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- Acute Risk to Benthic Organisms............................................... 17 

2. Risks to Aquatic Plants ..................................................................................................... 18 

3. Risks to Terrestrial Animals and Non-target Terrestrial 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 Terrestrial 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 

2
I. Executive Summary 

Lambda-cyhalothrin is a synthetic pyrethroid insecticide, that 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, and is currently being 

proposed for use on cereal grains, cucurbit vegetables, 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 vegetables, 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) (DP Barcode D262918, D262919, D279087, D279088) 

are very similar to the proposed new uses, and therefore, 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 chronic 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-cyhalothrin (June 12, 2002) should 

be consulted for estimates and characterization of toxicity 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 uses are roughly two to four times higher than the 

EECs generated in the previous assessment; therefore, 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-dwelling organisms were generated anew in this 

assessment and were found to be roughly 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 properties and toxicity profile, this screening level risk 

assessment has identified acute risk to non-target listed and non-listed freshwater and estuarine/marine 

invertebrates, freshwater and estuarine/marine fish, freshwater and estuarine/ marine benthic organisms, 

mammals, and insects, and chronic risk to freshwater and estuarine/ marine invertebrates, freshwater fish, 

freshwater and estuarine/ marine benthic organisms, birds, reptiles, and mammals resulting from the 

proposed use patterns. Although acute risk estimates for freshwater non-vascular plants are below the 

Agency’s LOCs, acute risk to aquatic vascular plants and terrestrial plants could not be evaluated due to 

the lack of acceptable 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 chemicals to phytotoxic effects despite being applied on or 

near agricultural plants, it appears unlikely 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-cyhalothrin (PC Code: 128897) insecticide on cereal grains, 

cucurbit vegetables, grass forage, fodder and hay, wild rice and tuberous and corm vegetables. Lambda3
cyhalothrin is a synthetic pyrethroid, a class of pesticides 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 uses 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 only used in small areas to the west of the Dakotas 

and Texas in 1997. 

Table 1. Summary use information for lambda-cyhalothrin, based on current and proposed (in bold) 

labels for Karate® Insecticide and Warrior® Insecticide. Current uses assessed in the Environmental 

Fate and Effects Division’s Science Chapter of the 2002 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 

4
Table 1. Summary use information for lambda-cyhalothrin, based on current and proposed (in bold) 

labels for Karate® Insecticide and Warrior® Insecticide. Current uses assessed in the Environmental 

Fate and Effects Division’s Science Chapter of the 2002 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. 

5
Figure 1. Map highlighting the major uses 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 average annual pesticide use intensity expressed as average weight (in 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 estimates of pesticide use 

rates for individual crops that were compiled by the National Center for Food and Agricultural Policy during 1995-1998 and on 1997 Census of 

Agriculture county crop acreage. The maps do not represent a specific year, but rather show typical use patterns over the four year period 1995 

through 1998. Use intensity rates are expressed as the pounds applied per square mile of mapped agricultural land in a county. The area of 

mapped agricultural land for each county was obtained from an enhanced version of the 1992 USGS National Land Cover Data (NLCD). The key 

limitations of the data used to produce these maps include the following: (1) state use-coefficients represent an average for the entire state and 

consequently do not reflect the local variability of pesticide management practices found within states and counties, (2) pesticide use estimates 

are not for a specific year, but represent typical use patterns for a four year period, (3) state pesticide use coefficients may 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 calculate the pesticide use intensity and display the data was derived from 30-meter satellite remote sensing data 

which may over estimate or underestimate the actual agricultural land area. The maps are not intended for making local-scale estimates of 

pesticide use, such as estimates at the county level. Please refer to Method for Estimating Pesticide Use for a detailed discussion of how the 

pesticide use data were developed.

B. Exposure Characterization 

1. Aquatic Exposure 

6
In a previous Environmental Fate and Effects Division 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), Tier 2 aquatic modeling (PRZM/EXAMS-with the aid of the 

user interphase, pe4) was used to estimate the concentrations of lambda-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 represent the proposed uses of lambda-cyhalothrin. For 

the purpose of the modeling, the maximum annual and per event application rate, maximum number of 

applications per season, and the minimum intervals between the applications were selected to estimate the 

aquatic exposure concentrations. In general, the crops 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 determine 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 for conifer and deciduous trees. 

As demonstrated in Table 1, the usage patterns are similar between the registered uses assessed in 

EFED’s 2002 Section 3 risk assessment and the new uses assessed in this document. In addition, in the 

2002 Section 3 for lambda-cyhalothrin, the Estimated Exposure Concentrations (EECs) resulted in 

numerous exceedances of both acute and chronic LOCs for aquatic organisms. Therefore, for the current 

proposed new uses of lambda-cyhalothrin on cereal grains, cucurbit vegetables, grass forage, fodder and 

hay, wild rice and tuberous and corm vegetables, Tier 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 generate 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 values. Even though these chronic EECs were smaller 

than the EEC obtained from the Rice Model (that typically 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. runoff/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 aerial applications assuming 1% and 3.9% drift, 

respectively, as well as for theoretical aerial applications assuming 0% drift. Typically, 1% drift is the 

default input value in PRZM/EXAMS for ground applications, and 5% drift is the default assumption for 

aerial applications. However, because labels for lambda-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 current 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 

7
(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 are 0.224 ppb (stone fruit), 0.039 ppb (coniferous and 

deciduous trees), and 0.030 ppb (coniferous and deciduous trees). Since EECs for the new uses are 

roughly two to four times higher than the EECs generated 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 concept, while all other EECs are based on a Tier 2 

aquatic model. 

Table 2. PRZM/EXAMS Estimated Environmental Concentrations (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 and Effects Division 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). b The default drift assumption for aerial applications 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 Concentration in the Sediment/Pore water

Lambda-cyhalothrin, like other pyrethroids, 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, as indicated by its 

relatively high KOC (average KOC= 333,200 mL/g). Therefore, coupled with lambda-cyhalothrin’s 

moderate persistence in aquatic environments, sediment bound lambda-cyhalothrin could present a 

toxicity risk for benthic aquatic life and aquatic ecosystems in general. Exposure to this sediment can 

result in a direct impact to aquatic life through respiration, ingestion, dermal contact, as well as indirect 

8
impact through alterations of the food chain. Although estimates of sediment exposure were not generated 

in previous risk assessments for lambda-cyhalothrin, 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 becomes 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 used 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 organic 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 (KOC), which is constant for every chemical and represents the ratio of the 

chemical concentration in water to the concentration 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/gOC). Similar responses were also observed across sediments when interstitial water concentrations 

were used to normalize biological availability. 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/gOC basis can be predicted by multiplying the effect concentration in water by the chemical KOC. 

 (LC50 ug/L x KOC L/KgOC x 1 KgOC/1000gOC = LC50 ug/gOC) 

Since, the Agency uses a deterministic method for its screening 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., 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 toxic 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 generate EECs from sediment and porewater. By relying 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. 

