UNITED STATES ENVIRONMENTAL PROTECTION AGENCY WASHINGTON, D. C. 20460

O F F I C E O F 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 th e 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 (Doc ket 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 (~12 0) were received, and rather than address each one individually, EFED has grouped them into categories, and addressed common issues within the categories.

1General 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 ag ricultural crops and direct water applications. One of these documents, the response from the Copper Sulfate Task Force (CSTF) included an attachment detailing use ra tes and application frequenc ies for various crops. Characterizing the use patterns and application rates for th e vast array of both coppercontaining products and crops has been a chal lenge for both the Agency and the CSTF. The data provided by the CSTF indicate that most agricultural us ers appear to be applying copper-containing products at rates substantially lowe r 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 us ed 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 BE AD, and input from speci fic grower groups (See Agricultural Uses section) have been incorporated into the revise d ecological risk

assessment.

Comments on Direct Water Uses

The Agency received approximately 70 comme nts regarding the dire ct application of copper-containing products to water. Prim arily, this was from users who apply the products to control nuisance al gae and aquatic weeds, but so me 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 ecologi cal risk assessment released for public comment, BEAD has compil ed 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 comme nts regarding the use of copper-containing products on agricultural crops. Se veral of these (#0017, #0041, #0091, and #0099) contained detailed information regarding use practices and applica tion rates for certain crops. Application rates and patterns (timing, frequency, interval) provided by these groups was consistent with the State Averag e rates determined by BEAD, and the CSTF application rate data, and has been incor porated 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 eval uation 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 com pounds 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 incl ude an analysis of copper input into sewer systems due to its use as a root-kille r. The currently exis ting “Down the Drain” model previously used by the Agency to addr ess 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 clos ely with the Office of Water in development of the ecological risk assessment. The Daphnia acute LC 50 used in EFED’s aquatic assessment is essentially the sa me value used for the establishment of the Aquatic Life Criteria, and both programs ha ve used the BLM to incorporate copper speciation effects. The two programs have diffe rent procedures to determine final values. OW uses a community-based approach, and sets the value to be prot ective of 95% of the organisms in the species sensitivity distribut ion. EFED determines risk quotients based on estimated environmental concentrations (EEC s) 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 LC 50 values normalized to laboratory water, which repres ents a situation wher e copper is readily bioavailable, and thus, lower concentrations ar e more toxic. As the water quality criteria document (EPA 2003, pg 14) notes, “site-water chemistry parameters are needed to
evaluate a criterion.” The c opper pesticide eco logical risk assessmen t is a site-specific evaluation using actual water chemistry data , and results are presented in terms of number of sites exceeding the EFED pre-esta blished levels of concern (LOC) for various concentrations of copper introduced into the sy stem 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 us ed median water quality data from USGS water monitoring sites. Because water chemistr y 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 va riations in water chem istry parameters. It was assumed that variations in water quality conditions within a monitoring sites (temporal scale) is lower than variati on in water quality conditions among water monitoring sites (spatial scale). The use of USGS water qual ity 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 m onitoring sites encompassed a range of conditions, including some very vulnerable wate r chemistries. OW is currently working

3on implementation guidance for calculating site-specific criteria for use of water quality
data in the BLM model.

• Request for a cumulative envir onmental risk assessment. In general, OPP does not conduct cumulative ecological risk assessm ents. For copper, because it has so many potential routes for introduction into the e nvironment, 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 la bel. Currently, labels contain an aquatic hazard statement, and will continue to do s o. 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 commen ts (#0154, #160, #0179, #0181) that provided background information on the environmental fa te 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 K d or K oc . While the ionic state of coppe r 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 coppe r 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 noticeabl e toxic effects becaus e of binding. This concept is taken into account in th e 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 th e simplifying assumption that all compounds used for direct water treatments will dissociate rapidly. The document notes that some compounds will dissocia te 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 evaluate d based on the copper activity ( i.e., bioavailability), thus assuming that a ll the copper added to the water system is available for partitioning (in EXAMS) a nd speciation (in the BLM) allows EFED to estimate an upper bound to exposure.

4UNITED STATES ENVIRONMENTAL PROTECTION AGENCY WASHINGTON, D. C. 20460

O F F I C E O F PREVENTION, PESTICIDES AND TOXIC SUBSTANCES

Chemical: Coppers (C opper 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 E ffects 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 comment s received during the public comment period. No major technical changes were made, but appli cation rates appear to be more similar to the state average rates used in the version released for public comm ent. EFED has modified the agricultural use section to more thoroughly evaluate exposure a nd effects at the lower application

rates.The copper compounds are produced by a variet y of manufacturers, and are currently registered for a wide variety of agricultural us es, direct water applications, and for use in domestic sanitary sewers to c ontrol growth of tree roots. Antimicrobial applications are
not addressed in this eco logical risk assessment.

As a bridging strategy to addr ess the range of copper compou nds included in this action,
EFED has evaluated all of them on the ba sis of ionic copper (the cupric ion Cu 2+ ), regardless of the counter ion, or other moie ties 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 qualitat ively in the text. Copper is a unique pesticide. In addition to ha ving 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. Becau se 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 th e aquatic environment, and may exist in a number of ionic states, i on-pairs, and organic comple xes simultaneously (known as “speciation”), as well as sorbed to suspe nded particles. Thus , the total dissolved concentration is not truly reflective of poten tial copper toxicity. To account for copper speciation, EFED opted to use the Biotic Li gand Model (BLM) in conjunction with the
Pesticide Root Zone Mode l (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 Dr aft Ambient Aquatic Life Criteria for Copper to perform the aquatic toxicity assessment. It has b een reviewed and approved by EPA’s Scientific Advisory Board (SAB). Currently, BLM has only been parameterized and validated for freshwater environments, thus the saltwater ev aluation is on the basis of dissolved copper rather than copper activity. The saltwater ev aluation is also consis tent with the Draft Ambient Aquatic Life Criteria for Copper developed by OW.

The water quality data used in BLM simula tion were derived from 811 USGS monitoring sites to evaluate site-specifi c toxicity and copper speciation in a variety of surface water conditions. It is assumed these water qual ity conditions are representative of water quality in ambient surface across the Unite d States. Thus, the freshwater aquatic evaluation is presented in terms of percenta ge of sites where th e risk quotients (RQ) exceed a particular le vel 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 represen tative labels and state averag e use rates, we have also
included a number of “what-if” estimations to provide additional benchmarks for the risk managers. Updated assessments focus on appli cation rates between 1-7.5 lb Cu/A. Input during the public comment period indicates most agricultural applications fall within this

range.

2Key components of the risk assessment are as follows:

Aquatic Assessment

• Site water chemistry, esp ecially the alkalinity, pH, and dissolved organic carbon (DOC), determines copper toxicity thr ough speciation of dissolved Cu. Because site conditions differ, EFED has used the BLM and USGS monitoring data to develop site specific LC 50 s for freshwater systems in terms of dissolved Cu 1 as well as predict the concentration of Cu 2+ ion (Cu activity). Exposure to copper
was based on the concentration of Cu 2+ ion rather than di ssolved Cu. Aquatic RQs were developed based on Cu activities.

• An analysis of ambient water quality condi tions at the USGS monitoring stations
indicate five out of the 811 mon itoring sites (<1%) have ambient Cu 2+ concentrations exceeding the Daphnia LC 50 (on an activity basis) . Water quality
conditions at these sites in cluded low pH (acidic), lo w DOC, and low alkalinity. Additionally, some of the sites were a ssociated with point sources of Cu
contamination such as stormwater outfalls.

• Based on water chemistry, the site specific estimated LC 50 s for aquatic invertebrates ranged from 0.3 to 1,900 ppb di ssolved Cu, with the majority (90%) between 1 and 200 ppb dissolved Cu. The majority (91%) of site specific LC 50 s for fish were <600 ppb dissolved Cu.

• Direct water applications typically reco mmend 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. Typi cally, 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 EXA Ms 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 organism s. 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 invertebra tes. Minimizing advers e 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 Cu 2+ ion (Cu activity) because this accounts for the speciation of copper, which gr eatly affects toxicit y. Site-specific LC 50 s and runoff concentrations are presented in term s 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 estim ates 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 di ssolved 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 a quatic 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 si tes for aquatic invertebrates and 45% of
the sites for fish.

• Row crops: Row crop label application rate s are substantially lower than orchard crops. Usage estimates from BEAD show th at 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 si tes 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 LO Cs with the concentration of dissolved copper, and an equations to correlate th e peak concentration of dissolved copper in the water body with applic ation rate. Peak concen trations, while partly a function of application rate , can vary widely dependent on site characteristics, climate, and timing of application. Effect s 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 th e sites evaluated are expected to exceed the acute risk LOC fo r 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 dissipa tion 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 mu ch 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 water 2 concentrations ranged from 0.4 to 45 ppb dissolved Cu. Estimated sediment pore water concentrations af ter 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 LD 50 for birds was 98 ppm Cu and for mammals was 114 ppm Cu. The acute dietary LD 50 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 valu es for various compounds were expressed on the basis of copper, rather than the copper containi ng compound. This somewhat reduced the variability in toxicity le vels 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 so luble, thereby making the Cu 2+ ion more readily available to the organism following inge stion. Some studies suggest that the composition of food contaminated with c opper may also affect bioavailability. Because organisms have homeostatic m echanisms 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 efficien cy correction factor was applied.

• As with the aquatic assessment, EFED ev aluated 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 assessm ent. At an application rate of 3 lb Cu/A birds and mammals consuming grass an d/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 exceed ed in all food categories for both birds
and mammals.

2 Sediment pore water is an esti mate of the bioavailable fraction.

5• At sites where copper is continuously a pplied, it will accumulate in the soil, although the degree of bioavailability is un certain, and will vary dependent on site conditions. Concentrations of 60-100 pp m 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, applicati on rates, and frequency of application. Although the model evaluates the applicat ion 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 rema in <100 ppm, even at the highest application rate. While approaches the dose-based LD 50 for mammals, it is significantly below the dietary-based LD 50 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 estimat e the runoff and drift of applied Cu. This modeling was conducted using a range of K d values to represent differential sorption in sand and clay-textu red 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 lo ss and distributions of Cu on suspended
sediment and runoff water were sim ilar for PRZM simulations and field monitoring studies.

• Median water quality parameters for 811 USGS monitoring sites were used to represent water quality c onditions across the United States. These data are expected to represent the most likely wa ter quality conditions in ambient surface

waters.

• Chemical speciation modeling usin g the BLM was conducted without consideration of competitive equilibria with other common metals (such as Fe 3+

, Zn 2+ , Al 3+ , etc.) or redox conditions. Redox c onditions in the water column and surface sediments were assumed to be oxic (aerobic). This assumption is an expected condition in orde r to support aquatic organisms. The lack of
consideration of other metals in th e speciation modeling is expected to underestimate prediction of Cu 2+ concentrations in the water column due to the metal competition for ion pairs and liga nds. Cupric ion concentrations, as predicted by PRZM/EXAMS/BLM, are within the range of Cu 2+ concentrations
for known Cu minerals. These data s uggest the simulation modeling is not outside of the thermodynamic bounding condi tions for Cu mine ral stability.

6• A bridging strategy was implemented to assess a variety of Cu compounds and complexes using a unified assessment appr oach. This strategy assumes complete
dissociation into Cu 2+ and the counter ion. This assumption is expected to provide a conservative estimate of Cu 2+ concentrations in the exposure

assessment.

• Application rates for the various co pper compounds were derived from representative labels. Hi ghest label application rate s were 32 lb Cu/acre for orchard crops and 3.6 lb Cu/acre for row cr ops. These application rates appear to be higher than the rates gene rally used. Labels did not clearly state the number of applications or a maximum application ra te of copper for a year or season, and input from growers suggest they appl y 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 concentrati ons 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 woul d 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 (r 2 ). Therefore, there is considerable uncertain ty associated with predicted Cu uptake.

• The BLM has been parameterized, validated, and tested for animals in freshwater ecosystems. It is appropriate for asse ssing copper speciation for aquatic plants, but not toxicity. A version is curren tly 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 m echanisms, and species sensitivity may vary widely.

Data Requirements

EFED used data from registrant-submitte d studies, other Agency programs, and open literature. No specific data requirements were identified.

7Endangered Species Statement

Endangered species acute risk LOCs we re exceeded for fresh- and saltwater invertebrates, and saltwater fish at applica tion 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 bi rds, reptiles, terrestrial phase amphbians,
and mammals. Chronic risk LOCs were exceed ed 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 app lications. Terrestrial plants were the only category of organism quantitatively evaluated that di d not exceed endangered species LOCs.

EFED conducted LOCATES search on the agri cultural crops identified as the most common applicators of copper- containing pesticides to id entify species with a high probability of exposure but other species may be affected as well. LOCATES identified a total of 467 animal species as occurri ng in counties containing these crops.

Additional analysis regarding co-occurrence of pesticide application and species location, and better information regarding applicati on rates and practices on specific crops are required to refine the estimate of what e ndangered 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, 2006Table 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....................................................................................... 543 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 Incide nt 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.................................................................................................... 1194 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) Me thodology 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................................................................................... 1295 List of Tables

Table 1 Summary of Risk Conclusions ....................................................................................... 13 Table 2 Summary of Endangere d Species Risk Conclusions ...................................................... 15 Table 3 Copper Compounds Addressed in this RED................................................................... 17 Table 4 Usage Analysis for C opper 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 Interv als Used in PRZM/EXAMS Modeling............................. 37 Table 8 Summary of USGS Water Quality Data Used in the BLM 1

........................................... 39 Table 9 Suspended Sediment USGS Monitoring Data................................................................ 42
Table 10 Estimated Water Column Dissolv ed 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 Colu mn 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 a nd Measured Runoff Concentrations ................................. 49 Table 17 Estimated Dissolved Copper Concen trations for Direct Water Applications............... 54 Table 18 Predicted Concentrations for Direct Applications........................................................ 55
Table 19 Estimated Cu 2+ 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 Rates 1 Equivalent to 10% Site Exceedences............................ 77 Table 26 Aquatic RQ Summary Tabl e: Direct Water Applications ............................................ 78
Table 27 Estimated Percent of Water Body Treated at 1 ppm Cu 2+ Equivalent to 10% Site
Exceedences....................................................................................................................

...... 80 Table 28 Percentage of Sites Exceeding LO Cs for Use of Copper as a Root-killer.................... 80 Table 29 Comparison of Application Ra tes Derived from Different Sources............................. 82 Table 30 Summary of Acute Risk LOC Exceedences in Aquatic Environments........................ 85 Table 31 Range of Sediment Pore Water Di ssolved Copper Concentrations for Various
Scenarios......................................................................................................................

