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

OFFICE OF PREVENTION, PESTICIDES, AND TOXIC SUBSTANCES



# Environmental Fate and Ecological Risk Assessment for Lambda-cyhalothrin New Use Registration

1:1 mixture of the (Z)-(1R,3R), S ester and (Z)-(1S,3S)

Prepared by: José Luis Meléndez, Chemist Michael Hoffmann, Biologist

Reviewed by: Mah Shamim, Ph.D., Branch Chief United States Environmental Protection Agency Office of Pesticide Programs Environmental Fate and Effects Division Environmental Risk Branch V 1200 Pennsylvania Ave. Mail Code 7507P Washington, D.C. 20460

### Table of Contents

I. Executive Summary ................................................................................................................... 3 II. Problem Formulation and Analysis .......................................................................................... 3

A. Use Characterization ............................................................................................................. 3 B. Exposure Characterization ..................................................................................................... 6 1. Aquatic Exposure ............................................................................................................... 6 2. Terrestrial Exposure ......................................................................................................... 10 C. Conceptual Model ................................................................................................................ 12 1. Risk Hypotheses ................................................................................................................ 12 2. Diagram ............................................................................................................................. 13 III. Risk Characterization ............................................................................................................ 15

A. Risk Estimation .................................................................................................................... 15 1. Risks to Aquatic Animals .................................................................................................. 15

a. Water Column Exposure- Acute and Chronic Risk to Animals .................................... 15 b. Sediment Exposure- Acut e Risk to Benthic Organisms ............................................... 17 2. Risks to Aquatic Plants ..................................................................................................... 18 3. Risks to Terrestrial Anim als and Non-target Terrestri al and Semi-aquatic Plants ........... 19 B. Risk Description ................................................................................................................... 19 1. Risks to Aquatic Organisms .............................................................................................. 20

a. Aquatic Animals and Plants: Water Column Exposure ................................................ 21 b. Aquatic Animals: Sediment Exposure .......................................................................... 21 2. Risks to Terre strial Organisms .......................................................................................... 23 IV. References .............................................................................................................................. 23 IV. Appendices ............................................................................................................................ 25

Appendix A. Aquatic Exposure Information ........................................................................... 25 Appendix B. Data Requirements ............................................................................................. 68 Appendix C. Fate and Transport Characterization .................................................................. 71 Appendix D. T-REX Model (Version 1.2.3, August, 2005) ................................................... 77 Appendix E. The Risk Quotient Method and Levels of Concern ........................................... 88 Appendix F. Ecological Effects Data ..................................................................................... 90

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### I. Executive Summary

Lambda-cyhalothrin is a synthetic pyrethroid insecticid e, that is currently registered for use on cotton, corn, wheat, peas and beans, fruiting vegetables, can ola, sugarcane, sorghum, wheat hay, pome fruits, stone fruits, other small grains, non crop-land, trees and as a termite barrier, and is currently being proposed for use on cereal grains, cucurbit vegetabl es, grass forage, fodder and hay, wild rice and tuberous and corm vegetables. The usage patterns of the registered uses assessed in Environmental Fate and Effects Division’s Ecological Risk Assessment (June 12, 2002) for the Section 3 request for new uses of lambda-cyhalothrin on peas and beans, fruiting vege tables, canola, sugarcane, sorghum, wheat, wheat hay and other small grains, peanut hay, pome fruit, stone fruit, tree nuts, termite barrier, tobacco, noncropland and trees (conifer and deciduous trees) (D P Barcode D262918, D2629 19, D279087, D279088) are very similar to the proposed new uses, and theref ore, the terrestrial and aquatic EECs and risks were expected to be similar. In fact, runs of the terrestrial exposure model T-REX (Version 1.2.3, dated August 8, 2005) demonstrated that the acute and ch ronic risk estimates for birds and mammals should be roughly equivalent for the maximum exposure scenario for the proposed new uses and the previously assessed tree nut scenario since the EECs of chemical residues on potential forage items for the two scenarios are approximately the same. Therefore, the Environmental Fate and Effects Division’s Ecological Risk Assessment for previously registered uses for lambda-cyhalothri n (June 12, 2002) should be consulted for estimates and characterization of toxi city and risk to all terrestrial organisms for the proposed new uses.

However, the comparison of actual water column EECs resulting from the already registered uses in the 2002 Section 3 for lambda-cyhalothrin and the current proposed new uses demonstrates that the highest peak, 21-day, and 60-day EECs for the proposed new u ses are roughly two to four times higher than the EECs generated in the previous assessment; theref ore, although the previous assessment should be consulted for the characterization of the aquatic toxicity profile for lambda-cyhalothrin, risk estimates for all aquatic water column-dwelling and benthic-dwe lling organisms were gene rated anew in this assessment and were found to be r oughly two to four times higher than the risk estimates based on the maximum exposure scenario considered in the 2002 assessment.

In summary, based on lambda-cyhalothrin’s fate properti es and toxicity profile, this screening level risk assessment has identified acute risk to non-target listed and non-list ed freshwater and estuarine/marine invertebrates, freshwater and estuarine/marine fish, freshwater and estuarine/ marine benthic organisms, mammals, and insects, and chronic risk to freshwater a nd estuarine/ marine invertebrates, freshwater fish, freshwater and estuarine/ marine benthic organisms, birds, reptiles, and mammals resulting from the proposed use patterns. Although acute risk estimat es for freshwater non-vascular plants are below the Agency’s LOCs, acute risk to aquatic vascular plants and terrestrial plants coul d not be evaluated due to the lack of acceptable toxicity data. However, ba sed on lambda-cyhalothrin’s neural toxic mode of action, the lack of studies demonstrating adverse effect s of lambda-cyhalothrin or any other pyrethroid to plants, and the fact that no incident reports have reliably linked lambda-cyhalothrin or any other compound in the synthetic pyrethroid class of chemicals to phytotoxic effects despite being applied on or near agricultural plants, it appears unlik ely that it poses a phytotoxic concern.



### II. Problem Formulation and Analysis

A. Use Characterization

The purpose of this screening-level ecological assessment is to evaluate the risk to non-target organisms from the proposed new uses of lambda-cyhalothri n (PC Code: 128897) insecticide on cereal grains, cucurbit vegetables, grass forage, fodder and hay, wildrice and tuberous and corm vegetables. Lambda3

### cyhalothrin is a synthetic pyrethroid, a class of pestic ides that is noted for having toxic effects on aquatic organisms at extremely low levels. Lambda-cyhalothrin is currently registered for use on cotton, corn, wheat, peas and beans, fruiting vegetables, canola, sugarcane, sorghum, wheat hay, pome fruits, stone fruits, other small grains, non crop-land, trees and as a termite barrier. Two major end use products of lambda-cyhalothrin are Karate® Insecticide with Zeon Technology (EPA Reg. No. 100-1097) (PP321), which is an emulsifiable concentrate and Warrior ® Insecticide with Zeon Technology (EPA Reg. No. 100-1112), which is a capsule suspension.

Table 1 is a summary of agricultural use patterns for lambda-cyhalothrin. The uses in bold are the proposed new uses. The use information was obtained from the current label for Karate® Insecticide and Warrior® Insecticide, and the proposed labels for Karate® Insecticide and Warrior® Insecticide. Figure 1 is a use map of lambda-cyhalothrin. The major u ses were cotton, corn, wheat, and sweet corn (in that order). Together, these crops constituted over 83% of the use of the chemical in 1997. The use area covers the cotton and the corn belts, a large use area from the north of Texas to Oklahoma and Kansas, and large portions of the East and Northeast coasts, where estuarine/ marine habitats may be exposed to the chemical. Surprisingly, lambda-cyhalothrin was on ly used in small areas to the west of the Dakotas and Texas in 1997.

Table 1. Summary use information for lambda-cyh alothrin, based on current and proposed (in bold) labels for Karate® Insecticide and Warrior® Insectic ide. Current uses assessed in the Environmental Fate and Effects Division’s Science Chapter of the 2 002 Section 3, are highlighted with diagonal lines.

Use Single App. Rate (lb. a.i./A) # of Apps. Seasonal App. Rate (lb. a.i./A) App. Interval (days) App. Method Incorporation Depth (inches)

Cereal Grains: Barley, Buckwheat, Oat, Triticale, Wheat, Wheat hay 0.03 2 0.06 3 G,A 0

Cucurbit Vegetables: Chayote (fruit), Chinese waxgourd, Citron melon, Cucumber, Gherkin, Ghourd (edible), Momordica species, Muskmelon (hybrids and/or cultivars of Cucumis melo ), Pumpkin, Summer squash (includes various varieties), Winter squash (also includes various types of squash), Watermelon, includes hybrids 0.03 6 0.18 5 G,A 0

Grass Forage, Fodder and Hay: Pasture and rangeland grass, Grass grown for hay or silage, and Grass grown for seeds. 0.03 1 per cutting;

3 per

season 0.03 per cutting; 0.09 per

season N/A, 1 per cutting G,A 0

Rice, Wild Rice 0.04 3 0.12 5 G,A 0

Tuberous and Corm Vegetables: Arracacha, Arrowhoot, Artichoke, Canna (edible), Cassava (bitter and sweet), Chayote (root), Chufa, Dasheen, Ginger, Leren, Sweet potato, Tanier, Turmeric, Yam (bean and true) 0.03 4 0.12 7 G,A 0

Sorghum 0.03 ~2.7 0.08 3 G,A 0

Sugarcane 0.04 4 0.16 7 G,A 0

Wheat,Wheat Hay, Triticale 0.03 2 0.06 3 G,A 0

Canola 0.03 3 0.09 5 G,A 0

4Table 1. Summary use information for lambda-cyh alothrin, based on current and proposed (in bold) labels for Karate® Insecticide and Warrior® Insectic ide. Current uses assessed in the Environmental Fate and Effects Division’s Science Chapter of the 2 002 Section 3, are highlighted with diagonal lines.

Single App. Seasonal App. # of App. Incorporation Use Rate (lb. a.i./A) Apps. App. Rate Interval (lb. a.i./A) (days) Method Depth (inches)

Fruiting Vegetables 0.03 12 0.36 5 G,A 0

Legume Vegetables 0.03 4 0.12 5 G,A 0

Pome Fruits 0.04 5 0.20 5 G,A 0

Stone Fruits 0.04 5 0.20 5 G,A 0

Tobacco 0.03 3 0.09 7 G,A 0

Tree Nuts 0.04 4 0.16 5 G,A 0

Conifers and deciduous trees (plantations and nurseries) 0.04 6 0.24 N/A G,A 0

Conifers and deciduous trees (seed orchards) Ground apps: apply directly to the tree or apply at max. 0.156

Aerial apps: max. 0.117 4@0.125

5@0.1 0.5 N/A

May Assume 7 G,A 0

Non-cropland (excluding public land) 0.04 5 0.2 N/A G 0

Cotton 0.04 5 0.20 3 G,A, ULV 0

Peanuts 0.03 4 0.12 7 G,A 0

Rice 0.04 3 0.12 3 G,A 0

Soybeans 0.03 2 0.06 5 G,A 0

Alfalfa and Alfalfa Grown for Seed 0.03 4 0.12 N/A G,A 0

Cereal Grains (field corn, popcorn, seed corn) 0.09 at plant, 0.06 after silk initiation, and 0.03 after corn has reached the

milk stage Varies 0.12 from at plant and

foliar applications 3-4 G,A 0

Cereal Grains (Sweet Corn) 0.12 from at plant and foliar

applications 4 0.48 N/A G,A 0

Cole crops 0.03 8 0.24 5 G,A 0

Lettuce 0.03 1 0.03 5 G,A 0

Onion, Garlic 0.03 8 0.24 5 G,A 0

Sunflower 0.03 4 0.12 5 G,A 0

G=ground; A=aerial; ULV=ultra low volume applications; N/A = not available.

5Figure 1. Map highlighting the major us es of Lambda-Cyhalothrin in 1997. http://ca.water.usgs.gov/pnsp/pesticide_use_maps/show_map.php?year=97&map=m6083

Caution: The pesticide use maps available from this site show the aver age annual pesticide use intensity expressed as average weight (i n pounds) of a pesticide applied to each square mile of agricultural land in a county. The area of each map is based on state-level estim ates of pesticide use rates for individual crops that were comp iled by the National Center for Food a nd Agricultural Policy during 1995-1998 and on 1997 Census of Agriculture county crop acreage. The maps do not represent a speci fic year, but rather show typical use patterns over the four year period 1995 through 1998. Use intensity rates are expressed as the pounds app lied per square mile of mapped agricultural land in a county. The area of mapped agricultural land for each county was obtained from an enhan ced version of the 1992 USGS National Land Cover Data (NLCD) . The key limitations of the data used to produce th ese maps include the following: (1) state us e-coefficients repres ent an average for t he entire state and consequently do not reflect the local variability of pesticide ma nagement practices found within states and counties, (2) pesti cide use estimates are not for a specific year, but represent typical use patterns fo r a four year period, (3) state pesticide use coefficients ma y not have been available for all states where a pesticide may have been applied to agricultural land, and therefore, are not displayed on the maps, (4) the county crop acreage is based on the 1997 Census of Agriculture and may not represent all crop acreage because of Census nondisclosure rules , and (5) agricultural land area used to cal culate the pesticide use intensity and display the data was derived from 30-meter satellite r emote sensing data which may over estimate or underestimate the actual agricultura l land area. The maps are not intended for making local-scale es timates of pesticide use, such as estimates at the county level. Please refer to Method for Estimating Pe sticide Use for a detailed discus sion of how the pesticide use data were developed.



### B. Exposure Characterization

1. Aquatic Exposure

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### In a previous Environmental Fate and Effects Divi sion Ecological Risk Assessment (June 12, 2002) for the Section 3 request for new uses of lambda-cyhalo thrin on peas and beans, fruiting vegetables, canola, sugarcane, sorghum, wheat, wheat hay and other small grains, peanut hay, pome fruit, stone fruit, tree nuts, termite barrier, tobacco, non-cropland and trees (conifer and deciduous trees) (DP Barcode D262918, D262919, D279087, D279088), Tier 2 aquatic modeling (PRZM/EXAMS-with the aid of the user interphase, pe4) was used to estimate the concentrations of lam bda-cyhalothrin in the water column of surface water resulting from the various proposed uses. The following food crops, namely, fruiting vegetables (tomato), stone fruits (peaches), tree nuts (almonds), and wheat and the non-food crops, namely, conifer and deciduous trees, were used to re present the proposed uses of lambda-cyhalothrin. For the purpose of the modeling, the maximum annual an d per event application rate, maximum number of applications per season, and the minimum intervals be tween the applications were selected to estimate the aquatic exposure concentrations. In general, the cr ops scenarios were selected to represent the geographic locations where the specific crops are grown in large quantities. The locations and specific crops selected to represent the crop groups that were modeled to de termine potential risks to aquatic organisms include the following: FL-tomato for fruiting vegetables, GA- peach for stone fruits, CA-almonds for tree nuts, ND-wheat and OR-Christmas tree fo r conifer and deciduous trees.

As demonstrated in Table 1 , the usage patterns are similar betw een the registered uses assessed in EFED’s 2002 Section 3 risk assessment and the new uses a ssessed in this document. In addition, in the 2002 Section 3 for lambda-cyhalothrin, the Estima ted Exposure Concentrations (EECs) resulted in numerous exceedances of both acute and chronic LOCs fo r aquatic organisms. Therefore, for the current proposed new uses of lambda-cyhalothrin on cereal gr ains, cucurbit vegetables, grass forage, fodder and hay, wild rice and tuberous and corm vegetables, Ti er II modeling was performed using the FL cucumber and NC sweet potato scenarios in PRZM/EXAMS and the various input parameters as described in Appendix A . In addition to using PRZM/EXAMS to gene rate EECs, estimation of EECs for wild rice was also performed separately using a Tier 1 Rice Model ( Appendix A ). These crop scenarios were selected as representatives among all of the proposed new uses because they had the highest seasonal application rates and were expected to result in the highest exposure to aquatic organisms.

The Rice Model was refined, consistent with its Tier 1 nature, to account for aerobic aquatic metabolism, and aqueous photolysis, to obtain suitable chronic va lues. Even though these chronic EECs were smaller than the EEC obtained from the Rice Model (that typica lly are utilized for chronic calculation of the risk quotients as well), the refinement is still considered conservative. The details of the calculations performed by the EFED, and an explanation of the refinement appear in Appendix A

. Table 2 presents the results obtained from the refinement for wild rice.

To explore the relative contributions of drift vs. ru noff/erosion to the estimated environmental exposure concentrations, the PRZM/EXAMS scenarios were also run under varying drift assumptions. Specifically, both scenarios were run for ground and ae rial applications assuming 1% and 3.9% drift, respectively, as well as for theoretical aerial applica tions assuming 0% drift. Typically, 1% drift is the default input value in PRZM/EXAMS for ground applica tions, and 5% drift is the default assumption for aerial applications. However, because labels for lam bda-cyhalothrin require 150 ft buffer zones for aerial application, EECs were generated based on a 3.9% drift assumption, the drift estimate generated by AgDRIFT® when a 150 ft buffer is employed. Although EECs were estimated assuming 0% drift for characterization purposes (see the Risk Description section of the chapter), risk estimates were not generated based on the later theoretical EECs.

The water column EECs for aquatic organisms resulting from the already registered uses described in the 2002 Section 3 for lambda-cyhalothrin and the cu rrent proposed new uses are compared below in Table 2 . As demonstrated in the table, the highest EECs for the proposed new uses exceed the highest EECs for already registered uses; the highest peak, 21-day and 60-day EECs for the proposed uses are 0.414 ppb

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### (NC sweet potato), 0.170 ppb (wild rice), and 0.089 ppb (wild rice), respectively. In addition, the respective highest EECs for the registered uses ar e 0.224 ppb (stone fruit), 0.039 ppb (coniferous and deciduous trees), and 0.030 ppb (c oniferous and deciduous trees). Since EECs for the new uses are roughly two to four times higher than the EECs generate d in the previous assessment for registered uses, risk estimates for aquatic organisms are expected to be two to four times higher and will be calculated and discussed in the the Risk Characterization Section of this document. It should be noted that the EECs generated for the wild rice correspond to a Tier I c oncept, while all other EECs are based on a Tier 2 aquatic model.

Table 2. PRZM/EXAMS Estimated Environmental Con centrations (in ppb) of Lambda cyhalothrin in the Water Column Based on Proposed and Registered Uses.

Surface Water Concentrations (ppb) Exposure Scenario Peak 21-day 60-day

Current Proposed Uses

NC sweet potato (aerial, 0.04 lb/acre, 4x, 7 days); 3.9 % drift b 0.414 0.048 0.033

NC sweet potato (aerial, 0.04 lb/acre, 4x, 7 days); 0% drift 0.409 0.045 0.030

NC sweet potato (ground, 0.04 lb/acre, 4x, 7 days); 1% drift for ground applications 0.414 0.048 0.033

Wild rice (aerial, 0.04 lb/acre, 3x, 5 days) 0.270 0.170 0.089

FL cucumber (aerial, 0.03 lb/acre, 6x, 5 days); 3.9% drift b 0.047 0.011 0.007

FL cucumber (aerial, 0.03 lb/acre, 6x, 5 days); 0% drift 0.023 0.002 0.001

FL cucumber (ground, 0.03 lb/acre, 6x, 5 days) ; 1% drift for ground applications 0.026 0.004 0.003

Previously Registered Uses a

Fruiting vegetables (aerial, 0.03 lb/acre, 12x, 5 days) 0.222 0.028 0.023

Stone fruit, (aerial, 0.04 lb/acre, 5x, 5 days) 0.224 0.026 0.017

Tree nuts (aerial, 0.04 lb/acre, 4x, 5 days) 0.105 0.018 0.010

Wheat (aerial, 0.03 lb/acre, 2x, 3 days) 0.116 0.013 0.008

Conifer and deciduous trees (aerial, 0.04 lb/acre, 12x, 5 days) 0.118 0.039 0.030

a These uses were reviewed in a previous Environmental Fate a nd Effects Division Ecological Risk Assessment (June 12, 2002) for t he Section 3 request for new uses of lambda-cyhalothrin on peas and beans, fruiting vege tables, canola, sugarcane, sorghum, wheat , wheat hay and other small grains, peanut hay, po me fruit, stone fruit, tree nuts, term ite barrier, tobacco, non-cropland and trees (c onifer and deciduous trees) (DP Barcode D 262918, D262919, D279087, D279088).

b The default drift assumption for aerial app lications in PRZM/EXAMS is typically 5% . However, a 3.9% drift assumption was employed due to label requirements that specify the use of 150 ft buffer. This drift estimate is obtained from AgDRIFT®.



### Equilibrium Partitioning and Concentr ation in the Sediment/Pore water Lambda-cyhalothrin, like other pyrethroids, is a lipoph ilic compound that can adsorb readily to particulate and sediment, thus possibly limiting its exposure to aq uatic life in the water column but increasing toxic exposure in the benthos. Sediment can act as a reservoir for lipophilic persistent compounds. The sediment and particulate likely adsorb a high percen tage of lambda-cyhalothrin, as indicated by its relatively high K OC 

### (average K OC 

### = 333,200 mL/g). Therefore, coupled with lambda-cyhalothrin’s moderate persistence in aquatic environments, sediment bound lambda-cyhal othrin could present a toxicity risk for benthic aquatic life and aquatic eco systems in general. Exposure to this sediment can result in a direct impact to aquatic life through respir ation, ingestion, dermal contact, as well as indirect

8

### impact through alterations of the food chain. Alt hough estimates of sediment e xposure were not generated in previous risk assessments for lambda-cyhalothr in, in this assessment PRZM/ EXAMS was used to estimate concentrations in the porewater and sediment compartments of the aquatic system for the new proposed usage scenarios. These EECs can be found in Table 3

. Evaluating the risk to aquatic life from this exposure b ecomes problematic especially if there is a lack of adequate sediment toxicity and exposure data. Therefore, in order to assess this potential for pesticide risk to aquatic benthic systems, the Environmental Fate and Effects Division (The Agency) of the Office of Pesticides Program (OPP) has adopted the method u sed by the OW that relies on the theory of equilibrium partitioning (EqP) of chemicals. This theory is based on the hydrophobicity and concentrations of the chemical normalized to organi c carbon (OC) in sediment (De Toro et al. 1991) and holds that a nonionic chemical in sediment partitions between sediment organic carbon, interstitial (pore) water and benthic organisms. At equilibrium, if the concentration in any phase is known, then the concentration in the other phases can be predicted. A key component to this theory is the chemicals organic carbon coefficient (K OC 

### ), which is constant for every chemical and represents the ratio of the chemical concentration in water to the concentra tion in organic carbon. The document, “Technical Basis for the Derivation of Equilibrium Partitioning Sedime nt Guidelines (ESGs) for the Protection of Benthic Organisms: Nonionic Organics” (USEPA, 2000), demonstrates that biological responses of benthic organisms to nonionic organic chemicals in sediments are different when the sediment concentrations are expressed on a dry weight basis, but similar when expressed on a ug chemical/g organic carbon basis (ug/g OC 

### ). Similar responses were also observed across sediments when interstitial water concentrations were used to normalize biological availability. The T echnical Basis Document further demonstrates that if the toxic effect concentration in water is known (e .g., LC50), the effect concentration in sediment on a ug/g OC 

### basis can be predicted by multiplying the eff ect concentration in water by the chemical K OC



### .

(LC50 ug/L x K OC 

### L/Kg OC 

### x 1 Kg OC 

### /1000g OC 

### = LC50 ug/g OC 

### )

Since, the Agency uses a deterministic method for it s screening level risk assessment, the calculation of risk quotient values (RQ) is important for assessing po ssible risk. The RQ values are calculated by taking the ratio of the estimated exposure concentrations (EEC) to the toxicity effect value (e.g., LC50, NOAEC). The EEC values are model generated (e.g., PRZM/ EXAMS) and reflect peer evaluated and approved scenarios for assessing pesticide exposure to an aquatic environment. However, the PRZM/EXAMS output produces water column EEC values, as well as sediment and porewater EEC values. Therefore, in order to assess possible t oxic pesticide exposure to aquatic organisms from sediments, the Agency is using the PRZM/EXAMS model which incorporates the principles of the equilibrium partitioning theory, in order to genera te EECs from sediment and porewater. By relying on sediment and/or porewater output values, the Agen cy has two ways for calculating RQ values for sediments by using porewater exposure values and bulk sediment values.

The calculations that rely on porewater can be cal culated by dividing the PRZM/EXAMS output value for porewater concentrations by the dissolved concentra tions in the water column that caused toxicity in bioassays (e.g., LC50).

EEC porewater ug/L / LC50 ug/L

If sediment effects data are available (LC50 ug/kg OC 

### ), RQs can be produced by using the PRZM/ EXAMS sediment output value for sediment.

EEC sediment ug/kg OC 

### / LC50 ug/kg OC

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### Since actual sediment effects data were not availabl e, RQs could not be calculated based on exposure via sediment, and RQs were calculated based on pore wate r EECs only. Without adequate sediment toxicity studies this estimation approach appears prudent for a screening level assessment of the potential for toxic risk to aquatic benthic organisms (Walter Berry , U.S. EPA Laboratory, Narragansett RI, personal communication). However, it should be stressed that exposure and risk to benthic organisms may be significantly underestimated in this assessment because it was assumed that the main source of contact of lambda-cyhalothrin to the sediment dwellers is the pore water; however, these organisms may be in constant contact with the sediments and even feed from them or from other small organisms that are contaminated, thereby increasing their exposure and potentia l for toxic effects. In order to generate sound estimates of risk in future assessments, it is critical to account for all of these factors (e.g., interstitial water respiration, sediment ingestion or other sed iment integument exchange) by using actual sediment toxicity values based on both pore water exposure and sediment exposure. For additional discussion of the assumptions and uncertainties of the EqP approach, please refer to Appendix A

.

Table 3. Estimated Environmental Concentrations (i n ppb) of Lambda-cyhalothrin in the Benthic Pore Water and Sediment. Exposure Scenario Peak 21-day

Pore Water EECs ( μ g a.i./L)

NC sweet potato (aerial, 0.04 lb/acre, 4x, 7 days); 3.9% drift a 0.00790 0.00773 NC sweet potato (ground, 0.04 lb/acre, 4x, 7 days); 1% drift for ground applications 0.00790 0.00773

FL cucumber (aerial, 0.03 lb/acre, 6x, 5 days); 3.9% drift a 0.00135 0.00133 FL cucumber (ground, 0.03 lb/acre, 6x, 5 days); 1% drift for ground applications 0.00065 0.00064

Sediment EECs (μg a.i./kg sediment)

NC sweet potato (aerial, 0.04 lb/acre, 4x, 7 days); 3.9% drift a 105.5 102.6 NC sweet potato (ground, 0.04 lb/acre, 4x, 7 days); 1% drift for ground applications 105.5 102.6

FL cucumber (aerial, 0.03 lb/acre, 6x, 5 days); 3.9% drift a 18.0 17.7 FL cucumber (ground, 0.03 lb/acre, 6x, 5 days); 1% drift for ground applications 8.68 8.54

a The default drift assumption for aerial app lications in PRZM/EXAMS is typically 5%. However, a 3.9% drift assumption was empl oyed due to label requirements that specify the use of 150 ft buf fer. This drift estimate is obtained from AgDRIFT®.



### 2. Terrestrial Exposure

A primary concern with lambda-cyhalothrin is that birds and mammals may be exposed shortly after application through oral or dietary exposure to vege tative plant material or insects when foraging in the treated fields for nesting material or food. Therefore, for lambda-cyhalothrin spray applications, estimation of pesticide concentrations in wildlif e food items focuses on quantifying possible dietary ingestion of residues on vegetative matter and in sects. The EFED TeRrestrial EXposure model T-REX (T-REX, Version 1.2.3, dated Augus t 8, 2005) is used to estimate exposures and risks to avian and mammalian species. Input values for avian and mammalian toxicity as well as chemical application and foliar dissipation half-life data are required to run the model. The model provides estimates of exposure concentrations and risk quotients (RQs). Specifi cally, the model provides estimates of concentrations (upper-bound and mean) of chemical residues on the su rface of different types of foliage and insects that may be dietary sources of exposure to avian, ma mmalian, reptilian, or terrestrial-phase amphibian receptors. The surface residue concentration (ppm) is estimated by multiplying the application rate (pounds active ingredient per acre) by a value sp ecific to each food item. These values (termed the Hoerger-Kenaga estimates) along with a more detaile d discussion of the methodology implemented by TREX, are presented in Appendix D (T-REX Model).

10

### For multiple applications, the EEC is determined by adding the mass on the surface immediately following the application to the mass of the chem ical still present on the surfaces on the application (determined based on first order kinetics using the foliar half-life as the rate constant). Uncertainties in the terrestrial EECs are associated with a lack of da ta on dissipation from foliar surfaces. When data are absent, as in this case, EFED assumes a 35-day foliar dissipation half-life, based on the work of Willis and McDowell (1987). In this respect, the EECs for lambda-cyhalothrin may be an overestimation of actual concentrations if the half-life under field conditi ons is lower than the default value. Because foliar dissipation data are not available, the extent to wh ich EECs may be overestimated or underestimated is uncertain.

Risks could also be overestimated if the actual app lication rate, frequency of a pplication, or number of applications are lower than the input parameters used for the conservative exposure scenario that was modeled. For the purposes of this risk assessment, the T-REX model was run for agricultural uses with the maximum proposed application rates, the maxi mum number of applications, and the minimum interval between applications for each usage scenario, to assess risk to terrestrial organisms. Three of the 5 proposed new uses were modeled in T-REX to estim ate terrestrial EECs. The use on cereal grains was chosen for modeling because it had the shortest app lication interval, the use on cucurbit vegetables was chosen for modeling because it had the highest number of applications and seasonal rate, and the use on rice was chosen for modeling because it had the highest single application rate.

The results of the modeling can be found below in Table 4 . It also includes the model estimates of terrestrial exposure concentrations in food items (s hort grass, tall grass, broadleaves/forage/ small insects and seeds/large insects) derived according to Hoerge r and Kenaga (1972), Fletcher et al. (1994) and Pfleeger et al. (1996) in the previous Environm ental Fate and Effects Division Ecological Risk Assessment (June 12, 2002) for the Section 3 requ est for new uses of lambda-cyhalothrin on peas and beans, fruiting vegetables, canola, sugarcane, sorghu m, wheat, wheat hay and other small grains, peanut hay, pome fruit, stone fruit, tree nuts, termite barrier, tobacco, non-cropland and trees (conifer and deciduous trees) (DP Barcode D 262918, D262919, D279087, D27 9088). These EECs were also generated based on the maximum application rates, maximum number of applications, and minimal intervals between the applications, assuming a first-or der degradation rate and a default foliar dissipation half-life of 35 days. A wide range of exposure scenarios were selected in estimating EECs for the uses registered in 2002, and based on the seasonal application rate, lambda-cyhalothrin application to conifer and deciduous trees represented the highest exposure scenario and the application to wheat represented the lowest exposure scenario of the crops selecte d to represent the already registered uses.

As mentioned previously, an examimation of Table 1 reveals that the usage patterns are similar between the registered uses assessed in EFED’s 2002 Sec tion 3 risk assessment and the uses proposed, and therefore, the terrestrial EECs are expected to be similar. As demonstrated in the Table 4 , the EECs for the maximum exposure scenario for the proposed new uses (EEC range = 2 to 34; based on 6 aerial applications under a 5-day interval to cucurbits at a maximum rate of 0.03 lb a.i./acre) are well below the EECs for the maximum exposure scenario for the alread y registered uses (EEC range = 5 to 74; based on 12 aerial applications under a 5-day interval to conife r and deciduous trees at a maximum rate of 0.04 lb a.i./acre). Since the EECs from the maximum usage scenario for the new uses are roughly half of the EECs from the maximum usage scenario evaluated in th e previous assessment for registered uses, risk estimates for terrestrial organisms are expected to be half as high. In addition, given that EECs are approximately the same between the maximum exposur e scenario for the proposed new uses (cucurbits) and the previously assessed tree nut scenario (EEC range = 2 to 33; based on 4 aerial applications under a 5-day interval to tree nuts at a maximum rate of 0.04 lb a.i./acre), risk estimates for birds and mammals should be roughly equivalent for the two scenarios. Therefore, the Environmental Fate and Effects Division’s Ecological Risk Assessment (June 12, 2002 ) for the Section 3 request for new uses of lambda11

### cyhalothrin on peas and beans, fruiting vegetables, canola, sugarcane, sorghum, wheat, wheat hay and other small grains, peanut hay, pome fruit, stone fruit, tree nuts, termite barrier, tobacco, non-cropland and trees (conifer and deciduous trees) (DP Barcode D262918, D262919, D279 087, D279088) should be referred to for the evaluation of potential risk of la mbda-cyhalothrin to terrestrial organisms resulting from the proposed uses on cereal grains, cucurbit vegeta bles, grass forage, fodder and hay, wild rice and tuberous and corm vegetables.

Table 4. Upper-Bound Dietary-based EECs (ppm) for Lambda-cyhalothrin in Various Food Items a

Concentrations in Wildlife Food items (ppm) Crops or Crop Groups and Application Information b Short Grass Tall Grass Broadleaves/ Forage/ Small insects Seeds/ Large Insects

Current Proposed Uses (Based on T-REX output)

Cucurbits (aerial, 0.03 lb/acre, 6x, 5 days) 34 16 19 2

Rice (aerial, 0.04 lb/acre, 3x, 5 days) 26 12 15 2

Cereal (aerial, 0.03 lb/acre, 2x, 3 days) 14 6 8 1

Previously Registered Uses (Based on Ell-Fate Output in 2002)

Fruiting vegetables (aerial, 0.03 lb/acre, 12x, 5 days) 53 24 30 3

Stone fruit, (aerial, 0.04 lb/acre, 5x, 5 days) 40 18 22 3

Tree nuts (aerial, 0.04 lb/acre, 4x, 5 days) 33 15 19 2

Wheat (aerial, 0.03 lb/acre, 2x, 3 days) 14 6 8 1

Conifer and deciduous trees (aerial, 0.04 lb/acre, 12x, 5 days) 74 34 42 5

a EEC equivalent dose = Upper- bound Kenega value * (%BW consumed/100). %BW consumed = 114%, 65%, and 29% for small, medium, and large birds, respectively.

b All application information was derived from the proposed product label. The T- REX default half-life of 35-days was used for modeling purposes because appropriate fo liar dissipation data were unavailable.



### C. Conceptual Model

1. Risk Hypotheses

Risk hypotheses are specific assumptions about potentia l adverse effects (i.e., changes in assessment endpoints) and may be based on theory and logic, em pirical data, mathematical models, or probability models (US EPA 2004). For this assessment, the risk is stressor-initiated, where th e stressor is the release of lambda-cyhalothrin to the environment. The foll owing risk hypothesis is presumed for this screening level assessment:

The use of lambda-cyhalothrin on agricultural cr ops involves situations where terrestrial and/or aquatic animals may be exposed to the chemical . Based on lambda-cyhalothrin’s persistence, mode of action, direct toxicity and potential i ndirect effects to trophic food webs, EFED assumes that this compound has the potential to cause reduced survival/reproductive ability and growth impairment in both terrestrial and aquatic organisms.

