### 1 OFFICE OF CHEMICAL SAFETY AND POLLUTION PREVENTION **UNITED ST AT**  **ES ENVIRONMENT AL**  **PROTECTION A GENCY** 

WA SHINGTON, D.C. 20460



### PC Code : 288202 DP Barcode : D 391853 **MEMORANDUM DATE:**  November 4 , 2011 **SUBJECT:** [ Revised to Include Leafy Petioles ] Estimated Drinking Water Concentrations for Cy prodinil and its Metabolite CGA
- 249287 for the New Use of the Chemical on Various New Tree Nuts, Bulb Onion , Green O nion , Le af y Vegetable (Except B rassica), Leafy

Petioles, Fruiting Vegetable, Pome Fruit, Caneberry , Bushberry , Small Fruit Climbing (Except Fuzzy Kiwifruit), Low Growing Berry (Except Cranberry) and Dragon Fruit **FROM:** José L
. Meléndez, Chemist

Environmental Risk Branch V Environmental F ate and Effects Division (7507P) **THROUGH:** Mah T. Shamim, Ph.D., Branch Chief

Environmental Risk Branch 5 Environmental Fate and Effects Division (7507P) **TO:** Lisa Jones, Risk Manager Reviewer

Shaha Joy

ner , Risk Manager #2 0 Cy nthia Giles
- Parker**,** Branch Chief Fungicide Branch Laura Nollen, Risk Manager Reviewer Barbara Madden, Risk Manager #05 Daniel Rosenblatt, Branch Chief Risk Integration, Minor Use and Emergency Response Branch Registration Division (7505P) **AND:** Thurston Morton, Chemist

Christine Olinger, Acting Branch Chief Risk Assessment Branch 4 Health Effects Division (7509P)

### 2

This memo presents the Estimated Drinking Water Concentrations (EDWCs) for cy prodinil, an active ingredient of Vangard ® 

### WG, Switch TM 

### 62.5, and Inspire SuperTM Fungicides, and its metabolite CGA
- 249287
. Itwas revised to include leafy petioles (subgroup 4B), which were not included in the June 30, 2011 drinking waters assessment (DWA) ( D 385884+). Base d on a review of the use information, it was found that all the newly proposed crops have a similar or lower application rate than the maximum application rate of 0.47 lb a.i./A applied 3 times/year, or 1.4 lb a.i./A/year, previously modeled using the New York grapes scenario
. EDWCs for the new uses should be similar than those already calculated for grapes; therefore, a new DWA is not required. The values reported in the previous assessment can be used to cover the new crops. An electronic cop y of the p revious DWA is provided in **Attachment A** (DP Barcode D 382086 ) , which also provides structures and nomenclature of cy prodinil and its metabolite CGA
- 249287 ( as per the Metabolism Assessment Review Committee’s (MARC) decision document)
. T he tier 2 aquatic mo dels PRZM/EXAMS and the tier 1 model SCI
- GROW were used to obtain EDWCs in surface water and groundwater, respectively . The acute EDWC in surface water is 34.79 μg/L for the total residues of cy prodinil and CGA
- 249287 ( i.e. , cy prodinil + CGA
249287). The chronic EDWC in surface waters is 24.65 μg/Lfor the total residues of cy prodinil and CGA
- 249287. The cancer/chronic EDWC in surface waters is 16.38 μg/L for the total residues of cy

prodinil and CGA
- 249287. All surface waters EDWCs were obtained using the New York grapes PRZM scenario. The SCI
- GROW generated EDWC for the use on grapes is 0.0861 μg/L for the total residues of cy prodinil and CGA
- 249287. The summary of the results is presented in the **Table 1** of the **Attachme nt A** 
. For details on methods, characterization of results, uncertainties, etc. , please, refer to the **Attachment A**
. Should it be required, additional refinements may be available. For example, regional PCAs and ty pical use rates may

be options to be used should it be requested b y HED. **Identification of specific data gaps** : The environmental fate data base for cy prodinil is considered substantiall y complete; there are no new data available for this assessment. There is uncertainty with the aqueous photoly sis study (MRID 43908422 ) . It was carried out with natural (unsterilized) water. Phototransformation of cy prodinil in the irradiated samples followed a biphasic pattern, with slow transformation at the beginning. The possibility of microbial tran sformation is not ruled out. For modeling purposes, it was assumed that cy prodinil is stable to aqueous photoly sis, which is a conservative assumption. **Use information:** Three end
- use products are involved in this DWA , as follow s. One product contains only cy prodinil, while two of the products have another active ingredient :

 **Vangard ®**  **WG Fungicide** (EPA Reg. No. 100
- 828), containing 75.0% cyprodinil A
. I
. and 25.0% other ingredients  **Switch® 62.5G Fungicide** (EPA Reg. No. 100
- 953) containing 37.5% cyprodini l A
. I
. , 25.0% fludioxonil A
. I
. and 37.5% other ingredients

### 3

 **Inspire SuperTM Fungicide** (EPA Reg. No. 100
- 1317) contain ing 24.1% cy prodinil A
. I
. , 8.4% difenoconazole A .I. and 67.5% other ingredients A previous DWA, dated November 8, 2010 ( **Attachment A** ) , involved only the products Vangard® WG and Switch® 62.5G Fungicides and the request to appl y a maximum of two times aerially

the product to most of the crops. The registrant also requested the approval of chemigation method of application for several of the crops. One of the proposed changes evaluated in this DWA , for the products Vangard® WG and Inspire SuperTM Fungicides , is a tolerance petition to include several nut trees , crop group 14 . These are added crops besides almonds and pistachios , which are already approved for cy prodinil
. Furthermore, it is proposed to reduce the pre
- harvest interval for almonds from 60 days to 14 day s . However, the maximum application rate on tree nuts is the same than previously assessed for almonds. In a separate request (IR
- 4 tolerance petition) involving all three product labels, the registrant is proposing to add the following crops groups to the labels:  Bulb onion subgroup 3
- 07A  Green onion subgroup 3
- 07B  Leafy vegetable subgroup 4A, except brassica  Le afy petioles subgroup 4B 

###  Fruiting vegetable group 8
- 10  Pome fruit group 11
- 10  Caneberry

subgroup 13
- 07A  Bushberry

subgroup 13
- 07B  Small fruit climbing subgroup 13
- 07F, except fuzzy kiwifruit  Low growing berry

subgroup 13
- 07G, except cranberry  Dragon fruit **Tab le**  **1** provides a summary of the use information for the pesticide cy prodinil ( i.e. , the table does not include the other two active ingredients). Generally , n o more than two sequential applications are allowed as part of a resistance management strategy (unless otherwise stated for a crop). The label require s a buffer zone to protect lakes, reservoirs, rivers, permanent streams, marshes or natural ponds, estuaries and commercial fish ponds. For ground applications the buffer zone is 75 ft ; meanwhile , fo r aerial applications the buffer zone is 150 ft
. A vegetative filter strip should be allowed within 10 ft of aquatic areas. Furthermore, other measures of precaution are required ( e.g. a pplications when gusts or sustained wind s exceed 1 0 mph are not allo wed). The following crops were previousl y modeled . All the crops for which aerial applications are allowed were modeled using all aerial applications as the most conservative scenario.  CA almond (covers tree nuts crop group 14 )  NY grape (covers grapes and associated crops)  CA fruit (covers pome fruits)

### 4

 MIcherry

(despite having a lower single app lication rate, it has the same max imum seasonal rate ; thus, it covers other stone fruits )  GA onion (covers crops under the onion group)  FL strawberry

(covers crops under the strawberry and other berries category)  PA tomato (covers crops under the fruiting vegetables category)  OR Snap Bean, MO Melon and NC sweet potato (they have the same application rate than leafy vegetables and leafy pet ioles ; thus, they co ver the new crop s)  CA fruit and MI cherry covers the new crop dragon fruit Since previously

modeled crops cover the new proposed crops, the results of the previous DWA can be used for the new uses. **Table 1**  **. Summary of use information for cyprodinil, based on Vangard**  **®** 

### WG (EPA Reg. No. **100 -**  **828) , Switch® 62.5G**  **(EPA Reg. No. 100 -**  **953) and Inspire SuperTM (EPA Reg. No. 1317)**  **Fungicides .**  **Changes or new crops are shaded blue**  **. Scenarios that**  **we re previously modeled**  **are shaded yellow**  **. U**  **se S**  **ingle App Rate**  **(lb a.i./A) Number of** 

