### _________________________ _____________________ _________________________ _________ United States Office of Water EPA

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Environmental Protection 4304T July 2016

Agency



# DRAFT AQUATIC LIFE AMBIENT

ESTUARINE/MARINE WATER

QUALITY CRITERIA FOR

COPPER

- 2016

### ii EPA

- 822

- P

- 16

- 001

DRAFT AQUATIC LIFE

AMBIENT ESTUARINE/MARINE WATER QUALITY CRITERIA FOR

COPPER

- 2016

(CAS Registry Number 7440

- 50

- 8 )

J uly 2016

U.S. ENVIRONMENTAL PROTECTION AGENCY

OFFICE OF WATER

OFFICE OF SCIENCE AND TECHNOLOGY

HEALTH AND ECOLOGICAL CRITERIA DIVISION

WASHINGTON, D.C.

### iii 

## NOTICES

This document provides information for states and tribes authorized to administer a water

quality standards program, to consider in adopting water quality standards under the Clean Water

Act (CWA), to protect aquatic life from toxic effects of copper in estuarine/marine

environments. Under the CWA, states and tribes are to ad opt water quality criteria to protect

designated uses. State and tribal decision makers retain the discretion to adopt approaches on a

case

- by

- case basis that differ from these criteria when appropriate. While this document contains

EPA’s scientific recomm endations regarding ambient concentrations of copper in

estuarine/marine environments that protect aquatic life, it does not substitute for the CWA or

EPA’s regulations; nor is it a regulation itself. Thus, it cannot impose legally binding

requirements on EPA, states, tribes, or the regulated community, and might not apply to a

particular situation based upon the circumstances. EPA may change this document in the future.

This document has been approved for publication by the Office of Science and Technology

, Office of Water, U.S. Environmental Protection Agency.

Mention of trade names or commercial products does not constitute endorsement or

recommendation for use. This document can be downloaded from:

http://www.epa.gov/waterscience/criteria/aqlife.html

.

### iv 

## FOREWORD

Section 304(a) (l) of the Clean Water Act, 33 U.S.C. § 1314(a)(1), directs the

Administrator of the Environmental Protection Agency to publish water quality criteria that

accurat ely reflect the latest scientific knowledge on the kind and extent of all identifiable effects

on health and welfare that might be expected from the presence of pollutants in any body of

water, including ground water. This document is EPA’s new recommended ambient water

quality criteria (AWQC) for the protection of aquatic life based upon consideration of available

information relating to effects of copper on estuarine/marine organisms, and consideration of

independent external peer review and EPA workgroup comments.

The term "water quality criteria" is used in two sections of the Clean Water Act: section

304(a)(l) and section 303(c)(2). The term has different meanings in each section. In section 304,

the term represents a non

- regulatory, scientific assessm ent of ecological and human health

effects. The criteria presented in this document are such a scientific assessment of ecological

effects. In section 303(c), the term water quality criteria refer to criteria adopted by a state or

authorized tribe as part of their legally

- binding water quality standards. Criteria in water quality

standards establish the maximum acceptable pollutant concentrations in ambient waters

protective of the state’s designated uses. States and authorized tribes may adopt water qualit y

criteria in their water quality standards that have the same numerical values as EPA’s

recommended section 304(a)(1) criteria. However, states and authorized tribes may decide to

adopt water quality criteria different from EPA’s section 304 recommendations to reflect local

environmental conditions and human exposure patterns. Alternatively, states and authorized

tribes may use different data and assumptions than EPA in deriving numeric criteria that are

scientifically defensible and protectiv e of designated uses. It is not until their adoption as part of

state or tribal water quality standards and approved by EPA (or in limited instances promulgated

by EPA) under section 303(c) that criteria become applicable water quality standards for Clean

Water Act purposes. Information to assist the states and authorized tribes in modifying the

recommended criteria presented in this document is contained in the Water Quality Standards

Handbook (U.S. EPA 2014). This handbook and additional information on th e development of

water quality standards and other water

- related programs of this agency have been developed by

the Office of Water.

This document does not establish or affect legal rights or obligations. It does not establish

a binding norm and cannot be finally determinative of the issues addressed. Agency decisions in

any particular situation will be made by applying the Clean Water Act and EPA regulations on

the basis of specific facts presented and scientific information then available.

Elizabeth Southerland

Director

Office of Science and Technology

### v



## AUTHORS / REVIEWERS / ACKNOWLEDGEMENTS

Technical Analysis Leads

Michael Elias, Office of Water, Office of Science and Technology, Health and Ecological

Criteria Division, Washington, DC

elias.mike@epa. gov

Joseph Beaman, Office of Water, Office of Science and Technology, Health and Ecological

Criteria Division, Washington, DC

Reviewers (2016)

Elizabeth Behl, Colleen Flaherty, Kathryn Gallagher, Office of Water, Office of Science and

Technology, Health and Ecological Criteria Division, Washington, DC

EPA Peer Reviewers (2016)

Cindy Roberts, U.S. EPA, Office of Research and Development, Office of Science Policy,

Washington, DC

Russ Erickson, U.S. EPA, Office of Research and Development, Mid

- Continent Ec ology

Division, Duluth, MN

Glynis Hill, U.S. EPA, Office of Policy, Office of Regulatory Policy and Management,

Washington, DC

Jeff Gallagher, U.S. EPA, Office of Chemical Safety and Pollution Prevention, Office of

Pollution Prevention and Toxics, Washin gton, DC

Keith Sappington, U.S. EPA, Office of Chemical Safety and Pollution Prevention, Office of

Pesticides Programs, Arlington, VA

Lars Wilcut and Heather Goss, U.S. EPA, Office of Water, Office of Science and Technology,

Washington, DC

David Hair and William Cooper, U.S. EPA, Office of Water, Office of Wastewater Management,

Washington, DC

Joel Hansel, U.S. EPA Region 4, Atlanta, GA

Candice Bauer, U.S. EPA Region 5, Chicago, IL

Lareina Guenzel, U.S. EPA Region 8, Denver, CO

Jane Hashimoto and T errence Fleming, U.S. EPA Region 9, San Francisco, CA

Mark Jankowski, U.S. EPA Region 10, Seattle, WA

### vi 

## EXECUTIVE SUMMARY

Guidance documents containing aquatic life criteria recommendations for copper (Cu)

have been updated and published by EPA over the p ast 30 years as new science becomes

available (e.g., U.S. EPA 1980, 1984, 1986a, 1995a, 1996, 2003, 2007 )

. EPA’s most recent 2007

updated recommended criteria for copper only provided an update for freshwater organisms

, and

differed from EPA’s previous metals criteria in that the biotic ligand model (BLM) (Di Toro et

al. 2001) addressed the me tal availability to organisms

. The complexing ligands in water

compete with the biotic ligand for metals and other cations in the water. Unlike the empirical

toxici ty to water har d ness relationships

, which EPA used to establish copper criteria prior to

2007 , the BLM explicitly accounts for individual water quality variables, is not linked to a

particular correlation among st the variables, and can address variables th at are not a factor in the

hardness relationship. EPA did not update e stuarine/marine criteria in 2007 because a saltwater

BLM had not been sufficiently developed and tested at that time.

This document utilizes the recently developed saltwater BLM to prov ide updated BLM

based acute and chronic water quality criteri a (WQC) for copper that are applicable to both

estuarine and marine waters. Th is saltwater BLM includes a new characterization of copper

binding to natural organic matter (NOM) in estuarine/ marine systems and considers the binding

of copper to the surface membranes of embryo

- larval stages of several sensitive marine

invertebrates. Development of the saltwater BLM for copper is detailed in Chadwick et al.

(2008 ).

EPA is developing the recommen ded ambient WQC for copper in estuarine/ marine

waters pursuant to its authority under § 304(a) (1) of the Clean Water Act (CWA). EPA developed

t he copper aquatic life criteria using peer reviewed methods and data that EPA determined to be

acceptable for the ir derivation as described in U.S. EPA’s “ Guidelines for Deriving Numerical

National Water Quality Criteria for the Protection of Aquatic Organisms and Their Uses ”

( Guidelines ) ( Stephan et al. 1985). Th is update include s the evaluation of data submitted in

support of the registration of copper

- containing pesticide s that were reviewed by EPA’s Office

of Pesticide Programs a nd studies reported in the open literature.

The resulting recommended ambient WQC indicate that estuarine/marine aquatic

organisms would have an appropriate level of protection if the 1

- hour average and four

- day

### vii

average dissolved copper concentration s do not respectively exceed the acute and chronic criteria

concentrations calculated by the saltwater BLM more than once every three years on average

.

For the 201 6 draft acute criteria , EPA has changed the duration to 1 hour from the 24 hours EPA

recommended in the 200 3 draft c opper criteria for estuarine/marine organisms and the 2007

recommended freshwater copper criteria . EPA made this change to the 2016 criteria to reflect the

acute criteria duration recommended in EPA’s Guidelines (see Section 4.1.2 )

. Because this

updated WQC re lies on the BLM, t he numeric WQC change accordingly in response to changes

in water quality parameters (i.e., temperature, salinity, dissolved organic carbon and pH)

. At an

example pH of 8.0, temperature of 2 2 °C , DOC of 1.0 mg/L and salinity of 32 ppt, the 2016 acute

criterion magni t ude is 2.0 μg/L copper (lowered to protect the commercially important red

abalone Haliotis rufescens ) , and the chronic criterion magnitude is 1.3 μg/L copper . Additional

examples at different water chemistry conditions are provi ded in Appendix I.

This document provides guidance to states and authorized tribes to consider in adopting

water quality standards under the CWA to protect estuarine/marine aquatic life from the acute

and chronic effects of copper. Under the CWA, states a nd authorized tribes may adopt these

WQC into water quality standards to protect designated uses. While this document constitutes

EPA’s scientific recommendations regarding ambient concentrations of copper, this document

does not substitute for the CWA or EPA’s regulations

, nor is it a regulation itself. Thus, it cannot

impose legally binding requirements on EPA, states, authorized tribes, or the regulated

community, and it might not apply to a particular situation based upon the circumstances. State

and tr ibal decision

- makers retain the discretion to adopt approaches on a case

- by

- case basis that

differ from this guidance when appropriate.

### viii 

## TABLE OF CONTENTS

NOTICES

................................ ................................ ................................ ................................ ....... iii

FOREWORD

................................ ................................ ................................ ................................ . iv

AUTHORS / REVIEWERS / ACKNOWLEDGEMENTS

................................ ............................ v

EXECUTIVE SUMMARY

................................ ................................ ................................ ........... vi

TABLE OF CONTENTS

................................ ................................ ................................ ............. viii

LIST OF FIGURES

................................ ................................ ................................ ....................... ix

LIST OF TABL ES

................................ ................................ ................................ .......................... x

LIST OF APPENDICIES

................................ ................................ ................................ ............... x

ACRONYMS

................................ ................................ ................................ ................................ . xi

1 INTRODUCTION

................................ ................................ ................................ .................. 1

2 PROBLEM FORM ULATION

................................ ................................ ................................ 4

2.1 Overview of Copper Sources and Occurrence

................................ ................................ 4

2.2 Environmental Fate and Transport of Copper in the Aquatic Environment

................. 12

2.3 Overview of Copper Toxicity

................................ ................................ ....................... 14

2.4 Overview of Historic and BLM Criteria Development Methods

................................ . 17

2.5 Conceptual Model

................................ ................................ ................................ ......... 29

2.6 Assessment Endpoints

................................ ................................ ................................ .. 31

2.7 Measurement Endpoints

................................ ................................ ................................ 31

2.7.1 Overview of Toxicity Data Requirements

................................ ................................ 32

2.7.2 Measures of Effect

................................ ................................ ................................ .... 33

2.8 Analysis Plan

................................ ................................ ................................ ................ 36

2.8.1 Acute Criterion Derivation

................................ ................................ ....................... 37

2.8.2 Chronic Criterion Derivation

................................ ................................ .................... 38

2.8.3 BLM Evaluation

................................ ................................ ................................ ........ 38

3 EFFECTS ANALYSES FOR AQUATIC ORGANISMS

................................ .................... 41

3.1 Summary of Acute Studies

................................ ................................ ........................... 41

3.2 Summary of Chronic Studies

................................ ................................ ........................ 46

3.3 Summary of BLM Water Quality Input Parameters

................................ ..................... 47

3.4 Bioaccumulation

................................ ................................ ................................ ........... 48

3.5 Toxicity to Aquatic Plants

................................ ................................ ............................ 48

3.6 The National Estuarine/Marine Criteria for Copper

................................ ..................... 49

3.6.1 Acute Criterion Calculation

................................ ................................ ...................... 49

3.6.2 Chronic Criterion Calculation

................................ ................................ ................... 5 3

3.7 Summary of National Criteria

................................ ................................ ....................... 55

3.8 Identification of Data Gaps for Aquatic Organisms

................................ ..................... 56

3.8.1 Chronic Toxicity Data for Estuarine/Marine Animals

................................ .............. 56

3.8.2 Chronic Toxicity Data for Aquatic Vascular Plants and Algae

................................ 56

3.8.3 BLM Uncertainties and Performance

................................ ................................ ....... 57

4 EFFECTS CHARACTERIZATION

................................ ................................ .................... 58

4.1 Estuarine/Marine Acute Toxicity Data

................................ ................................ ......... 58

4.1.1 Uncertainty in the Estuarine/Marine FAV Calculation

................................ ............ 59

4.1.2 Acute Criteria Duration

................................ ................................ ............................. 60

4.2 Estuarine/Marine Chronic Toxicity Data

................................ ................................ ...... 61

4.2.1 Uncertainty in the Estuarine/Marine FCV Calcul ation

................................ ............. 62

### ix

4.3 Bioaccumulation

................................ ................................ ................................ ........... 63

4.3.1 Uncertainty with Copper Exposure Routes

................................ ............................... 63

4.4 Effects on Aquatic Plants

................................ ................................ .............................. 67

4.5 Protection of Endangered Species

................................ ................................ ................ 68

4.5.1 Acute Toxicity Data for Listed Species

................................ ................................ .... 69

4.5.2 Chronic Toxicity Data for Listed Species

................................ ................................ . 69

4.6 Comparison of Draft 2003 and 2016 Criteria Values

................................ ................... 69

5 REFERENCES

................................ ................................ ................................ ..................... 72



## LIST OF FIGURES

Figure 1. Copper Usage Data for Agriculture.

................................ ................................ ................ 7

Figure 2. Environmental Bridging Chemical Species for Copper (Cu) Minerals and Complexes.

................................ ................................ ................................ ................................ ........ 14

Figure 3. Conceptual Diagram Showing Relationship between Chemical Speciation, Metal

Binding at Biotic Ligand (BL) Sites, and Competition at These BL Sites for Other

Cations.

................................ ................................ ................................ .......................... 20

Figure 4. Percent Abnormal Cells in Test Waters with Different Composition (primarily DOC)

for M. galloprovincialis (Panel A) and S. purpuratus (P anel B).

................................ .. 23

Figure 5. Predicted Copper Binding to Biotic Ligand Sites on Cell Membranes (solid lines) by

the Saltwater BLM for Copper with a Single Set of Parameters Compared with

Measured Copper Accumulation for Embryo

- larval Stages of M. galloprovincialis

(Panel A) and S. purpuratus (Panel B).

................................ ................................ ......... 24

Figure 6. Predicted Copper Toxicity by the Saltwater BLM for Copper (solid lines) in Response

to C hanging DOC from a Variety of Estuarine and Marine Sites Compared with

Measured Copper Toxicity for Embryo

- larval Stages of M. galloprovincialis (Panel A)

and S. purpuratus (Panel B).

................................ ................................ .......................... 26

Figure 7. Predicted Copper Toxicity by the Saltwater BLM for Copper (solid lines) in Response

to Changing DOC from a Variety of Estuarine and Marine Sites Compared with

Measured Copper Toxicity for Embryo

- larval Stages of Dendraster (Panel A) and

Crassostrea (Panel B).

................................ ................................ ................................ ... 27

Figure 8. Conceptual Model for Copper Effects on Aquatic Organisms.

................................ ..... 30

Figure 9. Ranked Estuarine/Marine GMAVs.

................................ ................................ .............. 51

Figure 10. Reported Dissolved Cu LC 50 

### s Ranked by the Geomean of the Normalized Cu Values

(i.e., SMAVs).

................................ ................................ ................................ ................ 52

Figure 11. Ranked Estuarine/Marine GMCVs.

................................ ................................ ............. 55

### x 

## LIST OF TABLES

Table 1. Ambient Dissolved and Total Copper Concentrations Reported for Coastal Harbors and

Marinas.

................................ ................................ ................................ ......................... 12

Table 2. Summary of Assessment Endpoints and Measures of Effect Used in Criteria Derivation.

................................ ................................ ................................ ................................ ........ 32

Table 3. Summary Table of Ac ceptable Toxicity Data Used to Meet the Minimum Data

Requirements in the “1985 Guidelines” and Count of Phyla, Families, Genera and

Species.

................................ ................................ ................................ .......................... 35

Table 4. Water Quality Input Parameters for the Freshwater and Saltwater Versions of the BLM.

................................ ................................ ................................ ................................ ........ 39

Table 5. Ranked Estuarine/Marine Genus Mean Acute Values.

................................ .................. 42

Table 6. Ranked Estuarine/Marine Genus Mean Chronic Values with Species Mean Acute

C hronic Ratios.

................................ ................................ ................................ .............. 47

Table 7. Water Quality Input Parameters Used for Saltwater BLM

- Normalization.

................... 48

Table 8. Estuarine/Marine Water Final Acute Value (FAV) and Criteria Calculations.

.............. 50

Table 9. Comparison of the Four Most Sensitive Taxa Used to Calculate the Estuarine/Marine

FAV and CMC in the 2003 Draft Copper Document and 2016 Update.

....................... 71



## LIST OF APPENDICIES

Appendix A Acceptable Estuarine/Marine Acute Toxicity Data

................................ ............ A

- 1

Appendix B Acceptable Chronic Toxicity Data

................................ ................................ ...... B

- 1

Appendix C Estuarine/Marine Plant Toxicity Data

................................ ................................ C

- 1

Appendix D Acceptable Estuarine/Marine Bioaccumulation Data

................................ ......... D

- 1

Appendix E Other Estuarine/Marine Toxicity Data

................................ ................................ . E

- 1

Appendix F Data Not Used in the Development of the Aquatic Life Ambient Estuarine/Marine

Water Quality Criteria for Copper

................................ ................................ ....... F

- 1

Appendix G Species Numbers Used in BLM Analysis

................................ ........................... G

- 1

Appendix H Water Chemistry Used in BLM Analysis

................................ ........................... H

- 1

Appendix I Discussion of BLM Water Quality Parameters in the Estuarine/Marine

Environment and Example Numeric Criteria Values

................................ ........... I

- 1

### xi 

## ACRONYMS

ACR Acute

- Chronic Ratio

ALC Aquatic Life Criteria

BL Biotic Ligand

BLM Biotic Ligand Model

CCC Criterion Continuous Concentration

CF Conversion Factors

CHESS Chemical Equilibria in Soils and Solutions

CMC Criterion Maximum Concentration

CWA Clean Water Act

DIC Dissolved Inorganic Carbon

DOC Dissolved Organic Carbon

DOM Dissolved Organic Matter

EC 50 

### /EC 20 

### Effect concentration to 50%/20% of the test population

ELS Early Life Stage

EPA Environmental Protection Agency

FACR Final Acute

- Chronic Ratio

FAV Final Acute Value

FCV Final Chronic Value

FFDCA Federal Food, Drug and Cosmetic Act

FIAM Free Ion Activity Model

FQPA Food Quality Protection Act

GDCI Generic Data Call

- In

GMAV Genus Mean Acute Value

GMCV Genus Mean Chronic Value

GSIM Gill Surface Interaction Model

HA Humic Acid

IC 50 

### Inhibition Concentration where effect is inhibited 50% compared to control organism

LA 50 

### Lethal Level of Accumulation at 50 % e ffect l evel

LC 50 

### Lethal C oncentration to 50% of the test population

LOAEC Lowes t Observed Adverse Effect Concentration

LOEC Lowest O bserved E ffect C oncentration

MATC Maximum A cceptable T oxicant C oncentration (geometric mean of NOEC and LOEC)

MDR Minimum Data Requirements

Me:BL Metal

- Biotic Ligand Complex

MSE Mean Square Error

NASQAN National Stream Quality Accounting Network

NOAEC No Observed Adverse Effect Concentration

NOEC No O bserved E ffect C oncentration

NOM Natural Organic Matter

PLC Partial Life

- Cycle

RED Reregistration Eligibility Decision

SMAV Species Mean Acute Value

SMCV Species Mean Chronic Value

SSD Species S ensitivity D istribution

TSS Total Suspended Solids

WER Water

- Effect Ratio

WET Whole Effluent Toxicity

WHAM Windermere Humic Aqueous Model

WQC Water Quality Criteria

### 1



## 1 INTRODUCTION

The U.S. Environmental Protection Agency (EPA) is developing ambient water quality

criteria (WQC) for copper (Cu) for the protection of aquatic life in estuarine/marine waters

through its authority under § 304(a) (1) of t he Clean Water Act (CWA). Over the past 3 0 years the

EPA has published a number of guidance documents containing aquatic life criteria

re commendations for copper ( U.S. EPA 1980, 1984, 1986a, 1995a, 1996, 2003, and 2007 ). The

most recent 2007 updated recomm ended WQC document only provided an update for freshwater

criteria, and differed from EPA ’s previous metals criteria primarily with regard to how metal

availability to organisms is addressed. EPA based p revious criteria recommendations on

empirical relationships between toxicity and water hardness. In t he 2007 freshwater acute and

chronic recommended criteria , EPA instead used the biotic ligand model (BLM) ( Di Toro et al.

2001 ). The BLM is based on the premise that : ( 1) toxicity is relat ed to the amount of metal

bound to a biochemical site (the biotic ligand) ; and ( 2) binding is related to the total dissolved

metal and complexing ligand concentrations in water. The biotic ligand is a binding site on

biological membranes which is associate d with the mechanism of toxicity in the organism

. Some

ligands and cations complex with metal s in water

, while other elements compete for binding sites

on the biotic ligand with the uncomplexed, bioavailable metal s in water. Unlike the empirical

har d ness r elationships, the BLM explicitly account s for a broader range of water quality

variables , including variables that are not a factor in the hardness relationship . T he BLM is not

linked to a particular correlation among st these variables

.

EPA’s current recommended estuarine/marine criteria for copper are based on data for 33

species representing 26 genera (U.S. EPA 1995a). EPA last updated t he e stuarine / marine criteria

as draft in 2003 and were derived without normalization of the available toxic ity data. EPA

based t he draft 200 3 acute criterion on Species Mean Acute Values ( SMAVs ) for 52 species in

4 4 genera ( 34 invertebrates and 1 8 fish species)

, with mussels, oysters and the summer flounder

identified as the most sensitive species. Chronic salt water tests were available only for the

sheepshead minnow, Cyprinodon variegatus in the 2003 draft document

. Sufficient toxicity data

were available to fulfill requirements to calculat e an acute estuarine/marine criterion using a

species sensitivity distribution (SSD) , as described in EPA’s Guidelines ( Stephan et al. 1985 )

.

T he Fin a l Acute Value ( FAV ) and Criterion Maximum Concentration ( CMC ) were lowered to be

### 2

protective of the commercially and recreationally important mussel, Mytilus

. Data were not

sufficient to calculate the chronic estuarine/marine criterion using a SSD , and therefore Acute

Chronic Ratios (ACRs) were used to derive the 2003 draft criterion.

EPA did not update t he estuarine/marine criteria at the time of the 2007 release of th e

BLM

- based freshwater criteria because the saltwater BLM had not been sufficiently developed

or tested. This has now been addressed and details about the development of the saltwater

version of the copper BLM were published in Chadwick et al. (2008 )

. The saltwater BLM for

copper includes a new description of copper binding to natural organic matter (NOM )

represented by dissolved organic carbon ( DOC ) in the model . DOC is an analytical measurement

used to quantify NOM in marine systems, and considers copper binding to the biological

membranes of embryo

- larval stages of several sensitive marine invertebrates. The chemical

properties of NOM in saltwater and freshwater are similar as NOM from either medium can

strongly affect the chemistry and bioavailability of copper to aquatic biota. However, the

distribution of binding sites for NOM in marine waters differs enough from those in freshwater

that a new BLM model was developed for saltwater

. This document utilizes an updated version

of th e saltwater BLM

, which wa s originally published in Chadwick et al. (2008)

, to provide

B LM

- based water quality criteria for copper that are applicable to both estuarine and marine

waters. Although the original development of the BLM ( Chadwick et al. 2008) focused on

several sensitive marine invertebrates, application of the model to the development of

estuarine/ marine WQC required changes to the model to account for additional species over a

wider range of copper concentrations.

The pr esent document contains EPA’s criteria recommendations for the protection of

aquatic life in ambient estuarine/marine water from both acut e and chronic toxic effects of

copper. EPA updated t he estuarine/marine WQC provided in this document in accordance wi th

methods outlined in the Agency’s “ Guidelines for Deriving Numerical National Water Quality

Criteria for the Protection of Aquatic Organisms and Their Uses ” ( EPA Guidelines) (Stephan et

al. 1985). This document describes scientifically defensible water qua lity criteria values for

copper in estuarine/marine waters pursuant to CWA § 304(a) (1)

, derived utilizing best available

data in a manner consistent with the EPA Guidelines and reflecting the latest available scientific

information and best professional scientific judgments of toxicological effects

. O nce finalized,

### 3

these criteria will supersede EPA’s previously published recommendations for copper in

estuarine/marine water

.

This criteria document provides updated guidance to s tates and authorized t ribes to adopt

water quality standards under the CWA to protect estuarine/marine aquatic life from copper.

Under the CWA, s tates and authorized t ribes adopt WQC to protect designated uses. Although

this document constitutes EPA’s scientific recommendations regar ding ambient concentrations

of copper in estuarine/marine waters , it does not substitute for the CWA or EPA’s regulations,

nor is it a regulation itself. Thus, it cannot impose legally binding requirements on EPA, s tates,

authorized t ribes, or the regulated community, and might not apply to a particular situation based

o n the circumstances. State and t ribal decision makers retain the discretion in adopting

approaches, on a case

- by

- case basis, that differ from this guidance when appropriate.

### 4



## 2 PROBL EM FORMULATION

Problem formulation provides a strategic framework to develop water quality criteria by

providing an overview of a chemical’s sources and occurrence, fate and transport in the

environment, and toxicological characteristics and factors affect ing toxicity. A problem

formulation uses this information to develop a conceptual model and identify the most relevant

chemical properties and endpoints for evaluation. The structure of the problem formulation

developed for copper in estuarine/marine water s is consistent with U.S. EPA’s Guidelines for

Ecological Risk Assessment (U.S. EPA 1998) and the approach used by EPA for pesticide

effects assessment (U.S. EPA 2004)

.

Since copper is a registered pesticide in the United States

, EPA issued Registration

St andards in 1986 for copper sulfate ( U.S. EPA 1986 a ) and in 1987 for Group II copper

compounds ( U.S. EPA 1987) . As a result, Generic Data Call

- In (GDCI) notices were issued to

registrants in 1987 and 1993 . The GDCI notices required registrants to submit eco logical

fate/effects studies and product chemistry/residue and avian toxicity studies for various copper

compounds as part of the 40 CFR Part 158 data necessary to support reregistration (U.S. EPA

2010a). In further support of reregistration, and as requir ed by FIFRA and the Federal Food,

Drug and Cosmetic Act (FFDCA) and amended by the Food Qua lity Protection Act (FQPA),

EPA completed the copper Reregistration Eligibility Decision (RED) . The RED was signed in

July 2006 and was published

, along with support ing documents, for public comment in August

20 06. The revised RED, which addressed the public comments, is available online (U.S. EPA

2009).

2.1 Overview of Copper Sources and Occurrence

Copper is a naturally occurring element in the earth's crust, with concentratio ns typically

ranging from 55 to 70 mg/ k g (Nriagu 1979). U.S. soil l evels commonly range from 1 to 40

mg/k g and average around 9 mg/ k g (Tisdale et al. 1985 ). Copper ranks 14 th 

### in relative abundance

amongst all elements and is typically found combined with other minerals in the form of oxides,

carbonates and sulfides ( CDA 2003 ; Chemicool 2012). T he highest copper concentrations are

found in basaltic igneous rocks (averaging approximately 90 mg/kg), while much lower

concentrations ( averagi ng 4 mg/kg ) are found in sedimentary limestones (CDA 2003).

### 5

Copper is commonly found in aquatic systems as a result of both natural and

anthropogenic sources (Nriagu 1979) . Natural sources of copper to aquatic systems include

geological deposits, weatheri ng and erosion of rocks and soils and volcanic activity (Kious and

Tilling 1996). It is estimated that , on average, a pproximately 68% of the copper released to

surface water s originate s from these sources (ATSDR 1990). Natura lly occurring copper

concentrations have been reported to range from 0.03 to 0.23 μg/L in surface seawaters ( Bowen

1985). In a review paper, Kennish (1998 ) reported copper concentrations ranging from 0.3 to 3.8

μg/L in estuarine waters and from 0.1 to 2.5 μg/L in coastal wate rs of the United States.

Copper concentrations in estuarine environment s receiving anthropogenic inputs ca n

range from background to more than 15 μg/L

, and concentrations in impacted coastal waters

have been reported to range from 0.5 to 2.6 μg/L (Interna tional Copper Association 2003)

. I t

should be noted , however, that much of the quantit at ive metals data for samples collected from

natural waters prior to the mid

- 1970s are considered inaccurate due to contamination from

sampling methods or containers.

El evated concentrations of copper in the aquatic environment can result from both natural

sources, such as from the erosion of soils, and from numerous anthropogenic point and nonpoint

sources. The following discussion provides a description of some of the most notable

anthropogenic sources.

A broad range of m ining/resource extraction activities can re present a source of copper to

the aquatic environment via both permitted discharges from active mines and uncontrolled

releases from abandoned mines

. Abandoned mines are a notable source of copper du e to acid

mine drainage, which solubilizes and transports a broad range of metals, including copper, to

adjacent waterbodies

. Copper mining activities can , in particular, represent a source of copper to

the environme nt , with t he majority of both historic and ongoing copper mining activity in the

U.S. occurring in Arizona, Utah, New Mexico, Nevada and Montana (CDA 2012 )

. EPA

estimated that mining has impacted headwater streams in more than 40 percent of watersheds in

t he western United States ( U.S. EPA 1994b, 2012 a ).

Coppe r is widely used in pesticides and e levated concentrations of copper in the

environment can result from the application and us e of registere d pesticides. The first copper

containing pesticide registration was issued in 1956. Currently

, there are 19 copper compounds

### 6

that have active food use registrations (12 for agricultural uses and 7 for antimicrobial uses) and

that are subject to tolerance reassessment and registration review (U.S. EPA 2010a).

Copper is widely used as a broad

- spectrum bactericide, fungicide, antimicrobial,

herbicide, algaecide

, and molluscicide for a variety of agricultural, commercial and urban

purposes . Marketed trade names include Ko cide

, CuproFix

, Basicop, K

- Tea, Cutrine Ultra and

Triangle. I n 2002, for example, it was estimated that approximately 106 million pounds of

copper was applied nationwide as an agricultural fungicide ( Figure 1 ). Primary applications

were to rice (25%), citrus fruit (23%), walnuts (10%) and grapes (7%), with lesser amounts used

on tomato es , peach es , almond s , apple s, cherries , and potato es (U.S. EPA 2010a).

As pesticidal products, c opper

- containing compounds are also applied directly to aquatic

systems to control algae, cyanobacteria, aquatic weeds, leeches, mollusks and tadpole shrimp

(TDC Environmental 2004; U.S. EPA 2010a)

. A ntimicrobia l pesticide use s in clude wood

preservative s including surface and pressure treatments, architectural and antifoulant paints,

algae resistant roofing shingles, human drinking water treatment, and other material

preservative s . Urban uses include application to control algae and moss in lawns , algae in

outdoor swimming pools

, and root growth in sewage and irrigation systems.

### 7

Figure 1

. Copper Usage Data for Agriculture

. (Source: http://water.usgs.gov/nawqa/pnsp/usage/maps/show_map.php?year=02&map=m5011 , accessed

on May 25, 2010)

.



### C opper is an essential micronutrient for plant growth and agric ultural fertilizers and

biosolids containing co pper are applied to bolster deficient soils and increase crop yields (CDA

2003; University of Minnesota 2009). Copper is also used as a feed supplement for cattle and

other livestock to prevent a deficiency th at can make cattle less responsive to vaccines and more

susceptible to disease (Oregon State University 2011)

, and to improve weight gain

. Other

agricultural uses include copper sulfate in dairy cattle foot baths to control hairy heel warts

(Jokela et al. 2010), which can introduce copper to the environment.

A number of other industries have been identified as sources of copper to the

e nvironment, including leather and leather product manufacturers, metal fabricators, and

electrical equipment manufacturers , amongst others (Patterson et al. 1998; CDA 2003; TDC

Environmental 2004). Copper is also released to the environment from the burning of fossil fuels

(oil, diesel and coal) and wood (CDA 2003).

Urban runoff from the numerous and unrelated upland sources can cumulatively

represent a n important anthropogenic source of copper to surface water. In addition to the uses

### 8

already discussed, s ou rces of copper to runoff include copper roofs and gutters, chromate copper

arsenate (CCA) treat ed wood 1



### , automotive brake pads and tail pipe emissions , asphalt, coolant

leaks and construction erosion

. Storm water runoff is estimated to contribute approximately 2%

of the total copper released to waterways ( ASTDR 1990 ) compared to 68% contributed from

soils through natural weathering and disturbance (Georgopoulis et al. 2001). However, i n a study

of copper sources to the San Fran cisco Bay , urban runoff was estimated to contribute

approximately 53 percent of the copper loading to the Bay ( 45,000 to 47,000 pounds per year ;

TDC Environmental 2004 ).

In estuarine and marine waters

, and to lesser extent freshwater environments , antifouling

paints and coatings ( als o known as Antifouling Systems or AFS ’s) are pesticidal products used to

protect boat/ship hulls, underwater surfaces, buoys and barges, while CCA

- impregnated timber s

are used for the decking and pilings of boat docks and marine struct ures. Antifouling paints and

coatings are intended to retard the growth of algae, weeds, and other encrusting organisms such

as barnacles and mussels on the underwater portion of vessel hulls and underwater surfaces

.

These encrusting organisms can foul hulls and other underwater surfaces , increasing corrosion

and drag, reducing safety and maneuverability, decreasi ng fuel efficiency and economy, and

lengthening transit times ( WHOI 1952 ). The development of antifouling paints and coatings has

a long history, as mariners have tried for centuries to keep vessel hulls free from barnacles and

other fouling growth (Thomas and Brooks 2010) . In the late 1950s and early 1960s, antifouling

paint formulations using tributyltin (TBT) were introduced and proved to be excellent at

preventing hull fouling

. However, restrictions on the use of TBT

- based compounds due to severe

enviro nmental impacts opened the market for manufacturers to develop new biocides for use on

vessels ( Kiaune and Singhasemanon 201 1)

. Alternative metal s

, including copper and zinc, are

currently used as substitutes for TBT.

The most common form of copper used i n antifouling paints and coatings is cuprous

oxide, which acts as a preventative biocide by leaching into the water. M ost marine antifouling

paints contai n 40 to 70 percent cuprous oxide by weight . Since cuprous oxide is comprised of 89

percent copper by w eight, typical cuprous oxide marine antifouling paints are 36 to 62 percent

copper by weight ( TDC Environmental 2004 ). Alt hough not as common, c opper thiocyanate and

1 In December 2003, chromated arsenicals manufacturers voluntarily discontinued manufacturing chromated

arsenicals

- treated wood products for homeowner uses ( U.S. EPA 2010 b )

### 9

copper hydroxid e are also used as biocides in antifouling paints and coatings . C opper thiocyanate

has the advantage of being compatible with aluminum. The contribution of copper to receiving

waters from c opper thiocyanate and copper hydroxid e paints is small relative to biocides

containing cuprous oxide ( TDC Environmental 2004 ).

Antif ouling paints and coatings applied to vessel hulls represent one of the most

commonly identified sources o f copper in marinas. A number of studies have been done to

estimate t he loading of copper from these paints and coatings

. EPA estimated that copper lo ading

from the use of these biocides in California’s Lower Newport Bay, which harbors approximately

10,000 boats, contributed more than 62,000 pounds of copper annually through passive leaching

and underwater hull cleaning ( U.S. EPA 2002 ). T his release cou ld account for as much as 80

percent of the copper input into the Lower Newport Bay

. Although this may represent an

extreme case , based on the high number and density of boats that are docked and the minimal

water circulation and flush ing of the harbor

, it illustrates the potential significance of antifouling

paints and coatings as a source of copper to the aquatic environment

.

The U.S. Navy and private researchers conducted two copper source loading studies for

the San Diego Bay in the late 1990s ( Joh nson et al. 1998 ; PRC Environmental Management,

Inc.1997 ). Both studies concluded that antifouling paints and coatings accounted for the majority

of dissolved copper loading to the bay. The San Diego Regional Water Quality Control Board

estimated that pass ive leaching and the underwater hull cleaning of the 2,400 boats berthed in the

Shelter Island Yacht Basin marina collectively contribute 98 percent of the copper discharged to

the basin ( Singhasemanon et al. 2009 ). Approximately 95 percent of the 1.8 poun ds of copper

estimated to be released by each boat per year is believed to leach from antifouling paints and

coatings while boats are moored at the dock , while the remaining five percent is believed to be

released during underwater hull cleaning activities (TDC Environmental 2004)

.

Copper leaching from vessel hulls represents a potential water quality concern in ports

throughout the United States

, includ ing ports in the Chesapeake Bay, Port Ca naveral and Indian

River Lagoon in Fl orida, and various harbors in Washington State (Carson et al. 2009). In

addition to AFS, antifouling paint particles are generated during boat maintenance and from

ab an d on ed structures and ships. These particles have the potential to leach metals more rapidly

due to the increase d surface area and also may be consumed by benthic invertebrates (Turner

2010).

### 10

As presented in EPA’s Study of Discharges Incidental to Normal Operation of

Commercial Fishing Vessels and Other Non

- Recreational Vessels Less than 79 Feet (U.S. EPA

2010b), el evated levels of copper were found in the ambient water associated with a number of

harbors and marinas ( Table 1 ). A recent study of AFS biocides in C alifornia marinas found

dissolved copper concentrations ranging from 0.1

- 18.4 μg/L in the water , which are similar to the

range of concentrations reported in U.S. EPA (2010b) . Concentrations were significantly higher

in salt

- and brackish water marinas tha n in freshwater marinas (Singhasemanon 2008).

### 11

Case Study: Mass Balance for Sources of Copper to the San Francisco Bay

There is a long history of investigation of copper sources to the San Francisco Bay and

surrounding area, where copper has been a pollutant of concern since the late 1980s. The 1989

designation of the lower South San Francisco Bay as impaired by copper (listing under § 30 3(d) of

the CWA) caused government agencies and businesses to make a significant inve stment in copper

source identification and reduction measures. These activities created a wealth of information on

copper releases to surface water s and greatly expanded the understanding of options to prevent or

reduce copper releases to San Francisco Bay.

Copper Sources in Urban Runoff and Shoreline Activities (TDC Environmental 2004) was

prepared for the Clean Estuary Partnership to summarize available information about the sources

of copper in urban runo ff that is released directly into the Bay from shor eline activities. M arine

antifouling paint and copper algaecides applied to shoreline lagoons were included in the

evaluation of direct release sources . The report did not address discharges from industrial or

municipal wastewater tr eatment plants or non

- u rban copper sources, such as sediment erosion

from open space, agricultural pesticide use, mine drainage, and reservoir releases. These were not

considered to be significant sources of copper to urban runoff or from shoreline activities.

Nine categories of copper sources were found to have the potential to make a significant

c ontribution to copper levels in the San Francisco Bay Area via urban runoff and releases from

shoreline activities. These sources are listed below, order ed from highest to lowest based on the

estimated magnitude of loading:

 Marine antifouling coatings

 Vehicle brake pads

 Architectural copper

 Copper pesticides (including shoreline algaecides) and CCA

- treated wood

 Industrial copper use s

 Copper air emissions



###  Soil erosion

 Copper in domestic water discharged to storm drains

 Vehicle fluid leaks and dumping

In theory, there are thousands of potential sources for copper in urban runoff and shoreline

activities. Additional information characterizing sources of copper is summarized in Diffuse

Sources of Environmental Copper in the United States ( CDA 2003).

### 12

Table 1

. Ambient Dissolved Copper Concentrations Reported for Coastal Harbors and

Marinas.

Location Ambient Water

Copper Dissolved

(μg/L)

Baltimore (Fort McHenry), MD 18.7

Baltimore (Fells Point), MD 24.2

Gloucester, MA <5 a



### New Bedford, MA <5 a



### Philadelphia, PA <5 a



### Havre de Grace, MD <5 a



### Pensacola, FL 1.8

Gulf Breeze, FL 3.1

Lafitte, LA 3

Bayou La Batre, AL 4.3

Pass Christian, MS 4

Slidell, LA 2.4

Convent, LA 2.4

Sitka SB, AK <5 a



### Sitka, AK <5 a

a 

### Limit of detection

( Source: U.S. EPA 2010b)

.

Monitoring in the Southern California Bight demonstrated that sediment from marinas

throughout southern California had consistently elevated copper levels compared to surrounding

waters (Bay et al. 2000). S urveys around the United States routi nely find ele vated copper

concentrations in marina and harbor sediments relat ive to other areas with less vessel traffic or

shoreline activities (NOAA 1994; U.S. EPA 1999).

2.2 Environmental Fate and Transport of Copper in the Aquatic Environment

Elemental c opper, atomic number 29, is a reddish solid with a molecular weight of

63.546 g/mol. Copper has a density of 8.94 g/mL at 20 ° C , a melting point of 1,083 ° C and is

insoluble in water. C opper naturally occurs as two stable isotopes ( 63 

### Cu and 65 

### Cu) along with

numerous unstable radioisotopes . B eing a metallic element, copper will not break dow n and

continues to cycle in the environment after it is released ( Eisler 1998 ).

Copper exists in four oxidation states : Cu 0 

### , Cu + 

### , Cu 2 + 

### , and Cu 3 + 

### . T he cupric ion (Cu 2 + 

### )

oxidation state is the form of copper generally encountered in water. Elemental copper (Cu 0 

### ) is

slightly soluble in dilute ammonia and is not oxidized in water, cuprous copper (Cu + 

### ) is only

### 13

found in water when complexed (oxides, hydroxides and ligands), an d trivalent copper (Cu 3 + 

### )

does not occur naturally. The pH of the medium and presence of other chemical species usually

controls which form s of Cu + 

### or Cu 2 + 

### are found ( ATSDR 1990 ; Eisler 1998 ). I n oxic natural

wat er s with neutral pH and above, the f ree cupr ic (Cu 2+ 

### ) ion is generally a minor species (Stumm

and Morgan 1981). T he cupric ion instead generally reacts with inorganic and organic chemicals

in solution and in suspension

, and forms moderate to strongly complexed solutes and precipitates

with the numer ous inorganic and organic constituents of natural waters (e.g., carbonate,

phosphate, and organic materials). An overview of the chemistry of copper in aqueous systems is

provided in Figure 2 ( U.S. EPA 2010a ).

Copper hydroxide, copper carbonate and cupric ion are the dominant copper species in

seawater (U.S. EPA 1980). This is in contrast to freshwater, where cupric salts (chlori de, nitrate

and sulfate) are generally highly soluble and where solubility decreases under reducing

conditions and is modified by water pH, temperature and hardness. Copper flux from

estuarine/marine sediments is influenced by the presence of ligands in th e sediment pore waters.

In a study of two contrasting types of organic rich estuarine sediments from the Chesapeake Bay,

it was determined that most of the total dissolved copper fluxing from these sediments would be

complexed by ligands during the sedimen t

- water exchange , and t hese sediments will influence

the copper speciation in overlying waters when these ligands are released (Skrabal et al. 2000)

.

Due to the complexation of the copper from the pore waters, only a small fraction of the copper

is exchang ed as an organic species (the most bioavailable form) (Skrabal et al. 2000), indicating

that the geochemistry of copper from estuarine/marine sediments is an important determinant of

the fate and transport of copper to aquatic organisms.

### 14

Figure 2

. Environmental Bridging Chemical Species for Copper (Cu) Minerals and

Complexes.

2.3 Overview of Copper Toxicity

Copper is a micronutrient for organisms at low concentrations and is recognized as

essential to virtually all plants and animals (Kapustka et al. 2004). It is also a key atom in the

oxygen c arrying prote in (hemocyanin) of some invertebrates. However, it can become toxic to

some forms of aquatic life at elevated concentrations. The specific mode of toxic action depends

on the organism. In bacteria, fungi and algae, excess copper causes disruption of cell membrane

integrity and the subsequent leakage of the cell contents (Borkow a nd Gabbay 2005). In

mollusks, copper alters the normal function of peroxidase enzymes and surfa ce epithelia

, often

producing peroxidation products that lethally disrupt vital functions of membranes and cells

(Cheng 1979). In the mussel, Mytilus galloprovincialis , elevated copper concentrations have

been found to interfere with Ca +2 

### homeostasis in th e gill, and disrupt Na/K ATPase and Ca +2

### 15

ATPase activities (Viarengo et al. 1996). Copper also affects the gills of crabs, reducing

hemocyanin

- oxygen affinity in these organisms. Hansen et al. (1992) attributed copper exposed

crab ( Carcinus maenas ) mortali ty to reduced oxygen transport and subsequent tissue hypoxia,

with reductions in the activities of regulatory enzymes of ATP

- synthesizing pathways.

In marine fish, copper adversely affects osmoregulatory processes, ATP

- synthesizing

pathways and ion transport across the gills, and cause s oxidative stress damage. The osmotic

balance maintained by the gastrointestinal tract and gills in marine teleost fish is disrupted when

elevated copper levels inhibit water absorption by the gut (active uptake of Na + 

### and Cl

- 

### ) and/or

the secretion of Na + 

### and Cl



### by the gills (inhibition of branchial Na + 

### /K +



### - ATPase) (Marshall and

Grosell 2005; Stagg and Shuttleworth 1982). Excretion of nitrogenous waste by teleost fish can

also be impacted by copper, with elevated plasm a ammonia concentrations observed in seawater

acclimated rainbow trout exposed to 400 μg/L copper (Wilson and Taylor 1993). In contrast,

marine elasmobranchs retain nitrogenous compounds for osmoregulatory purposes, and exposure

of spiny dogfish ( Squalus a canthias ) to 1,000 μg/L copper resulted in a loss of plasma urea (De

Boeck et al. 2007). Dodoo et al. (1992) observed inhibited calcium transport in juvenile flounder

( Paralichthys sp .) exposed to copper, and speculated that it was caused by copper interfe rence

with gill chloride cells.

Copper can also induce cellular oxidative stress, through the formation of reactive

oxygen species (ROS), inhibition of antioxidant enzymes, alteration of the mitochondrial

electron

- transfer chain, or depletion of cellular glutathione (Shukla et al. 1987; Freedman et al.

1989; Stohs and Bagchi 1995; Rau et al. 2004; Wang et al. 2004). Oxidative stress is normally

mitigated with cellular antioxidant mechanisms, but prolonged exposure to elevated copper

concentrations can exha ust these defenses, and may result in the oxidation of DNA (strand

break), lipids (impaired cell membrane permeability) and proteins (Grosell 2012). ROS

neutralization includes antioxidant enzymes such as catalase, glutathione peroxidase and

reductase, and Cu/Zn superoxide dismutase. D etoxifying mechanisms include the induction of

metallothioneins and heat shock protein 70 (Sato and Bremner 1993; McDuffee et al. 1997;

Evans and Halliwell 2001). In summary, excessive copper concentrations compromise normal

c ell functions by disrupting osmoregulation and ion flow, inhibiting enzymes and ATP

- driven

pumps, and inducing oxidative stress, resulting in cell toxicity from oxidative damage and

### 16

disruption of cell homeostasis, and leading to changes in internal pH bala nce, membrane

potential, and osmosis (Okocha and Adedeji 2012).

Copper concentrations typically build up in tissues at the site of exposure, such as the gill

surface and gut tract wall (Chevreuil et al. 1995). Copper is then transferred via circulation to

other tissues and organs, with the liver and kidney typically accumulating high concentrations

relative to muscle tissues (Grosell 2012). Although copper bioaccumulates in some aquatic

species, there does not appear to be a consistent relationship between body burden and

toxicological effect (Meyer et al. 2005; DeForest and Meyer 2015). This inconsistent relationship

between whole body tissue concentration and toxic effect may be related to specific organs

and/or tissues where the accumulation is occurring. Therefore, it may not be accurately

quantified by whole body tissue residue analysis, and/or the metabolic bioavailability of copper

in tissues.

Since copper is an important trace nutrient, some organisms may have mechanisms for

maintaining homeostasis, such as detoxification, making it more difficult to study th e

relationship between body burden and toxic effect . Detoxification mechanisms in aquatic

organisms, including the formation and activation of antioxidants, metallothionein, glutathione,

and heat shock proteins ( McGeer et al. 2011) effectively sequester the metal in a detoxified form,

thereby allowing the organism to accumulate elevated levels of copper before displaying a toxic

response. While the amount of detoxified metal that an aquatic organis m can accumulate is

theoretically unlimited, an organism will only experience toxic effects once the concentration of

metabolically required metal is exceeded (Rainbow 2002; Rainbow and Smith 2013). Under

natural conditions, most accumulated copper in tiss ues is expected to exist in a detoxified state,

which may explain the poor relationship between whole body tissue residue concentrations and

toxic effect o bserved in tested aquatic invertebrates and fish ( Rainbow 2002).

