EPA’s Review of Revised 2016 Freshwater Acute Cadmium Criterion for Oregon in 

accordance with the Reasonable and Prudent Alternatives in the National Marine 

Fisheries Service 2012 Biological Opinion on Oregon’s Toxic Water Quality Standards

The information provided in this document addresses the process for deriving a criterion specified in the 

reasonable and prudent alternative (RPA) for Oregon’s freshwater acute cadmium criterion, contained in the 

National Marine Fisheries Service (NMFS) 2012 biological opinion.1

BACKGROUND INFORMATION

On May 20, 2004, the Oregon Environmental Quality Commission (EQC) adopted 89 new and revised criteria 

for 25 chemicals. The freshwater acute cadmium (Cd) criterion was one of the revised criteria included in 

Oregon’s adoption. Oregon submitted their revisions to the Environmental Protection Agency (EPA) for review 

and action on July 8, 2004. At that time, the freshwater acute cadmium criterion adopted by Oregon was 

consistent with the EPA’s 304(a) recommendation.2

The EPA submitted a biological evaluation of the effects of the revised freshwater acute cadmium criterion to 

the NMFS on January 14, 2008. On August 14, 2012, the NMFS completed their biological opinion and found 

the revised freshwater acute cadmium criterion would jeopardize the continued existence of endangered 

salmonids. The NMFS 2012 biological opinion contains a process for deriving a freshwater acute cadmium 

criterion which is intended to avoid jeopardizing the continued existence of listed species or the destruction or 

adverse modification of designated critical habitat.

On January 31, 2013, EPA took formal action under the Clean Water Act to approve, in part, and disapprove, in 

part, Oregon’s toxics criteria for aquatic life. EPA approved 38 of the 833 new and revised water quality criteria 

and disapproved 45 of the 83 new and revised water quality criteria that Oregon adopted. The disapproval 

action included the freshwater acute cadmium criterion that was evaluated in the NMFS jeopardy opinion.

I. RPA ANALYSIS

Introduction:

The RPA steps in the NMFS 2012 biological opinion outlined a process for deriving an acute cadmium

criterion (see Appendix A for the language contained in the RPA). The process can be summarized in the

following steps:

1. Use toxicity data specific to salmonids. If new toxicity data becomes available for green sturgeon and 

eulachon then this data should be used in the analysis.

2. Toxicity data must be curve-fitted where the literature provides the necessary raw data. Note: in this 

document the term “curve-fitted” is referred to as the “concentration-response (C-R) curve.”

3. The curve-fitted data, or concentration-response curve, must be used to extrapolate a threshold acute 

effects concentration. For example, if the threshold effect is considered to be at the LC05, the 

1 Jeopardy and Adverse Modification of Critical Habitat Biological Opinion for the Environmental protection Agency’s Proposed

Approval of Certain Oregon Administrative Rules Related to Revised Water Quality Criteria for Toxic Pollutants, NMFS, August 14,

2012. 2 EPA’s 304(a) recommendation was the 2001 Update of Ambient Water Quality Criteria for Cadmium, EPA-822-R-01-001, April 2001.

3 In 2007, Oregon made corrections to their water quality standards and inadvertently removed 6 aquatic life criteria from their

standards (acute and chronic freshwater and saltwater arsenic, and acute and chronic saltwater chromium VI). Therefore, in, 2013,

EPA acted on 83 of Oregon’s original criteria (i.e., 89 minus 6). Oregon re-adopted these 6 criteria into their water quality standards

in January 2014. EPA successfully completed ESA consultation and approved the re-adoption of these 6 criteria in February 2014.

1

 
concentration on the curve associated with the LC05 would be considered the threshold effect.4 The 

minimum effects threshold shall be used to derive the criteria instead of using the EPA acute adjustment 

factor or the acute-to-chronic ratio to derive criteria.5

4. Derived criteria must be model-adjusted to account for chemical mixtures.

5. An appropriate population model must be applied to the derived criteria, and must predict no negative 

change in the intrinsic population growth rate.

Section A below addresses RPA steps 1 through 3 (i.e., deriving an acute criterion based on the minimum 

threshold effect from the concentration-response curve), Section B addresses RPA step 4 (i.e., mixtures 

analysis), and Section C addresses RPA step 5 (i.e., population model).

A. Process for Deriving Acute Cadmium Criterion from Toxicity Studies for Salmonids

EPA performed the following C-R curve analysis to derive minimum effect thresholds (i.e., LC10 and LC05) for

salmonids in order to meet RPA steps 1-3 (below) specifically pertaining to acute cadmium. As stated in the 

NMFS 2012 biological opinion:

“...EPA shall derive criteria for acute ammonia, acute cadmium, and acute and chronic aluminum in 

compliance with the following five requirements: 

1) Only use toxicity data for ammonia, cadmium, and aluminum that is specific to salmonid fishes 

(if new information becomes available for these compounds for green sturgeon and eulachon, 

then EPA shall include this data in its analysis); 

2) All toxicity data used to derive the numeric criteria must be curve-fitted, where the literature 

provides the necessary data to perform this step; 

3) When available, the curve-fitted toxicity data must be used to extrapolate threshold acute and 

chronic toxic effect concentrations;...” 

When performing the C-R analysis to fulfill the RPAs above, EPA also considered the acute aspects of the 

specifics discussed in the NMFS 2012 biological opinion below. 

“More specifically, EPA shall ensure that the derived criteria are developed in compliance with the 

following mandatory sideboards: 

The EPA shall use toxicity data specific to salmonid fishes. The EPA shall use the acute and chronic 

toxicity data in this opinion as a minimum data set. For green sturgeon and eulachon, EPA shall use the 

salmonid fishes toxicity data for this analysis, as described in section 2.6.2 in this opinion, in addition to 

any new data that becomes available for green sturgeon and eulachon. 

The EPA shall use toxicity data based on exposure-response curves and fixed duration toxicity tests to 

estimate acute and chronic toxic effect thresholds to assess effects on multiple life stages and multiple 

endpoints, to include at a minimum: mortality, latent mortality, reproduction, growth, physiological, 

cellular, behavioral, and biochemical effects, where the data exists. The EPA may use existing toxicity 

data for ammonia, cadmium, and aluminum or generate new data, but the data shall be curve-fitted (see 

4 The LC05 is the concentration of a pollutant that would be lethal to 5% of the individuals in toxicity tests.

5 If the raw data is provided in a toxicity test, EPA can (1) calculate a concentration-response curve for each individual toxicity test

using the Toxicity Relationship Analysis Program (TRAP, version 1.30a) to generate LC05 and LC10 values, and (2) use the 

geometric mean of the LC05 and LC10 values for each genus or species (if only one genus) to generate a species distribution (SD) 

curve (a minimum of 15 data points is needed to develop a SD) to calculate the “minimum effect threshold” NMFS requested in 

the RPA.

2

 
Figure 2.6.1.1) to determine the minimum effect thresholds (e.g., 5%) at which acute and chronic toxic 

effects are predicted. The minimum effects thresholds shall be used to derive the criteria instead of using 

the EPA acute adjustment factor or the acute-to-chronic ratio to derive criteria.”

EPA’s goal was to identify the minimum acute effect threshold for salmonids, sturgeon, and eulachon exposed 

to cadmium in freshwater per the RPAs provided by NMFS 2012 biological opinion. Specific EPA objectives 

included:

1. Conduct a literature search for cadmium toxicity studies with green sturgeon and eulachon and review 

them for technical adequacy according to the EPA, Office of Water (OW), Aquatic Life Criteria 

Guidelines (Stephen et al. 1985).

6

2. For those green sturgeon and eulachon studies that meet test acceptability requirements and contain 

enough data, calculate normalized C-R curves.

3. Determine if EPA’s on-line version of the Interspecies Correlation Estimation program (WebICE) can 

be used to estimate cadmium-specific LC50(s) for green sturgeon or eulachon if no acceptable acute 

toxicity data exist.

4. Obtain the acute cadmium toxicity test data reported in the salmonid studies cited by EPA in the 304(a) 

cadmium criteria document (dated March 2016), and, if sufficient data are available, calculate a 

hardness-normalized C-R curve (at 100 mg/L hardness as CaCO3) for each test. 

a. Unfortunately, because the acute toxicity data tables contained in the NMFS 2012 biological 

opinion largely did not specify test species or citations for toxicity values provided, EPA was 

unable to use the acute toxicity data from the NMFS 2012 biological opinion as a minimum data 

set (as specified in RPA specifics above). Consequently, EPA considered the high-quality 

salmonid toxicity data, used to calculate the 2016 freshwater acute cadmium criterion that also

had available raw data to perform C-R analysis. The quality of toxicity data used in both criteria 

derivation and C-R analysis was assessed following the 1985 Guidelines.