The calculations that rely on porewater can be calculated by dividing the PRZM/EXAMS output value for 

porewater concentrations by the dissolved concentrations 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/kgOC), RQs can be produced by using the PRZM/ EXAMS 

sediment output value for sediment. 

EEC sediment ug/kgOC / LC50 ug/kgOC

9
Since actual sediment effects data were not available, RQs could not be calculated based on exposure via 

sediment, and RQs were calculated based on pore water 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 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., interstitial 

water respiration, sediment ingestion or other sediment 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 (in ppb) of Lambda-cyhalothrin in the Benthic Pore 

Water and Sediment. 

Exposure Scenario Peak 21-day 

Pore Water EECs (μg 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 applications 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®. 

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 vegetative 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 wildlife food items focuses on quantifying possible dietary 

ingestion of residues on vegetative matter and insects. The EFED TeRrestrial EXposure model T-REX 

(T-REX, Version 1.2.3, dated August 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). Specifically, the model provides estimates of concentrations 

(upper-bound and mean) of chemical residues on the surface of different types of foliage and insects that 

may be dietary sources of exposure to avian, mammalian, 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 specific to each food item. These values (termed the 

Hoerger-Kenaga estimates) along with a more detailed 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 chemical 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 data 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 conditions is lower than the default value. Because foliar 

dissipation data are not available, the extent to which EECs may be overestimated or underestimated is 

uncertain. 

Risks could also be overestimated if the actual application rate, frequency of application, 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 maximum 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 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 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 (short grass, tall grass, broadleaves/forage/ small insects 

and seeds/large insects) derived according to Hoerger and Kenaga (1972), Fletcher et al. (1994) and 

Pfleeger et al. (1996) in the previous Environmental Fate and Effects Division 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). These EECs were also 

generated based on the maximum application rates, maximum number of applications, and minimal 

intervals between the applications, assuming a first-order 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 selected 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 Section 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 already registered uses (EEC range = 5 to 74; based on 

12 aerial applications under a 5-day interval to conifer 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 the 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 exposure 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, D279087, D279088) should be 

referred to for the evaluation of potential risk of lambda-cyhalothrin to terrestrial organisms resulting 

from the proposed uses on cereal grains, cucurbit vegetables, 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 Itemsa

Crops or Crop Groups and Application Concentrations in Wildlife Food items (ppm) 

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 foliar dissipation data were unavailable. 

C. Conceptual Model 

 

 1. Risk Hypotheses 

Risk hypotheses are specific assumptions about potential adverse effects (i.e., changes in assessment 

endpoints) and may be based on theory and logic, empirical data, mathematical models, or probability 

models (US EPA 2004). For this assessment, the risk is stressor-initiated, where the stressor is the release 

of lambda-cyhalothrin to the environment. The following risk hypothesis is presumed for this screening 

level assessment: 

The use of lambda-cyhalothrin on agricultural crops 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 indirect 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. 

12
13

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 environmental transport medium, a point of exposure for 

ecological receptors, and a feasible route of exposure. 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 chemical 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 wildlife (i.e., mammals, birds, amphibians, and reptiles), 

terrestrial and semi-aquatic plants, and soil invertebrates. Aquatic receptors (e.g., freshwater and 

estuarine/marine fish and invertebrates, and amphibians) 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 other aquatic environments. This information formed the basis for identifying 

potential endpoints, stressors, and ecological effects 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 agricultural crops has been established, refined and 

included in Figure 2. In establishing the diagram for the conceptual 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 summary of the available environmental fate data is 

presented in Appendix C. 
Figure 2. Ecological conceptual exposure model for spray applications of lambda-cyhalothrin.

Stressor Lambda-cyhalothrin applied as ground/aerial spray to agricultural cropsSource/TransportPathw ays

Volatilization

/ Wind 

Suspension

Direct

Deposition

Spray

Drift

Runoff/

Erosion

Leaching

Infiltration/Percolation

Source/ExposureMedia

Terrestrial Food 

Residues (foliage, 

fruit, insects)

Upland

Foliage/Soil

Riparian/

Wetland 

Foliage/Soil

Water Column, 

Sediment

Groundwater

ExposurePoint

Ingestion & Dermal 

Uptake

Direct contact and root uptake

Gill/ Integument 

Uptake and 

Ingestion

ReceptorsAttributeChanges

Terrestrial Organisms:

Birds, Mammals,

Reptiles, Terrestrial 

Insects

Terrestrial

Upland

Plants

Individual Animals

Reduced survival

Reduced growth

Reduced reproduction

Aquatic 

Invertebrates

and Vertebrates

Amphibians

Wetland/ 

Riparian

Plants

Individual Plants

Seedling emergence

Vegetative vigor

Individual Animals

Reduced survival

Reduced growth

Reduced

reproduction

Plant population

Reduced

population

growth

** The dotted lines represent unlikely routes of exposure

Food Web Exposure 

(Bioaccumulation)

Piscivorous

Vertebrates

(Birds and 

mammals)

Aquatic 

Plants
15

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 lambda-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 acute and chronic toxicity values. The RQs are then 

compared to the Agency’s levels of concern (LOCs). These LOCs, summarized in Appendix E, are the 

Agency’s interpretive policy and are used to analyze potential risk to non-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 invertebrates, 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 exposure) pore water concentrations obtained 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-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) 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 restricted use (LOC 0.1), and acute endangered species (LOC 

0.05) are exceeded for both, freshwater and estuarine/ marine 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 lambda-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 restricted use, and acute endangered species are exceeded 

for freshwater fish (RQ = 1.29), but only the acute restricted 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 estuarine/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 uses of lambda-cyhalothrin. The RQs are based on the 

most sensitive toxicity values for each taxonomic group; the LC50/EC50 values for freshwater invertebrates, 

estuarine/ marine invertebrates, freshwater fish, and estuarine/ marine fish are 0.007 μg a.i./L (Gammarus 

pulex; MRID 00152730), 0.005 μg a.i./L (Mysidopsis bahia; MRID 00152729), 0.210 μg a.i./L (Lepomis 

macrochirus; MRID 151598), and 0.807 μg a.i./L (Cyprinodon variegates; MRID 00153506), respectively. The 

EEC values (μg/L) used to calculate RQs are peak concentrations.

Acute RQs (EEC/LC50 or EC50)

Exposure Scenario Invertebrates Fish 

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 applications in PRZM/EXAMS is typically 5%. However, a 3.9% drift assumption was employed due 

to label requirements that specify the use of 150ft buffer. A 3.9% drift estimate is generated using AgDRIFT® under a 150ft buffer zone 

assumption. 

