action, if not there will be no further action conducted on the exposure unit.

If the [true mean as estimated by the 90%UCL (or average if using ISM) calculated using the sample mean) lead concentration] within [the upland area exposure unit within the perimeter of the site] is ≥ [robin ESL for population (or robin ESL for individual if listed bird species present)] then exposure unit requires Stage III risk assessment or targeted remediation action, if not there will be no further action conducted on the exposure unit.



6. Specific Error TolerancesSpecifying the decision maker’s tolerable limits on decision errors limits uncertainty in the data. Decision errors occur because of:

• Sampling error, which occurs because the sampling design is unable to capture and control the complete extent of heterogeneity that exists as the true state of the environment

• Measurement error, which occurs because analytical methods and instruments are not perfect

To account for or control these errors (mostly when collecting discrete samples), define:• Variability of each COPC• Decision errors and consequences (for each alternative action)• Null hypothesis (e.g., site is assumed contaminated until shown to be clean)• Error rates (Alfa and Beta)- incorrectly walking away from a dirty site, or incorrectly cleaning a clean

site• Action level (AL)• The Lower Bound of the Gray Region (LGBR)• The Gray Region (delta)

Notes for consideration when specifying error tolerances:• The Gray Region is the range of possible parameter values within which the consequences of a decision error

are relatively minor. The Gray Region is bounded on one side by the action level (AL) and the other side by the parameter value where the consequence of decision error begins to be significant (i.e., the LBGR). The Width of the Gray Region =AL-LBGR. Note the closer the LGBR is to the action level, the more discrete samples are needed.

• Relying on an estimate of the mean contaminant concentration in a volume of soil using a small number of discrete samples can lead to costly decision errors. Simulation studies, empirical evidence, and sampling theory suggest that low numbers of discrete samples do not produce very accurate or precise estimates of the mean because such an approach does not account for heterogeneity. Only when the true mean is well above or well below an action level (a situation never known in the field) can even a small number of discrete samples result in a correct decision (ITRC 2012).

• Rather than using discrete samples, collecting samples using Incremental Sampling Methodology (ISM) offers a more affordable and straightforward approach to determine exposure concentrations and allows for direct comparison to action levels. ISM can be used to obtain a exposure point concentration of decision unit that is based on the mean concentration (or a 90% upper confidence limit of triplicate ISM values if triplicate quality control results indicates high relative standard deviation of about ≥35%). The mean or 90% UCL can then be directly compared to the action level to make a management decision.

7. Optimize Sample DesignIdentify the most resource effective data collection and analysis design that satisfies the planning process objectives in the previous 6 steps.

• Review the DQO steps• Develop alternative sampling designs• Select tolerances/Gray Region and math expressions for each alternative and perform a

preliminary data quality assessment• Select optimal sample size the satisfies the planning process objectives• Check if number samples exceeds project resource constraints• Compare costs for conducting sampling plan for discrete analysis versus costs associated with

ISM analysis



References:

Stage 3 (Risk Assessment):Efroymson, R.A, Nicolette , J.P., and Suter II, G.W.. 2003. A Framework for Net Environmental Benefit

Analysis for Remediation or Restoration of Petroleum-Contaminated Sites. ORNL/TM-2003/17. Oak Ridge National Laboratory, Oak Ridge, Tennessee.

Kapustka, L. A., Bowers, K., Isanhart, J., Martinez-Garza, C., Finger, S., Stahl, R. G. and Stauber, J. (2016), Coordinating ecological restoration options analysis and risk assessment to improve environmental outcomes. Integr Environ Assess Manag, 12: 253–263.

7 Step Data Quality Objective Process:Adapted From:Ramsey, C. 2009. Sampling for environmental decision making. Training class manual. Envirostat, Inc.

May 4-7, 2009, Ft. Collins, Colorado.Tindall, S. 2010. Managing uncertainty with systematic planning: Developing defensible sample designs

for environmental decision making. Training class manual. QE3C, Inc. May 15-17, 2010, Portland, Oregon.

References and related materials: Deming, W.E. 1950. Some theory of sampling. Dover publications, New York. 640 pp.ITRC (Interstate Technology & Regulatory Council). 2012. Incremental sampling methodology. Interstate

Technology & Regulatory Council, Incremental Sampling Methodology Team. http://www.itrcweb.org/ism-1/

U.S. Environmental Protection Agency. 2000a. Guidance for the data quality objectives process. EPA QA/G4. Final report EPA/600/R-96/055. Office of Environmental Information, Washington, DC.

U.S. Environmental Protection Agency. 2000b. Data quality objectives process for hazardous waste site investigations. EPA QA/G-4HW. Final report EPA/600/R-00/007. Office of Environmental Information, Washington, DC.

U.S. Environmental Protection Agency. 2000c. Guidance for data quality assessment: Practical methods for data analysis. EPA QA/G-9, QA00 Update. Final Report EPA/600/R-96/084. Report EPA/600/R-96/084.

U.S. Environmental Protection Agency. 2002. Guidance on choosing a sampling design for environmental data collection for use in developing a quality assurance project plan. EPA QA/G-5S. Final report EPA/240/R-02/005. Office of Environmental Information. Washington, DC. 166 pp.

U.S. Environmental Protection Agency. 2006. Guidance on systematic planning using the data quality objectives process. EPA QA/G-4. Final report EPA/240/B-06/001. Office of Environmental Information, Washington, DC. 111 pp.



Appendix B.1: Stage 2 Soil Sampling Approach for Deriving Exposure Concentrations and Screening Environmental Risk at Cleanup Sites

Introduction This appendix describes a Stage 2 sampling approach that could help screen environmental cleanup sites

out of the ecological risk assessment (ERA) process when ecological impacts are unlikely, and provides

clear and prescriptive guidance to move the ERA process forward smoothly and reduce delays in

decision making.

The soil sampling approach used to characterize contaminant concentrations at a cleanup site is an

important component for accurately representing exposure concentrations for terrestrial receptors,

addressing a level of confidence around the exposure estimate, and screening site data against ecological

screening levels (ESLs) or ecological benchmark values (EBVs).1Oregon Administrative Rules (OAR)

and DEQ (1998) risk guidance do not provide specific recommendations for using any particular

sampling approach to sample media at Oregon cleanup sites. The Hazardous Substance Remedial Action

Rules (OAR 340-122-0098) state that “The Department shall require appropriate sampling approaches

and data quality requirements to support the risk assessment and remedy selection processes.” DEQ

(1998) risk guidance recommends the following regarding development of sampling and analysis plans:

• “A statement of data quality objectives (DQOs) for all key components of the field and/or

laboratory investigations, considering that DQOs should be used in conjunction with, and not as

a substitute for, a scientifically defensible experimental design.

• The risk assessor should ensure that sampling covers areas and media of ecological interest and

that analytical detection levels are set low enough to be of ecological significance, as determined

by the analysis plan (which includes DQOs and the QA/QC plan).

• If statistical analyses are desired, the study methodology and protocols should ensure that

quantitative data will be collected.”

1 The subgroup is recommending that EBVs be developed to gradually replace DEQ‘s ESLs. For details, see Appendix C. When an EBV is used, then additional evaluations must be conducted to show how the analysis meets the acceptable level of risk for populations of ecological receptors as defined in rule.



Because nuances in sampling approaches and uncertainty in results can lead to delays in assessment as

well as very different outcomes when screening sites in or out for further assessment, a specific

approach is presented in this appendix to more reliably obtain exposure estimates, consistently address

uncertainty, and enable DEQ to make remedial action decisions to improve sites to the point where no

further cleanup action is necessary. A primary goal in this process is to obtain the best environmental

data needed to make decisions as inexpensively and quickly as possible. Consistent with rule and

guidance, the proposed approach will require development of a conceptual site model (CSM) to inform

the sampling, use of DQOs in conjunction with the experimental design, coverage of areas

representative of ecological receptors, and a quantitative and defensible analysis plan.

Stage 2 Sampling Methodology

The sampling approach first relies on the completion of the Stage 1 CSM after a site is considered for

further action. At the beginning of Stage 2, a planning team meets during the planning meeting and uses

best professional judgment to review and modify the CSM as needed and derive the DQOs for the site,

which include identifying the spatial boundary, the sampling unit, and sampling design. A key

component in this approach is the designation of a DU (or multiple DUs for larger sites) and

distinguishing between types of DUs to meet specific sampling objectives. To represent a local

population of small home range receptors or a large home range receptor, multiple 0.5-acre HDUs can

be sampled separately, as single units, and the results combined through averaging to determine an EPC

that represents a larger HDU. Alternatively, a large HDU can be selected and sampled as a single unit.

Typically, the sampling approach and design used within a single DU should meet specific objectives

and not attempt to mix multiple objectives (i.e., a SDU cannot also serve as an HDU). However, one or

more SDUs or other DUs can be identified within an HDU, and an HDU might be located inside of a

greater than 0.5- acre SDU. Even if an HDU and an SDU are co-located, they have been defined for

distinct reasons and each should have its own DQOs and sampling design. DQOs that clearly define the

spatial boundary, types of DUs, and the sampling unit can improve decision making by preventing

delays commonly associated with and exacerbated by insufficient or unrepresentative sampling.

After the DUs are established, the next phase of the process is to identify the sampling design (number,

type, and exact locations of samples) needed to represent the DU. For the Stage 2 approach, the

minimum allowable size for a small home range receptor HDU is 0.5 acres, and average contaminant

concentrations within the HDU are compared to ESLs or EBVs for the shrew and American robin

(Turdus migratorius) only (or the lower value for the two receptors). With this approach, it is imperative

that the HDU be characterized using grid sampling, as defined above, to meet the assumption of equal

exposure for a small home range receptor moving randomly across the area. If judgmental sampling is

used instead, then decision-making is vulnerable to disagreements about unquantified estimation errors.

EPA (2002) recommends using systematic or grid sampling approach when estimating a population

mean and to produce information on spatial or temporal patterns. EPA (2002) states that “Grid sampling

insures all areas are represented in the sample and can provide confidence that a site has been fully

characterized.” ITRC (2012) supports grid sampling when using ISM and reports that “The systematic

sampling patterns ensure relatively even spatial distribution of samples across the site and are generally

easier to implement in the field.” Other approaches such as simple random sampling (non-systematic) or



judgmental sampling that do not incorporate a gridded design would not necessarily meet the

assumptions of an equal exposure over the defined area.

A primary importance of using systematic grid sampling, and preferably ISM, to estimate the EPC is to

prevent subjectively biasing the data. Intentionally sampling areas within a HDU that are not suspected

of being contaminated to impart a “low bias”, or sampling only in areas of suspected contamination to

impart a “high bias”, does not represent how a receptor uses the entire HDU and can increase the

likelihood of decision errors (see Exhibit A for further discussion on this topic).

EPA (1992b) provides details of representative soil sampling techniques and how to reduce bias in

sampling. In some cases, there may be physical or other constraints at a site that prevent systematic grid

or ISM sampling. In these situations, methodology must be proposed at the planning meeting that shows

how the sample approach best represents use of the area by a receptor. Likewise, when specific

information is available on spatial use of a receptor, a sample design reflecting knowledge of this

information can proposed at the planning meeting. Specific recommendations and guidance on sampling

approaches is presented in Exhibit B. In all cases, sampling methodologies must meet DQOs and results

pass data quality assessment, and the assumptions and limitations of the method must be discussed in the

sampling plan.

Stage 2 Screening Methodology

The initial stage of screening of the EPC against ESLs or EBVs occurs for an exposure area defined as

the 0.5-acre HDU. If threatened or endangered (T&E) species are present at a site, or the site is within

designated critical habitat for the species, then the EPC within each 0.5-acre HDU sampled must be

below the individual level-based ESLs or EBVs for small home range receptors (i.e., shrew or robin) to

screen the site out for further risk assessment. If the robin and shrew are not suitable surrogates for the

T&E species present at the site (e.g., for less mobile species such as plants, invertebrates, reptiles, or

amphibians), then these receptors will have to be evaluated separately at the individual level, potentially

using an decision unit at a smaller size that is more representative of the less mobile receptor. For wider-

ranging or large home range T&E receptors, see additional information below.

If T&E species or their critical habitat are not present at a site, then the EPC within a 0.5-acre HDU (or

the average of a set of HDUs representing a population) can be screened against population level-based

ESLs or EBVs for small home range receptors (shrew and robin).

To represent a local assessment population area (LAPA) of small home range receptors (shrew and

robin), a larger HDU up to two2 acres can be screened by comparing the EPC to a population-level

2The LAPA of 2 acres is a suggested value determined using parameters for a vagrant shrew (body weight of 0.007 kg, median natal dispersal distance of

0.07 km) and model by Santini et al. (2013) resulting in a local population area based on dispersal of 4 acres. The 4 acres is considered to be the minimal

patch size that would sustain a healthy population of shrews (mainland island patch). However, Landis and Deines (2008) describe how populations in

smaller patches (which may not be sustainable by themselves) are important, depending on patch arrangement on the landscape in relation to one another, to sustain a mainland island patch through dispersal dynamics (i.e., dispersing individuals from the smaller patch are important to maintaining a mainland

island patch). The “critical” size of these smaller patches relative to the mainland island patch is unknown but considered to be smaller than the mainland

island patch. To protect these smaller patches, it is assumed that one-half the size of the mainland patch (i.e., 2 acres) would serve as a uncertainty factor that could be protective of individuals in a smaller patch that are important to maintaining the mainland island patch, and also would represent a LAPA.



based ESL or EBV. The LAPA can be represented by sampling four individual HDUs and combining

averages to screen the EPC against population level-based ESLs (shrew or robin), or by sampling one

entire two-acre area by grid sampling to obtain a single average concentration as the EPC. The ESLs or

EBVs used to screen against the EPC would be the shrew and robin population level-based ESLs or

EBVs. An EPC lower that the ESL or EBV would result in a no further ecological risk assessment

action, whereas an exceedance would mean a targeted response action or continuation into the next

phase of the risk assessment. If the combined area for grouped HDUs (of similar habitat types) for the

site is smaller than two acres, or there is evidence from the CSM to indicate that specific areas within the

LAPA would not be within the area of contamination, then a spatially-based area use factor can be

incorporated to screen soil data rather than sampling the entire LAPA. In these cases, an EPC can be

“diluted” by the proportion of 0.5-acre HDUs that are not within the contaminated area in the LAPA.

There are four possible “dilution factors” (1, 0.75, 0.5, 0.25) that can be applied to a LAPA,

corresponding to the HDUs that are not within the contaminated area. For example, if there are two 0.5-

acre HDUs that are not within the contaminated areas of a 2-acre LAPA, then the EPC for the LAPA is

multiplied by 0.5, which represents percent of the LAPA that is not within a contaminated area and

overlaps the site grouped HDUs. The resulting value can be compared to shrew and robin population

level-based ESLs or EBVs. This evaluation is considered to meet OAR 340-122-0084 requirement that

risk estimate shall be made “…at the level of the population for all other plants or animals in the locality

of the facility.”