1213 

### In order for a chemical to pose an ecological risk , it must reach ecological receptors in biologically significant concentrations. An exposure pathway is the means by which a pesticide moves in the environment from a source to an ecological receptor. For an ecological exposure pathway to be complete, it must have a source, a release mechanism, an envi ronmental transport medium, a point of exposure for ecological receptors, and a feasible route of expos ure. In addition, the potential mechanisms of transformation (i.e., which transformation products may form in the environment, in which media, and how much) must be understood, especially for a chem ical whose metabolites/transformation products are of greater toxicological concern than the parent compound. The assessment of ecological exposure pathways, therefore, includes an examination of the source and potential migration pathways for constituents, and the determination of potential exposure routes (e.g., ingestion, inhalation, and dermal absorption).

Ecological receptors that may potentially be exposed to lambda-cyhalothrin and its transformation products include terrestrial and semi-aquatic wildlif e (i.e., mammals, birds, amphibians, and reptiles), terrestrial and semi-aquatic plants, and soil invert ebrates. Aquatic receptors (e.g., freshwater and estuarine/marine fish and invertebrates, and amphibi ans) may also be exposed as a result of potential migration of lambda-cyhalothrin via spray drift and/ or runoff/ erosion from the site of application to various watersheds and othe r aquatic environments. This informat ion formed the basis for identifying potential endpoints, stressors, and ecological effect s associated with uses of lambda-cyhalothrin.



### 2. Diagram

Based on the preliminary iterative process of examining fate and effects data, the conceptual model or the risk hypothesis model for spray application to agri cultural crops has been established, refined and included in Figure 2. In establishing the diagram for the con ceptual model it was necessary to go through an iterative process to identify: (1) likely stressors/exposure pathways and (2) organisms that are most relevant and applicable to this assessment. The su mmary of the available environmental fate data is presented in Appendix C

.Figure 2. Ecological conceptual exposure model for spray applications of lambda-cyhalothrin.StressorLambda-cyhalothrin applied as ground/aerial spray to agricultural cropsSource/TransportPathw aysVolatilization/ WindSuspensionDirectDepositionSprayDriftRunoff/ErosionLeachingInfiltration/PercolationSource/ExposureMediaTerrestrial FoodResidues (foliage,fruit, insects)UplandFoliage/SoilRiparian/WetlandFoliage/SoilWater Column,SedimentGroundwaterExposurePointIngestion & DermalUptakeDirect contact and root uptakeGill/ IntegumentUptake andIngestionReceptorsAttributeChangesTerrestrial Organisms:Birds,Mammals,Reptiles,TerrestrialInsectsTerrestrialUplandPlantsIndividual AnimalsReduced survivalReduced growthReduced reproductionAquaticInvertebratesand VertebratesAmphibiansWetland/RiparianPlantsIndividual PlantsSeedling emergenceVegetative vigorIndividual AnimalsReduced survivalReduced growthReducedreproductionPlant populationReducedpopulationgrowth** The dotted lines represent unlikely routes of exposureFood Web Exposure(Bioaccumulation)PiscivorousVertebrates(Birds andmammals)AquaticPlants15 

### III. Risk Characterization

A. Risk Estimation

Results of the exposure and toxicity effects data are used to evaluate the likelihood of adverse ecological effects on non-target species. For the assessment of la mbda-cyhalothrin risks, the risk quotient (RQ) method is used to compare exposure and measured toxicity values (refer to Appendix E ). Estimated environmental concentrations (EECs) are divided by ac ute and chronic toxicity values. The RQs are then compared to the Agency’s levels of c oncern (LOCs). These LOCs, summarized in Appendix E , are the Agency’s interpretive policy and are u sed to analyze potential risk to no n-target organisms and the need to consider regulatory action. These criteria are used to indicate when a pesticide’s use as directed on the label has the potential to cause adverse effects on non-target organisms.



### 1. Risks to Aquatic Animals

To assess risk of lambda-cyhalothrin to non-target aquatic animals (i.e., fish and invertebrates) surface water EECs for lambda-cyhalothrin (parent only) were obtained from the Tier II aquatic model PRZM/ EXAMS based on the label for the proposed new uses (see Table 1 ). This risk assessment uses the peak concentration in surface water, generated from the PRZM/ EXAMS model and the rice model to represent acute exposure to fish and aquatic invertebrates. To represent chronic exposure to aquatic animals, the 21- day average concentration is used for aquatic inverteb rates, and the 60-day average concentration is used for fish. In the absence of toxicity data for benthic organisms, RQs are calculated using surrogate toxicity data from standard water column toxicity bioassays with invertebrates and EECs based on peak (acute exposure) and 21-day (chronic exposur e) pore water concentrations obtai ned from the Tier 2 aquatic model PRZM/ EXAMS (see the Aquatic Exposure section of the Exposure Characterization for additional details). Since no additional data have recently been submitted for lambda-cyhalothrin, the most sensitive toxicity reference values for aquatic animals exposed to lambda-cyhalothrin that were available in the previous Environmental Fate and Effects Division Ecological Risk Assessment (June 12, 2002) for the Section 3 request for new uses of lambda-cyhalothr in on peas and beans, fruiting vegetables, canola, sugarcane, sorghum, wheat, wheat hay and other small gr ains, peanut hay, pome fruit, stone fruit, tree nuts, termite barrier, tobacco, non-cropland and trees (c onifer and deciduous trees) (DP Barcode D262918, D262919, D279087, D279088) were used to calculate RQs as described in Tables 5 to 8 below.



### a. Water Column Exposure- Acute and Chronic Risk to Animals

The LOCs for acute risk (LOC 0.5), acute restrict ed use (LOC 0.1), and acute endangered species (LOC 0.05) are exceeded for both, freshwater and estuarine/ ma rine invertebrates exposed to lambda-cyhalothrin under every exposure scenario considered in this assessment (RQ range = 3.57 to 59.14 and 5.00 to 82.80 for freshwater and estuarine/ marine invertebrates, respectively; Table 5 ).

The LOCs for acute risk, acute restricted use, and acute endangered species are exceeded for both freshwater and estuarine/ marine fish exposed to lam bda-cyhalothrin under the NC sweet potato scenario (maximum RQs = 1.97 and 0.51 for freshwater and estuarine/ marine fish, respectively; Table 5 ). For the wild rice scenario, the LOCs for acute risk, acute rest ricted use, and acute endangered species are exceeded for freshwater fish (RQ = 1.29), but only the acute r estricted use and acute endangered species LOCs are exceeded for estuarine/ marine fish (RQ = 0.33; Table 5 ). For the FL cucumber scenario, the acute restricted use and acute endangered species LOCs are exceeded for freshwater fish (maximum RQ = 0.22; Table 5 ). Only the LOC for acute endangered species is exceeded for estuarine/ marine fish under the FL cucumber scenario (maximum RQ =0.06; Table 5 ).16 

### The LOC for chronic risk (LOC 1) was exceeded for both freshwater and estuarine/ marine invertebrates exposed to lambda-cyhalothrin under every exposure scenario considered in this assessment (RQ range = 2 to 85 and 20 to 850 for freshwater and estu arine/marine invertebrates, respectively; Table 6 ). Chronic RQs for freshwater fish exceeded the chronic risk LOC under the NC sweet potato scenario (maximum RQ = 1.06) and the wild rice scenario (RQ = 2.87), but no other chronic RQs for fish exceeded the chronic risk LOC ( Table 6 ).

Table 5. Comparison of the acute RQs calculated for freshwater and estuarine/marine invertebrates and fish associated with the proposed new agricultural us es of lambda-cyhalothrin. The RQs are based on the most sensitive toxicity values fo r each taxonomic group; the LC 50 /EC 50 values for freshwater invertebrates, estuarine/ marine invertebrates, freshwater fish, and estuarine/ marine fish are 0.007 μ g a.i./L ( Gammarus pulex ; MRID 00152730), 0.005 μ g a.i./L ( Mysidopsis bahia ; MRID 00152729), 0.210 μ g a.i./L ( Lepomis macrochirus ; MRID 151598), and 0.807 μ g a.i./L ( Cyprinodon variegates ; MRID 00153506), respectively. The EEC values ( μ g/L) used to calculate RQs are peak concentrations

. Acute RQs ( EEC/LC 50 or EC 50 )

Invertebrates Fish Exposure Scenario Peak EEC (μg/L) Freshwater Estuarine/ Marine Freshwater Estuarine/ Marine

NC sweet potato (aerial, 0.04 lb/acre, 4x, 7 days); 3.9 % drift d 0.414 59.14 a, b, c 82.80 a, b, c 1.97 a, b, c 0.51 a, b, c

NC sweet potato (ground, 0.04 lb/acre, 4x, 7 days); 1% drift for ground applications 0.414 59.14 a, b, c 82.80 a, b, c 1.97 a, b, c 0.51 a, b, c

Wild rice (aerial, 0.04 lb/acre, 3x, 5 days) 0.270 38.57 a, b, c 54.00 a, b, c 1.29 a, b, c 0.33 a, b

FL cucumber (aerial, 0.03 lb/acre, 6x, 5 days); 3.9% drift d 0.047 6.71 a, b, c 9.40 a, b, c 0.22 a, b 0.06 a

FL cucumber (ground, 0.03 lb/acre, 6x, 5 days); 1% drift for ground applications 0.025 3.57 a, b, c 5.00 a, b, c 0.12 a, b 0.03

a RQ exceeds LOC for acute endangered species ( ≥ 0.05)

b RQ exceeds LOC for acute restricted use ( ≥ 0.1)

c RQ exceeds LOC for acute risk ( ≥ 0.5)

d The default drift assumption for aerial app lications in PRZM/EXAMS is typically 5%. However, a 3.9% drift assumption was empl oyed due to label requirements that specify the use of 150ft buffer. A 3.9% drift estimate is generated using AgDRIFT® under a 150ft bu ffer zone assumption.

Table 6. Comparison of the chronic RQs calculated for freshwater and estuarine/marine invertebrates and fish associated with the proposed new agricultural us es of lambda-cyhalothrin. The RQs are based on the most sensitive toxicity values for each taxonomic group; the NOAEC val ues for freshwater invertebrates, estuarine/marine invertebrates, freshwater fish, and estuarine/marine fish are 0.002 μ g a.i./L ( Daphnia

magna ; MRID 41217501), 0.0002 μ g a.i./L ( Mysidopsis bahia ; Accession Number 073989), 0.031 μ g a.i./L ( Pimephales promelas ; MRID 41519001), and 0.25 μ g a.i./L ( Cyprinodon variegates ; MRID 00152732), respectively. Th e EEC values ( μ g/L) used to calculate RQs for invertebrates and fish are the 21-day and 60- day concentrations, respectively

. Chronic RQs Invertebrates (21-day EEC/NOAEC) Chronic RQs Fish (60-day EEC/NOAEC) Exposure Scenario 21- day EEC (μg/L) Freshwater Estuarine/ Marine 60- day EEC (μg/L) Freshwater Estuarine/ Marine

NC sweet potato (aerial, 0.04 lb/acre, 4x, 7 days); 3.9 % drift b 0.048 24.00 a 240.00 a 0.033 1.06 a 0.13

NC sweet potato (ground, 0.04 lb/acre, 4x, 7 days); 1% drift for ground applications 0.048 24.00 a 240.00 a 0.033 1.06 a 0.1317 Table 6. Comparison of the chronic RQs calculated for freshwater and estuarine/marine invertebrates and fish associated with the proposed new agricultural us es of lambda-cyhalothrin. The RQs are based on the most sensitive toxicity values for each taxonomic group; the NOAEC val ues for freshwater invertebrates, estuarine/marine invertebrates, freshwater fish, and estuarine/marine fish are 0.002 μ g a.i./L ( Daphnia

magna ; MRID 41217501), 0.0002 μ g a.i./L ( Mysidopsis bahia ; Accession Number 073989), 0.031 μ g a.i./L ( Pimephales promelas ; MRID 41519001), and 0.25 μ g a.i./L ( Cyprinodon variegates ; MRID 00152732), respectively. Th e EEC values ( μ g/L) used to calculate RQs for invertebrates and fish are the 21-day and 60- day concentrations, respectively

. Chronic RQs Invertebrates (21-day EEC/NOAEC) Chronic RQs Fish (60-day EEC/NOAEC) Exposure Scenario 21- day EEC (μg/L) Freshwater Estuarine/ Marine 60- day EEC (μg/L) Freshwater Estuarine/ Marine

Wild rice (aerial, 0.04 lb/acre, 3x, 5 days) 0.170 85.00 a 850.00 a 0.089 2.87 a 0.36

FL cucumber (aerial, 0.03 lb/acre, 6x, 5 days); 3.9% drift b 0.011 5.50 a 55.00 a 0.007 0.23 0.03

FL cucumber (ground, 0.03 lb/acre, 6x, 5 days); 1% drift for ground applications 0.004 2.00 a 20.00 a 0.003 0.10 0.01

a RQ exceeds the LOC for chronic risk ( ≥ 1)

b The default drift assumption for aerial appli cations in PRZM/EXAMS is typically 5%. However, a 3.9% drift assumption was emplo yed due to label requirements that specify the use of 150 ft buffer. A 3.9% drift estimate is generated using AgDRIFT® under a 150 ft buf fer zone assumption.



### b. Sediment Exposure- Acute Risk to Benthic Organisms

The LOCs for acute risk (LOC 0.5), acute restrict ed use (LOC 0.1), and acute endangered species (LOC 0.05) are exceeded for both, freshwater and estuarine / marine benthic organisms exposed to lambdacyhalothrin, under the NC sweet potato exposure scen ario (maximum RQs = 1.13 and 1.58 for freshwater and estuarine/marine benthic organisms, respectively; Table 7 ). Under the FL cucumber scenario, there are exceedances of the acute restricted use and acute endangered species LOCs for both, freshwater, and estuarine/ marine benthic organisms (maximum RQs = 0.19 and 0.27 for freshwater and estuarine/ marine benthic organisms, respectively; Table 7 ).

The LOC for chronic risk (LOC 1) was exceeded for both freshwater and estuarine/ marine benthic organisms exposed to lambda-cyha lothrin under the NC sweet potato exposure scenario (maximum RQs= 3.87 and 38.65 for freshwater and estuarine/ marine benthic organisms, respectively; Table 8 ). Under the FL cucumber scenario, there are ex ceedances of the chronic risk LOC for estuarine/marine benthic organisms (maximum RQ = 6.65), but not for freshwater benthic organisms (maximum RQ = 0.67; Table 8 ).

Table 7. Comparison of the acut e RQs calculated for freshwater and estuarine/marine benthic organisms associated with the proposed new agricultural uses of lambda-cyhalothrin. The lowe st acute toxicity values reported in freshwater invertebrates (EC 50 = 0.007 μ g a.i./L in Gammarus pulex ; MRID 00152730) and estuarine/marine invertebrates (EC 50 = 0.005 μ g a.i./L in Mysidopsis bahia ; MRID 00152729) were used as surrogate toxicity values for sediment-dwelling organism s exposed to lambda-cyhalothrin in pore water. The EEC values ( μ g/L) used to calculate RQs are peak concentrations

. Acute RQ Benthic Organisms Exposure Scenario Peak Pore Water EEC

( μ g a.i./L) Freshwater Estuarine/Marine

NC sweet potato (aerial, 0.04 lb/acre, 4x, 7 days); 3.9 % drift d 0.00790 1.13 a, b, c 1.58 a, b, c18 Table 7. Comparison of the acut e RQs calculated for freshwater and estuarine/marine benthic organisms associated with the proposed new agricultural uses of lambda-cyhalothrin. The lowe st acute toxicity values reported in freshwater invertebrates (EC 50 = 0.007 μ g a.i./L in Gammarus pulex ; MRID 00152730) and estuarine/marine invertebrates (EC 50 = 0.005 μ g a.i./L in Mysidopsis bahia ; MRID 00152729) were used as surrogate toxicity values for sediment-dwelling organism s exposed to lambda-cyhalothrin in pore water. The EEC values ( μ g/L) used to calculate RQs are peak concentrations

. Acute RQ Benthic Organisms Exposure Scenario Peak Pore Water EEC

( μ g a.i./L) Freshwater Estuarine/Marine

NC sweet potato (ground, 0.04 lb/acre, 4x, 7 days); 1% drift for ground applications 0.00790 1.13 a, b, c 1.58 a, b, c

FL cucumber (aerial, 0.03 lb/acre, 6x, 5 days); 3.9% drift d 0.00135 0.19 a, b 0.27 a, b

FL cucumber (ground, 0.03 lb/acre, 6x, 5 days); 1% drift for ground applications 0.00065 0.09 a 0.13 a, b

a RQ exceeds LOC for acute endangered species ( ≥ 0.05)

b RQ exceeds LOC for acute restricted use ( ≥ 0.1)

c RQ exceeds LOC for acute risk ( ≥ 0.5)

d The default drift assumption for aerial appli cations in PRZM/EXAMS is typically 5%. However, a 3.9% drift assumption was emplo yed due to label requirements that specify the use of 150 ft buffer. A 3.9% drift estimate is generated using AgDRIFT® under a 150 ft buf fer zone assumption.

Table 8. Comparison of the chronic RQs calculated for freshwater and estuarin e/marine benthic organisms associated with the proposed new agricultural uses of lambda-cyhalothrin. Th e lowest chronic toxicity values reported in freshwater invertebrates (NOAEC = 0.002 μ g a.i./L in Daphnia magna ; MRID 41217501) and estuarine/marine invertebrates (NOAEC = 0.0002 μ g a.i./L in Mysidopsis bahia ; Accession Number 073989) were used as surrogate toxicity values for sediment-dw elling organisms exposed to lambdacyhalothrin in pore water. The EEC values reflect 21-d ay pore water estimates that are in equilibrium with sediment concentrations (average K OC = 333,200).

Chronic RQ Benthic Organisms Exposure Scenario 21-day Pore Water EEC ( μ g a.i./L) Freshwater Estuarine/Marine

NC sweet potato (aerial, 0.04 lb/acre, 4x, 7 days); 3.9 % drift b 0.00773 3.87 a 38.65 a

NC sweet potato (ground, 0.04 lb/acre, 4x, 7 days); 1% drift for ground applications 0.00773 3.87 a 38.65 a

FL cucumber (aerial, 0.03 lb/acre, 6x, 5 days); 3.9% drift b 0.00133 0.67 6.65 a

FL cucumber (ground, 0.03 lb/acre, 6x, 5 days); 1% drift for ground applications 0.00064 0.32 3.20 a

a RQ exceeds the LOC for chronic risk ( ≥ 1)

b The default drift assumption for aerial appli cations in PRZM/EXAMS is typically 5%. However, a 3.9% drift assumption was emplo yed due to label requirements that specify the use of 150 ft buffer. A 3.9% drift estimate is generated using AgDRIFT® under a 150 ft buf fer zone assumption.



### 2. Risks to Aquatic Plants

To assess risk of lambda-cyhalothrin to non-target aquatic plants (i.e., fish and invertebrates) surface water EECs for lambda-cyhalothrin (parent only) were obt ained from the Tier II aquatic model PRZM/ EXAMS based on the label for the proposed new uses (see Table 1 ). This risk assessment uses the peak concentration in surface water, generated from the PRZM/ EXAMS model to freshwater aquatic nonvascular plants. Since no additional data have recently been submitted for lambda-cyhalothrin, the most sensitive toxicity reference values for aquatic organisms exposed to lambda-cyhalothrin that were available19 

### in the previous Environmental Fate and Effects Divi sion Ecological Risk Assessment (June 12, 2002) for the Section 3 request for new uses of lambda-cyhalot hrin on peas and beans, fruiting vegetables, canola, sugarcane, sorghum, wheat, wheat hay and other small gr ains, peanut hay, pome fruit, stone fruit, tree nuts, termite barrier, tobacco, non-cropland and trees (c onifer and deciduous trees) (DP Barcode D262918, D262919, D279087, D279088) were used to calculate RQs as described in Table 9 below.

Toxicity data are either inadequate or unavailabl e to calculate RQs based on the following measurement endpoints (e.g., acute or chronic toxic ity reference values) and receptors:

 EC 50 

### values for estuarine/marine and freshwater vascular aquatic plants

 EC 50 

### values for estuarine/marine non-vascular aquatic plants

As can be seen below in Table 9 , none of the acute RQs for freshwa ter non-vascular plants exceeded the LOC (1) for any of the modeled crop use scenarios in this assessment. RQs ranged from 0.0001 to 0.0013 for both non-endangered and endangered species.

Table 9. Comparison of the acute RQs calculated for freshwater non-vascular aquatic plants associated with the proposed new agricultural uses of lambda-cyhalothrin. The RQs are based on the EC 50 and NOAEC values of >310 μ g a.i./L and 310 μ g a.i./L ( Selenastrum capricornutum ; MRID 00152731), respectively. The EEC values ( μ g/L) used to calculate RQ s are peak concentrations

. Exposure Scenario Peak Water Column EEC

( μ g a.i./L) RQs Non-Endangered Species a RQs Endangered

Species a

NC sweet potato (aerial, 0.04 lb/acre, 4x, 7 days); 3.9 % drift b 0.414 0.0013 0.0013

NC sweet potato (ground, 0.04 lb/acre, 4x, 7 days); 1% drift for ground applications 0.414 0.0013 0.0013

Wild rice (aerial, 0.04 lb/acre, 3x, 5 days) 0.270 0.0009 0.0009

FL cucumber (aerial, 0.03 lb/acre, 6x, 5 days); 3.9% drift b 0.047 0.0002 0.0002

FL cucumber (ground, 0.03 lb/acre, 6x, 5 days); 1% drift for ground applications 0.025 0.0001 0.0001

a All RQs are below the LOCs for aquatic plants ( ≥ 1)

b The default drift assumption for aerial appli cations in PRZM/EXAMS is typically 5%. However, a 3.9% drift assumption was emplo yed due to label requirements that specify the use of 150 ft buffer. A 3.9% drift estimate is generated using AgDRIFT® under a 150 ft buf fer zone assumption.



### 3. Risks to Terrestrial Animals an d Non-target Terrestrial and Semiaquatic Plants

Please refer to the section of the Risk Description in this assessment entitled, “Risks to Terrestrial Organisms,” for information on the risks to terrestrial animals and non-target terrestrial and semi-aquatic plants.



### B. Risk Description

Based on lambda-cyhalothrin’s fate properties and toxic ity profile, this screening level risk assessment has identified acute risk to non-target listed and non-list ed freshwater and estuarie/ marine invertebrates, freshwater and estuarie/marine fish, freshwater and es tuarine/ marine benthic organisms, mammals, and insects, and chronic risk to freshwater and estuarine/ marine invertebrates, freshwater fish, freshwater and estuarine/ marine benthic organisms, birds, re ptiles, and mammals resulting from the proposed use patterns. Although acute risk estimates for freshwate r non-vascular plants are below the Agency’s LOCs,20 

### acute risk to aquatic vascular plants and terrestrial plants could not be evaluated due to the lack of acceptable toxicity data.



### 1. Risks to Aquatic Organisms

In the 2002 Section 3 for lambda-cyhalothrin, the Es timated Environmental Concentrations (EECs) for aquatic environments resulted in numerous exceedan ces of both acute and chronic LOCs for water column-dwelling animals; since the usage patterns of the registered uses assessed in EFED’s 2002 Section 3 risk assessment and the proposed new uses are similar ( Table 1 ), it was expected that there would be similar exposure and risk to the same taxonomic gr oups for the proposed new uses. However, the comparison of actual water column EECs resulting from the already registered and the current proposed new uses in Table 2 demonstrates that the highest peak, 21-day, and 60-day EECs for the proposed new uses are roughly double to quadruple the highest peak, 21-day, and 60-day EECs generated in the previous assessment; therefore, risk estimat es for the maximum exposure scenarios considered in this assessment for the proposed new uses were two to four times higher than the risk estimates based on the maximum exposure scenarios considered for the registered uses.

Table 2 also demonstrates that there is very little change in the predicted peak water concentrations for the maximum exposure scenario considered in this assessme nt (NC sweet potato) when drift assumptions for the scenario are varied (i.e., ground application vs. aeria l application vs. 0% drift). This suggests that the major route of exposure to aquatic environmen ts under the maximum exposure scenario is via runoff/erosion. However, under the FL cucumber s cenario, exposure concentrations are doubled when applications are made via aerial equipment rather than via ground equipment or when 0% drift was assumed. This suggests that the contribution to th e peak EEC from runoff/erosion for this scenario was low, and changes in the peak EECs were due to drift. Variation in actual risk estimates with changes in assumptions for the proposed new uses can be found in Tables 5 to 9

.

Due to its high K OC 

### , lambda-cyhalothrin is expected to be immobile in soil envi ronments (average K OC 

### = 333,200 mL/g, n=10). It is highly unlikely to r each ground waters; however, despite the protective imposed buffer zone and buffer strip, it could reach adj acent surface waters via spray drift or runoff events (accompanied by erosion). Once there, the chemical may partition with the sediment and organic matter, and will linger for periods of time of many months to a year (aquatic metabolism half-lives on the order of 113-142 days). The sediment serves as a repository of the chemical after numerous applications, in dynamic equilibrium with the pore water and the surface wa ter. There is a source of uncertainty, related to the two types of buffers imposed by the labels of lambda-cyhalothrin. PRZM/ EXAMS with the aid of AgDRIFT®, can account (quantify) for the reduction in th e level of spray drift due to a buffer zone of 150 ft (for aerial applications), when a scenario is driven by drift, such as in the case of the FL cucumbers scenario. However, at this time, the EFED does not have a tool to allow to account for the possible mitigation that a maintained vegetative filter strip 10 ft wide may produce, when a scenario is driven by runoff with erosion, as in the case of the NC sweet pot atoes scenario. Due to th is uncertainty, since it is likely that the buffer strip is offering mitigation to runoff, it appears that the actual risk posed by lambdacyhalothrin could be lower than predicted by the models.

There is also a level of uncertainty in the analysis and risk characterization presented in this document, due to the fact that one of the scenarios was analyzed using the Tier I aquatic rice model, while the other two scenarios were analyzed with the Tier 2 aquatic model PRZM/ EXAMS. Despite the fact that the result of the rice model was refined to obtain chronic values, pressumably, the Tier 2 aquatic model provides more reliable and realistic EECs.21 

### a. Aquatic Animals and Plants: Water Column Exposure

Unlike the previous risk assessment that considered risk only to water column-dwelling organisms, evaluation of risk to aquatic organisms in this assessme nt was approached by dividing the aquatic system into two very general compartments, the water column and the benthos. The first compartment, the water column, which is defined as the aquatic area between surface and the benthos (approximately 6 inches above the bottom), represents an area where organisms are free-swimming and can feed and breed at the surface, mid water and/ or on the benthos (sediment). Direct pesticidal contact (e.g., gill lamella, ingestion, and integument) to these organisms is assumed to be from the surface water via drift and/or runoff. Based on the available information provided from the label and registrant, the Agency has identified acute and chronic risk concerns to aquatic organisms for a pplications of lambda-cyhalothrin. Specifically, these concerns include risk to listed and non-listed fish, aquatic crustaceans, snails, clams, aquatic insects, and amphibians.

This assessment has confirmed that aquatic areas adj acent to fields where lambda-cyahalothrin is applied may be at risk should exposure occur, and that the risk is greatest for aerial applications. In addition, a comparison of the acute RQs among the aquatic animals show that the invertebrates are significantly more at risk than fish, although acute RQs for both freshwa ter and estuarine/ marine invertebrates and fish are well above the LOCs. The acute risk quotients for freshwater invertebrates (highest RQ=59.14) are approximately 30-fold greater than those for freshwa ter fish (highest RQ=1.97), and the acute risk quotients for estuarine/ marine invertebrates (highest RQ=82.8) are approximately 162-fold greater than those for estuarine/ marine fish (highest RQ=0.51). For chronic risk, the same pattern is demonstrated, as chronic risk quotients for freshwater invertebrates (highest RQ=85) are approximately 30-fold greater than those for freshwater fish (highest RQ=2.87), and the chronic risk quotients for estuarine/ marine invertebrates (highest RQ=850) are approximately 2361 -fold greater than those for estuarine/ marine fish (highest RQ=0.36).

Based on the highest acute RQ of 82.8 and an LOC of 0.05 for endangered species, the peak EECs would have to be approximately 1700 times lower to ensu re that all RQs for aquatic water column-dwelling organisms are below all acute risk LOCs. Based on th e highest chronic RQ, chronic EECs would have to be reduced by approximately 850 times to ensure that all RQs for aquatic water column-dwelling organisms are below the chronic risk LOC.

Risk quotients derived for freshwater non-vascular aquatic plants indicate that the risk is low. Risk to estuarine/ marine non-vascular plants and freshwater a nd estuarine/ marine vascular plants could not be evaluated due to the lack of toxicity data. However, based on lambda-cyhalothrin’s neural toxic mode of action, the lack of studies demonstrating adverse effect s of lambda-cyhalothrin or any other pyrethroid to plants, and the fact that no incident reports have reliably linked lambda-cyhalo thrin or any other compound in the synthetic pyrethroid class of chemicals to phytotoxic effects despite being applied on or near agricultural plants, it appears unlikely that it poses a phytotoxic concern.



### b. Aquatic Animals: Sediment Exposure

Although this compound binds readily to particulate and organic carbon in the water column (average K OC 

### = 333,200), possibly limiting bioavailability (in terms of freely-dissolved lambda-cyhalothrin) in this media, the bound residues settle onto the benthos, in creasing their concentrations in the sediment. Exposure to this sediment can result in a direct impact to aquatic life through respiration, ingestion, dermalcontact, as well as indirect impact through alterations of the food chain. Coupled with lambdacyhalothrin’s expected persistence in anaerobic environments, sediment bound lambda-cyhalothrin could22 

### present a toxicity risk for benthic and epibenthic aquatic life, and aquatic ecosystems in general. Therefore, the second aquatic compartment that was c onsidered was the benthos, which is composed of sediments and an area 6 inches above the sediment (epibe nthos). The benthos is composed of a diversity of aquatic invertebrates (e. g., insect larvae, crustaceans, molluscs) and species of fish (e.g., catfish), as well as certain critical life stages of organisms that reside in the water column; the benthos is also the initial breeding strata and nursery area for several species of fish, especially commercial species such as salmonids. The benthos can also be a source of food items for several species of fish that are actively feeding on the organisms in the sediment and/or captu ring organisms that are emerging from this area.

The evaluation of toxic risk to th e benthic organisms was approached by assuming equilibrium partitioning of a high K OC 

### compound like lambda-cyhalothrin between th e sediment and the pore water (i.e., the water found between particulates in the sediment). Risk to the benthos was assessed, using EECs for pore water that were model-generated (PRZM/ EXAMS). In addition, EFED assumes that benthic organisms are no more sensitive to toxic compounds than those organi sms living in the water column, and measures of effects used in calculating RQ values for pore water exposure were derived from standard water column studies in the absence of sediment toxicity data (e.g., LC 50 

### , EC 50 

### ). Although sediment systems are assumed to adsorb a large portion of lambda-cyhalothr in over a short period of time, EFED chose to use the resulting concentrations in pore water that are at equilibrium with sediment loads for the EECs.

EFED stresses that the Equilibrium Partitioning model is a screening-level tool and notess that there is uncertainty regarding the amount of sorbed pesticide that may contribute to the toxicity of organisms, that the model generated sediment/pore water values may be an overestimation or un derestimation of actual exposure values noted in the laboratory or field, and th at inherent variations in biological uptake as result of differences in feeding pathways, organism life st age, and population-level effects versus individual responses could affect the toxicity of sorbed pesticid e to benthic organisms. In addition, it should be stressed that exposure and risk to benthic organisms may be significantly underestimated in this assessment because it was assumed that the main source of contact of lambda-cyhalothrin to the sediment dwellers is the pore water; however, these organisms ma y be in constant contact with the sediments and even feed from them or from other small organism s that are contaminated, thereby increasing their exposure and potential for toxic effects. In order to generate sound estimates of risk in future assessments, it is critical to account for all of these factors (e.g., in terstitial water respiration, sediment ingestion or other sediment integument exchange) by using actual sediment toxicity values based on both pore water exposure and sediment exposure. Therefore, acute a nd chronic sediment toxicity data are needed to confirm the findings of this screening-level tool and to fully characterize eff ects to these animals. For additional discussion of the assumptions and uncertainties of the EqP approach, please refer to Appendix A

. Based on the available information provided and th e equilibrium-partinioning theory, the Agency has identified acute and chronic risk concerns to aqua tic freshwater and estuarine /marine benthic-dwelling organisms for applications of lambda-cyhalothrin ( Tables 7 and 8 ). Acute RQs range from 0.09 to 1.3 and 0.13 to 1.58 for freshwater and estuarine/marine bent hic organisms, respectively, with exceedances of acute risk, acute restricted, and acute endangered sp ecies LOCs. Chronic risk LOC is exceeded, and RQs range from 0.32 to 3.87 and 3.20 to 38.65 for fr eshwater and estuarine/marine benthic organisms, respectively.

Based on the highest acute RQ of 1.58 and an LOC of 0.05 for endangered species, the peak EECs would have to be approximately 32 times lower to ensure that all RQs for aquatic benthic-dwelling organisms are below all acute risk LOCs (acute risk, acute restri cted, and acute endangered species). Based on the highest chronic RQ, chronic EECs would have to be reduced by approximately 39 times to ensure that all RQs for aquatic benthic-dwelling organisms are below the chronic risk LOC.23 

### 2. Risks to Terrestrial Organisms

As mentioned previously, an examimation of Table 1 reveals that the usage patterns are similar between the registered uses assessed in EFED’s 2002 Secti on 3 risk assessment and the proposed new uses, and therefore, the terrestrial EECs and risks are expected to be similar. In fact, the acute and chronic risk estimates for birds and mammals should be roughly e quivalent for the maximum exposure scenario for the proposed new uses (EEC range = 2 to 34; based on 6 aerial applications under a 5-day interval to cucurbits at a maximum rate of 0.03 lb a.i./ acre) and the prev iously assessed tree nut scenario (EEC range = 2 to 33; based on 4 aerial applications under a 5-day interval to tree nuts at a maximum rate of 0.04 lb a.i./ acre), since the EECs of chemical residues on potential forage items for the two scenarios are approximately the same ( Table 4 ). Therefore, the Environmental Fate and Effects Division’s Ecological Risk Assessment (June 12, 2002) for the Section 3 request for new uses of lambda-cyhalothrin on peas and beans, fruiting vegetables, canola, sugarcane, sorghum, wheat, wheat hay and other small grains, peanut hay, pome fruit, stone fruit, tree nuts, termite barrier, tobacco, non-cropland and trees (conifer and deciduous trees) (DP Barcode D262918, D262919, D279087, D279088) should be referred to for estimates and characterization of risk to all terrestrial organisms resulting from the proposed uses on cereal grains, cucurbit vegetables, grass forage, fodder and hay, wild ri ce and tuberous and corm vegetabl es. In summary, based on lambdacyhalothrin’s fate properties and toxicity profile, the 2002 review identified acute risk to non-target listed and non-listed mammals, and chronic risk to birds, reptiles, and mammals resu lting from the proposed use patterns. Although quantitative risk estimates for te rrestrial non-target insects were not made, available data on honey bee acute contact studies suggest that lambda-cyhalothrin is highly toxic to honeybees (LD50 = 0.038 μ g a.i./bee) and that the potential risk to polli nators and other beneficial insects from use of lambda-cyhalothrin is very high. In addition, risks to non-target terrestrial and semi-aquatic plants could not be evaluated due to the lack of toxicity data; however, based on lambda-cyhalothrin’s neural toxic mode of action, the lack of studies demonstrating adverse effects of lambda-cyhalothrin or any other pyrethroid to plants, and the fact that no incident reports have reliably linked lambda-cyhalothrin or any other compound in the synthetic pyrethroid class of ch emicals to phytotoxic effects despite being applied on or near agricultural plants, it appears un likely that it poses a phytotoxic concern.