Table 6. Comparison of the chronic RQs calculated for freshwater and estuarine/marine invertebrates and 

fish associated with the proposed new agricultural uses of lambda-cyhalothrin. The RQs are based on the 

most sensitive toxicity values for each taxonomic group; the NOAEC values for freshwater invertebrates, 

estuarine/marine invertebrates, freshwater fish, and estuarine/marine fish are 0.002 μg a.i./L (Daphnia 

magna; MRID 41217501), 0.0002 μg a.i./L (Mysidopsis bahia; Accession Number 073989), 0.031 μg a.i./L 

(Pimephales promelas; MRID 41519001), and 0.25 μg a.i./L (Cyprinodon variegates; MRID 00152732), 

respectively. The EEC values (μg/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 

Exposure Scenario (60-day EEC/NOAEC) 

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 0.13 
17

Table 6. Comparison of the chronic RQs calculated for freshwater and estuarine/marine invertebrates and 

fish associated with the proposed new agricultural uses of lambda-cyhalothrin. The RQs are based on the 

most sensitive toxicity values for each taxonomic group; the NOAEC values for freshwater invertebrates, 

estuarine/marine invertebrates, freshwater fish, and estuarine/marine fish are 0.002 μg a.i./L (Daphnia 

magna; MRID 41217501), 0.0002 μg a.i./L (Mysidopsis bahia; Accession Number 073989), 0.031 μg a.i./L 

(Pimephales promelas; MRID 41519001), and 0.25 μg a.i./L (Cyprinodon variegates; MRID 00152732), 

respectively. The EEC values (μg/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 

Exposure Scenario (60-day EEC/NOAEC) 

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 applications 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. A 3.9% drift estimate is generated using AgDRIFT® under a 150 ft buffer zone 

assumption. 

 b. Sediment Exposure- Acute Risk to Benthic Organisms

The LOCs for acute risk (LOC 0.5), acute restricted 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 scenario (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-cyhalothrin 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 exceedances 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 acute RQs calculated for freshwater and estuarine/marine benthic organisms 

associated with the proposed new agricultural uses of lambda-cyhalothrin. The lowest acute toxicity values 

reported in freshwater invertebrates (EC50 = 0.007 μg a.i./L in Gammarus pulex; MRID 00152730) and 

estuarine/marine invertebrates (EC50 = 0.005 μg a.i./L in Mysidopsis bahia; MRID 00152729) were used as 

surrogate toxicity values for sediment-dwelling organisms exposed to lambda-cyhalothrin in pore water. The 

EEC values (μg/L) used to calculate RQs are peak concentrations. 

Acute RQ 

Exposure Scenario Benthic Organisms 

Peak Pore 

Water EEC 

(μg 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, c
18

Table 7. Comparison of the acute RQs calculated for freshwater and estuarine/marine benthic organisms 

associated with the proposed new agricultural uses of lambda-cyhalothrin. The lowest acute toxicity values 

reported in freshwater invertebrates (EC50 = 0.007 μg a.i./L in Gammarus pulex; MRID 00152730) and 

estuarine/marine invertebrates (EC50 = 0.005 μg a.i./L in Mysidopsis bahia; MRID 00152729) were used as 

surrogate toxicity values for sediment-dwelling organisms exposed to lambda-cyhalothrin in pore water. The 

EEC values (μg/L) used to calculate RQs are peak concentrations. 

Acute RQ 

Exposure Scenario Benthic Organisms 

Peak Pore 

Water EEC 

(μg 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 applications 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. A 3.9% drift estimate is generated using AgDRIFT® under a 150 ft buffer zone 

assumption. 

Table 8. Comparison of the chronic RQs calculated for freshwater and estuarine/marine benthic organisms 

associated with the proposed new agricultural uses of lambda-cyhalothrin. The lowest chronic toxicity 

values reported in freshwater invertebrates (NOAEC = 0.002 μg a.i./L in Daphnia magna; MRID 41217501) 

and estuarine/marine invertebrates (NOAEC = 0.0002 μg a.i./L in Mysidopsis bahia; Accession Number 

073989) were used as surrogate toxicity values for sediment-dwelling organisms exposed to lambdacyhalothrin in pore water. The EEC values reflect 21-day pore water estimates that are in equilibrium with 

sediment concentrations (average KOC= 333,200). 

Chronic RQ 

Benthic Organisms Exposure Scenario 

21-day 

Pore Water 

EEC 

(μg 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 applications 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. A 3.9% drift estimate is generated using AgDRIFT® under a 150 ft buffer 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 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 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 available 
19

in the previous Environmental Fate and Effects Division 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) were used to calculate RQs as described in Table 9 below. 

Toxicity data are either inadequate or unavailable to calculate RQs based on the following measurement 

endpoints (e.g., acute or chronic toxicity reference values) and receptors: 

 EC50 values for estuarine/marine and freshwater vascular aquatic plants 

 EC50 values for estuarine/marine non-vascular aquatic plants 

As can be seen below in Table 9, none of the acute RQs for freshwater 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 EC50 and NOAEC values 

of >310 μg a.i./L and 310 μg a.i./L (Selenastrum capricornutum; MRID 00152731), respectively. The EEC values 

(μg/L) used to calculate RQs are peak concentrations.

Exposure Scenario Peak Water 

Column EEC 

(μg 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 applications 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. A 3.9% drift estimate is generated using AgDRIFT® under a 150 ft buffer zone assumption.

3. Risks to Terrestrial Animals and 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 toxicity profile, this screening level risk assessment has 

identified acute risk to non-target listed and non-listed freshwater and estuarie/marine invertebrates, 

freshwater and estuarie/marine fish, freshwater and estuarine/ marine benthic organisms, mammals, and 

insects, and chronic risk to freshwater and estuarine/ marine invertebrates, freshwater fish, freshwater and 

estuarine/ marine benthic organisms, birds, reptiles, and mammals resulting from the proposed use 

patterns. Although acute risk estimates for freshwater 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 Estimated Environmental Concentrations (EECs) for 

aquatic environments resulted in numerous exceedances 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 groups 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 estimates 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 assessment (NC sweet potato) when drift assumptions for 

the scenario are varied (i.e., ground application vs. aerial application vs. 0% drift). This suggests that the 

major route of exposure to aquatic environments under the maximum exposure scenario is via 

runoff/erosion. However, under the FL cucumber scenario, 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 the 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 KOC, lambda-cyhalothrin is expected to be immobile in soil environments (average KOC= 

333,200 mL/g, n=10). It is highly unlikely to reach ground waters; however, despite the protective 

imposed buffer zone and buffer strip, it could reach adjacent 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 water. 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 the 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 potatoes scenario. Due to this 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 assessment 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 applications 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 adjacent 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 freshwater 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 freshwater 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 ensure that all RQs for aquatic water column-dwelling 

organisms are below all acute risk LOCs. Based on the 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 and 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 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 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 

KOC= 333,200), possibly limiting bioavailability (in terms of freely-dissolved lambda-cyhalothrin) in this 

media, the bound residues settle onto the benthos, increasing their concentrations in the sediment. 