To evaluate wider-ranging receptors, this approach allows for combining individual HDUs (of similar

habitat types) or sampling within the entire range of the receptor in the same way as sampling within a

LAPA, but in this case the breeding or foraging range (or distribution-based home range model

representing a core use area) for the receptor would frame the size and boundary of the entire HDU. The

same area use factor method would apply for the wider-ranging receptor as described above, but the 0.5-

acre HDU “dilution factors” would be proportional to the average breeding range or foraging range of

the receptor rather than the LAPA. Receptors used in the assessment would be American kestrel (Falco

sparverius) and long-tailed weasel (Mustela frenata). The EPCs calculated within the average foraging

or breeding range of the kestrel and long-tailed weasel can be compared to kestrel and weasel individual

level-based ESLs or EBVs (for assessing risk to larger ranging threatened and endangered birds, and

mammals) or population level-based ESLs or EBVs (for non-threatened and endangered birds, and

mammals). For this approach, there is no LAPA-type evaluation for wider-ranging receptors because

typically the average foraging or breeding ranges of wider-ranging species (e.g., kestrel or weasel) is far

greater than the site. In the judgment of the subgroup, assumptions about off-site exposure would be too

speculative to rely on in Stage 2, and the site should progress to Stage 3 if a kestrel or long-tailed weasel

EBV is exceeded by the site-wide mean soil concentration.

This approach for sampling and screening soil generic ESLs for terrestrial receptors is an option that

allows users to collect sample data efficiently, representatively, and in a cost-effective manner. The

This LAPA of 2 acres is assumed to be protective of robins, as the home range of robins (0.3 to 0.6 acres) is similar to vagrant shrews, although the

foraging and social behavior of robins are quite different from shrews and results in a high degree of uncertainty for protection of birds using this method.



approach is more prescriptive than previous risk guidance (DEQ 1998) in requiring a more specific

sampling method using systematic grid sampling to best represent equal exposure of a receptor across a

site. This straightforward approach allows risk managers and RPs to know up front what is expected of

the ecological risk assessment, which helps keep the process moving forward and avoid expensive

delays caused by indecision and uncertain data.

References



Interstate Technology & Regulatory Council (ITRC). 2012. Incremental sampling methodology.

Interstate Technology & Regulatory Council, Incremental Sampling Methodology Team. Washington,

D.C. www.itrcweb.org.

Oregon Department of Environmental Quality (DEQ). 1998 (updated 2001). Guidance for ecological

risk assessment: Levels I, II, III, IV. Oregon Department of Environmental Quality, Portland, Oregon.


correlates of dispersal distance in terrestrial mammals. Hystrix, the Italian Journal of Mammalogy.

24:181-186.

Sample, B. E., C. Schlekat, D. J. Spurgeon, C. Menzie, J. Rauscher, and B. Adams. 2013.

Recommendations to improve wildlife exposure estimation for development of soil screening and

cleanup values. Integrated Environmental Assessment and Management 10:372-387.




concentration term. Final Report 9285.7-08I. Intermittent Bulletin Volume 1 Number 1. Office of Solid

Waste and Remedial Response, Washington, D.C.


techniques and strategies. Final Report EPA/600/R-92/128. Office of Research and Development,

Washington, D.C.


environmental data collection for use in developing a quality assurance project plan. EPA QA/G-5S.

Office of Environmental Information, Washington, D.C.

http://www.itrcweb.org/



Exhibit A, A Note on Exposure Estimates and Site Screening

Two key elements that determine whether or not a site screens out from further ecological risk

assessment are the Ecological Screening Level (ESL) or Ecological Benchmark Value (EBV)3selected to

represent the risk assessment and the exposure point concentration (EPC) used to represent a Habitat

Decision Unit (HDU). For example, a site is less likely to screen out when the ESLs are conservatively

low, or the EPC is unrepresentatively high due to collection of intentionally-biased sampling methods.

Risk practitioners have commented that the no- and low-observed adverse effect levels used to derive

some ESLs are unnecessarily conservative or are not very good estimates for use in assessing risk, and

are not very effective in screening a site out from further assessment (Sample at al. 2013). Likewise,

EPCs calculated based on data collected from a sampling area with the intention of biasing the exposure

value high to be “conservative” have an increased likelihood of mistakenly screening a site in as

contaminated. For ESLs, few other values (such as effect concentration data) are currently available for

terrestrial receptors to improve their reliability, and continued use of at least some ESLs in screening

remains likely at this time, even if the development of EBVs to replace ESLs is incentivized. However,

the statistic used to represent the EPC can be determined in a manner that is more representative of a

true average concentration, as compared to a higher “maximum” or UCL estimate of the average (which

is a common approach in risk guidance) and would likely result in more decisions to correctly screen a

site out from further assessment. DEQ (1998) indicates that for the EPC,

“(a) concentration should be used that represents a reasonable maximum exposure given the

characteristics of the medium and the site-related species…” and

“For terrestrial wildlife consuming soil, vegetation, or animal foods, the 90th percentile UCL on

the mean is the appropriate media concentration for comparison with the SLV.”

However, DEQ Hazardous Substances Remediation Action Rules (OAR 340-122-0084) provide some

flexibility on recommending use of the 90th percentile, stating “…unless a greater or lesser best estimate

is acceptable to the Department.” If using the ISM approach to represent an HDU in the manner

described in this appendix, then the average concentration (rather than the maximum or 90% UCL) in

the entire HDU should be considered a better estimate of the EPC. The approach using ISM sampling

provides a clear path forward for the risk manager to make a risk decision based on comparing an EPC

based on an unbiased average to ESLs (or eventually EBVs), as well as providing a level of certainty

around the decision.

3 See Appendix C to the terrestrial subgroup’s recommendations for phasing out ESLs and replacing them with EBVs. If an EBV is used, then additional evaluations must be conducted to show how the analysis meets the acceptable level of risk for populations of ecological receptors as defined in rule.



Exhibit B, Technical Issue Paper – Recommendations for Sampling Approaches for Deriving Surface Soil Exposure Estimates within Habitat Decision Units at Cleanup Sites

Prepared for: Oregon Department of Environmental Quality

Ecological Risk Assessment Technical Workgroup

Submitted by:

Jeremy Buck

U.S. Fish and Wildlife Service

Oregon Fish and Wildlife Office

Portland, Oregon

December 16, 2016

Background

A common issue that arises at contaminated sites during the planning stage is how to best represent

contaminant concentrations over a given spatial area. Once a spatial boundary for sampling has been

delineated, the exact number and location of samples that will best represent concentrations within the

boundary must be determined. Various approaches to determine the number and location of samples

include methods based on statistical theory and those based on professional judgment. This issue paper

defines these approaches and addresses the advantages and disadvantages for their use in selecting the

number and location of samples for characterizing surface soil within a habitat decision unit (HDU),

defined as the spatial boundary within which a receptor is assumed to move randomly across and receive

equal exposure to all parts of the area. The purpose of this paper is to provide recommendations to the

Oregon Department of Environmental Quality (DEQ) Ecological Risk Assessment Technical

Workgroup and Terrestrial Ecological Risk Assessment Subgroup (Subgroup) for consideration in use

for evaluating ecological risk at contaminated sites.

Terminology The two main categories of sampling approaches used to characterize contaminant concentrations

include statistically-based methods (referred to here as probability-based sampling or probabilistic

sampling) where the number and location of samples are determined statistically, and judgmental

sampling, where the number and location of samples are determined using professional judgment or

opinion. Both these methods are used to obtain an average concentration (sometimes represented as an

upper confidence limit or a maximum concentration) within a decision unit (DU) or some other spatial



area. The average concentration can represent an exposure point concentration (EPC) for use in

comparison to an ecological screening level (ESL) that will support a decision to screen a site out from

further ecological risk assessment (EPC value below an ESL) or screen a site in for further ecological

risk assessment (EPC value is above an ESL). The U.S. Environmental Protection Agency (EPA 2002)

provides definitions of sampling terms and guidance for choosing a sampling design for environmental

data to obtain representative exposure estimates, and provides the following definitions for the two main

categories of sampling designs:

Judgmental sampling – the number and location of samples is based on knowledge of the feature or

condition under investigation and on professional judgment. Inferences are based on professional

judgment, not statistical scientific theory. Conclusions about the target population are limited and

depend entirely on the validity and accuracy of professional judgment.

Probabilistic sampling – the number and location of samples is based on sampling theory involving the

random selection of sampling units. Each member of the population from which the sample was selected

has a known probability of selection. Statistical inferences can be made about the sampled population

from the data obtained from the sampling units.

With both approaches, expert judgment and opinion are used in all stages when developing the sample

plan, except in probabilistic sampling the final number and location of samples is based on statistics

rather than professional opinion.

Advantages and Disadvantages of Judgmental and Probabilistic Approaches The advantages of judgmental sampling are primarily associated with cost, being cheaper and easier to

implement than probabilistic sampling, and EPA (2002) considers this approach as very efficient when

there is reliable historical and physical knowledge about a relatively small feature or condition. The

advantages of probability-based sampling primarily include the ability to provide results within

uncertainty limits, make statistical inferences, and handle decision error criteria (a key component of

meeting data quality objectives).

The disadvantages of judgmental sampling are that the approach cannot be used to evaluate precision of

estimates or make statistical inferences, and it depends solely on expert knowledge. The disadvantages

in probability-based designs primarily include a high cost associated with obtaining the samples needed

to meet statistical requirements (resource intense), and potential physical constraints in obtaining some

samples at random locations.

EPA (2002) indicates judgmental sampling is appropriate to investigate relatively small-scale features or

conditions when there is reliable knowledge about the feature or condition, when an extremely small

number of samples will be selected for characterization, or when schedule or emergency considerations

preclude a statistical design. EPA notes that results can be used to screen an area for presence or absence

of contamination at levels of concern (including risk-based screening levels), although if contamination

is found, follow-up sampling is likely to involve statistical designs. EPA (2002) states the limitations of

the approach as “Judgmental sampling does not allow the level of confidence (uncertainty) of the



investigation to be accurately quantified. In addition, judgmental sampling limits the statistical

inferences that can be made to the units actually analyzed, and extrapolation from those units to the

overall population from which the units were collected is subject to unknown selection bias.”

With probabilistic sampling, there are a number of possible statistically-based sample designs that EPA

(2002) describes for characterizing contaminant concentrations. The systematic grid sampling method is

a probabilistic approach that is recommended for use when:

estimating a population mean and confidence limits and producing information on spatial and

temporal patterns;

making an inference about a population such as the mean when environmental measurements are

known to be heterogeneous (e.g., such as soil); and

looking for hot spots that could be missed with other sampling designs.

Grid sampling relies on locating samples at designated nodes of a geometrical grid pattern (for example,

square, rectangle, triangle, hexagon). Sampling occurs at equally-spaced intervals on the nodes or within

the grid cells (systematic grid sampling or systematic random sampling) or randomly within grid cells

(stratified random sampling or random sampling within grids). When representing surface soil (i.e., a

heterogeneous material) within an HDU that assumes relatively equal use by a receptor, systematic grid

sampling can provide better coverage of soil compared to other probabilistic methods (EPA 1992a) and

will be the primary probabilistic method described in this issue paper. Incremental Sampling

Methodology (ISM), a grid-based sampling approach based on collection of many increments over the

grid and combining them into a single sample (ITRC 2012), is based on statistical theory and is

considered a type of systematic grid sampling for the purposes of this issue paper. Limitations of

systematic grid sampling, as described in EPA (2002), include that it may not be as efficient when prior

information is known that could be used as a basis for stratification, or when certain population

properties of interest are aligned with the grid (i.e., if a known pattern of contamination coincides with

the regularity of the grid design). If these situations exist, then other systematic or stratified approaches

may be warranted.

Use of Judgmental or Nonprobabilisitic Sampling Judgmental sampling has been a preferred approach to characterize sites when budgets for sampling are

limited and when there is a recognized or preconceived belief that probabilistic sampling will exceed

budgets. EPA (1991, 2002) recognizes the approach for use when there is existing, reliable knowledge at

the site when:

addressing a relatively small-scale problem;

assessing conditions or features during the initial phase of site sampling;

performing an initial risk assessment using only few samples;

evaluating known contaminated areas prior to using an unbiased method to characterize

exposure; and



identifying hot spots when used in combination with a systematic grid approach.

However, EPA guidance (1991, 1992a, 1992b, 2000, 2002, 2015) notes specific problems that arise

when using nonprobabilistic methods such as judgmental sampling approaches (including low density,

biased, and purposive sampling), and in many cases cautions against using samples collected under these

approaches for making risk-based screening decisions.

A key element of sampling error that leads to poor decisions is not accounting for the inherent

heterogeneity of soil in a sample design. If a specific DU contains highly uniform materials (particle

mass and size) over a uniform gradient of contaminant concentrations, then it may be possible to

characterize an area with a few samples. However, this condition is hardly ever found in nature,

especially for materials as heterogeneous as soil. Heterogeneity is typically not well characterized with

low density sampling, and smaller sample sizes typically result in greater sample variation (EPA 2002).

ITRC (2012) summarizes this issue in the following statements:

“…there is a large body of work in classical statistics, Gy sampling theory, industry experience,

and empirical evidence (e.g., results from duplicate samples) which suggests that (a) soil is

highly heterogeneous even on extremely small scales and (b) small numbers of discrete samples

are not likely to provide accurate or precise estimates of mean concentrations. Low-density

discrete sampling plans therefore cannot be relied on to consistently produce high-quality

decisions.”

“Heterogeneity makes representative sampling difficult. Sampling errors are manifested as

variability (i.e., imprecision observed as large differences in results between replicate samples)

and/or bias in the data set (i.e., data results significantly over or under the true concentrations).”

“Relying on an estimate of the mean contaminant concentration in a volume of soil using a small

number of discrete samples can lead to costly decision errors.”

Problems associated with soil heterogeneity and sampling error manifest in other aspects of judgmental

sampling and data interpretation, especially due to the inability to address bias or estimate means with

confidence intervals. EPA (1992a) guidance for preparation of soil sampling protocols identified

problems with judgmental sampling in the early 1990s, stating that “This technique is often used with

one of the other methods in unusual pollution situations or where effects have been seen in the past. The

problem with the approach is that it tends to lead to sloppy science and wrong conclusions. The

scientist’s own bias is built into the sampling effort and the data, therefore, is often suspect.”