An additional consideration is the potential for copper in aquatic prey items (e.g.,

invertebrates) to adversely affect higher trophic level organisms

, such as fish and aquatic

dependent wildlife via dietary exposure . This exposure pathway does not show a c onsistent dose

response relationship because the bioavailability of copper to top predators differ s substantially

among prey species that are consumed ( U.S. EPA 19 9 3 ) . Further, t here are numerous different

prey types and amounts eaten by each predator , thus complicating the estim ate of a safe dose to

higher trophic level organisms ( this and other uncertainties are discussed in Section 4.3.1 ).

### 17

Overall, however , the risk to h igher trophic level species is considered low because researchers

have found that copper generally does not accumulate or biomagnify in aquatic food chains

(Lewis and Cave 1982; Suedel et al. 1994). The evaluation of effects from the direct exposure of

organism tissues (e.g.

, gills and other biological membranes) to copper in water is therefore

considered more applicable to the development of criteria for aquatic life and was the focus of

the development of criteria for estuarine/marine aquatic life.

The toxicity of copper to a quatic life is related primarily to the activity of the cupric ion,

and possibly to some hydroxy complexes (Allen and Hansen 1996; Andrew 1976; Andrew et al.

1977; Borgmann and Ralph 1983; Chakoumakos et al. 1979; Chapman and McCrad y 1977;

Dodge and Theis 1979; Howarth and Sprague 1978; Pagenkopf 1983; Petersen 1982; Rueter

1983). Examples of the response of organisms to cupric ion activity, and limited exceptions, are

reviewed by Campbell (1995). Any changes in water quality that wo uld be expected to decrease

free copper ion activity also would be expected to decrease copper bioavailability and resulting

toxicity. For example, increases in pH, alkalinity, and NOM (as represented by DOC) would all

tend to decrease copper bioavailabili ty and be associated with increased copper LC 50 

### values. The

following section discusses in detail the characterization of water quality parameters and their

effect on bioavailability.

2.4 Overview of Historic and BLM Criteria Development Methods

Early nationa l recommended aquatic life criteria for copper (U.S. EPA 1980, 1984,

1995a, 1996, 2003) considered bioavailability effects for freshwater organisms based on water

hardness by incorporating linear regression equations into the criterion

- calculation procedur e to

account for the decreasing acute and chronic toxicity of copper to freshwater biota with

increasing water hardness. Temperature did not vary significantly for tests with most species, pH

values were often not reported or were highly variable, and alka linity and DOC were rarely

reported. Accordingly, freshwater criteria for copper, and those for several other metals, were

established as functions of water hardness alone. However, the regression coefficients for

hardness did not only reflect how hardness affected copper toxicity. H ardness was instead a

surrogate for other co

- varying water quality parameters that were not included in the regression

analyses and t h e criteria based on hardness alone did not explicitly account for the mo difying

effects of the se other water parameters.

### 18

An alternate approach that has been proposed to predict metal toxicity is to (1) identify

the bioavailable f

orm(s) of the metal; (2) analyze or calculate the concentration(s) of the

bioavailable form(s) in the exposure water; and (3) predict the toxicity based on an empirical

relationship between the biological response and the concentration(s) of the bioavailable form s

( Santore et al. 2001 ). This approach only requires the direct measure or calculation (using a

geochemical

- specia tion model) of the free metal ion ( Cu 2+ 

### ) concentration , which is the

bioavailable

- fraction of copper in water

. T he concentration of Cu 2+ 

### has been demonstrated to be

an accurate indicator of acute toxicity, as characterized by trends in the LC 50 

### values, eve n in the

presence of varying levels of inorganic or organic ligands, which can complex with copper and

alter the Cu 2+ 

### concentration (e.g., Borgmann 1983; Santore et al. 2001). This approach , however,

loses accuracy when other cations are present in water t hat can interact with biota. For example,

the LC 50 

### of Cu 2+ 

### increases significantly as the concentration of Ca 2+ 

### ( a major component of

water hardness) increase s (Campbell 1995; Meyer et al. 1999) . This trend indicates that the

concentration of cupric ion al one is not always sufficient to predict toxicity.

In general, there is no universally constant bioavailable fraction of a metal that can be

identified by chemical analyses (Meyer et al. 2002). The interactions amongst the key abiotic

components in exposure water must be considered in conjunction with the interactions of those

key abiotic components directly with biota. Metal bioavailability may also be modified by

competitive interactions at the biotic ligand (i.e. biological membranes of toxic interaction ).

Increased sodium and calcium concentrations, for example, can reduce the binding of copper to

physiologically active binding sites and can thereby reduce copper bioavailability. Cation

competition also has an effect on the complexation of copper by DOC, and this interaction will

partially offset competitive interactions that occur at the biotic ligand

. The complex interactions

of Cu 2+ 

### with dissolved components, suspended particles, and biota therefore must be

simultaneously considered in order to accurat ely predict copper toxicity.

The chemical speciation of copper in natural waters and explanatory power of the free

copper ion in characterizing copper toxicity were first recognized more than 30 years ago

(Anderson and Morel 1978; Sunda and Gillespie 1979; Sunda and Guillard 1976; Sunda and

Lewis 1978; Zitko et al. 1973). These concepts were eventually formalized in models that linked

metal chemistry and biological effects, such as the gill surface interaction model (GSIM)

(Pagenkopf 1983) and the free ion activity model (FIAM) (Morel 1983). Playle and others

### 19

demonstrated that copper binding to fish gills can be modeled using a chemical speciation

approach (Playle et al. 1993a, 1993b). MacRae and others demonstrated that copper binding on

the gill shows a do se

- response relationship with mortality (MacRae et al. 1999). Although early

models showed remarkable utility, several critical issues remained. Perhaps most notably, and

until recently

, few models could predict metal chemistry in the presence of NOM over a range of

environmental conditions (Bergman and Dorward

- King 1997). A considerable amount of

information about metals speciation in the environment has since become available and

computing techniques have been further develope d to simulate metal speciatio n (e. g., Nordstrom

et al. 1979). T hese early efforts , however, laid the foundation for the development and use of the

BLM to predict adverse effect levels of metals as a function of site

- specific water chemistry (Di

Toro et al. 2001). A more comprehensive review of these historical developments is presented in

Paquin et al. (2002).

The BLM is a metal bioavailability model that considers chemical and physiological

effects information for metals in aquatic environments and was originally developed for

freshwa ter settings (Di Toro et al. 2001; Paquin et al. 2002; Santore et al. 2001) . The approach

was first presented to EPA’s Science Advisory Board in 1999 where it received a generally

favorable response (U.S. EPA 1999, 2000). Like the FIAM and GSIM, the BLM is based on a

description of the chemical speciation of metals in aqueous systems ( Figure 3 ). Chemical

speciation is simulated as an equilibrium system that includes the complexation of inorganic ions

and NOM. The chemical system for the original freshwater BLM was simulated by the chemical

equilibria in soils and solutions (CHESS) model (Santor e and Driscoll 1995), including a

description of metal interactions with NOM based on the Windermere humic aqueous model

(WHAM) (Tipping 1994). A significant advantage of the NOM chemistry developed for WHAM

is that reactions and parameter values were deve loped by simultaneously considering numerous

NOM samples and numerous metals. A chemical de scription was needed specifically

characterizing chemical speciation for the saltwater BLM , but the basic principles of metal

speciation are similar to those establi shed by the development of the models used for the original

freshwater BLM (Chadwick et al. 2008).

### 20

Figure 3

. Conceptual Diagram Showing Relationship between Chemical Speciation, Metal

Binding at Biotic Ligand (BL) Sites, and Comp etition at These BL Sites for Other Cations

. ( A dapted from Santore et al

. 2001)

.

In addition to considering chemical speciation, the BLM also includes reactions that

describe the chemical interactions of copper and other cations with physiologically active sites,

termed biotic ligands (BLs)

. BL s correspond to the proximate site of action of toxicity in aquatic

organisms and can be present on any biological membrane . The model parameters define the

degree of interaction based on binding affinity charac teristics measured in gill

- loading

experiments. The BL is represented by a characteristic binding site density and conditional

stability constant for each of the dissolved chemical species with which it reacts. Predictions of

metal toxicity are made by ass uming that the dissolved metal LC 50 

### , which varies with water

chemistry, is always associated with a fixed critical level of metal binding with the BL. This

fixed level of metal

- biotic ligand (Me:BL) accumulation at 50 percent mortality has been

referred to as the “lethal accumulation 50%” (LA 50 

### ), but since the BLM can also apply to sub

lethal endpoints

, this parameter has been more generic ally t ermed “critical accumulation

. ”

Copper accumulation on the BL is characterized by a rapid and reversible chemical i nteraction

with binding sites on biological membranes, and is not in any other way similar to accumulation

that results from uptake within the organism

. It is assumed to be constant, regardless of the

chemical characteristics of the water (Meyer et al. 199 9, 2002). This combination of reactions

### 21

that describe aqueous metal speciation and organism interactions allows the BLM to predict

copper toxicity to a variety of organisms over a variety of water quality conditions (Santore et al.

2001).

The saltwater BLM for copper was developed from independent datasets that could be

used to characterize copper speciation, surficial copper binding to membranes

, and toxicity

(Chadwick et al. 2008) . The chemistry model used to represent interactions between copper and

diss olved organic matter (DOM, usually measured as DOC) included four discrete ligands and

was calibrated to titration results with over 60 water samples . The calibrated model was then

validated using an additional dataset that was similar in breadth (>60 titr ations). The established

relationship between free copper, dissolved copper, and DOC in marine waters was demonstrated

to describe the range of copper c oncentrations that bracketed anticipated marine criteria val ues

that would be protective of sensitive ma rine invertebrates (Chadwick et al. 2008). The

development effort included calibration and validation steps. Extensive datasets from San Diego

Bay and Pearl Harbor were used in the analysis. Subsets of the data from each site were assigned

as calibration or validation data. Calibration data were us ed in the parameterization of the model,

while the validation data were only used to test overall goodness of fit (Chadwick et al. 2008).

Validation was performed by comparison with chemical speciation data (i.e., free copper ion),

and measured copper toxi city to sensitive marine invertebrates.

Binding constants for copper and other cations to the BL for the saltwater BLM were

developed from data reported by Rosen et al. (2008), which included copper accumulation data

for both Mytilus galloprovincialis and Strongylocentrotus purpuratus. These accumulation data

were measured in short

- term exposures designed to quantify copper interactions with the

surficial membranes of embryolarval forms of these marine organisms and should not be equated

with whole

- body acc umulation in more well

- developed life stages, which may represent uptake

and incorporation of copper in the tissue of multiple organs. The dose

- response (percent

abnormal) curves for different water samples having different DOC levels differed from each

ot her when the exposure was characterized only on the basis of dissolved copper. However, a

single dose

- response curve can characterize copper toxicity in these different samples when

exposure is expressed as embryo

- larvae whole body copper concentrations ( Figure 4 )

. The

ability of a single relationship between accumulation and toxicity in different samples indicates

that the surficial copper binding to ce ll membranes (which can be measured as whole b ody

### 22

accumulation in embryolarval forms of these organisms ) on the larval life stages is directly

related to the copper bound to the site of toxic action. The resulting saltwater BLM is thus

demonstrated to consistently simulate accumulated copper using a single model representation

for both M. galloprovincialis and S. purpuratus , as shown in Figure 5

.

An advantage of the BLM is that most of the parameters are invariant for different

organisms, despite the complexity of the modeling framework. All of the thermodynamic

constants used to simulate inorganic and organic chemical equilibrium reactions are d etermined

by characteristics of the metal and the available ligands. As such, the constants do not change for

simulations involving different organisms. This is an important consideration in the development

of the BLM. In a recent review, Erickson (2013) c autioned against the introduction of additional

parameters that weaken the mechanistic framework of the model. In particular, Erickson

cautioned about inferring accumulation

- based effects from toxicity measurements. In the

development of the marine copper BLM , the critical accumulation for several sensitive

organisms were taken from direct measurements ( Figure 4 ) rather than inferred from toxicity

data. These measurements confirmed several assumptions made during the development of the

freshwater model. First

, that the same accumulation model (and hence the same BL parameters)

could be used to describe accumulatio n to different organisms [ for example Mytilus in Figure 4

(Panel A) and Strongylocentrotus in Figure 4 (Panel B ) ] . Second

, that the difference in

sensitivity between these organisms is due to different critical accumulation levels (vertical

dashed lines in Figure 4 ) . The critical accumulation, therefore, is the only model parameter that

is needed to account for differences in organism sensitivity.

### 23 A

B

Figure 4

. Percent Abnormal Cells in Test Waters with Different Composition (primarily

DOC) for M. galloprovincialis (Panel A) and S. purpuratus (Panel B)

. ( Samples collected from different areas are labeled with the sample identifier (N or S). Values c ollapse

i nto a s ingle d ose r esponse w hen c ompared w ith m easured c opper accumulation)

. 

### (Chadwick et al.

2008)

.

### 24 A

B

Figure 5

. Predicted Copper B inding to BL S ites on C ell M embranes (solid lines) by the

Saltwater BLM for Copper w ith a Single Set of Parameters Compared w ith Measured

Copper Accumulation for Embryo

- larval Stages of M. galloprovincialis (Panel A) and S.

purpuratus (Panel B)

. (Samples collected from different areas are labeled with the sample identifier (N or S). (Chad wick et al.

2008).

### 2 5

Toxicity data were used to evaluate the critical accumulation values for M.

galloprovincialis and S. purpuratus and to predict EC 50 

### values for these t wo organisms. Coupled

with the toxicity data, the BLM can predict how much dissolved copp er is associated with

crit ical accumulation in waters of varying composition, and how toxicity change s in response to

changes in key environmental variables

, such as DOC. The resulting model can predict toxicity

to both M. g alloprovincialis and S. purpuratus over a wide range of conditions for waters from

different geographic regions ( Figure 6 )

.

Accumulation values that w ere available for M. galloprovincialis and S. purpuratus we re

not available for other organisms having toxicity data

. T o incorporate other organisms into t he

BLM

, water effect concentration s (ECs) were extrapolated for the biological species for w hich

accumulation data are not available. This is the same approach as was used for the BLM

- based

copper criteria for fresh water (U.S. EPA 2007). The general procedure used for the freshwater

criteria development was to normalize all available toxicity data to selected water chemistry

values , calculate criteria values at these conditions , and then use the normalization procedure to

compute criteria at other water chemistry conditions

. With this approach, t he BL parameter

values developed from M. galloprovincialis and S. purpuratus accumula tion measurements are

assumed to be constant for other sensitive ma rine invertebrates. This approach has been shown to

work well when used to predict copper effect levels for other freshwater organisms (U.S. EPA

2007) . The same accumulation model was first used to evaluate the critical accumulation for the

additional organisms, and then used to predict effect levels . It was determined that 94% of all

predictions were within a factor of two of the measured EC 50 

### ( Figure 7 ).

### 26 A

B

Figure 6

. Predicted Copper Toxicity by the Saltwater BLM for Copper (solid lines) in

Response to Changing DOC f rom a Variety of Estuarine and Marine Sites Compared with

Measured Copper Toxicity for Embryo

- larval Stages of M. galloprovincialis (Panel A) and

S. purpur atus (Panel B).

(Dashed lines indicate plus or minus a factor of two around the solid line. Variation within these

boundaries represents the variability of replicate toxicity tests).

### 27 A

B

Figure 7

. Predicted Copper Toxicity by th e Saltwater BLM for Copper (solid lines) in

Response to Changing DOC f rom a Variety of Estuarine and Marine Sites Compared w ith

Measured Copper Toxicity for Embryo

- larval Stages of Dendraster (Panel A) and

Crassostrea (Panel B).

(Dashed lines indicate plus or minus a factor of two around the solid line. Variation within these

boundaries represents the variability of replicate toxicity tests).

### 28

While many of the concepts and conditions applicable to the freshwater BLM for copper

also apply to estuarine/marin e waters, there are some differences. First, the concentrations of all

ions in saltwater are much higher than in freshwater (Morel and Hering 1983). Second, in waters

with constant salinity, the ionic composition is well defined and consistent so the likel ihood that

changes in ion ic composition could result in observable bioavailability effects is lower than for

freshwater (Stumm and Morgan 1981). Although water samples from estuaries may be collected

across a range of salinities, toxicity tests with copper are typically conducted with embryo

- larval

stage s of sensitive marine invertebrates such as Mytilus or Crassostrea (Arnold et al. 2010a;

Rosen et al. 2005)

. A vailable toxicity data indicate that t he early life stages of these bivalve

molluscs are amongst the most sensitive marine organisms to copper (U.S. E PA 1995a; Table 3).

However

, the early life stages of these species have a narrow r ange of salinity tolera nce. W hen

used to test copper toxicity in estuarine samples, standard procedures therefore require that the

salinity of test solutions be incr eased to full marine salinity (e.g., 30 to 32 ppt; U.S. EPA 1995a).

Although it is expected that cation competitio n plays a role in determining metal bioavailability

along salinity gradients, the effects of salinity on copper bioavailability are absent in the majority

of toxicity da ta sets that are available

, due to the standard practice of adjusting samples to full

s trength salinity

. In tests where estuarine samples have been salted up to marine salinity, the

potential effects of variable salinity on copper toxicity have been eliminated, leaving only DOC

as the primary toxicity modifying factor (such as in Figure 6 and Figure 7 ).

Recent tests with sensitive invertebrates capable of tolerating a wide range of salinities

have shown that the same bioavailability relationships involving pH, DOC, and salinity also

apply in estuar ine conditio ns when tested over a range of salinities (Arnold et al. 2010b, 2010c;

Cooper et al. 2012; Hall et al. 1997, 2008). These studies have shown that copper bioavailability

is reduced at high salinity , which is consistent with effects pred icted by the saltwater BLM for

copper. For example, Arnold et al

. (2010c) found that EC 50 

### s for Brachion u s plicatilis rang ed

from less than 40 μg/L at a salinity of 5 ppt, to approximately 70 μg/ L at a salinity of 30 ppt.

S imilar results were reported by Co oper et al

. (2012) for B. plicatilis

. The overall results from

Cooper et al

. (2012) suggest that both salinity and DOC are important in estuarine samples and

the combined effects are consistent with predict ions by the saltwater BLM

. Increasing salinity

was also shown to have variable effects to the polychaete Hediste (Ozoh 1992a,b). I n exposures

### 29

with sediment, the effect of salinity on copper toxicity was small and variable depending on the

temperature, while in water

- only exposures t here was a reduction in copper bioavailability with

increasing salinity similar to that seen in rotifers (Ozoh 1992a,b). The saltwater BLM for c opper

is therefore considered predictive of copper effects to sensitive estuarine invertebrates.

2.5 Conceptual Mod el

A conceptual model characterizes relationships betw een human activities, stressors and

ecological effects on the assessment endpoints identified for evaluation (U.S. EPA 1998). The

conceptual model links exposure characteristics with the ecological endp oints important for the

development of management goals. Under the CWA, these management goals are established by

states and tribes as designated uses of waters of the United States (for example, the protection of

aquatic life). In deriving aquatic life cr iteria, U.S. EPA is developing acceptable thresholds for

pollutants that, if not exceeded, are expected to be protective of aquatic life. A state and/or tribe

may implement these criteria by adopting them into their respective water quality standard s.

The conceptual model depicted in Figure 8 provides a broad overview of how aquatic

organisms could be exposed to copper in the estuarine/marine environment . As depicted in

Figure 8 and discussed in Section 2.1

, c opper enters the environment from both natural and

anthropogeni c sources. The environmental fate properties of copper indicate that weathering and

erosion of natural sources and inputs from a variety of anthropogenic sources represent potential

mechanisms t hat can transport copper from these sources to surface water ( TDC Environmental

2004; U.S. EPA 2010a). The model also depict s exposure pathways for potential biological

receptors ( e.g., non

- target aquatic animals) and potential attribute changes ( e.g., reduced

survival, growth and reproduction) in those receptors due to c opper exposure. The conceptual

model diagram ( Figure 8 ) depicts where the BLM predicts how water quality parameters

(especially DOC) influence the uptake/gill or integument exposure pathway

. Copper also has the

potential for adsorption to sediment and to bioaccumulate in aquatic organism tissues . T here is

accordingly the potential for the exposure of benthic organis ms to copper in sediment (pore

wat er) and the potential for the exposure of carnivorous mammals and birds via the consumption

of aquatic in vertebrates and fish that have accumulated copper (terrestrial effects were not

assessed) . Aquatic toxicity assessments assume anthropogenic exposure occurs primarily as a

result of direct release/discharge to surface water and /or following partitioning from sediment to

### 30

surface water

. The transport and l eaching of copper from groundwater to surface water is

assumed to be negligible (U.S. EPA 2010a).

The conceptual model is intended to provide a broad overview of how aquatic organisms

can potentially be exposed to c opper . Transport mechanisms and exposure pathways are not

considered in the derivation of aquatic life criteria

. Derivation of criteria instea d focuses on the

effects of copper on survival, growth and reproduction of aquatic organisms based on its

presence in the aquatic environment

. However, the pathways, receptors, and attribute changes

depicted in Figure 8 may be helpful for states and authorized tribes as they adopt criteria into

standards and need to evaluate potential exposure pathways affecting designated uses.

Figure 8

. Conceptual Model for Copper Effects on Aquatic Organisms.

(Dotted arrows indicate exposure pathways that have a low likelihood of contributing to ecological risk ).

### 31

2.6 Assessment Endpoints

Assessment endpoints are defined as the ex plicit expressions of the environme ntal values

to be protected and are comprised of both the ecological entity (e.g., a species, community, or

other entity) and the attributes or characteristics of the entity to be protected (U.S. EPA 1998).

Assessment end points may be identified at any level of organization (e.g., individual organism

,

population, community). In context of the CWA , aquatic life criteria for toxic substances are

typically determined based on the results of toxicity tests with aquatic organis ms, for which

adverse effects on growth, reproduction or survival are measured. This information is aggregated

into a species sensitivity analysis that characterizes an impact to the aquatic community. Criteria

are designed to be protective of the vast ma j ority of aquatic organisms in an aquatic community

(i.e., approximately the 95 th 

### per centile of tested aquatic organisms representing the aquatic

community). Assessment endpoints consistent with the criteria developed in this document are

summarized in Table 2

.

2.7 Measurement Endpoints

Assessment endpoints require one or more measures of ecological effect, which are

termed “measurement endpoints

. ” Measur ement endpoints are the measures of ecological effect

used to characterize or quantify changes in the attributes of an assessment endpoint or changes in

a surrogate entity or attribute, in this case a response to chemical exposure. Toxicity data are

used a s measures of direct and indirect effects on representative biological receptors. The

selected measures of effect for the development of aquatic life criteria encompass changes in the

growth, reproduction, and survival of aquatic organisms.

The toxicity d ata used for development of the aquatic life criteria depend on the

availability of applicable toxicity test outcomes, the acceptability of test methodologies, and an

in

- depth evaluation of the acceptability of each specific test, as performed by the U.S. EPA per

its Guidelines (1985) . Measurement endpoints for the development of aquatic life criteria are

derived using acute and chronic toxicity studies for representative test species, which are then

quantitatively and qualitatively analyzed, as described i n the Analysis Plan below. Measurement

endpoints considered for each assessment endpoint in this criteria document are summarized in

Table 2

. The following sections discuss toxicity data requirements for the fulfillment of these

measurement endpoints.

### 32

Table 2

. Summary of Assessment Endpoints and Measures o f Effect Used in Criteria

Derivation.

Assessment Endpoints for the Aquatic

Community Measures of Effect

Survival, growth, biomass, and reproduction of

fish and invertebrates (estuarine/marine) Acute: LC 50 

### , EC 50



### Chronic: EC 20 

### , MATC (only used when an EC 20 

### could not be calculated for the genus)

Maintenance and growth of aquatic plants from

standing crop or biomass ( estuarine/marine) LOEC, EC 20 

### , EC 50 

### , IC 50 

### , reduced growth rate, cell

viability, calculated MATC

MATC=Maximum acceptable toxicant concentration (geometric mean of NOEC and LOEC)

NOEC=No observed effect concentration

LOEC=Lowest observed effect concentration

LC 50 =Lethal concentration to 50% of the test population

EC 50 /EC 20 =Effect concentration to 50%/20% of the test population

IC 50 =Concentration of copper at which some effect is inhibited 50% compared to control organism



### 2.7.1 Overview of Toxicity Data Requirements

U.S. EPA has specific data requirements to assess the potential effects of a stressor on an

aquatic ecosystem and develop 304(a) aquatic life criteria under the CWA. To develop 304(a)

criteria for estuarine/marine aquatic life under CWA, EPA typically requires the following :

 Acute toxicity test species data from a minimum of eight diverse taxonomic groups as

follows:

o tw o families in the phylum Chordata

o a family in a phylum other than Arthropoda or Chordata

o a family from either Mysidae or Peneidae

o three other families not in the phylum Chordata (may include Mysidae or

Penaeidae, whichever was not used above)

o any other family

 Chronic toxicity te st data (longer

- term survival, growth, or reproduction) are generally

required for a minimum of three taxa, with at least one chronic test being from an

acutely

- sensitive species. Acute

- chronic ratios can be calculated with data f or species of

aquatic anim als from at least three different families if the following data requirements

are met:

o at least one is a fish

o at least one is an invertebrate

o at least one is an acutely sensitive sal twater species (the other two may be

freshwater species)

### 33

2.7.2 Measures of Ef

fect

Acute measures of effect

The acute measures of effect used for organisms in this document are the LC 50 

### , EC 50 

### , and

IC 50



### . LC stands for “Lethal Concentration” and an LC 50 

### is the concentration of a chemical that is

estimated to kill 50 percent of the test organisms

. EC stands for “Effective Concentration” and

the EC 50 

### is the concentration of a chemical that is estimated to produce a specific effect in 50

percent of the test organisms

. IC stands for “Inhibitory Concentration” and the IC 50 

### is the

concentration of a chemical that is estimated to inhibit some biological process (i.e. growth, etc.)

by 5 0 percent compared to a control.

Chronic measures of effect

The e ndpoints for chronic measures of exposure are the NOEC, LOEC, MATC and EC 20



### .

The NOEC (i.e., “No

- Observed

- Effect

- Concentration”) is the highest test concentration at which

none of the observed effects were statistically different from the control

. The LOEC (i.e.,

“Lowest

- Observed

- Effect

- Concentration”) is the lowest test concentration at w hich observed

effects is statistically different from the control

. The Maximum Acceptable Toxicant

Concentration (MATC) is the calculated geometric mean of the NOEC and LOEC. T he EC 20



### ,

which represents a 20 percent effect/inhibition concentration, is a low level of effect that is

generally significantly different from the control treatment.

Data available for measuring effect

Effect d ata for copper were obtained from studies published in the open literature and

identified in a search of the ECOTOXicology database ( Available online at:

https://cfpub.epa.gov/ecotox/ )

. ECOTOX is a source of high quality toxicity data for aquatic life,

terrestrial plants, and wildlife. The database was created an d is maintained by the EPA, Office of

Research and Development, National Health and Environmental Effects Research Laboratory's

Mid

- Continent Ecology Division

. The latest comprehensive literature search for this document

was conducted in April 2016

.

Follo win g initial identification with the ECOTOX database search, a further evaluation of

available data was performed by EPA to determine test acceptability

. The amount of toxicity

testing data available for any given pollutant varies significantly, depending primarily on

whether it has raised any significant environmental issues and, in the case of a pesticide, how

### 34

long it has been registered. Appendix A of Quality Criteria for Water 1986 ( U.S. EPA 1986 b )

provides an in

- depth discussion of the minimum data req uirements and data quality requirements

for aquatic life criteria development.

As discussed above, t he assessment endpoints for aquatic life criteria are based on the

growth, reproduction, and survival of the assessed taxa , while t he specific measures of effect are

provided by the acute and chronic toxicity data ( Table 2 )

. The toxicity endpoints derived from

these data are expressed as the g eometric means of acute values for a ll species of the same genus

(GMAVs) or geometric means of the chronic values for a ll species of the same genus ( GM C Vs )

.

GMAVs and GMCVs are used in the applicable species sensitivity distribution s of the available

aquat ic community data to derive the acute and chronic aquatic life criteria

.

Table 3 provides a summary of the data used to fulfill the minimum data requirements

(MDR) outlined in the EPA Guidelines ( Stephan et al. 1985) for derivation of the

estuarine/marine acute criteri on for copper

. It also provides a summary of the number of

families, genera, and species with acceptable acute and chronic toxicity data. There are a total of

seven phyla in the acute copper toxicity database representing 63 families

, 7 8 genera , and 89

specie s . The copper toxicity dataset far exceeds the MDRs for derivation of an estuarine/marine

acute criterion. A cceptable estuarine/marine copper chronic value s are available for only two

species, the euryhaline rotifer, Brachionus plicatilis (Arnold et al. 2010b ) and the sheepshead

minnow

, Cyprinodon variegatus (Hughes et al. 1989) . Consistent with U.S. EPA’s Guidelines,

freshwater toxicity data were therefore integrated into the derivation of the chronic criterion.

Data that were determined to have acceptab le quality and to be useable in the derivation of water

quality criteria as described in U.S. EPA’s Guidelines for the derivation of acute and chronic

criteria are presented in Appendix Table A

- 1 and Appendix Table B

- 1 , respectively.

### 35

Table 3 . Summary Table of Acceptable Toxicity Data Used to Meet the Minimum Data Requirements in EPA’s Guidelines and

Count of Phyla, Families, Genera and Species.

Family Minimum Data Requirement

( Estuarine /Marine) Acute

Phylum / Family / Genus Chronic

Phylum / Family / Genus

Family in the phylum Chordata Chordata / Atherinopsidae / Menidia Chordata / Cyprinodontidae / Cyprinodon

Family in the phylum Chordata Chordata / Sciaenidae / Leiostomus

- Either the Mysidae or Penaeidae family Arthropoda / Mysidae / Americamysis

- Family in a phylum other than Arthropoda or Chordata Mollusca / Mytilidae / Mytilus Rotifera / Brachionidae / Brachionus

Family in a phylum other than Chordata Rotifera / Brachionidae / Brachionus

- Family in a phylum other than Chordata Echinodermata / Diadematidae / Diadema

- Family in a phylum other than Chordata Cnidaria / Aiptasiidae / Aiptasia

- Any other family Arthropoda / Crangonida / Crangon

- Dash (

- ) indicates requirement not met (i.e., no acceptable data).

Estuarine/Marine Acute Estuarine /Marine Chronic

Phylum Families GMAVs SMAVs Families GMAVs SMAVs

Annelida 4 5 5

- - - Arthropoda 23 31 34

- - -

Chordata 18 21 24 1 1 1

Cnidaria 1 1 1

- - -

Echinodermata 5 5 6

- - -

Mollusca 11 14 18

- - -

Rotifera 1 1 1 1 1 1

Total 63 78 89 2 2 2

### 36

2.8 Analysis Plan

Although the BLM

- based approach for copper in estuarine/marine waters has now been

developed for use in place of the former

, non

- BLM

- based approach, the updated criteria

derivations in this document are still based on the principles set forth in EPA’s Guidelines

( Stephan et al. 1985 ). Therefore, it is useful to review how the Guidelines are applied.

During CWA § 304(a) criteria development, U.S. EPA reviews and considers all relevant

toxicity test data. Information available for all relevant species and genera are reviewed to

identify: ( 1) data from acceptable tests that meet data quality standards; and ( 2) whether the

acceptable data meet the MDRs as outlined in U.S. EPA’s Guidelines ( Stephan et al. 1985 ; U.S.

EPA 1986 b ). The taxa represented b y the different groups comprising the MDR s are comprised

of taxa with different ecological, trophic, taxonomic and functional characteristics in aquatic

ecosystems, and are intended to be a representative subset of the diversity within a typical

aquatic community. Although the aquatic life criteria process is base d on selected toxicity

endpoints from the most sensitive species tested, the criteria derived may not necessarily reflect

the most sensitive species existing in a specific environment. If plants are more sensitive than

vertebrates and invertebrates, plant criteria are developed if sufficient data are available to

support its derivation

.

Application of the saltwater BLM to the derivation of the estuarine/marine F inal Acute

V alue is analogous to procedures already described in EPA’s criteria for metals criter ia using

empirical hardness regressions. For these hardness

- dependent metals criteria, LC 50 

### s at various

hardness levels are normalized to a selected hardness using the regression slopes. Similarly

, the

acceptable acute and chronic data are normalized to th e selected water chemistry conditions

using the BLM, and then the criteria are derived according to the Guidelines. The values

presented below are relative only to the selected water chemistry for comparison purposes. The

saltwater BLM

- based criteria will in some cases be more stringent and in other cases less

stringent than the previous criteria , depending on specific water conditions used with the BLM

.

As there is not a single criterion value to use for comparison purposes, it will only be possible to

pro vide illustrative examples of each situation.

### 37

2.8.1 Acute Criterion Derivation

As recommended by the Guidelines, acute criteria are based on a species se nsitivity

distribution (SSD) comprised of genus mean acute values (GMAVs), which are calculated from

species mean acute values (SMAVs) for available and acceptable data

. SMAVs are calculated

using the geometric mean for all acceptable toxicity tests for a given species (e.g. all tests for

Mytilus edulis )

. If only one test is available, the SMAV is that test value by default

. GMAVs are

then calculated using the geometric means of all SMAVs within a given genus (e.g. all SMAVs

for the genus Mytilus

- Mytilus edulis

, Mytilus galloprovincialis )

.

The est uarine/marine acute criterion is based on the Final Acute Value (FAV). The FAV

is determined by first ordering the GMAVs by rank from most sensitive (Rank 1) to least

sensitive (Rank N

) for linear regression analysis. The regression analysis is typically driven by

the four most sensitive genera reflect ing the lowest GMAVs in the sensitivity distribution, based

on the need to interpolate or extrapolate (as appropriate) to the 5 th 

### percentile of the distribution

represented by the tested genera

. The FAV represents a hypothetical genus more sensitive than

95 percent of representative gene ra. Consistent with EPA’s Guidance, b ecause more than 59

GMAVs were available for copper , the FAV was derived from the four GMAVs that have

cumulative probabilities closest to the 5 th 

### percentile toxicity value for all the tested genera. The

acute criterion , defined as the Criterion Maximum Concentration (CMC)

, is then calculated by

dividing the FAV by two, which is intended to provide an acute criterion protective of nearly all

individuals in the distribution ( Stephan et al. 1985 )

. T he FAV may be lowered to protect

recreationally or commercially important species

.

As discussed above, a cute toxicity test data must be available for species from a

minimum of eight genera with a specified minimum required taxonomic diversity as established

by the MDRs . Th e diversity of tested species required by the MDRs is intended to ensure the

protection of various components of an aquatic ecosystem. Although the aquatic life criteria

derivation process relies on selected toxicity endpoints from the sensitive species tested, it does

not necessarily mean that the selected toxicity endpoints reflect the sensitivity of the most

sensitive species existing with in a given habitat

. The intent of the eight MDR s is instead to serve

as a rep resentative sample of the aquatic community , with the MDR s represent at ive of the

different ecological, trophic, taxonomic and functional differences observed in the natural

aquatic ecosystem

. Use of the SSD method where the criteria value s are based on the four most

### 38

sensitive taxa is reflective of the whole distribution, representing a censored statistical approach

that improves estimation of the lower tail when the shape of the whole distribution is uncertain

.

2.8.2 Chronic Criterion Derivation

A chronic criterion is typically determined by one of two methods. If MDRs are met with

acceptable chronic test data available for all eight families, then the chronic criteria can be

derived using the same method as for the acute criteria, employing chronic values (e.g., EC 20 

### )

estimated from acceptable toxicity tests. In cases where less chronic data are available , but where

there are at least three chronic tests from taxa that also have appropriate acute toxicity data

, the

chronic criterion can be derived by determ ining an appropriate acute

- chronic ratio (ACR)

. The

ACR is a way of establishing a relationship between the acute and chronic toxicities of a

chemical to aquatic organism

. A CRs can be used to derive chronic criteria with data for species

of aquatic animals provided that the MDR of at least three species is met and that:

 at least one species is a fish

 at least one species is an invertebrate

 at least one species is an acutely sensitive estuarine/marine species ( the other two species

data may be freshwater or estuarine/marine

, as appropriate

, for the derivation )

.

ACRs are calculated by dividing the acute toxicity test values by a “paired” chronic test value

.

Tests for a chemical are considered paired when they are conducted by the same laboratory, with

the sa me test organism and with the same dilution water. A chronic criterion is not derived if

there is more than a ten

- fold difference among st ACRs and if there is no clear trend related to

species sensitivity ( Stephan et al. 1985 ). If these criteria are met

, t he Final Acute

- Chronic Ratio

( FACR ) may be the geomet ric mean of the available ACRs or an individual ACR (or

combination therefore), based on the most sensitive taxa. The Final Chronic Value (FCV) is then

estimated by dividing the FAV by the FACR. This serves as the basis for the chronic criterion

.

T he FCV then may be lowered if necessary to protect recreationally or commercially important

species

.

2.8.3 BLM Evaluation

U se of the BLM to predict the b ioavailability and toxicity of copper to estuarine/marine

o rganisms under site

- specific conditions is a significant modification from the previous criteria

derivation methodology , which used no relationships (e.g., salinity) to adjust the criteria. As

detailed in Section 2.4 , t he BLM is based on the premise that toxicity is related to metal bound to

### 39

a biochemical site (the biotic ligand) and that binding is related to total dissolved metal

concentrations an d complexing ligands in the water , with the BLM explicitly account ing for

individual water quality variables that affect bioavailability and toxicity

. This document utilizes

the recently developed saltwater BLM to provide an updated B LM

- based water quality criterion

that is applicable to marine and estuari ne waters

.



### Table 4 summarizes the water quality input parameters required for the freshwater and

marine copper BLMs. As shown in Table 4 , the saltwater BLM for copper h as relatively few

input parameters, compared with the freshwater BLM.

Table 4 . Water Quality Input Parameters for the Freshwater and Saltwater Versions of the

BLM.

Freshwater BLM Input Parameters Saltwater BLM Input Parameters

Temperature Temperature

pH pH

DOC DOC

Calcium Salinity

Magnesium

Sodium

Potassium

Sulfate

Chloride

Alkalinity

Sulfide

Because the ionic composition of marine water is relatively constant (Turekian 1968), all

of the cations, anions, and alkalinity are esti mated from salinity. The major dissolved ions in

seawater (Cl, Na, Mg, SO 4 

### , Ca, K, HCO 3 

### ), and used in toxicity tests, are present in constant

ratios. Individual ion concentrations can therefore be easily calculated from a known salinity or

from the known concentration of a single ion (Pilson 1998). Th e defined and consistent ionic

composition of saltwater is what reduces the needed input parameters for the copper saltwater

BLM to just temperatu re, pH, DOC, and salinity. Approximating the ionic content of variable

salinity samples in this way assumes that the freshwater component mixing with the marine

water is devoid of ions. Actual freshwaters mixing into estuaries will, of course, have variable

### 40

ionic content. The deviation from this simp lified assumption and the actual chemistry of the

estuary will depend on how ionically rich the freshwater is, and how far up stream the estuary

(i.e., to how low a salinity level) the estimation is used. It is clear, however, that to the extent that

the ac tual ionic content is different, it will always be higher than the estimate, and therefore the

estimate will always be conservative

. Despite the reduction in the number of parameters needed

,

much of the currently available aquatic toxicity literature for m etals does not include the

measurement or reporting of all key BLM input parameters . Additional data were therefore

obtained from the authors, additional measurements were made in relevant wa ter sources, or

input parameters were estimated when necessary to fill in these data gaps

. As with any modeling

effort, however, the reliability of the BLM

- derived accumulation and toxicity values for this

project are subject to the limitations of the input measurements and estimation procedures

described above.

The c riteria presented herein are the agency’s best estimate of maximum concentrations

of copper to protect most estuarine/marine aquatic organisms from any unacceptable short

- or

long

- term effects. Results of such intermediate calculations such as SMAV and chr onic values

are specified to four significant figures to prevent round ing error s in subsequent calculations and

the number of places beyond the decimal point does not reflect the precision of the value.

### 41



## 3 EFFECTS ANALYSES FOR AQUATIC ORGANISMS

3.1 Summary of A cute Studies

T he acute criterion or CMC was calculated according to the procedure described in the

following section

. The reported acute toxicity values ( LC 50 

### s or EC 50 

### s ) determined to be

acceptable for use in criteria development ( summarized in Appendix Table A

- 1 ) and individual

test water chemistry parameters were first used to calculate lethal accumulation values (LA 50 

### s )

.

The LA 50 

### s represen t the critical threshold concentration s at the biotic ligand that result in acute

toxicity and were used to normalize toxicity values (e.g., LC 50 

### s) to a standard water condition

( Appendix Table A

- 1 , footnote e ). As used here, “normalization” refers to the procedure by

which all of the measured effect levels were adjusted, via use of the BLM, to predict effect

concentrations that would h ave been expected in the selected water chemistry ( see Section 3.3 )

.

LA 50 

### s were determined by running the saltwater BLM in speciation mode (see BLM User’s

Guide) 2



### . Th e resulting normalized effect concentrations were then used to calculate the Species

Mean Acute Values (SMAVs), Genus Mean Acute Values (GMAVs), and the Final Acute Value

(FAV) according to EPA’s Guidelines procedure. These values are rel evant (for comparison

purposes across species) only at the selected water chemistry values specified, but are used to

allow the BLM model to predict the FAV and criteria in any water chemistry condition

. Data that

were identified during the review, but tha t were not considered to be acceptable and not included

in the criteria calculations are listed in Appendix Table E

- 1

.

Acceptable data on the acute eff ects of copper on estuarine/marine species were available

for 89 species representing 78 genera ( Table 5 )

. BLM

- normalized (at the selected water

chemistry) SMAVs ranged from 3. 944 μg/L for the most sensitive species

, the red abalone,

Haliotis rufescens , to 81,550 μg/L for the least sensitive spe cies, the amphipod Corophium

volutator . Molluscs were among the most sensitive species, with H

. rufescens

, Mytilus edulis and

M. galloprovincialis

, having three of the five lowest SMAVs

. The other two of five lowest

SMAVs were for the copepod, Tigriopus californicus

, and the purple sea urchin,

Strongylocentrotus purpuratus ( Arnold et al. 2010a ; City of San Jose 1998 ; Dinnel et al. 1989 ;

2 The saltwater BLM has the same two prediction modes (speciation and toxicity) as the freshwater model. The

speciation mode is only used in the context of a data processing step and is n ot a mode that is needed or publicly

available in the software distributed for calculating estuarine/ marine criteria.

### 42

O’Brien et al. 1988 ; Rosen et al. 2008 ). Invertebrates , including molluscs

, were general ly more

sensitive than fish, rep resenting 19 of the 20 lowest G MAVs ( Table 5 ).

Table 5 . Ranked Estuarine/Marine Genus Mean Acute Values.

(All values were normalized to select water chemistry conditions

, see Section 3.3 ).

Rank Genus Mean

Acute Value

(μg/L) Genus Species Species Mean

Acute Value

(μg/L)

78 81,550 Corophium Amphipod,

Corophium volutator 81,550

77 43,694 Rangia Clam,

Rangia cuneata 43,694

76 >33,000 Opsanus Gulf toadfish,

Opsanus beta >33,000

75 31,716 Limulus Horseshoe crab,

Limulus polyphemus 31,716

74 >29,733 Gammarus Amphipod,

Gammarus duebeni >29,733

73 8,976 Callinectes Blue crab,

Callinectes sapidus 8,976

72 8,863 Micropogonias Atlantic croaker,

Micropogonias undulatus 8,863

71 8,423 Rivulus Mangrove killifish,

Rivulus marmoratus 8,423

70 4,898 Mugil Striped mullet,

Mugil cephalus 4,898

69 4,428 Centropomus Fat snook,

Centropomus parallelus 4,428

68 4,145 Lagodon Pinfish,

Lagodon rhomboides 4,145

67 3,715 Nitokra Copepod,

Nitokra spinipes 3,715

66 3,690 Boleophthalmus Mud

- skipper,

Boleophthalmus sp. 3,690

65 3,014 Litopenaeus Whiteleg shrimp,

Litopenaeus vannamei 3,014

64 2,590 Palaemonetes Grass shrimp,

Palaemonetes pugio 2,590

63 2,512 Terapon Thornfish,

Terapon jarbua 2,512

62 2,492 Emerita Sand crab,

Emerita analoga 2,492

61 2,163 Palaemon Decapod,

Palaemon elegans 2,163

60 2,057 Amphiascoides Copepod,

Amphiascoides atopus 2,057

### 43

Rank Genus Mean

Acute Value

(μg/L) Genus Species Species Mean

Acute Value

(μg/L)

59 1,675 Eurythoe Polychaete,

Eurythoe complanata 1,675

58 1,672 Sphaeroma Isopod,

Sphaeroma serratum 1,672

57 1,538 Crepidula Gastropod,

Crepidula convexa 1,105

Gastropod,

Crepidula fornicata 2,141

56 1,534 Archosargus Sheepshead,

Archosargus probatocephalus 1,534

55 1,416 Turbo Whelk,

Turbo coronatus 1,416

54 1,089 Planaxis Grooved snail,

Planaxis sulcatus 1,089

53 1,058 Penaeus Tiger shrimp,

Penaeus monodon 1,058

52 875.7 Trachinotus Pompano,

Trachinotus carolinus 875.7

51 730.8 Carcinus Shore crab,

Carcinus maenas 730.8

50 646.9 Perna Asian green mussel,

Perna viridis 646.9

49 623.4 Hediste Polychaete,

Hediste ( Nereis ) diversicolor 623.4

48 611.0 Cymatogaster Shiner perch,

Cymatogaster aggregata 611.0

47 589.5 Ophionereis Bristle star,

Ophionereis dubia 589.5

46 556.3 Fundulus Mummichog,

Fundulus heteroclitus 556.3

45 515.7 Allorchestes Amphipod,

Allorchestes compressa 515.7

44 512.2 Cyprinodon Leon Springs pupfish, *

Cyprinodon bovinus 778.0

Sheepshead minnow,

Cyprinodon variegatus 337.2

43 445.6 Oncorhynchus Coho salmon, *

Oncorhynchus kisutch 445.6

42 350.2 Mercenaria Hard clam,

Mercenaria mercenaria 350.2

41 341.6 Balanus Barnacle,

Balanus amphitrite 139.7

Barnacle,

Balanus eburneus 835.4

40 260.8 Farfantepenaeus Pink shrimp,

Farfantepenaeus duorarum 260.8

### 44

Rank Genus Mean

Acute Value

(μg/L) Genus Species Species Mean

Acute Value

(μg/L)

39 255.4 Crangon Shrimp,

Crangon crangon 255.4

38 229.9 Morone Striped bass,

Morone saxatilis 229.9

37 222.9 Loligo Squid,

Loligo opalescens 222.9

36 190.6 Leiostomus Spot,

Leiostomus xanthurus 190.6

35 185.0 Atherinops Topsmelt,

Atherinops affinis 185.0

34 130.1 Echinogammarus Amphipod,

Echinogammarus olivii 130.1

33 112.8 Neanthes Polychaete,

Neanthes arenaceodentata 112.8

32 106.8 Metapenaeus Shrimp,

Metapenaeus sp. 106.8

31 106.4 Pseudopleuronectes Winter flounder,

Pseudopleuronectes americanus 106.4

30 101.2 Pseudodiaptomus Copepod,

Pseudodiaptomus coronatus 101.2

29 99.77 Tisbe Copepod,

Tisbe furcata 99.77

28 87.98 Hydroides Polychaete,

Hydroides elegans 87.98

27 85.48 Orchomenella Amphipod,

Orchomenella pinguis 85.48

26 82.57 Americamysis Mysid,

Americamysis bahia 96.60

Mysid,

Americamysis bigelowi 70.57

25 75.27 Elasmopus Amphipod,

Elasmopus rapax 75.27

24 72.63 Aiptasia Sea anemone,

Aiptasia pallida 72.63

23 64.47 Menidia Inland silverside,

Menidia beryllina 46.01

Atlantic silverside,

Menidia menidia 85.97

Tidewater silverside,

Menidia peninsulae 67.73

22 64.20 Scorpaenichthys Cabezon,

Scorpaenichthys marmoratus 64.20

21 53.80 Anaitides Polychaete,

Anaitides maculata 53.80

20 35.72 Cancer Dungeness crab,

Cancer magister 35.72

### 45

Rank Genus Mean

Acute Value

(μg/L) Genus Species Species Mean

Acute Value

(μg/L)

19 32.60 Neomysis Mysid,

Neomysis mercedis 32.60

18 28.37 Homarus Lobster,

Homarus americanus 28.37

17 28.35 Spisula Surf clam,

Spisula solidissima 28.35

16 23.03 Mya Softshell clam,

Mya arenaria 23.03

15 23.03 Brachionus Rotifer,

Brachionus plicatilis 23.03

14 22.44 Eurytemora Copepod,

Eurytemora affinis 22.44

13 16.49 Dendraster Sand dollar,

Dendraster excentricus 16.49

12 16.40 Acartia Copepod,

Acartia clausi 21.86

Copepod,

Acartia tonsa 12.31

11 15.35 Argopecten Bay scallop,

Argopecten irradians 15.35

10 13.85 Arbacia Sea urchin,

Arbacia punctulata 13.85

9 12.58 Diadema Long

- spined sea urchin,

Diadema antillarum 12.58

8 12.38 Mulinia Coot clam,

Mulinia lateralis 12.38

7 10.29 Strongylocentrotus Green sea urchin,

Strongylocentrotus droebachiensis 13.29

Purple sea urchin,

Strongylocentrotus purpuratus 7.971

6 10.10 Crassostrea Pacific oyster,

Crassostrea gigas 11.94

Eastern oyster,

Crassostrea virginica 8.537

5 9.572 Holmesimysis Mysid,

Holmesimysis costata 9.572

4 9.153 Haliotis Black abalone, *

Haliotis cracherodii 21.24

Red abalone,

Haliotis rufescens 3.944

3 8.848 Paralichthys Summer flounder,

Paralichthys dentatus 8.848

2 7.847 Tigriopus Copepod,

Tigriopus californicus 7.847

1 5.577 Mytilus Blue mussel,

Mytilus edulis 4.238

### 46

Rank Genus Mean

Acute Value

(μg/L) Genus Species Species Mean

Acute Value

(μg/L)

Mediterranean mussel,

Mytilus galloprovincialis 7.338

a 

### From Appendix Table A

- 1

.