6

5. Identify the minimum effects thresholds (i.e., lethal or effect concentration, LC or EC, at the 5 or 10 

percent response level) for each test based on the C-R curve generated for all salmonid, green sturgeon 

and eulachon studies, and, when estimating/extrapolating the minimum effect thresholds, note if there 

are any technical or statistical issues. For example, note if the minimum effect threshold is estimated to 

be below the control response or if the threshold lies beyond the bounds of what the data (statistically) 

allow.

a. To access study-specific data and summary sheets relating to the C-R curve fit analysis, please 

see the attached excel file entitle: C-R Curve Fit Analysis Spreadsheets_A.

Summary:

No acceptable studies were found in the literature search for acute (or chronic) cadmium toxicity to green 

sturgeon or eulachon. The WebICE LC50 values predicted for sturgeon at the genus (Acipenser) and familylevel (Acipenseridae) based on acute cadmium toxicity to Xyrauchen texanus (razorback sucker) were 23.28 

and 23.73 μg/L (dissolved Cd, hardness = 100 mg/L), respectively. X. texanus was selected as the surrogate 

species following WebICE model selection guidance. Given data limitations, WebICE could not estimate 

cadmium toxicity to eulachon at the species, genus, or family-level.

Twenty-nine acute cadmium toxicity tests from seven salmonid studies identified by EPA contained sufficient 

data to generate a C-R curve and calculate minimum effect thresholds (see Table 1). The geometric mean LC10

and LC05 values for 28 of the 29 tests with no technical or statistical issues were 2.18 and 1.89 μg/L total 

cadmium normalized to 100 mg/L (as CaCO3) hardness, respectively. The salmonid-specific geometric mean 

6 Stephan, C.E., D.I. Mount, D.J. Hansen, J.H. Gentile, G.A. Chapman, and W.A. Brungs. 1985. Guidelines for deriving numerical 

national water quality criteria for the protection of aquatic organisms and their uses. PB85-227049. National Technical Information 

Service, Springfield, VA. 98 pp.

3

 
LC10 and LC05 values expressed as dissolved cadmium (after application of the conversion factor of 0.944), are 

2.06 and 1.79 μg/L, respectively. Using concentration-response data, EPA also calculated the salmonid specific 

LC50 value to be 3.93 μg/L as total cadmium at a hardness of 100 mg/L (3.71 μg/L, dissolved cadmium; see 

Excel file entitle: C-R Curve Fit Analysis Spreadsheets_A).

EPA posted its final 304(a) national recommended cadmium criteria online on March 30, 2016 (EPA-820-R-16-

002). The acute criterion magnitude is 1.8 μg/L (dissolved cadmium at 100 mg/L hardness, EPA aquatic life 

criteria are reported to two significant figures) and is equivalent to the salmonid LC05 C-R curve-based 

minimum effects threshold and more stringent than the salmonid LC10 C-R curve-based minimum effects 

threshold. 

EPA notes that the full definition of the acute cadmium criterion includes frequency and duration aspects in 

addition to magnitude (concentration): the full definition of the acute cadmium criterion, based on the definition

given in Stephan et al. (1985) is that the one-hour (duration) average concentration does not exceed the criterion 

maximum concentration (CMC) more than once every three years (frequency) on the average. This is a 

conservative approach that captures possible latent effects, considering that acute criteria are based on 96-hour 

continuous concentration laboratory exposure toxicity tests.

When considering the magnitude and duration components of both acute and chronic cadmium criteria together, 

EPA calculated (Equation 1) the acute magnitude may only be met for a total of < 14 hours before the chronic 

criterion is exceeded.

Equation 1: [>CCC] = [(CMC)(X)/96]

Where:

CCC = >0.25 μg/L = chronic criterion exceedance,

CMC = 1.8 μg/L = acute criterion magnitude,

96 = chronic criterion duration,

X= number of hours the acute criterion can be met before chronic criterion is exceeded.

As a result, considering only 96-hour effect concentrations does not adequately account for additional 

protection provided by the duration component of the acute cadmium criterion. Therefore, 14-hour LC50 values 

may better reflect magnitude and duration components of the criterion; however, such data remain largely 

unreported. For comparative purposes, EPA calculated 14-hour acute cadmium LC50 values from two studies

used in the C-R analysis where data permitted (Table 1, Stratus Consulting 1999, Tests 9901 for rainbow trout 

and bull trout). These particular tests were chosen to derive 14-hour LC50 values because they calculated LC50

values for multiple exposure durations using empirically measured toxicity data. Availability of empirically 

measured toxicity data at multiple exposure durations is necessary before LC50 values can be estimated for 

exposure durations for which empirical data are unavailable, such as 14 hour exposures.

The specific data from the Stratus Consulting (1999) study used in the calculation of 14-hour LC50 values were 

toxicity tests termed test phase 9901, specifically those performed in water with a pH = 7.5, hardness = 30.7

mg/L as CaCO3, and water temperature of 8°C. These pH and water hardness values are nearly identical to the 

mean water chemistry conditions in the Willamette River at Portland, Oregon, part of a major migration route

for multiple salmonid species. For both bull trout and rainbow trout, Stratus Consulting (1999) calculated LC50

values for 48, 60, 72, 84, 96, 108, 120, 132 and 144 hour exposures to acutely toxic cadmium concentrations. 

A graph of LC50 concentrations on the y-axis and exposure durations on the x-axis yields a curve, termed a 

time-to-effect curve, where LC50 concentrations are higher at shorter exposure durations than they are at longer 

exposure durations. Visually, such a graph looks similar to an exponential decay curve, where the LC50 values 

4
eventually become asymptotic to the x-axis. The LC50 concentration at the asymptote to the x-axis (exposure 

duration) is the incipient lethal level. Multiple statistical methods have historically been employed to fit time-toeffect curves, including exponential, hyperbolic and polynomial regressions, as well as Michaelis-Menten 

kinetic and power functions. Once a curve has been fit to time-to-effect data, the curve can be extrapolated in 

both directions. Extrapolation to longer exposure durations result in the calculation of the incipient lethal level, 

whereas extrapolation to shorter exposure durations permit calculation of LC50 values for shorter exposure 

durations than were estimated from empirically recorded toxicity test data.

EPA has determined that for the Stratus Consulting (1999) bull trout and rainbow trout toxicity data, a 

polynomial regression provided the best fit of the time-to-effect data for both bull trout and rainbow trout, with 

coefficients of variation (r2) greater than 0.99 for both data sets. Once normalized to a hardness of 100 mg/L as 

CaCO3, the calculated 14-hour cadmium LC50 values for rainbow trout and bull trout were 13.77 μg/L and 

40.20 μg/L (dissolved Cd), respectively. The 14-hour rainbow trout LC50 values is 73% greater than the 96-hour 

salmonid-mean LC50 (i.e., 3.71 μg/L, dissolved cadmium, hardness = 100), while the 14-hour bull trout LC50 is 

more than 90% greater than the salmonid-mean 96-hour LC50 value.

It is important to reiterate that the acute criterion duration is only one hour, not 14 hours. Therefore, 14-hour 

acute criterion exposures could not occur continuously, as was the case in toxicity tests used to calculate 14-

hour LC50 values. EPA further extrapolated along the time-to-effect curve to specifically capture the one hour 

duration specified in the acute cadmium criterion. One-hour LC50 values for rainbow trout and bull trout are 

18.85 μg/L and 66.88 μg/L (dissolved cadmium, hardness = 100 mg/L), respectively.

Regardless of variable exposure duration, the magnitude component of the 2016 acute criterion of 1.8 μg/L 

(dissolved cadmium at 100 mg/L hardness) is equal to the salmonid minimum effects threshold NMFS specified 

that EPA should use to derive the acute cadmium criterion. (From the NMFS 2012 biological opinion: “The 

minimum effects thresholds shall be used to derive the criteria instead of using the EPA acute adjustment factor 

or the acute-to-chronic ratio to derive criteria.”). Based on this analysis, EPA concludes that RPA steps 1-3, 

are met.

5
Table 1. Summary of LC10 and LC05 Values Calculated for 29 Tests with Available C-R data from seven Acceptable Studies Investigating the 

Acute Toxicity of Cadmium to Salmonids (studies from Appendix A of the 2016 304(a) cadmium aquatic life criteria document).