### IV. References

Di Toro DM, Zarba CS, Hansen DJ, Berry WJ, Swar tz RC, Cowan CE, Pavlou SP, Allen HE Thomas NA, Paquin PR. 1991. Technical basis for establishing sediment quality criteria for nonionic organic chemicals using equilibrium partitioning. Environ Toxicol Chem 10:1541-1583.

Fletcher, J.S., J.E. Nellessen, and T.G. Pfleeger. 1994. Literature review and evaluation of the EPA food-chain (Kenaga) nomogram, an instrument for est imating pesticide residues on plants. Env. Toxicol. Chem. 13:1381-1391.

Hoerger, F. and E. E. Kenaga. 197 2. Pesticide residues on plants: correlation of representative data as a basis for estimation of their magnitude in the environment. in : F. Coulston and F. Korte (editors), Environmental Quality and Safety: Chemistry, To xicology, and Technology. Vol I. Georg Thieme Publishers, Stuttgart, West Germany, pp. 9-28.

Pfleeger, T.G., A. Fong, R. Hayes, H. Ratsch and C. Wickliff. 1996. Field evaluation of the EPA (Kenaga) nomogram, a method for estimating wildlife exposure to pesticide residues on plants. Env. Toxicol. Chem. 15:535-543, 1996.24 

### Ramasamy S, Maher I, Jennings P, Abel S. June 12, 2002. Environmental Fate and Effects Division Ecological Risk Assessment for the Section 3 request for new uses of lambda-cyhalothrin on peas and beans, fruiting vegetables, canola, sugarcane, sorghum, wheat, wheat hay and other small grains, peanut hay, pome fruit, stone fruit, tree nuts, termite barrier, tobacco, non-cropland and trees (conifer and deciduous trees). DP Barcode D2629 18, D262919, D2790 87, D279088.

T-REX. 2005. Terrestrial Residue Exposure Mode l (T-REX), Version 1.2.3. August 8, 2005. Environmental Fate and Effects Division, Office of Pesticide Programs, U.S. Environmental Protection Agency, Washington, D.C.

U.S. EPA. 2004. U.S. Environm ental Protection Agency. Overview of the Ecological Risk Assessment Process in the Office of Pesticide Programs, U.S. Environmental Protection Agency: Endangered and Threatened Species Effects Determinations. Office of Prevention, Pesticide, and Toxic Substances. January 23.

Willis, G.H. and L.L. McDowell. 1987. Pesticide persistence on foliage. Re views of Environmental Contamination and Toxicology, Vol. 100, page 23 (Springer-Verlag, New York, Inc)25 

### IV. Appendices



## Appendix A. Aquatic Exposure Information

Measures of Exposure for Aquatic Modeling

• For aerial applications, the measurement of the level of drift was performed with the model AgDRIFT®, in the Tier I Aerial Mode, which is cap able to determine “quantitatively” the level of drift to the EXAMS standard pond from a predetermined buffer zone.

• For agricultural uses, exposure concentrations fo r aquatic ecosystems assessments were estimated based on EFED’s Tier 2 aquatic model PRZM/EXAMS. A graphical user interface (pe4), developed by the EPA < http://www.epa.gov/oppefed1/models/water >, was used to facilitate inputting chemical and use specific parameters into the appropriate PRZM input files (inp) and EXAMS chemical files. This approach empl oys PRZM, which simulates the processes in the agricultural field, such as runoff and erosion, on a daily time step. The runoff and erosion flux output data from PRZM are used as chemical loadings to EXAMS, which simulates surface water in order to predict the EECs. Two PRZM field (crop) scenarios were modeled: FL cucumbers and NC sweet potatoes . These scenarios represented crops with the highest application rates, among the available crop-scenarios representative of the new uses of lambda-cyhalothrin (see additional notes below). EECs for ecological risk assessment were determined using a pond modeling scenario which describes a generi c scenario for the EXAMS component of the modeling exercise.

• Since lambda-cyhalothrin binds to organic carbon (mean K OC 

### = 333,200 mg/L), and could accumulate in aquatic sediment, toxic exposure to organisms living in this media is a concern. EFED has estimated lambda-cyhalothrin sediment exposure to benthic organisms by calculating pore water exposure values using the PRZM/ EXAM S model. Screening level RQs for sediment dwelling organisms were estimated with an ex trapolation method recommended by the Office of Water (USEPA). This was based on the Agency Equilibrium Partitioning Sediment Guidelines (ESG) under the Clean Water Act [CWA Section 30 4(a)(2)]. After consultation with the OW, EFED adopted the equilibrium partitioning (EqP) me thod to be used when sediment toxicity and exposure data are not available (see below). The EqP theory holds that a nonionic compound in the sediment partitions between sediment organi c carbon, interstitial (pore) water and benthic organisms (Di Toro et al. , 1991, U.S. Environmental Protection Agency, 2000). At equilibrium, if the concentration in any phase is known, then the concentration in the other phases can be predicted through the organic/ carbon soil partition coefficient. The EECs are calculated from the pore water concentration (an output from PRZM/ EXAMS) through the K OC



### .

• In order to determine concentrations in a rice pa ddy (for wild rice), the EFED utilized the interim approach, which represents a tier I concept. In sh ort, pesticide is applied to a model rice paddy and instantaneously partitions itself between the wa ter column and the sediment. Both the volume of the water column and the mass of the sedimen t are fixed quantities that were chosen to be reasonably representative of a rice paddy.

• The Rice Model (“Policy for Estimating Aqueous Co ncentrations from Pesticides Labeled for Use on Rice,” 10/29/02 Memorandum, From Steven Bradbury, To EFED), was utilized to obtain EEC for Wild Rice. The value was assumed to be th e “peak” EEC, and refinements were performed to account for aerobic aquatic metabolis m and aqueous photolysis. Even though this is a refinement26 

### of the Tier 1 Rice Model or concept, it is still considered a Tier 1 approach, and the results, conservative.27 

### Aquatic Exposure Modeling

For agricultural uses, exposure concentrations for aquatic ecosystems assessments were estimated based on EFED’s Tier II aquatic models PRZM v3.12 Beta an d EXAMS v2.98.04. A graphical user interface (pe4v01), developed by the EPA < http://www.epa.gov/oppefed1/models/water >, was used to facilitate inputting chemical and use specific parameters into the appropriate PRZM input files (inp) and EXAMS chemical files. The Pesticide Root Zone Model (PRZ M) field or orchard crop scenario is the basic file which describes the local or regional climatological info rmation, soil hydrology, soil characteristics, crop characteristics, and the pesticide properties necessary to determine pesticide loadings to ground or surface water. This basic file constitutes the first part of the “exposure scenario.” It simulates the processes in the agricultural field, such as runoff and erosion, on a da ily time step. The runoff and erosion flux output data from PRZM are used as chemical loadings to E XAMS (Exposure Analysis Modeling System), which simulates surface water in order to predict the Estim ated Exposure Concentrations (EECs). The PRZM scenarios selected for modeling were Florida cucumb ers and North Carolina sweet potatoes. EECs for ecological risk assessment were determined using a pond modeling scenario which describes a standard scenario for the EXAMS component of the modeling exercise (EXAMS Mississippi pond).

To determine the level of spray drift for a buffer zone of 150 ft imposed in the label for this chemical, the model AgDRIFT® v2.01 was utilized. A simple calc ulation was performed with the “toolbox” Deposition Assessment with the Tier 2 level of AgDRIFT® and the following assumptions: drop size distribution ASAE Fine to Medium (D V0.5 

### = 254.72 μm; D V0.9 

### = 443.58 μm), wind speed of 10 mph and boom height of 10 ft. The level of drift (fraction) obtained was 0. 039 (3.9%). The level of drift for ground applications was kept at a conservative 1%.

Following is a table of input parameters for lambda-cyhalothrin. The table provides comments which explain how each input parameter was selected accord ing to the EFED input parameter guidance, version II, dated 02/28/02. The output files from PRZM/EXAMS appear below in this Appendix. This Appendix also provides further information about the models PRZM, EXAMS, AgDRIFT®, the Rice Model and the Equilibrium Partitioning theory.

Table A. Input Parameters Utilized in PRZM/EXAMS lambda-cyhalothrin: Parameter (units) VALUE(S) SOURCES COMMENTS Output File Name lcyhcucu lcyhswpo --- ---

Chemical Name l-cyhalothrin Crop Name FL Cucumber NC Sweet potato Application Rate Cuc. 0.0336 Kg a.i./ha S. pt. 0.0336 Kg a.i./ha Proposed labels for Karate® Insecticideand Warrior® Insecticide. Cucumber 0.03 lb a.i./A Sweet potato 0.03 lb a.i./A

Day of Application (daymonth) Cucumber – 10-11 Swt. Pot. – 01-08 Number of Applications Allowed Cucumber 6 Sweet potato 4 Proposed labels for Karate® Insecticideand Warrior® Insecticide. Minim Interval between Applications (days) Cucumber 5 Sweet potato 7 Proposed labels for Karate® Insecticideand Warrior® Insecticide.28 Table A. Input Parameters Utilized in PRZM/EXAMS lambda-cyhalothrin: Parameter (units) VALUE(S) SOURCES COMMENTS K OC 333,200 mL/g 44861503, 45447413 Average of 10 available values ranging from 110,000 to 724,000 mL/g OC . The K OC model was utilized as per recommendation of the Science Advisory Comity (SAP). Aerobic Soil Metabolism (days) 56.5 00151607, 00089995 Represents the 90 th percentile of the upper confidence bound on the mean for the following six values: 24, 43, 46, 48, 53, 73 days; ave. 47.83; std. dev. 14.46 days. As per current guidance, dated 02/28/02. Incorporation Depth 0.0 Proposed labels for Karate® Insecticideand Warrior® Insecticide. Method of Application Aerial Ground Proposed labels for Karate® Insecticideand Warrior® Insecticide. Buffer Zone (ft.) 150 ft aerial 25 ft ground Proposed labels for Karate® Insecticideand Warrior® Insecticide. Application Efficiency (fraction) 0.95 aerial 0.99 ground Guidance for Selecting Input Parameters inModeling the Environmental Fate and Transport of Pesticides, v.II, 02/28/02 Spray Drift (fraction) 0.039 aerial 0.01 ground AgDRIFT® Tier 2 Aerial Kept at 1.0% Solubility in Water (ppm) At 20°C 0.05 00151580 at pH 6.5; 10X the actual solubility as per current guidance, dated 02/28/02. Aerobic Aquatic Metabolism (days) 44.8 44861506, 44367402 Represents the 90 th percentile of the upper confidence bound on the mean for the following three values: 21, 34, 46 days; ave. 33.67; std. dev. 10.21 days. As per current guidance, dated 02/28/02. Anaerobic Aquatic Metabolism (days) 159.0 44367401, 00151607 Represents the 90 th percentile of the upper confidence bound on the mean for the following two values: 113, 142 days; ave. 127.5; std. dev. 14.5 days.29 Table A. Input Parameters Utilized in PRZM/EXAMS lambda-cyhalothrin: Parameter (units) VALUE(S) SOURCES COMMENTS As per current guidance, dated 02/28/02. Hydrolysis at pH 7 stable 00151604 Aqueous Photolysis @ pH 7 and 25°C (days) 26 44861501 Maximum value

Molecular Weight (g/mol) 449.86 -- Unlabeled Vapor Pressure (torr or mmHg) 1.5x10 -9 INTERNATIONAL PROGRAMME ON CHEMICAL SAFETY (IPCS) Health and Safety Guide No. 38 Henry’s Law Constant (atm-m 3 /mol) 2.4x10 -7 Registrant data

CAM (Chemical Application Method) 1 Soil applied Guidance for Selecting Input Parameters inModeling the Environmental Fate and Transport of Pesticides, v.II, 2/28/02 IPSCND 3 remaining pesticide on foliage is retained as surface residue and continues to undergo decay Guidance for Selecting Input Parameters inModeling the Environmental Fate and Transport of Pesticides, v.II, 2/28/02 FEXTRC, Foliar extraction 0.5 Guidance for Selecting Input Parameters inModeling the Environmental Fate and Transport of Pesticides, v.II, 2/28/02 PLDKRT, Decay rate on foliage (day -1 ) 0 Guidance for Selecting Input Parameters inModeling the Environmental Fate and Transport of Pesticides, v.II, 2/28/02 PLVKRT, Volatilization rate from foliage 0 Guidance for Selecting Input Parameters inModeling the Environmental Fate and Transport of Pesticides, v.II, 2/28/02 UPTKF, Uptake factor 0 Guidance for Selecting Input Parameters inModeling the Environmental Fate and Transport of Pesticides, v.II, 2/28/02 Write Benthic Pore Water Concentrations? Yes

Write benthic sediment file? Yes30 

### Selection of PRZM scenarios and limitations: The crops assessed included Cereal Grains (Barley, Buckwheat, Oat, Triticale, Wheat, Wheat hay), Cucurbit Vegetables [Chayote (fruit), Chinese waxgour d, Citron melon, Cucumber, Gherkin, Ghourd (edible), Momordica species, Muskmelon (hybrids and/or cultivars of Cucumis melo ), Pumpkin, Summer squash (includes various varieties), Winter squash (also includes various types of squash), Watermelon, includes hybrids], Grass Forage, Fodder and Hay (Pasture and rangeland grass, Grass grown for hay or silage, and Grass grown for seeds), Wild Rice, Tube rous and Corm Vegetables [Arracacha, Arrowhoot, Artichoke, Canna (edible), Cassava (bitter and sweet), Chayote (root), Chufa, Dasheen, Ginger, Leren, Sweet potato, Tanier, Turmeric, Yam (bean and true)]. In short, there are five new crop groups for which the registrant is requiring registration: cereal grains, cucurbit vegetables, grass forage, fodder and hay, wild rice, and tuberous and corm vegetables. Since the calculations for the rice model are relatively simple, they were included in the assessment. Of the four cr op groups remaining, grass forage has a seasonal rate of only 0.09 lb a.i./A, and cereal grains has a seasonal application rate of only 0.06 lb a.i./A. Therefore, the EFED concentrated its efforts on cucurbit vegetables (seasonal application rate of 0.18 lb a.i./A) and tuberous and corm vegetables (seasona l application rate of 0.12 lb a.i./A). Two suitable scenarios were available, one per crop group. The Florida cu cumbers crop scenario is representative of cucurbit vegetables, while the North Carolina sweet potatoes cr op scenario is representative of tuberous and corm vegetables.

Table B provides the EECs of lambda-cyhalothrin in the water column. The highest peak EEC was obtained from the NC sweet potato scenario. By comparison, the EECs for the NC sweet potato ground scenario, were identical to all the EECs for the aerial s cenario. On the other hand, the peak EEC for the FL cucumber aerial scenario was around 10 times smaller than the peak EEC for the NC sweet potato. It is also noted that the ground and the 0% drift peak EEC s of the FL cucumber scenario are much smaller than the peak EEC for the aerial run of the same scenario. It appears that the latter scenario has a large component of spray drift, while the NC sweet potato scenario is dominated by runoff/erosion.

Table B. Estimated Environmental Concentrations of Lambda-cyhalothrin in the Water Column in ppb Scenario Peak 21-day 60-day FL cucumber 0.0470 0.0113 0.00710 NC sweet potato 0.414 0.0479 0.0328 FL cucumber ground 0.0246 0.00413 0.00262 NC sweet potato ground 0.414 0.0479 0.0328

FL cucumber 0% drift 0.0228 0.00195 0.00148 NC sweet potato 0% drift 0.409 0.0449 0.0301

Wild rice 0.270



### Rice Model (covers Wild Rice) The Tier I Rice Model was derived in EFED from the following simple relationship (see details about the model below)

EEC = 10 9 M T

------------------ V T + m sed K d31 

### V T 

### = 1.067 x 10 6 

### L/ha

m sed 

### = 130,000 Kg/ha 10 9 

### = units factor K d 

### = partition coefficient, selected as per input guidelines (see above) M T 

### = total mass of pesticide in Kg applied per ha of paddy (application rate in Kg a.i./ha)

EEC = (10 9 

### μg/Kg) (0.134 Kg/ha)

------------------------------------------------------------- 1.067 x 10 6 

### L/ha + (130,000 Kg/ha) (3810 L/Kg)

= 0.270 μg/L = 0.270 ppb

Rice Model Refinement

The rate constants were calculated from the half-lives as follows:

t 1⁄2 

### = -ln (2) / k or k = -ln (2) / t 1⁄2



### Since the formula that describes a first order reaction is:

[A] = e -k total 

### and t 1⁄2 total 

### = (50/100) therefore ln(50/100)= ln (0.5)/-k total 

### [A] o



### t 1⁄2 photolysis 

### = 25 days; k photolysis 

### = - 0.0277 days -1



### t 1⁄2 aerobic aquatic metabolism 

### = 33.7 days; k aerobic aquatic metabolism 

### = - 0.0207 days -1



### the half life is 14.3 days.

For lambda cyhalothrin, [A] 0 

### = 0.270 μg/L, and k total 

### = -0.0485 days -1



### The 21 day average concentration is 0.170 μg/L.)

The 60 day average concentration is 0.089 μg/L.)

For additional details, see below.

Equilibrium Partitioning and Concentr ation in the Sediment/Pore water As mentioned previously, lambda-cyhalothrin is a lipophilic compound that can adsorb readily to particulate and sediment, thus possibly limiting its exposure to aquatic life in the water column but increasing toxic exposure in the benthos. Sediment can act as a reservoir for lipophilic persistent compounds. The sediment and particulate likely adsorb a high percentage of lambda-cyhalothrin TGAI, as indicated by its relatively high K OC 

### . Therefore, coupled with lambda-c yhalothrin’s persistence in aerobic and anaerobic aquatic environments , sediment bound lambda-cyhalothrin TGAI could present a toxicity risk for benthic aquatic life and a quatic ecosystems in general.

Therefore, in order to assess this potential for pesticid e risk to aquatic benthic systems, the Environmental Fate and Effects Division (EFED) of the Office of Pe sticides Program (OPP) has adopted the method used by the Office of Water that relies on equilibrium partiti oning (EqP) of chemicals. The EqP theory is based on the hydrophobicity and concentrations of the chem ical normalized to organic carbon (OC) in sediment (De Toro et al. 1991) and holds that a nonionic chemical in sediment partitions between sediment organic32 

### carbon, interstitial (pore) water and benthic organisms. At equilibrium, if the concentration in any phase is known, then the concentration in the other phases can be predicted. A key component to this theory is the chemicals organic carbon coefficient (K OC 

### ), which is constant for every chemical and represents the ratio of the chemical concentration in water to the con centration in organic carbon. The document, “Technical Basis for the Derivation of Equilibrium Partitioning Sediment Guidelines (ESGs) for the Protection of Benthic Organisms: Nonionic Organics” (Di Toro, et al. 1991), demonstrates that biological responses of benthic organisms to nonionic organic chemicals in sediments are different when the sediment concentrations are expressed on a dry wei ght basis, but similar when expressed on a u g chemical/g organic carbon basis ( u g/g oc 

### ). Similar responses were also observed across sediments when interstitial water concentrations were used to normalize biological av ailability. The Technical Basis Document further demonstrates that if the toxic effect concentration in water is known (e.g., LC 50 

### ), the effect concentration in sediment on a u g/g oc 

### basis can be predicted by multiplying the effect concentration in water by the chemical K oc 

### .

(LC 50 

### u g/L x Koc L/Kg oc 

### x 1 Kg oc 

### /1000g oc 

### = LC 50 

### u g/g oc 

### )

Since, EFED uses a deterministic method for its scree ning level risk assessment, the calculation of risk quotient values (RQ) is important for assessing possible risk. The RQ values are calculated by taking the ratio of the estimated exposure concentrations (EEC) to the toxicity effect value (e.g., LC 50 

### , NOAEC). The EEC values are model generated (e.g., PRZM/EXAMS) and reflect peer evaluated and approved scenarios for assessing pesticide exposure to an aquatic e nvironment. However, the PRZM/EXAMS output produces water column EEC values, as well as pore wate r EEC values. Therefore, to assess possible toxic pesticide exposure to aquatic orga nisms from sediments, EFED is us ing the PRZM/EXAMS to generate EECs for pore water model based on the principles of th e equilibrium partitioning theory, by relying on pore water output values.

The calculations that rely on pore water can be cal culated by dividing the PRZM/EXAMS output value for pore water concentrations by the dissolved concentra tions in the water column that caused toxicity in bioassays using lambda-cyhalothrin TGAI (e.g., LC 50 

### ).

RQ benthic organisms 

### = EEC pore water μg/L / LC50 μg/L

Additional details on the equilibrium partitioning theory can be found below.

Table C provides the EECs for the pore water. The p eak EECs follow a similar trend than the peak EECs for the water column; however, they are just a fraction in magnitude.

Table D provides the sediment concentrations. Note that they are much more higher than the pore water column concentrations.

Table C. Estimated Environmental Concentrations of Lambda-cyhalothrin in the Pore Water in ppb Scenario Peak 21-day 60-day FL cucumber 0.00135 0.00133 0.00125 NC sweet potato 0.00790 0.00773 0.00745 FL cucumber ground 0.000651 0.000641 0.00059 NC sweet potato ground 0.00790 0.00773 0.00745

Table D. Estimated Environmental Concentrations of Lambda-cyhalothrin in the sediment in ppb Scenario Peak 21-day 60-day33 Table D. Estimated Environmental Concentrations of Lambda-cyhalothrin in the sediment in ppb Scenario Peak 21-day 60-day FL cucumber 18.0 17.7 16.7 NC sweet potato 105.5 102.6 99.3 FL cucumber ground 8.68 8.54 7.93 NC sweet potato ground 105.5 102.6 99.3

Information About PRZM, EXAMS, AgDRIFT®, the Ri ce Model and Sediment Calculations (EqP Theory)



### Background Information About PRZM and EXAMS The Tier II aquatic model employs PRZM (Pesticide Root Zone Model; version 3.12 Beta compiled May 24, 2001) and EXAMS (Exposure Analysis Modeling System; version 2.98.04, compiled November 12, 2002). PRZM simulates processes such like runoff and er osion from an agricultural field on a daily time step. The runoff and erosion flux output data from PR ZM are used as chemical loadings to the EXAMS surface water program in order to predict the EECs. A graphical user interface (pe4v01.pl) developed by the EPA ( http://www.epa.gov/oppefed1/ models/water ) was used to facilitate inputting chemical and use specific parameters into the appropriate PRZM input files (inp) and EXAMS chemical files.

PRZM is a one-dimensional, dynamic, compartmental model that can be used to simulate chemical movement in unsaturated soil systems within and immedi ately below the plant root zone. It has two major components: hydrology (and hydraulics) and chemical transport. The hydrologic component for calculating runoff and erosion is based on the Soil Conservation Service curve number technique and the Universal Soil Loss Equation. Evapotranspiration is est imated either directly from pan evaporation data, or based on an empirical formula. Water movement is simulated by the use of generalized soil parameters, including field capacity, wilting point, and saturation water content.

The chemical transport component can simulate pesticid es or other chemicals. For pesticides, the transport component can simulate pesticide application on the soil or on the plant foliage. Biodegradation can also be considered in the root zone. Dissolved, adsorbed, and vapor-phase concentrations in the soil are estimated by simultaneously considering the processes of pesticide uptake by plants, surface runoff, erosion, decay, volatilization, foliar washoff, advec tion, dispersion, and retardation. For nitrogen, simulation of surface applications, atmospheric depos ition, and septic effluent discharge may all be simulated.

EXAMS is a model that has a set of process modules that link fundamental chemical properties to limnological processes that control the kinetics and trans port of chemicals in aquatic systems. It provides facilities for steady state or long-term evaluation of chronic chemical discharg es, initial-value approaches for studying short-term contaminant releases, and full kinetic simulations that allow for monthly variation in mean climatological factors, and changes in contam inant loadings on daily time scales. It is fairly and relatively complex model that requires more input variables, ranging from hydro-geological and weather data to pesticide physicochemical properties, mobility coefficients, and degradation rate constants in the aqueous and sediment phases.

The PRZM scenarios selected for modeling were Florid a cucumbers and North Carolina sweet potatoes. EECs for ecological risk assessment were determined using a pond modeling scenario which describes a generic scenario for the EXAMS component of the modeling exercise (Mississippi standard pond).

Background Information About AgDRIFT® :34 

### The AgDRIFT® model is used to generate deposition values in a tiered approach. Results from the Spray Drift Task Force, a consortium of industry groups and ot her interested parties that worked together in the development of AgDRIFT® (SDTF), were used to confir m the model results at each of the different levels of analysis. The aerial tiers consist of a mathema tical model. For example, AgDRIFT® predicts the motion of spray material released from aircraft; including the mean position of the material and the position variance about the mean as a result of turbulen t fluctuations, pointing toward a prediction of spray drift (from the User’s Manual). Three major variables control the level of drift: the wind speed (it is assumed that the wind is in the direction of the pond, more wind speeds favor drift), the boom height (the higher, the more the level of drift), and the droplet size (smaller droplets drift more). If more refinement are desired, the spray volume is another variable that observations show that have a relatively high effect on the level of drift (smaller volumes favor drift). In order to obtain the level of drift assigned to a particular buffer zone, the model provides a “toolbox ” named Aquatic Assessment. In the toolbox, one can define the standard ecological pond, and obtain th e level of drift for any particular buffer zone as a fraction.

Background Information on the Rice Model and Model Refinement This interim policy establishes a Tier I estimati on model for surface water exposure from the use of pesticides in rice paddies. The single water-concentration estimates calculated with this model should represent both acute and chronic surface water e xposure, and should provide the representative concentration for aquatic ecological risk assessments. Water concentrations are estimated by a partitioning concept without considerations for mass transfer or degradation. As such, it provides conservative estimates that are consistent with a Tier 1 concept. In short, a pesticide is applied to a model rice paddy and instantaneously partitions itself between the water column and the sediment. Both the volume of the water column and the mass of the sediment are fixe d quantities that were chosen to be reasonably representative of a rice paddy. The Tier I Rice M odel was derived in EFED from the following simple relationship: EEC = 10 9 M T

------------------ V T + m sed K d 

### V T 

### = 1.067 x 10 6 

### L/ha

m sed 

### = 130,000 Kg/ha 10 9 

### = units factor K d 

### = partition coefficient M T 

### = total mass of pesticide in Kg applied per ha of paddy (application rate in Kg a.i./ha) Assumptions Most of the assumptions used in this model ensu re that its output represents protective estimates of concentration. The assumptions include the following: 1. Movement of pesticide on susp ended sediment is not considered. 2. Degradation does not occur. 3. Partitioning to sediment is instantaneous. 4. Water is available for human or wildlife exposure instantaneously.

Model Refinement: The rate constants were calculated from the half-lives as follows:

t 1⁄2 

### = -ln (2) / k or k = -ln (2) / t 1⁄2



### Since the formula that describes a first order reaction is:

[A] = e -kat 

### for photolysis [A] o35 

### And, [B] = e -kbt 

### for aerobic aquatic metabolism, then, [B] o



### [A] [B] = e -kat 

### x e -kbt 

### = e -t(ka + kb) 

### [A] o 

### [B] o



### Since [A] = [B] = [lambda-cyhalothrin],

[A] = e -k total x1⁄2 

### and t 1⁄2 total 

### = (50/100) therefore ln(50/100)= ln (0.5)/-k total 

### [A] o



### t 1⁄2 hydrolysis 

### = stable (If there was any hydrolysis then it woul d have to be factored out of the aerobic aquatic metabolism half-life.)

t 1⁄2 photolysis 

### = 25 days; k photolysis 

### = - 0.0277 days -1



### t 1⁄2 aerobic aquatic metabolism 

### = 33.7 days; k aerobic aquatic metabolism 

### = - 0.0207 days -1



### the half life is 14.3 days.

For lambda cyhalothrin, [A] 0 

### = 0.270 μg/L, and k total 

### = -0.0485 days -1



### Note: [A] = [B] = [lambda-cyhalothrin] [A] 0 

### = [B] 0 

### = [lambda-cyhalothrin] o 

### = [A] initial



### Background, Sediment Calculations and Assumptions Screening Level RQ values (Sediment) Contamination of sediments is a widespread ecologica l problem that can pose a potential risk to a wide variety of aquatic organisms and aquatic ecosystems. All aquatic life has some contact either direct or indirect with sediments as a media for habitat and or a source of food. This is an ecologically important habitat where significant densities and diversities of be nthic and epibenthic species occur. Embryonic life stages and gametes of infaunal, epibenthic and wa ter column species of a variety of commercially important fisheries can also be found directly in cont act with sediments (e.g., salmon, trout, clams, oysters) during critical stages of their development. A wide host of fish and aquatic invertebrates live in or on the benthos in direct or close proximity of sediments. Because of the widely accepted recognition that sediments serve as a dynamic media for aquatic ecosy stems, government organizations, as well as industry have come to realize that sediments can act as a repository for many contaminants, especially those that are lipophilic. This recognition of the potential for problem is manifest through exampl es of deleterious effects from contaminated sediments and their significant im pact on commercial fisheries (e.g., TBT and effects to shell fish), ecosystem diversity (e.g., TBT and en docrine effects to mollusks), and possible impact to endangered species (e.g., salmonides in the Pacific Northwest). State and federal regulatory agencies currently rely on several assessment tools in order to evaluate the toxic effects of contaminated sediments on marine and freshwater communities that include measures of chemical concentration, bioaccumulation, and biological toxicity. The combination of defining e xposure and effects can provide a first step for an integrative approach to defining sediment quality and the potential for risk to ecosystems and populations. Sediment toxicity tests are considered to be a powerful assessment tool that help to define the potential for acute and chronic risk to aquatic systems from c ontaminated sediment exposure. The use of sediment testing and sediment evaluation can often complete the risk picture for many compounds that are present in the water column for a relatively short time. The potential for lambda-cyhalothrin risk to aquatic36 

### invertebrates via sediment exposure suggests indirect e ffects to fish populations that are dependent upon invertebrates in the food chain, as well as direct effects to fish life stages that may be in direct contact with this media. The magnitude of these effects can be compounded since lambda-cyhalothrin has the potential to be persistent in aquatic systems. Sediment test can facilitate the use of relatively sensitive life stages (e.g., 2nd and third instar for chironomus) in addressing toxicity from this media. Acute sediment tests can measure effects that include survival, growth and emergence, while chronic studies can add important information on reproduction.

The risk quotients (RQ) for sediment dwelling organi sms were estimated with an extrapolation method recommended by the USEPA Office of Water (OW). This was based on the Agency’s Equilibrium Partitioning Sediment Guidelines (ESG) under the Clean Water Act [CWA Section 304(a)(2)]. Often the Agency is faced with the problem of assessing risk to aquatic systems from compounds that readily bind to particulate and eventually accumulate in the sediment. This issue is more problematic if sediment toxicity date and/or monitoring information are also not availa ble. Therefore, in order to address this concern, The Agency has consulted with the OW, and adopted a method for extrapolating exposure values (i.e., bulk sediment and porewater) that relies on the equilibri um partitioning (EqP) of nonionic compounds in sediment. The EqP theory holds that a nonionic chemical in sediment partitions between sediment organic carbon, interstitial (pore) water and benthic organisms. At equilibrium, if the concentration in any phase is known, then the concentration in the other phases can be predicted through the organic/carbon soil partition coefficient (K OC 

### ). In order to generate exposure concentrations from sediment (ug/Kg OC 

### ) and porewater (ug/L) for calculating RQs, The Agency relies on the output from the PRZM/EXAMS model. The effects components, are standard water column toxicity endpoints (e.g., most conservative LC50, NOAEC). This extrapolation method is useful for estimating potential sediment exposure values, as well as sediment toxicity values that can be used in a screening level risk assessment.

Rationale for EqP Use in the Agency Assessing Risk to Sediment Organisms Lambda-cyhalothrin is a lipophilic compound with high K OC 

### and K O/W 

### values(333,200 and 1.0x10 7



### , respectively), that can adsorb readily to particulate and sediment with resulting exposure to benthic aquatic life through respiration, ingestion, dermal contact, as well as indirect impact to other species through food chain alterations. Since, sediment can act as a reservoir for this compoun d, the bioavailability to aquatic organisms living in this medium is a concern that th e Agency is trying to addr ess through consultation with the EPA Office of Water (OW).

Under the Clean Water Act (CWA Section 304(a)(2) the Environmental Protection Agency (EPA) and the States are expected to develop programs for protecting the chemical, physical, and biological integrity of the nation’s waters. In order to meet the objectiv es of the CWA, EPA’s Office of water (OW) has periodically issued ambient water quality criteria (WQC). However, toxic contaminants in bottom sediments of lakes, rivers, wetlands, and coastal wa ters can also create potential for environmental degradation even if water column contamination values are low and comply with the Agencies water quality criteria. In order to evaluate this possible concern the OW also calculates Equilibrium Partitioning Sediment Guidelines (ESG).

Pesticide compounds that bind readily to particulat e and organic carbon may have a limited exposure to aquatic organisms in the water column. However, this increase in particulate-bound-pesticides can result in an accumulation of compounds in or on the sediment that may have the potential for toxic impact to benthic and epibenthic aquatic organisms (e.g., early li fe stage of many invertebrates and fish, as well as crabs and shrimp). However, evaluating the risk to aquatic life from this exposure becomes problematic especially if there is a lack of adequate sediment t oxicity and exposure data. Therefore, in order to assess this potential for pesticide risk to aquatic benthic systems, the Environmental Fate and Effects Division (The Agency) of the Office of Pesticides Program (O PP) has adopted the method used by the OW that37 

### relies on the theory of equilibrium partitioning (E qP) of chemicals. This theory is based on the hydrophobicity and concentrations of the chemical normalized to organic carbon (OC) in sediment (De Toro et al. 1991) and holds that a nonionic chemic al in sediment partitions between sediment organic carbon, interstitial (pore) water and benthic organisms. At equilibrium, if the concentration in any phase is known, then the concentration in the other phases can be predicted. A key component to this theory is the chemicals organic carbon coefficient (K OC 

### ), which is constant for every chemical and represents the ratio of the chemical concentration in water to the con centration in organic carbon. The document, “Technical Basis for the Derivation of Equilibrium Partitioning Sediment Guidelines (ESGs) for the Protection of Benthic Organisms: Nonionic Organics” (USEPA, 2000), demonstrates that biological responses of benthic organisms to nonionic organic chemicals in sediments are different when the sediment concentrations are expressed on a dry weight basis, but similar when expressed on a ug chemical/g organic carbon basis (ug/g OC 

### ). Similar responses were also observed across sediments when interstitial water concentrations were used to normalize biological av ailability. The Technical Basis Document further demonstrates that if the toxic effect concentration in water is known (e.g., LC50), the effect concentration in sediment on a ug/g OC 

### basis can be predicted by multiplying th e effect concentration in water by the chemical K OC



### .

(LC50 ug/L x K OC 

### L/Kg OC 

### x 1 Kg OC 

### /1000g OC 

### = LC50 ug/g OC 

### )

Since, The Agency uses a deterministic method for it s screening level risk assessment, the calculation of risk quotient values (RQ) is important for assessing po ssible risk. The RQ values are calculated by taking the ratio of the estimated exposure concentrations ( EEC) to the toxicity effect value (e.g., LC50, NOAEC). The EEC values are model generated (e.g., PRZM/ E XAMS) and reflect peer evaluated and approved scenarios for assessing pesticide expos ure to an aquatic environment. However, the PRZM/EXAMS output produces water column EEC values, as well as sediment and porewater EEC values. Therefore, in order to assess possible toxic pesticide exposure to aquatic or ganisms from sediments, The Agency is using the PRZM/EXAMS model which incorporates the principles of the equilibrium partitioning theory, in order to generate EECs from sediment and porewater. By relyi ng on sediment and/or porewater output values, The Agency has two ways for calculating RQ values for sediments by using porewater exposure values and bulk sediment values. RQ values can be produced by using the PRZM/ EXAMS EEC output value for sediment as follows:

EEC sediment ug/ug OC 

### / LC50 ug/g OC



### The calculations that rely on porewater can be cal culated by dividing the PRZM/EXAMS output value for porewater concentrations by the dissolved concentra tions in the water column that caused toxicity in bioassays (e.g., LC50).

