UNITED STATES ENVIRONMENTAL PROTECTION AGENCY

WASHINGTON, D. C. 20460 

 OFFICE OF

PREVENTION, PESTICIDES 

AND TOXIC SUBSTANCES 

Chemical: Coppers (Copper sulfate, 

copper group II, copper salts, copper 

and oxides) 

PC Code: 02401, 008101,023401, 

022901, 022702, 022703, 008001, 

023501, 023503, 023104, 024407, 

024403, 024409, 023306 

DP Barcode: 319168 

MEMORANDUM

DATE: April 20, 2006 

SUBJECT: Response to Comments on the Ecological Risk Assessment for ReRegistration of Copper sulfate (Case#0636), Group II copper compounds 

(Case #0649), and Copper salts (Case#4029) for use on crops and as direct 

water applications (Docket ID EPA-HQ-OPP-2005-0558 

FROM: Paige Doelling Brown, Ph.D., Fisheries Biologist 

 James Hetrick, Ph.D., Senior Chemist 

Nancy Andrews, Ph.D, Branch Chief 

 Environmental Risk Branch 1 

Environmental Fate and Effects Division (7507C) 

TO: Rosanna Louie, Chemical Review Manger 

 Reregistration Branch 3 (RB3) 

 Special Review and Re-Registration Division (7505C) 

EFED has reviewed the comments submitted to the Agency during the public comment 

period. A substantial number of responses (~120) were received, and rather than address 

each one individually, EFED has grouped them into categories, and addressed common 

issues within the categories. 

1
General Comments and Input from the Copper Sulfate Task Force 

Two comments (#0018 and 0032) were received that supported continued use of coppercontaining products for both agricultural crops and direct water applications. One of 

these documents, the response from the Copper Sulfate Task Force (CSTF) included an 

attachment detailing use rates and application frequencies for various crops. 

Characterizing the use patterns and application rates for the vast array of both coppercontaining products and crops has been a challenge for both the Agency and the CSTF. 

The data provided by the CSTF indicate that most agricultural users appear to be 

applying copper-containing products at rates substantially lower than the rates currently 

permitted on some labels. Application rates provided by the CSTF are similar to the 

“State Average” rates determined by BEAD and used in the version of the ecological risk 

assessment released for public comment. The CSTF application rate data, along with 

refined State Average rates determined by BEAD, and input from specific grower groups 

(See Agricultural Uses section) have been incorporated into the revised ecological risk 

assessment. 

Comments on Direct Water Uses 

The Agency received approximately 70 comments regarding the direct application of 

copper-containing products to water. Primarily, this was from users who apply the 

products to control nuisance algae and aquatic weeds, but some organizations also use 

copper to control other organisms, such as snails and leeches, which may transmit 

disease. Some of these comments contained detailed information about application rates 

and practices. Since the completion of the version of the ecological risk assessment 

released for public comment, BEAD has compiled a more detailed use characterization 

for the direct use applications. This use characterization, updated with inputs from the 

public comment has been incorporated into the revised ecological risk assessment. 

Comments on Agricultural Uses 

The Agency received approximately 40 comments regarding the use of copper-containing 

products on agricultural crops. Several of these (#0017, #0041, #0091, and #0099) 

contained detailed information regarding use practices and application rates for certain 

crops. Application rates and patterns (timing, frequency, interval) provided by these 

groups was consistent with the State Average rates determined by BEAD, and the CSTF 

application rate data, and has been incorporated into the revised ecological risk 

assessment. 

Comments from California Water Resource Management Agencies 

The Agency received several comments from water resource management agencies in the 

state of California (#0123, #0125, #0130,#0148, #0152). While not all agencies had the 

same specific comments, there were several common themes. 

2
• No saltwater organism specific assessment. The Biotic Ligand Model (BLM) , as 

it currently exists, is not appropriate for evaluation of saltwater environments. A section 

addressing these effects has been added in the revised document. The saltwater 

assessment includes risk quotients (RQs) derived from total dissolved copper rather than 

activity based RQs like the freshwater assessment. 

• No assessment of copper-containing compounds used as root killers in sewer 

systems, and other urban uses (including turf uses, wood preservatives and swimming 

pools). The assessment has been updated to include an analysis of copper input into 

sewer systems due to its use as a root-killer. The currently existing “Down the Drain” 

model previously used by the Agency to address chemicals such as permethrin was used 

for the analysis. Antimicrobial uses are not evaluated by EFED 

• Comparison to and coordination with Aquatic Life Criteria established by the 

Agency’s Office of Water (OW). EFED has coordinated closely with the Office of Water 

in development of the ecological risk assessment. The Daphnia acute LC50 used in 

EFED’s aquatic assessment is essentially the same value used for the establishment of the 

Aquatic Life Criteria, and both programs have used the BLM to incorporate copper 

speciation effects. The two programs have different procedures to determine final values. 

OW uses a community-based approach, and sets the value to be protective of 95% of the 

organisms in the species sensitivity distribution. EFED determines risk quotients based 

on estimated environmental concentrations (EECs) and the most sensitive species within 

a particular taxa group (i.e., fish, aquatic invertebrates, aquatic plants). The Criterion 

Maximum Concentration (CMC) of 2.1 ppb derived for copper is based on LC50 values 

normalized to laboratory water, which represents a situation where copper is readily 

bioavailable, and thus, lower concentrations are more toxic. As the water quality criteria 

document (EPA 2003, pg 14) notes, “site-water chemistry parameters are needed to 

evaluate a criterion.” The copper pesticide ecological risk assessment is a site-specific 

evaluation using actual water chemistry data, and results are presented in terms of 

number of sites exceeding the EFED pre-established levels of concern (LOC) for various 

concentrations of copper introduced into the system due to use of a pesticide. Thus, the 

process of the evaluations is different, but the end results are consistent. The explanation 

of how the evaluation methods compare has been clarified in the revised ecological risk 

assessment. 

• Use of median water chemistry conditions. In order to account for variations in 

water chemistry on a national basis, EFED used median water quality data from USGS 

water monitoring sites. Because water chemistry conditions at a particular site can vary 

both temporally and spatially, the selection of median water chemistry parameters at each 

site was used to represent the most likely water or typical water quality conditions. This 

approach limits consideration of temporal variations in water chemistry parameters. It 

was assumed that variations in water quality conditions within a monitoring sites 

(temporal scale) is lower than variation in water quality conditions among water 

monitoring sites (spatial scale). The use of USGS water quality data, however, allowed a 

spatially explicit assessment because all the monitoring sites are geo-referenced, which 

promotes GIS analysis for regional and local effects from water quality conditions on 

copper speciation. The distribution of monitoring sites encompassed a range of 

conditions, including some very vulnerable water chemistries. OW is currently working 

3
on implementation guidance for calculating site-specific criteria for use of water quality 

data in the BLM model.

• Request for a cumulative environmental risk assessment. In general, OPP does 

not conduct cumulative ecological risk assessments. For copper, because it has so many 

potential routes for introduction into the environment, a cumulative assessment would go 

well beyond the scope of authority granted to OPP under FIFRA. 

• Label language (aquatic hazard, no use 96 hours prior to rain). One comment 

suggested warnings and restrictions on the label. Currently, labels contain an aquatic 

hazard statement, and will continue to do so. No use 96 hours prior to rain may be 

considered as a mitigation measure but could seriously affect the effectiveness of coppercontaining compounds on agricultural crops. 

Comments on Environmental Fate of Copper and Appropriateness of Models 

The Agency received several comments (#0154, #160, #0179, #0181) that provided 

background information on the environmental fate of copper, and suggested alternative 

methods and/or models that could be used to estimate exposure concentrations. 

• Appropriateness of PRZM-EXAMS to evaluate metal concentrations in runoff. In 

performing the initial assessment, EFED recognized that PRZM-EXAMS was developed 

primarily for organic chemicals commonly used as pesticides. Both components of the 

linked model address partitioning between water and soil or sediment using Kd or Koc. 

While the ionic state of copper affects binding, it is unlikely to differ significantly from 

the partitioning beyond the range of certainty associated with the model. EFED 

compared the estimates produced by PRZM and EXAMS to field studies and mineral 

stability diagrams to ensure estimated copper concentrations were reasonable. The BLM 

was used to address copper speciation in the water column. 

• Bioavailability of copper in soil and sediment. EFED agrees that copper 

concentrations in soil and sediment may exceed concentrations determined to be toxic to 

certain organisms, yet not produce noticeable toxic effects because of binding. This 

concept is taken into account in the evaluations of those compartments. 

• Behavior of chelated coppers differ from copper salts. Because of the range of 

products addressed in the risk assessment, EFED made the simplifying assumption that 

all compounds used for direct water treatments will dissociate rapidly. The document 

notes that some compounds will dissociate more slowly, and thus produce lower 

concentrations of copper. Typically, compounds that dissociate slower than the salts are 

used at lower concentrations. Ecological effects are evaluated based on the copper 

activity (i.e., bioavailability), thus assuming that all the copper added to the water system 

is available for partitioning (in EXAMS) and speciation (in the BLM) allows EFED to 

estimate an upper bound to exposure. 

4
UNITED STATES ENVIRONMENTAL PROTECTION AGENCY

WASHINGTON, D. C. 20460 

 OFFICE OF

PREVENTION, PESTICIDES 

AND TOXIC SUBSTANCES 

Chemical: Coppers (Copper sulfate, copper 

group II, copper salts, copper and oxides) 

PC Code: 02401, 008101,023401, 022901, 

022702, 022703, 008001, 023501, 023503, 

023104, 024407, 024403, 024409, 023306 

DP Barcode: 319168 

MEMORANDUM

DATE: April 20, 2006 

SUBJECT: Transmittal Memo for the Ecological Risk Assessment for Re-Registration of 

Copper sulfate (Case#0636), Group II copper compounds (Case #0649), and 

Copper salts (Case#4029) for use on crops and as direct water applications 

(Docket ID EPA-HQ-OPP-2005-0558) 

FROM: Paige Doelling Brown, Ph.D., Fisheries Biologist 

 James Hetrick, Ph.D., Senior Chemist 

Nancy Andrews, Ph.D, Branch Chief 

 Environmental Risk Branch 1 

Environmental Fate and Effects Division (7507C) 

TO: Rosanna Louie, Chemical Review Manger 

 Reregistration Branch 3 (RB3) 

 Special Review and Re-Registration Division (7505C) 

Attached please find Environmental Fate and Effects Division’s (EFED) revised environmental 

risk assessment for the proposed re-registration of copper sulfate, copper group II compounds, 

and copper salts. Revisions are based on comments received during the public comment period. 

No major technical changes were made, but application rates appear to be more similar to the 

state average rates used in the version released for public comment. EFED has modified the 

agricultural use section to more thoroughly evaluate exposure and effects at the lower application 

rates. 
The copper compounds are produced by a variety of manufacturers, and are currently 

registered for a wide variety of agricultural uses, direct water applications, and for use in 

domestic sanitary sewers to control growth of tree roots. Antimicrobial applications are 

not addressed in this ecological risk assessment. 

As a bridging strategy to address the range of copper compounds included in this action, 

EFED has evaluated all of them on the basis of ionic copper (the cupric ion Cu2+), 

regardless of the counter ion, or other moieties included in the complex. Where physical 

or molecular properties of the complex affect the fate and or toxicity of a particular 

compound differently than the general case, it is discussed qualitatively in the text. 

Copper is a unique pesticide. In addition to having toxic properties, it also is an essential 

trace element for organisms. It is an element and will not break down further. Thus 

copper introduced to the environment, as a pesticide will continue to be processed 

through natural geochemical cycling. Because of this, EFED has addressed soil and 

sediment accumulation in the risk assessment in addition to the usual direct endpoints 

evaluated. 

Copper is highly reactive, especially in the aquatic environment, and may exist in a 

number of ionic states, ion-pairs, and organic complexes simultaneously (known as 

“speciation”), as well as sorbed to suspended particles. Thus, the total dissolved 

concentration is not truly reflective of potential copper toxicity. To account for copper 

speciation, EFED opted to use the Biotic Ligand Model (BLM) in conjunction with the 

Pesticide Root Zone Model (PRZM)/EXposure Analysis Modeling System (EXAMS) 

model for the freshwater endpoints. The BLM was developed for and used by EPA’s 

Office of Water to develop Draft Ambient Aquatic Life Criteria for Copper to perform 

the aquatic toxicity assessment. It has been reviewed and approved by EPA’s Scientific 

Advisory Board (SAB). Currently, BLM has only been parameterized and validated for 

freshwater environments, thus the saltwater evaluation is on the basis of dissolved copper 

rather than copper activity. The saltwater evaluation is also consistent with the Draft 

Ambient Aquatic Life Criteria for Copper developed by OW. 

The water quality data used in BLM simulation were derived from 811 USGS monitoring 

sites to evaluate site-specific toxicity and copper speciation in a variety of surface water 

conditions. It is assumed these water quality conditions are representative of water 

quality in ambient surface across the United States. Thus, the freshwater aquatic 

evaluation is presented in terms of percentage of sites where the risk quotients (RQ) 

exceed a particular level of concern (LOC), rather than just a single RQ value. 

Based on the label analysis provided by BEAD, application rates for copper vary widely, 

both for crops (0.3-32 lbs Cu/acre) and direct water applications (0.25-3.4 ppm dissolved 

Cu). Thus, while EFED has assessed the risk associated with the highest label permitted 

application rates from representative labels and state average use rates, we have also 

included a number of “what-if” estimations to provide additional benchmarks for the risk 

managers. Updated assessments focus on application rates between 1-7.5 lb Cu/A. Input 

during the public comment period indicates most agricultural applications fall within this 

range. 

2
Key components of the risk assessment are as follows: 

Aquatic Assessment 

• Site water chemistry, especially the alkalinity, pH, and dissolved organic carbon 

(DOC), determines copper toxicity through speciation of dissolved Cu. Because 

site conditions differ, EFED has used the BLM and USGS monitoring data to 

develop site specific LC50s for freshwater systems in terms of dissolved Cu1

 as 

well as predict the concentration of Cu2+ ion (Cu activity). Exposure to copper 

was based on the concentration of Cu2+ ion rather than dissolved Cu. Aquatic 

RQs were developed based on Cu activities. 

• An analysis of ambient water quality conditions at the USGS monitoring stations 

indicate five out of the 811 monitoring sites (<1%) have ambient Cu 2+

concentrations exceeding the Daphnia LC50 (on an activity basis) . Water quality 

conditions at these sites included low pH (acidic), low DOC, and low alkalinity. 

Additionally, some of the sites were associated with point sources of Cu 

contamination such as stormwater outfalls. 

• Based on water chemistry, the site specific estimated LC50s for aquatic 

invertebrates ranged from 0.3 to 1,900 ppb dissolved Cu, with the majority (90%) 

between 1 and 200 ppb dissolved Cu. The majority (91%) of site specific LC50s 

for fish were <600 ppb dissolved Cu. 

• Direct water applications typically recommend dissolved copper concentrations of 

0.1-1 ppm, and sometimes higher, depending on the target pest. A concentration 

of 990 ppb dissolved Cu, correlative to a target concentration of 1 ppm dissolved 

Cu (for algal control) was used to evaluate effects from this type of application. 

At this concentration, RQs at 100% of the sites exceed acute LOCs for 

invertebrates, fish, and aquatic plants. Chronic RQs at >95% of the sites exceed 

LOCs for invertebrates and fish. Typically, only a portion of a waterbody or a 

band along the shoreline is treated. EFED evaluated effects of treating only a 

portion of the water body, using the EXAMs standard farm pond. This may allow 

fish or mobile invertebrates to move away from the treated area, but will affect 

more sedentary or less mobile organisms. Generally, at even the lowest 

application rate (0.1 ppm) approximately 25 % of the sites in the USGS data set 

would exceed the acute risk LOC for fish, and 85% would exceed the acute risk 

LOC for aquatic invertebrates. Minimizing adverse effects of non-target 

organisms will depend on careful use by the resource managers who apply the 

products. 

 

1

 The risk assessment is based on concentration of Cu2+ ion (Cu activity) because this 

accounts for the speciation of copper, which greatly affects toxicity. Site-specific LC50s 

and runoff concentrations are presented in terms of dissolved Cu because that is what is 

most commonly measured and regulated. 

3
• Orchard crops and grapes: Orchard crops and grapes typically have the highest 

application rates, and based on usage estimates from BEAD, are the greatest users 

of copper sulfate and copper hydroxide. Estimated peak concentrations at label 

rates ranged from 17 to 350 ppb total dissolved copper depending on crop and 

application site. At the highest concentration (350 ppb dissolved Cu, PA apple 

scenario) RQs at >99% of the sites exceed the acute LOC for aquatic invertebrates 

and plants, and RQs at 80% of the sites exceed the acute LOC for fish. The 

chronic LOC is exceeded at 98% of the sites for aquatic invertebrates and 45% of 

the sites for fish. 

• Row crops: Row crop label application rates are substantially lower than orchard 

crops. Usage estimates from BEAD show that tomatoes and peppers are the most 

heavily treated with copper sulfate and copper hydroxide. Estimated peak 

concentrations ranged from 2 to 55 ppb dissolved Cu. At the highest 

concentration (55 ppb dissolved Cu) RQs at 58% of the sites exceed the acute 

LOC for aquatic invertebrates, RQs at 14% of the sites exceed the acute LOC for 

fish, and RQs at 98% of the sites exceed the acute RQ for aquatic plants. The 

chronic LOC is exceeded at 55% of the sites for aquatic invertebrates and 10% of 

the sites for fish. 

• EFED analyzed a wide range of use scenarios, and developed an equation to 

correlate the number of sites exceeding LOCs with the concentration of dissolved 

copper, and an equations to correlate the peak concentration of dissolved copper 

in the water body with application rate. Peak concentrations, while partly a 

function of application rate, can vary widely dependent on site characteristics, 

climate, and timing of application. Effects expected at various application rates 

ranging from 1 to 7.5 lb Cu/A are detailed in the executive summary of the risk 

assessment. At an application rate of 3 lb Cu/A, 10% of the sites evaluated are 

expected to exceed the acute risk LOC for freshwater invertebrates, the most 

sensitive taxa. At an application rate of 5.0 lb Cu/A, the acute risk LOC for 

saltwater fish is exceeded. 

• Based on field studies submitted to the Agency, the dissipation half-life for 

dissolved copper is 10 days. This dissipation half-life reflects the time for 50% 

disappearance of copper from the water column into the sediment. Application 

intervals listed in labels include “as needed” and 7-14 day intervals, potentially 

introducing copper into the environment much more quickly than it will dissipate. 

4
• A substantial portion (80-90%) of the copper that runs off the field is sorbed to 

suspended sediment in runoff waters. While this component is not expected to be 

readily bioavailable, copper concentrations in the sediment of the receiving waters 

or depositional areas downstream will be elevated. Estimated first year sediment 

pore water2 concentrations ranged from 0.4 to 45 ppb dissolved Cu. Estimated 

sediment pore water concentrations after 30 years of accumulation ranged from 

13.7 to 2680 ppb dissolved Cu. Sediment pore water concentrations, on both a 1-

year and 30-year basis, may be high enough to cause toxic effects to benthic 

organisms in some locations. 

Terrestrial Assessment

• The acute oral LD50 for birds was 98 ppm Cu and for mammals was 114 ppm Cu. 

The acute dietary LD50 for birds was 991 ppm Cu. Copper is classed as 

moderately toxic to both birds and mammals. 

• The NOAEC for monocots was 6.8 lb Cu/acre and for dicots was 36.7 lb Cu/acre. 

• In all cases, toxicity values for various compounds were expressed on the basis of 

copper, rather than the copper containing compound. This somewhat reduced the 

variability in toxicity levels between the various compounds. Copper sulfate 

appears to be more toxic than some of the other compounds, possibly due to the 

fact that it is extremely soluble, thereby making the Cu2+ ion more readily 

available to the organism following ingestion. Some studies suggest that the 

composition of food contaminated with copper may also affect bioavailability. 

Because organisms have homeostatic mechanisms for regulating copper uptake, 

EFED has evaluated effects on terrestrial organisms based on dietary toxicity tests 

whenever possible. Dietary-based acute toxicity data were not available for 

mammals, so a copper absorption efficiency correction factor was applied. 

• As with the aquatic assessment, EFED evaluated terrestrial effects expected at 

various application rates ranging from 1 to 7.5 lb Cu/A. These effects are detailed 

in the executive summary of the risk assessment. At an application rate of 3 lb 

Cu/A birds and mammals consuming grass and/or leaves in the treated area could 

be affected acutely. LOCs for endangered birds and mammals are exceeded for all 

food categories. Chronic risk LOCs exceeded in all food categories for both birds 

and mammals. 

 

2

 Sediment pore water is an estimate of the bioavailable fraction. 

5
• At sites where copper is continuously applied, it will accumulate in the soil, 

although the degree of bioavailability is uncertain, and will vary dependent on site 

conditions. Concentrations of 60-100 ppm Cu are potentially harmful to soil 

invertebrates, terrestrial plants, and soil microorganisms. Based on modeling, 

potentially harmful concentrations may be reached within 2-20 years, dependent 

on site conditions, application rates, and frequency of application. Although the 

model evaluates the application site, overspray areas where wildlife may reside 

and/or forage may be affected as well. 

• Some plants concentrate copper from soil, potentially making it available to 

herbivorous and omnivorous organisms. Copper concentrations in plants were 

calculated, and appear to remain <100 ppm, even at the highest application rate. 

While approaches the dose-based LD50 for mammals, it is significantly below the 

dietary-based LD50 for birds. Concentration of copper by plants is expected to 

pose little to no risk for birds and mammals. 

Uncertainities, Assumptions, and Limitations 

• PRZM/EXAMS modeling was used to estimate the runoff and drift of applied Cu. 

This modeling was conducted using a range of Kd values to represent differential 

sorption in sand and clay-textured soils. With the exception of aquatic dissipation 

from the water column, Cu was assumed to be persistent in soil and sediment. A 

comparison of edge-of-field Cu copper loss and distributions of Cu on suspended 

sediment and runoff water were similar for PRZM simulations and field 

monitoring studies. 

• Median water quality parameters for 811 USGS monitoring sites were used to 

represent water quality conditions across the United States. These data are 

expected to represent the most likely water quality conditions in ambient surface 

waters. 

• Chemical speciation modeling using the BLM was conducted without 

consideration of competitive equilibria with other common metals (such as Fe3+, 

Zn2+, Al3+, etc.) or redox conditions. Redox conditions in the water column and 

surface sediments were assumed to be oxic (aerobic). This assumption is an 

expected condition in order to support aquatic organisms. The lack of 

consideration of other metals in the speciation modeling is expected to 

underestimate prediction of Cu2+ concentrations in the water column due to the 

metal competition for ion pairs and ligands. Cupric ion concentrations, as 

predicted by PRZM/EXAMS/BLM, are within the range of Cu2+ concentrations 

for known Cu minerals. These data suggest the simulation modeling is not 

outside of the thermodynamic bounding conditions for Cu mineral stability. 

6
 

• A bridging strategy was implemented to assess a variety of Cu compounds and 

complexes using a unified assessment approach. This strategy assumes complete 

dissociation into Cu2+ and the counter ion. This assumption is expected to 

provide a conservative estimate of Cu2+ concentrations in the exposure 

assessment. 

• Application rates for the various copper compounds were derived from 

representative labels. Highest label application rates were 32 lb Cu/acre for 

orchard crops and 3.6 lb Cu/acre for row crops. These application rates appear to 

be higher than the rates generally used. Labels did not clearly state the number of 

applications or a maximum application rate of copper for a year or season, and 

input from growers suggest they apply copper-containing compound with a high 

frequency when disease pressure is high. Therefore, the exposure assessment 

assumed 4 applications at 7-day intervals. 

• First year peak aquatic copper concentrations were used due to the long half-life 

of copper, rather than the 1-in-10 year peak concentrations typically used in 

EFED assessments. Because of the way the model is written, the long half-life 

made copper appear to accumulate in the water body at much greater 

concentrations than would actually occur. However, the first year peak 

concentration may not be the highest peak concentration in the 30-year 

simulation. 

• The plant uptake of Cu was estimated using a regression equation. This 

regression equation has an extremely low coefficient of determination (r2

). 

Therefore, there is considerable uncertainty associated with predicted Cu uptake. 

• The BLM has been parameterized, validated, and tested for animals in freshwater 

ecosystems. It is appropriate for assessing copper speciation for aquatic plants, 

but not toxicity. A version is currently under development to address aquatic 

plants, as well as marine and estuarine systems. 

• Copper is both highly reactive and a trace nutrient, thus there is significant 

uncertainty in estimating effective toxic doses to terrestrial organisms. 

Composition of the diet, homeostatic mechanisms, and species sensitivity may 

vary widely. 

Data Requirements 

EFED used data from registrant-submitted studies, other Agency programs, and open 

literature. No specific data requirements were identified. 

7
Endangered Species Statement 

Endangered species acute risk LOCs were exceeded for fresh- and saltwater 

invertebrates, and saltwater fish at application rates of 1 lb Cu/A. Endangered species 

acute risk LOCs for freshwater fish and amphibians were exceeded at 8% of the sites at 

application rates of 3 lb Cu/A. At 1 lb Cu/A endangered species acute risk LOCs were 

exceeded for herbivorous and insectivorous birds, reptiles, terrestrial phase amphbians, 

and mammals. Chronic risk LOCs were exceeded for all food groups in the affected taxa. 

Based on available data, aquatic vascular plants are not expected to be affected except in 

the case of direct water applications. Terrestrial plants were the only category of 

organism quantitatively evaluated that did not exceed endangered species LOCs. 

EFED conducted LOCATES search on the agricultural crops identified as the most 

common applicators of copper-containing pesticides to identify species with a high 

probability of exposure but other species may be affected as well. LOCATES identified 

a total of 467 animal species as occurring in counties containing these crops. 

Additional analysis regarding co-occurrence of pesticide application and species location, 

and better information regarding application rates and practices on specific crops are 

required to refine the estimate of what endangered species may be affected by use of 

copper-containing pesticides. 