* Listed species.

3.2 Summary of Chronic Studies

A cceptable estuarine/marine copper chronic value s are available for only two species, the

euryhaline rotifer

, Brachionus plicatilis (Arnold et al. 2010b ) and the sheepshead minnow

,

Cyprinodon variegatus (Hughes et al. 1989) ( Appendix Table B

- 1 ). These chronic toxicity

value s were ob tained from a multigeneration life

- cycle test with th e rotifer

, and a flow

- through

early life stage ( ELS ) test with the sheepshead minnow . Copper concentrations were measured in

the test chambe rs of both tests

. A s for the acute values , the chronic values presented below are

BLM

- normalized and are relevant (for comparison purposes across species) only at the selected

water chemistry values specified, but are used to allow the BLM model to predict the criteria in

any water chemistry condition.

The sta tic multigeneration life cycle test with the rotifer

, conducted by Arnold et al.

( 2010b ), was used to develop an acute

- chronic ratio for the species ( Table 6 ). Neonates were

exposed to seven copper concen trations in artificial seawater for 96 hours (Note: due to the life

history of this short

- lived organism, this duration represents a chronic exposure) . T he intrinsic

rate of rotifer population increase was negatively affected ( 37% de c rease ) at 10.3 μg/L dissolved

copper , but not at 6.1 μg/L , with a MATC value of 7.927 μg/L

. The authors reported an EC 20 

### of

10.9 μg/ L dissolved copper , or 13.23 μg/L once BLM normalized . D ividi ng the 48

- hr LC 50 

### s from

this st udy by the EC 20 

### resulted in an ACR of 1.229 (13.4 μg/L / 10.9 μg/L ) when the rotifers were

not fed in the acute test

, and an ACR of 1.908 (20.8 μg/L / 10.9 μg/L ) when the rotifers were fed

in the acute test ( Appendix Table B

- 2 ).

The ELS test with sheepshead minnow did not provide concentration

- response data and

regression analysis could not be done . In the 28

- day ELS test, growth was reported to be a mo re

sensitive endpoint than mortality, and the chronic value for growth was 249 μg total Cu / L (or

226.8 μg dissolved Cu

/L)

. The BLM normalized MATC is 204.1 μg / L dissolved copper.

### 47

D ividi ng the 96

- hr LC 50 

### from this study by the 28

- day chronic value (368/249 μg / L ) resulted in

an ACR of 1.475 ( Appendix Table B

- 2 ).

Table 6 . Ranked Estuarine/Marine Genus Mean Chronic Values with Species Mean Acute

Chronic Ratios.

(All values were normalized to select water chemistry conditions

, see Section 3.3 ).

Rank Genus Mean

Chronic Value

(μg/L) Genus Species Species Mean

Chronic Value

(μg/L) a 

### ACR

2 204.1 Cyprinodon Sheepshead minnow,

Cyprinodon variegatus 204.1 1.475

1 13.23 Brachionus Rotifer,

Brachionus plicatilis 13.23 1.229 /

1.908 fed

a 

### From Appendix Table B

- 1

.

Other chronic toxicity data deemed un acceptable for quantitative use in the criteria

derivation ( Appendix Table E

- 1 ) , but generally considered to be representative were evaluated

to determine ACRs for additional species for purposes of comparison . A 28

- day LC 50 

### of 56 μg/L

was reported for the polychaete

, Neanthes arenaceodentata ( Pesch and Hoffman 1982) , which

yields an ACR of 2.298 when divided into the SMAV of 128.7 μg/L. Pesch et al. ( 1979 ) re ported

an EC 50 

### of 5.8 μg/L for reduced growth for the bay scallop

, Argopecten irradians

, based on

exposure to copper for 42 days. Division of the SMAV (25.01 μg/L) by this value gives an ACR

of 4.312

. Data for these two additional invertebrate species, a lthough not used quantitatively in

the criteria derivation

, are consistent with and generally support the lower (<2) ACRs g iven for

the rotifer and sheepshead minnow.

3.3 Summary of BLM Water Quality Input Parameters

Table 7 summarizes the selected water quality input parameters used for the saltwater

BLM normalization

. The designation of these parameters is not in and of itself important other

than to define a c onsistent set of conditions to which to normalize all the data

. The LC 50 

### and

EC 50 

### values presented in Appendix Table A

- 1 were standardized to these sp ecified water

chemistry conditions (see footnote “ e ” ). The reported chemistry for each individual study is

presented in Appendix Table H

- 1 and summary statistics of all the test conditions are provided

in Appendix Table H

- 2

. Likewise

, the estuarine/marine chronic values in Appendix Table B

- 1

are normalized to the same specified water chemistry conditions. These inputs were standardized

### 48

in order to perform calculations with a consistent set of parameters and to ensure the selection of

these parameters does not affect either the rank order of the species sensitivity distribution or the

resulting criteria calculations (Di Toro et al. 2001). Following normalization of the data

presented in Appendix Table A

- 1 , t he BLM can be used to calculate an FAV which accounts for

changes t o any variable included in the model (i.e., temperature, pH, salinity, and DOC)

. DOC is

typically the most important variable because pH tends to have limited variation in marine water

,

while s alinity and temperature have a lesser effect on copper bioavailability than does DOC

.

Table 7 . Water Quality Input Parameters Used for Saltwater BLM

- Normalization.

Saltwater BLM Input Parameters Saltwater BLM Input Value

Temperature 2 2°C

pH 8

DOC 1.0 mg/L

Salinity 32 ppt

3.4 Bioaccumulation

Copper bioaccumulates in aquatic organisms

, although increased accumulation through

trophic levels in aquatic food chains (i.e., biomagnification) is not usually observed (Lewis and

Cave 1982; Suedel et al. 1994). Total uptake generally depends on the environmental copper

concentration, exposure ro ute and the duration of exposure (McGeer et al. 2000).

Bioconcentration Factors (BCFs) typically vary with the bioavailable concentration of copper in

water, with higher BCFs occurring at lower copper concentrations (McGeer et al. 2003; U.S.

EPA 2010a). So me of the highest reported BCFs for copper are for marine and freshwater

bivalves (Hamelink et al. 1994). Copper bioavailability and toxicity is promoted by oxine and

other lipid soluble synthetic organic chelators in marine ecosystems (Bryan and Langston 1992).

In marine sediments, bioavailability is altered by increased acid volatile sulfide (AVS) content

(Casas and Crecelius 1994), and ligand concentration (Skrabal et al. 2000) . A more detailed

discussion of bioaccumulative factors is provided in the Eff ects Characterization ( Section 4.3 )

.

3.5 Toxicity to Aquatic Plants

No acceptable estuarine/marine copper toxicity tests are available for algal or aquatic

vascular plant species for which the concentrations of test material were measured. Therefore, a

### 49

Final Plant Value (FPV) could not be determined. Effects on aquatic plants are discussed

qualitatively in the Effects Characterization ( Section 4.4 )

.

3.6 The National Estuarine/Marine Criteria for Copper

3.6.1 Acute Criterion Calculation

Acceptable acute t oxicity values are available for 89 species representing 63 taxonomic

families ( Table 3 ) . The ranked GMAVs are presented in Figure 9 and the ranked SMAVs and

summaries of acu te toxicity test data for individual species are shown in Figure 10 f or

comparison . Because more than 59 GMAVs were available for copper, the FAV was derived

from the four GMAVs that have cumulative probabilities closest to the 5 th 

### percentile toxicity

value for all the tested genera

. The 5 th 

### percentile of the species sensitivity distribution , equivalent

to the FAV, was estimated as 9.138 μg/L ( Table 8 ) (Note: the FAV changes with respect to the

conditions at the site, and the values represented below only apply to the selected conditions in

Table 7 )

. For previous estuarine/marine criteria, the FAV was lowered to protect commercially

and recreationally important mussel species . F or these data

, a value that is protective of

commercially and recreationally important species would involve lowering the FAV to the

S MAV for Haliotis rufescens

, which is the lowe st SMAV among st commercially and

recreationally important species with a value of 3.944 μg/L

. The calculated FAV was therefore

lowered to the SMAV for H

. rufescens and the CMC was set to this lowered FAV divided by

two ( 3.944 /2= 2.0 μg/L ) ( Table 8 )

.

### 50

Table 8

. Estuarine/Marine Water Final Acute Value (FAV) and Criteria Calculations.

(All values were normalized to select water chemistry conditions see Section 3.3 ).

N Rank b 

### Genus GMAV ln(GMAV) ln(GMAV) 2 

### P=R/(N+1) sqrt(P)

78 5 Holmesimysis 9.572 2.26 5.10 0.063 0.252

4 Haliotis 9.153 2.21 4.90 0.051 0.225

3 Paralichthys 8.848 2.18 4.75 0.038 0.195

2 Tigriopus 7.847 2.06 4.24 0.025 0.159

Sum: 8.71 19.00 0.177 0.831

S 2



### = 4.575

L = 1.734

A = 2.212

FAV (calculated) = 9.138

FAV ( H. rufescens lowered) = 3.944

CMC a 

### = 2.0



### Where, S=slope, L=intercept, A=ln(FAV); and FAV=final acute value

a 

### When the t emperature=22°C, pH=8, DOC=1. 0 mg/L, and salinity =32 ppt

. b 

### According to the G uidelines, ranks 2

- 5 are used in the calculation of the FAV ( Stephan et al.

1985 ).

T he recommended CMC of 2.0 μg/L is specific for the seawater chemistry specified in

Table 7

, which consists of the following physical and chemical parameter assumptions:

t empera ture=22°C, pH=8, DOC= 1.0 mg/L and s alinity=32 ppt

. T he BLM analysi s can be

adjusted to incorporate different physical and chemical parameters to be protective of aquatic life

under varied conditions (see Appendix I )

.

### 51

Figure 9 . Ranked Estuarine/Marine GMAVs.

### 52

Figure 10 . Reported D issolved Cu LC 50 

### s R anked by the G eomean of the N ormalized Cu V alues (i.e., SMAVs).

(For each species, the box shows the range from the 25 th 

### to the 75 th 

### percentile of the available BLM normalized EC 50 

### s, and the geometric mean

SMAV is shown by the horizontal line within the box. The whiskers show the maximum and minimu m values, exclusive of outlier points . O utliers

are shown as individual symbols. Test species are identified on the x

- axis labels using species numbers listed in Appendix Table G

- 1 ).

### 53

3.6.2 Chronic Criterion Calculation

The Criterion Continuous Concentration (CCC) can be derived either from c hronic v alues

if the MDR s are met

, or from the FAV divided by a F ACR ( Stephan et al. 1985 )

. Since

estuarine/marine chronic values are available for only two species and the MDR is not met

, the

FAV divided by the FACR was used to determine the CCC.

Two valid estuarine/marine ACRs are available for c opper ( Table 6 ). The s heepshead

minnow

, Cyprinodon variegatus

, is a relatively insensitive estuarine/marine water species on an

acute basis , with a GMAV falling at approximately the midway point of sensitivity of all the

tested estuarine/marine genera (Rank 44 ) , while the rotifer Brachionus plicatilis is mo re

sensitive

, with a GMAV falling with in the lower quarter of the all tested species (Rank 15 )

( Table 5 )

. The lowest estuarine/marine acute values are from tests with embryos and larvae of

molluscs and embryos of summer flounder, which are also likely to be the most sensitive life

stages of these species. Although estuarine/marine ACRs are not available for these sensitive

species, ACRs are available for the most acutely sensitive freshwater species tested to date for

copper ( Appendix Table B

- 2 ).

Individual ACRs varied amongst studies ranging from <1 ( 0.142 ) for Ceriodaphnia dubi a

( Harmon et al. 2003 ) to 191.6 for the snail, Campeloma decisum (Arthur and Leonard 1970).

Species mean ACRs range d from 1.229 for the rotifer

, B. plicatilis to 171.2 for the freshwater

snail, C. decisum . The Guidelines outline four primary ways to combine ACRs to calculate an

appropriate FACR.

 If the species mean acute

- chronic ratios seems to increase or decrease as the SMAV

increases, the Final Acute

- Chronic Ratio should be calculated as the geometric mean of

the acute

- chronic ratios for species whose SMAVs are close to the Final Acute Value.

 If no major trend is apparent and the acute

- chronic ratios for a number of species are

within a factor of ten, the Final Acute

- Chronic Ratio should be calculated as the

geometric mean of all the species mean acute

- chronic ratios available for both freshwater

and s altwater species.

 For acute tests conducted on metals and possibly other substances with embryos and

larvae of barnacles, bivalve molluscs, sea urchins, lobsters, crabs, shrimp, and abalones,

it is probably appropriate to assume that the acute

- chronic ratio is 2. Thus, if the lowest

available SMAVs were determined with em bryos and larvae of such species, the Final

Acute

- Chronic Ratio should probably be assumed to be 2, so that the Final Chronic Value

is equal to the Criterion Maximum Concentration.

### 54

 If the most appropriate species mean acute

- chronic ratios are less than 2.0 , and especially

if they are less than 1.0, acclimation has probably occurred during the chronic test.

Because continuous exposure and acclimation cannot be assured to provide adequate

prot ection in field situations, the Final Acute

- Chronic Ratio should be assumed to be 2,

so that the Final Chronic Value is equal to the Criterion Maximum Concentration.

Since the available ACRs are not within a factor of 10, and because a relationship is

evident between acute sensitivity and ACRs, the FACR was calculated as the geometric mean of

the ACRs for species with SMAVs close to the FAV , and that have taxonomically related marine

species . The FACR of 3.022 was calculated as the geometric mean of the genus mean ACRs for

five sensitive freshwater genera

, C eriodaphnia ( 3 .268 ), D aphnia ( 4.057 ), Oncorhynchus ( 3.630 )

,

Acipenser (5.757) and Cottus (2.0 75)

, along with the two estuarine/marine genus mean ACRs for

Cyprinodon ( raised to 2.0 ) and Brachionus ( raised to 2.0 ) ( Appendix Table B

- 2 ). The final

chronic value (FCV) for copper at the selected water chemistry ( Table 7 ) is the FAV of 3.944

μg/L (lowered to protect H. rufescens ) divided by the FACR and equals 1.3 μg/L Cu. The CCC,

which is equivalent to the FCV

, is lower than the two acceptable GMCVs available for copper

( Figure 11 ) at the specified chemistry.

### 55

Figure 11 . Ranked Estuarine/Marine GMCVs.

3.7 Summary of National Criteria

The resulting recommended ambient WQC indicate that estuari ne/marine aquatic

organisms would have an appropriate level of protection if the 1

- hour average and four

- day

average dissolved copper concentration s do not respectively exceed the acute and chronic criteria

concentrations calculated by the saltwater BLM mo re than once every three years on average.

For the 201 6 acute criteria , EPA has changed the duration to 1 hour from the 24 hours EPA

applied in the 200 3 draft c opper criteria document and the 2007 freshwater copper criteria

document. EPA made this change to the 2016 criteria to reflect the acute criteria duration

recommended in the Guidelines (see Section 4.1.2 )

. The WQC numeric values will change in

response to changes in water quality parameters (i.e., temperature, salinity, dissolved organic

carbon and pH)

.

### 56

For example

, at the selected water chemistry conditions chosen for BLM

- normalization

( temperature=22°C, pH=8, DOC=1.0 mg/L and salinity=32 ppt )

, the resulting recommended

ambient WQC indicate that estuarine/marine aquatic organisms would have an appropriate level

of protection if the 1

- hour average dissolved copper concentration does not e xceed 2.0 μg/L

more than once every three years on average

, and if the four

- day average dissolved copper

concentration does not exceed 1.3 μg/L more than once every three years on average . The re may

be an exception, however, if a locally important species is more sensitive.

T he BLM can be used to adjust criteria values to be protective under different

temperature, pH, DOC, and salinity conditions

. For example

, when the site conditions are

changed to assume a temperature=2 0 °C, pH=8, DOC= 4 .0 mg/L and salini ty= 15 ppt (which may

be typical conditions for an estuary with moderate DOC concentrations) , the resulting CMC and

CCC are 7.1 and 4.7 μg/L , respectively

. Appendix I provides a discussion of temperature, pH,

DOC and salinity conditions expected to occur in estuarine and marine waters around the United

States, a discussion of environmental variables af fecting each of these conditions , and additional

examples of numer ic criteria values for copper depending on selected water quality inputs.

3.8 Identification of Data Gaps for Aquatic Organisms

3.8.1 Chronic Toxicity Data for Estuarine/Marine Animals

Limited acceptable chronic copper toxicity data are available for es tuarine/marine animal

species. Studies are available for only two estuarine/marine animal species, as discussed in

Section 3.2

. T he FCV is therefore based on the use of a FACR. The FACR assumes that the

relationship between acute and chronic toxicity for each species is constant. Acceptable ACRs

are averaged across taxa to calculate the final overall relationship between the acute and chronic

toxicity values. Since freshwater ACRs are used to bolster the calculation of the FACR, due to

only two estuarine/marine genus

- level ACR s being available, this creates an additional

uncertainty in the estuarine/marine FCV.

3.8.2 Chronic Toxicity Data for Aquatic Vascula r Plants and Algae

Acceptable toxicity d ata are limited for aquatic vascular plan ts and algae for which the

concentrations of test material were measured . Accordingly, t he available plant data did not meet

the MDRs established in the Guidelines to support the derivation of a plant

- based value

( Appendix Table C

- 1 )

. However, analysis of the toxicity data that are available for

### 57

estuarine/marine plant specie s, which is discussed in Section 4.4

, suggests that a chronic

criterion value that is protective of est uarine/marine animals would also be protective of aquatic

plants (see Section 4.4 )

.

3.8.3 BLM Uncertainties and Performance

The BLM used to update the estuarine/marine copper crit eria employs equilibrium

reactions for copp er and other anions/cations using a single and simple type of surface ligand to

characterize the effects of all physical and chemical expo sure cond itions on toxic ity. As such, t he

model is a simplified and ap proximate representation of a complex set of chemical reactions and

transfers that are involved with envi ronmental copper eliciting toxicity. As already noted, cation

effects m ay involve mechanisms in addition to com petition for a surface ligand. Further, t he

microenvironment at the gill surface and other biological membranes of toxic interaction fo r

juvenile and adult fish might change copper speciation, but the most sensitive organism s to

which the criteria are applicable ( and lik ely to determine the FAV ) are embryo

- larval life stages

of invertebrates that do not hav e a gill microenvironment. Final ly, because the biotic ligand

refers to specific binding sites in the organism, accumulation measurements taken from digests

of whole embryonic stage s, or based on bulk gill tissue could include metal in addition to that

bound t o t he biotic ligand, including metal that has been taken up and t ransported by the cell or

organ

.

Despite the uncertainties described in this section , the BLM provides a reasonable

mechanistic framework for the well

- established effects of copper speciation, explicitly

addres sing the relative bioavailability of different copper species. It also includes a plausible

mechanism tha t allows the effects of cations to be addressed and uses a comprehensive model for

calculating the concentrations of various copper species. Even if th e mechanistic descriptions are

incomplete, this model allows the major empirical effects of complexing ligands and competing

cations to be described in a more comprehensive and reasonable fashion than other approaches

(U.S. EPA 2007).

### 58



## 4 EFFECTS CHARACTERIZA TION

The Effects Characterization section evaluates the potential effects of copper on

estuarine/marine aquatic life based on available test data and describe s additional lines of

evidence that were not used directly in the criteria calculations, but whic h support the 201 6

aquatic life criteria values. This section also provide s a summary of uncertainties and

assumptions, and explanations for decisions about the acceptability and use of data in the effects

assessment . Finally, this section describe s substa ntive differences between the 2003 draft copper

A L C and th e 201 6 update

, based on incorporation of the latest scientific information

.

All acceptable acute and chronic values used to derive criteria are presented in Appendix

Table A

- 1 and Appendix Table B

- 1 , respectively

. Studies that were determin ed to be

scie ntifically sound

, but not meeting with screening guidelines for inclusion in criteri a

calcula tions are presented in Appendix Table E

- 1

. St udies that were not used qualitatively or

quantitatively in th e criter ia development and the reason th ey were not used are provided in

Appendix Table F

- 1

.

4.1 Estuarine/Marine Acute Toxicity Data

Acceptable acute toxicity data are available for 89 estuarine/marine species representing

78 genera. These data were used to support the development of an estuarine/marine acute

criterion

.

A quatic invertebrates are more acutely sensitive to copper than fi sh in the marine

environment. Amongst the ten most sensitive genera to copper, nine are invertebrates and are

primarily represented by bivalves and echinoderms. BLM

- normalized SMAVs for coppe r range

from 3.944 to 81,550 μg/L. The most sensitive genus is the mussel Mytilus , followed by the

copepod

, Tigriopus , with BLM

- normalized GMAVs of 5.577 and 7.847 μg/L, respectively. The

two most tolerant genera were the amphipod, Corophium

, and the clam

, Rangia , with BLM

normalized GMAVs of 81,550 and 43,694 μg/L, respectively ( Table 5 ).

Several studies were identified as not meeting screening guidelines for inclusion in

criteri a calculations ( Appendix Table E

- 1 ), but showed similar ranges of toxicity for a number

of the most sensitive specie s (Note: the values below were BLM

- normalized to the same water

quality parameters in Table 7 )

. Manley et al. (1984 ) reported a 72

- hr LOEC of 4.258 μg/ L

copper to Mytilus edulis , which is similar to the GMAV for the genus ( 5.577 μg/L). Similarly

,

### 59

Fitzpatrick et al. (2008 ) observed increased abnormal larval development of Mytilus trossulus

embryos exposed to 4.623 μg/L copper for 48 hours. The Pacific oyster

, Crassostrea gigas

, was

investigated by several authors and acute effect levels were observed at concentrations ranging

from 1.890 to 65.90 μg/L copper for embryos exposed from one to three days, which is similar to

the SMAV of 11.94 μg/L for the sp ecies ( Brooks et al. 2007 ; Harrison et al. 1981 ; Worboys et al.

2002 ). Eisler (1977) reported a 7

- day LC 50 

### of 16.22 μg/L copper for the soft

- shell clam Mya

arenaria

, which is close to the GMAV of 23.03 μg/L reported for thi s species.

For fish, Anderson et al. (1994 ) reported 7

- day LC 50 

### s for topsmelt

, Atherinops affinis

,

larva that ranged from 25.46 to 78.71 μg/L copper. Pacific herring embryos, Clupea harengus

pallasi

, non BLM

- normalized acute effect levels ranged from 33 to 900 μg/L copper ( Rice and

Harrison 1978 ). A 4

- day LC 50 

### of > 164.4 μg/L copper was reported for larva of t he s heepshead

minnow, Cyprinodon variegates ( Hutchinson et al. 1994 )

. Cobia

, Rachycentron canadum

, 4

- day

LC 50 

### s ranged from 25.75 t o 130.1 μg/L copper ( Dung et al. 2005 ). The acute effect levels

observed for all these species are similar to the BLM

- normalized GMAV ( 64.20 μg/L copper )

reported for the cabezon

, Scorpaenichthys marmoratus , which was the second most sensitive fish

species (Rank 22

, Table 5 ) with acceptable acute data

.

4.1.1 Uncertainty in the E stuarine/ M arine FAV C alculation

A number of uncertainties are associated with calculation of the FAV as described in the

Guidelines ( Stephan et al. 1985 ), and include use of limited data for a species or genus,

application of safety factors, and extrapolation of laboratory data to the field. There are a number

of cases in the acute database where only one acute test is used to determine the SMAV

, and

subsequently the GMAV is based on the one acute test. In this situation

, species variability

within a particular genus is unknown. The GMAV is still valid, in spite of absence of these

additional data.

The final step in the acut e criteria derivation process is to divide the FAV by a safety

factor of 2 to yield the CMC. The CMC is set as equal to half of the FAV to represent a low level

of effect for the fifth percentile genus, rather than a 50% effect. This adjustment factor was

derived from an analysis of 219 acute toxicity tests with a variety of chemicals (see 43 FR

21506

- 21518 for a c omplete description) where mortality data were used to determine the

highest tested concentration that did not cause mortality greater than that observed in the control

### 60

(or between 0 and 10%). Application of this safety factor is justified because that con centration

represents minimal acute toxicity to the species.

Application of water

- only laboratory toxicity tests to develop water quality criteria to

protect aquatic species is a basic premise of the Guidelines, supported by the requirements of a

diverse a ssemblage of eight families and the protection of 95 percent of all species. Confirmation

has been reported by a number of researchers ( Clements and Kiffney 1996; Clements et al. 2002;

Mebene 2006; Norgberg

- King and Mount 1986 ) , thereby indicating that on the whole,

extrapolation from the laboratory to the field is a scientifically valid and protective approach for

aquatic life criteria development

.

4.1.2 Acute C riteria D uration

For the 2016 acute estuarine /marine c opper criteria, EPA has changed the duration to 1

-

hour from the 24 hours EPA applied in the 200 3 draft c opper criteria document and the 2007

freshwater copper document . EPA made this change to the 2016 criteria to reflect the acute

criteria duration recommended in the Guidelines. Both t he 200 3 and 2007 c opper criteria

document s used a 24

- hour duration, but did not detail the rationale for this duration , and EPA has

further examined this issue as part of the 2016 criteria update.

EPA revise d the acute duration i n this document to be consistent with the more protective

1

- hour duration, which is generally supported by and consistent with the Guidelines. T he

Guidelines, for example, states the following:

“For the CMC the averaging period should again be substantiall y less than the lengths of

the tests it is based on, i.e., substantially less than 48 to 96 hours. One hour is probably

an appropriate averaging period because high concentrations of some materials can

cause death in one to three hours. Even when organisms do not die within the first hour

or so, it is not known how many might have died due to delayed effects of this short of an

exposure. Thus it is not appropriate to allow concentrations above the CMC to exist for

as long as one hour. The durations of the a veraging periods in national criteria have

been made short enough to restrict allowable fluctuations in the concentration of the

pollutant in the receiving water and to restrict the length of time that the concentration in

the receiving water can be contin uously above a criterion concentration.” ( Stephan et al.

1985 , page 5)

### 61

... “the one

- hour average should never exceed the CMC

. ” ( Stephan et al. 1985 , page 6)

Additional information supporting the 1

- hour averaging period is presented in the

Technical Support Document for Water Quality

- based Toxics Control (U.S. EPA 1991) which

states :

“For acute criteria, EPA recommends an averaging period of 1

- hour. That is, to protect

against acute effects, the 1

- hour average exposure should not exceed the CMC. The 1

-

hour acute averaging period was derived primarily from data on response time for

toxicity to ammonia, a fast

- acting toxicant. The l

- hour averaging period is expected to be

fully protective for the fastest

- acting toxicants, and even more protecti ve for slower

acting toxicants.” (U.S. EPA 1991 , page 35 )

The frequency of allowed exceedances is once in three years on average, as recommended

in the Guidelines ( Stephan et al. 1985 ). This is based on the ability of aquatic ecosystems to

recover from cr iteria exceedances , which will depend in part on the magnitude and duration of

the exceedance ( s )

.

4.2 Estuarine/Marine Chronic Toxicity Data

Data for only two estuarine/marine species are suitable for d erivation of a chronic

criterion. S uitable data are avai lable for the rotifer, Brachionus plicatilis ( BLM

- normalized

SMCV= 13.23 μg/L dissolved Cu ) and the sheepshead minnow, Cyprinodon variegatus ( BLM

normalized SMCV= 204.1 μg/L dissolved Cu ).

Several studies that were identified as not meeting with screening guidelines for inclusion

in criteri a calculations reported chronic sublethal effects of copper on estuarine/marine

invertebrates ( Appendix Table E

- 1 ). The following data are BLM

- normalized , unless noted

.

Three scleractinian coral s pecies along with their algal symbiont s were exposed to three

measured copper concentrations for five weeks under flow

- through conditions (Bielmyer et al.

2010). The authors reported reduced growth chronic values of 14.69, >20.31 and <4.04 μg/L

copper (not BLM

- normalized) for Acropora cervicornis

, Montastraea faveolata and Pocillopora

damicornis , respectively. Pesch et al. (1979 ) reported reduced growth for the b ay scallop

,

A rgopecten irradians

, after exposure to 3.681 μg/L copper for 42

- day s . Gill alterations were

observed by Frias

- Espericueta et al. (2008a ) in juvenile whiteleg shrimp

, Litopenaeus vannamei

,

### 62

after exposure to 80.61 μg/L copper for 28 days. The 26 to 28

- day LC 50 

### s for the polychaete

worms, Cirriformia spirabranchia and Neanthes arenaceodentata, ranged from 25.53 to 35.97

μg/L copper (Milanovich et al. 1976; Pesch and Hoffman 1982 ; Pesch and Morgan 1978 ).

Channeled whelk, Busycon canaliculatum , Mediterranean muss el, Mytilus galloprovincialis , and

quahog clam, Mercenaria , 28

- to 77

- day LC 50 

### effect levels ranged from 25 to 470 μg/L copper

(not BLM

- normalized) (Bat et al. 2013; Betzer and Yevich 1975; Shuster and Pringle 1968 ).

Limited chronic data are available for estuarine /marine fish species. Lacoue

- Labarthe et

al. ( 2010 ) exposed cuttlefish ( Sepia officinalis ) eggs to four unmeasured copper concentrations

for 50 days and reported a hatchling weight NOEC and LOEC of 2.3 and 23 μg/L (not BLM

n ormalized) , respectively. Several authors ( Engel et al. 1976 ; Swedmark and Granmo 1981 )

conducted 14

- day exposures for different species and reported copper not BLM

- normalized LC 50



### effect levels of 10 μg/L for the Atlantic cod

, Gadus morhua

, 150 μg/L for the p infish

, Lagodon

rhomboids

, 160 μg/L for the spot

, Leiostomus xanthurus , 210 μg/L for the Atlantic croaker

,

Micropogonias undulates

, and 610 μg/L for the Atlantic menhaden

, Brevoortia tyrannus

.

Although the e xposure periods were shorter than typically used for chronic studies, t hese data

indicate response concentrations that are generally similar to the chronic effect level reported by

Hughes et al. (1989 ) for sheepshead minnow

, Cyprinodon variegatus ( BLM

- normalized

SMCV= 204.1 μg/L dissolved Cu ) , which was the only estuarine/marine fish for which

acceptable chronic toxicity data were available

.

4.2.1 Uncertainty in the E stuarine/ M arine FCV C alculation

In addition to the uncertainties described above for the acute criteria derivation ( Section

4.1.1 ) and identification of data gaps ( Section 3.8.1 ) , the estuarine/marine FCV calculat ion is

also influenced by the estimation of chronic values with MATC methods. The estimation of

chronic values with an EC 20 

### regression analysis is preferred over the use of MATCs because

MATCs are highly dependent on the concentrations tested and can therefore potentially bias the

chronic value either higher or lower than the EC 20



### . Point estimates also provide additional

information that is difficult to determine with an MATC, such as a measure of effect level across

a range of tested concentr ations. A MATC was used to determine the chronic value for the

sheepshead minnow, whereas an EC 20 

### was estimated for the rotifer

.

### 63

4.3 Bioaccumulation

Bioconcentration factors (BCFs) for copper in estuarine/marine water are provided in

Appendix Table D

- 1

. In estuarine/marine water

, the polychaete worms

, Phyllodoc maculate

,

Neanthes arenaceodentata and Eudistylia vancouveri , had copper BCFs of 2,500, 2, 9 50 and

1,006 , respectively ( McLusky and Phillips 1975 ; Pesch and Morgan 1978 ; Young et al. 1979 ).

BCFs for six species of estuarine/marine bivalve molluscs range from 790 for the soft

- shell clam

,

Mya arenaria ( Shuster and Pringle 1968 )

, to 57,000 for the Pacific oyster

, Crassostrea gigas

( Han and Hung 1990 ). Similarly, Shuster and Pringle (1968 ) found that the eastern oyster

,

Crassostrea virginica

, could concentrate copper to levels 27,800 times greater than ambient

water concentrations during a 140

- day continuou s exposure to 25 μg/L copper . Even though the

tissue of the oyster became bluish

- green , morta lities were only slightly greater than in the

controls. There are no BCF data for estuarine/marine fish or crustaceans meeting the data quality

objectives required for inclusion in Appendix Table D

- 1 of this document

.

4.3.1 Uncertainty with C opper E xposure R outes

Aquatic organisms can accumulate copper from both aqueous and dietary exposure

routes. The relative importance of each, however, is dependent upon the species. The filter

feeding oyster Crassostrea gigas was found to accumulate more copper from ambient water than

from phytoplankton food items (Ettajani et al. 1992), as did the suspension feeding cockle,

Cerastoderma edule (Absil et al. 1996). Guo et al. (2013) ex posed the abalone, Haliotis discus

hannai , for eight weeks to either aqueous or dietary copper and observed that substantially more

copper was accumulated in muscle tissue from the water exposure (10.8 fold increase) than the

macroalgae diet (2.0 fold incr ease). Similar copper absorption efficiency or accumulation levels

from water and diet were observed by Absil et al. (1994) for the sediment

- dwelling bivalve,

Macoma balthica (efficiencies ranged from 71

- 87% in aqueous exposures and from 78

- 90% in

foodborn e exposures), and by Long and Wang (2005) for the marine target fish, Terapon jarbua

(approximately two

- fold increase for both). Pinho et al. (2007) also observed similar waterborne

and waterborne plus dietborne copper accumulation for the copepod Acartia tonsa , irrespective

of the salinity level (5, 15 and 30 ppt). Although accumulation decreased as salinity increased, no

significant differences were observed between the exposure routes at each salinity exposure

(from approximately 6.5 to 11.5 fold increas es). Copper burdens in blackhead seabream

Acanthopagrus schlegelii schlegelii intestine and liver after aqueous exposure (130 and 110 μg/g

### 64

dw, respectively) were comparable to those after dietary exposure (140 and 95 μg/g dw,

respectively) (Dang et al. 201 2). In contrast, Bielmyer et al. (2005a) found significantly higher

copper accumulation in the intestine and liver of saltwater

- acclimated hybrid striped bass

( Morone chrysops x Morone saxatilis ) exposed to dietary copper (approximately 8

- fold and 2

-

fold i ncreases, respectively) than those exposed to aqueous copper (no significant increases). In

summary, the primary route of copper accumulation varies among species, with no consistent

pattern.

The specific tissues/organs affected in an aquatic organism are also dependent on the

exposure route. Several authors have postulated that copper speciation influences exposure route

and the subsequent tissues and organs affected (Henry et al. 2012; Martins et al. 2011; Wang and

Fisher 1996). Bivalve molluscs and crust aceans primarily accumulate dissolved metals across the

gills, and particulate forms within the gut. In crustaceans, aqueous metals can be adsorbed to the

body surface or taken up internally by ingestion, passive diffusion, or facilitated transport (Wang

a nd Fisher 1998). For example, dissolved copper adsorbs onto the chitosan exoskeleton of

pelagic and benthic crustaceans (Henry et al. 2012; Hook and Fisher 2001), or inert chitin

surfaces of insects (Hare 1992), where it is rendered unavailable to interfer e with internal

metabolic processes. In contrast, ingested copper can accumulate into internal tissues potentially

interfering with a variety of metabolic and reproductive processes (Hook and Fisher 2001).

Copper assimilated from food is stored in the soft tissue of oysters ( Amiard

- Triquet et al. 1992).

Lobsters accumulate aqueous copper primarily in their gills ( Canli and Furness 1993) , with most

of the dietary copper deposited in the digestive gland (Chou et al. 1987 ).

In marine fish, uptake of dissolve d copper is either by the gills or the intestinal tract, and

is sometimes influenced by ambient water and dietary levels (Grosell 2012). Accumulation of

dissolved copper by the gills can be by either passive (diffusion) or active (pump) transport (Neff

200 2). Aqueous accumulation of copper via intestinal tissues is due to the ingestion of seawater

for osmoregulatory purposes (Grosell et al. 2003, 2004). Fish exposed to metals in the presence

of food initially absorb copper in the intestinal tract and to som e degree the stomach, and

subsequently transfer it to other tissues via the circulatory system (Wood et al. 2012). Water

borne copper primarily accumulated in the gill of the skate, Raja erinacea , and the sc ulpin,

Myoxocephalus octodecemspinosus (Gosell et al. 2003). However, Blanchard and Grosell (2005)

exposed the killifish, Fundulus heteroclitus , to aqueous copper at different salinities and

### 65

observed the highest accumulations in the liver, gill and intestine. In comparison, dietary copper

(as copper cont aminated oysters) accumulated mainly in the intestine and to some extent the gill

of the killifish, Fundulus heteroclitus (Blanchard et al. 2009).

In an effort to determine the most toxic exposure route, three studies have compared the

adverse effects of copper to marine organisms exposed separately to both aqueous and dietary

copper. Bielmyer et al. (2005a) exposed saltwater

- acclimated (15 ppt salinity) hybrid striped bass

( Morone chrysops x Morone saxatilis ) to dietary (571 to 1013 μg Cu/g), aqueous (22 to 44 μg

Cu/L) and dietary plus aqueous copper concentrations for 42 days. None of the exposures

scenarios had significant growth effects when compared to controls, although the authors noted

that the dietary copper exposed fish had significant liver and i ntestinal copper accumulation.

Conversely, Lauer and Bianchini (2010) observed exposure route differences when a copepod

( Acartia tonsa ) was exposed for six days to either dietary, aqueous or dietary plus aqueous

copper concentrations at three different sa linities (5, 15, 30 ppt). The copepods were exposed to

three concentrations of aqueous copper, fed diatoms that were exposed to three aqueous

concentrations of copper for 24 hours, or a combination of both. Pulsed exposures lasted 12

hours each day over th e six

- day experiment, after which the copepods were transferred to clean

media and allowed to reproduce for 24 hours. The water only exposure was the most toxic

exposure route, with reduced egg production EC 50 

### s of 9.9, 36.8 and 48.8 μg/L dissolved copper

,

followed by the dietary plus aqueous exposure with EC 50 

### s of 40.1, 63.7 and 109.9 μg/L dissolved

copper at 5, 15 and 30 ppt, respectively. The diet only exposures exhibited the least effect, with a

maximum of 43 percent reduction in reproduction regardless of exposure concentration or test

salinity. A similar toxicological difference in exposure routes was observed in a 28

- day study of

juvenile blackhead seabream ( Acanthopagrus schlegelii schlegelii ) that was either fed a

contaminated diet of copper or expos ed to only copper in seawater. When based on similar

estimated influx rates, the aqueous exposure was more toxic (31 percent mortality) than the diet

only exposure (<10 percent mortality) (Dang et al. 2012).

Several other investigators examined the toxic effects of dietary copper exposures to

marine organisms. Roberts et al. (2006) observed reduced survival of juvenile amphipods

( Peramphithoe parmerong ) fed a contaminated macroalgae that was cultured i n a spiked solution

containing 100 μg/L copper for 30 d ays. However, spiked solutions of up to 300 μg/L copper had

no effect on the growth of survivors. Juvenile grey mullet ( Chelon labrosus ) fed a high

- Cu diet

### 66

of 2,400 μg/g dry weight for 67 days did not experience any mortality, but growth rate was

reduced b y 43 percent (Baker et al. 1998). Sea urchins ( Lytechinus variegatus ) fed two copper

containing formulated diets (36 or 144 μg Cu/g) over twelve weeks had no significant difference

in mortality, total diameter and total dry weight compared to the controls that were fed 12 μg

Cu/g (Powell et al. 2010). Similarly, no death was observed when juvenile rock fish ( Sebastes

schlegeli ) were fed one of four copper diets (50, 100, 250, 500 μg/g) for 60 days, but the specific

growth rates for weight and length were re duced at 100 μg Cu/g and 250 μg Cu/g, respectively

(Kang et al. 2005; Kim and Kang 2004). Lin et al. (2008) fed juvenile grouper ( Epinephelus

malabaricus ) copper diets with eight different copper concentrations ranging from 0.11 to 20.05

μg Cu/g for eight weeks. Weight gain and feed efficiency was significantly greater in diets

containing 4.37 and 6.56 μg Cu/g, but was less in diets with ≤1.66 or ≥11.03 μg Cu/g. Survival

in all exposures was ≥80 percent with no dose

- response observed amongst treatments. No

mortality was observed when adult male crabs ( Neohelice granulata ) were fed copper dosed

algae (300 μg Cu/g) twice a week for five weeks. However, it should be noted that the exposure

regime was equivalent to mean weekly doses of 6 μg Cu/g per crab (Sabati ni et al. 2009).

Bielmyer et al. (2006b) exposed adult copepods ( Acartia tonsa ) to four copper

- enriched

diatom diets for seven days at a salinity of 30 ppt. The authors reported the 7

- day reproductive

EC 20 

### as 22.3 μg Cu/g dry weight, or 1.2 μg Cu/L (the l owest diatom medium exposure

concentration). In contrast, Lauer and Bianchini (2010) observed a diet

- only 6

- day reproductive

EC 20 

### of 23 μg Cu/g dry weight at a salinity of 30 ppt, or 40.1 μg Cu/L based on the diatom

culture medium. In addition, they report ed waterborne reproductive EC 20 

### s ranging from 8.3 to

27.4 μg Cu/L. A review by Deforest and Meyer (2015) compared the results of these two studies

and noted the following study design differences which may explain why the waterborne copper

effect levels ar e different: 1) the dilution water in the Lauer and Bianchini (2010) study had a

higher DOC level; 2) two different species of diatoms were used; 3) the diatoms were exposed

for seven days in the Bielmyer et al. (2006b) study versus only 24 hours; and 4) t he feeding

regimes differed between the two studies. In addition, the Bielmyer et al. (2006b) study had

unacceptable control survival (<80 percent) for a chronic test, which suggests that the test

organisms may have been subjected to stresses other than co pper during the exposure. So

, while

the 1.2 μg Cu/L effect concentration from the Bielmyer et al. (2006b) appears to be low, it may

not be representative of the copper water effect concentration to this species. A nd a s discussed

### 67

earlier in Section 2.3 , the apparent lack of aquatic food chain biomagnification ( Lewis and Cave

1982; Suedel et al. 1994 ) reduces the risk to higher trophic level predators including aquatic

dependent wildlife.

Understanding the toxicological link between accumulated metal tissue levels and the

observation of adverse effects remains difficult to characterize, and therefore has received

considerable interest in recent years (Adams et al. 2011; Mebane 2006; Wood et al 2012). The

poorly understood link between copper tissue levels and corresponding adverse effects is in part

due to the various mechanisms utilized by different species to detoxify and/or sequester copper,

thereby rendering it biologically unavailable. A well

- known and widespread copper

detoxification mechanism is the production of metal binding proteins (e.g., metallothioneins) by

a number of invertebrates and fi sh in response to a metal exposure. Adams et al. (2011) noted

that aquatic organisms contain a diverse array of homeostatic mechanisms that are both metal

and species

- specific, and therefore the risk to the aquatic organism could not be determined by

whol e

- body tissue residue levels for metals, further suggesting tissue

- based copper criteria may

not accurately reflect ecotoxicological effects of copper under real

- world exposure scenarios at

the national

- level. Thus, it is unclear if the copper accumulated in a specific fish organ is

bioavailable or sequestered. Therefore, the link between total copper tissue levels and adverse

effects is difficult to quantify since the majority of accumulated copper may be in a detoxified

form.

4.4 Effects on Aquatic Plants

Da ta are available on the toxicity of copper to 26 species of estuarine/marine aquatic

plants ; however, these data were not used quantitatively in this effects assessment because the y

did not meet the MDRs established in the Guidelines to support the derivat ion of a plant

- based

value ( Appendix Table C

- 1 ) . The species for which toxicity data are available encompass

several classes of aquatic plants, inclus ive of microalga, cyanobacterium, diatoms,

dinoflagellates, green and red alga, and two species of k elp. The following data are not BLM

normalized. A copper concentration of 6 0 μg/L copper caused a 50% decrease in photosynthesis

in the giant kelp, Macrocystis pyrefera ( Clendenning and North 1959 ), whereas a 21

- d ay

exposure to 5 μg/L copper reduced gametophyte development rate in the kelp

, Laminaria

saccharina ( Chung and Brinkhuis 1986 ). Zhu et al. (2011) reported a 7

- day growth rate LOEC of

50 μg/L copper for the brown alga, Hizikia fusiformis , and the less sensitive green seaweed , Ulva

### 68

pertusa

, had a chlorophyll fluorescence EC 50 

### of 711 μg/L copper (Kumar et al. 2009)

. Growth

reduction in the red alga, Champia parvul a, occurred in both the tetraspor ophyte and female

plants exposed to copper concentrations of 4.6 and 4.7 μg/L copper

, respectively ( Steele and

Thursby 1983 ). Another red algal species, Ceramium tenuicorne , had a 7

- day growth EC 50 

### of 6.4

μg/L copper

. Dinoflagellates were equally sensitive to copper with gr owth rate reductions

occurring at concentrations that ranged from 5 to 12,740 μg/L copper , with most reductions

occurring at concentrations <50 μg/L copper . Diatoms were also sensitive to copper, with the

most sensitive species

, Thalassio sira aestevallis , h aving reduced growth at 19 μg/L copper with

a 3

- 4 day exposure period ( Hollibaugh et al. 1980 ).

The most sensitive plant effect concentrations were BLM

- normalized to the same water

chemistry to allow comparison to the FCV. All of the n ormalized va lues were greater than the

FCV except a static, unmeasured 4

- day IC 50 

### for reduced growth of 0.8320 μg/L dissolved copper

for the golden/brown flagellate ( Isochrysis sp .) (Garr 2012). Saifullah (1978) reported a BLM

normalized growth LOEC of 2.2 57 μg/L copper for two dinoflagellates ( Prorocentrum micans

and Scrippsiella faeronense ) at 8 and 5 days, respectively. The red alga

, Champia parvula

, had

BLM

- normalized effect concentrations that ranged from 2.078 to 6.159 μg/L based on reduced

growth and reproduction (Steele and Thursby 1983). G iant kelp

, Macrocystis pyrifera

, exposed

to measured copper for 19

- 20 days using renewal procedures exhibited reduced sporophyte

production at a BLM

- normalized concentration of 4.552 μg/ L copper (Anderson et al. 1990). The

most sensitive effect concentration of 0.8320 μg/L copper reported by Garr (2012) was based on

nominal concentrations and

, as recommended by the Guidelines ( Stephan et al. 1985 )

, cannot be

used to calculate a FPV. Since the majority of the other values show sensitivity to copper that is

similar to animal s, a chronic criterion that protect s estuarine/marine animals should also protect

plants

.

4.5 Protection of Endangered Species

The estuarine/marine dataset for copper is ex tensive for the evaluation of acute toxicity

,

but few data are available for the evaluation of chronic toxicity. Only limited data are available

for species that are Federally

- listed as threatened or endangered by the NOAA National Marine

Fisheries Service. Summari es are provided here of data that are available for listed species and

demonstrat e that

, bas ed on the best and most current available data, the draft c opper criteria in

this 201 6 update are protective of threatened or endangered species.

### 69

4.5.1 Acute Toxicity Data for Listed Species

There are only three endangered and/or threatened estuarine/marine species that have

acceptable acute toxicity data. The black abalone, Haliotis cracherodii

, was tested as an adult in

an acute static

- renewal exposure with a BLM

- normalized value of 21.24 μg/L copper ( Martin et

al. 1977 ). The genus Haliotis was the fourth most sensitive genus with the embryo non

endangered abalone species H. rufescens with a BLM

- normalized value of 3.944 μg/L copper

.

The endangered/threatened Coho salmon smolt ( Oncorhynchus kisutch ) was the 43 rd 

### most

sensitive genera tested and had a BLM

- normalized value of 445.6 μg/L copper

. The Leon

Sprin gs pupfish, Cyprinodon bovinus, had a BLM

- normalized SMAV of 778.0 μg/L copper,

with the genus ranking 44 th



### .

4.5.2 Chronic Toxicity Data for Listed Species

There is no threatened and/or endangered estuarine/marine species with acceptable or

other chronic toxicity data for copper.

4.6 Comparison of Draft 200 3 and 201 6 Criteria Values

New acute data for estuarine/marine species have been added to the 201 6 update . A total

of 78 genera are used to derive the estuarine/marine CMC of 2.0 μg/L in the 2 01 6 update (w hen

selected water chemistry values were used for BLM normalization) in comparison to the 4 4

genera used for the 200 3 draft criteria , which resulted in a CMC of 3.1 μg/ L ( Table 9 ). The draft

2003 acute criterion is more stringent than the current recommended 1995 criterion of 4.8 μg/ L,

because of additional data for sensitive organisms (U.S. EPA 1995a , 2003 ). The 201 6 update

uses the BLM to incorporate the interaction and effect of water physical and chemical parameter s

( pH, temperature, salinity and DOC) that affect the bioavailability of copper to aquatic

organisms

. Thus, the numeric water quality criteria values derived from the BLM are dependent

upon site

- specific water quality parameter s

. The updated BLM

- based WQC will in some cases

be more stringent and in other cases less stringent than the previous criteria (whi ch are not

adjusted based on water chemistry condition). As there is not a single WQC value to use for

comparison purposes, the values presented in Table 9 are illustrative only at the selected water

chemistry values used for BLM

- normalization ( Table 7 ).