EEC porewater ug/L / LC50 ugL

Assumptions of the equilibrium partitioning model Three principle observations that underlie the equilibrium partitioning (EqP) approach: 1. The concentrations of nonionic organic chemic als in sediments (expressed on an organic carbon basis) and in interstitial waters correlate with observed biological effects on sediment-dwelling organisms across a range of sediments. 2. Partitioning models can relate sediment concentrations for nonionic organic chemicals on an organic carbon basis to freely-dissolved concentrations in interstitial water. 3. The distribution of sensitivities of benthic organisms is similar to that of water column species.

The EqP approach assumes that the partitioning of a chemical between sediment organic carbon and38 

### interstitial water is at or near equilibrium. Another a ssumption is that the concentration in either phase can be predictive using appropriate partition coefficient and the measured concentration in the other phase. Furthermore, it is assumed that organisms receive equivalent exposure from water-only exposures or from any equilibrated phase (interstitial water via respira tion; from sediment via ingestion or other sediment integument exchange). The final assumption is that for nonionic compounds, effect concentrations in sediments on an organic carbon basis can be predicte d using the organic carbon partition coefficient (Koc) and effects concentrations in the water.

This method to estimate the risk to sediment dwelling or ganisms has certain uncertainties. First, it appears that the exposure may be underestimated because it a ssumes that the only source of contact of lambdacyhalothrin to the sediment dwellers is the pore wa ter; however, these organisms may be in constant contact with the sediments and even feed from them or from other small organisms that are contaminated. Second, the sensitivity of the sediment dwellers toward s lambda-cyhalothrin is assumed to be similar to that of water column dwellers in the absence of data , adding uncertainty to the calculation. Finally, some organisms dwell in the sediment only partially, ( e.g. tadpoles) and the risk is very uncertain in those cases.

Run Inputs and Outputs



### PRZM/EXAMS OUTPUT FILES

FL CUCUMBER:

stored as lcyhcucu.out Chemical: l-cyhalothrin PRZM environment: FLcucumberC.txt modified Satday, 12 October 2002 at 15:40:38 EXAMS environment: pond298.exv modified Thuday, 29 August 2002 at 16:33:30 Metfile: w12842.dvf modified Wedday, 3 July 2002 at 09:04:28 Water segment concentrations (ppb)

Year Peak 96 hr 21 Day 60 Day 90 Day Yearly 1961 0.03874 0.01139 0.009471 0.005592 0.003728 0.0009192 1962 0.03967 0.01233 0.01041 0.006166 0.004454 0.002605 1963 0.04837 0.01322 0.01095 0.006809 0.004971 0.003184 1964 0.04826 0.015 0.01129 0.007001 0.005258 0.003861 1965 0.04004 0.0127 0.0108 0.006643 0.004927 0.003353 1966 0.03999 0.01265 0.01074 0.006494 0.004803 0.003298 1967 0.03989 0.01254 0.01065 0.006468 0.004753 0.003089 1968 0.04 0.01266 0.01075 0.006507 0.004804 0.003116 1969 0.04013 0.01279 0.01147 0.007439 0.005469 0.003536 1970 0.04018 0.01283 0.01095 0.006686 0.005002 0.003801 1971 0.04008 0.0127 0.01085 0.006565 0.004902 0.003447 1972 0.03991 0.01255 0.01073 0.006528 0.004793 0.003151 1973 0.03982 0.01296 0.01058 0.006548 0.004791 0.003135 1974 0.03988 0.01253 0.01064 0.00653 0.004794 0.003091 1975 0.03979 0.01244 0.01054 0.00629 0.004602 0.002979 1976 0.03995 0.01261 0.01071 0.006456 0.004757 0.00307 1977 0.03982 0.01247 0.01061 0.006333 0.004616 0.003034 1978 0.03981 0.01244 0.01057 0.006376 0.004677 0.003175 1979 0.04755 0.01485 0.01116 0.006917 0.005256 0.003999 1980 0.04001 0.01267 0.01086 0.006537 0.004821 0.003319 1981 0.04011 0.01277 0.01087 0.006913 0.005127 0.003538 1982 0.0401 0.01273 0.01087 0.006643 0.004971 0.003522 1983 0.04035 0.0128 0.01097 0.007116 0.005272 0.003571 1984 0.03999 0.01262 0.01076 0.006482 0.004802 0.00339 1985 0.03978 0.01244 0.01053 0.006299 0.004624 0.003006 1986 0.04202 0.01264 0.01062 0.006314 0.004622 0.003052 1987 0.04002 0.01266 0.01082 0.00653 0.004841 0.003361 1988 0.04109 0.01497 0.01181 0.007112 0.005206 0.00330439 1989 0.03989 0.01297 0.01068 0.006599 0.004832 0.003206 1990 0.03974 0.01238 0.0105 0.006238 0.00456 0.003058

Sorted results Prob. Peak 96 hr 21 Day 60 Day 90 Day Yearly 0.032258064516129 0.04837 0.015 0.01181 0.007439 0.005469 0.003999 0.0645161290322581 0.04826 0.01497 0.01147 0.007116 0.005272 0.003861 0.0967741935483871 0.04755 0.01485 0.01129 0.007112 0.005258 0.003801 0.129032258064516 0.04202 0.01322 0.01116 0.007001 0.005256 0.003571 0.161290322580645 0.04109 0.01297 0.01097 0.006917 0.005206 0.003538 0.193548387096774 0.04035 0.01296 0.01095 0.006913 0.005127 0.003536 0.225806451612903 0.04018 0.01283 0.01095 0.006809 0.005002 0.003522 0.258064516129032 0.04013 0.0128 0.01087 0.006686 0.004971 0.003447 0.290322580645161 0.04011 0.01279 0.01087 0.006643 0.004971 0.00339 0.32258064516129 0.0401 0.01277 0.01086 0.006643 0.004927 0.003361 0.354838709677419 0.04008 0.01273 0.01085 0.006599 0.004902 0.003353 0.387096774193548 0.04004 0.0127 0.01082 0.006565 0.004841 0.003319 0.419354838709677 0.04002 0.0127 0.0108 0.006548 0.004832 0.003304 0.451612903225806 0.04001 0.01267 0.01076 0.006537 0.004821 0.003298 0.483870967741936 0.04 0.01266 0.01075 0.00653 0.004804 0.003206 0.516129032258065 0.03999 0.01266 0.01074 0.00653 0.004803 0.003184 0.548387096774194 0.03999 0.01265 0.01073 0.006528 0.004802 0.003175 0.580645161290323 0.03995 0.01264 0.01071 0.006507 0.004794 0.003151 0.612903225806452 0.03991 0.01262 0.01068 0.006494 0.004793 0.003135 0.645161290322581 0.03989 0.01261 0.01065 0.006482 0.004791 0.003116 0.67741935483871 0.03989 0.01255 0.01064 0.006468 0.004757 0.003091 0.709677419354839 0.03988 0.01254 0.01062 0.006456 0.004753 0.003089 0.741935483870968 0.03982 0.01253 0.01061 0.006376 0.004677 0.00307 0.774193548387097 0.03982 0.01247 0.01058 0.006333 0.004624 0.003058 0.806451612903226 0.03981 0.01244 0.01057 0.006314 0.004622 0.003052 0.838709677419355 0.03979 0.01244 0.01054 0.006299 0.004616 0.003034 0.870967741935484 0.03978 0.01244 0.01053 0.00629 0.004602 0.003006 0.903225806451613 0.03974 0.01238 0.0105 0.006238 0.00456 0.002979 0.935483870967742 0.03967 0.01233 0.01041 0.006166 0.004454 0.002605 0.967741935483871 0.03874 0.01139 0.009471 0.005592 0.003728 0.0009192

0.1 0.046997 0.014687 0.011277 0.0071009 0.0052578 0.003778 Average of yearly averages: 0.00320567333333333

Inputs generated by pe4.pl - 8-August-200340 Data used for this run: Output File: lcyhcucu Metfile: w12842.dvf PRZM scenario: FLcucumberC.txt EXAMS environment file: pond298.exv Chemical Name: l-cyhalothrin Description Variable Name Value Units Comments Molecular weight mwt 449.86 g/mol Henry's Law Const. henry 2.4E-7 atm-m^3/mol Vapor Pressure vapr 1.5E-9 torr Solubility sol 0.05 mg/L Kd Kd mg/L Koc Koc 333200 mg/L Photolysis half-lifekdp 26 days Half-life Aerobic Aquatic Metabolism kbacw 44.8 days Halfife Anaerobic Aquatic Metabolism kbacs 159.0 days Halfife Aerobic Soil Metabolism asm 56.5 days Halfife Hydrolysis: pH 7 0 days Half-life Method: CAM 1 integer See PRZM manual Incorporation Depth:DEPI 0 cm Application Rate: TAPP 0.0336 kg/ha Application Efficiency: APPEFF 0.95 fraction Spray Drift DRFT 0.039 fraction of application rate applied to pond Application Date Date 10-11 dd/mm or dd/mmm or dd-mm or dd-mmm Interval 1 interval 5 days Set to 0 or delete line for single app. Interval 2 interval 5 days Set to 0 or delete line for single app. Interval 3 interval 5 days Set to 0 or delete line for single app. Interval 4 interval 5 days Set to 0 or delete line for single app. Interval 5 interval 5 days Set to 0 or delete line for single app. Record 17: FILTRA IPSCND 3 UPTKF 0 Record 18: PLVKRT 0 PLDKRT 0 FEXTRC 0.5 Flag for Index Res. Run IR Pond Flag for runoff calc. RUNOFF none none, monthly or total(average of entire run)

stored as lcyhcucuben.out Chemical: l-cyhalothrin PRZM environment: FLcucumberC.txt modified Satday, 12 October 2002 at 15:40:38 EXAMS environment: pond298.exv modified Thuday, 29 August 2002 at 16:33:30 Metfile: w12842.dvf modified Wedday, 3 July 2002 at 09:04:28 Benthic segment concentrations (ppb)

Year Peak 96 hr 21 Day 60 Day 90 Day Yearly 1961 0.0009128 0.0009109 0.0008649 0.0005439 0.0003626 8.941e-005 1962 0.001103 0.001102 0.001086 0.0008329 0.0008049 0.000624 1963 0.001247 0.001246 0.001231 0.001024 0.001021 0.0007854 1964 0.001348 0.001346 0.001322 0.001292 0.001263 0.0009755 1965 0.001278 0.001273 0.00125 0.001197 0.001156 0.0008544 1966 0.001204 0.001202 0.001183 0.001151 0.00112 0.0008365 1967 0.001184 0.001182 0.001166 0.001078 0.001047 0.0007736 1968 0.001206 0.001204 0.001187 0.001057 0.001027 0.000784 1969 0.001469 0.001467 0.001446 0.001102 0.00109 0.0008728 1970 0.001442 0.00144 0.001425 0.001402 0.001374 0.0009903 1971 0.001227 0.001224 0.001196 0.001155 0.001133 0.0008721 1972 0.001177 0.001174 0.001162 0.001076 0.001051 0.000784 1973 0.001177 0.001175 0.001153 0.00108 0.001047 0.0007788 1974 0.001191 0.001188 0.001172 0.001065 0.001021 0.0007672 1975 0.001153 0.001146 0.00112 0.001062 0.001018 0.0007403 1976 0.001193 0.001191 0.001172 0.001014 0.0009747 0.0007621 1977 0.001157 0.001156 0.001143 0.001109 0.001071 0.0007606 1978 0.001145 0.001143 0.00112 0.001073 0.001068 0.0007922 1979 0.001326 0.001324 0.001304 0.001169 0.001159 0.0009985 1980 0.001259 0.001252 0.001226 0.001179 0.001142 0.0008437 1981 0.001307 0.001305 0.001241 0.001169 0.001155 0.0008848 1982 0.001301 0.001295 0.001278 0.00123 0.00119 0.000897341 1983 0.001347 0.001345 0.001326 0.001122 0.001113 0.0008879 1984 0.001336 0.001331 0.001308 0.001256 0.001215 0.0008733 1985 0.00114 0.001138 0.001121 0.001057 0.001019 0.0007477 1986 0.001138 0.001136 0.001114 0.001027 0.001005 0.0007573 1987 0.001212 0.00121 0.001187 0.001028 0.001017 0.0008354 1988 0.001334 0.001331 0.001313 0.001091 0.001069 0.0008179 1989 0.001273 0.001266 0.001234 0.00118 0.001134 0.0008065 1990 0.001185 0.001178 0.001149 0.001101 0.001068 0.0007643

Sorted results Prob. Peak 96 hr 21 Day 60 Day 90 Day Yearly 0.032258064516129 0.001469 0.001467 0.001446 0.001402 0.001374 0.0009985 0.0645161290322581 0.001442 0.00144 0.001425 0.001292 0.001263 0.0009903 0.0967741935483871 0.001348 0.001346 0.001326 0.001256 0.001215 0.0009755 0.129032258064516 0.001347 0.001345 0.001322 0.00123 0.00119 0.0008973 0.161290322580645 0.001336 0.001331 0.001313 0.001197 0.001159 0.0008879 0.193548387096774 0.001334 0.001331 0.001308 0.00118 0.001156 0.0008848 0.225806451612903 0.001326 0.001324 0.001304 0.001179 0.001155 0.0008733 0.258064516129032 0.001307 0.001305 0.001278 0.001169 0.001142 0.0008728 0.290322580645161 0.001301 0.001295 0.00125 0.001169 0.001134 0.0008721 0.32258064516129 0.001278 0.001273 0.001241 0.001155 0.001133 0.0008544 0.354838709677419 0.001273 0.001266 0.001234 0.001151 0.00112 0.0008437 0.387096774193548 0.001259 0.001252 0.001231 0.001122 0.001113 0.0008365 0.419354838709677 0.001247 0.001246 0.001226 0.001109 0.00109 0.0008354 0.451612903225806 0.001227 0.001224 0.001196 0.001102 0.001071 0.0008179 0.483870967741936 0.001212 0.00121 0.001187 0.001101 0.001069 0.0008065 0.516129032258065 0.001206 0.001204 0.001187 0.001091 0.001068 0.0007922 0.548387096774194 0.001204 0.001202 0.001183 0.00108 0.001068 0.0007854 0.580645161290323 0.001193 0.001191 0.001172 0.001078 0.001051 0.000784 0.612903225806452 0.001191 0.001188 0.001172 0.001076 0.001047 0.000784 0.645161290322581 0.001185 0.001182 0.001166 0.001073 0.001047 0.0007788 0.67741935483871 0.001184 0.001178 0.001162 0.001065 0.001027 0.0007736 0.709677419354839 0.001177 0.001175 0.001153 0.001062 0.001021 0.0007672 0.741935483870968 0.001177 0.001174 0.001149 0.001057 0.001021 0.0007643 0.774193548387097 0.001157 0.001156 0.001143 0.001057 0.001019 0.0007621 0.806451612903226 0.001153 0.001146 0.001121 0.001028 0.001018 0.0007606 0.838709677419355 0.001145 0.001143 0.00112 0.001027 0.001017 0.0007573 0.870967741935484 0.00114 0.001138 0.00112 0.001024 0.001005 0.0007477 0.903225806451613 0.001138 0.001136 0.001114 0.001014 0.0009747 0.0007403 0.935483870967742 0.001103 0.001102 0.001086 0.0008329 0.0008049 0.00062442 0.967741935483871 0.0009128 0.0009109 0.0008649 0.0005439 0.0003626 8.941e-005

0.1 0.0013479 0.0013459 0.0013256 0.0012534 0.0012125 0.00096768 Average of yearly averages: 0.000798593666666667

Inputs generated by pe4.pl - 8-August-2003

Data used for this run: Output File: lcyhcucu Metfile: w12842.dvf PRZM scenario: FLcucumberC.txt EXAMS environment file: pond298.exv Chemical Name: l-cyhalothrin Description Variable Name Value Units Comments Molecular weight mwt 449.86 g/mol Henry's Law Const. henry 2.4E-7 atm-m^3/mol Vapor Pressure vapr 1.5E-9 torr Solubility sol 0.05 mg/L Kd Kd mg/L Koc Koc 333200 mg/L Photolysis half-lifekdp 26 days Half-life Aerobic Aquatic Metabolism kbacw 44.8 days Halfife Anaerobic Aquatic Metabolism kbacs 159.0 days Halfife Aerobic Soil Metabolism asm 56.5 days Halfife Hydrolysis: pH 7 0 days Half-life Method: CAM 1 integer See PRZM manual Incorporation Depth:DEPI 0 cm Application Rate: TAPP 0.0336 kg/ha Application Efficiency: APPEFF 0.95 fraction Spray Drift DRFT 0.039 fraction of application rate applied to pond Application Date Date 10-11 dd/mm or dd/mmm or dd-mm or dd-mmm Interval 1 interval 5 days Set to 0 or delete line for single app. Interval 2 interval 5 days Set to 0 or delete line for single app. Interval 3 interval 5 days Set to 0 or delete line for single app. Interval 4 interval 5 days Set to 0 or delete line for single app. Interval 5 interval 5 days Set to 0 or delete line for single app. Record 17: FILTRA IPSCND 3 UPTKF 0 Record 18: PLVKRT 0 PLDKRT 0 FEXTRC 0.5 Flag for Index Res. Run IR Pond Flag for runoff calc. RUNOFF none none, monthly or total(average of entire run)

stored as lcyhcucubensed.out Chemical: l-cyhalothrin PRZM environment: FLcucumberC.txt modified Satday, 12 October 2002 at 14:40:38 EXAMS environment: pond298.exv modified Thuday, 29 August 2002 at 15:33:30 Metfile: w12842.dvf modified Wedday, 3 July 2002 at 08:04:28 Sediment segment concentrations (ppb)

Year Peak 96 hr 21 Day 60 Day 90 Day Yearly 1961 12.17 12.14 11.53 7.25 4.833 1.192 1962 14.71 14.68 14.47 11.1 10.73 8.318 1963 16.63 16.6 16.41 13.65 13.61 10.47 1964 17.97 17.94 17.62 17.22 16.83 13 1965 17.04 16.96 16.66 15.95 15.41 11.39 1966 16.04 16.02 15.77 15.34 14.93 11.15 1967 15.79 15.76 15.54 14.36 13.95 10.31 1968 16.08 16.05 15.83 14.09 13.68 10.45 1969 19.58 19.55 19.27 14.69 14.52 11.63 1970 19.22 19.2 19 18.69 18.31 13.2 1971 16.35 16.32 15.95 15.4 15.1 11.62 1972 15.68 15.66 15.49 14.34 14.01 10.45 1973 15.68 15.66 15.37 14.4 13.96 10.38 1974 15.87 15.84 15.63 14.2 13.61 10.2343 1975 15.37 15.28 14.93 14.16 13.56 9.868 1976 15.9 15.87 15.62 13.51 12.99 10.16 1977 15.42 15.4 15.23 14.78 14.28 10.14 1978 15.26 15.23 14.92 14.31 14.23 10.56 1979 17.68 17.65 17.38 15.59 15.45 13.31 1980 16.78 16.69 16.34 15.72 15.23 11.25 1981 17.42 17.39 16.54 15.58 15.4 11.79 1982 17.34 17.26 17.04 16.39 15.86 11.96 1983 17.96 17.92 17.67 14.96 14.83 11.84 1984 17.8 17.74 17.43 16.74 16.2 11.64 1985 15.2 15.17 14.94 14.09 13.58 9.966 1986 15.17 15.15 14.85 13.69 13.4 10.09 1987 16.15 16.12 15.82 13.71 13.56 11.14 1988 17.78 17.75 17.5 14.54 14.25 10.9 1989 16.97 16.87 16.46 15.73 15.11 10.75 1990 15.79 15.7 15.32 14.67 14.23 10.19

Sorted results Prob. Peak 96 hr 21 Day 60 Day 90 Day Yearly 0.032258064516129 19.58 19.55 19.27 18.69 18.31 13.31 0.0645161290322581 19.22 19.2 19 17.22 16.83 13.2 0.0967741935483871 17.97 17.94 17.67 16.74 16.2 13 0.129032258064516 17.96 17.92 17.62 16.39 15.86 11.96 0.161290322580645 17.8 17.75 17.5 15.95 15.45 11.84 0.193548387096774 17.78 17.74 17.43 15.73 15.41 11.79 0.225806451612903 17.68 17.65 17.38 15.72 15.4 11.64 0.258064516129032 17.42 17.39 17.04 15.59 15.23 11.63 0.290322580645161 17.34 17.26 16.66 15.58 15.11 11.62 0.32258064516129 17.04 16.96 16.54 15.4 15.1 11.39 0.354838709677419 16.97 16.87 16.46 15.34 14.93 11.25 0.387096774193548 16.78 16.69 16.41 14.96 14.83 11.15 0.419354838709677 16.63 16.6 16.34 14.78 14.52 11.14 0.451612903225806 16.35 16.32 15.95 14.69 14.28 10.9 0.483870967741936 16.15 16.12 15.83 14.67 14.25 10.75 0.516129032258065 16.08 16.05 15.82 14.54 14.23 10.56 0.548387096774194 16.04 16.02 15.77 14.4 14.23 10.47 0.580645161290323 15.9 15.87 15.63 14.36 14.01 10.45 0.612903225806452 15.87 15.84 15.62 14.34 13.96 10.45 0.645161290322581 15.79 15.76 15.54 14.31 13.95 10.38 0.67741935483871 15.79 15.7 15.49 14.2 13.68 10.31 0.709677419354839 15.68 15.66 15.37 14.16 13.61 10.23 0.741935483870968 15.68 15.66 15.32 14.09 13.61 10.19 0.774193548387097 15.42 15.4 15.23 14.09 13.58 10.16 0.806451612903226 15.37 15.28 14.94 13.71 13.56 10.14 0.838709677419355 15.26 15.23 14.93 13.69 13.56 10.09 0.870967741935484 15.2 15.17 14.92 13.65 13.4 9.966 0.903225806451613 15.17 15.15 14.85 13.51 12.99 9.868 0.935483870967742 14.71 14.68 14.47 11.1 10.73 8.318 0.967741935483871 12.17 12.14 11.53 7.25 4.833 1.192

0.1 17.969 17.938 17.665 16.705 16.166 12.896 Average of yearly averages: 10.6448

Inputs generated by pe4.pl - 8-August-2003

Data used for this run: Output File: lcyhcucu Metfile: w12842.dvf PRZM scenario: FLcucumberC.txt EXAMS environment file: pond298.exv Chemical Name: l-cyhalothrin Description Variable Name Value Units Comments Molecular weight mwt 449.86 g/mol Henry's Law Const. henry 2.4E-7 atm-m^3/mol Vapor Pressure vapr 1.5E-9 torr Solubility sol 0.05 mg/L Kd Kd mg/L Koc Koc 333200 mg/L Photolysis half-lifekdp 26 days Half-life Aerobic Aquatic Metabolism kbacw 44.8 days Halfife44 Anaerobic Aquatic Metabolism kbacs 159.0 days Halfife Aerobic Soil Metabolism asm 56.5 days Halfife Hydrolysis: pH 7 0 days Half-life Method: CAM 1 integer See PRZM manual Incorporation Depth:DEPI 0 cm Application Rate: TAPP 0.0336 kg/ha Application Efficiency: APPEFF 0.95 fraction Spray Drift DRFT 0.039 fraction of application rate applied to pond Application Date Date 10-11 dd/mm or dd/mmm or dd-mm or dd-mmm Interval 1 interval 5 days Set to 0 or delete line for single app. Interval 2 interval 5 days Set to 0 or delete line for single app. Interval 3 interval 5 days Set to 0 or delete line for single app. Interval 4 interval 5 days Set to 0 or delete line for single app. Interval 5 interval 5 days Set to 0 or delete line for single app. Record 17: FILTRA IPSCND 3 UPTKF 0 Record 18: PLVKRT 0 PLDKRT 0 FEXTRC 0.5 Flag for Index Res. Run IR Pond Flag for runoff calc. RUNOFF none none, monthly or total(average of entire run) Write Benthic Porewater File? benthic 1 Write Benthic Sediment File? benthicsed 1

RUN WITH 0% DRIFT FL CUCUMBERS

stored as lcyhcucu.out Chemical: l-cyhalothrin PRZM environment: FLcucumberC.txt modified Satday, 12 October 2002 at 14:40:38 EXAMS environment: pond298.exv modified Thuday, 29 August 2002 at 15:33:30 Metfile: w12842.dvf modified Wedday, 3 July 2002 at 08:04:28 Water segment concentrations (ppb)

Year Peak 96 hr 21 Day 60 Day 90 Day Yearly 1961 0.01544 0.004319 0.00104 0.0003672 0.0002448 6.037e-005 1962 0.002505 0.000938 0.000611 0.0004798 0.0004508 0.0003645 1963 0.01102 0.00311 0.001259 0.0008409 0.0007403 0.000532 1964 0.01929 0.005754 0.001932 0.001572 0.001507 0.001115 1965 0.004973 0.002099 0.0009978 0.0007638 0.0007388 0.0006087 1966 0.005812 0.002066 0.0009008 0.0007064 0.0006578 0.0005024 1967 0.003983 0.001249 0.0006026 0.0004374 0.0003941 0.0003231 1968 0.004922 0.001428 0.0005236 0.0004643 0.0004232 0.0002999 1969 0.02917 0.008606 0.002578 0.001208 0.0009444 0.0006719 1970 0.008184 0.003 0.00166 0.001498 0.001463 0.00097 1971 0.0123 0.003894 0.001373 0.0009585 0.0008642 0.0006819 1972 0.00565 0.001944 0.0009959 0.0007311 0.0006597 0.0005092 1973 0.008401 0.002493 0.0009656 0.0006849 0.0006164 0.000478 1974 0.009781 0.003465 0.001203 0.0007716 0.0006714 0.0004881 1975 0.004323 0.001384 0.0008292 0.0006083 0.0005366 0.0003979 1976 0.0139 0.003843 0.001204 0.0008435 0.0007274 0.000409 1977 0.004695 0.001446 0.0005959 0.0004835 0.0004437 0.0002909 1978 0.009935 0.002857 0.001046 0.0007095 0.0006432 0.0004238 1979 0.04534 0.01266 0.004084 0.002528 0.002162 0.001328 1980 0.003994 0.001536 0.0009135 0.0008534 0.0008355 0.000652 1981 0.0232 0.00634 0.001947 0.001248 0.001087 0.0007552 1982 0.00429 0.002317 0.001373 0.001107 0.001003 0.0007887 1983 0.01477 0.004454 0.001773 0.001094 0.001034 0.000863 1984 0.004954 0.001769 0.0009952 0.0009497 0.0009183 0.0006598 1985 0.004834 0.002162 0.0007517 0.0005213 0.0004965 0.0003548 1986 0.01008 0.003434 0.001094 0.0007166 0.0006244 0.0004034 1987 0.01074 0.004767 0.001813 0.001318 0.001207 0.000729 1988 0.01551 0.005095 0.001808 0.001021 0.0008091 0.0006112 1989 0.005808 0.002004 0.0009308 0.0008306 0.0007923 0.0005931 1990 0.005659 0.001864 0.001039 0.000776 0.0007025 0.0004805

Sorted results Prob. Peak 96 hr 21 Day 60 Day 90 Day Yearly45 0.032258064516129 0.04534 0.01266 0.004084 0.002528 0.002162 0.001328 0.0645161290322581 0.02917 0.008606 0.002578 0.001572 0.001507 0.001115 0.0967741935483871 0.0232 0.00634 0.001947 0.001498 0.001463 0.00097 0.129032258064516 0.01929 0.005754 0.001932 0.001318 0.001207 0.000863 0.161290322580645 0.01551 0.005095 0.001813 0.001248 0.001087 0.0007887 0.193548387096774 0.01544 0.004767 0.001808 0.001208 0.001034 0.0007552 0.225806451612903 0.01477 0.004454 0.001773 0.001107 0.001003 0.000729 0.258064516129032 0.0139 0.004319 0.00166 0.001094 0.0009444 0.0006819 0.290322580645161 0.0123 0.003894 0.001373 0.001021 0.0009183 0.0006719 0.32258064516129 0.01102 0.003843 0.001373 0.0009585 0.0008642 0.0006598 0.354838709677419 0.01074 0.003465 0.001259 0.0009497 0.0008355 0.000652 0.387096774193548 0.01008 0.003434 0.001204 0.0008534 0.0008091 0.0006112 0.419354838709677 0.009935 0.00311 0.001203 0.0008435 0.0007923 0.0006087 0.451612903225806 0.009781 0.003 0.001094 0.0008409 0.0007403 0.0005931 0.483870967741936 0.008401 0.002857 0.001046 0.0008306 0.0007388 0.000532 0.516129032258065 0.008184 0.002493 0.00104 0.000776 0.0007274 0.0005092 0.548387096774194 0.005812 0.002317 0.001039 0.0007716 0.0007025 0.0005024 0.580645161290323 0.005808 0.002162 0.0009978 0.0007638 0.0006714 0.0004881 0.612903225806452 0.005659 0.002099 0.0009959 0.0007311 0.0006597 0.0004805 0.645161290322581 0.00565 0.002066 0.0009952 0.0007166 0.0006578 0.000478 0.67741935483871 0.004973 0.002004 0.0009656 0.0007095 0.0006432 0.0004238 0.709677419354839 0.004954 0.001944 0.0009308 0.0007064 0.0006244 0.000409 0.741935483870968 0.004922 0.001864 0.0009135 0.0006849 0.0006164 0.0004034 0.774193548387097 0.004834 0.001769 0.0009008 0.0006083 0.0005366 0.0003979 0.806451612903226 0.004695 0.001536 0.0008292 0.0005213 0.0004965 0.0003645 0.838709677419355 0.004323 0.001446 0.0007517 0.0004835 0.0004508 0.0003548 0.870967741935484 0.00429 0.001428 0.000611 0.0004798 0.0004437 0.0003231 0.903225806451613 0.003994 0.001384 0.0006026 0.0004643 0.0004232 0.0002999 0.935483870967742 0.003983 0.001249 0.0005959 0.0004374 0.0003941 0.0002909 0.967741935483871 0.002505 0.000938 0.0005236 0.0003672 0.0002448 6.037e-005

0.1 0.022809 0.0062814 0.0019455 0.00148 0.0014374 0.0009593 Average of yearly averages: 0.000578179

Inputs generated by pe4.pl - 8-August-2003

Data used for this run: Output File: lcyhcucu Metfile: w12842.dvf PRZM scenario: FLcucumberC.txt EXAMS environment file: pond298.exv46 Chemical Name: l-cyhalothrin Description Variable Name Value Units Comments Molecular weight mwt 449.86 g/mol Henry's Law Const. henry 2.4E-7 atm-m^3/mol Vapor Pressure vapr 1.5E-9 torr Solubility sol 0.05 mg/L Kd Kd mg/L Koc Koc 333200 mg/L Photolysis half-lifekdp 26 days Half-life Aerobic Aquatic Metabolism kbacw 44.8 days Halfife Anaerobic Aquatic Metabolism kbacs 159.0 days Halfife Aerobic Soil Metabolism asm 56.5 days Halfife Hydrolysis: pH 7 0 days Half-life Method: CAM 1 integer See PRZM manual Incorporation Depth:DEPI 0 cm Application Rate: TAPP 0.0336 kg/ha Application Efficiency: APPEFF 0.95 fraction Spray Drift DRFT 0.00 fraction of application rate applied to pond Application Date Date 10-11 dd/mm or dd/mmm or dd-mm or dd-mmm Interval 1 interval 5 days Set to 0 or delete line for single app. Interval 2 interval 5 days Set to 0 or delete line for single app. Interval 3 interval 5 days Set to 0 or delete line for single app. Interval 4 interval 5 days Set to 0 or delete line for single app. Interval 5 interval 5 days Set to 0 or delete line for single app. Record 17: FILTRA IPSCND 3 UPTKF 0 Record 18: PLVKRT 0 PLDKRT 0 FEXTRC 0.5 Flag for Index Res. Run IR Pond Flag for runoff calc. RUNOFF none none, monthly or total(average of entire run) Write Benthic Porewater File? benthic 1 Write Benthic Sediment File? benthicsed 1

FL cucumbers ground application stored as lcyhcucu.out Chemical: l-cyhalothrin PRZM environment: FLcucumberC.txt modified Satday, 12 October 2002 at 14:40:38 EXAMS environment: pond298.exv modified Thuday, 29 August 2002 at 15:33:30 Metfile: w12842.dvf modified Wedday, 3 July 2002 at 08:04:28 Water segment concentrations (ppb)

Year Peak 96 hr 21 Day 60 Day 90 Day Yearly 1961 0.01674 0.005147 0.002435 0.001722 0.001148 0.0002831 1962 0.01036 0.003349 0.002863 0.001772 0.001342 0.0009541 1963 0.02106 0.005833 0.003609 0.002283 0.001713 0.001235 1964 0.02094 0.006829 0.003597 0.002464 0.002323 0.001866 1965 0.01056 0.003545 0.003067 0.002074 0.001623 0.001338 1966 0.01049 0.003478 0.002996 0.001904 0.001482 0.00124 1967 0.01039 0.00338 0.002902 0.001888 0.001437 0.001046 1968 0.01045 0.003442 0.002958 0.001874 0.001442 0.001035 1969 0.03142 0.009909 0.004313 0.002856 0.002144 0.001435 1970 0.01069 0.003946 0.003201 0.002357 0.002321 0.001737 1971 0.0134 0.004842 0.003141 0.002031 0.001624 0.00142 1972 0.01057 0.003583 0.003076 0.002038 0.001562 0.001208 1973 0.01042 0.003907 0.002933 0.002059 0.001561 0.001179 1974 0.01062 0.004037 0.00299 0.002048 0.001578 0.001176 1975 0.01042 0.003407 0.002925 0.001833 0.001413 0.001076 1976 0.01502 0.004537 0.002999 0.001906 0.001481 0.001108 1977 0.01036 0.003341 0.002907 0.001787 0.001337 0.001006 1978 0.01113 0.003751 0.002893 0.001866 0.001422 0.001147 1979 0.0478 0.01375 0.004798 0.00313 0.002713 0.002069 1980 0.01058 0.003573 0.003194 0.002023 0.001577 0.001363 1981 0.02497 0.007393 0.003123 0.002337 0.001834 0.0015 1982 0.01068 0.003656 0.003194 0.002134 0.001718 0.001523 1983 0.01629 0.005527 0.003435 0.002594 0.002011 0.001594 1984 0.01054 0.003518 0.003048 0.001947 0.001723 0.00138847 1985 0.01041 0.003401 0.002917 0.001831 0.001415 0.00105 1986 0.01307 0.004256 0.00301 0.00186 0.001416 0.0011 1987 0.01183 0.005607 0.003165 0.00204 0.001853 0.001435 1988 0.01704 0.007669 0.004185 0.002626 0.00197 0.001327 1989 0.0105 0.003921 0.003045 0.002124 0.001623 0.001288 1990 0.01039 0.003375 0.0029 0.001804 0.001424 0.001162