8
Ecological Risk Assessment for 

Re-registration 

Copper-Containing Pesticides 

(Case#0636 Copper Sulfate, 

Case#0649 Group II Copper Compounds, 

Case #4029 Copper Salts, and 

Case # 4025 Copper and Oxides) 

April 20, 2006 

 
 Table of Contents

1.0 Executive Summary................................................................................................................ 8 

1.1 Nature of Stressor ............................................................................................................... 8 

1.2 Status of Labels................................................................................................................... 9 

1.3 Copper Speciation and Fate ................................................................................................ 9 

1.4 Potential Risk.................................................................................................................... 10 

1.4.1 Aquatic Assessment.................................................................................................. 10 

1.4.2 Terrestrial Assessment.............................................................................................. 11 

1.4.3 Risk Conclusions ...................................................................................................... 12 

1.5 Endangered Species Assessment ...................................................................................... 14 

2.0 Problem Formulation ............................................................................................................ 16 

2.1 Stressor Source and Distribution .................................................................................. 18 

2.1.1 Chemical and Physical Properties............................................................................. 18 

2.1.2 Mode of Action......................................................................................................... 18 

2.2 Use Characterization......................................................................................................... 19 

2.2.1 Agricultural Uses ...................................................................................................... 19 

2.2.2 Direct Water Applications ........................................................................................ 20 

2.2.3 Urban Uses................................................................................................................ 21 

2.3 Environmental Exposure Strategy .................................................................................... 21 

2.4 Site Vulnerability Analysis and Scenario Selection ......................................................... 23 

2.5 Assessment Endpoints ...................................................................................................... 25 

2.5.1 Ecosystems Potentially at Risk ................................................................................. 25 

2.5.2 Ecological Effects ..................................................................................................... 26 

2.6 Conceptual Models ........................................................................................................... 26 

2.7 Risk Hypotheses............................................................................................................... 29 

2.8 Key Uncertainties and Information Gaps ......................................................................... 29 

3.0 Aquatic Assessment.......................................................................................................... 31 

3.1 General Approach ............................................................................................................. 31 

3.1.1 Agricultural Uses ...................................................................................................... 31 

3.1.2 Direct Aquatic Uses .................................................................................................. 32 

3.1.3 Urban Uses (Root Killers) ........................................................................................ 35 

3.2 Aquatic Exposure Assessment.......................................................................................... 35 

3.2.1 PRZM-EXAMS Modeling Inputs and Scenario Selection ....................................... 35 

3.2.2 USGS Monitoring Data and BLM Water Chemistry Parameters............................. 38 

3.2.3 PRZM-EXAMS Modeling Output............................................................................ 42 

3.2.4 Spray Drift Exposure Estimates................................................................................ 46 

3.2.5 PRZM/EXAMS Output-Sediment Pore Water Cu Concentrations.......................... 47 

3.2.6 Evaluation of Aquatic Exposure Modeling............................................................... 49 

3.2.7 Chemical Equilibrium Analysis................................................................................ 50 

3.2.8 Direct Aquatic Application....................................................................................... 54 
3 

3.2.9 Urban Uses (Root-Killers) ........................................................................................ 55 

3.3 Ecological Effects Analysis .............................................................................................. 56 

3.3.1 BLM Endpoints and Corrections .............................................................................. 56 

3.3.2 Aquatic Plant Guideline Data ................................................................................... 59 

3.3.3 Aquatic Incident Data Review.................................................................................. 59 

3.3.4 Bioaccumulation ....................................................................................................... 60 

3.4 Risk Estimation................................................................................................................. 60 

3.4.1 Method of Assessment.............................................................................................. 60 

3.4.2 Analysis of Site Chemistry ....................................................................................... 61 

3.4.3 RQ Summary for Agricultural Uses ......................................................................... 66 

3.4.4 RQ Summary for Direct Water Applications............................................................ 77 

3.4.5 RQ Summary for Urban Uses (Root-killers) ............................................................ 80 

3.5 Risk Description................................................................................................................ 81 

3.5.1 Agricultural Crops .................................................................................................... 81 

3.5.2 Direct Water Applications ........................................................................................ 85 

3.5.3 Urban Uses (Root-killers)......................................................................................... 85 

3.5.4 Sediment Accumulation............................................................................................ 86 

4.0 Terrestrial Assessment.......................................................................................................... 86 

4.1 Exposure ........................................................................................................................... 86 

4.1.2 Avian and Small Mammal Exposure - (TREX)........................................................ 86 

4.1.3 Terrestrial Plant Exposure - (TerrPlant) ................................................................... 88 

4.1.3 Soil Accumulation .................................................................................................... 90 

4.2 Effects Analysis ................................................................................................................ 92 

4.2.1 Avian Guideline Data ............................................................................................... 93 

4.2.2 Small Mammal Data ................................................................................................. 96 

4.2.3 Terrestrial Plants, Insects, and Microbial Processes................................................. 98 

4.2.4 Terrestrial Incident Data Review............................................................................ 100 

4.3 Terrestrial Risk Estimation ............................................................................................. 101 

4.3.1 Avian Risk Estimation ............................................................................................ 101 

4.3.2 Mammals Risk Estimation...................................................................................... 106 

4.3.3 Plants, Insects, and Microbial Processes................................................................. 111 

4.3.4 Soil Accumulation and Plant Bioaccumulation ...................................................... 112 

4.3 Terrestrial Risk Description............................................................................................ 114 

4.4.1 Avian and Mammals............................................................................................... 114 

4.4.2 Plants, Insects, and Microbial Processes................................................................. 115 

5.0 Endangered Species Analysis ............................................................................................. 116 

5.1 LOCATES....................................................................................................................... 117 

5.2 Probit Analysis................................................................................................................ 118 

5.2.1 Aquatic Organisms.................................................................................................. 118 

5.2.2 Terrestrial Organisms.............................................................................................. 118 

5.3 Aquatic Ecosystems........................................................................................................ 119 

5.4 Terrestrial Ecosystems.................................................................................................... 119 
4 

APPENDIX A Aquatic Exposure Model and Results................................................................ 123 

APPENDIX B TerrPlant Model and Results ............................................................................. 124 

APPENDIX C Ecological Effects Data...................................................................................... 125 

APPENDIX D The Risk Quotient (RQ) Methodology and Levels of Concern (LOC) ............. 126 

APPENDIX E Detailed Risk Quotients ...................................................................................... 127 

APPENDIX F Summary of Endangered and Threatened Species............................................. 128 

APPENDIX K Ecotoxicity Bibliography................................................................................... 129 
5 

List of Tables 

 

Table 1 Summary of Risk Conclusions ....................................................................................... 13 

Table 2 Summary of Endangered Species Risk Conclusions ...................................................... 15 

Table 3 Copper Compounds Addressed in this RED................................................................... 17 

Table 4 Usage Analysis for Copper Sulfate and Copper Hydroxide........................................... 20 

Table 5 Application Rates for Cu(II) Ligands and Organic Salts................................................ 33 

Table 6 PRZM/EXAMS Input Parameters for Cu....................................................................... 36 

Table 7 Application Rates and Intervals Used in PRZM/EXAMS Modeling............................. 37 

Table 8 Summary of USGS Water Quality Data Used in the BLM1

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

Table 9 Suspended Sediment USGS Monitoring Data................................................................ 42 

Table 10 Estimated Water Column Dissolved Copper Concentrations Based on Label 

Application Rates.................................................................................................................. 43 

Table 11 Estimated Water Column Dissolved Copper Concentrations Based on State Average 

Rates...................................................................................................................................... 44 

Table 12 Estimated 60-day Water Column Dissolved Copper Concentrations........................... 45 

Table 13 Aerial Spray Drift Loadings ......................................................................................... 46 

Table 14 Ground Spray Drift Loadings ....................................................................................... 46 

Table 15 PRZM/EXAMS Estimated Sediment Pore Water Dissolve Copper Concentrations ... 48 

Table 16 Comparison of Predicted and Measured Runoff Concentrations ................................. 49 

Table 17 Estimated Dissolved Copper Concentrations for Direct Water Applications............... 54 

Table 18 Predicted Concentrations for Direct Applications........................................................ 55 

Table 19 Estimated Cu2+ in Receiving Waters from Root-Killer ................................................ 55 

Table 20 Aquatic Plant Toxicity Guideline Studies .................................................................... 59 

Table 21 Aquatic RQ Summary Table: Orchard Label Rates ..................................................... 66 

Table 22 Aquatic RQ Summary Table: Row Crop Label Rates.................................................. 67 

Table 23 Aquatic RQ Summary Table: Orchard Average Application Rate............................... 68 

Table 24 Aquatic RQ Summary Table: Row Crop Average Application Rate ........................... 69 

Table 25 Estimated Application Rates1

 Equivalent to 10% Site Exceedences............................ 77 

Table 26 Aquatic RQ Summary Table: Direct Water Applications ............................................ 78 

Table 27 Estimated Percent of Water Body Treated at 1 ppm Cu2+ Equivalent to 10% Site 

Exceedences.......................................................................................................................... 80 

Table 28 Percentage of Sites Exceeding LOCs for Use of Copper as a Root-killer.................... 80 

Table 29 Comparison of Application Rates Derived from Different Sources............................. 82 

Table 30 Summary of Acute Risk LOC Exceedences in Aquatic Environments........................ 85 

Table 31 Range of Sediment Pore Water Dissolved Copper Concentrations for Various 

Scenarios............................................................................................................................... 86 

Table 32 Estimated Environmental Concentrations Based on Label Application Rates............. 88 

Table 33 Estimated Environmental Concentrations Based on Average Application Rates ........ 88 

Table 34 Estimated Environmental Concentrations Based on Label Application Rates............. 89 

Table 35 Estimated Environmental Concentrations Based on Average Application Rates ........ 89 

Table 36 Avian Guideline Data ................................................................................................... 94 

Table 37 Avian Data from ECOTOX .......................................................................................... 95 
6 

Table 38 Acute Oral Toxicity in Rats (Guideline 81-1) .............................................................. 96 

Table 39 Chronic Toxicity in Rats (Guideline 83-3, developmental).......................................... 97 

Table 40 Avian and Mammal Screening Values for Superfund Site (Sample et al., 1996) ........ 97 

Table 41 Small Mammal Data from ECOTOX ........................................................................... 98 

Table 42 Terrestrial Plant Data from ECOTOX.......................................................................... 99 

Table 43 Terrestrial Insect Guideline Data.................................................................................. 99 

Table 44 Earthworm, Plant, and Microbial Processes Screening Values for Superfund Sites 

(Efroymson et al., 1997a, Efroymson et al., 1997b)........................................................... 100 

Table 45 Avian RQ Summary Table: Orchard Label Rates ...................................................... 102 

Table 46 Avian RQ Summary Table: Row Crop Label Rates................................................... 103 

Table 47 Avian RQ Summary Table: Orchard Average Rates.................................................. 104 

Table 48 Avian RQ Summary Table: Row Crop Average Rates ............................................. 105 

Table 49 Mammal RQ Summary: Orchard Label Rates............................................................ 107 

Table 50 Mammal RQ Summary: Row Crop Label Rates ........................................................ 108 

Table 51 Mammal RQ Summary: Orchard Average Rates ....................................................... 109 

Table 52 Mammal RQ Summary: Row Crop Average Rates.................................................... 110 

Table 53 Terrestrial Plant RQs Based on Maximum Label Application Rate.......................... 111 

Table 54 Summary of LOC Exceedences and RQs for Birds and Mammals............................ 115 

Table 55 Summary of Endangered Taxa Potentially at Risk..................................................... 116 

Table 56 Number of Endangered Species Potentially Affected by Copper-Containing Pesticides

............................................................................................................................................. 117 
7 

List of Figures 

Figure 1 Environmental Fate Bridging Strategy for Cu Minerals and Complexes...................... 22 

Figure 2 Conceptual Model for Agricultural Uses ...................................................................... 27 

Figure 3 Conceptual Model for Direc Water Applications.......................................................... 28 

Figure 4 Cumulative Probability Distribution for Median pH..................................................... 40 

Figure 5 Cumulative Probability Distribution for Median DOC................................................. 40 

Figure 6 Cumulative Probability Distribution for Median Alkalinity ......................................... 41 

Figure 7 Cu Activities in Ambient Surface Waters on Cu(II) Mineral Stability Diagram.......... 52 

Figure 8 Cu Activities for PA Apple Scenario on Cu(II) Mineral Stability Diagram ................. 52 

Figure 9 Sediment Pore Water Activites on Cu(II) Mineral Stability Diagram .......................... 53 

Figure 10 Site Specific Aquatic Assessment Using the BLM ..................................................... 58 

Figure 11 Percentage of Sites Exceeding Acute Risk LOC, Aerial Spray Drift.......................... 75 

Figure 12 Percentage of Sites Exceeding ES Acute Risk LOC, Aerial Spray Drift.................... 76 

Figure 13 Percentage of Sites Exceeding Acute Risk LOC,Ground Spray Drift ........................ 76 

Figure 14 Percentage of Sites Exceeding ES Acute Risk ES LOC, Ground Spray Drift............ 77 

Figure 15 Percentage of Sites Exceeding Acute Risk LOC, Direct Water Application.............. 79 

Figure 16 Percentage of Sites Exceeding ES Acute Risk LOC, Direct Water Application ........ 79 

Figure 17 Correlation of Runoff Concentrations with Percentage of Exceedences .................... 84 

Figure 18 Percentage of Sites Exceeding Acute Risk LOC, Agricultural Uses .......................... 84 

Figure 19a Soil Accumulation at Maximum Label Rate for PA Apple Scenario......................... 91 

Figure 19b Soil Accumulation at State Average Rate for PA Apple Scenario............................. 91 

Figure 20a Estimated Plant Uptake of Copper at Maximum Label Rate for PA Apple Scenario

............................................................................................................................................. 113 

Figure 20b Estimated Plant Uptake of Copper at State Average Rate for PA Apple Scenario.. 113 

List of Maps 

Map 1 Sites with Vulnerable Water Chemistry ........................................................................... 24 

Map 2 Estimated Site Specific Daphnia LC50.............................................................................. 63 

Map 3 Estimated Site Specific Trout LC50 .................................................................................. 64 

Map 4 Measured Dissolved Copper and Estimated Site Specific Daphnia LC50 ........................ 65 

Map 5 Daphnia Acute RQs, Highest Runoff, Orchard Use, Label Rates.................................... 70 

Map 6 Daphnia Acute RQs, Highest Runoff, Orchard Use, Average Rates ............................... 71 

Map 7 Daphnia Acute RQs, Highest Runoff, Row Crop Use, Label Rates ................................ 72 

Map 8 Daphnia Acute RQs, Highest Runoff, Row Crop Use, Average Rates............................ 73 

Map 9 Daphnia Acute RQs, Lowest Runoff, Row Crop Use, Label Rates ................................. 74 
8 

1.0 Executive Summary 

This ecological risk assessment covers the copper sulfate, copper group II salts, oxides, 

hydroxides, and complexes used on food crops as fungicides and bacteriocides; and directly in 

aquatic environments primarily for aquatic plant control. Most of these compounds dissociate in 

the environment to form ionic copper1

 (usually Cu2+), and the counter ion. The chemistry of 

Cu2+ is complex because it forms inorganic (including CuOH+, Cu(OH)2

0

, Cu(OH)3

-

 , Cu(OH)4 

2

, 

CuCl+

, CuCl2

0

, CuCl3

- , CuHCO3-

, etc.) species and soluble complexes with organic ligands (e.g. 

DTPA, EDTA, HEDTA, humic acids, and fulvic acids)2

 in solution. Throughout the assessment, 

the cupric ion (Cu 2+) has been evaluated as the active ingredient. Because copper is a metallic 

element, it will continue to cycle via biogeochemical mechanisms in the environment once it is 

released. Copper occurs naturally in the environment, and is also introduced from a wide range 

of anthropogenic activities, including mining and industrial processes Because it is both 

ubiquitous and toxic, it is also regulated by other U.S. Environmental Protection Agency 

programs. The Office of Water (OW) regulates it under the Clean Water Act (CWA), and 

released draft Ambient Aquatic Life Criteria for copper in 2003. The aquatic portion of the 

assessment uses a standard Environmental Fate and Effects Division (EFED) tool, the Pesticide 

Root Zone Model and Exposure Analysis Modeling System (PRZM/EXAMS) to estimate runoff, 

and a tool used by OW, the Biotic Ligand Model (BLM) to estimate the potential toxicity and 

concentration of the Cu2+ ion in aquatic systems. This modeling approach assumes chemical 

equilibria with no consideration of chemical kinetics with regard to precipitation/dissolution, 

complex formation, adsorption/desorption, and oxidation/reduction. In terrestrial ecosystems, 

copper is a contaminant of concern (COC) under the Comprehensive Environmental Response, 

Compensation, and Liability Act (CERCLA). Environmental screening levels used by the Office 

of Solid Waste and Emergency Response (OSWER) have been used in the assessment for 

evaluation of some endpoints. 

1.1 Nature of Stressor 

Although at high concentrations copper is toxic, it is also an important trace element for living 

organisms, and some have developed biochemical processes for maintaining homeostasis. This, 

in combination with the fact that tolerance to elevated concentrations of metals is common to 

many plants and animals results in a significant variance in toxicity estimates, making it difficult 

to establish definitive endpoints for some taxa. Terrestrial organisms are assumed to ingest 

copper when consuming foliage, fruit, or insects contaminated with copper. Acute copper 

toxicity via ingestion can cause bloody vomiting, hypotension, coma, and jaundice (Goyer 1996). 

Chronic effects noted in toxicity tests include reduced survival and growth of young. In aquatic 

systems, copper binds to the gill membranes, interfering with osmoregulatory processes and 

causing acute toxicity. 

 

1

 Cu2+ is shorthand for Cu[H20]6

2+, the hexaquocopper (II) ion. 2

 Inorganic and organic copper complexes replace the bound water of the hexaquocoppe (II) ion with the ligand. 

Hence CuCl2

0

 is actually [Cu[H20]4Cl2]

0

. 
9 

1.2 Status of Labels 

This risk assessment considers 15 separate compounds, incorporated by multiple manufacturers 

into a range of end-use products for use on a vast array of crops and also for direct application to 

aquatic environments. Application rates used in this risk assessment are based on a review of 

representative labels for CuSO4 and Cu(OH)2 for agricultural crops. The representative labels 

indicate a wide range of use rates (1 to 32 lbs Cu/A) with the highest rates on orchard crops. 

Labels were unclear regarding the frequency of application and total number of applications 

permitted on a yearly basis, which limits the ability to assess the total Cu loading on an 

application site. The highest label rates located are used in the assessment, in accordance with 

EFED’s standard assessment protocol. The highest application rates were significantly greater 

(in some cases almost twice) than many of the other labeled rates, and EFED also evaluated state 

average application rates, as supplied by the Biological Economic Analysis Division (BEAD). 

Unless stated on the label, four applications of Cu at 7-day intervals were assumed. During the 

public comment period input from the Copper Sulfate Task Force (CSTF), grower groups, and 

additional analysis by BEAD indicated that agricultural application rates are substantially lower 

than many of the current label rates. Typical rates for row crops appear to be less than 1lb Cu/A, 

and typical rates for orchards are in the 1-5 lb Cu/A range. Many users apply copper-containing 

pesticides with a high frequency. Thus, in addition to evaluations of the highest rates, EFED has 

included summaries of effects expected at application rates ranging from 1 lb Cu/A to 7.5 lb 

Cu/A. 

Direct water applications include a broad range of rates and use sites. Based on analysis by 

BEAD and input from public comments, typical applications for control of algae and aquatic 

weeds target concentrations ranging from 0.1-1 ppm Cu. Applications are often made multiple 

times, at 2-4 week intervals. Applications for control of mollusks, leeches, or crustaceans are at 

higher rates (1-2.5 ppm) but similar intervals. 

1.3 Copper Speciation and Fate 

Because copper is an element, it continues to cycle in the environment after it is released. 

Copper occurs naturally in the environment, and is also introduced by a wide variety of 

anthropogenic sources, thus there is always a background concentration, and there is no way to 

distinguish the particular source. Studies, both in terrestrial and aquatic ecosystems, have shown 

that even in some cases where copper concentrations are elevated, toxic effects to organisms are 

not evident. This has been associated with the speciation3

 of copper, and the fact that Cu2+ will 

form inorganic and organic complexes, which may or may not be toxic. Additionally, Cu2+ has a 

high sorption affinity for soil, sediments, and organic matter which limits bioavailability. 

Because these factors are dependent on water chemistry as well as sediment/soil properties, the 

relative toxicity and bioavailability of Cu 2+ is highly site specific. Consideration of site specific 

properties on a national scale limits the resolution of this risk assessment. 

 

3

 Speciation is the relative proportion of total copper as cupric ion (Cu2+), cuprous ion (Cu+), inorganic complexes, 

organic complexes and minerals (amorphous or crystalline). 
10 

For the aquatic risk assessment, Cu(II) compound uses on terrestrial crops were modeled using 

the PRZM/EXAM models for estimating Cu runoff from a 10 ha field into a standard small water 

body. A range of crop scenarios with diverse geography was selected to ensure a representation 

of crop-climate-agronomic combinations. To assess the speciation and consequent toxicity, 

EFED has used the Biotic Ligand Model (BLM), which accounts for the effects of major 

dissolved ions and dissolved organic carbon (DOC) present in natural surface waters. These ions 

and DOC may reduce the toxicity of the Cu ion by binding it and making it not bioavailable. 

The BLM was used by EPA’s Office of Water to establish Ambient Water Quality Criteria. The 

model has been reviewed and approved by the Scientific Advisory Board (SAB). The BLM 

model was used to estimate the concentration of Cu2+ ion (copper activity) and toxicity in the 

standard small water body using site-specific water chemistry monitoring data from 811 USGS 

sites distributed across the nation. Peak, 21-day average, and 60-day average Cu2+

concentrations were estimated for each runoff scenario. Risk quotients were derived for aquatic 

invertebrates and fish by comparing the copper activity derived from runoff with the copper 

activity representing an aquatic invertebrate or fish LC50 at the specific site, based on water 

chemistry. The resulting risk quotients (RQs) are compared to the EFED pre-established levels 

of concern (LOC), and expressed as the percentage of sites exceeding those LOCs. EFED fit 

equations to the data generated in this process. These equations allow an estimate of dissolved 

copper concentrations based on application rates, and an estimate of how many of the USGS 

sites exceed a given endpoint at a particular dissolved copper concentration. 

Terrestrial effects were assessed using EFED’s standard assessment methodology, with the 

exception of the fact that toxicity endpoints for studies from all compounds were converted to 

express the toxicity value on the basis of copper. Standard assessment methodologies included 

the use of the Terrestrial Exposure Model (TREX) for evaluation of toxic effects to birds and 

mammals, and TerrPlant for terrestrial plants. TREX estimates exposure by using the Kenaga 

nomogram to calculate pesticide residue on food items, and ingested dose based on allometric 

equations. TREX calculates RQs using both dose-based and dietary-based toxicity values. Due 

to the reactivity of copper, the dietary-based values are probably a better estimator of what might 

occur in the wild. Because no acute dietary toxicity endpoints were available, EFED 

incorporated an absorption efficiency factor into the chronic dose-based RQ calculations for 

mammals. TerrPlant estimates exposure from both runoff and spray drift. Separate RQs are 

calculated for monocotyledon and dicotyledon plants. 

1.4 Potential Risk 

1.4.1 Aquatic Assessment 

Aquatic assessments addressed both direct water applications, and runoff. In all cases, the 

estimated concentration of copper was put into the BLM to determine site specific Cu 2+

concentration, and this concentration was compared to the site specific toxicity values to 

determine risk quotients (RQs). Estimated peak runoff of Cu concentrations ranged from 350 

parts per billion (ppb) to 2 ppb, depending on the application rate, timing of application, 

meteorological conditions, soil type, and cropping practices associated with the particular 

scenario. At the highest Cu 2+concentration, >98% of the sites exceeded the acute and chronic 
11 

risk LOCs for aquatic invertebrates, >99% exceeded the acute risk LOC for plants, 80% 

exceeded the acute risk LOC for fish, and 68% exceeded the chronic risk LOC for fish. Analysis 

of the various scenarios showed that in order to prevent aquatic invertebrate LOC exceedances at 

95% of the sites assessed, aquatic copper concentrations should be 3.4 ppb or less. However, at 

this concentration, 41% of the sites exceed the endangered species acute risk LOCs for 

invertebrates, and 2% of the sites exceed the endangered species acute risk LOCs for fish. 

Although a number of site-specific factors influence runoff concentrations, 3.4 ppb dissolved Cu 

correlates to application rates of approximately 1.5 lb Cu./A. 

1.4.2 Terrestrial Assessment 

The terrestrial assessment quantitatively addressed acute and chronic endpoints for birds and 

mammals, and vegetative vigor endpoints for terrestrial plants. A qualitative assessment was 

done for terrestrial insects. Using dose-based and dietary-based endpoints, copper is classed as 

moderately toxic to birds. No acute dietary studies were located for mammals. Dose-based 

endpoints show copper to be moderately toxic to mammals. In all cases, toxicity values for 

various compounds were expressed on the basis of copper, rather than the copper containing 

compound. This somewhat reduced the variability in toxicity levels between the various 

compounds. Copper sulfate appears to be more toxic than some of the other compounds, 

possibly due to the fact that it is extremely soluble, thereby making the Cu2+ ion more readily 

available to the organism following ingestion. Some studies suggest that the composition of 

food contaminated with copper may also affect bioavailability. Based on an acute contact study 

with honey bees, it is practically non-toxic to terrestrial insects, although the effects of ingestion 

are unknown. Vegetative vigor study results show copper to be relatively non-toxic to mature 

terrestrial plants. No observable adverse effects concentrations (NOAECs) were 6.8 lb Cu/acre 

for monocots and 36.7 lb Cu/acre for dicots. 

At the highest orchard application rate, RQs for all sizes and food classes of birds exceeded the 

acute risk, chronic risk, and endangered species acute risk LOCs. At the highest row crop 

application rate, RQs for all sizes and food classes of birds exceeded the chronic risk, and 

endangered species acute risk LOCs. Most birds also exceeded the acute risk LOCs, with the 

exception of the large (1000g) bird eating fruits and pods (dose-based) and the class of birds 

eating fruits and pods (dietary-based). At the highest orchard application rate, RQs for all sizes 

and food classes of mammals exceeded the chronic risk, and endangered species acute risk 

LOCs. RQs for all sizes and food classes of mammals except the largest granivores exceed the 

acute risk LOC. At the highest row crop application rate, RQs for all sizes and food classes of 

mammals except the granivores exceeded the acute risk, the chronic risk, and the endangered 

species acute risk LOCs. A summary of effects expected at concentrations ranging from 1-7.5 lb 

Cu/A is presented in Table 1. 

At sites where copper is continuously applied, it will accumulate in the soil, although the degree 

of bioavailability is uncertain, and will vary dependent on site conditions. Concentrations of 60-

100 ppm Cu are potentially harmful to soil invertebrates, terrestrial plants, and soil 

microorganisms. Based on modeling, potentially harmful concentrations may be reached within 

2-20 years, dependent on site conditions, application rates, and frequency of application. 
12 

Although the model evaluates the application site, overspray areas where wildlife may reside 

and/or forage may be affected as well. Some plants concentrate copper from soil, potentially 

making it available to herbivorous and omnivorous organisms. Copper concentrations in plants 

were calculated, and appear to remain <100 ppm, even at the highest application rate. While this 

is above the dose-based LD50 for birds and approaches the dose-based LD50 for mammals, it is 

significantly below the dietary-based LD50 for birds. Concentration of copper by plants is 

expected to pose little to no risk for birds and mammals. 

1.4.3 Risk Conclusions 

Agricultural Uses 

Based on the data available and tools used in this assessment, current labelled rates for copper 

compounds appear to pose risk to all taxa quantitatively evaluated, except terrestrial plants, 

frreshwater vascular plants, and saltwater plants. However, input from the user community and 

additional analysis of usage data by BEAD during the public comment period indicate that 

application rates are often significantly below current label rates. Copper can be toxic in the <10 

parts-per-billion (ppb) range for aquatic organisms and in the 50-150 ppm range for birds and 

small mammals. Table 1 summarizes potential effects at various application rates, based on the 

assumptions of 4 applications at 7-day intervals. 
13 

Table 1 Summary of Risk Conclusions 

Rate 

(lb Cu/A) 

Aquatic 

EEC (ppb) 

Potential Effects on 

Aquatic Environments 

Potential Effects on 

Terrestrial Environments 

1.0 2.2 Appears unlikely to cause harm in 

most locations. 

Appears unlikely to cause harm in most 

locations. 

1.5 3.4 

Could affect freshwater nonvascular plants, and aquatic 

invertebrates, both freshwater and 

saltwater. Freshwater invertebrate 

LOCs exceeded at 5% of the sites 

evaluated. 

Birds and mammals consuming grass 

and/or leaves in the treated area could be 

affected. 

3.0 7.2 

Could affect freshwater nonvascular plants, fresh- and saltwater 

invertebrates, and saltwater fish. 

Freshwater invertebrate LOCs 

exceeded at 10% of the sites 

evaluated. Endangered species 

LOC for fish exceeded at 8% of the 

sites evaluated. 

Birds and mammals consuming grass 

and/or leaves in the treated area could be 

affected acutely. LOCs for endangered 

birds and mammals are exceeded for all 

food categories. Chronic risk LOCs 

exceeded in all food categories for both 

birds and mammals. 

5.0 12.1 

Could affect freshwater nonvascular plants, fresh- and saltwater 

invertebrates, and saltwater fish. 

Freshwater invertebrate LOCs 

exceeded at 17% of the sites 

evaluated. Endangered species 

LOC for fish exceeded at 13% of 

the sites evaluated. 

Birds and mammals consuming grass 

and/or leaves in the treated area could be 

affected acutely. LOCs for endangered 

birds and mammals are exceeded for all 

food categories. Chronic risk LOCs 

exceeded in all food categories for both 

birds and mammals. 

7.5 18.6 

Could affect freshwater nonvascular plants, fresh- and saltwater 

invertebrates, and saltwater fish. 

Freshwater invertebrate LOCs 

exceeded at 25% of the sites 

evaluated. Endangered species 

LOC for fish exceeded at 13% of 

the sites evaluated. 

Birds and mammals consuming grass 

and/or leaves in the treated area could be 

affected acutely. LOCs for endangered 

birds and mammals are exceeded for all 

food categories. Chronic risk LOCs 

exceeded in all food categories for both 

birds and mammals. 

Direct water applications 

For almost any direct water application of copper products, there is likely to be effects on 

invertebrates and a reduction of primary production. Fish and larger, more mobile invertebrates 

may be able to move out of the treated zone until the copper dissipates, but smaller and more 

sedentary invertebrates will be affected. Recovery of the affected organisms will vary on a siteto-site basis, and the specific effects on any given ecosystem is impossible to predict given the 

scale of this assessment. Populations of phytoplankton and zooplankton (the organisms most 

likely to be lethally affected by use of copper) are dynamic. In aquatic systems where copper is 

applied frequently the community may shift to more copper tolerant organisms, and/or some of 

the organisms present may develop metabolic pathways for dealing with higher copper loading. 
14 

The copper will accumulate in the sediments, which serve as a sink in aquatic systems. Under 

most conditions, sediment-bound copper is not readily bioavailable. 

Minimizing adverse effects of non-target organisms will depend on careful use by the resource 

managers who apply the products. Managers should be aware that copper remaining suspended 

in the water column and or sorbed to entrained sediment could affect downstream resources. 

1.5 Endangered Species Assessment 

Because of the number of crops registered for copper compounds and the potential for direct 

water applications, exposure to copper derived from pesticides may occur anywhere in the 

United States. This screening level assessment can identify taxa with a high likelihood of being 

affected based on either sensitivity to copper or location in a geographic area where coppercontaining pesticides are frequently used on agricultural crops. The list of species identified in 

this assessment should not be considered all-inclusive. Because copper is introduced into the 

environment from multiple anthropogenic sources, as well as naturally occurring background 

concentrations, risk at specific geographic locations may vary considerably from that estimated 

from pesticidal applications alone. Assessment of any cumulative effect is beyond the scope of 

this risk assessment. 

For agricultural applications, RQs exceeded the endangered species acute risk LOC for aquatic 

invertebrates, fish, amphibians, birds, reptiles, and mammals. Specific taxa affected are 

dependent on application rates, and are detailed in Table 2. Direct water applications are likely 

to affect mostly aquatic taxa, although there may be certain instances (e.g. Everglades snail kite), 

where they may affect terrestrial organisms indirectly due to reduction of a specific prey item. 

Aquatic vascular plants are only expected to be at risk from direct water applications. EFED 

conducted LOCATES search on the agricultural crops identified as the most common applicators 

of copper-containing pesticides to identify species with a high probability of exposure (Appendix 

F), but other species may be affected as well. 
15 

Table 2 Summary of Endangered Species Risk Conclusions 

Rate 

(lb Cu/A) Aquatic Ecosystem Terrestrial Ecosystem 

1.0 

FW Aquatic Invertebrates: Endangered species 

acute risk LOC exceeded at 27% of sites.

FW Fish, Aquatic Phase Amphibians: Endangered 

species acute risk LOC exceeded at 1% of sites. 

SW Aquatic Invertebrates: Exceeds endangered 

species LOC (RQ=0.36) 

SW Fish: Exceeds endangered species LOC 

(RQ=0.17) 

Birds, Reptiles, and Terrestrial Phase 

Amphibians: Endangered species acute risk 

LOC exceedences for herbivores and 

insectivores. Chronic risk exceedences for all 

food groups. 

Mammals: Endangered species acute risk LOC 

exceedences for herbivores and insectivores. 

Chronic risk exceedences for all food groups. 

1.5 

FW Aquatic Invertebrates: Endangered species 

acute risk LOC exceeded at 41% of sites.

FW Fish, Aquatic Phase Amphibians: Endangered 

species acute risk LOC exceeded at 2% of sites. 

SW Aquatic Invertebrates: Exceeds endangered 

species LOC (RQ=0.55)

SW Fish: Exceeds endangered species LOC 

(RQ=0.27) 

Birds, Reptiles, and Terrestrial Phase 

Amphibians: Endangered species acute risk 

LOC exceedences for herbivores and 

insectivores. Chronic risk exceedences for all 

food groups. 

Mammals: Endangered species acute risk LOC 

exceedences for herbivores and insectivores. 

Chronic risk exceedences for all food groups. 

3.0 

FW Aquatic Invertebrates: Endangered species 

acute risk LOC exceeded at 69% of sites.

FW Fish, Aquatic Phase Amphibians: Endangered 

species acute risk LOC exceeded at 8% of sites. 

SW Aquatic Invertebrates: Exceeds endangered 

species LOC (RQ=1.16)

SW Fish: Exceeds endangered species LOC 

(RQ=0.57) 

Birds, Reptiles, and Terrestrial Phase 

Amphibians: Endangered species acute risk 

and chronic risk LOC exceedences for all food 

groups. 