The four most sensitive genera with available data were used to calculate the CMC in the

2003 draft document ( because n < 59 GMAVs ), while the second to fifth more sensitive genera

### 70

are used in the 201 6 update ( because n≥59 GMAVs ). The CMC reported in U.S. EPA 1995a,

2003 ( draft )

, and this 201 6 (draft) document w ere lowered to protect commercially important

aquatic species, Mytilus edulis

, Mytilus sp. and H. rufescens , respectively. The approximately 35

percent decrease in the 201 6 CMC relative to the 2003 draft CMC is primarily due to the use of

the BLM model and the default selected water quality parameters

, and the additional genera used

to calculate the new CMC including the following : amphipods ( Allorchestes

, Echinogammarus

,

Gammarus and Orchomonella ), barnacle Balanus

, mussel Perna

, crabs ( Callinectes and

Emerita ), horseshoe crab Limulus

, bristle star Ophionereis , copepods ( Nitokra and Tisbe ),

decapod Palaemon , gastropods ( Crepidula

, Planaxis and Turbo ), shrimps ( Farfantepenaeus

,

Metapenaeus

, Litopenaeus

, Palaemonetes and Penaeus ), hard clam Mercenaria , isopod

Sphaeroma , sea urchin s ( Arbacia and Diadema ) , polychaetes ( Eurythoe and Hydroides ), rotifer

Brachionus , sand dollar Dendraster , sea anemone Aiptasia , Gulf toadfish Opsanus , mud

- skipper

Boleophthalmus , fat snook Centropomus a nd thornfish Terapon.

O ne new estuarine/marine species with acceptable chronic data

, the r otifer, Brachionus

plicatilis

, was included in th e 201 6 updat e . The addition of this species, along with sheepshead

minnow data , which was included in the 2003 draft document, results in a total of two species

with chronic values and ACRs. (Note: the chronic value used in the 1995 ALC from Lussier et

al. 1985 for the mysid, Americamysis bahia, is no longer considered valid because of poor

control survival). The 201 6 CCC of 1.3 μg/L copper was derived from division of the FAV of

3.944 μg/L by the FACR of 3.022 , which is less than the 1995 CCC of 3.1 μg/L ( FAV of 9.625

μg/L divided by an FACR of 3. 127), and the 2003 draft CCC of 1.9 μg/L (FAV of 6.188 μg/L

divided by a n FACR of 3.23) at the selected water chemistry conditions

. As noted for the acute

criterion, t he lower CCC presented in th e 201 6 update relative to the previous criteria reflects use

of the BLM that incorporates water physical and chemistry interactions that affect the

bioavailability of copper to aquatic organisms.

### 71

Table 9 . Comparison of the Four Most Sensitive Taxa Used to Calculate the

Estuarine/Marine FAV and CMC in the 2003 Draft Copper Document and 2016 Update.

2003 Draft Copper Estuarine/Marine FAV and CMC 201 6 Copper Update Estuarine/Marine FAV and

CMC (at selected chemistry conditions )

Species SMAV

(μg/L) GMAV

[Rank]

(μg/L) Species SMAV

(μg/L) GMAV

[Rank]

(μg/L)

Mysid,

Holmesimysis costata 9.572 9.572

[5]

Sea urchin,

Strongylocentrotus purpuratus 12.81 12.81

[4] Black abalone,

Haliotis cracherodii 21.24 9.153

[ 4 ] Summer flounder,

Paralichthys dentatus 12.66 12.66

[3] Red abalone,

Haliotis rufescens 3.944

Eastern oyster,

Crassostrea virginica 14.49 12.60

[2] Summer flounder,

Paralichthys dentatus 8.848 8.848

[3]

Pacific oyster,

Crassostrea gigas 10.96 Copepod,

Tigriopus californicus 7.847 7.847

[2]

Blue mussel,

Mytilus edulis 21.50 11.53

[1] Blue m ussel,

Mytilus edulis 4.238 5.577 *

[1] Mussel,

Mytilus sp. 6.19 Mediterranean mussel,

Mytilus galloprovincialis 7.338

Number of GMAVs 44 Number of GMAVs 78

FAV (calculated) 12.34 FAV (calculated) 9.138

CMC (calculated) 6.170 CMC (calculated) 4.6

Lowered FAV a 6.188 Lowered FAV b 3.944

Recommended CMC 3.1 Recommended CMC 2. 0 c



### * Not used to calculate CMC since number of GMAVs ≥59.

a 

### Dissolved copper final acute value (FAV) was lowered from 12.3 4 to 6.188 to protect Mytilus sp

.

b 

### Dissolved copper final acute value (FAV) was lowered from 9.138 to 3.944 to protect Haliotis rufescens

.

c 

### When Temperature=22°C, pH=8, DOC=1.0 mg/L, and S alinity=32 ppt

.

### 72



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### A

- 1



## Appendix A Acceptable Estuarine /Marine Acute Toxicity Data

### A

- 2

Appendix Table A

- 1 . Acceptable Estuarine/Marine Acute Toxicity Data.

Species Organism

Age, Size or

Lifestage Method a Chemical b Reported

LC 50 /EC 50 ( t otal μg/L) c Reported

LC 50 /EC 50 ( d issolved μg/L) d BLM

Data

Label BLM

Normalized

LC 50 /EC 50 (μg/L) e Species

Mean Acute

Value

(μg/L) f Reference

Sea anemone

, Aiptasia pallida - R, M N 148 134.5 12 72.63 72.63 Main et al. 2010

Rotifer

, Brachionus plicatilis Neonate,

0

- 3 hr S, M N

- 13.4 50 16.55

- Arnold et al. 2010b

Rotifer

, Brachionus plicatilis Neonate,

0

- 3 hr S, M N

- 20.8 51 26.58

- Arnold et al. 2010b

Rotifer

, Brachionus plicatilis Neonate, <4hr S, M N

- <12.80 53 < 34.12

- Arnold et al. 2010c

Rotifer

, Brachionus plicatilis Neonate, <4hr S, M N

- <12.60 54 < 31.66

- Arnold et al. 2010c

Rotifer

, Brachionus plicatilis Neonate, <4hr S, M N

- <12.90 55 < 29.67

- Arnold et al. 2010c

Rotifer

, Brachionus plicatilis Neonate, <4hr S, M N

- <12.50 56 < 26.19

- Arnold et al. 2010c

Rotifer

, Brachionus plicatilis Neonate, <4hr S, M N

- 10.1 57 20.41

- Arnold et al. 2010c

Rotifer

, Brachionus plicatilis Neonate, <4hr S, M N

- 119.1 58 57.15

- Arnold et al. 2010c

Rotifer

, Brachionus plicatilis Neonate, <4hr S, M N

- 173.4 59 54.09

- Arnold et al. 2010c

Rotifer

, Brachionus plicatilis Neonate, <4hr S, M N

- 80.7 60 58.41

- Arnold et al. 2010c

Rotifer

, Brachionus plicatilis Neonate, <4hr S, M N

- 45.5 61 30.52

- Arnold et al. 2010c

Rotifer

, Brachionus plicatilis Neonate,

0

- 2 hr S, M

- - 27.7 745 62.17

- Saunders 2012

Rotifer

, Brachionus plicatilis Neonate,

0

- 2 hr S, M

- - 23.3 746 29.42

- Saunders 2012

Rotifer

, Brachionus plicatilis Neonate,

0

- 2 hr S, M

- - 11.2 747 8.347

- Saunders 2012

Rotifer

, Brachionus plicatilis Neonate,

0

- 2 hr S, M

- - 19.7 748 31.19

- Saunders 2012

Rotifer

, Brachionus plicatilis Neonate,

0

- 2 hr S, M

- - 46.8 749 17.47

- Saunders 2012

Rotifer

, Brachionus plicatilis Neonate,

0

- 2 hr S, M

- - 48.9 750 8.115

- Saunders 2012

### A

- 3

Species Organism

Age, Size or

Lifestage Method a Chemical b Reported

LC 50 /EC 50 ( t otal μg/L) c Reported

LC 50 /EC 50 ( d issolved μg/L) d BLM

Data

Label BLM

Normalized

LC 50 /EC 50 (μg/L) e Species

Mean Acute

Value

(μg/L) f Reference

Rotifer,

Brachionus plicatilis Newly

hatched, <6 hr S, M S 42.07 38.24 760 8.034

- Tait 2013

Rotifer,

Brachionus plicatilis Newly

hatched, <6 hr S, M S 49.44 44.94 761 21.89

- Tait 2013

Rotifer,

Brachionus plicatilis Newly

hatched, <6 hr S, M S 62.28 56.61 762 7.599

- Tait 2013

Rotifer,

Brachionus plicatilis Newly

hatched, <6 hr S, M S 46.07 41.88 763 8.182

- Tait 2013

Rotifer,

Brachionus plicatilis Newly

hatched, <6 hr S, M S 25.1 22.82 764 16.92

- Tait 2013

Rotifer,

Brachionus plicatilis Newly

hatched, <6 hr S, M S 21.16 19.23 765 15.25

- Tait 2013

Rotifer,

Brachionus plicatilis Newly

hatched, <6 hr S, M S 58.15 52.86 766 26.75

- Tait 2013

Rotifer,

Brachionus plicatilis Newly

hatched, <6 hr S, M S 26.82 24.38 767 43.03

- Tait 2013

Rotifer,

Brachionus plicatilis Newly

hatched, <6 hr S, M S 35.52 32.29 768 29.01 23.03 Tait 2013

Polychaete

, Anaitides maculata - S, U S 120 100.6 505 53.80 53.80 McLusky and Phillips

1975

Polychaete

, Eurythoe complanata Immature,

1.0 g S, U

- 1,300 1,089 170 1,675 1,675 Marcano et al. 1996

Polychaete

, Hediste (Nereis) diversicolor - S, U S 200 167.6 193 125.3

- Jones et al. 1976

Polychaete

, Hediste (Nereis) diversicolor - S, U S 445 372.9 194 792.4

- Jones et al. 1976

Polychaete

, Hediste (Nereis) diversicolor - S, U S 480 402.2 195 726.9

- Jones et al. 1976

Polychaete

, Hediste (Nereis) diversicolor - S, U S 410 343.6 196 403.9

- Jones et al. 1976

Polychaete

, Hediste (Nereis) diversicolor Juvenile R, U N 357 299.2 197 505.9

- Ozoh 1992a

Polychaete

, Hediste (Nereis) diversicolor Juvenile R, U N 357 299.2 198 475.6

- Ozoh 1992a

Polychaete

, Hediste (Nereis) diversicolor Juvenile R, U N 247 207.0 199 177.4

- Ozoh 1992a

### A

- 4

Species Organism

Age, Size or

Lifestage Method a Chemical b Reported

LC 50 /EC 50 ( t otal μg/L) c Reported

LC 50 /EC 50 ( d issolved μg/L) d BLM

Data

Label BLM

Normalized

LC 50 /EC 50 (μg/L) e Species

Mean Acute

Value

(μg/L) f Reference

Polychaete

, Hediste (Nereis) diversicolor Juvenile R, U N 307 257.3 200 279.7

- Ozoh 1992a

Polychaete

, Hediste (Nereis) diversicolor Juvenile R, U N 400 335.2 201 485.9

- Ozoh 1992a

Polychaete

, Hediste (Nereis) diversicolor Juvenile R, U N 462 387.2 202 597.2

- Ozoh 1992a

Polychaete

, Hediste (Nereis) diversicolor Juvenile R, U N 375 314.3 203 386.0

- Ozoh 1992a

Polychaete

, Hediste (Nereis) diversicolor Juvenile R, U N 362 303.4 204 340.1

- Ozoh 1992a

Polychaete

, Hediste (Nereis) diversicolor Juvenile R, U N 480 402.2 205 539.9

- Ozoh 1992a

Polychaete

, Hediste (Nereis) diversicolor Juvenile R, U N 512 429.1 206 602.1

- Ozoh 1992a

Polychaete

, Hediste (Nereis) diversicolor Juvenile R, U N 360 301.7 207 302.0

- Ozoh 1992a

Polychaete

, Hediste (Nereis) diversicolor Juvenile R, U N 500 419.0 208 508.2

- Ozoh 1992a

Polychaete

, Hediste (Nereis) diversicolor Adult R, U N 402 336.9 209 660.1

- Ozoh 1992b

Polychaete

, Hediste (Nereis) diversicolor Adult R, U N 724 606.7 210 1,718

- Ozoh 1992b

Polychaete

, Hediste (Nereis) diversicolor Adult R, U N 339 284.1 211 389.5

- Ozoh 1992b

Polychaete

, Hediste (Nereis) diversicolor Adult R, U N 776 650.3 212 1,533

- Ozoh 1992b

Polychaete

, Hediste (Nereis) diversicolor Adult R, U N 723 605.9 213 1,286

- Ozoh 1992b

Polychaete

, Hediste (Nereis) diversicolor Adult R, U N 725 607.6 214 1,192

- Ozoh 1992b

Polychaete

, Hediste (Nereis) diversicolor Adult R, U N 900 754.2 215 1,539

- Ozoh 1992b

Polychaete

, Hediste (Nereis) diversicolor Adult R, U N 754 631.9 216 1,127

- Ozoh 1992b

Polychaete

, Hediste (Nereis) diversicolor Adult R, U N 870 729.1 217 1,262

- Ozoh 1992b

Polychaete

, Hediste (Nereis) diversicolor Adult R, U N 890 745.8 218 1,302

- Ozoh 1992b

Polychaete

, Hediste (Nereis) diversicolor Adult R, U N 763 639.4 219 988.6

- Ozoh 1992b

### A

- 5

Species Organism

Age, Size or

Lifestage Method a Chemical b Reported

LC 50 /EC 50 ( t otal μg/L) c Reported

LC 50 /EC 50 ( d issolved μg/L) d BLM

Data

Label BLM

Normalized

LC 50 /EC 50 (μg/L) e Species

Mean Acute

Value

(μg/L) f Reference

Polychaete

, Hediste (Nereis) diversicolor Adult R, U N 825 691.4 220 1,016

- Ozoh 1992b

Polychaete

, Hediste (Nereis) diversicolor - R, U

- 921.5 772.2 221 569.7 623.4 Mouneyrac et al. 2003

Polychaete

, Neanthes arenaceodentata Adult F, M N 77 69.99 469 50.01

- Pesch and Morgan

1978

Polychaete

, Neanthes arenaceodentata Adult F, M N 200 181.8 470 158.3

- Pesch and Morgan

1978

Polychaete

, Neanthes arenaceodentata - F, M N 222 201.8 472 181.1 112.8 Pesch and Hoffman

1982

Polychaete

, Hydroides elegans Larva R, U S 100 83.8 230 87.98 87.98 Bao et al. 2011

Black abalone

, Haliotis cracherodii Adult R, U S 50 41.9 187 21.24 21.24 Martin et al. 1977

Red abalone

, Haliotis rufescens Adult R, U S 65 54.47 189 27.77 g

- Martin et al. 1977

Red abalone

, Haliotis rufescens Larva S, U S 114 95.53 190 49.87 g

- Martin et al. 1977

Red abalone

, Haliotis rufescens Embryo S, M C 8.8 8 191 3.944 3.944 Hunt et al. 1989

Whelk

, Turbo coronatus 2.36 cm,

7.42 g R, U S 3,790 3,176 577 1,416 1,416 Kidwai and Ahmed

1999

Gastropod

, Crepidula convexa Juvenile R, U C 325 272.4 114 1,105 1,105 Untersee and Pechenik

2007

Gastropod

, Crepidula fornicata Larva R, U C 636.3 533.2 116 2,141 2,141 Untersee and Pechenik

2007

Grooved snail

, Planaxis sulcatus 1.92 cm,

1.38 g R, U S 1,010 846.38 507 1,089 1,089 Kidwai and Ahmed

1999

Blue mussel

, Mytilus edulis Juvenile,

15.8 mm R, U C 122

- 333 72.69 g

- Nelson et al. 1988

### A

- 6

Species Organism

Age, Size or

Lifestage Method a Chemical b Reported

LC 50 /EC 50 ( t otal μg/L) c Reported

LC 50 /EC 50 ( d issolved μg/L) d BLM

Data

Label BLM

Normalized

LC 50 /EC 50 (μg/L) e Species

Mean Acute

Value

(μg/L) f Reference

Blue mussel

, Mytilus edulis Embryo S, U S 5.8 4.86 331 2.445

- Martin et al. 1981

Blue mussel

, Mytilus edulis Embryo S, M S 8.92 8.11 334 4.181

- TOXSCAN, Inc. 1991a

Blue mussel

, Mytilus edulis Embryo S, M S 8.19 7.44 335 3.851

- TOXSCAN, Inc. 1991b

Blue mussel

, Mytilus edulis Embryo S, M S 8.29 7.54 336 3.843

- TOXSCAN, Inc. 1991c

Blue mussel

, Mytilus edulis Embryo R, M S 13.1 12.5 337 8.719

- Science Applications

International

Corporation 1993

Blue mussel

, Mytilus edulis Embryo R, M S 14.1 14.1 338 10.40

- Science Applications

International

Corporation 1993

Blue mussel

, Mytilus edulis Embryo R, M S 12.2 11.3 339 7.863

- Science Applications

International

Corporation 1993

Blue mussel

, Mytilus edulis Embryo R, M S 12.8 11.9 340 8.265

- Science Applications

International

Corporation 1993

Blue mussel

, Mytilus edulis Embryo S, M S 7.16 5.95 341 3.524

- City of San Jose 1998

Blue mussel

, Mytilus edulis Embryo S, M S 5.85 5.21 342 3.059

- City of San Jose 1998

Blue mussel

, Mytilus edulis Embryo S, M S 5.03 5.05 343 3.022

- City of San Jose 1998

Blue mussel

, Mytilus edulis Embryo S, M S 3.82 3.75 344 2.230

- City of San Jose 1998

Blue mussel

, Mytilus edulis Embryo S, M S 5.86 5.45 345 3.204

- City of San Jose 1998

Blue mussel

, Mytilus edulis Embryo S, M S 4.7 3.8 346 2.241

- City of San Jose 1998

Blue mussel

, Mytilus edulis Embryo S, M S 6.42 4.97 347 2.949

- City of San Jose 1998

Blue mussel

, Mytilus edulis Embryo S, M S 6.22 5.72 348 3.355

- City of San Jose 1998

Blue mussel

, Mytilus edulis Embryo S, M S 6.21 5.84 349 3.423

- City of San Jose 1998

Blue mussel

, Mytilus edulis Embryo S, M S 5.87 5.44 350 3.187

- City of San Jose 1998

### A

- 7

Species Organism

Age, Size or

Lifestage Method a Chemical b Reported

LC 50 /EC 50 ( t otal μg/L) c Reported

LC 50 /EC 50 ( d issolved μg/L) d BLM

Data

Label BLM

Normalized

LC 50 /EC 50 (μg/L) e Species

Mean Acute

Value

(μg/L) f Reference

Blue mussel

, Mytilus edulis Embryo S, M S 5.4 4.75 351 2.797

- City of San Jose 1998

Blue mussel

, Mytilus edulis Embryo S, M S 6 5.1 352 3.053

- City of San Jose 1998

Blue mussel

, Mytilus edulis Embryo S, M S 9.05 8.3 353 4.912

- City of San Jose 1998

Blue mussel

, Mytilus edulis Embryo S, M S 6.92 5.34 354 3.138

- City of San Jose 1998

Blue mussel

, Mytilus edulis Embryo S, M S 7.19 5.02 355 2.946

- City of San Jose 1998

Blue mussel

, Mytilus edulis Embryo S, M S 5.56 4.39 356 2.548

- City of San Jose 1998

Blue mussel

, Mytilus edulis Embryo S, M S 8.48 7.5 357 4.434

- City of San Jose 1998

Blue mussel

, Mytilus edulis Embryo S, M S 7.36 6.79 358 3.995

- City of San Jose 1998

Blue mussel

, Mytilus edulis Embryo S, M S 7.85 5.29 359 3.090

- City of San Jose 1998

Blue mussel

, Mytilus edulis Embryo S, M S 8.02 6.82 360 3.989

- City of San Jose 1998

Blue mussel

, Mytilus edulis Embryo S, M S 9.5 7.81 361 4.649

- City of San Jose 1998

Blue mussel

, Mytilus edulis Embryo S, M S 7.29 5.59 362 3.270

- City of San Jose 1998

Blue mussel

, Mytilus edulis Embryo S, M S 8.93 6.35 363 3.792

- City of San Jose 1998

Blue mussel

, Mytilus edulis Embryo S, M S 4.54 3.94 364 2.316

- City of San Jose 1998

Blue mussel

, Mytilus edulis Embryo S, M S 4.73 3.9 365 2.315

- City of San Jose 1998

Blue mussel

, Mytilus edulis Embryo S, M N

- 3.52 369 7.142

- Arnold et al. 2008

Blue mussel

, Mytilus edulis Embryo S, M N

- 4.66 370 5.259

- Arnold et al. 2008

Blue mussel

, Mytilus edulis Embryo S, M N

- 21.6 371 4.284

- Arnold et al. 2008

Blue mussel

, Mytilus edulis Embryo S, M N

- 25.2 372 4.907

- Arnold et al. 2008

Blue mussel

, Mytilus edulis Embryo S, M N

- 8.03 373 4.057

- Arnold et al. 2008

### A

- 8

Species Organism

Age, Size or

Lifestage Method a Chemical b Reported

LC 50 /EC 50 ( t otal μg/L) c Reported

LC 50 /EC 50 ( d issolved μg/L) d BLM

Data

Label BLM

Normalized

LC 50 /EC 50 (μg/L) e Species

Mean Acute

Value

(μg/L) f Reference

Blue mussel

, Mytilus edulis Embryo S, M N

- 9.9 374 4.552

- Arnold et al. 2008

Blue mussel

, Mytilus edulis Embryo S, M N

- 14 375 4.048

- Arnold et al. 2008

Blue mussel

, Mytilus edulis Embryo S, M N

- 17.5 376 4.665

- Arnold et al. 2008

Blue mussel

, Mytilus edulis Embryo, 4 hr

post fert S, M S 17.46 17.83 366 13.350

- CH2M Hill 1999b

Blue mussel

, Mytilus edulis Embryo, 4 hr

post fert S, M S 22.81 21.35 367 16.11

- CH2M Hill 1999b

Blue mussel

, Mytilus edulis Embryo, 4 hr

post fert S, M S 27.37 26.1 368 19.88 4.238 CH2M Hill 1999b

Mediterranean mussel

, Mytilus galloprovincialis Embryo S, M

- - 8.3 380 5.606

- Arnold 2005

Mediterranean mussel

, Mytilus galloprovincialis Embryo S, M

- - 8.1 381 5.471

- Arnold 2005

Mediterranean mussel

, Mytilus galloprovincialis Embryo S, M

- - 9.5 382 15.94

- Arnold 2005

Mediterranean mussel

, Mytilus galloprovincialis Embryo S, M

- - 6 383 10.08

- Arnold 2005

Mediterranean mussel

, Mytilus galloprovincialis Embryo S, M

- - 6.9 384 6.984

- Arnold 2005

Mediterranean mussel

, Mytilus galloprovincialis Embryo S, M

- - 7.1 385 5.993

- Arnold 2005

Mediterranean mussel

, Mytilus galloprovincialis Embryo S, M

- - 9.4 386 4.761

- Arnold 2005

Mediterranean mussel

, Mytilus galloprovincialis Embryo S, M

- - 6.8 387 22.14

- Arnold 2005

Mediterranean mussel

, Mytilus galloprovincialis Embryo S, M

- - 12.4 388 17.88

- Arnold 2005

Mediterranean mussel

, Mytilus galloprovincialis Embryo S, M

- - 21.7 389 8.459

- Arnold 2005

Mediterranean mussel

, Mytilus galloprovincialis Embryo S, M

- - 25 390 7.919

- Arnold 2005

Mediterranean mussel

, Mytilus galloprovincialis Embryo S, M

- - 19.1 391 8.415

- Arnold 2005

Mediterranean mussel

, Mytilus galloprovincialis Embryo S, M

- - 21.3 392 21.65

- Arnold 2005

### A

- 9

Species Organism

Age, Size or

Lifestage Method a Chemical b Reported

LC 50 /EC 50 ( t otal μg/L) c Reported

LC 50 /EC 50 ( d issolved μg/L) d BLM

Data

Label BLM

Normalized

LC 50 /EC 50 (μg/L) e Species

Mean Acute

Value

(μg/L) f Reference

Mediterranean mussel

, Mytilus galloprovincialis Embryo S, M

- - 19.4 393 13.13

- Arnold 2005

Mediterranean mussel

, Mytilus galloprovincialis Embryo S, M

- - 19.3 394 9.315

- Arnold 2005

Mediterranean mussel

, Mytilus galloprovincialis Embryo S, M

- - 18.9 395 8.705

- Arnold 2005

Mediterranean mussel

, Mytilus galloprovincialis Embryo S, M

- - 17 396 17.25

- Arnold 2005

Mediterranean mussel

, Mytilus galloprovincialis Embryo S, M

- - 20.1 397 10.19

- Arnold 2005

Mediterranean mussel

, Mytilus galloprovincialis Embryo S, M

- - 27.8 398 8.809

- Arnold 2005

Mediterranean mussel

, Mytilus galloprovincialis Embryo S, M

- - 17.3 399 6.740

- Arnold 2005

Mediterranean mussel

, Mytilus galloprovincialis Embryo S, M

- - 16.3 400 4.713

- Arnold 2005

Mediterranean mussel

, Mytilus galloprovincialis Embryo S, M

- - 19.4 401 4.266

- Arnold 2005

Mediterranean mussel

, Mytilus galloprovincialis Embryo S, M

- - 30.9 402 9.499

- Arnold 2005

Mediterranean mussel

, Mytilus galloprovincialis Embryo S, M

- - 19.6 403 8.275

- Arnold 2005

Mediterranean mussel

, Mytilus galloprovincialis Embryo S, M

- - 14.7 404 14.90

- Arnold 2005

Mediterranean mussel

, Mytilus galloprovincialis Embryo S, M

- - 20.3 405 13.75

- Arnold 2005

Mediterranean mussel

, Mytilus galloprovincialis Embryo S, M

- - 20.7 406 9.538

- Arnold 2005

Mediterranean mussel

, Mytilus galloprovincialis Embryo S, M

- - 16.8 407 8.958

- Arnold 2005

Mediterranean mussel

, Mytilus galloprovincialis Embryo S, M

- - 16.4 408 16.64

- Arnold 2005

Mediterranean mussel

, Mytilus galloprovincialis Embryo S, M

- - 17.8 409 12.04

- Arnold 2005

Mediterranean mussel

, Mytilus galloprovincialis Embryo S, M

- - 15.3 410 9.116

- Arnold 2005

Mediterranean mussel

, Mytilus galloprovincialis Embryo S, M

- - 16.9 411 10.07

- Arnold 2005

Mediterranean mussel

, Mytilus galloprovincialis Embryo S, M

- - 12.4 412 12.55

- Arnold 2005

### A

- 10

Species Organism

Age, Size or

Lifestage Method a Chemical b Reported

LC 50 /EC 50 ( t otal μg/L) c Reported

LC 50 /EC 50 ( d issolved μg/L) d BLM

Data

Label BLM

Normalized

LC 50 /EC 50 (μg/L) e Species

Mean Acute

Value

(μg/L) f Reference

Mediterranean mussel

, Mytilus galloprovincialis Embryo S, M

- - 18.2 413 8.782

- Arnold 2005

Mediterranean mussel

, Mytilus galloprovincialis Embryo S, M

- - 24.2 414 5.001

- Arnold 2005

Mediterranean mussel

, Mytilus galloprovincialis Embryo S, M

- - 13.8 415 6.655

- Arnold 2005

Mediterranean mussel

, Mytilus galloprovincialis Embryo S, M

- - 14.5 416 8.158

- Arnold 2005

Mediterranean mussel

, Mytilus galloprovincialis Embryo S, M

- - 16.7 417 11.29

- Arnold 2005

Mediterranean mussel

, Mytilus galloprovincialis Embryo S, M

- - 24.8 418 3.085

- Arnold 2005

Mediterranean mussel

, Mytilus galloprovincialis Embryo S, M

- - 20.1 419 7.274

- Arnold 2005

Mediterranean mussel

, Mytilus galloprovincialis Embryo S, M

- - 19.2 420 9.731

- Arnold 2005

Mediterranean mussel

, Mytilus galloprovincialis Embryo S, M

- - 22.4 421 7.567

- Arnold 2005

Mediterranean mussel

, Mytilus galloprovincialis Embryo S, M

- - 50.5 422 5.686

- Arnold 2005

Mediterranean mussel

, Mytilus galloprovincialis Embryo S, M

- - 23.3 423 5.901

- Arnold 2005

Mediterranean mussel

, Mytilus galloprovincialis Embryo S, M

- - 22.7 424 10.01

- Arnold 2005

Mediterranean mussel

, Mytilus galloprovincialis Embryo S, M

- - 14.2 425 8.459

- Arnold 2005

Mediterranean mussel

, Mytilus galloprovincialis Embryo S, M

- - 30.3 426 6.397

- Arnold 2005

Mediterranean mussel

, Mytilus galloprovincialis Embryo S, M

- - 16.5 427 7.597

- Arnold 2005

Mediterranean mussel

, Mytilus galloprovincialis Embryo S, M

- - 21.1 428 8.224

- Arnold 2005

Mediterranean mussel

, Mytilus galloprovincialis Embryo S, M

- - 14.5 429 6.385

- Arnold 2005

Mediterranean mussel

, Mytilus galloprovincialis Embryo S, M

- - 23.4 430 5.266

- Arnold 2005

Mediterranean mussel

, Mytilus galloprovincialis Embryo S, M

- - 18.4 431 7.457

- Arnold 2005

Mediterranean mussel

, Mytilus galloprovincialis Embryo S, M

- - 19.7 432 9.075

- Arnold 2005

### A

- 11

Species Organism

Age, Size or

Lifestage Method a Chemical b Reported

LC 50 /EC 50 ( t otal μg/L) c Reported

LC 50 /EC 50 ( d issolved μg/L) d BLM

Data

Label BLM

Normalized

LC 50 /EC 50 (μg/L) e Species

Mean Acute

Value

(μg/L) f Reference

Mediterranean mussel

, Mytilus galloprovincialis Embryo S, M

- - 21.1 433 12.60

- Arnold 2005

Mediterranean mussel

, Mytilus galloprovincialis Embryo S, M

- - 33.3 434 3.502

- Arnold 2005

Mediterranean mussel

, Mytilus galloprovincialis Embryo S, M

- - 21.3 435 7.443

- Arnold 2005

Mediterranean mussel

, Mytilus galloprovincialis Embryo S, M

- - 14 436 7.089

- Arnold 2005

Mediterranean mussel

, Mytilus galloprovincialis Embryo S, M

- - 30.2 437 3.043

- Arnold 2005

Mediterranean mussel

, Mytilus galloprovincialis Embryo S, M

- - 11.1 438 3.501

- Arnold 2005

Mediterranean mussel

, Mytilus galloprovincialis Embryo S, M

- - 14.8 439 10.72

- Arnold 2005

Mediterranean mussel

, Mytilus galloprovincialis Embryo S, M

- - 13 440 11.98

- Arnold 2005

Mediterranean mussel

, Mytilus galloprovincialis Embryo S, M

- - 71 441 8.327

- Arnold 2005

Mediterranean mussel

, Mytilus galloprovincialis Embryo S, M

- - 24.8 442 7.663

- Arnold 2005

Mediterranean mussel

, Mytilus galloprovincialis Embryo S, M

- - 17.1 443 11.57

- Arnold 2005

Mediterranean mussel

, Mytilus galloprovincialis Embryo S, M

- - 16.6 444 12.03

- Arnold 2005

Mediterranean mussel

, Mytilus galloprovincialis Embryo S, M

- - 52.9 295 10.60

- Arnold et al. 2006

Mediterranean mussel

, Mytilus galloprovincialis Embryo S, M

- - 59.4 296 7.044

- Arnold et al. 2006

Mediterranean mussel

, Mytilus galloprovincialis Embryo S, M

- - 47.9 297 5.029

- Arnold et al. 2006

Mediterranean mussel

, Mytilus galloprovincialis Embryo S, M

- - 48.2 298 10.26

- Arnold et al. 2006

Mediterranean mussel

, Mytilus galloprovincialis Embryo S, M

- - 54 299 8.348

- Arnold et al. 2006

Mediterranean mussel

, Mytilus galloprovincialis Embryo S, M

- - 47.8 300 4.867

- Arnold et al. 2006

Mediterranean mussel

, Mytilus galloprovincialis Embryo S, M

- - 19.6 301 13.37

- Arnold et al. 2006

Mediterranean mussel

, Mytilus galloprovincialis Embryo S, M

- - 34.4 302 4.797

- Arnold et al. 2006

### A

- 12

Species Organism

Age, Size or

Lifestage Method a Chemical b Reported

LC 50 /EC 50 ( t otal μg/L) c Reported

LC 50 /EC 50 ( d issolved μg/L) d BLM

Data

Label BLM

Normalized

LC 50 /EC 50 (μg/L) e Species

Mean Acute

Value

(μg/L) f Reference

Mediterranean mussel

, Mytilus galloprovincialis Embryo S, M

- - 56.8 303 5.261

- Arnold et al. 2006

Mediterranean mussel

, Mytilus galloprovincialis Embryo S, M

- - 15.9 304 11.60

- Arnold et al. 2006

Mediterranean mussel

, Mytilus galloprovincialis Embryo S, M

- - 33.8 305 5.555

- Arnold et al. 2006

Mediterranean mussel

, Mytilus galloprovincialis Embryo S, M

- - 20 306 10.21

- Arnold et al. 2006

Mediterranean mussel

, Mytilus galloprovincialis Embryo S, M

- - 22.5 307 4.874

- Arnold et al. 2006

Mediterranean mussel

, Mytilus galloprovincialis Embryo S, M

- - 54.4 308 4.614

- Arnold et al. 2006

Mediterranean mussel

, Mytilus galloprovincialis Embryo S, M

- - 14.7 309 8.814

- Arnold et al. 2006

Mediterranean mussel

, Mytilus galloprovincialis Embryo S, M

- - 16.1 310 4.820

- Arnold et al. 2006

Mediterranean mussel

, Mytilus galloprovincialis Embryo S, M

- - 41.6 311 4.273

- Arnold et al. 2006

Mediterranean mussel

, Mytilus galloprovincialis Embryo S, M

- - 11.8 312 11.95

- Arnold et al. 2006

Mediterranean mussel

, Mytilus galloprovincialis Embryo S, M

- - 11.7 313 9.874

- Arnold et al. 2006

Mediterranean mussel

, Mytilus galloprovincialis Embryo S, M

- - 12.3 314 4.296

- Arnold et al. 2006

Mediterranean mussel

, Mytilus galloprovincialis Embryo S, M

- - 14.1 315 4.464

- Arnold et al. 2006

Mediterranean mussel

, Mytilus galloprovincialis Embryo S, M N

- 9.7 316 1.614

- Arnold et al. 2007

Mediterranean mussel

, Mytilus galloprovincialis Embryo S, M N

- 8.6 317 21.80

- Arnold et al. 2007

Mediterranean mussel

, Mytilus galloprovincialis Embryo S, M N

- 7.5 318 58.07

- Arnold et al. 2007

Mediterranean mussel

, Mytilus galloprovincialis Embryo S, M N

- 5.13 446 7.443

- Arnold et al. 2008

Mediterranean mussel

, Mytilus galloprovincialis Embryo S, M N

- 3.56 447 3.602

- Arnold et al. 2008

Mediterranean mussel

, Mytilus galloprovincialis Embryo S, M N

- 30.6 448 6.329

- Arnold et al. 2008

Mediterranean mussel

, Mytilus galloprovincialis Embryo S, M N

- 21.7 449 3.847

- Arnold et al. 2008

### A

- 13

Species Organism

Age, Size or

Lifestage Method a Chemical b Reported

LC 50 /EC 50 ( t otal μg/L) c Reported

LC 50 /EC 50 ( d issolved μg/L) d BLM

Data

Label BLM

Normalized

LC 50 /EC 50 (μg/L) e Species

Mean Acute

Value

(μg/L) f Reference

Mediterranean mussel

, Mytilus galloprovincialis Embryo S, M N

- 12.2 450 6.503

- Arnold et al. 2008

Mediterranean mussel

, Mytilus galloprovincialis Embryo S, M N

- 6.91 451 3.164

- Arnold et al. 2008

Mediterranean mussel

, Mytilus galloprovincialis Embryo S, M N

- 20.2 452 6.206

- Arnold et al. 2008

Mediterranean mussel

, Mytilus galloprovincialis Embryo S, M N

- 11.5 453 3.053

- Arnold et al. 2008

Mediterranean mussel

, Mytilus galloprovincialis Embryo S, M S

- 6.36 454 4.824

- Rosen et al. 2008

Mediterranean mussel

, Mytilus galloprovincialis Embryo S, M S

- 8.68 455 5.051

- Rosen et al. 2008

Mediterranean mussel

, Mytilus galloprovincialis Embryo S, M N

- 6.28 456 8.040

- Arnold et al. 2010a

Mediterranean mussel

, Mytilus galloprovincialis Embryo S, M N

- 14.4 457 5.646

- Arnold et al. 2010a

Mediterranean mussel

, Mytilus galloprovincialis Embryo S, M N

- 28.2 458 7.341

- Arnold et al. 2010a

Mediterranean mussel

, Mytilus galloprovincialis Embryo S, M N

- 34.8 459 6.205

- Arnold et al. 2010a

Mediterranean mussel

, Mytilus galloprovincialis Embryo S, M N

- 10.9 460 9.118

- Arnold et al. 2010a

Mediterranean mussel

, Mytilus galloprovincialis Embryo S, M N

- 21 461 10.06

- Arnold et al. 2010a

Mediterranean mussel

, Mytilus galloprovincialis Embryo S, M N

- 31.6 462 9.065

- Arnold et al. 2010a

Mediterranean mussel

, Mytilus galloprovincialis Embryo S, M N

- 37.2 463 7.459

- Arnold et al. 2010a

Mediterranean mussel

, Mytilus galloprovincialis Embryo, 4 cell S, M N

- 12.66 319 11.87

- DePalma et al. 2011

Mediterranean mussel

, Mytilus galloprovincialis Embryo, 4 cell S, M N

- 22.72 320 6.452

- DePalma et al. 2011

Mediterranean mussel

, Mytilus galloprovincialis Embryo, 4 cell S, M N

- 19.01 321 8.304

- DePalma et al. 2011

Mediterranean mussel

, Mytilus galloprovincialis Embryo, 4 cell S, M N

- 20.67 322 6.237

- DePalma et al. 2011

Mediterranean mussel

, Mytilus galloprovincialis Embryo, 4 cell S, M N

- 16.04 323 9.176

- DePalma et al. 2011

Mediterranean mussel

, Mytilus galloprovincialis Embryo, 4 cell S, M N

- 20.45 324 6.781

- DePalma et al. 2011

### A

- 14

Species Organism

Age, Size or

Lifestage Method a Chemical b Reported

LC 50 /EC 50 ( t otal μg/L) c Reported

LC 50 /EC 50 ( d issolved μg/L) d BLM

Data

Label BLM

Normalized

LC 50 /EC 50 (μg/L) e Species

Mean Acute

Value

(μg/L) f Reference

Mediterranean mussel

, Mytilus galloprovincialis Embryo, 4 cell S, M N

- 31.58 325 4.646

- DePalma et al. 2011

Mediterranean mussel

, Mytilus galloprovincialis Embryo, 4 cell S, M N

- 30.96 326 9.895

- DePalma et al. 2011

Mediterranean mussel

, Mytilus galloprovincialis Embryo, 4 cell S, M N

- 15.96 327 10.27

- DePalma et al. 2011

Mediterranean mussel

, Mytilus galloprovincialis Embryo, 4 cell S, M N

- 31.19 328 4.748

- DePalma et al. 2011

Mediterranean mussel

, Mytilus galloprovincialis 20

- 39 mm S, U S 1,670 1,399 730 2,285 g

- Bat et al. 2013

Mediterranean mussel

, Mytilus galloprovincialis 40

- 59 mm S, U S 1,450 1,215 731 1,946 g

- Bat et al. 2013

Mediterranean mussel

, Mytilus galloprovincialis 60

- 79 mm S, U S 1,180 988.8 732 1,529 g

- Bat et al. 2013

Mediterranean mussel

, Mytilus galloprovincialis 50

- 80 mm S, U S 800.0 670.4 733 944.8 g

- Bat et al. 2013

Mediterranean mussel,

Mytilus galloprovincialis Embryo S, M C

- 8.9 769 4.345

- Fabbri et al. 2014

Mediterranean mussel,

Mytilus galloprovincialis Embryo S, M C

- 8.7 770 4.258

- Fabbri et al. 2014

Mediterranean mussel,

Mytilus galloprovincialis Embryo S, M C

- 12.2 752 4.321

- Deruytter et al. 2015

Mediterranean mussel,

Mytilus galloprovincialis Embryo S, M C

- 10.1 753 8.568

- Deruytter et al. 2015

Mediterranean mussel,

Mytilus galloprovincialis Embryo S, M C

- 13.4 754 3.556

- Deruytter et al. 2015

Mediterranean mussel,

Mytilus galloprovincialis Embryo S, M C

- 4.1 755 7.452

- Deruytter et al. 2015

Mediterranean mussel,

Mytilus galloprovincialis Embryo S, M C

- 13.6 756 2.946

- Deruytter et al. 2015

Mediterranean mussel,

Mytilus galloprovincialis Embryo S, M C

- 10.3 757 3.734

- Deruytter et al. 2015

Mediterranean mussel,

Mytilus galloprovincialis Embryo S, M C

- 11.0 758 3.990

- Deruytter et al. 2015

Mediterranean mussel,

Mytilus galloprovincialis Embryo S, M C

- 5.0 759 3.385 7.338 Deruytter et al. 2015

Asian green mussel,

Perna viridis Juvenile,

1.6 cm, 0.12 g R, M C

- 500.0 771 646.9 646.9 Rajkumar 2012

### A

- 15

Species Organism

Age, Size or

Lifestage Method a Chemical b Reported

LC 50 /EC 50 ( t otal μg/L) c Reported

LC 50 /EC 50 ( d issolved μg/L) d BLM

Data

Label BLM

Normalized

LC 50 /EC 50 (μg/L) e Species

Mean Acute

Value

(μg/L) f Reference

Bay scallop

, Argopecten irradians Juvenile,

21.2 mm R, U C 29 24.30 32 15.35 15.35 Nelson et al. 1988

Pacific oyster

, Crassostrea gigas Adult,

13

- 17 cm F, M S 560.00

- 88 662.0 g

- Okazaki 1976

Pacific oyster

, Crassostrea gigas Embryo S, U C 11.5 9.640 89 4.918

- Coglianese and Martin

1981

Pacific oyster

, Crassostrea gigas Embryo S,M C 12.06 10.96 90 6.871

- Harrison et al. 1981

Pacific oyster

, Crassostrea gigas Embryo S, M C 12 10.91 93 12.88

- Knezovich et al. 1981

Pacific oyster

, Crassostrea gigas Embryo S, U S 5.3 4.440 94 2.237

- Martin et al. 1981

Pacific oyster

, Crassostrea gigas Embryo S, M Copper 25.8 23.45 96 50.05

- S.R. Hansen &

Associates 1992

Pacific oyster

, Crassostrea gigas Embryo S, M Copper 30.5 27.72 97 59.35 11.94 S.R. Hansen &

Associates 1992

Eastern oyster

, Crassostrea virginica Embryo S, U C 15.1 12.65 106 6.699

- MacInnes and

Calabrese 1978

Eastern oyster

, Crassostrea virginica Embryo S, U C 18.7 15.67 107 8.284

- MacInnes and

Calabrese 1978

Eastern oyster

, Crassostrea virginica Embryo S, U C 18.3 15.34 108 8.110

- MacInnes and

Calabrese 1978

Eastern oyster

, Crassostrea virginica Embryo S, M N

- 11.2 109 14.40

- Arnold et al. 2010a

Eastern oyster

, Crassostrea virginica Embryo S, M N

- 22.4 110 8.791

- Arnold et al. 2010a

Eastern oyster

, Crassostrea virginica Embryo S, M N

- 30.7 111 7.994

- Arnold et al. 2010a

Eastern oyster

, Crassostrea virginica Embryo S, M N

- 40.7 112 7.259 8.537 Arnold et al. 2010a

Coot clam

, Mulinia lateralis Embryo R, M S 25.2 21 286 14.84

- Science Applications

International

Corporation 1993

Coot clam

, Mulinia lateralis Embryo R, M S 19.1 14.9 287 10.49

- Science Applications

International

Corporation 1993

### A

- 16

Species Organism

Age, Size or

Lifestage Method a Chemical b Reported

LC 50 /EC 50 ( t otal μg/L) c Reported

LC 50 /EC 50 ( d issolved μg/L) d BLM

Data

Label BLM

Normalized

LC 50 /EC 50 (μg/L) e Species

Mean Acute

Value

(μg/L) f Reference

Coot clam

, Mulinia lateralis Embryo R, M S 18.4 17.3 288 12.12

- Science Applications

International

Corporation 1993

Coot clam

, Mulinia lateralis Embryo R, M S 18.6 16.9 289 11.70

- Science Applications

International

Corporation 1993

Coot clam

, Mulinia lateralis Embryo R, M S 18.9 19.3 290 13.49

- Science Applications

International

Corporation 1993

Coot clam

, Mulinia lateralis Embryo R, M S 18.4 17.4 291 12.09 12.38 Science Applications

International

Corporation 1993

Clam

, Rangia cuneata - S, U S 8,000 6,704 526 66,022

- Olson and Harrel 1973

Clam

, Rangia cuneata - S, U S 7,400 6,201 527 28,918 43,694 Olson and Harrel 1973

Surf clam

, Spisula solidissima Juvenile,

15.9 mm R, U C 51 42.74 536 28.35 28.35 Nelson et al. 1988

Hard clam

, Mercenaria mercenaria Larva,

160

- 180 μm S, U S 398.2 333.7 274 350.2 350.2 Becerra

- Huencho 1984

Softshell clam

, Mya arenaria 38

- 49 mm,

3.6

- 6.0 g S, U C 39 32.68 293 23.03 23.03 Eisler 1977

Squid

, Loligo opalescens Post

- hatch

larva S, M C 309 280.9 243 222.9 222.9 Dinnel et al. 1989

Copepod

, Pseudodiaptomus coronatus - S, U C 235.4 197.3 509 127.8

- Gentile 1982

Copepod

, Pseudodiaptomus coronatus - S, U

- 138 115.6 510 62.64

- Gentile and Cardin

1982

Copepod

, Pseudodiaptomus coronatus Adult S, U C 235.4 197.3 511 129.5 101.2 Lussier and Cardin

1985

Copepod

, Eurytemora affinis - S, U C 928.0

- 151 1,361 g

- Gentile 1982

### A

- 17

Species Organism

Age, Size or

Lifestage Method a Chemical b Reported

LC 50 /EC 50 ( t otal μg/L) c Reported

LC 50 /EC 50 ( d issolved μg/L) d BLM

Data

Label BLM

Normalized

LC 50 /EC 50 (μg/L) e Species

Mean Acute

Value

(μg/L) f Reference

Copepod

, Eurytemora affinis - S, U

- 526.0

- 152 632.5 g

- Gentile and Cardin

1982

Copepod

, Eurytemora affinis Nauplii, 24 hr R, M N 30.6 27.82 153 14.27

- Sullivan et al. 1983

Copepod

, Eurytemora affinis Nauplii, 24 hr R, M N 31.1 28.27 154 14.50

- Sullivan et al. 1983

Copepod

, Eurytemora affinis Nauplii, 24 hr R, M N 28.7 26.09 155 13.36

- Sullivan et al. 1983

Copepod

, Eurytemora affinis Nauplii, 24 hr R, M N 7.5 6.82 156 3.453

- Sullivan et al. 1983

Copepod

, Eurytemora affinis Nauplii, 24 hr R, M N 33.7 30.63 157 15.74

- Sullivan et al. 1983

Copepod

, Eurytemora affinis Nauplii, 24 hr S, M C

- 69.4 158 22.99

- Hall et al. 1997

Copepod

, Eurytemora affinis Nauplii, 24 hr S, M C

- 71 161 28.51

- Hall et al. 2008

Copepod

, Eurytemora affinis Nauplii, 24 hr S, M C

- 104 162 54.19

- Hall et al. 2008

Copepod

, Eurytemora affinis Nauplii, 24 hr S, M C

- 67.6 163 44.69

- Hall et al. 2008

Copepod

, Eurytemora affinis Nauplii, 24 hr S, M C

- 58.1 164 45.39

- Hall et al. 2008

Copepod

, Eurytemora affinis Nauplii, 24 hr S, M C

- 76.2 165 37.25

- Hall et al. 2008

Copepod

, Eurytemora affinis Nauplii, 24 hr S, M C

- 108 166 34.92

- Hall et al. 2008

Copepod

, Eurytemora affinis Nauplii, 24 hr S, M C

- 111 167 24.40

- Hall et al. 2008

Copepod

, Eurytemora affinis Nauplii, 24 hr S, M C

- 166 168 23.81 22.44 Hall et al. 2008

Copepod

, Acartia clausi - S, U C 48.80 40.89 1 21.15

- Gentile 1982

Copepod

, Acartia clausi - S, U

- 52.00 43.58 2 22.59 21.86 Gentile and Cardin

1982

Copepod,

Acartia tonsa - S, U C 17 14.25 4 8.367

- Sosnowski and Gentile

1978

Copepod,

Acartia tonsa - S, U C 55 46.09 5 28.36

- Sosnowski and Gentile

1978

### A

- 18

Species Organism

Age, Size or

Lifestage Method a Chemical b Reported

LC 50 /EC 50 ( t otal μg/L) c Reported

LC 50 /EC 50 ( d issolved μg/L) d BLM

Data

Label BLM

Normalized

LC 50 /EC 50 (μg/L) e Species

Mean Acute

Value

(μg/L) f Reference

Copepod,

Acartia tonsa - S, U C 31 25.98 6 13.31

- Sosnowski and Gentile

1978

Copepod,

Acartia tonsa - S, U

- 17 14.25 7 7.262

- Gentile and Cardin

1982

Copepod,

Acartia tonsa M ixed ages R, M C

- 41.80 734 609.2 g

- Monteiro et al. 2013

Copepod,

Acartia tonsa M ixed ages R, M C

- 67.40 735 533.7 g

- Monteiro et al. 2013

Copepod,

Acartia tonsa M ixed ages R, M C

- 108.7 736 470.8 g 12.31 Monteiro et al. 2013

Copepod,

Amphiascoides atopus Adult, female S, M C 334.24 303.8 737 1,192

- Caramujo et al. 2012

Copepod,

Amphiascoides atopus Adult, female S, M C 538.67 489.7 738 1,905

- Caramujo et al. 2012

Copepod,

Amphiascoides atopus Adult, female S, M C 741.83 674.3 739 2,614

- Caramujo et al. 2012

Copepod,

Amphiascoides atopus Adult, female S, M C 857.19 779.2 740 3,017 2,057 Caramujo et al. 2012