Study

Species 

(common)

Test 

Description

Hardness 

(mg/L) Dissolved?

Unadjusted1

Unadjusted 

(Total2)

Hardness 

Normalized 

(Total)3

Species-Study 

Geometric Mean TRAP 

Flags4 LC10 LC05 LC10 LC05 LC10 LC05 LC10 LC05 Exclude Comments

Besser et al. 

2007 Rainbow trout

Acute 2 103 yes 2.578 2.370 2.730 2.510 2.652 2.438

3.197 2.964

IP

Acute 3 103 yes 3.64 3.327 3.855 3.523 3.744 3.422

IP, no 

convergence yes

No model 

convergence

Acute 4 103 yes 3.747 3.503 3.968 3.710 3.854 3.603

large SE –

X50 & S

Brinkman 

2012

Rio Grande 

cutthroat trout 44.9 yes 3.509 3.275 3.607 3.367 7.898 7.371 7.898 7.371 IP, no CI

Davies et al. 

1993

Acute 1 –

200H, 30 

alk see notes no

see 

notes

see 

notes 0.392 0.289

Hardness differed 

for individual conc., 

was normalized 

prior to TRAP. 

Hardness >50 from 

Mg, not CaCO3.

Acute 2 –

200H, 30 

alk see notes no

see 

notes

see 

notes 1.303 1.080

Hardness differed 

for individual conc., 

was normalized 

prior to TRAP. 

Hardness >50 from 

Mg, not CaCO3.

Acute 1 –

50H, 30 alk see notes no

see 

notes

see 

notes 4.332 3.963

Hardness differed 

for individual conc., 

was normalized 

prior to TRAP. 

Hardness >50 from 

Mg, not CaCO3. 

Source water 

hardness = 45 

mg/L.

Acute 2 –

50H, 30 alk see notes no

see 

notes

see 

notes 5.661 5.337 IP, no CI

Hardness differed 

for individual conc., 

was normalized 

prior to TRAP. 

Hardness >50 from 

Mg, not CaCO3. 

Source water 

hardness = 45 

mg/L.

Rainbow trout Acute 1 –

unaged hard 281 yes 9.966 9.434 10.893 10.311 3.961 3.750

3.225 2.845

no CI

6
Study

Species 

(common)

Test 

Description

Hardness 

(mg/L) Dissolved?

Unadjusted1

Unadjusted 

(Total2)

Hardness 

Normalized 

(Total)3

Species-Study 

Geometric Mean TRAP 

Flags4 LC10 LC05 LC10 LC05 LC10 LC05 LC10 LC05 Exclude Comments

Davies and 

Brinkman 

1994b

Acute 2 –

unaged hard 281 yes 6.000 5.298 6.558 5.791 2.385 2.106

Acute 1 –

aged hard 258 yes 3.334 2.641 3.644 2.887 1.441 1.141 IP

Retained, but 

flagged due to 

uncertainty of 

response between 2 

highest conc.

Acute 2 –

aged hard 276 yes 6.924 6.121 7.568 6.690 2.801 2.476

IP, large SE 

– X50 & S

Acute 1 –

unaged soft 29 yes 1.890 1.726 1.943 1.774 6.526 5.960 no CI

Acute 2 –

unaged soft 28 yes 1.266 1.116 1.301 1.147 4.524 3.988

Phipps and 

Holcombe 

1985 Rainbow trout 44.4 no 1.955 1.759 1.955 1.759 4.328 3.894 4.328 3.894

Stratus 

Consulting 

1999

Bull trout

Bank 1 –

Bull, H30.7, 

pH 7.5, 

9901 30.7 no 0.685 0.643 0.685 0.643 2.177 2.044

2.412 2.111

no CI

Bank 2 –

Bull, H89.3, 

pH 7.54, 

9901 89.3 no 3.146 2.705 3.146 2.705 3.514 3.021

Bank 3 –

Bull, H30, 

pH 6.65, 

9901 30 no 1.502 1.255 1.502 1.255 4.880 4.078

Bank 3 –

Bull, H29.3, 

pH 7.56, 

9905 29.3 no 0.526 0.453 0.526 0.453 1.747 1.506

Bank 2 –

Bull, H33.7, 

pH 7.58, 

9908 31.7 no 0.443 0.366 0.443 0.366 1.365 1.126

Bank 3 –

Bull, H30.2, 

pH 7.57, 

9908 30.2 no 0.685 0.642 0.685 0.642 2.211 2.072 IP, no CI

Rainbow trout

Bank 1 –

RBT, 

H30.7, pH 

7.51, 9901 30.7 no 0.393 0.349 0.393 0.349 1.250 1.110

0.995 0.845

7
Study

Species 

(common)

Test 

Description

Hardness 

(mg/L) Dissolved?

Unadjusted1

Unadjusted 

(Total2)

Hardness 

Normalized 

(Total)3

Species-Study 

Geometric Mean TRAP 

Flags4 LC10 LC05 LC10 LC05 LC10 LC05 LC10 LC05 Exclude Comments

Stratus 

Consulting 

1999 (Cont.)

Bank 2 –

RBT, 

H89.3, pH 

7.52, 9901 89.3 no 1.059 0.827 1.059 0.827 1.183 0.924

Bank 3 –

RBT, H30, 

pH 6.66, 

9901 30 no 0.413 0.319 0.413 0.319 1.341 1.037

Bank 3 –

RBT, 

H29.3, pH 

7.39, 9905 29.3 no 0.242 0.212 0.242 0.212 0.804 0.706

Bank 2 –

RBT, 

H31.7, pH 

7.43, 9908 31.7 no 0.251 0.217 0.251 0.217 0.774 0.669

Bank 3 –

RBT, 

H30.2, pH 

7.42, 9908 30.2 no 0.244 0.224 0.244 0.224 0.788 0.722

Stubblefield 

1990 (ENSR)

Brown trout 48 no 1.190 0.977 1.190 0.977 2.441 2.004 2.441 2.004

Rainbow trout 52 no 0.716 0.585 0.716 0.585 1.358 1.109 1.358 1.109

Mountain 

Whitefish 52 no na na na na yes

No C-R 

relationship.

Toxicity assay not 

included as one of 

29 tests with 

sufficient C-R data.

1 – When multiple TRAP model solutions were available, the model that most effectively fit the low effect range was selected.

2 – For those studies where unadjusted LCx values were calculated on the basis of dissolved cadmium because only measured dissolved cadmium concentrations were reported, 

the LCx values were converted to total cadmium (see Unadjusted Total) using conversion factors of 1.028, 1.059 and 1.093 for total hardness levels closest to 50, 100 and 200 

mg/L, respectively. The approach and conversion factors are consistent with approach and conversion factors used in Appendix A of the 2016 ALC document.

3 – Hardness normalization equation= EXP(0.9789*4.605+((LN(LC50))-(0.9789*(LN(hardness)))) based on acute Cd toxicity-hardness pooled slope of 0.9789 derived March 

2016

4 – IP (inadequate partial responses), no convergence (model could not converge to a solution), no CI (confidence intervals could not be calculated), large SE (large standard error 

for X50 (EC50) or S (slope) parameter)

8
C

B. Mixture Analysis

The information provided in this section addresses RPA step 4 contained in the NMFS 2012 biological 

opinion. RPA step 4 pertains specifically to ensuring the acute cadmium criterion is adjusted, as necessary, 

to account for pollutant mixtures in freshwaters. The RPA includes the following language:

EPA shall ensure that each derived criterion for ammonia, cadmium, and aluminum is adjusted to 

account for chemical mixtures using a concentration–addition model or response-addition model 

to determine whether or not exposure to multiple compounds will result in additive effects to the 

listed species considered in this opinion. The concentration–addition model or response-addition 

model shall include all compounds listed in Table 1.1. If the mixture effects prediction is greater

than one, EPA shall adjust the concentrations for ammonia, cadmium, and aluminum until the 

mixture effects prediction is less than one.

The NMFS 2012 biological opinion assumed the following mixture of pollutants would occur in a 

waterbody. Therefore, EPA used the following pollutants (below) in the mixture analysis consistent with 

the approach outlined in the NMFS 2012 biological opinion:

Aluminum Copper

Arsenic Cadmium

Chromium III Lead

Nickel Selenium

Chromium VI Silver

Tributyltin Zinc

EPA used the following equation, specified in the NMFS 2012 biological opinion for the mixtures analysis 

(below):

Equation 2: 

ECxMix =

Where:

n

∑

I = 1

I

EC

xi

9
n = the number of compounds in the mixture,

Ci = assessment exposure concentration (acute criterion),

ECxi = assessment lethal effects concentration (geometric mean of the criterion-specific toxicity data set).