**Apps .**  **Y early App.** 

**Rate (lb a.i./A)**  **I nterval** 

**B etween**  **Apps . (days)**  **App**

**Method Pre**  **- H**  **arvest**

**I nterval**  **(days)** Almond ( CA almond) 0.47 3 1.4 NS or 14 (1) G, A ***** 14 Pistachio 0.33 4 1.3 14 G, A ***** 7 Tree Nuts (beech, Brazil nut, butternut, cashew, chestnut, chinquapin, filbert (hazelnut), hickory nut, macadamia nut, pecan, walnut (black and English)) 0.47 3 1.4 NS (2) G, A ***** 14
Citrus (lemon, lime) 0.33 1 0.33 N/A G 0 Grapes (NY Grape ) (including cultivars, varieties, and/or hybrids of these; Amur river grape, hardy kiwifruit, maypop, schisandra berry ; and muscadines, gooseberry for I nspire SuperTM only) 0.47 3 1.4 7 G, A ***** (5) 7 ;

( 14 days for Inspire SuperTM only) Kiwi 0.47 2 0.94 7 G, A ***** 0 Pome Fruits ( CA fruit) (apples, azarole, crabapples, loquat, mayhaw, medlar, pears, Asian pear, quince , Chinese quince, Japanese quince, tejocote and cultivars, varieties and/or hybrids of these ) 0.23 5
- 6 1.4 7 G, A ***** (6) 0

Stone Fruits ( MI Cherry) (apricot, tart cherries, nectarines, peaches, plums, prunes) 0.23, 0.47 in CA 6,

3 in CA 1.4

1.4 in CA NS

(3) G, A ***** 2 Tropical Fruits ( Dragon fruit , lychee, longan, Spanish lime, rambutan, pulasan , avocado, black sapote, canistel, mamey sapote, mango, papaya, sapodilla and star apple ) 0.33 4 1.3 7 G, A ***** (5 ) 0
Beans (dried and succulent, except cow peas) ( OR Snap Bean) (garbanzo bean or chickpea, grain lupin bean, sweet lupin bean, white lupin bean, white sweet lupin bean, kidney bean, lima bean, mung bean, navy bean, pinto bean, snap bean, wax bean, fava bean, asparagus bean and blackeyed pea) 0.33 4 1.3 7 G, A ***** , C 7

### 5

**Table 1**  **. Summary of use information for cyprodinil, based on Vangard**  **®** 

### WG (EPA Reg. No. **100 -**  **828) , Switch® 62.5G**  **(EPA Reg. No. 100 -**  **953) and Inspire SuperTM (EPA Reg. No. 1317)**  **Fungicides .**  **Changes or new crops are shaded blue**  **. Scenarios that**  **we re previously modeled**  **are shaded yellow**  **. U**  **se S**  **ingle App Rate**  **(lb a.i./A) Number of** 

**Apps .**  **Y early App.** 

**Rate (lb a.i./A)**  **I nterval** 

**B etween**  **Apps . (days)**  **App**

**Method Pre**  **- H**  **arvest**

**I nterval**  **(days)** Berries : (including all cultivars and/ or hybrids of these) Bushberries (aronia berry, black currant, blueberry high and low bush, Buffalo currant, Chilean guava, currant, edible honeysuckle , elderberry, European barberry, gooseberry, high bush cranberry, huckleberry, jostaberry, juneberry (Saskatoon berry), lingonberry, native currant, red currant, salal, sea buckt horn) Caneberries (blackberry, loganberry, red and black raspberry , wild raspberry) 0.33 4 1.3 7 G, A ***** (5 ) 0

Brassica (cole) leafy vegetables (broccoli, Chinese broccoli, broccoli raab, Brussel sprouts, cabbage, Chinese cabbage, cauliflower, cavalo broccolo, collards, kale, kohlrabi, mizuna, mustard greens, mustard spinach, rape greens and turnip greens) 0.33 4 1.3 7 G, A ***** , C 7

Cucurbit Crops ( MO Melon) ( cantaloupe, cucumber, guourds, honeydew, muskmelon, watermelon, chayote, Chinese waxgourd, Momordica spp
. (bitter melon, balsam apple) , pumpkin, squash and zuc chini ) 0.33 4 1.3 7 G, A ***** , C 1
Herbs, Dried and Fresh (angelica, balm, basil, borage, burnet, camomille, catnip, dried chervil leaves, chive, clary, coriander leaves {cilantro} , costmary, culantro leaves, curry leaves, dillweed, horehound, hyssop, lavender, lemongrass, lovage leaves, marigold, marjoram, nasturtium, dried parsley leaves, pennyroyal, rosemary, rue, sage, summer and winter savory, sweet bay, tansy, tarragon, thyme, wintergreen, woodruff and wormwood) 0.33 4 1.3 7 G, A ***** , C 7

Leafy Vegetables (except brassica) (head and leaf of lettuce, amaranth, arugula, chervil, edible chrysanthemum, corn salad, cress, dandelion, dock, escarole endive (escarole), New Zealand spinach , orach, parsley, purslane, radicchio , spinach, spinach vine ) Leafy Petioles ( Cardoon celery; celery; Chinese celery; celtuce; Florence fennel; rhubarb; Swiss chard) 0.33 4 1.3 7 G, A ***** , C (7) 0

Leaves of Root and Tuber Vegetables (NC Sweet Potato ) (carrot, garden beet, sugar beet, edible burdock, cassava, celeriac, chicory, dasheen, parsnip, Oriental radish, rutabaga, black salsify, Spanish salsify, sweet potato, tanier, turnip rooted chervil, true yam) 0.33 4 1.3 (4 ) 7 G, A ***** , C 7

Root Vegetables (except sugar beet) (edible burdock, carrot, celeriac, chicory, garden beet, ginseng, horseradish, parsnip, Oriental radish, rutabaga, black salsify, Spanish salsify, skirret, turnip, turnip root parsley, turnip rooted chervil) 0.33 4 1.3 (4 ) 7 G, A ***** , C 7

### 6

**Table 1**  **. Summary of use information for cyprodinil, based on Vangard**  **®** 

### WG (EPA Reg. No. **100 -**  **828) , Switch® 62.5G**  **(EPA Reg. No. 100 -**  **953) and Inspire SuperTM (EPA Reg. No. 1317)**  **Fungicides .**  **Changes or new crops are shaded blue**  **. Scenarios that**  **we re previously modeled**  **are shaded yellow**  **. U**  **se S**  **ingle App Rate**  **(lb a.i./A) Number of** 

**Apps .**  **Y early App.** 

**Rate (lb a.i./A)**  **I nterval** 

**B etween**  **Apps . (days)**  **App**

**Method Pre**  **- H**  **arvest**

**I nterval**  **(days)** Bulb Onion ( GA Onion) ( Chinese onion, dry bulb onion, daylily bulb, Fritillaria bulb , garlic, great headed garlic, lily bulb, pearl onion, potato onion, serpent garlic, shallot) Green Onion (Beltsville bunching onion, Chinese chive fresh leaves, fresh chive leaves, Fritillaria leaves, fresh onion, green onion, Hosta elegans, Kurrat, lady’s leek, leek, macrostem onion, shallot fresh leaves, tree tops onion, Welsh onion tops, wild leek, wild onion) Onions Grown for Seed 0.47 3 at 0.43 1.3 7 G, A ***** , C (7) 7

Straw berries ( FL Strawberry) (including cultivars, varieties, and/or hybrids of these, bearberry, bildberry, cloudberry, mountries, partridgeberry) 0.47 3 at 0.43 1.3 7 G, A ***** , C (5) 0
Tomato es, Peppers, Eggplant and Other Fruiting Vegetables ( PA Tomato ) (African eggplant, bush tomato, bell pepper, cocona, currant tomato, eggplant, garden huckleberry, Goji berry, groundcherry, Martynia, naranjilla, okra, pea eggplant, pepino, bell pepper, nonbell pepper, Roselle, scarlet eggplant, sunberry, t omatillo , tomato, tree tomato) 0.33 4 1.3 7 G, A ***** , C 0

Watercress 0.33 4 1.3 7 G, C 0 G = ground; A ***** = Aerial ( maximum of two aerial applications allowed); C = Chemigation ; NS = Not specified. (1). For Vangard® WG o ne application at 5
- 10% bloom, 50
- 100% bloom and at petal fall. For Inspire SuperTM the minimum retreatment interval is 14 days and the maximum single application rate is 0.33 lb a.i./A. (2 ). Apply when conditions are conducive to disease
. It is noted that the supplemental labels for Switch® 62.5G and Inspire Su perTM do not have this crop group. (3 ). One application at bloom stage, second application at full bloom, in CA, two applications during the preharvest period. (4 ). For radish, only 2 applications per crop and 4 applications per year. (5). The supplemental label for Switch® 62.5G only indicates that only one aerial application is allowed, and only in CA
. Otherwise, only ground applications are allowed for the product. (6). This crop group not included in the supplemental label for Switch® 62.5G. (7). The supplemental label for Inspire SuperTM does not have these crop groups.