Exposure to this sediment can result in a direct impact to aquatic life through respiration, ingestion, dermal 

contact, as well as indirect impact through alterations of the food chain. Coupled with lambdacyhalothrin’s expected persistence in anaerobic environments, sediment bound lambda-cyhalothrin could 
22

present a toxicity risk for benthic and epibenthic aquatic life, and aquatic ecosystems in general. 

Therefore, the second aquatic compartment that was considered was the benthos, which is composed of 

sediments and an area 6 inches above the sediment (epibenthos). 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 capturing organisms that are emerging from this area. 

The evaluation of toxic risk to the benthic organisms was approached by assuming equilibrium partitioning 

of a high KOC compound like lambda-cyhalothrin between the 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 organisms 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., LC50, EC50). Although sediment systems are 

assumed to adsorb a large portion of lambda-cyhalothrin 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 underestimation of actual 

exposure values noted in the laboratory or field, and that inherent variations in biological uptake as result 

of differences in feeding pathways, organism life stage, and population-level effects versus individual 

responses could affect the toxicity of sorbed pesticide 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 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 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., interstitial 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 and chronic sediment toxicity data are needed to 

confirm the findings of this screening-level tool and to fully characterize effects 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 the equilibrium-partinioning theory, the Agency has 

identified acute and chronic risk concerns to aquatic 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 benthic organisms, respectively, with exceedances of 

acute risk, acute restricted, and acute endangered species LOCs. Chronic risk LOC is exceeded, and RQs 

range from 0.32 to 3.87 and 3.20 to 38.65 for freshwater 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 restricted, 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 Section 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 equivalent 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 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), 

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 rice and tuberous and corm vegetables. 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 resulting from the proposed use 

patterns. Although quantitative risk estimates for terrestrial 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 μg a.i./bee) and that the potential risk to pollinators 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 chemicals to phytotoxic effects despite being applied 

on or near agricultural plants, it appears unlikely that it poses a phytotoxic concern. 

IV. References 

Di Toro DM, Zarba CS, Hansen DJ, Berry WJ, Swartz 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 estimating pesticide residues on plants. Env. Toxicol. 

Chem. 13:1381-1391. 

Hoerger, F. and E. E. Kenaga. 1972. 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, Toxicology, 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 D262918, D262919, D279087, D279088. 

T-REX. 2005. Terrestrial Residue Exposure Model (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. Environmental 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. Reviews 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 capable to determine “quantitatively” the level of 

drift to the EXAMS standard pond from a predetermined buffer zone. 

• For agricultural uses, exposure concentrations for 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 employs 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 generic scenario for the EXAMS component of the modeling exercise. 

• Since lambda-cyhalothrin binds to organic carbon (mean KOC = 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/ EXAMS model. Screening level RQs for sediment 

dwelling organisms were estimated with an extrapolation 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 304(a)(2)]. After consultation with the OW, 

EFED adopted the equilibrium partitioning (EqP) method 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 organic 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 KOC. 

• In order to determine concentrations in a rice paddy (for wild rice), the EFED utilized the interim 

approach, which represents a tier I concept. In short, 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 fixed quantities that were chosen to be 

reasonably representative of a rice paddy. 

• The Rice Model (“Policy for Estimating Aqueous Concentrations 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 the “peak” EEC, and refinements were performed to 

account for aerobic aquatic metabolism and aqueous photolysis. Even though this is a refinement 
26

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 and 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 (PRZM) field or orchard crop scenario is the basic file 

which describes the local or regional climatological information, 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 daily time step. The runoff and erosion flux output data 

from PRZM are used as chemical loadings to EXAMS (Exposure Analysis Modeling System), which 

simulates surface water in order to predict the Estimated Exposure Concentrations (EECs). The PRZM 

scenarios selected for modeling were Florida cucumbers 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 calculation 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 (DV0.5 = 254.72 μm; DV0.9 = 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 according 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® Insecticide 

and 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® Insecticide 

and Warrior® Insecticide. 

Minim Interval between 

Applications (days) 

Cucumber 5 

Sweet potato 7 

Proposed labels for 

Karate® Insecticide 

and Warrior® Insecticide. 
28

Table A. Input Parameters Utilized in PRZM/EXAMS lambda-cyhalothrin: 

Parameter (units) VALUE(S) SOURCES COMMENTS 

KOC 333,200 mL/g 44861503, 

45447413 

Average of 10 available 

values ranging from 

110,000 to 724,000 mL/gOC. 

The KOC model was utilized 

as per recommendation of 

the Science Advisory 

Comity (SAP). 

Aerobic Soil Metabolism 

(days) 

56.5 00151607, 

00089995 

Represents the 90th

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® Insecticide 

and Warrior® Insecticide. 

Method of Application Aerial 

Ground 

Proposed labels for 

Karate® Insecticide 

and Warrior® Insecticide. 

Buffer Zone (ft.) 150 ft aerial 

25 ft ground 

Proposed labels for 

Karate® Insecticide 

and Warrior® Insecticide. 

Application Efficiency 

(fraction) 

0.95 aerial 

0.99 ground 

Guidance for Selecting 

Input Parameters in 

Modeling 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 90th

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 90th

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-m3

/mol) 

2.4x10-7 Registrant data 

CAM (Chemical 

Application Method) 

1 Soil applied Guidance for Selecting 

Input Parameters in 

Modeling 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 in 

Modeling the Environmental Fate and 

Transport of Pesticides, v.II, 

2/28/02 

FEXTRC, Foliar extraction 0.5 Guidance for Selecting 

Input Parameters in 

Modeling 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 in 

Modeling the Environmental Fate and 

Transport of Pesticides, v.II, 

2/28/02 

PLVKRT, Volatilization 

rate from foliage 

0 Guidance for Selecting 

Input Parameters in 

Modeling the Environmental Fate and 

Transport of Pesticides, v.II, 

2/28/02 

UPTKF, Uptake factor 0 Guidance for Selecting 

Input Parameters in 

Modeling the Environmental Fate and 

Transport of Pesticides, v.II, 

2/28/02 

Write Benthic Pore Water 

Concentrations? 

Yes 

Write benthic 

sediment file? 

Yes 
30

Selection of PRZM scenarios and limitations:

The crops assessed included Cereal Grains (Barley, Buckwheat, Oat, Triticale, Wheat, Wheat hay), 

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], Grass Forage, Fodder and Hay (Pasture and rangeland grass, Grass grown for hay or 

silage, and Grass grown for seeds), Wild Rice, 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)]. 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 crop 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 (seasonal application rate of 0.12 lb a.i./A). Two suitable scenarios were 

available, one per crop group. The Florida cucumbers crop scenario is representative of cucurbit 

vegetables, while the North Carolina sweet potatoes crop 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 scenario. 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 EECs 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 = 109 MT 

 ------------------ 

 VT + msed Kd 
31

VT = 1.067 x 106 L/ha 

msed = 130,000 Kg/ha 

109

 = units factor 

Kd = partition coefficient, selected as per input guidelines (see above) 

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

EEC = (109 μg/Kg) (0.134 Kg/ha) 

 ------------------------------------------------------------- 

 1.067 x 106

 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: 

 t1⁄2 = -ln (2) / k or k = -ln (2) / t1⁄2 

Since the formula that describes a first order reaction is: 

 [A] = e-k total and t1⁄2 total = (50/100) therefore ln(50/100)= ln (0.5)/-ktotal

 [A]o 

t1⁄2 photolysis = 25 days; kphotolysis = - 0.0277 days-1 

t1⁄2 aerobic aquatic metabolism = 33.7 days; kaerobic aquatic metabolism = - 0.0207 days-1 

the half life is 14.3 days. 