ECxMix = the sum of toxic units in the mixture, where a toxic unit (TU) is defined as Ci/ECxi

In calculating the acute criterion-specific ECxi values (geometric mean of LC50 values from acute toxicity 

tests) in the table below, EPA used LC50 effect concentrations from acute tests with salmonid fishes, 

supplied in Tables 2.6.2.2.1.1 through 2.6.2.2.12.1 of the NMFS 2012 biological opinion for aluminum, 

arsenic, chromium III and VI, lead, nickel, selenium, silver, tributyltin and zinc. In a number of these tables 

(e.g., Tables 2.6.2.2.1.1 through 2.6.2.2.12.1; aluminum, arsenic, nickel, selenium, silver, tributyltin and 

zinc), NMFS included effect concentrations from chronic tests and tests for which there is no test duration 

information when calculating geometric mean LC50 values. Because NMFS concluded the chronic cadmium 

criteria is adequately protective of salmonid species, EPA only considered effect concentrations from acute

tests when calculating the acute criterion-specific ECxi for each chemical used in the mixture analysis. As a 

result, the geometric mean values for aluminum, arsenic, nickel, selenium, silver, tributyltin and zinc in the 

table below are different than the geometric mean values presented in Tables 2.6.2.2.1.1 through Table 

2.6.2.2.12.1 of the NMFS 2012 biological opinion. With respect to the acute criterion-specific ECxi values 

for copper and cadmium, EPA utilized acute toxicity data (LC50) for salmonids from EPA’s updated 304(a) 

criteria documents. Specifically, EPA considered acute cadmium salmonid data used to calculate the acute 

cadmium 304(a) criterion value. Using this information and the equation above, EPA calculated a mixture 

effects prediction result of 0.944.

1. Tables 2.6.2.2.1.1 through 2.6.2.2.12.1 of the NMFS 2012 biological opinion included data for salmonids, eulachon and green 

sturgeon, but the tables do not provide references or specify which tests are associated with which species. Therefore EPA 

used all of LC50 effect concentrations in the tables, with the exception of chronic test data and data where test duration was not 

identified. 

2. Metals criteria calculated assuming a hardness of 100 mg/L CaCO3.

3. Acute criterion was derived using EPA’s 2007 freshwater copper criterion (biotic ligand model) using input values based on 

Oregon-specific ecoregion data (i.e.,10th percentile of existing concentrations of DOC, calcium, magnesium, sodium, 

potassium, sulfate, chloride, pH, temperature and alkalinity from Oregon’s Level III ecoregions).

Chemical

Acute 

Criterion 

(Ci) (μg/L)

 Acute ECxi TU

Aluminum1 750 4275 0.175

Arsenic1 340 12917 0.026

Cadmium2, 1.8 5.9 0.305

Chromium III1,2 570 9825 0.058

Chromium VI1 16 68333 0.000

Copper 5.143 96.00 0.054

Lead1,2 65 14675 0.004

Nickel1,2 470 29548 0.016

Selenium1 190 3945 0.048

Silver1,2 3.2 67.55 0.047

Tributyltin1 0.46 4.31 0.107

Zinc1,2 120 1162.81 0.103

 ECxMix 0.944

10
Summary:

The result of the mixtures analysis is less than 1. Salmonids exposed to multiple pollutants, including cadmium, 

in freshwaters are unlikely to suffer toxicity greater than the assessment effect concentrations. In addition to 

multiple metals, the mixtures analysis also considered an algaecide (tributyltin; TBT) most commonly detected 

in oceans and estuaries. Therefore, the mixtures analysis (section B) may overestimate mixture toxicity in 

freshwaters. Based on the Section B mixtures analysis, EPA concludes RPA step 4 is met.

11
Table 2. Freshwater Salmonid Acute Toxicity Data Used for RPA (step 4) Mixtures Analysis

Species Chemical

Hardness

(mg/L CaCO3)

Acute Value

(μg/L, Total)

Normalized Acute 

Value1

(μg/L, dissolved) Reference

Rio Grande cutthroat trout

(fry, 0.26 g),

Oncorhynchus clarkii virginalis

Cadmium 

sulfate 44.9 2.467

(2.40 reported dissolved) 5.099 Brinkman 2012

Coho salmon (parr),

Oncorhynchus kisutch

Cadmium 

chloride 22 2.7 11.215 Chapman 1975

Rainbow trout (130 mm),

Oncorhynchus mykiss

Cadmium 

sulfate 31 1.75 5.198 Davies 1976a

Rainbow trout

(swim-up fry, 0.17 g),

Oncorhynchus mykiss

Cadmium 

chloride 23 1.3 5.172 Chapman 1978

Rainbow trout (parr, 6.96 g),

Oncorhynchus mykiss

Cadmium 

chloride 23 1.0 3.978 Chapman 1978

Rainbow trout (8.8 g),

Oncorhynchus mykiss

Cadmium 

chloride 44.4 3.0 6.269

Phipps and 

Holcombe 1985

Rainbow trout 

(juvenile, 18.3 g),

Oncorhynchus mykiss

Cadmium 

chloride 52 1.88

3.365

Stubblefield 1990

Rainbow trout (1.8 g),

Oncorhynchus mykiss - 47 2.66 5.257 Davies et al. 1993

Rainbow trout (1.8 g),

Oncorhynchus mykiss - 204 3.15 1.479 Davies et al. 1993

Rainbow trout (1.8 g),

Oncorhynchus mykiss - 49 3.02 5.730 Davies et al. 1993

Rainbow trout (1.8 g),

Oncorhynchus mykiss - 224 6.12 2.623 Davies et al. 1993

Rainbow trout (fry, 1.0 g),

Oncorhynchus mykiss

Cadmium 

sulfate 29 2.79 8.846

Davies and Brinkman 

1994b

Rainbow trout (fry, 2.5 g),

Oncorhynchus mykiss

Cadmium 

sulfate

258

(aged solution) 8.54 3.187

Davies and Brinkman 

1994b

Rainbow trout (fry, 2.5 g),

Oncorhynchus mykiss

Cadmium 

sulfate 281 13.4 4.600

Davies and Brinkman 

1994b

Rainbow trout (fry, 1.0 g),

Oncorhynchus mykiss

Cadmium 

sulfate 28 2.09 6.858

Davies and Brinkman 

1994b

Rainbow trout (fry, 2.5 g),

Oncorhynchus mykiss

Cadmium 

sulfate

276

(aged solution) 10.5 3.668

Davies and Brinkman 

1994b

Rainbow trout (fry, 2.5 g),

Oncorhynchus mykiss

Cadmium 

sulfate 281 10.0 3.433

Davies and Brinkman 

1994b

Rainbow trout (263 mg),

Oncorhynchus mykiss

Cadmium 

chloride 30.7 0.71 2.129

Stratus Consulting 

1999

Rainbow trout (659 mg),

Oncorhynchus mykiss

Cadmium 

chloride 29.3 0.47 1.475

Stratus Consulting 

1999

Rainbow trout (1,150 mg),

Oncorhynchus mykiss

Cadmium 

chloride 31.7 0.51 1.482

Stratus Consulting 

1999

Rainbow trout (1,130 mg),

Oncorhynchus mykiss

Cadmium 

chloride 30.2 0.38 1.158

Stratus Consulting 

1999

Rainbow trout (299 mg),

Oncorhynchus mykiss

Cadmium 

chloride 30.0 1.29 3.956

Stratus Consulting 

1999

12
Species Chemical

Hardness

(mg/L CaCO3)

Acute Value

(μg/L, Total)