Sorted results Prob. Peak 96 hr 21 Day 60 Day 90 Day Yearly 0.032258064516129 0.0478 0.01375 0.004798 0.00313 0.002713 0.002069 0.0645161290322581 0.03142 0.009909 0.004313 0.002856 0.002323 0.001866 0.0967741935483871 0.02497 0.007669 0.004185 0.002626 0.002321 0.001737 0.129032258064516 0.02106 0.007393 0.003609 0.002594 0.002144 0.001594 0.161290322580645 0.02094 0.006829 0.003597 0.002464 0.002011 0.001523 0.193548387096774 0.01704 0.005833 0.003435 0.002357 0.00197 0.0015 0.225806451612903 0.01674 0.005607 0.003201 0.002337 0.001853 0.001435 0.258064516129032 0.01629 0.005527 0.003194 0.002283 0.001834 0.001435 0.290322580645161 0.01502 0.005147 0.003194 0.002134 0.001723 0.00142 0.32258064516129 0.0134 0.004842 0.003165 0.002124 0.001718 0.001388 0.354838709677419 0.01307 0.004537 0.003141 0.002074 0.001713 0.001363 0.387096774193548 0.01183 0.004256 0.003123 0.002059 0.001624 0.001338 0.419354838709677 0.01113 0.004037 0.003076 0.002048 0.001623 0.001327 0.451612903225806 0.01069 0.003946 0.003067 0.00204 0.001623 0.001288 0.483870967741936 0.01068 0.003921 0.003048 0.002038 0.001578 0.00124 0.516129032258065 0.01062 0.003907 0.003045 0.002031 0.001577 0.001235 0.548387096774194 0.01058 0.003751 0.00301 0.002023 0.001562 0.001208 0.580645161290323 0.01057 0.003656 0.002999 0.001947 0.001561 0.001179 0.612903225806452 0.01056 0.003583 0.002996 0.001906 0.001482 0.001176 0.645161290322581 0.01054 0.003573 0.00299 0.001904 0.001481 0.001162 0.67741935483871 0.0105 0.003545 0.002958 0.001888 0.001442 0.001147 0.709677419354839 0.01049 0.003518 0.002933 0.001874 0.001437 0.001108 0.741935483870968 0.01045 0.003478 0.002925 0.001866 0.001424 0.0011 0.774193548387097 0.01042 0.003442 0.002917 0.00186 0.001422 0.001076 0.806451612903226 0.01042 0.003407 0.002907 0.001833 0.001416 0.00105 0.838709677419355 0.01041 0.003401 0.002902 0.001831 0.001415 0.001046 0.870967741935484 0.01039 0.00338 0.0029 0.001804 0.001413 0.001035 0.903225806451613 0.01039 0.003375 0.002893 0.001787 0.001342 0.001006 0.935483870967742 0.01036 0.003349 0.002863 0.001772 0.001337 0.0009541 0.967741935483871 0.01036 0.003341 0.002435 0.001722 0.001148 0.000283148 0.1 0.024579 0.0076414 0.0041274 0.0026228 0.0023033 0.0017227 Average of yearly averages: 0.00127627333333333

Inputs generated by pe4.pl - 8-August-2003

Data used for this run: Output File: lcyhcucu Metfile: w12842.dvf PRZM scenario: FLcucumberC.txt EXAMS environment file: pond298.exv Chemical Name: l-cyhalothrin Description Variable Name Value Units Comments Molecular weight mwt 449.86 g/mol Henry's Law Const. henry 2.4E-7 atm-m^3/mol Vapor Pressure vapr 1.5E-9 torr Solubility sol 0.05 mg/L Kd Kd mg/L Koc Koc 333200 mg/L Photolysis half-lifekdp 26 days Half-life Aerobic Aquatic Metabolism kbacw 44.8 days Halfife Anaerobic Aquatic Metabolism kbacs 159.0 days Halfife Aerobic Soil Metabolism asm 56.5 days Halfife Hydrolysis: pH 7 0 days Half-life Method: CAM 1 integer See PRZM manual Incorporation Depth:DEPI 0 cm Application Rate: TAPP 0.0336 kg/ha Application Efficiency: APPEFF 0.99 fraction Spray Drift DRFT 0.01 fraction of application rate applied to pond Application Date Date 10-11 dd/mm or dd/mmm or dd-mm or dd-mmm Interval 1 interval 5 days Set to 0 or delete line for single app. Interval 2 interval 5 days Set to 0 or delete line for single app. Interval 3 interval 5 days Set to 0 or delete line for single app. Interval 4 interval 5 days Set to 0 or delete line for single app. Interval 5 interval 5 days Set to 0 or delete line for single app. Record 17: FILTRA IPSCND 3 UPTKF 0 Record 18: PLVKRT 0 PLDKRT 0 FEXTRC 0.5 Flag for Index Res. Run IR Pond Flag for runoff calc. RUNOFF none none, monthly or total(average of entire run) Write Benthic Porewater File? benthic 1 Write Benthic Sediment File? benthicsed 1

stored as lcyhcucuben.out Chemical: l-cyhalothrin PRZM environment: FLcucumberC.txt modified Satday, 12 October 2002 at 14:40:38 EXAMS environment: pond298.exv modified Thuday, 29 August 2002 at 15:33:30 Metfile: w12842.dvf modified Wedday, 3 July 2002 at 08:04:28 Benthic segment concentrations (ppb)

Year Peak 96 hr 21 Day 60 Day 90 Day Yearly 1961 0.0003331 0.0003324 0.0002817 0.0001607 0.0001071 2.641e-005 1962 0.0003417 0.0003412 0.0003362 0.0003082 0.0003007 0.0002421 1963 0.0004438 0.0004433 0.0004397 0.0004023 0.0003874 0.0003086 1964 0.000624 0.0006231 0.0006127 0.0006002 0.0005941 0.0004828 1965 0.0005181 0.0005159 0.000507 0.0004867 0.0004727 0.0003577 1966 0.0004462 0.0004458 0.0004411 0.0004281 0.0004203 0.0003265 1967 0.0003724 0.0003717 0.0003646 0.0003505 0.0003469 0.0002679 1968 0.0003707 0.0003702 0.0003649 0.0003337 0.0003246 0.0002665 1969 0.0006544 0.0006534 0.0006444 0.0004304 0.0003787 0.0003473 1970 0.0006908 0.0006897 0.000681 0.0006663 0.0006619 0.0004778 1971 0.0004884 0.0004874 0.0004789 0.0004571 0.0004421 0.0003706 1972 0.000419 0.0004183 0.0004123 0.0003997 0.0003908 0.0003087 1973 0.0004229 0.0004215 0.0003934 0.0003879 0.0003809 0.0003002 1974 0.0004219 0.0004191 0.0004071 0.0003836 0.0003689 0.0003013 1975 0.0004072 0.000405 0.0003956 0.0003761 0.0003609 0.0002787 1976 0.0003828 0.0003823 0.0003762 0.00032 0.0003083 0.000281849 1977 0.0003944 0.0003939 0.0003892 0.0003799 0.0003686 0.0002602 1978 0.0004168 0.0004161 0.0004115 0.000395 0.0003789 0.0002905 1979 0.0008047 0.0008018 0.0007851 0.0007299 0.0006821 0.0005255 1980 0.0005158 0.0005132 0.0005024 0.0004876 0.0004754 0.000365 1981 0.0005447 0.0005436 0.0005346 0.0005123 0.0004916 0.00038 1982 0.0005284 0.0005275 0.0005198 0.000508 0.0004987 0.0004045 1983 0.0005755 0.0005642 0.0005455 0.0004788 0.0004716 0.0004016 1984 0.0005757 0.0005739 0.0005645 0.0005443 0.0005299 0.0003802 1985 0.0003697 0.0003684 0.0003624 0.00035 0.0003394 0.0002688 1986 0.0003895 0.0003886 0.000381 0.0003594 0.0003436 0.0002793 1987 0.000524 0.0005228 0.000512 0.0004891 0.0004707 0.0003653 1988 0.0005499 0.000549 0.0005394 0.000412 0.0003965 0.0003316 1989 0.0005261 0.000523 0.0005102 0.0004957 0.000478 0.0003399 1990 0.0004357 0.0004348 0.0004247 0.0004133 0.0004121 0.0003042

Sorted results Prob. Peak 96 hr 21 Day 60 Day 90 Day Yearly 0.032258064516129 0.0008047 0.0008018 0.0007851 0.0007299 0.0006821 0.0005255 0.0645161290322581 0.0006908 0.0006897 0.000681 0.0006663 0.0006619 0.0004828 0.0967741935483871 0.0006544 0.0006534 0.0006444 0.0006002 0.0005941 0.0004778 0.129032258064516 0.000624 0.0006231 0.0006127 0.0005443 0.0005299 0.0004045 0.161290322580645 0.0005757 0.0005739 0.0005645 0.0005123 0.0004987 0.0004016 0.193548387096774 0.0005755 0.0005642 0.0005455 0.000508 0.0004916 0.0003802 0.225806451612903 0.0005499 0.000549 0.0005394 0.0004957 0.000478 0.00038 0.258064516129032 0.0005447 0.0005436 0.0005346 0.0004891 0.0004754 0.0003706 0.290322580645161 0.0005284 0.0005275 0.0005198 0.0004876 0.0004727 0.0003653 0.32258064516129 0.0005261 0.000523 0.000512 0.0004867 0.0004716 0.000365 0.354838709677419 0.000524 0.0005228 0.0005102 0.0004788 0.0004707 0.0003577 0.387096774193548 0.0005181 0.0005159 0.000507 0.0004571 0.0004421 0.0003473 0.419354838709677 0.0005158 0.0005132 0.0005024 0.0004304 0.0004203 0.0003399 0.451612903225806 0.0004884 0.0004874 0.0004789 0.0004281 0.0004121 0.0003316 0.483870967741936 0.0004462 0.0004458 0.0004411 0.0004133 0.0003965 0.0003265 0.516129032258065 0.0004438 0.0004433 0.0004397 0.000412 0.0003908 0.0003087 0.548387096774194 0.0004357 0.0004348 0.0004247 0.0004023 0.0003874 0.0003086 0.580645161290323 0.0004229 0.0004215 0.0004123 0.0003997 0.0003809 0.0003042 0.612903225806452 0.0004219 0.0004191 0.0004115 0.000395 0.0003789 0.0003013 0.645161290322581 0.000419 0.0004183 0.0004071 0.0003879 0.0003787 0.0003002 0.67741935483871 0.0004168 0.0004161 0.0003956 0.0003836 0.0003689 0.0002905 0.709677419354839 0.0004072 0.000405 0.0003934 0.0003799 0.0003686 0.0002818 0.741935483870968 0.0003944 0.0003939 0.0003892 0.0003761 0.0003609 0.0002793 0.774193548387097 0.0003895 0.0003886 0.000381 0.0003594 0.0003469 0.0002787 0.806451612903226 0.0003828 0.0003823 0.0003762 0.0003505 0.0003436 0.0002688 0.838709677419355 0.0003724 0.0003717 0.0003649 0.00035 0.0003394 0.000267950 0.870967741935484 0.0003707 0.0003702 0.0003646 0.0003337 0.0003246 0.0002665 0.903225806451613 0.0003697 0.0003684 0.0003624 0.00032 0.0003083 0.0002602 0.935483870967742 0.0003417 0.0003412 0.0003362 0.0003082 0.0003007 0.0002421 0.967741935483871 0.0003331 0.0003324 0.0002817 0.0001607 0.0001071 2.641e-005

0.1 0.00065136 0.00065037 0.00064123 0.00059461 0.00058768 0.00047047 Average of yearly averages: 0.000328050333333333

Inputs generated by pe4.pl - 8-August-2003

Data used for this run: Output File: lcyhcucu Metfile: w12842.dvf PRZM scenario: FLcucumberC.txt EXAMS environment file: pond298.exv Chemical Name: l-cyhalothrin Description Variable Name Value Units Comments Molecular weight mwt 449.86 g/mol Henry's Law Const. henry 2.4E-7 atm-m^3/mol Vapor Pressure vapr 1.5E-9 torr Solubility sol 0.05 mg/L Kd Kd mg/L Koc Koc 333200 mg/L Photolysis half-lifekdp 26 days Half-life Aerobic Aquatic Metabolism kbacw 44.8 days Halfife Anaerobic Aquatic Metabolism kbacs 159.0 days Halfife Aerobic Soil Metabolism asm 56.5 days Halfife Hydrolysis: pH 7 0 days Half-life Method: CAM 1 integer See PRZM manual Incorporation Depth:DEPI 0 cm Application Rate: TAPP 0.0336 kg/ha Application Efficiency: APPEFF 0.99 fraction Spray Drift DRFT 0.01 fraction of application rate applied to pond Application Date Date 10-11 dd/mm or dd/mmm or dd-mm or dd-mmm Interval 1 interval 5 days Set to 0 or delete line for single app. Interval 2 interval 5 days Set to 0 or delete line for single app. Interval 3 interval 5 days Set to 0 or delete line for single app. Interval 4 interval 5 days Set to 0 or delete line for single app. Interval 5 interval 5 days Set to 0 or delete line for single app. Record 17: FILTRA IPSCND 3 UPTKF 0 Record 18: PLVKRT 0 PLDKRT 0 FEXTRC 0.5 Flag for Index Res. Run IR Pond Flag for runoff calc. RUNOFF none none, monthly or total(average of entire run) Write Benthic Porewater File? benthic 1 Write Benthic Sediment File? benthicsed 1

stored as lcyhcucubensed.out Chemical: l-cyhalothrin PRZM environment: FLcucumberC.txt modified Satday, 12 October 2002 at 14:40:38 EXAMS environment: pond298.exv modified Thuday, 29 August 2002 at 15:33:30 Metfile: w12842.dvf modified Wedday, 3 July 2002 at 08:04:28 Sediment segment concentrations (ppb)

Year Peak 96 hr 21 Day 60 Day 90 Day Yearly 1961 4.44 4.43 3.755 2.142 1.428 0.3521 1962 4.555 4.548 4.481 4.108 4.009 3.228 1963 5.916 5.909 5.86 5.363 5.164 4.114 1964 8.318 8.306 8.168 8 7.919 6.436 1965 6.906 6.876 6.759 6.487 6.301 4.769 1966 5.948 5.942 5.88 5.706 5.603 4.353 1967 4.963 4.955 4.861 4.672 4.623 3.57151 1968 4.941 4.934 4.864 4.448 4.326 3.552 1969 8.722 8.71 8.589 5.737 5.048 4.63 1970 9.209 9.193 9.078 8.881 8.823 6.369 1971 6.51 6.497 6.383 6.093 5.894 4.94 1972 5.585 5.576 5.496 5.327 5.209 4.115 1973 5.637 5.619 5.244 5.171 5.077 4.001 1974 5.624 5.586 5.426 5.113 4.917 4.016 1975 5.428 5.398 5.273 5.013 4.811 3.714 1976 5.103 5.096 5.015 4.265 4.11 3.756 1977 5.257 5.25 5.189 5.063 4.914 3.468 1978 5.555 5.547 5.486 5.265 5.05 3.873 1979 10.73 10.69 10.47 9.729 9.093 7.005 1980 6.875 6.841 6.697 6.5 6.337 4.866 1981 7.26 7.246 7.126 6.829 6.553 5.065 1982 7.043 7.032 6.928 6.771 6.647 5.392 1983 7.672 7.52 7.272 6.382 6.286 5.354 1984 7.674 7.649 7.524 7.256 7.063 5.067 1985 4.928 4.91 4.83 4.665 4.524 3.584 1986 5.192 5.18 5.078 4.791 4.58 3.723 1987 6.985 6.969 6.824 6.519 6.274 4.869 1988 7.33 7.318 7.19 5.491 5.286 4.42 1989 7.013 6.971 6.801 6.608 6.371 4.531 1990 5.808 5.795 5.66 5.51 5.493 4.055

Sorted results Prob. Peak 96 hr 21 Day 60 Day 90 Day Yearly 0.032258064516129 10.73 10.69 10.47 9.729 9.093 7.005 0.0645161290322581 9.209 9.193 9.078 8.881 8.823 6.436 0.0967741935483871 8.722 8.71 8.589 8 7.919 6.369 0.129032258064516 8.318 8.306 8.168 7.256 7.063 5.392 0.161290322580645 7.674 7.649 7.524 6.829 6.647 5.354 0.193548387096774 7.672 7.52 7.272 6.771 6.553 5.067 0.225806451612903 7.33 7.318 7.19 6.608 6.371 5.065 0.258064516129032 7.26 7.246 7.126 6.519 6.337 4.94 0.290322580645161 7.043 7.032 6.928 6.5 6.301 4.869 0.32258064516129 7.013 6.971 6.824 6.487 6.286 4.866 0.354838709677419 6.985 6.969 6.801 6.382 6.274 4.769 0.387096774193548 6.906 6.876 6.759 6.093 5.894 4.63 0.419354838709677 6.875 6.841 6.697 5.737 5.603 4.531 0.451612903225806 6.51 6.497 6.383 5.706 5.493 4.42 0.483870967741936 5.948 5.942 5.88 5.51 5.286 4.353 0.516129032258065 5.916 5.909 5.86 5.491 5.209 4.115 0.548387096774194 5.808 5.795 5.66 5.363 5.164 4.114 0.580645161290323 5.637 5.619 5.496 5.327 5.077 4.055 0.612903225806452 5.624 5.586 5.486 5.265 5.05 4.016 0.645161290322581 5.585 5.576 5.426 5.171 5.048 4.001 0.67741935483871 5.555 5.547 5.273 5.113 4.917 3.873 0.709677419354839 5.428 5.398 5.244 5.063 4.914 3.756 0.741935483870968 5.257 5.25 5.189 5.013 4.811 3.723 0.774193548387097 5.192 5.18 5.078 4.791 4.623 3.714 0.806451612903226 5.103 5.096 5.015 4.672 4.58 3.584 0.838709677419355 4.963 4.955 4.864 4.665 4.524 3.571 0.870967741935484 4.941 4.934 4.861 4.448 4.326 3.552 0.903225806451613 4.928 4.91 4.83 4.265 4.11 3.468 0.935483870967742 4.555 4.548 4.481 4.108 4.009 3.228 0.967741935483871 4.44 4.43 3.755 2.142 1.428 0.3521

0.1 8.6816 8.6696 8.5469 7.9256 7.8334 6.2713 Average of yearly averages: 4.37293666666667

Inputs generated by pe4.pl - 8-August-2003

Data used for this run: Output File: lcyhcucu Metfile: w12842.dvf PRZM scenario: FLcucumberC.txt EXAMS environment file: pond298.exv Chemical Name: l-cyhalothrin Description Variable Name Value Units Comments Molecular weight mwt 449.86 g/mol52 Henry's Law Const. henry 2.4E-7 atm-m^3/mol Vapor Pressure vapr 1.5E-9 torr Solubility sol 0.05 mg/L Kd Kd mg/L Koc Koc 333200 mg/L Photolysis half-lifekdp 26 days Half-life Aerobic Aquatic Metabolism kbacw 44.8 days Halfife Anaerobic Aquatic Metabolism kbacs 159.0 days Halfife Aerobic Soil Metabolism asm 56.5 days Halfife Hydrolysis: pH 7 0 days Half-life Method: CAM 1 integer See PRZM manual Incorporation Depth:DEPI 0 cm Application Rate: TAPP 0.0336 kg/ha Application Efficiency: APPEFF 0.99 fraction Spray Drift DRFT 0.01 fraction of application rate applied to pond Application Date Date 10-11 dd/mm or dd/mmm or dd-mm or dd-mmm Interval 1 interval 5 days Set to 0 or delete line for single app. Interval 2 interval 5 days Set to 0 or delete line for single app. Interval 3 interval 5 days Set to 0 or delete line for single app. Interval 4 interval 5 days Set to 0 or delete line for single app. Interval 5 interval 5 days Set to 0 or delete line for single app. Record 17: FILTRA IPSCND 3 UPTKF 0 Record 18: PLVKRT 0 PLDKRT 0 FEXTRC 0.5 Flag for Index Res. Run IR Pond Flag for runoff calc. RUNOFF none none, monthly or total(average of entire run) Write Benthic Porewater File? benthic 1 Write Benthic Sediment File? benthicsed 1

NC SWEET POTATO:

stored as lcyhswpt.out Chemical: l-cyhalothrin PRZM environment: NCSweetPotatoC.txt modified Friday, 8 August 2003 at 08:25:48 EXAMS environment: pond298.exv modified Thuday, 29 August 2002 at 16:33:30 Metfile: w13722.dvf modified Wedday, 3 July 2002 at 09:05:50 Water segment concentrations (ppb)

Year Peak 96 hr 21 Day 60 Day 90 Day Yearly 1961 0.2246 0.06874 0.03377 0.01981 0.01699 0.006203 1962 0.1287 0.04164 0.02051 0.01573 0.01433 0.01135 1963 0.1885 0.0564 0.02187 0.01617 0.01483 0.01191 1964 0.4563 0.1264 0.04676 0.03118 0.0277 0.01636 1965 0.09107 0.04166 0.02381 0.01885 0.01852 0.01622 1966 0.1033 0.05246 0.03198 0.02339 0.021 0.01465 1967 0.316 0.09354 0.04319 0.0293 0.02618 0.01674 1968 0.1719 0.05497 0.02444 0.02197 0.02172 0.01737 1969 0.2624 0.08014 0.03784 0.03015 0.02802 0.01919 1970 0.2881 0.09041 0.04286 0.02896 0.02645 0.02003 1971 0.1982 0.08612 0.0446 0.0344 0.03089 0.02093 1972 0.2107 0.07165 0.03682 0.02987 0.02768 0.021 1973 0.1783 0.06797 0.0351 0.02581 0.02308 0.01915 1974 0.1854 0.07981 0.03463 0.02638 0.02413 0.01747 1975 0.1434 0.06721 0.02738 0.02122 0.01964 0.01626 1976 0.387 0.1082 0.04049 0.02725 0.02448 0.01637 1977 0.2964 0.08974 0.03584 0.02974 0.02733 0.01909 1978 0.05428 0.02523 0.02019 0.01968 0.01931 0.01575 1979 0.4123 0.1154 0.03941 0.02679 0.02424 0.01547 1980 0.192 0.06007 0.03156 0.02255 0.02041 0.01633 1981 0.2584 0.0738 0.0362 0.02899 0.02677 0.01741 1982 0.07209 0.03064 0.01929 0.01884 0.01846 0.01537 1983 0.1369 0.04234 0.0176 0.01558 0.01393 0.01213 1984 0.1003 0.03243 0.01489 0.01295 0.01266 0.01124 1985 0.232 0.08345 0.03084 0.01956 0.01776 0.0123453 1986 0.2167 0.08873 0.05145 0.03261 0.02853 0.01703 1987 0.4552 0.1279 0.0502 0.03293 0.02937 0.01986 1988 0.2959 0.08903 0.048 0.03285 0.02987 0.02096 1989 0.4138 0.1177 0.04397 0.03164 0.0286 0.02101 1990 0.144 0.05092 0.02294 0.01965 0.01919 0.01617

Sorted results Prob. Peak 96 hr 21 Day 60 Day 90 Day Yearly 0.032258064516129 0.4563 0.1279 0.05145 0.0344 0.03089 0.02101 0.0645161290322581 0.4552 0.1264 0.0502 0.03293 0.02987 0.021 0.0967741935483871 0.4138 0.1177 0.048 0.03285 0.02937 0.02096 0.129032258064516 0.4123 0.1154 0.04676 0.03261 0.0286 0.02093 0.161290322580645 0.387 0.1082 0.0446 0.03164 0.02853 0.02003 0.193548387096774 0.316 0.09354 0.04397 0.03118 0.02802 0.01986 0.225806451612903 0.2964 0.09041 0.04319 0.03015 0.0277 0.01919 0.258064516129032 0.2959 0.08974 0.04286 0.02987 0.02768 0.01915 0.290322580645161 0.2881 0.08903 0.04049 0.02974 0.02733 0.01909 0.32258064516129 0.2624 0.08873 0.03941 0.0293 0.02677 0.01747 0.354838709677419 0.2584 0.08612 0.03784 0.02899 0.02645 0.01741 0.387096774193548 0.232 0.08345 0.03682 0.02896 0.02618 0.01737 0.419354838709677 0.2246 0.08014 0.0362 0.02725 0.02448 0.01703 0.451612903225806 0.2167 0.07981 0.03584 0.02679 0.02424 0.01674 0.483870967741936 0.2107 0.0738 0.0351 0.02638 0.02413 0.01637 0.516129032258065 0.1982 0.07165 0.03463 0.02581 0.02308 0.01636 0.548387096774194 0.192 0.06874 0.03377 0.02339 0.02172 0.01633 0.580645161290323 0.1885 0.06797 0.03198 0.02255 0.021 0.01626 0.612903225806452 0.1854 0.06721 0.03156 0.02197 0.02041 0.01622 0.645161290322581 0.1783 0.06007 0.03084 0.02122 0.01964 0.01617 0.67741935483871 0.1719 0.0564 0.02738 0.01981 0.01931 0.01575 0.709677419354839 0.144 0.05497 0.02444 0.01968 0.01919 0.01547 0.741935483870968 0.1434 0.05246 0.02381 0.01965 0.01852 0.01537 0.774193548387097 0.1369 0.05092 0.02294 0.01956 0.01846 0.01465 0.806451612903226 0.1287 0.04234 0.02187 0.01885 0.01776 0.01234 0.838709677419355 0.1033 0.04166 0.02051 0.01884 0.01699 0.01213 0.870967741935484 0.1003 0.04164 0.02019 0.01617 0.01483 0.01191 0.903225806451613 0.09107 0.03243 0.01929 0.01573 0.01433 0.01135 0.935483870967742 0.07209 0.03064 0.0176 0.01558 0.01393 0.01124 0.967741935483871 0.05428 0.02523 0.01489 0.01295 0.01266 0.006203

0.1 0.41365 0.11747 0.047876 0.032826 0.029293 0.020957 Average of yearly averages: 0.0163787666666667

Inputs generated by pe4.pl - 8-August-2003

Data used for this run: Output File: lcyhswpt Metfile: w13722.dvf PRZM scenario: NCSweetPotatoC.txt EXAMS environment file: pond298.exv Chemical Name: l-cyhalothrin Description Variable Name Value Units Comments Molecular weight mwt 449.86 g/mol Henry's Law Const. henry 2.4E-7 atm-m^3/mol Vapor Pressure vapr 1.5E-9 torr Solubility sol 0.05 mg/L Kd Kd mg/L Koc Koc 333200 mg/L Photolysis half-lifekdp 26 days Half-life Aerobic Aquatic Metabolism kbacw 44.8 days Halfife Anaerobic Aquatic Metabolism kbacs 159.0 days Halfife Aerobic Soil Metabolism asm 56.5 days Halfife Hydrolysis: pH 7 0 days Half-life Method: CAM 1 integer See PRZM manual Incorporation Depth:DEPI 0 cm Application Rate: TAPP 0.0336 kg/ha Application Efficiency: APPEFF 0.95 fraction Spray Drift DRFT 0.039 fraction of application rate applied to pond Application Date Date 01-08 dd/mm or dd/mmm or dd-mm or dd-mmm54 Interval 1 interval 7 days Set to 0 or delete line for single app. Interval 2 interval 7 days Set to 0 or delete line for single app. Interval 3 interval 7 days Set to 0 or delete line for single app. Record 17: FILTRA IPSCND 3 UPTKF 0 Record 18: PLVKRT 0 PLDKRT 0 FEXTRC 0.5 Flag for Index Res. Run IR Pond Flag for runoff calc. RUNOFF none none, monthly or total(average of entire run)

stored as lcyhswptben.out Chemical: l-cyhalothrin PRZM environment: NCSweetPotatoC.txt modified Friday, 8 August 2003 at 08:25:48 EXAMS environment: pond298.exv modified Thuday, 29 August 2002 at 16:33:30 Metfile: w13722.dvf modified Wedday, 3 July 2002 at 09:05:50 Benthic segment concentrations (ppb)

Year Peak 96 hr 21 Day 60 Day 90 Day Yearly 1961 0.00423 0.004218 0.004149 0.00392 0.003786 0.001377 1962 0.004243 0.004238 0.004207 0.00404 0.003724 0.00316 1963 0.004323 0.004318 0.004267 0.004116 0.003871 0.003368 1964 0.007102 0.007082 0.006953 0.006827 0.006689 0.004458 1965 0.006097 0.006084 0.006028 0.0059 0.005797 0.004797 1966 0.005306 0.005294 0.005181 0.005001 0.004943 0.004096 1967 0.007009 0.00699 0.006871 0.006562 0.006372 0.004645 1968 0.005901 0.005889 0.005797 0.005672 0.005541 0.004967 1969 0.007377 0.007364 0.007312 0.007108 0.006967 0.005377 1970 0.007292 0.007271 0.007075 0.00666 0.006513 0.00576 1971 0.007937 0.007916 0.007764 0.007629 0.007501 0.005865 1972 0.007385 0.007373 0.007276 0.007134 0.007039 0.005997 1973 0.006703 0.006689 0.006629 0.006504 0.00638 0.005561 1974 0.006657 0.006641 0.006498 0.006225 0.006073 0.004943 1975 0.005557 0.005552 0.005534 0.005445 0.005358 0.004665 1976 0.006397 0.006383 0.006239 0.006104 0.006018 0.004592 1977 0.007371 0.007353 0.007182 0.006927 0.006808 0.005357 1978 0.006273 0.00626 0.006226 0.00612 0.006018 0.004678 1979 0.006318 0.0063 0.00621 0.006095 0.005999 0.004239 1980 0.005597 0.005581 0.005464 0.005363 0.005274 0.004684 1981 0.006796 0.006779 0.00663 0.006422 0.006382 0.004819 1982 0.006072 0.006063 0.006013 0.005886 0.005769 0.004541 1983 0.00409 0.004087 0.004068 0.003947 0.003916 0.003427 1984 0.004065 0.004062 0.004041 0.003984 0.003915 0.003259 1985 0.004668 0.004657 0.004563 0.004314 0.004198 0.00336 1986 0.007614 0.007593 0.007399 0.007009 0.006769 0.004656 1987 0.007985 0.007961 0.007781 0.007482 0.007298 0.00557 1988 0.008007 0.007989 0.007844 0.007578 0.007436 0.005943 1989 0.007306 0.007281 0.00714 0.007012 0.006969 0.005995 1990 0.006411 0.006392 0.006314 0.006138 0.005992 0.004742

Sorted results Prob. Peak 96 hr 21 Day 60 Day 90 Day Yearly 0.032258064516129 0.008007 0.007989 0.007844 0.007629 0.007501 0.005997 0.0645161290322581 0.007985 0.007961 0.007781 0.007578 0.007436 0.005995 0.0967741935483871 0.007937 0.007916 0.007764 0.007482 0.007298 0.005943 0.129032258064516 0.007614 0.007593 0.007399 0.007134 0.007039 0.005865 0.161290322580645 0.007385 0.007373 0.007312 0.007108 0.006969 0.00576 0.193548387096774 0.007377 0.007364 0.007276 0.007012 0.006967 0.00557 0.225806451612903 0.007371 0.007353 0.007182 0.007009 0.006808 0.005561 0.258064516129032 0.007306 0.007281 0.00714 0.006927 0.006769 0.00537755 0.290322580645161 0.007292 0.007271 0.007075 0.006827 0.006689 0.005357 0.32258064516129 0.007102 0.007082 0.006953 0.00666 0.006513 0.004967 0.354838709677419 0.007009 0.00699 0.006871 0.006562 0.006382 0.004943 0.387096774193548 0.006796 0.006779 0.00663 0.006504 0.00638 0.004819 0.419354838709677 0.006703 0.006689 0.006629 0.006422 0.006372 0.004797 0.451612903225806 0.006657 0.006641 0.006498 0.006225 0.006073 0.004742 0.483870967741936 0.006411 0.006392 0.006314 0.006138 0.006018 0.004684 0.516129032258065 0.006397 0.006383 0.006239 0.00612 0.006018 0.004678 0.548387096774194 0.006318 0.0063 0.006226 0.006104 0.005999 0.004665 0.580645161290323 0.006273 0.00626 0.00621 0.006095 0.005992 0.004656 0.612903225806452 0.006097 0.006084 0.006028 0.0059 0.005797 0.004645 0.645161290322581 0.006072 0.006063 0.006013 0.005886 0.005769 0.004592 0.67741935483871 0.005901 0.005889 0.005797 0.005672 0.005541 0.004541 0.709677419354839 0.005597 0.005581 0.005534 0.005445 0.005358 0.004458 0.741935483870968 0.005557 0.005552 0.005464 0.005363 0.005274 0.004239 0.774193548387097 0.005306 0.005294 0.005181 0.005001 0.004943 0.004096 0.806451612903226 0.004668 0.004657 0.004563 0.004314 0.004198 0.003427 0.838709677419355 0.004323 0.004318 0.004267 0.004116 0.003916 0.003368 0.870967741935484 0.004243 0.004238 0.004207 0.00404 0.003915 0.00336 0.903225806451613 0.00423 0.004218 0.004149 0.003984 0.003871 0.003259 0.935483870967742 0.00409 0.004087 0.004068 0.003947 0.003786 0.00316 0.967741935483871 0.004065 0.004062 0.004041 0.00392 0.003724 0.001377

0.1 0.0079047 0.0078837 0.0077275 0.0074472 0.0072721 0.0059352 Average of yearly averages: 0.00462993333333333

Inputs generated by pe4.pl - 8-August-2003

Data used for this run: Output File: lcyhswpt Metfile: w13722.dvf PRZM scenario: NCSweetPotatoC.txt EXAMS environment file: pond298.exv Chemical Name: l-cyhalothrin Description Variable Name Value Units Comments Molecular weight mwt 449.86 g/mol Henry's Law Const. henry 2.4E-7 atm-m^3/mol Vapor Pressure vapr 1.5E-9 torr Solubility sol 0.05 mg/L Kd Kd mg/L Koc Koc 333200 mg/L Photolysis half-lifekdp 26 days Half-life Aerobic Aquatic Metabolism kbacw 44.8 days Halfife Anaerobic Aquatic Metabolism kbacs 159.0 days Halfife Aerobic Soil Metabolism asm 56.5 days Halfife Hydrolysis: pH 7 0 days Half-life Method: CAM 1 integer See PRZM manual Incorporation Depth:DEPI 0 cm56 Application Rate: TAPP 0.0336 kg/ha Application Efficiency: APPEFF 0.95 fraction Spray Drift DRFT 0.039 fraction of application rate applied to pond Application Date Date 01-08 dd/mm or dd/mmm or dd-mm or dd-mmm Interval 1 interval 7 days Set to 0 or delete line for single app. Interval 2 interval 7 days Set to 0 or delete line for single app. Interval 3 interval 7 days Set to 0 or delete line for single app. Record 17: FILTRA IPSCND 3 UPTKF 0 Record 18: PLVKRT 0 PLDKRT 0 FEXTRC 0.5 Flag for Index Res. Run IR Pond Flag for runoff calc. RUNOFF none none, monthly or total(average of entire run)

stored as lcyhswptbensed.out Chemical: l-cyhalothrin PRZM environment: NCSweetPotatoC.txt modified Friday, 8 August 2003 at 07:25:48 EXAMS environment: pond298.exv modified Thuday, 29 August 2002 at 15:33:30 Metfile: w13722.dvf modified Wedday, 3 July 2002 at 08:05:50 Sediment segment concentrations (ppb)