Copepod

, Tigriopus californicus Egg/Embryo R, U N 229 191.9 557 108.6 g

- O'Brien et al. 1988

Copepod

, Tigriopus californicus Nauplii,

Stage 1 R, U N 76 63.69 558 31.78 g

- O'Brien et al. 1988

Copepod

, Tigriopus californicus Nauplii,

Stage 2 R, U N 19 15.92 559 7.847

- O'Brien et al. 1988

Copepod

, Tigriopus californicus Nauplii,

Stage 3 R, U N 159 133.24 560 69.79 g

- O'Brien et al. 1988

Copepod

, Tigriopus californicus Nauplii,

Stage 4 R, U N 184 154.19 561 82.66 g

- O'Brien et al. 1988

Copepod

, Tigriopus californicus Nauplii,

Stage 5 R, U N 261 218.72 562 129.6 g

- O'Brien et al. 1988

Copepod

, Tigriopus californicus Nauplii,

Stage 6 R, U N 305 255.59 563 161.9 g

- O'Brien et al. 1988

Copepod

, Tigriopus californicus Copepodite,

Stage 1 R, U N 375 314.25 564 218.7 g

- O'Brien et al. 1988

Copepod

, Tigriopus californicus Copepodite,

Stage 2 R, U N 496 415.65 565 322.7 g

- O'Brien et al. 1988

Copepod

, Tigriopus californicus Copepodite,

Stage 3 R, U N 413 346.09 566 250.9 g

- O'Brien et al. 1988

### A

- 19

Species Organism

Age, Size or

Lifestage Method a Chemical b Reported

LC 50 /EC 50 ( t otal μg/L) c Reported

LC 50 /EC 50 ( d issolved μg/L) d BLM

Data

Label BLM

Normalized

LC 50 /EC 50 (μg/L) e Species

Mean Acute

Value

(μg/L) f Reference

Copepod

, Tigriopus californicus Copepodite,

Stage 4 R, U N 394 330.2 567 234.7 g

- O'Brien et al. 1988

Copepod

, Tigriopus californicus Copepodite,

Stage 5 R, U N 394 330.2 568 234.7 g

- O'Brien et al. 1988

Copepod

, Tigriopus californicus Adult R, U N 762 638.56 569 557.4 g 7.847 O'Brien et al. 1988

Copepod

, Tisbe furcata Newborn

nauplii R, M S

- 178 571 99.77 99.77 Bechmann 1994

Copepod

, Nitokra spinipes Adult S, U C 1,800 1,508 478 2,781

- Bengtsson 1978

Copepod,

Nitokra spinipes - S, U C 2,100 1,760 772 4,961 3,715 Ytreberg et al. 2010

Barnacle

, Balanus amphitrite Nauplii, Stage

2 S, U S 145 121.5 44 64.73

- Qi u et al. 2005

Barnacle

, Balanus amphitrite Nauplii, Stage

4 S, U S 156 130.7 45 70.50

- Qi u et al. 2005

Barnacle

, Balanus amphitrite Nauplii, Stage

6 S, U S 213 178.5 46 105.6

- Qi u et al. 2005

Barnacle

, Balanus amphitrite Nauplii, Stage

2 S, U S 720 603.4 741 791.1 139.7 Prato et al. 2012

Barnacle,

Balanus eburneus Nauplii, Stage

2 S, U S 750 628.5 742 835.4 835.4 Prato et al. 2012

Mysid

, Americamysis bahia 24 hr F, M N 181 164.5 16 96.60

- Lussier et al. 1985

Mysid

, Americamysis bahia 2

- 30 hr R, M S 209 164.0 17 153.7 h

- Science Applications

International

Corporation 1993

Mysid

, Americamysis bahia Juvenile,

<24 hr R, U C 72.32 60.60 18 32.34 h

- Cripe 1994

Mysid

, Americamysis bahia <48 hr S, M

- 110 99.99 19 99.37 h

- Ho et al. 1999

Mysid

, Americamysis bahia <48 hr S, M

- 250 227.3 20 189.0 h

- Ho et al. 1999

Mysid

, Americamysis bahia <48 hr S, M

- 360 327.2 21 39.29 h 96.60 Ho et al. 1999

### A

- 20

Species Organism

Age, Size or

Lifestage Method a Chemical b Reported

LC 50 /EC 50 ( t otal μg/L) c Reported

LC 50 /EC 50 ( d issolved μg/L) d BLM

Data

Label BLM

Normalized

LC 50 /EC 50 (μg/L) e Species

Mean Acute

Value

(μg/L) f Reference

Mysid

, Americamysis bigelowi 24 hr F, M N 141 128.2 23 70.57 70.57 Gentile 1982

Mysid

, Holmesimysis costata <3 d S, M C 27 24.54 223 12.08

- Hunt et al. 1989

Mysid

, Holmesimysis costata Juvenile, 3 d S, M C 17 15.45 224 7.588 9.572 Martin et al. 1989

Mysid

, Neomysis mercedis Neonate, >5 d F, M S 28.27 25.7 474 16.73

- Brandt et al. 1993

Mysid

, Neomysis mercedis Juvenile,

>15 d F, M S 87.58 79.61 475 52.85

- Brandt et al. 1993

Mysid

, Neomysis mercedis Juvenile,

>15 d F, M S 63.7 57.9 476 39.19 32.60 Brandt et al. 1993

Isopod

, Sphaeroma serratum - S, U S 1,980 1,659 534 1,672 1,672 Bat et al. 1999a

Amphipod

, Corophium volutator Adult, 4

- 7 mm S, U S 20,740 17,380 79 81,550 81,550 Bat et al. 1998

Amphipod

, Echinogammarus olivii - S, U S 250 209.5 137 130.1 130.1 Bat et al. 1999a

Amphipod

, Gammarus duebeni Adult,

60

- 90 mg R, U C >10,000 >8,380 185 >29,733 >29,733 Moulder 1980

Amphipod

, Allorchestes compressa - F, M S 480 436.3 14 515.7 515.7 Ahsanullah et al. 1988

Amphipod

, Elasmopus rapax Juvenile,

0.54 mm R, U S 78 65.36 141 75.57

- Bao et al. 2008

Amphipod

, Elasmopus rapax Juvenile R, U S 77 64.53 142 74.97 75.27 Bao et al. 2011

Amphipod,

Orchomenella pinguis Adult R, U

- 179.8 150.7 773 85.48 85.48 Bach et al. 2014

### A

- 21

Species Organism

Age, Size or

Lifestage Method a Chemical b Reported

LC 50 /EC 50 ( t otal μg/L) c Reported

LC 50 /EC 50 ( d issolved μg/L) d BLM

Data

Label BLM

Normalized

LC 50 /EC 50 (μg/L) e Species

Mean Acute

Value

(μg/L) f Reference

Pink shrimp

, Farfantepenaeus duorarum Post

- larva,

3

- 5 d R, U C 393.3 329.6 503 260.8 260.8 Cripe 1994

Tiger shrimp,

Penaeus monodon Post

- larva R, U C 660 553.1 743 746.8

- Kumar 2012

Tiger shrimp,

Penaeus monodon Post

- larva,

Stage 12 R, M C

- 950.0 774 1,498 1,058 Rajkumar 2012

Whiteleg shrimp

, Litopenaeus vannamei 1.2 cm R, U C 37,000 4,200 239 3,014 3,014 Frias

- Espericueta et al.

2003

Shrimp

, Metapenaeus sp. 2.45 cm,

3.905 g R, U S 220 184.36 276 106.8 106.8 Kidwai and Ahmed

1999

Decapod

, Palaemon elegans - S, U S 2,520 2,112 487 2,163 2,163 Bat et al. 1999a

Grass shrimp

, Palaemonetes pugio Embryo, 9 d S, U C 860.3 720.9 489 2,590 2,590 Rayburn and Fisher

1999

Shrimp

, Crangon crangon Larva, 1

- 3 d S, U S 330 276.5 85 255.4 255.4 Connor 1972

Lobster

, Homarus americanus Larva stage 1,

24 hr S, U N 48 40.22 226 28.37 28.37 Johnson and Gentile

1979

Dungeness crab

, Cancer magister Larva S, U S 49 41.06 68 20.60

- Martin et al. 1981

Dungeness crab

, Cancer magister Zoea S, M C 96 87.26 69 61.93 35.72 Dinnel et al. 1989

Blue crab

, Callinectes sapidus Juvenile,

8.3 cm R, M C

- 337.2 65 6,403

- Martins et al. 2011

Blue crab

, Callinectes sapidus Juvenile,

8.3 cm R, M C

- 3,365 66 12,583 8,976 Martins et al. 2011

Shore crab

, Carcinus maenas Larva, 1

- 3 d S, U S 600 502.8 71 730.8 730.8 Connor 1972

### A

- 22

Species Organism

Age, Size or

Lifestage Method a Chemical b Reported

LC 50 /EC 50 ( t otal μg/L) c Reported

LC 50 /EC 50 ( d issolved μg/L) d BLM

Data

Label BLM

Normalized

LC 50 /EC 50 (μg/L) e Species

Mean Acute

Value

(μg/L) f Reference

Sand crab

, Emerita analoga Immature,

8

- 10 mm S, U C 2,000 1,676 144 2,492 2,492 Valdovinos and Zuniga

2002

Horseshoe crab,

Limulus polyphemus Embryo,

Stage 20,

Sandy Hook R, U S 2,000 1,676 775 3,473 Botton et al. 1998

Horseshoe crab,

Limulus polyphemus Embryo,

Stage 20,

Delaware Bay R, U S 171,000 143,298 776 289,605 Botton et al. 1998

Horseshoe crab,

Limulus polyphemus Larva,

Sandy Hook R, U S 637,000 533,806 777 1,066,174 g 31,716 Botton et al. 1998

Bristle star

, Ophionereis dubia 0.14 g R, U S 960 804.48 483 589.5 589.5 Kidwai and Ahmed

1999

Sea urchin,

Arbacia punctulata Embryo S, M S 30 27 778 13.85 13.85 Nelson et al. 2010

Green sea urchin

, Strongylocentrotus droebachiensis Embryo S, M C 21 19.09 538 13.29 13.29 Dinnel et al. 1989

Purple sea urchin

, Strongylocentrotus purpuratus Embryo S, M C 6.3 5.73 543 3.966

- Dinnel et al. 1989

Purple sea urchin

, Strongylocentrotus purpuratus Embryo S, M S 14.38 13.52 547 8.030

- City of San Jose 1998

Purple sea urchin

, Strongylocentrotus purpuratus Embryo S, M S 15.05 12.77 548 7.593

- City of San Jose 1998

Purple sea urchin

, Strongylocentrotus purpuratus Embryo S, M S

- 14.3 549 5.768

- Rosen et al. 2008

Purple sea urchin

, Strongylocentrotus purpuratus Embryo S, M N

- 14.8 550 12.41

- Arnold et al. 2010a

Purple sea urchin

, Strongylocentrotus purpuratus Embryo S, M N

- 24.3 551 11.66

- Arnold et al. 2010a

Purple sea urchin

, Strongylocentrotus purpuratus Embryo S, M N

- 30.2 552 8.661

- Arnold et al. 2010a

Purple sea urchin

, Strongylocentrotus purpuratus Embryo S, M N

- 46.4 553 9.320 7.971 Arnold et al. 2010a

Sand dollar

, Dendraster excentricus Embryo S, M C 33 30 125 21.43

- Dinnel et al. 1989

### A

- 23

Species Organism

Age, Size or

Lifestage Method a Chemical b Reported

LC 50 /EC 50 ( t otal μg/L) c Reported

LC 50 /EC 50 ( d issolved μg/L) d BLM

Data

Label BLM

Normalized

LC 50 /EC 50 (μg/L) e Species

Mean Acute

Value

(μg/L) f Reference

Sand dollar

, Dendraster excentricus Embryo S, M N

- 18.9 129 15.89

- Arnold et al. 2010a

Sand dollar

, Dendraster excentricus Embryo S, M N

- 36.4 130 17.57

- Arnold et al. 2010a

Sand dollar

, Dendraster excentricus Embryo S, M N

- 46.2 131 13.31

- Arnold et al. 2010a

Sand dollar

, Dendraster excentricus Embryo S, M N

- >75.80 132 > 15.32 16.49 Arnold et al. 2010a

Long

- spined sea urchin

, Diadema antillarum Adult, ~1 yr F, M S

- 25 134 12.58 12.58 Bielmyer et al. 2005b

Coho salmon

, Oncorhynchus kisutch Smolt,

132 mm F, M C 601 546.3 481 445.6 445.6 Dinnel et al. 1989

Mangrove killifish

, Rivulus marmoratus 4

- 6 week F, M S

- 1,250 529 7,419

- Lin and Dunson 1993

Mangrove killifish

, Rivulus marmoratus 4

- 6 week F, M S

- 1,610 530 9,563 8,423 Lin and Dunson 1993

Leon Springs pupfish,

Cyprinodon bovinus 0.42 g S, U S 1306 1094.4 781 5,304 Sappington et al. 2001;

Dwyer et al. 2005;

Mayer et al. 2008

Leon Springs pupfish,

Cyprinodon bovinus 0.42 g S, U S >204 >171.0 782 > 114.1 778.0 Sappington et al. 2001;

Dwyer et al. 2005;

Mayer et al. 2008

Sheepshead minnow

, Cyprinodon variegatus Larva,

>24 hr F, M S/C 368 334.5 120 337.2

- Hughes et al. 1989

Sheepshead minnow

, Cyprinodon variegatus Juvenile,

0.24 g S, U S 630 527.9 779 1,946 h

- Sappington et al. 2001;

Dwyer et al. 2005;

Mayer et al. 2008

Sheepshead minnow

, Cyprinodon variegatus Juvenile,

0.24 g S, U S >204 >171.0 780 >114.1 h 337.2 Sappington et al. 2001;

Dwyer et al. 2005;

Mayer et al. 2008

Mummichog

, Fundulus heteroclitus 2.7 g S, U S 3,100 2,598 172 10,647 g

- Dorfman 1977

Mummichog

, Fundulus heteroclitus 2.7 g S, U S 2,000 1,676 173 3,452 g

- Dorfman 1977

### A

- 24

Species Organism

Age, Size or

Lifestage Method a Chemical b Reported

LC 50 /EC 50 ( t otal μg/L) c Reported

LC 50 /EC 50 ( d issolved μg/L) d BLM

Data

Label BLM

Normalized

LC 50 /EC 50 (μg/L) e Species

Mean Acute

Value

(μg/L) f Reference

Mummichog

, Fundulus heteroclitus 2.7 g S, U C 2,300 1,927 174 7,401 g

- Dorfman 1977

Mummichog

, Fundulus heteroclitus 2.7 g S, U C 400 335.2 175 386.2 g

- Dorfman 1977

Mummichog

, Fundulus heteroclitus 4

- 6 week F, M S

- 1,690 176 10,040 g

- Lin and Dunson 1993

Mummichog

, Fundulus heteroclitus 7 d R, M S ~360.00 ~327.20 178 578.9

- Grosell et al. 2007

Mummichog

, Fundulus heteroclitus 7 d R, M S ~640.00 ~581.80 179 1,837

- Grosell et al. 2007

Mummichog

, Fundulus heteroclitus 7 d R, M S >937.00 >851.70 180 > 2,345

- Grosell et al. 2007

Mummichog

, Fundulus heteroclitus 7 d R, M S ~500.00 ~454.50 181 476.9

- Grosell et al. 2007

Mummichog

, Fundulus heteroclitus 7 d R, M S ~340.00 ~309.10 182 190.8

- Grosell et al. 2007

Mummichog

, Fundulus heteroclitus 7 d R, M S 294 267.25 183 130.6 556.3 Grosell et al. 2007

Topsmelt

, Atherinops affinis Larva, 8 d S, M C 288 261.8 36 249.8

- Anderson et al. 1991

Topsmelt

, Atherinops affinis Larva, 8 d S, M C 212 192.7 37 145.5

- Anderson et al. 1991

Topsmelt

, Atherinops affinis Larva, 8 d S, M C 235 213.6 38 174.1 185.0 Anderson et al. 1991

Inland silverside

, Menidia beryllina - S, M S 115.41 104.9 262 55.31

- TOXSCAN, Inc. 1991a

Inland silverside

, Menidia beryllina - S, M S 63.05 57.31 263 29.97

- TOXSCAN, Inc. 1991b

Inland silverside

, Menidia beryllina - S, M S 123 111.8 264 58.77 46.01 TOXSCAN, Inc. 1991c

Atlantic silverside

, Menidia menidia Larva, 3 wk F, M N 66.6 60.54 266 42.95

- Cardin 1982; 1985

Atlantic silverside

, Menidia menidia Larva, 1 wk F, M N 216.5 196.8 267 176.4

- Cardin 1982; 1985

Atlantic silverside

, Menidia menidia Larva, 3 d F, M N 97.6 88.72 268 64.33

- Cardin 1982; 1985

### A

- 25

Species Organism

Age, Size or

Lifestage Method a Chemical b Reported

LC 50 /EC 50 ( t otal μg/L) c Reported

LC 50 /EC 50 ( d issolved μg/L) d BLM

Data

Label BLM

Normalized

LC 50 /EC 50 (μg/L) e Species

Mean Acute

Value

(μg/L) f Reference

Atlantic silverside

, Menidia menidia Larva, 2 wk F, M N 155.9 141.7 269 112.1 85.97 Cardin 1982; 1985

Tidewater silverside

, Menidia peninsulae Larva, 19 d S, U N 140 117.3 271 67.46

- Hansen 1983

Tidewater silverside

, Menidia peninsulae 19 d S, U

- 141 118.2 272 68.00 67.73 D'Asaro 1985

Striped mullet,

Mugil cephalus Fingerling,

1.5 cm, 0.13 g R, M C

- 2,740 744 4,898 4,898 Rajkumar 2012

Shiner perch

, Cymatogaster aggregata Adult, 97 mm F, M C 418 380.0 118 611.0 611.0 Dinnel et al. 1989

Mud

- skipper

, Boleophthalmus sp. 2.84 cm, 0.13

g R, U S 3,710 3,109 48 3,690 3,690 Kidwai and Ahmed

1999

Striped bass

, Morone saxatilis 45.6

- 60.6 mm F, M C 8,400 7,636 280 74,083 g

- Hetrick et al. 1982

Striped bass

, Morone saxatilis 70 d S, U S 69.4 58.16 281 229.9

- Palawski et al. 1985

Striped bass

, Morone saxatilis Fingerling,

1

- 2 mo. S, U S 2,680 2,246 282 656.4 g

- Reardon and Harrell

1990

Striped bass

, Morone saxatilis Fingerling,

1

- 2 mo. S, U S 8,080 6,771 283 2,207 g

- Reardon and Harrell

1990

Striped bass

, Morone saxatilis Fingerling,

1

- 2 mo. S, U S 7,880 6,603 284 16,706 g 229.9 Reardon and Harrell

1990

Spot

, Leiostomus xanthurus Adult,

0.5

- 0.6 g S, U N 280 234.6 236 189.3

- Hansen 1983

Spot

, Leiostomus xanthurus 0.5

- 0.6 g S, U

- 282 236.3 237 191.9 190.6 D'Asaro 1985

Atlantic croaker

, Micropogonias undulatus 16

- 19 cm S, U C 5,660 4,743 278 8,863 8,863 Steele 1983

Sheepshead

, Archosargus probatocephalus 18

- 21 cm S, U C 1,140 955.3 30 1,534 1,534 Steele 1983

### A

- 26

Species Organism

Age, Size or

Lifestage Method a Chemical b Reported

LC 50 /EC 50 ( t otal μg/L) c Reported

LC 50 /EC 50 ( d issolved μg/L) d BLM

Data

Label BLM

Normalized

LC 50 /EC 50 (μg/L) e Species

Mean Acute

Value

(μg/L) f Reference

Pinfish

, Lagodon rhomboides 13

- 17 cm S, U C 2,750 2,305 234 4,145 4,145 Steele 1983

Thornfish

, Terapon jarbua Juvenile,

10 cm, 25 g R, U

- 2,500 2,095 555 2,512 2,512 Vijayavel et al. 2006

Pompano

, Trachinotus carolinus Juvenile,

0.25 g, 25 mm S, U S 557.3 467.0 573 920.9

- Birdsong and Avault

1971

Pompano

, Trachinotus carolinus Juvenile,

0.25 g, 25 mm S, U S 597.2 500.5 574 770.0

- Birdsong and Avault

1971

Pompano

, Trachinotus carolinus Juvenile,

0.25 g, 25 mm S, U S 796.2 667.2 575 947.0 875.7 Birdsong and Avault

1971

Summer flounder

, Paralichthys dentatus Juvenile, 46 d,

18

- 22 mm S, M S 610 586.0 499 2,265 h

- CH2M Hill 1999a

Summer flounder

, Paralichthys dentatus Juvenile, 48 d,

20

- 24 mm S, M S 1,029 928.0 500 3,990 h

- CH2M Hill 1999a

Summer flounder

, Paralichthys dentatus Juvenile, 57 d,

24

- 28 mm S, M S 606 597.0 501 1,775 h

- CH2M Hill 1999a

Summer flounder

, Paralichthys dentatus Embryo

- Early cleavage F, M C 16.3 14.82 496 10.36

- Cardin 1982; 1985

Summer flounder

, Paralichthys dentatus Embryo

- Early cleavage F, M C 11.9 10.82 497 7.556

- Cardin 1982; 1985

Summer flounder

, Paralichthys dentatus Embryo

-

Blastula F, M C 111.8

- 498 75.97 g 8.848 Cardin 1982; 1985

Winter flounder

, Pseudopleuronectes americanus Blastula F, M N 167.3 152.1 513 129.8

- Cardin 1982; 1985

Winter flounder

, Pseudopleuronectes americanus Blastula F, M N 158 143.6 514 121.0

- Cardin 1982; 1985

Winter flounder

, Pseudopleuronectes americanus Blastula

- Embryo F, M C 173.7 157.9 515 135.7

- Cardin 1982; 1985

Winter flounder

, Pseudopleuronectes americanus Fertilization/

Pre

- cleavage F, M C 132.8 120.7 516 94.46

- Cardin 1982; 1985

Winter flounder

, Pseudopleuronectes americanus Blastula

- Embryo F, M N 148.2 134.7 517 109.3

- Cardin 1982; 1985

Winter flounder

, Pseudopleuronectes americanus Early cleavage

- Embryo F, M N 98.2 89.26 518 65.94 106.4 Cardin 1982; 1985

### A

- 27

Species Organism

Age, Size or

Lifestage Method a Chemical b Reported

LC 50 /EC 50 ( t otal μg/L) c Reported

LC 50 /EC 50 ( d issolved μg/L) d BLM

Data

Label BLM

Normalized

LC 50 /EC 50 (μg/L) e Species

Mean Acute

Value

(μg/L) f Reference

Gulf toadfish

, Opsanus beta 22

- 53 g F, M S >21,607 >19,641 485 > 33,000 >33,000 Grosell et al. 2004

Cabezon

, Scorpaenichthys marmoratus Post

- hatch

larva S, M C 95 86.36 532 64.20 64.20 Dinnel et al. 1989

Fat snook,

Centropomus parallelus J uvenile, 3.5

g, 6.8 cm S, M C 1,880 1,709 751 4,428 4,428 Oliveria et al. 2014

a S=static, R=renewal, F=flow

- through, U=unmeasured, M=measured.

b S=copper sulfate, N=copper nitrate, C=copper chloride.

c Values in this column are total copper LC 50 or EC 50 values as reported by author.

d Values in this column are dissolved copper LC 50 or EC 50 values either reported by the author

, or if the author did not report a dissolved value

, then a conversion factor (CF)

was applied to the total copper LC 50 to estimate dissolved copper values (If copper was unmeasured, the total copper was multipl i ed by 0.838, if it was measured, it was

multiplied by 0.909).

e Normalization Chemistry (only Temp, pH, DOC, and Salinity are needed for the model, but values for other ions are shown for reference).

Temperature

( °C) pH DOC

(mg/L) Salinity

(ppt) Ca

(mg/L) Mg

(mg/L) Na

(mg/L) K

(mg/L) SO 4

(mg/L) Cl

(mg/L) Alkalinity

(mg/L)

22 8 1.0 32 367.2 1144.0 9607.5 355.7 2417.0 17244.3 89.8

f Bolded BLM Normalized values were used in the SMAV calculation

.

g Value not used in the SMAV calculation, only the most sensitive life stage of the species.

h Value not used in the SMAV calculation because flow

- through measured tests available.

### B

- 1



## Appendix B Acceptable Chronic Toxicity Data

### B

- 2

Appendix Table B

- 1

. Acceptable Estuarine/Marine Chronic Toxicity Data

.

Species Test a Chemical b Endpoint Salinity

(g/kg) Chronic

Limits

(μg/L) Chronic

Value

( t otal μg/L) Chronic Value

( d issolved μg/L) BLM

Data

Label BLM

Normalized

Chronic Value

(Dissolved μg/L) c Reference

Rotifer,

Brachionus plicatilis LC N Intrinsic rate of

rotifer population 15 6.1

- 10.3

- 10.9

(EC 20 ) C1 13.23 Arnold et al. 2010b

Sheepshead minnow,

Cyprinodon variegatus ELS C Growth 30 172

- 362 249.5 226.8 C2 204.1 Hughes et al. 1989

a LC=life

- cycle; PLC=partial life

- cycle; ELS=early life stage.

b S=copper sulfate, N=copper nitrate, C=copper chloride.

c Normalization Chemistry (only Temp, pH, DOC, and Salinity are needed for the model, but values for other ions are shown for r eference).

Temperature

( °C) pH DOC

(mg/L) Salinity

(ppt) Ca

(mg/L) Mg

(mg/L) Na

(mg/L) K

(mg/L) SO 4

(mg/L) Cl

(mg/L) Alkalinity

(mg/L)

22 8 1.0 32 367.2 1144.0 9607.5 355.7 2417.0 17244.3 89.8



### Appendix Table B

- 2

. Acute

- Chronic Ratios

.

Species Hardness

(mg/L as

CaCO 3 ) Acute Value

(μg/L) Chronic Value

(μg/L) Acute to Chronic

Ratio Reference Species Mean

ACR Used in

FACR

calculation

FRESHWATER

Snail,

Campeloma decisum 35

- 55 1,673 a 8.73 191.6 Arthur and Leonard 1970

171.2 Snail,

Campeloma decisum 35

- 55 1,673 a 10.94 153.0 Arthur and Leonard 1970

Pond snail,

Lymnaea stagnalis 123 24.9 5.307 4.692 Ng et al. 2011 4.692

Oyster mussel,

Epioblasma capsaeformis 162 26 7.530 3.453 Wang et al. 2007b 3.453

Fatmucket,

Lampsilis siliquoidea 165 34 7.201 4.722 Wang et al. 2007b 4.722

### B

- 3

Species Hardness

(mg/L as

CaCO 3 ) Acute Value

(μg/L) Chronic Value

(μg/L) Acute to Chronic

Ratio Reference Species Mean

ACR Used in

FACR

calculation

Rainbow mussel,

Villosa iris 171 27 7.679 3.516 Wang et al. 2007b

2.733 Rainbow mussel,

Villosa iris 101

(DOC=0.5) 15 8.3 1.807 Wang et al. 2011a

Rainbow mussel,

Villosa iris 100

(DOC=10) 72 35 2.057 Wang et al. 2011a

Rainbow mussel,

Villosa iris 98

(DOC=2.5) 32 7.5 4.267 Wang et al. 2011a

Cladoceran,

Ceriodaphnia dubia 179 28.42 b 7.9 3.597 Belanger et al. 1989

3.268 x Cladoceran,

Ceriodaphnia dubia 94.1 63.33 b 19.36 3.271 Belanger et al. 1989

Cladoceran,

Ceriodaphnia dubia 57 13.4 24.5 0.5469 g Oris et al. 1991

Cladoceran,

Ceriodaphnia dubia - 17.974 c 9.17 1.960 Carlson et al. 1986

Cladoceran,

Ceriodaphnia dubia 54

- 72 4.16 29.34 0.1418 g Harmon et al. 2003

Cladoceran,

Ceriodaphnia dubia 82.4 18 3.641 4.944 Cooper et al. 2009

Cladoceran,

Daphnia ambigua 54

- 72 6.53 22.38 0.2918 g Harmon et al. 2003

-

Cladoceran,

Daphnia magna 51 26 12.58 2.067 Chapman et al.

(Manuscript)

3.419 x Cladoceran,

Daphnia magna 104 33.76 d 19.89 1.697 Chapman et al.

(Manuscript)

Cladoceran,

Daphnia magna 211 69 6.06 11.39 Chapman et al.

(Manuscript)

Cladoceran,

Daphnia pulex 57.5 25.737 2.83 9.094 Winner 1985

4.814 x Cladoceran,

Daphnia pulex 115 27.6 7.07 3.904 Winner 1985

Cladoceran,

Daphnia pulex 230 28.79 9.16 3.143 Winner 1985

Rainbow trout,

Oncorhynchus mykiss 120 80 27.77 2.881 Seim et al. 1984 2.357 x

### B

- 4

Species Hardness

(mg/L as

CaCO 3 ) Acute Value

(μg/L) Chronic Value

(μg/L) Acute to Chronic

Ratio Reference Species Mean

ACR Used in

FACR

calculation

Rainbow trout,

Oncorhynchus mykiss 104 83 35.08 2.366 Besser et al. 2007

Rainbow trout,

Oncorhynchus mykiss 100 61.48 h 32 1.921 Wang et al. 2014;

Ingersoll and Mebane

2014

Chinook salmon,

Oncorhynchus tshawytscha 20

- 45 33.1 5.92 5.591 Chapman 1975, 1982 5.591 x

White sturgeon,

Acipenser transmontanus 100 8.06 1.4 5.757 Wang et al. 2014;

Ingersoll and Mebane

2014 5.757 x

Mottled sculpin,

Cottus bairdii 102 45 28.47 1.581 Besser et al. 2007

2.075 x Mottled sculpin,

Cottus bairdii 104 12 4.408 2.722 Besser et al. 2007

Bluntnose minnow,

Pimephales notalus 172

- 230 231.9 e 18 12.88 Horning and Neiheisel

1979 12.88

Fathead minnow,

Pimephales promelas 200 449.6 i 12.86 34.96 Mount 1968

21.25 Fathead minnow,

Pimephales promelas 202 474.8 j 19.72 24.08 Pickering et al. 1977

Fathead minnow,

Pimephales promelas 45 106.9 f 9.38 11.40 Lind et al. 1978

Fathead minnow,

Pimephales promelas - 250 <61 >4.098 k Scudder et al. 1988

Bluegill,

Lepomis macrochirus 21

- 40 1,100 27.15 40.52 Benoit 1975 40.52

Species Salinity

(g/kg) Acute Value

(μg/L) Chronic Value

(μg/L) Acute to Chronic

Ratio Reference Species Mean

ACR Used in

FACR

calculation

ESTUARINE/MARINE WATER

Rotifer,

Brachionus plicatilis 15 13.4

(unfed) 10.9 1.229 Arnold et al. 2010b 1.229

(unfed) x

### B

- 5

Species Salinity

(g/kg) Acute Value

(μg/L) Chronic Value

(μg/L) Acute to Chronic

Ratio Reference Species Mean

ACR Used in

FACR

calculation

Rotifer,

Brachionus plicatilis 15 20.8

(fed) 10.9 1.908 Arnold et al. 2010b 1.908

(fed)

Sheepshead minnow,

Cyprinodon variegatus 30 368 249.5 1.475 Hughes et al. 1989 1.475 x

a Geometric mean of two values from Arthur and Leonard (1970).

b Geometric mean of five values from Belanger et al. (1989). ACR is based on dissolved metal measurements.

c Geometric mean of two values from Carlson et al. (1986).

d Geometric mean of two values from Chapman et al. (Manuscript).

e Geometric mean of three values from Horning and Neiheisel (1979).

f Geometric mean of three values from Lind et al. (1978).

g ACR from Oris et al. (1991) and Harmon et al. (2003) not used in calculating overall ratio for species it is <1.

h Geometric mean of two values from Wang et al. 2014; Ingersoll and Mebane 2014.

i Geometric mean of two values from Mount 1968.

j Geometric mean of two values from Pickering et al. 1977.

k ACR from Scudder et al. (1988) not used in calculating overall ratio for species since it is non

- definitive.



### Freshwater FACR (from Copper Freshwater AWQC 2007 Document)

= 3.22

Estuarine/Marine FA CR ( geometric mean of values with an x)

= 3.022

### C

- 1



## Appendix C Estuarine/Marine Plant Toxicity Data

### C

- 2

Appendix Table C

- 1

. Estuarine/Marine Plant Toxicity Data

.

Species Method a Chemical Salinity

(g/kg) Duration

(days) Effect Result

( t otal μg/L) Result

(dissolved μg/L) Reference

Dinoflagellate,

Amphidinium carteri S, U Copper

chloride 21 21 83% reduction in growth <50 Erickson et al. 1970

Dinoflagellate,

Cochlodinium polykrikoides S, U Copper

sulfate - 3 EC 50 12,740 Ebenezer and Ki 2012

Dinoflagellate,

Cochlodinium polykrikoides S, U Copper

sulfate - 3 EC 50 5,030 Ebenezer and Ki 2012

Dinoflagellate,

Gymnodinium splendens S, U Copper

sulfate 31.6

- 33.3 5 LOEC

(growth) 20 18.18 Saifullah 1978

Dinoflagellate,

Prorocentrum micans S, U Copper

sulfate 31.6

- 33.3 8 LOEC

(growth) 5 4.545 Saifullah 1978

Dinoflagellate,

Prorocentrum minimum S, U Copper

sulfate 30

- 35 3 EC 50

(biomass) 1,074 Guo and Ki 2012

Dinoflagellate,

Prorocentrum minimum S, U Copper

- 3 EC 50

(cell #) 1,070 Guo et al. 2012

Dinoflagellate,

Scrippsiella faeroense S, U Copper

sulfate 31.6

- 33.3 5 LOEC

(growth) 5 4.545 Saifullah 1978

Dinoflagellate,

Simbiodinium microadriaticum S, M Copper

sulfate Full strength

seawater 23 46% reduction in growth

(significant) 40 Goh and Chou 1997

Dinoflagellate,

Simbiodinium microadriaticum S, M Copper

sulfate Full strength

seawater 23 26% reduction in growth (not

significant) 42 Goh and Chou 1997

Golden/brown flagellate,

Isochrysis sp. S, U Copper

sulfate 36 4 IC 50 (growth) 2 1.8 Garr 2012

Brown alga,

Hizikia fusiformis S, U Copper

sulfate - 7 NOEC

- LOEC

(relative growth rate) 25

- 50 Zhu et al. 2011

Cyanobacterium,

Cyanobium sp. S, M Copper

sulfate 33 3 EC 50

(cell #) 500 Alquezar and Anastasi

2013

Alga,

Platymonas helgolandica var.

tsingtaoensis S, U Copper

sulfate - 1.5 hr EC 50

(% motile cells) 848.4 Zheng et al. 2012

Alga,

Platymonas subcordiformis S, U Copper

sulfate - 1.5 hr EC 50

(% motile cells) 320.9 Zheng et al. 2012

Green alga,

Chlorella stigmatophora S, M Copper

chloride 35 21 EC 50

(cell volume) 70 Christensen et al. 1979

Green alga (zoospores),

Enteromorpha intestinalis S, U

- - 5 EC 50 (development to 2+ cell stage) 10 Fletcher 1989

Green alga,

Olisthodiscus luteus S, U Copper

chloride 21 14 74% reduction in growth <50 Erickson et al. 1970

Alga,

Ulva pertusa S, U

- 26

- 35 4 EC 50 (chlorophyll fluorescence) 711 Kumar et al. 2009

### C

- 3

Species Method a Chemical Salinity

(g/kg) Duration

(days) Effect Result

( t otal μg/L) Result

(dissolved μg/L) Reference

Alga,

Ulva lactuca R, M Copper

chloride 32 3 EC 50 (growth) 127 Wendt et al. 2013

Diatom,

Odontella mobiliensis S, M Copper

chloride 30 3 EC 50 (growth) 298.4 Manimaran et al. 2012

Diatom,

Nitzschia closterium - - - 4 EC 50 (growth) 33 Rosko and Rachlin 1975

Diatom,

Nitzschia thermalis S, U Copper

sulfate 35.7 Several No growth 38.1 Metaxas and Lewis 1991

Diatom,

Skeletonema costatum S, U Copper

chloride 21 14 58% reduction in growth 50 Erickson et al. 1970

Diatom,

Skeletonema costatum S, U Copper

sulfate 35.7 Several LOEC

(no growth) 31.8 Metaxas and Lewis 1991

Diatom,

Skeletonema costatum S, U Copper

chloride - 4 EC 50 (growth) 45 Nassiri et al. 1997

Diatom,

Thalassiosira aestevallis S, U Copper

chloride - 3.0

- 4 Reduced growth 19 Hollibaugh et al. 1980

Red alga,

Ceramium tenuicorne S, U Copper

chloride 7 7 EC 50 (growth) 6.4 Ytreberg et al. 2010

Red alga (tetrasporophyte),

Champia parvula R, M Copper

chloride 30 11 Reduced growth 4.6 4.181 Steele and Thursby 1983

Red alga (tetrasporophyte),

Champia parvula R, M Copper

chloride 30 11 Reduced production 13.3 12.09 Steele and Thursby 1983

Red alga (mature),

Champia parvula R, M Copper

chloride 30 14 Reduced female growth 4.7 4.272 Steele and Thursby 1983

Red alga (mature),

Champia parvula R, M Copper

chloride 30 14 Stopped sexual reproduction 7.3 6.636 Steele and Thursby 1983

Red seaweed,

Gracilaria lemaneiformis S, U Copper

sulfate 25 6 LOEC

(growth rate) 50 Huang et al. 2013

Red seaweed,

Gracilariopsis longissima S, U Copper

sulfate 33 7 EC 50 (growth )

P lants collected from clean and

polluted sites

- April 31.1 28.27 Brown et al. 2012

Red seaweed,

Gracilariopsis longissima S, U Copper

sulfate 33 7 EC 50 (growth )

P lants collected fro m clean and

polluted sites

- Oct. 25.8 23.45 Brown et al. 2012

Red seaweed,

Gracilariopsis longissima S, U Copper

sulfate 33 7 EC 20 (growth )

P lants collected from clean and

polluted sites

- April 12.6 11.45 Brown et al. 2012

### C

- 4

Species Method a Chemical Salinity

(g/kg) Duration

(days) Effect Result

( t otal μg/L) Result

(dissolved μg/L) Reference

Red seaweed,

Gracilariopsis longissima S, U Copper

sulfate 33 7 EC 20 (growth )

P lants collected fro m clean and

polluted sites

- Oct. 11.3 10.27 Brown et al. 2012

Kelp (meiospore),

Laminaria saccharina R, U Copper

sulfate - 21 Reduced gametophyte

development rate 5 Chung and Brinkhuis

1986

Kelp (1

- 3 cm sporophyte),

Laminaria saccharina S, U Copper

sulfate - 9 LOEC

(100% mortality) 100 Chung and Brinkhuis

1986

Kelp (8

- 10 cm sporophyte),

Laminaria saccharina S, U Copper

sulfate - - 23% decrease in blade growth 10 Chung and Brinkhuis

1986

Giant kelp,

Macrocystis pyrifera S, U

- - 4 EC 50 (photosynthesis) 60 Clendenning and North

1959

Giant kelp,

Macrocystis pyrifera R, M Copper

chloride 36 19

- 20 NOEC

(sporophyte production) <10.2 < 9.2718 Anderson et al. 1990

Giant kelp,

Macrocystis pyrifera R, M Copper

chloride 36 19

- 20 LOEC

(sporophyte production) 10.2 9.2718 Anderson et al. 1990

a S=static, R=renewal, F=flow

- through, U=unmeasured, M=measured.

### D

- 1



## Appendix D Acceptable Estuarine/Marine Bioaccumulation Data

### D

- 2

Appendix Table D

- 1 . Acceptable Estuarine/Marine Bioaccumulation Data.

Species Chemical Concentration

in water

(μg /L) Salinity

(g/kg) Duration

(days) Tissue BCF

or

BAF Reference

Polychaete,

Phyllodoce maculata Copper

sulfate 40 Full strength

seawater 35 Whole body 2,500 McLusky and

Phillips 1975

Polychaete,

Neanthes arenaceodentata Copper

nitrate 40 31 28 Whole body 2,950 Pesch and Morgan

1978

Polychaete,

Eudistylia vancouveri Copper

chloride 6 30.4 29 Body (less radioles) 1,006 Young et al. 1979

Blue mussel (0.45 cm),

Mytilus edulis Copper

chloride 3 25 550 Soft tissue 7,730 Calabrese et al.

1984

Blue mussel (0.45 cm),

Mytilus edulis Copper

chloride 7.9 25 550 Soft tissue 4,420 Calabrese et al.

1984

Blue mussel (0.45 cm),

Mytilus edulis Copper

chloride 12.7 25 550 Soft tissue 5,320 Calabrese et al.

1984

Mediterranean mussel

(6.02

- 6.34 cm),

Mytilus galloprovincialis Field study 0.285 37

- 38 266 Soft tissue 3,263 Martincic et al.

1992

Mediterranean mussel

(6.02

- 6.34 cm),

Mytilus galloprovincialis Field study 0.446 37

- 38 266 Soft tissue 2,491 Martincic et al.

1992

Mediterranean mussel

(6.02

- 6.34 cm),

Mytilus galloprovincialis Field study 0.203 37

- 38 266 Soft tissue 4,384 Martincic et al.

1992

Mediterranean mussel

(6.02

- 6.34 cm),

Mytilus galloprovincialis Field study 0.177 37

- 38 266 Soft tissue 4,915 Martincic et al.

1992

Bay scallop (5.12

- 6.26 cm),

Argopecten irradians Copper

chloride 4.56 29

- 32 56 Muscle 185 Zaroogian and

Johnson 1983

Bay scallop (5.12

- 6.26 cm),

Argopecten irradians Copper

chloride 4.56 29

- 32 56 Viscera 3,816 Zaroogian and

Johnson 1983

Pacific oyster,

Crassostrea gigas Field study 25.45

- 32 Soft tissue 34,600 Han and Hung

1990

Pacific oyster,

Crassostrea gigas Field study 9.66

- 32 Soft tissue 57,000 Han and Hung

1990

Pacific oyster,

Crassostrea gigas Field study 10.37

- 32 Soft tissue 33,400 Han and Hung

1990

### D

- 3

Species Chemical Concentration

in water

(μg /L) Salinity

(g/kg) Duration

(days) Tissue BCF

or

BAF Reference

Eastern oyster,

Crassostrea virginica Field study 25 31 140 Soft tissue 27,800 Shuster and Pringle

1968

Soft

- shell clam,

Mya arenaria Field study 100 31 35 Soft tissue 790 Shuster and Pringle

1968

### E

- 1



## Appendix E Other Estuarine/Marine Toxicity Data

### E

- 2

Appendix Table E

- 1

. Other Estuarine/Marine Toxicity Data

.

Species Chemical Duration

(days) Effect Effect

Concentration

( t otal μg/L) Effect

Concentration

( d issolved μg/L) Reference

Ciliate,

Euplotes crassus - 8 hr NOEC

(survival) 31,775

- Gomiero et al. 2012 b

Bacterium,

Vibrio fischeri Copper

sulfate 15 min EC 50

(luminescence) 397

- Rosen et al. 2008

Bacterium,

Vibrio fischeri Copper

chloride 15 min EC 50

(luminescence) 800

- Ytreberg et al. 2010

Dinoflagellate,

Ceratocorys horrida Copper

sulfate 1 EC 50

(luminescence) 166

- Rosen et al. 2008

Dinoflagellate,

Lingulodinium polyedrum Copper

sulfate 1 EC 50

(luminescence) 90

- Rosen et al. 2008

Dinoflagellate,

Pyrocystis noctiluca Copper

sulfate 1 EC 50

(luminescence) 185

- Rosen et al. 2008

Fungus,

Halophytophthora elongata Copper

chloride 5 NOEC

- LOEC

(biomass) 10,000

- 100,000

- Leano and Pang 2010

Fungus,

Halophytophthora spinosa Copper

chloride 5 NOEC

- LOEC

(biomass) 1,000

- 10,000

- Leano and Pang 2010

Fungus,

Halophytophthora vesicula Copper

chloride 5 NOEC

- LOEC

(biomass) 1,000

- 10,000

- Leano and Pang 2010

Green alga,

Chlorella autotrophyca Copper

sulfate 3 EC 50

(biomass)

(initial cell density=10 3 cells/ml) 9.6

- Moreno

- Garrido et al.

2000

Green alga,

Chlorella autotrophyca Copper

sulfate 3 EC 50

(biomass)

(initial cell density =5x10 3 cells/ml) 19.3

- Moreno

- Garrido et al.

2000

Green alga,

Chlorella autotrophyca Copper

sulfate 3 EC 50

(biomass)

(initial cell density=10 4 cells/ml) 38.3

- Moreno

- Garrido et al.

2000

Green alga,

Isochrysis galbana Copper

sulfate 3 EC 50

(biomass)

(initial cell density=10 3 cells/ml) 0.4

- Moreno

- Garrido et al.

2000

Green alga,

Isochrysis galbana Copper

sulfate 3 EC 50

(biomass)

(initial cell density=5x10 3 cells/ml) 3.6

- Moreno

- Garrido et al.

2000

Green alga,

Isochrysis galbana Copper

sulfate 3 EC 50

(biomass)

(initial cell density=10 4 cells/ml) 4.4

- Moreno

- Garrido et al.

2000

Green alga,

Nannochloris atomus Copper

sulfate 3 EC 50

(biomass)

(initial cell density=10 3 cells/ml) 16.7

- Moreno

- Garrido et al.

2000

### E

- 3

Species Chemical Duration

(days) Effect Effect

Concentration

( t otal μg/L) Effect

Concentration

( d issolved μg/L) Reference

Green alga,

Nannochloris atomus Copper

sulfate 3 EC 50

(biomass)

(initial cell density=5x10 3 cells/ml) 27.3

- Moreno

- Garrido et al.

2000

Green alga,

Nannochloris atomus Copper

sulfate 3 EC 50

(biomass)

(initial cell density=10 4 cells/ml) 46.2

- Moreno

- Garrido et al.

2000

Diatom,

Ceratoneis closterium Copper

sulfate 3 IC 50 (growth rate) 7.1

- Hook et al. 2014

Diatom,

Cylindrotheca closterium Copper

sulfate 72 hr EC 50 (growth) 29

- Araujo et al. 2008

Diatom,

Cylindrotheca closterium Copper

sulfate 72 hr EC 50 (growth) 22

- Araujo et al. 2008

Diatom,

Cylindrotheca closterium Copper

sulfate 72 hr EC 50 (growth) 23

- Araujo et al. 2008

Diatom,

Cylindrotheca closterium Copper

sulfate 72 hr EC 50 (growth) 23

- Araujo et al. 2008

Diatom,

Phaeodactylum tricornutum Copper

sulfate 3 EC 50

(biomass)

(initial cell density=10 3 cells/ml) 9.8

- Moreno

- Garrido et al.

2000

Diatom,

Phaeodactylum tricornutum Copper

sulfate 3 EC 50

(biomass)

(initial cell density=5x10 3 cells/ml) 34.4

- Moreno

- Garrido et al.

2000

Diatom,

Phaeodactylum tricornutum Copper

sulfate 3 EC 50

(biomass)

(initial cell density=10 4 cells/ml) 35.0

- Moreno

- Garrido et al.