Normalized Acute 

Value1

(μg/L, Dissolved) Reference

Rainbow trout (289 mg),

Oncorhynchus mykiss

Cadmium 

chloride 89.3 2.85 3.005

Stratus Consulting 

1999

Rainbow trout

(swim-up fry, 0.131 g),

Oncorhynchus mykiss

- 103 3.7

3.393

Besser et al. 2007

Rainbow trout

(juvenile, 0.496 g),

Oncorhynchus mykiss

- 103 5.2

4.768

Besser et al. 2007

Rainbow trout

(18 dph, 0.1 g, 24.33 cm),

Oncorhynchus mykiss

Cadmium 

chloride 104 3.061

(2.89 reported dissolved) 2.780

Calfee et al. 2014

Rainbow trout

(32 dph, 0.12 g, 26.67 cm),

Oncorhynchus mykiss

Cadmium 

chloride 107 5.115

(4.83 reported dissolved) 4.518

Calfee et al. 2014

Rainbow trout

(46 dph, 0.22 g, 32.1 cm),

Oncorhynchus mykiss

Cadmium 

chloride 107 2.933

(2.77 reported dissolved) 2.591

Calfee et al. 2014

Rainbow trout

(60 dph, 0.33 g, 37.1 cm),

Oncorhynchus mykiss

Cadmium 

chloride 104 3.929f(3.71 reported dissolved) 3.568

Calfee et al. 2014

Rainbow trout

(74 dph, 0.42 g, 40.3 cm),

Oncorhynchus mykiss

Cadmium 

chloride 96 4.808

(4.54 reported dissolved) 4.723

Calfee et al. 2014

Rainbow trout

(95 dph, 0.7 g, 45.43 cm),

Oncorhynchus mykiss

Cadmium 

chloride 103 3.135

(2.96 reported dissolved) 2.874

Calfee et al. 2014

Rainbow trout 

(juvenile, 26 dph),

Oncorhynchus mykiss

Cadmium 

chloride 100 5.401

(5.1 reported dissolved) 5.099

Wang et al. 2014a

Chinook salmon (juvenile),

Oncorhynchus tshawytscha

Cadmium 

chloride 25 1.41 5.170 Chapman 1978; 1982

Chinook salmon

(swim-up fry, 0.23 g),

Oncorhynchus tshawytscha

Cadmium 

chloride 23 1.8

7.161

Chapman 1978

Chinook salmon (juvenile),

Oncorhynchus tshawytscha

Cadmium 

sulfate 21 1.1 4.784

Finlayson and Verrue 

1982

Lake whitefish

(yearling, 140 mm, 22 g),

Coregonus clupeaformis

- 81 530 614.827 McNicol 1997

Mountain whitefish (209 g),

Prosopium williamsoni

Cadmium 

chloride 52 >8.29 >14.839 Stubblefield 1990

Brown trout 

(fingerling, 22.4 g),

Salmo trutta

Cadmium 

chloride 48 2.85

5.518

Stubblefield 1990

Brown trout (fingerling),

Salmo trutta

Cadmium 

sulfate 37.6 2.37 5.827

Davies and Brinkman 

1994c

Brown trout (fry),

Salmo trutta

Cadmium 

sulfate 29.2 1.23 3.874

Brinkman and 

Hansen 2004a; 2007

13
Species Chemical

Hardness

(mg/L CaCO3)

Acute Value

(μg/L, Total)

Normalized Acute 

Value1

(μg/L, Dissolved) Reference

Brown trout (fry),

Salmo trutta

Cadmium 

sulfate 67.6 3.9 5.401

Brinkman and 

Hansen 2004a; 2007

Brown trout (fry),

Salmo trutta

Cadmium 

sulfate 151 10.1 6.368

Brinkman and 

Hansen 2004a; 2007

Bull trout (76.1 mg),

Salvelinus confluentus

Cadmium 

chloride

30.7

(pH=7.5) 0.91 2.729

Stratus Consulting 

1999

Bull trout (200 mg),

Salvelinus confluentus

Cadmium 

chloride

29.3

(pH=7.5) 0.99 3.108

Stratus Consulting 

1999

Bull trout (221 mg),

Salvelinus confluentus

Cadmium 

chloride

31.7

(pH=7.5) 1.00 2.907

Stratus Consulting 

1999

Bull trout (218 mg),

Salvelinus confluentus

Cadmium 

chloride

30.2

(pH=7.5) 0.90 2.742

Stratus Consulting 

1999

Bull trout (84.2 mg),

Salvelinus confluentus

Cadmium 

chloride

30.0

(pH=6.5) 2.89 8.864

Stratus Consulting 

1999

Bull trout (72.7 mg),

Salvelinus confluentus

Cadmium 

chloride

89.3

(pH=7.5) 6.06 6.390

Stratus Consulting 

1999

Brook trout 

(yearling, 21 cm, 110 g),

Salvelinus fontinalis

- 45

(44-46) >405 >835.25 Drummond and 

Benoit 1976

Brook trout (100 g),

Salvelinus fontinalis

Cadmium 

chloride 47.4 5,080 9,957.3 Holcombe et al. 1983

1. Values under the heading “Normalized Acute Value” have been normalized to a hardness of 100 mg/L

and are presented as dissolved cadmium.

a) Hardness normalization equation = EXP(0.9789*4.605+((LN(LC50))-(0.9789*(LN(hardness))))

b) Total to dissolved adjustment factor (at hardness = 100 mg/L) = 0.944

14
C. Population Model

The information provided in this section addresses RPA step 5 contained in the NMFS 2012 biological opinion. 

RPA step 5 pertains specifically to assessing the potential effects of cadmium on salmonids at the populationlevel. The RPA includes the following language:

To ensure that the derived numeric criteria for ammonia, cadmium, and aluminum meet the population

growth rate condition of the RPA, EPA shall run the criteria for ammonia, cadmium, and aluminum

through a population model (e.g., Leslie Matrix), parameterized for Pacific salmonid fishes. Model

requirements include: (1) scenarios based on change in first year survival; (2) an assumption that the

populations are density-independent, to reduce the probability of Type II errors; (3) sigmoid slopes are

generated from the data used to derive the numeric criteria, and if a slope cannot be generated from the

data, EPA shall use the default sigmoid slope of 3.6 used in this opinion; and (4) exposure-response

scenarios using the geometric mean of the curve-fitted data, and the minimum species mean value of the

curve-fitted data from the toxicity data used to derive the numeric criteria.

Population Model Methods:

Of the 28 acceptable 96-hour toxicity studies used to calculate minimum effect thresholds (Section A), 26 were

model-compatible (Table 3). For population model analysis, EPA included all 96-hour acute values (i.e., 96-hour 

LC50) from tests using fish in the 0-10g range (i.e., juvenile or first-year fish). EPA specifically considered 0-

10g salmonid fishes because population-level effects predicted from the model are most sensitive to first-year fish 

survival (See 2012 NMFS biological opinion, Appendix III, Table A-1). Most importantly, the model uses the 

acute exposure-response relationship from the toxicity data to adjust only the first-year survival parameter. Thus, it 

would be inappropriate to apply test results from other salmonid life stages to any survival response to first-year fish. 

Toxicity tests not included in population modeling were those that used large juvenile fish (i.e., second-year

juveniles based on size and/or weight), or adult fish. Toxicity test data (e.g., 96-hour LC50) included in the 

population model dataset was obtained from tests using rainbow trout, Rio Grande cutthroat trout, and bull trout 

(geometric mean 96-hour LC50 = 3.572 μg/L, dissolved Cd, hardness = 100 mg/L). The minimum species mean 

value (96-hour LC50) of all included species was for rainbow trout (rainbow trout geometric mean 96-hour LC50

= 3.36 μg/L, dissolved Cd, hardness = 100 mg/L). All 96-hour LC50 values were converted to total cadmium (as 

necessary), then adjusted to hardness of 100 mg/L CaCO3, and finally converted back to the dissolved fraction,

consistent with approach and conversion factors used in Appendix A of the 2016 aquatic life criteria document.

Concentration-response relationships were estimated using raw data from acceptable toxicity tests (Table 3)

using the following two parameter logistic function (Equation 3):

Equation 3: percent survival = 100/(1+(concentration/LC50)^slope),

where survival (as percent) and concentration (μg/L dissolved Cd) were regressed to generate LC50 and slope 

estimates for each toxicity test in Table 3. The geometric mean of all calculated 96-hour LC50 values and slope 

values, as well as the minimum species mean value (i.e., rainbow trout geometric mean 96-hour LC50) and 

corresponding slope value, were used as input for the population model. The geometric mean of the modelcompatible 96-hour LC50 data is 3.572 μg/L (dissolved Cd, hardness = 100 mg/L) and the geometric mean slope 

of concentration-response test data is 4.978 (unitless). The minimum species mean 96-hour LC50 value is 3.360 

μg/L (dissolved Cd, hardness = 100 mg/L), with a slope of 4.562.

EPA ran four additional model scenarios based on 14-hour and 1-hour acute LC50 values (see Section A) and 

slopes for rainbow trout and bull trout (Stratus Consulting 1999). EPA used 14-hour and 1-hour LC50 values, when 

15
available, to understand population-level effects of cadmium, when the population model more accurately reflects 

the acute cadmium criterion by considering the duration component (i.e., averaging period) of the criterion. 