Results based on judgmental sampling are especially problematic when calculating an upper confidence

limit (UCL) to represent an EPC. The 90 percent UCL, or the value (when calculated repeatedly) that

equals or exceeds the true mean 90 percent of the time, is commonly used to represent an EPC. Oregon

Hazardous Substances Remedial Action Rules (OAR 340-122-0084) specifically state that “Risk

assessments utilizing only deterministic methods shall provide both central tendency and upper-bound

estimates of exposure and risk.” DEQ (1998) risk guidance states “The exposure concentration that will

be compared to the screening level value (SLV) depends on the characteristics of the receptor. A

concentration should be used that represents a reasonable maximum exposure given the characteristics

of the medium and the site-related species…” and “For terrestrial wildlife consuming soil, vegetation, or



animal foods, the 90th percentile UCL on the mean is the appropriate media concentration for

comparison with the SLV.”

Typically, too few samples are collected using judgmental sampling to meet the data requirements for

the calculation of an UCL. Numerous EPA guidance documents caution against using nonprobabilistic

data for extrapolating to the entire site or for calculating a UCL, stating:

EPA 1991-“Resource constraints sometimes restrict the number of samples for the risk

assessment and therefore potentially increase the variability associated with the results. When the

number of samples that can be taken is restricted, judgmental sampling may identify the

chemicals of potential concern, but cannot estimate the uncertainty of chemical quantities. The

reasonable maximum exposure or upper confidence limit cannot be calculated from results of a

judgmental design.”

EPA 2000- “…when nonprobabilistic sampling approaches are used, quantitative statements

about data quality are limited only to the measurement error component of total study error and

the results cannot be extrapolated to the entire site unless the data are being used to support

explicit (usually deterministic) scientific models, such as ground water contaminant fate and

transport.”

EPA 2002- “When using judgmental sampling, statistical analysis cannot be used to draw

conclusions about the target population. Conclusions can only be drawn on the basis of

professional judgment. The usefulness of judgmental sampling will depend on the study

objectives, the study size and scope, and the degree of professional judgment available. When

judgmental sampling is used, quantitative statements about the level of confidence in an estimate

(such as confidence intervals) cannot be made.”

Caution should also be used when collecting judgmental samples with the intention of obtaining a

conservative “high bias” exposure estimate, as portions of a HDU and exposure area that have lower

concentration will be underrepresented, and the results can be more likely to exceed screening values

and indicate the site needs further assessment when otherwise it may have screened out for further

action. High-biased data will also have a high degree of uncertainty which may not be adequately

characterized, and EPA (1991) states “Uncertainty in the analytical data, compounded by uncertainty

caused by the selection of the transport models, can yield results that are meaningless or that cannot be

interpreted.” This process can lead to indecision and result in lengthy and costly delays preventing a

cleanup project from moving forward. Pre-existing knowledge of the contaminant source and

distribution (or obvious visual cues) is required for successful use of a “high bias” judgmental sampling

plan. ITRC (2012) notes that “Judgmental sampling plans can be used effectively with low numbers of

discrete samples if the basis for determining the sample location and the volume of soil it applies to is

appropriate. For instance, judgmental sampling plans may be useful when obvious source areas of high

concentrations are present.” EPA (1992b) also provides guidance on interpreting results from low

density sampling data, noting that “For exposure areas with limited amounts of data or extreme

variability in measured or modeled data, the UCL can be greater than the highest measured or modeled

concentration. In these cases, if additional data cannot practicably be obtained, the highest measured or

modeled value could be used as the concentration term. Note, however, that the true mean still may be



higher than this maximum value (i.e., the 95 percent UCL indicates a higher mean is possible),

especially if the most contaminated portion of the site has not been sampled.”

ProUCL (EPA 2015), a software package commonly used to estimate UCLs, and EPA (2000) data

quality objectives guidance discuss the minimum number of samples needed to reliably calculate

exposure terms, and recommend at least 10 samples be used to calculate these values (although the

documents actually identify small sample sizes as less than 20 to 30, with sizes above these values

associated with greater reliability). The software guide cautions that “From a mathematical point of

view, the statistical methods incorporated in ProUCL and described in this guidance document for

estimating EPC terms and BTVs [background threshold values], and comparing site versus background

concentrations can be performed on small site and background data sets (e.g., of sizes as small as 3).

However, those statistics may not be considered representative and reliable enough to make important

cleanup and remediation decisions which will potentially impact human health and the environment.” It

should be noted that ProUCL allows for calculation of statistics from three samples primarily to

incorporate comparison of triplicate results from ISM samples. A key assumption listed in the software

guidance (EPA 2015) is “A UCL of the mean (of a population)…should be computed using a randomly

collected (simple random or systematic random) data set representing a single statistical population (e.g.,

site population or background population).”

Although low density data are problematic for calculating a UCL, ITRC (2012) notes that in some cases

it is possible to make decisions based on few samples under very specific conditions, stating:

“This is not to say that a low-density discrete sampling approach is insufficient for all cases. If,

for example, the true mean in a DU is orders of magnitude above or below the action level for a

contaminant of interest, it is possible that a correct decision could be made from very few (or

even one) discrete samples. The key factors are the degree of heterogeneity present at the various

scales, the action level, and the magnitude of the true mean. Since, as is often the case,

knowledge about heterogeneity or the magnitude of the true mean is seldom available (which is

why sampling is being conducted), relying on data from low-density discrete sampling plans is

more likely to result in decision errors.”

Use of Probabilistic Sampling EPA (1992a) soil guidance provides specific details describing all the known types of error associated

with soil sampling, and provides specific methodologies to help overcome sampling error and reduce

sampling bias. Sampling in a probabilistic manner is one of the best ways to overcome sampling error

and represent confidence limits at a site, and the soil guidance recommends a systematic grid approach

for evaluating soil, noting the following:

“The systematic sampling plan is an attempt to provide better coverage of the soil study area

than could be provided with the simple random sample or the stratified random sampling plan.

The exploratory study discussed earlier in this section is an example of the use of some form of

grid pattern. The systematic sampling design is in reality a stratification based upon spatial

distribution over the site.



Systematic sampling collects samples in a regular pattern (usually a grid or line transect) over

the areas under investigation. The starting point is located by some random process similar to

those discussed above in the section on locating sampling points. The samples are collected at

regular intervals in one or more directions. The orientation of the grid lines should also be

randomly selected unless there is a suspected plume, in which case, the orientation of one axis

of the grid should lie parallel to the plume axis. This is especially important if geostatistics are

being used to aid in interpreting the data.”

ITRC (2012) supports this approach and states “Simple random sampling, systematic random sampling,

and systematic grid sampling yield unbiased estimates of the mean. The systematic sampling patterns

ensure relatively even spatial distribution of samples across the site and are generally easier to

implement in the field.” EPA (2002) guidance also recognizes the utility of grid sampling when

characterizing soil, stating that “Grid sampling insures all areas are represented in the sample and can

provide confidence that a site has been fully characterized.”

Probabilistic sampling is also best used for characterizing mean concentrations and estimating

confidence intervals around the mean for comparison to an action level. EPA (2002) notes that “When

using probabilistic sampling, the data analyst can draw quantitative conclusions about the sampled

population. That is, in estimating a parameter (for example, the mean), the analyst can calculate a 95%

confidence interval for the parameter of interest. If comparing this to a threshold, the analyst can state

whether the data indicate that the concentration exceeds or is below the threshold with a certain level of

confidence.” The guidance further notes that “An essential feature of a probability-based sample is that

each member of the population from which the sample was selected has a known probability of

selection. When a probability-based design is used, statistical inferences may be made about the sampled

population from the data obtained from the sampling units.”

With probabilistic sampling, one can calculate a one-sample t-test to compare a sample mean to a

threshold parameter or action level, which is a common method used at Superfund sites to screen

contaminated soil (EPA 2000) to determine whether a baseline risk assessment is necessary for a

particular contaminant of potential interest. In this case, sufficient samples need to be collected in a

random manner (typically based on a systematic grid pattern) to approximate a normal distribution and

to calculate a sample mean and standard deviation. Then, a calculated t value is determined as follows:

𝑐𝑎𝑙𝑐𝑢𝑙𝑎𝑡𝑒𝑑 𝑡 =𝑠𝑎𝑚𝑝𝑙𝑒 𝑚𝑒𝑎𝑛 (×̅) − 𝑎𝑐𝑡𝑖𝑜𝑛 𝑙𝑒𝑣𝑒𝑙

𝑠𝑡𝑎𝑛𝑑𝑎𝑟𝑑 𝑑𝑒𝑣𝑖𝑎𝑡𝑖𝑜𝑛 (𝑠)/√𝑠𝑎𝑚𝑝𝑙𝑒 𝑠𝑖𝑧𝑒 (𝑛)

If the calculated t is less than the value listed in the table of critical values of a Student’s t distribution,

then the site is considered “clean.” It should be noted that when using this method, an adequate number

of samples need to be collected because the critical value depends upon sample size, data distribution,

and confidence level. With small sample sizes (<8 to 10 as indicated in ProUCL guidance) the critical

values are large and unstable and UCLs are driven by the critical values, whereas with large sample size

corresponding differences in critical values become more stable and increase reliability of results (EPA

2015). Samples collected based on judgmental sampling are unsuitable for use in a t-test because sample

size is typically small, samples are not collected randomly, and results may not be normally distributed



(or too few samples are collected to identify the underlying distribution). In contrast, the equation

becomes much simpler when using ISM samples. ISM (described below) provides a reasonably

unbiased estimate of the mean contaminant concentration in a DU, which can be directly compared to

the action level to make determinations. The variability that would otherwise affect the critical value

with discrete sampling is accounted for or incorporated into the ISM field collection and laboratory

subsampling methods (ISTM 2012). Therefore, the sample mean can be directly compared to the action

level to determine if the site is “clean.”

A limitation of using probabilistic sampling is the high cost associated with obtaining the appropriate

number of samples to represent mean contaminant concentrations in soil. Typically 20 to 30 or more

discrete samples would be needed to characterize an area to obtain reliable confidence interval estimates

(EPA 2000, 2015). At some sites where substantial information about contaminant releases and

distribution already exists, this type of sampling is sometimes considered overly excessive to

characterize a site. However, ISM sampling can be conducted at much lower costs to obtain a

representative mean within a DU and still meet the statistical rigor of probabilistic sampling. EPA

(1992a) and ITRC (2012) discuss how ISM addresses sampling error and represents soil concentrations,

and is often a preferred approach for representing an exposure area for surface soil. ITRC (2012)

characterizes ISM as:

“…a structured composite sampling and processing protocol that reduces data variability and

provides a reasonably unbiased estimate of mean contaminant concentrations in a volume of soil

targeted for sampling. ISM provides representative samples of specific soil volumes defined as

decision units (DUs) by collecting numerous increments of soil (typically 30–100 increments)

that are combined, processed, and subsampled according to specific protocols.”

“ISM is increasingly being used in the environmental field for sampling contaminants in soil.

Proponents have found that the sampling density afforded by collecting many increments,

together with the disciplined processing and subsampling of the combined increments, in most

cases yields more consistent and reproducible results than those obtained by more traditional

(i.e., discrete) sampling approaches.”

Because all the increments are combined into one sample to represent a DU, analyses costs are greatly

reduced compared to a discrete probabilistic approach requiring analysis of at least 20 or more

individual samples. With ISM, a single average concentration represents the DU, and this average can be

used to screen against threshold values to make risk decisions. If needed, replicate ISM samples can be

collected within the DU to estimate confidence intervals. Information about individual sample locations

within the DU is not available when using ISM, but in most cases this should not be a problem when the

primary objective is to compare the average concentration of a definitive area to risk thresholds derived

for a specific receptor. Because ISM incorporates a gridded approach, the average within a HDU will

represent equal exposure for a receptor randomly moving across the site.

Recommendations For the purposes of characterizing a HDU to obtain an exposure estimate in soil to compare to risk-

based thresholds, the following hierarchy of recommendations is proposed for consideration:



1. Use ISM (ISTM 2012) for estimating mean contaminant concentrations of the HDU (or triplicate

ISM samples to obtain confidence intervals) for direct comparison to ESLs. If physical or other

constraints prevent ISM, or data from individual sample points are needed, then:

2. Use systematic grid sampling (EPA 2002) to estimate a mean and confidence intervals based on

at least 20 individual samples collected (EPA 2000, 2015), and use the 90% UCL to compare to

ESLs. If physical or other constraints (such as if a known pattern of contamination coincides

with the regularity of the grid), then:

3. Use systematic or stratified sampling (EPA 2002) to estimate a mean and confidence intervals

based on at least 10 (preferably >20) individual samples collected (EPA 2002, 2015), and use the

90% UCL to compare to ESLs. If physical or other constraints prevent systematic or stratified

sampling (or substantial information is already known about contamination within the HDU),

then:

4. Use any of the recommended designs described above or use a judgmental design with at least 10

randomly collected samples to obtain a mean and confidence intervals, and use the 90% UCL to

compare to ESLs). This design can be used to impart a “high-bias” to the data if there is pre-

existing knowledge about contaminants at the site. If extensive knowledge about contamination

at a site exists and the objective of sampling is to a) characterize a relatively small-scale

problem; b) to assess the initial phase of site sampling; or c) evaluate known contaminated areas

prior to using an unbiased method to characterize exposure; then

5. Use any of the recommended designs above or use a judgmental design with at least three

samples with the intent to add a “high-bias” to the data. If comparing data obtained in this

manner to ESLs, then screen the result of each sample individually (point-by-point observation

comparison method) to the thresholds rather than the mean or UCL (EPA 2015).

6. For any of the methods described above, the assumptions and limitations of the method should

be described in the uncertainty section, along with how the data quality objectives and data

usability goals were addressed. If data usability goals are not met, then resampling may be

required using a more rigorous approach, or a thorough description should be added to the report

detailing how the data might be biased by the approach.

7. If judgmental sampling is used for obtaining an estimate to compare to an ESL, then the

following (or similar) caveat should be added to the assumptions: “Judgmental sampling does

not allow the level of confidence (uncertainty) of the investigation to be accurately quantified. In

addition, judgmental sampling limits the statistical inferences that can be made to the units

actually analyzed, and extrapolation from those units to the overall population from which the

units were collected is subject to unknown selection bias.”

References

DEQ (Oregon Department of Environmental Quality). 1998 (updated 2002). Guidance for ecological




ITRC (Interstate Technology & Regulatory Council). 2012. Incremental sampling methodology.





U.S. Environmental Protection Agency. 1992a. Preparation of soil sampling protocols: sampling


Washington, D.C.

U.S. Environmental Protection Agency. 1992b. Supplemental guidance to RAGS: Calculating the



U.S. Environmental Protection Agency. 2000. Data quality objectives process for hazardous waste site

investigations. Final Report EPA QA/G-4HW. Office of Environmental Information, Washington, DC.


environmental data collection for use in developing a quality assurance project plan. EPA QA/G-5S.,


U.S. Environmental Protection Agency. 2015. ProUCL version 5.1 user guide: Statistical software for

environmental applications for data sets with and without nondetect observations. Final Report

EPA/600/R-07/041 prepared by A. Singh and R. Machle, Lockheed Martin/SERAS, Edison, New Jersey

for F. Barnett, ORD Site Characterization and Monitoring Technical Support Center, U.S.