......... 86
Table 32 Estimated Environmental Concentr ations Based on Label Application Rates............. 88
Table 33 Estimated Environmental Concentrat ions Based on Average Application Rates ........ 88
Table 34 Estimated Environmental Concentr ations Based on Label Application Rates............. 89
Table 35 Estimated Environmental Concentrat ions Based on Average Application Rates ........ 89
Table 36 Avian Guideline Data .................................................................................................

.. 94
Table 37 Avian Data from ECOTOX .......................................................................................... 956 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 Pr ocesses 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 Ta ble: Orchard Average Rates.................................................. 104 Table 48 Avian RQ Summary Table: Row Crop Average Rates ............................................. 105 Table 49 Mammal RQ Summar y: Orchard Label Rates............................................................ 107 Table 50 Mammal RQ Summar y: 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 Base d 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 Pote ntially Affected by Copper-Containing Pesticides

............................................................................................................................... .............. 1177 List of Figures

Figure 1 Environmental Fate Bridging St rategy for Cu Minerals and Complexes...................... 22 Figure 2 Conceptual Model for Agricultural Uses ...................................................................... 27 Figure 3 Conceptual Model fo r 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 Di stribution for Median Alkalinity ......................................... 41 Figure 7 Cu Activities in Ambient Surface Wa ters on Cu(II) Mineral Stability Diagram.......... 52 Figure 8 Cu Activities for PA Apple Scenar io 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 Exceedi ng 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 Acut e Risk LOC, Direct Water Application.............. 79 Figure 16 Percentage of Sites Exceeding ES Ac ute Risk LOC, Direct Water Application ........ 79 Figure 17 Correlation of Runoff Concentra tions 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 Aver age 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 LC 50 .............................................................................. 63 Map 3 Estimated Site Specific Trout LC 50 .................................................................................. 64 Map 4 Measured Dissolved Copper and Estimated Site Specific Daphnia LC 50 ........................ 65 Map 5 Daphnia Acute RQs, Highest R unoff, Orchard Use, Label Rates.................................... 70 Map 6 Daphnia Acute RQs, Highest Runo ff, Orchard Use, Average Rates ............................... 71 Map 7 Daphnia Acute RQs, Highest R unoff, Row Crop Use, Label Rates ................................ 72 Map 8 Daphnia Acute RQs, Highest Runo ff, Row Crop Use, Average Rates............................ 73 Map 9 Daphnia Acute RQs, Lowest R unoff, Row Crop Use, Label Rates ................................. 748 1.0 Executive Summary

This ecological risk assessment covers the c opper sulfate, copper gr oup II salts, oxides, hydroxides, and complexes used on food crops as f ungicides and bacteriocides; and directly in aquatic environments primarily for aquatic plant control. Most of thes e compounds dissociate in the environment to form ionic copper 1 (usually Cu 2+ ), and the counter ion. The chemistry of
Cu 2+ is complex because it forms inorganic (including CuOH + , Cu(OH) 2 0 , Cu(OH) 3 - , Cu(OH) 4 2

, CuCl + , CuCl 2 0 , CuCl 3 - , CuHCO 3 - , etc.) species and soluble comp lexes 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 ingr edient. Because copper is a metallic element, it will continue to cycle via biogeoche mical 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 processe s Because it is both ubiquitous and toxic, it is also regulated by other U.S. Environmental Protection Agency programs. The Office of Water (OW) regulat es 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 Modeli ng 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 Cu 2+ ion in aquatic systems. This modeling approach assumes chemical equilibria with no consideration of chemical ki netics with regard to precipitation/dissolution, complex formation, adsorption/desorption, and oxid ation/reduction. In te rrestrial ecosystems, copper is a contaminant of concern (COC) unde r the Comprehensive Environmental Response, Compensation, and Liability Act (CERCLA). Envir onmental 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 copp er is toxic, it is also an im portant 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 va riance 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 insect s contaminated with copper. Acute copper toxicity via ingestion can cau se bloody vomiting, hypotension, co ma, 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 osmore gulatory processes and causing acute toxicity.

1 Cu 2+ is shorthand for Cu[H 2 0] 6 2+ , the hexaquocopper (II) ion.

2 Inorganic and organic copper complexes replace the boun d water of the hexaquocoppe (II) ion with the ligand.
Hence CuCl 2 0 is actually [Cu[H 2 0] 4 Cl 2 ] 0

.9 1.2 Status of Labels

This risk assessment considers 15 separate co mpounds, incorporated by multiple manufacturers into a range of end-use products fo r use on a vast array of crops and also for direct application to aquatic environments. Application rates used in this risk asse ssment are based on a review of representative labels for CuSO 4 and Cu(OH) 2 for agricultural crops. Th e representative labels indicate a wide range of use rates (1 to 32 lb s Cu/A) with the highest rates on orchard crops. Labels were unclear regarding the frequency of application a nd 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 high est application rates were significantly greater (in some cases almost twice) than many of the ot her labeled rates, and EFED also evaluated state average application rates, as supplied by the Biological Economi c 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 Su lfate Task Force (CSTF), grower groups, and additional analysis by BEAD indicat ed that agricultural applicati on rates are substantially lower than many of the current label rate s. Typical rates for row crops a ppear 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 additi on to evaluations of the highest rates, EFED has
included summaries of effects e xpected at application rates ra nging 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 comme nts, typical applications for control of algae and aquatic weeds target concentrations ranging from 0.1-1 pp m Cu. Applications ar e often made multiple times, at 2-4 week intervals. Applications for co ntrol 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 intr oduced by a wide variety of anthropogenic sources, thus there is always a background concentration, a nd there is no way to distinguish the particular source. Studies, both in terrestrial and aquati c ecosystems, have shown that even in some cases where copper concentrati ons are elevated, toxic effects to organisms are
not evident. This has been associated with the speciation 3 of copper, and the fact that Cu 2+ will form inorganic and organic complexes, which may or may not be toxic. Additionally, Cu 2+ has a high sorption affinity for soil, sediments, a nd organic matter which limits bioavailability. Because these factors are dependent on water chem istry as well as sediment/soil properties, the relative toxicity and bioavailability of Cu 2+ is highly site specific. Cons ideration 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 (Cu 2+ ), cuprous ion (Cu + ), inorganic complexes, organic complexes and minerals (amorphous or crystalline).10 For the aquatic risk assessment, Cu(II) compound us es on terrestrial crops were modeled using the PRZM/EXAM models for estimating Cu runoff fr om a 10 ha field into a standard small water body. A range of crop scenarios with diverse geogr aphy was selected to en sure a representation of crop-climate-agronomic comb inations. To assess the specia tion 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 a nd making it not bioavailable. The BLM was used by EPA’s Office of Water to es tablish Ambient Water Quality Criteria. The model has been reviewed and approved by the Scientific Advisory Board (SAB). The BLM
model was used to estimat e the concentration of Cu 2+ ion (copper activity) and toxicity in the standard small water body using site-specific water chemistry m onitoring data from 811 USGS
sites distributed across th e nation. Peak, 21-day average, and 60-day average Cu 2+

concentrations were estimated for each runoff scen ario. Risk quotients were derived for aquatic invertebrates and fish by comparing the copper activity derived from runoff with the copper activity representing an aquati c invertebrate or fish LC 50 at the specific site, based on water chemistry. The resulting risk quot ients (RQs) are compared to th e EFED pre-esta blished levels of concern (LOC), and expressed as the percen tage 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 rate s, and an estimate of how many of the USGS sites exceed a given endpoint at a part icular dissolved copper concentration.

Terrestrial effects were asse ssed using EFED’s standard as sessment methodology, with the exception of the fact that toxic ity endpoints for studies from all compounds were converted to express the toxicity value on th e basis of copper. Standard assessment methodologies included the use of the Terrestrial Expos ure 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 f ood items, and ingested dose based on allometric equations. TREX calculates RQs using both dose-ba sed and dietary-based t oxicity values. Due to the reactivity of copp er, the dietary-based values are probabl y a better estimator of what might occur in the wild. Because no acute dietary toxicity endpoints were available, EFED incorporated an absorption efficiency factor in to the chronic dose-based RQ calculations for mammals. TerrPlant estimates exposure from bo th 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 in to the BLM to determine site specific Cu 2+ concentration, and this concentration was compar ed to the site specific toxicity values to determine risk quotients (RQs). Estimated peak runoff of Cu concentr ations 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 site s exceeded the acute and chronic11 risk LOCs for aquatic invertebrates, >99% exceeded the acute risk LOC for plants, 80%
exceeded the acute risk LOC for fi sh, 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 shou ld 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-specifi c 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 addres sed acute and chronic endpoints for birds and mammals, and vegetative vigor endpoints for terrestrial plants. A qualitative assessment was
done for terrestrial insects. Us ing 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 modera tely toxic to mammals. In a ll 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 Cu 2+ 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 eff ects concentrations (NOAECs) were 6.8 lb Cu/acre
for monocots and 36.7 lb Cu/acre for dicots.

At the highest orchard applicati on rate, RQs for all sizes and food classes of birds exceeded the acute risk, chronic risk, and endangered specie s acute risk LOCs. At the highest row crop application rate, RQs for all sizes and food cla sses 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-bas ed). At the highest orchard a pplication rate, RQs for all sizes
and food classes of mammals exceeded the chro nic risk, and endangered species acute risk LOCs. RQs for all sizes and food classes of ma mmals except the largest granivores exceed the acute risk LOC. At the highest row crop applic ation rate, RQs for all sizes and food classes of mammals except the granivores exceeded the ac ute risk, the chronic ri sk, and the endangered species acute risk LOCs. A summary of effects expected at concentrat ions 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 depe ndent on site conditions. Concentrations of 60- 100 ppm Cu are potentially harm ful 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, a nd frequency of application.12 Although the model evaluates the application site, overspray ar eas where wildlife may reside and/or forage may be affected as well. Some plants concentrate c opper 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 applicat ion rate. While this
is above the dose-based LD 50 for birds and approaches the dose-based LD 50 for mammals, it is significantly below the dietary-based LD 50 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 th is assessment, current labelled rates for copper compounds appear to pose risk to all taxa quantitatively evalua ted, except terrestrial plants, frreshwater vascular plants, and saltwater plants . However, input from the user community and additional analysis of usage data by BEAD dur ing the public comment period indicate that application rates are often signifi cantly below current label rates. Copper can be toxic in the <10 parts-per-billion (ppb) range for aquatic orga nisms 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 c opper products, there is lik ely 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 moresedentary 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. P opulations of phytoplankton and z ooplankton (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 mo re copper tolerant organisms, and/or some of the organisms present may develop metabolic path ways for dealing with higher copper loading.14 The copper will accumulate in the sediments, which serve as a si nk in aquatic systems. Under most conditions, sediment-bound coppe r is not readily bioavailable

.

Minimizing adverse effects of non-target organi sms 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 entrai ned sediment could affect downstream resources.

1.5 Endangered Species Assessment

Because of the number of crops registered for copper compounds and th e 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 geogra phic area where coppercontaining pesticides are frequently used on agricultural crops. The list of species identified in
this assessment should not be cons idered all-inclusive. Because copper is introduced into the environment from multiple anthropogenic sour ces, as well as naturally occurring background concentrations, risk at specific geographic locations may vary cons iderably 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, reptile s, and mammals. Specific taxa affected are dependent on application ra tes, and are detailed in Table 2. Direct water a pplications are likely to affect mostly aquatic taxa, alt hough there may be cer tain instances ( e.g. Everglades snail kite), where they may affect terrestrial organisms indir ectly due to reduction of a specific prey item. Aquatic vascular plants are only ex pected to be at risk from di rect water applications. EFED conducted LOCATES search on the ag ricultural crops iden tified as the most common applicators of copper-containing pesticides to identify speci es 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 ri sk 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 ri sk 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 ri sk exceedences for all food groups.

Direct
Water (1 ppm) Vitrually all application rates exceed acute risk andendangered species acute risk for aquatic nonvascular plants, freshwat er 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 coppe r, rather than an organic moiet y. Although it exists in a variety of organic and inorganic complexes, it is most toxic as the cupric ion (Cu 2+ ). This screening
level risk assessment eval uates the toxicity of Cu 2+ . The assessment strategy assumes rapid, complete dissociation of the Cu 2+ and its counter ion. Organic lig ands/chelates are expected to behave differently. They will stay in suspension longer, and the Cu 2+ will be less available to aquatic organisms. Specific chemicals addr essed in the risk assessment are listed in Table 3. A more refined risk assessment for copper-conta ining 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 pentah ydrate copper sulfate CuSO 4 ≅ 5H 2 O 249.65 25.4 PC024401

basic copper sulfate copper sulfate,
tribasic 3Cu(OH) 2 ≅ CuSO 4 468.29 54.2 PC008101

copper hydroxide none Cu(OH) 2 81.56 77.9 PC023401

cuprous oxide Cu 2 O 143.08 88.8 PC025601

copper carbonate copper carbonate, basic Cu(OH) 2 CuCO 3 221.12 57.5 PC022901

copper ammonium complex copper
tetraamine Cu(NH 3 ) 4 2+ 131.58 48.3 PC 022702

copper ammonium carbonate complex none CuNH 3 (HCO 3 ) 2 190.54 33.3 PC022703

basic copper chloride copper chloride, basic; copper oxychloride 3 Cu(OH) 2 ≅ CuCl 2 427.133 59.5 PC008001

copper oxychloride basic cupric
chloride Cu 2 Cl(OH) 3 213.57 59.5 PC 023501

copper oxychloride sulfate none 3Cu(OH) 2 ≅ CuCl 2 + 3Cu(OH) 2 ≅ CuSO 4 879.43 57.8 PC023503

Copper salts of fatty and rosin
acids Cu Soap Mixture of compounds NA NA PC023104

Copper ethylenediamine Cu-EDA C 2 H 8 N 2 Cu 123.54 51.43 PC024407

Copper triethanolamine complex Cu-TEA C 6 H 15 O 3 NCu +2 212.54 29.89 PC024403

Copper ethanolamine complex C 2 H 7 ONCu +2 124.54 51.01 PC024409

Copper octanoate Cu Soap C 8 H 16 O 2 Cu 207.54 30.61 PC023306
*approximate formula, may vary slightly depending on manufacturing processes, molecular weight and percent copper calculated based on formula18 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 le vel, copper is an essential element for living systems, and is a key atom in the oxygen carryin g protein, hemocyanin, for some invertebrates. Various forms of copper occur naturally in the envi ronment. 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 cont aining pesticide is applied, it must be assumed
that there is an existi ng background concentration that must be considered.