Population models based on 14-hour LC50 values were selected to represent acute exposure scenarios that could 

occur without exceeding the chronic cadmium criterion. Specifically, the acute criterion magnitude (i.e., 

concentration) could only be met for < 14 hours throughout the chronic criterion duration (i.e., 96 hours) before the 

chronic criterion is exceeded, assuming cadmium concentrations are 0.0 μg/L for the remaining 82 hours of the 

chronic criterion duration.

Notably, 14-hour continuous acute exposures would exceed the acute cadmium criterion by exceeding the duration 

component, even though the magnitude component remains at criterion concentrations. Therefore, 1-hour LC50 

values represent the maximum continuous acute cadmium exposure allowed by the acute cadmium criterion (i.e., 

1.8 μg/L dissolved Cd at hardness = 100 mg/L for 1 hour). As a result, population model runs using 1-hour LC50

values explicitly reflect the acute criterion duration. 

EPA is currently undergoing analyses to explore potential methods for accurately considering excursion frequency 

in the population model. Potential methods for accurately considering the frequency component of the acute 

criterion remain preliminary and are therefore not presented here. 

In total, EPA ran the population model under six scenarios: 

1. Juvenile, salmonid-mean 96-hour LC50 with corresponding slope

2. Juvenile, 96-hour lowest salmonid species mean value (i.e., rainbow trout) with corresponding slope

3. Juvenile, rainbow trout 14-hour LC50 with corresponding slope

4. Juvenile, bull trout 14-hour LC50 with corresponding slope

5. Juvenile, rainbow trout 1-hour LC50 with corresponding slope

6. Juvenile, bull trout 1-hour LC50 with corresponding slope

Each model scenario (above) was run for four salmonid life histories:

1. Chinook, ocean type

2. Chinook, stream type

3. Coho

4. Sockeye

Population Model Results:

All four salmonid life-history models using the salmonid geometric mean 96-hour LC50 value predict three percent 

mortality with a negative change in the mean population growth rate (lambda) of one percent. Using the 96-

hour minimum species mean LC50 value, the four salmonid life-history models predict five percent mortality 

with a negative change in lambda ranging from one to two percent. 

The primary output of the population model is a mean lambda value calculated from 10,000 individual model 

iterations; the variation in the iterations themselves provides an estimate of overall model variability. Figure 1 

shows histograms summarizing individual model iterations for a control population of ocean-type chinook 

(chinookotc in blue) and a population exposed to cadmium (chinookote in yellow). To generate Figure 1 data, 

the chinook (ocean type life history) population model was run using the geomean LC50 value based on 0-10g 

salmonid fishes exposed to cadmium for 96 continuous hours. Histograms for lambda estimates from control 

and exposed populations overlap to the extent it is visually difficult to distinguish the two. The histograms

suggest there is no detectable difference between the model output of lambda for a control population and a 

population exposed to cadmium at the proposed criterion magnitude over exposure durations (i.e., 96 hours)

and excursion frequencies that are inconsistent with the acute cadmium criterion. Model output indicated a 

16
change in lambda of 1 % between control and exposed mean lambda estimates of chinook (ocean type) 

populations, while also specifying a change in lambda of 12.7 % is required to detect a significant change 

between the control and exposed mean lambda estimates. For all life history and exposure scenario model 

runs, the change in lambda between control and exposed populations never exceeded one standard deviation 

of the control lambda.

When using LC50 data that more accurately consider the duration component of the acute cadmium criterion 

(i.e., 14-hour LC50 values for rainbow trout and bull trout), the model predicts zero mortality and no negative 

change in lambda for each fish life history model run (Table 4). Similarly, when using LC50 data that 

accurately consider the duration component of the acute cadmium criterion (i.e., 1-hour LC50 values for 

rainbow trout and bull trout), the model also predicts zero mortality and no negative change in lambda for 

each fish life history model run (Table 4).

Summary:

The ability of the population model to detect a population-level effect from cadmium exposure is limited given 

the variability of the control population lambda values determined from 10,000 model iterations. Variation in 

both control and exposed lambda values results from the underlying variation associated with the demographic 

information used to parameterize the model matrix. Appendix 3 of the NMFS 2012 biological opinion, which 

describes the technical details of the population model, states (pg. 750):

The percent change in lambda is considered different from control when the difference is greater than the 

percent of one standard deviation of the control lambda.

In other words, the difference between the mean lambda of the control population and the mean lambda of the 

exposed population must be greater than one standard deviation of the distribution of control lambda values in 

order to statistically tell them apart (note: these values are provided in the model output and are shown in Table 

4).

For each life history, the model provides a summary estimate of the inherent uncertainty in its estimate of 

change in lambda between the control and exposed scenarios (i.e., the percent change in lambda). For all 

scenarios run (see Table 4), values of the percent change in lambda representing a significant change range from 

4.3 to 12.9 percent. In other words, the population model is not adequately sensitive to identify differences in 

lambda that may be caused by cadmium exposure if the threshold for acceptance is “no net negative change.” If 

the threshold of acceptance is mean exposed population lambda values falling within one standard deviation of 

the control population lambda means (as noted in Appendix 3 of the NMFS 2012 biological opinion), then all 

population model scenarios run for each salmonid life history suggest no population-level effects of cadmium. 

Using toxicity estimates based on 96-hour exposures in the population model results in overly conservative 

model output that does not reflect how duration and frequency components of the acute cadmium criterion 

further protect salmon populations, in addition to the criterion magnitude. EPA believes that incorporating 

frequency and duration aspects into the population model is consistent with the RPA. Therefore, EPA also ran 

the population model using 14-hour and 1-hour toxicity data that more accurately considers the duration component 

of the acute cadmium criterion (see Section A). Population models run using 14-hour and 1-hour toxicity data resulted 

in no life history models showing significant differences between the lambdas for control populations and those 

exposed to the acute cadmium criterion magnitude. When the appropriate duration aspect of the criterion is 

incorporated in the model runs, there are no population-level risks. Therefore, EPA concludes RPA step 5 is 

met.

17
Table 3. 96-Hour Acute Juvenile Salmonid Toxicity Data Sources for Population Model Analysis

Study Species (common) Test Description Hardness (mg/L) Dissolved? Notes

Besser et al. 2007 Rainbow trout Acute 2 103 yes

Acute 4 103 yes

Brinkman 2012 Rio Grande cutthroat trout 44.9 yes

Davies et al. 19931,2 Rainbow trout

Acute 1 - 200H, 30 

alk see notes no

Hardness differed for individual conc., was 

normalized prior to regression. Hardness 

>50 from a Mg salt, not a Ca salt. Source 

water hardness = 45 mg/L.

Acute 2 - 200H, 30 

alk see notes no

Hardness differed for individual conc., was 

normalized prior to regression. Hardness 

>50 from a Mg salt, not a Ca salt. Source 

water hardness = 45 mg/L.

Acute 1 - 50H, 30 alk see notes no

Hardness differed for individual conc., was 

normalized prior to regression. Hardness 

>50 from a Mg salt, not a Ca salt. Source 

water hardness = 45 mg/L.

Acute 2 - 50H, 30 alk see notes no

Hardness differed for individual conc., was 

normalized prior to regression. Hardness 

>50 from a Mg salt, not a Ca salt. Source 

water hardness = 45 mg/L.

Davies and Brinkman 

1994b Rainbow trout

Acute 1 - unaged hard 281 yes

Acute 2 - unaged hard 281 yes

Acute 1 - aged hard 258 yes

Retained, but flagged due to uncertainty of 

response between 2 highest conc.