Environmental Protection Agency, Atlanta, Georgia. Office of Research and Development, Washington,

D.C.



Appendix B.2: Stage 2 Soil Sampling and Ecological Screening Approach Introduction

This appendix describes a Stage II sampling and screening approach for soil that could help screen out

sites where ecological impacts are not likely.

Oregon Administrative Rules (OAR) and DEQ (1998) risk guidance provide recommendations for using

a particular sampling approach to sample media at Oregon cleanup sites. The Hazardous Substance

Remedial Action Rules (OAR 340-122-0098) state that “The Department shall require appropriate

sampling approaches and data quality requirements to support the risk assessment and remedy selection

processes.” DEQ (1998) risk guidance recommends the following regarding development of sampling

and analysis plans:

“A statement of data quality objectives (DQOs) for all key components of the field and/or

laboratory investigations, considering that DQOs should be used in conjunction with, and not as

a substitute for, a scientifically defensible experimental design.

The risk assessor should ensure that sampling covers areas and media of ecological interest and

that analytical detection levels are set low enough to be of ecological significance, as determined

by the analysis plan (which includes DQOs and the QA/QC plan).

If statistical analyses are desired, the study methodology and protocols should ensure that

quantitative data will be collected.”

For the purposes of this specific ecological screening approach, clarifications to the soil sampling

program are presented. Consistent with rule and guidance, the proposed sampling approach will require

development of a conceptual site model (CSM) to inform the sampling, use of DQOs in conjunction

with the experimental design, coverage of areas representative of ecological receptors, and an analysis

plan.

Proposed Stage II Sampling Methodology The Stage II sampling approach first relies on the completion of the Stage I CSM after a site is

considered for further action. At the beginning of Stage II, a Planning Team of experts meets during the

Planning Meeting (see Appendix A) and uses best professional judgment to review and modify the CSM

as needed and derive the DQOs for the site, which include identifying the spatial boundary, the sampling

unit, and sampling design. A key component in this approach is the designation of a DU (or multiple

DUs for larger sites) and distinguishing between types of DUs to meet specific sampling objectives. To

represent a local population of small home range receptors or a large home range receptor, multiple

HDUs can be sampled separately, as single units, and the results combined through averaging to

determine an exposure concentration that represents a larger HDU. Alternatively, a large HDU can be



selected and sampled as a single unit. Typically, the sampling approach and design used within a single

DU should meet specific objectives and not attempt to mix multiple objectives (i.e., a SDU cannot also

serve as an HDU). However, one or more SDUs or other DUs can be identified within an HDU. The

primary reasons for establishing a DU prior to sampling is to clearly define the sampling unit and

sample support needed to collect a representative sample that will support a particular decision.

After the DUs are established, the next phase of the process is to identify the sampling design (number,

type, and exact locations of samples) needed to represent the DU. For the Stage II sampling approach,

the minimum allowable size for a small home range receptor HDU is 0.5 acres, and result of interest is

the EPC (i.e., average contaminant concentration within the HDU). As mentioned above, ISM is an

effective approach for estimating the average concentration of a DU, and is a recommended sampling

method when little information is available regarding contaminant distributions in soil at a site.

In cases where ISM sampling may not be practical or necessary, alternative sampling methodologies to

estimate the average concentration in the DU may be proposed and vetted during the Stage II Planning

Meeting. Sampling methodologies must meet DQOs and results pass data quality assessment, and the

assumptions and limitations of the method discussed in the sampling plan.

Stage II Screening Methodology The screening step in this example involves comparing EPCs from one or more HDUs to relevant ESLs

If threatened or endangered (T&E) species are present, HDUs are defined as the home range size of an

individual member of the focal T&E species. If the EPC for a HDU sampled with the streamlined

approach is below relevant individual-level based ESLs, then the HDU screens out from further risk

assessment for T&E species. This evaluation is considered to meet OAR 340-122-0084 requirement that

risk estimate shall be made “…at the level of the individual for species present in the locality of the

facility if species is listed as threatened or endangered…”. If less-mobile receptors T&E plants,

invertebrates, reptiles, or amphibians are present on the site, then these receptors may be evaluated

separately.

If no T&E species are present at a site, then EPCs for small home range invertivores such as the shrew

and American robin (Turdus migratorius) are compared to population-level based ESLs for the shrew

and robin. Again, the minimum size of the HDU for small home range receptors is 0.5-acres based on

home range size of a shrew). To represent a local assessment population area (LAPA) of small home

range receptors (shrew and robin), a larger HDU of 5 acres can be screened during the Stage II process

by comparison of the EPCs to a population-level based ESL. In this example, the assessment population

of small home range receptors is assumed to reside in an area that is 10 times the size of an individual

home range. The LAPA can be represented by sampling individual HDUs and combining averages to

screen against the EPC. An EPC for the population that is lower that the ESLs would result in a no

further ecological risk assessment action, whereas an exceedance would mean a targeted response action

or continuation into the next phase of the risk assessment. If the areal extent of soil contamination is

smaller than the LAPA, or there is evidence from the CSM to indicate that specific areas within the

LAPA would not be contaminated, then a spatially-based area use factor can be incorporated to evaluate

risk rather than sampling the entire LAPA. In these cases, an EPC can be weighted by the proportion of

0.5 acre HDUs that are not contaminated within the LAPA. For example, if there are two



uncontaminated 0.5-acre HDUs within a 5-acre LAPA, then the EPC for the LAPA is multiplied by

0.20, which represents 20 percent of the LAPA that is uncontaminated. The resulting value can be

compared to shrew and robin population-level based ESLs to determine if a target response action can

occur (such as within an individual HDU if HDUs were sampled separately), if additional risk

assessment is needed, or if no-further-action (NFA) is warranted. This evaluation is considered to meet

OAR 340-122-0084 requirement that risk estimate shall be made “…at the level of the population for all

other plants or animals in the locality of the facility.”

To evaluate wider-ranging receptors, Stage II allows for combining individual HDUs (of similar habitat

types) or sampling within the entire range of the receptor in the same way as sampling within a LAPA,

but in this case the breeding or foraging range (or distribution-based home range model representing a

core use area) for the receptor would frame the size and boundary of the entire HDU. The same areause

factor method would apply for the wider-ranging receptor as described above, but the weighting

factorswould be proportional to the average breeding range or foraging range of the receptor rather than

the LAPA. For the Stage II approach, the receptors used in the assessment would be American kestrel

(Falco sparverius) and long-tailed weasel (Mustela frenata).The EPCs calculated within the average

foraging or breeding range of the American kestrel and long-tailed weasel can be compared to kestrel

and weasel population-level based ESLs to determine if a target response action can occur, if additional

risk assessment is needed, or if NFA is warranted. The LAPA for wider-ranging species can be defined

in a similar manner as described previously for the shrew and robin. If portions of the LAPA are

uncontaminated, weighting factors can be applied to account for the proportion of uncontaminated soil

within the LAPA.

The proposed Stage II approach for sampling soil and screening soil data against generic ESLs for

terrestrial receptors is an option that allows users to collect sample data efficiently, representatively, and

in a cost-effective manner. The approach is more prescriptive than previous risk guidance (DEQ 1998).

This approach is proposed to clarify the requirements of the ecological risk assessment process, which

helps keep the process moving forward and avoid expensive delays caused by indecision and uncertain

data.

References



Interstate Technology & Regulatory Council (ITRC). 2012. Incremental sampling methodology.



Oregon Department of Environmental Quality (DEQ). 1998 (updated 2001). Guidance for ecological





http://www.itrcweb.org/





Washington, D.C.


environmental data collection for use in developing a quality assurance project plan. EPA QA/G-5S.



88

Appendix B.3: Stage 2 Approach for Conducting Site Screening and Representing a Local Assessment Population Area

Submitted by: Jeremy Buck

U.S. Fish and Wildlife Service

Oregon Fish and Wildlife Office

February 17, 2017

This appendix describes an example for an approach to complete the Stage 2 process. The intent

of Stage 2 is to initiate systematic planning and develop objectives to obtain high quality data

that will provide clear and prescriptive guidance to determine when a site will screen out from

further assessment and when to move forward into ecological risk assessment. The approach

described herein expands upon previously submitted approaches (see Appendices B.1, B.2, and

C) and proposes one method that follows the Stage 2 flowchart for identifying contaminants of

potential ecological concern, screening soil concentrations, and identifying a local assessment

population area.

Stage 2 Systematic Planning/Screening Approach When Stage 1 indicates a cleanup site should be considered for further action, the systematic

planning process is initiated. Information on systematic planning can be found in U.S.

Environmental Protection Agency (EPA) guidance documents (EPA 2006). A primary goal of

the process is to obtain defensible, high quality data so environmental decisions can be made

cost-effectively without delays that are often associated with too much uncertainty and

insufficient data. The process provides more opportunities for sites to screen out or undergo

targeted response actions early in the process compared to the current risk assessment approach,

and therefore more sites are expected to be cost-effectively closed while still maintaining

environmental protection.

The process is initiated with a meeting of a planning team to review and modify the conceptual

site model (CSM) as needed and derive the data quality objectives (DQOs) for the site, which

include identifying the spatial boundary, the population of interest, the sampling unit, and

sampling design.


89

Appendix B.1, Exhibit B provides recommendations for the sampling design. A key component

in this approach is the designation of a decision unit, or multiple decision units for larger sites,

and distinguishing between types of decision units to meet specific sampling objectives. The

process of defining decision units has been described in Appendices B.1 and B.2. Habitat

decision units (HDUs) are established to identify contaminants of potential ecological concern

and calculate exposure point concentrations (EPCs) to compare to screening levels (SLs) that are

considered protective of ecological receptors. Source decision units (SDUs) can be derived to

identify sources and to better define areas for targeted response actions. Typically, the sampling

approach and design used within a single decision unit should meet specific objectives and not

attempt to mix multiple objectives (i.e., a SDU cannot also serve as a HDU). However, one or

more SDUs or other decision units can be identified within a HDU. Even if a HDU and an SDU

are co-located, they have been defined for distinct reasons and each should have its own DQOs

and sampling design. DQOs that clearly define the spatial boundary, types of decision units, and

the sampling unit can improve decision making by preventing delays commonly associated with

and exacerbated by insufficient or unrepresentative sampling.

To represent threatened or endangered (T&E) species or their critical habitat (for protection at

the individual level), the following HDU guidelines should be used for site screening:

For T&E plant and invertebrate species (i.e., mobility-restricted species), the HDU is the

size of the habitat patch where the plant or invertebrate occurs on the site.

For more mobile T&E species, the habitat evaluated and size of HDU should be based on

information specific to the T&E receptor, if available.

If information specific to the T&E receptor is unavailable, then the minimum-sized HDU

for small home range receptors (defined below) should be used to represent the T&E

species.

To represent species at the population level, specific terrestrial ecological receptors have been

identified for use in site screening and the HDU has a pre-defined size. The receptors include the

following:

Small Home Range Receptors (SHRs)

Vagrant shrew

American robin

Large Home Range Receptors (LHRs)

Long-tailed weasel

American kestrel

The HDU used for assessing receptors at the population level has a minimum size of 0.5 acres.

The 0.5-acre area is considered representative of home ranges for small birds and mammals, and

is based on the average home range of a female vagrant shrew. To represent a local population of


90

SHRs or to represent the home range of a LHR, multiple 0.5-acre HDUs can be sampled

separately, as single units, and the results combined through averaging to determine an EPC that

represents a larger HDU. Alternatively, a large HDU can be selected and sampled as a single unit

to calculate an EPC. Appendix B.1, Exhibit B provides recommended sampling approaches for

the HDU.

To identify contaminants of potential ecological concern, soil screening values provide a

valuable tool to rapidly assess a contaminated site. However, there is a large degree of

uncertainty in values typically used in screening. Values incorporating no- or low- observable

adverse effect levels (NOAELs/LOAELs) have inherent problems (see Appendix C), and often

result in screening values that are no different from background concentrations. However,

current Oregon Department of Environmental Quality (DEQ) cleanup rules require the use of

NOAEL-based values for assessing risk at the individual level. At the population level, DEQ

cleanup rules require the use of an ecological benchmark value (EBV), defined as the median

lethal dose or concentration (LD50/LC50) value, or other toxicological benchmarks adjusted to

equate to the LD50/LC50. DEQ rules further indicate that populations should meet an acceptable

risk level, which can be interpreted for convenience as a relatively low probability of exposure to

a contaminant. In order to meet the acceptable risk rule using sampling approaches that

incorporate incremental sampling methodology (ISM) as recommended in Appendix B.1. Exhibit

B, adjustments to result interpretation are typically required that are more complex than needed

for a Stage 2 assessment. Therefore, when ISM is used during Stage 2, it is recommended that

the EPC for a HDU is compared to an soil exposure estimate that incorporates the effective dose

or concentration (ECx/EDx) as the toxicity reference value (TRV), where x ≤ 20%. When

EC/ED-based exposure estimates are unavailable, then a LOAEL-based value can be used in its

place, based on the methodology used for the DEQ Terrestrial Ecological Risk-Based

Concentrations (RBCs) previously submitted to the Workgroup by DEQ. Soil exposure estimates

derived using ECx/EDx-based TRVs can be used to both screen contaminants of potential

ecological concern and screen a site in or out for further assessment. The ECx/EDx-based TRV is

expected to meet a low probability of exposure when x ≤ 20% and thus meet the intent of the

acceptable risk rule. If needed, additional assessment can be made during Stage 3 to assess

populations using the EBV. If a HDU is sampled using probabilistic discrete sampling (see

Appendix B.1. Exhibit B), then additional modeling can be completed using spatially-explicit

methods or the binomial equation previously used by DEQ to ensure the acceptable risk rule is

met.

When identification of contaminants of potential ecological concern is needed and information

from the conceptual site model is insufficient to identify the contaminants, the following is

recommended:

For T&E species, compare EPC within the HDU to NOAEL-based soil exposure

estimates, such as the RBC for bird and mammal T&E species or the lower of the two

values.


91

For populations, compare EPC within the HDU to LOAEL-based soil exposure

estimates, such as the RBC for non-T&E bird and mammal species or the lower of the

two values.

For screening a site to consider for further ecological assessment, the following is recommended:

For T&E species, compare EPC within the HDU to ECx/EDx-based soil exposure

estimates, where x ≤ 10% and data used to derive ECx/EDx-based exposure estimates

incorporate ingestion rates and body weights specific to the T&E receptor. When

receptor-specific information is unavailable, use values based on a surrogate receptor.

When ECx/EDx data are unavailable for surrogates, use LOAEL-based values such as

the RBChigh_est for bird and mammal T&E species.