Year Peak 96 hr 21 Day 60 Day 90 Day Yearly 1961 56.38 56.22 55.3 52.26 50.46 18.36 1962 56.56 56.49 56.08 53.85 49.65 42.12 1963 57.62 57.55 56.88 54.86 51.6 44.89 1964 94.67 94.41 92.68 91 89.17 59.42 1965 81.27 81.1 80.36 78.64 77.27 63.94 1966 70.73 70.56 69.06 66.66 65.88 54.6 1967 93.42 93.18 91.59 87.47 84.93 61.92 1968 78.66 78.5 77.28 75.61 73.86 66.21 1969 98.34 98.16 97.47 94.75 92.87 71.68 1970 97.19 96.92 94.31 88.77 86.82 76.78 1971 106 106 103 102 99.98 78.17 1972 98.44 98.28 96.98 95.09 93.83 79.94 1973 89.35 89.16 88.36 86.69 85.04 74.13 1974 88.73 88.53 86.62 82.97 80.95 65.89 1975 74.08 74.01 73.77 72.58 71.42 62.18 1976 85.27 85.09 83.16 81.36 80.22 61.21 1977 98.25 98.01 95.73 92.33 90.74 71.4 1978 83.61 83.44 82.99 81.58 80.22 62.36 1979 84.21 83.98 82.78 81.25 79.96 56.5 1980 74.61 74.39 72.83 71.49 70.3 62.44 1981 90.59 90.36 88.38 85.6 85.07 64.23 1982 80.94 80.82 80.16 78.45 76.9 60.53 1983 54.52 54.48 54.22 52.62 52.2 45.68 1984 54.19 54.15 53.87 53.1 52.19 43.44 1985 62.22 62.07 60.82 57.51 55.96 44.78 1986 101 101 98.63 93.43 90.23 62.06 1987 106 106 104 99.74 97.28 74.25 1988 107 106 105 101 99.11 79.22 1989 97.39 97.06 95.17 93.46 92.9 79.91 1990 85.45 85.2 84.16 81.81 79.87 63.21

Sorted results Prob. Peak 96 hr 21 Day 60 Day 90 Day Yearly 0.032258064516129 107 106 105 102 99.98 79.94 0.0645161290322581 106 106 104 101 99.11 79.91 0.0967741935483871 106 106 103 99.74 97.28 79.22 0.129032258064516 101 101 98.63 95.09 93.83 78.17 0.161290322580645 98.44 98.28 97.47 94.75 92.9 76.78 0.193548387096774 98.34 98.16 96.98 93.46 92.87 74.25 0.225806451612903 98.25 98.01 95.73 93.43 90.74 74.13 0.258064516129032 97.39 97.06 95.17 92.33 90.23 71.68 0.290322580645161 97.19 96.92 94.31 91 89.17 71.4 0.32258064516129 94.67 94.41 92.68 88.77 86.82 66.21 0.354838709677419 93.42 93.18 91.59 87.47 85.07 65.89 0.387096774193548 90.59 90.36 88.38 86.69 85.04 64.2357 0.419354838709677 89.35 89.16 88.36 85.6 84.93 63.94 0.451612903225806 88.73 88.53 86.62 82.97 80.95 63.21 0.483870967741936 85.45 85.2 84.16 81.81 80.22 62.44 0.516129032258065 85.27 85.09 83.16 81.58 80.22 62.36 0.548387096774194 84.21 83.98 82.99 81.36 79.96 62.18 0.580645161290323 83.61 83.44 82.78 81.25 79.87 62.06 0.612903225806452 81.27 81.1 80.36 78.64 77.27 61.92 0.645161290322581 80.94 80.82 80.16 78.45 76.9 61.21 0.67741935483871 78.66 78.5 77.28 75.61 73.86 60.53 0.709677419354839 74.61 74.39 73.77 72.58 71.42 59.42 0.741935483870968 74.08 74.01 72.83 71.49 70.3 56.5 0.774193548387097 70.73 70.56 69.06 66.66 65.88 54.6 0.806451612903226 62.22 62.07 60.82 57.51 55.96 45.68 0.838709677419355 57.62 57.55 56.88 54.86 52.2 44.89 0.870967741935484 56.56 56.49 56.08 53.85 52.19 44.78 0.903225806451613 56.38 56.22 55.3 53.1 51.6 43.44 0.935483870967742 54.52 54.48 54.22 52.62 50.46 42.12 0.967741935483871 54.19 54.15 53.87 52.26 49.65 18.36

0.1 105.5 105.5 102.563 99.275 96.935 79.115 Average of yearly averages: 61.715

Inputs generated by pe4.pl - 8-August-2003

Data used for this run: Output File: lcyhswpt Metfile: w13722.dvf PRZM scenario: NCSweetPotatoC.txt EXAMS environment file: pond298.exv Chemical Name: l-cyhalothrin Description Variable Name Value Units Comments Molecular weight mwt 449.86 g/mol Henry's Law Const. henry 2.4E-7 atm-m^3/mol Vapor Pressure vapr 1.5E-9 torr Solubility sol 0.05 mg/L Kd Kd mg/L Koc Koc 333200 mg/L Photolysis half-lifekdp 26 days Half-life Aerobic Aquatic Metabolism kbacw 44.8 days Halfife Anaerobic Aquatic Metabolism kbacs 159.0 days Halfife Aerobic Soil Metabolism asm 56.5 days Halfife Hydrolysis: pH 7 0 days Half-life Method: CAM 1 integer See PRZM manual Incorporation Depth:DEPI 0 cm Application Rate: TAPP 0.0336 kg/ha Application Efficiency: APPEFF 0.95 fraction Spray Drift DRFT 0.039 fraction of application rate applied to pond Application Date Date 01-08 dd/mm or dd/mmm or dd-mm or dd-mmm Interval 1 interval 7 days Set to 0 or delete line for single app. Interval 2 interval 7 days Set to 0 or delete line for single app. Interval 3 interval 7 days Set to 0 or delete line for single app. Record 17: FILTRA IPSCND 3 UPTKF 0 Record 18: PLVKRT 0 PLDKRT 0 FEXTRC 0.5 Flag for Index Res. Run IR Pond Flag for runoff calc. RUNOFF none none, monthly or total(average of entire run) Write Benthic Porewater File? benthic 1 Write Benthic Sediment File? benthicsed 1

NC SWEET POTATO 0% DRIFT stored as lcyhswpt.out Chemical: l-cyhalothrin PRZM environment: NCSweetPotatoC.txt modified Friday, 8 August 2003 at 08:25:48 EXAMS environment: pond298.exv modified Thuday, 29 August 2002 at 16:33:30 Metfile: w13722.dvf modified Wedday, 3 July 2002 at 09:05:5058 Water segment concentrations (ppb)

Year Peak 96 hr 21 Day 60 Day 90 Day Yearly 1961 0.2232 0.05932 0.03046 0.01768 0.0151 0.005249 1962 0.1267 0.03971 0.01858 0.01385 0.01234 0.009521 1963 0.1863 0.05422 0.01972 0.01406 0.01265 0.009716 1964 0.4536 0.1237 0.04414 0.02869 0.02529 0.01402 1965 0.0711 0.03125 0.01716 0.0168 0.01651 0.01381 1966 0.1004 0.04425 0.02476 0.01882 0.01714 0.01224 1967 0.3131 0.09071 0.03713 0.02531 0.0227 0.01433 1968 0.1691 0.05227 0.02207 0.01949 0.01839 0.01494 1969 0.2596 0.07735 0.03512 0.02624 0.02396 0.01673 1970 0.2735 0.08171 0.03572 0.02467 0.02277 0.01752 1971 0.1918 0.07486 0.03849 0.03056 0.02754 0.01846 1972 0.2078 0.06719 0.03232 0.02649 0.02461 0.01857 1973 0.172 0.06455 0.02794 0.02095 0.01904 0.01671 1974 0.1827 0.0771 0.03198 0.02238 0.02039 0.01508 1975 0.1409 0.06465 0.02488 0.01883 0.01732 0.01383 1976 0.3844 0.1056 0.03794 0.02482 0.0221 0.014 1977 0.2937 0.08711 0.03329 0.02645 0.02427 0.01669 1978 0.04433 0.02241 0.01809 0.01763 0.0173 0.01338 1979 0.4096 0.1127 0.03681 0.02433 0.02185 0.01311 1980 0.1893 0.05745 0.02723 0.01927 0.01745 0.01398 1981 0.2204 0.06308 0.02879 0.02473 0.02315 0.01507 1982 0.06976 0.02831 0.01719 0.01679 0.01645 0.01299 1983 0.1346 0.04003 0.01533 0.01338 0.0117 0.009768 1984 0.09775 0.02992 0.01204 0.01092 0.01067 0.00886 1985 0.2283 0.08011 0.02545 0.01598 0.01462 0.009978 1986 0.2142 0.08609 0.04558 0.02894 0.02534 0.01471 1987 0.4525 0.1253 0.04765 0.03052 0.02701 0.01755 1988 0.2931 0.08634 0.04493 0.03024 0.02729 0.01863 1989 0.4076 0.1144 0.03878 0.02821 0.02554 0.01865 1990 0.1418 0.04869 0.02069 0.01764 0.01723 0.01386

Sorted results Prob. Peak 96 hr 21 Day 60 Day 90 Day Yearly 0.032258064516129 0.4536 0.1253 0.04765 0.03056 0.02754 0.01865 0.0645161290322581 0.4525 0.1237 0.04558 0.03052 0.02729 0.01863 0.0967741935483871 0.4096 0.1144 0.04493 0.03024 0.02701 0.01857 0.129032258064516 0.4076 0.1127 0.04414 0.02894 0.02554 0.01846 0.161290322580645 0.3844 0.1056 0.03878 0.02869 0.02534 0.01755 0.193548387096774 0.3131 0.09071 0.03849 0.02821 0.02529 0.01752 0.225806451612903 0.2937 0.08711 0.03794 0.02649 0.02461 0.01673 0.258064516129032 0.2931 0.08634 0.03713 0.02645 0.02427 0.01671 0.290322580645161 0.2735 0.08609 0.03681 0.02624 0.02396 0.01669 0.32258064516129 0.2596 0.08171 0.03572 0.02531 0.02315 0.01508 0.354838709677419 0.2283 0.08011 0.03512 0.02482 0.02277 0.01507 0.387096774193548 0.2232 0.07735 0.03329 0.02473 0.0227 0.01494 0.419354838709677 0.2204 0.0771 0.03232 0.02467 0.0221 0.01471 0.451612903225806 0.2142 0.07486 0.03198 0.02433 0.02185 0.01433 0.483870967741936 0.2078 0.06719 0.03046 0.02238 0.02039 0.01402 0.516129032258065 0.1918 0.06465 0.02879 0.02095 0.01904 0.014 0.548387096774194 0.1893 0.06455 0.02794 0.01949 0.01839 0.01398 0.580645161290323 0.1863 0.06308 0.02723 0.01927 0.01745 0.01386 0.612903225806452 0.1827 0.05932 0.02545 0.01883 0.01732 0.01383 0.645161290322581 0.172 0.05745 0.02488 0.01882 0.0173 0.01381 0.67741935483871 0.1691 0.05422 0.02476 0.01768 0.01723 0.01338 0.709677419354839 0.1418 0.05227 0.02207 0.01764 0.01714 0.01311 0.741935483870968 0.1409 0.04869 0.02069 0.01763 0.01651 0.01299 0.774193548387097 0.1346 0.04425 0.01972 0.0168 0.01645 0.01224 0.806451612903226 0.1267 0.04003 0.01858 0.01679 0.0151 0.009978 0.838709677419355 0.1004 0.03971 0.01809 0.01598 0.01462 0.009768 0.870967741935484 0.09775 0.03125 0.01719 0.01406 0.01265 0.009716 0.903225806451613 0.0711 0.02992 0.01716 0.01385 0.01234 0.009521 0.935483870967742 0.06976 0.02831 0.01533 0.01338 0.0117 0.00886 0.967741935483871 0.04433 0.02241 0.01204 0.01092 0.01067 0.00524959 0.1 0.4094 0.11423 0.044851 0.03011 0.026863 0.018559 Average of yearly averages: 0.0140650666666667

Inputs generated by pe4.pl - 8-August-2003

Data used for this run: Output File: lcyhswpt Metfile: w13722.dvf PRZM scenario: NCSweetPotatoC.txt EXAMS environment file: pond298.exv Chemical Name: l-cyhalothrin Description Variable Name Value Units Comments Molecular weight mwt 449.86 g/mol Henry's Law Const. henry 2.4E-7 atm-m^3/mol Vapor Pressure vapr 1.5E-9 torr Solubility sol 0.05 mg/L Kd Kd mg/L Koc Koc 333200 mg/L Photolysis half-lifekdp 26 days Half-life Aerobic Aquatic Metabolism kbacw 44.8 days Halfife Anaerobic Aquatic Metabolism kbacs 159.0 days Halfife Aerobic Soil Metabolism asm 56.5 days Halfife Hydrolysis: pH 7 0 days Half-life Method: CAM 1 integer See PRZM manual Incorporation Depth:DEPI 0 cm Application Rate: TAPP 0.0336 kg/ha Application Efficiency: APPEFF 0.95 fraction Spray Drift DRFT 0.0 fraction of application rate applied to pond Application Date Date 01-08 dd/mm or dd/mmm or dd-mm or dd-mmm Interval 1 interval 7 days Set to 0 or delete line for single app. Interval 2 interval 7 days Set to 0 or delete line for single app. Interval 3 interval 7 days Set to 0 or delete line for single app. Record 17: FILTRA IPSCND 3 UPTKF 0 Record 18: PLVKRT 0 PLDKRT 0 FEXTRC 0.5 Flag for Index Res. Run IR Pond Flag for runoff calc. RUNOFF none none, monthly or total(average of entire run)

stored as lcyhswptben.out Chemical: l-cyhalothrin PRZM environment: NCSweetPotatoC.txt modified Friday, 8 August 2003 at 08:25:48 EXAMS environment: pond298.exv modified Thuday, 29 August 2002 at 16:33:30 Metfile: w13722.dvf modified Wedday, 3 July 2002 at 09:05:50 Benthic segment concentrations (ppb)

Year Peak 96 hr 21 Day 60 Day 90 Day Yearly 1961 0.003712 0.003702 0.003637 0.003439 0.003322 0.0012 1962 0.00364 0.003636 0.003611 0.003451 0.00312 0.002709 1963 0.003642 0.003638 0.003596 0.003456 0.003331 0.002801 1964 0.006292 0.006274 0.006165 0.00607 0.005938 0.003846 1965 0.005433 0.005422 0.005372 0.005257 0.005166 0.004165 1966 0.004503 0.004493 0.004398 0.00425 0.004159 0.003464 1967 0.006132 0.006116 0.006017 0.005751 0.005587 0.004011 1968 0.005156 0.005146 0.005065 0.004963 0.004828 0.004326 1969 0.006574 0.006562 0.006504 0.006329 0.006202 0.004731 1970 0.006372 0.006355 0.006184 0.005823 0.005707 0.005098 1971 0.007089 0.007068 0.006962 0.006848 0.006711 0.005213 1972 0.006599 0.006589 0.006496 0.006379 0.006301 0.005356 1973 0.006017 0.006004 0.005951 0.005839 0.005728 0.004917 1974 0.005813 0.005801 0.005677 0.005441 0.00531 0.004315 1975 0.004887 0.004883 0.004862 0.00479 0.004715 0.004025 1976 0.00559 0.005576 0.005451 0.005349 0.005279 0.003969 1977 0.006546 0.00653 0.006381 0.006165 0.006067 0.004725 1978 0.00561 0.005599 0.005571 0.005478 0.005387 0.004056 1979 0.005482 0.005467 0.005404 0.005324 0.005251 0.00362260 1980 0.004856 0.004845 0.00481 0.004724 0.004646 0.00407 1981 0.005974 0.00596 0.005828 0.005659 0.005641 0.004206 1982 0.005408 0.005401 0.005357 0.005243 0.00514 0.003918 1983 0.003421 0.003418 0.003401 0.003316 0.003297 0.002807 1984 0.003416 0.003414 0.003398 0.003349 0.003293 0.002633 1985 0.003805 0.003799 0.003776 0.003621 0.003484 0.00274 1986 0.006767 0.006749 0.006578 0.006225 0.006015 0.004049 1987 0.007194 0.007173 0.007003 0.006731 0.006568 0.004967 1988 0.007195 0.00718 0.007046 0.00682 0.006698 0.005333 1989 0.006487 0.006476 0.006379 0.006212 0.006197 0.005378 1990 0.005754 0.005737 0.005667 0.00551 0.005379 0.004141

Sorted results Prob. Peak 96 hr 21 Day 60 Day 90 Day Yearly 0.032258064516129 0.007195 0.00718 0.007046 0.006848 0.006711 0.005378 0.0645161290322581 0.007194 0.007173 0.007003 0.00682 0.006698 0.005356 0.0967741935483871 0.007089 0.007068 0.006962 0.006731 0.006568 0.005333 0.129032258064516 0.006767 0.006749 0.006578 0.006379 0.006301 0.005213 0.161290322580645 0.006599 0.006589 0.006504 0.006329 0.006202 0.005098 0.193548387096774 0.006574 0.006562 0.006496 0.006225 0.006197 0.004967 0.225806451612903 0.006546 0.00653 0.006381 0.006212 0.006067 0.004917 0.258064516129032 0.006487 0.006476 0.006379 0.006165 0.006015 0.004731 0.290322580645161 0.006372 0.006355 0.006184 0.00607 0.005938 0.004725 0.32258064516129 0.006292 0.006274 0.006165 0.005839 0.005728 0.004326 0.354838709677419 0.006132 0.006116 0.006017 0.005823 0.005707 0.004315 0.387096774193548 0.006017 0.006004 0.005951 0.005751 0.005641 0.004206 0.419354838709677 0.005974 0.00596 0.005828 0.005659 0.005587 0.004165 0.451612903225806 0.005813 0.005801 0.005677 0.00551 0.005387 0.004141 0.483870967741936 0.005754 0.005737 0.005667 0.005478 0.005379 0.00407 0.516129032258065 0.00561 0.005599 0.005571 0.005441 0.00531 0.004056 0.548387096774194 0.00559 0.005576 0.005451 0.005349 0.005279 0.004049 0.580645161290323 0.005482 0.005467 0.005404 0.005324 0.005251 0.004025 0.612903225806452 0.005433 0.005422 0.005372 0.005257 0.005166 0.004011 0.645161290322581 0.005408 0.005401 0.005357 0.005243 0.00514 0.003969 0.67741935483871 0.005156 0.005146 0.005065 0.004963 0.004828 0.003918 0.709677419354839 0.004887 0.004883 0.004862 0.00479 0.004715 0.003846 0.741935483870968 0.004856 0.004845 0.00481 0.004724 0.004646 0.003622 0.774193548387097 0.004503 0.004493 0.004398 0.00425 0.004159 0.003464 0.806451612903226 0.003805 0.003799 0.003776 0.003621 0.003484 0.002807 0.838709677419355 0.003712 0.003702 0.003637 0.003456 0.003331 0.002801 0.870967741935484 0.003642 0.003638 0.003611 0.003451 0.003322 0.00274 0.903225806451613 0.00364 0.003636 0.003596 0.003439 0.003297 0.00270961 0.935483870967742 0.003421 0.003418 0.003401 0.003349 0.003293 0.002633 0.967741935483871 0.003416 0.003414 0.003398 0.003316 0.00312 0.0012

0.1 0.0070568 0.0070361 0.0069236 0.0066958 0.0065413 0.005321 Average of yearly averages: 0.00402636666666667

Inputs generated by pe4.pl - 8-August-2003

Data used for this run: Output File: lcyhswpt Metfile: w13722.dvf PRZM scenario: NCSweetPotatoC.txt EXAMS environment file: pond298.exv Chemical Name: l-cyhalothrin Description Variable Name Value Units Comments Molecular weight mwt 449.86 g/mol Henry's Law Const. henry 2.4E-7 atm-m^3/mol Vapor Pressure vapr 1.5E-9 torr Solubility sol 0.05 mg/L Kd Kd mg/L Koc Koc 333200 mg/L Photolysis half-lifekdp 26 days Half-life Aerobic Aquatic Metabolism kbacw 44.8 days Halfife Anaerobic Aquatic Metabolism kbacs 159.0 days Halfife Aerobic Soil Metabolism asm 56.5 days Halfife Hydrolysis: pH 7 0 days Half-life Method: CAM 1 integer See PRZM manual Incorporation Depth:DEPI 0 cm Application Rate: TAPP 0.0336 kg/ha Application Efficiency: APPEFF 0.95 fraction Spray Drift DRFT 0.0 fraction of application rate applied to pond Application Date Date 01-08 dd/mm or dd/mmm or dd-mm or dd-mmm Interval 1 interval 7 days Set to 0 or delete line for single app. Interval 2 interval 7 days Set to 0 or delete line for single app. Interval 3 interval 7 days Set to 0 or delete line for single app. Record 17: FILTRA IPSCND 3 UPTKF 0 Record 18: PLVKRT 0 PLDKRT 0 FEXTRC 0.5 Flag for Index Res. Run IR Pond Flag for runoff calc. RUNOFF none none, monthly or total(average of entire run)

NC Sweet Potato ground application:

stored as lcyhswpt.out Chemical: l-cyhalothrin PRZM environment: NCSweetPotatoC.txt modified Friday, 8 August 2003 at 07:25:48 EXAMS environment: pond298.exv modified Thuday, 29 August 2002 at 15:33:30 Metfile: w13722.dvf modified Wedday, 3 July 2002 at 08:05:50 Water segment concentrations (ppb)

Year Peak 96 hr 21 Day 60 Day 90 Day Yearly 1961 0.2246 0.06874 0.03377 0.01981 0.01699 0.006203 1962 0.1287 0.04164 0.02051 0.01573 0.01433 0.01135 1963 0.1885 0.0564 0.02187 0.01617 0.01483 0.01191 1964 0.4563 0.1264 0.04676 0.03118 0.0277 0.01636 1965 0.09107 0.04166 0.02381 0.01885 0.01852 0.01622 1966 0.1033 0.05246 0.03198 0.02339 0.021 0.01465 1967 0.316 0.09354 0.04319 0.0293 0.02618 0.01674 1968 0.1719 0.05497 0.02444 0.02197 0.02172 0.01737 1969 0.2624 0.08014 0.03784 0.03015 0.02802 0.01919 1970 0.2881 0.09041 0.04286 0.02896 0.02645 0.02003 1971 0.1982 0.08612 0.0446 0.0344 0.03089 0.02093 1972 0.2107 0.07165 0.03682 0.02987 0.02768 0.02162 1973 0.1783 0.06797 0.0351 0.02581 0.02308 0.01915 1974 0.1854 0.07981 0.03463 0.02638 0.02413 0.01747 1975 0.1434 0.06721 0.02738 0.02122 0.01964 0.01626 1976 0.387 0.1082 0.04049 0.02725 0.02448 0.01637 1977 0.2964 0.08974 0.03584 0.02974 0.02733 0.01909 1978 0.05428 0.02523 0.02019 0.01968 0.01931 0.01575 1979 0.4123 0.1154 0.03941 0.02679 0.02424 0.01547 1980 0.192 0.06007 0.03156 0.02255 0.02041 0.01633 1981 0.2584 0.0738 0.0362 0.02899 0.02677 0.01741 1982 0.07209 0.03064 0.01929 0.01884 0.01846 0.01537 1983 0.1369 0.04234 0.0176 0.01558 0.01393 0.01213 1984 0.1003 0.03243 0.01489 0.01295 0.01266 0.01124 1985 0.232 0.08345 0.03084 0.01956 0.01776 0.01234 1986 0.2167 0.08873 0.05145 0.03261 0.02853 0.01703 1987 0.4552 0.1279 0.0502 0.03293 0.02937 0.01986 1988 0.2959 0.08903 0.048 0.03285 0.02987 0.02096 1989 0.4138 0.1177 0.04397 0.03164 0.0286 0.02101 1990 0.144 0.05092 0.02294 0.01965 0.01919 0.01617

Sorted results Prob. Peak 96 hr 21 Day 60 Day 90 Day Yearly 0.032258064516129 0.4563 0.1279 0.05145 0.0344 0.03089 0.02101 0.0645161290322581 0.4552 0.1264 0.0502 0.03293 0.02987 0.021 0.0967741935483871 0.4138 0.1177 0.048 0.03285 0.02937 0.02096 0.129032258064516 0.4123 0.1154 0.04676 0.03261 0.0286 0.02093 0.161290322580645 0.387 0.1082 0.0446 0.03164 0.02853 0.02003 0.193548387096774 0.316 0.09354 0.04397 0.03118 0.02802 0.01986 0.225806451612903 0.2964 0.09041 0.04319 0.03015 0.0277 0.01919 0.258064516129032 0.2959 0.08974 0.04286 0.02987 0.02768 0.01915 0.290322580645161 0.2881 0.08903 0.04049 0.02974 0.02733 0.01909 0.32258064516129 0.2624 0.08873 0.03941 0.0293 0.02677 0.01747 0.354838709677419 0.2584 0.08612 0.03784 0.02899 0.02645 0.01741 0.387096774193548 0.232 0.08345 0.03682 0.02896 0.02618 0.01737 0.419354838709677 0.2246 0.08014 0.0362 0.02725 0.02448 0.01703 0.451612903225806 0.2167 0.07981 0.03584 0.02679 0.02424 0.01674 0.483870967741936 0.2107 0.0738 0.0351 0.02638 0.02413 0.01637 0.516129032258065 0.1982 0.07165 0.03463 0.02581 0.02308 0.01636 0.548387096774194 0.192 0.06874 0.03377 0.02339 0.02172 0.01633 0.580645161290323 0.1885 0.06797 0.03198 0.02255 0.021 0.01626 0.612903225806452 0.1854 0.06721 0.03156 0.02197 0.02041 0.01622 0.645161290322581 0.1783 0.06007 0.03084 0.02122 0.01964 0.01617 0.67741935483871 0.1719 0.0564 0.02738 0.01981 0.01931 0.01575 0.709677419354839 0.144 0.05497 0.02444 0.01968 0.01919 0.01547 0.741935483870968 0.1434 0.05246 0.02381 0.01965 0.01852 0.01537 0.774193548387097 0.1369 0.05092 0.02294 0.01956 0.01846 0.01465 0.806451612903226 0.1287 0.04234 0.02187 0.01885 0.01776 0.01234 0.838709677419355 0.1033 0.04166 0.02051 0.01884 0.01699 0.01213 0.870967741935484 0.1003 0.04164 0.02019 0.01617 0.01483 0.01191 0.903225806451613 0.09107 0.03243 0.01929 0.01573 0.01433 0.01135 0.935483870967742 0.07209 0.03064 0.0176 0.01558 0.01393 0.01124 0.967741935483871 0.05428 0.02523 0.01489 0.01295 0.01266 0.006203

0.1 0.41365 0.11747 0.047876 0.032826 0.029293 0.020957 Average of yearly averages: 0.0163787666666667

Inputs generated by pe4.pl - 8-August-2003

Data used for this run: Output File: lcyhswpt Metfile: w13722.dvf PRZM scenario: NCSweetPotatoC.txt EXAMS environment file: pond298.exv Chemical Name: l-cyhalothrin Description Variable Name Value Units Comments Molecular weight mwt 449.86 g/mol Henry's Law Const. henry 2.4E-7 atm-m^3/mol Vapor Pressure vapr 1.5E-9 torr Solubility sol 0.05 mg/L63 Kd Kd mg/L Koc Koc 333200 mg/L Photolysis half-lifekdp 26 days Half-life Aerobic Aquatic Metabolism kbacw 44.8 days Halfife Anaerobic Aquatic Metabolism kbacs 159.0 days Halfife Aerobic Soil Metabolism asm 56.5 days Halfife Hydrolysis: pH 7 0 days Half-life Method: CAM 1 integer See PRZM manual Incorporation Depth:DEPI 0 cm Application Rate: TAPP 0.0336 kg/ha Application Efficiency: APPEFF 0.95 fraction Spray Drift DRFT 0.039 fraction of application rate applied to pond Application Date Date 01-08 dd/mm or dd/mmm or dd-mm or dd-mmm Interval 1 interval 7 days Set to 0 or delete line for single app. Interval 2 interval 7 days Set to 0 or delete line for single app. Interval 3 interval 7 days Set to 0 or delete line for single app. Record 17: FILTRA IPSCND 3 UPTKF 0 Record 18: PLVKRT 0 PLDKRT 0 FEXTRC 0.5 Flag for Index Res. Run IR Pond Flag for runoff calc. RUNOFF none none, monthly or total(average of entire run) Write Benthic Porewater File? benthic 1 Write Benthic Sediment File? benthicsed 1

stored as lcyhswptben.out Chemical: l-cyhalothrin PRZM environment: NCSweetPotatoC.txt modified Friday, 8 August 2003 at 07:25:48 EXAMS environment: pond298.exv modified Thuday, 29 August 2002 at 15:33:30 Metfile: w13722.dvf modified Wedday, 3 July 2002 at 08:05:50 Benthic segment concentrations (ppb)

Year Peak 96 hr 21 Day 60 Day 90 Day Yearly 1961 0.00423 0.004218 0.004149 0.00392 0.003786 0.001377 1962 0.004243 0.004238 0.004207 0.00404 0.003724 0.00316 1963 0.004323 0.004318 0.004267 0.004116 0.003871 0.003368 1964 0.007102 0.007082 0.006953 0.006827 0.006689 0.004458 1965 0.006097 0.006084 0.006028 0.0059 0.005797 0.004797 1966 0.005306 0.005294 0.005181 0.005001 0.004943 0.004096 1967 0.007009 0.00699 0.006871 0.006562 0.006372 0.004645 1968 0.005901 0.005889 0.005797 0.005672 0.005541 0.004967 1969 0.007377 0.007364 0.007312 0.007108 0.006967 0.005377 1970 0.007292 0.007271 0.007075 0.00666 0.006513 0.00576 1971 0.007937 0.007916 0.007764 0.007629 0.007501 0.005865 1972 0.007385 0.007373 0.007276 0.007134 0.007039 0.005997 1973 0.006703 0.006689 0.006629 0.006504 0.00638 0.005561 1974 0.006657 0.006641 0.006498 0.006225 0.006073 0.004943 1975 0.005557 0.005552 0.005534 0.005445 0.005358 0.004665 1976 0.006397 0.006383 0.006239 0.006104 0.006018 0.004592 1977 0.007371 0.007353 0.007182 0.006927 0.006808 0.005357 1978 0.006273 0.00626 0.006226 0.00612 0.006018 0.004678 1979 0.006318 0.0063 0.00621 0.006095 0.005999 0.004239 1980 0.005597 0.005581 0.005464 0.005363 0.005274 0.004684 1981 0.006796 0.006779 0.00663 0.006422 0.006382 0.004819 1982 0.006072 0.006063 0.006013 0.005886 0.005769 0.004541 1983 0.00409 0.004087 0.004068 0.003947 0.003916 0.003427 1984 0.004065 0.004062 0.004041 0.003984 0.003915 0.003259 1985 0.004668 0.004657 0.004563 0.004314 0.004198 0.00336 1986 0.007614 0.007593 0.007399 0.007009 0.006769 0.004656 1987 0.007985 0.007961 0.007781 0.007482 0.007298 0.00557 1988 0.008007 0.007989 0.007844 0.007578 0.007436 0.005943 1989 0.007306 0.007281 0.00714 0.007012 0.006969 0.005995 1990 0.006411 0.006392 0.006314 0.006138 0.005992 0.004742

Sorted results Prob. Peak 96 hr 21 Day 60 Day 90 Day Yearly64 0.032258064516129 0.008007 0.007989 0.007844 0.007629 0.007501 0.005997 0.0645161290322581 0.007985 0.007961 0.007781 0.007578 0.007436 0.005995 0.0967741935483871 0.007937 0.007916 0.007764 0.007482 0.007298 0.005943 0.129032258064516 0.007614 0.007593 0.007399 0.007134 0.007039 0.005865 0.161290322580645 0.007385 0.007373 0.007312 0.007108 0.006969 0.00576 0.193548387096774 0.007377 0.007364 0.007276 0.007012 0.006967 0.00557 0.225806451612903 0.007371 0.007353 0.007182 0.007009 0.006808 0.005561 0.258064516129032 0.007306 0.007281 0.00714 0.006927 0.006769 0.005377 0.290322580645161 0.007292 0.007271 0.007075 0.006827 0.006689 0.005357 0.32258064516129 0.007102 0.007082 0.006953 0.00666 0.006513 0.004967 0.354838709677419 0.007009 0.00699 0.006871 0.006562 0.006382 0.004943 0.387096774193548 0.006796 0.006779 0.00663 0.006504 0.00638 0.004819 0.419354838709677 0.006703 0.006689 0.006629 0.006422 0.006372 0.004797 0.451612903225806 0.006657 0.006641 0.006498 0.006225 0.006073 0.004742 0.483870967741936 0.006411 0.006392 0.006314 0.006138 0.006018 0.004684 0.516129032258065 0.006397 0.006383 0.006239 0.00612 0.006018 0.004678 0.548387096774194 0.006318 0.0063 0.006226 0.006104 0.005999 0.004665 0.580645161290323 0.006273 0.00626 0.00621 0.006095 0.005992 0.004656 0.612903225806452 0.006097 0.006084 0.006028 0.0059 0.005797 0.004645 0.645161290322581 0.006072 0.006063 0.006013 0.005886 0.005769 0.004592 0.67741935483871 0.005901 0.005889 0.005797 0.005672 0.005541 0.004541 0.709677419354839 0.005597 0.005581 0.005534 0.005445 0.005358 0.004458 0.741935483870968 0.005557 0.005552 0.005464 0.005363 0.005274 0.004239 0.774193548387097 0.005306 0.005294 0.005181 0.005001 0.004943 0.004096 0.806451612903226 0.004668 0.004657 0.004563 0.004314 0.004198 0.003427 0.838709677419355 0.004323 0.004318 0.004267 0.004116 0.003916 0.003368 0.870967741935484 0.004243 0.004238 0.004207 0.00404 0.003915 0.00336 0.903225806451613 0.00423 0.004218 0.004149 0.003984 0.003871 0.003259 0.935483870967742 0.00409 0.004087 0.004068 0.003947 0.003786 0.00316 0.967741935483871 0.004065 0.004062 0.004041 0.00392 0.003724 0.001377

0.1 0.0079047 0.0078837 0.0077275 0.0074472 0.0072721 0.0059352 Average of yearly averages: 0.00462993333333333