Acute 2 - aged hard 276 yes

Acute 1 - unaged soft 29 yes

Acute 2 - unaged soft 28 yes

Phipps and Holcombe 

1985 Rainbow trout 44.4 no

Stratus Consulting 1999

Bull trout

Bank 1 - Bull, H30.7, 

pH 7.5, 9901 30.7 no

Bank 2 - Bull, H89.3, 

pH 7.54, 9901 89.3 no

Bank 3 - Bull, H30, 

pH 6.65, 9901 30 no

Bank 3 - Bull, H29.3, 

pH 7.56, 9905 29.3 no

Bank 2 - Bull, H31.7, 

pH 7.58, 9908 31.7 no

Bank 3 - Bull, H30.2, 

pH 7.57, 9908 30.2 no

Rainbow trout

Bank 1 - RBT, H30.7, 

pH 7.51, 9901 30.7 no

Bank 2 - RBT, H89.3, 

pH 7.52, 9901 89.3 no

Bank 3 - RBT, H30, 

pH 6.66, 9901 30 no

Bank 3 - RBT, H29.3, 

pH 7.39, 9905 29.3 no

Bank 2 - RBT, H31.7, 

pH 7.43, 9908 31.7 no

Bank 3 - RBT, H30.2, 

pH 7.42, 9908 30.2 no

 

18
Table 4. Population Model Analysis Results

Geometric Mean 96-Hour LC50 (0-10g salmonids)

Parameter Value Output Control Exposed

Chemical Cd % change lambda - -1

Concentration 1.8 % chg l std - 12.7

LC50 3.572 lambda mean 1.09 1.08

LC50 slope 4.978 lambda std 0.1 0.1

species chinook, ot S1 5.64E-03 5.46E-03

% Mortality 3 Significant change 9.1

Percent Exposed 100

Chemical Cd % change lambda - -1

Concentration 1.8 % chg l std - 4.3

LC50 3.572 lambda mean 1 0.99

LC50 slope 4.978 lambda std 0.03 0.03

species chinook, st S1 6.44E-02 6.22E-02

% Mortality 3 Significant change 3.1

Percent Exposed 100

Chemical Cd % change lambda - -1

Concentration 1.8 % chg l std - 7.9

LC50 3.572 lambda mean 1.01 1

LC50 slope 4.978 lambda std 0.06 0.06

species sockeye S1 2.57E-02 2.49E-02

% Mortality 3 Significant change 5.6

Percent Exposed 100

Chemical Cd % change lambda - -1

Concentration 1.8 % chg l std - 7.4

LC50 3.572 lambda mean 1.03 1.02

LC50 slope 4.978 lambda std 0.05 0.05

species coho S1 2.97E-02 2.87E-02

% Mortality 3 Significant change 5.3

Percent Exposed 100

96-Hour Lowest Species Mean Value (0-10g; rainbow trout)

Parameter Value Output Control Exposed

Chemical Cd % change lambda - -1

Concentration 1.8 % chg l std - 12.7

LC50 3.36 lambda mean 1.09 1.07

LC50 slope 4.562 lambda std 0.1 0.1

species chinook, ot S1 5.64E-03 5.33E-03

% Mortality 5 Significant change 9.1

Percent Exposed 100

Chemical Cd % change lambda - -1

Concentration 1.8 % chg l std - 4.3

LC50 3.36 lambda mean 1 0.99

LC50 slope 4.562 lambda std 0.03 0.03

19
species chinook, st S1 6.43E-02 6.08E-02

% Mortality 5 Significant change 3.1

Percent Exposed 100

Chemical Cd % change lambda - -1

Concentration 1.8 % chg l std - 7.8

LC50 3.36 lambda mean 1.01 1

LC50 slope 4.562 lambda std 0.06 0.06

species sockeye S1 2.58E-02 2.43E-02

% Mortality 5 Significant change 5.6

Percent Exposed 100

Chemical Cd % change lambda - -2

Concentration 1.8 % chg l std - 7.3

LC50 3.36 lambda mean 1.03 1.01

LC50 slope 4.562 lambda std 0.05 0.05

species coho S1 2.97E-02 2.80E-02

% Mortality 5 Significant change 5.3

Percent Exposed 100

14-Hour LC50 (rainbow trout)

Parameter Value Output Control Exposed

Chemical Cd % change lambda - 0

Concentration 1.8 % chg l std - 12.9

LC50 13.767 lambda mean 1.09 1.09

LC50 slope 4.131 lambda std 0.1 0.1

species chinook, ot S1 5.62E-03 5.64E-03

% Mortality 0 Significant change 9.1

Percent Exposed 100

Chemical Cd % change lambda - 0

Concentration 1.8 % chg l std - 4.4

LC50 13.767 lambda mean 1 1

LC50 slope 4.131 lambda std 0.03 0.03

species chinook, st S1 6.44E-02 6.44E-02

% Mortality 0 Significant change 3.1

Percent Exposed 100

Chemical Cd % change lambda - 0

Concentration 1.8 % chg l std - 7.9

LC50 13.767 lambda mean 1.01 1.01

LC50 slope 4.131 lambda std 0.06 0.06

species sockeye S1 2.56E-02 2.57E-02

% Mortality 0 Significant change 5.6

20
Percent Exposed 100

Chemical Cd % change lambda - -0

Concentration 1.8 % chg l std - 7.5

LC50 13.767 lambda mean 1.03 1.03

LC50 slope 4.131 lambda std 0.05 0.05

species coho S1 2.97E-02 2.96E-02

% Mortality 0 Significant change 5.3

Percent Exposed 100

14-hour LC50 (bull trout)

Parameter Value Output Control Exposed

Chemical Cd % change lambda - -0

Concentration 1.8 % chg l std - 12.8

LC50 40.198 lambda mean 1.09 1.09

LC50 slope 9.47 lambda std 0.1 0.1

species chinook, ot S1 5.65E-03 5.64E-03

% Mortality 0 Significant change 9.1

Percent Exposed 100

Chemical Cd % change lambda - 0

Concentration 1.8 % chg l std - 4.4

LC50 40.198 lambda mean 1 1

LC50 slope 9.47 lambda std 0.03 0.03

species chinook, st S1 6.43E-02 6.44E-02

% Mortality 0 Significant change 3.1

Percent Exposed 100

Chemical Cd % change lambda - -0

Concentration 1.8 % chg l std - 7.9

LC50 40.198 lambda mean 1.01 1.01

LC50 slope 9.47 lambda std 0.06 0.06

species sockeye S1 2.58E-02 2.57E-02

% Mortality 0 Significant change 5.6

Percent Exposed 100

Chemical Cd % change lambda - -0

Concentration 1.8 % chg l std - 7.5

LC50 40.198 lambda mean 1.03 1.03

LC50 slope 9.47 lambda std 0.05 0.05

species coho S1 2.97E-02 2.97E-02

% Mortality 0 Significant change 5.3

Percent Exposed 100

21
1-Hour LC50 (rainbow trout)

Parameter Value Output Control Exposed

Chemical Cd % change lambda - 0

Concentration 1.8 % chg l std - 12.9

LC50 18.85 lambda mean 1.09 1.09

LC50 slope 4.131 lambda std 0.1 0.1

species chinook, ot S1 5.62E-03 5.64E-03

% Mortality 0 Significant change 9.1

Percent Exposed 100

Chemical Cd % change lambda - 0

Concentration 1.8 % chg l std - 4.4

LC50 18.85 lambda mean 1 1

LC50 slope 4.131 lambda std 0.03 0.03

species chinook, st S1 6.44E-02 6.44E-02

% Mortality 0 Significant change 3.1

Percent Exposed 100

Chemical Cd % change lambda - 0

Concentration 1.8 % chg l std - 7.9

LC50 18.85 lambda mean 1.01 1.01

LC50 slope 4.131 lambda std 0.06 0.06

species sockeye S1 2.56E-02 2.57E-02

% Mortality 0 Significant change 5.6

Percent Exposed 100

Chemical Cd % change lambda - 0

Concentration 1.8 % chg l std - 7.5

LC50 18.85 lambda mean 1.03 1.03

LC50 slope 4.131 lambda std 0.05 0.05

species coho S1 2.97E-02 2.97E-02

% Mortality 0 Significant change 5.3

Percent Exposed 100

1-hour LC50 (bull trout)

Parameter Value Output Control Exposed

Chemical Cd % change lambda - 0

Concentration 1.8 % chg l std - 12.9

LC50 66.878 lambda mean 1.09 1.09

LC50 slope 9.47 lambda std 0.1 0.1

species chinook, ot S1 5.62E-03 5.64E-03

% Mortality 0 Significant change 9.1

22
Percent Exposed 100

Chemical Cd % change lambda - 0

Concentration 1.8 % chg l std - 4.4

LC50 66.878 lambda mean 1 1

LC50 slope 9.47 lambda std 0.03 0.03

species chinook, st S1 6.43E-02 6.43E-02

% Mortality 0 Significant change 3.1

Percent Exposed 100

Chemical Cd % change lambda - 0

Concentration 1.8 % chg l std - 7.9

LC50 66.878 lambda mean 1.01 1.01

LC50 slope 9.47 lambda std 0.06 0.06

species sockeye S1 2.57E-02 2.57E-02

% Mortality 0 Significant change 5.7

Percent Exposed 100

Chemical Cd % change lambda - 0

Concentration 1.8 % chg l std - 7.5

LC50 66.878 lambda mean 1.03 1.03

LC50 slope 9.47 lambda std 0.05 0.05

species coho S1 2.97E-02 2.97E-02

% Mortality 0 Significant change 5.3

Percent Exposed 100

23
Figure 1. Histograms summarizing individual model iterations of the control and exposed scenarios for 

the chinook ocean-type life history model. X axis indicates lambda estimate while Y axis indicates the 

number of iterations (counts) for each unique lambda estimate. Blue bars indicate control population 

(chinookotc) iterations; yellow bars indicate exposed population (chinookote) iterations. Green indicates 

overlap between two histograms. Data used to generate figure were from the population model using the

geometric mean of 96 hour toxicity data for 0-10 g salmonid fishes as input (Table 4). 