For populations, compare EPC within the HDU to ECx/EDx-based soil exposure

estimates, where x ≤ 20% and data used to derive ECx/EDx-based exposure estimates

are based on a suitable surrogate SHR or LHR (such as species listed in Table 1).

When EC/ED data are unavailable for surrogates, use LOAEL-based exposure

estimates such as the RBCmean for bird and mammal non-T&E species. If the EPC for

populations is above the ECx/EDx-based estimates or RBCmean values, then consider a

target response action for the site or further site evaluation based on a local assessment

populationarea, as defined below.

Local Assessment Population Area Local population areas for use in risk assessment have been previously defined by Hope and

Peterson (2000) and Ryti et al. (2004) and others, and are used to define a spatial area where risk

assessment can be conducted at the population scale. The local assessment population area

(LAPA) identifies the boundary around habitat patches that will be considered in the risk

assessment in relation to the contaminated area. The LAPA is best defined using geographic and

anthropogenic features (physical boundaries) to determine and limit the size of the LAPA. When

these boundaries are not sufficient to limit an area, then the LAPA will differ depending on the

receptors being evaluated, as follows:

For T&E species, no LAPA needs to be identified because receptors are assessed at the

individual level, and the assessment area may be limited to the home range of the T&E

receptor.

For sessile or less mobile receptors, the LAPA includes all individuals within habitat

patches or inhabiting contaminated soil within the contaminated area.


92

For SHRs, the LAPA includes the habitat patches within a four-acre area, calculated

based on median dispersal distance and body size estimated for a small home range

receptor (explained below).

For LHRs, the assessment area will be the home range (typically the 50% core use area or

smallest average home range) for a LHR (explained below).

Table 1. Home range size and population assessment areas for small and large home range

receptors.

Receptor Receptor home range (core areasa,

range during breeding or nesting, or

smallest reported average home range)

Assessment population

area

Small Home Range Receptor

Vagrant Shrew 0.22 hab (0.55 ac) female breeding

0.10 hab (0.26 ac) male and female

average during non-breeding

5 acre

2.6 acre

American Robin 0.12 hac (0.30 ac) adult breeding 3 acre

Large Home Range Receptor

Long-tailed Weasel 5.3 had (13 ac) female core area 13 acre

American Kestrel 13 hae (32 ac) adult male winter 32 acre

Red-tailed Hawk 85 haf (210 ac) female spring 210 acre

a Core areas defined in Samuel et al. (1985) and Clapp and Beck (2015).

b Average from Hawes (1977)

c Average from Young (1951).

d Female core area (Hajduk 2008).

e Adult male kestrel wintering is range used for representing the smallest available average range because female breeding range is

unreported (Meyer and Balgooyen 1987).

f Average from Petersen (1979).

The LAPA for SHRs can be estimated in a number of ways (see Appendix B.1 and B.2). For

example, Appendix B.1 describes estimating a LAPA of four acres based on natal dispersal of a

vagrant shrew (body weight of 0.007 kg, median natal dispersal distance of 0.07 km) using a

dispersal model by Santini et al. (2013). In this case, the four-acre LAPA based on shrew

parameters is assumed to be also representative of small home range birds such as robins due to

similar characteristics of small body size and home range sizes. Home range size averages about

0.55 acres for breeding female vagrant shrews (Hawes 1977) and 0.30 acres for robins (Young

1951). The four acres is considered representative of the LAPA for both robins and shrews even


93

though robins may use the habitat within the LAPA differently than shrews (i.e., a number of

robins may congregate and forage intensively in one particular area within the LAPA and then

fly off to another area that could be outside the LAPA). Alternatively, a five-acre LAPA could be

defined and justified as described in Appendix B.2 based on using a generic value of 10 times the

home range. The remaining example below will be described using a four-acre LAPA, but the

principle is the same regardless of LAPA size.

The four-acre LAPA is divided into eight separate 0.5-acre HDUs or, alternatively, the entire

four-acre area can be considered one population-based HDU if sampled appropriately (such as

with ISM or with the appropriate number and location of discrete samples). For ISM samples,

the EPC for SHRs is calculated by combining average contaminant concentrations from the eight

HDUs, or is the average contaminant concentration from the entire four-acre HDU, and is

screened against screening levels described in the previous section for shrew and robin. If

discrete sampling is used, then the EPC is represented by the 90% upper confidence limit (UCL)

of the average concentration within each of the 0.5-acre HDUs, or is the 90% UCL of the entire

four-acre HDU if sampled as one unit. If the contaminated area or locality of facility is smaller

than four acres, or there is evidence from the CSM to strongly indicate that specific areas within

the LAPA would not be within the area of contamination, then a population area use factor

(PAUF) can be incorporated rather than sampling the entire LAPA. A PAUF is the proportion of

uncontaminated area within the LAPA. In these cases, an EPC can be weighted by the proportion

of 0.5-acre HDUs that are not within the contaminated area in the LAPA. For example, if there

are two uncontaminated 0.5-acre HDUs within a four-acre LAPA, then the EPC for the LAPA is

multiplied by the PAUF which represents 25 percent of the LAPA that is uncontaminated. If

neighboring contaminated sites exist or are suspected to exist within a LAPA that have not been

suitably sampled, then the EPC is screened using the sampled HDUs within the LAPA (or the

single average from the entire sampled portion of the LAPA).

The Stage 2 process for screening wider ranging species (i.e., a LHR) is similar to SHRs except

the assessment area is delineated by either the smallest average home range or the core-use area

(from distribution-based home range models) for the long-tailed weasel and American kestrel

(Table 1). This home range frames the size and boundary where HDUs will be sampled (or the

area can be considered one HDU if sampled appropriately). For LHRs, a LAPA is not calculated

due to the differences in use of spatial areas for larger receptors (Hope and Peterson 2000) and

assumptions about off-site exposure for these receptors would be too speculative to rely on in

Stage 2. The area within the home range of these receptors is apportioned into multiple 0.5-acre

HDUs, and sampled in the same manner as for SHRs (see Appendix B.1 and B.2). Alternatively,

the entire home range can be evaluated as a single HDU if sampled appropriately.

If the entire range of the LHR does not incorporate the entire contaminated area or locality of

facility, then area use factors (AUFs) can be used to weight the EPC in the same manner that

PAUFs are used for SHRs. The AUF represents the proportion of the uncontaminated area that is

within the LHR’s core use area (i.e., the proportion of 0.5-acre HDUs that are not within the


94

contaminated area). If neighboring contaminated sites exist or are suspected to exist within the

home range that have not been suitably sampled, then the EPC is screened against the sum of the

sampled and contaminated HDUs within the home range (or the single average from the entire

sampled portion of the home range).

For T&E receptors, the home range (core use area or smallest home range available) specific to

the T&E receptors is the area used to compare EPCs to individual level-based screening values.

If T&E receptor information on home range is unavailable, then American kestrel or long-tailed

weasel can be used as surrogates, incorporating appropriate adjustment factors if needed. For

non-T&E LHRs, the EPCs are compared to population level-based screening levels for long-

tailed weasel and American kestrel.

For any screening assessment on a receptor group (i.e., T&E receptors, SHRs, or LHRs), an EPC

lower that the screening level would result in a no further ecological risk assessment action,

whereas an exceedance would mean a targeted response action or continuation into the next

phase (Stage 3) of risk assessment.

Prey Tissue

It should be noted that during any part of the Stage 2 assessment, tissue from prey items such as

earthworms is encouraged to be collected to better address availability of contaminants, or to

compare to tissue-based screening levels. Prey tissue should be collected within HDUs and

associated with soil samples if possible to determine a soil to tissue accumulation factor

(provided both soil and tissue are collected appropriately). In cases where tissue screening levels

are available (based on NOAEL or LOAEL or ECx/EDx values) and tissue is collected

representatively within a HDU, then tissue screening levels will have higher priority and

importance than soil screening values.

Case Example for Evaluating Contaminated Soil

The method described above was used to evaluate decision units previously established at

Willamette Cove (located along the lower Willamette River at river mile 7) for the purpose of

screening contaminants in soil for SHRs. Although actual soil sample data were used in the

example, the size and location of the decision units have been modified and the results do not

reflect actual EPCs or decisions that were made at the site. The data from these examples were

primarily discrete data, although some ISM samples were collected in these decision units and

are reported here as well. Contaminants evaluated included chromium, copper, lead, and zinc.

Figure 1 shows two four-acre decision units (LAPAs), DU1 (green) and DU2 (blue) and

individual samples within the decision units. The orange area in LAPA-2 represents three 0.5-

acre HDUs within the LAPA that are considered “outside the facility” and uncontaminated for

purposes of this example. It should be noted that the number or location of the discrete soil

samples within the decision units do not follow recommended guidance for characterizing a

decision unit as described in Appendix B.1. Exhibit B, but are used in this example because the


95

data represent actual concentrations within the area. In Figure 1, each LAPA is represented with

an EPC calculated based on the 90% UCL for the entire four-acre LAPA. Figure 2 shows the

same two LAPA decision units, but each unit has been divided into eight 0.5-acre HDUs

(numbered one through eight in the figure) that are sampled separately. In this case, the average

concentration from each of the eight HDUs is used to estimate a 90% UCL for the entire LAPA.

For this example, the sample results within each HDU are considered an average for the HDU.

This approach is recommended when information is needed on smaller areas within the HDU,

such as conducting a targeted response action on a specific HDU, and is an especially useful

approach when using ISM (see Figures 3 and 4 for an example of a gridded sampling design that

would be used for characterizing HDUs using ISM). For both examples (Figures 1 and 2), the

uncontaminated area within LAPA-2 is used to weight the EPC before comparing to screening

levels, as shown in Table 2 (when using the approach which entails sampling the entire LAPA as

a decision unit) and Table 3 (when delineating and sampling individual HDUs).

The example shows that using the PAUF approach allowed zinc HDUs to pass screening (Table

3), whereas additional assessment of zinc would have been otherwise needed if the PAUF was

not applied in the assessment (Table 2).

Table 2. Comparison of exposure point concentrations (EPCs), calculated using the entire four-acre

local assessment population area (LAPA), to screening levels for soil sample data collected from

the Willamette Cove along the lower Willamette River. In this example the entire LAPA is sampled

as one population habitat decision unit (i.e., all samples within the four-acre unit are used to

calculate one EPC to compare to screening levels). The EPC for LAPA-1 is determined based on

contamination within the entire area, and the EPC for LAPA-2 is based on a weighted approach

because a portion of the area within the LAPA is without contamination and outside the locality of

facility (Figure 1). All values are in mg/kg dry weight.

EPCa Back-

groundb

Screening Levelsc EPCa

90% UCL 95% UPL RBC EcoSSL DEQ ISM Result

LAPA-1d, 4 acres, 9 discrete samplese, all within contaminated area

Chromium 25.3 76 160 26 20 16.1

Copper 140 34 82 28 950 293

Lead 504 79 26 11 80 310

Zinc 418 183 610 46 125 238

LAPA-2d, 4 acres, 7 discrete samplese, not all within contaminated area

Chromium 55.1 x 3/8=20.7f 76 160 26 20 11.7

Copper 926 x 3/8=347f 36 82 28 950 404


96

Lead 529 x 3/8=198f 79 26 11 80 164

Zinc 603 x 3/8=226f 183 610 46 125 187

a Exposure point concentration (EPC) for LAPA-1, and weighted EPC for LAPA-2, calculated within a four-acre decision unit at

Willamette Cove. The EPC was reported for discrete samples as the 90% upper confidence limit (UCL) as calculated by ProUCL

software version 5.1 (values reported are the 90% Student’s-t UCL based data size, apparent distribution, and skewness as

recommended by the software, although the software indicated sample size for all samples were too small (i.e., <10 samples) to

evaluate data distribution or run reliable statistics). The EPC value was also determined using incremental sampling methodology

(ISM) within a 5-acre area that encompasses the 4-acre LAPA. ISM results should not be directly compared to discrete results but

can be compared to screening levels.

bBackground concentrations are the 95% upper prediction limit (UPL) in soil samples from the Portland Basin (DEQ 2013).

Background concentrations are compared to individual sample points, and if any sample value is above the background value then

the site is above background.

cScreening levels included risk-based concentrations(RBCs) determined using mean ingestion rate values from draft document

previously submitted to the Workgroup, the U.S. Environmental Protection Agency’s (EPA 2017) Ecological Soil Screening values

(EcoSSLs), and the Oregon Department of Environmental Quality’s (DEQs) ecological risk screening values reported from Table 1

(DEQ 1998) for populations.Values in parentheses are the lower of the bird or mammal screening value. Screening level values with

red highlight indicate samples from the site exceeded background and the EPC exceeded the screening level (failed screening);

yellow indicates EPC exceeded the screening level but all samples were below background value (passed screening), and no

highlight indicates samples may have been below or above background buy EPC was below the screening level (passed screening).

dThe local assessment population area (LAPA) used in this example is four acres based on dispersal assessment for vagrant shrews.

e It should be noted here that ProUCL software recommends a sample size greater than 10 and preferably more than 20 to calculate

UCLs, but too few samples were available for this particular example. Appropriate sample size and location of samples within

decision units are discussed in Appendices B.1 (Exhibit B) and B.2. The location and number of samples shown in this example

should not be considered part of a recommended sampling approach.

f There are 1.5 acres of uncontaminated area within the LAPA (equivalent to three 0.5-acre HDUs) that is outside the area of

contamination for the facility. Therefore, the EPC is weighted by the population area use factor (PAUF), which is the proportion of

uncontaminated HDUs (in this case 3) over the total number of possible HDUs (i.e.,8) within the four-acre contaminated area (see

Figure 1, LAPA-DU2).


97

Table 3. Comparison of exposure point concentrations (EPCs), calculated by first delineating eight habitat decision units (HDUs)

within each four-acre local assessment population area (LAPA), to screening levels for soil sample data collected from the

Willamette Cove along the lower Willamette River. In this example the eight 0.5-acre HDUs are sampled within the LAPA before

calculating a 90% upper confidence limit using the eight average values. The EPC for LAPA-1 is determined based on

contamination within the entire area, and the EPC for LAPA-2 is based on a weighted approach because a portion of the area (three

HDUs) within the LAPA is without contamination and outside the locality of facility (Figure 2). All values are in mg/kg dry

weight.

Habitat Decision Unit

1 2 3 4 5 6 7 8 EPCa PAUFb

Weighted EPCc

(PAUF x EPC)

BKDd

RBCe SL

LAPA-1f, 4 acres, average of all samples within an HDUg, all within contaminated area

Chromium 18.9 19.

3

14.

4

38.

3

18.

7

27.

8

11 26.

3

26.2 8/8 1 x 26.2 = 26.2 76 160

Copper 81.4 102 33.

6

273 50.

4

226 34.

6

35.

2

151 8/8 1 x 35.2 = 151 36 82

Lead 280 636 111 755 175 820 35.