Mammals: Endangered species acute risk LOC 

exceedences for herbivores, insectivores, and 

frugivores. Chronic risk exceedences for all 

food groups. 

5.0 

FW Aquatic Invertebrates: Endangered species 

acute risk LOC exceeded at 85% of sites.

FW Fish, Aquatic Phase Amphibians: Endangered 

species acute risk LOC exceeded at 13% of sites. 

SW Aquatic Invertebrates: Exceeds endangered 

species LOC (RQ=1.95)

SW Fish: Exceeds endangered species LOC 

(RQ=0.96) 

Birds, Reptiles, and Terrestrial Phase 

Amphibians: Endangered species acute risk 

and chronic risk LOC exceedences for all food 

groups. 

Mammals: Endangered species acute risk LOC 

exceedences for herbivores, insectivores, and 

frugivores. Chronic risk exceedences for all 

food groups. 

7.5 

FW Aquatic Invertebrates: Endangered species 

acute risk LOC exceeded at 93% of sites.

FW Fish, Aquatic Phase Amphibians: Endangered 

species acute risk LOC exceeded at 23% of sites. 

SW Aquatic Invertebrates: Exceeds endangered 

species LOC (RQ=3.00)

SW Fish: Exceeds endangered species LOC 

(RQ=1.47) 

Birds, Reptiles, and Terrestrial Phase 

Amphibians: Endangered species acute risk 

and chronic risk LOC exceedences for all food 

groups. 

Mammals: Endangered species acute risk LOC 

exceedences for herbivores, insectivores, and 

frugivores. Chronic risk exceedences for all 

food groups. 

Direct 

Water 

(1 ppm) 

Vitrually all application rates exceed acute risk and 

endangered species acute risk for aquatic nonvascular plants, freshwater invertebrates, and 

saltwater invertebrates. Many application rates 

exceed acute risk and endangered species acute risk 

LOCs for fish. Some application rates exceed the 

acute risk LOC for aquatic vascular plants

Unlikely to cause direct effects on terrestrial 

organisms. May cause indirect effects due to 

reduction in prey base or modifications in 

aquatic community structure. 
16 

2.0 Problem Formulation 

Unlike most pesticides evaluated by EFED, the active ingredient in copper compounds proposed 

for registration (Table 1) is copper, rather than an organic moiety. Although it exists in a variety 

of organic and inorganic complexes, it is most toxic as the cupric ion (Cu2+ ). This screening 

level risk assessment evaluates the toxicity of Cu2+. The assessment strategy assumes rapid, 

complete dissociation of the Cu2+ and its counter ion. Organic ligands/chelates are expected to 

behave differently. They will stay in suspension longer, and the Cu2+ will be less available to 

aquatic organisms. Specific chemicals addressed in the risk assessment are listed in Table 3. A 

more refined risk assessment for copper-containing pesticides which do not dissociate quickly 

may require a more refined assessment. 
17 

Table 3 Copper Compounds Addressed in this RED 

Common name Other names Formula* Molecular 

weight* 

Percent 

Cu* 

PC Code 

copper sulfate pentahydrate copper sulfate CuSO4≅5H2O 249.65 25.4 PC024401 

basic copper sulfate copper sulfate, 

tribasic 

3Cu(OH)2≅CuSO4 468.29 54.2 PC008101 

copper hydroxide none Cu(OH)2 81.56 77.9 PC023401 

cuprous oxide Cu2O 143.08 88.8 PC025601 

copper carbonate copper 

carbonate, basic 

Cu(OH)2CuCO3 221.12 57.5 PC022901 

copper ammonium complex copper 

tetraamine 

Cu(NH3)4

 2+ 131.58 48.3 PC 022702 

copper ammonium carbonate 

complex 

none CuNH3(HCO3)2 190.54 33.3 PC022703 

basic copper chloride copper chloride, 

basic; copper 

oxychloride 

3 Cu(OH)2≅CuCl2 427.133 59.5 PC008001 

copper oxychloride basic cupric 

chloride 

Cu2Cl(OH)3 213.57 59.5 PC 023501 

copper oxychloride sulfate none 3Cu(OH)2≅CuCl2 + 

3Cu(OH)2≅CuSO4

879.43 57.8 PC023503 

Copper salts of fatty and rosin 

acids 

Cu Soap Mixture of 

compounds 

NA NA PC023104 

Copper ethylenediamine Cu-EDA C2H8N2Cu 123.54 51.43 PC024407 

Copper triethanolamine 

complex 

Cu-TEA C6H15O3NCu+2 212.54 29.89 PC024403 

Copper ethanolamine complex C2H7ONCu+2 124.54 51.01 PC024409 

Copper octanoate Cu Soap C8H16O2Cu 207.54 30.61 PC023306 

*approximate formula, may vary slightly depending on manufacturing processes, molecular weight and percent 

copper calculated based on formula
18 

2.1 Stressor Source and Distribution 

2.1.1 Chemical and Physical Properties 

Copper is a transition metal, with an atomic number of 29, an atomic weight of 63.5, and two 

naturally occurring isotopes. At a certain level, copper is an essential element for living 

systems, and is a key atom in the oxygen carrying protein, hemocyanin, for some invertebrates. 

Various forms of copper occur naturally in the environment. It is used in a wide variety of 

industrial and consumer applications, in addition to being used in pesticidal applications for over 

100 years, thus in most areas where a copper containing pesticide is applied, it must be assumed 

that there is an existing background concentration that must be considered. 

2.1.2 Mode of Action 

Copper is used as an algicide, fungicide, and molluscicide, but the specific toxic mode of action 

varies between these taxonomic groups. Exposure to excess copper causes disruption of the 

cellular membrane, with the thiol groups as the primary target (Eisler 2000). In fishes, copper 

causes gill damage, and can interfere with osmoregulatory processes. It has been associated with 

effects on ATP-synthesizing pathways, and can interfere with energy metabolism. In algae, it 

causes increased permeability of the cell membrane and leakage of the cell contents. For 

molluscs, it disrupts peroxidase enzymes, and affects the functioning of the surface epithelia. In 

mammals, excess copper causes alterations in biomolecules and lipid peroxidation. Few avian 

wildlife studies are available, but domestic chicks showed damage to the gizzard lining, and 

domestic ducklings and turkeys accumulated copper in their livers. Copper has not been 

associated with carcinogenic, mutagenic, or teratogenic effects except at high concentrations. 

Copper is an important trace element. Copper is a cofactor in some enzymes, including 

tyrosinase and cytochrome oxidase (Lehninger 1975). In these types of enzymes, the metal may 

serve as a catalysis center, a bridging atom, or a stabilization element. Substitution of one metal 

ion for another may disrupt functioning of the enzyme. Copper is also important in cellular 

respiration, as a component of cytochrome c oxidase. In algal cells, it serves a similar electron 

transport function in a protein called plastocyanin. Most organisms have biochemical pathways 

capable of dealing with moderate doses (Eisler 2000). Copper may be bound to metallothioneins 

and stored or excreted. This binding is a reversible process, and homeostatic processes within 

the organism regulate the amount of copper circulating. Metallothionein production is an 

inducible process, and organisms in a copper (or other metal) rich environment often exhibit 

elevated concentrations. 
19 

2.2 Use Characterization 

Copper has been widely used in pesticidal applications for more than a hundred years. For the 

purposes of this ecological risk assessment, applications have been grouped into two categories: 

orchard and row crop uses, and direct water applications. These two categories are represented 

by separate conceptual models Antimicrobial applications such as wood preservatives and boat 

bottom paints are not included in this risk assessment, and will be addressed in a separate 

registration action conducted by the Antimicrobial Divison. 

2.2.1 Agricultural Uses 

Several copper compounds, including copper sulfate and copper hydroxide, are used as 

fungicides and bacteriocides on a variety of row crops and orchards. Generally, the pesticides 

may be applied as an aerial, ground dilute, or ground concentrate spray. It is registered for use 

on a wide variety of crops including, but not limited to: 

 Orchard crops - citrus, nuts, apples, apricots, banana, coffee, peach, pear, and plum 

 Row crops - barley, oats, wheat, beans, broccoli, cabbage, carrots, melons, and tomatoes 

 Small fruits and vines - blueberry, strawberry, grapes, and hops 

 Turfgrass and some ornamentals 

Timing of application varies by crop. As labels are currently written, there are no limitations on 

the number of applications. Frequency of application is variable, but some intervals are as short 

as 5 days, or on an “as needed” basis. Application rates used in the assessment are based on the 

label analysis and state average rates determined by BEAD, and are detailed in the aquatic 

exposure section (Table 11). Input from the user community and a more detailed analysis by 

BEAD during the public comment period showed the majority of users applied copper products 

at rates below (sometimes significantly) those currently recommended on the labels, but that for 

many of the high-use crops, applications were frequent. A comparison of rates compiled from 

various sources is included in the risk description section (Table 29). 

Although copper sulfate and copper hydroxide are currently labeled for use on a wide variety of 

crops, a relatively small number of crops account for the majority of the usage. Based on 

Screening Level Usage Analysis (SLUA) conducted by BEAD, the following crops have been 

identified as major users of copper based pesticides. The evaluation is based on pesticide usage 

data for agricultural crops during the years of 1998-2003. Turf uses are not included. Usage 

analyses were available for copper sulfate pentahydrate (PC024401) and copper hydroxide 

(PC023401). In order to evaluate the amount of applied elemental copper, the pounds of active 

ingredient (lbs a.i.) were converted to pounds of copper (lbs Cu). High usage crops are shown 

below in Table 2. Nine specific crops account for 73.2% of the total use. This data was 

provided after the PRZM-EXAMS modeling was completed, thus the specific crops modeled by 

EFED do not include all of the high-use crops 
20 

Table 4 Usage Analysis for Copper Sulfate and Copper Hydroxide 

Crop type Percent of use Specific crops included in a category Greatest use 

Orchard, Citrus 36.0% Grapefruit, lemons, limes, oranges, 

tangelos, tangerines 

Oranges (25.1%) 

Grapefruit (8.8%) 

Orchard, nuts 26.6% Almonds, filberts, pecans, pistachios, 

walnuts 

Walnuts (17.6%) 

Almonds (7.6%) 

Orchard, other 10.7% Apples, apricots, avocados, cherries, 

nectarines, olives, peaches, pears, plums Peaches (2.8%) 

Row crops 20.0% 

Beans (dry & green), broccoli, cabbage, 

canteloupe, carrots, cauliflower, celery, 

collards, corn (sweet), cotton, cucumber, 

eggplant, garlic, greens (mustard & turnip), 

lettuce, onions, peas, peanuts, peppers, 

potatoes, pumpkins, spinach, squash, sugar 

beets, tomatoes, watermelon, wheat 

Tomatoes (9.8%) 

Peppers (2.5%) 

Vines and small fruit 5.4% Grapes, blackberries, blueberries, 

raspberries, strawberries, Grapes (5.2%) 

Rice 1.3% Rice Rice (1.3%) 

2.2.2 Direct Water Applications 

Evaluation of the use patterns and rates for direct water applications was conducted by BEAD 

(Aquatic Use Memorandum, 2/15/06, DP#324176). The summary in this chapter includes the 

information relevant to the ecological risk assessment (e.g., rates, frequencies, concentrations, 

and use sites). The analysis was conducted by BEAD using research articles as well as other 

relevant authoritative publications, with input from the user community. 

For algaecide and aquatic herbicide uses, the copper compounds are applied at a range of rates 

between 0.2 – 1.0 ppm elemental copper. Average copper rates for algae control were 0.5 ppm 

for susceptible species and 0.75 - 1.0 ppm for resistent species. Average copper rates for weed 

control were 0.2 - 0.5 ppm for susceptible species and up to 1.0 ppm for resistent species. The 

average number of annual applications to a given water body were ranged between two and four, 

with none of these applications being made to more than 25 - 33% of a given water body at any 

one time. Generally, applications are made at an interval of approximately two weeks. 

Information regarding the use to control mollusks, leeches, and tadpole shrimp was difficult to 

obtain. Based on information available, use rates ranged from 1.0 ppm to as high as 2.5 ppm 

elemental copper. Direct water application of copper sulfate pentahydrate for snail control was 

found to be within the 1.0 to 1.5 ppm concentration. Control of snails and leeches in ponds and 

other associated quiescent water bodies is for human health as well as agricultural and 
21 

aquacultural reasons. Aquaculture systems rely on direct water applications for the control of 

snails and tadpole shrimp at rates of 1.0 to 2.5 ppm concentration of copper. 

2.2.3 Urban Uses 

Copper-containing compounds have a number of pesticidal uses in urban settings, including 

wood treatments, lawn treatments (as a fungicide), use in pools and fountains, root killers for 

sanitary sewers, and anti-fouling paints. The majority of these uses are considered anti-microbial 

applications, and will be addressed in a separate risk assessment produced by the Anti-microbials 

Division (AD) at a later date. The two uses under the purview of EFED are lawn uses, and use 

as a root-killer. Lawn uses are considered with agricultural uses (as turf). Typically, copper 

sulfate pentahydrate crystals are used for root-killers. Application directions recommend 

flushing 2 lbs of product (25.4% copper, approximately 0.51 lbs elemental copper) down the 

toilet every 6 months to control tree root growth. This treatment is not recommended for septic 

systems. In some localities, sales of these products have been banned, as their use was found to 

contribute significantly to overall loading of copper in some watersheds. Water contaminated 

with copper from use of these products is expected to be processed through water treatment 

facilities prior to release to receiving waters. 

2.3 Environmental Exposure Strategy 

Subdivision N guideline studies submitted to the Agency are inappropriate to assess the 

environmental fate of inorganic copper compounds because copper will not degrade in the 

environment. Copper applied as a pesticide is indistinguishable from naturally occurring copper 

species in the environment. However, Subdivision N guideline studies are appropriate for 

organic Cu complexes because the organic portion of the compound may degrade through abiotic 

and biotic processes. Because Cu is a common constituent of the inorganic and organic 

complexes of Cu and is the active ingredient, environmental fate assessments of copper 

compounds have been combined into a single fate assessment. There are sufficient 

environmental fate data to use a chemical equilibria approach for assessing the environmental 

fate of Cu2+. Uncertainties in the assessment are associated with chemical kinetics (i.e. the rate ) 

of mineral precipitation-dissolution, oxidation-reduction, and complexation. This assessment 

addresses terrestrial food crop and direct aquatic uses of Cu(II) salts, oxides, hydroxides, and 

complexes. 

Cu(II) salts, hydroxides, and oxides will dissociate to form Cu2+ and a counter anion. The extent 

of dissociation is controlled by the solubility of the compound. The chemistry of copper in 

aqueous systems is complex and it involves more than one oxidation state of copper, as well as 

the formation of mineral phases, neutral species, and complexes. Figure 1 provides an overview 

of the chemistry of copper in aqueous systems. In this overview, it is assumed that metallic 

copper is the reacting chemical species. 
22 

Metallic (Cu0

) can oxidize to form Cu(I) and Cu(II) species in solution or as solid phases. The 

oxidation of Cu(0) to Cu(I) or Cu (II) depends on the redox conditions4 of the medium. The 

form in which Cu(I) or Cu(II) species is found depends on the pH of the medium and the nature 

and concentration of other chemical species that can form Cu-containing species. For example, 

inorganic Cu (II) species that could Cu(II) salts, oxides and hydroxides that may be found as 

soluble or insoluble species. Cu(I) species may include some oxides and hydroxides. In addition, 

Cu(I) or Cu(II) may form complexes with a variety of naturally occurring ligands. However, the 

concentration of “free copper” is controlled by the pH of the medium. When used as pesticides, 

(free Cu(II) ion) is released via dissolution of Cu(II) salts, oxides/hydroxides and/or by the 

breakdown of organic complexes and/or degradation of the organic moiety. 

 

4

 Redox potential is the tendency of the environment to deplete molecular oxygen from the system to form oxygen 

containing compounds. Redox can be measured as an electrical potential in millivolts (mV). It also controls the 

chemical forms of other compounds in the environment. 

Natural

Cu0

Cu2+

Cu+

Cu (II)

Minerals

Cu (I)

Minerals

Inorganic Cu

Complexes

Organic Cu

Complexes

Figure 1 – Environmental Fate Bridging Strategy for Cu Minerals and Comple xes

Natural

Cu0

Cu2+

Cu+

Natural

Cu0

Cu2+

Cu+

Cu (II)

Minerals

Cu (I)

Minerals

Inorganic Cu

Complexes

Organic Cu

Complexes

Figure 1 – Environmental Fate Bridging Strategy for Cu Minerals and Comple xes
23 

2.4 Site Vulnerability Analysis and Scenario Selection 

Copper is used extensively as an orchard fungicide, and orchard crops have the highest 

application rates, thus to assist in selecting scenarios to estimate environmental concentrations, 

sites determined to be vulnerable were compared with locations of known orchard cultivation 

(Map 1). Based on AgCensus data available from USDA, orchard production is heavily 

concentrated in California and Florida, Hawaii, Washington state (Yakima Valley), and Oregon 

(Willamette Valley). Other areas with significant orchard concentrations include southern 

Arizona and New Mexico, eastern Texas and Oklahoma, western Michigan, western New York, 

southwestern Georgia and southeastern Alabama, and an area along the Appalachian Ridge 

extending from Virginia to New York. Many of these areas appear to have vulnerable water 

chemistries5

 based on the USGS data, including areas in the Pacific Northwest, California, South 

Central Texas, and New England. 

Copper compounds are also currently registered for use on a wide variety of row crops, including 

vegetables (e.g., tomatoes, lettuce), fruits (e.g., watermelon, honey dew), field crops (e.g, wheat, 

oats), small fruits (e.g., strawberry, blueberry) and vines (e.g., grapes). In general, application 

rates for these crops are lower than for the orchard crops. The number of crops for which copper 

compounds are registered means that copper exposure from pesticide use may occur in virtually 

any agricultural area in the United States. Areas that are not within intensive orchard cultivation, 

but which have vulnerable water chemistries based on the USGS data include Southern Idaho, 

Colorado, sections of the Midwest, and the Eastern coastal plain. Certain areas of the Eastern 

coastal plain do grow some of the other high use crops, such as tomatoes and peppers. 

ARCMAP GIS software was used to analyze the site water chemistry on a spatial basis. Sites 

that might be more vulnerable to copper toxicity (operationally defined by EFED as DOC# 3.0 

mg/L and/or alkalinity < 50 mg/L as CaCO3) were mapped. Of the 811 sites, 450 (55%) fit into 

this category. While there was significant variability within regions, vulnerable sites were 

common in New England/glacial shield areas, the Eastern Coastal Plain, the Pacific Northwest 

(Washington and Oregon), California’s Central Valley, and Hawaii. A cluster of very vulnerable 

sites was identified in North Carolina, with very low alkalinity and DOC. Several of these sites 

are designated as “tile drainage” (in essence, groundwater, with lower ionic concentrations and 

DOC than most surface waters) or “drainage ditch” (indicating possible clear water discharge, 

also with low ionic strength and DOC). Thus, these sites may overstate the potential for risk in 

the Southeastern Coastal Plain if they do not represent typical conditions in surface waters. A 

significant number of sites in this area were removed from the data set because water 

temperature was outside the range of the BLM. This area is expected to be somewhat vulnerable 

due to its generally low alkalinity, although in some locations high DOC content may mitigate 

copper toxicity. 

 

5

 For this analysis, sites with dissolved organic carbon (DOC) <3 mg/L and/or alkalinity < 45 mg/L were considered 

vulnerable. 
DOC<3 or alk<45

USGS sites with BLM data

Crop Scenario Locations

ACRES

Less than 250

251 - 999

1000 - 24999

25000 - 49999

50000 or more

Map 1

Sites Potentially Vulnerable to Copper Toxicity

And Counties Classified by Acres of Orchards

0 100 200 400 600 800

Miles Coppers Assessment

Created by: PDB 06/10/05

USEPA/OPP/EFED

Data Sources:

Chemistry: USGS NASQA and NASQAN

Crops: 1997 USDA AgCensus
25 

2.5 Assessment Endpoints 

Because the active ingredient of Cu(II) mineral salts, hydroxides, oxides, and Cu(II) complexes 

is Cu2+, a unified risk assessment approach was formed for the pesticides addressed in this risk 

assessment. Therefore, an important consideration in the risk assessment is the use site of the 

various pesticides. The assessment endpoints will be addressed as separate components: 

endpoints affected by agricultural uses, endpoints affected by direct water applications, and 

endpoints affected by urban uses. 

2.5.1 Ecosystems Potentially at Risk 

For each of the primary methods of application, the ecosystems at risk include all areas where 

the level of copper contamination might reasonably be expected to be high enough to directly 

affect the resident organisms. Because copper continues to cycle, potential effects from 

environmental sinks such as soil and sediment are also considered. 

Agricultural Uses 

For typical crop and orchard applications, the ecosystem at risk is the field and adjacent aquatic 

and terrestrial environments that might be affected by runoff or spray drift. Atmospheric 

deposition is not expected to be an important exposure route in this scenario. Aquatic 

concentrations resulting from this application method are expected to be significantly lower than 

the direct application method. In the water body, pelagic and benthic elements will be 

considered. Terrestrial evaluations will include non-target insects, soil invertebrates, birds, and 

mammals. Copper has the potential to bioaccumulate in some organisms and the importance of 

this as an exposure route will be evaluated. 

Direct Water Applications

When copper is applied directly to water, the ecosystem at risk consists primarily of that 

particular water body, but also includes the downstream outlet of the water body, if one exists. 

Within the water body, compartments of concern are the water column, sediments, and pore 

water. Organisms of concern include aquatic plants (algae and vascular), aquatic invertebrates, 

fish, amphibians, and birds or mammals which may rely on the reservoir as a drinking water 

source. The downstream reach also consists of a water column and benthic component. 

Dependent on flow regime, deposition of copper contaminated sediment into downstream flood 

plains, marshes, or estuaries may be of concern. Copper has the potential to bioaccumulate in 

some organisms and the importance of this as an exposure route will be evaluated. 

Urban Uses 

Urban uses considered include lawn applications and root-killers. The ecosystem of concern for 

lawn applications is the same as those considered in the agricultural uses, and is addressed 

therein. The ecosystem of concern for the root-killers is the receiving waters. Organisms of 

concern include aquatic plants (algae and vascular), aquatic invertebrates, fish, and amphibians. 
26 

2.5.2 Ecological Effects 

Evaluation of ecological effects will focus initially on the direct effects to the groups of surrogate 

organisms residing in the ecosystems at risk. If levels of concern are exceeded for direct effects, 

indirect effects to endangered species (e.g. food chain, decrease in community diversity) will be 

evaluated based on the group of organisms exceeding the LOC. 

Direct

Direct effects to be evaluated are the survival, growth, and reproduction of various taxa of 

organisms exposed to copper containing compounds. Effects will be assessed based on ionic 

copper as the toxic constituent. Taxonomic groups include aquatic plants (algae and vascular), 

aquatic invertebrates, aquatic vertebrates, terrestrial plants, terrestrial invertebrates, birds, and 

mammals. Exposure routes may vary dependent on type of application (direct water, orchard, or 

row crop). In some situations, copper has been shown to bioaccumulate and/or biomagnify 

(Eisler 2000). These effects are discussed qualitatively. 

Indirect 

When copper-containing compounds are applied directly to water, common indirect effects 

include a decline in primary productivity, and a potential shift in community composition. If the 

endangered species direct effect LOCs are exceeded, effects on the food chain, and habitat 

quality will be assessed as necessary. In Florida, copper has been associated with a decline in 

the primary food source of the endangered snail kite (Rostrhamus sociabilis) (Eisler 2000). In 

areas where aquatic plants are heavily treated with copper compounds, it also appears to 

accumulate to potentially toxic concentrations in the livers of endangered West Indian manatee 

(Trichechus manatus)(Eisler 2000). 

2.6 Conceptual Models 

Separate conceptual models have been developed for agriculatural uses (Figure 2), and direct 

water applications (Figure 3.) Models are shown on the following two pages. 
27 

Figure 2 - Conceptual Model for Orchard and Row Crop Application

Stressor Copper applied to crop

Source Runoff Spray drift Direct applicationReceptors

Terrestrial Birds Mammalsinsects

Individual organismsReduced survivalReduced growthReduced reproduction

Food chainReduction in primary productivityReduction in preyShift in community composition

Habitat inReduced Communi

AttributeChange

Aquatic plantsinvertebratesvertebrates

Terrestrial plants

Soil accumul

leaching and 

Soil inverte

Terrestrial exposure Routes include:Dermal contactDiet

Figure 2 - Conceptual Model for Orchard and Row Crop Application

Stressor Copper applied to crop

Source Runoff Spray drift Direct applicationReceptors

Terrestrial Birds Mammalsinsects

Individual organismsReduced survivalReduced growthReduced reproduction

Food chainReduction in primary productivityReduction in preyShift in community composition

Habitat inReduced Communi

AttributeChange

Aquatic plantsinvertebratesvertebrates

Terrestrial plants

Soil accumul

leaching and 

Soil inverte

Terrestrial exposure Routes include:Dermal contactDiet
28 

Figure 3 - Conceptual Model for Direct Water Application

Individual organismsReduced survivalReduced growthReduced reproduction

Food chainReduction in primary productivityShift in community composition

Habitat inteReduced coDO decreas

AttributeChange

Copper applied directly to water

Water column Sediments 

StressorSource

Receptors Algae Vascular Plants Pelagic invertebrates Benthic inverte

Aquatic vertebrates

Porewate

Figure 3 - Conceptual Model for Direct Water Application

Individual organismsReduced survivalReduced growthReduced reproduction

Food chainReduction in primary productivityShift in community composition

Habitat inteReduced coDO decreas

AttributeChange

Copper applied directly to water

Water column Sediments 

StressorSource

Receptors Algae Vascular Plants Pelagic invertebrates Benthic inverte

Aquatic vertebrates

Porewate
29 

2.7 Risk Hypotheses 

Copper containing pesticides may pose a variety of risks for both aquatic and terrestrial 

organisms, including the following. 

• Copper in runoff from agricultural areas and direct applications may kill aquatic plants, 

aquatic invertebrates, or fish. 

• Copper in runoff from agricultural areas and direct application may reduce populations of 

aquatic plants, aquatic invertebrates, or fish, causing changes in the community. 

• Copper in runoff from agricultural areas and direct application may accumulate in 

sediments, resulting in chronic impacts to the benthic community. 

• Copper in runoff from agricultural areas and direct application may be bioaccumulating 

in aquatic organisms. 

• Copper deposited on plant surfaces may affect birds and/or small mammals ingesting the 

affected vegetation. 

• Copper accumulating in soils may be toxic to plants or animals residing on the site. 

2.8 Key Uncertainties and Information Gaps 

• Copper speciation is profoundly influenced by site chemistry. An effort has been made 

to examine a wide variety of sites, with special emphasis on sites with conditions that might 

make copper highly available, but sites may exist with conditions beyond the bounds of data 

available. This may increase or decrease the risk associated with the site. 

• Copper is an element, thus it will continue to cycle in the environment indefinitely. 

Changes in site conditions over time will affect copper availability and toxicity, and may 

increase or decrease the risk associated with the site. 

• Copper exists in the environment as a natural background element. While this has been 

taken into consideration in the risk assessment, localized enrichment may occur that is beyond 

the level of spatial resolution available for the assessment. Enrichment may increase the risk 

associated with the site. 

• Copper has myriad uses other than pesticides, and anthropogenically elevated 

concentrations may occur in or near pesticide use areas. This may or may not be discernable 

from the spatial data used in the assessment. Elevated concentrations may increase the risk 

associated with the site. 

• Copper has important biochemical functions for the organisms assessed, and the 

regulatory mechanisms controlling copper homeostasis are complex. Toxicity of copper to 

organisms in the wild may be under- or over-estimated by available toxicity data. 

• In certain instances, metal toxicity is additive, and in other instances exposure to other 

metals may convey some protection to the organism (i.e., induction of metallothioneins). The 

effect of multiple metals is not within the scope of this assessment. The assessment may underor over-estimate the effects of copper in these situations but is more likely to under-estimate the 

risk than over-estimate it. 
30 

• Natural genetic variability in wild organisms affects their response to copper. Risk may 

be under- or over-estimated by available toxicity data. 

• Current approved labels cover a wide range of application rates, some of which may not 

be realistic. If allowed application rates are in excess of what is applied by most growers, risk 

will be overestimated. 
31 

3.0 Aquatic Assessment 

3.1 General Approach 

A quantitative exposure assessment of Cu(II) salts was conducted (Jones and Hetrick, 11/7/91) in 

support of the 1994 registration decision for copper . Because this earlier assessment did not 

consider Cu2+ complexation by organic ligands and its effect on Cu speciation as well as 

representative national water quality conditions for ambient surface water, a refined exposure 

assessment was conducted using the Biotic Ligand Model (BLM) in conjunction with USGS 

water quality monitoring data. The USGS monitoring data are expected to be representative of 

water quality conditions in ambient surface waters across the United States. 

3.1.1 Agricultural Uses

The environmental fate of metallic copper is dependent on oxidation of elemental Cu to form 

either cuprous (Cu+

) or cupric (Cu2+) ions. Elemental Cu is oxidized to form Cu+ ions at redox 

potentials of pE6 > 8.87 and Cu2+ ions should form at pE > 5.745 (Lindsay, 1979). 

Concentrations of soluble Cu2+ and Cu+

 is dependent on redox potential; cuprous ions (Cu+) will 

predominate in suboxic and anoxic environments (pE < 2.62 at pH 7 or pE + pH < 9.62). The 

oxidation rates of metallic copper are unknown. 

Cupric hydroxide, cupric oxide, cuprous oxide, CuSO4, metallic copper, copper chloride, copper 

oxychloride sulfate, copper ammonium carbonate, and copper carbonate are also used as 

fungicides on terrestrial food crops. These uses allow direct application of copper salts into 

terrestrial environments. Copper (II) salts in soil are expected to dissociate into Cu2+ and the 

counter anion. The fate of metallic copper and Cu+

 ions will be controlled by the environmental 

redox potential and by the nature and concentration of other chemical species that may form 

complexes with Cu(I). Cupric (Cu2+) ions will predominate free Cu ion in well aerated (pe+pH 

>9.62 at pH 7) soil environments. The fate of Cu2+ ion will be controlled by soil binding and by 

the nature and concentration of other chemical species that may form complexes with Cu(II). 