2.1.2 Mode of Action

Copper is used as an algicide, fungicide, and mollu scicide, but the specific toxic mode of action varies between these taxonomic groups. Expos ure to excess copper cau ses disruption of the cellular membrane, with the thiol groups as the primary target (E isler 2000). In fishes, copper causes gill damage, and can interfere with osmoregulat ory processes. It has been associated with effects on ATP-synthesizing pathways, and can inte rfere with energy metabolism. In algae, it causes increased permeability of the cell membra ne and leakage of th e cell contents. For molluscs, it disrupts peroxidase enzymes, and a ffects the functioning of th e surface epithelia. In mammals, excess copper causes alterations in bi omolecules and lipid peroxidation. Few avian wildlife studies are available, but domestic chicks showed da mage to the gizzard lining, and domestic ducklings and turkeys accumulated copp er in their livers. Copper has not been associated with carcinogenic, mutagenic, or tera togenic 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 en zyme. 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 cal led plastocyanin. Most organisms have biochemical pathways capable of dealing with modera te doses (Eisler 2000). Copper may be bound to metallothioneins
and stored or excreted. This bi nding is a reversible process, and homeostatic processes within the organism regulate the amount of copper ci rculating. Metallothi onein production is an inducible process, and organisms in a copper (o r other metal) rich environment often exhibit
elevated concentrations.19 2.2 Use Characterization

Copper has been widely used in pe sticidal applications for more than a hundred years. For the purposes of this ecological risk assessment, appli cations have been grouped into two categories: orchard and row crop uses, and di rect water applications. Thes e two categories are represented by separate conceptual models Antimicrobial ap plications 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 hydrox ide, 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 gro und concentrate spray. It is registered for use on a wide variety of crops in cluding, but not limited to:

Orchard crops - citrus, nuts, apples, apri cots, banana, coffee, peach, pear, and plum Row crops - barley, oats, wheat, beans, bro ccoli, cabbage, carrots, melons, and tomatoes
Small fruits and vines - bluebe rry, 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 applica tion is variable, but some intervals are as short as 5 days, or on an “as needed” basis. Applicat ion rates used in the assessment are based on the label analysis and state average rates determ ined by BEAD, and are detailed in the aquatic exposure section ( Table 11). Input from the user commun ity and a more detailed analysis by BEAD during the public comment period showed the majority of users ap plied copper products at rates below (sometimes significantly) those cu rrently 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 accoun t for the majority of the usage. Based on Screening Level Usage Analysis (SLUA) conduc ted by BEAD, the following crops have been identified as major users of copper based pestic ides. The evaluation is based on pesticide usage data for agricultural crops dur ing the years of 1998-2003. Turf us es are not included. Usage analyses were available for copper sulfat e 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). Hi gh usage crops are shown below in Table 2. Nine specific crops account for 73.2% of the total us e. This data was provided after the PRZM-EXAMS modeling was co mpleted, thus the specific crops modeled by EFED do not include all of the high-use crops20 Table 4 Usage Analysis for Co pper Sulfate and Copper Hydroxide

Crop type Percent of use Specific crop s 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 di rect water applications was conducted by BEAD (Aquatic Use Memorandum, 2/15/06, DP#324176). Th e summary in this chapter includes the information relevant to the ecological risk asse ssment (e.g., rates, frequencies, concentrations, and use sites). The analysis was conducted by BE AD using research articles as well as other
relevant authorita tive publications, with input from the user community.

For algaecide and aquatic herbicide uses, the co pper compounds are applied at a range of rates between 0.2 – 1.0 ppm elemental copper. Averag e copper rates for algae control were 0.5 ppm for susceptible species and 0.75 - 1.0 ppm for resist ent 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 give n 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, applicati ons 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 fo r snail control was found to be within the 1.0 to 1.5 ppm concentrati on. Control of snails and leeches in ponds and other associated quiescent water bodies is fo r human health as well as agricultural and21 aquacultural reasons. Aquaculture systems rely on direct water applicati ons 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 pest icidal 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 majori ty 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 unde r the purview of EFED are lawn uses, and use
as a root-killer. Lawn uses are considered w ith agricultural uses (as turf). Typically, copper sulfate pentahydrate crystals ar e used for root-killers. App lication directions recommend flushing 2 lbs of product (25.4% copper, appr oximately 0.51 lbs elem ental copper) down the toilet every 6 months to contro l tree root growth. This treatme nt is not recommended for septic systems. In some localities, sales of these pr oducts have been banned, as their use was found to contribute significantly to overall lo ading of copper in some watersheds

. Water contaminated with copper from use of these products is exp ected to be processed through water treatment facilities prior to release to receiving waters.

2.3 Environmental Exposure Strategy

Subdivision N guideline studies submitted to th e Agency are inappropriate to assess the environmental fate of inorganic copper com pounds because copper will not degrade in the environment. Copper applied as a pesticide is indistinguishable from na turally occurring copper species in the environment. However, Subdi vision N guideline studies are appropriate for organic Cu complexes because the organic por tion 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 singl e fate assessment. There are sufficient environmental fate data to use a chemical equilibria approach for assessing the environmental
fate of Cu 2+ . Uncertainties in the assessment are associated with chemical kinetics ( i.e. the rate ) of mineral precipitation-dissolu tion, oxidation-reduction, and comp lexation. This assessment addresses terrestrial food crop and direct aqua tic uses of Cu(II) salts, oxides, hydroxides, and complexes.

Cu(II) salts, hydroxides, and oxide s will dissociate to form Cu 2+ and a counter anion. The extent of dissociation is controlled by the solubility of th e 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 (Cu 0 ) 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 conditions 4 of the medium. The form in which Cu(I) or Cu(II) species is found depe nds on the pH of the medium and the nature and concentration of other chemical species th at can form Cu-containi ng species. For example, inorganic Cu (II) species that could Cu(II) salts, oxides and h ydroxides that may be found as soluble or insoluble species. Cu(I) species ma y include some oxides and hydroxides. In addition, Cu(I) or Cu(II) may form complexes with a variet y of naturally occurring ligands. However, the concentration of “free copper” is controlled by the pH of the medi um. When used as pesticides, (free Cu(II) ion) is released vi a 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 electr ical potential in millivolts (mV). It also controls the chemical forms of other compounds in the environment. Natural

Cu 0
Cu 2+
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

Cu 0
Cu 2+
Cu + Natural

Cu 0
Cu 2+
Cu + Cu (II)
Minerals Cu (I)
Minerals

Inorganic Cu Complexes Organic Cu Complexes

Figure 1

– Environmental Fate Bridging Strategy for Cu Minerals and Comple xes23 2.4 Site Vulnerability Analysis and Scenario Selection

Copper is used extensively as an orchard f ungicide, and orchard crops have the highest application rates, thus to assist in selecting s cenarios to estimate environmental concentrations, sites determined to be vulnerable were compar ed with locations of known orchard cultivation (Map 1). Based on AgCensus data availabl e from USDA, orchard production is heavily concentrated in California and Florida, Hawa ii, Washington state (Yak ima Valley), and Oregon (Willamette Valley). Other areas with significant orchard concentrations include southern Arizona and New Mexico, eastern Texas and Ok lahoma, western Michigan, western New York, southwestern Georgia and southeastern Alabam a, and an area along the Appalachian Ridge extending from Virginia to New York. Many of these areas appear to have vulnerable water
chemistries 5 based on the USGS data, including areas in the Pacific Northwest, California, South Central Texas, and New England.

Copper compounds are also currently registered fo r 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, bluebe rry) and vines ( e.g ., grapes). In ge neral, application rates for these crops are lower than for the orch ard crops. The number of crops for which copper compounds are registered means that copper exposu re from pesticide use may occur in virtually any agricultural area in the United States. Areas that are not within inte nsive orchard cultivation,
but which have vulnerable water chemistries ba sed on the USGS data include Southern Idaho, Colorado, sections of the Midwest, and the Easter n coastal plain. Certain areas of the Eastern coastal plain do grow some of the other hi gh use crops, such as tomatoes and peppers.

ARCMAP GIS software was used to analyze the si te water chemistry on a spatial basis. Sites that might be more vulnerable to copper toxi city (operationally de fined by EFED as DOC # 3.0 mg/L and/or alkalinity < 50 mg/L as CaCO 3 ) 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, th e Eastern Coastal Plain, the Pacific Northwest (Washington and Oregon), California’s Central Valle y, 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, gr oundwater, with lower ionic concentrations and DOC than most surface waters) or “drainage ditc h” (indicating possible clear water discharge, also with low ionic strength and DOC). Thus, these sites may overs tate the potential for risk in
the Southeastern Coastal Plain if they do not represent typical c onditions in surface waters. A significant number of sites in this area we re removed from the data set because water temperature was outside the range of the BLM. Th is area is expected to be somewhat vulnerable due to its generally low alkali nity, 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.D O C < 3 o r a l k < 4 5

U S G S s i t e s w i t h B L M d a t a

C r o p S c e n a r i o L o c a t i o n s
A C R E S

L e s s t h a n 2 5 0

2 5 1

- 9 9 9

1 0 0 0

- 2 4 9 9 9

2 5 0 0 0

- 4 9 9 9 9

5 0 0 0 0 o r m o r e 

## M a p 1 S i t e s P o t e n t i a l l y V u l n e r a b l e t o C o p p e r T o x i c i t y A n d C o u n t i e s C l a s s i f i e d b y A c r e s o f O r c h a r d s

0 2 0 0 4 0 0 6 0 0 8 0 0 1 0 0 M i l e s C o p p e r s A s s e s s m e n t C r e a t e d b y : P D B 0 6 / 1 0 / 0 5 U S E P A/ O P P / E F E D D a t a S o u r c e s : C h e m i s t r y : U S G S N A S Q A a n d N A S Q A N C r o p s : 1 9 9 7 U S D A A g C e n s u s25 2.5 Assessment Endpoints

Because the active ingredient of Cu(II) mineral salts, hydroxides, oxides, and Cu(II) complexes
is Cu 2+ , a unified risk assessment approach was formed for the pesticides addressed in this risk assessment. Therefore, an important considerati on in the risk assessment is the use site of the various pesticides. The assessment endpoints w ill be addressed as separate components: endpoints affected by agricultura l uses, endpoints affected by di rect 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 reasonabl y be expected to be high enough to directly affect the resident organisms. Because coppe r continues to cycle, potential effects from
environmental sinks such as soil a nd sediment are also considered.

Agricultural Uses For typical crop and orchard applications, the ecosyst em at risk is the field and adjacent aquatic and terrestrial environments that might be a ffected 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 wate r body, pelagic and benthic elements will be
considered. Terrestrial evaluations will include n on-target insects, soil invertebrates, birds, and mammals. Copper has the potential to bioaccumul ate 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 downs tream outlet of the water body, if one exists. Within the water body, compartments of concer n are the water column, sediments, and pore water. Organisms of concern in clude aquatic plants (algae and va scular), aquatic invertebrates, fish, amphibians, and birds or mammals which may rely on the reservoi r 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 concer n. 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 consider ed 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 (a lgae and vascular), a quatic invertebrates, fish, and amphibians.26 2.5.2 Ecological Effects

Evaluation of ecological effects w ill focus initially on the direct e ffects 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 ch ain, decrease in community diversity) will be evaluated based on the group of organisms exceeding the LOC.

Direct
Direct effects to be evaluate d 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 incl ude aquatic plants (algae and vascular), aquatic invertebrates, aquatic vertebrates, terrestr ial plants, terrestrial i nvertebrates, birds, and mammals. Exposure routes may vary dependent on t ype 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 di rectly to water, co mmon indirect effects include a decline in primary produc tivity, and a potential shift in community composition. If the endangered species direct effect LOCs are ex ceeded, effects on the food chain, and habitat quality will be assessed as necessary. In Florid a, copper has been associated with a decline in the primary food source of th e endangered snail kite (Rostrhamus sociabilis) (Eisler 2000). In areas where aquatic plants ar e 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 develope d for agriculatural uses (Figure 2), and direct water applications (Figure 3.) Models are shown on the following two pages.27Figure 2-Conceptual Model for Orchard and Row Crop ApplicationsCopper applied to cropStressorSourceRunoffDirect applicationSpray driftReceptorsBirdsMammalsTerrestrialinsectsIndividual organismsReduced survivalReduced growthReduced reproductionFood chainReduction in primary productivityReduction in preyShift in community compositionHabitat integrityReduced coverCommunity changeAttributeChangeAquaticplantsinvertebratesvertebratesTerrestrialplantsSoil accumulation,leaching and runoffSoilinvertebratesTerrestrial exposureRoutes include:Dermal contactDietFigure 2-Conceptual Model for Orchard and Row Crop ApplicationsCopper applied to cropStressorSourceRunoffDirect applicationSpray driftReceptorsBirdsMammalsTerrestrialinsectsIndividual organismsReduced survivalReduced growthReduced reproductionFood chainReduction in primary productivityReduction in preyShift in community compositionHabitat integrityReduced coverCommunity changeAttributeChangeAquaticplantsinvertebratesvertebratesTerrestrialplantsSoil accumulation,leaching and runoffSoilinvertebratesTerrestrial exposureRoutes include:Dermal contactDiet28Figure 3-Conceptual Model for Direct Water ApplicationIndividual organismsReduced survivalReduced growthReduced reproductionFood chainReduction in primary productivityShift in community compositionHabitat integrityReduced coverDO decreaseAttributeChangeCopper applieddirectly to waterWater columnSedimentsStressorSourceReceptorsAlgaeVascular PlantsBenthicinvertebratesPelagic invertebratesAquatic vertebratesPorewaterFigure 3-Conceptual Model for Direct Water ApplicationIndividual organismsReduced survivalReduced growthReduced reproductionFood chainReduction in primary productivityShift in community compositionHabitat integrityReduced coverDO decreaseAttributeChangeCopper applieddirectly to waterWater columnSedimentsStressorSourceReceptorsAlgaeVascular PlantsBenthicinvertebratesPelagic invertebratesAquatic vertebratesPorewater29 2.7 Risk Hypotheses

Copper containing pesticides may pose a variet y 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 agricultu ral areas and direct applica tion may reduce populations of aquatic plants, aquatic inve rtebrates, or fish, causing changes in the community.

• Copper in runoff from agricultural areas a nd direct application may accumulate in sediments, resulting in chronic impacts to the benthic community.

• Copper in runoff from agricultural areas a nd 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 s ite chemistry. An effort has been made to examine a wide variety of sites, with spec ial 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 decreas e the risk associated with the site.

• Copper is an element, thus it will continue to cycle in the envi ronment indefinitely. Changes in site conditions over time will aff ect copper availability and toxicity, and may
increase or decrease the risk associated with the site.

• Copper exists in the environment as a natura l background element. While this has been
taken into consideration in the risk assessment, localized enri chment 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 pest icides, and anthropog enically elevated concentrations may occur in or near pesticide us e 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 functi ons for the organisms assessed, and the regulatory mechanisms controlling copper homeost asis are complex. T oxicity of copper to organisms in the wild may be under- or over-estimated by available toxicity data.