For lambda cyhalothrin, [A]0 = 0.270 μg/L, and ktotal = -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 Concentration 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 KOC. Therefore, coupled with lambda-cyhalothrin’s persistence in aerobic 

and anaerobic aquatic environments, sediment bound lambda-cyhalothrin TGAI could present a toxicity 

risk for benthic aquatic life and aquatic ecosystems in general. 

Therefore, in order to assess this potential for pesticide risk to aquatic benthic systems, the Environmental 

Fate and Effects Division (EFED) of the Office of Pesticides Program (OPP) has adopted the method used 

by the Office of Water that relies on equilibrium partitioning (EqP) of chemicals. The EqP 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 chemical in sediment partitions between sediment organic 
32

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 (KOC), which is constant for every chemical and represents the ratio 

of the chemical concentration in water to the concentration 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 weight basis, but similar when expressed on a ug chemical/g organic 

carbon basis (ug/goc). Similar responses were also observed across sediments when interstitial water 

concentrations were used to normalize biological availability. 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/goc basis can be predicted by multiplying the effect concentration in water by the 

chemical Koc. 

 (LC50 ug/L x Koc L/Kgoc x 1 Kgoc/1000goc = LC50 ug/goc) 

Since, EFED uses a deterministic method for its screening 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., 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 pore water EEC values. Therefore, to assess possible toxic 

pesticide exposure to aquatic organisms from sediments, EFED is using the PRZM/EXAMS to generate 

EECs for pore water model based on the principles of the equilibrium partitioning theory, by relying on 

pore water output values. 

The calculations that rely on pore water can be calculated by dividing the PRZM/EXAMS output value for 

pore water concentrations by the dissolved concentrations in the water column that caused toxicity in 

bioassays using lambda-cyhalothrin TGAI (e.g., LC50). 

 RQbenthic 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 peak 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-day 
33

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 Rice 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 erosion from an agricultural field on a daily time 

step. The runoff and erosion flux output data from PRZM 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 immediately 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 estimated 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 pesticides 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, advection, dispersion, and retardation. For nitrogen, 

simulation of surface applications, atmospheric deposition, 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 transport of chemicals in aquatic systems. It provides 

facilities for steady state or long-term evaluation of chronic chemical discharges, 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 contaminant 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 Florida 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 other interested parties that worked together in the 

development of AgDRIFT® (SDTF), were used to confirm the model results at each of the different levels 

of analysis. The aerial tiers consist of a mathematical 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 turbulent 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 the 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 estimation 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 exposure, 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 fixed quantities that were chosen to be reasonably 

representative of a rice paddy. The Tier I Rice Model was derived in EFED from the following simple 

relationship: 

 EEC = 109 MT 

 ------------------ 

 VT + msed Kd 

 VT = 1.067 x 106 L/ha 

 msed = 130,000 Kg/ha 

 109

 = units factor 

 Kd = partition coefficient 

 MT = 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 ensure that its output represents protective estimates of 

concentration. The assumptions include the following: 

1. Movement of pesticide on suspended 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: 

 t1⁄2 = -ln (2) / k or k = -ln (2) / t1⁄2 

Since the formula that describes a first order reaction is: 

 [A] = e-kat for photolysis 

 [A]o 
35

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 t1⁄2 total = (50/100) therefore ln(50/100)= ln (0.5)/-ktotal

 [A]o 

t1⁄2 hydrolysis = stable (If there was any hydrolysis then it would have to be factored out of the aerobic aquatic 

metabolism half-life.) 

t1⁄2 photolysis = 25 days; kphotolysis = - 0.0277 days-1 

t1⁄2 aerobic aquatic metabolism = 33.7 days; kaerobic aquatic metabolism = - 0.0207 days-1 

the half life is 14.3 days. 

For lambda cyhalothrin, [A]0 = 0.270 μg/L, and ktotal = -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 ecological 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 benthic and epibenthic species occur. Embryonic life 

stages and gametes of infaunal, epibenthic and water column species of a variety of commercially 

important fisheries can also be found directly in contact 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 ecosystems, 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 examples of deleterious effects 

from contaminated sediments and their significant impact on commercial fisheries (e.g., TBT and effects 

to shell fish), ecosystem diversity (e.g., TBT and endocrine 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 exposure 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 contaminated 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 aquatic 
36

invertebrates via sediment exposure suggests indirect effects 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 organisms 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 available. 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 equilibrium 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 (KOC). In order to generate exposure concentrations from sediment (ug/KgOC) 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 KOC and KO/W values(333,200 and 1.0x107

, 

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 compound, the bioavailability to aquatic 

organisms living in this medium is a concern that the Agency is trying to address 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 objectives 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 waters 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 particulate 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 life 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 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 used by the OW that 
37

relies on the theory of equilibrium partitioning (EqP) 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 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 (KOC), which is constant for every chemical and represents the ratio 

of the chemical concentration in water to the concentration 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/gOC). Similar responses were also observed across sediments when interstitial water 

concentrations were used to normalize biological availability. 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/gOC basis can be predicted by multiplying the effect concentration in water by the 

chemical KOC. 

 (LC50 ug/L x KOC L/KgOC x 1 KgOC/1000gOC = LC50 ug/gOC) 

Since, The Agency uses a deterministic method for its screening 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., 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 toxic 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 

generate EECs from sediment and porewater. By relying 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/ugOC / LC50 ug/gOC 

The calculations that rely on porewater can be calculated by dividing the PRZM/EXAMS output value for 

porewater concentrations by the dissolved concentrations 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 chemicals 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 and 
38

interstitial water is at or near equilibrium. Another assumption 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 respiration; 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 predicted using the organic carbon partition coefficient (Koc) 

and effects concentrations in the water. 

This method to estimate the risk to sediment dwelling organisms has certain uncertainties. First, it appears 

that the exposure may be underestimated because it assumes that the only source of contact of lambdacyhalothrin 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. 