6

280 539 8/8 1 x 539 = 539 79 26

Zinc 228 461 148 740 137 387 159 475 449 8/8 1 x 449 = 449 183 610

LAPA-2f, 4 acres, discrete samplesg, not all within contaminated area

Chromium 63.8 35.

7

25.

8

18.

3

68.

6

NC NC NC 57.9 3/8 0.375 x 57.9=21.7 76 160

Copper 121

7

708 182 121 744 NC NC NC 904 3/8 0.375 x 904=339 36 82

Lead 539 532 376 322 468 NC NC NC 513 3/8 0.375 x 513=192 79 26

Zinc 740 510 262 154 623 NC NC NC 626 3/8 0.375 x 626=235 183 610


98

a Exposure point concentration (EPC) calculated within a four-acre decision unit at Willamette Cove. The EPC was reported for discrete samples as the 90%

upper confidence limit (UCL) of the average values within each decision unit, as calculated by ProUCL software version 5.1 (values reported are the 90%

Student’s-t UCL based data size, apparent distribution, and skewness as recommended by the software, although the software indicated sample size for all

samples were too small (i.e., <10 samples) to evaluate data distribution or run reliable statistics).

b Population area use factor (PAUF) represents the proportion of the area that is uncontaminated (in this case, the proportion of 0.5-acre habitat decision units

that are uncontaminated or below screening levels within the 4-acre LAPA). The PAFU is one (8/8) for LAPA-1 because all areas are within the facility and

potentially contaminated, whereas the PAUF for LAPA-2 is 0.375 (3/8) because the HDUs are outside the facility or uncontaminated.

c Weighted EPC is the EPC multiplied by the PAUF and is compared to the screening level. The bolded number is the final EPC value used for screening.

dBackground (BKD) concentrations are the 95% upper prediction limit in soil samples from the Portland Basin (DEQ 2013).Background concentrations are

compared to individual sample points, and if any sample value is above the background value then the site is above background.

e The screening level (SL) used for this example is the risk-based concentrations (RBCs based on mean ingestion rate values) from draft document previously

submitted to the Workgroup. Red shading indicates the weighted EPC was above the SL and “Failed” screening, whereas no shading indicates the weighted

EPC was below the SL and “Passed” screening.

f The local assessment population area (LAPA) used in this example is four acres based on dispersal assessment for vagrant shrews.

g It should be noted here that ProUCL software recommends a sample size greater than 10 and preferably more than 20 to calculate UCLs, but too few

samples were available for this particular example. Appropriate sample size and location of samples within decision units are discussed in Appendices B.1

(Exhibit B) and B.2. The location and number of samples shown in this example should not be considered part of a recommended sampling approach.


99

Figure 1. Four-acre local assessment population area (LAPA) decision units (LAPA- DU1 in green and DU2 in blue) derived to assess soil contamination at

Willamette Cove along the lower Willamette River. Red dots with black centers indicate soil sample locations. The orange area with LAPA-DU2 represents

three 0.5-acre habitat decision units that are outside the contaminated area of the facility (for purposes of this example).


100

Figure 2. Four-acre local assessment population area (LAPA) decision units (LAPA- DU1 in green and DU2 in blue) derived to assess soil contamination at

Willamette Cove along the lower Willamette River. Red dots with black centers indicate soil sample locations. Each LAPA in this example is delineated into

eight numbered habitat decision units (HDUs). The orange area with LAPA-DU2 represents three 0.5-acre HDUs that are outside the contaminated area of the

facility (for purposes of this example).


101

Figure 3. Sample coverage using Incremental Sampling Methodology on each four-acre local assessment population area (LAPA) decision units (LAPA- DU1 in

green and DU2 in blue) derived to assess soil contamination at Willamette Cove along the lower Willamette River. Symbols within each LAPA indicate sample

location for collection of an increment. Increment location within each LAPA is based on 60 increments applied to a triangular grid with random start of first

location. The analysis of the 60 increments, combined into a single ISM sample analysis, represents the average contaminant concentration for the entire LAPA.

This average concentration can be directly compared to screening levels. The grayish area with LAPA-DU2 represents three 0.5-acre habitat decision units that

are outside the contaminated area of the facility (for purposes of this example).


102

Figure 4. Sample coverage using Incremental Sampling Methodology on each of eight habitat decision units (HDUs) within four-acre local assessment

population area (LAPA) decision units (LAPA- DU1 in green and DU2 in blue) derived to assess soil contamination at Willamette Cove along the lower

Willamette River. Symbols within HDU indicate sample location for collection of an increment. Increment location within each HDU is based on about 30

increments applied to a triangular grid with random start of first location. The analysis of the 30 increments, combined into a single ISM sample analysis,

represents the average contaminant concentration within each HDU. The eight average results can be used to calculate an average or 90% upper confidence limit

within the LAPA. This average concentration can be directly compared to screening levels. The grayish area with LAPA-DU2 represents three 0.5-acre habitat

decision units that are outside the contaminated area of the facility (for purposes of this example).


103

References Clapp, J.G., and J.L. Beck. 2015. Evaluating distributional shifts in home range estimates.

Ecology and Evolution5:3,869-3,878.

DEQ (Oregon Department of Environmental Quality). 1998 (updated 2002). Guidance for

ecological risk assessment: Levels I, II, III, IV. Waste Management and Cleanup Division,

Cleanup Policy and Program Development Section. Portland, Oregon.

DEQ. 2013. Development of Oregon background metals concentrations in soil.Land Quality

Division, Cleanup Program. Portland, Oregon. 35 pp.

Hajduk, L.I. 2008. Space use and habitat selection of long-tailed weasels (Mustela frenata) in

southern Illinois.M.S. Thesis, Southern Illinois University at Carbondale. 50 pp.

Hawes, M.L. 1977. Home range, territoriality, and ecological separation in sympatric shrews,

Sorex vagrans and Sorex obscurus Journal of Mammalogy58:354–367.

Hope, B.K., and J.A. Peterson. 2000. A procedure for performing population-level ecological

risk assessments. Environmental Management 25:281-289.

Meyer, R. L., and T.G. Balgooyen. 1987. A study and implications of habitat separation by sex

of wintering American kestrels (Falco sparverius L.). Raptor Research 6:107-123.

Petersen, L. 1979. Ecology of great horned owls and red-tailed hawks in southeastern Wisconsin.

Wisconsin Department Natural Resources Technical Bulletin Number 111. Madison, Wisconsin.

64 pp.

Ryti, R. T., J. Markwiese, R. Mirenda, and L. Soholt. 2004. Preliminary remediation goals for

terrestrial wildlife. Human and Ecological Risk Assessment 10:437-450.

Samuel, M. D., D. J. Pierce, and E. O. Garton. 1985. Identifying areas of concentrated use within

the home range. Journal of Animal Ecology 54:711-719.


correlates of dispersal distance in terrestrial mammals. Hystrix, the Italian Journal of

Mammalogy 24:6.

U.S. Environmental Protection Agency (EPA). 2006. Guidance on systematic planning using the

data quality objectives process. EPA QA/G-4.Office of Environmental Information, Washington,

D.C.

EPA. 2017. Ecological soil screening level (Eco-SSL) guidance and documents.

https://www.epa.gov/risk/ecological-soil-screening-level-eco-ssl-guidance-and-documents.

Accessed February 9, 2017.

Young, H. 1951. Territorial behavior in the eastern robin. Proceedings of the Linnaean Society of

New York. Number 58-62:1-37.

https://www.epa.gov/risk/ecological-soil-screening-level-eco-ssl-guidance-and-documents


104


Appendix C: Selection of Toxicity Reference Values and Development of Ecological Benchmark Values

The Oregon Department of Environmental Quality (DEQ) convened the Ecological Risk Assessment

(ERA) Technical Workgroup to provide input to the Cleanup Program on efforts to revise current ERA

guidance. The Terrestrial ERA Subgroup (Subgroup) was formed with the task of providing

recommendations to the Workgroup for additions or revisions to the Oregon ERA guidance. This

appendix describes recommendations for identifying and using information from the scientific literature

to develop toxicological benchmarks for use in assessing risk to terrestrial ecological receptor groups.

Section 1 summarizes the method for identifying toxicity reference values (TRVs) for use in updating

Oregon DEQ Level II ERA screening levels. Section 2 offers recommendations for future development

of ecological benchmark values (EBVs) using a methodology that is more rigorous, data intensive,

amenable to updating as new data become available, and consistent with the level of protection

stipulated in OAR 320-120-0115 (21). Once they have been developed, these EBVs should be used in

Stages 2 and 3 of the proposed 3-stage ERA process.When an EBV is used in the process, then

additional evaluations must be conducted to show how the analysis meets the acceptable level of risk for

populations of ecological receptors as defined in rule.

Many TRVs used in ERA are based on no-observed-adverse-effect levels (NOAELs) or lowest-

observed-adverse-effect levels (LOAELs). The development of point estimate TRVs based on NOAELs

or LOAELs has been widely criticized. For example, NOAEL and LOAEL values may not be associated

with biologically relevant threshold responses, do not provide information about the magnitude of

effects, and are significantly influenced by study design (e.g., dose/concentration intervals, replication,

and statistical power). Alternative TRVs based on dose/response relationships avoid some of the

problems associated with reliance on NOAELs or LOAELs. TRVs based on an effective dose (EDx)

where x refers to an acceptable effect level would be preferable to those based on NOAELs or LOAELs.

However, for many chemicals, insufficient information is available to develop robust EDx estimates. For

practical reasons, TRVs discussed below are based on more plentiful NOAEL and LOAEL values. If

sufficient data are available, we recommend deriving TRVs using an EDx approach. Guidance would

need to be developed defining the acceptable effect level and other aspects of EDx derivation.

Source Hierarchy for Selection of Toxicity Reference Values

Toxicity reference values (TRVs) for wildlife species are typically doses of environmental contaminants

that represent exposure that are not expected to result in ecologically adverse effects on the target

species. TRVs are used during the ERA process to evaluate whether site-specific exposure may

represent unacceptable risk to wildlife receptors. For the Oregon ERA process, TRVs are being used to


105


develop Soil Screening Levels (SSLs) and/or Ecological Benchmark Values (EBVs) for the Stage II

analysis, and will allow direct comparison of data on contaminant concentrations in site media to

evaluate risk.

This appendix describes the process used in selecting TRVs to update SSLs for wildlife receptors. TRVs

for aquatic receptors, plants, and invertebrates will be developed separately. The recommended process

is to evaluate TRVs from the scientific literature, and identify values for use in developing SSLs or

EBVs. Identification and use of TRVs is common practice in ERAs, and multiple databases representing

compilations of information from primary scientific literature are available. To date, the most

comprehensive compilation was prepared by the US Environmental Protection Agency (EPA) for

calculating Ecological Soil Screening Values (Eco-SSLs, EPA 2005). EPA’s process includes a

compilation and evaluation of studies from the primary toxicological literature, standard evaluation and

scoring of the study design and data quality. Studies were scored and a minimum score was established

for use of the results in developing TRVs for the Eco-SSLs.

Eco-SSL documents are available for 23 chemicals, including mostly metals but also polyaromatic

hydrocarbons (PAHs) and some chlorinated pesticides. Other environmental databases are used as the

primary source of TRVs for the chemicals for which Eco-SSLs were not available. Data from the Eco-

SSL documents are used according to the following hierarchy:

No-observed-effects-levels (NOAELs) derived by EPA are identified for use in individual-based risk

analysis for threatened/endangered species. Where EPA identified NOAELs as the geometric mean

(geomean) of candidate studies, the value is used unaltered. If the NOAEL TRV identified for EcoSSL

was from an individual study, that value is used.

LOAELs are calculated from the same database of information. LOAELs are developed as follows:

1. If EPA selected a geomean of the growth and reproduction endpoints for the NOAEL, then the

geomean of growth and reproduction LOAELs is calculated and selected for the LOAEL.

2. If EPA selected a specific study as the NOAEL based on an analysis of bounding (EPA 2005,

Appendices D and E), then the LOAEL is selected from the same study as the NOAEL.

3. If a NOAEL geomean was not calculated and a LOAEL was not available from the study of

the selected NOAEL, then the geomean of available LOAELs for growth and reproduction are

selected as the LOAEL.

For chemicals not evaluated for the Eco-SSLs, NOAELs and LOAELs are taken of the compilation

prepared for Oak Ridge National Laboratory (Sample, et al., 1996). The values used are taken from

Appendix A of Sample et al, 1996, which presents the TRVs calculated directly from the original studies;

i.e., no body size or physiological scaling factors were applied. Where TRVs are not available in either of

the above sources, a literature search is conducted using secondary and primary literature sources.

Secondary sources included TRVs that have been approved by EPA and/or DEQ in other ERAs in Oregon,

such as the Portland Harbor Baseline Ecological Risk Assessment (Windward Environmental 2013).


106


In most cases, direct measures of NOAELs and/or LOAELs for specific COCs are not available for the

representative species used in the ESL development. Since sensitivity to chemicals can vary among

species, DEQ incorporates uncertainty factors to avoid underestimating risk of toxicity for more

sensitive species. The feeding guild use factors are also selectively applied to Eco-SSL TRVs taken from

individual studies (but that are selected by EPA according to Eco-SSL rules). Uncertainty factors are

not applied to Eco-SSL TRVs based on geometric means of multiple studies for growth, survival, and

reproduction (for NOAEL or LOAEL).

Recommended for Future Development of Ecological Benchmark Values

The subsection above summarized the method for identifying TRVs for use in updating Oregon DEQ

Level II ERA screening levels. The following provides a recommended approach for developing wildlife

EBVs. These EBVs, along with an analysis that meets the acceptable risk rule, will be appropriate for

using in Stages 2 and 3 of the proposed three-stage Oregon ERA process. The purpose of this section is

to facilitate the adoption of an EBV development approach that a) fully utilizes the available

ecotoxicological data b) is consistent with OAR 320-120, and c) provides incentives for filling important

data gaps.

OAR 320-120-0115 (21) defines the EBV as either the highest NOAEL for individual ecological

receptors considering effects on reproductive success or the median lethal dose or concentration (LD50

or LC501) for populations of ecological receptors. By OAR 320-120-0084, risk estimates are to be

made:

At the level of the individual for species present in the locality of the facility if the species is

listed as threatened or endangered species pursuant to 16 U.S.C. 1531 et seq. or ORS 496.172

At the level of the population for all other plants or animals in the locality of the facility

Although OAR 320-120-0115 (21) defines the EBV for populations as an LD50 or LC50, inclusion of a

median effect dose or concentration (ED50 of EC50) for reproductive effects should be considered.

Chemicals such as DDx can cause adverse effects on reproduction at much lower exposure levels than

those associated with mortality effects, and adverse reproductive effects have the potential to influence

population dynamics. Guidance will need to be developed clarifying the types of reproductive effects

likely to be closely correlated with individual fitness that would be used in ED50 or EC50 derivations.