### 7 **Attachment A .**  **Electronic Copy of Previous DWA**  **UNITED STA TES ENVIRONMENTA**  **L PROTECTION A GENCY** 

**WA SHINGTON, D.C. 20460** 
**OFFICE OF CHEMICAL SAFETY**  **AND POLLUTION**  **PREVENTION**



### PC Code : 288202 DP Barcode : D 382086 **MEMORANDUM DATE:**  November 8 th 

### 2010 **SUBJECT:** Estimated Drinking Water Concentrations for C yp rodinil and its Metabolite

CGA
- 249287 for the Section 3 New Use of the Chemical on Multiple Crops by Aerial and Chemigation Methods of Application **FROM:** José Luis Meléndez, Chemist

Environmental Risk Branch V Environmental Fate and Effects Division (7507P) **THROUGH:** Mah T. Shamim, Ph.D., Chief

Environmental Risk Branch 5 Environmental Fate and Effects Division (7507P) **TO:** Lisa Jones, Risk Manager Reviewer

Mary Waller, Risk Manager #21 Cy nthia Giles
- Parker**,** Chief Fungicide Branch Registration Division (7505P) **AND:** Ray

Kent, Chief Risk Assessment Branch 4 Health Effects Division (7509P) This memo presents revised Estimated Drinking Water Concentrations (EDWCs) for cy prodinil, an active ingredient of S witch TM 

### 62.5 and Vangard ® 

### WG Fungicides ) , and its metabolite CGA
249287 , 1 

### ba sed on a maximum appl ication rate of 0.47 lb a.i./A applied 3 times/ye ar, or 1.4 lb a.i./A/year, on grapes . The models PRZM/ EXAMS and SCI
- GROW were used in obtaining EDWCs in surface water and groundwater, respectively
. The acute EDWC in surface water i s 34.79 μg/L for the total residues of cy prodinil and CGA
- 249287 ( i.e. , cy prodinil + CGA
249287). The chronic EDWC in surface waters is 24.65 μg/Lfor the total residues of cy prodinil and CGA
- 249287. The cancer/ chronic EDWC in surface waters is 16.38 μg/L for the total residues of cy

prodinil and CGA
- 249287. All surface waters EDWCs were obtained using the
1 For the structures and nomenclature of cyprodinil and CGA
- 249287, refer to the **Appendix**
.

### 8

New York grapes PRZM scenario. The SCI
- GROW generated EDWC for the use on grapes is 0.0861 μg/L for the total residues of cy prodinil and CGA
- 24928 7. The summary of the results is presented in the **Table 1**
. **EXECUTIVE SUMMARY** Cy prodinil ( CAS name 4
- cycloprop yl
- 6
- methyl
-N
- phen yl
- 2
- py

rimidinamine; IUPAC name 4
- cyclopropyl
- 6
- methyl
-N

- phenylpy

rimidin
- 2
- amine ; PC code 288202 ; and CAS number 121552
- 61
- 2 ) is a py

rimidine fungicide. Cy

prodinil has been classified by the Fungicide Resistance Action Committee (FRAC) as a FRAC Code 9 fungicide, using their classification scheme of fungicides according to m ode of a ction (MOA or MoA). The MOA is inhibition of aminoacids and protein s ynthesis ( Group Name AP or anilino py rimidine ; Chemical group name anilino py rimidine; Resistance risk: Medium) <http://edis.ifas.ufl.edu/PI131 , accessed 10/01/2010 >. The active ingredient of this fungicide belongs to the chemical class of anilino
- py rimidines and exhibits a systemic mode of action with no cross resistance to currentl y used disease control products. The s ys temic action of cy prodinil comes from its lipoph ilic properties. It is easil y absorbed into and across the cuticle and wax layers of leaves and fruits from where it continuously

distributes and penetrates into other plant parts. Biochemical studies indicate that the MOA for cy

prodinil comes from its int erference with biosy nthesis of methionine. Itmay also impede the secretion on fungal hydrol yt ic enzy mes, thus resulting in impaired fungal pathogenesis and growth. Currently , cy

prodinil is used in a variety of crops such as beans, berries, brassica (col e) leafy vegetables, carrots, herbs, leafy vegetables (except brassica and spinach), onions, strawberries, tomatoes, herbs, various tropical fruits, root vegetables, cucurbit vegetables, kiwifruit, lemon and watercress. Presently , this pesticide is applie d by ground methods only , except in California, where the label includes one aerial application per season for some crops
. This action involve s only the product Vangard ® 

### Fung icide, with the active ingredient cy prodinil. Another product, SwitchTM Fungicide, contains the active ingredients cy prodinil and fludioxonil; however, it is not included in this action. This is a drinking water assessment (DWA) for the Section 3 product registration of the aerial and chemigation applications of cyprodinil o n the following crops: A m aximum of two aerial applications allowed per year (additional applications via ground methods also allowed, depending on the crop): almonds, grapes, kiwi, pistachios, pome fruits, stone fruits, tropical fruits and berries. A m aximum of two aerial applications allowed per year ( additional applications via ground methods also allowed, depending on the crop ) and/ or chemigation applications : dried and succulent beans (except cowpeas), brassica (cole) leafy vegetables, cucurbit vege tables, dried and fresh herbs, leafy

vegetables (except brassica and spinach), leaves of root and tuber vegetables (including sugar beets), root vegetables (except sugar beet), onions and garlic, strawberries and tomatoes & tomatillos. C hemigation application s (also applications via conventional ground methods allowed):

### 9

watercress. There are no changes for cy prodinil on citrus ( i.e. , lemon and lime), for which only ground applications are allowed. A s creening
- level DWA for cy prodinil is presente d in this document. For surface waters the linked PRZM/ EXAMS tier 2 aquatic models were used, and for ground waters, the tier 1 aquatic model SCI
- GROW was utilized. For the assessment, maximum application rates and minimum intervals between applications were used. In the Metabolism Assessment Review Committee’s (MARC) decision document it was concluded that the transformation product of cy prodinil, CGA
- 249287 (4
- cyclopropyl
- 6
- methylpy rimidin
- 2
- amine) is of potential concern for drinking water sources. Therefore, EDWCs of CGA
- 249287 were also simulated using the PRZM/ EXAMS and SCI
- GROW models. For surface waters, this degradate and its parent were modeled individually ( i.e. , using the residue summation or RS approach , as opposed to the total residue or TR approach) (note: the RS approach is described in the Anal ys is Plan and Anal ys is sections of this DWA). This was done because a single degradate was modeled and sufficient environmental fate and phy sicochemical characteristic information was available for modeling. Furthermore, the solubility , persistence and mobility characteristics of parent and degradate were different and their structures differ (refer to the **Appendix** for structures). Although the maximum EDWC resulted from the use on grapes in NY , this DWA is based on the use o f multiple crop locations and multiple crop uses, representative of the maximum seasonal application rate. Represented states included CA, NY, MI, OR, MO, NC, GA, FL and PA and represented crops included almonds, fruits (po me and stone fruits ), grapes, cherries, snap beans, melons, sweet potatoes, onions, strawberries and tomatoes
. Two uncertainties are worth mentioning related to the RS approach: first, the approach assumes that the maximum concentration of CGA
- 249287 occ urs at the time of application (CGA
- 249287 was actuall y a maximum at 28 day s posttreatment in the aerobic soil metabolism study ), and second, CGA
- 249287 was assumed to be stable to some routes of degradation for which there was no fate data available. The environmental fate data base for cy prodinil is essentially

complete. There is uncertainty with the aqueous photolysis study . It was carried out with natural (unsterilized) water. Phototransformation of cy prodinil in the irradiated samples followed a biphasic pattern, with slow transformation at the beginning. The possibility of microbial transformation is not ruled out. There is also uncertainty with the soil photodegradation study . It is suspected that there was microbial transformation instead of p hotodegradation. The amount of cy prodinil in the irradiated and dark control samples were similar. Of these uncertainties in the fate database, onl y the aqueous photoly sis may

have an effect on the modeled EDWCs for cy prodinil because it is a direct input parameter in the model. For modeling purposes, it was assumed that cy prodinil and its degradate are stable to aqueous photoly sis, which is a conservative assumption. In this assessment EDWCs may be overestimates because onl y two aerial applications are proposed for the application of cy prodinil on grapes with a third application via ground. In this assessment, all three applications were assumed to be aerial.