Second, the sensitivity of the sediment dwellers towards 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 0.003304 
39

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-2003 
40

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 0.0008973 
41

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

 0.000624 
42

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 10.23 
43

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 Halfife 
44

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 Yearly 
45

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.exv 
46

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 0.001388 
47

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

 0.0002831 
48

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 0.0002818 
49

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

 0.0002679 
50

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 3.571 
51

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/mol 
52

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 0.01234 
53

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-mmm 
54

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

 0.005377 
55

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 cm 
56

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 64.23 
57

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 09:05:50 
58

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

 0.005249 
59

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 0.003622 
60

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

 0.002709 
61

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 0.021 
62

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/L 
63

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 Yearly 
64

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.txt 
65

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 74.25 
66

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: FILTRA 
67

 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 
68

Appendix B. Data Requirements 

Table B-1. Environmental Fate Data Requirements for Lambda-cyhalothrin 

Guideline 

Number Data Requirement MRID 

Study 

Classification1

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 Classification1

Are Additional 

Data Needed for 

Risk Assessment? 

Birds

71-1a Avian acute oral LD50

Mallard Duck 

151594 Acceptable No 

71-2a Avian subacute dietary LC50

Bobwhite quail 

151596 Acceptable No 

71-2b Avian subacute dietary LC50

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 LC50/EC50

Bluegill Sunfish 

151598 Acceptable No 

72-1b Freshwater fish acute LC50/EC50

Bluegill Sunfish (Formulation) 

151601 

43908812 

Acceptable 

Acceptable 

No 

72-1c Freshwater fish acute LC50/EC50

Rainbow trout 

151597 Acceptable No 

72-1d Freshwater fish acute LC50/EC50

Rainbow trout (Formulation) 

151600 

43908813 

Acceptable 

Acceptable 

No 

72-2a Freshwater invertebrate, 

Daphnia EC50

Gammarus pulex EC50

151599 

152730 

Acceptable 

Supplemental 

No 

72-2b Freshwater invertebrate, Daphnia EC50

(Formulation) 

151602 

43908811 

Supplemental 

Acceptable 

No 

72-3a Estuarine/marine fish acute LC50

sheepshead minnow 

153506 Acceptable No 

72-3b Estuarine/marine acute invertebrate EC50

(eastern oyster) 

152728 Acceptable No 

72-3c Estuarine/marine acute invertebrate EC50 

(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 - No 
70

Table B-2. Ecological Effects Data Requirements for Lambda-cyhalothrin 

Study 

Guideline Data Requirement MRID # Study Classification1

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 LD50 (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 scientifically sound, but does not satisfy guideline; Invalid: study is not 

scientifically sound and does not satisfy guideline. 
71

Appendix C. Fate and Transport Characterization 

Table 2 summarizes the physical/chemical and environmental 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 

(1S,3S)-3-[(1Z)-2-chloro3,3,3-trifluoro-1- 

propenyl]-2,2-

dimethylcyclopropanecarboxylate 

– IUPAC name: 

(R)-α-cyano-3-

phenoxybenzyl (1S,3S)-3-

[(Z)-2-chloro-3,3,3-

trifluoropropenyl]-2,2-

dimethylcyclopropanecarboxylate and (S)-αcyano-3-phenoxybenzyl 

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

2,2-dimethylcyclopropanecarboxylate 

 Molecular Formula C23H19ClF3NO3 EPI SuiteTM -- 

 Molecular Weight 449.86 g/mole -- Unlabeled 

Solubility of the parent 

(at pH 6.5, 20o

C) 

0.005 ppm or 5 ppb MRID 

00151580 

– 

Solubility of XV(at 25oC) 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/cm3 at 25°C -- -- 

Melting Point 49.2°C IPCS(1) -- 

Decomposition >275°C IPCS(1) -- 

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

Henry’s Law constant 2.4x10-7 Atm-cm3/mole Registrant data -- 

pKa (20 oC) >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 GUIDE 
72

 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 KO/W) 

7.0 IPCS(1) KO/W = 1.0x107 

Hydrolysis Half-life 

[pH 5, 7, 9] 

pH 5 = stable 

pH 7 = stable 

pH 9, t1⁄2 = 13 days 

MRID 

00151604 

--. 

Aqueous Photolysis Half-life 

(pH 5) 

t1⁄2 = 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 

t1/2 = 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 

t1/2 = 113, 142 days MRID 

44367401, 

00151607 

-- 

Aerobic Aquatic Metabolism 

Half-life 

t1/2 = 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 (KOC, mL/gOC) 

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 

(Kd, 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* 

Kd model describes the 

mobility better than KOC. 

Mean Kd = 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 Sandy Loam after 24 

hr of equilibration (>80% for one of 

the conditions).*

MRID 

44861509* *Supplemental 

Organic Carbon Partition 

Coefficient (KOC) for XV 

(mL/gOC) 

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 

(Kd, 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-cyhalothrin is substantially complete, but it contains 

various supplemental studies. It is sufficient for a Tier I Drinking Water Assessment. Lambdacyhalothrin is expected to have little mobility in soil surfaces and, therefore, leaching into 

groundwater is not expected to be an important environmental fate process (average KOC= 

333,200 n=10). Volatilization from moist or dry surfaces is not expected to be an important 

transport process. Lambda-cyhalothrin has a relatively low vapor pressure and Henry’s Law 

constant (1.5x10-9 mm Hg and 2.4x10-7 Atm-cm3

/mole, respectively). With a pKa >9, lambda 

cyhalothrin is expected to be neutral in natural 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 hydrolyzes in a matter of weeks under alkaline conditions (half-life 

13 days at pH 9). Lambda-cyhalothrin is more stable to light than the first or second generation 

pyrethroids like allethrin and resmethrin, but still undergoes some photolysis in water, with halflives of about a month or more in distilled water (half-life 25 days). On soil, the half-life is fairly 

stable (with little degradation on the 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-cyhalothrin 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. Terrestrial 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 structure to that of lambda-cyhalothrin, dissipation from plant foliage 

occurs with half-lives on the order of 5-6 days, but it may be higher for the total residues. A low 

rate of volatilization was observed from leaves (88% of applied remaining on the leaves after 24 

hours(2

). The chemical does not translocate in the plant 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 Substance Lambda-Cyhalothrin, 7572/VI/97-final; Jan 25, 2001
75

waters. However, despite the protective imposed buffer zone and buffer strip, it could reach 

adjacent surface waters via spray drift or runoff events (via erosion). Once there, the chemical 

will partition with the sediment and will linger for long periods of time (months). The sediment 

serves as a repository of the chemical after numerous applications, in dynamic equilibrium with 

the pore water and the surface water. Lambda-cyhalothrin is moderately bioaccumulative (448X 

in the whole body), but it depurates slowly (only 10-15% depuration after 21 days). It appears 

that situations may occur, where this chemical may 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 major degradates appear to be (±)cis- or trans-3-(2-

trifluoromethyl,2-chloro-ethenyl) 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 cyhalothrin, 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 concerns in humans. The degradate appears to 

degrade readily to carbon dioxide (t1/2, avg. = 8.9 days; n=3), and it appears to partition with the 

sediment. It has low mobility based on the estimated KOC value of 770,900 mL/gOC, from 

structure activity relationship (SAR) modeling. The potential for groundwater contamination 

with the degradate is low. However, it is likely to reach surface water via runoff (via erosion) 

after a rainfall event. 