2000

Diatom,

Phaeodactylum tricornutum Copper

sulfate 3 IC 50 (growth) 8.5

- Osborn and Hook

2013

Coral (explants),

Montastraea franksi Copper

sulfate 8 hr NOEC

(paling/tissue loss) 100

- Venn et al. 2009

Coral (explants),

Montastraea franksi Copper

sulfate 8 hr NOEC

- LOEC

(increase hsp70, hsp90 & P

- gp

expression) 10.0

- 30

- Venn et al. 2009

Bryzoan,

Bugula neritina - 2 100% mortality 500

- Piola and Johnston

2006

Bryzoan,

Watersipora subtorquata - 2 100% mortality 500

- Piola and Johnston

2006

Bryzoan,

Schizoporella errata - 2 100% mortality 500

- Piola and Johnston

2006

Bryzoan,

Tricellaria occidentalis - 2 100% mortality 500

- Piola and Johnston

2006

### E

- 4

Species Chemical Duration

(days) Effect Effect

Concentration

( t otal μg/L) Effect

Concentration

( d issolved μg/L) Reference

Hydroid,

Campanularia flexuosa - 11 Growth rate inhibition 10.0

- 13

- Stebbing 1976

Hydroid,

Campanularia flexuosa - - Enzyme inhibition 1.43

- Moore and Stebbing

1976

Hydromedusa,

Phlalldium sp. - 1 LC 50 36

- Reeve et al. 1976

Ctenophore,

Pleurobrachia pileus - 1 LC 50 33

- Reeve et al. 1976

Ctenophore,

Mnemiopsis mccrdayi - 1 LC 50 17

- 29

- Reeve et al. 1976

Rotifer,

Brachionus plicatillis - 1 LC 50 100

- Reeve et al. 1976

Polychaete,

Phyllodoce maculata - 9 LC 50 80

- McLusky and Phillips

1975

Polychaete (adult),

Neanthes arenaceodentata Copper

nitrate 28 LC 50 44 40 Pesch and Morgan

1978

Polychaete,

Neanthes arenaceodentata Copper

nitrate 7 LC 50 137

- Pesch and Hoffman

1982

Polychaete,

Neanthes arenaceodentata Copper

nitrate 10 LC 50 98

- Pesch and Hoffman

1982

Polychaete,

Neanthes arenaceodentata Copper

nitrate 28 LC 50 56

- Pesch and Hoffman

1982

Polychaete (larva, 0.10 mg),

Neanthes arenaceodentata Copper

chloride 4 LC 50 311

- Pesch et al. 1986

Polychaete (larva, 0.10 mg),

Neanthes arenaceodentata Copper

chloride 4 LC 50 252

- Pesch et al. 1986

Polychaete (larva, 0.10 mg),

Neanthes arenaceodentata Copper

chloride 4 LC 50 224

- Pesch et al. 1986

Polychaete (larva, 0.10 mg),

Neanthes arenaceodentata Copper

chloride 28 LC 50 83

- Pesch et al. 1986

Polychaete (larva, 0.10 mg),

Neanthes arenaceodentata Copper

chloride 28 LC 50 81

- Pesch et al. 1986

Polychaete (larva, 0.10 mg),

Neanthes arenaceodentata Copper

chloride 28 LC 50 86

- Pesch et al. 1986

Polychaete,

Nereis virens Copper

sulfate 8 LC 50 20.97

- Caldwell et al. 2011

Polychaete,

Cirriformia spirabranchia Copper

nitrate 26 LC 50 40

- Milanovich et al. 1976

Polychaete (adult),

Hydroides elegans Copper

sulfate 2 LC 50 715 649.9 Xie et al. 2005

### E

- 5

Species Chemical Duration

(days) Effect Effect

Concentration

( t otal μg/L) Effect

Concentration

( d issolved μg/L) Reference

Polychaete (larva),

Hydroides elegans Copper

sulfate 2 LC 50 120 100.6 Bao et al. 2008

Flatworm,

Parorchis acanthus Copper

sulfate 2 NOEC

- LOEC

( successful encystment) 10

- 100 Morley et al. 2003

Nematode (adult, 3

- 4 d),

Caenorhabditis elegans Copper

chloride 4 LC 50 256 214.5 Williams and

Dusenbery 1990

Annelids (mixed species, larva)

- 1 LC 50 89

- Reeve et al. 1976

Black abalone,

Hailotis cracherodil - 4 Histopathological gill abnormalities >32

- Martin et al. 1977

Barnacle (nauplii),

Amphibalanus variegatus - 1 EC 50 (swimming) 81.29

- Gall et al. 2013

Red abalone,

Hailotis rufescens - 4 Histopathological gill abnormalities >32

- Martin et al. 1977

Channeled whelk,

Busycon canaliculatum - 77 LC 50 470

- Betzer and Yevich

1975

Mud snail,

Nassarius obsoletus - 3 Decrease in oxygen consumption 100

- MacInnes and

Thurberg 1973

Blue mussel,

Mytilus edulis Copper

chloride 7 LOEC

(mortality) 200 167.6 Scott and Major 1972

Blue mussel (10

- 15 mm),

Mytilus edulis - 3 LOEC

(growth) 10 8.38 Manley et al. 1984

Blue mussel (51

- 58 mm),

Mytilus edulis Copper

sulfate 5 LOEC

(mortality) 100 83.8 Al

- Subiai et al. 2011

Mediterranean mussel (adult, 5 cm),

Mytilus galloprovincialis Copper

chloride 5 LOEC

(lysosomal membrane stability) 2.3 1.927 Bolognesi et al. 1999

Mediterranean mussel (50

- 80 mm),

Mytilus galloprovincialis - 28 LC 50 (no sediment present) 100 Bat et al. 2013

Mediterranean mussel (50

- 80 mm),

Mytilus galloprovincialis - 28 LC 50 (sediment present) 250 Bat et al. 2013

Mediterranean mussel (5

- 6 cm),

Mytilus galloprovincialis - 4

(16°C) NOEC

- LOEC

(decrease lysosomal membrane

stability in digestive gland) 20

- 40 Negri et al. 2013

Mediterranean mussel (5

- 6 cm),

Mytilus galloprovincialis - 4

(20°C) NOEC

- LOEC

(decrease lysosomal membrane

stability in digestive gland) 20

- 40 Negri et al. 2013

Pacific blue mussel (sperm),

Mytilus trossulus Copper

chloride 100 min. Reduced sperm swimming speed 100 90.9 Fitzpatrick et al. 2008

Pacific blue mussel (sperm),

Mytilus trossulus Copper

chloride 100 min. Reduced fertilization success 100 90.9 Fitzpatrick et al. 2008

Pacific blue mussel (embryo),

Mytilus trossulus Copper

chloride 2 Increased abnormal larval development 10 9.09 Fitzpatrick et al. 2008

### E

- 6

Species Chemical Duration

(days) Effect Effect

Concentration

( t otal μg/L) Effect

Concentration

( d issolved μg/L) Reference

Bay scallop,

Argopecten irradians - 42 EC 50 (growth) 5.8 Pesch et al. 1979

Bay scallop,

Argopecten irradians - 119 100% mortality 5 Zaroogian and Johnson

1983

Pacific oyster (embryo),

Crassostrea gigas Copper

chloride 2 EC 50 (development) 10 9.09 Harrison et al. 1981

Pacific oyster (embryo),

Crassostrea gigas Copper

chloride 2 EC 50 (development)

(2 mg/L humic matter added) 28 25.45 Harrison et al. 1981

Pacific oyster (embryo),

Crassostrea gigas Copper

chloride 2 NOEC

(development) 2 1.676 Coglianese 1982

Pacific oyster (embryo, ≤4 hr),

Crassostrea gigas Copper

sulfate 3 EC 50 (arrested development) 4.46 3.737 Worboys et al. 2002

Pacific oyster (embryo),

Crassostrea gigas Copper

chloride 1 EC 50

(normal D

- stage larval development) 20.77 18.88 Brooks et al. 2007

Pacific oyster (embryo),

Crassostrea gigas Copper

chloride 1 EC 50

(normal D

- stage larval development) 24.33 22.12 Brooks et al. 2007

Pacific oyster (embryo),

Crassostrea gigas Copper

chloride 1 EC 50

(normal D

- stage larval development) 41.09 37.35 Brooks et al. 2007

Pacific oyster (embryo),

Crassostrea gigas Copper

chloride 1 EC 50

(normal D

- stage larval development) 37.87 34.42 Brooks et al. 2007

Pacific oyster (embryo),

Crassostrea gigas Copper

chloride 1 EC 50

(normal D

- stage larval development) 38.17 34.70 Brooks et al. 2007

Pacific oyster (embryo),

Crassostrea gigas Copper

chloride 1 EC 50

(normal D

- stage larval development) 40.52 36.83 Brooks et al. 2007

Eastern oyster (larva),

Crassostrea virginica - 12 LC 50 46

- Calabrese et al. 1977

Common rangia,

Rangla cuneata - 4 LC 50 (<1 g/kg salinity) 210

- Olson and Harrel 1973

Quahog clam (larva),

Mercenaria mercenaria - 8.0

- 10 LC 50 30

- Calabrese et al. 1977

Quahog clam (larva),

Mercenaria mercenaria - 77 LC 50 25

- Shuster and Pringle

1968

Common Pacific littleneck,

Protothaca staminea - 17 LC 50 39

- Roesijadi 1980

Soft

- shell clam,

Mya arenaria - 7 LC 50 35

- Eisler 1977

Copepod,

Undinula vulgaris - 1 LC 50 192

- Reeve et al. 1976

Copepod,

Euchaeta marina - 1 LC 50 188

- Reeve et al. 1976

### E

- 7

Species Chemical Duration

(days) Effect Effect

Concentration

( t otal μg/L) Effect

Concentration

( d issolved μg/L) Reference

Copepod,

Metridia pacifica - 1 LC 50 176

- Reeve et al. 1976

Copepod,

Labidocera scotti - 1 LC 50 132

- Reeve et al. 1976

Copepod,

Acartia clausi - 2 LC 50 34

- 82

- Moraitou

- Apostolopoulou 1978

Copepod,

Acartia tonsa - 6 LC 50 9.0

- 7.3

- Sosnowski et al. 1979

Copepod,

Acartia tonsa - 1 LC 50 104

- 311

- Reeve et al. 1976

Copepod (adult),

Acartia tonsa Copper

chloride 2 LC 50 ~40 36.36 Pinho and Bianchini

2010

Copepod (adult),

Acartia tonsa Copper

chloride 2 LC 50 ~90 81.81 Pinho and Bianchini

2010

Copepod (adult),

Acartia tonsa Copper

chloride 2 LC 50 ~110 99.99 Pinho and Bianchini

2010

Copepod (adult),

Nitokra spinipes Copper

sulfate 3 LC 50 323 293.6 Ward et al. 2011

Copepod (nauplii, 24 hr),

Eurytemora affinis Copper

chloride 2 LC 50

- 83.0 Hall et al. 1997

Copepod (nauplii, 24 hr),

Eurytemora affinis Copper

chloride 8 LC 50

- 64.0 Hall et al. 1997

Copepod (nauplii, <24 hr),

Tisbe battagliai Copper

sulfate 2 LC 50 83.1

- Diz et al. 2009

Copepod (adult gravid female),

Tisbe battagliai Copper

sulfate 3 LC 50 157

- Diz et al. 2009

Copepod (adult gravid female),

Tisbe battagliai Copper

sulfate 3 EC 50 (fecundity) 30.8

- Diz et al. 2009

Copepod,

Tisbe holothuriae - 2 LC 50 80

- Moraitou

- Apostolopoulou and

Verriopoulos 1982

Copepod (mixed species, nauplii)

- 1 LC 50 90

- Reeve et al. 1976

Amphipod,

Ampelisca abdita - 7 LC 50 90

- Scott et al.

(Manuscript)

Euphauslid,

Euphausia pacifica - 1 LC 50 14

- 30

- Reeve et al. 1976

Grass shrimp,

Palaemonetes pacifica - 4 LC 50 12,600

- Curtis et al. 1979;

Curtis and Ward 1981

Coon stripe shrimp

(larva/zoea, stage 1),

Pandalus danae Copper

sulfate 46 Development 13.42 12.20 Young et al. 1979

### E

- 8

Species Chemical Duration

(days) Effect Effect

Concentration

( t otal μg/L) Effect

Concentration

( d issolved μg/L) Reference

Sand shrimp (adult, 61 mm),

Crangon sp. Copper

chloride 4 LC 50 898

- Dinnel et al. 1989

Shrimp (adult),

Crangon crangon Copper

sulfate 2 LC 50 29,500 24,721 Connor 1972

Whiteleg shrimp

(juvenile, 5

- 6.5 cm),

Litopenaeus vannamei Copper

chloride 28 Gill alterations 186.5 156.3 Frias

- Espericueta et al.

2008a

Whiteleg shrimp (juvenile, 1.5

- 2 g),

Litopenaeus vannamei Copper

sulfate 4 LC 50 35,120 29,431 Frias

- Espericueta et al.

2008b

Whiteleg shrimp

(juvenile, 11.74 cm, 9.40 g),

Litopenaeus vannamei Copper

chloride 4 NOEC

- LOEC

(increase hemolymph clotting time) 370

- 3,730

- Bautista

- Covarrubias

et al. 2015

Pacific asteroid (sperm/egg),

Asterias amurensis Copper

chloride 80 min. EC 50

(fertilization) 200 167.6 Lee et al. 2004

Sand dollar (gamete),

Dendraster excentricus Copper

sulfate 40 min. NOEC

(fertilization) 10 8.380 Bailey et al. 1995

Sand dollar (gamete),

Dendraster excentricus Copper

sulfate 40 min. NOEC

(fertilization) 13.1 10.98 Bailey et al. 1995

Sand dollar (sperm),

Dendraster excentricus Copper

chloride 80 min. EC 50

(fertilization) 26 23.63 Dinnel et al. 1989

Blue crab (juvenile, 8.3 cm, 43.4 g),

Callinectes sapidus Copper

chloride 4 LC 50

- 33.75 Martins et al. 2011b

Blue crab (juvenile, 8.3 cm, 43.4 g),

Callinectes sapidus Copper

chloride 4 LC 50

- 3,367 Martins et al. 2011b

Shore crab (adult),

Carcinus maenas Copper

sulfate 2 LC 50 109,000 91,342 Connor 1972

Long

- spined sea urchin (embryo),

Diadema antillarum Copper

sulfate ~ 40 hr EC 50 (abnormal development) - 11 Bielmyer et al. 2005b

Sea urchin (sperm),

Arbacia punctulata - - 58% decrease in sperm motility 300

- Young and Nelson

1974

Sea urchin (sperm/egg),

Arbacia punctulata - 80 min. IC 50

(fertilization) 27.7 23.21 Neiheisel and Young

1992

Sea urchin (sperm/egg),

Arbacia punctulata - 80 min. IC 50

(fertilization) 34.6 28.99 Neiheisel and Young

1992

Sea urchin (sperm/egg),

Arbacia punctulata - 80 min. IC 50

(fertilization) 47.7 39.97 Neiheisel and Young

1992

Sea urchin (embryo, 1 hpf),

Arbacia punctulata Copper

sulfate 2 IC 50

(fertilization) 28.0 21.4 Science Applications

International

Corporation 1993

Green sea urchin (sperm),

Strongylocentrotus droebachiensis Copper

chloride 80 min. EC 50

(fertilization) 59 53.63 Dinnel et al. 1989

### E

- 9

Species Chemical Duration

(days) Effect Effect

Concentration

( t otal μg/L) Effect

Concentration

( d issolved μg/L) Reference

Red sea urchin (sperm),

Strongylocentrotus franciscanus Copper

chloride 80 min. EC 50

(fertilization) 1.9 1.727 Dinnel et al. 1989

Sea urchin (embryo),

Paracentrotus lividus - 2 LC 50 >500 >419.0 Radenac et al. 2001

Sea urchin (embryo),

Paracentrotus lividus - 2 LOEC

(development) 50 41.9 Radenac et al. 2001

Purple sea urchin (sperm),

Strongylocentrotus purpuratus Copper

chloride 80 min. EC 50

(fertilization) 25 22.73 Dinnel et al. 1989

Purple sea urchin (gamete),

Strongylocentrotus purpuratus Copper

sulfate 40 min. NOEC

(fertilization) 20 16.76 Bailey et al. 1995

Purple sea urchin (gamete),

Strongylocentrotus purpuratus Copper

sulfate 40 min. NOEC

(fertilization) 19.7 16.51 Bailey et al. 1995

White sea urchin (egg/sperm),

Lytechinus pictus Copper

sulfate 20 min. IC 50

(fertilization) 180 150.8 Jonczyk et al. 2001

White sea urchin (egg/sperm),

Lytechinus pictus Copper

sulfate 20 min. IC 50

(fertilization) 90.9 76.17 Jonczyk et al. 2001

White sea urchin (egg/sperm),

Lytechinus pictus Copper

sulfate 20 min. IC 50

(fertilization) 277 232.1 Jonczyk et al. 2001

White sea urchin (egg/sperm),

Lytechinus pictus Copper

sulfate 20 min. IC 50

(fertilization) 120 100.6 Jonczyk et al. 2001

White sea urchin (egg/sperm),

Lytechinus pictus Copper

sulfate 20 min. IC 50

(fertilization) 122 102.2 Jonczyk et al. 2001

White sea urchin (egg/sperm),

Lytechinus pictus Copper

sulfate 20 min. IC 50

(fertilization) 152 127.4 Jonczyk et al. 2001

White sea urchin (egg/sperm),

Lytechinus pictus Copper

sulfate 20 min. IC 50

(fertilization) 135 113.1 Jonczyk et al. 2001

White sea urchin (egg/sperm),

Lytechinus pictus Copper

sulfate 20 min. IC 50

(fertilization) 249 208.7 Jonczyk et al. 2001

White sea urchin (egg/sperm),

Lytechinus pictus Copper

sulfate 20 min. IC 50

(fertilization) 33.4 27.99 Jonczyk et al. 2001

White sea urchin (egg/sperm),

Lytechinus pictus Copper

sulfate 20 min. IC 50

(fertilization) 51.8 43.41 Jonczyk et al. 2001

White sea urchin (egg/sperm),

Lytechinus pictus Copper

sulfate 20 min. IC 50

(fertilization) 243 203.6 Jonczyk et al. 2001

White sea urchin (egg/sperm),

Lytechinus pictus Copper

sulfate 20 min. IC 50

(fertilization) 20.8 17.43 Jonczyk et al. 2001

White sea urchin (egg/sperm),

Lytechinus pictus Copper

sulfate 20 min. IC 50

(fertilization) 20.9 17.51 Jonczyk et al. 2001

White sea urchin (egg/sperm),

Lytechinus pictus Copper

sulfate 20 min. IC 50

(fertilization) 55.7 46.68 Jonczyk et al. 2001

### E

- 10

Species Chemical Duration

(days) Effect Effect

Concentration

( t otal μg/L) Effect

Concentration

( d issolved μg/L) Reference

White sea urchin (egg/sperm),

Lytechinus pictus Copper

sulfate 20 min. IC 50

(fertilization) 126 105.6 Jonczyk et al. 2001

White sea urchin (egg/sperm),

Lytechinus pictus Copper

sulfate 20 min. IC 50

(fertilization) >200 >167.6 Jonczyk et al. 2001

Arrow worm,

Sagitta hispida - 1 LC 50 43

- 460

- Reeve et al. 1976

Cuttlefish (egg),

Sepia officinalis Copper

chloride 50 NOEC

- LOEC

(hatchling weight) 2.3

- 23

- Lacoue

- Labarthe et al.

2010

Atlantic menhaden,

Brevoortia tyrannus - 14 LC 50 610

- Engel et al. 1976

Topsmelt (larva, 9d),

Atherinops affinis Copper

chloride 7 LC 50 (test species fed) 162 147.3 Anderson et al. 1994

Topsmelt (larva, 9d),

Atherinops affinis Copper

chloride 7 LC 50 (test species fed) 55.7 50.63 Anderson et al. 1994

Topsmelt (larva),

Atherinops affinis Copper

chloride 7 LC 50 365 331.8 McNulty et al. 1994

Topsmelt (larva, 9d),

Atherinops affinis Copper

chloride 7 LC 50 134 121.8 McNulty et al. 1994

Pacific herring (embryo),

Clupea harengus pallasi - 6 Incipi e nt LC 50 33

- Rice and Harrison

1978

Pacific herring (larva),

Clupea harengus pallasi - 2 Incipi e nt LC 50 900

- Rice and Harrison

1978

Atlantic cod (embryo),

Gadus morhua - 14 LC 50 10

- Swedmark and

Granmo 1981

Mummichog,

Fundulus heteroclitus - 21 Histopathological lesions <500

- Gardner and La Roche

1973

Mummichog,

Fundulus heteroclitus - 4 Enzyme inhibition 600

- Jackim 1973

Atlantic silverside,

Menidia menidia - 4 Histopathological lesions <500

- Gardner and La Roche

1973

Sheepshead minnow (larva, ≤24 hr),

Cyprinodon variegatus Copper

nitrate 4 LC 50 (test species fed) >220 >200.0 Hutchinson et al. 1994

Sheepshead minnow (larva, ≤24 hr),

Cyprinodon variegatus Copper

nitrate 7 Survival 160 145.4 Hutchinson et al. 1994

Northern anchovy (embryo),

Engraulis mordax Copper

chloride 32 hr LC 50 185 168.2 Rice et al. 1980

Northern anchovy (larva),

Engraulis mordax Copper

chloride 46 hr LC 50 372 338.1 Rice et al. 1980

Pinfish,

Lagodon rhomboides - 14 LC 50 150

- Engel et al. 1976

### E

- 11

Species Chemical Duration

(days) Effect Effect

Concentration

( t otal μg/L) Effect

Concentration

( d issolved μg/L) Reference

Spot,

Leiostomus xanthurus - 14 LC 50 160

- Engel et al. 1976

Atlantic croaker,

Micropogonias undulatus - 14 LC 50 210

- Engel et al. 1976

Winter flounder,

Pseudopleuronectes americanus - 14 Histopathological lesions 180

- Baker 1969

Cobia (egg),

Rachycentron canadum Copper

sulfate 1 LC 50 91 76.26 Dung et al. 2005

Cobia (larva, 1 d),

Rachycentron canadum Copper

sulfate 4 LC 50 60 50.28 Dung et al. 2005

Cobia (juvenile, 20 d),

Rachycentron canadum Copper

sulfate 4 LC 50 87 72.91 Dung et al. 2005

Cobia (young, 40 d),

Rachycentron canadum Copper

sulfate 4 LC 50 240 201.1 Dung et al. 2005

Mahi mahi (4 hpf, blastula stage),

Coryphaena hippurus Copper

chloride 2 LC 50 15.5 14.09 Adema

- Hannes and

Shenker 2008

Mangrove killifish

(adult, 2.5 cm, 0.5 g),

Kryptolebias marmoratus Copper

chloride 2 LOEC

(MT transcript induction) 10 8.380 Rhee et al. 2009

### F

- 1



## Appendix F Data Not Used in the Development of the Aquatic Life Ambient

Estuarine/Marine Water Quality Criteria for Copper

### F

- 2

Appendix Table F

- 1 . Unused Studies Along with Reason.

Species Reference Reason Data Cl assified as Unused

Green mussel,

Perna viridis Aanand et al. 2010 Only one exposure concentration

Herring,

Clupea harengus Abbasi and Sheckley 1995 Only three exposure concentrations

Oyster,

Crassostrea virginica Abbe and Sanders 1986 Mixture

Oyster,

Crassostrea virginica Abbe and Sanders 2000 Mixture, Field exposure

Bivalve,

Malcoma balthica Absil et al. 1993 Steady state not reached for bioaccumulation

study; Exposed in situ

Blue mussel,

Mytilus edulis Adema et al. 1972 Lack of detail (foreign language)

Sheepshead minnow,

Cyprinodon variegatus Adeyemi and Klerks 2012 Only one exposure concentration

Sheepshead minnow,

Cyprinodon variegatus Adeyemi et al. 2012 Only one exposure concentration

Mediterranean sponge,

Crambe crambe Agel et al. 2001 Pre

- exposure to toxicant

European eel,

Anguilla anguilla Ahmad et al. 2005 Only two exposure concentrations

European eel,

Anguilla anguilla Ahmad et al. 2008 Only two exposure concentrations

Crab,

Scylla serrata Ahmed et al. 1997 Only one ex posure concentration

Amphipod,

Allorchestes compressa Ahsanullah and Williams 1991 Low control survival (77.5%)

Teleost,

Trematomus bernacchii

Teleost,

Chionodraco hamatus Albergoni et al. 2000 Mixture; Survey, so prior exposure to many

chemicals

Various species Alekseev et al. 2010 Dilution water not characterized

Cyanobacteria,

Cyanobium sp. Alquezar and Anastasi 2013 Algal study

Turbot,

Scophthalmus maximus Alvarado et al. 2005 Only two exposure concentrations; No

information on seawater

Turbot,

Scophthalmus maximus Alvarado et al. 2006 Only two exposure concentrations

Sea urchin,

Paracentrotus lividus Amaroli et al. 2013 Only one exposure concentration

Polychaete,

Nereis diversicolor

Peppery furrow shell,

Scrobicularia plana

Common shri mp,

Crangon crangon

European flounder,

Platichthys flesus Amiard et al. 1985 No control information; No information on

dilution water

Blue mussel,

Mytilus edulis Amiard

- Triquet et al. 1986 Bioaccumulation: steady state not documented

(16 day exposure)

Potworm,

Enchytraeus albidus Amorim and Scott

- Fordsmand

2012 Terrestrial exposure

### F

- 3

Species Reference Reason Data Cl assified as Unused

Various species Anderson and Norberg

- King

1991 Lack of exposure details; dilution water not

characterized

Diatom,

Phaeodactylum tricornutum Angel et al. 2015 Only one exposure; Pulsed exposure

Anemone,

Bunodosoma cangicum Anjos et al. 2014 Not North American species; Only two

exposure concentrations

Mediterranean mussel,

Mytilus galloprovincialis Arnold et al. 2005 Modeling study (BLM)

Mussel,

Mytilus sp. A rnold and Cotsifas 2008 Review and analysis of previously reported

data

Green Mussel,

Perna viridis Arockia Vasanthi et al. 2012 Field survey, exposure concentration not

known

Flathead mullet,

Mugil cephalus Arockia Vasanthi et al. 2013 Field survey, exposure concentration not

known

Mangrove crab,

Scylla serrata Arumugam and Ravindranath

1987 Not North American species; No LC 50 data

Oyster,

Crassostrea virginica Ayling 1974 Mixture

Blue mussel,

Mytilus edulis Bakhmet et al. 2012 Only three exposure concentrations

Polychaete,

Hydroides elegans Bao et al. 2010 Effect of copper on biofilm development and

larval settlement

Copepod,

Tigriopus japonicus Bao et al. 2013 Not North American species

Brown mussel,

Perna perna Baraj et al. 2011 Only one exposure concentration

Copepod,

Tigriopus brevicornis Barka 2007 Only three exposure concentrations

Copepod,

Tigriopus brevicornis Barka et al. 2010 Only three exposure concentrations

Blue shark,

Prionace glauca Barrera

- Garcia et al. 2013 Field surv ey, exposure concentration not

known

Isopod,

Idotea baltica Bat et al. 199b LT50 is the endpoint

Sea urchin,

Strongylocentrotus purpuratus Bay et al. 1983 Only two exposure concentrations

Echinoid,

Phylum Echinodermata Bay et al. 1993 Review

Coral Berry et al. 2013 Field survey, exposure concentration not

known

Amphipod,

Parhalella natalensis Bhat and Vamsee 1993 Discrepancy in results; No control information

Hybrid striped bass,

Morone chrysops x Morone

saxatilis Bielmyer et al. 2005a Bioaccumulation: steady state not documented

Hybrid striped bass,

Morone chrysops x Morone

saxatilis Bielmyer et al. 2006a Only two fish per concentration

Copepod,

Acartia tonsa Bielmyer et al. 2006b Dietary exposure

### F

- 4

Species Reference Reason Data Cl assified as Unused

Coral,

Acropora cervicornis

Coral,

Pocillopora damicornis

Coral,

Montastrea faveolata

Dinoflagellate,

Symbiodinium sp. Bielmyer et al. 2010 Exposed coral and algal species at the same

time

Sea urchin,

Strongylocentrotus

droebachiensis Bielmyer et al. 2012 Dietary exposure

Sydney rock oyst er,

Saccostrea commercialis Birch and Hogg 2011 Not North American species; Sediment

exposure

Amphipod,

Gammarus annulatus Bisbal 1987 Only two exposure concentrations

Oyster,

Saccostrea cucullata Biswas et al. 2013 Field survey, exposure concentration not

known

Killifish,

Fundulus heteroclitus Blanchard and Grosell 2005 Bioaccumulation: steady state not documented

Killifish,

Fundulus heteroclitus Blanchard and Grosell 2006 Only two exposure concentrations

Oyster,

Crassostrea virginica Blanchard et al. 2009 Bioaccumulation: steady state not documented

Plaice,

Pleuronectes platessa

Herring,

Clupea harengus Blaxter 1977 Only one exposure concentration

Striped bass,

Morone saxatilis Bodammer 1985 No control information; Culture water

contained 57 ug/ L copper

American sand lance,

Ammodytes americanus Bodammer 1987 Only two exposure concentrations

Atlantic horseshoe crab,

Limulus polyphemus Botton and Itow 2009 Review

Brown mussel,

Perna perna Boudjema et al. 2014 Only three exposure concentrations

Crab,

Neohelice granulata

Clam,

Mesodesma mactroides Boyle et al. 2013 Not North American species; Only one

exposure concentration

Ostracod,

Diacypris compacta Brooks et al. 1995 Hypersaline conditions in exposure media

Three Mytlius species Brooks et al. 2015 Bioaccumulation: unmeasured exposure

Red seaweed,

Gracilariopsis longissima Brown et al. 2012 Algal study

Gastropod,

Littorina littoralis

Brown seaweed,

Fucus vesiculosus Bryan 1983 Mixture

Peppery furrow shell,

Scrobicularia plana

Polychaete,

Hediste diversicolor Buffet et al. 2011 Only one exposure concentration

Polychaete,

Hediste diversicolor Burlinson and Lawrence 2007a Mixture (field exposure)

### F

- 5

Species Reference Reason Data Cl assified as Unused

Polychaete,

Hediste diversicolor Burlinson and Lawrence 2007b Prior exposure (sequentially exposed to

increasing copper)

Amphipod,

Melita plumulosa

Copepod,

Nitocra spinipes Campana et al. 2012 Sediment exposure

Sheepshead,

Archosargus probatocephalus Cardeilhac et al. 1979 Only one exposure concentration

Polychaete,

Arenicola marina Casado

- Martinez et al. 2010 Sediment exposure

Mediterranean mussel,

Mytilus galloprovincialis Casas et al. 2008 Mixture

Starfish,

Asterias rubens

White sea urchin,

Echinus acutus Catarino et al. 2008 Mixture

Mediterranean sponge,

Chondrosia reniformis Cebrian et al. 2006 Mixture

Mediterranean sponge,

Crambe crambe

Mediterranean sponge,

Scopalina lophyropoda Cebrian and Uriz 2007a Only one exposure concentration

Mediterranean sponge,

Scopalina lophyropoda Cebrian and Uriz 2007b Only one exposure concen tration

Sponge cell Cebrian and Uriz 2007c Only two exposure concentrations

Wedge sole,

Dicologlossa cuneata

Brill,

Scophthalmus rhombus

Senegalese sole,

Solea senegalensis Chairi et al. 2010 Injected toxicant; Not North American species

Oyster,

Saccostrea cucullata Chaharlang et al. 2012 Field survey, exposure concentration not

known

Oyster,

Crassostrea virginica

Oyster,

Crassostrea gigas Chang 1995 Exposure via biofilm

Oyster,

Crassostrea virginica

Oyster,

Crass ostrea gigas Chang et al. 1996 Exposure via biofilm

Mussel,

Mytilus trossulus Chelomin et al. 1998 Mixture

Goby,

Synechogobius hasta Chen et al. 2013 Not North American species; Only two

exposure concentrations

Oyster,

Crassostrea gigas Cheng 1988a Only one exposure concentration

Oyster,

Crassostrea gigas Cheng 1988b Only one exposure concentration

Gastropod,

Babylonia lutosa Cheung and Wong 1998 Only three exposure concentrations

Hagfish Chiu and Mok 2011 Field survey, exposure concentration not

known

### F

- 6

Species Reference Reason Data Cl assified as Unused

Rockbream,

Oplegnathus fasciatus Cho et al. 2006 Only three exposure concentrations

Red alga,

Porphya yezoensis Choi et al. 2005 Lack of exposure details; number of exposure

concentrations not provided

Snail,

Bulinus rohlfsi Chu 1976 Formulation (50% copper sulfate)

Alga,

Colpomenia sinuosa Cirik et al. 2012 Adsorption study

Mussel,

Echyridella menziesii Clearwater et al. 2014 Not North American species

Bivalve,

Bathymodiolus azoricus Company et al. 2008 Only one exposure concentration

Brown seaweed,

Ascophyllum nodosum

Brown seaweed,

Fucus vesiculosus Connan and Stengel 2011 Only three exposure concentrations

Snail,

Ilyanassa obsoleta Conrad 1988 Mixture (copper and antibiotic)

Kelp,

Lessonia nigrescens Contreras et al. 2007 Not North American species

Amphipod,

Gammarus locusta Correia et al. 2002a Only three exposure concentrations

Amphipod,

Gammarus locusta Correia et al. 2002b Only three exposure concentrations

Sea bass,

Dicentrarchus labrax Cotou et al. 2009 Mixture (source of co pper was antifouling

painted nets); Not North American species

European sea bass,

Dicentrarchus labrax Cotou et al. 2012 Inappropriate form of toxicant (copper

- treated

nets)

Black

- chinned tilapia,

Sarotherodon melanotheron Coulibaly et al. 2012 Field survey, exposure concentration not

known

Epibionts Crespo et al. 2014 Only one exposure concentration

Blue mussel,

Mytilus edulis Curtis et al. 2000 Only four organisms per concentration

Rough periwinkle,

Littorina saxatilis Daka and Hawkins 2004 Mixture

Pacific oyster,

Crassostrea gigas Damiens et al. 2006 Only three exposure concentrations

Black sea bream,

Acanthopagrus schlegeli Dang et al. 2009 Prior exposure

Blackhead seabream,

Acanthopagrus schlegelii

schlegelii Dang et al. 2012 Not Nort h American species

Scallop,

Pecten maximus

Pacific oyster,

Crassostrea gigas Davies and Paul 1986 Inappropriate form of toxicant (copper oxide

based anti

- fouling paint)

Spiny dogfish,

Squalus acanthias De Boeck et al. 2007 Only three exposure concentrations

Spotted dogfish,

Scyliorhinus canicula De Boeck et al. 2010 Only one exposure concentration; Not North

American species

Mediterranean mussel,

Mytilus galloprovincialis Deruytter et al. 2013 Test results not reported, only the model

developed

Guppy,

Poecilia vivipara de Souza Machado et al. 2013 Not North American species

### F

- 7

Species Reference Reason Data Cl assified as Unused

Snakehead catfish,

Channa striata Devi and Gopal 1986 Not North American species

Asian paddle crab,

Charybdis japonica Ding and Wang 2010 Not North American speci es; Text in foreign

language

Mediterranean mussel,

Mytilus galloprovincialis Dragun et al. 2010 Mixture; Survey, so prior exposure to many

chemicals

Duran and Beiras 2013 Review of previously published studies

Sea urchin,

Strongylocentrotus intermedius

Sea urchin,

Strongylocentrotus nudus Durkina 1995 Only three exposure concentrations

Polychaete,

Nereis diversicolor Durou et al. 2005 LT50 is the endpoint

Dinoflagellate,

Cochlodinium polykrikoides Ebenezer and Ki 2012 Algal study

Sea urchin,

Tripneustes gratilla Edullantes and Galapate 2014 Not North American species

Mummichog,

Fundulus heteroclitus Eisler and Gardner 1973 Mixture

Clam,

Macoma balthica Eldon et al. 1980 Dilution water not characterized

Oyster,

Saccostrea cucullata

Oyster,

Crassostrea lugubris

Oyster,

Crassostrea belcheri Elfwing and Tedengren 2002 Only one exposure concentration

Barnacle,

Elminius modestus Elliott et al. 1985a Bioaccumulation: static, unmeasured exposure

Mussel,

Mytilus edulis planulatus Elliott e t al. 1985b Bioaccumulation: steady state not achieved

Crab,

Carcinus maenas Elumalai et al. 2005 Only nine animals per concentration

Coral El

- Sorogy et al. 2012 Field survey, exposure concentration not

known

Oyster Engel and Fowler 1979 Only two exposure concentration

Mediterranean mussel,

Mytilus galloprovincialis Fabbri and Capuzzo 2006 Only one exposure concentration

Sea urchin,

Paracentrotus lividus Fabbrocini and D'Adamo 2011 Not North American species; Lack of details

(no control information/procedures)

Benthic foraminiferal

assemblages Fabrizio and Rodolfo 2012 Sediment present in media

Mediterranean mussel,

Mytilus galloprovincialis Fafandel et al. 2008 Only three exposure concentrations

Fish,

Etroplus maculatus

Clam,

Villorit a cyprinoides var.

cochinensis

Prawn,

Macrobranchium idella idella

Crab,

Paratelphusa hydrodromus Fernandez et al. 1996 Dilution water not characterized

### F

- 8

Species Reference Reason Data Cl assified as Unused

Polychaete,

Laeonereis acuta Ferreira

- Cravo et al. 2009 Only one exposure concentration

Ascidian,

Ciona intestinalis Ferro et al. 2013 Only one exposure concentration

Rotifer,

Brachionus plicatilis Filenko and Samoylova 2008 Dilution water not characterized

Whiting,

Merlangius merlangus

Goatfish,

Mullus barbatus Findik and Cicek 2011 Field survey, exposure concentration not

known

Blue mussel,

Mytilus edulis Fokina and Nemova 2012 Lack of detail (abstract only)

Blue mussel,

Mytilus edulis Fokina et al. 2013 Only three exposure concentrations

Sole,

Solea senegalensis Fonseca et al. 2009 Only three exposure concentrations

Copepod,

Tigriopus brevicornis Forget et al. 1999 Mixture

Ascidian,

Ciona intestinalis Franchi et al. 2012 Only one exposure concentration

Oyster,

Crassostrea gigas Frazier 1976 Mixture

Japanese flounder,

Paralichthys olivaceus

Red Sea bream,

Pagrus major Furuta et al. 2008 Not North American species

Seam bream,

Sparus aurata

Bivalve,

Scapharca inaequivalvis Gabbianelli et al. 2003 Only one exposure concentration

Sole,

Solea senegalensis Galindo et al. 2012 Field survey, exposure concentration not

known

Barnacle,

Amphibalanus variegatus Gall et al. 2013 Not North American species

Sea squirt,

Styela plicata Galletly et al. 2007 Only three exposure concentrations

Rotifer,

Brachionus rotundiformis Gama

- Flores et al. 2005 Not North American species

Isopod,

Idotea baltica Gambardella et al. 1998 Only acclimated one day

Brown flagellate,

Isochvysis sp. Garr 2012 Algal study

Asteroid,

Coscinasterias muricata Georgiades et al. 2006 Only three exposure concentrations

Polychaete,

Laeonereis acuta Geracitano et al. 2002 Only two exposure concentrations

Polychaete,

Laeonereis acuta Geracitano et al. 2004 Only two exposure concentrations

Oyster,

Crassostrea gigas

Mussel,

Mytilus edulis Geret et al. 2002a Bioaccumulation: unmeasured exposure and

steady state not achieved

Clam,

Ruditapes decussatus Geret et al. 2002b Only three exposure concentrations

### F

- 9

Species Reference Reason Data Cl assified as Unused

Isopod,

Exosphaeroma gigas Giarratano et al. 2007 Only 24 hour acclimation

Coon stripe shrimp,

Pandalus danae Gibson 1976 Acclimated to one temperature and tested at

another

Clam,

Paphia malabarica Gireesh and Gopinathan 2009 Only one exposure concentration

Copepod,

Acartia sinjiensis Gissi et al. 2013 Not North American species

Alga,

Phaeocystis antarctica Gissi et al. 2015 Not North American species

Coho salmon,

Oncorhynchus kisutch

Masu salmon,

Oncorhynchus masou

Siberian sturgeon,

Acipenser baeri Glubokov 1990 No dose response

Doughboy scallop,

Mimachlamys asperrima Golding et al. 2006 No tox icity information; Not North American

species

Mediterranean mussel,

Mytilus galloprovincialis Gomes et al. 2011 Only one exposure concentration

Mediterranean mussel,

Mytilus galloprovincialis Gomes et al. 2013 Only one exposure concentration

Protozoa,

Euplotes crassus Gomiero et al. 2012 a Protozoa; Lack of details (abstract only)

Protozoa,

Euplotes crassus Gomiero et al. 2014 Protozoa

Polychaete,

Hydroides elegans Gopalakrishnam et al. 2007 Prior exposure

Abalone,

Haliotis rubra Gorski and Nugegoda 2006b Lack of detail (not sure what units the effect

concentration is in)

Giant sea scallop,

Placopecten magellanicus Gould et al. 1985 Bioaccumulation: steady state not achieved

Giant sea scallop,

Placopecten magellanicus Gould et al. 1986 Lack of details (abstract only)

White prawn,

Penaeus indicus

Green mussel,

Perna viridis

Brine shrimp,

Artemia salina Govindarajan et al. 1993 Lack of details (procedure)

European eel,

Anguilla anguilla Gravato et al. 2006 Prior exposure

Skate,

Raja erinacea

Sculpin,

Myoxocephalus

octodecemspinosus Grosell et al. 2003 Only two exposure concentrations

Brine shrimp,

Artemia franciscana

Cladoceran,

Daphnia magna

Alga,

Selenastrum capricornutum Guida et al. 2008 Mixed species exposure

### F

- 10

Species Reference Reason Data Cl assified as Unused

Dinoflagellate,

Prorocentrum minimum Guo and Ki 2012 Algal study

Dinoflagellate,

Prorocentrum minimum Guo et al. 2012 Algal study

Abalone,

Haliotis discus Guo et al. 2013 Not North American species

Babylon snail,

Babylonia areolata Hajimad and Vedamanikam

2014 Not North American species

Handy 2003 Review

Amphipod Hanna et al. 2013 Inappropriate form of toxicant (nanoparticles)

Shore crab,

Carcinus maenas Hansen et al. 1992 Only one exposure concentration

Blue mussel,

Mytilus edulis Harrison et al. 1983 Only three exposure concentrations

Rats and Mice Hasegawa et al. 1989 Non

- aquatic organisms

Polychaete,

Nereis diversicolor Hateley et al. 1989 Mixture (field exposure)

Shore crab,

Carcinus maenas Hebel et al. 1999 Only five organisms per concentration

Coral,

Montipora capitata Hedouin and Gates 2013 Not North American species

Blue mussel,

Mytilus edulis Hellou et al. 2003 Mixture

Dinoflagellate,

Alexandrium catenella Herzi et al. 2013 Contaminated dilution water

Flower crab,

Portunus pelagicus Hilmy et al. 1985 Dilution water not characterized; Not North

American species

Blue mussel,

Mytilus edulis Hines et al. 2010 Only two exposure concentrations

Brown mussel,

Perna perna Hodgson and Hoebeke 1984 Only five organisms per concentration

Blue mussel,

Mytilus edulis Hoher et al. 2013 Only three exposure concentrations

Hori et al. 1996 Lack of details (foreign language)

Isopod,

Porcellio scaber Hornung et al. 1998 Sediment present in media

Alga Horta

- Puga et al. 2013 Field survey, exposure concentration not

known

Sea anemone,

Aiptasia pulchella Howe et al. 2012 Not North American species

Sea anemone,

Aiptasia pulchella Howe et al. 2014 Not North American species

Nematode,

Enoplus brevis Howell 1984 LT50 is the endpoint

Various species Hrovat et al. 2009 Review

Red alga,

Gracilaria lemaneiformis

Red alga,

Gracilaria lichenoides Huang et al. 2013 Algal study

Baltic clam,

Macoma balthica

Cockle,

Cerastoderma edule Hummel et al. 1998 Sediment present in media

Pacific kelps Huovinen et al. 2010 Only one exposure concentration

### F

- 11

Species Reference Reason Data Cl assified as Unused

Bivalve,

Austriella cf plicifera Hutchins et al. 2008 Sediment present in media

Bivalve,

Indoaustriella lamprelli Hutchins et al. 2009 Sediment present in media

Protozoa,

Alexandrium minutum Hwang and Lu 2000 Protozoa

Copepod,

Paracyclopina nana Hwang et al. 2010 Only one exposure concentration

Amphipod

, Corophium sp. Hyne and Everett 1998 No control survival information, and author

suggests poor control survival if no sediment

present

Seabream,

Sparus aurata Isani et al. 2012 Not North American species

Indian edible oyster,

Crassostrea madrasensis Ittoop et al. 2009 Not North American species; Only three

exposure concentrations; Dilution water not

characterized

Hard clam,

Mercenaria mercenaria Ivanina et al. 2013 Only two exposure concentrations

Filter feeders Jara

- Marini et al. 2013 Field survey, exposure concentration not

known

Copepod,

Tigriopus japonicus Jeong et al. 2014 Not North American species

Pearl oyster,

Pinctada fucata Jing et al. 2006 Only two exposure concentrations

Butterfish,

Poronotus triacanthus Jiraungkoorskul et al. 2007 Only one exposure concentration

Pink shrimp,

Penaeus duorarum

Shrimp,

Penaeus stylirostris

Shrimp,

Penaeus setiferus Johnson 1974 Only two or three exposure concentrations;

Purity of test material questionable

Jones et al. 1968 Review

Isopods Jones 1975 Only two exposure concentrations

Brine shrimp,

Artemia salina Jorgensen and Jensen 1977 Brine shrimp used

Mediterranean mussel,

Mytilus galloprovincialis Kanduc et al. 2011 Field survey, exposure concentration not

known

Mangrove crab,

Macrophthalmus erato Kannupandi et al. 2001 Only three exposure concentrations

Sea bass,

Dicentrarchus labrax Kentouri et al. 1993 Only one exposure concentration

Killifish,

Aphanius dispar Khan and Khan 1999 Dilution water not characterized; Not North

American species

Heliozoon,

Raphidiophrys contractilis Khan et al. 2006 Lack of exposure details; dilution water not

characterized

Copepod,

Tigriopus japonicus Ki et al. 2009 Only one exposure concentration; Not North

American species

Copepod,

Tigriopus japonicus Kim et al. 2012 Not North American species; Lack of

exposure details

Various bivalves Klumpp and Burdon

- Jones

1982 Mixture (field exposure)

### F

- 12

Species Reference Reason Data Cl assified as Unused

Sea urchin,

Hemicentrotus pulcherrimus

Sea urchin,

Anthocidaris crassispina Kobayashi and Okamura 2002 Inappropriate form of toxicant (copper

pyrithione)

Black sea bivalve mollusks,

Anadara inaequivalvis &

Chamelea gallina Kolyuchlina and Ismailov 2011 Not North American species

Mediterranean mussel,

Mytilus galloprovincialis Koukouzika and Dimitriadis

2008 Only one exposure concentration

Shore crab,

Carcinus maenas Krang and Ekerholm 2006 Only two exposure concentrations

Eastern oyster,

Crassostrea virginica Krishnamurthy 1994 Bioaccumulation: static exposure

Nile tilapia,

Oreochromis niloticus Kulac et al. 2013 Only one exposure concentration

Oyster,

Saccostrea cucullata

Snail,

Cerithium rubus Kumari and Nair 1992 Bioaccumulation: static, unmeasured exposur e

Coral,

Platygyra acuta Kwok and Ang 2013 Not North American species

Copepod,

Tigriopus japonicus Kwok et al. 2009 Prior exposure; Not North American species

Cuttlefish,

Sepia officinalis Lacoue

- Labarthe et al. 2009 Only one exposure concentration; Not North

American species

Sea snail,

Hexaplex trunculus Lahbib et al. 2013 Field survey, exposure concentration not

known

Green alga,

Ulva lactuca

Seaweed,

Codium fragile

Seaweed,

Jania rubens

Alga,

Dictyota dichotoma Laib and Leghouchi 2012 Field survey, exposure concentration not

known

Red sea bream,

Chrysophrys major Lan and Chen 1991 Lack of detail (text in foreign language)

Copepod,

Acartia tonsa Lauer and Bianchini 2010 Intermittent exposure (12hr exposed and 12hr

clean)

Estuarine crab,

Neohelice granulata Lauer et al. 2012 Not North American species; Only one

exposure concentration

Crab,

Chasmagnathus granulatus Lavolpe et al. 2004 Only two exposure concentrations

Ammonia (foraminifera) Le Cadre and Debenay 2006 Protozoa

Flatworm,

Stylochus pygmaeus Lee and Johnston 2007 Only two exposure concentrations

Blue crab,

Callinectes sapidus Lee and Oshima 1998 Lack of exposure details; dilution water not

characterized

Blue crab,

Callinectes sapidus Lee et al. 1999 Dilution water not characterized

Copepod,

Tigriopus japonicus Lee et al. 2008a Only two exposure concentrations; Not North

American species

### F

- 13

Species Reference Reason Data Cl assified as Unused

Hairy

- handed crab,

Hemigrapsus crenulatus

Shield shell limpet,

Scutus breviculus Lee et al. 2010 Only two exposure concentrations; Not North

Americ an species

Blue mussel,

Mytilus edulis

Clam,

Macoma balthica Lehtonen and Leinio 2003 Only two exposure concentrations

Copepod,

Euchaeta japonica Lewis et al. 1972 Only three exposure concentrations

Polychaete,

Spirobranchus lamarckii Lewis et al. 2013 Not North American species

Gastropod,

Onchidium struma Li et al. 2009 Sediment present in media

Chinese oyster,

Ostrea plicatula Li et al. 2010 Not North American species

Mussel,

Mytilus coruscus Li et al. 2012a Not North American species

Seagrass,

Thalassia hemprichii Li et al. 2012b Not North American species; Only three

exposure concentrations

Shrimp,

Penaeus japonicus Liao and Hsieh 1988 LT50 is the endpoint in the acute exposure;

Chronic and bioaccumulation exposure was

not measured

Shrimp,

Pe naeus chinensis Liu 1995 Lack of detail (text in foreign language)

Fish,

Synechogobius hasta Liu et al. 2010 Not North American species; Only two

exposure concentrations

Four marine bivalves Liu et al. 2012 Mixture

Crescent

- banded tigerfish,

Terapon jarbua Long and Wang 2005 Prior exposure

Crab,

Petrolisthes galathinus Lopez Greco et al. 2002 Only two exposure concentrations

Blue mussel,

Mytilus edulis Lorenzo et al. 2005 Bioaccumulation: steady state not achieved

Diatoms Lozano et al. 2014 Only two exposure concentrations

Shore crab,

Carcinus maenas Lundebye and Depledge 1998a Only six organisms per concentration

Shore crab,

Carcinus maenas Lundebye and Depledge 1998b Only six organisms per concentration

Eastern oyster,

Crassostrea virginica Lunz 1972 River water used as dilution water;

Bioaccumulation: steady state not achieved

Hermit crab,

Clibanarius longitarsus Lyla and Khan 2011 Not North American species

Eastern oyster,

Crassost rea virginica Macey et al. 2010 Only four organisms per concentration; Only

three exposure concentrations

Guppy,

Poecilia vivipara Machado et al. 2013 Not North American species; Only three

exposure concentrations

Eastern oyster,

Crassostrea virginica MacInnes 1981 Mixture

Mud snail,

Nassarius obsoletus MacInnes and Thurberg 1973 Too few organisms per exposure concentration

(n=5)

Stone

- loach,

Nemacheilus barbatulus Mackereth and Smyly 1951 Lack of details (abstract only)

### F

- 1 4

Species Reference Reason Data Cl assified as Unused

Spiny lobster,

Panulirus homarus Maharajan et al. 2011 Not North American species; Only two

exposure concentrations

Spiny lobster,

Panulirus homarus Maharajan et al. 2012a Not North American species; Only two

exposure concentrations

Spiny lobster,

Panulirus homarus Maharajan et al. 2012b Not North American species

Sponge,

Hymeniacidon perlevis Mahaut et al. 2013 Field survey, exposure concentration not

known

Pacific oyster,

Crassostrea gigas Mai et al. 2012 Only three exposure concentrations

Diatom,

Odontella mobiliensis Manimaran et al. 2012 Algal study

Various bivalves Manley and Davenport 1979 Review

Grass shrimp,

Palaemonetes pugio Manyin 2008 Only acclimated for 24 hours; Only two

exposure concentrations

Grass shrimp,

Palaemonetes pugio Manyin and Rowe 2009 Only three exposure concentrations

Grass shrimp,

Palaemonetes pugio Manyin and Rowe 2010 Only two exposure concentrations

Limpet,

Patella vulgata Marchan et al. 1999 Surgically altered test species

Blue mussel,

Mytilus edulis Martin et al. 1975 Chelating agent used in exposure media

Shore clam,

Ruditapes philippinarum Martin

- Diaz et al. 2005 Only one exposure concentration

Blue crab,

Callinectes sapidus Martins et al. 2011a Only one exposure concentration

Persian sturgeon,

Acipenser persicus Mashroofeh et al. 2012 Field survey, exposure concentration not

known

Clam,

Sunetta scripta

Mussel,

Perna viridis Mathew and Damodaran 1997 Only one exposure concentration

Mussel,

Perna viridis

Clam,

Meretrix casta Mathew and Menon 1984 Insufficient acclimation time

European sea star,

Asterias rubens Matranga et al. 2012 Mixture; Not North American species

Amphipod,

Corophium volutator

Polychaete,

Hediste diversicolor Mayor et al. 2008 Sediment toxicity test

Amphipod,

Leptocheirus plumulosus McGee et al. 1999 Mixture and sediment exposure

Bryzoa,

Watersipora subtorquata McKenzie et al. 2011 Only two exposure concentrations

Lobster,

Homarus americanus McLeese 1974 LT50 is the endpoint; Only five organisms per

concentration

McLeese 1976 Species name not given

### F

- 15

Species Reference Reason Data Cl assified as Unused

Clam,

Macoma balthica

Shrimp,

Crangon septemspinosa

Shrimp,

Pandalus montagui

Polychaete,

Nereis virens McLeese and Ray 1986 Only six organisms per concentration

Crab,

Chasmagnathus granulata Medesani et al. 2004a Only one exposure concentration

C rab,

Chasmagnathus granulata Medesani et al. 2004b Only one exposure concentration

Amphipod,

Corophium multisetosum Menchaca et al. 2010 Not North American species; Sediment

exposure

Polychaete,

Capitella sp. Mendez and Green

- Ruiz 2005 Only three exposure concentrations

Polychaete,

Capitella sp. Mendez and Green

- Ruiz 2006 Only three exposure concentrations

Pacific oyster,

Crassostrea gigas Metzger et al. 2012 Only one exposure concentration

Turbot,

Psetta maxima Mhadhbi et al. 2010 Not North American species

Blue

- green alga,

Synechococcus sp.