### 10

**Table 1** provides a summary of the Tier 2 modeled drinking water concentrations. **Table 1. Maximum**  **E stimated**  **D rinking**  **W ater**  **C oncentration**  **s for the Use of Cyprodin i**  **l (expressed as total residue**  **s of cyprodinil plus its degradate**  **CGA -**  **249287 )**  **DRINKING WATER SOURCE (MODEL USED)**  **USE (rate modeled per year**  **) MAXIMUM ESTIMATED DRINKING WATER**  **CONCENTRATION (EDWC) ( ppb**  **)** Groundwater (SCI
- GROW) Grapes (1.4 lb a.i.) Ac ute and Chronic 0.0861 Surface water (PRZM/ EXAMS) NY grapes (1.4 lb a.i.) Ac ute 34.79 Chronic 24.65 Cancer/Chronic 16.38 

### The National Water Quality Assessment (NAWQA) data warehouse does not have monitoring data on cy

prodinil. The STORET (short for Storage Retrieval) database does contain some monitoring data. Should it be required, additional refinements may be available. For, example, regional PCAs and ty pical use rates may

be used should it be requested by the HED. **PROBLEM FORMULATION Background**  In a previous drinking water assessment, dated 12/ 16 /20 03 , e stimated drinking w ater c oncentrations (EDWCs) of cy prodinil and its metabolite CGA
- 249287, due to the proposed use of the chemical on leafy

greens, subgroup 4A (except spinach), snap, dry and succulent beans, and almonds. In a later review dated 09/12/2006, on the use of the chemical on various crops , using aerial applications in the state of California , p reliminary results indicated that EDWCs were of similar order of magnitude than the 2003 review . Therefore, the EFED rel ied on its 2003 drinking w ater analy sis using the Oregon s nap b eans scenario
. On 05/02/2008, the EFED issued a new DWA for new uses on various new crops. The resulting highest EDWCs were for the NY grape scenario. Later, in a 12/10/2009 DWA, the EFED relied on the 2008 DWA for EDWCs. The environmental fate data base for cy prodinil is considered substantiall y complete; there are no new data available for this assessment. The molecular weight of cy prodinil is 225.29 g/mol. It is ‘ readil y solu

ble ’ in water (13 ppm at pH 7, FAO 2000). From its octanol/ water partition coefficient, it seems likely to partition with organic tissues and other organic media. It is alkaline in water (pH 9.5 and pKa = 4.44). Finally, it is not likely to volatilize substantially , with a vapor pressure of 3.80x10 - 6 

### mmHg and a Henry ’s L aw constant of 7.04x10 - 8 

### Atm
- m 3 

### /mol at 20°C. Cy prodinil binds to sediment and particulate. It appears to be a persistent compound under most conditions, except aerobic soil metabolism, as demonstrated in laboratory studies. Cy prodinil appears to bind strongl y to particulate and sediment, showing relatively low soil mobility (K OC 

### range 1550 to 2030); its potential for groundwater contamination appears to be low. However, due to its high persistence under aquatic conditions, aquifers that lie below areas that have low organic content and coarse textured soils or shallow leaky aquifers could be prone to contamination. Even though buffer zones can ameliorate moderately the level of spray drift, the potential for runoff still exists for long periods of time. Cy prodinil ’ s high affinity

to sorb to

### 11

soil and particulate suggests the potential for runoff in eroded particles. This stability and binding to particulate and organic matter (mainly under anaerobic conditions) suggests that cy prodinil residues in sediments could contribute to a possible resuspension of the compound through mixing and mass balance for an extended period
. One d egradates of cy prodinil has been considered of concern, C GA
- 249287 (moderately mobile) (maxima 11.7% at 28 day s in the aerobic soil metabolism study and 14.2% in the aerobic aquatic metabolism study)
. **Use Characterization Table 2**  is a summary of all agricultural use patterns for cy prodinil. The use information was obtained from the current and proposed labels for Vangard ® 

### WG
. The proposed changes are bolded and highlighted **yellow**
. **Table 2**  **. Summary of use information f or cyprodinil, based on Vanguard**  **®** 

### WG Fungicide **label (EPA Reg. No. 100 -**  **828)**
**USE SINGLE**  **APP. RATE (lb a.i./A)**  **NUMBER**

**OF APPS. YEARLY** 

**APP. RATE (lb a.i./A)**  **INTERVAL**

**BETWEEN APPS. (days)**  **APP.**

**METHOD (**  ***** **) Pre**  **- H**  **arvest**

**I NTERVAL**  **(days)** Almond 0.47 3 1.4 NS (1) G, **A** 60 Citrus (lemon, lime) 0.33 1 0.33 N/A G 0 Grapes 0.47 3 1.4 7 G, **A** 7 Kiwi 0.47 2 0.94 7 G, **A** 0 Pistachio 0.33 4 1.3 14 G, **A** 7 Pome Fruits (apples, crabapples, loquat, mayhaw, pears, quince) 0.23 5
- 6 1.25# 7 G, **A** 0 Stone Fruits (apricot, tart cherries, nectarines, peaches, plums, prunes) 0.23, 0.47 in CA 6,

3 in CA 1.4

1.4 in CA NS (2) G, **A** 2 Tropical Fruits (lychee, longan, Spanish lime, rambutan, pulasan , avocado, black sapote, canistel, mamey sapote, mango, papaya, sapodilla and star apple ) 0.33 4 1.3 7 G, **A** 0 Beans (dried and succulent, except cow

peas) (garbanzo bean or chickpea, grain lupin bean, sweet lupin bean, white lupin bean, white sweet lupin bean, kidney bean, lima bean, mung bean, navy bean, pinto bean, snap bean, wax bean, fava bean, asparagus bean and blackeyed pea) 0.33 4 1.3 7 G, **A, C** 7

Berries ( Bushberries: blueberry, currant, elderberry, gooseberry, huckleberry, Caneberries: blackberry, loganberry, red and black raspberry, Juneberry , Ligonberry and Salal ) 0.33 4 1.3 7 G, **A** 0
Brassica (cole) leafy vegetables (broccoli, Chinese broccoli, broccoli raab, Brussel sprouts, cabbage, Chinese cabbage, cauliflower, cavalo broccolo, collards, kale, kohlrabi, mizuna, mustard greens, mustard spinach, rape greens and turnip greens) 0.33 4 1.3 7 G, **A, C** 7

### 12

**Table 2**  **. Summary of use information f or cyprodinil, based on Vanguard**  **®** 

### WG Fungicide **label (EPA Reg. No. 100 -**  **828)**
**USE SINGLE**  **APP. RATE (lb a.i./A)**  **NUMBER**

**OF APPS. YEARLY** 

**APP. RATE (lb a.i./A)**  **INTERVAL**

**BETWEEN APPS. (days)**  **APP.**

**METHOD (**  ***** **) Pre**  **- H**  **arvest**

**I NTERVAL**  **(days)** Cucurbit Crops ( cantaloupe, cucumber, guourds, honeydew, muskmelon, watermelon, chayote, Chinese waxgourd, Momordica spp
. (bitter melon, balsam apple) , pumpkin, squash and zuchini ) 0.33 4 1.3 7 G, **A, C** 1

Herbs, Dried and Fresh (angelica, balm, basil, borage, burnet, camomille, catnip, dried chervil leaves, chive, clary, coriander leaves {cilantro} , costmary, culantro leaves, curry leaves, dillweed, horehound, hyssop, lavender, lemongrass, lovage leaves, marigold, marjoram, nasturtium, dried parsley leaves, pennyroyal, rosemary, rue, sage, summer and winter savory, sweet bay, tansy, tarragon, thyme, wintergreen, woodruff and wormwood) 0.33 4 1.3 7 G, **A, C** 7

Leafy Vegetables (except brassica and spinach) (head and leaf of lettuce, amaranth, arugula, chervil, edible chrysanthemum, corn salad, cress, dandelion, dock, escarole endive, orach, parsley, purslane, radicchio) 0.33 4 1.3 7 G, **A, C** 0

Leaves of Root and Tuber Vegetables (carrot, garden beet, sugar beet, edible burdock, cassava, celeriac, chicory, dasheen, parsnip, Oriental radish, rutabaga, black salsify, Spanish salsify, sweet potato, tanier, turnip rooted chervil, true yam) 0.33 4 1.3 (3) 7 G, **A, C** 7

Root Vegetables (except sugar beet) (edible burdock, carrot, celeriac, chicory, garden beet, ginseng, horseradish, parsnip, Oriental radish, rutabaga, black salsify, Spanish salsify, skirret, turnip, turnip root parsley, turnip rooted chervil) 0.33 4 1.3 (3) 7 G, **A, C** 7

Onions (dry bulb, green, onions grown for seed) 

### , Garlic 0.47 3 at 0.43 1.3 7 G, **A, C** 7 Straw berries 0.47 3 at 0.43 1.3 7 G, **A, C** 0 Tomato & Tomatillo 0.33 4 1.3 7 G, **A, C** 0 Watercress 0.33 4 1.3 7 G, **C** 0 **(*** **)** G = ground; **A = Aerial ( maximum of two aerial applications allowed**  **); C = Chemigation**  ; NS = Not specified. #Maximum rate per year was slightly decreased from 1.4 lb a.i./A. (1). One application at 5
- 10% bloom, 50
- 100% bloom and at petal fall. (2). One application at bloom stage, second application at full bloom, in CA, two appli cations during the preharvest period. (3). For radish, only 2 applications per crop and 4 applications per year. 