Because Cu2+ has a high binding affinity for soil, the Cu2+ ion is not expected to move into 

ground waters. However, applied Cu may move from the site application on entrained sediments 

in runoff waters. Runoff simulations of Cu(II) salts in Aiken County, South Carolina and 

Kossuth County, Iowa indicates that introduced Cu (8.25% of the applied Cu) was removed from 

the application site on entrained sediments in runoff waters (Jones and Hetrick, 1991). The 

effect of introduced Cu on the water quality of surface waters is dependent on water pH, 

alkalinity, and dissolved organic carbon. 

 

6

 pE= Eh (millivolts)/59.2 
32 

3.1.2 Direct Aquatic Uses 

Copper sulfate and other copper compounds are applied directly to aquatic environments, 

generally for control of weeds and algae, but also to control other nuisance species, such as snails 

and leeches. To assess the effects of direct water uses, EFED used EXAMS (ver. 2.98.04, 

7/18/02) to estimate the expected water column concentration, followed by the BLM to calculate 

risk quotients. EXAMS accounts for sediment:water partitioning, and the BLM incorporates the 

effects of copper speciation. Based on information provided during public comment, direct 

water applications in ponds, lakes, and embayments, are generally applied in bands near the 

shoreline, or only to a portion of a smaller waterbody (typically 25-30%). For algae and aquatic 

weeds, the target concentration is 0.1-1 ppm. For snails, leeches, and other similar organisms, it 

is typically higher, from 1-2.5 ppm. 

Copper concentrations of approximately 1 ppm are well below the solubility of CuSO4 and hence 

complete dissociation of CuSO4 is expected. Chelated coppers may take longer to dissociate, 

and may remain suspended in the water column longer. The 1 ppm concentration is used as an 

upper bound for the chelated compounds. Once dissociation occurs, the soluble Cu2+ ion will 

become incorporated into the natural copper cycle within the aquatic environment. Eventually, 

the introduced, soluble Cu2+ concentration will approach ambient, soluble Cu concentrations 

because of binding to sediments. Partitioning coefficients of Cu2+ can range from 100 to 

100,000 L/kg in soil and sediments. The actual dissipation time of "introduced", soluble Cu2+

depends on the physicochemical properties of the aquatic environment (pH, water hardness, 

redox conditions, etc). Data from aquatic field dissipation studies indicate a rapid dissipation 

rate (t1/2 = 10 days) for the "introduced", soluble Cu. It is important to recognize Cu2+

dissipation is heavily dependent on sediment binding, and that, unless relocated by physical 

processes such as scouring, the sediment in a waterbody treated with copper compounds will

serves as a sink for the additional copper. The additional copper from direct water applications 

may or may not be discernable from existing background concentrations. Copper is not readily 

bioavailable in sediments, in part because of binding to organic matter in the sediment, and in 

part because of redox conditions. These factors have been taken into consideration when 

calculating and evaluating sediment pore water concentrations.

Inorganic/Organic Cu(II) Ligands and Organic Salts 

Cu(II) ligands are used as wood preservatives, antifoulant, fungicides, and algicides 

These compounds are different from the Cu(II) minerals and salts because they do not fully 

dissociate in the environment. Additionally, the extent of dissociation is dependent on 

competitive equilibria with other cations (including Ca2+, Mg2+, Mn+4, Fe 3+, Zn2+, etc.) as well as 

environmental redox and pH conditions (Lindsay, 1978). The fate assessment for Cu ligands is 

focused, when possible, on the theoretical chemical equilibria of the Cu-ligand species with 

competing cations and the behavior of the counter ligand in the environment. Because Cu2+ is 

considered the active ingredient of the Cu(II) compounds and complexes, the estimation of 
33 

environmental concentrations will assume complete dissociation in order to predict conservative 

EECs. However, it is important to note that Cu ligands may exhibit different environmental fate 

properties from Cu 2+ such as higher mobility in soils and sediments. Estimation of 

environmental concentrations will depend on the application rate and use patterns. 

Table 5 Application Rates for Cu(II) Ligands and Organic Salts 

Cu(II) Ligand Label Use Pattern

Max Single 

Application Rate Peak EEC1

(ug Cu/L)

Copper Ammonium EPA Reg No. 10465-3 Terrestrial 

Food Crops 2.63 kg Cu/ha 5.58 

Copper Ethanolamine EPA Reg No. 8959-12 Aquatic 

Algicide 67.2 kg Cu/ha 49.92

Copper Ethylene diamine EPA Reg. No. 1812-312 Aquatic 

Algicide 1000 ug/L 1000 

Copper Triethanolamine EPA Reg No. 8959-20 Aquatic 

Algicide 400 ug/L 400 

Copper Octanoate EPA Reg No. 67702-2 Terrestrial 

Food Crops 1.060 kg Cu/ha 2.02 

Copper Salts of Rosin and 

Fatty Acid EPA Reg 4-UGA Terrestrial Food Crops Not Defined3

 NA 

1-Peak EECs for terrestrial crops were estimated using the following regression equation: Peak EEC= -0.3800+ 2.5358*(lbs Cu/A). This 

regression equation was developed from PRZM/EXAMS estimated a single year, peak Cu 2+ concentrations in the standard farm pond and from 

Cu2+ applications rates (lbs Cu2+/A) on representative crops (Figure 12). 

2- Assumes application in 1 ha standard small water body at 2 meters deep (20E6 liters)

3- Application rates could not be calculated from the label because a recommended application rate is not on the label. 

Copper Ammonium Complex 

The chemical formula for copper ammonium ligand is Cu(NH3)4

2+ . This complex is formed 

through a reaction of Cu 2+ and ammonia (Cu2+ + 4NH3 : Cu(NH3)4

2+). The stability constant for 

Cu(NH3)4

2+ formation is 1.20 X 1013 moles/dm3

 (Log K= 13.079 moles/liters) 

(http:/www.chemguide.co.uk/ inorganic /complexations/stabconst.html). 

Copper triethanolamine complex, Copper ethylene diamine, Copper ethanolamine complex 

Chemical equilibria of Cu triethanolamine (Cu-TEA) complex indicates the complex is a stable 

soluble Cu species in acidic environments (Sillen, 1964 and 1971). In neutral and alkaline 

environments the Cu-TEA complex is not stable because of increased stability of the inorganic 

Cu(OH)2

o

 species. Chemical equilibria of Cu ethylene diamine chelate (Cu-EDA) indicate the 

complex is stable from pH 5 to 9 (Sillen, 1964 and 1971). The stability of the Cu-TEA and CuEDA complexes relative to other organic Cu complexes is unknown at this time. No fate data 
34 

has been submitted for ethylene diamine and triethanolamine. However, open-literature data 

suggest amine complex should degrade through microbial-mediated processes. Degradate 

identities and degradation time cannot be evaluated without laboratory metabolism data. 

Copper octanoate 

Copper octanoate (also known as Cu soap) is the Cu salt of a fatty acid. It is degraded through 

hydrolysis to form of Cu 2+ and the octanonate (8 carbon carbon fatty acid) moiety 

(http://www.epa.gov/fedrgstr/EPA-PST/1997/August/Day-01/p20361.html). The fatty acid 

moiety is degraded through beta-oxidation. 

Copper salts of rosin and fatty acids 

These compounds are used on terrestrial food and non-food crops including avocados, berries, 

cherries, citrus, grapes, mangoes, peaches, nectarines, strawberries, walnuts beans, broccoli, 

potatoes, azaleas, pine, junipers, and maples. The registrant also submitted environmental fate 

data from Arizona Chemical (Regulatory Bulletin #3-Biodegradability) and open scientific 

literature. The data indicate that fatty acids (oleic, linoleic, and stearic acids) and resin acids 

(abietic, palustric, and pirmaric acids) are rapidly degraded by microbial-mediated mineralization 

(80 to 85% degradation for 7-days in sewage sludge). The registrant also submitted data from 

the open-literature on environmental chemistry of Cu and biological effects of resin acids. These 

data indicate abietic acid and its dimer dihydroabietic acid can be metabolized by 

Flavobacterium resinovorum and Pseudomonas resinovorans. These organisms can metabolize 

rosin acids from Pinus maritima, methyl abietate, dehydroabietic acid, neobietic, and 

levopimaric acids. However, the organisms could not completely metabolize tetrahydroabietic 

acid, daniellic acid, sclaeol, dipterocarpol, cholesterol, and rosin esters. 

Rosin acids are a complex mixture of organic acids from oleoresin exudate in longleaf pine 

(Pinus palustris) and slash pine (Pinus elliottii). Rosin acids have been identified as abietic type 

acids (including abietic acid, levopimaric acid, nonabietic acid, palustric acid, dehydroabietic 

acid, dihydroabietic acid, tetrahydroabietic acid) and pimaric type acids (including pimaric acid, 

isopimaric acid, and delta 8,9-isopimaric acid). Abietic acid (1,2,3,4,4a,5,6,10,10a-decahydro1,4a-dimethyl-7-(1-methylethyl)-1-phenanthrenecarboxylic acid) and pimaric acid (7-ethyl1,2,3,4,4a,4b,5,6,7,9,10,10a-dodecahydro-1,4a,7-trimethyl-1-phenanthrenecarboxylic acid) are 

insoluble in water (Windholz et al., 1983 and Weast, 1968). Abiatic acids may be metabolized 

by lactic and butyric bacteria. (Merck, 1983). Based on the cited literature, rosin acids may have 

a low binding affinity to soil/sediments because rosin acids should be an anionic species in most 

environments. Low soil/sediment binding affinities are expected for compounds with carboxylic 

function groups. The degradation of rosin acids appears to be dependent on microbiallymediated processes, with the rate and final degradate dependent on type of rosin acid. 
35 

3.1.3 Urban Uses (Root Killers) 

Conventional7

 urban uses of copper-containing pesticides include turf applications and addition 

of copper to domestic sewage lines to prevent tree root growth. Turf applications are addressed 

in the agricultural use section. In response to comments, primarily from the state of California, 

EFED has included an assessment of root killers using the “Down the Drain” model, EFAST 2.0, 

developed by the Office of Toxic Substances to estimate the concentrations of household 

chemicals delivered to receiving waters following treatment. Concentrations in receiving waters 

are estimated based on flow recurrence events, and represent low flow conditions. 

Concentrations calculated using this model are not directly comparable to concentrations 

estimated using EXAMS, which is based on a standard, constant-volume waterbody. To 

calculate risk quotients, the BLM was used to estimate copper activity based on the median water 

chemistry of the USGS monitoring sites, and then compared to the activity associated with the 

site-specific invertebrate and fish LC50s. 

3.2 Aquatic Exposure Assessment 

3.2.1 PRZM-EXAMS Modeling Inputs and Scenario Selection 

A refined Cu exposure assessment was conducted to address uncertainties associated with the 

impact of complexation with dissolved organic carbon (DOC) and variable water quality in 

ambient surface water. 

PRZM/EXAMS input parameters (Table 6) for Cu 2+ did not follow the standared EFED input 

parameter guidance because of the elemental nature of Cu . Degradation rates in soil and water 

were assumed to be 1,000,000 days for estimation of peak concentrations of Cu2+. The 

estimation of 21-day average concentration was estimated using a 10-day aerobic aquatic 

metabolism half-life to mimic rapid dissipation of Cu from the water column (MRID 00099539, 

00062074, 411890-01). Soil/sediment partition coefficients for sand and clay soils were used to 

bracket estimated Cu2+ concentrations in the water column and sediment pore water. Vapor 

pressure and Henry’s Constant were assumed to be extremely low to mimic the elemental nature 

of Cu. 

For terrestrial uses of copper, off-site movement of introduced copper was estimated using the 

PRZM/EXAMS models [PE4V1(8/13/03) shell using PRZM3.12 (5/2401) and EXAMS 2.98.04 

(7/18/02)] with the standard small pond used in FIFRA ecological risk assessments. 

PRZM/EXAMS modeling scenarios were selected to represent the various crop groupings, which 

provided a range of geographic conditions and use rates (Table 7). Use rates for CuSO4, 

CuSO4*5H2O, and Cu(OH)2 were derived from representative labels. Because of the vast array 

of labels, representative labels were chosen to represent the Cu application rates. The number of 

applications and application intervals were generally not specified on labels. Therefore, unless 

 

7

 Defined as uses that are not antimicrobial in nature. Antimicrobial pesticides, and uses in pools will be addressed 

in a separate action by the Antimicrobials Division. 
36 

otherwise specified on the label, the modeling was conducted using 4 applications at 7-day 

intervals. 

Table 6 PRZM/EXAMS Input Parameters for Cu 

Parameters Input Value and Units Source of Information

Soil Partition Coefficients 400 L/kg sand soil 

3600 L/kg clay soil Jones and Hetrick, 1991 

Molecular Weight 63.54 g/mole Atomic Weight of Cu 

Solubility in Water 5892 mg/L at 250

C Solubility of Cu(OH)2 with fixed 

water chemistry 

Vapor Pressure 1.00E-15 Torr Default to eliminate volatilization 

Henry’s Law Constant 1.00E-15 atm m3

/mole Default to eliminate volatilization 

Hydrolysis T1/2 Stable Default due elemental nature of Cu 

Aqueous Photolysis 1000000 days Default due elemental nature of Cu 

Aerobic Soil Metabolism 1000000 days Default due elemental nature of Cu 

Anaerobic Soil Metabolism 1000000 days Default due elemental nature of Cu 

Aerobic Aquatic Metabolism 1000000 days 

10 days (Dissipation Half-Life) 

A 10 day aquatic field dissipation 

half-life was used to estimate the 

21day average concentration. 
37 

Table 7 Application Rates and Intervals Used in PRZM/EXAMS Modeling 

Crop State

Maximum 

Application 

Rate 

(kg Cu/ha)

Average 

Application 

Rate 

(kg Cu/ha)

Number of 

Application

First 

Application 

Date

Application 

Intervals 

(days)

CA 0.59 ND 4 10-May 30 

MN 0.59 ND 4 10-May 30 

NC 0.59 ND 4 10-May 30 

Alfalfa 

TX 0.59 ND 4 10-May 30 

Almond CA 11.87 2.58 2 1-March 210 

NC 19 1.79 4 25-March 7 

Apples PA 19 2.24 4 25-March 7 

OR 19 4.25 4 1-May 7 

CA 15.43 3.81 4 15-October 7 

Citrus 

FL 15.43 2.24 4 15-May 7 

CA 1.18 ND 4 8-May 7 

FL 1.18 ND 4 15-November 7 

IL 1.18 ND 4 1-June 7 

NC 1.18 ND 4 11-May 7 

Corn 

OH 1.18 ND 4 1-June 7 

Filberts CA 35.62 ND 2 10-November 14 

Grapes CA 4.75 0.67 4 1-February 7 

Peaches GA 14.84 3.70 2 1-April 240 

ID 3.56 0.78 4 30-May 7 

Potatoes 

ME 3.56 0.90 4 30-May 7 

FL 6.10 ND 2 1-June 30 

Turf 

PA 6.10 ND 2 1-June 30 

Walnut CA 29.68 3.47 4 7-March 7 

ND-Not determined 
38 

3.2.2 USGS Monitoring Data and BLM Water Chemistry Parameters 

Because the PRZM/EXAMS model cannot account for chemical speciation of Cu , 

the Biotic Ligand Model (BLM) (Windows Version 2.0.0, 4/03) was used to estimate Cu 2+

concentration in the water column and sediment pore water of ambient surface water. Water 

quality input parameters required for the BLM include water temperature, pH, Cu concentration 

(:g/L), dissolved organic carbon (DOC) concentration (mg/L), humic acid (%), sulfate (SO4

 2- ) 

concentration (mg/L), calcium (Ca2+) concentration (mg/L) , magnesium (Mg2+) concentration 

(mg/L), potassium (K+

) concentration (mg/L), chloride (Cl-) concentration (mg/L), alkalinity 

(CaCO3 equivalence mg/L), and sulfide (S2-) concentration (mg/L). Parameters for the BLM 

model were populated using USGS water quality monitoring data for filtered water (Table 8). 

The monitoring data provided all data input parameters except the humic acid percentage. 

Humic acid percentage was assumed to be correlated to the DOC concentration using a firstorder regression equation (humic acid percentage= 9.9155 + 1.6892*DOC). This regression 

equation was derived using the low and high bounding conditions for DOC and humic acid 

percentage in the development of the BLM. Correlations of DOC and humic acid concentrations 

have been found in surface water (Aoki, et al., 2004). 

The USGS water quality monitoring data were censored to remove all samples with water input 

parameters outside the range of the model. The censored USGS water quality data were further 

analyzed using Statistical Analysis System (SAS) to derive site specific descriptive statistics 

including mean, median, minimum, maximum, and standard deviation. Median water quality 

conditions for 811 sites were used in the BLM model to represent water column conditions in 

surface water across the United States (Appendix A). Median conditions were selected rather 

than worst case conditions because they represent the conditions most likely to occur. 

Variability across sites is expected to be greater than variability at a single site. 

Additionally, the USGS provided monitoring data on total digestible Cu in suspended sediments 

to assess ambient Cu concentrations in sediments. These data were used to estimate ambient 

concentrations of Cu in sediment and sediment pore water. 

PRZM-EXAMS estimated Cu concentrations (peak and 21-day average concentration) for low 

Kd (sand soil) and high Kd (clay soil) for each crop scenario were used as the Cu input 

concentration in the BLM model. Median water quality conditions for 811 sites provided the 

water chemistry for the BLM model. BLM simulations provided an estimation of the Cu2+

activity (moles/liter) in the water column and sediment pore water. 

The BLM model for Cu speciation is sensitive to changes in pH, DOC, humic acid percentage, 

and alkalinity. These input parameters are discussed in more detail. 
39 

Table 8 Summary of USGS Water Quality Data Used in the BLM1

Parameter Units Data Range for 

BLM 

Missing 

Data Low Value High Value Median Value 

Average 

Value 

Temperature 0C 10 to 25 0 10 24.5 17.4 17.2 

pH 4.9 to 9.2 0 5.05 9.2 8.0 7.85 

Cu :g/L 363 1.0 51.4 1.2 2.61 

DOC mg/L 0.05 to 29.65 0 0.2 29.2 3.00 4.06 

Humic Acid2 % 10 to 60 0 10 29.15 14.90 16.69 

Ca2+ mg/L 0.204 to 120.24 0 0.95 114 37.6 40.62 

Mg2+ mg/L 0.024 to 51.9 0 0.18 51.8 10.6 13.02 

Na+ mg/L 0.16 to 236.9 0 0.88 190 10.3 21.09 

K+ mg/L 0.039 to 278.4 0 0.09 18 2.2 2.93 

SO4

2- mg/L 0.096 to 278.4 0 0.10 270 26.1 44.46 

Cl- mg/L 0.32 to 279.72 0 0.32 266 11 22.66 

Alkalinity mg/L 1.99 to 360 0 2.0 311 116 120.61 

S2- mg/L ND 811 ND ND ND ND 

1- Data represent median site water quality conditions within the range of data for development of BLM 

2- Humic acid percentage was estimated from the DOC concentration 

ND – No data available, oxic conditions assumed 

The surface water pH ranged from 5.05 to 9.2. The median water pH in surface water was 8.0. 

Regional analysis of water pH indicates lower pH values (pH < 7) are generally found in the 

eastern United States. In contrast, high water pH values were generally found in the western 

United States. This regional analysis is an approximation because it does not consider site 

specific factors on water pH such as acid mine drainage, karst regions, etc. 
40 

 pH

456789 10

Cumu al t vi e Probability 0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

Figure 4 : Cumulative Probability Distribution of Site Specific Median pH from USGS 

Monitoring Data 

The DOC data has some uncertainties because there were several samples with extremely high 

DOC values (>29.65 mg/L). The high DOC values are suspected to be associated with methanol 

contamination from rinsing sampling equipment. As a consequence of the possible 

contamination, the samples with high DOC values (>29.65 mg/L) were removed from the BLM 

input parameter data set to avoid unreliable estimation of Cu2+ activities. The median DOC 

concentration was 3 mg/L. Although the DOC concentration in surface water should be site 

specific, GIS analyses suggest regional differences in DOC. Sites in the southern United States 

and north-central United States generally have higher DOC water values (18 to 29 mg/L) than 

sites in the northeastern and western United States. 

 

Figure 5 : Cumulative Probability Distribution of Site Specific Median DOC from USGS 

Monitoring Data 

DOC (mg/L)

0 5 10 15 20 25 30 35

Cumu al t vi e Probability 0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0
41 

Water alkalinity ranged from 2 to 311 mg CaCO3 equivalence/L. Median water alkalinity is 116 

mg/CaCO3 equivalence/L. Alkalinity in surface water appears to be regionally dependent. 

Higher alkalinity values (>117 mg/L) were generally found in the central and western United 

States. 

 

Figure 6 : Cumulative Probability Distribution of Site Specific Median Alkalinity from USGS 

Monitoring Data 

Ambient Cu Concentrations 

Surface Water 

Cu concentrations in ambient surface water ranged from <1 to 51.40 :g/L. The median Cu 

concentration was 1.2 :g/L (Table 8). For purposes of this assessment, Cu concentrations 

reported as < minimum reporting limit (MRL) were assumed to equal to the MRL (1 :g/L). 

Because the median Cu concentration is slightly higher than the MRL, it indicates the 

distribution of Cu concentrations at those sites where it was measured is highly skewed to lower 

concentrations. The USGS sites with high Cu concentrations (>20 :g/L) were Apsen Creek, CA 

(Sampling Station # 384301119393001), South Platte River, CO (Sampling Station # 

392740105404400), Animas River (Sampling Station #9359020), and the Ohio River (Sampling 

Station # 403304081305700). These sites have low DOC (<2.65 mg/L), alkalinity (< 6mg/L), 

and pH (<6.3), and would be considered vulnerable sites using the criteria EFED established for 

this assessment. 

Suspended Sediment and Sediment Pore Water 

Total Cu concentrations in digested suspended sediment (expressed on a :g Cu/gram dry 

sediment) ranged from 1 to 1900 :g/g (Table 9). The median total Cu concentration in sediment 

was 22 :g/g. The distribution of total Cu concentrations was highly skewed toward lower 

concentrations (<100 :g/g). 

Alkalinity (mg/L)

0 50 100 150 200 250 300 350

Cumu al t vi e Probability 0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0
42 

Sediment pore water concentrations were estimated using a simple partitioning model 

(Kd=Csediment/Cwater) using the suspended sediment Cu concentration as the Csediment. This 

estimation approach assumes 100% of the Cu on the suspended sediment is readily exchangeable 

with the pore water. Maximum pore water concentrations for sediments could range from 528 to 

4750 :g/L. Median sediment pore water concentrations are predicted to range from 6 to 55 :g/L, 

which is comparable to PRZM/EXAMS estimated sediment pore water concentrations (0.05 to 

44 :g/L) for the first year simulation. 

Table 9 Suspended Sediment USGS Monitoring Data 

Parameter Units Number of 

Values Low Value High Value Median Value 

Average 

Value 

Total Cu in 

Sediment 

(Digestion) 

μg/g 1278 1 1900 22 39 

Estimated Cu in 

Pore Water1

(Kd=3.6L/g) 

μg/L 1278 0.2 528 6 11 

Estimated Cu in 

Pore Water1

(Kd=0.4 L/g) 

μg/L 1278 3 4750 55 99 

1- Estimation assume equilibrium with Cu on suspended sediment. Used Cw=Cs/Kd, where Cs=total Cu Sediment and 

Kd=3600L/kg (3.6L/g) or 400L/kg (0.4L/g) 

3.2.3 PRZM-EXAMS Modeling Output 

Water Column Cu Concentrations 

Water column concentrations were predicted using the PRZM/EXAMS simulations. As 

expected, these simulations show Cu accumulation in the water column. Because of this 

accumulation, the reporting of a 1-in-10 year return frequency concentration is not appropriate. 

Therefore, the reported data describe the concentration of introduced Cu in the water column as 

well as the accumulation rate during a 30 year use period. The highest water column water 

concentrations were found with sediment exhibiting a low Kd for each scenario. The PA apple 

scenario had the highest concentration and accumulation rate of introduced Cu (Table 10). 
43 

Table 10 Estimated Water Column Dissolved Copper Concentrations Based on Label Application Rates 

1-in-10 year Concentration 

(ug/L)

First Year Concentration 

(ug/L)

Crop State Low Kd High Kd Low Kd High Kd

Peak 21-day Peak 21-day Peak 21-day Peak 21-day

Accumulation 

Slope 

for Peak Conc.

(ug/L/year)

CA 14.2 13.1 2.9 0.4 1.8 0.7 1.4 0.1 0.46 

MN 27.1 3.2 3.1 0.7 1.8 0.5 1.4 0.1 0.98 

NC 52.5 4.3 6.5 1.3 1.8 0.6 1.4 0.1 1.87 

Alfalfa 

TX 84.5 7.8 6.1 0.9 2.9 0.7 1.4 0.1 0.52 

Almond CA 216.7 18.9 54.8 7.4 31.4 10.9 27 1.7 6.83 

NC 1848 159.9 631.6 123.1 71.7 36 45.6 5.8 73.9 

Apples PA 3529 256.3 817.9 168.4 350 119 365 26.8 119.92 

OR 1317 125 431.7 102.8 70.6 34.5 44 5.7 46 

CA 349.2 324.9 70.4 11.6 57.4 32.5 35.6 4.6 10.87 

Citrus 

FL 1766 104.7 382.7 58.8 57.4 23.8 35.8 4.6 64.78 

CA 167 17.1 42.8 8.3 13.2 4.4 9.2 0.8 5.75 

FL 202.2 10.2 34.8 5.1 4.4 1.9 2.7 0.3 7.54 

IL 286.2 22.2 50.4 10.9 22.4 8.4 19.5 1.6 9.70 

NC 234.9 15.8 45.5 8.8 9.3 4.1 8.1 1.0 8.26 

Corn 

OH 255.8 18.9 53.5 10.5 18.4 6.1 15.3 1.3 8.26 

Filberts CA 2768 279.9 415.2 198 162 68 81.6 11.1 13.53 

Grapes CA 110.7 3.6 23.1 4.2 17.6 3.0 11.0 1.4 3.46 

Peaches GA 381.5 32.7 277.5 30.5 25.6 8.2 27.3 1.8 12.95 

ID 122.7 13 53 9.1 13.2 5.9 8.3 1.1 4.22 

Potatoes 

ME 662.5 63.4 139.6 38.1 54.9 22.8 46.2 4.9 23.92 

FL 579.8 64.4 152.1 25.5 45.8 14.1 10.7 1.0 26.34 

Turf 

PA 839.1 66.6 177.1 24.5 60.9 16 11.9 1.4 19.45 

Walnut CA 1057 103 267.9 48.3 110 55.2 68.8 68.7 33.97 
44 

The state average application rates reduced the application rates and hence cause a reduction in 

water column concentrations (Table 11). As expected, the PA apple scenario had the highest Cu 

concentration (41.2 :g/L) and accumulation rate (14.14 :g/L/year). 

Table 11 Estimated Water Column Dissolved Copper Concentrations Based on State Average Rates 

1-in-10 year Concentration 

(ug/L)

First Year Concentration 

(ug/L)

Crop State Low Kd High Kd Low Kd High Kd

Peak 21-day Peak 21-day Peak 21-day Peak 21-day

Accumulation 

Slope 

for Peak Conc.

(ug/L/year)

Almond CA 47.1 4.5 11.9 4.5 6.8 2.2 6.8 2.2 1.48 

NC 173.8 15.1 59.5 11.6 6.8 3.4 4.3 0.5 6.96 

Apples PA 416.5 31.3 96.4 19.9 41.2 14.1 43 3.2 14.14 

OR 295.2 28 96.7 23.1 15.8 7.7 9.9 1.3 10.32 

CA 86.3 7.8 17.5 2.9 14.2 6.7 8.8 1.1 2.68 

Citrus 

FL 256.4 15.3 55.5 8.5 8.3 3.5 5.2 0.7 9 

Grapes CA 15.7 1.6 3.3 0.6 2.5 1.3 1.6 0.2 0.49 

Peaches GA 95.1 8.1 69.2 7.6 6.4 2.1 6.8 0.5 3.22 

ID 270.5 2.9 11.7 2.0 2.9 1.3 1.8 0.2 0.93 

Potatoes 

ME 166.4 15.4 35.1 9.6 13.8 5.5 11.6 1.2 6.02 

Walnut CA 123.7 12.1 31.3 5.6 12.9 6.5 8.0 1.0 3.98 
45 

Table 12 Estimated 60-day Water Column Dissolved Copper Concentrations 

 Label Rates Average Rates

1-in-10 year 

Concentration

(ug/L)

First Year 

Concentration

(ug/L)

1-in-10 year 

Concentration

(ug/L)

First Year 

Concentration 

(ug/L) Crop State

Low 

Kd

High 

Kd

Low 

Kd

High 

Kd

Low 

Kd

High 

Kd

Low 

Kd

High 

Kd

CA 13.0 0.4 0.6 0.1 NC NC NC NC 

MN 2.2 0.7 0.4 0.1 NC NC NC NC 

PA 3.2 1.3 0.5 0.1 NC NC NC NC 

Alfalfa 

TX 4.7 0.8 0.5 0.1 NC NC NC NC 

Almond CA 15.3 8.3 4.5 0.7 3.3 1.8 1.0 0.2 

NC 128.0 114.3 23.4 4.0 12.1 10.6 2.2 0.4 

Apples PA 212.6 153.6 74.6 16.5 25.5 18.2 8.8 1.9 

OR 94.7 96.7 20.5 3.4 21.2 21.7 4.6 0.8 

CA 312.9 9.8 20.5 2.72 5.2 2.4 4.0 0.7 

Citrus 

FL 76.4 53.5 13.8 2.7 11.2 7.8 2.0 0.4 

CA 13.8 8.0 2.1 0.4 NC NC NC NC 

FL 8.0 4.9 1.0 0.2 NC NC NC NC 

IL 16.9 10.0 6.3 1.2 NC NC NC NC 

NC 12.1 8.1 2.9 0.7 NC NC NC NC 

Corn 

OH 14.8 9.7 5.3 1.0 NC NC NC NC 

Filberts CA 221.4 191.9 43.1 6.7 NC NC NC NC 

Grapes CA 2.0 3.6 1.4 0.8 1.1 0.5 0.8 0.1 

Peaches GA 23.0 26.1 3.6 0.8 5.7 6.5 0.9 0.2 

ID 10.3 8.6 3.4 0.6 2.3 1.9 0.8 0.1 

Potatoes 

ME 54.1 36.7 17.3 3.5 13.1 9.2 4.2 0.9 

FL 45.4 20.8 9.6 0.9 NC NC NC NC 

Turf 

PA 43.9 23.5 7.5 0.8 NC NC NC NC 

Walnut CA 86.9 43.9 32.9 5.3 10.2 5.1 3.9 0.6 

NC- Not calculated 
46 

3.2.4 Spray Drift Exposure Estimates 

A screening level spray drift analysis was conducted to assess the impact of Cu2+ drift from 

terrestrial crop uses on aquatic environments. The analysis assumes drift loadings of 5% of the 

application rate for aerial spray and 1% of application rate for ground spray, into the standard 

farm pond used in EXAMS. Estimated Cu2+ loading and peak Cu2+ concentration are shown in 

Table 13 and Table 14. 