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

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

DEGRADATE and MAXIMUM CONCENTRATION 

STUDY TYPE SOURCE 

(1RS)-cis-3(ZE)-2-

chloro-3,3,3-trifluro1-propenyl)-2,2-

dimethylcylopropanecarboxylate, 

Compound Ia (% 

applied) 

(1RS)-trans-3-(ZE-2-

chloro-3,3,3-

trifluoroprop-1-enyl)-

2,2-

dimethylcyclopropanecarboxylic acid, 

Compound Ib (% 

applied) 

(1R) 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 

(1RS)-cis-3(ZE)-2-

chloro-3,3,3-trifluro1-propenyl)-2,2-

dimethylcylopropanecarboxylate, 

Compound Ia (% 

applied) 

(1RS)-trans-3-(ZE-2-

chloro-3,3,3-

trifluoroprop-1-enyl)-

2,2-

dimethylcyclopropanecarboxylic acid, 

Compound Ib (% 

applied) 

(1R) 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 Toxicology, 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 calculates the residues on avian and mammalian food items along with the 

dissipation rate of a chemical applied to foliar surfaces (for single or multiple applications) in order to 

estimate acute and reproductive risk quotients. LD50 ft-2 values are calculated for both broadcast and 

banded (granular and liquid) applications 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 following 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 (inputs 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, enter 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 adjusted 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 models may incorporate a provision of 

intervals of varying length. The risk 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 possible mitigation effort effects on risk 

outcomes. 

 B. Avian and Mammalian Endpoints 

To calculate risk quotients, user-supplied avian and mammalian toxicity endpoints need 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). Typically, 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 release 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 entered if the assessor believes that body 

weight does not influence toxicity of the chemical being assessed. 

EFED policy states that for screening risk assessments, 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 document 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 different species are similar to each other because T-REX 

adjusts the toxicity values based on body weight and food intake of the tested organism compared with the 

assessed organism. Therefore, when data are available 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 the model assumes a set body weight for tested bobwhite 

quail (178 g) and mallard duck (1580 g) unless another body weight is entered to the 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 obtained 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 values 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 study 
80

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 LD50, LC50, NOAEC and/or NOAEL from acceptable or supplemental studies are used in 

screening-level risk assessment of mammals. For non-screening level assessments, 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 the 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 weight of 350 g will result in inaccuracies when 

extrapolating test endpoints to modeled animals. Therefore, if a mammalian species other than rats is used 

(e.g. dog, rabbit, mink), use the time-weighted average body weight of the animals that were tested in the 

experiment (from the DER or the original 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 use 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 Dietary Residue Concentrations (Foliar Spray)

The methods used by T-REX to estimate risk from consumption of selected contaminated food items is 

described below. For this analysis, T-REX calculates 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 determined 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 calculate 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 description. Replacing the upper bound residues with the mean 

residues is not a valid mitigation approach when upper bound residues result in LOC exceedances. Based 

on the estimated dietary residue concentrations from the upper bound and mean Kenaga values, T-REX 

calculates the associated doses for various size classes 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 concentration based risk quotients are discussed below. 
81

 

This section describes how T-REX estimates the following: (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 previous applications are summed. The maximum 

concentration calculated out of the 365 days is returned 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 order decay rate from the following first order rate 

equation: 

 CT = Cie

-kT

 or in log form: 

 ln (CT/Ci) = kT 

 Where 

 CT = concentration at time T = day zero. 

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

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 Kenaga nomogram (Hoerger and Kenaga, 1972) 

as modified by Fletcher (1994). For maximum concentrations, additional 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 dissipation data submitted to EFED are found scientifically valid and 

statistically robust for a specific pesticide, the 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 simulation. 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 derived 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 weight 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 Different 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 consume 22.8 grams of food daily (114% of its body 

weight), a 100-gram bird would consume 65 grams of food 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 selected 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 wet 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 the 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 weight 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 have markedly 

different consumption requirements. 

T-REX calculates food intake based on dry weight and wet 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 animal'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 acute values (LD50s) are adjusted because dose-based risk 

quotients are not calculated for the chronic risk estimation. 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 are used for the adjustment (U.S. EPA 1993): 

 Adjusted avian LD50: 

 AdjLD 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 animal (178g bobwhite; 1580g mallard; 350g rat) 

 AW = body weight of assessed animal (avian: 20g, 100g, and 1000g) 

 x = Mineau scaling factor for birds; EFED default 1.15 

84

 

 

Adjusted mammalian NOAELs and LD50s (note that the 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 based 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 consume more food relative to their body weight than larger animals or that 

differential amounts of food are consumed depending on the water content and nutritive value of the food. 

The dose-based risk quotients do account for these factors. 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 (mg/kg-food item) / LC50 (mg/kg-diet) 

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

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. 

AdjNOAEL 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 amount 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 information 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 concern (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 application summary. The input summary reiterates the 

parameters supplied by the user on the "input" worksheet. The other two sections calculate LD50 ft-2 

values for row/band/in-furrow applications and broadcast applications, respectively. 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 incorporation in these equations for various 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 calculated 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 determine 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 selected 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 the 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 use on rice was chosen for modeling because it had the 

highest single application rate. 

Table D4. Upper-Bound Terrestrial EECs (ppm) Estimated for Lambda-cyhalothrin in Various Food 

Items a

Crops or Crop Groups and Application Concentrations in Wildlife Food items (ppm) 

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 foliar 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 estimating pesticide residues on plants. Environ. Tox. And 

Chem. 13(9):1383-1391. 

Hoerger, F. and E.E. Kenaga. 1972. Pesticide residues on plants: correlation of representative data as a 

basis for estimation of their magnitude in the environment. IN: F. Coulston and F. Corte, eds., 

Environmental Quality and Safety: Chemistry, Toxicology 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 Screening Level Avian Risk Assessments for Spray 

Applications of Pesticides. OPP/EFED, USEPA. July 7, 2000. 

U.S. EPA. 1992. Comparative analysis of acute avian risk from granular pesticides. Office of Pesticide 

Programs. U.S. EPA. March 1992. 