To be consistent with the current rule definition, the discussion below focuses on use of LD50 or LC50

values in EBV derivation.

1 LD50 and LC50 are the dose and concentration respectively that elicit 50% mortality in the test population. The LD50 or LC50 has been established by rule as the primary ecological benchmark value (EBV) for populations of ecological receptors. When using an EBV in the process, evaluations must be conducted to show how the analysis meets the acceptable level of risk for populations of ecological receptors as defined in rule.


107


If a NOAEL, LD50 or LC50, as applicable, is not available for the ecological receptors considered in a

risk assessment, then EBV may be derived from other toxicological endpoints for those receptors or

appropriate surrogates for those receptors, adjusted with uncertainty factors to equate to a NOAEL,

LD50 or LC50. It is to be based, to the extent practicable, on studies whose routes of exposure and

duration of exposure are commensurate with the expected routes and duration of exposure for ecological

receptors considered in the risk assessment, or appropriate surrogates for those receptors. As

recommended by Allard et al. (2009), any uncertainty factors incorporated into an assessment should be

scientifically supported, and generic uncertainty factors (such as those based on 10-fold reductions)

should not be used.

Approach

The proposed approach for wildlife EBVs is to use benchmark dose (or concentration)2 thresholds for all

chemicals of potential concern (COPCs), to the extent that toxicological data are sufficient. The

proposed benchmark dose threshold approach involves the derivation of dose-response curves and LD50

values based on the primary literature. This approach has been described in recent scientific literature

(Mayfield et al. 2013; Allard et al. 2009) and EPA guidance (EPA 2012). It has been used in previous

ecological risk assessments in the Pacific Northwest (e.g., for the derivation of TRVs in the Coeur

d’Alene baseline ecological risk assessment (BERA) (CH2M HILL and USR Corp. 2001) and for

evaluation of PCBs and mink the Portland Harbor BERA (Windward 2013). This approach is

recommended over the LOAEL approach3 because LOAELs correspond to inconsistent response levels

across studies, endpoints and chemicals (EPA 2012).

Step 1. Compile ecotoxicological data

The first step in the EBV approach is to compile all relevant and appropriate wildlife ecotoxicity data.

The work group recommends that these data be compiled in a DEQ database. This database should be

updated whenever new relevant and appropriate ecotoxicity data are obtained through the State’s ERA

process, and that the ERA process be designed to handle frequent updates.

The studies used to derive the EPA’s Eco-SSLs (EPA 2005) are based on an extensive search and

review of the ecotoxicological literature. The work group recommends that the studies used to derive

Eco-SSLs should be the starting point for the DEQ wildlife ecotoxicity database. The database should

over time be supplemented with additional relevant wildlife ecotoxicity data, including datasets that

have become available since the Eco-SSL database was developed and datasets that will be developed in

the future.

The quality assurance and quality control (QA/QC) process for determining ecotoxicity data

acceptability should be reasonable and definitive, so that it does not fall on regulatory project managers

(RPMs) to make judgments about data acceptability. Again, Eco-SSL provides a good starting point for

2Henceforth we use the terms “benchmark dose” and “LD50,” as shorthand for “benchmark dose or concentration” and “LD50 or LC50.”

3 The LOAEL approach is what is currently used by DEQ to develop TRVs.


108


defining data acceptability criteria. The work group recommends that a detailed process for periodically

updating and refining data acceptability criteria be developed and included in DEQ’s ERA guidance.

The responsible parties who are engaged in DEQ ERAs should have the option of a) using the DEQ’s

wildlife ecotoxicity database, b) conducting a literature review to supplement and update the DEQ’s

wildlife ecotoxicity database, and/or c) generating new data to supplement and update DEQ’s wildlife

ecotoxicity database. Updates to DEQ’s wildlife ecotoxicity database should be permanent, so that

subsequent ecological risk assessments are always using EBVs based on the most up-to-date DEQ

wildlife ecotoxicity database.

Not all of the datasets in DEQ’s ecotoxicity database will be suitable for developing dose-response

relationships because not all ecotoxicity studies are successful in measuring multiple response levels.

Only those datasets that meet the criteria for inclusion in benchmark dose evaluation (Step 2 below)

should be used to determine dose-response curves. Uses for data from datasets that meet data

acceptability criteria, but are not suitable for developing dose-response relationships, will be discussed

below.

For some COPCs, at least initially, none of the datasets in DEQ’s ecotoxicity database will be suitable

for developing dose-response relationships. In these cases, other methods for estimating the LD50 or

LC50 should be evaluated. At this point the work group has not formally defined these other methods

and how they are to be used. We recommend that DEQ convene a follow-up panel of experts to do that,

and that these methods be spelled out in DEQ’s updated ERA guidance. These methods might include

using information from across studies and across COPCs to estimate the slope of the dose-response

curve and extrapolate to the LD50 from a LOAEL, using information from across studies and across

COPCs to develop a relationship between mortality and another test endpoint (e.g., growth or

reproduction). If no reliable LD50 can be derived, the work group recommends that the responsible

party be given two options:

Select a LOAEL as a surrogate for the LD50. This should be the LOAEL that provides the best

estimate of the LD50. It will not necessarily be the lowest LOAEL. The magnitude of effect at

that LOAEL relative to the LD50 should be discussed as part of the ERA’s risk characterization.

Obtain new data, either through a review of the recent peer-reviewed literature or by generating

new ecotoxicity datasets.

Step 2. Define the wildlife ecotoxicity datasets for benchmark dose evaluation

Benchmark dose evaluation is a procedure for estimating LDx (in this case LD50) by fitting dose-

response curves to ecotoxicity datasets, then selecting an EBV from among the derived LD50 values. As

noted above, ecotoxicity datasets that are suitable for fitting dose-response curves are not currently

available for some chemicals, in which case alternative methods will have to be used to estimate the

LD50. This section is about establishing which wildlife ecotoxicity datasets are suitable for benchmark

dose evaluation.

The appropriate wildlife ecotoxicity datasets will be defined as follows:


109


Only peer-reviewed studies measuring mortality will be used

Toxicity studies using dietary exposures to represent the dietary exposure pathway will be used

preferentially; other modes of exposure (i.e., gavage, drinking water, injection) will be

considered only if dietary exposures are unavailable. The uncertainties of extrapolation of these

routes of exposure to dietary ingestion must be discussed in the ERA if they are used.

Only controlled toxicity studies that used standardized and/or peer-reviewed experiment

methods, in which a clear concentration- or dose-response relationship was reported over the

control and dose levels evaluated, will be used. This principle generally excludes field studies,

except in some situations were laboratory data are unavailable, or specific sensitive endpoints are

in question (e.g, field studies evaluating eggshell thinning or egg mortality associated with DDE

or other organochlorine compounds).

Only toxicity studies based on single chemical exposure (except for specific chemical mixtures,

such as PCBs or chemicals with similar modes of action like dioxin and furans) will be used.

This principle generally excludes field studies, unless there is a specific sensitive endpoint where

data are not available based on laboratory studies. For mercury and selenium, studies based on

exposure to organic forms (environmentally relevant forms for dietary exposure) will be

preferred over inorganic forms.

Toxicity studies using domestic species for the evaluation of egg production will not be used

directly for setting EBVs, as these domestic birds have indeterminate egg-laying rates relative to

wild bird species where clutch size is typically determinate. Other endpoints (e.g., infertility,

eggshell thinning, egg desiccation, embryo death, etc.) from these studies that meet the other data

acceptability criteria would be considered, and egg production endpoints might be used, in

combination with other endpoints, as part of a larger body of information that might inform EBV

selection.

The ecotoxicity datasets for dose-response development will include only the following types of

studies:

o Studies conducted over a chronic (≥10 wks for birds, ≥1 yr for mammals (Sample et al.

1996)) duration or critical life stage (reproductive period)

o Studies with tested dose levels resulting in a dose-response that allows for curve-fitting

(see Step 3)

Step 3. Determine LD50 based on dose-response curves

EBVs should be determined based on a benchmark dose approach for each COPC for birds and

mammals separately, as follows:

On a study-specific basis, develop dose-response curves based on all the dose levels and

magnitude of effect reported.

On a study-specific basis, derive a dose-response curve and identify the LD50 using a statistical

program such as EPA’s Toxicity Relationship Analysis Program (TRAP) interface which fits an

effects versus exposure relationship based on toxicity data

(http://www.epa.gov/med/Prods_Pubs/trap.htm)

Provide confidence intervals for dose-response curves

http://www.epa.gov/med/Prods_Pubs/trap.htm


110


Select the lowest LD50 as the EBV

Receptor-specific LD50s may be selected if sufficient data are available for a selected receptor

species (e.g., shrew) and/or receptor feeding guild (e.g., herbivores, invertivores). A range of

LD50s may also be considered if sensitivities vary widely across species

Additional Considerations

Data selected for TRV development should not include use of allometric scaling, use of generic

uncertainty factors (such as 10-fold reductions) in lieu of scientifically supported uncertainty

factors, extrapolating across taxonomic classes, extrapolating between species, or extrapolating

chronic TRVs from acute data without scientific support (based on recommendations from

Allard et al. 2009).

Data should be included in the database that measures an acceptable reduction in endpoint

performance (not necessarily limited to mortality, reproduction, and growth) relative to the

negative control for the purposes of deriving an EDx or ECx value, as recommended by Allard et

al. (2009). Rather than using at LOAEL value, it may be preferably to simply plot dose–response

data using a scatterplot and use the underlying relationship to select a TRV. With this method,

the dose–response relationship can at least help address uncertainty and possible implications of

exposure to doses exceeding the TRV.

Bioavailability should be considered in Stage 3 as part of the exposure estimate rather than the

EBV, considering relative bioavailability from the general literature. Examples of literature-

based bioavailability (as bioaccessibility estimates) are presented in Sample et al. (2013).

Relative bioavailability estimates account for the bioavailability expected at a site relative to the

bioavailability of the contaminant (e.g., metal salt) used in laboratory studies on which the EBV

is based.

This recommended approach focuses on the development to EBVs for birds and mammals, for

which ecotoxicity data are relatively more abundant. Amphibians and reptiles are also potential

receptors. In general, there are limited ecotoxicity data for amphibians and reptiles. The

following sources should be considered if it is deemed necessary to include amphibian or reptile

receptors in an ERA:

o EPA ECOTOX database (http://cfpub.epa.gov/ecotox/advanced_query.htm )

o Canadian Wildlife Service Reptile and Amphibian Toxicological Literature (RATL)

database (Pauli et al. 2000)

Other compilation publications (e.g., Sparling et al. (2000)) should also be considered as

potential data sources. Consideration of the relative toxicity of amphibians and reptiles to other

receptors (such as fish or wildlife receptors) for the COPCs evaluated may also be considered to

determine whether toxicity values used for other receptors are expected to be protective of

amphibians and reptiles.

http://cfpub.epa.gov/ecotox/advanced_query.htm


111


References Allard P, Fairbrother A, Hope BK, Hull RN, Johnson MS, Kapustka LA, Mann G, McDonald B, Sample

BE. 2009. Recommendations for the development and application of wildlife toxicity reference values.

Integr Environ Assess Manage 6(1):28-37.

CH2M HILL, USR Corp. 2001. COEUR D'ALENE BASIN REMEDIAL INVESTIGATION/

FEASIBILITY STUDY. ECOLOGICAL RISK ASSESSMENT - FINAL. VOLUME 1, 1 (Parts 1 and

7), 2, 5, 6, 7, 10. For U.S. Environmental Protection Agency, Region 10, Seattle, WA.

EPA. 2005. Guidance for developing ecological soil screening levels (Eco-SSLs). OSWER Directive

92857-55. Issued November 2003; revised October 2005 [online]. US Environmental Protection

Agency, Washington, DC. Available from: http://rais.ornl.gov/documents/ecossl.pdf.

EPA. 2012. Benchmark dose technical guidance. EPA/100/R-12/001. US Environmental Protection

Agency, Washingon, DC.

Mayfield DB, Johnson MS, Burris JA, Fairbrother A. 2013. Furthering the derivation of predictive

wildlife toxicity reference values for use in soil cleanup decisions. Integr Environ Assess Manag

10(3):358-371.

Pauli BD, Perrault JA, Money SL. 2000. RATL: a database of reptile and amphibian toxicology

literature. National Wildlife Research Center, Canadian Wildlife Service, Hull, Quebec, Canada.

Sample B.E., Opresko DM. Suter GW. 1996. Toxicological benchmarks for wildlife. 1996 revision.

ES/ERM-86/R3. Office of Environmental Management, US Department of Energy, Washington, DC.

Sample B.E., Schlekat C, Spurgeon DJ, Menzie C, Rauscher J, Adams B. 2013. Recommendations to

improve wildlife exposure estimation for development of soil screening and cleanup values. Integr

Environ Assess Manag 10(3):372-387.

Sparling DW, Linder G, Bishop CA, eds. 2000. Ecotoxicology of amphibians and reptiles. SETAC

Technical Publications Series, Ingersoll CG, ed. Society of Environmental Toxicology and Chemistry

(SETAC) Press, Pensacola, FL.

Windward. 2013. Portland Harbor RI/FS, Final Remedial Investigation Report, Appendix G: Baseline

ecological risk assessment. Final. Prepared for the Lower Willamette Group. Windward Environmental

LLC, Seattle, WA.

http://rais.ornl.gov/documents/ecossl.pdf


112


Appendix D: Assessment Population

Operational Definitions of the Assessment Population for Wildlife The Ecological Work Group has discussed several alternatives for defining the assessment population

for terrestrial wildlife. Some of the operational definitions that appeared to have relatively broad support

are as follows:

1. A group of individuals within an area that includes the Facility and is bounded by landscape

conditions (e.g., topographic or anthropogenic features) likely to represent important dispersal

barriers for the assessment endpoint species.

This definition is based on DEQ’s preferred approach as outlined in current guidance. This assessment

population represents a group of individuals that are typically more likely to interact with one another

than with individuals of other groups, and are also likely to be exposed to contaminants at a site.

2. A group of individuals within an area centered around the Facility that is approximately 25 times

the size of a typical home range of an individual of the assessment endpoint species.

Again, this definition is based on DEQ’s preferred approach in guidance for situations where the

boundaries of the assessment population cannot be readily defined using landscape conditions near the

Facility.

3. A group of individuals likely to persist into the foreseeable future (< 100 years) under baseline

conditions (i.e., no significant effects from a released contaminant).

This particular operational definition of the assessment population has not been discussed in detail with

the Work Group. The foundation for this definition is OAR 340-122-0084(3)(f) regarding the nature of

baseline ecological risk assessments which states that “…local populations may be evaluated with a

weight-of-evidence analysis or population viability analysis, respectively.” The underlying concept is

that the entity (population) being assessed should have a reasonable chance of persisting into the

foreseeable future under baseline conditions (e.g., absent site-related contaminant effects), thus

warranting investments in protection. Population viability analysis concepts such as the minimum viable

population (MVP) are then used to define the assessment population.