• In certain instances, metal toxicity is additi ve, and in other instan ces exposure to other metals may convey some protection to the organi sm (i.e., induction of metallothioneins). The effect of multiple metals is not within the sc ope of this assessment. The assessment may underor over-estimate the effects of copper in these si tuations but is more likely to under-estimate the
risk than over-estimate it.30 • Natural genetic variability in wild organism s 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, so me 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 wa s conducted (Jones and Hetrick, 11/7/91) in support of the 1994 registration decision for copper . Because this earlier assessment did not
consider Cu 2+ complexation by organic ligands and its effect on Cu speciation as well as representative national water quality conditions for ambient su rface water, a refined exposure assessment was conducted using the Biotic Liga nd Model (BLM) in conjunction with USGS water quality monitoring data. Th e USGS monitoring data are expect ed to be representative of water quality conditions in ambient su rface waters across the United States.

3.1.1 Agricultural Uses

The environmental fate of metallic copper is de pendent on oxidation of elemental Cu to form either cuprous (Cu + ) or cupric (Cu 2+ ) ions. Elemental Cu is oxidized to form Cu + ions at redox potentials of pE 6 > 8.87 and Cu 2+ ions should form at pE > 5.745 (Lindsay, 1979).
Concentrations of soluble Cu 2+ 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, CuSO 4 , metallic copper, c opper chloride, copper oxychloride sulfate, copper ammonium carbonate, and copper carbonate are also used as fungicides on terrestrial food crops. These uses allow direct applicati on of copper salts into
terrestrial environments. C opper (II) salts in soil are expe cted to dissociate into Cu 2+ 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 chem ical species that may form complexes with Cu(I). Cupric (Cu 2+ ) ions will predominate free Cu ion in well aerated (pe+pH >9.62 at pH 7) soil environments. The fate of Cu 2+ 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 Cu 2+ has a high binding affinity for soil, the Cu 2+ ion is not expected to move into ground waters. However, applied Cu may move fr om 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 th e water quality of surface wate rs is dependent on water pH, alkalinity, and dissolved organic carbon.

6 pE= Eh (millivolts)/59.232 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 dire ct 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:wat er partitioning, and the BLM incorporates the effects of copper speciation. Based on inform ation provided during publ ic comment, direct water applications in ponds, la kes, and embayments, are genera lly applied in bands near the shoreline, or only to a portion of a smaller wa terbody (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 CuSO 4 and hence complete dissociation of CuSO 4 is expected. Chelated coppers may take longer to dissociate, and may remain suspended in the water column l onger. The 1 ppm concentration is used as an upper bound for the chelated compounds. On ce dissociation occurs, the soluble Cu 2+ ion will become incorporated into the natural copper cycl e within the aquatic envi ronment. Eventually, the introduced, soluble Cu 2+ concentration will approach ambi ent, soluble Cu concentrations because of binding to sediments. Partitioning coefficients of Cu 2+ can range from 100 to 100,000 L/kg in soil and sediments. The actual di ssipation time of "int roduced", soluble Cu 2+ depends on the physicochemical properties of th e aquatic environment (pH, water hardness, redox conditions, etc )

. Data from aquatic field dissipation studies indicate a rapid dissipation rate (t 1/2 = 10 days) for the "introduced", solubl e Cu. It is important to recognize Cu 2+ 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 b ackground 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 factor s have been taken into consideration when calculating and evaluating sedime nt 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) mi nerals 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 Ca 2+ , Mg 2+ , Mn +4 , Fe 3+ , Zn 2+

, etc .) as well as environmental redox and pH conditions (Lindsay, 1978). The fate assessment for Cu ligands is focused, when possible, on the theoretical chemi cal equilibria of the Cu-ligand species with competing cations and the behavior of the c ounter ligand in the environment. Because Cu 2+ is considered the active ingredient of the Cu (II) compounds and complexes, the estimation of33 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 EEC 1 (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 49.9 2

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 Defined 3 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 deve loped from PRZM/EXAMS estimated a single year, peak Cu 2+ concentrations in the standard farm pond and from
Cu 2+ applications rates (lbs Cu 2+ /A) on representative crops (Figure 12). 2- Assumes application in 1 ha standard smal l 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(NH 3 ) 4 2+ . This complex is formed through a reaction of Cu 2+ and ammonia (Cu 2+ + 4NH 3 : Cu(NH 3 ) 4 2+ ). The stability constant for Cu(NH 3 ) 4 2+ formation is 1.20 X 10 13 moles/dm 3 (Log K= 13.079 moles/liters) (http:/www.chemguide.co.uk/ inorganic /c omplexations/stabconst.html).

Copper triethanolamine complex, Copper ethylene diamine, Copper ethanolamine complex

Chemical equilibria of Cu triethanolamine (Cu-TE A) 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 et hylene 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 comp lexes is unknown at this time. No fate data34 has been submitted for ethylene diamine and triethanolamine. However, open-literature data suggest amine complex should degrade through microbial-mediated processes. Degradate identities and degrada tion 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 a nd non-food crops includin g avocados, berries, cherries, citrus, grapes, mangoes, peaches, nectar ines, strawberries, walnuts beans, broccoli, potatoes, azaleas, pine, junipers, and maples. The registrant also submitted environmental fate data from Arizona Chemical (Regulatory Bulle tin #3-Biodegradability) and open scientific
literature. The data indicate that fatty acids (oleic, linoleic, an d stearic acids) and resin acids (abietic, palustric, and pirmaric acids) are rapi dly degraded by microbial -mediated mineralization (80 to 85% degradation for 7-days in sewage slud ge). The registrant also submitted data from the open-literature on environmenta l chemistry of Cu and biological effects of resin acids. These
data indicate abietic acid and its dime r dihydroabietic acid can be metabolized by
Flavobacterium resinovorum and Pseudomonas resinovorans . These organisms can metabolize
rosin acids from Pinus maritima , methyl abietate, dehydroa bietic acid, neobietic, and levopimaric acids. However, the organisms coul d not completely metabolize tetrahydroabietic acid, daniellic acid, sclaeol, dipterocar pol, cholesterol, and rosin esters.

Rosin acids are a complex mixture of organic aci ds 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, le vopimaric acid, nonabietic acid, pa lustric acid, dehydroabietic acid, dihydroabietic acid, tetrahydr oabietic 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 W east, 1968). Abiatic acids may be metabolized by lactic and butyric bacteria. (M erck, 1983). Based on the cited li terature, rosin acids may have a low binding affinity to soil/sediments because ro sin acids should be an anionic species in most environments. Low soil/sediment binding affini ties are expected for compounds with carboxylic function groups. The degradation of rosin ac ids 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)

Conventional 7 urban uses of copper-contain ing 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 “Dow n 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 tr eatment. Concentrations in receiving waters
are estimated based on flow recurrence even ts, 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-v olume waterbody. To calculate risk quotients, the BLM was used to es timate copper activity based on the median water chemistry of the USGS monitoring sites, and then compared to the activity associated with the site-specific invert ebrate and fish LC 50 s.

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 di ssolved organic carbon (DOC) a nd 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 estim ation of peak concentrations of Cu 2+ . The estimation of 21-day average concentration wa s estimated using a 10-day aerobic aquatic metabolism half-life to mimic rapid dissipati on 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 Cu 2+ concentrations in the water colu mn and sediment pore water. Vapor pressure and Henry’s Constant we re assumed to be extremely low to mimic the elemental nature
of Cu.

For terrestrial uses of copper, off-site moveme nt of introduced copper was estimated using the PRZM/EXAMS models [PE4V1(8/13/03) sh ell 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 geographi c conditions and use rates ( Table 7). Use rates for CuSO 4 , CuSO 4 *5H 2 O, 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 inte rvals were generally not specified on labels. Therefore, unless

7 Defined as uses that are not antimicrobial in nature. An timicrobial pesticides, and uses in pools will be addressed in a separate action by the Antimicrobials Division.36 otherwise specified on the labe l, the modeling was conducted us ing 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 25 0 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 m 3 /mole Default to eliminate volatilization

Hydrolysis T 1/2 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

PA 19 2.24 4 25-March 7 Apples

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 determined38 3.2.2 USGS Monitoring Data and BLM Water Chemistry Parameters

Because the PRZM/EXAMS model cannot accoun t 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 in clude water temperature, pH, Cu concentration ( : g/L), dissolved organic carbon (DOC) concentr ation (mg/L), humic acid (%), sulfate (SO 4 2- ) concentration (mg/L), calcium (Ca 2+ ) concentration (mg/L) , magnesium (Mg 2+ ) concentration (mg/L), potassium (K + ) concentration (mg/L), chloride (Cl-) concentration (mg/L), alkalinity (CaCO 3 equivalence mg/L), and sulfide (S 2- ) concentration (mg/L). Parameters for the BLM model were populated using USGS water qual ity monitoring data fo r filtered water ( Table 8). The monitoring data provided all data input pa rameters except the humic acid percentage. Humic acid percentage was assume d to be correlated to the DOC concentration using a firstorder regression equation (humic acid per centage= 9.9155 + 1.6892*DOC). This regression equation was derived using the low and hi gh 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 cen sored to remove all samples with water input parameters outside the range of the model. Th e censored USGS water quality data were further analyzed using Statistical Analysis System (SAS) to derive site specific descriptive statistics including mean, median, minimum, maximum, a nd standard deviation. Median water quality
conditions for 811 sites were used in the BLM m odel 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 repres ent the conditions most likely to occur. Variability across sites is expected to be greater than variabil ity at a single site.

Additionally, the USGS provided m onitoring data on total digestible Cu in suspended sediments
to assess ambient Cu concentrations in sediment s. These data were used to estimate ambient concentrations of Cu in sediment and sediment pore water.

PRZM-EXAMS estimated Cu concentrations (pea k and 21-day average concentration) for low
K d (sand soil) and high K d (clay soil) for each crop scenario were used as the Cu input
concentration in the BLM model. Median wate r quality conditions for 811 sites provided the water chemistry for the BLM model. BLM si mulations provided an estimation of the Cu 2+ 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 paramete rs are discussed in more detail.39 Table 8 Summary of USGS Water Quality Data Used in the BLM 1

Parameter Units Data Range for
BLM Missing
Data Low Value High Value Median
Value Average
Value

Temperature 0 C 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 Acid 2 % 10 to 60 0 10 29.15 14.90 16.69

Ca 2+ mg/L 0.204 to 120.24 0 0.95 114 37.6 40.62

Mg 2+ 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

SO 4 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

S 2- mg/L ND 811 ND ND ND ND

1- Data represent median site wate r 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. Th e 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 ap proximation because it does not consider site specific factors on water pH such as aci d mine drainage, karst regions, etc.40 pH 456789 10 C u m u l a t i v e P r o b a b i l i t y

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 th ere were several samples with extremely high DOC values (>29.65 mg/L). The high DOC values ar e suspected to be associated with methanol contamination from rinsing sampling equipm ent. As a consequence of the possible contamination, the samples with high DOC va lues (>29.65 mg/L) were removed from the BLM input parameter data set to a void unreliable estimation of Cu 2+ activities. The median DOC concentration was 3 mg/L. Although the DOC c oncentration in surface water should be site specific, GIS analyses suggest re gional differences in DOC. Site s 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 C u m u l a t i v e P r o b a b i l i t y

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.041 Water alkalinity ranged from 2 to 311 mg CaCO 3 equivalence/L. Median water alkalinity is 116 mg/CaCO 3 equivalence/L. Alkalinity in surface wa ter appears to be regionally dependent. Higher alkalinity values (>117 mg/L) were gene rally found in the centr al 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 surf ace 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 sli ghtly 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 Plat te 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 vulnerabl e sites using th e 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 to tal Cu concentrations was highly skewed toward lower concentrations (<100 : g/g). Alkalinity (mg/L) 0 50 100 150 200 250 300 350 C u m u l a t i v e P r o b a b i l i t y

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.042 Sediment pore water concentrations were estimated using a simple partitioning model (K d =C sediment /C water ) using the suspended sediment Cu concentration as the C sediment . This estimation approach assumes 100% of the Cu on th e suspended sediment is readily exchangeable with the pore water. Maximum pore water concen trations for sediments could range from 528 to
4750 : g/L. Median sediment pore water concentrat ions 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) μ g/g 1278 1 1900 22 39

Estimated Cu in

Pore Water 1
(K d =3.6L/g) μ g/L 1278 0.2 528 6 11

Estimated Cu in

Pore Water 1
(K d =0.4 L/g) μ g/L 1278 3 4750 55 99

1- Estimation assume equilibrium with Cu on suspended se diment. 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 predicte d using the PRZM/EXAMS simulations. As expected, these simulations show Cu accumulati on 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 desc ribe the concentration of introdu ced 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 K d 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)

Low Kd High Kd Low Kd High Kd Crop State

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

PA 3529 256.3 817.9 168.4 350 119 365 26.8 119.92 Apples

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 33.9744 The state average application rates reduced the application rates and he nce cause a reduction in water column concentrations ( Table 11). As expected, the PA a pple scenario had the highest Cu concentration (41.2 : g/L) and accumulation rate (14.14 : g/L/year).

Table 11 Estimated Water Column Dissolved Copp er Concentrations Based on State Average Rates

1-in-10 year Concentration (ug/L) First Year Concentration (ug/L)

Low Kd High Kd Low Kd High Kd Crop State

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

PA 416.5 31.3 96.4 19.9 41.2 14.1 43 3.2 14.14 Apples

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 3.9845 Table 12 Estimated 60-day Water Colu mn 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

PA 212.6 153.6 74.6 16.5 25.5 18.2 8.8 1.9 Apples

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 calculated46 3.2.4 Spray Drift Exposure Estimates

A screening level spray drift analysis was conducted to assess the impact of Cu 2+ drift from terrestrial crop uses on aquatic e nvironments. The analysis assume s drift loadings of 5% of the application rate for aerial spray and 1% of a pplication rate for ground sp ray, into the standard farm pond used in EXAMS. Estimated Cu 2+ loading and peak Cu 2+ concentration are shown in
Table 13 and Table 14.

Table 13 Aerial Spray Drift Loadings

Application Rate (kg Cu 2+ /ha) Cu 2+ Drift Loading (kg) Estimated Peak Concentration 1 ( μ g/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 Cu 2+ in the standard farm pond (20E6 liters).