Inputs generated by pe4.pl - 8-August-2003

Data used for this run: Output File: lcyhswpt Metfile: w13722.dvf PRZM scenario: NCSweetPotatoC.txt65 EXAMS environment file: pond298.exv Chemical Name: l-cyhalothrin Description Variable Name Value Units Comments Molecular weight mwt 449.86 g/mol Henry's Law Const. henry 2.4E-7 atm-m^3/mol Vapor Pressure vapr 1.5E-9 torr Solubility sol 0.05 mg/L Kd Kd mg/L Koc Koc 333200 mg/L Photolysis half-lifekdp 26 days Half-life Aerobic Aquatic Metabolism kbacw 44.8 days Halfife Anaerobic Aquatic Metabolism kbacs 159.0 days Halfife Aerobic Soil Metabolism asm 56.5 days Halfife Hydrolysis: pH 7 0 days Half-life Method: CAM 1 integer See PRZM manual Incorporation Depth:DEPI 0 cm Application Rate: TAPP 0.0336 kg/ha Application Efficiency: APPEFF 0.95 fraction Spray Drift DRFT 0.039 fraction of application rate applied to pond Application Date Date 01-08 dd/mm or dd/mmm or dd-mm or dd-mmm Interval 1 interval 7 days Set to 0 or delete line for single app. Interval 2 interval 7 days Set to 0 or delete line for single app. Interval 3 interval 7 days Set to 0 or delete line for single app. Record 17: FILTRA IPSCND 3 UPTKF 0 Record 18: PLVKRT 0 PLDKRT 0 FEXTRC 0.5 Flag for Index Res. Run IR Pond Flag for runoff calc. RUNOFF none none, monthly or total(average of entire run) Write Benthic Porewater File? benthic 1 Write Benthic Sediment File? benthicsed 1

stored as lcyhswptbensed.out Chemical: l-cyhalothrin PRZM environment: NCSweetPotatoC.txt modified Friday, 8 August 2003 at 07:25:48 EXAMS environment: pond298.exv modified Thuday, 29 August 2002 at 15:33:30 Metfile: w13722.dvf modified Wedday, 3 July 2002 at 08:05:50 Sediment segment concentrations (ppb)

Year Peak 96 hr 21 Day 60 Day 90 Day Yearly 1961 56.38 56.22 55.3 52.26 50.46 18.36 1962 56.56 56.49 56.08 53.85 49.65 42.12 1963 57.62 57.55 56.88 54.86 51.6 44.89 1964 94.67 94.41 92.68 91 89.17 59.42 1965 81.27 81.1 80.36 78.64 77.27 63.94 1966 70.73 70.56 69.06 66.66 65.88 54.6 1967 93.42 93.18 91.59 87.47 84.93 61.92 1968 78.66 78.5 77.28 75.61 73.86 66.21 1969 98.34 98.16 97.47 94.75 92.87 71.68 1970 97.19 96.92 94.31 88.77 86.82 76.78 1971 106 106 103 102 99.98 78.17 1972 98.44 98.28 96.98 95.09 93.83 79.94 1973 89.35 89.16 88.36 86.69 85.04 74.13 1974 88.73 88.53 86.62 82.97 80.95 65.89 1975 74.08 74.01 73.77 72.58 71.42 62.18 1976 85.27 85.09 83.16 81.36 80.22 61.21 1977 98.25 98.01 95.73 92.33 90.74 71.4 1978 83.61 83.44 82.99 81.58 80.22 62.36 1979 84.21 83.98 82.78 81.25 79.96 56.5 1980 74.61 74.39 72.83 71.49 70.3 62.44 1981 90.59 90.36 88.38 85.6 85.07 64.23 1982 80.94 80.82 80.16 78.45 76.9 60.53 1983 54.52 54.48 54.22 52.62 52.2 45.68 1984 54.19 54.15 53.87 53.1 52.19 43.44 1985 62.22 62.07 60.82 57.51 55.96 44.78 1986 101 101 98.63 93.43 90.23 62.06 1987 106 106 104 99.74 97.28 74.2566 1988 107 106 105 101 99.11 79.22 1989 97.39 97.06 95.17 93.46 92.9 79.91 1990 85.45 85.2 84.16 81.81 79.87 63.21

Sorted results Prob. Peak 96 hr 21 Day 60 Day 90 Day Yearly 0.032258064516129 107 106 105 102 99.98 79.94 0.0645161290322581 106 106 104 101 99.11 79.91 0.0967741935483871 106 106 103 99.74 97.28 79.22 0.129032258064516 101 101 98.63 95.09 93.83 78.17 0.161290322580645 98.44 98.28 97.47 94.75 92.9 76.78 0.193548387096774 98.34 98.16 96.98 93.46 92.87 74.25 0.225806451612903 98.25 98.01 95.73 93.43 90.74 74.13 0.258064516129032 97.39 97.06 95.17 92.33 90.23 71.68 0.290322580645161 97.19 96.92 94.31 91 89.17 71.4 0.32258064516129 94.67 94.41 92.68 88.77 86.82 66.21 0.354838709677419 93.42 93.18 91.59 87.47 85.07 65.89 0.387096774193548 90.59 90.36 88.38 86.69 85.04 64.23 0.419354838709677 89.35 89.16 88.36 85.6 84.93 63.94 0.451612903225806 88.73 88.53 86.62 82.97 80.95 63.21 0.483870967741936 85.45 85.2 84.16 81.81 80.22 62.44 0.516129032258065 85.27 85.09 83.16 81.58 80.22 62.36 0.548387096774194 84.21 83.98 82.99 81.36 79.96 62.18 0.580645161290323 83.61 83.44 82.78 81.25 79.87 62.06 0.612903225806452 81.27 81.1 80.36 78.64 77.27 61.92 0.645161290322581 80.94 80.82 80.16 78.45 76.9 61.21 0.67741935483871 78.66 78.5 77.28 75.61 73.86 60.53 0.709677419354839 74.61 74.39 73.77 72.58 71.42 59.42 0.741935483870968 74.08 74.01 72.83 71.49 70.3 56.5 0.774193548387097 70.73 70.56 69.06 66.66 65.88 54.6 0.806451612903226 62.22 62.07 60.82 57.51 55.96 45.68 0.838709677419355 57.62 57.55 56.88 54.86 52.2 44.89 0.870967741935484 56.56 56.49 56.08 53.85 52.19 44.78 0.903225806451613 56.38 56.22 55.3 53.1 51.6 43.44 0.935483870967742 54.52 54.48 54.22 52.62 50.46 42.12 0.967741935483871 54.19 54.15 53.87 52.26 49.65 18.36

0.1 105.5 105.5 102.563 99.275 96.935 79.115 Average of yearly averages: 61.715

Inputs generated by pe4.pl - 8-August-2003

Data used for this run: Output File: lcyhswpt Metfile: w13722.dvf PRZM scenario: NCSweetPotatoC.txt EXAMS environment file: pond298.exv Chemical Name: l-cyhalothrin Description Variable Name Value Units Comments Molecular weight mwt 449.86 g/mol Henry's Law Const. henry 2.4E-7 atm-m^3/mol Vapor Pressure vapr 1.5E-9 torr Solubility sol 0.05 mg/L Kd Kd mg/L Koc Koc 333200 mg/L Photolysis half-lifekdp 26 days Half-life Aerobic Aquatic Metabolism kbacw 44.8 days Halfife Anaerobic Aquatic Metabolism kbacs 159.0 days Halfife Aerobic Soil Metabolism asm 56.5 days Halfife Hydrolysis: pH 7 0 days Half-life Method: CAM 1 integer See PRZM manual Incorporation Depth:DEPI 0 cm Application Rate: TAPP 0.0336 kg/ha Application Efficiency: APPEFF 0.95 fraction Spray Drift DRFT 0.039 fraction of application rate applied to pond Application Date Date 01-08 dd/mm or dd/mmm or dd-mm or dd-mmm Interval 1 interval 7 days Set to 0 or delete line for single app. Interval 2 interval 7 days Set to 0 or delete line for single app. Interval 3 interval 7 days Set to 0 or delete line for single app. Record 17: FILTRA67 IPSCND 3 UPTKF 0 Record 18: PLVKRT 0 PLDKRT 0 FEXTRC 0.5 Flag for Index Res. Run IR Pond Flag for runoff calc. RUNOFF none none, monthly or total(average of entire run) Write Benthic Porewater File? benthic 1 Write Benthic Sediment File? benthicsed 168 

## Appendix B. Data Requirements

Table B-1. Environmenta l Fate Data Requirements for Lambda-cyhalothrin

Guideline Number Data Requirement MRID Study Classification 1 Are Additional Data Needed for Risk Assessment

161-1 Hydrolysis 00151604 S No

161-2 Photodegradation in Water 44861501 00151605 S No

161-3 Photodegradation on Soil 40052405 S No

161-4 Photodegradation in Air NA Waived No

162-1 Aerobic Soil Metabolism 00151607 00089995 44861505 A No

162-2 Anaerobic Soil Metabolism _ _ _

162-3 Anaerobic Aquatic Metabolism 44367401 S Yes

162-4 Aerobic Aquatic Metabolism 44367402 44861506 S

A Yes

163-1 Leaching-Adsorption/Desorption 44861503 44861509 A

S No

163-2 Laboratory Volatility NA Waived No

163-3 Field Volatility NA Waived No

164-1 Terrestrial Field Dissipation 40052407 A No

164-2 Aquatic Field Dissipation NA

_ CR*

164-3 Forestry Dissipation NA Waived No

165-4 Accumulation in Fish 00152746 S Yes

165-5 Accumulation – Aquatic Non-target Organisms NA - - - - CR*

166-1 Groundwater – Small Prospective NA Waived No

201-1 Droplet Size Spectrum - - - - - - - - 2

- - - -

202-1 Spray Drift Field Evaluation - - - - - - - - 2

- - - -

1 Core: study satisfies guideline; Supplemental: study is scientifically sound, but does not satisfy guideline; Invalid: study is not scientifically sound and does not satisfy guideline. 2The registrant is a member of the Spray Drift Task Force and is not required to do these guideline studies.

* Conditionally required, depending on the results of the bioaccumulation in fish study or metabolism studies.69 Table B-2. Ecological Effects Data Requirements for Lambda-cyhalothrin

Study Guideline Data Requirement MRID # Study Classification 1 Are Additional Data Needed for Risk Assessment?

Birds

71-1a Avian acute oral LD 50 Mallard Duck 151594 Acceptable No

71-2a Avian subacute dietary LC 50 Bobwhite quail 151596 Acceptable No

71-2b Avian subacute dietary LC 50 Mallard Duck 151595 Acceptable No

71-4a Avian Reproduction Bobwhite quail No Study N/A No

71-4b Avian Reproduction Mallard duck 41512101 Acceptable No

Fish and Invertebrates

72-1a Freshwater fish acute LC 50 /EC 50 Bluegill Sunfish 151598 Acceptable No

72-1b Freshwater fish acute LC 50 /EC 50 Bluegill Sunfish (Formulation) 151601 43908812 Acceptable Acceptable No

72-1c Freshwater fish acute LC 50 /EC 50 Rainbow trout 151597 Acceptable No

72-1d Freshwater fish acute LC 50 /EC 50 Rainbow trout (Formulation) 151600 43908813 Acceptable Acceptable No

72-2a Freshwater invertebrate, Daphnia EC 50 Gammarus pulex EC 50 151599 152730 Acceptable Supplemental No

72-2b Freshwater invertebrate, Daphnia EC 50 (Formulation) 151602 43908811 Supplemental Acceptable No

72-3a Estuarine/marine fish acute LC 50 sheepshead minnow 153506 Acceptable No

72-3b Estuarine/marine acute invertebrate EC 50 (eastern oyster) 152728 Acceptable No

72-3c Estuarine/marine acute invertebrate EC 50 (mysid shrimp) 152729 Acceptable No

72-5 Freshwater fish-life-cycle chronic Fathead minnow 41519001 Supplemental No

72-4b Freshwater invertebrate life cycle (Daphnia) 152733 41217501 Supplemental Supplemental No

72-4c Estuarine/marine fish early life-stage (Sheepshead minnow) 152732 Acceptable No

72-4b Estuarine/marine life cycle (Mysid) Acc. No. 073989 (MRID not available) Acceptable

No

72-7 Mesocosm Study 41253901 - No70 Table B-2. Ecological Effects Data Requirements for Lambda-cyhalothrin

Study Guideline Data Requirement MRID # Study Classification 1 Are Additional Data Needed for Risk Assessment?

74-1 Acute Sediment Testing (Freshwater and Estuarine/marine) No study - Yes

EPA/600/R-99/064 and EPA/600/R01/020 Chronic Sediment Testing (Freshwater and Estuarine/marine) No study - Yes

Mammals

81-1 Acute mammalian oral LD 50 (Rat) Active Ingredient Formulation 259805 259805 Minimum Guideline No

83-3a Chronic Mammalian Developmental -Rat No study - No

83-3b Chronic Mammalian Developmental -Rabbit No study - No

83-4 Rat 2-generation reproduction study No study - Yes

Plants

122-1a Terrestrial plants (Tier I) - Seedling Emergence No study - No

123-1b Terrestrial plants (Tier I) -Vegetative Vigor No study - No

123-2 Aquatic plants (Tier II) Freshwater green algae 152731 Supplemental No

123-2 Freshwater Blue-green algae No study - No

123-2 Freshwater Diatoms No study - No

123-2 Marine Diatoms No study - No

123-2 Vascular Plant Lemna gibba No study - No

Non-target Insects

141-1 Acute Honeybee Contact Technical Formulation

Acute Honeybee Oral Technical Formulation 40052409 40052409

40052409 40052409 Acceptable Acceptable

Acceptable Acceptable No

141-2 Honeybee Residue on Foliage 40436302 Acceptable No

1 Acceptable: study satisfies guideline; Supplemental: study is sc ientifically sound, but does not satisfy guideline; Invalid: st udy is not scientifically sound and does not satisfy guideline.71 

## Appendix C. Fate and Trans port Characterization

Table 2 summarizes the physical/chemical and envi ronmental fate/transport properties of lambdacyhalothrin.

Table 2. Summary of physical/chemical and environmental fate and transport properties of lambda-cyhalothrin.

PARAMETER VALUE(S) (units) SOURCE COMMENT

Chemical Name: lambdacyhalothrin CAS name: rel -( R )-cyano(3- phenoxyphenyl)methyl (1 S ,3 S )-3-[(1 Z)-2-chloro3,3,3-trifluoro-1-

propenyl]-2,2-dimethylcyclopropanecarboxylate – IUPAC name: ( R )- α -cyano-3- phenoxybenzyl (1 S ,3 S )-3- [( Z )-2-chloro-3,3,3- trifluoropropenyl]-2,2-dimethylcyclopropanecarboxylate and ( S )- α

cyano-3-phenoxybenzyl (1 R ,3 R )-3-[( Z)-2-chloro3,3,3-trifluoropropenyl]-

2,2-dimethylcyclopropanecarboxylate

Molecular Formula C 23 H 19 ClF 3 NO 3 EPI SuiteTM --

Molecular Weight 449.86 g/mole -- Unlabeled

Solubility of the parent (at pH 6.5, 20 o C) 0.005 ppm or 5 ppb MRID 00151580 –

Solubility of XV(at 25 o C) 0.009 ppm or 9 ppb -- Estimated from log Kow (SAR; WSKOW v1.40).

Solubility of lambdacyhalothrin in organic solvents Soluble IPCS( 1 )

--

Relative Density (water = 1) 1.33 g/cm 3 at 25°C -- --

Melting Point 49.2°C IPCS(1)

--

Decomposition >275°C IPCS(1)

--

Vapor Pressure (20 o C) 1.5x10 -9 mmHg IPCS(1) –

Henry’s Law constant 2.4x10 -7 Atm-cm 3 /mole Registrant data

-- pKa (20 o C) >9 Manufacturer Data obtained from the web.

1 INTERNATIONAL PROGRAMME ON CHEMICAL SAFETY (IPCS) Health and Safety Guide No. 38 CYHALOTHRIN AND LAMBDACYHALOTHRIN HEALTH AND SAFETY GUIDE72 Table 2. Summary of physical/chemical and environmental fate and transport properties of lambda-cyhalothrin.

PARAMETER VALUE(S) (units) SOURCE COMMENT

Octanol/Water Partition Coefficient (20°C) (log K O/W ) 7.0 IPCS(1) K O/W = 1.0x10 7

Hydrolysis Half-life [pH 5, 7, 9] pH 5 = stable pH 7 = stable pH 9, t 1⁄2 = 13 days MRID 00151604 --.

Aqueous Photolysis Half-life (pH 5) t 1⁄2 = 25 days (average) 26 days (maximum) MRID 44861501 --

Soil Photolysis Half-life Sandy Loam, fairly stable, only 13-16% degraded after

ca. 35 days. MRID 40052405 --

Aerobic Soil Metabolism Half-life t 1/2 = 24, 43, 46, 48, 53, 73 days**

12 days, Loam* 15 days, Silt Loam* MRID 00151607, 00089995,

45447410, 44861504 **Acceptable

*Supplemental data

Aerobic Soil Metabolism Half-life for metabolite XV 8.0, 8.8, 9.9 days 44861505 --

Anaerobic Aquatic Metabolism Half-life t 1/2 = 113, 142 days MRID 44367401, 00151607 --

Aerobic Aquatic Metabolism Half-life t 1/2 = 21 days flooded sand, 34 days flooded sandy loam, 46 days+ MRID 44861506, 44367402+ +Tested under gradient redox potential.73 Table 2. Summary of physical/chemical and environmental fate and transport properties of lambda-cyhalothrin.

PARAMETER VALUE(S) (units) SOURCE COMMENT

Organic Carbon Partition Coefficient (K OC , mL/g OC ) Sandy Loam 346,000 Loamy Sand 200,000 Silty Clay Loam 298,000

Loamy Sand 724,000 Silty Clay Loam 209,000

Sandy Loam 270,000 Sandy Loam 305,000 Loamy Sand 352,000 Sand 518,000 Sandy Loam 110,000;

------------------------------- Loamy Sand 28176, Sandy Loam 74212,

Silty Loam 53345, Sandy Loam 62242 # MRID 44861503,

45447413 Mean = 333,200

#Supplemental: Four values for cyhalothrin,

instead of lambdacyhalothrin.

Soil Partition Coefficient (K d , mL/g) Sandy Loam 3810 Loamy Sand 5880 Silty Clay Loam 5880

Loamy Sand 2100 Silty Clay Loam 4490

Sandy Loam 6890 Sandy Loam 7610 Loamy Sand 3470

Sand 2400 Sandy Loam 4870;

------------------------------- Loamy Sand 555, Sandy Loam 601, Silty Loam 630, Sandy Loam 355 # MRID 44861503*,

45447413* K d model describes the mobility better than K OC . Mean K d = 4740 mL/g.

#Four values for

cyhalothrin.

Aged Adsorption/Desorption In aged batch equilibrium study (up to 8 weeks of incubation), ≥ 97.6% of

the applied radioactivity remained adsorbed to the Sa ndy Loam after 24 hr of equilibration (>80% for one of the conditions).* MRID 44861509* *Supplemental

Organic Carbon Partition Coefficient (K OC ) for XV (mL/g OC ) 770,900 -- Estimated through the SAR modeling.74 Table 2. Summary of physical/chemical and environmental fate and transport properties of lambda-cyhalothrin.

PARAMETER VALUE(S) (units) SOURCE COMMENT

Organic Carbon Partition Coefficient for m-PBA (K d , mL/g) Could Not Determine Sand

3.11 Silt Loam 0.98 Sandy Loam 1 2.44 Sandy Loam 2 MRID: 43424901* *Supplemental

Terrestrial Field Dissipation

Half-life 12-64 days IL Clay Loam MS Silt Loam 2 radiolabels for PP321; EC MRID 40052407 --

Bioaccumulation in Fish 161X edible

448X whole

883X non-edible 10-15% depuration after 21 days MRID: 42868203, 00152746 --



### The environmental fate database for lambda-cyhalo thrin is substantially co mplete, but it containsvarious supplemental studies. It is sufficient for a Tier I Drinking Water Assessment. Lambdacyhalothrin is expected to have little mobility in soil surfaces and, ther efore, leaching into groundwater is not expected to be an importa nt environmental fate process (average K OC 

### = 333,200 n=10). Volatilization from moist or dry su rfaces is not expected to be an important transport process. Lambda-cyhalothrin has a re latively low vapor pres sure and Henry’s Law constant (1.5x10 -9 

### mm Hg and 2.4x10 -7 

### Atm-cm 3 

### /mole, respectively). With a pKa >9, lambda cyhalothrin is expected to be neutral in natura l environments, but will be affected in alkaline environments. Lambda-cyhalothrin is moderately persistent in the environment and degrades slowly through a combination of biotic and abiotic mechanisms. Lambda-cyhalohrin is stable in acidic and neutral water, but hydrol yzes in a matter of weeks under alkaline conditions (half-life 13 days at pH 9). Lambda-cyhalothrin is more st able to light than the first or second generation pyrethroids like allethrin and re smethrin, but still undergoes some photolysis in water, with halflives of about a month or more in distilled water (h alf-life 25 days). On soil, the half-life is fairly stable (with little degradation on th e order of ~13% in 35 days). It appears that the alpha cyano group stabilizes the molecule and it does not undergo photolysis readily. Under both aerobic and anaerobic soil metabolism conditions, lambda-cyhalo thrin biodegrades at moderate rates, with half-lives ranging from 12 to 72 days, but in aquatic metabolism conditions, it biodegrades more slowly, with half-lives on the order of about 113-142 days. Terrest rial field dissipation studies indicate that a combination of these mechanisms of dissipation take place. Half-lives of 12-64 days were observed in the field. Willis and McDowell ( ref. 2 ) indicate that for synthetic pyrethroids with similar structur e to that of lambda-cyhalothri n, dissipation from plant foliage occurs with half-lives on the or der of 5-6 days, but it may be highe r for the total residues. A low rate of volatilization was observe d from leaves (88% of applied remaining on the leaves after 24 hours( 2 

### ). The chemical does not translocate in the pl ant tissue. Lambda-cyhalothrin is expected to be immobile in soil environments. Due to its low mobility, it is highly unlikely to reach ground

2 European Commission Review Report for the Active Substa nce Lambda-Cyhalothrin, 7572/VI/97-final; Jan 25, 200175 

### waters. However, despite the protective impos ed buffer zone and buffer strip, it could reach adjacent surface waters via spray drift or runoff ev ents (via erosion). Once there, the chemical will partition with the sediment and will linger fo r long periods of time (months). The sediment serves as a repository of the chemical after num erous applications, in dynamic equilibrium with the pore water and the surface water. Lambda-cyh alothrin is moderately bioaccumulative (448X in the whole body), but it depurates slowly (onl y 10-15% depuration after 21 days). It appears that situations may occur, where this chemical ma y persist in fish tissue for extended periods of time.

The (±)cis- or trans-3- (2-trifluoromethyl,2-chloro-ethenyl) 2,2-dimethylcyclopropane carboxylic acid and 3-phenoxybenzaldehyde are the result of the hydrolysis of the ester linkage of the pyrethroid structure. However, in general, the majo r degradates appear to be (±)cis- or trans-3-(2- trifluoromethyl,2-chloro-ethen yl) 2,2-dimethylcyclopropane carboxylic acid and 3-phenoxybenzoic acid (3-PBA, or 3-PBacid, the hydrolysate of 3-phenoxybenzaldehyde). It appears that 3- phenoxybenzaldehyde oxidizes quickly to 3-PBA. The findings in the field corroborate the laboratory predictions.

Ring-hydroxylated lambda cyha lothrin, degradate XV, formed in aerobic soil microbial degradation (12% of the applied at 63 days post-treatment) was included in the drinking water assessment due to its potential toxicological co ncerns in humans. Th e degradate appears to degrade readily to carbon dioxide (t 1/2, avg. 

### = 8.9 days; n=3), and it appe ars to partition with the sediment. It has low mobili ty based on the estimated K OC 

### value of 770,900 mL/g OC 

### , from structure activity relationship (SAR) modeling. The potential for gr oundwater contamination with the degradate is low. However, it is likel y to reach surface water via runoff (via erosion) after a rainfall event.

Table 2 provides a summary of the data on th e transformation products of lambda-cyhalothrin.

Table 2. Summary of degradate formation from degradation of lambda-cyhalothrin.

DEGRADATE and MAXIMUM CONCENTRATION

STUDY TYPE SOURCE (1 RS )-cis-3( ZE )-2-chloro-3,3,3-trifluro1-propenyl)-2,2-dimethylcylopropanecarboxylate, Compound Ia (% applied) (1 RS )-trans-3-( ZE -2- chloro-3,3,3- trifluoroprop-1-enyl)- 2,2-dimethylcyclopropanecarboxylic acid, Compound Ib (% applied) (1 R ) cis α -( S ) cis

α -( R ) α -cyano-3-(4-hydroxyphenoxy) benzyl

3-(Z-2-chloro3,3,3- trifluoroprop-1- enyl)-2,2-dimethylcyclopropanecarboxylate, Degradate XV (% applied)76 

### Table 2. Summary of degradate formation from degradation of lambda-cyhalothrin.

DEGRADATE and MAXIMUM CONCENTRATION

STUDY TYPE SOURCE (1 RS )-cis-3( ZE )-2-chloro-3,3,3-trifluro1-propenyl)-2,2-dimethylcylopropanecarboxylate, Compound Ia (% applied) (1 RS )-trans-3-( ZE -2- chloro-3,3,3- trifluoroprop-1-enyl)- 2,2-dimethylcyclopropanecarboxylic acid, Compound Ib (% applied) (1 R ) cis α -( S ) cis

α -( R ) α -cyano-3-(4-hydroxyphenoxy) benzyl

3-(Z-2-chloro3,3,3- trifluoroprop-1- enyl)-2,2-dimethylcyclopropanecarboxylate, Degradate XV (% applied)

Aqueous Photolysis MRID: 44861501 13.7 @ 282 hr (cyclopropane ring) 7.1% @ 282 hr (cyclopropane ring) Others : 3-phenoxybenzoic acid 25.0% @ 247 hr;phenoxybenzaldehyde was a minor degradate (5.5% @ 247 hr)

Aerobic Aquatic

Metabolism MRID: 44861506*,

44367402 11.4% @ 30 days in a 98 day study, and 11.4% @ 14 days in the sediment of the SL sediment system. 14.4% @ 14 days, and 0.7 to 3.3% from 4 to 30 days in the sediment of the sand sediment system. 11.4% @ 30 days, and 10.6% @ 30 days in the sediment of the SL sediment system.

0.4-1.3% @ 0.125-7 days and 8.7@ 7 days in the sediment of the sand sediment system

Terrestrial Field

Dissipation MRID: 40052407 Transformation products monitored at the two sites were reported to be at low levels.

Data for hydrolysis, soil photolysis, aerobic soil metabolism, and anaerobic aquatic metabolism not available.



### References:

1. Willis, G.H. and L.L. McDowell. 1987. Pesticide persistence on foliage. Reviews of Environmental Contamination and Toxicol ogy, Vol. 100, page 23 (Springer-Verlag, New York, Inc) 2. Laskowski, 2002 Rev. Environ. Contam. Toxicol. 174:49-170

************************************************************************77 

## Appendix D. T-REX Model (Version 1.2.3, August, 2005)

I. Introduction

This spreadsheet-based model calcula tes the residues on avian and mammalian food items along with the dissipation rate of a chemical applied to foliar surf aces (for single or multiple applications) in order to estimate acute and reproductive risk quotients. LD 50 ft-2 values are calculated for both broadcast and banded (granular and liquid) applica tions using an adjusted LD50 method. The results are presented by weight class for various sized birds and mammals for each type of application. Avian and mammalian risk quotients are also calculated for seed treatment applications to various crop seeds.

T-REX uses the same principle as the batch code models FATE and TERREEC that calculate terrestrial exposure concentration estimates on plant surfaces fo llowing pesticide application. However, T-REX performs a number of calculations that neither FATE nor TERREEC perform. For example, T-REX adjusts acute and chronic toxicity values based on the relative body weight of the animal being assessed compared with the animal used in the toxicity studies. T-REX also calculates risk quotients for granular applications and seed treatments.

II. Inputs

Inputs needed to run T-REX include the following (input s denoted with an * are required; inputs denoted with a *C are required when multiple applications are being modeled:

A. Pesticide Application Data

Chemical name: Enter either the chemical or common name used in the assessment.

Use: Enter the type of use (e.g., turf, residential, crop, foliar, right-of-way, etc.) If applicable, also provide crop name.

Product name and form: Enter the name of the formulated product as it appears on the subject label, including any indication of the form of the product (e.g. 10g - 10% granular, wp - wettable powder, etc.)

% A.I.*: Enter the % A.I. for the formulation (from the label). If an application rate for a formulated product is used, ente r the % A.I. for the formulation. However, if the application rate to be entered has already been adjusted for % A.I., use 100 % in this cell.

Application Rate*: Enter the maximum label application rate (pounds ai/acre). If your application rate has already been adju sted for active ingredient, make sure you have entered 100 in the % A.I. cell above; otherwise, enter your application rate in lbs formulation/A here and then the % A.I. in the product in the above cell.

Foliar Dissipation Half-life* : Enter the foliar dissipation half-life in days. EFED policy requires the risk assessor to consult available magnitude of residue (171-4), the reduction of residue (171-5) and the foliar dissipation (132-1) studies submitted by the registrant to HED for determining pesticide residue half-life for wildlife food items used for terrestrial wildlife exposure modeling.78 

### Another source for dissipation data for wildlife exposure modeling purposes is Willis and McDowell (1987; available at F:\USER\SHARE\Models\Terrestrial Exposure\TREX). In the event that the above data sources do not provide a suitable half-life estimate, the EFED default value is 35 days. When using the defaults, the risk assessor is urged to evaluate the effect of alternative assumptions of residue half life assumption on the outcome of the terrestrial wildlife risk assessment and include this evaluation in the discussion of risk assessment uncertainties.

Application Interval*c: Enter the minimum interval (days) between multiple applications (if any). Note: This version of the model can only accommodate uniform application intervals; subsequent m odels may incorporate a provision of intervals of varying length. The ri sk assessor may evaluate the effect of using application intervals other than the minimum interval on the label to explore possible mitigation effort effects on risk outcomes.

Number of Applications*c: Enter the number of applications. EFED policy states that screening risk assessments should consider the maximum number of applications specified on the product label. However, the risk assessor may elect other numbers of applications to explore po ssible mitigation effort effects on risk

outcomes.

B. Avian and Mammalian Endpoints

To calculate risk quotients, user-supplied avian and mamma lian toxicity endpoints n eed to be entered into the 'Endpoints' section of the Inputs worksheet. These endpoints can be found in avian acute oral LD50, avian acute dietary LC50, avian reproduction NOAEC/L, acute mammalian LD50 or LC50, and mammalian reproduction NOAEC/L toxicity studies.

T-REX requires that both the chosen endpoint (entered in the blue cell) and the test species be included (chosen from the drop-down menu options). For example, one would enter an avian LD50 of 500 mg/kgbw and that this endpoint was based on a Bobwhite quail study (i .e., chosen from the drop-down menu immediately to the right of the LD50 input cell). Ty pically, endpoint data for bobwhite quail, mallard duck, and laboratory rats from submitted studies or open literature will be used. In the case where data on bird species other than bobwhite quail or mallard duck are assessed (e.g. Japanese quail), choose "other" from the species drop down menu and enter the body weight of the species. A similar option for mammals is not currently available in this version of T-REX. Calculations for animals other than rats need to be done by hand using equations included in this user's guide until the re lease of the next version of T-REX. See the program author for assistance if needed.

1. Avian Endpoints

The following avian toxicity endpoints may be entered into T-REX : LD50 Enter LD50 for dose-based acute effects endpoint (mg/kg-bw).

LC50 Enter LC50 for dietary-based acute effects endpoint (mg/kg-diet).79 

### Reported Chronic Endpoint Enter NOAEL if reported in mg/kg-bw or NOAEC if reported in mg/kgdiet.

Mineau Scaling Factor If chemical-specific data are available the user can specify the avian scaling factor (see Mineau, et al.,1996) Otherwise, enter the EFED default value of (1.15). T-REX will not run unless a Mineau scaling factor is entered. However, zero can be ente red if the assessor believes that body weight does not influence toxicity of the chemical being assessed.

EFED policy states that for screening risk assessmen ts, the lowest LD50, LC50, NOAEC and/or NOAEL from acceptable or supplemental studies be used. For non-screening risk assessments, the risk assessor may elect other values as necessary, but must documen t in the risk assessment why the lowest tested endpoint was not used. However, the assessor should determine that the lowest toxicity value from a laboratory study results in the lowest adjusted toxicity values for the various weight classes being assessed. This is important when the toxicity values from diffe rent species are similar to each other because T-REX adjusts the toxicity values based on body weight and f ood intake of the tested organism compared with the assessed organism. Therefore, when data are availa ble from multiple species, adjusted LD50s should be calculated for all species and the lowest value should be used.

The risk assessor should note that this version of th e model assumes a set body weight for tested bobwhite quail (178 g) and mallard duck (1580 g) unless another bod y weight is entered to th e right of this cell or "other" is selected for a test species. Use of "other" species or studies involving subject animals markedly different from the assumed body weights requires the risk assessor to provide the alternate body weight and the species name. These data should be obtaine d from the study report if possible (time weighted average). Alternatively, reference body weight values may be obtained from a variety of sources including U.S. EPA (1993) and the testing laboratory.

2. Mammalian Endpoints

The following mammalian endpoints may be entered into T-REX:

LD50 Enter LD50 (mg/kg-bw) for dose-based acute effects endpoint.

LC50 Enter LC50 (mg/kg-diet) for dietary-based acute effects endpoint.

Reported Chronic Endpoint Enter NOAEL if reported in mg/kg-bw or NOAEC if reported in mg/kgdiet.

Enter EITHER the NOAEL or the NOAEC. To the right of the cell is a drop down menu for the units in which the endpoint is expressed. The model will automatically make default adjustments for units to express the endpoint BOTH as NOAEC and NOAEL by assuming that a laboratory rat consumes 5% of its body weight daily (i.e., divide the concentration in food (ppm) by 20 to calculate the dose in mg/kg-bw). However, if a reproduction study reports toxicity valu es in units of dose (mg/kg-bw) and dietary concentration (mg/kg-diet), then both of these values should be used over the estimated values calculated by T-REX. Because the current version of T-REX only allows for input of either a dose or dietary concentration (not both), T-REX needs to be run twice when a study80 

### reports toxicity values in terms of concentration (mg/kg-diet) and dose (mg/kg-bw).

If a rat reproduction study is unavailable, the risk assessor may use the rat teratogenicity study NOAEL or NOAEC, but must identify this alternative endpoint use and must discuss in the risk description the limitations. Studies other than reproduction or developmental toxicity studies are not currently used by EFED to calculate risk quotients.

The lowest LD 50 

### , LC 50 

### , NOAEC and/or NOAEL from acceptable or supplemental studies are used in screening-level risk assessment of mammals. For non-screening level assessment s, the risk assessor may select other values as necessary, but must document in the risk assessment why the lowest tested endpoint was not used.

The risk assessor should note that this version of th e model assumes a set body weight of 350 g for the tested organism, assuming they are laboratory rats. Use of other species or studies involving subject animals markedly different from the assumed body we ight of 350 g will result in inaccuracies when extrapolating test endpoints to modeled animals. Theref ore, if a mammalian species other than rats is used (e.g. dog, rabbit, mink), use the time-weighted average bod y weight of the animals that were tested in the experiment (from the DER or the or iginal study report). Alternatively, reference body weight values may be obtained from a variety of sources including U.S. EPA (1993) and the testing laboratory. However, TREX does not currently allow the use to enter body weights of mammals that differ from the 350-gram laboratory rat. Therefore, adjusted toxicity values would need to be performed by hand.

C. Additional Inputs for LD50 ft-2 analysis

Because lambda-cyhalothrin is not intended for u se as a granular, no additional inputs for the LD50 ft -2 

### analysis are needed.

D. Additional Inputs for Seed Treatment Analysis

Because lambda-cyhalothrin is not intended for use as a seed treatment, no additional inputs are needed.