### Presently , this pesticide is applied by ground methods only , except in California, where the label includes one aerial application per season for some crops . It is noted, that some of the proposed crops may

be rotated or planted more than once a year ( e.g. lettuce, Brussels sprouts, cab b age and carrot s ). However, the rates indicated in the fourth column in **Table 2**  are actuall y the rates allow ed per ye ar. Thus, for crops that are planted more than once a year, the derived EDWCs are not underestimations. The label require s a buffer zone to protect lakes, reservoirs, rivers,

### 13

permanent streams, marshes or natural ponds, estuaries and commercial fish ponds. For ground applications, the buffer zone is 75 ft ; while f or aerial applications, the buffer zone is 150 ft. A vegetative filter strip should be allowed within 10 ft of aquatic areas. Furthermore, other measures of precaution are required ( e .g. a pplications when gusts or sustained wind s exceed 1 0 mph are not allowed)
. No more than two sequential applications are allowed as part of a resistance management strategy
. The use patterns selected for modeling involved the highest application rate s : e.g. , for grapes , the highest application rate and minimum interval were used (three applications at 0.47 lb a.i./A per application at 7
- day

intervals)
. Since aerial and ground applications cannot be modeled together with PRZM/ EXAMS, it was assumed that all three applications were aerial although the label calls for a maximum of two aerial applications and one ground application. **Figure 1** provides the 2002 estimated annual agricultural use of cy prodinil. Major use crops for cy prodinil in 2002 were grapes (~ 42% of national use, with over 50,000 pounds of the chemical applied) and almonds (~32% of national use, with over 35,000 pounds of active ingredient applied). Major use areas were at the time, C A , the west coast zone (OR, ID) , the Midwest (MI and WI) , the east coast zone (VA, NC) , the northeast and portions of central F L
. At this time, there are no readil y available more current usage and typical use data, such as typical application rate, number of applications, or interval between applicatio ns.

**Fig. 1. 2002 Estimated Annual Agricultural Use for Cyprodinil 2**  **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 - lev el estimates of pesticide use rates for individual crops that were compiled by the CropLife Foundation, Crop Protection Research Institute du ring based on information collected during 1999 through 2004 and on 2002 Census of Agriculture county crop acreage. The maps do not represent a
2 Available at http://water.usgs.gov/nawqa/pnsp/usage/maps/ (accessed 10/01/2010).

### 14

specific year, but rather show typical use patterns over the five year period 1999 through 2004. Use intensity rates are expressed as the pounds applied per square mile of mapped agricultural land in a county. The area of mappe d 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 th ese maps include the follow ing: (1) state use coefficients represent an average fo r the entire state and consequently do not reflect the local variability of pesticide management practices found w ithin states and counties, (2) pesticide use estimates are not for a specific year, but represent typical use patterns for the five year perio d, (3) state pesticide use coefficients may not have been available for all states w here a pesticide may hav e been applied to agricultural land, and therefore, are not displayed on the maps, (4) the county crop acreage is based on the 2002 Census of Agricu lture 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 that may over esti mate 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 Metho d for Estimating Pesticide Use for a detailed discussion of how the pesticide use data were developed. 

### Conceptual Model For cy prodinil, the following drinking water hy pothesis is being employed for this assessment: Cyprodinil use in accordance with the label, results in potential contamination of, both, surface and ground water resources. It may also result in the contamination of surface and ground water resources with the major degradate of concern CGA
- 249287. The conceptual site model is a generic graphic depiction of the risk hy pothesis ( **Figure 2** )
. Through a preliminary

iterative process of examining available data, the conceptual model ( i.e. , the risk hy

pothesis) has been refined to reflect the likely exposure pathways that are most relevant and applicable to this assessment (refer to the following figure).

**Figure 2. Conceptual Site Model for Cyprodinil** Cy prodinil is applied to the field and there may be crop absorption since the chemical is sy stemic (the chemical is absorbed through the cuticle and wax layers of leaves and fruits because it is lipophilic). In addition, spray drift is an important factor in the contamination of nearb y surface waters. As the field may be kept irrigated, large runoff events accompanied with erosion may be a factor in horizontal movement due to the tendency of the chemical to sorb to soil and particulate. Since cy

prodinil appears to be a persistent compound, it may be available for long

### 15

periods of time in the field (several months). Vertical movement to subsurfaces is expected to be a relativel y minor component for cyprodinil. Furthermore, volatilization, is expected to be a very minor route of dissipation for the active ingredient. Cy prodinil’s major degradate, CGA
249287 is also a factor that is considered. It may result in runoff and leaching (high solubility and relativel y low Kd 

### = 3.97 mL/gand KOC 

### range 180
- 867 mL/g OC 

### ), and volatilization may play a fac tor in the dissipation of the chemical (vapor pressure = 1.62 x 10 - 3 

### mmHg and Henry ’s Law Constant = 3.46 x 10 - 6 

### atm - m 3 

### /mol). **Analysis Plan** The following scenarios were previousl y modeled, with aerial applications: CA grapes, CA almonds and CA fruits (representing pome and stone fruits ) . The following scenarios will be considered for modeling in this assessment: CA almond, CA fruit, FL strawberry , GA onion, MI cherry , MO melon, NC sweet potato, NY grape, OR snap bean and PA tomato . These crop/ scenari o combinations are representative of the major uses and/ or the highest seasonal ap plication rates. Also, they are representative of diverse regions of the U.S. T he maximum application rate and the minimum interval between applications will be utilized i n all instances
. Even though onl y two aerial applications are allowed for these crops, the linked models PRZM/ EXAMS (using the shell PE5.pl) cannot model independentl y aerial and ground applications; therefore, all aerial applications will be assumed, wh ich is a conservative approach. As per a Scientific Advisory Panel (SAP) recommendation 3 

### , the residue summation (RS) approach will be taken. The a pplication rate for the parent and the degradation product need s to be adjusted to account for the molecular weight ratio of degradate to parent and the normalized maximum percentage of degradation product produced
. This method requires environmental fate data for the degradate of concern, CGA
- 249287
. It also requires manual post
- processing of the output data (daily

EECs) to obtain the 1
- in
- 10 year estimated exposure concentrations (EECs), using a spreadsheet that calculates the 90 th 

### percentile EECs; which is considered to equal the 1
- in
- 10 year EECs
. There are no major uncertainties in the chemical ’s fate dat abase. The aqueous photolysis study resulted in a half

- life of 22 day s, but the review concluded that there may be little aqueous photoly sis and that aqueous photolysis is not a major route of dissipation for cy prodinil. The reason is that the study was conducted with an unsterilized solution. For modeling purposes, EFED assumed that the cyprodinil is stable to aqueous photoly sis. This uncertainty is expected to affect both the peak and long term EDWCs; however, the assumption is conservative. At this time, the HED is expected to need onl y acute, chronic and cancer/ chronic endpoints. The Tier 2 aquatic linked models PRZM/ EXAMS and the Tier 1 aquatic model SCI
- GROW will be used to obtain the EDWCs.

3 SAP (The FIFRA Scientific Advisory Panel). 2009. Minutes for the SAP Meeting on selected issues associated with risk assessment process for pesticides with persistent, bio
- accumulative and toxic characteristics. October 28
- 31, 2008. Arlington, VA. (Docume nt No. 2009
- 01 dated 01/29/2009) http://www.epa.gov/scipoly/sap/meetings/2008/102808_mtg.htm (accessed 10/05/2010).