USEPA. 1993. Wildlife Exposure Factors Handbook. Volume 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 foliage. Environ. Contam. Toxicol. 100:23-73. 
Appendix E. The Risk Quotient 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 effects observed in laboratory studies, when the chemical is 

used as directed. Risk quotients are expressed as the ratio of the estimated environmental concentration 

(EEC) to the species-specific toxicity reference value (TRV): 

RQ

EEC

TRV =

Units for EEC and TRV should be the same (e.g., μg/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 Riska EECb/LC50 or LD50/sqftc or LD50/dayd 0.5 

Acute Restricted Usee EEC/LC50 or LD50/sqft or LD50/day (or LD50 <50 mg/kg) 0.2 

Acute Endangered Speciesf EEC/LC50 or LD50/sqft or LD50/day 0.1 

Chronic Risk EEC/NOAEC 1 

Aquatic Animals

Acute Risk EECg

/LC50 or EC50 0.5 

Acute Restricted Use EEC/LC50 or EC50 0.1 

Acute Endangered Species EEC/LC50 or EC50 0.05 

Chronic Risk EEC/NOAEC 1 

Terrestrial and Semi-aquatic Plants

Acute Risk EEC/EC25 1 

Acute Endangered Species EEC/EC05 or NOAEC 1 

88
89

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

Risk Presumption RQ LOC

Aquatic Plants

Acute Risk EECh/EC50 1 

Acute Endangered Species EECg

/EC05 or NOAEC 1 

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

b

Estimated environmental concentration (ppm) on avian/mammalian food items c

mg/ft2

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-day 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 Endangered Species Protection Program to identify pesticides whose use 

may cause adverse impacts on endangered and threatened 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-specific mechanisms as specified by state partners. A 

final program, which may be altered from the interim 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 future 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 are necessary. Such modifications would most likely 

consist of the generic label statement referring pesticide 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 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. 
90

Appendix F. Ecological Effects Data 

These data are presented here as they were in the 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 vegetables, 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) (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 cyhalothrin in on Freshwater and Estuarine Fish 

Species Study 

Guideline 

% 

A.I. 

Toxicity Endpoint 

(95 % Confidence 

Interval) μg a.i. /L 

Toxicity 

Classification 

Study 

Classification 

MRID 

# 

Freshwater Fish

Bluegill Sunfish 

(Lepomis 

macrochirus)

72-1a 98 LC50 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 LC50 96 hr : 2.2 (1.9-2.7) 

NOAEC : 0.77 

very highly toxic Core 151601 

Bluegill Sunfish 

(Lepomis 

macrochirus)

72-1b 24 LC50 96 hr : 1.2 (1.0-1.5) 

NOAEC :0.46 

very highly toxic Core 43908812 

Rainbow Trout 

(Oncorhynchus 

mykiss)

72-1c 98 LC50 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 LC50 96 hr : 3.4 

NOAEC : N/A 

very highly toxic Core 151600 

Rainbow Trout 

(Oncorhynchus 

mykiss)

72-1d 24 LC50 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 LC50 96 hr : 0.807 (0.672-

0.967) 

NOAEC :≥0.29 (mortality) 

very highly toxic Core 153506 
91

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 sensitive to toxic effects of lambda cyhalothrin than 

estuarine/marine fish. 

 

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

Species Study 

Guideline 

% 

A.I. 

Toxicity Endpoint 

(95% Confidence Interval) 

μg 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 studies conducted using aquatic invertebrates of both 

freshwater and estuarine marine origin. In general, lambda cyhalothrin and the formulation products are 

classified as very highly toxic to aquatic invertebrates. Among the freshwater invertebrates, Gammarus 

pulex is more sensitive to lambda cyhalothrin than Daphnia magna in acute toxicity tests (EC50 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) μg a.i. /L 

Toxicity 

Classification1

Study 

Classification 

MRID # 

Freshwater Invertebrates 

Daphnia magna 72-2a 

 

96.5 EC50 48 hr :0.23 

(0.18-0.29) 

NOAEC : 0.04 

very highly toxic Core 151599 

Daphnia magna 72-2 

 

5.5 EC50 48 hr : 0.04 

 (0.03-0.06) 

NOAEC: Not established 

very highly toxic Supplemental 151602 

Daphnia magna 72-2 

 

12.9 EC50 48 hr : 0.065 

 (0.04-0.11) 

NOAEC: Not established 

very highly toxic Supplemental 151602 

Daphnia magna 72-2 

 

24 EC50 48 hr : 0.18 

 (0.14-0.23) 

NOAEC : 0.03 (immobility) 

very highly toxic Core 43908811 

Gammarus pulex 72-2a 94 EC50 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 LC50 48 hr : >590 

NOAEC : 590 

(immobility) 

highly toxic Core 152728 

Mysid Shrimp 

(Mysidopsis 

bahia) 

72-3c >97 LC50 96 hr : 0.005 

(0.004-0.006) 

NOAEC :Not established 

very highly toxic Core 152729 
93

Table F-4 presents the results from the chronic 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 indicates that mysid shrimps are more sensitive to 

lambda cyhalothrin toxicity than Daphnia. 

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

Species Study 

Guideline 

% 

A.I. 

Toxicity Endpoint 

(95% Confidence Interval) 

μg 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 cyhalothrin in aquatic vascular plants. One study conducted 

using aquatic non-vascular plant (freshwater green algae) reported the EC50 as >310 ppb. Also no studies 

are reported on non-vascular plants of estuarine/marine 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 Lambda cyhalothrin on Aquatic Plants 

Species Study 

Guideline 

% 

A.I. 

Toxicity Endpoint 

μg a.i. /L 

Study 

Classification 

MRID # 

Freshwater Non-vascular Plants 

Green Algae

Selenastrum 

capricornutum

123-2 

 

96.5 EC50 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, viable 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 LD50 : > 3950 mg/Kg BW Practically non 

toxic 

Core 151594 

Bobwhite quail 

(Colinus 

virginianus) 

71-2a 99.6 LC50 : >5300 mg/Kg diet Practically non 

toxic 

Core 151596 

Mallard duck 

(Anas 

platyrhynchos) 

71-2b 96.5 LC50 : 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 LD50 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 Studies of Lambda cyhalothrin 

Species Study 

Guideline 

% 

A.I. 

Toxicity Endpoint 

(Confidence Interval) 

Study 

Classification 

MRID # 

Rats 81-1 92.6-

96 

LD50: 79 mg/kg-bw (males) 

LD50: 56 (40-78) mg/kg-bw (females) 

Minimum 259805 

Rats 81-1 13.1 LD50: 64 mg/kg-bw (males) 

LD50: 101 (75-213) mg/kg-bw (females) 

Guideline 259805 

As EFED understands, HED has not received the developmental or reproduction toxicity studies for 

lambda cyhalothrin. In the HIARC report (November 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 Toxicity Studies of Cyhalothrin (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 study 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 highest 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 concluded 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, respectively, 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 products 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 LT50 (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 LT50 of greater than 24 hours suggest that PP321 is highly toxic to honey bees. 

 

Table F-9. Nontarget Insect Toxicity 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 

LD50 : 0.038 μg a.i./bee 

LD50 : 0.909 μg a.i./bee 

Highly Toxic 

Highly Toxic 

Core 

Core 

40052409 

40052409 

Honey bees 

(Apis 

mellifera) 

141-1 

Contact 

Oral 

5.04 

5.04 

LD50 : 0.098 μg a.i./bee 

LD50 : 0.483μg a.i./bee 

Highly Toxic 

Highly Toxic 

Core 

Core 

40052409 

40052409 

Honey bees 

(Apis 

mellifera) 

141-2 

(foliage) 

PP321 LT50 : 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 mentioned 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 should be present no appreciable hazard to honey bees 

were reported (MRID 40436303).