III. Risk Estimation Based on Dietar y Residue Concentrations (Foliar Spray)

The methods used by T-REX to estimate risk from co nsumption of selected contaminated food items is described below. For this analysis, T-REX calcu lates EECs and risk quotients based on both the upper bound and mean residue concentrations as presented by Hoerger and Kenaga (1972) and modified by Fletcher et al. (1994). These concentrations are dete rmined using nomograms that relate application rate of a pesticide to residues remaining on dietary items of terrestrial organisms. The results of the upper bound and mean residue levels are presented in separate tabs (“upper bound Kenaga” and “mean Kenaga”); however, the methods used to calcula te EECs and risk quotients are equivalent. Only RQs from the upper bound Kenaga worksheet are to be used for comparison to levels of concern in the

assessment. The mean residues, and the RQs generated from them, presented in the mean Kenaga worksheet are to be used only for risk descripti on. Replacing the upper bound residues with the mean residues is not a valid mitigation approach when up per bound residues result in LOC exceedances. Based on the estimated dietary residue concentrations fro m the upper bound and mean Kenaga values, T-REX calculates the associated doses for various size cla sses of birds and mammals. Both the dietary concentration (mg/kg-dietary item) and the resulting estimated doses (mg/kg-bw) may be used for risk estimation. The resulting dietary based and concentr ation based risk quotients are discussed below.81 

### This section describes how T-REX estimates the followi ng: (1) residue concentrations on selected food items (mg/kg-dietary item); (2) dose-based EECs (mg/ kg-bw) from dietary concentrations on selected food items; (3) adjusted toxicity values; and (4) risk quotients.

A. Calculation of Dietary Concentrations on Selected Food Items

The spreadsheet calculates the pesticide residue concentrations on each selected food item on a daily interval for one year. When multiple applications are modeled, residue concentrations resulting from the final application and remaining residue from pr evious applications are summed. The maximum concentration calculated out of the 365 days is return ed as the EEC used to estimate potential risk to birds and mammals as described below. Dissipation of a chemical applied to foliar surfaces for single or multiple applications is calculated assuming a first or der decay rate from the following first order rate equation:

CT = C i 

### e -kT



### or in log form:

ln (CT/C i 

### ) = kT

Where

CT = concentration at time T = day zero. C i 

### = concentration, in parts per million (PPM), present initially (on day zero) on the surfaces. C i 

### is calculated by multiplying the application rate, in pounds active ingredient per acre, by 240 for short grass, 110 for tall grass, and 135 for broad-leafed plants/small insects and 15 for fruits/pods/large insects based on the Kena ga nomogram (Hoerger and Kenaga, 1972) as modified by Fletcher (1994). For maximum concentrations, additi onal applications are converted from pounds active ingredient per acre to PPM on the plant surface and the additional mass added to the mass of the chemical still present on the surfaces on the day of application. k = If the foliar dissipati on data submitted to EFED are found scientifically valid and statistically robust for a specific pesticide, th e 90% upper confidence limit of the mean halflives should be used. When scientifically valid, statistically robust data are not available, EFED recommends using a default half-life value of 35 days. The use of the 35-day halflife is based on the highest reported value ( 36.9 days), as reported by Willis and McDowell (Pesticide persistence on foliage, Environ. Contam. Toxicol, 100:23-73, 1987). T = time, in days, since the start of the simu lation. The initial application is on day 0. The simulation is designed to run for 365 days.

The dietary concentrations estimated using the above methodology may be used directly to calculate risk quotients, but may also be used to calculate dose-based EECs (mg/kg-bw) for various size classes of mammals and birds as below.

B. Calculating EEC Equivalent Doses based on Estimated Dietary Concentrations on Selected Bird and Mammal Food Items

EECs (mg/kg-bw) for various size classes of mammals and birds may be calculated based on the dietary residue concentrations deri ved using the equations presented above. To allow for this type of analysis, the

### EECs and toxicity values are adjusted based on food intake and body wei ght differences so that they are comparable for a given weight class of animal. The size classes assessed are small (20-gram), medium (100-gram), and large (1000-gram) birds, and small (15-gram), medium (35-gram), and large (1000-gram)mammals. Equations used to calculate food intake (grams/day) and to adjust toxicity values for dosebased risk quotients are presented below.

Calculating Food Intake for Differen t Size Classes of Birds and Mammals:

Daily food intake (g/day) is assumed to correlate with body weight using the following empirically derived equation (U.S. EPA, 1993):

Avian consumption



### F BW

W =

− 0 648

1 0 651 

### . * ( ) .



### where:

F = food intake in grams of fresh weight per day (g/day)

BW = body mass of animal (g)

W = mass fraction of water in the food (EFED value = 0.8 for birds and herbivorous mammals, 0.1 for granivorous mammals)

Based on this equation, a 20-gram bird would c onsume 22.8 grams of food daily (114% of its body weight), a 100-gram bird would consume 65 grams of f ood daily (65% of its body weight daily), and 1000- gram bird would consume 290 grams of food daily (29% of its body weight). These data, together with the residue concentrations (mg/kg-food item) on select ed food items calculated from the Kenaga nomogram, are used to estimate the dose (mg/kg-bw) of residue consumed by the three size classes of birds as discussed below. Using a small (20-gram) bird as an example, a dietary concentration of 100 mg/kg-diet (ppm) x 1.14 kg diet/kg bw (114%) would result in an equivalent dose-based EEC of 114 mg/kg-bw. TREX calculates food intake based on dry weight and we t weight of food items. The dose-based assessment uses the wet weight food consumption values by assuming that dietary items are 80% water by weight. However, if dietary items of a species being assessed are known, then a refined dose-based EEC can be calculated using appropriate water fractions of the food items.

A similar relationship between body weight and food intake has been derived for mammals (U.S. EPA 1993):

Mammalian food consumption (g/day)

82 

### where: F BW

W =

−

0 621

1 0 564 

### . * ( ) .



### F = food intake in grams of fresh weight per day (g/day)

### BW = body mass of animal (g)

W = mass fraction of water in the food (EFED value = 0.8 for birds and herbivorous mammals, 0.1 for granivorous mammals)

The scaling factors result in a percent body weight consumed presented in the following table for each weight class of mammal. These values are used in th e same manner described for birds to calculate dosebased EECs (mg/kg-bw). Note the difference in food intake of grainivores compared with herbivores and insectivores. This is caused by the difference in the assumed mass fraction of water in their diets.

Table D1. Scaling factors and percent body weig ht consumed for 3 weight classes of mammals.

Organism and Body Weight Food Intake (g day -1 ) a Percent Body Weight Consumed (day -1) a

15 g 14.3 / 3.2 95 / 21

35 g 23 / 5.1 66 / 15

1000 g 150 / 34 15 / 3

a The first number in this column is specific to herbivores/insectivores. The second number is for granivores. These groups ha ve markedly different consumption requirements.



### T-REX calculates food intake based on dry weight and we t weight of food items (wet weight is used for RQ calculations). The dose-based assessment uses the wet weight food consumption values by assuming that dietary items are 80% water by weight (10% for granivores). However, if dietary items of a species being assessed are known, then a refined dose-based EEC can be calculated using appropriate water fractions of the food items.

C. Calculating Adjusted Toxicity Values

The dose-based EECs (mg/kg-bw) derived above are compared with LD50 or NOAEL (mg/kg-bw) values from acceptable or supplemental toxicity studies that are adjusted for the size of the animal tested compared with the size of the animal being assessed (e.g., 20-gram bird). These exposure values are presented as mass of pesticide consumed per kg body weight of the animal being assessed (mg/kg-bw). EECs and toxicity values are relative to the an imal's body weight (mg residue/kg bw) because consumption of the same mass of pesticide residue results in a higher body burden in smaller animals compared with larger animals. For birds, only acu te values (LD50s) are adjust ed because dose-based risk quotients are not calculated for the chronic risk estim ation. Adjusted mammalian LD50s and reproduction NOAELs (mg/kg-bw) are used to calculate dose-based acute and chronic risk quotients for 15-, 35-, and 1000-gram mammals. The following equations ar e used for the adjustment (U.S. EPA 1993):

Adjusted avian LD50:



### Adj LD LD AW

TW x



### . ( )

50 50 1



### = ⎛ ⎝ ⎜ ⎞ ⎠

⎟ −



### where:

83

### Adj. LD50 = adjusted LD50 (mg/kg-bw) calculated by the equation LD50 = endpoint reported from bird study (mg/kg-bw) TW = body weight of tested anim al (178g bobwhite; 1580g mallard; 350g rat) AW = body weight of assessed anim al (avian: 20g, 100g, and 1000g) x = Mineau scaling factor for birds; EFED default 1.15

84 

### Adjusted mammalian NOAELs and LD50s (note that th e same equation is used to adjust the NOAEL):

where:

Adj. NOAEL or LD50 = adjusted NOAEL or LD50 (mg/kg-bw) NOAEL or LD50 = endpoint reported from bird study (mg/kg-bw) TW = body weight of tested animal (350g rat) AW = body weight of assessed animal (15g, 35g, 1000g)

D. Calculating Risk Quotients

Two types of risk quotients are calculated by T-REX b ased on the estimated dietary residue concentrations determined from the Kenaga nomogram: (1) dietary based RQs; and (2) dose based RQs. These RQs are not equivalent. Dietary risk quotients are calculated by directly comparing the concentration of a pesticide administered (or estimated to be administered) to experimental animals in the diet in a toxicity study to the concentration estimated to be on selected food items. These risk quotients do not account for the fact that smaller-sized animals need to consum e more food relative to their body weight than larger animals or that differential amounts of food are consumed depending on th e water content and nutritive value of the food. The dose-based risk quotients do account for these factor s. The dose-based RQs incorporate the ingestion rate-adjusted exposure from the various food items to the different weight classes of birds and the weight class-scaled toxicity endpoints. Formulas presented in Table D2 are used to calculate dose-based and dietary based risk quotients:

Table D2. Formulas used to calculate dose- and dietary-based risk quotients.

Duration Dose or Dietary RQ Surrogate Organism Equation

Dose-based Birds and mammals Acute Daily Exposure (mg/kg-bw) / adjusted LD50 (mg/kgbw) Acute

Dietary-based Birds Kenaga EEC (m g/kg-food item) / LC50 (mg/kg-diet)

Dietary-based Birds and mammals EEC (mg/kg-food item) / NOAEC (mg/kg-diet) Chronic

Dose-based Mammals EEC (mg/kg- bw) / Adjusted NOAEL (mg/kg-bw)



### These risk quotients are compared to the Agency's LOCs to determine if risk is greater than EFED's concern level. 

### Adj NOAEL or LD NOAEL or LD TW

AW . ( .

50 50 0 25



### = ⎛ ⎝ ⎜ ⎞ ⎠

⎟ )85 

### IV. Risk Estimation Based on the LD50 ft-2 Analysis

T-REX includes the capability to calculate the LD50 ft-2 risk index values with the user supplied information. Conceptually, an LD50 ft-2 is the am ount of a pesticide estimated to kill 50% of exposed animals in each square foot of applied area. Although a square foot does not have defined ecological relevance, and any unit area could be used, risk presumably increases as the number of LD50s/ft2 increases. The LD50/ft2 is used to estimate risk for granular formulations and row, banded, and in-furrow applications. For additional inform ation on the LD50 ft-2 risk index, please reference U.S. EPA (1992). The LD50 ft-2 is calculated using a toxicity value (adjusted LD50) and the EEC (mg a.i. ft-2) and is directly compared with the Agency's levels of concer n (LOCs). Additional toxicity data are not needed for this calculation.

Results of the LD50 ft-2 analysis are presented in the "LD50 ft-2" tab. Simply click on the LD50 ft-2 tab to display this page. There are three main sections in this worksheet: the input summary, row/band/infurrow application summary, and broadcast applica tion summary. The input summary reiterates the parameters supplied by the user on the "input" work sheet. The other two sections calculate LD50 ft-2 values for row/band/in-furrow applica tions and broadcast applications, r espectively. The calculations are based on a toxicity (adjusted LD50) and exposure (mg a.i./ft2) value. Adjusted LD50s were discussed in Section III.C. Equations used to calculate EECs are presented below for broadcast and banded granular and liquid applications. Percent in corporation in these equations for va rious application types entered by the assessor into T-REX is presented in Table D3.

Banded granular applications: mg ai ft-2 = (application rate H % a.i. H 453,590 mg/lb)/(no. of rows A-1 H row length H bandwidth)

exposed mg ai ft-2 = mg ai ft-2 H % unincorporation

Banded liquid applications: mg ai ft-2 = (mg ai 1000 ft-1 row)/(1000 ft H bandwidth)

exposed mg ai ft-2 = mg ai ft-2 H % unincorporation

Broadcast granular applications: mg ai ft-2 = (application rate H % AI H 453,590 mg/lb)/43,560 ft2 acre-1

Broadcast liquid applications: mg ai ft-2 = (fl oz product A-1 H 28349 mg/oz H % AI)/43,560 ft2 acre-1

Table D3. Percent unincorporated assumed for several types of applications.

% incorporated T-Banded - covered with specified amount of soil: 1% In-furrow, drill, or shanked-in: 1% Side-dress, banded, mix, or lightly incorporate with soil: 15% Broadcast, mix, or lightly incorporated: 15% Side-dress, banded, unincorporated: 100% Broadcast, aerial broadcast, unincorporated: 100%



### Based on these EECs, the LD50 ft-2 is calcu lated using the following equation:

LD50 ft-2 = EEC (mg a.i./ft-2) / (Adj LD50 H bw (kg) of assessed animal)86 

### V. Actual Input Parameters and Terrestrial Estimated Environmental Concentrations (EECs)

The actual application information used to determ ine terrestrial EECs on food items for lambdacyhalothrin are listed below in Table D4 . In addition, a summary of the predicted residues of lambdacyhalothrin that may be expected to occur on sel ected avian or mammalian food items immediately following application are presented in Table D4

.

For the purposes of this risk assessment, the T-REX model was run for agricultural uses with the maximum proposed application rates, the maximum number of applications, and the minimum interval between applications for each usage scenario, to assess risk to terrestrial organisms. The T-REX default half-life of 35-days and a Mineau scaling factor of 1.15 were used for modeling purposes because chemical-specific data were unavailable.Three of th e 5 proposed new uses were modeled in T-REX to estimate terrestrial EECs. The use on cereal grains was chosen for modeling because it had the shortest application interval, the use on cucurbit vegetables was chosen for modeling because it had the highest number of applications and seasonal rate, and the u se on rice was chosen for modeling because it had the highest single application rate.

Table D4. Upper-Bound Terrestria l EECs (ppm) Estimated for Lambda -cyhalothrin in Various Food Items a

Concentrations in Wildlife Food items (ppm) Crops or Crop Groups and Application Information b Short Grass Tall Grass Broadleaves/ Forage/ Small insects Seeds/ Large Insects

Cucurbits (aerial, 0.03 lb/acre, 6x, 5 days) 34 16 19 2

Rice (aerial, 0.04 lb/acre, 3x, 5 days) 26 12 15 2

Cereal (aerial, 0.03 lb/acre, 2x, 3 days) 14 6 8 1

a EEC equivalent dose = Upper- bound Kenega value * (%BW consumed/100). %BW consumed = 114%, 65%, and 29% for small, medium, and large birds, respectively.

b All application information was derived from the proposed product label. The T- REX default half-life of 35-days was used for modeling purposes because appropriate fo liar dissipation data were unavailable.



### VI. References

Dunning, J.B. 1984. Body weights of 686 species of North American birds. Western Bird Banding Assoc. Monograph No. 1.

Fletcher, J.S., J.E. Nellesson and T. G. Pfleeger. 1994. Literature review and evaluation of the EPA foodchain (Kenaga) nomogram, an instrument for estimati ng pesticide residues on plants. Environ. Tox. And Chem. 13(9):1383-1391.

Hoerger, F. and E.E. Kenaga. 1972. Pesticide r esidues on plants: correlation of representative data as a basis for estimation of their magnitude in the envi ronment. IN: F. Coulston and F. Corte, eds., Environmental Quality and Safety: Chemistry, Toxi cology and Technology. Vol 1. George Theime Publishers, Stuttgart, Germany. pp. 9-28.87 

### Mineau, P., B.T. Collins, A. Baril. 1996. On the use of scaling factors to improve interspecies extrapolation to acute toxicity in birds. Reg. Toxicol. Pharmacol. 24:24-29.

Urban, D. J. 2000. Guidance for Conducting Sc reening Level Avian Risk Assessments for Spray Applications of Pesticides. OPP/EFED, USEPA. July 7, 2000.

U.S. EPA. 1992. Comparative analysis of acute avia n risk from granular pesticides. Office of Pesticide Programs. U.S. EPA. March 1992.

USEPA. 1993. Wildlife Exposure Factors Handbook. Vo lume I of II. EPA/600/R-93/187a. Office of Research and Development, Washington, D. C. 20460.

USEPA. 1995. Great Lakes Water Quality Technical Support Document for Wildlife Criteria. Office of Water, Washington D.C. Document Number EPA-820-B095-009.

Willis and McDowell. 1987. Pesticide persistence on fo liage. Environ. Contam. Toxicol. 100:23-73.

## Appendix E. The Risk Quot ient Method and Levels of Concern

The risks to terrestrial and aquatic organisms are determined based on a method by which risk quotients (RQs) are compared with levels of concern (LOCs). This method provides an indication of a chemical’s potential to cause an effect in the field from effect s observed in laboratory studies, when the chemical is used as directed. Risk quotients are expressed as th e ratio of the estimated environmental concentration (EEC) to the species-specific toxi city reference value (TRV): 

# RQ EEC

TRV =

Units for EEC and TRV should be the same (e.g., μ g/L or ppb). The RQ is compared to the LOC as part of a risk characterization. Acute and chronic LOCs for terrestrial and aquatic organisms are given in recent Agency guidance (EPA, 2004) and summarized in Table E-1 below.

Table E1. Level of concern (LOC) by risk presumption category (EPA, 2004).

Risk Presumption RQ LOC

Mammals and Birds

Acute Risk a EEC b /LC 50 or LD 50 /sqft c or LD 50 /day d 0.5

Acute Restricted Use e EEC/LC 50 or LD 50 /sqft or LD 50 /day (or LD 50 <50 mg/kg) 0.2

Acute Endangered Species f EEC/LC 50 or LD 50 /sqft or LD 50 /day 0.1

Chronic Risk EEC/NOAEC 1

Aquatic Animals

Acute Risk EEC g /LC 50 or EC 50 0.5

Acute Restricted Use EEC/LC 50 or EC 50 0.1

Acute Endangered Species EEC/LC 50 or EC 50 0.05

Chronic Risk EEC/NOAEC 1

Terrestrial and Semi-aquatic Plants

Acute Risk EEC/EC 25 1

Acute Endangered Species EEC/EC 05 or NOAEC 1

8889 Table E1. Level of concern (LOC) by risk presumption category (EPA, 2004).

Risk Presumption RQ LOC

Aquatic Plants

Acute Risk EEC h /EC 50 1

Acute Endangered Species EEC g /EC 05 or NOAEC 1

potential for acute toxicity for receptor species if RQ > LOC (EPA, 2004).

b Estimated environmental concentrati on (ppm) on avian/mammalian food items

c mg/ft 2

d mg of toxicant consumed per day

e Potential for acute toxicity for receptor species, even considering restricted use classification, if RQ > LOC (EPA, 2004).

f Potential for acute toxicity for endangered species of receptor species if RQ > LOC (EPA, 2004).

g EEC = ppb or ppm in water

h EEC = lbs a.i./A



### For the Tier II aquatic assessment of lambda-cyhalothrin, acute exposure is represented by the peak EEC value and chronic exposure is represented by the 21-da y and 60-day EEC value for invertebrates and fish, respectively, calculated using PRZM/EXAMS.

EECs used to assess acute and chronic risk to avian and mammalian species to lambda-cyhalothrin were calculated using the model T-REX. Currently the Agency does not perform assessments for chronic risk to plants or acute/chronic risks to non-target terrestrial invertebrates.

The Agency has developed an Enda ngered Species Protection Program to identify pesticides whose use may cause adverse impacts on endangered and threaten ed species, and to implement mitigation measures that will eliminate the adverse impacts. At present, the program is being implemented on an interim basis as described in a Federal Register notice (54 FR 27984-28008, July 3, 1989), and is providing information to pesticide users to help them protect these species on a voluntary basis. As currently planned, the final program will call for label modifications referring to required limitations on pesticide uses, typically as depicted in county-specific bulletins or by other site-sp ecific mechanisms as specified by state partners. A final program, which may be altered from the inte rim program, will be described in a future Federal Register notice. The Agency is not imposing label modifications at this time. Rather, any requirements for product use modifications will occur in the fu ture under the Endangered Species Protection Program.

Limitations in the use of lambda-cyhalothrin may be required to protect endangered and threatened species, but these limitations have not been defined and may be formulation specific. The Agency will notify the registrants if any label modifications ar e necessary. Such modifications would most likely consist of the generic label statement referring pes ticide users to use limitations contained in county Bulletins.

Literature Cited

U.S. EPA. 1989. U.S. Environmental Protection Agency. Endangered Species Program. Washington, DC. Federal Register: 27984-28008, July 3.

U.S. EPA. 2004. U.S. Environmental Protection Agen cy. Overview of the Ecological Risk Assessment Process in the Office of Pesticide Programs, U.S. Environmental Protection Agency: Endangered and Threatened Species Effects Determinations. Office of Prevention, Pesticide, and Toxic Substances. January 23.90 

## Appendix F. Ecological Effects Data

These data are presented here as they were in th e Environmental Fate and Effects Division’s Ecological Risk Assessment (June 12, 2002) for the Section 3 request for new uses of lambdacyhalothrin on peas and beans, fruiting vegeta bles, canola, sugarcane, sorghum, wheat, wheat hay and other small grains, peanut hay, pome fruit, stone fruit, tree nuts, termite barrier, tobacco, noncropland and trees (conifer and deciduous t rees) (DP Barcode D262918, D262919, D279087, D279088).

Aquatic Toxicity Studies

Fish Toxicity

Acute toxicity studies performed in bluegill and rainbow trout using either technical lambda cyhalothrin or the formulation products indicate that the chemical is very highly toxic to freshwater fish. The results from acute toxicity study using sheepshead minnow also indicate lambda cyhalothrin is very highly toxic to fish of estuarine/marine origin. The results of acute toxicity studies conducted in freshwater and estuarine/marine fish are summarized in Table F-1

.

Table F-1. Acute Toxic Effects of Lambda cyha lothrin in on Freshwater and Estuarine Fish

Species Study Guideline % A.I. Toxicity Endpoint (95 % Confidence Interval) μ g a.i. /L Toxicity Classification Study Classification MRID #

Freshwater Fish

Bluegill Sunfish (Lepomis macrochirus) 72-1a 98 LC 50 96 hr : 0.210 (0.16- 0.31) NOAEC : 0.16 (mortality) very highly toxic Core 151598

Bluegill Sunfish (Lepomis macrochirus) 72-1b 12.9 LC 50 96 hr : 2.2 (1.9-2.7) NOAEC : 0.77 very highly toxic Core 151601

Bluegill Sunfish (Lepomis macrochirus) 72-1b 24 LC 50 96 hr : 1.2 (1.0-1.5) NOAEC :0.46 very highly toxic Core 43908812

Rainbow Trout (Oncorhynchus mykiss) 72-1c 98 LC 50 96 hr : 0.240 (0.20- 0.29) NOAEC : 0.11 (mortality) very highly toxic Core 151597

Rainbow Trout (Salmo gairdneri) 72-1d 12.9 LC 50 96 hr : 3.4 NOAEC : N/A very highly toxic Core 151600

Rainbow Trout (Oncorhynchus mykiss) 72-1d 24 LC 50 96 hr : 2.7 (2.3-3.1) NOAEC :1.3 (mortality) very highly toxic Core 43908813

Estuarine/Marine Fish

Sheepshead Minnow ( Cyprinodon variegatus ) 72-3a 96.5 LC 50 96 hr : 0.807 (0.672- 0.967) NOAEC : ≥ 0.29 (mortality) very highly toxic Core 15350691 

### Table F-2 provides the results of chronic toxicity studies of lambda cyhalothrin conducted using freshwater or estuarine/marine fish. Based on NOECs in fathead minnow and sheepshead minnow (0.03 versus 0.25 ppb), freshwater fish are relatively more sen sitive to toxic effects of lambda cyhalothrin than estuarine/marine fish.

Table F-2. Chronic Toxicity Effect s of Lambda cyhalothrin in Fish

Species Study Guideline % A.I. Toxicity Endpoint (95% Confidence Interval)

μ g a.i. /L Study Classification MRID #

Freshwater Fish

Fathead Minnow ( Pimephales promelas ) 72-5 96.7 NOAEC: 0.031 LOAEC: 0.062 (adult growth; young survival and growth) Supplemental 415190-01

Estuarine/Marine Fish

Sheepshead Minnow ( Cyprinodon variegatus ) 72-4a 96.6 NOAEC: 0.25 LOAEC: 0.38 (weight of the survival) Core 152732



### Aquatic Invertebrates Toxicity

Table F-3 summarizes the results from acute toxicity studi es conducted using aquatic invertebrates of both freshwater and estuarine marine orig in. In general, lambda cyhalothri n and the formulation products are classified as very highly toxic to aquatic inve rtebrates. Among the freshwater invertebrates, Gammarus pulex is more sensitive to lambda cyhalothrin than Daphnia magna in acute toxicity tests (EC 50 

### 0.007 ppb versus 0.23 ppb)92 Table F-3. Acute Toxic Effects of Lambda cyhalothrin in Aquatic Invertebrates

Species Study Guideline % A.I. Toxicity Endpoint (95% Confidence Interval) μ g a.i. /L Toxicity Classification 1 Study Classification MRID #

Freshwater Invertebrates

Daphnia magna 72-2a 96.5 EC 50 48 hr :0.23 (0.18-0.29) NOAEC : 0.04 very highly toxic Core 151599

Daphnia magna 72-2 5.5 EC 50 48 hr : 0.04 (0.03-0.06) NOAEC: Not established very highly toxic Supplemental 151602

Daphnia magna 72-2 12.9 EC 50 48 hr : 0.065 (0.04-0.11) NOAEC: Not established very highly toxic Supplemental 151602

Daphnia magna 72-2 24 EC 50 48 hr : 0.18 (0.14-0.23) NOAEC : 0.03 (immobility) very highly toxic Core 43908811

Gammarus pulex 72-2a 94 EC 50 96 hr : 0.007 (0.005-0.009) NOAEC : 0.0005 (mortality) very highly toxic Supplemental 152730

Estuarine/Marine Invertebrates

Eastern Oyster ( Crassostrea gigas ) Mollusk Shell Deposition 72-3b 96.5 LC 50 48 hr : >590 NOAEC : 590 (immobility) highly toxic Core 152728

Mysid Shrimp ( Mysidopsis bahia ) 72-3c >97 LC 50 96 hr : 0.005 (0.004-0.006) NOAEC :Not established very highly toxic Core 15272993 

### Table F-4 presents the results from the chr onic toxicity studies performed in Daphnia magna and mysid shrimp selected as surrogates for freshwater and estuarine/marine invertebrates, respectively. The comparison of NOECs reported for both the species i ndicates that mysid shrimps are more sensitive to lambda cyhalothrin toxicity than Daphnia.

Table F-4. Chronic Toxic Effects of Lamb da cyhalothrin in Aquatic Invertebrates

Species Study Guideline % A.I. Toxicity Endpoint (95% Confidence Interval)

μ g a.i. /L Study Classification MRID #

Freshwater Invertebrates

Daphnia magna 72-4b 92.8 NOAEC: 0.004 LOAEC:0.005 Number of young/female Supplemental 152733

Daphnia magna 72-4b 96.6 NOAEC: 0.002 LOAEC: 0.0035 Number of young/female, Total young Supplemental 41217501

Estuarine/Marine Invertebrates

Mysid 72-4b 98.5 NOAEC: 0.0002 LOAEC: 0.0005 Number of young per reproductive day and Number of young/treatment Core MRID (not available) Accession Number 073989



### Aquatic Plants Toxicity

There is no study reported testing lambda cyhaloth rin in aquatic vascular plants. One study conducted using aquatic non-vascular plant (freshwater green algae) reported the EC 50 

### as >310 ppb. Also no studies are reported on non-vascular plants of estuarine/marin e origin (e.g., marine diatoms). The results of lambda cyhalothrin on freshwater green algae are summarized in Table F-5

.

Table F-5. Acute Toxic Effects of La mbda cyhalothrin on Aquatic Plants

Species Study Guideline % A.I. Toxicity Endpoint

μ g a.i. /L Study Classification MRID #

Freshwater Non-vascular Plants

Green Algae Selenastrum capricornutum 123-2 96.5 EC 50 96 hr :>310 NOAEC : ≥ 310 Supplemental 152731



### Terrestrial Toxicity Studies

Avian Toxicity

Lambda cyhalothrin (Karate) is practically non-toxic to water fowl on an acute oral basis (MRID 151594). In subacute dietary studies, lambda cyhalothrin is practically nontoxic to upland game birds (MRID 151596) and slightly toxic to water fowl (MRID 151596). Results from waterfowl reproduction study indicated that eggs laid, eggs set, eggs cracked, viab le embryos, live embryos, normal hatchlings and 14-94 

### day old survivors were not affected at levels up to 30ppm (MRID 41512101). There is no reproduction study available for bobwhite quail.

Summary of the acute and chronic avian studies are presented in Table F-6

.

Table F-6. Avian Toxicity Studies of Lambda cyhalothrin

Species Study Guideline % A.I. Toxicity Endpoint (Confidence Interval) Toxicity Classification Study Classification MRID #

Mallard duck ( Anas platyrhynchos ) 71-1a 96 LD 50 : > 3950 mg/Kg BW Practically non toxic Core 151594

Bobwhite quail ( Colinus virginianus ) 71-2a 99.6 LC 50 : >5300 mg/Kg diet Practically non toxic Core 151596

Mallard duck ( Anas platyrhynchos ) 71-2b 96.5 LC 50 : 3948 mg/Kg diet Slightly toxic Core 151595

Mallard duck (

Anas platyrhynchos ) 71-4b 96.3 NOAEC : ≥ 30 mg a.i./kg diet (highest dose tested) - Core 41512101



### Mammalian Toxicity

In both acute oral studies conducted using technical and formulation products, lambda cyhalothrin is reported to be toxic to mammals as indicated by the low LD 50 

### values (MRID 259805). The results of acute toxicity studies performed in male and female rodents are summarized in Table F-7

.95 Table F-7. Mammalian Toxicity St udies of Lambda cyhalothrin

Species Study Guideline % A.I. Toxicity Endpoint (Confidence Interval) Study Classification MRID #

Rats 81-1 92.6- 96 LD 50 : 79 mg/kg-bw (males) LD 50 : 56 (40-78) mg/kg-bw (females) Minimum 259805

Rats 81-1 13.1 LD 50 : 64 mg/kg-bw (males) LD 50 : 101 (75-213) mg/kg-bw (females) Guideline 259805



### As EFED understands, HED has not received the deve lopmental or reproduction toxicity studies for lambda cyhalothrin. In the HIARC report (Nove mber 20, 2001), HED bridged the developmental and reproduction toxicity data from cyhalothrin for lambda cyhalothrin. The results of developmental and reproduction toxicity studies are presented in Table F-8

.

Table F-8. Chronic Mammalian To xicity Studies of Cyhalothri n (Not Lambda cyhalothrin)

Species Study Guideline % A.I. Toxicity Endpoint (Confidence Interval) Study Classification MRID #

Rats 83-3a 89.3 Maternal: NOAEL: 10 mg/kg/day LOAEL 15 mg/kg/day

Developmental NOAEL: 15 mg/kg/day (highest dose tested) LOAEL: N/A Acceptable guideline 154800

Rabbits 83-3b 89.3 Maternal:

1 NOAEL: 10 mg/kg/day

1 LOAEL 30 mg/kg/day Developmental

3 NOAEL: 30 mg/kg/day

3 LOAEL: N/A Acceptable guideline 154801

Rats 83-4 89.2 Systemic Parental/Offspring NOAEL 30 ppm (1.5 mg/kg/day) Parental/Offspring LOAEL 100 ppm (5.0 mg/kg/day) Reproductive NOAEL 100 ppm (5.0 mg/kg/day) LOAEL (N/A) Acceptable guideline 154802

### In the developmental toxicity st udy using the rats, maternal NOAEL (10 mg/kg BW/day) was established based on uncoordinated movements in limbs, reduced body weight and food consumption. Since no developmental effects were observed, the high est dose tested, 15 mg/kg BW/day was reported as developmental NOAEL.

In the rabbit developmental toxicity study, the maternal NOAEL and LOAEL was established as 10 and 30 mg/kg/day based on decreased body weight gain. No treatment related developmental effects were observed and therefore, the highest dose tested ( 30 mg/kg/day) was concl uded as developmental NOAEL

In a three generation reproduction study, Wistar rats were fed technical cyhalothrin (89.2%) in the diet, 0, 10, 30, 100 ppm (approximately 0, 0.5, 1.5, and 5.0 mg/Kg/day). The parental/offspring systemic NOAELs and LOAELs are 1.5 and 5.0 mg/kg/day, re spectively, based on decreased mean body weight and body weight gain and reduced mean pup weight and pup weight gain. The reproductive NOAEL is 5.0 mg/kg/day, the highest dose tested.

Nontarget Insects Toxicity

Lambda cyhalothrin as well as the formulation produc ts are highly toxic to honey bees in the acute contact as well as oral toxicity studies (MRID 40052409) ( Table F-9 ). The toxicity of lambda cyhalothrin residues to bees caged onto treated alfalfa foliage for 24 hours decreased with time after application. The LT 50 

### (age of the residue lethal to 50% of the bees) of the 0.013 lb a.i./acre was between 4 and 12 hours and that for 0.03 lb a.i/acre was about 23 hours. The NOEL (time to no effect) was 24 to 48 hours for the lower rate and in excess of the 96 hours for the higher (MRID 40436302) ( Table F-9 ). The LT 50 

### of greater than 24 hours suggest that PP321 is highly toxic to honey bees.

Table F-9. Nontarget Insect Toxici ty Studies of Lambda cyhalothrin

Species Study Guideline % A.I. Toxicity Endpoint (95 % Confidence Interval) Toxicity Classification Study Classification MRID #

Honey bees ( Apis mellifera ) 141-1 Contact

Oral 96

96 LD 50 : 0.038 μ g a.i./bee

LD 50 : 0.909 μ g a.i./bee Highly Toxic

Highly Toxic Core

Core 40052409

40052409

Honey bees ( Apis mellifera ) 141-1 Contact

Oral 5.04

5.04 LD 50 : 0.098 μ g a.i./bee

LD 50 : 0.483 μ g a.i./bee Highly Toxic

Highly Toxic Core

Core 40052409

40052409

Honey bees ( Apis mellifera ) 141-2 (foliage) PP321 LT 50 : 4-12 hours for 0.013 lb/acre; 23 hrs for 0.031 lb/acre

NOAEL: 24-48 hrs for 0.013 lb/acre and 96 hrs for 0.031 lb/acre - Core 40436302



### In addition to the foliage residue study menti oned in the above Table (MRID 40436302), other field studies also indicate lambda cyhalothrin has long residual toxicity. For example, a honey bee foraging study conducted on simulated honey dew on winter wheat indicated that inhibition of foraging by lambda cyhalothrin was detectable up to 3 days, but was strongly marked in the first 24 hours. PP321 at 7.5 and 15 g a.i per ha on cereals where there is honey dew s hould be present no appreciable hazard to honey bees were reported (MRID 40436303).