### ANALYSIS

**Environmental Fate** A summary

t able of phys ic o chemical and environmental fate cy prodinil, including measured parameters, val **Table 3**
. **Table 3**  **. Summary of physicochemical and environmental fate prop**  **erties of cyprodinil.**

**PARAMETER** Chemical Name 4
- cyclopropyl

Structure

Molecular Weight Physical State Powder with agglomerates at 20°C, with a weak odor and beige color Density at 20°C Solubility (20 o C) 16 Vapor Pressure (20 o C) Henry’s Law constant pKa

pH at 25°C Solubilities in g/l at 25°C In ethanol 160, acetone 610, toluene 460, n Octanol
- Water Partition Coefficient (K OW , at 20 o C) log P



### 16

chemical and environmental fate and transport properties of cy prodinil, including measured parameters, val ues, data sources, and comments **. Summary of physicochemical and environmental fate and**  **transport VALUE(S) (units)**  **SOURCE COMMENT**  cyclopropyl
- 6
- methyl
-N

- phenyl
- 2
- pyrimidinamine Chemical Data Sheet CAS name 4
- cyclopropyl
- 6
- methyl
-N
phenylpyrimidin
- 2
- amine IUPAC name

225.29 g/mole Registrant Data Powder with agglomerates at 20°C, with a weak odor and beige color EPA Fact Sheet

1.21 g/cm3 EPA Fact Sheet 16
- 20 ppm @ pH 5; 13 ppm @ pH 7; and 15 ppm @ pH 9 MRID: 43709003. 3.80 x 10 - 6 mmHg MRID: 43709003. 7.04 x 10 - 8 atm - m 3 /mole --- Estimated from vapor pressure and water solubility. 4.44 Tomlin, C.D.S. (ed.) The Pesticide Manual

- World Compendium, 11th ed., British Crop Protection Council, Surrey, England 1997, p. 319 9.5 EPA Fact Sheet In ethanol 160, acetone 610, toluene 460, n
-hexane 30 , n - octanol 160 Tomlin, C.D.S. (ed.) log P O/W = 3.9 @ pH 5; 4.0 @ pH 7;

and 4.0 @ pH 9 P O/W = 10,000 @ pH 7 MRID: 43709003. 

### transport properties of

is included in **transport**
**COMMENT** CAS name IUPAC name

–

--

--

–

– Estimated from vapor pressure and water solubility. The Pesticide Manual World Compendium, 11th ed., British Crop Protection Council, Surrey, England 1997, p. 319

---

---

–

### 17

**Table 3**  **. Summary of physicochemical and environmental fate and**  **transport prop**  **erties of cyprodinil.**

**PARAMETER VALUE(S) (units)**  **SOURCE COMMENT**  Hydrolysis Half

- life (pH 5, 7, 9; (25 o C) Stable to hydrolysis at pH 5, 7, and 9. MRID: 43709044. Stable at all pHs. Aqueous Photolysis Half

- life (pH 5) DT 50 = 22 days In unsterilized water; suspected microbial transformation instead of

photolysis. MRID: 43908422. Phototransformation followed a biphasic pattern, w. slow transformation during the first 9 days, followed by an increased rate from days 9
- 30. Soil Photolysis Half

- life t 1/2 = 64
- 70 days
- s uspected

microbial transformation instead of photodegradation. MRID: 43908423 and 43908424. vs. 160
- 86 days for the dark control Aerobic Soil Metabolism Half
- life LS t 1/2 = 40 and 50 days

SL t 1/2 = 22 and 31 days MRID: 43908425, 43908426, 43709045, and 43709046. For the SL, the pattern was

biphasic, the half lives reported include data from 0 to 21 days. Anaerobic Soil Metabolism Half
- life After aerobic incubation (half
- lives of 16
- 98 days), during anaerobic conditions, the compound was stable MRID: 43908427 and 43908428 --- Anaerobic Aquatic Metabolism Half
- life Stable for 369 days. MRID: 44186406
. – Aerobic Aquatic Metabolism Half
- life t 1/2 = 106
- 126 days for the Rhine river; 165
- 178 days for the pond system from Switzerland, and 612 days for the pond system from Denton, TX. MRID: 45518701, 45518702, 43908429, and 43908430
. _
Organic Carbon Partition Coefficient (K

OC ) (mL /g OC ) SL 2030 S 1770 L 1630 CL 1550 MRID: 43709047
. Moderately to Slightly Mobile (FAO of the UN classification) Soil Partition Coefficient (K d) (mL /g) SL 16.3 S 14.2 L 24.3 CL 31.2 MRID: 43709047
. –
Soil Partition Coefficient K d and K

OC CGA
- 249287 (mL/g or mL/g OC ) Soil/ K d K

OC SL 5.23 650 S 6.97 867 CL 3.48 173 L 3.88 260 LS 0.31 180 MRID 43908431 Moderately mobile

Soil Partition Coefficient K d and K

OC CGA
- 321915 (mL/g or mL/g OC ) Soil/ K d K

OC SL 2.52 313 S 1.45 180 CL 0.99 49.7 L 1.14 76.5 LS 0.25 147 MRID 43908432 Mobile to Moderately mobile

Soil Partition Coefficient K d and K

OC CGA
- 275535 (mL/g or mL/g OC ) Soil/ K d K

OC SL 1 60.3 7500 S 26.7 3320 L1 32.1 2070 L2 33.3 2900 LS 4.39 2550 SL2 8.31 1810 MRID 44186407 Slightly mobile

### 18

**Table 3**  **. Summary of physicochemical and environmental fate and**  **transport prop**  **erties of cyprodinil.**

**PARAMETER VALUE(S) (units)**  **SOURCE COMMENT**  Terrestrial Field Dissipation Half
- life Applied to two plots, one w. 6 applications at 0.5 lb a.i./A, and another at 3.0 lb a.i./A: CA half
- lives 42 days multiple applics. 47 days single applic. and NY 14 to 28 days. Non
- linear first order half
- life was 35 days. First order half lives in NY were 88
- 92 days. MRID: 44186408, 44186437, 44186409, 44186436
. _

Bioaccumulation in Fish Total residue : Edible 100X Non
- edible 777X Whole fish 466X BCF based on parent only : Edible 33X Non
- edible 90X Between 76 and 83% of the radioactivity depurated after one day; and >97% depurated by the third day. MRID: 43924501.



### The major route of dissipation of cy prodinil in the field appears to be the aerobic soil metabolism (22
- 50 day s in four measurements of two soils, with a biphasic pattern). Laboratory data supports that cy

prodinil shows moderate to very slow degradation t o other routes of dissipation. It is highly

persistent in anaerobic aquatic environments, and degrades slowly in aerobic aquatic environments (half

- lives of 106
- 126 day s in river sy stem; 165
- 612 day s in pond sy stems). Aqueous and soil photolysis have been found to be minor degradation pathway s for this chemical. C yprodinil is stable to hydrol ys is in the pH range of 5
- 9. The results of the field studies were of the same order of magnitude than the aerobic soil metabolism (CA half lives 42
- 47 day s and NY half lives 14
- 28 day s). C yprodinil does not readil y leach to ground water, and has a relatively

high affinity

to bind to soil and particulate matter, it is m oderatel y to s lightl y mobile (FAO mobility

c lassification; Kd 

### range = 14.2

– 31.2 m L/ g; KOC 

### range = 1,550

– 2,030 m L/ g OC 

### ). Given the relatively low vapor pressure of cy prodinil ( 3.80 x 10 - 6 

### mmHg) , its low Henry ’s Law Constant ( 7.04 x 10 - 8 

### atm - m 3 

### /mol) , and its tendency to bind to soils and sediments (average K OC 

### = 1745 mL/g OC 

### ), the chemical is n ot expected to volatilize readily from wet or dry surfaces in the environment. Furthermore, cy prodinil is not expected to be a good leacher. The likely routes of exposure to aquatic environments will be from spray drift and the contamination of surface w aters from run
- off and erosion events. Cy prodinil’s fate characteristics suggest that residues in the sediment can persist for several months to years , and the chemical can be present in the water column continuously when residues from the sediment are redistributed throughout the water body b y equilibration. The octanol/water partition coefficient predicts a high potential for bio concentration for cy prodinil (log K OW 

### = 4 at pH 7.0 ; KOW 

### = 10,000 ). However, cy prodinil residues bio
concentrated onl y with maximum BCFs of 100, 777, and 466, in the edible, non
- edible, and whole fish tissues, respectively . The rate of depuration was rapid. Between 76 and 83% of the radioactivity

depurated after one day ; while ≥97% depurated b y the third day.