Diatom,

Thalassiosira weissflogii

Dinoflagellate,

Prorocentrum minimum Miao et al. 2005 Algal study; Excessive NTA in the media

Ribbed mussel,

Geukensia demissa Miller 1986 Lack of details (abstract onl y)

Ribbed mussel,

Geukensia demissa Miller 1988 Only two exposure concentrations

Meiofaunal community Millward et al. 2001 Mixture

Sea bream,

Sparus aurata Minghetti et al. 2008 Prior exposure

Diatom,

Haslea ostrearia Minier et al. 1998 Algal study

Shrimp,

Penaeus monodon Misra et al. 2005 Not North American species; Dilution water

not characterized

White mussel,

Donax trunculus Mizrahi and Achituv 1989 Not North Americans species; Only five

organisms per concentration

White mussel,

Donax trunculus Mizrahi et al. 1993 Not North Americans species; Only three

exposure concentrations

Mummichog,

Fundulus heteroclitus Mochida et al. 2008 Mixture

Fish Mohan et al. 2012 Field survey, exposure concentration not

known

Coral Mokhtar et al. 2012 Field survey, exposure concentration not

known

Pacific oyster,

Crassostrea gigas Money et al. 2011 Mixture

### F

- 16

Species Reference Reason Data Cl assified as Unused

Mediterranean mussel,

Mytilus galloprovincialis

Blue mussel,

Mytilus edulis Moore et al. 2007 Only one exposure concentration

Oyster,

Crassostrea gigas Moraga et al. 2005 Only two exposure concentrations

Brown alga,

Ectocarpus siliculosus Morris and Russell 1973 Algal study; Prior exposure (tolerant strain)

Mozambique tilapia,

Oreochromis mossam bica Mukhopadhyay 1983 Lack of details (abstract only)

Clam,

Tapes philippinarum Munari and Mistri 2007 Only one exposure concentration; Possible

prior exposure

Shrimp,

Penaeus monodon Munshi et al. 1996a Not North American species; Variable time for

LC 50 values

Shrimp,

Penaeus penicillatus Munshi et al. 1996b Only acclimated for one hour

Blue crab,

Callinectes sapidus Mutlu et al. 2011 Field survey, exposure concentration not

known

Pikeperch Nabavi et al. 2012 Field survey, exposure concentration not

known

Mussel,

Mytilus trossolus Nadella et al. 2009 Only acclimated for 24 hours

Mussel,

Mytilus viridis Nair et al. 1977 Only eight animals per concentration

Common cockle,

Cerastoderma edule Naylor 1987 Not North American species

Blue crab,

Callinectes similis Neff and Anderson 1977 Only three exposure concentrations

Polychaete,

Pectinaria koreni

Polychaete,

Nephthys ciliata

Mussel,

Mytilus calcarea

Mussel,

Mytilus baltica Neuhoff and Theede 1984 Lack of details (procedure)

Mussel,

Perna viridis Nicholson 1999 Only three exposure concentrations

Green mussel,

Perna viridis Ng and Wang 2007 Mixture

European eel,

Anguilla anguilla Nunes et al. 2014 Only three exposure concentrations

Polychaete,

Eurythoe complanata Nusetti et al. 1998 Only one exposure concentration

Senegal sole,

Solea senegalensis Oliva et al. 2009 Not North American species; Only acclimated

for 24 hours

European eel,

Anguilla anguilla Oliveira et al. 2008 Only one exposure concentration

Fish and shellfish Olmedo et al. 2013 Field survey, exposure concentration not

known

Fish and crustaceans Olsen 2011 Review of previously published studies

### F

- 17

Species Reference Reason Data Cl assified as Unused

Flat oyster,

Ostrea edulis

Pacific oyster,

Crassostrea gigas Ong et al. 2013 Field survey, exposure concentration not

known

Mummichog,

Fundulus heteroclitus Ortiz et al. 1999 Bioaccumulation: static, unmeasured

exposure, steady state not achieved

Hermit crab,

Clibanarius africanus Otitoloju and Don

- Pedro 2006 Sediment present in media

Alga,

Fucus vesiculosus Owen et al. 2012 Algal study; Only two exposure concentrations

Fish and mollusks Oya et al. 1939 Text in foreign language

Mussel,

Lithophaga lithophaga Ozsuer and Sunlu 2013 Field survey, exposure concentration not

known

Blue crab,

Callinectes sapidus Paganini and Bianchini 2009 Excised cells

Sea urchin,

Paracentrotus lividus

Sea urchin,

Echinus esculentus Pagano et al. 1986 Lack of details (procedures; dilution water not

characterized)

Sea urchin Pagano et al. 2002 Mixture

Crab,

Charybdis japonica Pan et al. 2011 Not North American species

Copepod,

Tigriopus japonicus Park et al. 2014 Not North American species

Scallop,

Pecten maximus

Oyster,

Crassostrea gigas Paul and Davies 1986 Formulation (Hard Racing Red)

Red drum,

Sciaenops ocellatus Peppard et al. 1991 Formulation (Copper Control®, 8.5% copper)

Mussel,

Perna perna Pereira et al. 2007 Mixture

Pistol prawn,

Alpheus malabaricus malabaricus Perumal and Subramanian

1985 Excessive control mortality (20%)

Polychaete,

Neanthes arenaceodentata Pesch 1979 Only one exposure concentration

Green mussel,

Perna viridis Pillai and Menon 1998 Excised tissue

Mangrove crab,

Ucides cordatus Pinheiro et al. 2012 Mixture

Copepod,

Acartia tonsa Pinho et al. 2007 Only one exposure concentration

Sea urchin,

Paracentrotus lividus Pinsino et al. 2011 Only one exposure concentration

Bryzoans Piola and Johnston 2009 Surgically altered test species

Polychaete,

Nereis diversicolor Pook et al. 2009 Prior exposure

Amphipod,

Gammarus aequicauda Prato and Biandolino 2005 Sediment toxicity test

Copepod,

Tigriopus fulvus Prato et al. 2013a Not North American species

Amphipod,

Gammarus aequicauda Prato et al. 2013b Only two exposure concentrations

Oyster Prytherch 1931 Mixture (field exposure)

### F

- 18

Species Reference Reason Data Cl assified as Unused

Mediterranean mussel,

Mytilus galloprovincialis Pytharopoulou et al. 2011 Only three exposure concentrations

Mediterranean mussel,

Mytilus galloprovincialis Pytharopoulou et al. 2013 Only one exposure concentration

Decapod,

Palaemonetes varians Rainbow and Smith 2013 Not North American species

Mullet,

Mugil cephalus Rajkumar and Milton 2011a Dilution water not characterized

Green mussel,

Perna viridis Rajkumar and Milton 2011b Dilution water not characterized

Snail,

Cerithidae cingulata

Bivalve,

Modiolus philippinarum Ramakritinan et al. 2012 Not North American species

Polychaete,

N ereis sp. Raymont and Shields 1963 Inappropriate form of toxicant (copper sodium

citrate)

Crab,

Scylla serrata Reddy 1997 Only one exposure concentration

Green alga,

Enteromorpha compressa Reed and Moffat 1983 Plant study

Antarctic scallop,

Adamussium colbecki Regoli et al. 1997 Only one exposure concentration

Antarctic scallop,

Adamussium colbecki Regoli et al. 1998 Only two exposure concentrations

Coral,

Goniastrea aspera Reichelt

- Brushett and Harrison

1999 Only three exposure concentrations

Coral,

Lobophytum compactum Reichelt

- Brushett and

Michalek

- Wagner 2005 Not North American species; Lack of details

(exposure duration not given)

Polychaetes Reish 1978 Lack of details (procedure)

Amphipod

, Corophium insidiosum

Amphipod,

Elasmopus bampo Reish 1993 No control survival information

Polychaete,

Ctenodrilus serratus

Polychaete,

Ophryotrocha diadema Reish and Carr 1978 Citrate added to dilution water

Polychaetes Reish and LeMay 1991 Dilution water not characterized

Polychaete,

Neanthes arenaceodentata

Polychaete,

Capitella capitata Reish et al. 1976 Citrate added to dilution water

Copepod,

Tigriopus japonicus Rhee et al. 2009 Not North American species

Copepod,

Tigriopus japonicus Rhee et al. 2013 Not North American species; Only three

exposure concentrations

Eastern oyster,

Crassostrea virginica Ringwood et al. 1998 Only two exposure concentrations

Copepod,

Tigriopus fulvus Rinna et al. 2011 Not North American species

### F

- 19

Species Reference Reason Data Cl assified as Unused

Mediterranean mussel,

Mytilus galloprovincialis

Sand dollar,

Dendraster excentricus

Purple sea urchin,

Strongylocentrotus purpuratus Rivera

- Duarte et al. 2005 Lack of exposure details; dilution water not

characterized

Amphipod,

Peramphithoe parmerong Roberts et al. 2006 Not North American species

Red drum,

Sciaenops ocellatus Robinson et al. 2013 Prior exposure to pollutant

Clam,

Chamaelea gallina Rodriguez

- Ortega et al. 2003 Only three exposure concentrations

Sea snail,

Hexaplex ( Murex ) trunculus Romeo et al. 2006 Only three exposure concentrations

Mediterranean mussel,

Mytilus galloprovincialis

Purple sea urchin,

Strongylocentrotus purpuratus

Sand dollar,

Dendraster excentricus Rosen et al. 2005 Mixture

Clam,

Venerupis decussata Ruiz

- Azcona et al. 2013 Not North American species

Bivalves Sakellari et al. 2013 Field survey, exposure concentration not

known

Various organisms Salazar and Salazar 1986 Only three exposure concentrations

Various organisms Salazar and Salazar 1989 Not applicable, No copper toxicity information

Brine shrimp,

Artemia salina Saliba and Krzyz 1976 Brine shrimp used

Blue mussel,

Mytilus edulis Sanchez

- Marin et al. 2012 Bioaccumulation study: steady state not

achieved

Purple se a urchin,

Strongylocentrus purpuratus Sanders and Martin 1994 Inappropriate form of toxicant (Cu

- NTA)

Crab,

Rhithropanopeus harrisii Sanders et al. 1984 Lack of details (procedure)

Mussel,

Brachiodontes exustus Sastre et al. 2005 Only three exposure concentrations

Clam,

Villorita cyprinoides var.

cochinensis Sathyanathan et al. 1988 Only two exposure concentrations; Not North

American species

Shark,

Scyliorhinus canicula Sayin et al. 2012 In vitro

Coral,

Montastraea franksi Schwarz et al. 2013 Only three exposure concentrations

Shore crab,

Carcinus maenas Scott

- Fordsmand and Depledge

1997 Bioaccumulation: unmeasured exposure

Crab,

Neoepisesarma mederi Selvakumar et al. 1987 Lack of details (proc edure)

Green mussel,

Perna viridis Sharma et al. 2006 Only one exposure concentration

Green mussel,

Perna viridis Sharma et al. 2007 Only one exposure concentration

Green mussel,

Perna viridis Shi and Wang 2004 Prior exposure

### F

- 20

Species Reference Reason Data Cl assified as Unused

Sea anemone,

Exaiptasia pallida Siddiqui et al. 2015 Only two exposure concentrations

Abalone,

Haliotis rufescens Silva

- Aciares et al. 2013 Only two exposure concentrations

Burrowing crab,

Neohelice granulata Simonetti et al. 2012 Field survey, exposure concentration not

known

Bivalve,

Tellina deltoidalis Simpson et al. 2012 Not North American species; Sediment

exposure

Prawn,

Metapenaeus dobsoni Sivadasan et al. 1986 Not North American species; Test species fed

Clam,

Ruditapes decussatus Sobral and Widdows 1997 Bioaccumulation: unmeasured exposure,

steady state not achieved

White shrimp,

Litopenaeus vannamei Soegianto et al. 2013 Only three exposure concentrations

Javelin goby,

Synechogobius hasta Song et al. 2013 Not North American species; Only three

exposure concentrations

Javelin goby,

Synechogobius hasta Song et al. 2014 Not North American species

Brown alga,

Dictyota kunthii Sordet et al. 2014 Only one exposure concentration

Winkle,

Littorina littorea Soto et al. 1999 Excised tissue

Snail,

Nassarius reticulatus Sousa et al. 2005 Not North American species

Hydroid,

Campanularia flexuosa Stebbing 1981 Colony exposure

Blue mussel,

Mytilus edulis Steinert and Pickwell 1985 Excised tissue

Abalone,

Haliotis midae Stofberg et al. 2011 Not North American species; Poor control

survival (≤20%)

Amphipod,

Melita plumulosa

Bivalve,

Spisula trigonella

Bivalve,

Tellina deltoidalis Strom et al. 2011 Sediment exposure

Brown alga,

Ascophyllum nodosum Stromgren 1979 Algal study

Alga,

Synechococcus Stuart et al. 2009 Inappropriate form of toxicant (Cu

- EDTA)

Blue mussel,

Mytilus edulis Sturesson 1984 Bioaccumulation: unmeasured exposure

Polychaete,

Perinereis aibuhitensis Sun et al. 2009 Not North American species

Copepod,

Acartia tonsa Sunda et al. 1990 Mixture

Blue mussel,

Mytilus edulis Sunila 1988 Only one exposure concentration

Blue mussel,

Mytilus edulis Sutherland and Major 1981 Only one exposure concentration

Sea urchin,

Strongylocentrotus intermedius

Sea urchin,

Strongylocentrotus nudus Syasina et al. 1992 Only two exposure concentrations

### F

- 21

Species Reference Reason Data Cl assified as Unused

Green mussel,

Perna viridis

Mussel,

Septifer virgatus Sze and Lee 1995 Only one exposure concentration

Pacific oyster,

Crassostrea gigas Tanguy et al. 2002 Only one exposure concentration

Sydney rock oyster,

Saccos trea glomerata Taylor et al. 2013 Only one exposure concentration

European eel,

Anguilla anguilla Teles et al. 2005 Only two exposure concentrations

Green mussel,

Perna viridis Thiagarajan et al. 2006 Only one exposure concentration

Fish Thiyagarajan et al. 2012 Field survey, exposure concentration not

known

Mummichog,

Fundulus heteroclitus Thomas 1915 Only one exposure concentration

Green crab,

Carcinus maenas

Rock crab,

Cancer irroratus Thurberg et al. 1973 Copper level high in dilution water

Blue mussel,

Mytilus edulis Trevisan et al. 2011 Only one exposure concentration

Shore crab,

Carcinus maenas Truchot and Rtal 1998 Bioaccumulation: steady state not achieved

Mussel,

Mytilus californianus

Blue mussel,

Mytilus edulis Tullis 1980 Only four organisms per concentration

Brine shrimp,

Artemia salina Umarani et al. 2012 Brine shrimp used

Crab,

Sesarma quadratum Valarmathi and Azariah 2002 Only two exposure concentrations

Gilthead seabream,

Sparus aurata Varo et al. 2007 Only three exposure con centrations

Bivalve,

Glycymeris yessoensis Vasil'eva et al. 1979 Bioaccumulation: unmeasured exposure

Mysid,

Mysidopsis juniae Vaz et al. 2011a Lack of details (procedure); Not North

American species

Mysid,

Mysidopsis juniae Vaz et al. 2011b Inappropriate form of toxicant (nanoparticles);

Not North American species

Babylon snail,

Babylonia areolata Vedamanikam and Hayimad

2014 Not North American species

Abalone,

Haliotis rufescens Viant et al. 2002 Only two exposure concentrations

Protozoa,

Euplotes crassus Viarengo et al. 1996 Protozoa

Brown mussel,

Perna perna Vosloo et al. 2012 Bioaccumulation study: steady state not

achieved

Nematode,

Monhystera disjuncta Vranken et al. 1991 Agar media used

Saltmarsh cordgrass,

Spartina alterniflora Waddell and Kraus 1990 Terrestrial exposure

Cladoceran,

Moina monogolica Wang et al. 2007a Dietary exposure

### F

- 22

Species Reference Reason Data Cl assified as Unused

Abalone,

Haliotis discus hannai Wang et al. 2009 Not North American species

Sea urchin,

Strongylocentrotus intermedius Wang et al. 2011a Not North American species; Mixture

Bivalves Wang et al. 2011b Field survey, exposure concentration not

known

Grouper,

Epinephelus coioides Wang et al. 2014 Only two exposure concentration

Alga,

Aureococcus anophagefferens Wange et al. 2012 Algal study; Exc essive EDTA in the media

Rock sea urchin,

Paracentrotus lividus Warnau et al. 1996 Not North American species; Dilution water

not characterized

Sea urchin,

Arbacia punctulata Waterman 1937 Lack of details (procedure)

Mollusks Watling 1981 Lack of exposure details; dilution water not

characterized

Brown alga,

Aureococcus anophagefferens Wei et al. 2013 Only three exposure concentrations

Macroalga,

Ulva lactuca Wendt et al. 2013 Algal study

Polychaete,

Perinereis nuntia Won et al. 2012 Only one exposure concentration; Not North

American species

Shore crab,

Carcinus maenas Wong and Rainbow 1986 Method paper

Soft shell clam,

Mya arenaria

Eastern oyster,

Crassostrea virginica Wright and Zamuda 1987 Bioaccumualtion: steady state not achieved;

Chela tor (NTA) added to dilution water

Green mussel,

Perna viridis Wu and Wang 2010 Only one exposure concentration

Prawn,

Penaeus orientalis kishinouye

Clam,

Potamocorbula laevis Xu and Jing 1995 Dilution water not characterized

Sea urchin,

Glyptocidaris crenularis Xu et al. 2010 Not North American species; Lack of

exposure details

Black abalone,

Haliotis cracherodii Yaffe 1979 Only one exposure concentration; No true

control croup

Polychaeta,

Perinereis aibuhitensis Yang et al. 2012 Only three exposure concentrations

Sea urchin,

Arbacia punctulata Young and Nelson 1974 Only one exposure concentration

Chinese prawn,

Penaeus orientalis Zang et al. 1993 Dilution water not characterized; Not North

American species

Oyster,

Crassostrea hongkongensis Zhang and Zhang 2012 Not North American species

Clam,

Venerupis ( Ruditapes )

philippinarum Zhang et al. 2012 Only two exposure concentrations

Guppy,

Poecilia vivipara Zimmer et al. 2012 Not North American species; Only one

exposure concentrations

Ornate wrasse

, Thalassoma pavo Zizza et al. 2014 Not North American species

### G

- 1



## Appendix G Species Numbers Used in BLM Analysis

### G

- 2

Appendix Table G

- 1

. Species Numbers Used in BLM Analysis

.

Organism Species Species

Number

Blue mussel Mytilus edulis 1

Mussel Mytilus galloprovincialis 2

Copepod Tigriopus californicus 3

Summer flounder Paralichthys dentatus 4

Red abalone Haliotis rufescens 5

Black abalone Haliotis cracherodii 6

Mysid Holmesimysis costata 7

Eastern oyster Crassostrea virginica 8

Pacific oyster Crassostrea gigas 9

Purple sea urchin Strongylocentrotus purpuratus 10

Green sea urchin Strongylocentrotus droebachiensis 11

Coot clam Mulinia lateralis 12

Long

- spined sea urchin Diadema antillarum 13

Sea urchin Arbacia punctulata 14

Bay scallop Argopecten irradians 15

Copepod Acartia tonsa 16

Copepod Acartia clausi 17

Sand dollar Dendraster excentricus 18

Copepod Eurytemora affinis 19

Softshell clam Mya arenaria 20

Rotifer Brachionus plicatilis 21

Surf clam Spisula solidissima 22

Lobster Homarus americanus 23

Mysid Neomysis mercedis 24

Dungeness crab Cancer magister 25

Polychaete Anaitides maculata 26

Cabezon Scorpaenichthys marmoratus 27

Inland silverside Menidia beryllina 28

Tidewater silverside Menidia peninsulae 29

Atlantic silverside Menidia menidia 30

Sea anemone Aiptasia pallida 31

Amphipod Elasmopus rapax 32

Mysid Americamysis bigelowi 33

Mysid Americamysis bahia 34

Amphipod Orchomenella pinguis 35

Polychaete Hydroides elegans 36

Copepod Tisbe furcata 37

Copepod Pseudodiaptomus coronatus 38

Winter flounder Pseudopleuronectes americanus 39

Shrimp Metapenaeus sp. 40

Polychaete Neanthes arenaceodentata 41

Amphipod Echinogammarus olivii 42

Topsmelt Atherinops affinis 43

Spot Leiostomus xanthurus 44

Squid Loligo opalescens 45

### G

- 3

Organism Species Species

Number

Striped bass Morone saxatilis 46

Shrimp Crangon crangon 47

Pink shrimp Farfantepenaeus duorarum 48

Barnacle Balanus amphitrite 49

Barnacle Balanus eburneus 50

Hard clam Mercenaria mercenaria 51

Coho salmon Oncorhynchus kisutch 52

Sheepshead minnow Cyprinodon variegatus 53

Leon Springs pupfish Cyprinodon bovinus 54

Amphipod Allorchestes compressa 55

Mummichog Fundulus heteroclitus 56

Bristle star Ophionereis dubia 57

Shiner perch Cymatogaster aggregata 58

Polychaete Hediste diversicolor 59

Asian green mussel Perna viridis 60

Shore crab Carcinus maenas 61

Pompano Trachinotus carolinus 62

Tiger shrimp Penaeus monodon 63

Grooved snail Planaxis sulcatus 64

Whelk Turbo coronatus 65

Sheepshead Archosargus probatocephalus 66

Gastropod Crepidula convexa 67

Gastropod Crepidula fornicata 68

Isopod Sphaeroma serratum 69

Polychaete Eurythoe complanata 70

Copepod Amphiascoides atopus 71

Decapod Palaemon elegans 72

Sand crab Emerita analoga 73

Thornfish Terapon jarbua 74

Grass shrimp Palaemonetes pugio 75

Whiteleg shrimp Litopenaeus vannamei 76

Mud

- skipper Boleophthalmus sp. 77

Copepod Nitokra spinipes 78

Pinfish Lagodon rhomboides 79

Fat snook Centropomus parallelus 80

Striped mullet Mugil cephalus 81

Mangrove killifish Rivulus marmoratus 82

Atlantic croaker Micropogonias undulatus 83

Blue crab Callinectes sapidus 84

Amphipod Gammarus duebeni 85

Horseshoe crab Limulus polyphemus 86

Gulf toadfish Opsanus beta 87

Clam Rangia cuneata 88

Amphipod Corophium volutator 89

### H

- 1



## Appendix H Water Chemistry Used in BLM Analysis

### H

- 2

Normalizing the toxicity data with the marine BLM requires four water chemistry

parameters in seawater: salinity, pH, DOC, and temperature. The marine BLM calculation uses

all the same ions that are needed in the freshwater BLM (i.e., Ca, Mg, Na, K, SO 4 

### , Cl, and

alkalinity ), but these ion concentrations are calculated from salinity with the assump tion that ion

composition of marine waters is constant. To normalize the toxicity data included in this

document the complete BLM chemistry for each reported value is needed. If any of the four

marine BLM parameters were missing from the data source, value s for the missing parameters

were estimated.

Several strategies were used to in the process for determining suitable estimates for

missing parameters.

1. If the missing data were from a natural water body and other data were reported for the

same or similar location, then an average value from the reported values was used as an

estimate for missing values. Similarly, if the missing data were from a study in artificial

seawater and other studies reported chemistry for the same type of artificial seawater,

the n an average value from the reported chemistry was used to estimate missing values.

2. For DOC in artificial seawaters

, the reported DOC concentrations in Arnold et al. (2007)

were used for any test conducted in either Instant Ocean or Tropic Marin e salts.

3. If there were no other data for a location or artificial water, or the location was not given,

then default values were used. These values were 30 ppt of s alinity, pH of 7.8, 2.00 mg

C/L of DOC, and a temperature of 20°C. These values were chosen based on the typical

composition of seawater, and the average conditions reported in other toxicity tests.

### H

- 3

Appendix Table H

- 1

. Water Chemistry Used in BLM Analysis

.