Table 14 Ground Spray Drift Loadings

Application Rate (kg Cu 2+ /ha) Cu 2+ Drift Loading (kg) Estimated Peak Concentration 1 ( μ g/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 Cu 2+ in the standard farm pond (20E6 liters).47 3.2.5 PRZM/EXAMS Output-Sediment Pore Water Cu Concentrations

Sediment pore concentrations were pred icted 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 exposu re assessment. Therefore, the reported data attempt to describe the concentration of introduc ed 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 K d 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)

Low Kd High Kd Crop State

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

PA 44.7 1740 6.35 240 59.11 8.07 Apples

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 4.5249 3.2.6 Evaluation of Aquatic Exposure Modeling

Recognizing that PRZM was originally design ed to estimate concentrations of organic compounds commonly used in pestic ides, EFED compared open litera ture with measured copper concentrations in runoff to ensure PRZM predic tions appeared reasonable. As a cross-check on the ability of the BLM to estimate Cu 2+ concentrations in surface waters the estimate concentrations were compared to Cu mineral stability diagrams

Field Monitoring Observations

Open literature data indicate that agronomic mana gement techniques (such as vegetative furrows, vegetative mulch, black plastic mulch) can lim it 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 o ff-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/m 2 ) 85,259 1,009 129

Runoff Volume (L/m 2 ) 0.1-to-101 1 14-76 2 (vetch) 13.7-147 (plastic) 34-143

Soil Erosion (g/m 2 ) 0.2- to-10,500 1

median=90 average=340 38.7-118 2 (vetch) 247-535 (vetch) 0.1-730

Total Edge-of-Field Cu (mg/m 2 ) 0.0001 to 58.7 1

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 K d and high K d assumptions.
2- Runoff volumes were calculated on seasonal basis or annual basis.50 Although the PRZM modeling (a PA apple scenario) and field monito ring studies were similar in geographic location, PRZM modeling was based on higher application rates than the field studies. The comparisons of erosion rates a nd runoff volumes are based on similar mass/volume per unit area (m 2 ) 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 th e PRZM simulation for the PA apple scenario are within the range of runoff a nd erosion estimates in the field studies. The
distribution of erosion events in dicates a highly skewed distribu tion due to a few extremely high erosion events (10,500 g/m 2 ). However, average erosion losse s 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 eros ion losses coupled with the high Cu application rates in the PRZM simulati on led to a few events with high losses of Cu. The Cu partitioning in runoff water and suspende d sediment was similar for the PRZM modeling and actual field monitoring data. As expecte d, 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:

• Cu 2+ concentrations above some known Cu mineral stability boundaries suggest supersaturation of the Cu minerals;

• Cu 2+ concentrations below some known Cu mineral stability bounda ries suggest under saturation to the Cu minerals; and

• Cu 2+ concentrations on a known Cu minera l 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 Cu 2+ ion is the predominant ion due to oxic nature (pE+pH> 12) of surface water. Thes e conditions were assumed because aquatic organisms require oxygen for norma l biological function. Cupric (Cu 2+ ) ion activities in ambient surface waters suggest chemical equilibria conditi ons 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 scenar io, exceed the solubility of CuO (tenorite) under51 neutral and alkaline pH conditions. In acidic surface waters, however, Cu 2+ 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 Cu 2+ in sediment pore water (Figur e9) were constructed under the premise the surface sediment (<5 cm depth) is an oxic (pE+pH >12) environment. These
conditions were assumed because benthic or ganisms 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 Cu 2+ activities in sediment pore waters is dependent on the sorption potential of the
sediment. Low K d sediments such as sands may have Cu 2+ activities supersaturated to CuO (tenorite) in neutral and alkaline pore waters of surface sediments. High K d sediments such as clay may have Cu 2+ activities are supersaturated to cupric ferrite in equilibrium with soil Fe. In acidic sediments, however, Cu 2+ activities are approaching equilib rium with cupric ferrite in equilibrium with amorphous Fe(OH) 3 or soil Cu regardless of the K d of the sediment for Cu. One interesting observation is that estimated Cu 2+ 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 e nvironments (pE +pH < 5), chalcocite (Cu 2 S) is expected to control Cu activiti es. Based on water quality parame ters in the USGS monitoring data, chalcocite precipitation is expected to o ccur 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 Wa ters on Cu(II) Minerals Stability Diagram

Figure 8 : Cu Activities for the PA Apple Scen ario on Cu(II) Minerals Stability Diagram pH 3456789 10 11 C u A c t i v i t y ( m o l e s / l i t e r )

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 l o g C u A c t i v i t y ( m o l e s / l i t e r )

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 apples53 Figure 10 : Sediment Pore Water Cu Activ ities from USGS Monitoring Data on a Cu(II) Minerals Stability Diagram Suspended Sediment (Low Kd Sediments)

pH 3456789 10 11 C u 2 + A c t i v i t y ( m o l e s / l i t e r )

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 C u 2 + A c t i v i t y ( m o l e s / l i t e r )

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 Activity54 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 μ g/L ( Table 17). Higher Cu 2+ concentrations are expected for swimming pool water systems and sewage systems. These uses are not e xpected to directly impact aquatic ecosystems without some prior treatment process.

Table 17 Estimated Dissolved Copper Concen trations 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 pub lic comment period indicate that the majority of users treat only a portion of a small water body when appl ying copper-containing products for algae and aquatic weed control. Additional screening leve l modeling was conducted for direct applications
of Cu 2+ to aquatic environments. EXAMS 2.98.04 (7 /18/02) was employed to account for sediment:water partitioning and dissipation rates of Cu 2+ from the water column. The modeling scenario assumed the standard farm pond (20E 6 liters) in Florida (pond environment file w12842.dvf) treated at variable volumes with a target concentration of 1 ppm Cu 2+ . The modeling was conducted using a low K d sediment (K d =400) and aquatic di ssipation rate of 10 days. Two treatments were assumed, with an interval of 30 days. Applications of Cu 2+ were modeled for May 10 th and June 10 th

. Table 18 shows the variable volumes and the predicted peak Cu 2+ concentration in the water column.55 Table 18 Predicted Concentrat ions for Direct Applications

Percent of
Pond
Treated Cu 2+ Loading

(kg) Estimated Cu 2+

Concentration 1 ( μ g/L) EXAMS Predicted Peak
Cu 2+ Concentration ( μ g/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 wa s conducted to assess the impact of copper containing root inhibitors use in sewage systems on aquatic environments. No nati onal use data were available. EFED made the conservative assumption that ea ch household in the United States could apply copper sulfate crystals in accord ance with label instructions. The modeling approach employed the disposal model in EFAST 2.0. It was a ssumed 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 applica tion twice a year. This assumption equates to an estimated production mass of 4,940,366.7 kg Cu 2+

, in root killer product s. 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 Cu 2+ (1.8%) during sewage treatment, with the estimate based on copper sulfate. Selected exposure estimates were the 10 th percentile 7q10 8 for daily peak concentration and the 10 th percentile 30q5 for 21- and 60-day average concentrations ( Table 19).

Table 19 Estimated Cu 2+ in Receiving Waters from Root-Killer

Flow Frequency Dilution Factor Cu 2+

Concentration ( μ g/L) 7Q10 1.00 117.80 30Q5 1.80 65.45

8 The 10 th percentile 7Q10 is equal to the upper 90 th percentile concentration during 10-year return frequency for the 7-day lowest flow conditions. The 10 th percentile 30Q5 is equal to the upper 90 th 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 sulf ate (USEPA 1986a) waived and/or reserved the ecotoxicity studies for copper compounds, a lthough 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 ha ve been updated by EPA’s Office of Water (OW), and Office of Solid Waste and Emergency Res ponse (OSWER), based primarily on extensive review and analysis of open literature. To re main consistent with other EPA programs, EFED has incorporated new ecological effects eval uation 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 chem istry, with copper at its most
toxic in waters of low ionic st rength and/or low in dissolved or ganic carbon (DOC). The pH of the water also affects toxicity. The update d 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 comb ined speciation and toxicity m odel, allows calculation of toxicity values based on site sp ecific water chemistry. Using this model, OW developed genus, specific toxicity values for 27 genera of aqua tic organisms (Appendix E), in a normalized water chemistry. This species sensitivity distribution was used to establish the final acute value (FAV)
of 4.2 μ g/L dissolved Cu, and set the criter ia mean concentration (CMC) of 2.1 μ g/L dissolved Cu. Studies used by OW meet the ECOTOX criteria used by EFED for evaluating open literature. The BLM and draft Ambient Aquatic Li fe Criteria have been through the peer review process, and approved by Scientif ic Advisory Panel (SAP).

Although an overall water concentration criteria exists, and under the CWA, receiving waters must meet the criteria established by OW, ecol ogical risk assessments for pesticides require evaluation of potential risk to spec ific aquatic taxon: invertebrate s, 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 Unite d 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 LC 50 s for Daphnia magna (cladoceran, representing aquatic invertebrates), and Pimephales promelas (fathead minnow, representing fi sh). To ensure the risk assessment is as protective as possible of non-target species, EFED uses th e lowest scientifically defensible toxicity value avai lable. Daphnia were the most sensitive genera of aquatic invertebrates for which data were available, a nd the most sensitive aquatic species overall. Salmonids (genus Onchorynchus ; GMAV of 29.11 μ g/L) are the most sensitive fish species, but at the time of this assessment, the BLM had not yet been implemented to calculate the LC 50 for this genus, thus EFED elected to adjust the fathead minnow LC 50 s produced by the BLM by the
ratio of the Onchorynchus GMAV to the Pimephales GMAV (29.11 μ g/L:72.07 μ g/L;57 adjustment factor 0.404). One speci es of amphibian, the boreal toad (Bufo boreas; GMAV 49.06) was included in the genus di stribution used by OW to deve lop the criteria . The boreal
toad was less sensitive to c opper than the salmonid genus Onchorynchus , and it is unknown how sensitive this species is compared with othe r amphibians, thus the estimated Onchorynchus
LC 50 s were used to assess risk to amphi bians. The BLM does not evaluate LC 50 s for any aquatic plant species, although the Office of Water did lo cate acceptable open litera ture. These studies represent a wide range of endpoi nts and water chemistries, and much of the chemistry data required for the BLM is not included in the pape rs. Standard guideline studies (MRIDs) were submitted to EFED for aquatic plants. Laboratory test conditions (low DOC, moderate hardness, moderate pH) represent a moderate toxicity situ ation. The most sensitive aquatic plant species tested, the green alga, Selenastrum capricornutum , (LC 50 3.1 ppb) was selected to represent this taxa. The BLM was used in speciation mode to convert the LC 50 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 fr eshwater 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 Maxi mum Concentration (CMC) was calculated (to be protective of 95% of aquatic species ), toxicity values used to a ssess risk to specific genera are greater than the established CMC.

The minimum data requirements for chronic toxi city were not met, so OW elected to use the acute-to-chronic ratio (ACR) approa ch 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 repr esented in the species sensitiv ity distribution used by OW to
establish the saltwater criteria. This distri bution 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 st ages. 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 LC 50 of 12.66 ppb. Other fish species in the distribution (which included salmonids ) appeared to be less sensitive (LC 50 >85 ppb).

9 The criterion mean concentration (CMC) is the FAV divided by a safety factor of 2.58PRZM/EXAMSSIMULATIONS(Site SpecificScenarios)BioticLigandModel(BLM)Site SpecificUSGS Water QualityMonitoring DataEECS (mol Cu2+/L){Cu}water{Cu}sediment pore waterSite SpecificDaphnia magnaLC50(ppb)Trout.LC50(ppb)Exposure:DevelopingSite SpecificEECsEECs(ppb)[Cu]water[Cu]sediment pore waterBioticLigandModel(BLM)Effects:DevelopingSite Specific LC50sSite SpecificDaphnia magnaLC50(mol Cu2+/L)Trout LC50(mol Cu2+/L)Site SpecificRQsDaphnia magnaTroutFigure 10-Site Specific AquaticAssessment Using the BLMPRZM/EXAMSSIMULATIONS(Site SpecificScenarios)BioticLigandModel(BLM)Site SpecificUSGS Water QualityMonitoring DataEECS (mol Cu2+/L){Cu}water{Cu}sediment pore waterEECS (mol Cu2+/L){Cu}water{Cu}sediment pore waterSite SpecificDaphnia magnaLC50(ppb)Trout.LC50(ppb)Exposure:DevelopingSite SpecificEECsEECs(ppb)[Cu]water[Cu]sediment pore waterBioticLigandModel(BLM)Effects:DevelopingSite Specific LC50sSite SpecificDaphnia magnaLC50(mol Cu2+/L)Trout LC50(mol Cu2+/L)Site SpecificDaphnia magnaLC50(mol Cu2+/L)Trout LC50(mol Cu2+/L)Site SpecificRQsDaphnia magnaTroutFigure 10-Site Specific AquaticAssessment Using the BLM59 3.3.2 Aquatic Plant Guideline Data

Table 20 Aquatic Plant T oxicity Guideline Studies

Species LC 50 (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) 0.0031 a 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 whet her there is signif icant under-reporti ng of incidents.

Of the 24 reported incidents, 7 we re associated with terrestrial plants, and in all of the cases, certainty was rated as possible or probable. On e case, on tomatoes in Washington state, was in accordance with registered use. For the other incidents, affecti ng 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 incident s 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 registered 10 . The other incidents were ca ses 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 num ber of fish ranging from 100 to 1,000, except for one case in New York, where the report lists > 1,000,000 fish kille d. Fishes affected include carp, bass, trout, sunfish, perch, catfish, shiner, and mosquitofi sh. Other organisms reported

10 In cases where the legality of the application is unk nown, EFED makes the conservative assumption that the application was in accordance with registered use.60 include frogs, clams, and turtles. In all ca ses, effects reported were mortalities, but the mechanisms (direct toxicity or secondary eff ects such as low dissolved oxygen) were not specified.

3.3.4 Bioaccumulation

In developing the criteria, OW also ev aluated bioaccumulation. Copper is known to bioaccumulate, especially in aquatic inverteb rates 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 concentr ation of copper in the water, with higher BCFs occurring at lower concentrations. The im portance of copper bioaccumulation in aquatic
foodchains is not well established. Because c opper 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 laborator y 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 depe ndent on the chemistry of receivi ng 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 determinan ts of copper toxicity. Because water chemistry varies widely from region to region based on ge ology, 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 labor atory toxicity tests, EFED elected to evaluate aquatic copper toxicity using the Biotic Ligand Model (BLM) and water ch emistry data from USGS monitoring sites. Because DOC is so critical in determining toxi city, only sites with measured DOC data were
considered. The available data set was then cens ored 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 vari ed 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 LC 50 s 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, A ppendix 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 b een 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 calcula ted based on the Genus Mean Acute Values (GMAVs) for Onchorynchus (LC 50 =29.11 ppb, 7 species evaluated) and Pimephales (LC 50 =72.07, 1 species evaluated.) Estimated site specific LC 50 s for the fathead minnow were adjusted using this f actor, and the resulting estimated Onchorhynchus LC 50 was used to evaluate site specific risk to fish. EFED uses fish toxicity data to evaluate risk to aquatic vertebrates, including amphibian s. The draft Ambient Water Quality Criteria contained a GMAV for one amphibian, the boreal toad (Bufo boreas; LC 50 =49.06 ppb ), showing it to be less sensitive than the salmonids. Although it is un known 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, a nd 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-ch ronic ratio (ACR) of 3.23 for freshwater organisms, although insufficient data were availabl e to establish a saltwater ACR (USEPA 2003a). The BLM only estimates acute toxicity, so the ACR was applied to site specific LC 50 s for both the daphnids and salmonids to ge nerate site specific chronic toxicity
values.