### 19

As it has been in dicated, there is uncertainty with the aqueous photol ys is study . It was carried out with natural (unsterilized) water. Phototransformation of cy prodinil in the irradiated samples followed a biphasic pattern, with slow transformation taking place during the first nine day s, followed b y an increased rate from days 9
- 30. The possibility of microbial transformation is not ruled out. A p revious review4 

### concluded that “based on calculated DT 50 

### and observed transformation pattern, photoly sis of cy prodinil would not be considered a major pathway of dissipation in natural waters
. ” This uncertainty affects the modeling results because the aqueous photoly sis is an input parameter for PRZM/ EXAMS; h owever, it is not an input parameter in SCI
- GROW. There is also uncertainty with the soil photodegradation study. The calculated half
- lives were 64
- 70 day s; however, it is suspected that there was microbial transformation instead of photodegradation beca use the amount of cy

prodinil in the irradiated and dark control samples were similar. Photodegradation on soil surfaces is not expected to play a major role in the dissipation of cy

prodinil. This uncertainty does not affect the modeling results because the soil photodegradation is not an input parameter for PRZM/ EXAMS or SCI
- GROW. **Table 4**  summarizes the available data on the formation of transformation products by each process in the studies reviewed. **Table 4. Summary of degradate formation from degradation of cyprodinil.** 

**STUDY TYPE DEGRADATE and MAXIMUM CONCENTRATION** 

**SOURCE CGA**  **- 249287**  **(residue of concern) CGA**  **- 321915**  **CGA -**  **275535, CGA**   ** 304075, and CGA****** **304076 mixture** Hydrolysis Relatively stable MRID: 43709044. Aqueous Photolysis Not a contributor MRID: 43908422 Soil Photolysis Not a contributor MRID: 4390823 and 43908424 Aerobic Soil Metabolism 11.7% at 28 days
--- 13% at 14 days MRID: 43908425, 43908426, 43709045, and 43709046 Anaerobic Soil Metabolism Stable during the anaerobic phase MRID: 43908427, 43908428 Aerobic Aquatic Metabolism 14.2%
--- --- MRID: 45518701, 45518702, 43908429, and 43908430 Anaerobic Aquatic Metabolism Stable for 369 days MRID: 44186406. Terrestrial Field Dissipation 0.086 ppm in NY Detected in 0
- 6” depth in both sites, and 6
- 12” depth in CA between 60 to 240 days. Not monitored MRID: 44186409 and 44186436 

### The common denominator in **Table 4** is the presence of CGA
- 249287 , which is also identified as the residue of concern in this DWA
. T his metabolite is the major one in aerobic soil and aquatic metabolic condition
. CGA
- 249287 is moderatel y mobile . Even though leaching was not observed in the field, it may have gone undetected. This remains an uncertainty
. There is uncertainty abo ut the transformation products of cy prodinil. It appears that only under aerobic conditions there is degradation and relativel y little information was available about CGA
249287 , the degradate of concern, and CGA
- 3 21915.

4 Summary and conclusions were derived from US EPA/Canada PMRA Joint Review of March 1998.

### 20

**Drinking Water Exposure Modeling Modeling Approach and Input Parameters** 

 **Model Selection** SCI
- GROW (Screening Concentration in Ground Water v. 2.3; dated July 29, 2003 ) is a regression model used as a screening tool to estimate pesticide concentrations found in ground water used as drinking water. SCI
- GROW was developed by fitting a linear model to groundwater concentrations with the Relative Index of L eaching Potential (RILP) as the independent variable. Groundwater concentrations were taken from 90
- day average high concentrations from Prospective Ground Water studies; the RILP is a function of aerobic soil metabolism and the soil
- water partition coefficient. The outp ut of SCI
- GROW represents the concentrations that might be expected in shallow unconfined aquifers under sandy soils, which is representative of the ground water most vulnerable to pesticide contamination likely to serve as a drinking water source. (

**Ref. 9**  ) The Tier 2 aquatic model employ s PRZM (Pesticide Root Zone Model; version 3.12.2 compiled May 12, 2005 ) and EXAMS (Exposure Analy sis Modeling S ys tem; version 2.98.04.06 compiled April 25, 2005 ). PRZM simulates processes such like runoff and erosion fr om an agricultural field on a dail y 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 PE5.pl (v.5.0, November 15, 2006 ) d eveloped b y 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 file s. PRZM is a one
- dimensional, dy namic, compartmental model that can be used to simulate chemical movement in unsaturated soil sy stems 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 L oss Equation. Evapotranspiration is estimated either directly

from pan evaporation data, or ba sed 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 simultan eously

considering the processes of pesticide uptake b y plants, surface runoff, erosion, decay , volatilization, foliar washoff, advection, dispersion, and retardation. For nitrogen, simulation of surface applications, atmospheric deposition, and septic e ffluent 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 sy stems. 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

### 21

contaminant loadings on daily time scales. It is fairly

and relativel y complex model that requires more input variables, ranging from hydro - geological and weather data to pesticide phy sicochemical properties, mobility coefficients, and degradation rate const ants in the aqueous and sediment phases.

 **Scenario Selection.** The scenarios selected were CA almonds, CA fruits , NY grapes, MIcherries, OR snap beans, MO melon, NC sweet potato, GA onion, F L strawberries and PA tomato. These crops were representative of the major uses or the highest seasonal application rates. A lso, all these crops could be applied aeriall y. T he minimum interval between applications was utilized in each case (most conservative scenario was taken).

 **Model Inputs** The Metabolism Assessment Review Committee’s (MARC) decision document concluded that the transformation product CGA
- 249287 of cy prodinil is a potential concern for drinking water sources. Therefore, EDWCs of CGA
- 249287 were also simulated using the linked PRZM/ EXAMS , and SCI
- GROW models. EFED had only limited environmental fate data for this transformation product; however, KOC 

### of this metabolite was available. The aerobic soil metabolism half

- life was calculated from reported form ation
- decline curve of parent cy prodinil and CGA
- 249287 metabolite in the aerobic soil metabolism study (MRID 43908425). Selected phy sical and chemical parameters for CGA
- 249287 were also generated using EPISUITE, v. 3.12, which is a Windows ® 

### based suite o f ph ys ical/ chemical property and environmental fate estimation models developed by the EPA’s Office of Pollution Prevention Toxics and Sy racuse Research Corporation (SRC). For the output file of EPI SUITE, refer to the **Appendix**
. According to the SAP, although the simultaneous formation/ decline kinetic mod eling strategy is the preferred method for estimation of total residue concentrations, this method is highly dependent on the ability

to describe the formation and degradation kinetics of degradation products. To that end, the method requires environmental fate data for the toxic degradation products. Another important consideration is the ability to integrate these data into PRZM/ EXAMS model simulations. In light of these issues, alternative modelin g strategies could be employed such as the total residue (TR) approach or the residue summation (RS) approach depending on the availability of data. PRZM/ EXAMS model ing is used to obtain daily time series for calculatin g the 1
- in
- 10 year aquatic exposure concentrations for the RS method
. The 1
- in
- 10 year exposure concentrations are calculated using dail y concentration data b y means of a post - processing spreadsheet application
. Th e RS method requires assignment of an application rate for each of the individual chemical stressors ( i.e. , cy

prodinil and CGA
- 249287 ). These application rates are normalized according to the percentage of residue detected in aerobic soil metabolism studies and the molecular weight ratio of degradate and parent compounds . The aerobic soil was chosen because most of the chemical is expected to reach the soil s ys tem after application
. **Table 5** provides an example on the determination of the application rate usi ng the RS method for the application of cy prodinil on grapes. The two chemicals are assumed to be applied at time zero. Also, it is assumed that the maximum degradation of the parent and the maximum formation of degradates occur at

### 22

application. This ass umption constitutes an uncertainty of the RS method. CGA
- 249287 was actuall y a maximum at 28 days in the aerobic soil metabolism study
. **Table 5.**  **Example calculation of application rates for modeling of cyprodinil and its metabolite (example for the use**  **on grapes) Chemical Species**  **% Maximu m in Aerobic Soil Study**  **Application Rate (**  **lb a.i./A )**  **Molecular**

**Ratio Modeled Application Rate** 

**(lb a.i./A) Observed** * **Normalized** 

### Cyprodinil 100% 89.5% 0.421 1 **0.421** CGA
- 249287 11.7% 10.5% 0.0492 0.662 0.0327**  Total 111.7% 100% 0.47 The shaded and bolded area provides the results used in modeling. * Observed maximum values for parent and CGA 249287 in the aerobic soil metabolism studies ** CGA
- 249287 to cyprodinil molecular ratio = 149.20/ 225.29 