Table 13 Aerial Spray Drift Loadings 

Application Rate 

(kg Cu2+/ha) 

Cu2+ Drift Loading 

(kg) 

Estimated Peak Concentration1

(μg/L) 

35.62 1.781 89.05 

29.68 1.484 74.2 

19 0.95 47.5 

15.43 0.7715 38.575 

14.84 0.742 37.1 

11.87 0.5935 29.675 

6.1 0.305 15.25 

4.75 0.2375 11.875 

3.56 0.178 8.9 

1.18 0.059 2.95 

0.59 0.0295 1.475 

1-Estimated peak concentration of Cu2+ in the standard farm pond (20E6 liters). 

Table 14 Ground Spray Drift Loadings 

Application Rate 

(kg Cu2+/ha) 

Cu2+ Drift Loading 

(kg) 

Estimated Peak Concentration1

(μg/L) 

35.62 0.3562 17.81 

29.68 0.2968 14.84 

19 0.19 9.5 

15.43 0.1543 7.715 

14.84 0.1484 7.42 

11.87 0.1187 5.935 

6.1 0.061 3.05 

4.75 0.0475 2.375 

3.56 0.0356 1.78 

1.18 0.0118 0.59 

0.59 0.0059 0.295 

1-Estimated peak concentration of Cu2+ in the standard farm pond (20E6 liters).
47 

3.2.5 PRZM/EXAMS Output-Sediment Pore Water Cu Concentrations 

Sediment pore concentrations were predicted using the PRZM/EXAMS simulations (Table 15). 

As expected, these simulations show that Cu accumulates in the sediment. Because there was 

accumulation in the sediment, the reporting of a 1-in-10 year return frequency concentration is 

not an appropriate probabilistic EEC in the exposure assessment. Therefore, the reported data 

attempt to describe the concentration of introduced Cu on sediment as well as the accumulation 

rate during a 30-year use period. The highest pore water concentrations were found with 

sediment exhibiting a low Kd for each scenario. The PA apple scenario had the highest 

concentration of introduced Cu (44 :g/L) for the first year of model simulation. The highest 

accumulation rate (:g/L/year) was associated with the CA filbert scenario. 
48 

Table 15 PRZM/EXAMS Estimated Sediment Pore Water Dissolve Copper Concentrations 

Annual Peak Pore Water 

Concentration 

(ug/L) 

Crop State Low Kd High Kd

1st 

Year

30th 

Year

1st 

Year

30th 

Year

Accumulation 

Slope 

for Peak Conc. 

(ug/L/year) 

Low Kd 

Accumulation 

Slope 

for Peak Conc. 

(ug/L/year) 

High Kd 

CA 0.42 13.74 0.05 1.713 0.46 0.06 

MN 0.43 25.41 0.05 1.85 0.92 0.06 

NC 0.51 48.37 0.05 3.50 1.75 1.93 

Alfalfa 

TX 0.69 81.19 0.05 3.41 2.97 0.12 

Almond CA 3.38 140 0.53 26.57 4.69 0.90 

NC 6.66 398 0.91 73.36 15.59 2.83 

Apples PA 44.7 1740 6.35 240 59.11 8.07 

OR 10.96 650 1.44 134 22.87 4.82 

CA 10.62 325 1.25 38.63 10.87 1.30 

Citrus 

FL 17.48 1760 1.97 249 62.81 8.84 

CA 2.69 164 0.33 25.48 5.63 0.89 

FL 0.81 202 0.10 24.19 7.29 0.86 

IL 8.08 283 0.98 31.37 9.54 1.04 

NC 4.41 235 0.64 30.80 8.11 1.02 

Corn 

OH 10.62 325 1.25 38.63 8.74 1.03 

Filberts CA 33.13 2680 2.32 266 93.80 9.34 

Grapes CA 3.09 97.57 0.37 12.66 3.26 0.43 

Peaches GA 5.58 363 0.88 106 12.49 3.70 

ID 3.00 120 0.35 20.36 4.22 0.76 

Potatoes 

ME 18.26 695 2.74 91.54 23.66 3.06 

FL 12.92 800 0.72 88.62 26.88 3.13 

Turf 

PA 7.82 502 0.50 60.84 17.61 2.18 

Walnut CA 23.4 1020 2.67 134 1.93 4.52 
49 

3.2.6 Evaluation of Aquatic Exposure Modeling 

Recognizing that PRZM was originally designed to estimate concentrations of organic 

compounds commonly used in pesticides, EFED compared open literature with measured copper 

concentrations in runoff to ensure PRZM predictions appeared reasonable. As a cross-check on 

the ability of the BLM to estimate Cu2+ concentrations in surface waters the estimate 

concentrations were compared to Cu mineral stability diagrams 

Field Monitoring Observations 

Open literature data indicate that agronomic management techniques (such as vegetative furrows, 

vegetative mulch, black plastic mulch) can limit transport of introduced copper from the 

application site (Rice, et al., 2002; Rice et al., 2003). Rice et.al (2002, 2003) found that foliar 

applied copper was available for off-site movement through soil erosion. Table 16 provides a 

comparison of open literature field monitoring data and PRZM predictions. 

Table 16 Comparison of Predicted and Measured Runoff Concentrations 

Field Parameter PRZM Rice et al., 2002 Rice et al., 2004

Location PA Apple Scenario Beltsville, MD Beltsville MD 

Single Application 

Applied Cu (lbs/A) 

19 3 1.149 

Number of Applications 4 3 1 

Multiple Application 

Applied Cu (lbs/A) 

76 9 1.149 

Applied Cu (mg/m2) 85,259 1,009 129 

Runoff Volume (L/m2) 0.1-to-1011 14-762 (vetch) 

13.7-147 (plastic) 

34-143 

Soil Erosion (g/m2) 

0.2- to-10,5001

median=90 

average=340 

38.7-1182 (vetch) 

247-535 (vetch) 

0.1-730 

Total Edge-of-Field Cu 

(mg/m2

) 

0.0001 to 58.71

median=0.72 to 0.79 

mean= 3.2 to 3.2 

0.04-to-15.0 (vetch) 

0.26-74 (plastic) 

5.6 -15.1 

Cu in Suspended Sediment (%) 81- to-95 81.7-86.7 88 -93 

Cu in Runoff (%) 5 to 19 13.3-18.3 12-7 

1- Runoff volumes were calculated on an event basis for low Kd and high Kd assumptions. 

2- Runoff volumes were calculated on seasonal basis or annual basis. 
50 

Although the PRZM modeling (a PA apple scenario) and field monitoring studies were similar in 

geographic location, PRZM modeling was based on higher application rates than the field 

studies. The comparisons of erosion rates and runoff volumes are based on similar mass/volume 

per unit area (m2

) units. Rice et al., 2002 evaluated the influence of hairy vetch vegetative mulch 

and black plastic mulch on Cu runoff. Rice et al, 2004 evaluated the influence of black plastic 

mulch used with bare and vegetated furrows. Single event runoff volumes from the PRZM 

modeling also are comparable to the actual field monitoring data. 

The average and median runoff and erosion estimates from the PRZM simulation for the PA 

apple scenario are within the range of runoff and erosion estimates in the field studies. The 

distribution of erosion events indicates a highly skewed distribution due to a few extremely high 

erosion events (10,500 g/m2

). However, average erosion losses are within the range of observed 

erosion losses in field studies. The total edge of field Cu loss from the PRZM simulation is 

within the range of the field monitoring data. As expected, the high erosion losses coupled with 

the high Cu application rates in the PRZM simulation led to a few events with high losses of Cu. 

The Cu partitioning in runoff water and suspended sediment was similar for the PRZM modeling 

and actual field monitoring data. As expected, introduced Cu was predominately moved from 

the application site on entrained sediments. In general, it appears PRZM provides reasonable 

estimations of the runoff of copper applied to the field. 

3.2.7 Chemical Equilibrium Analysis 

Thermodynamic context of the BLM predicted concentrations of Cu 2+ concentrations were 

assessed using stability diagrams and mineral stability constants for known Cu(II) minerals 

(Lindsay, 1979). Interpretation of stability diagrams is as follows: 

• Cu2+ concentrations above some known Cu mineral stability boundaries suggest 

supersaturation of the Cu minerals; 

• Cu 2+ concentrations below some known Cu mineral stability boundaries suggest under 

saturation to the Cu minerals; and 

• Cu2+ concentrations on a known Cu mineral stability boundary suggest possible 

equilibrium condition with the Cu mineral. 

Stability Constants for Cu Minerals 

Dissolved Cu (Water Column) 

The construct of the stability diagrams assumes Cu2+ ion is the predominant ion due to oxic 

nature (pE+pH> 12) of surface water. These conditions were assumed because aquatic 

organisms require oxygen for normal biological function. Cupric (Cu 2+) ion activities in ambient 

surface waters suggest chemical equilibria conditions are not constant over a broad pH range 

(Figure 7). Copper activities in neutral and alkaline waters (pH>7) indicate supersaturation of 

cupric ferrite in equilibrium with soil Fe. Figure 8 illustrates Cu 2+ activities from the PA apple 

scenario, which is the highest Cu runoff scenario, exceed the solubility of CuO (tenorite) under 
51 

neutral and alkaline pH conditions. In acidic surface waters, however, Cu2+ activities appear to 

be in near equilibrium or under saturated to soil Cu for both ambient and introduced Cu. 

Sediment Pore Water 

The stability diagrams for Cu2+ in sediment pore water (Figure9) were constructed under the 

premise the surface sediment (<5 cm depth) is an oxic (pE+pH >12) environment. These 

conditions were assumed because benthic organisms require oxygen for normal biological 

function. Bed sediments (> 5 cm depth), however, are assumed to be more anoxic than surface 

sediments. Because of the variability of redox conditions and it potential effect on Cu chemistry, 

the impact of redox potential on Cu chemistry was evaluated. 

Estimated Cu2+ activities in sediment pore waters is dependent on the sorption potential of the 

sediment. Low Kd sediments such as sands may have Cu2+ activities supersaturated to CuO 

(tenorite) in neutral and alkaline pore waters of surface sediments. High Kd sediments such as 

clay may have Cu2+ activities are supersaturated to cupric ferrite in equilibrium with soil Fe. In 

acidic sediments, however, Cu 2+ activities are approaching equilibrium with cupric ferrite in 

equilibrium with amorphous Fe(OH)3 or soil Cu regardless of the Kd of the sediment for Cu. 

One interesting observation is that estimated Cu2+ activities in sediment pore water for high Kd 

sediments are similar to Cu 2+ activities found in the ambient surface water. This observation 

may indicate a steady-state condition between suspended sediment and the water column. 

Suboxic or anoxic redox potentials are expected in subsurface bed sediments. Under these 

environmental conditions, the cuprous Cu+ ion is expected to the predominant Cu ion. The 

controlling Cu mineral under suboxic redox potentials (pE+pH 5 to 15) is expected to be cuprous 

ferrite (Lindsay, 1979). In more reduced environments (pE +pH < 5), chalcocite (Cu2S) is 

expected to control Cu activities. Based on water quality parameters in the USGS monitoring 

data, chalcocite precipitation is expected to occur at a pE+pH range of 4.0 to 5.1. Under these 

conditions, the Cu activities are anticipated to be highly reduced due to the formation of a Cu 

sulfide mineral. This reduction in Cu activity is expected to reduce the bioavailability and 

toxicity of Cu (US EPA 2005). 
52 

 

 

Figure 7 : Cu Activities in Ambient Surface Waters on Cu(II) Minerals Stability Diagram 

Figure 8 : Cu Activities for the PA Apple Scenario on Cu(II) Minerals Stability Diagram 

pH

3456789 10 11

Cu Act vi ity (mo el s/liter) 1e-19

1e-18

1e-17

1e-16

1e-15

1e-14

1e-13

1e-12

1e-11

1e-10

1e-9

1e-8

1e-7

1e-6

1e-5

1e-4

1e-3

1e-2

1e-1

1e+0

1e+1

1e+2

1e+3

1e+4

 Cu(OH)2 

CuO 

 Soil Cu 

Cu ferrite-geothite 

 Cu ferrite-amphor 

Cu ferrite-soil Fe 

Ambient Cu Activity 

pH

3456789 10 11

ol g Cu Act vi ity (mo el s/liter) 1e-19

1e-18

1e-17

1e-16

1e-15

1e-14

1e-13

1e-12

1e-11

1e-10

1e-9

1e-8

1e-7

1e-6

1e-5

1e-4

1e-3

1e-2

1e-1

1e+0

1e+1

1e+2

1e+3

1e+4

Cu(OH)2 

 CuO 

 Soil Cu 

 Cupric ferrite-geothite 

 Cu ferrite-amphorous Fe(OH)3 

 Cupric ferrite-soil Fe 

Cu activity for PA apples 
53 

 

 

Figure 10 : Sediment Pore Water Cu Activities from USGS Monitoring Data on a Cu(II) 

Minerals Stability Diagram 

 

Suspended Sediment (Low Kd Sediments)

pH

3456789 10 11

Cu

2+

Act vi ity (mo el s/liter) 1e-19

1e-18

1e-17

1e-16

1e-15

1e-14

1e-13

1e-12

1e-11

1e-10

1e-9

1e-8

1e-7

1e-6

1e-5

1e-4

1e-3

1e-2

1e-1

1e+0

1e+1

1e+2

1e+3

1e+4

 Cu(OH)2 

 CuO 

Soil Cu 

Cu ferrite-geothite 

 Cu ferrite-amphor 

Cu ferrite-soil Fe 

pH vs LoKd ActCu 

Suspended Sediment (High Kd Sediments)

pH

3456789 10 11

Cu

2+

Act vi ity (mo el s/liter) 1e-19

1e-18

1e-17

1e-16

1e-15

1e-14

1e-13

1e-12

1e-11

1e-10

1e-9

1e-8

1e-7

1e-6

1e-5

1e-4

1e-3

1e-2

1e-1

1e+0

1e+1

1e+2

1e+3

1e+4

 Cu(OH)2 

 CuO 

Soil Cu 

Cu ferrite-geothite 

 Cu ferrite-amphor 

Cu ferrite-soil Fe 

Cu Activity 
54 

3.2.8 Direct Aquatic Application 

Direct application of Cu 2+ into aquatic environments based on labeled rates can result in peak 

concentrations of up to 990 μg/L (Table 17). Higher Cu 2+ concentrations are expected for 

swimming pool water systems and sewage systems. These uses are not expected to directly 

impact aquatic ecosystems without some prior treatment process. 

Table 17 Estimated Dissolved Copper Concentrations for Direct Water Applications 

Uses EPA Reg No 

Maximum 

Label Rate 

(ug/L) 

Maximum 

Daily Peak 

(ug/L) 

21- day 

Average 

(ug/L) 

60 day 

Average 

(ug/L) 

90 day 

Average 

(ug/L) 

Irrigation 

Systems 001812-00314 99 99 52 23 16 

Sewage 

Systems 070246-00001 1997 NA NA NA NA 

Swimming 

Pools, Water 

Systems 

070246-00001 3424 NA NA NA NA 

070246-00001 24 24 13 6 4 

01812-00313 990 990 522 234 158 

Lakes/Ponds/ 

Reservoirs 

01812-00304 990 990 522 234 158 

Ornamental 

Ponds/Aquia 070246-00001 24 24 13 6 4 

Information received during the public comment period indicate that the majority of users treat 

only a portion of a small water body when applying copper-containing products for algae and 

aquatic weed control. Additional screening level modeling was conducted for direct applications 

of Cu2+ to aquatic environments. EXAMS 2.98.04 (7/18/02) was employed to account for 

sediment:water partitioning and dissipation rates of Cu2+ from the water column. The modeling 

scenario assumed the standard farm pond (20E6 liters) in Florida (pond environment file 

w12842.dvf) treated at variable volumes with a target concentration of 1 ppm Cu2+. The 

modeling was conducted using a low Kd sediment (Kd=400) and aquatic dissipation rate of 10 

days. Two treatments were assumed, with an interval of 30 days. Applications of Cu2+

 were 

modeled for May 10th and June 10th. Table 18 shows the variable volumes and the predicted 

peak Cu2+ concentration in the water column. 
55 

Table 18 Predicted Concentrations for Direct Applications 

Percent of 

Pond 

Treated 

Cu2+

Loading 

(kg) 

Estimated Cu2+

Concentration1 

(μg/L) 

EXAMS Predicted Peak 

Cu2+ Concentration 

(μg/L) 

5 1 50 49.87 

10 2 100 99.70 

25 5 250 249 

50 10 500 451 

100 20 1000 903 

1 Assumes complete mixing in the pond for one application with 

no sediment sorption or dissipation. 

3.2.9 Urban Uses (Root-Killers) 

A screening level assessment was conducted to assess the impact of copper containing root 

inhibitors use in sewage systems on aquatic environments. No national use data were available. 

EFED made the conservative assumption that each household in the United States could apply 

copper sulfate crystals in accordance with label instructions. The modeling approach employed 

the disposal model in EFAST 2.0. It was assumed that each household in the United States 

(108,818,659 households,http://www.census.gov/population/projections/nation/hhfam/tableln.txt) used 0.5 lbs (0.227 kg) per application twice a year. This assumption equates to 

an estimated production mass of 4,940,366.7 kg Cu2+, in root killer products. The application 

rate and interval was based on the Southern Ag Copper Sulfate label (EPA Reg. No. 829-210). 

EPISuite was used to estimate removal efficiency of Cu2+ (1.8%) during sewage treatment, with 

the estimate based on copper sulfate. Selected exposure estimates were the 10th percentile 7q108

for daily peak concentration and the 10th percentile 30q5 for 21- and 60-day average 

concentrations (Table 19). 

Table 19 Estimated Cu2+ in Receiving Waters from Root-Killer 

Flow Frequency Dilution Factor 

Cu2+

Concentration 

(μg/L) 

7Q10 1.00 117.80 

30Q5 1.80 65.45 

 

8

 The 10th percentile 7Q10 is equal to the upper 90th percentile concentration during 10-year return frequency for the 

7-day lowest flow conditions. The 10th percentile 30Q5 is equal to the upper 90th percentile concentration during a 

5-year return frequency for the 30-day lowest flow conditions. 
56 

3.3 Ecological Effects Analysis 

The 1986 Re-registration guidance for copper sulfate (USEPA 1986a) waived and/or reserved 

the ecotoxicity studies for copper compounds, although some guideline studies were submitted 

for Group II compounds. However, copper is also regulated under the Clean Water Act (CWA) 

and the Comprehensive Environmental Response, Compensation and Liability Act (CERCLA). 

Recently, water, sediment, and soil criteria have been updated by EPA’s Office of Water (OW), 

and Office of Solid Waste and Emergency Response (OSWER), based primarily on extensive 

review and analysis of open literature. To remain consistent with other EPA programs, EFED 

has incorporated new ecological effects evaluation methods developed by OW and OSWER, 

where appropriate, and in accordance with EFED policies. 

3.3.1 BLM Endpoints and Corrections 

Copper toxicity in natural waters is largely a function of water chemistry, with copper at its most 

toxic in waters of low ionic strength and/or low in dissolved organic carbon (DOC). The pH of 

the water also affects toxicity. The updated Aquatic Life Criteria for Copper (EPA 2003) 

incorporates the influence of water chemistry by using the Biotic Ligand Model (BLM). The 

BLM (EPA 2003), essentially a combined speciation and toxicity model, allows calculation of 

toxicity values based on site specific water chemistry. Using this model, OW developed genus, 

specific toxicity values for 27 genera of aquatic organisms (Appendix E), in a normalized water 

chemistry. This species sensitivity distribution was used to establish the final acute value (FAV) 

of 4.2 μg/L dissolved Cu, and set the criteria mean concentration (CMC) of 2.1 μg/L dissolved 

Cu. Studies used by OW meet the ECOTOX criteria used by EFED for evaluating open 

literature. The BLM and draft Ambient Aquatic Life Criteria have been through the peer review 

process, and approved by Scientific Advisory Panel (SAP). 

Although an overall water concentration criteria exists, and under the CWA, receiving waters 

must meet the criteria established by OW, ecological risk assessments for pesticides require 

evaluation of potential risk to specific aquatic taxon: invertebrates, fish and plants. Because the 

toxicity of copper varies greatly depending on water chemistry, EFED opted to use existing 

water chemistry data to evaluate a range of sites across the United States. The general procedure 

for the analysis is shown in Figure 10. Water chemistry data collected by USGS (Table 6) was 

input into the BLM to calculate LC50s for Daphnia magna (cladoceran, representing aquatic 

invertebrates), and Pimephales promelas (fathead minnow, representing fish). To ensure the risk 

assessment is as protective as possible of non-target species, EFED uses the lowest scientifically 

defensible toxicity value available. Daphnia were the most sensitive genera of aquatic 

invertebrates for which data were available, and the most sensitive aquatic species overall. 

Salmonids (genus Onchorynchus; GMAV of 29.11 μg/L) are the most sensitive fish species, but 

at the time of this assessment, the BLM had not yet been implemented to calculate the LC50 for 

this genus, thus EFED elected to adjust the fathead minnow LC50s produced by the BLM by the 

ratio of the Onchorynchus GMAV to the Pimephales GMAV (29.11 μg/L:72.07 μg/L; 
57 

adjustment factor 0.404). One species of amphibian, the boreal toad (Bufo boreas; GMAV 

49.06) was included in the genus distribution used by OW to develop the criteria. The boreal 

toad was less sensitive to copper than the salmonid genus Onchorynchus, and it is unknown how 

sensitive this species is compared with other amphibians, thus the estimated Onchorynchus 

LC50s were used to assess risk to amphibians. The BLM does not evaluate LC50s for any aquatic 

plant species, although the Office of Water did locate acceptable open literature. These studies 

represent a wide range of endpoints and water chemistries, and much of the chemistry data 

required for the BLM is not included in the papers. Standard guideline studies (MRIDs) were 

submitted to EFED for aquatic plants. Laboratory test conditions (low DOC, moderate hardness, 

moderate pH) represent a moderate toxicity situation. The most sensitive aquatic plant species 

tested, the green alga, Selenastrum capricornutum, (LC50 3.1 ppb) was selected to represent this 

taxa. The BLM was used in speciation mode to convert the LC50 to Cu activity based on the 

chemistry of the test solution. Based on normalized water chemistry, the values used to evaluate 

potential effects of copper on freshwater aquatic organisms were: 

• Aquatic invertebrate - 3.6 ppb 

• Fish - 29.1 ppb 

• Aquatic plants - 3.1 ppb 

Due to the process by which the Criteria Maximum Concentration (CMC) was calculated (to be 

protective of 95% of aquatic species), toxicity values used to assess risk to specific genera are 

greater than the established CMC. 

 The minimum data requirements for chronic toxicity were not met, so OW elected to use the 

acute-to-chronic ratio (ACR) approach to derive chronic criteria. ACRs calculated from paired 

data sets ranged from 0.55 to 192. Based on normalized water chemistry, the ACR for 

freshwater organisms was determined to be 3.23. Sufficient saltwater data was not available to 

calculate the saltwater ACR, so the freshwater ACR is applied to marine and estuarine 

environments. 

A total of 44 genera were represented in the species sensitivity distribution used by OW to 

establish the saltwater criteria. This distribution included 34 species of invertebrates and 18 

species of fish. The calculated genera mean acute values (GMAVs) ranged from 11.5-6,448 ppb, 

and included some tests on sensitive early life stages. Salinity was appeared to affect copper 

toxicity, and those effects appear to be species specific. OW established a Final Acute Value 

(FAV)9

 of 6.19 ppb based on the most sensitive species (Mytilus, a commercially and 

recreationally important mussel species). The most sensitive fish species in the distribution was 

the summer flounder (Paralichthys dentatus), with an LC50 of 12.66 ppb. Other fish species in 

the distribution (which included salmonids) appeared to be less sensitive (LC50 >85 ppb). 

 

9

 The criterion mean concentration (CMC) is the FAV divided by a safety factor of 2. 
58 

PRZM/EXAMS

SIMULATIONS

(Site Specific 

Scenarios)

Biotic Ligand

Model(BLM)

Site Specific

USGS Water Quality

Monitoring Data

EECS (mol Cu2+/L)

{Cu} water 

{Cu} sediment pore water

Site Specific

Daphnia magna LC 50 (ppb)

Trout.LC 50 (ppb)

Exposure:Developing Site Specific EECs

EECs (ppb)

[Cu] water

[Cu] sediment pore water

Biotic Ligand

Model (BLM)

Effects:DevelopingSite Specific LC 50s

Site Specific

Daphnia magna LC 50 (mol Cu2+/L)

Trout LC 50 (mol Cu2+/L)

Site Specific RQs

Daphnia magna

Trout

Figure 10 -Site Specific AquaticAssessment Using the BLM

PRZM/EXAMS

SIMULATIONS

(Site Specific 

Scenarios)

Biotic Ligand

Model(BLM)

Site Specific

USGS Water Quality

Monitoring Data

EECS (mol Cu2+/L)

{Cu} water 

{Cu} sediment pore water

EECS (mol Cu2+/L)

{Cu} water 

{Cu} sediment pore water

Site Specific

Daphnia magna LC 50 (ppb)

Trout.LC 50 (ppb)

Exposure:Developing Site Specific EECs

EECs (ppb)

[Cu] water

[Cu] sediment pore water

Biotic Ligand

Model (BLM)

Effects:DevelopingSite Specific LC 50s

Site Specific

Daphnia magna LC 50 (mol Cu2+/L)

Trout LC 50 (mol Cu2+/L)

Site Specific

Daphnia magna LC 50 (mol Cu2+/L)

Trout LC 50 (mol Cu2+/L)

Site Specific RQs

Daphnia magna

Trout

Figure 10 -Site Specific AquaticAssessment Using the BLM
59 

3.3.2 Aquatic Plant Guideline Data 

Table 20 Aquatic Plant Toxicity Guideline Studies 

Species LC50 (ppm) 95% C.I. NOAEC (ppm) Classification 

(MRID)

Copper sulfate, pentahydrate

Duckweed 

(Lemna minor)

2.3 NR 0.10 Supplemental 

(43363604)

Bluegreen alga 

(Anabaena flos-aquae)

0.029 0.026-0.03 0.02 Core 

(43363602)

FW diatom 

(Navicula pelliculosa)

0.125 0.023-0.100 0.063 Core 

(43363601)

Green alga 

(Selenastrum 

capricornutum)

0.0031a 0.029-0.18 0.002 Core 

(43363603)

Marine diatom 

(Skeletonema costatum)

0.25 0.22-0.28 0.124 Core 

(43363605) a

 toxicity endpoint used in assessment 

3.3.3 Aquatic Incident Data Review 

Although copper compounds have been used as pesticides for over 100 years, relatively few 

incidents associated with the copper compounds are reported in the EIIS. EIIS runs were 

completed for all PC codes included in this action. Incidents were reported only for copper 

sulfate. It is unknown whether there is significant under-reporting of incidents. 

Of the 24 reported incidents, 7 were associated with terrestrial plants, and in all of the cases, 

certainty was rated as possible or probable. One case, on tomatoes in Washington state, was in 

accordance with registered use. For the other incidents, affecting corn and peanuts in Indiana, 

Minnesota, and Oklahoma, the legality of the use was not reported. Reported effects included 

plant damage, incapacitation, and pinched ears (corn). 

Seventeen of the reported incidents were associated with kills of aquatic organisms, primarily 

fish. Of these incidents, 10 were classified as possible, probable, or highly probable, and the 

pesticide was applied as registered10. The other incidents were cases of misuse (intentional or 

accidental), or effects unlikely to be related to the compounds in question. Reported incidents 

were generally fish kills, with the reported number of fish ranging from 100 to 1,000, except for 

one case in New York, where the report lists > 1,000,000 fish killed. Fishes affected include 

carp, bass, trout, sunfish, perch, catfish, shiner, and mosquitofish. Other organisms reported 

 

10 In cases where the legality of the application is unknown, EFED makes the conservative assumption that the 

application was in accordance with registered use. 
60 

include frogs, clams, and turtles. In all cases, effects reported were mortalities, but the 

mechanisms (direct toxicity or secondary effects such as low dissolved oxygen) were not 

specified. 

3.3.4 Bioaccumulation 

In developing the criteria, OW also evaluated bioaccumulation. Copper is known to 

bioaccumulate, especially in aquatic invertebrates like mollusks. Acceptable bioaccumulation 

studies were sparse, but the five BCFs that could be calculated are: 

• Fathead minnows 464 

• Asiatic clams 45,300 

• Polychaete worms 1,006-2,950 

• Mussels 2,491-7,730 

• Pacific oysters 33,400-57,000 

BCFs may vary greatly, dependent on the concentration of copper in the water, with higher BCFs 

occurring at lower concentrations. The importance of copper bioaccumulation in aquatic 

foodchains is not well established. Because copper is an important trace nutrient, some 

organisms may have mechanisms for maintaining homeostasis. Additionally, these mechanisms 

may be better developed in organisms chronically exposed to elevated levels of copper than in 

the naive organisms typically used in laboratory experiments. Thus, bioaccumulation has not 

been quantitatively evaluated in this assessment. 

3.4 Risk Estimation 

3.4.1 Method of Assessment 

Copper toxicity is heavily dependent on the chemistry of receiving waters. One assessment of 

San Diego Bay, CA showed that toxicity within the bay differed from 1.7 to 3.4 times between 

sites located near the mouth of the bay and the back of the bay (Rosen et al. 2005). Authors 

attributed this to differences in dissolved organic carbon (DOC) and total suspended solids 

(TSS). Copper ions form complexes with DOC, and can sorb to suspended solids. Water 

hardness and alkalinity are also prime determinants of copper toxicity. Because water chemistry 

varies widely from region to region based on geology, as well as within regions due to land use 

and cover, copper toxicity is site specific. Thus, instead of generically using the most sensitive 

endpoint derived from laboratory toxicity tests, EFED elected to evaluate aquatic copper toxicity 

using the Biotic Ligand Model (BLM) and water chemistry data from USGS monitoring sites. 