3.4.2 Analysis of Site Chemistry

Some sites (448; 55.2%) had measured dissolved c opper data available. In cases where copper was detected, but below the limit of quantitat ion, 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 unk nown. For sites with measured ambient copper, the concentrations were compared to estimated Daphnia LC 50 values to determine if existing
concentrations exceeded the estimated Daphnia LC 50 12 . Ambient concentrations at 5 sites (2 in

11 The data were not assumed to be normally distributed, and the medi an represents a better estimator of central tendency in non-normal distributions.

12 This was intended as an exercise to evaluate the estimated LC 50 s, thus the comparisons were directly between the
measured concentration and the BLM estimated Daphnia LC 50 . 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 Illi nois) exceeded. The two sites in Colorado also exceed the salmonid site specific LC 50 values. The cause for hi gh copper concentrations is
uncertain.

Based on site chemistry, estimated Daphnia LC 50 s ranged from 0.3 to 1,900 ppb, but the majority of the sites (90%) were between 1 pbb and 200 ppb. Estimated Onchorynchus LC 50 s 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 sl ightly between the invertebrate a nd the fish, reflecting differences in the mode and strength of coppe r toxicity for the two taxa. Es timations 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.D a p h n i a

_ L C 5 0

_ p p b

< 1 0

1 0

- 4 9

. 9

5 0

- 9 9

. 9

1 0 0

- 1 9 9

. 9

> 2 0 0

0 3 0 0 6 0 0 9 0 0 1

, 2 0 0 1 5 0 M i l e s 

## M a p 2 E s t i m a t e d D a p h n i a L C 5 0 B a s e d o n W a t e r C h e m i s t r y a n d B L M

C o p p e r s A s s e s s m e n t C r e a t e d b y : P D B 0 6 / 1 0 / 0 5 U S E P A/ O P P / E F E D D a t a S o u r c e s : W a t e r C h e m i s t r y : U S G S N A W Q A & N A S Q A N D a p h n i a L C 5 0 : E s t i m a t e d b a s e d o n B L MT r o u t

_ L C 5 0

< 1 0

1 0

. 1

- 1 0 0

1 0 1

- 5 0 0

5 0 1

- 1 0 0 0

> 1 0 0 0

0 3 1 0 6 2 0 9 3 0 1

, 2 4 0 1 5 5 M i l e s 

## M a p 3 E s t i m a t e d T r o u t L C 5 0 B a s e d o n W a t e r C h e m i s t r y a n d B L M

C o p p e r s A s s e s s m e n t C r e a t e d b y : P D B 0 7 / 2 6 / 0 5 U S E P A/ O P P / E F E D D a t a S o u r c e s : W a t e r C h e m i s t r y : U S G S N A W Q A & N A S Q A N T o x i c i t y : C a l c u l a t e d b y B L MD i s s C u > D a p h n i a L C 5 0

m e d

_ c u

N o t m e a s u r e d

0

. 2

- 2

2

. 1

- 1 0

1 0

. 1

- 1 5

1 5

. 1

- 5 1

. 4

0 3 0 0 6 0 0 9 0 0 1

, 2 0 0 1 5 0 M i l e s 

## M a p 4 M e a s u r e d D i s s o l v e d C o p p e r

a n d E s t i m a t e d D a p h n i a L C 5 0

C o p p e r s A s s e s s m e n t C r e a t e d b y : P D B 0 6 / 1 0 / 0 5 U S E P A/ O P P / E F E D D a t a S o u r c e s : W a t e r C h e m i s t r y : U S G S N A W Q A & N A S Q A N D a p h n i a L C 5 0 : E s t i m a t e d U s i n g B L M66 3.4.3 RQ Summary for Agricultural Uses

Orchard Application-Label Rates

As an initial screening, EFED compared all sites to a scen ario producing the highest runoff concentration of copper (Pennsylva nia apples, application rate 19 lb a.i./acre, Cu concentration 350 ppb). 13 Two variations on the scenario were run, one with a low K d (less sorption of copper to the soil), and one with a high K d (greater sorption of copper to the soil). Estimated peak environmental concentrations (EECs) were 350 ppb and 365 ppb 14 . 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 en dpoint, 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 a quatic plants, invertebra tes, and fish. RQ
summaries for the low K d estimate are shown below.

Table 21 Aquatic RQ Summary Table: Orchard Label Rates

Endpoint for RQ Minimum RQ Median RQ Maximum RQ Sites Exceeding
LOC 1 Sites Exceeding Endangered Species
LOC 1

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 K d scenario, for all other scenarios, low Kd concentrations were higher, thus to maintain consistency throughout the assessment, the low K d value (350 ppb) was
used.67 Row Crop Applications - Label Rates

As an initial screening, EFED compared all sites to a scen ario producing the highest runoff concentration of copper (Maine po tatoes, application rate 3.56 lb a.i./acre, Cu concentration 54.9 ppb). Two variations on the scenario were run, one with a low K d (less sorption of copper to the soil), and one with a high K d (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) we re 22.8 ppb and 4.9 ppb. EECs at 60-days post application were 17.3 ppb and 3.5 ppb. RQs were calc ulated 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 exceed ed 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 K d ) 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 = 1.068 Analysis Based on Average Applied Rates

As a number of the copper compound labels we re difficult to interpret, and calculated applications rates for some labe ls were extremely high, EFED opted to also calculate RQs based on average application rates s upplied by BEAD. Using the aver age rates, the Pennsylvania apples and Maine potatoes scenarios again produced the highest Cu concentrations in runoff. As with the labeled rates, runoff concentrati ons were compared to all USGS sites.

Orchard Applications The highest estimated runo ff concentration (low K d ) for orchard applications was Pennsylvania apples. Estimated peak environmental c oncentration (EEC) was 41.2 ppb. Estimated 21-day environmental concentration (EEC) wa s 14.1 ppb. Estimated 60-day environmental concentration (EEC) was 8.8 ppb. RQs were calcu lated 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 exceed ed 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 = 1.069 Row Crop Applications The highest EEC (low K d ) for row crop applications was 13.8 ppb, for Maine potatoes. The 21- day EEC was 5.5 ppb. Estimated 60-day enviro nmental concentrati on (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 a quatic 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 th e 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%P A

_ a p p l e s

< 0

. 0 5

< 0

. 5

> = 0

. 5

0 3 1 0 6 2 0 9 3 0 1

, 2 4 0 1 5 5 M i l e s C o p p e r s A s s e s s m e n t C r e a t e d b y : P D B 0 6 / 1 0 / 0 5 U S E P A/ O P P / E F E D D a t a S o u r c e s : W a t e r C h e m i s t r y : U S G S N A W Q A & N A S Q A N D a p h n i a L C 5 0 : E s t i m a t e d U s i n g B L M 

## M a p 5 D a p h n i a A c u t e R i s k Q u o t i e n t H i g h e s t R u n o f f f o r O r c h a r d U s e L a b e l A p p l i c a t i o n R a t e s

P e a k r u n o f f 3 5 0 p p bM E

_ p o t a t o e s

< 0

. 0 5

< 0

. 5

> = 0

. 5

0 3 1 0 6 2 0 9 3 0 1

, 2 4 0 1 5 5 M i l e s C o p p e r s A s s e s s m e n t C r e a t e d b y : P D B 0 6 / 1 0 / 0 5 U S E P A/ O P P / E F E D D a t a S o u r c e s : W a t e r C h e m i s t r y : U S G S N A W Q A & N A S Q A N D a p h n i a L C 5 0 : E s t i m a t e d U s i n g B L M 

## M a p 6 D a p h n i a A c u t e R i s k Q u o t i e n t H i g h e s t R u n o f f f o r R o w C r o p U s e L a b e l A p p l i c a t i o n R a t e s

P e a k r u n o f f 5 5 p p bP A

_ a p p l e s

< 0

. 0 5

< 0

. 5

> = 0

. 5

0 3 1 0 6 2 0 9 3 0 1

, 2 4 0 1 5 5 M i l e s C o p p e r s A s s e s s m e n t C r e a t e d b y : P D B 0 6 / 1 0 / 0 5 U S E P A/ O P P / E F E D D a t a S o u r c e s : W a t e r C h e m i s t r y : U S G S N A W Q A & N A S Q A N D a p h n i a L C 5 0 : E s t i m a t e d U s i n g B L M 

## M a p 7 D a p h n i a A c u t e R i s k Q u o t i e n t H i g h e s t R u n o f f f o r O r c h a r d U s e A v e r a g e A p p l i c a t i o n R a t e s

P e a k r u n o f f 4 1 p p bM E

_ p o t a t o e s

< 0

. 0 5

< 0

. 5

> = 0

. 5

0 3 1 0 6 2 0 9 3 0 1

, 2 4 0 1 5 5 M i l e s C o p p e r s A s s e s s m e n t C r e a t e d b y : P D B 0 6 / 1 0 / 0 5 U S E P A/ O P P / E F E D D a t a S o u r c e s : W a t e r C h e m i s t r y : U S G S N A W Q A & N A S Q A N D a p h n i a L C 5 0 : E s t i m a t e d U s i n g B L M 

## M a p 8 D a p h n i a A c u t e R i s k Q u o t i e n t H i g h e s t R u n o f f f o r R o w C r o p U s e A v e r a g e A p p l i c a t i o n R a t e s

P e a k r u n o f f 1 4 p p bC A

_ a l f a l f a

< 0

. 0 5

< 0

. 5

> = 0

. 5

0 3 1 0 6 2 0 9 3 0 1

, 2 4 0 1 5 5 M i l e s C o p p e r s A s s e s s m e n t C r e a t e d b y : P D B 0 6 / 1 0 / 0 5 U S E P A/ O P P / E F E D D a t a S o u r c e s : W a t e r C h e m i s t r y : U S G S N A W Q A & N A S Q A N D a p h n i a L C 5 0 : E s t i m a t e d U s i n g B L M 

## M a p 9 D a p h n i a A c u t e R i s k Q u o t i e n t L o w e s t R u n o f f f o r R o w C r o p U s e L a b e l A p p l i c a t i o n R a t e s

P e a k r u n o f f 2 p p b75 Analysis Based on Spray Drift

Peak concentrations of Cu 2+ from spray drift were speciated using BLM model to estimate the
concentration of ionic Cu 2+ . Median USGS monitoring site wa ter quality data for 811 sites were used as input parameters for the BLM mode l (Appendix C). Risk quotients were estimated [activity of Cu 2+ (site 1....811 )/LC50 (site 1....811 )] for each site for rainbow trout and Daphnia magna

. The individual site RQs were ranked to determ ine the number of sites exceeding the acute risk LOC of 0.5 and the endangered spec ies acute risk LOC of 0.05.

Site exceedences of aquatic LOC and ES a quatic LOC were found for both ground and aerial spray drift loadings. As expected, the num ber of site exceedences were greater for Daphnia

magna than for rainbow trout. This observation is due to the higher toxicity (lower LC 50 ) of
Cu 2+ to Daphnia magna . Figure 11 and 12 illustrate LOC exceed ences as function of application rate for aerial spray drift loadings. Figure 13 and 14 illustrate LOC exceedences as function of application rate for grou nd spray drift loadings.

Single Application Rate (lbs Cu 2+ /A) 0 10 20 30 40Percentage of Sites Exceeding the Acute LOC=0.5

0 20 40 60 80 100

Rainbow Trout Y=-1.3864+ 0.3475*X, R 2 =0.9434 D a p h n i a

m

a g n a

Y

= 4

. 7 5 9 1 + 2

. 2 8 7 2 *X

, R 2 =

0

. 9 6 2 6

Figure 11 Percentage of Sites Exceedi ng Acute Risk LOC, Aerial Spray Drift76 Single Application Rate lbs Cu 2+ /A) 0 10 20 30 40Percentage of Sites Exceeding the ES Acute LOC=0.05

0 20 40 60 80 100

R a i n b

o w T r o

u t

Y

= - 1

.

8 7 5 6 + 1

. 1 9 5 1 * X , R 2 =

0

.

9 9 6 2 Daphnia magna Y=98.7932(1-e -0.2313*X ), R 2 =0.9887

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

Single Application Rate (lbs Cu 2+ /A) 0 10 20 30 40Percentage of Sites Exceeding Acute LOC=0.5

0 5 10 15 20 25

Rainbow Trout
Y=-0.1772 +0.361*X R 2 =0.8785 D

a p h n i a

m

a g n a

Y

= - 0

. 5 5 2 8

+ 0

. 6 4 4 4 * X

R 2 =

0

. 9 9 6 7

Figure 13 Percentage of Sites Exceed ing Acute Risk LOC, Ground Spray Drift77 Single Application Rate (lbs Cu 2+ /A) 0 10 20 30 40Percentage of Sites Exceeding ES Acute LOC=0.05

0 20 40 60 80 100

Rainbow Trout Y=-0.2842 + 0.1481*X, R 2 =0.95 D a p h n i a

m

a g n a

Y

= 8

. 4 1 5 + 2

. 3 2 9 * X

, R 2 =

0

. 9 3 8 7

Figure 14 Percentage of Sites Exceedi ng ES Acute Risk LOC, Ground Spray Drift

Based on the fitted regression equations, the estimated Cu 2+ application rate to equivalent to a
10% site exceedence are shown in.

Table 25 Estimated Application Rates 1 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 Cu 2+/ 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 representa tive of the potential range of wate r 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 coppe r concentration is approximately 1 ppm (1,00078 ppb) although it varies dependent on site water chemistry and target alga species. Site-specific copper activities and risk quotient s were calculated for the maximum label rate of 990 ppb, as
shown in Table 26. The estimated average 21-day con centration 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 invertebrate s, and fish are exceeded at >96% of the sites.

Table 26 Aquatic RQ Summary Ta ble: 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 Cu 2+ for 1961 weather data were speciated using the
BLM model to estimate the concentration of ionic Cu 2+ . Median USGS monitoring site water quality data for 811 sites were used as input pa rameters for the BLM model (Appendix C). Risk quotients were estimated [activity of Cu 2+ (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 endange red 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 observati on is due to the higher toxicity (lower
LC 50 ) of Cu 2+ 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 100Site Exceedance Percentage of LOC=0.5

0 20 40 60 80 100

Daphnia magna Y=99.7865(1-e -0.1640*X ), R 2 =0.997

Rainbow Trout Y=114.3253(1-e -0.0192*X ), R 2 =0.99159

Figure 15 Percentage of Sites Exceeding Ac ute Risk LOC, Direct Water Applications

Treated Volume Percentage of Pond (20E6 liters) @ 1 mg Cu 2+ /L 0 20 40 60 80 100Site Exceendance Percentage of LOC=0.05

0 20 40 60 80 100

Daphnia magna Y=99.9217(1-e -0.7569*X ), R 2 =0.9999

Rainbow Trout Y=100.8454(1-e -0.0624*X ), R 2 =0.9962

Figure 16 Percentage of Sites Exceeding ES Acute Risk LOC, Direct Water Applications80 Based on the fitted regression e quations, the estimated volume of pond treated with 1 ppm Cu 2+

rate to allow no more than to allo w 10% site exceedences is shown in Table 27.