BLM

Data

Label Genus Reported chemistry Reported plus assumed chemistry a

Source water type Salinity,

g/kg pH DOC,

mg C/L Temp,

°C Salinity,

g/kg pH DOC,

mg C/L Temp,

°C

1 Acartia 30 30.00 7.80 2.00 20.00

2 Acartia Artificial saltwater 30 10 30.00 7.80 2.00 10.00

4 Acartia Natural saltwater (location not given) 10 10.00 7.80 2.00 20.00

5 Aca rtia Natural saltwater (location not given) 10 10.00 7.80 2.00 20.00

6 Acartia Natural saltwater (location not given) 30 30.00 7.80 2.00 20.00

7 Aca rtia Natural saltwater (location not given) 30 20 30.00 7.80 2.00 20.00

12 Aiptasia Natural seawater, filtered (SW; Whitney Laboratory) 35.00 23.00 35.00 7.80 2.00 23.00

14 Al lorchestes Natural saltwater (location not given) 34.1 7.8 20.3 34.10 7.80 2.00 20.30

16 Americamysis Natural saltwater (location not given) 30 22.5 30.00 7.80 2.00 22.50

17 Am ericamysis Natural saltwater (Narragansett Bay, Narragansett, RI) 31 7.755 20 31.00 7.76 1.45 20.00

18 Americamysis Natural saltwater (Santa Rosa Sound, FL) 25 7.95 25 25.00 7.95 2.00 25.00

19 Am ericamysis Natural saltwater (Narragansett Bay, RI) 30 7 20 30.00 7.00 1.45 20.00

20 Americamysis Natural saltwater (Narragansett Bay, RI) 30 8 20 30.00 8.00 1.45 20.00

21 Am ericamysis Natural saltwater (Narragansett Bay, RI) 30 9 20 30.00 9.00 1.45 20.00

23 Americamysis 30 30.00 7.80 2.00 20.00

30 Ar chosargus Artificial saltwater (Sea Lakes Systems, Euclid, OH) 30 22 30.00 7.80 2.00 22.00

32 Argopecten Natural saltwater (location not given) 25 7.2 20 25.00 7.20 2.00 20.00

36 At herinops Natural saltwater (Granite Canyon, Monterey County, CA) 35 7.8 21 35.00 7.80 1.74 21.00

37 Atherinops Natural saltwater (Granite Canyon, Monterey County, CA) 35 7.8 21 35.00 7.80 1.74 21.00

38 At herinops Natural saltwater (Granite Canyon, Monterey County, CA) 35 7.8 21 35.00 7.80 1.74 21.00

44 Balanus Artificial saltwater 34 24 34.00 7.80 2.00 24.00

45 Ba lanus Artificial saltwater 34 24 34.00 7.80 2.00 24.00

46 Balanus Artificial saltwater 34 24 34.00 7.80 2.00 24.00

48 Bo leophthalmus Natural saltwater (location not given) 37.54 7.92 20 37.54 7.92 2.00 20.00

50 Brachionus Artificial saltwater (Instant Ocean®) 15 7.45 <1.0 25 15.00 7.45 1.00 25.00

51 Br achionus Artificial saltwater (Instant Ocean®) 15 7.45 <1.0 25 15.00 7.45 1.00 25.00

53 Brachionus Artificial saltwater (Instant Ocean®) 6 7.6 <0.5 25.05 6.00 7.60 0.50 25.05

54 Br achionus Artificial saltwater (Instant Ocean®) 11 7.6 <0.5 25.05 11.00 7.60 0.50 25.05

55 Brachionus Artificial saltwater (Instant Ocean®) 15 7.8 <0.5 25.05 15.00 7.80 0.50 25.05

56 Br achionus Artificial saltwater (Instant Ocean®) 24 7.9 <0.5 25.05 24.00 7.90 0.50 25.05

57 Brachionus Artificial saltwater (Instant Ocean®) 29 7.9 <0.5 25.05 29.00 7.90 0.50 25.05

58 Br achionus Natural saltwater (Little Egg Harbor, NJ) 7 6.8 4.1 25.05 7.00 6.80 4.10 25.05

59 Brachionus Natural saltwater (Little Egg Harbor, NJ) 7 8.3 4 25.05 7.00 8.30 4.00 25.05

60 Br achionus Natural saltwater (Little Egg Harbor, NJ) 13 7.6 1.7 25.05 13.00 7.60 1.70 25.05

61 Brachionus Natural saltwater (Little Egg Harbor, NJ) 13 8.6 1.7 25.05 13.00 8.60 1.70 25.05

65 Ca llinectes Natural saltwater (Cassino Beach, Rio Grande, Brazil) 2.00 7.12 0.41 20.10 2.00 7.12 0.41 20.10

66 Callinectes Natural saltwater (Cassino Beach, Rio Grande, Brazil) 30 7.28 5.20 20.30 30.00 7.28 5.20 20.30

### H

- 4

BLM

Data

Label Genus Reported chemistry Reported plus assumed chemistry a

Source water type Salinity,

g/kg pH DOC,

mg C/L Temp,

°C Salinity,

g/kg pH DOC,

mg C/L Temp,

°C

68 Ca ncer Natural saltwater (Big Sur, Monterey County, CA) 33.79 8.1 15 33.79 8.10 2.00 15.00

69 Cancer Natural saltwater ( Puget Sound at West Point, Seattle , WA) 30 8.1 8.5 30.00 8.10 1.46 8.50

71 Ca rcinus Natural saltwater (location not given) 15 30.00 7.80 2.00 15.00

79 Corophium Natural saltwater (Ythan estuary, Aberdeenshire, Scotland) 32 7.2 11 32.00 7.20 2.00 11.00

85 Cr angon Natural saltwater (location not given) 15 30.00 7.80 2.00 15.00

88 Crassostrea Natural seawater, unfiltered 33 8 13 33.00 7.80 2.00 20.00

89 Cr assostrea Natural saltwater (Monterey, CA) 33 8.2 20 33.00 8.20 2.00 20.00

90 Crassostrea Natural saltwater (Bodega Bay, CA) 30 7.6 1.68

(TOC) 20 30.00 7.60 1.68 20.00

93 Cr assostrea Natural saltwater (Bodega Bay, CA) 30 7.6 20 30.00 7.60 0.89 20.00

94 Crassostrea Natural saltwater (Big Sur, Monterey County, CA) 33.79 8.1 20 33.79 8.10 2.00 20.00

96 Cr assostrea Natural saltwater (U.C. Marine Laboratory, Bodega Bay, CA) 30 <0.5 16 30.00 7.60 0.50 16.00

97 Crassostrea Natural saltwater (U.C. Marine Laboratory, Bodega Bay, CA) 30 <0.5 16 30.00 7.60 0.50 16.00

106 C rassostrea Natural saltwater (location not given) 26 7.7 20 26.00 7.70 2.00 20.00

107 Crassostrea Natural saltwater (location not given) 26 7.7 25 26.00 7.70 2.00 25.00

108 C rassostrea Natural saltwater (location not given) 26 7.7 30 26.00 7.70 2.00 30.00

109 Crassostrea Natural and Artificial saltwater 29.8 7.75 0.8 25 29.80 7.75 0.80 25.00

110 C rassostrea Natural and Artificial saltwater 29.6 7.82 2.6 25 29.60 7.82 2.60 25.00

111 Crassostrea Natural and Artificial saltwater 29.7 7.92 3.9 25 29.70 7.92 3.90 25.00

112 C rassostrea Natural and Artificial saltwater 29.6 7.97 5.7 25 29.60 7.97 5.70 25.00

114 Crepidula Artificial saltwater (Instant Ocean) 30 20 30.00 7.43 0.20 20.00

116 C repidula Artificial saltwater (Instant Ocean) 30 20 30.00 7.43 0.20 20.00

118 Cymatogaster Natural saltwater ( Puget Sound at West Point, Seattle , WA) 29.5 7.8 13.2 29.50 7.80 1.46 13.20

120 C yprinodon Natural saltwater (ERLN, Narragansett, RI) 30 25 30.00 7.92 1.45 25.00

125 Dendraster Natural saltwater ( Puget Sound at West Point, Seattle , WA) 30 8.5 12.75 30.00 8.50 1.46 12.75

129 D endraster Natural and Artificial saltwater 32 7.85 1.2 15 32.00 7.85 1.20 15.00

130 Dendraster Natural and Artificial saltwater 32 7.84 2.1 15 32.00 7.84 2.10 15.00

131 D endraster Natural and Artificial saltwater 32 7.88 3.5 15 32.00 7.88 3.50 15.00

132 Dendraster Natural and Artificial saltwater 32 7.89 5 15 32.00 7.89 5.00 15.00

134 D iadema Natural saltwater 33 33.00 7.80 2.00 20.00

137 Echinogammarus Natural saltwater (location not given) 17 8.1 15 17.00 8.10 2.00 15.00

141 E lasmopus Artificial saltwater (Tropic Marine) 33 8.25 25 33.00 8.25 0.60 25.00

142 Elasmopus Artificial seawater (FAS; sea salt: Tropic Marine, Germany) 33.00 8.25 25.00 33.00 8.25 0.60 25.00

144 E merita Natural saltwater (Pingueral Beach, Concepcion, Chile) 30 7.9 15 30.00 7.90 2.00 15.00

151 Eurytemora 30 30.00 7.80 2.00 20.00

152 E urytemora Artificial saltwater 30 20 30.00 7.80 2.00 20.00

153 Eurytemora Natural saltwater (location not given) 30.00 7.80 2.00 20.00

154 E urytemora Natural saltwater (location not given) 30.00 7.80 2.00 20.00

155 Eurytemora Natural saltwater (location not given) 30.00 7.80 2.00 20.00

### H

- 5

BLM

Data

Label Genus Reported chemistry Reported plus assumed chemistry a

Source water type Salinity,

g/kg pH DOC,

mg C/L Temp,

°C Salinity,

g/kg pH DOC,

mg C/L Temp,

°C

156 E urytemora Natural saltwater (location not given) 30.00 7.80 2.00 20.00

157 Eurytemora Natural saltwater (location not given) 30.00 7.80 2.00 20.00

158 E urytemora Natural estuarine water (Choptank River, Cambridge, MA) 15.5 8.35 24.55 15.50 8.35 3.63 24.55

161 Eurytemora Natural estuarine water (Choptank River, Cambridge, MA) 2.5 7.95 3.31 25 2.50 7.95 3.31 25.00

162 E urytemora Natural estuarine water (Choptank River, Cambridge, MA) 5 8.28 2.39 25 5.00 8.28 2.39 25.00

163 Eurytemora Natural estuarine water (Choptank River, Cambridge, MA) 15 8.38 1.68 25 15.00 8.38 1.68 25.00

164 E urytemora Natural estuarine water (Choptank River, Cambridge, MA) 25 8.09 1.34 25 25.00 8.09 1.34 25.00

165 Eurytemora Natural estuarine water (Choptank River, Cambridge, MA) 10 8.1 2.48 25 10.00 8.10 2.48 25.00

166 E urytemora Natural estuarine water (Choptank River, Cambridge, MA) 10 8.17 3.8 25 10.00 8.17 3.80 25.00

167 Eurytemora Natural estuarine water (Choptank River, Cambridge, MA) 10 8.17 5.6 25 10.00 8.17 5.60 25.00

168 E urytemora Natural estuarine water (Choptank River, Cambridge, MA) 10 7.94 8.47 25 10.00 7.94 8.47 25.00

170 Eurythoe Natural saltwater (location not given) 36 7.8 36.00 7.80 2.00 20.00

172 F undulus Natural saltwater (Horseshoe Cove or Asbury Park, NJ) 5.5 20 5.50 7.80 2.00 20.00

173 Fundulus Natural saltwater (Horseshoe Cove or Asbury Park, NJ) 23.6 20 23.60 7.80 2.00 20.00

174 F undulus Natural saltwater (Horseshoe Cove or Asbury Park, NJ) 6.1 20 6.10 7.80 2.00 20.00

175 Fundulus Natural saltwater (Horseshoe Cove or Asbury Park, NJ) 24 20 24.00 7.80 2.00 20.00

176 F undulus Artificial saltwater (Instant Ocean TM) 14 26.5 14.00 7.43 0.20 26.50

178 Fundulus Natural saltwater (Bear Cut, FL) 2.5 7.67 2.497 25 2.50 7.67 2.50 25.00

179 F undulus Natural saltwater (Bear Cut, FL) 5 7.72 2.33 25 5.00 7.72 2.33 25.00

180 Fundulus Natural saltwater (Bear Cut, FL) 10 7.74 2.395 25 10.00 7.74 2.40 25.00

181 F undulus Natural saltwater (Bear Cut, FL) 15 7.88 2.588 25 15.00 7.88 2.59 25.00

182 Fundulus Natural saltwater (Bear Cut, FL) 22 7.96 2.438 25 22.00 7.96 2.44 25.00

183 F undulus Natural saltwater (Bear Cut, FL) 35 8.07 2.308 25 35.00 8.07 2.31 25.00

185 Gammarus Natural saltwater (location not given) 33 7.5 15 33.00 7.50 2.00 15.00

187 H aliotis Natural saltwater (location not given) 33 14 33.00 7.80 2.00 14.00

189 Haliotis Natural saltwater (location not given) 33 14 33.00 7.80 2.00 14.00

190 H aliotis Natural saltwater (location not given) 30.4 8 13 30.40 8.00 2.00 13.00

191 Haliotis Natural saltwater (location not given) 34.5 7.875 14.75 34.50 7.88 2.00 14.75

193 H ediste Natural saltwater (location not given) 5 7 5.00 7.80 2.00 7.00

194 Hediste Natural saltwater (location not given) 10 7 10.00 7.80 2.00 7.00

195 H ediste Natural saltwater (location not given) 17.5 7 17.50 7.80 2.00 7.00

196 Hediste Natural saltwater (location not given) 34 7 34.00 7.80 2.00 7.00

197 Hediste Natural saltwater (location not given) 7.3 12 7.30 7.80 2.00 12.00

198 Hediste Natural saltwater (location not given) 7.3 17 7.30 7.80 2.00 17.00

199 H ediste Natural saltwater (location not given) 7.3 22 7.30 7.80 2.00 22.00

200 Hediste Natural saltwater (location not given) 14.6 12 14.60 7.80 2.00 12.00

201 H ediste Natural saltwater (location not given) 14.6 17 14.60 7.80 2.00 17.00

202 Hediste Natural saltwater (location not given) 14.6 22 14.60 7.80 2.00 22.00

203 H ediste Natural saltwater (location not given) 21.9 12 21.90 7.80 2.00 12.00

### H

- 6

BLM

Data

Label Genus Reported chemistry Reported plus assumed chemistry a

Source water type Salinity,

g/kg pH DOC,

mg C/L Temp,

°C Salinity,

g/kg pH DOC,

mg C/L Temp,

°C

204 Hediste Natural saltwater (location not given) 21.9 17 21.90 7.80 2.00 17.00

205 H ediste Natural saltwater (location not given) 21.9 22 21.90 7.80 2.00 22.00

206 Hediste Natural saltwater (location not given) 29.2 12 29.20 7.80 2.00 12.00

207 H ediste Natural saltwater (location not given) 29.2 17 29.20 7.80 2.00 17.00

208 Hediste Natural saltwater (location not given) 29.2 22 29.20 7.80 2.00 22.00

209 H ediste Natural saltwater (location not given) 7.6 12 7.60 7.80 2.00 12.00

210 Hediste Natural saltwater (location not given) 7.6 17 7.60 7.80 2.00 17.00

211 H ediste Natural saltwater (location not given) 7.6 22 7.60 7.80 2.00 22.00

212 Hediste Natural saltwater (location not given) 15.25 12 15.25 7.80 2.00 12.00

213 H ediste Natural saltwater (location not given) 15.25 17 15.25 7.80 2.00 17.00

214 Hediste Natural saltwater (location not given) 15.25 22 15.25 7.80 2.00 22.00

215 H ediste Natural saltwater (location not given) 22.8 12 22.80 7.80 2.00 12.00

216 Hediste Natural saltwater (location not given) 22.8 17 22.80 7.80 2.00 17.00

217 H ediste Natural saltwater (location not given) 22.8 22 22.80 7.80 2.00 22.00

218 Hediste Natural saltwater (location not given) 30.5 12 30.50 7.80 2.00 12.00

219 H ediste Natural saltwater (location not given) 30.5 17 30.50 7.80 2.00 17.00

220 Hediste Natural saltwater (location not given) 30.5 22 30.50 7.80 2.00 22.00

221 H ediste Artificial saltwater (Tropic Marin Neu) 16.3 10 16.30 8.25 0.60 10.00

223 Holmesimysis Natural saltwater (location not given) 37 7.8 14 37.00 7.80 2.00 14.00

224 H olmesimysis Natural saltwater (Big Sur, Monterey County, CA) 36.5 7.8 13 36.50 7.80 2.00 13.00

226 Homarus Natural seawater (Narragansett Bay, RI) 30.5 20 30.50 7.92 1.45 20.00

230 H ydroides Artificial seawater (FAS; sea salt: Tropic Marine, Germany) 33.00 8.25 25.00 33.00 8.25 0.60 25.00

234 Lagodon Artificial saltwater (Sea Lakes Systems, Euclid, OH) 30 22 30.00 7.80 2.00 22.00

236 L eiostomus Natural saltwater (location not given) 20 25 20.00 7.80 2.00 25.00

237 Leiostomus Natural saltwater (location not given) 20 25.15 20.00 7.80 2.00 25.15

239 L itopenaeus Natural saltwater (Mazatlan Bay, Mexico) 34 8.05 27.2 34.00 8.05 2.00 27.20

243 Loligo Natural saltwater ( Puget Sound at West Point, Seattle , WA) 30 8.1 8.6 30.00 8.10 1.46 8.60

262 M enidia Artificial saltwater 27.5 8.05 24.9 27.50 8.05 2.00 24.90

263 Menidia Artificial saltwater 28 8.125 24.45 28.00 8.13 2.00 24.45

264 M enidia Artificial saltwater 29 8.03 24.4 29.00 8.03 2.00 24.40

266 Menidia Natural saltwater (ERL, Narragansett, RI) 31 19 31.00 7.92 1.45 19.00

267 M enidia Natural saltwater (ERL, Narragansett, RI) 30.4 18.5 30.40 7.92 1.45 18.50

268 Menidia Natural saltwater (ERL, Narragansett, RI) 31 20 31.00 7.92 1.45 20.00

269 M enidia Natural saltwater (ERL, Narragansett, RI) 30 20 30.00 7.92 1.45 20.00

271 Menidia Natural saltwater (location not given) 20 25 20.00 7.80 2.00 25.00

272 Menidia Natural saltwater (location not given) 20 25.25 20.00 7.80 2.00 25.25

274 Mercenaria Natural saltwater (location not given) 30.00 7.80 2.00 20.00

276 M etapenaeus Natural saltwater (location not given) 38 7.81 28 38.00 7.81 2.00 28.00

278 Micropogonias Artificial saltwater (Sea Lakes Systems, Euclid, OH) 30 22 30.00 7.80 2.00 22.00

### H

- 7

BLM

Data

Label Genus Reported chemistry Reported plus assumed chemistry a

Source water type Salinity,

g/kg pH DOC,

mg C/L Temp,

°C Salinity,

g/kg pH DOC,

mg C/L Temp,

°C

280 M orone Natural saltwater (location not given) 10 7.1 22 10.00 7.10 2.00 22.00

281 Morone Artificial saltwater (Instant Ocean) 5 7.9 20 5.00 7.90 0.20 20.00

282 M orone Artificial saltwater (Rila® Marine mix) 5 8.5 26 5.00 8.50 2.00 26.00

283 Morone Artificial saltwater (Rila® Marine mix) 10 8.4 26 10.00 8.40 2.00 26.00

284 M orone Artificial saltwater (Rila® Marine mix) 15 7.8 26 15.00 7.80 2.00 26.00

286 Mulinia Natural saltwater (Narragansett Bay, Narragansett, RI) 31 7.755 20 31.00 7.76 1.45 20.00

287 M ulinia Natural saltwater (Narragansett Bay, Narragansett, RI) 29 8.03 20 29.00 8.03 1.45 20.00

288 Mulinia Natural saltwater (Narragansett Bay, Narragansett, RI) 30 8.035 20 30.00 8.04 1.45 20.00

289 M ulinia Natural saltwater (Narragansett Bay, Narragansett, RI) 32 8.035 20 32.00 8.04 1.45 20.00

290 Mulinia Natural saltwater (Narragansett Bay, Narragansett, RI) 30.5 8.04 20 30.50 8.04 1.45 20.00

291 M ulinia Natural saltwater (Narragansett Bay, Narragansett, RI) 31.5 8.045 20 31.50 8.05 1.45 20.00

293 Mya Natural saltwater (Narragansett, RI) 30 7.95 22 30.00 7.95 1.45 22.00

295 M ytilus Natural saltwater (Calleguas Creek 1, Ventura County, CA) 30 5.1 30.00 7.80 5.10 20.00

296 Mytilus Natural saltwater (Calleguas Creek 1, Ventura County, CA) 30 8.6 30.00 7.80 8.60 20.00

297 M ytilus Natural saltwater (Calleguas Creek 1, Ventura County, CA) 30 9.7 30.00 7.80 9.70 20.00

298 Mytilus Natural saltwater (Calleguas Creek 2, Ventura County, CA) 30 4.8 30.00 7.80 4.80 20.00

299 M ytilus Natural saltwater (Calleguas Creek 2, Ventura County, CA) 30 6.6 30.00 7.80 6.60 20.00

300 Mytilus Natural saltwater (Calleguas Creek 2, Ventura County, CA) 30 10 30.00 7.80 10.00 20.00

301 M ytilus Natural saltwater (Mugu Lagoon 3, Ventura County, CA) 30 1.5 30.00 7.80 1.50 20.00

302 Mytilus Natural saltwater (Mugu Lagoon 3, Ventura County, CA) 30 7.3 30.00 7.80 7.30 20.00

303 M ytilus Natural saltwater (Mugu Lagoon 3, Ventura County, CA) 30 11 30.00 7.80 11.00 20.00

304 Mytilus Natural saltwater (Mugu Lagoon 4, Ventura County, CA) 30 1.4 30.00 7.80 1.40 20.00

305 M ytilus Natural saltwater (Mugu Lagoon 4, Ventura County, CA) 30 6.2 30.00 7.80 6.20 20.00

306 Mytilus Natural saltwater (Mugu Lagoon 5, Ventura County, CA) 30 2 30.00 7.80 2.00 20.00

307 M ytilus Natural saltwater (Mugu Lagoon 5, Ventura County, CA) 30 4.7 30.00 7.80 4.70 20.00

308 Mytilus Natural saltwater (Mugu Lagoon 5, Ventura County, CA) 30 12 30.00 7.80 12.00 20.00

309 M ytilus Natural saltwater (Mugu Lagoon 6, Ventura County, CA) 30 1.7 30.00 7.80 1.70 20.00

310 Mytilus Natural saltwater (Mugu Lagoon 6, Ventura County, CA) 30 3.4 30.00 7.80 3.40 20.00

311 M ytilus Natural saltwater (Mugu Lagoon 6, Ventura County, CA) 30 9.9 30.00 7.80 9.90 20.00

312 Mytilus Natural saltwater (Granite Canyon, Ventura County, CA) 30 1 30.00 7.99 1.00 15.70

313 M ytilus Natural saltwater (Granite Canyon, Ventura County, CA) 30 1.2 30.00 7.99 1.20 15.70

314 Mytilus Natural saltwater (Granite Canyon, Ventura County, CA) 30 2.9 30.00 7.99 2.90 15.70

315 M ytilus Natural saltwater (Granite Canyon, Ventura County, CA) 30 3.2 30.00 7.99 3.20 15.70

316 Mytilus Artificial saltwater (Crystal Sea Marinemix) 30 5.9 30.00 7.80 5.90 20.00

317 M ytilus Artificial saltwater (HW Marinemix) 30 0.4 30.00 7.80 0.40 20.00

318 Mytilus Artificial saltwater (General

- Purpose salt) 30 0.1 30.00 7.80 0.10 20.00

319 M ytilus Artificial saltwater (Kent Marine) 30.6 8.17 1.087 18 30.60 8.17 1.09 18.00

320 Mytilus Natural saltwater (Chesapeake Bay) 29.9 8.1 3.606 18 29.90 8.10 3.61 18.00

321 M ytilus Natural saltwater (San Diego Bay) 29.9 8.02 2.326 18 29.90 8.02 2.33 18.00

### H

- 8

BLM

Data

Label Genus Reported chemistry Reported plus assumed chemistry a

Source water type Salinity,

g/kg pH DOC,

mg C/L Temp,

°C Salinity,

g/kg pH DOC,

mg C/L Temp,

°C

322 Mytilus Natural saltwater (Tomales Bay) 30.2 7.8 3.374 18 30.20 7.80 3.37 18.00

323 M ytilus Natural saltwater ( Puget Sound) 29.5 7.52 1.88 18 29.50 7.52 1.88 18.00

324 Mytilus Natural saltwater (Coal Harbour) 30.2 7.44 3.327 18 30.20 7.44 3.33 18.00

325 Mytilus Natural saltwater (Arthur Kill) 29.9 7.78 6.936 18 29.90 7.78 6.94 18.00

326 Mytilus Natural saltwater (Potomac River) 29.9 8.02 3.183 18 29.90 8.02 3.18 18.00

327 M ytilus Natural saltwater (Halifax Harbour) 29.9 7.65 1.619 18 29.90 7.65 1.62 18.00

328 Mytilus Natural saltwater (Albemarle Sound) 30.2 7.58 6.934 18 30.20 7.58 6.93 18.00

331 M ytilus Natural saltwater (Big Sur, Monterey County, CA) 33.79 8.1 17 33.79 8.10 2.00 17.00

333 Mytilus Natural saltwater (location not given) 25 6.9

- 7.5 20 25.00 7.20 2.00 20.00

334 M ytilus Artificial saltwater 27.5 8.05 24.9 27.50 8.05 2.00 24.90

335 Mytilus Artificial saltwater 28 8.125 24.45 28.00 8.13 2.00 24.45

336 M ytilus Artificial saltwater 29 8.03 24.4 29.00 8.03 2.00 24.40

337 Mytilus Natural saltwater (Narragansett Bay, Narragansett, RI) 30.5 8.025 20 30.50 8.03 1.45 20.00

338 M ytilus Natural saltwater (Narragansett Bay, Narragansett, RI) 31.5 8.5 20 31.50 8.50 1.45 20.00

339 Mytilus Natural saltwater (Narragansett Bay, Narragansett, RI) 31.5 8.075 20 31.50 8.08 1.45 20.00

340 M ytilus Natural saltwater (Narragansett Bay, Narragansett, RI) 31.5 8.05 20 31.50 8.05 1.45 20.00

341 Mytilus Natural saltwater (Granite Canyon, CA) 28 8.1 15.25 28.00 8.10 1.74 15.25

342 M ytilus Natural saltwater (Granite Canyon, CA) 28 8.05 15.45 28.00 8.05 1.74 15.45

343 Mytilus Natural saltwater (Granite Canyon, CA) 28 8.2 15.05 28.00 8.20 1.74 15.05

344 M ytilus Natural saltwater (Granite Canyon, CA) 28 8.2 15 28.00 8.20 1.74 15.00

345 Mytilus Natural saltwater (Granite Canyon, CA) 28 8.05 15.15 28.00 8.05 1.74 15.15

346 M ytilus Natural saltwater (Granite Canyon, CA) 28 8.15 14.9 28.00 8.15 1.74 14.90

347 Mytilus Natural saltwater (Granite Canyon, CA) 28 8.15 15.4 28.00 8.15 1.74 15.40

348 M ytilus Natural saltwater (Granite Canyon, CA) 28 8 15.7 28.00 8.00 1.74 15.70

349 Mytilus Natural saltwater (Granite Canyon, CA) 28 7.85 15.4 28.00 7.85 1.74 15.40

350 M ytilus Natural saltwater (Granite Canyon, CA) 28 8 15.45 28.00 8.00 1.74 15.45

351 Mytilus Natural saltwater (Granite Canyon, CA) 28 8.1 15.15 28.00 8.10 1.74 15.15

352 M ytilus Natural saltwater (Granite Canyon, CA) 28 8.2 15.05 28.00 8.20 1.74 15.05

353 Mytilus Natural saltwater (Granite Canyon, CA) 28 8.05 15 28.00 8.05 1.74 15.00

354 M ytilus Natural saltwater (Granite Canyon, CA) 28 8.05 15.2 28.00 8.05 1.74 15.20

355 Mytilus Natural saltwater (Granite Canyon, CA) 27.9 8.05 14.85 27.90 8.05 1.74 14.85

356 M ytilus Natural saltwater (Granite Canyon, CA) 27.5 7.85 15.6 27.50 7.85 1.74 15.60

357 Mytilus Natural saltwater (Granite Canyon, CA) 27.5 7.85 15.45 27.50 7.85 1.74 15.45

358 M ytilus Natural saltwater (Granite Canyon, CA) 28 7.85 14.95 28.00 7.85 1.74 14.95

359 Mytilus Natural saltwater (Granite Canyon, CA) 28 7.95 15.1 28.00 7.95 1.74 15.10

360 M ytilus Natural saltwater (Granite Canyon, CA) 28.75 7.9 14.85 28.75 7.90 1.74 14.85

361 Mytilus Natural saltwater (Granite Canyon, CA) 28 7.75 15.35 28.00 7.75 1.74 15.35

362 M ytilus Natural saltwater (Granite Canyon, CA) 28 7.95 15.3 28.00 7.95 1.74 15.30

363 Mytilus Natural saltwater (Granite Canyon, CA) 28 8.15 14.8 28.00 8.15 1.74 14.80

### H

- 9

BLM

Data

Label Genus Reported chemistry Reported plus assumed chemistry a

Source water type Salinity,

g/kg pH DOC,

mg C/L Temp,

°C Salinity,

g/kg pH DOC,

mg C/L Temp,

°C

364 M ytilus Natural saltwater (Granite Canyon, CA) 34 8.2 14.55 34.00 8.20 1.74 14.55

365 Mytilus Natural saltwater (Granite Canyon, CA) 34 8.25 14.55 34.00 8.25 1.74 14.55

366 M ytilus Natural diluted saltwater ( Narragansett , RI) 20 7.85 16 20.00 7.85 1.45 16.00

367 Mytilus Natural diluted saltwater ( Narragansett , RI) 20 7.85 16 20.00 7.85 1.45 16.00

368 Mytilus Natural diluted saltwater ( Narragansett , RI) 20 7.85 16 20.00 7.85 1.45 16.00

369 Mytilus Natural saltwater (Granite Canyon Marine Lab., Carmel, CA) 30 7.82 0.5 30.00 7.82 0.50 15.70

370 M ytilus Natural saltwater (Granite Canyon Marine Lab., Carmel, CA) 30 7.82 0.9 30.00 7.82 0.90 15.70

371 Mytilus Natural saltwater (South San Francisco Bay, San Francisco, CA) 30 7.95 5.1 30.00 7.95 5.10 20.00

372 M ytilus Natural saltwater (South San Francisco Bay, San Francisco, CA) 30 7.95 5.2 30.00 7.95 5.20 20.00

373 Mytilus Natural saltwater (Granite Canyon and San Francisco Bay water) 30 7.91 2 30.00 7.91 2.00 15.70

374 M ytilus Natural saltwater (Granite Canyon and San Francisco Bay water) 30 7.91 2.2 30.00 7.91 2.20 15.70

375 Mytilus Natural saltwater (Granite Canyon and San Francisco Bay water) 30 7.98 3.5 30.00 7.98 3.50 15.70

376 M ytilus Natural saltwater (Granite Canyon and San Francisco Bay water) 30 7.98 3.8 30.00 7.98 3.80 15.70

380 Mytilus Natural saltwater (Granite Canyon, CA) 30 <1.5 30.00 7.99 1.50 15.70

381 M ytilus Natural saltwater (Granite Canyon, CA) 30 <1.5 30.00 7.99 1.50 15.70

382 Mytilus Natural saltwater (Granite Canyon, CA) 30 0.6 30.00 7.99 0.60 15.70

383 M ytilus Natural saltwater (Granite Canyon, CA) 30 0.6 30.00 7.99 0.60 15.70

384 Mytilus Natural saltwater (Granite Canyon, CA) 30 1 30.00 7.99 1.00 15.70

385 M ytilus Natural saltwater (Granite Canyon, CA) 30 1.2 30.00 7.99 1.20 15.70

386 Mytilus Natural saltwater (Granite Canyon, CA) 30 High 30.00 7.99 2.00 15.70

387 M ytilus Natural saltwater (Granite Canyon, CA) 30 0.3 30.00 7.99 0.30 15.70

388 Mytilus Natural saltwater (Granite Canyon, CA) 30 0.7 30.00 7.99 0.70 15.70

389 M ytilus Natural saltwater (Redwood Creek, San Francisco, CA) 30 2.6 30.00 7.95 2.60 20.00

390 Mytilus Natural saltwater (Redwood Creek, San Francisco, CA) 30 3.2 30.00 7.95 3.20 20.00

391 M ytilus Natural saltwater (Redwood Creek, San Francisco, CA) 30 2.3 30.00 7.95 2.30 20.00

392 Mytilus Natural saltwater (Redwood Creek, San Francisco, CA) 30 Low 30.00 7.95 1.00 20.00

393 M ytilus Natural saltwater (San Bruno, San Francisco, CA) 30 <1.5 30.00 7.95 1.50 20.00

394 Mytilus Natural saltwater (San Bruno, San Francisco, CA) 30 2.1 30.00 7.95 2.10 20.00

395 M ytilus Natural saltwater (San Bruno, San Francisco, CA) 30 2.2 30.00 7.95 2.20 20.00

396 Mytilus Natural saltwater (San Bruno, San Francisco, CA) 30 Low 30.00 7.95 1.00 20.00

397 M ytilus Natural saltwater (Central Bay

- midpoint, San Francisco, CA) 30 2 30.00 7.95 2.00 20.00

398 Mytilus Natural saltwater (Central Bay

- midpoint, San Francisco, CA) 30 3.2 30.00 7.95 3.20 20.00

399 M ytilus Natural saltwater (Central Bay

- midpoint, San Francisco, CA) 30 2.6 30.00 7.95 2.60 20.00

400 Mytilus Natural saltwater (Central Bay

- midpoint, San Francisco, CA) 30 3.5 30.00 7.95 3.50 20.00

401 M ytilus Natural saltwater (Central Bay

- nearshore, San Francisco, CA) 30 4.6 30.00 7.95 4.60 20.00

402 Mytilus Natural saltwater (Central Bay

- nearshore, San Francisco, CA) 30 3.3 30.00 7.95 3.30 20.00

403 M ytilus Natural saltwater (Central Bay

- nearshore, San Francisco, CA) 30 2.4 30.00 7.95 2.40 20.00

404 Mytilus Natural saltwater (Central Bay

- nearshore, San Francisco, CA) 30 Low 30.00 7.95 1.00 20.00

405 M ytilus Natural saltwater (Oyster Point, San Francisco, CA) 30 <1.5 30.00 7.95 1.50 20.00

### H

- 10

BLM

Data

Label Genus Reported chemistry Reported plus assumed chemistry a

Source water type Salinity,

g/kg pH DOC,

mg C/L Temp,

°C Salinity,

g/kg pH DOC,

mg C/L Temp,

°C

406 Mytilus Natural saltwater (Oyster Point, San Francisco, CA) 30 2.2 30.00 7.95 2.20 20.00

407 M ytilus Natural saltwater (Oyster Point, San Francisco, CA) 30 1.9 30.00 7.95 1.90 20.00

408 Mytilus Natural saltwater (Oyster Point, San Francisco, CA) 30 Low 30.00 7.95 1.00 20.00

409 M ytilus Natural saltwater (Yerba Beuna Island, San Francisco, CA) 30 <1.5 30.00 7.95 1.50 20.00

410 Mytilus Natural saltwater (Yerba Beuna Island, San Francisco, CA) 30 1.7 30.00 7.95 1.70 20.00

411 M ytilus Natural saltwater (Yerba Beuna Island, San Francisco, CA) 30 1.7 30.00 7.95 1.70 20.00

412 Mytilus Natural saltwater (Yerba Beuna Island, San Francisco, CA) 30 Low 30.00 7.95 1.00 20.00

413 M ytilus Natural saltwater (San Pablo Bay, San Francisco, CA) 30 2.1 30.00 7.95 2.10 20.00

414 Mytilus Natural saltwater (San Pablo Bay, San Francisco, CA) 30 4.9 30.00 7.95 4.90 20.00

415 M ytilus Natural saltwater (San Pablo Bay, San Francisco, CA) 30 2.1 30.00 7.95 2.10 20.00

416 Mytilus Natural saltwater (San Pablo Bay, San Francisco, CA) 30 1.8 30.00 7.95 1.80 20.00

417 M ytilus Natural saltwater (San Pablo Bay B15

- B20, San Francisco, CA) 30 1.5 30.00 7.95 1.50 20.00

418 Mytilus Natural saltwater (San Pablo Bay B15

- B20, San Francisco, CA) 30 8.1 30.00 7.95 8.10 20.00

419 M ytilus Natural saltwater (San Pablo Bay B15

- B20, San Francisco, CA) 30 2.8 30.00 7.95 2.80 20.00

420 Mytilus Natural saltwater (San Pablo Bay B15

- B20, San Francisco, CA) 30 2 30.00 7.95 2.00 20.00

421 M ytilus Natural saltwater (Petaluma River, San Francisco, CA) 30 3 30.00 7.95 3.00 20.00

422 Mytilus Natural saltwater (Petaluma River, San Francisco, CA) 30 9 30.00 7.95 9.00 20.00

423 M ytilus Natural saltwater (Petaluma River, San Francisco, CA) 30 4 30.00 7.95 4.00 20.00

424 Mytilus Natural saltwater (Petaluma River, San Francisco, CA) 30 2.3 30.00 7.95 2.30 20.00

425 M ytilus Natural saltwater (East San Pablo Bay

- midpoint, San Francisco,

CA) 30 1.7 30.00 7.95 1.70 20.00

426 Mytilus Natural saltwater (East San Pablo Bay

- midpoint, San Francisco,

CA) 30 4.8 30.00 7.95 4.80 20.00

427 M ytilus Natural saltwater (East San Pablo Bay

- midpoint, San Francisco,

CA) 30 2.2 30.00 7.95 2.20 20.00

428 Mytilus Natural saltwater (East San Pablo Bay

- midpoint, San Francisco,

CA) 30 2.6 30.00 7.95 2.60 20.00

429 M ytilus Natural saltwater (East San Pablo Bay

- nearshore, San Francisco,

CA) 30 2.3 30.00 7.95 2.30 20.00

430 Mytilus Natural saltwater (East San Pablo Bay

- nearshore, San Francisco,

CA) 30 4.5 30.00 7.95 4.50 20.00

431 M ytilus Natural saltwater (East San Pablo Bay

- nearshore, San Francisco,

CA) 30 2.5 30.00 7.95 2.50 20.00

432 Mytilus Natural saltwater (East San Pablo Bay

- nearshore, San Francisco,

CA) 30 2.2 30.00 7.95 2.20 20.00

433 M ytilus Natural saltwater (Pacheco Creek, San Francisco, CA) 30 1.7 30.00 7.95 1.70 20.00

434 Mytilus Natural saltwater (Pacheco Creek, San Francisco, CA) 30 9.6 30.00 7.95 9.60 20.00

435 M ytilus Natural saltwater (Pacheco Creek, San Francisco, CA) 30 2.9 30.00 7.95 2.90 20.00

436 Mytilus Natural saltwater (Grizzly Bay, San Francisco, CA) 30 2 30.00 7.95 2.00 20.00

### H

- 11

BLM

Data

Label Genus Reported chemistry Reported plus assumed chemistry a

Source water type Salinity,

g/kg pH DOC,

mg C/L Temp,

°C Salinity,

g/kg pH DOC,

mg C/L Temp,

°C

437 M ytilus Natural saltwater (Grizzly Bay, San Francisco, CA) 30 10 30.00 7.95 10.00 20.00

438 Mytilus Natural saltwater (Grizzly Bay, San Francisco, CA) 30 3.2 30.00 7.95 3.20 20.00

439 M ytilus Natural saltwater ( Puget Sound SUZ001, Bangor, WA) 30 1.4 30.00 7.99 1.40 11.00

440 Mytilus Natural saltwater ( Puget Sound HCB002, Bangor, WA) 30 1.1 30.00 7.99 1.10 11.00

441 M ytilus Natural saltwater (Galveston Bay

- Horsepen Bayou, Clear Lake,

TX) 30 8.7 30.00 7.80 8.70 20.00

442 Mytilus Natural saltwater (West Galveston Bay, Clear Lake, TX) 30 3.3 30.00 7.80 3.30 20.00

443 M ytilus Natural saltwater (Narragansett Bay

- USEPA Dock Low Tide,

Narragansett, RI) 30 1.5 30.00 7.92 1.50 17.00

444 Mytilus Natural saltwater (Narragansett Bay

- USEPA Dock High Tide,

Narragansett, RI) 30 1.4 30.00 7.92 1.40 17.00

446 M ytilus Natural saltwater (Granite Canyon Marine Lab., Carmel, CA) 30 7.82 0.7 30.00 7.82 0.70 15.70

447 Mytilus Natural saltwater (Granite Canyon Marine Lab., Carmel, CA) 30 7.82 1 30.00 7.82 1.00 15.70

448 M ytilus Natural saltwater (South San Francisco Bay, San Francisco, CA) 30 7.95 4.9 30.00 7.95 4.90 20.00

449 Mytilus Natural saltwater (South San Francisco Bay, San Francisco, CA) 30 7.95 5.7 30.00 7.95 5.70 20.00

450 M ytilus Natural saltwater (Granite Canyon and San Francisco Bay water) 30 7.91 1.9 30.00 7.91 1.90 15.70

451 Mytilus Natural saltwater (Granite Canyon and San Francisco Bay water) 30 7.91 2.2 30.00 7.91 2.20 15.70

452 M ytilus Natural saltwater (Granite Canyon and San Francisco Bay water) 30 7.98 3.3 30.00 7.98 3.30 15.70

453 Mytilus Natural saltwater (Granite Canyon and San Francisco Bay water) 30 7.98 3.8 30.00 7.98 3.80 15.70

454 M ytilus Natural saltwater (San Diego Bay, CA) 34.3 7.89 1.3 15.5 34.30 7.89 1.30 15.50

455 Mytilus Natural saltwater (San Diego Bay, CA) 34.1 7.85 1.7 15.3 34.10 7.85 1.70 15.30

456 M ytilus Natural and Artificial saltwater 29.8 7.75 0.8 25 29.80 7.75 0.80 25.00

457 Mytilus Natural and Artificial saltwater 29.6 7.82 2.6 25 29.60 7.82 2.60 25.00

458 M ytilus Natural and Artificial saltwater 29.7 7.92 3.9 25 29.70 7.92 3.90 25.00

459 Mytilus Natural and Artificial saltwater 29.6 7.97 5.7 25 29.60 7.97 5.70 25.00

460 M ytilus Natural and Artificial saltwater 32 7.85 1.2 15 32.00 7.85 1.20 15.00

461 Mytilus Natural and Artificial saltwater 32 7.84 2.1 15 32.00 7.84 2.10 15.00

462 M ytilus Natural and Artificial saltwater 32 7.88 3.5 15 32.00 7.88 3.50 15.00

463 Mytilus Natural and Artificial saltwater 32 7.89 5 15 32.00 7.89 5.00 15.00

469 N eanthes Natural saltwater (Narragansett Bay, Narragansett, RI) 31 17 31.00 7.92 1.45 17.00

470 Neanthes Natural saltwater (Narragansett Bay, Narragansett, RI) 31 17 31.00 7.92 1.45 17.00

472 N eanthes Natural saltwater (Narragansett Bay, Narragansett, RI) 31 19 31.00 7.92 1.45 19.00

474 Neomysis Artificial saltwater (Marine Environment®) 2 17 2.00 7.80 2.00 17.00

475 N eomysis Artificial saltwater (Marine Environment®) 2 17 2.00 7.80 2.00 17.00

476 Neomysis Artificial saltwater (Marine Environment®) 2 17 2.00 7.80 2.00 17.00

478 N itokra Natural brackish water (location not given) 7 8 20 7.00 8.00 2.00 20.00

481 Oncorhynchus Natural saltwater ( Puget Sound at West Point, Seattle , WA) 28.6 8.1 13 28.60 8.10 1.46 13.00

483 O phionereis Natural saltwater (location not given) 41.7 8.01 23 41.70 8.01 2.00 23.00

485 Opsanus Natural saltwater (Bear Cut, FL) 30 23 30.00 7.84 2.43 23.00

### H

- 12

BLM

Data

Label Genus Reported chemistry Reported plus assumed chemistry a

Source water type Salinity,

g/kg pH DOC,

mg C/L Temp,

°C Salinity,

g/kg pH DOC,

mg C/L Temp,

°C

487 P alaemon Natural saltwater (location not given) 17 8.1 15 17.00 8.10 2.00 15.00

489 Palaemonetes Natural saltwater (Santa Rosa Sound, Gulf Breeze, FL) 20 7.4 27 20.00 7.40 2.00 27.00

496 P aralichthys Natural saltwater (ERL, Narragansett, RI) 30 14 30.00 7.92 1.45 14.00

497 Paralichthys Natural saltwater (ERL, Narragansett, RI) 30 13 30.00 7.92 1.45 13.00

498 P aralichthys Natural saltwater (ERL, Narragansett, RI) 30 12 30.00 7.92 1.45 12.00

499 Paralichthys Natural diluted saltwater ( Narragansett , RI) 22 7.4 20 22.00 7.40 1.45 20.00

500 P aralichthys Natural diluted saltwater ( Narragansett , RI) 22 7.4 20 22.00 7.40 1.45 20.00

501 Paralichthys Natural diluted saltwater ( Narragansett , RI) 22 7.6 20 22.00 7.60 1.45 20.00

503 F arfantepenaeus Natural saltwater (Santa Rosa Sound, FL) 25 7.95 25 25.00 7.95 2.00 25.00

505 Anaitides Natural saltwater (location not given) 10 30.00 7.80 2.00 10.00

507 P lanaxis Natural saltwater (location not given) 36.91 7.8 27 36.91 7.80 2.00 27.00

509 Pseudodiaptomus 30 30.00 7.80 2.00 20.00

510 P seudodiaptomus Artificial saltwater 30 20 30.00 7.80 2.00 20.00

511 Pseudodiaptomus Artificial saltwater (Kester) 30 15 30.00 7.80 2.00 15.00

513 P seudopleuronectes Natural saltwater (ERL, Narragansett, RI) 30 5 30.00 7.92 1.45 5.00

514 Pseudopleuronectes Natural saltwater (ERL, Narragansett, RI) 28 5 28.00 7.92 1.45 5.00

515 P seudopleuronectes Natural saltwater (ERL, Narragansett, RI) 30 8 30.00 7.92 1.45 8.00

516 Pseudopleuronectes Natural saltwater (ERL, Narragansett, RI) 30 5 30.00 7.92 1.45 5.00

517 P seudopleuronectes Natural saltwater (ERL, Narragansett, RI) 30 4.5 30.00 7.92 1.45 4.50

518 Pseudopleuronectes Natural saltwater (ERL, Narragansett, RI) 30 5 30.00 7.92 1.45 5.00

526 Rangia Artificial saltwater (Instant Ocean) 5.5 24 5.50 7.43 0.20 24.00

527 Rangia Artificial saltwater (Instant Ocean) 22 24 22.00 7.43 0.20 24.00

529 R ivulus Artificial saltwater (Instant Ocean TM) 14 26.5 14.00 7.43 0.20 26.50

530 Rivulus Artificial saltwater (Instant Ocean TM) 14 26.5 14.00 7.43 0.20 26.50

532 S corpaenichthys Natural saltwater ( Puget Sound at West Point, Seattle , WA) 27 7.9 8.3 27.00 7.90 1.46 8.30

534 Sphaeroma Natural saltwater (location not given) 17 8.1 15 17.00 8.10 2.00 15.00

536 S pisula Natural saltwater (location not given) 25 7.2 20 25.00 7.20 2.00 20.00

538 Strongylocentrotus Natural saltwater ( Puget Sound at West Point, Seattle , WA) 30 7.95 8.3 30.00 7.95 1.46 8.30

543 S trongylocentrotus Natural saltwater ( Puget Sound at West Point, Seattle , WA) 30 7.95 8.3 30.00 7.95 1.46 8.30

547 Strongylocentrotus Natural saltwater (Granite Canyon, CA) 33.5 8.3 14.85 33.50 8.30 1.74 14.85

548 S trongylocentrotus Natural saltwater (Granite Canyon, CA) 33.5 8.3 14.95 33.50 8.30 1.74 14.95

549 Strongylocentrotus Natural saltwater (San Diego Bay, CA) 34.2 8.09 2.47 15.8 34.20 8.09 2.47 15.80

550 S trongylocentrotus Natural and Artificial saltwater 32 7.85 1.2 15 32.00 7.85 1.20 15.00

551 Strongylocentrotus Natural and Artificial saltwater 32 7.84 2.1 15 32.00 7.84 2.10 15.00

552 S trongylocentrotus Natural and Artificial saltwater 32 7.88 3.5 15 32.00 7.88 3.50 15.00

553 Strongylocentrotus Natural and Artificial saltwater 32 7.89 5 15 32.00 7.89 5.00 15.00

555 T erapon Natural saltwater (location not given) 7.9 28 30.00 7.90 2.00 28.00

557 Tigriopus Artificial saltwater (AQUIL) 35 8 16 35.00 8.00 2.00 16.00

558 T igriopus Artificial saltwater (AQUIL) 35 8 16 35.00 8.00 2.00 16.00

### H

- 13

BLM

Data

Label Genus Reported chemistry Reported plus assumed chemistry a

Source water type Salinity,

g/kg pH DOC,

mg C/L Temp,

°C Salinity,

g/kg pH DOC,

mg C/L Temp,

°C

559 Tigriopus Artificial saltwater (AQUIL) 35 8 16 35.00 8.00 2.00 16.00

560 T igriopus Artificial saltwater (AQUIL) 35 8 16 35.00 8.00 2.00 16.00

561 Tigriopus Artificial saltwater (AQUIL) 35 8 16 35.00 8.00 2.00 16.00

562 T igriopus Artificial saltwater (AQUIL) 35 8 16 35.00 8.00 2.00 16.00

563 Tigriopus Artificial saltwater (AQUIL) 35 8 16 35.00 8.00 2.00 16.00

564 T igriopus Artificial saltwater (AQUIL) 35 8 16 35.00 8.00 2.00 16.00

565 Tigriopus Artificial saltwater (AQUIL) 35 8 16 35.00 8.00 2.00 16.00

566 T igriopus Artificial saltwater (AQUIL) 35 8 16 35.00 8.00 2.00 16.00

567 Tigriopus Artificial saltwater (AQUIL) 35 8 16 35.00 8.00 2.00 16.00

568 T igriopus Artificial saltwater (AQUIL) 35 8 16 35.00 8.00 2.00 16.00

569 Tigriopus Artificial saltwater (AQUIL) 35 8 16 35.00 8.00 2.00 16.00

571 T isbe Natural saltwater (Drobak, Oslofjord, Norway) 34 8 13 34.00 8.00 2.00 13.00

573 Trachinotus Natural saltwater (Grand Isle, LA) 10 22.5 10.00 7.81 2.00 22.50

574 T rachinotus Natural saltwater (Grand Isle, LA) 20 22.5 20.00 7.81 2.00 22.50

575 Trachinotus Natural saltwater (Grand Isle, LA) 30 7.81 22.5 30.00 7.81 2.00 22.50

577 T urbo Natural saltwater (location not given) 37.43 8.17 27 37.43 8.17 2.00 27.00

730 Mytilus Natural uncontaminated seawater (assumed collected from the

Sinop Coast of the Black Sea, Turkey) 17.5 7.95 1.92%

-

TOC 15 17.50 7.95 2.00 15.00

731 M ytilus Natural uncontaminated seawater (assumed collected from the

Sinop Coast of the Black Sea, Turkey) 17.5 7.95 1.92%

-

TOC 15 17.50 7.95 2.00 15.00

732 Mytilus Natural uncontaminated seawater (assumed collected from the

Sinop Coast of the Black Sea, Turkey) 17.5 7.95 1.92%

-

TOC 15 17.50 7.95 2.00 15.00

733 Mytilus Natural uncontaminated seawater (assumed collected from the

Sinop Coast of the Black Sea, Turke y) 17.5 7.95 15 17.50 7.95 2.00 15.00

734 Acartia Artificial salt water 5 6.88 <0.1 20 5.00 6.88 0.10 20.00

735 A cartia Artificial salt water 15 7.21 <0.1 20 15.00 7.21 0.10 20.00

736 Acartia Artificial salt water 30 7.49 <0.1 20 30.00 7.49 0.10 20.00

737 A mphiascoides Artificial salt water, Instant Ocean Sea Salt, USA 30 23 30.00 7.43 0.20 23.00

738 Amphiascoides Artificial salt water, Instant Ocean Sea Salt, USA 30 23 30.00 7.43 0.20 23.00

739 A mphiascoides Artificial salt water, Instant Ocean Sea Salt, USA 30 23 30.00 7.43 0.20 23.00

740 Amphiascoides Artificial salt water, Instant Ocean Sea Salt, USA 30 23 30.00 7.43 0.20 23.00

741 B alanus Filtered natural sea water (assumed collected at Ionian Sea,

southern Italy) 37 20 37.00 7.80 2.00 20.00

742 Balanus Filtered natural sea water (assumed collected at Ionian Sea,

southern Italy) 37 20 37.00 7.80 2.00 20.00

743 P enaeus Filtered natural saltwater (collected from unpolluted site in

Neelangarai, India) 28 7.78 28 28.00 7.78 2.00 28.00

744 Mugil Natural filtered se a water (source ) 28 7.78 28 28.00 7.78 2.00 28.00

745 B rachionus Artificial salt water, Instant Ocean Sea Salt, USA 4 6.3 1.4 25 4.00 6.30 1.40 25.00

### H

- 14

BLM

Data

Label Genus Reported chemistry Reported plus assumed chemistry a

Source water type Salinity,

g/kg pH DOC,

mg C/L Temp,

°C Salinity,

g/kg pH DOC,

mg C/L Temp,

°C

746 Brachionus Artificial salt water, Instant Ocean Sea Salt, USA 14 6.9 1.4 25 14.00 6.90 1.40 25.00

747 B rachionus Artificial salt water, Instant Ocean Sea Salt, USA 26 7.8 1.4 26 26.00 7.80 1.40 26.00

748 Brachionus Artificial salt water, Instant Ocean Sea Salt, USA 14 6.6 1.4 25 14.00 6.60 1.40 25.00

749 B rachionus Artificial salt water, Instant Ocean Sea Salt, USA 14 6.7 5 25 14.00 6.70 5.00 25.00

750 Brachionus Artificial salt water, Instant Ocean Sea Salt, USA 14 6.9 10 25 14.00 6.90 10.00 25.00

751 C entropomus Natural filtered estuarine water from the Piraqueacu River, Brazil 32.2 7.58 24.6 32.20 7.58 2.00 24.60

752 Mytilus Natural estuarine water (Nieuwpoort, Belgium) + DI water +

artificial sea water 22.9 3 16 22.90 7.80 3.00 16.00

753 M ytilus Natural estuarine water (Nieuwpoort, Belgium) + DI water +

artificial sea water 24.7 1.24 16 24.70 7.80 1.24 16.00

754 Mytilus Natural estuarine water (Nieuwpoort, Belgium) + DI water +

artificial sea water 25.1 3.92 16 25.10 7.80 3.92 16.00

755 M ytilus Natural estuarine water (Nieuwpoort, Belgium) + DI water +

artificial sea water 29.8 0.56 16 29.80 7.80 0.56 16.00

756 Mytilus Natural estuarine water (Nieuwpoort, Belgium) + DI water +

artificial sea water 29.8 4.66 16 29.80 7.80 4.66 16.00

757 M ytilus Natural estuarine water (Nieuwpoort, Belgium) + DI water +

artificial sea water 29.9 2.8 16 29.90 7.80 2.80 16.00

758 Mytilus Natural estuarine water (Nieuwpoort, Belgium) + DI water +

artificial sea water 30 2.8 16 30.00 7.80 2.80 16.00

759 M ytilus Natural estuarine water (Nieuwpoort, Belgium) + DI water +

artificial sea water 34.9 1.46 16 34.90 7.80 1.46 16.00

760 Brachionus Recon saltwater + natural saltwater (Bouctouche) 30.1 8 4.83 25 30.1 8 4.83 25

761 Brachionus Recon saltwater + natural saltwater (Petit Rocher) 30.2 8 2.1 25 30.2 8 2.1 25

762 Brachionus Recon saltwater + natural saltwater (Major Kollock Creek) 29.9 8 7.57 25 29.9 8 7.57 25

763 Brachionus Recon saltwater + natural saltwater (Naufrage Harbour) 29.9 8 5.2 25 29.9 8 5.2 25

764 Brachionus Recon saltwater + natural saltwater (Rathtrevor Beach) 30.1 8 1.37 25 30.1 8 1.37 25

765 Brachionus Recon saltwater + natural saltwater (Hawke's Bay) 30 8 1.28 25 30 8 1.28 25

766 Brachionus Recon saltwater + natural saltwater (Blackberry Bay) 29.9 8 2.03 25 29.9 8 2.03 25

767 Brachionus Recon saltwater + natural saltwater (Chesterman Beach) 30.1 8 0.55 25 30.1 8 0.55 25

768 Brachionus Recon saltwater + natural saltwater (Jimbo) 30.1 8 1.13 25 30.1 8 1.13 25

769 M ytilus Artificial seawater (ASTM 2004) 36 7.9

- 8.1 16 36 8 2 16

770 Mytilus Artificial seawater (ASTM 2004) 36 7.9

- 8.1 16 36 8 2 16

771 Perna Natural seawater (Neelangarai, India) 28 7.78 28 28 7.78 2 28

772 Nitokra Natural seawater 7 4.7

(TOC) 22 7 7.8 4.7 22

773 O rchomenella Natural seawater (source not defined) 33 10 33 7.8 2 10

774 Penaeus Natural seawater (Neelangarai, India) 28 7.78 28 28 7.78 2 28

775 L imulus Artificial seawater (Instant Ocean) 20 6.7

- 9.0 18

- 29 20 7.85 0.2 23.5

### H

- 15

BLM

Data

Label Genus Reported chemistry Reported plus assumed chemistry a

Source water type Salinity,

g/kg pH DOC,

mg C/L Temp,

°C Salinity,

g/kg pH DOC,

mg C/L Temp,

°C

776 Limulus Artificial seawater (Instant Ocean) 20 6.7

- 9.0 18

- 29 20 7.85 0.2 23.5

777 L imulus Artificial seawater (Instant Ocean) 20 6.7

- 9.0 18

- 29 20 7.85 0.2 23.5

778 Arbacia Natural seawater (source not provided) 30 8.01

- 8.06 20 30 8.035 2 20

779 C yprinodon Natural seawater (Gulf of Mexico) + DI water 2 20 2 7.8 2 20

780 Cyprinodon Natural seawater (Gulf of Mexico) + DI water 15 20 15 7.8 2 20

781 C yprinodon Natural seawater (Gulf of Mexico) + DI water 2 20 2 7.8 2 20

782 Cyprinodon Natural seawater (Gulf of Mexico) + DI water 15 20 15 7.8 2 20

C1 Brachionus Artificial saltwater (Instant Ocean) 15 7.3

- 7.6 <1.0 23.9

-

26.1 15 7.45 1 25

C2 Cyprinodon Natural saltwater (ERLN, Narragansett, RI) 28

- 32 23

- 27 30 7.92 1.45 25



### a Given the relatively constant composition of marine waters, average values were reasonable estimates for missing parameters i n a given toxicity test.

### H

- 16

Appendix Table H

- 2

. Summary Statistics of the Reported Water Chemistry for the

Acceptable Toxicity Tests

.

Salinity

( g/kg ) pH DOC

( mg C/L ) Temp erature

( °C )

Minimum 2.0 6.3 0.1 4.5

Maximum 41.7 9.0 12.0 30.0

Average 26. 5 7.9 3.3 19.0



### Appendix Table H

- 3 . Average Chemistry

Location Salinity

(g/kg) pH DOC

(mg C/L) Temp erature

( ° C)

Narragansett 7.92 1.45 17

Puget 7.99 1.46 11

Granite Canyon 7.99 1.74 15.7

Grand Isle 7.81

Bodega 7.6 0.893

San Francisco 7.95

Black Sea 2

Cambridge 3.63

Bear Cut 7.84 2.43

Instant Ocean 1 

### 7.43 0.2

Tropic Marin 1 

### 8.25 0.6

default 30 7.8 2 20

1 

### B ased on Arnold et al. 2007

.

### I

- 1



## Appendix I Discussion of BLM Water Quality Parameters in the

Estuarine/Marine Environment and Example Numeric

Criteria Values

### I

- 2

The pH of marine environments is relatively stable, where pH typically remains between

7.5 and 8.4 (Sverdrup et al. 1942). H owever, regional factors can temporarily affect pH in these

systems. For example, the upwelling of deeper more acidic waters along the west coast of North

America can temporarily lower the pH of surface waters (Feely et al. 2008). In comparison, pH

is much more variable in estuaries, embayments, harbors, and other semi

- enclosed coastal

systems. The influx of freshwater from rivers, groundwater, and surficial runoff can lower the

pH of these systems , based on the typically lower pH of freshw ater (around 7) ( Caldeira and

Wickett 2003). Photosynthesis, meanwhile, can incre ase pH levels and algal blooms have been

reported to increase pH l evels above 9 in some estuaries, t o the point where pH becomes lethal to

aquatic species (Hansen 2002).

The salinity of marin e systems is also relatively stable, with an average salinity of 35 ppt

and range of 32 to 38 ppt across the world’s oceans (Kalle 1971). Salinity within coastal waters

can have greater variability, due primarily to the input of freshwater from rivers, sur ficial runoff,

groundwater input, and tidal and coastal currents

. S alinity can also vary a s a result of diurnal,

seasonal, and annual cycles and episodic occur rences (e.g, storm events ) . Salin ity in semi

enclosed systems, including estu aries, embayments, a nd harbors can have extreme variability

over space and time, and can have salinity ranging from saline to freshwater (<2 ppt). In the

Cheseapeake Bay, for example, average salinity ranges from freshwater (<0.5 ppt) in the upper

reaches of the Bay to full marine salinity adjacent to the Atlantic Ocean (VIMS 2016). Salinity

typically decreases in the Chesapeake Bay during the spring, with increased freshwater inputs

resulting from rain and snowmelt

, and increases during the summer with increasing levels of

e vaporation (Levinton 2001). Inputs (e.g., municipal discharges) and changes in water flow

patterns as a result of anthropogenic activity can also significantly affect the salinity of estuarine

and marine systems

.

DOC in estuarine and marine systems in mos t cases reflects a diversity of inputs from

allochthonous and autochthonous sources that can originate from both terrestrial and aquatic

autotrophs (inclusive of unicellular algae and vascular plants) and heterotrophs (inclusive of

bacteria, fungi, and mul ticellular organisms) (Bauer and Bianchi 2011 ; Cloern 1996 ; Raymond

and Bauer 2001 ; Cauwet 2002 ; Aitkenhead

- Peterson et al. 2003 ; Bertilsson and Jones 2003). The

highest DOC concentrations are generally found in estuarine and associated riverine systems,

w ith DOC concentrations generally decreas ing with movement from the estuarine to marine

### I

- 3

environment (Bauer and Bianchi 2011). DOC concentr ations within estuarine and riverine

systems can vary greatly , with some of the highest known DOC concentrations occurr ing in

estuaries within the Gulf of Mexico, where DOC concentrations of greater than 1,000 μ M

(equivalent to approximately 12 mg/L) have been reported (Bauer and Bianchi 2011 ; Guo et al.

1999 ; Engelhaupt and Bianchi 2001). Although variable both spatially and temporally,

representative DOC values reported for most other estuarine and riverine systems are lower,

examples of which include Galveston Bay (145

- 469 μ M, equivalent to approximately 1.7

- 5.6

mg/L), Chesapeake Bay (118

- 215 μ M, equivalent to approximat ely 1.4

- 2.6 mg/L), and

Potomac/Patuxent River (92

- 333 μ M, equivalent to approximately 1.1

- 4.0 mgL ) (Guo and

Santschi 1997 ; Sigleo 1996).

River ine systems and adjacent wetlands frequently represent important sources of DOC

to estuarine and adjacent coasta l ecosystems (Del Giorgio and Pace 2008). The magnitude of

temporal variability in DOC loading within these systems has been shown to be related to the

predomi nant source of DOC (Bianchi et al. 1998, Mantoura and Woodward 1983, Thurman

1985). For example, fringing w etlands have been demonstrated to provide a mor e consistent

source of DOC than phytoplankton blooms (Bianchi et al. 1998 ; Mantoura and Woodward 1983 ;

Thurman 1985)

. Anthropogenic inputs of DOC via municipal and industrial discharge can also

alter the DOC present in estuarine and near coastal environments, either directly through the

discharge of DOC or indirectly, such as via the discharge of nutrients which can then increase

primary productivity.

Removal of DOC via flocculation typically occurs with the increasing ionic strength of

higher salinity environments (Guo et al. 1999). In coastal and marine environments, DOC is

mostly produced by biological processes (prim ary and secondary production) in the upper ocean,

and is then mixed downward and diluted by physical processes (Hansell and Carlson 2001).

Seasonal increases in DOC concentrations can occur as a result of phytoplankton blooms,

particularly in areas with st ratification that receive nutrient inputs during the winter (Hansell and

Carlson 2001). Deep ocean waters generally have the lowest DOC concentrations , reaching

levels of 2 μ M (equivalent to approximately 0.02 mg/L) or less. DOC concentrations thus tend to

be reduced in upwelling areas where deep waters dilute the surface water concentrations, even

when primary production levels are relatively high (Hansell and Carlson 2001).

### I

- 4

Marine water temperatures generally range from

- 2 ° C to 28 ° C, with some higher

tem peratures occurring seasonally in estuarine systems. T emperature is , in general, a function of

solar input , with higher tempera tures typically occurring at lower latitudes and during the

summer. Water temperatures in near coastal environments and semi

- encl osed systems such as

estuaries, embayments, and harbors typically have some of the greatest variability. This

variability is due primarily to the input of freshwater from rivers, sur ficial runoff, groundwater

discharge

, the shallower waters frequently pres ent in these systems, and tidal and coastal

currents. Temperatures in coa stal and open water marine environments often vary with different

,

frequently stratified wat er layers that are characterized by differing temperature and salinity.

Upwelling and curre nt patterns in these stratified systems can lead to local and regional alteration

in the temperature profile, such as observed with the California Current, w h ere cooler deeper

waters are brought to the surface and significantly reduce the surface water tem perature profile.

The following tables provide representative example saltwater BLM CMC and CCC

values determined with different temperature, pH, salinity, and DOC conditions.

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Appendix Table I

- 1 . Example BLM Numeric Criteria Values at 20°C and pH 7.8.

Salinity

(ppt) DOC

(mg C/L) FAV

( μg /L) CMC

( μg /L) CCC

( μg /L)

5 1 3.294 1.6 1.1

2 6.585 3.3 2.2

4 13.16 6.6 4.4

6 19.75 9.9 6.5

8 26.33 13 8.7

10 32.91 16 11

10 1 3.423 1.7 1.1

2 6.847 3.4 2.3

4 13.68 6.8 4.5

6 20.52 10 6.8

8 27.37 14 9.1

10 34.21 17 11

15 1 3.545 1.8 1.2

2 7.090 3.5 2.3

4 14.17 7.1 4.7

6 21.26 11 7.0

8 28.35 14 9.4

10 35.44 18 12

20 1 3.662 1.8 1.2

2 7.318 3.7 2.4

4 14.64 7.3 4.8

6 21.96 11 7.3

8 29.27 15 9.7

10 36.59 18 12

25 1 3.776 1.9 1.2

2 7.550 3.8 2.5

4 15.09 7.5 5.0

6 22.64 11 7.5

8 30.17 15 10

10 37.72 19 12

30 1 3.887 1.9 1.3

2 7.771 3.9 2.6

4 15.54 7.8 5.1

6 23.29 12 7.7

8 31.07 16 10

10 38.84 19 13

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- 6

Appendix Table I

- 2

. Example BLM Numeric Criteria Values at 20°C and pH 8. 0.

Salinity

(ppt) DOC

(mg C/L) FAV

( μg /L) CMC

( μg /L) CCC

( μg /L)

5 1 3.324 1.7 1.1

2 6.647 3.3 2.2

4 13.29 6.6 4.4

6 19.93 10 6.6

8 26.58 13 8.8

10 33.20 17 11

10 1 3.446 1.7 1.1

2 6.886 3.4 2.3

4 13.77 6.9 4.6

6 20.66 10 6.8

8 27.54 14 9.1

10 34.41 17 11

15 1 3.563 1.8 1.2

2 7.121 3.6 2.4

4 14.24 7.1 4.7

6 21.36 11 7.1

8 28.48 14 9.4

10 35.60 18 12

20 1 3.678 1.8 1.2

2 7.352 3.7 2.4

4 14.70 7.3 4.9

6 22.04 11 7.3

8 29.38 15 9.7

10 36.73 18 12

25 1 3.790 1.9 1.3

2 7.574 3.8 2.5

4 15.14 7.6 5.0

6 22.70 11 7.5

8 30.26 15 10

10 37.84 19 13

30 1 3.900 1.9 1.3

2 7.794 3.9 2.6

4 15.58 7.8 5.2

6 23.36 12 7.7

8 31.16 16 10

10 38.95 19 13

### I

- 7

Appendix Table I

- 3

. Example BLM Numeric Criteria Values at 20°C and pH 8. 2

. Salinity

(ppt) DOC

(mg C/L) FAV

( μg /L) CMC

( μg /L) CCC

( μg /L)

5 1 3.279 1.6 1.1

2 6.550 3.3 2.2

4 13.10 6.5 4.3

6 19.65 9.8 6.5

8 26.20 13 8.7

10 32.75 16 11

10 1 3.387 1.7 1.1

2 6.769 3.4 2.2

4 13.53 6.8 4.5

6 20.28 10 6.7

8 27.04 14 8.9

10 33.78 17 11

15 1 3.494 1.7 1.2

2 6.978 3.5 2.3

4 13.94 7.0 4.6

6 20.91 10 6.9

8 27.87 14 9.2

10 34.85 17 12

20 1 3.600 1.8 1.2

2 7.187 3.6 2.4

4 14.37 7.2 4.8

6 21.55 11 7.1

8 28.72 14 9.5

10 35.90 18 12

25 1 3.705 1.9 1.2

2 7.396 3.7 2.4

4 14.78 7.4 4.9

6 22.17 11 7.3

8 29.55 15 9.8

10 36.94 18 12

30 1 3.810 1.9 1.3

2 7.606 3.8 2.5

4 15.20 7.6 5.0

6 22.79 11 7.5

8 30.39 15 10

10 37.95 19 13