Because DOC is so critical in determining toxicity, only sites with measured DOC data were 

considered. The available data set was then censored to remove any sites with values above or 

below the parameters of the BLM. This resulted in a data set of 811 sites, representing 47 states 

(no sites in Maine, South Carolina, or Virginia). 
61 

The number of replicates and timing of sampling varied from site to site. For each site, summary 

statistics were generated using a SAS program, and the median water chemistry measurements 

were selected to represent the site.11 The BLM (Version 2.2) was run in the toxicity mode to 

estimate site specific LC50s for Daphnia magna (cladoceran; freshwater aquatic invertebrates) 

and Pimephales promelas (fathead minnow; freshwater fish). The BLM has been tested and 

validated for both these species. The genus Daphnia is the most sensitive freshwater 

invertebrate, based on the Genus Mean Acute Values (GMAVs) in the draft Ambient Water 

Quality Criteria (USEPA 2003a, Appendix E), thus use of this organism is in accordance with 

EFED policy of selecting the most sensitive organism. At the time this ecological risk 

assessment was developed, the BLM had not yet been validated for copper and rainbow trout. 

Based on the GMAVs salmonids of the genus Onchorhynchus are the fish most sensitive to 

copper. Thus, an Onchorhyncus-to-Pimephales ratio (0.404) was calculated based on the Genus 

Mean Acute Values (GMAVs) for Onchorynchus (LC50=29.11 ppb, 7 species evaluated) and 

Pimephales (LC50=72.07, 1 species evaluated.) Estimated site specific LC50s for the fathead 

minnow were adjusted using this factor, and the resulting estimated Onchorhynchus LC50 was 

used to evaluate site specific risk to fish. EFED uses fish toxicity data to evaluate risk to aquatic 

vertebrates, including amphibians. The draft Ambient Water Quality Criteria contained a 

GMAV for one amphibian, the boreal toad (Bufo boreas; LC50=49.06 ppb),showing it to be less 

sensitive than the salmonids. Although it is unknown how sensitive the boreal toad is to copper 

relative to other amphibian species, sufficient fish taxa were represented to indicate that the 

salmonids are among the most sensitive species, and they appear to be approximately 1.7x more 

sensitive than the boreal toad. 

As part of the development of the criteria, OW derived an acute-to-chronic ratio (ACR) of 3.23 

for freshwater organisms, although insufficient data were available to establish a saltwater ACR 

(USEPA 2003a). The BLM only estimates acute toxicity, so the ACR was applied to site 

specific LC50s for both the daphnids and salmonids to generate site specific chronic toxicity 

values.

3.4.2 Analysis of Site Chemistry 

Some sites (448; 55.2%) had measured dissolved copper data available. In cases where copper 

was detected, but below the limit of quantitation, concentrations were estimated at the 

quantitation limit (generally 1 ppb). Ambient copper levels measured ranged from 1 ppb to 51.4 

ppb. The source(s) of copper at these sites is unknown. For sites with measured ambient copper, 

the concentrations were compared to estimated Daphnia LC50 values to determine if existing 

concentrations exceeded the estimated Daphnia LC50

12. Ambient concentrations at 5 sites (2 in 

 

11 The data were not assumed to be normally distributed, and the median represents a better 

estimator of central tendency in non-normal distributions. 

12 This was intended as an exercise to evaluate the estimated LC50s, thus the comparisons were directly between the 

measured concentration and the BLM estimated Daphnia LC50. This was not evaluated as a risk quotient (RQ) or 

compared to any levels of concern (LOC) established by EFED. 
62 

Colorado, 1 in California, 1 in Ohio, and 1 in Illinois) exceeded. The two sites in Colorado also 

exceed the salmonid site specific LC50 values. The cause for high copper concentrations is 

uncertain. 

Based on site chemistry, estimated Daphnia LC50s ranged from 0.3 to 1,900 ppb, but the 

majority of the sites (90%) were between 1 pbb and 200 ppb. Estimated Onchorynchus LC50s 

ranged from 7.8 to 2,603 ppb, but the majority of the sites (91%) were < 600 ppb. The rank 

order of site toxicity differed slightly between the invertebrate and the fish, reflecting differences 

in the mode and strength of copper toxicity for the two taxa. Estimations of the chronic endpoint 

for invertebrates range from 0.1 ppb to 593 ppb and the chronic endpoints for fish range from 2 

ppb to 806 ppb. 
Daphnia_LC50_ppb

< 10

10 - 49.9

50 - 99.9

100 - 199.9

>200

0 150 300 600 900 1,200

Miles

Map 2

Estimated Daphnia LC50 Based on

Water Chemistry and BLM

Coppers Assessment

Created by: PDB 06/10/05

USEPA/OPP/EFED

Data Sources:

Water Chemistry: USGS NAWQA & NASQAN

Daphnia LC50: Estimated based on BLM
Trout_LC50

<10

10.1-100

101-500

501-1000

>1000

0 155 310 620 930 1,240

Miles

Map 3

Estimated Trout LC50 Based on

Water Chemistry and BLM

Coppers Assessment

Created by: PDB 07/26/05

USEPA/OPP/EFED

Data Sources:

Water Chemistry: USGS NAWQA & NASQAN

Toxicity: Calculated by BLM
Diss Cu > Daphnia LC50

med_cu

Not measured

0.2 - 2

2.1 - 10

10.1 - 15

15.1 - 51.4

0 150 300 600 900 1,200

Miles

Map 4

Measured Dissolved Copper

and Estimated Daphnia LC50

Coppers Assessment

Created by: PDB 06/10/05

USEPA/OPP/EFED

Data Sources:

Water Chemistry: USGS NAWQA & NASQAN

Daphnia LC50: Estimated Using BLM
66 

3.4.3 RQ Summary for Agricultural Uses 

Orchard Application-Label Rates

 As an initial screening, EFED compared all sites to a scenario producing the highest runoff 

concentration of copper (Pennsylvania apples, application rate 19 lb a.i./acre, Cu concentration 

350 ppb).13 Two variations on the scenario were run, one with a low Kd (less sorption of copper 

to the soil), and one with a high Kd (greater sorption of copper to the soil). Estimated peak 

environmental concentrations (EECs) were 350 ppb and 365 ppb14. Estimated 21-day 

environmental concentrations were 119 ppb and 26.8 ppb. Estimated 60-day environmental 

concentrations were 74.6 ppb and 16.5 ppb. For the acute endpoint, 99.4% of the sites exceeded 

the EFED acute level of concern (LOC) for invertebrates, 79.8% exceeded for fish, and 99.9% 

exceeded for aquatic plants. For the chronic endpoint, 98.2% of the sites exceeded the EFED 

chronic level of concern (LOC) for invertebrates and 44.9% exceeded for fish. The endangered 

species LOC was exceeded by >99% of sites for aquatic plants, invertebrates, and fish. RQ 

summaries for the low Kd estimate are shown below. 

Table 21 Aquatic RQ Summary Table: Orchard Label Rates 

Endpoint for RQ Minimum 

RQ 

Median RQ Maximum RQ Sites Exceeding 

LOC1

 Sites Exceeding 

Endangered Species 

LOC1

Acute 

Invertebrate 0.05 44.13 11,176 99.4% 100.0% 

Fish 0.01 1.60 646 79.8% 99.4% 

Aquatic Plant 0.40 1321.93 190,000 99.9% 99.9% 

Chronic 

Invertebrate 0.15 19.13 11,137 98.2% 

Fish 0.05 0.76 442 44.9% 

1

 Acute LOC for invertebrates and fish = 0.5, Acute endangered species LOC for invertebrates and fish = 0.05, acute 

and acute endangered species LOC for plants = 1.0, Chronic LOC for invertebrates, fish = 1.0 

 

13 Although the application rate for filberts (35.62 lb a.i./acre) was higher than apples, estimated Cu concentrations 

in the runoff, based on an orchard scenario in Oregon, were significantly lower (162 ppb) than the Pennsylvania 

apples (350 ppb), thus the highest application rate did not produce the greatest runoff concentration and was not 

used. 

14 Although the EEC for copper was slightly higher (4%) in the high Kd scenario, for all other scenarios, low Kd 

concentrations were higher, thus to maintain consistency throughout the assessment, the low Kd value (350 ppb) was 

used. 
67 

Row Crop Applications - Label Rates

 As an initial screening, EFED compared all sites to a scenario producing the highest runoff 

concentration of copper (Maine potatoes, application rate 3.56 lb a.i./acre, Cu concentration 54.9 

ppb). Two variations on the scenario were run, one with a low Kd (less sorption of copper to the 

soil), and one with a high Kd (greater sorption of copper to the soil). Estimated peak 

environmental concentrations (EECs) were 54.9 ppb and 46.2 ppb. Estimated 21-day 

environmental concentrations (EECs) were 22.8 ppb and 4.9 ppb. EECs at 60-days post 

application were 17.3 ppb and 3.5 ppb. RQs were calculated based on the more conservative low 

DOC estimate. For the acute endpoint, 58.1% of the sites exceeded the EFED acute level of 

concern (LOC) for invertebrates , 14.2% exceed for fish, and 98.3% exceed for aquatic plants. 

For the chronic endpoint, 54.5% of the sites exceeded the EFED chronic level of concern (LOC) 

for invertebrates and 9.5% exceed for fish. For the endangered species LOC, >98% of sites 

exceeded for aquatic plants and invertebrates, but only 43.3% exceeded for fish. RQ summaries 

for the more conservative estimate (low Kd) are shown below. 

Table 22 Aquatic RQ Summary Table: Row Crop Label Rates 

Endpoint for RQ Minimum 

RQ 

Median RQ Maximum RQ Sites Exceeding 

Acute or 

Chronic LOC 

 Sites Exceeding 

Endangered Species 

LOC 

Acute 

Invertebrate 0.01 0.76 807.02 58.1% 98.5% 

Fish 0.00 0.03 36.64 14.2% 43.3% 

Aquatic Plant 0.05 20.11 13,719 98.3% 99.4% 

Chronic 

Invertebrate 0.03 1.19 758.69 54.5% 

Fish 0.01 0.10 25.34 9.5% 

1

 Acute LOC for invertebrates and fish = 0.5, Acute endangered species LOC for invertebrates and fish = 0.05, acute 

and acute endangered species LOC for plants = 1.0, Chronic LOC for invertebrates, fish = 1.0
68 

Analysis Based on Average Applied Rates

As a number of the copper compound labels were difficult to interpret, and calculated 

applications rates for some labels were extremely high, EFED opted to also calculate RQs based 

on average application rates supplied by BEAD. Using the average rates, the Pennsylvania 

apples and Maine potatoes scenarios again produced the highest Cu concentrations in runoff. As 

with the labeled rates, runoff concentrations were compared to all USGS sites. 

Orchard Applications

The highest estimated runoff concentration (low Kd) for orchard applications was Pennsylvania 

apples. Estimated peak environmental concentration (EEC) was 41.2 ppb. Estimated 21-day 

environmental concentration (EEC) was 14.1 ppb. Estimated 60-day environmental 

concentration (EEC) was 8.8 ppb. RQs were calculated based on the more conservative low 

DOC estimate. For the acute endpoint, 49.2% of the sites exceeded the EFED acute level of 

concern (LOC) for invertebrates ,9.5% exceeded for fish, and 97.2% exceeded for aquatic plants. 

For the chronic endpoint, 37.4% of the sites exceeded the EFED chronic level of concern (LOC) 

for invertebrates and 6.7% exceeded for fish. For invertebrates, 96.2% of the sites exceeded the 

endangered species LOC, for aquatic plants 98.9% exceeded the endangered species LOC, and 

99.6% of the sites exceeded the endangered species LOC for fish. 

Table 23 Aquatic RQ Summary Table: Orchard Average Application Rate 

Endpoint for RQ Minimum 

RQ 

Median RQ Maximum RQ Sites Exceeding 

Acute or 

Chronic LOC 

 Sites Exceeding 

Endangered Species 

LOC 

Acute 

Invertebrate 0.01 0.47 498 49.2% 96.2% 

Fish 0.00 0.02 41.20 9.5% 35.8% 

Aquatic Plant 0.04 12.66 8,956 97.2% 98.9% 

Chronic 

Invertebrate 0.02 0.66 352 37.4% 

Fish 0.01 0.05 6.08 2.6% 

1

 Acute LOC for invertebrates and fish = 0.5, Acute endangered species LOC for invertebrates and fish = 0.05, acute 

and acute endangered species LOC for plants = 1.0, Chronic LOC for invertebrates, fish = 1.0
69 

Row Crop Applications

The highest EEC (low Kd) for row crop applications was 13.8 ppb, for Maine potatoes. The 21-

day EEC was 5.5 ppb. Estimated 60-day environmental concentration (EEC) was 5.5 ppb. For 

the acute endpoint, 17.6% of the sites exceeded the EFED acute level of concern (LOC) for

invertebrates , 1.2% exceeded for fish, and 84.1% exceeded for aquatic plants. For the chronic 

endpoint, 14.1% of the sites exceeded the EFED chronic level of concern (LOC) for 

invertebrates and 0.5% exceeded for fish. For aquatic plants 91.2% of the sites exceeded the 

endangered species LOC, for invertebrates 75.85% of the sites exceeded the endangered species 

LOC, and 11.8 % of the sites exceeded the endangered species LOC for fish. 

Table 24 Aquatic RQ Summary Table: Row Crop Average Application Rate 

Endpoint for RQ Minimum 

RQ 

Median RQ Maximum RQ Sites Exceeding 

Acute or 

Chronic LOC 

 Sites Exceeding 

Endangered Species 

LOC 

Acute 

Invertebrate 0.00 0.11 82.30 17.6% 75.8% 

Fish 0.00 0.01 2.34 1.2% 11.8% 

Aquatic Plant 0.01 3.04 1,823 84.1% 91.2% 

Chronic 

Invertebrate 0.01 0.23 88.63 14.1% 

Fish <0.01 0.02 2.04 0.5% 
PA_apples

<0.05

<0.5

>=0.5

0 155 310 620 930 1,240

Miles

Coppers Assessment

Created by: PDB 06/10/05

USEPA/OPP/EFED

Data Sources:

Water Chemistry: USGS NAWQA & NASQAN

Daphnia LC50: Estimated Using BLM

Map 5

Daphnia Acute Risk Quotient

Highest Runoff for Orchard Use

Label Application Rates

Peak runoff 350 ppb
ME_potatoes

<0.05

<0.5

>=0.5

0 155 310 620 930 1,240

Miles

Coppers Assessment

Created by: PDB 06/10/05

USEPA/OPP/EFED

Data Sources:

Water Chemistry: USGS NAWQA & NASQAN

Daphnia LC50: Estimated Using BLM

Map 6

Daphnia Acute Risk Quotient

Highest Runoff for Row Crop Use

Label Application Rates

Peak runoff 55 ppb
PA_apples

<0.05

<0.5

>=0.5

0 155 310 620 930 1,240

Miles

Coppers Assessment

Created by: PDB 06/10/05

USEPA/OPP/EFED

Data Sources:

Water Chemistry: USGS NAWQA & NASQAN

Daphnia LC50: Estimated Using BLM

Map 7

Daphnia Acute Risk Quotient

Highest Runoff for Orchard Use

Average Application Rates

Peak runoff 41 ppb
ME_potatoes

<0.05

<0.5

>=0.5

0 155 310 620 930 1,240

Miles

Coppers Assessment

Created by: PDB 06/10/05

USEPA/OPP/EFED

Data Sources:

Water Chemistry: USGS NAWQA & NASQAN

Daphnia LC50: Estimated Using BLM

Map 8

Daphnia Acute Risk Quotient

Highest Runoff for Row Crop Use

Average Application Rates

Peak runoff 14 ppb
CA_alfalfa

<0.05

<0.5

>=0.5

0 155 310 620 930 1,240

Miles

Coppers Assessment

Created by: PDB 06/10/05

USEPA/OPP/EFED

Data Sources:

Water Chemistry: USGS NAWQA & NASQAN

Daphnia LC50: Estimated Using BLM

Map 9

Daphnia Acute Risk Quotient

Lowest Runoff for Row Crop Use

Label Application Rates

Peak runoff 2 ppb
75 

Analysis Based on Spray Drift 

Peak concentrations of Cu2+ from spray drift were speciated using BLM model to estimate the 

concentration of ionic Cu2+. Median USGS monitoring site water quality data for 811 sites were 

used as input parameters for the BLM model (Appendix C). Risk quotients were estimated 

[activity of Cu2+

(site 1....811)/LC50 (site 1....811)] for each site for rainbow trout and Daphnia magna. 

The individual site RQs were ranked to determine the number of sites exceeding the acute risk 

LOC of 0.5 and the endangered species acute risk LOC of 0.05. 

Site exceedences of aquatic LOC and ES aquatic LOC were found for both ground and aerial 

spray drift loadings. As expected, the number of site exceedences were greater for Daphnia 

magna than for rainbow trout. This observation is due to the higher toxicity (lower LC50) of 

Cu2+ to Daphnia magna. Figure 11 and 12 illustrate LOC exceedences as function of application 

rate for aerial spray drift loadings. Figure 13 and 14 illustrate LOC exceedences as function of 

application rate for ground spray drift loadings. 

Single Application Rate (lbs Cu2+/A)

0 10 20 30 40

Percentage of Sites Exceeding the Acute LOC=0.5

0

20

40

60

80

100

Rainbow Trout

Y=-1.3864+ 0.3475*X, R2

=0.9434

Daphnia magna

Y=4.7591+ 2.2872*X, R2

=0.9626

Figure 11 Percentage of Sites Exceeding Acute Risk LOC, Aerial Spray Drift 
76 

Single Application Rate lbs Cu2+/A)

0 10 20 30 40

Percentage of Sites Exceeding the ES Acute LOC=0.05

0

20

40

60

80

100

Rainbow Trout

Y=-1.8756 + 1.1951*X, R2

=0.9962

Daphnia magna

Y=98.7932(1-e-0.2313*X), R2

=0.9887

Figure 12 Percentage of Sites Exceeding ES Acute Risk LOC, Aerial Spray Drift 

Single Application Rate (lbs Cu2+/A)

0 10 20 30 40

Percentage of Sites Exceeding Acute LOC=0.5 

0

5

10

15

20

25

Rainbow Trout

Y=-0.1772 +0.361*X R2

=0.8785

Daphnia magna

Y=-0.5528 + 0.6444*X R2

=0.9967

Figure 13 Percentage of Sites Exceeding Acute Risk LOC, Ground Spray Drift 
77 

Single Application Rate (lbs Cu2+/A)

0 10 20 30 40

Percentage of Sites Exceeding ES Acute LOC=0.05

0

20

40

60

80

100

Rainbow Trout

Y=-0.2842 + 0.1481*X, R2

=0.95

Daphnia magna

Y=8.415+ 2.329*X, R2

=0.9387

Figure 14 Percentage of Sites Exceeding ES Acute Risk LOC, Ground Spray Drift 

Based on the fitted regression equations, the estimated Cu2+ application rate to equivalent to a 

10% site exceedence are shown in. 

Table 25 Estimated Application Rates1 Equivalent to 10% Site Exceedences 

Freshwater Invertebrates Freshwater Fish 

Application 

Method Acute Risk 

LOC 

Endangered Species 

Acute Risk 

LOC 

Acute Risk LOC 

Endangered 

Species Acute Risk 

LOC 

Aerial Drift 

(lb Cu/A) 2.29 0.46 32.76 9.94 

Ground Drift 

(lb Cu/A) 16.37 0.68 28.19 69.44 

1

 Estimated application rates were derived using the fitted regression models. Models were solved for lbs Cu2+/A 

(X variable) at site exceedence of 10% exceedance (Y variable). 

3.4.4 RQ Summary for Direct Water Applications 

Although the majority of the USGS data is from flowing waters, rather than reservoirs, EFED 

has opted to use it as representative of the potential range of water chemistries in reservoirs and 

lakes until such time as better data are available. When used as an algicide in direct water 

applications, the recommended effective copper concentration is approximately 1 ppm (1,000 
78 

ppb) although it varies dependent on site water chemistry and target alga species. Site-specific 

copper activities and risk quotients were calculated for the maximum label rate of 990 ppb, as 

shown in Table 26. The estimated average 21-day concentration at this rate is 522 ppb, and the 

estimated average 60-day concentration is 234 ppb. For invertebrates, fish, and aquatic plants, 

>99% of sites exceed the endangered species LOC and the acute risk LOC. The chronic risk 

LOCs for aquatic invertebrates, and fish are exceeded at >96% of the sites. 

Table 26 Aquatic RQ Summary Table: Direct Water Applications 

Endpoint for RQ Minimum 

RQ 

Median RQ Maximum RQ Sites Exceeding 

Acute or 

Chronic LOC 

 Sites Exceeding 

Endangered Species 

LOC 

Acute 

Invertebrate 0.23 244 36,698 99.9% 100% 

Fish 0.06 11.5 2,319 99.8% 100% 

Aquatic Plant 1.70 7,219 623,859 100% 100% 

Chronic 

Invertebrate 0.85 510 74,035 99.9% 

Fish 0.20 9.35 3,383 96.9% 

1

 Acute LOC for invertebrates and fish = 0.5, Acute endangered species LOC for invertebrates and fish = 0.05, acute 

and acute endangered species LOC for plants = 1.0, Chronic LOC for invertebrates, fish = 1.0 

Water concentrations from the EXAMS modeling of partially treated waterbodies were treated in 

a similar fashion. Peak concentrations of Cu2+ for 1961 weather data were speciated using the 

BLM model to estimate the concentration of ionic Cu2+. Median USGS monitoring site water 

quality data for 811 sites were used as input parameters for the BLM model (Appendix C). Risk 

quotients were estimated [activity of Cu2+

(site 1....811)/LC50 (site 1....811)] for each site for rainbow 

trout and Daphnia magna. The individual site RQs were ranked to assess the number of sites 

exceeding the acute risk LOC of 0.5 and the endangered species acute risk LOC of 0.05 

Site exceedances of acute risk LOCs and endangered species acute risk LOCs were found for all 

modeled application scenarios. As expected, the number of site exceedences were greater for 

Daphnia magna than for rainbow trout. This observation is due to the higher toxicity (lower 

LC50) of Cu2+ to Daphnia magna. Figures 15 and 16 illustrate LOC exceedences as function of 

volume of pond treated at 1 mg/L. 
79 

Treated Volume Percentage of Pond (20E6 liters)@ 1mg/L

0 20 40 60 80 100

Site Exceedance Percentage of LOC=0.5

0

20

40

60

80

100

Daphnia magna

Y=99.7865(1-e-0.1640*X), R2

=0.997

Rainbow Trout

Y=114.3253(1-e-0.0192*X), R2

=0.99159

 

Figure 15 Percentage of Sites Exceeding Acute Risk LOC, Direct Water Applications 

Treated Volume Percentage of Pond (20E6 liters) @ 1 mg Cu2+/L

0 20 40 60 80 100

Site Exceendance Percentage of LOC=0.05

0

20

40

60

80

100

Daphnia magna

Y=99.9217(1-e-0.7569*X), R2

=0.9999

Rainbow Trout

Y=100.8454(1-e-0.0624*X), R2

=0.9962

Figure 16 Percentage of Sites Exceeding ES Acute Risk LOC, Direct Water Applications 
80 

Based on the fitted regression equations, the estimated volume of pond treated with 1 ppm Cu2+ 

rate to allow no more than to allow 10% site exceedences is shown in Table 27. 

Table 27 Estimated Percent of Water Body Treated at 1 ppm Cu2+ Equivalent to 10% Site Exceedences 

 Freshwater Invertebrates Freshwater Fish 

LOC Acute Risk LOC Endangered 

Species Acute 

Risk LOC 

Acute Risk LOC Endangered 

Species Acute 

Risk LOC 

Percent 

Treated 0.64 0.14 4.77 1.67 

1

 Estimated application rates were derived using the fitted regression models. Models were solved for lbs Cu2+/A 

(X variable) at site exceedence of 10% (Y variable). 

3.4.5 RQ Summary for Urban Uses (Root-killers) 

Based on output from the EFAST “Down-the-Drain” model, the percentage of sites exceeding 

the LOC as a result of copper introduced into sewer lines as a root killer was estimated. Given 

the lack of use data, and the use assumptions made by EFED, significant uncertainty is 

associated with these RQ estimates. Copper concentrations were speciated using BLM model to 

estimate the concentration of ionic Cu2+. Median USGS monitoring site water quality data for 

811 sites were used as input parameters for the BLM model (Appendix C). Risk quotients were 

estimated [activity of Cu2+

(site 1....811)/LC50 (site 1....811)] for each site for rainbow trout and 

Daphnia magna. The individual site RQs were ranked to assess the number of sites exceeding 

the acute risk LOC of 0.5 and the endangered species acute risk LOC of 0.05. 

Table 28 Percentage of Sites Exceeding LOCs for Use of Copper as a Root-killer 

7Q10 30Q5 Species Acute LOC ES Acute LOC Chronic LOC 

Daphnia Magna 85.45% 99.87% 73.85% 

Rainbow Trout 19.97% 51.4% 13.19% 
81 

3.5 Risk Description 

3.5.1 Agricultural Crops 

The risk description in the version of this ecological risk assessment released for public comment 

was based on the application rates described in previous sections of the aquatic assessment. 

Input from public comments, and additional analysis of usage rates by BEAD indicate that rates 

used by growers are often substantially lower than those permitted by existing labels. However, 

for some crops, applications are frequent. Use patterns differ by region, and are greatly affected 

by weather conditions during the growing season. For many crops, damp conditions are 

conducive to fungal and bacterial growth, thus copper-containing pesticides are applied more 

frequently under these circumstances. Gaining a clear picture of usage rates and patterns is 

difficult, given the variability. Table Table 29, below, summarizes rates and application 

frequencies for high use crops and some other crops of interest. The highest application rate 

reported the this group of crops was 7.9 lb ai/A, but the majority were below 5 lb ai/A, and many 

were below 1 lb ai/A. 

While it is impossible to model every situation, given the range of possibilities, EFED used the 

range of modeling data created during this assessment to develop a tool for risk management to 

estimate the risk associated with particular application rates. First, an equation (Figure 17) was 

fit to the relationship between application rate (generally derived from a sequence of 4 

applications with 7-day intervals). Second, equations were fit to the percentage of the 811 USGS 

sites exceeding the acute risk LOCs for aquatic invertebrates and fish (Figure 18). Using these 

equations, EFED can estimate the likely dissolved copper concentrations in the modeled water 

body, and evaluate what percent of the sites are likely to exceed acute risk levels of concern 

(Table 30) 

On an aquatic acute risk basis, agricultural use of copper as a pesticide is expected to cause little 

risk when applications are less than 1 lb Cu/A, and applications are spaced at least 7-days apart. 

The most sensitive water chemistry specific endpoint is that for the Daphnia magna. At 1.5 lbs 

Cu/A, 95% of the sites in the USGS data site do not exceed the acute risk LOC based on the 

Daphnia endpoint. However, the acute risk LOC for saltwater invertebrates is exceeded. 

Applications of copper-containing compounds at rates between 1.5 and 3 lb Cu/A may pose a 

risk to aquatic organisms at sites with vulnerable water chemistries. At 3 lbs Cu/A, only 90% of 

the freshwater sites in the distribution would be protected, and the expected dissolved 

concentration of copper exceeds the LOCs for both saltwater invertebrates and fish. Application 

rates above 3 lbs Cu/A likely pose a risk to both freshwater and saltwater environments. 
82 

Table 29 Comparison of Application Rates Derived from Different Sources 

Crop State Lb Cu/A Applications Source Compound 

Citrus 

CA 2.1 1.2 BEAD Cu hydroxide 

FL 2 1.7 BEAD Cu hydroxide 

TX 1.6 1.9 BEAD Cu hydroxide 

CA 3.7 1.2 BEAD Cu sulfate 

FL 1.0 1.6 BEAD Cu sulfate 

Not specified 1.5 1.5 CSTF Basic Cu sulfate 

Oranges 

(25.1%) 

Not specified 1.5 1.5 CSTF Cu hydroxide 

CA 2.9 1.3 BEAD Cu hydroxide 

FL 2.7 2.9 BEAD Cu hydroxide 

TX 2.4 1.9 BEAD Cu hydroxide 

CA 4.2 N/A BEAD Cu sulfate 

FL 1.8 21.9 BEAD Cu sulfate 

Not specified 2 3 CSTF Basic Cu sulfate 

Grapefruit 

(8.8%) 

Not specified 2 2 CSTF Cu hydroxide 

Other Orchard Crops 

CA 4.4 1.3 BEAD Cu hydroxide 

CA 7.9 1.2 BEAD Cu sulfate 

CA 1.2 N/A BEAD Cu hydroxide 

GA 2 N/A BEAD Cu sulfate 

GA 0.5-3 7 Pub cmt varied 

Not specified 3 4 CSTF Basic Cu sulfate 

Peaches (2.8%) 

Not specified 4 4 CSTF Cu hydroxide 

Nuts 

CA 3.4 1.4 BEAD Cu hydroxide 

CA 5.8 N/A BEAD Cu sulfate 

Not specified 9.8 1 CSTF Basic Cu sulfate 

Almonds 

(7.6%) 

Not specified 4.5 2 CSTF Cu hydroxide 

OR 5 1 BEAD Cu hydroxide 

OR 5.3 N/A BEAD Cu sulfate 

Filberts 

(high label 

rates) Not specified 4.2 2 CSTF Cu hydroxide 

CA 4.6 2 BEAD Cu hydroxide 

CA 2.6 N/A BEAD Cu sulfate Walnuts 

(17.6%) Not specified 7.8 2 CSTF Cu hydroxide 
83 

Table 29 (cont.) 