MVP is typically defined as the smallest isolated population having a high chance (e.g., 99%) chance of

remaining extant for a long period of time (e.g., 1,000 years) despite the foreseeable effects of

demographic, environmental, and genetic stochasticity, and natural catastrophes (Shaffer 1981). One

long-standing guiding principle in population viability analysis is the “50/500 rule”. Under this rule-of-

thumb, the effective population size (Ne) should be greater than 50 to prevent short-term (e.g., less than


113


about 100 years) extinction due to the effects of inbreeding, and greater than 500 to prevent long-term

loss of genetic variation due to genetic drift (Franklin, 1980). For the purposes of defining the

assessment population, the population size is defined as a Ne of 50 based on short-term persistence (<

100 years). The time frame associated with short-term persistence appears to approximately match the

time frame of “foreseeable future” that is often used by DEQ site assessments. Note that the Ne of 500 is

intended to protect the evolutionary potential of a population over significantly longer time frames.

It should be noted that Ne differs from census size of a population (Nc) that is the typical focus of

ecological studies. Ne is usually defined as the number of individuals in an ideal population that is able

to maintain the same genetic variability as a real population of interest. Nc is typically a measured count

or some other estimate of the total number of individuals in a population. Ne, the ideal population, is

typically based on a number of assumptions such as equal numbers of males and females, all individuals

are equally likely to produce offspring, mating is random, etc. In general, Ne is smaller than Nc because

it includes immature organisms that are nonbreeding, older adults that are beyond reproductive age, etc.

Although there is considerable variation, the ratio of Ne/Nc is typically about 0.1 in nature (Jamieson and

Allendorf, 2012). Therefore, for a typical species with a Ne of 50, the Nc would be about 500. For the

purposes of this operational definition, Ne/Nc is conservatively assumed to be 0.5, and Nc is defined as

100 individuals. The operational definition of the assessment population is 100 individuals that typically

reside in or near the Facility.

Population Risk Assessment Example

According to the above ecological risk assessment protocols and the definition of the acceptable risk

level given in OAR 340-122-0115(6), a basic population-level ecological risk assessment would involve

the following steps:

1. Define the size and distribution of the assessment population. This would be one aspect of

defining the assessment endpoint (OAR 340-122-0115(7)), and could be done as part of problem

formulation (OAR 340-122-0084(3)(a)).

a. For the purposes of this example, the assessment population is defined as 100 individuals

that reside in or near the Facility.

b. Assuming individuals of the assessment population have non-overlapping home ranges

(the approximate space use pattern of many small mammals and song birds that defend

territories), define the areal extent of the assessment population as 100 x the average

home range size of the assessment species. Alternatively, use typical population density

estimates to estimate the area that would support 100 individuals. Both home range size

and population density estimates are given for several key indicator species in the EPA’s

1993 Wildlife Exposure Factors Handbook.

2. Determine the ecological benchmark value (EBV) (OAR 340-122-0115(21)) for the assessment

endpoint. The EBV for population-level risk estimates is a median lethal dose (LD50) or some

analogous dose or concentration. If the initial EBV is a dose, express the EBV as a soil


114


concentration for the assessment species using standard exposure factors for soil ingestion rate

and body weight (note that for bioaccumlative chemicals one may also want to include food

ingestion rate and a bioaccumulation factor) as follows:

𝑆𝐶𝑒𝑏𝑣 =𝐸𝐵𝑉𝑑 × 𝐵𝑊

𝑆𝐼𝑅

Where,

SCebv = Soil concentration associated with EBV dose (mg/kg)

EBVd = EBV dose in mg/kg-d

SIR = Soil ingestion rate (kg/d)

3. Characterize the spatial distribution of a chemical within the boundaries of the assessment

population. Options include, but are not limited to, the following:

a. Divide the areal extent of the assessment population into decision units and use

incremental sampling methods to estimate the mean chemical concentration in each

decision unit.

b. Map chemical concentrations over space using isoconcentration contours or kriging

techniques.

c. Use Thiessen polygons to map chemical concentrations within the areal extent of the

assessment population.

4. Estimate the proportion of the assessment population that may be exposed to soil concentrations

greater than or equal to the SCebv (i.e., concentration that could result in an exposure equivalent

to an EBV dose). Recall that the acceptable risk level is no more than a 10 percent chance that 20

percent of the total local population will be exposed to the ecological benchmark value. One

basic option is to determine if the areal extent of contamination exceeding SCebv is larger than 20

x the average individual home range size (i.e., 20% of assessment population). This method

assumes negligible uncertainty in EBV, home range size, and other exposure assumptions used in

the model population. It also assumes individuals in the population have non-overlapping home

ranges.

Assuming that some formal step is needed to estimate if there is more than a 10% chance that

20% of population could be exposed to the SCebv, an alternative evaluation approach can be used.

The above DEQ definition of acceptable risk for a population includes two probability

statements. To formally evaluate these statements, the model population must have variability. In

the previously mentioned DEQ guidance, variability in the model population is created by

assuming individual chemical exposures vary as a function of concentrations in soil, and all other


115


aspects of exposure are assumed constants. DEQ assumes that chemical concentrations in soil of

the assessment population area fit an idealized probability distribution. It is then assumed that the

distribution of individual exposure doses is identical to the distribution of soil concentrations. No

information regarding the spatial distribution of chemical concentrations (or exposures) is used

in this DEQ model.

When fitting sample results to an idealized distribution to create variability (e.g., DEQ method),

one assumes each soil sample result is a representative and independent observation of the soil

population. Assuming that the underlying population fits a known distribution (e.g., normal)

allows for the evaluation of specific probability statements. This approach is best suited for

situations where discrete samples have been collected throughout the population area of interest.

The approach is poorly suited for situations where environmental concentrations are measured in

decision units. By design, sampling in decision units is intended to characterize the average

concentration in a given area. Decision units based on exposure considerations are not intended

to be random observations of some underlying soil concentration population that extends outside

the decision unit. Fitting decision unit sample results to some assumed distribution in order to

support a decision about a larger population essentially defeats the purpose of creating decision

units in the first place.

When data from decision units are available, variability in the model population can be created

by considering the range in values of exposure factors other than soil concentration (e.g., soil

ingestion rate, food ingestion rate, home range size, body weight, bioaccumulation factor, or

others). One simple approach for estimating the acceptable risk level where soil concentrations

are estimated for decision units is as follows:

a. Assume that individuals are evenly distributed throughout the population area, and that

each individual in a particular decision unit is exposed to the average concentration in

that decision unit.

b. Create a distribution of 80th percentile exposure doses for the population by assuming one

or more exposure factors (other than soil concentration) can vary. The 80th percentile of

an exposure dose distribution is associated with the most exposed 20% of the population.

i. For example, variability can be created in the model by assuming that soil

ingestion rate (or other factors) can be one of 3 (or more) values: “x”, “y”, and

“z”. For soil ingestion rate “x”, estimate the average individual exposure dose in

each decision unit, and combine all individuals from all decision units to get a

distribution of exposure doses in the population. Find the 80th percentile when soil

ingestion rate is “x”. Repeat this process and find the 80th percentile for the

distribution based on assumed soil ingestion rates “y” and “z”. Combine these 80th

percentiles to create an 80th percentile exposure dose distribution.

c. Find the 90th percentile (10% chance) of the 80th percentile exposure dose distribution

and compare this to the EBV. If this 90th percentile is above the EBV, conclude risks to

the model population are unacceptable.


116


References Calder, W. H., III. 1984. Size, function, and life history. Harvard University Press, Cambridge,

Massachusetts.

DEQ. 2000. Guidance for ecological risk assessment—Level III baseline. Oregon Department of

Environmental Quality. March.

Franklin, I.R. 1980. Evolutionary change in small populations. In Conservation Biology: an

Evolutionary–Ecological Perspective (Soule´, M.E. and Wilcox, B.A., eds), pp. 135–150.

Harestad, A. S., and F. L. Bunnell. 1979. Home range and body weight—a reevaluation. Ecology

60:389–402.

Hope, B. K., and J. A. Peterson. 2000. A procedure for performing population-level ecological risk

assessments. Environmental Management 25(3):281-289.

Jamieson, I.G. and Allendorf, F.W. (2012) How does the 50/500 rule apply to MVPs? Trends Ecol.

Evol. 27, 578–584

Peters, R. H. 1983. The ecological implications of body size. Cambridge University Press, Cambridge.

Schoener, T. W. 1968. Sizes of feeding territories among birds. Ecology 49:123–140.

Shaffer, M.L., 1981. Minimum population sizes for species conservation. BioScience 31, 131–134.

USEPA. 2003. Generic ecological assessment endpoints (GEAEs) for ecological risk assessment. Risk

Assessment Forum, U.S. Environmental Protection Agency. EPA/630/P-02/004F, October.

Waser, P. M. 1987. A model predicting dispersal distance distributions. Pages 251–256 in B. D.

Chepko-Sade and Z. T. Halpin (eds.), Mammalian dispersal patterns. University of Chicago Press,

Chicago.


117


Appendix E: Using Net Environmental Benefit Analysis in Stage 3 (Risk Assessment) of the Recommended 3-Stage Oregon

(1) General requirements for risk assessments include:

The following describes net environmental benefit analysis (NEBA) and provides recommendations for

using NEBA in the Oregon ecological risk assessment (ERA) process.

OAR 340-122-0084(4) requires the conduct of residual risk assessments for candidate remedial action

alternatives prior to the selection or approval of a remedial action. It further stipulates that residual risk

assessments include:

d) A quantitative assessment of the risk resulting from concentrations of untreated waste or

treatment residuals remaining at the facility at the conclusion of any treatment or excavation and

offsite disposal activities taking into consideration current and reasonably likely future land and

water use scenarios and the exposure assumptions used in the baseline risk assessment; and

e) A qualitative or quantitative assessment of the adequacy and reliability of any institutional or

engineering controls to be used for management of treatment residuals and untreated hazardous

substances remaining at the facility.

f) The combination of (a) and (b) constitute a residual risk assessment that must demonstrate to the

Department that acceptable levels of risk as defined by OAR 340-122-0115 would be attained in

the locality of the facility.

OAR 340-122-0090(3)(e) requires that all candidate remedial action alternatives be assessed for the

reasonableness of the cost of the remedial action, by considering, among other things, the degree to

which the costs of the remedial action are proportionate to the benefits to human health and the

environment created through risk reduction or risk management, as well as any other information

relevant to cost-reasonableness.

Taken together, residual risk and cost-reasonableness assessments required by Oregon Administrative

Rules can be used to identify and compare the net environmental benefits of alternative risk

management options.

At least one state, Texas, already has provisions for the use of NEBA in its rules for conducting ERAs at

contamination sites (TCEQ Publication RG-263). Responses must conform to one of two options for

performance standards, termed Remedy Standards A and B (30 TAC 350.31). Under Remedy Standard

A, affected media must be removed or decontaminated to permanently reduce COC concentrations


118


below critical protective concentration levels (PCLs)1 (350.32). Under Remedy Standard B, removal,

decontamination, or control measures may be applied to prevent exposure media exceeding critical

PCLs (350.33). Under Remedy Standard B, use of such control measures may entail post-response care

and associated financial assurance [350.33(g–n)]. With the exception of Class 1 groundwater resources

(which require decontamination), the person may choose to implement either a Remedy Standard A or

B. In a Remedy Standard B response targeted toward ecological concerns, the person may conduct an

ecological services analysis to evaluate the net benefit of the response to ecological resources

[350.77(f)(2)]. The action is complete once the applicable Remedy Standard A or B objectives have

been satisfied (350.34).

The federal rules for compensatory mitigation for losses of aquatic resources [FR73(70):19594-19705]

provide another useful example for thinking about the use of NEBA in Oregon ERAs. Compensatory

mitigation involves actions taken to create environmental benefits that offset unavoidable adverse

impacts to wetlands, streams and other aquatic resources authorized by Clean Water Act section 404

permits and other Department of the Army permits. Compensatory mitigation can be located at or

adjacent to the impact site (i.e., on-site compensatory mitigation) or at another location generally within

the same watershed as the impact site (i.e., offsite compensatory mitigation). Compensatory mitigation

is a critical tool in helping the federal government meet the national goal of ‘‘no net loss’’ of wetland

acreage and function; as such NEBA is a fundamental underlying principle of the federal rules for

compensatory mitigation for losses of aquatic resources.

The workgroup recognizes the importance of identifying and comparing the net environmental benefits

of alternative risk management options, and recommends that steps be taken to facilitate, through

updates to its ERA guidance, the use of net environmental benefit analysis (NEBA) in Oregon ERAs.

Efroymson et al. (2003) describe NEBA as “a methodology for identifying and comparing net

environmental benefits of alternative management options, usually applied to contaminated sites.” They

define net environmental benefits as “the gains in environmental services or other ecological properties

attained by remediation or ecological restoration, minus the environmental injuries caused by those

actions.”

The workgroup has the following recommendations about the use of NEBA in Oregon ERAs:

The OAR 340-122-0084(4) requirement that residual risk assessments be performed for remedial

action alternatives prior to selecting or approving a remedial action should be routinely enforced.

NEBA should be incorporated at the front end of Stage 3 to encourage formulation of remedial

action alternatives that are designed to both reduce risk and improve the gains in environmental

services or other ecological properties. This will require that remedial action alternatives be

defined early in Stage 3.

NEBA methodology should be left flexible in guidance. NEBA requirements will vary from site

to site, depending on a) the nature and extent of candidate remedial action alternatives and b) the

variance and uncertainty in the residual risks and costs of those alternatives.

1 The lower of the human-health PCL or ecological PCL for each COC is called the critical PCL.


119


Rules changes should be considered to establish boundaries and expectations on parties opting to

use NEBA to evaluate remedial alternatives in an ERA.

The State of Oregon should create a policy environment that allows NEBA practices to develop

because of their long-term potential to simultaneously to reduce the costs and increase the pace

of environmental cleanups.

By creating conditions for NEBA to succeed, the State of Oregon will realize environmental benefits

sooner and at lower cost to responsible parties and DEQ. This has already been demonstrated in Texas,

where net environmental benefits can be achieved by restoration or the setting aside of a comparable

type of habitat as that which is impacted to offset residual ecological risk at an affected property. A net

environmental benefits analysis or similar evaluation of ecological services may be used in the

determination of the appropriate level of compensation. The formal process employed in Texas is

detailed in Section 5.3, including Figures 5-3 and 5-4 in TCEQ Publication RG-263.

References Efroymson, R. A., J. P. Nicolette, and G. W. Suter II. 2003. A framework for net environmental benefit

analysis for remediation or restoration of petroleum-contaminated sites. ORNL/TM-2003/17. Oak Ridge

National Laboratory, Oak Ridge, Tennessee.