Table 27 Estimated Percent of Water Body Treated at 1 ppm Cu 2+ 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 Cu 2+/ A (X variable) at site exceeden ce 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 intr oduced into sewer lines as a r oot killer was estimated. Given the lack of use data, and th e use assumptions made by EFED , significant uncertainty is associated with these RQ es timates. Copper concentrations were speciated using BLM model to
estimate the concentration of ionic Cu 2+ . Median USGS monitoring si te water quality data for 811 sites were used as input parameters for th e BLM model (Appendix C). Risk quotients were estimated [activity of Cu 2+ (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 en dangered 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 ecolo gical 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 anal ysis 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 th e 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 hi ghest 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 ev ery situation, given the range of possibilities, EFED used the range of modeling data created dur ing this assessment to develop a tool for risk management to estimate the risk associated with particular a pplication rates. First, an equation (Figure 17 ) was fit to the relationship between application ra te (generally derived from a sequence of 4 applications with 7-day interval s). Second, equations were fit to the percentage of the 811 USGS sites exceeding the acute risk LOCs for aquatic in vertebrates 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 li kely to exceed acute risk levels of concern ( Table 30)

On an aquatic acute risk basis, ag ricultural use of copper as a pestic ide 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 fo r saltwater invertebrates is exceeded. Applications of copper-containi ng compounds at rates between 1.5 and 3 lb Cu/A may pose a risk to aquatic organisms at site s with vulnerable water chemistrie s. At 3 lbs Cu/A, only 90% of
the freshwater sites in the distribution would be protecte d, and the expected dissolved concentration of copper exceeds the LOCs for both saltwater invert ebrates and fish. Application rates above 3 lbs Cu/A likely pose a risk to both freshwater and sa ltwater environments.82 Table 29 Comparison of Applicatio n 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 hydroxide83 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 hydroxide84 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 400Percent Site Exceeding LOC

0 10 20 30 40 50 60 70 80 90 100

Rainbow Trout y=-0.8624 + 0.244*X, R 2 =0.9865 Daphnia magna y=105.53(1-e -0.0143*X ), R 2 =0.9957

Figure 18 Percentage of Sites Exceedi ng 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 P e a k C u 2 + C o n c ( u g / L )

0 20 40 60 80 100

Y=-0.3800+2.5358(X) r 2 =0.7585 Table 30 Summary of Acute Risk LO C Exceedences in Aquatic Environments

Freshwater Saltwater

Plant Rate
Cu lb/A (Cu ppb) Algae (RQ) Vascular (RQ) Invertebrate 1 Fish 1 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 exceedi ng 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 typi cal application rate of 1 ppm, peak concentrations of Cu 2+ 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 wate rbody, peak concentrations of Cu 2+ ranged from 0.05-0.5 ppm. This presumes rapid mixing throughout th e waterbody. Assuming a 1 ppm Cu target concentration, 90% of the USGS s ites would exceed the acute risk LOC for invertebrates if 1% of the waterbody were treated, and 90% of the US GS sites would exceed the acute risk LOC for
invertebrates if 5% of th e waterbody were treated.

For almost any direct water application of c opper products, there is lik ely 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 wi ll be affected. Recovery of the affected organisms will vary on a site-to-site basis, a nd 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 lik ely 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 organi sms present may develop metabolic pathways for dealing with higher copper loading.

Minimizing adverse effects of non-target organi sms 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 entrai ned sediment could affect downstream resources.

3.5.3 Urban Uses (Root-killers)

Based on the concentration estimates generated by the “Down-the-Drain” an alysis, use of copper sulfate crystals as a root killer in domestic sewer systems may result in receiving waters high enough to affect aquatic inverteb rate populations, and fish on bot h an acute and chronic basis.86 Based on the assumptions used in the EFED an alysis, approximately 85% of the USGS sites exceeded the acute risk LOC for aquatic inverteb rates and approximately 20% of the USGS sites
exceeded the acute risk LOC for fish. Given the si te-specific nature of use patterns, sewersheds, and receiving water chemistry and flow range, a more definitive analys is 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 bioavailable 15 , and may cause toxic effects. Estimates of pore wate r concentration based on the various scenarios
evaluated are included in th e aquatic exposure section ( Table 15). Estimated concentrations are given for the 1 st year and 30 th year at both a low K d and a high K d . As a conservative estimate of the likelihood of effects, concen trations in the pore water co uld be put into the BLM. and compared to site water chemistry to estimate pot ential 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 toxic ity. However, estimated peak pore water concentrations suggest that there may be some ri sk to benthic organisms in surface water bodies receiving runoff from lands trea ted with copper-containing pesticid es. Below, Table 20 details the range of estimated pore wate r concentrations. As a first ap proximation, 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 analys is. It must also be noted that the flow regime and bed characteristic s of the receiving waters will play an important part in sediment toxicity.

Table 31 Range of Sediment Po re Water Dissolved Copper Concentr ations for Various Scenarios

Type of Sediment Accumulation
time Min Cu (ppb) Scenario Max Cu (ppb) Scenario

Low K d 1 year 0.42 CA alfalfa 44.7 PA apples

30 year 13.7 CA alfa lfa 2680 CA filberts

High K d 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 exposur e to copper was estimated using EFED’s Terrestrial Exposure (TREX, Version 1.1) spreadsh eet. 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 pe sticide ingested by the organism is based on the assumptions that 1) the organism forages 100% of the time in a tr eated 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, t hus 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 th e aquatic assessment, both orchard and row crop applications are considered.88 Label Application Rates

The highest orchard label applicat ion rate is 31.8 lb a.i./acre for filberts. The label designated application interval is 14 days, with a total of 2 applications. Th e highest row crop label application rate is 3.2 lb a.i./a cre for potatoes. Intervals be tween applications, and maximum number of applications were not specified on th e label. For modeling, 4 applications at an interval of 7-days were assumed. Pr edicted residues are shown below in Table 32.

Table 32 Estimated Environmental Concentr ations 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 applica tion rate is 3.8 lb a.i./acre fo r 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 potatoe s in Maine. For modeling, 4 applica tions at an interval of 7-days
were assumed. Predicted residues are shown below in Table 33.

Table 33 Estimated Environmental Concentr ations 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 Ex posure - (TerrPlant)

Terrestrial plant exposure was determined usi ng TerrPlant (Version date d 03/02/04). TerrPlant uses the application rate, and sol ubility of the chemical to estimate loading to areas adjacent to the application site. Both upland and semi-aqua tic areas are considered. Total loading to adjacent drier areas (upland) includes sheet runoff and drift. Total loading to semi-aquatic areas (wetland) includes ch annelized runoff and drift. Solubility of copper is >100 ppm. Terrestrial plant exposure was calculated based on both the highest label applicati on rates and the highest average application rates reporte d by BEAD. As with the aquatic assessment, both orchard and89 row crop applications are considered.

Label Application Rates The highest orchard label applicat ion 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. Pred icted residues are shown below in
Table 34.

Table 34 Estimated Environmental Concentr ations 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 applica tion 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 Concentr ations 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 0.0490 4.1.3 Soil Accumulation

Because of the frequent applica tion 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 concen trations in the soil could be toxic to plants, to soil invertebrate s, or to microorganisms in the soil which play a critical role in nutrient processing. Additionally, high concentrati ons of copper in the soil can be taken up by on-site plants, potentially beco ming 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 copp er in the surface horizon (upper 10 cm) for the Pennsylvania apples scenario, at both the maximu m label rate (19 lb Cu/acre; Figure 13a), and the state average application rate (2.2 kg Cu/ha; Figure 13b). Ac cumulation is shown in yearly
increments. At the maximum label application rate, soil concentra tions at the treated site exceed high ambient soil concentrations (100 ppm) within 2 years. At th e state average application rate, (presuming no background copper) soil concentrati ons reach the average ambient conditions (30 ppm) in 6 years, and exceed the high am bient 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 o i l C o n c e n t r a t i o n ( m g / k g )

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 C u C o n c e n t r a t i o n ( m g / k g )

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 t oxic effect is exerted by the copper ion binding to the gill, toxicity for te rrestrial organisms has been assessed based on dietary uptake. Although acute poisoning can oc cur and may be severe enough to cause death,
mammals are known to have biochemical mechan isms for controlling uptake of copper and maintaining homeostasis (Goyer 1996). Althoug h less well researched, it is likely similar
mechanisms exist for birds and other terrestria l organisms. Acute poisoning effects include hepatic necrosis and hemolytic anemia (G oyer 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 metalloth ioneins. Copper abso rption, excretion, and
turnover time have been studied in laborat ory rats (Johnson and L ee 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 ( 64 Cu or 67 Cu), turnover of copper in rats appear s fairly rapid, with three separa te studies estimating an average biological half-life of be tween 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 inve stigators 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 c opper appeared to be bi-phasic, with an initial rapid decline producing a biolog ical half-life of approximate ly 70 hours (Linder and Roboz 1986). The break between phases occurred at ar ound the 70-hour point. The second phase was slower, with an estimated half-life of 220 hours. The investigators interpre ted this as indicating there are “ at least two copper ‘compartments’ or ‘pools’ in the body, w ith 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 estima tion, absorption efficiencies for rats with no known metabolic deficiencies ranged from 22-63% . Absorption efficiency was consistently lower at high doses. Dietary copper concentr ations 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 ASTDR 16 Toxicological Profile for Copper . Thus, it appears that at least up to dietary concentrati ons measured in these studies, small mammals have compensatory mechanisms to increase absorption of copper at low concentrations, and reduce absorp tion of copper at high concentra tions, 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

16 Agency for Toxic Substances and Disease Registry93 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 incorpor ate these uptake effects, but dos e-based endpoints will not. In order to account for these mechanisms, an abso rption efficiency correction of 22% (a high copper availability situation) wa s 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 av ailable for acute effects.

4.2.1 Avian Guideline Data

Table 36 contains data for birds from guideline st udies 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 metall ic copper using the percent copper conversions shown in Table 1. For clarity, both values ar e listed in the table.94 Table 36 Avian Guideline Data

Species Compound LD 50 /LC 50 (mg/kg) LOAEL (mg/kg) 95% C.I. NOAEL (mg/kg) Classification (MRID)

Acute oral (Guideline 71-1)

Copper sulfate pentahydrate 384 Bobwhite

as copper 98 a ND 0-infinity ND Core (00067456)

Tri-basic copper sulfate 642 80 Bobwhite

as copper 348 43 N/A ND Supplemental (00106120)

Acute dietary (Guideline 71-2)

Tri-basic copper sulfate 1829 Bobwhite

as copper 991 a NR NR NR Acceptable (00811103)

Tri-basic copper sulfate 4640 2150 Mallard

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 500 Mallard

as copper NR ND NA

390 Supplemental (43396301)

Copper oxychloride
sulfate 500 100 (eggshell thickness) Bobwhite

as copper NR

289 NA

58 a Core (43338001)

Copper oxychloride
sulfate 1000 Mallard

as copper NR ND NA

578 Supplemental (43396301)

a toxicity endpoint used in assessment ND - not determined, NA - not applicable, NR - not reported95 An ECOTOX search on copper sulfate, coppe r 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

EC 50 (ppm Cu) NOAEL (ppm Cu)

Acute dose 98
Acute dietary 991 Current Endpoints from
Guideline Studies Chronic 58

Type of study Species Compound LD 50 (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 ND 150 50 61379 Chronic (reduced egg production) Chicken (Gallus domesticus) Copper sulphate ND 976 496 59136

ND - Not determined96 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 e ffects on small mammals. EFED se lected the lowest acute oral
LD 50 s from HED’s “one-liner” database for copper and copper sulfate. Data are shown below ( Table 38) in terms of both compound and metalli c copper. Metallic copper conversions were performed using the molecular weight pe rcentages of copper shown in Table 1.

Table 38 Acute Oral Toxici ty in Rats (Guideline 81-1)

As compound As copper
Compound LD 50 (mg/kg bwt) 95% C.I. (mg/kg bwt) LD 50 (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 reported97 Only one chronic mammal guideline study was located ( Table 39), but alternative sources of data
were considered. Benchmarks fo r evaluating copper contaminati on at Superfund sites have been established, based on open lite rature values (Sample et al ., 1996, Efroymson et al., 1997, Efroymson et al., 1997b). Organisms for whic h copper benchmarks have been established include earthworms, microorganisms and heterotr ophic 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
in Table 40. The mink value has been used as a chronic mammalian endpoint to calculate RQs, but avian guideline studies provi de a more sensitive chronic e ndpoint 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 reducedfood 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 bwt a 85.5 mg/kg diet a
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 th an in controls. Reduced survivorship of kits was noted in the 50 ppm treatment

group.

a toxicity endpoint used in assessment98 An ECOTOX search on copper sulfate, coppe r oxide, and the copper group II compounds generated a number of refere nces for terrestrial mammals. Table 41 shows the most sensitive endpoints from the ECOTOX searc h, along with the endpoints base d on guideline studies and
other reviewed data.

Table 41 Small Mammal Data from ECOTOX

LD 50 (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 LD 50 (ppm Cu) LOAEL (ppm Cu) NOAEL (ppm Cu) ECOTOX
Reference #

Acute dose Rat Copper
chloride 300 1 ND 200 73169

Acute dietary None currently identified

Chronic (ova recovery rate, fertilization rate, blastocyst hatching) Mouse (Mus musculus) Copper
carbonate ND ND 11 2 59141

ND-No data

1 - Listed by authors as “let hal dose,” but no formal LD 50 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, Insect s, and Microbial Processes

Terrestrial Plants Vegetative vigor and seedling emergence data fo r terrestrial plants were not available from registrant-submitted guideline studies, but a substantial amount of data regarding effects on terrestrial plants was locate d through ECOTOX. Although li mited resources prevented a complete review of all data, the most sensitiv e endpoints expressed in units usable by EFED’s TerrPlant model were used to evaluate the impact of copper on the vegetati ve vigor of terrestrial plants. No suitable values for evaluating seedlin g 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 EC 25 (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 endange red 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 26.8 6.8 44317 Copper Sulfate

Dicot Kidney
bean Vegetative vigor 144.5 36.7 40559

Table 43 Terrestrial Insect Guideline Data

As compound As copper Compound

Effect Effect Toxicity Classification (MRID)

Copper Group II

Copper ammonium complex LD 50 >100 μ g/bee ND Practically
non-toxic Core (40764702)

Copper oxychloride
sulfate 7% mortality at
14.3 μ g/bee 7% mortality at
8.3 μ g/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 in sects, and lack of time to thoroughly analyze toxicity data, EFED has drawn no firm conclusion regarding th e potential toxicity of copper compounds to terrestrial insects.100 Table 44 Earthworm, Pl ant, and Microbial Proce sses 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 sulfatas e, urease, and phosphatase.