Crop State Lb Cu/A Applications Source Compound 

Vegetables 

CA 0.9 1.8 BEAD Cu hydroxide 

FL 1.1 10.3 BEAD Cu hydroxide 

NJ 0.8 4.8 BEAD Cu hydroxide 

FL 1 N/A BEAD Cu sulfate 

NJ 0.3 3.4 BEAD Cu sulfate 

Not specified 0.9 4 CSTF Basic Cu sulfate 

Peppers (2.5%) 

Not specified 0.7 12 CSTF Cu hydroxide 

CA 1.1 1.4 BEAD Cu hydroxide 

FL 1.3 12.2 BEAD Cu hydroxide 

NJ 0.9 3.3 BEAD Cu hydroxide 

FL 1.7 N/A BEAD Cu sulfate 

NJ 1 N/A BEAD Cu sulfate 

Not specified 0.9 8 CSTF Basic Cu sulfate 

Tomatoes 

(9.8%) 

Not specified 1 12 CSTF Cu hydroxide 

Vines and Small Fruits 

CA 0.6 1.6 BEAD Cu hydroxide 

NY 0.9 1.4 BEAD Cu hydroxide 

CA 2 N/A BEAD Cu sulfate 

NY 1.2 N/A BEAD Cu sulfate 

Not specified 2 4 CSTF Basic Cu sulfate 

Grapes (5.2%) 

Not specified 1.4 4 CSTF Cu hydroxide 

OR 0.5-4.0 2.5 Pub cmt varied 

OR 1.6 1.4 BEAD Cu hydroxide 

OR 2 1 BEAD Cu sulfate 

Blackberries 

(public 

comment) Not specified 0.5 2 CSTF Cu hydroxide 

OR 1.5-5 2 Pub cmt varied 

OR 2.3 1.9 BEAD Cu hydroxide 

OR 2.1 1.8 BEAD Cu sulfate 

Blueberries 

(public 

comment) Not specified 2.0 1 CSTF Cu hydroxide 

OR 0.75-3.5 1-2 Pub cmt varied 

CA 1.4 1.6 BEAD Cu hydroxide 

CA 1.4 N/A BEAD Cu sulfate 

MI 1.4 3.4 BEAD Cu hydroxide 

Strawberries 

(public 

comment 

Not specified 0.7 8 CSTF Cu hydroxide 
84 

Figure 17 - Correlation of Peak Cu 2+ Concentrations in the Standard Small Water Body with 

Application Rates 

Acute Site Exceedance

Cu Concentration (ug/L)

0 100 200 300 400

Percent Site Exceeding LOC

0

10

20

30

40

50

60

70

80

90

100

Rainbow Trout

y=-0.8624 + 0.244*X, R2

=0.9865

Daphnia magna

y=105.53(1-e-0.0143*X), R2

=0.9957

Figure 18 Percentage of Sites Exceeding Acute Risk LOC, Agricultural Uses 

Relationship of Cu Application Rate 

and Peak Cu Concentration 

Cu Application Rate (lb Cu/A)

0 5 10 15 20 25 30 35

Peak Cu2+ Conc (ug/L)

0

20

40

60

80

100

Y=-0.3800+2.5358(X) r2=0.75
85 

Table 30 Summary of Acute Risk LOC Exceedences in Aquatic Environments 

Freshwater Saltwater 

Plant 

Rate 

Cu lb/A 

(Cu ppb) Algae (RQ) Vascular (RQ) Invertebrate1

 Fish1 Plant (RQ) Invertebrate (RQ) Fish (RQ) 

1.0 (2.2) Yes (0.7) No (<0.01) 3.2% <1% No (<0.01) No (0.35) No (0.17) 

1.5 (3.4) Yes (1.1) No (<0.01) 5.0% <1% No (0.01) Yes (0.55) No (0.27) 

3.0 (7.2) Yes (2.3) No (<0.01) 10.3% <1% No (0.03) Yes (1.2) Yes (0.56) 

5.0 (12.3) Yes (4.0) No (<0.01) 17.0% <1% No (0.05) Yes (2.0) Yes (0.99) 

7.5 (18.6) Yes (6.0) No (<0.01) 24.6% <1% No (0.07) Yes (3.0) Yes (1.5) 

1 Presented in terms of percentage of sites in the USGS data set exceeding the acute risk LOC

3.5.2 Direct Water Applications 

Direct water applications of copper-containing pesticides range from 0.1-2.5 ppm Cu, depending 

on the target pest. At a typical application rate of 1 ppm, peak concentrations of Cu2+ are 

predicted by EXAMS to be approximately 0.9 ppm if the pesticide were to be applied to the 

entire waterbody. Typically, only a portion of a waterbody is treated. In the analysis of partial 

treatments of the standard waterbody, peak concentrations of Cu2+ ranged from 0.05-0.5 ppm. 

This presumes rapid mixing throughout the waterbody. Assuming a 1 ppm Cu target 

concentration, 90% of the USGS sites would exceed the acute risk LOC for invertebrates if 1% 

of the waterbody were treated, and 90% of the USGS sites would exceed the acute risk LOC for 

invertebrates if 5% of the waterbody were treated. 

For almost any direct water application of copper products, there is likely to be effects on 

invertebrates and a reduction of primary production. Fish and larger, more mobile invertebrates 

may be able to move out of the treated zone until the copper dissipates from the water column, 

but smaller and more sedentary invertebrates will be affected. Recovery of the affected 

organisms will vary on a site-to-site basis, and the specific effects on any given ecosystem is 

impossible to predict given the scale of this assessment. Populations of phytoplankton and 

zooplankton (the organisms most likely to be lethally affected by use of copper) are dynamic. In 

aquatic systems where copper is applied frequently the community may shift to more copper 

tolerant organisms, and/or some of the organisms present may develop metabolic pathways for 

dealing with higher copper loading. 

Minimizing adverse effects of non-target organisms will depend on careful use by the resource 

managers who apply the products. Managers should be aware that copper remaining suspended 

in the water column and or sorbed to entrained sediment could affect downstream resources. 

3.5.3 Urban Uses (Root-killers) 

Based on the concentration estimates generated by the “Down-the-Drain” analysis, use of copper 

sulfate crystals as a root killer in domestic sewer systems may result in receiving waters high 

enough to affect aquatic invertebrate populations, and fish on both an acute and chronic basis.
86 

Based on the assumptions used in the EFED analysis, approximately 85% of the USGS sites 

exceeded the acute risk LOC for aquatic invertebrates and approximately 20% of the USGS sites 

exceeded the acute risk LOC for fish. Given the site-specific nature of use patterns, sewersheds, 

and receiving water chemistry and flow range, a more definitive analysis would have to be 

conducted on a watershed basis. 

3.5.4 Sediment Accumulation 

PRZM-EXAMS modeling showed that copper accumulated in the sediment. Generally, 

contaminants in the sediment pore water are considered to be more bioavailable15, and may 

cause toxic effects. Estimates of pore water concentration based on the various scenarios 

evaluated are included in the aquatic exposure section (Table 15). Estimated concentrations are 

given for the 1st year and 30th year at both a low Kd and a high Kd. As a conservative estimate of 

the likelihood of effects, concentrations in the pore water could be put into the BLM. and 

compared to site water chemistry to estimate potential effects to benthic organisms. However, 

because the pore water will have slightly different water chemistry than the water column (higher 

in organic carbon and particulate matter, both of which tend to ameliorate the effects of copper), 

this would overestimate the potential toxicity. However, estimated peak pore water 

concentrations suggest that there may be some risk to benthic organisms in surface water bodies 

receiving runoff from lands treated with copper-containing pesticides. Below, Table 20 details 

the range of estimated pore water concentrations. As a first approximation, these concentrations 

could be compared to the percent exceedance versus runoff concentration graph (Figure 17) to 

determine which application sites might need a more detailed sediment analysis. It must also be 

noted that the flow regime and bed characteristics of the receiving waters will play an important 

part in sediment toxicity. 

Table 31 Range of Sediment Pore Water Dissolved Copper Concentrations for Various Scenarios 

Type of Sediment Accumulation 

time 

Min Cu 

(ppb) 

Scenario Max Cu 

(ppb) 

Scenario 

Low Kd 1 year 0.42 CA alfalfa 44.7 PA apples 

 30 year 13.7 CA alfalfa 2680 CA filberts 

High Kd 1 year 0.05 CA alfalfa 6.35 PA apples 

 30 year 1.7 CA alfalfa 249 FL citrus 

4.0 Terrestrial Assessment 

4.1 Exposure 

4.1.2 Avian and Small Mammal Exposure - (TREX) 

 

15 Contaminants sorbed to sediment may potentially be available to organisms that ingest sediment. 
87 

For birds and small mammals, dietary exposure to copper was estimated using EFED’s 

Terrestrial Exposure (TREX, Version 1.1) spreadsheet. TREX automates calculation of expected 

environmental concentrations for four classes of food items using residue estimates based on the 

Kenaga nomogram (Hoerger and Kenaga 1972, Fletcher et al. 1994). The nomogram was 

derived from an extensive analysis of field data, and is most appropriate for spray applications. 

EFED uses the predicted upper bound residue to assess risk to organisms consuming food items 

contaminated by the pesticide. The amount of pesticide ingested by the organism is based on the 

assumptions that 1) the organism forages 100% of the time in a treated area, and 2) 100% of its 

diet is comprised of a particular food item. Potential toxicity estimates are based on peak 

residues. A search of OPPIN showed that no foliar dissipation studies have been submitted for 

the copper compounds addressed in this RED, thus a typical half-life of 35 days was used 

(TREX, Ver 1.1 Guidance, EFED, 12/7/04; Willis and McDowell 1987). Elemental copper will 

not be degraded by photolysis or hydrolosis. Wash-off due to precipitation is expected to be the 

primary process governing how long copper remains on plant surfaces. 

Exposure was assessed using both the highest label application rates and the highest average 

application rates reported by BEAD. As with the aquatic assessment, both orchard and row crop 

applications are considered. 
88 

Label Application Rates

The highest orchard label application rate is 31.8 lb a.i./acre for filberts. The label designated 

application interval is 14 days, with a total of 2 applications. The highest row crop label 

application rate is 3.2 lb a.i./acre for potatoes. Intervals between applications, and maximum 

number of applications were not specified on the label. For modeling, 4 applications at an 

interval of 7-days were assumed. Predicted residues are shown below in Table 32. 

Table 32 Estimated Environmental Concentrations Based on Label Application Rates 

Food Item Category Orchard Upper Bound Residue 

(ppm) 

Row Crop Upper Bound Residue 

(ppm) 

Short grass 13,416 2,525 

Tall grass 6,149 1,157 

Broadleaf plants/small insects 7,546 1,420 

Fruits/pods/seeds/large insects 839 158 

Average Application Rates 

The highest orchard average application rate is 3.8 lb a.i./acre for apples in the state of Oregon. 

Application interval was 7-days, with a total of 4 applications. The highest average application 

rate is 0.8 lb a.i./acre for potatoes in Maine. For modeling, 4 applications at an interval of 7-days 

were assumed. Predicted residues are shown below in Table 33. 

Table 33 Estimated Environmental Concentrations Based on Average Application Rates 

Food Item Category Orchard Upper Bound Residue 

(ppm) 

Row Crop Upper Bound Residue 

(ppm) 

Short grass 2,999 631 

Tall grass 1,374 289 

Broadleaf plants/small insects 1,686 355 

Fruits/pods/seeds/large insects 187 39 

4.1.3 Terrestrial Plant Exposure - (TerrPlant) 

Terrestrial plant exposure was determined using TerrPlant (Version dated 03/02/04). TerrPlant 

uses the application rate, and solubility of the chemical to estimate loading to areas adjacent to 

the application site. Both upland and semi-aquatic areas are considered. Total loading to 

adjacent drier areas (upland) includes sheet runoff and drift. Total loading to semi-aquatic areas 

(wetland) includes channelized runoff and drift. Solubility of copper is >100 ppm. Terrestrial 

plant exposure was calculated based on both the highest label application rates and the highest 

average application rates reported by BEAD. As with the aquatic assessment, both orchard and 
89 

row crop applications are considered. 

Label Application Rates

The highest orchard label application rate is 31.8 lb a.i./acre for filberts. The highest row crop 

label application rate is 3.2 lb a.i./acre for potatoes. Predicted residues are shown below in 

Table 34. 

Table 34 Estimated Environmental Concentrations Based on Label Application Rates 

 Orchard Crops Row Crops 

Application Method Adjacent 

upland 

(lbs ai/acre) 

Adjacent 

wetland 

(lbs ai/acre) 

Drift only 

(lbs ai/acre) 

Adjacent 

upland 

(lbs ai/acre) 

Adjacent 

wetland 

(lbs ai/acre) 

Drift only 

(lbs ai/acre) 

Ground spray 1.91 16.22 0.32 0.19 1.63 0.03 

Aerial, air blast, 

spray chemigation 

2.54 11.13 1.59 0.26 1.12 0.16 

Average Application Rates

The highest orchard average application rate is 3.8 lb a.i./acre for apples in the state of Oregon. 

The highest average application rate is 0.8 lb a.i./acre for potatoes in Maine. Estimated 

environmental concentrations are shown in Table 35. 

Table 35 Estimated Environmental Concentrations Based on Average Application Rates 

Orchard Crops Row Crops 

Application Method Adjacent 

upland 

(lbs ai/acre) 

Adjacent 

wetland 

(lbs ai/acre) 

Drift only 

(lbs ai/acre) 

Adjacent 

upland 

(lbs ai/acre) 

Adjacent 

wetland 

(lbs ai/acre) 

Drift only 

(lbs ai/acre) 

Ground spray 0.23 1.94 0.04 0.05 0.51 0.01 

Aerial, air blast, 

spray chemigation 

0.30 1.33 0.19 0.06 0.28 0.04 
90 

4.1.3 Soil Accumulation 

Because of the frequent application of copper-containing pesticides at high rates, and the fact 

that elemental copper remains in the soil, EFED also evaluated the potential for accumulation in 

the soil, and potential uptake by on-site plants. High copper concentrations in the soil could be 

toxic to plants, to soil invertebrates, or to microorganisms in the soil which play a critical role in 

nutrient processing. Additionally, high concentrations of copper in the soil can be taken up by 

on-site plants, potentially becoming available to herbivorous or omnivorous organisms foraging 

in the treated field or over-spray areas. 

Soil accumulation values are generated by PRZM as part of the process of modeling runoff 

concentrations. The accumulated concentrations were compared against typical ambient copper 

concentrations in soil, which range from 2 ppm to 100 ppm (average 30 ppm; Lindsay 1979). 

Figure 13 shows the yearly accumulation of copper in the surface horizon (upper 10 cm) for the 

Pennsylvania apples scenario, at both the maximum label rate (19 lb Cu/acre; Figure 13a), and 

the state average application rate (2.2 kg Cu/ha; Figure 13b). Accumulation is shown in yearly 

increments. At the maximum label application rate, soil concentrations at the treated site exceed 

high ambient soil concentrations (100 ppm) within 2 years. At the state average application rate, 

(presuming no background copper) soil concentrations reach the average ambient conditions (30 

ppm) in 6 years, and exceed the high ambient conditions (100 ppm) in 21 years. 
91 

 

Figure 19a and 19b: Soil accumulation of copper at maximum label, and state average rates 

PA apples (maximum rate)

Days

0 2000 4000 6000 8000 10000 12000 14000

S

oil C

oncentrat oi n (m

g/kg)

0

200

400

600

800

1000

1200

1400

High Ambient Soil Cu Concentration (100 mg/kg)

PA apples (state average application rate)

Days

0 2000 4000 6000 8000 10000 12000 14000

Cu C

oncentrat oi n (mg/kg)

0

20

40

60

80

100

120

140

160

High Ambient Soil Cu Concentration (100 mg/kg) 

Average Ambient Soil Cu Concentration ( 30 mg/kg)

Low Ambient Soil Cu Concentration (2 mg/kg)
92 

4.2 Effects Analysis 

Unlike many substances assessed by EFED, copper is a naturally occurring substance, and an 

important micronutrient. Unlike aquatic organisms, where the toxic effect is exerted by the 

copper ion binding to the gill, toxicity for terrestrial organisms has been assessed based on 

dietary uptake. Although acute poisoning can occur and may be severe enough to cause death, 

mammals are known to have biochemical mechanisms for controlling uptake of copper and 

maintaining homeostasis (Goyer 1996). Although less well researched, it is likely similar 

mechanisms exist for birds and other terrestrial organisms. Acute poisoning effects include 

hepatic necrosis and hemolytic anemia (Goyer 1996). A common symptom of poisoning is 

emesis (vomiting). 

Copper atoms are a component of several important enzymes, and reserve copper is stored in the 

liver and bone marrow, often bound to metallothioneins. Copper absorption, excretion, and 

turnover time have been studied in laboratory rats (Johnson and Lee 1988, Linder and Roboz 

1986, Owen 1964, Yu et al., 1993). Copper is excreted primarily in the bile (faeces), although a 

small percentage is also excreted in the urine. Based on radiotracer experiments (64Cu or 67Cu), 

turnover of copper in rats appears fairly rapid, with three separate studies estimating an average 

biological half-life of between 48 and 81 hours (Johnson and Lee 1988, Linder and Roboz 1986, 

Yu et al., 1993). Turnover rate varied dependent on administered dose, strain of rat, and age of 

rat. No studies compared differences between genders, although some investigators chose to use 

only female rats, and others used only males. At higher doses, biological half-life was shorter in 

all studies. One study did note that the decline in copper appeared to be bi-phasic, with an initial 

rapid decline producing a biological half-life of approximately 70 hours (Linder and Roboz 

1986). The break between phases occurred at around the 70-hour point. The second phase was 

slower, with an estimated half-life of 220 hours. The investigators interpreted this as indicating 

there are “ at least two copper ‘compartments’ or ‘pools’ in the body, with different rates of 

turnover.” 

Two studies (Johnson and Lee 1988, Yu et al., 1993) estimated copper absorption from dietary 

sources. Dependent on dose and method of estimation, absorption efficiencies for rats with no 

known metabolic deficiencies ranged from 22-63%. Absorption efficiency was consistently 

lower at high doses. Dietary copper concentrations ranged from 0.4- 100 ppm. In a study 

evaluating bioaccumulation models for mice (Torres and Johnson 2001), the authors calculated a 

“GI absorption-elimination factor” of 28% based on data in the ASTDR16 Toxicological Profile 

for Copper. Thus, it appears that at least up to dietary concentrations measured in these studies, 

small mammals have compensatory mechanisms to increase absorption of copper at low 

concentrations, and reduce absorption of copper at high concentrations, at least from dietary 

sources. No data were located to indicate at what copper concentration these compensatory 

mechanisms might be overwhelmed. The TREX model assumes that 100% of the ingested 

 

16Agency for Toxic Substances and Disease Registry 
93 

chemical is bioavailable, and uses that estimate as an effective dose (adjusted by allometric 

equations). Based on the existing data, this does not appear to be the case for copper. Dietarybased endpoints likely incorporate these uptake effects, but dose-based endpoints will not. In 

order to account for these mechanisms, an absorption efficiency correction of 22% (a high 

copper availability situation) was applied to the mammal dose-based risk quotient calculations. 

Bird dose-based calculations were not corrected, as it is uncertain to what extent the actual 

percentages may be valid across taxa, and dietary-based data were available for acute effects. 

4.2.1 Avian Guideline Data 

Table 36 contains data for birds from guideline studies submitted to the Agency. In all studies 

listed, the endpoints were reported using the technical compound as the active ingredient. These 

values were converted to metallic copper using the percent copper conversions shown in Table 1. 

For clarity, both values are listed in the table. 
94 

Table 36 Avian Guideline Data 

Species Compound LD50/LC50

(mg/kg)

LOAEL 

(mg/kg)

95% C.I. NOAEL 

(mg/kg)

Classification 

(MRID)

Acute oral (Guideline 71-1)

Copper sulfate 

pentahydrate 

Bobwhite 384 

 as copper 98a

ND 0-infinity ND Core 

(00067456) 

Tri-basic 

copper sulfate 

Bobwhite 642 80 

as copper 348 43 

N/A ND Supplemental 

(00106120) 

Acute dietary (Guideline 71-2)

Tri-basic 

copper sulfate 

Bobwhite 1829 

as copper 991a

NR NR NR Acceptable 

(00811103) 

Tri-basic 

copper sulfate 

Mallard 4640 2150 

as copper 

ND 

2515 

NA 

1165 

Supplemental 

(00099587) 

Reproductive (Guideline 71-4)

Copper 

hydroxide 

500 100 

(eggshell 

thickness) 

Bobwhite 

as copper 

NR 

390 

NA 

78 

Core 

(43338001) 

Copper 

hydroxide 

Mallard 500 

as copper 

NR ND NA 

390 

Supplemental 

(43396301) 

Copper 

oxychloride 

sulfate 

500 100 

(eggshell 

thickness) 

Bobwhite 

as copper 

NR 

289 

NA 

58a

Core 

(43338001) 

Copper 

oxychloride 

sulfate 

Mallard 1000 

as copper 

NR ND NA 

578 

Supplemental 

(43396301) 

a toxicity endpoint used in assessment

ND - not determined, NA - not applicable, NR - not reported
95 

An ECOTOX search on copper sulfate, copper oxide, and the copper group II compounds 

generated a substantial number of references for birds. While copper can be toxic at high levels, 

it is often used a dietary supplement for domestic poultry at lower concentrations Table 37 shows 

some of these more sensitive endpoints from the ECOTOX search, along with the endpoints 

based on guideline studies. No acute bird studies were identified. The risk assessment uses the 

guideline-based endpoints 

Table 37 Avian Data from ECOTOX 

EC50

 (ppm Cu)

NOAEL 

(ppm Cu)

Acute dose 98

Acute dietary 991 Current Endpoints from 

Guideline Studies

Chronic 58 

Type of study Species Compound LD50

(ppm Cu)

LOAEL 

 (ppm Cu)

NOAEL 

(ppm Cu)

ECOTOX 

Reference #

Copper 

sulphate 176 ND ND

Acute dose

Chicken 

(Gallus 

domesticus) Copper 

oxychloride 751 ND ND

38759

Acute dietary 

(reduced 

weight gain)

Mallard duck 

(Anas 

platyrhynchos)

Copper 

sulphate ND 400 200 61377

Chicken 

(Gallus 

domesticus)

Copper 

sulphate Chronic ND 150 50 61379

(reduced egg 

production) Chicken 

(Gallus 

domesticus)

Copper 

sulphate ND 976 496 59136

ND - Not determined 
96 

4.2.2 Small Mammal Data 

No wild mammal data has been submitted to the Agency, thus data from laboratory rodents (rats) 

was used to evaluate potential effects on small mammals. EFED selected the lowest acute oral 

LD50s from HED’s “one-liner” database for copper and copper sulfate. Data are shown below 

(Table 38) in terms of both compound and metallic copper. Metallic copper conversions were 

performed using the molecular weight percentages of copper shown in Table 1. 

Table 38 Acute Oral Toxicity in Rats (Guideline 81-1) 

As compound As copper

Compound LD50 

(mg/kg bwt)

95% C.I. 

(mg/kg bwt)

LD50 

(mg/kg bwt)

95% C.I. 

(mg/kg bwt)

Classification 

(MRID)

Copper sulfate

Copper sulfate 

(pentahydrate) 

790 (male) 

450 (female) 

416-1501 (m) 

346-585 (f) 

200 (male) 

114 (female)a

106-381 (m) 

88 - 149 (f) 

Acceptable 

(43396201) 

Copper Group II

Copper hydroxide 2233 (male) 

2160 (female) 

Not available 1739 (male) 

1683 (female) Not available Acceptable 

(41421602) 

Copper chloride 1796 (male) 

2006 (female) 

Not available 1068 (male) 

1194 (female) 

Not available Acceptable 

(43769501) 

Copper oxychloride 1537 (male) 

1370 (female) 

Not available 915 (male) 

815 (female) 

Not available Acceptable 

(00155931) 

Copper carbonate >2000 Not available >1150 Not available Acceptable 

(41889302) 

Copper salts

Copper salts of 

fatty and rosin 

acids 

>7000 Not available Not available (Not 

determined) 

Copper ethylene 

diamine 

(as elemental) 

 Not available 527 (male) 

462 (female) 

Not available Acceptable 

(41759201) 

Copper 

triethanolamine 

complex 

1170 (male) 

1312 (female) 

Not available Not available Acceptable 

(41759301) 

Copper octanoate >2000 Not available Not available Acceptable 

(43947504) a

 toxicity endpoint used in assessment 

ND - not determined, NA - not applicable, NR - not reported
97 

Only one chronic mammal guideline study was located (Table 39), but alternative sources of data 

were considered. Benchmarks for evaluating copper contamination at Superfund sites have been 

established, based on open literature values (Sample et al., 1996, Efroymson et al., 1997, 

Efroymson et al., 1997b). Organisms for which copper benchmarks have been established 

include earthworms, microorganisms and heterotrophic soil processes, and terrestrial plants. 

Based on dietary studies, chronic NOAELs were available for mammals (mink, Aulerich et al., 

1982) and birds (domestic chicken, Mehring et al., 1960). These benchmarks are presented 

inTable 40. The mink value has been used as a chronic mammalian endpoint to calculate RQs, 

but avian guideline studies provide a more sensitive chronic endpoint for birds and have been 

used in the assessment. 

Table 39 Chronic Toxicity in Rats (Guideline 83-3, developmental) 

Compound Endpoints 

(mg/kg/day) 

as compound 

Endpoints 

(mg/kg/day) 

as copper 

Effects 

Copper 

triethanolamine 

complex 

Maternal 

NOAEL 100 

LOAEL 700 

Developmental 

NOAEL 100 

LOAEL 700 

Maternal 

NOAEL 29.9 

LOAEL 209 

Developmental 

NOAEL 29.9 

LOAEL 209 

Maternal effects included weight loss and reduced 

food consumption. Developmental effect was postimplantation loss of embryo. 

Table 40 Avian and Mammal Screening Values for Superfund Site (Sample et al., 1996) 

Category Benchmark Confidence Effects 

Birds 

Test species: 

domestic chicken 

(day old chicks) 

NOAEL 

47 mg/kg bwt 

570 ppm diet 

LOAEL 

61.7 mg/kg bwt 

749 ppm diet 

Not given Chronic dietary exposure. Effects were reduced growth 

and mortality. At 749 ppm dose growth was reduced by 

>30% and mortality was 15%. 

Mammals 

Test species: 

mink 

NOAEL 

11.7 mg/kg bwta

 

85.5 mg/kg dieta

LOAEL 

15.1 mg/kg bwt 

110.5 mg/kg diet 

Not given Chronic dietary exposure during reproduction. Effects 

were reduced survivorship of kits. Copper dose 

represented a base in food (60.5 ppm) plus a supplement 

(25, 50, 100, and 200 ppm). At 25 ppm in diet, kit 

survivorship was greater than in controls. Reduced 

survivorship of kits was noted in the 50 ppm treatment 

group. 

a

 toxicity endpoint used in assessment 

 
98 

An ECOTOX search on copper sulfate, copper oxide, and the copper group II compounds 

generated a number of references for terrestrial mammals. Table 41 shows the most sensitive 

endpoints from the ECOTOX search, along with the endpoints based on guideline studies and 

other reviewed data. 

Table 41 Small Mammal Data from ECOTOX 

LD50

 (ppm Cu) 

NOAEL 

(ppm Cu) 

Acute dose 114 ND 

Acute Dietary ND ND Current Endpoints from Guideline 

Studies 

Chronic ND 11.7 

Type of Study Species Compound LD50

(ppm Cu) 

LOAEL 

 (ppm Cu) 

NOAEL 

(ppm Cu) 

ECOTOX 

Reference # 

Acute dose Rat Copper 

chloride 3001

 ND 200 73169 

Acute dietary None currently identified 

Chronic (ova 

recovery rate, 

fertilization rate, 

blastocyst hatching) 

Mouse 

(Mus musculus)

Copper 

carbonate ND ND 112

 59141 

ND-No data 

1

 - Listed by authors as “lethal dose,” but no formal LD50 was calculated, and mortality data was not included in 

paper 

2

- NOAEL is the amount of copper occurring in unpurified diet. Concentrations below this amount were identified 

as a deficiency. 

4.2.3 Terrestrial Plants, Insects, and Microbial Processes 

Terrestrial Plants 

Vegetative vigor and seedling emergence data for terrestrial plants were not available from 

registrant-submitted guideline studies, but a substantial amount of data regarding effects on 

terrestrial plants was located through ECOTOX. Although limited resources prevented a 

complete review of all data, the most sensitive endpoints expressed in units usable by EFED’s 

TerrPlant model were used to evaluate the impact of copper on the vegetative vigor of terrestrial 

plants. No suitable values for evaluating seedling emergence effects were located in the initial 

review of the data. As with other effects endpoints, the data were corrected to express the 

toxicity value in terms of elemental copper. Raw data to calculate the EC25 (used to determine 

the acute RQ) were not available at the time of this draft. The NOAEC from the most sensitive 

endpoint was used to calculate the acute endangered species RQ. NOAECs were available for 

both monocots and dicots. 
99 

Table 42 Terrestrial Plant Data from ECOTOX 

Compound Plant Type Species Type of 

Endpoint 

NOAEC 

(lb a.i./acre) 

NOEAC 

(lb Cu/acre) 

Reference 

Monocot Corn Vegetative 

vigor 

Copper Sulfate 26.8 6.8 44317 

Dicot Kidney 

bean 

Vegetative 

vigor 

144.5 36.7 40559 

Table 43 Terrestrial Insect Guideline Data 

Compound As compound As copper

Effect Effect

Toxicity Classification 

(MRID)

Copper Group II

Copper ammonium 

complex 

LD50 

>100 μg/bee

ND Practically 

non-toxic 

Core 

(40764702) 

Copper oxychloride 

sulfate 

7% mortality at 

14.3 μg/bee 

7% mortality at 

8.3 μg/bee 

ND Acceptable 

(00036935) 

ND-not determined 

On an acute contact basis, copper does not appear to be toxic to honey bees. However, because 

of the difficulty of estimating exposure for insects, and lack of time to thoroughly analyze 

toxicity data, EFED has drawn no firm conclusion regarding the potential toxicity of copper 

compounds to terrestrial insects. 
100 

Table 44 Earthworm, Plant, and Microbial Processes Screening Values for Superfund Sites (Efroymson et 

al., 1997a, Efroymson et al., 1997b) 

Category Benchmark Confidence Effects 

Earthworms 60 ppm in soil Moderate Reproductive endpoints most sensitive. Some variability 

by genus. LC50 for E. fetida in an OECD artificial 

substrate in the 550-650 range. 

Microorganisms 

and heterotrophic 

processes 

100 ppm in soil High Copper reduces rates of denitrification and N 

mineralization by modifying enzyme pathways such a 

dehydrogenase, aryl sulfatase, urease, and phosphatase. 

100 ppm in soil Low 

(derived 

from <10 

values) 

Terrestrial plants Copper reduced weight of roots stems, shoots, and leaves 

0.06 ppm in 

solution 

Moderate Copper reduced length and weight. Species evaluated 

include both woody and herbaceous plants. 