II. SUMMARY OF ACUTE RPA RESPONSE ANALYSIS

The available toxicity dataset for cadmium was relatively large compared to other pollutants. As a result, EPA 

was able to perform RPA steps 1-5 using quality data which would be considered acceptable for 304(a) water 

quality criteria derivation. The EPA followed the process outlined in RPA steps 1-3 in the NMFS 2012 

biological opinion to estimate a minimum effects threshold (e.g., LC5 or LC10) for cadmium. EPA identified 29 

acute cadmium toxicity tests from seven salmonid studies that contained sufficient quality data to generate a CR curve and calculate minimum effect thresholds. Twenty-eight studies (i.e., those without technical or 

statistical errors) were specifically used to calculate minimum effect thresholds. The salmonid-specific 

minimum effect thresholds are 2.06 μg/L (LC10, dissolved Cd, hardness = 100 mg/L) and 1.79 μg/L (LC05, 

dissolved Cd, hardness = 100 mg/L). Because the acute cadmium criterion magnitude for Oregon is equal to the 

salmonid minimum effects threshold (LC05) that NMFS specified EPA use in deriving the acute cadmium 

criterion, EPA concludes that RPA steps 1-3 are met. Furthermore, the mixtures analysis suggests that metal 

mixtures in freshwaters will not result in toxic effects to salmonids, eulachon, and green sturgeon greater than 

the assessment effect concentrations. As a result, EPA also concludes that RPA step 4 is met.

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Population model (based on 96 hour LC50 values) output demonstrated that cadmium-exposed population 

lambda values never differed from control population lambda values by more than one standard deviation of the 

control lambda distribution. As a result, the population model did not detect significant differences in 

population-level effects of cadmium between control (i.e., unexposed to cadmium) and exposed salmonid 

populations. Additionally, EPA used the population model with inputs that are consistent with the magnitude 

and duration components of the acute cadmium criterion and found no change in the intrinsic growth.7

Therefore, EPA considers RPA step 5 to be met. 

This RPA analysis demonstrates that the acute aquatic life cadmium criterion the EPA is proposing to 

promulgate in Oregon is consistent with the intent of the RPA and avoids jeopardizing Endangered Species Act 

threatened and endangered species or adversely modifying their designated critical habitat. 

7 EPA is currently undergoing analyses to explore potential methods for accurately considering excursion frequency in the population 

model. 

25

 
Appendix A

Reasonable and Prudent Alternatives for Cadmium

Acute. The EPA shall disapprove the State of Oregon’s acute criterion of 2.0 μg/L at 100 mg/L CaCO3 for 

freshwater cadmium. The EPA shall use the Process for Deriving Criteria, specified below, to derive an acute 

criterion for the State of Oregon for freshwater cadmium. The EPA shall recommend that the State adopt, and 

EPA will promulgate if necessary, the derived acute cadmium criterion. The EPA will ensure that the derived 

acute ammonia, cadmium or aluminum criteria will be effective within 24 months after EPA’s final action to 

approve or disapprove Oregon’s proposed water quality criteria under the CWA.

Process for Deriving Criteria (pages 550 – 551 of the NMFS 2012 biological opinion):

The EPA shall use the process for deriving criteria, specified below, to set an acute criterion for

freshwater cadmium.

The EPA shall utilize analytical methods that meet NMFS-specified requirements to derive numeric

criteria for aquatic life, taking into account the same factors considered by NMFS in completing its

analysis for the other criteria in this opinion. In particular, the EPA shall derive criteria for acute

ammonia, acute cadmium, and acute and chronic aluminum in compliance with the following five

requirements:

1) Only use toxicitydata for ammonia, cadmium, and aluminum that isspecific to salmonid fishes (if

new information becomes available for these compounds for green sturgeon and eulachon, then

EPA shall include this data in its analysis);

2) All toxicity data used to derive the numeric criteria must be curve-fitted, where the literature

provides the necessary data to perform this step;

3) When available, the curve-fitted toxicity data must be used to extrapolate threshold acute and

chronic toxic effect concentrations;

4) Derived criteria must be model-adjusted to account for chemical mixtures; and

5) An appropriate population model must be applied to the derived criteria, and must predict no

negative change in the intrinsic population growth rate (e.g., lambda).

More specifically, EPA shall ensure that the derived criteria are developed in compliance with the

following mandatory sideboards:

• The EPA shall use toxicity data specific to salmonid fishes. The EPA shall use the acute and chronic

toxicity data in this opinion as a minimum data set. For green sturgeon and eulachon, EPA shall use the

salmonid fishes [sic] toxicity data for this analysis, as described in section 2.6.2 in this opinion, in

addition to any new data that becomes available for green sturgeon and eulachon.

• The EPA shall use toxicity data based on exposure-response curves and fixed duration toxicity tests to

estimate acute and chronic toxic effect thresholds to assess effects on multiple life stages and multiple

endpoints, to include at a minimum: mortality, latent mortality, reproduction, growth, physiological, cellular,

behavioral, and biochemical effects, where the data exists. The EPA may use existing toxicity data for

26
ammonia, cadmium or aluminum... or generate new data, but the data shall be curve-fitted (see Figure

2.6.1.1) to determine the minimum effect thresholds (e.g., 5%) at which acute and chronic toxic effects are

predicted.

• The EPA shall ensure that each derived criterion for ammonia, cadmium, and aluminum is adjusted to

account for chemical mixtures using a concentration–addition model or response-addition model to

determine whether or not exposure to multiple compounds will result in additive effects to the listed species

considered in this opinion. The concentration–addition model or response-addition model shall include all

compounds listed in Table 1.1. If the mixture effects prediction is greater than one, EPA shall adjust the

concentrations for ammonia, cadmium, and aluminum until the mixture effects prediction is less than one.

• The EPA shall ensure that the derived criteria for ammonia, cadmium, and aluminum do not result in a

negative change in the intrinsic population growth rate based on the geometric mean abundance data for each

life history type, i.e., coho salmon (O. kisutch), sockeye salmon (O. nerka) and ocean-type and stream-type

Chinook salmon (O. tshawytscha), of salmonid fish considered in this opinion, at the population scale. The

EPA shall use stream-type Chinook salmon as a surrogate for steelhead, and ocean-type Chinook salmon as a

surrogate for chum salmon in the population model, as described in section 2.6.5.1 of this opinion. Pacific

salmon and steelhead abundance data is available from the Northwest Fisheries Science Center Salmon

Population Summary Database

8

or from the Columbia Basin Fish and Wildlife Authority Status of the Fish and

Wildlife Resources Database

9

. The abundance data used for the population growth rate analysis shall include

data from all years with available abundance data. For green sturgeon and eulachon, EPA shall use the

salmonid fishes toxicity data and modeling results as surrogate data and outputs for this analysis.

• To ensure that the derived numeric criteria for ammonia, cadmium, and aluminum meet the population

growth rate condition of the RPA, EPA shall run the criteria for ammonia, cadmium, and aluminum through a 

population model (e.g., Leslie Matrix), parameterized for Pacific salmonid fishes. Model requirements

include: (1) scenarios based on change in first year survival; (2) an assumption that the populations are

density-independent, to reduce the probability of Type II errors; (3) sigmoid slopes are generated from the

data used to derive the numeric criteria, and if a slope cannot be generated from the data, EPA shall use the

default sigmoid slope of 3.6 used in this opinion; and (4) exposure-response scenarios using the geometric

mean of the curve-fitted data, and the minimum species mean value of the curve-fitted data, and the

minimum species mean value of the curve-fitted data, from the toxicity data used to derive the numeric

criteria.

8 https://www.webapps.nwfsc.noaa.gov/sps

9 http;//sort.cbfwa.org

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