100 ppm in soil Low (derived
from <10 values) Copper reduced weight of roots stems, shoots, and leaves Terrestrial plants

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 actio n. 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 unde r-reporting of incidents.

Of the 24 reported incidents, 7 we re associated with terrestrial plants, and in all of the cases, certainty was rated as possible or probable. On e case, on tomatoes in Washington state, was in accordance with registered use. For the other incidents, affecti ng 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 al so calculates potential dose of applied pesticides for three size cla sses of birds and mammals, using generalized allometric equations (Nagy 1987), and assuming the organisms fo rage exclusively within the treated area. Thus, for each size class of bi rd and food category, an ingested dose can be
estimated based on the EECs derived from the Ke naga nomogram. The same method is used to
determine effective doses for the various size clas ses 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 (G uideline study 71-2) endpoints to estimate acute risk quotients. Chronic endpoints are ba sed on data from the avian reproductive studies (Guideline study 71-4). Based on the acceptabl e 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 LD 50 of 98 mg Cu/kg bwt (copper su lfate pentahydrate, MRID 00067456)

• Acute dietary LC 50 of 991 mg Cu/kg (tri-basic copper sulfate, MRID00811103)

• Chronic NOAEL of 58 mg/kg bwt (coppe r oxychloride sulfat e; MRID 43338001)

Given the presence of mechanisms control ling copper uptake, EFED believes the most appropriate value for evaluating potential e ffects on birds are dietary-based values.

For both birds and mammals, risk quotients we re calculated based on both the highest label applied rate, and the highest state average ra te supplied by BEAD. Application rates for orchards and row crops are considered separa tely. 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 orchar d 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 220 a,b 98.7 a,b 31.2 a,b 13.5 a,b 231 c

Tall grass 101 a,b 45.3 a,b 14.3 a,b 6.2 a,b 106 c

Broadleaf plants/small
insects 124 a,b 55.5 a,b 17.5 a,b 7.6 a,b 130 c

Fruits/pods/seeds/lg
insects 13.8 a,b 6.2 a,b 2.0 a,b 0.9 a,b 14.5 c

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 LO C 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 41.5 a,b 18.6 a,b 5.9 a,b 2.6 a,b 43.5 c

Tall grass 19.0 a,b 8.5 a,b 2.7 a,b 1.2 a,b 20.0 c

Broadleaf plants/small
insects 23.3 a,b 10.5 a,b 3.3 a,b 1.4 a,b 24.5 c

Fruits/pods/seeds/lg
insects 2.6 a,b 1.2 a,b 0.4 b 0.2 b 2.7 c

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 orch ard 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 gra ss, tall grass, and broadleaf plants food categories all exceed the acu te 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 49.3 a,b 22.1 a,b 7.0 a,b 3.0 a,b 51.7 c

Tall grass 22.6 a,b 10.1 a,b 3.2 a,b 1.4 a,b 23.7 c

Broadleaf plants/small
insects 27.7 a,b 12.4 a,b 4.0 a,b 1.7 a,b 29.1 c

Fruits/pods/seeds/lg
insects 3.1 a,b 1.4 a,b 0.4 b 0.2 b 3.2 c

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 th e short grass, tall grass, and broadleaf plant categories exceed the endangered species acute risk LOC and the ch ronic 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 di etary-based RQs. Birds consuming the fruits and pods food category exceed the endangered speci es 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 10.4 a,b 4.7 a,b 1.47 a,b 0.6 a,b 10.9 c

Tall grass 4.8 a,b 2.1 a,b 0.67 a,b 0.3 b 5.0 c

Broadleaf plants/small
insects 5.8 a,b 2.6 a,b 0.83 a,b 0.4 b 6.1 c

Fruits/pods/seeds/lg
insects 0.7 a,b 0.3 b 0.1 b <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 toxi city 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 gui deline 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 (T able 29). Modifications were made in the TREX spreadsheet to account for the 1 kg body we ight of the mink. The following data were used to develop mammal RQs:

• Acute oral LD 50 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 in clude a 22% absorption factor (see discussion in effects section) to account for dietary effect s. 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 applica tion rate, RQs for all size classes of mammals consuming plants or small insects exceed the acute risk, endangered sp ecies acute risk, and chronic risk LOCs. Except for 1000g granivores, all size classes and food groups ev aluated 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 11.2 a,b 9.6 a,b 5.1 a,b 381 c 327 c 172 c 157 c

Tall grass 5.1 a,b 4.4 a,b 2.3 a,b 175 c 150 c 78.8 c 71.9 c

Broadleaf plants/small insects 6.3 a,b 5.4 a,b 2.8 a,b 214 c 184 c 96.8 c 88.3 c

Fruits/pods/seeds/lg insects 0.7 a,b 0.6 a,b 0.3 b 23.8 c 20.5 c 10.8 c 9.8 c

Seeds (granivores) 0.15 b 0.14 b 0.06 5.3 c 4.7 c 2.2 c

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 applicati on for row crop use was potatoes at 3.2 lb a.i./acre (4 applications, 7-day interval. Risk quotient s for all mammals consuming he rbivorous material and small insects exceed the acut risk LOC except for the 1000g animals eating tall gr ass. Risk quotients for all size classes and diet groups except granivores and 1000g frugivores exceed the endangered species acute risk LOC. Dietary-ba sed RQs for all diet groups exceed the chronic
risk LOC.

Table 50 Mammal RQ Summa ry: 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 71.8 c 61.6 c 32.4 c 29.5 c

Tall grass 0.97 a,b 0.8 a,b 0.44 b 32.9 c 28.2 c 14.9 c 13.5 c

Broadleaf plants/small insects 1.2 a,b 1.0 a,b 0.53 a,b 40.4 c 34.7 c 18.2 c 16.6 c

Fruits/pods/seeds/lg insects 0.13 b 0.11 b 0.06 4.5 c 3.9 c 2.0 c 1.9 c

Seeds (granivores) 0.03 0.03 0.01 1.0 c 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 classe s of organisms consuming the short grass, tall grass, broadleaf plants, and small insects ex ceed 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. RQ s 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 85.2 c 73.2 c 38.5 c 35.1 c

Tall grass 1.2 a,b 0.98 a,b 0.52 a,b 39.1 c 33.5 c 17.6 c 16.1 c

Broadleaf plants/small insects 1.4 a,b 1.21 a,b 0.63 a,b 47.9 c 41.2 c 21.6 c 19.7 c

Fruits/pods/seeds/lg insects 0.16 b 0.13 b 0.07 5.3 c 4.6 c 2.4 c 2.2 c

Seeds (granivores) 0.03 0.03 0.01 1.2 c 1.0 c 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 RQ s for the small mammals consuming short grass exceed the acute risk LOC, although RQs for a ll size classes of mammals consuming grass, broadleaf plants, and small insects exceed the enda ngered 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 17.9 c 15.4 c 8.1 c 7.4 c

Tall grass 0.24 b 0.21 b 0.11 b 8.2 c 7.1 c 3.8 c 3.4 c

Broadleaf plants/small insects 0.30 b 0.25 b 0.13 b 10.1 c 8.7 c 4.6 c 4.2 c

Fruits/pods/seeds/lg insects 0.03 0.03 0.01 1.1 c 1.0 c 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 quotient s for upland and wetland areas adja cent to the application site based on a combination of the poten tial runoff from the field and sp ray 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 emerge nce. The more sensitive NOAEC is used to evaluate potential effects on e ndangered plants, and the EC 25 is used to evaluate acute effects on non-endangered plants. RQs were calculated fo r endangered species vege tative vigor endpoints for both monocots and dicots, using the maximum la bel rates for orchards and row crops. No RQs exceeded the LOC. Based on available data, th ere appears to be no acut e 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 (Vegetative vigor) Application

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=1112 4.3.4 Soil Accumulation and Plant Bioaccumulation

While the potential effects of copper in soil are de pendent on a variety of site specific factors, including but not limited to soil pH, percent organic ma tter, and sand/clay/loam content, the soil screening levels developed for use at Supe rfund sites (Efroymson 1997a) can be used as a benchmark for evaluating potentially harmful concen trations. Potentially harmful concentrations range from 60 ppm (earthworms) to 100 ppm (terrestrial plan ts, microorganisms). Based on PRZM modeling, potentially harmful soil concentr ations may be reached within 2-20 years, dependent on application rate a nd frequency of application. Note that while the model evaluates accumulation in the soil of the field, overspray areas adjacent to the fi eld where wildlife may reside and/or forage may be affected as well.

Some plants concentrate copper from soil, and th is 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 averag e and the upper bound of the 95% confidence interval) for plants growing in the concentrations of coppe r that are estimated for the Pennsylvania apple scenario. Fo r 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 accumu lation in plants over the 30 year simulation stays below 100 ppm. For the state average ap plication 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 c oncentrations 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 P l a n t C u C o n c e n t r a t i o n ( m g / k g )

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 P l a n t C u C o n c e n t r a t i o n ( m g C u / k g o f d r y p l a n t )

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 Concentration114 4.3 Terrestrial Risk Description

Information submitted during the public comm ent period, and additional analysis by BEAD indicated that copper is often applied at substantially below cu rrent labeled, but that it is often applied frequently rates (see disc ussion in Aquatic Risk Descriptio n). To assist in making risk management decisions, EFED used TREX to calcula te risk quotients for a range of application
rates from 1 lb Cu/A to 7.5 lb Cu/A. In all cas es, applications were appl ied 4 times, at intervals of 7-days. The absorption effi ciency factor was incorporated into the mammal estimation. Risk quotients presented are ba sed on dietary endpoints.

4.4.1 Avian and Mammals

There were exceedences of the acute risk LOC for birds at all rates eval uated. Acute risk RQs ranged from 0.1-6. At 1lb Cu/A, only the birds c onsuming short grass exceeded the LOC, but at 1.5 lb Cu/A risk quotients for all birds consum ing plants and birds consuming small insects exceed the LOC. Risk quotients for birds consum ing 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 quotie nts 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 chroni c risk LOC. The picture for mammals was similar, with the RQs for animals consuming all items except fru its 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 an d reduced food consumption at doses of around 700 ppm/day, both in tests conduc ted on rats and birds. Effects on offspring included loss of embryo, and reduced survivorship. How likely these effect s are to occur in the wild is unknown. In humans, chronic copper toxicity is uncommon, though not unknown, and is
often associated with deficienci es 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 animal s display any kind of a voidance behavior.115 Table 54 Summary of LOC Exceedences and RQs for Birds and Mammals

Birds Mammals Rate Cu (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 pl ants near the application site, either from dir ect contact or based on soil upta ke. Based on available contact toxicity data, it does not appear to pose a risk to terrestri al insects. Based on accumulation curves, copper may accumulate in soil to con centrations 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 wide spread, there is a reasonable expe ctation 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 wate r applications are expected primar ily to affect aquatic systems. Anticipated indirect effects are changes in pr imary productivity (aquatic systems only) and/or modifications in the prey base. Indirect effect s 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 pot entially at risk for indirect effects.

Table 55 Summary of Endangered Taxa Potentially at Risk

Listed Taxa Direct E ffects Indirect Effects Terrestrial and semi-aquatic plants (monocots) No No Terrestrial and semi-aquatic plants (dicots) No No

Insects No No
Birds Yes 4 Yes 1 Terrestrial Phase Amphibians Yes 4 No Reptiles Yes 4 Yes 1

Mammals Yes 4 Yes 1 Aquatic vascular plants Yes 3, 4 No
Freshwater Fish Yes 4 Yes 2 Aquatic Phase Amphibians Yes 4 Yes 2

Freshwater invertebrates Yes 4 Yes 2

Saltwater Fish Yes 4 Yes 2

Saltwater Invertebrates Yes 4 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 chronic117 5.1 LOCATES Using LOCATES, EFED is able to identify organi sms residing in proximity to the crops most commonly found to apply copper. RQs for all ta xa 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 th e following crop groups: ci trus, all, walnuts, almonds, filberts, peaches, tomatoes, bell peppers, and grapes. Because the minimum number of acres was set as low as possible, this repres ents a conservative estim ate 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-c ontaining pesticides to affect endangered or threatened species in all states. A list of species potentially aff ected is included as Appendix F. A more explicit assessment of poten tial 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

Taxa 1 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 taxa118 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 respons e curve is not appropria te. Data are not av ailable to perform a probit analysis for the saltwater organisms

5.2.2 Terrestrial Organisms

Birds Based on an assumption of a probit dose respons e relationship with a default slope of 4.5, and
and LD 50 of 98 ppm Cu, the corresponding estimated chance of individual mortality associated with the endangered species LOC of 0.1 for bi rds is 1 in 294,000. Although the Agency has assumed a probit dose response rela tionship in establishing the liste d species LOCs, the available data for the toxicity study ge nerating RQs for this taxonomic gr oup do not statistically support a probit dose response relationshi p (p<0.05) and so the confid ence in the estimated event probabilities based on this dose response relati onship and the listed species LOC is low.

Small Mammals Based on an assumption of a probit dose respons e relationship with a default slope of 4.5, and
and LD 50 of 114 ppm Cu, the corresponding estimated ch ance 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 relati onship 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 chem istry, 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 a pplication rates of 3.0 lb Cu/A.

Indirect Effects Indirect effects on aquatic ecosyst ems may be grouped primarily into two categories: removal of the prey base, and/or shifts in community stru cture. While copper is toxic to most aquatic organisms, the most sensitive are the non-vascular aquatic plants and aquatic invertebrates. Elimination of organisms at th e base of the food chain will likely also redu ce populations of organisms which feed on them, unless these organi sms 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 in clude higher trophic le vels in the affected waterbody (e.g., fish or turtles), as well as pisc ivorous birds or mammals dependent on it for food. A shift in the community structure, by elim ination of the more sensitive organisms, could
be either beneficial or detrimental to the endangered species dependent on the affected waterbody. Detrimental effects include grea ter competition for limited resources, and/or removal of a species that creates a more favor able 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 pha se 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, potentia l indirect effects are much the same as in an aquatic system: elimination of the prey base, and /or shifts in the trophi c 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 detrimental120 REFERENCES

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Yu, S., Vander Berg, GJ., and Beynan, AC. 1995. Copper metabolism in analbuminaemic rats fed a high-copper diet. Comp. Biochem. Physiol. 110A: 259-266.ECOLOGICAL RISK ASSESSMENT FO R RE-REGISTRATION OF COPPER SULFATE (CASE #0636), GROUP II CO PPER 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 RI SK ASSESSMENT ON COPPERS.

DUE TO THE SIZE OF THE ECOLOGI CAL 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.