4.2.4 Terrestrial Incident Data Review 

Although copper compounds have been used as pesticides for over 100 years, relatively few 

incidents associated with the copper compounds are reported in the EIIS. EIIS runs were 

completed for all PC codes included in this action. No incidents were reported for any of the 

Copper Group II compounds, and only 24 incidents were reported for the copper sulfates. It is 

unknown whether there is significant under-reporting of incidents. 

Of the 24 reported incidents, 7 were associated with terrestrial plants, and in all of the cases, 

certainty was rated as possible or probable. One case, on tomatoes in Washington state, was in 

accordance with registered use. For the other incidents, affecting corn and peanuts in Indiana, 

Minnesota, and Oklahoma, the legality of the use was not reported. Reported effects included 

plant damage, incapacitation, and pinched ears (corn). 
101 

4.3 Terrestrial Risk Estimation 

The TREX spreadsheet described in the section on terrestrial exposure also calculates potential 

dose of applied pesticides for three size classes of birds and mammals, using generalized 

allometric equations (Nagy 1987), and assuming the organisms forage exclusively within the 

treated area. Thus, for each size class of bird and food category, an ingested dose can be 

estimated based on the EECs derived from the Kenaga nomogram. The same method is used to 

determine effective doses for the various size classes of mammals. The estimated doses are used 

to calculate risk quotients, which are then compared to pre-established LOCs. 

4.3.1 Avian Risk Estimation 

Dietary exposure is frequently the most likely exposure route for birds, and EFED uses both dose 

based (Guideline study 71-1) and dietary based (Guideline study 71-2) endpoints to estimate 

acute risk quotients. Chronic endpoints are based on data from the avian reproductive studies 

(Guideline study 71-4). Based on the acceptable registrant-submitted studies for copper 

compounds, the bobwhite quail was the more sensitive of the two standard test organisms. The 

following data were used to develop avian RQs: 

• Acute oral LD50 of 98 mg Cu/kg bwt (copper sulfate pentahydrate, MRID 00067456) 

• Acute dietary LC50 of 991 mg Cu/kg (tri-basic copper sulfate, MRID00811103) 

• Chronic NOAEL of 58 mg/kg bwt (copper oxychloride sulfate; MRID 43338001) 

Given the presence of mechanisms controlling copper uptake, EFED believes the most 

appropriate value for evaluating potential effects on birds are dietary-based values. 

For both birds and mammals, risk quotients were calculated based on both the highest label 

applied rate, and the highest state average rate supplied by BEAD. Application rates for 

orchards and row crops are considered separately. Conditions assumed for modeling are the 

same as those described in the section on terrestrial exposure. 
102 

4.3.1.1 Label Applied Rates

Orchard Application

The highest label rate for orchard applications was for filberts (31.8 lb a.i./acre). At this 

application rate, all size classes of birds exceed the acute, acute endangered species, and chronic 

levels of concern for all food items. 

Table 45 Avian RQ Summary Table: Orchard Label Rates 

Acute dose-based RQs

Acute 

dietary-based 

RQs

Chronic 

RQs

Risk quotients based on 

Kenaga upper bound EEC 

20g bird 100g bird 1000 g bird All birds All birds

Short grass 220a,b 98.7a,b 31.2a,b 13.5a,b 231c

Tall grass 101a,b 45.3a,b 14.3a,b 6.2a,b 106c

Broadleaf plants/small 

insects 124a,b 55.5a,b 17.5a,b 7.6a,b 130c

Fruits/pods/seeds/lg 

insects 13.8a,b 6.2a,b 2.0a,b 0.9a,b 14.5c

a exceeds acute risk LOC (0.5) 

b exceeds endangered species acute risk LOC (0.1) 

c exceeds chronic risk LOC (1.0)
103 

Row Crop Applications

The highest label rate for row crop applications was for potatoes (3.56 lb a.i./acre). At this 

application rate, all size classes of birds consuming the short grass, tall grass, and broadleaf plant 

food categories exceed the acute risk levels of concern. The small (20g) and medium (100 g) 

birds consuming a diet of fruits, pods, seeds, or large insects exceed the acute risk LOC, using 

the dose-based calculation. All size classes of birds consuming all food types exceed the 

endangered species acute risk LOC and the chronic risk LOC. 

Table 46 Avian RQ Summary Table: Row Crop Label Rates 

Acute dose-based RQs 

Acute 

dietary-based 

RQs 

Chronic RQs Risk quotients based on 

Kenaga upper bound EEC 

20g bird 100g bird 1000g bird All birds All birds

Short grass 41.5a,b 18.6a,b 5.9a,b 2.6a,b 43.5c

Tall grass 19.0a,b 8.5a,b 2.7a,b 1.2a,b 20.0c

Broadleaf plants/small 

insects 23.3a,b 10.5a,b 3.3a,b 1.4a,b 24.5c

Fruits/pods/seeds/lg 

insects 2.6a,b 1.2a,b 0.4b

 0.2b 2.7c

a exceeds acute risk LOC (0.5) 

b exceeds endangered species acute risk LOC (0.1) 

c exceeds chronic risk LOC (1.0) 
104 

4.3.1.2 Average Applied Rates

Orchard applications

The highest average rate for orchard applications was for apples (3.8 lb a.i./acre). At this 

application rate, all size classes of birds exceed the endangered species acute risk LOC and the 

chronic risk LOC for all food items. Birds consuming the short grass, tall grass, and broadleaf 

plants food categories all exceed the acute risk and chronic risk LOCs. 

Table 47 Avian RQ Summary Table: Orchard Average Rates 

Acute dose-based RQs 

Acute 

dietary-based 

RQs 

Chronic RQs Risk quotients based on 

Kenaga upper bound EEC 

20g bird 100g bird 1000g bird All birds All birds

Short grass 49.3a,b 22.1a,b 7.0a,b 3.0a,b 51.7c

Tall grass 22.6a,b 10.1a,b 3.2a,b 1.4a,b 23.7c

Broadleaf plants/small 

insects 27.7a,b 12.4a,b 4.0a,b 1.7a,b 29.1c

Fruits/pods/seeds/lg 

insects 3.1a,b 1.4a,b 0.4b

 0.2b 3.2c

a exceeds acute risk LOC (0.5) 

b exceeds endangered species acute risk LOC (0.1) 

c exceeds chronic risk LOC (1.0) 
105 

Row Crop Applications

The highest average rate for row crop applications was for potatoes (0.8 lb a.i./acre). At this 

application rate, birds consuming the short grass, tall grass, and broadleaf plant categories exceed 

the endangered species acute risk LOC and the chronic risk LOC. Using dose-based RQs, all 

bird consuming these food categories also exceed the acute risk LOC. Only birds consuming 

short grass exceed the acute risk LOC using the dietary-based RQs. Birds consuming the fruits 

and pods food category exceed the endangered species acute risk LOC using dose-based RQs, 

but not dietary-based RQs. Only the small bird (20g) in this category exceeds the acute risk 

LOC using the dose-based RQ. 

Table 48 Avian RQ Summary Table: Row Crop Average Rates 

Acute dose-based RQs 

Acute 

dietary-based 

RQs 

Chronic RQs Risk quotients based on 

Kenaga upper bound EEC 

20g bird 100g bird 1000g bird All birds All birds

Short grass 10.4a,b 4.7a,b 1.47a,b 0.6a,b 10.9c

Tall grass 4.8a,b 2.1a,b 0.67a,b 0.3b 5.0c

Broadleaf plants/small 

insects 5.8a,b 2.6a,b 0.83a,b 0.4b

 6.1c

Fruits/pods/seeds/lg 

insects 0.7a,b 0.3b

 0.1b <0.1 0.7 

a exceeds acute risk LOC (0.5) 

b exceeds endangered species acute risk LOC (0.1) 

c exceeds chronic risk LOC (1.0)
106 

4.3.2 Mammals Risk Estimation 

A number of registrant-submitted acute rat toxicity studies (Guideline 81-1) were available 

(Table 27). The most sensitive of these studies was selected for use as the acute mammal 

endpoint. No reproductive or two-generation guideline studies for any of the copper compounds 

listed in this action were located in OPPIN, thus EFED opted to use the chronic NOAEL for 

mink in the Superfund site screening guidelines (Table 29). Modifications were made in the 

TREX spreadsheet to account for the 1 kg body weight of the mink. The following data were 

used to develop mammal RQs: 

• Acute oral LD50 of 114 mg Cu/kg bwt (copper sulfate pentahydrate, MRID 43396201) 

• Chronic NOAEL of 11.7 mg Cu/kg bwt , and 85.5 mg Cu/kg diet (mink, Sample et al., 

1996) 

Acute dose-based RQs have been adjusted to include a 22% absorption factor (see discussion in 

effects section) to account for dietary effects. Because dietary-based chronic data were 

available, the chronic dose-based values were not adjusted. 
107 

4.3.2.1 Label Applied Rates

Orchard Applications

The highest label rate application for orchard use was filberts at 32 lb a.i./acre (2 applications, 7-

day interval). At this application rate, RQs for all size classes of mammals consuming plants or 

small insects exceed the acute risk, endangered species acute risk, and chronic risk LOCs. 

Except for 1000g granivores, all size classes and food groups evaluated exceed the endangered 

species acute risk LOC. 

Table 49 Mammal RQ Summary: Orchard Label Rates 

Acute dose-based RQs 

(adjusted for 22% 

absorption efficiency) 

Chronic dose-based RQs Chronic 

dietary-based RQs 

Risk Quotients based on 

Kenaga upper bound EEC 

15g 35g 1000g 15g 35g 1000g All mammals 

Short grass 11.2a,b 9.6 a,b 5.1 a,b 381c 327c 172c 157c

Tall grass 5.1a,b 4.4 a,b 2.3 a,b 175c 150c 78.8c 71.9c

Broadleaf plants/small insects 6.3a,b 5.4 a,b 2.8 a,b 214c 184c 96.8c 88.3c

Fruits/pods/seeds/lg insects 0.7a,b 0.6 a,b 0.3b 23.8c 20.5c 10.8c 9.8c

Seeds (granivores) 0.15b 0.14 b 0.06 5.3c 4.7c 2.2c

a exceeds acute risk LOC (0.5)

b exceeds endangered species acute risk LOC (0.1) 

c exceeds chronic risk LOC (1.0)
108 

Row Crop Applications

The highest label rate application for row crop use was potatoes at 3.2 lb a.i./acre (4 applications, 

7-day interval. Risk quotients for all mammals consuming herbivorous material and small 

insects exceed the acut risk LOC except for the 1000g animals eating tall grass. Risk quotients 

for all size classes and diet groups except granivores and 1000g frugivores exceed the 

endangered species acute risk LOC. Dietary-based RQs for all diet groups exceed the chronic 

risk LOC. 

Table 50 Mammal RQ Summary: Row Crop Label Rates 

Acute dose-based RQs 

(adjusted for 22% 

absorption efficiency) 

Chronic dose-based RQs Chronic 

dietary-based RQs 

Risk Quotients based on 

Kenaga upper bound EEC 

15g 35g 1000g 15g 35g 1000g All mammals 

Short grass 2.1 a,b 1.8 a,b 0.95 a,b 71.8c 61.6c 32.4c 29.5c

Tall grass 0.97 a,b 0.8 a,b 0.44 b 32.9c 28.2c 14.9c 13.5c

Broadleaf plants/small insects 1.2 a,b 1.0 a,b 0.53 a,b 40.4c 34.7c 18.2c 16.6c

Fruits/pods/seeds/lg insects 0.13 b 0.11 b 0.06 4.5c 3.9c 2.0c 1.9c

Seeds (granivores) 0.03 0.03 0.01 1.0c 0.9 0.4 

a exceeds acute risk LOC (0.5) 

b exceeds endangered species acute risk LOC (0.1) 

c exceeds chronic risk LOC (1.0) 
109 

4.3.2.2 Average Rates

Orchard Applications

The highest label rate application for orchard use was apples at 3.8 lb a.i./acre (4 applications, 7-

day interval). Risk quotients for all size classes of organisms consuming the short grass, tall 

grass, broadleaf plants, and small insects exceed both the acute risk LOC and the endangered 

species LOC. Endangered species acute risk LOCs are also exceeded for the 15g and 35g 

mammals consuming fruits and large insects. RQs for all diet classes exceed the chronic risk 

LOC. 

Table 51 Mammal RQ Summary: Orchard Average Rates 

Acute dose-based RQs 

(adjusted for 22% 

absorption efficiency) 

Chronic dose-based RQs Chronic 

dietary-based RQs 

Risk Quotients based on 

Kenaga upper bound EEC 

15g 35g 1000g 15g 35g 1000g All mammals 

Short grass 2.5 a,b 2.2 a,b 1.13 a,b 85.2c 73.2c 38.5c 35.1c

Tall grass 1.2 a,b 0.98 a,b 0.52 a,b 39.1c 33.5c 17.6c 16.1c

Broadleaf plants/small insects 1.4 a,b 1.21 a,b 0.63 a,b 47.9c 41.2c 21.6c 19.7c

Fruits/pods/seeds/lg insects 0.16 b 0.13 b 0.07 5.3c 4.6c 2.4c 2.2c

Seeds (granivores) 0.03 0.03 0.01 1.2c 1.0c 0.5 

a exceeds acute risk LOC (0.5) 

b exceeds endangered species acute risk LOC (0.1) 

c exceeds chronic risk LOC (1.0) 
110 

Row Crop Applications

The highest average rate application for row crop use was potatoes at 0.8 lb a.i./acre (4 

applications, 7-day interval). Only the RQs for the small mammals consuming short grass 

exceed the acute risk LOC, although RQs for all size classes of mammals consuming grass, 

broadleaf plants, and small insects exceed the endangered species acute risk LOC. Dietary-based 

RQs for the mammals consuming grass, broadleaf plants, and small insects exceed the chronic 

LOC. 

Table 52 Mammal RQ Summary: Row Crop Average Rates 

Acute dose-based RQs 

(adjusted for 22% 

absorption efficiency) 

Chronic dose-based RQs Chronic 

dietary-based RQs 

Risk Quotients based on 

Kenaga upper bound EEC 

15g 35g 1000g 15g 35g 1000g All mammals 

Short grass 0.53 a,b 0.45 b 0.24 b 17.9c 15.4c 8.1c 7.4c

Tall grass 0.24 b 0.21 b 0.11 b 8.2c 7.1c 3.8c 3.4c

Broadleaf plants/small insects 0.30 b 0.25 b 0.13 b 10.1c 8.7c 4.6c 4.2c

Fruits/pods/seeds/lg insects 0.03 0.03 0.01 1.1c 1.0c 0.5 0.5 

Seeds (granivores) 0.01 0.01 <0.01 0.3 0.2 0.1 

a exceeds acute risk LOC (0.5) 

b exceeds endangered species acute risk LOC (0.1) 

c exceeds chronic risk LOC (1.0) 
111 

4.3.3 Plants, Insects, and Microbial Processes 

TerrPlant calculates risk quotients for upland and wetland areas adjacent to the application site 

based on a combination of the potential runoff from the field and spray drift from the application. 

This type of exposure is then compared to seedling emergence endpoints, based on the 

assumption that the pesticide in dissolve phase is not available to the mature plant. The amount 

of pesticide deposited on the mature plant by spray drift is calculated and compared to a 

vegetative vigor endpoint. Risk quotients are calculated separately for monocots and dicots. No 

data were located to evaluate seedling emergence. The more sensitive NOAEC is used to 

evaluate potential effects on endangered plants, and the EC25 is used to evaluate acute effects on 

non-endangered plants. RQs were calculated for endangered species vegetative vigor endpoints 

for both monocots and dicots, using the maximum label rates for orchards and row crops. No 

RQs exceeded the LOC. Based on available data, there appears to be no acute risk to terrestrial 

plants from spray drift. 

Table 53 Terrestrial Plant RQs Based on Maximum Label Application Rate 

Orchard Crops (32 lb Cu/acre) 

Adjacent upland 

(Seedling emergence) 

Adjacent wetland 

(Seedling emergence) Drift only Application (Vegetative vigor) Method 

Monocot Dicot Monocot Dicot Monocot Dicot 

Ground spray No endpoint No endpoint No endpoint No endpoint 0.05 0.01 

Aerial, airblast, 

spray 

chemigation 

No endpoint No endpoint No endpoint No endpoint 0.24 0.04 

1 Terrestrial endangered species LOC=1 
112 

4.3.4 Soil Accumulation and Plant Bioaccumulation 

While the potential effects of copper in soil are dependent on a variety of site specific factors, 

including but not limited to soil pH, percent organic matter, and sand/clay/loam content, the soil 

screening levels developed for use at Superfund sites (Efroymson 1997a) can be used as a 

benchmark for evaluating potentially harmful concentrations. Potentially harmful concentrations 

range from 60 ppm (earthworms) to 100 ppm (terrestrial plants, microorganisms). Based on 

PRZM modeling, potentially harmful soil concentrations may be reached within 2-20 years, 

dependent on application rate and frequency of application. Note that while the model evaluates 

accumulation in the soil of the field, overspray areas adjacent to the field where wildlife may 

reside and/or forage may be affected as well. 

Some plants concentrate copper from soil, and this may make it more available to herbivorous 

and omnivorous organisms. Plant uptake factors (PUFs) (USEPA 2003b) were used to estimate 

how much copper might be accumulated by the on-site plants. Shown below in Figure 14a and 

14b are the accumulation curves (both average and the upper bound of the 95% confidence 

interval) for plants growing in the concentrations of copper that are estimated for the 

Pennsylvania apple scenario. For comparison, the estimated uptake (95% CI) for plants growing 

in ambient conditions is also shown in each figure. Even at the maximum label application rate 

(19 kg/ha), and using the 95% CI copper accumulation in plants over the 30 year simulation 

stays below 100 ppm. For the state average application rate (2.2 kg/ha), and the 95% CI, 

accumulation in the plants stays below 35 ppm. In comparison to residues directly from the 

application of the pesticides concentrations of copper in plant tissue derived from uptake from 

the soil are much lower and likely pose little or no risk to organisms ingesting the plants. 
113 

 

Figure 20a and 20b - Estimated plant uptake of Cu from soil, PA apples scenario 

PA Apples (19 lbs/A)-Estimated Terrestrial Plant Cu Uptake 

from PRZM Soil Concentrations from 10 cm Surface 

Horizon 

Days

0 2000 4000 6000 8000 10000 12000 14000

Plant Cu C

oncentration (m

g/kg)

0

20

40

60

80

100

Upper 95 CI- 100 mg Cu/kg soil 

Upper 95 CI- 2 mg Cu/kg soil

U95% CI - 30 mg Cu /kg soil

Average Plant Concentration

Upper 95 CI Plant Concentration

PA Apples (2.24 kg/ha)-Estimated Terrestrial Plant Cu Uptake 

from PRZM Soil Concentrations from 10 cm Surface 

Horizon 

Days

0 2000 4000 6000 8000 10000 12000 14000

Plant Cu C

onc

entration (m

g

Cu/k

g

of dry

plant)

0

5

10

15

20

25

30

35

Upper 95 CI- 100 mg Cu/kg soil 

Upper 95 CI- 2 mg Cu/kg soil

U95% CI - 30 mg Cu /kg soil

Average Plant Concentration

Upper 95 CI Plant Concentration
114 

4.3 Terrestrial Risk Description 

Information submitted during the public comment period, and additional analysis by BEAD 

indicated that copper is often applied at substantially below current labeled, but that it is often 

applied frequently rates (see discussion in Aquatic Risk Description). To assist in making risk 

management decisions, EFED used TREX to calculate risk quotients for a range of application 

rates from 1 lb Cu/A to 7.5 lb Cu/A. In all cases, applications were applied 4 times, at intervals 

of 7-days. The absorption efficiency factor was incorporated into the mammal estimation. Risk 

quotients presented are based on dietary endpoints. 

4.4.1 Avian and Mammals 

There were exceedences of the acute risk LOC for birds at all rates evaluated. Acute risk RQs 

ranged from 0.1-6. At 1lb Cu/A, only the birds consuming short grass exceeded the LOC, but at 

1.5 lb Cu/A risk quotients for all birds consuming plants and birds consuming small insects 

exceed the LOC. Risk quotients for birds consuming fruits, pods and large insects do not exceed 

the LOC, even at the rate of 7.5 lb Cu/A. 

There were also exceedences of the acute risk LOC for mammals at all rates evaluated. Acute 

risk RQs ranged from <0.01-5. At 1 lb Cu/A, only mammals consuming short grass exceeded 

the LOC, but at any of the higher rates, mammals eating plants and/or small insects exceeded the 

acute risk LOC. Risk quotients for mammals consuming fruits, pods and large insects do not 

exceed the acute risk LOC, even at the rate of 7.5 lb Cu/A. 

For both birds and mammals, animals consuming plants or small insects exceed the endangered 

species LOC at the application rates of 1 and 1.5 lb Cu/A. At the application rate of 3 lb Cu/A, 

all classes of animals consuming items treated with copper exceed the endangered species LOC. 

Chronic RQs for birds ranged from 0.9 –102, and even at 1 lb Cu/A, animals consuming all food 

items except fruits and pods exceeded the chronic risk LOC. At 1.5 lb Cu/A, birds consuming all 

food categories exceeded the chronic risk LOC. The picture for mammals was similar, with the 

RQs for animals consuming all items except fruits and pods exceeding the chronic risk LOC at 

application rates of 1 and 1.5 lb Cu/A. At 3 lb Cu/A, mammals consuming all food categories 

exceeded the chronic risk LOC. 

Chronic effects noted in toxicity tests included weight loss and reduced food consumption at 

doses of around 700 ppm/day, both in tests conducted on rats and birds. Effects on offspring 

included loss of embryo, and reduced survivorship. How likely these effects are to occur in the 

wild is unknown. In humans, chronic copper toxicity is uncommon, though not unknown, and is 

often associated with deficiencies in copper metabolic pathways (Goyer 1996). Estimates of the 

biological half-life of copper in rats is around 2-3 days Johnson and Lee 1988, Linder and Roboz 

1986, Yu et al., 1993). It is unknown whether animals display any kind of avoidance behavior. 
115 

Table 54 Summary of LOC Exceedences and RQs for Birds and Mammals 

Rate Cu Birds Mammals 

(lb ai/A) Acute (RQs) Chronic (RQs) Acute (RQs) Chronic (RQs) 

1.0 Yes (0.1-0.8) Yes (0.9-13) Yes (<0.01-0.7) Yes (0.6-9.2) 

1.5 Yes (0.1-1.2) Yes (1.3-20) Yes (0.01-1.0) Yes (0.9-14) 

3.0 Yes (0.2-2.4) Yes (2.6-40.8) Yes (0.01-2.0) Yes (1.7-28) 

5.0 Yes (0.35-4) Yes (4.3-68) Yes (0.02-3.3) Yes (2.9-46) 

7.5 Yes (0.4-6) Yes (6.4-102) Yes (0.03-5) Yes (4.3-69) 

4.4.2 Plants, Insects, and Microbial Processes 

Use of copper-containing pesticides does not appear to pose a risk to terrestrial plants near the 

application site, either from direct contact or based on soil uptake. Based on available contact 

toxicity data, it does not appear to pose a risk to terrestrial insects. Based on accumulation 

curves, copper may accumulate in soil to concentrations high enough to affect plants, soil 

invertebrates, and microbial soil processes. 
116 

5.0 Endangered Species Analysis 

Because copper-containing pesticides are registered for so many crops, and the use of copper 

products in water bodies is so widespread, there is a reasonable expectation that all listed species 

will be exposed to copper from pesticidal applications. Table 55 summarizes which taxa may be 

at risk based on exceedences of the endangered species LOC. Endangered species LOC for both 

terrestrial and aquatic organisms exceedences occur at application rates of 1 lb Cu/A 

(agricultural crops). Direct water applications are expected primarily to affect aquatic systems. 

Anticipated indirect effects are changes in primary productivity (aquatic systems only) and/or 

modifications in the prey base. Indirect effects have been assumed to potentially occur for any 

taxa that consumes other organisms for which the acute risk LOC has been exceeded. All 

aquatic organisms were presumed to be potentially at risk for indirect effects. 

Table 55 Summary of Endangered Taxa Potentially at Risk 

Listed Taxa Direct Effects Indirect Effects 

Terrestrial and semi-aquatic plants (monocots) No No 

Terrestrial and semi-aquatic plants (dicots) No No 

Insects No No 

Birds Yes4 Yes1

Terrestrial Phase Amphibians Yes4 No 

Reptiles Yes4 Yes1

Mammals Yes4 Yes1

Aquatic vascular plants Yes3, 4 No 

Freshwater Fish Yes4 Yes2

Aquatic Phase Amphibians Yes4 Yes2

Freshwater invertebrates Yes4 Yes2

Saltwater Fish Yes4 Yes2

Saltwater Invertebrates Yes4 No 1 Potential food chain effects for organisms consuming birds, mammals, aquatic invertebrates, aquatic phase 

amphibians or fish 

2 Potential modifications in primary productivity or community structure of lower trophic levels 

3 Direct water applications only 

4 Acute and chronic
117 

5.1 LOCATES 

Using LOCATES, EFED is able to identify organisms residing in proximity to the crops most 

commonly found to apply copper. RQs for all taxa quantitatively evaluated except terrestrial 

plants exceeded the endangered species LOC. Search criteria used in LOCATES included a 

minimum of 1 acre of any crop of concern and the following crop groups: citrus, all, walnuts, 

almonds, filberts, peaches, tomatoes, bell peppers, and grapes. Because the minimum number of 

acres was set as low as possible, this represents a conservative estimate of how many species 

might be affected. A total of 467 unique species co-occur with these crop groups. Based on the 

search criteria, there is potential for copper-containing pesticides to affect endangered or 

threatened species in all states. A list of species potentially affected is included as Appendix F. 

A more explicit assessment of potential risk to these species is beyond the scope of this screening 

level assessment. 

Table 56 Number of Endangered Species Potentially Affected by Copper-Containing Pesticides 

Taxa1

 Number of Species 

Amphibian 17 

Birds 72 

Freshwater mussel 70 

Crustacean 21 

Fish 131 

Mammal 55 

Reptile 29 

Snail 72 

Aquatic species (animals) 2 311 

Terrestrial species (animals) 3 156 

Total species (direct effects) 467 

1

As categorized in LOCATES 

2

 Amphibian, freshwater mussel, crustacean, fish, & snail taxa 3

 Bird, mammal, & reptile taxa 
118 

5.2 Probit Analysis 

5.2.1 Aquatic Organisms 

Because of the method of evaluation for the freshwater aquatic assessment (BLM), probit 

analysis of a specific-dose response curve is not appropriate. Data are not available to perform a 

probit analysis for the saltwater organisms 

5.2.2 Terrestrial Organisms 

Birds

Based on an assumption of a probit dose response relationship with a default slope of 4.5, and 

and LD50 of 98 ppm Cu, the corresponding estimated chance of individual mortality associated 

with the endangered species LOC of 0.1 for birds is 1 in 294,000. Although the Agency has 

assumed a probit dose response relationship in establishing the listed species LOCs, the available 

data for the toxicity study generating RQs for this taxonomic group do not statistically support a 

probit dose response relationship (p<0.05) and so the confidence in the estimated event 

probabilities based on this dose response relationship and the listed species LOC is low. 

Small Mammals

Based on an assumption of a probit dose response relationship with a default slope of 4.5, and 

and LD50 of 114 ppm Cu, the corresponding estimated chance of individual mortality associated 

with the endangered species LOC of 0.1 for small mammals is 1 in 294,000. Although the 

Agency has assumed a probit dose response relationship in establishing the listed species LOCs, 

the available data for the toxicity sudy generating RQs for this taxonomic group do not 

statistically support a probit dose response relationship (p<0.05) and so the confidence in the 

estimated event probabilities based on this dose response relationship and the listed species LOC 

is low. 
119 

5.3 Aquatic Ecosystems 

Direct Effects

Based on the analysis of site specific water chemistry, there appears to be an acute endangered 

species risk for saltwater fish, and both saltwater and freshwater invertebrates at agricultural 

application rates as low as 1.0 lb Cu/A. Greater than 5% of the sites evaluated exceed the 

endangered species acute risk LOC for freshwater fish at the application rates of 3.0 lb Cu/A. 

Indirect Effects

Indirect effects on aquatic ecosystems may be grouped primarily into two categories: removal of 

the prey base, and/or shifts in community structure. While copper is toxic to most aquatic 

organisms, the most sensitive are the non-vascular aquatic plants and aquatic invertebrates. 

Elimination of organisms at the base of the food chain will likely also reduce populations of 

organisms which feed on them, unless these organisms are able to forage in an unaffected area, 

or are sufficiently generalist in their prey preference to consume an alternative food source. For 

aquatic systems, organisms potentially affected include higher trophic levels in the affected 

waterbody (e.g., fish or turtles), as well as piscivorous birds or mammals dependent on it for 

food. A shift in the community structure, by elimination of the more sensitive organisms, could 

be either beneficial or detrimental to the endangered species dependent on the affected 

waterbody. Detrimental effects include greater competition for limited resources, and/or 

removal of a species that creates a more favorable environment for the endangered species. 

Beneficial effects might include removal of a competing organism that is less sensitive than the 

endangered species, or a shift to a preferred food source. The likelihood and potential impact of 

indirect effects is beyond the scope of this screening level assessment. 

5.4 Terrestrial Ecosystems 

Direct Effects

The RQs for birds, reptiles, terrestrial phase amphibians, and mammals exceed both acute 

endangered species and chronic risk LOCs at the application rate of 1.0 lb Cu/A. 

Indirect effects

In a terrestrial system, potential indirect effects are much the same as in an aquatic system: 

elimination of the prey base, and /or shifts in the trophic structure. Organisms most likely to be 

affected include raptors and carnivorous mammals whose diets include the small mammals and 

birds, and whose overall territory includes a significant amount of land treated with coppercontaining pesticides. As with aquatic species, effects may be beneficial or detrimental 
120 

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ECOLOGICAL RISK ASSESSMENT FOR RE-REGISTRATION OF COPPER 

SULFATE (CASE #0636), GROUP II COPPER COMPOUNDS (CASE #0649), AND 

COPPER SALTS (CASE #4026), APRIL 20, 2006. 

NO REVISIONS WERE MADE IN THE APPENDICES OF THE OCTOBER 24, 

2005 VERSION OF THE ECOLOGICAL RISK ASSESSMENT ON COPPERS. 

DUE TO THE SIZE OF THE ECOLOGICAL ASSESSMENT, THE APPENDICES 

WERE EXCLUDED. PLEASE REFER TO THE OCTOBER 24, 2005 VERSION 

IN THE DOCKET (EPA-HQ-OPP-2005-0558-0007) FOR ACCESS TO THE 

APPENDICES.