### Tables of model parameter input values for SCI
- GROW ( **Tables 6a** and **6b** ) and PRZM/ EXAMS ( **Tables 7a** and **7b** ) are based on the current input parameter guidance, dated 10/22/2009 (

**Ref. 10**  )
. **Table 6 a**  **. SCI -**  **GROW (v 2.3) input parameter values for cyprodinil use on grapes 1**  

### .

**PARAMETER (units) VALUE(S)**  **SOURCE COMMENT**  Maximum Application Rate (lb a.i./A) 0.421 Proposed label. Proposed label for SwitchTM fungicide. For calculation of application rate, see **Table 5**
. Number of Applications per Year 3 Proposed label. Represents most - conservative scenario in which the total maximum rate per year is applied in three

applications. Organic Carbon Partition Coefficient (K OC ; mL /g) 1700 MRID: 437090
- 47 Median value of the following K OC ’s 2030, 1770, 1630, 1550. Aerobic Soil Metabolism Half
- life (days) 35.5 MRID: 43908425, 43908426, 43709045, and 43709046. Median value, since there are four or more half
- life values: 50, 40, 31, 22 days.
1. Data were selected according to the Guidance for Selecting Input P arameters in Modeling the Environmental Fate and Transport of Pesticides ( Version 2.1 , dated October 22, 2009). 

### Table 6 **b . SCI**  **- GROW (v2.3) input parameter values for CGA**  **-** 249287 **use on grapes 1**  

### .

**PARAMETER (units) VALUE(S)**  **SOURCE COMMENT**  Maximum Application Rate (lb a.i./A) 0.0327 Proposed label. For calculation of application rate, see **Table 5**
. Number of Applications per Year 3 Proposed label. Represents most
- conservative scenario in which the total maximum rate per year is applied in three

applications. Organic Carbon Partition Coefficient (K OC ; mL /g) 173 MRID 43709047, 43908431 Lowest value of the following K OC ’s: 173, 180, 260, 650, and 867 . There is greater than a three
- fold variation between the values. Aerobic Soil Metabolism Half
- life (days) 72 --- Available value. 1. Data were selected according to the Guidance for Selecting Input P arameters in Modeling the Environmental Fate and Transport of Pesticides ( Version 2.1 , dated October 22, 2009).

### 23

The cy prodinil label requires that , for resistance management, two applications of the chemical should be alternate d with a chemical with a different mode of action for two applications . In this assessment, it was assumed that the alternate fungicide is also applied at 7
- day intervals. Thus, for example, for grapes, the chemical is firstly applied once, an alternate fungicide is applied twice, and then cy

prodinil is applied twice. The corresponding intervals between applications are 21 and 7 day s (21
- day interval between the 1 st 

### and 2 nd 

### application, and 7
- day interval between the 2 nd 

### and 3 rd 

### application). A total of 3 applications of cy prodinil are modeled at the maximum rate for the example use on grapes. [Similarly , for four applications the intervals are 7, 21 and 7 day s, and f

or si x applications the intervals are 7, 21, 7, 21 and 7 day s .] The application dates were obtained from the corresponding metadata files, the crop profiles, meteorological files and the label. **Table 7a**  **. Input Parameters Utilized in PRZM/EXAMS for Cyprodinil 1**  

### PARAMETER **VALUE(S) SOURCES**  **COMMENTS** Output File Name CYPRODIN
--- --- Chemical Name Cy prodinil
--- --- Crop Names Almond, grape, pome and stone fruits ( e.g. , apple, cherry), avocado, beans ( e.g. , snap bean), cabbage, melon, sweet potato, onion, straw berry and tomato Proposed label for

Vangard ® WG (EPA Reg. No. 100
- 828) ---

PRZM Scenario Scenario/ Represented Crop CA almond/ almond CA fruit/ pome fruits NY grape/ grape MI cherries/ stone fruit OR snap bean/ bean MO melon/ cucurbit vegetable NC sweet potato/ leaves of root & tuber vegetable GA onion/ onions and garlic FL straw berry/ strawberry PA tomato/ tomato & tomatillo --- Representative of a variety of crops, taking into consideration most geographical regions in the US , maximum application rates and aerial applications
.

Application Rate Crop/ Rate in kg a.i./ha CA almond/ 0.472 CA fruit/ 0.472 NY grape/ 0.472 MI cherries/ 0.231 OR snap bean/ 0.331 MO melon/ 0.331 NC sweet potato/ 0.331 GA onion/ 1 @ 0.361 + 2 @ 0.472 FL straw berry/ 1 @ 0.361 + 2 @ 0.472 PA tomato/ 0.331 Proposed label for Vangard ® WG (EPA Reg. No. 100
- 828) ; refer to **Table 5** for an example of the calculation of the application rate to be used in modeling. Crop/ Rate in lb a.i./A

CA almond/ 0.421 CA fruit/ 0.421 (in CA) NY grape/ 0.421 MI cherries/ 0.206 OR snap bean/ 0.295 MO melon/ 0.295 NC sweet potato/ 0.295 GA onion/ 1 @ 0.322 + 2 @ 0.421 FL straw berry/ 1 @ 0.322 + 2 @ 0.421 PA tomato/ 0.295

### 24

**Table 7a**  **. Input Parameters Utilized in PRZM/EXAMS for Cyprodinil 1**  

### PARAMETER **VALUE(S) SOURCES**  **COMMENTS** Number of Applications Allowed CA almond/ 3 CA fruit/ 3 NY grape/ 3 MI cherries/ 6 OR snap bean/ 4 MO melon/ 4 NC sweet potato/ 4 GA onion/ 3 FL straw berry/ 3 PA tomato/ 4 Proposed label for Vangard ® WG (EPA Reg. No. 100
- 828) ---

Interval between Applications (days) CA almond/ 21, 7 (assumed) CA fruit/ 21, 7 (assumed) NY grape/ 21, 7 MI cherries/ 7, 21, 7, 21, 7 OR snap bean/ 7, 21, 7 MO melon/ 7, 21, 7 NC sweet potato/ 7, 21, 7 GA onion/ 21, 7 FL straw berry/ 21, 7 PA tomato/ 7, 21, 7 Proposed label for Vangard ® WG (EPA Reg. No. 100
- 828) As per label requirement,

for resis tance management, after two applications, alternate with a different mode of action for two applications.
Day of Application Crop/ Day
- Month

CA almond/ 01
- 03 CA fruit/ 18
- 04 NY grape/ 15
- 08 MI cherries/ 05
- 05 OR snap bean/ 02
- 07 MO melon/ 30
- 05 NC sweet potato/ 22
- 07 GA onion/ 20
- 04 FL straw berry/ 02
- 01 PA tomato/ 01
- 07 Estimated from metadata file, the crop profiles, meteorological files and label. Crop/ PHI (days)

CA almond/ 60 CA fruit/ 2 NY grape/ 7 MI cherries/ 2 OR snap bean/ 7 MO melon/ 1 NC sweet potato/ 7 GA onion/ 7 FL straw berry/ 0 PA tomato/ 0 KOC 1,745 MRID: 437090
- 47 Average KOC value among four values ranging from 1550 to 2030 ml/g. The KOC mo del was utilized since it describes better the mobility of cyprodinil. Aerobic Soil Metabolism (day s) 44.3 MRID: 439084
- 26 Represents the 90 th percentile of the upper confidence bound on the mean of four half

- life values: 40, 50, 22, 31 days; mean = 35.75 days; std. dev. = 10.40 days Incorporation Depth 0.0 in Proposed label
--- Method of Application Aerial Proposed label
--- Buffer Zone (ft.) 150 aerial Proposed label
--- Application Efficiency (fraction) 0.95 aerial
--- --- Spray Drift (fraction) 0.16 aerial applications
--- --- Solubility in Water at pH 7 (ppm) (20°C) 13 MRID 437090
- 03
---

### 25

**Table 7a**  **. Input Parameters Utilized in PRZM/EXAMS for Cyprodinil 1**  

### PARAMETER **VALUE(S) SOURCES**  **COMMENTS** Aerobic Aquatic Metabolism (days) 382.3 MRID 439084
- 26, 439084
- 29, 439084
- 30, 455187
- 01 & 455187
- 02 Represents the 90 th

percentile of the upper confidence bound on the mean of five half

- life values: 106, 126, 165, 178 and 612 days; mean = 237.40 days; std. dev. = 211.41days Anaerobic Aquatic Metabolism (days) Stable MRID 441864
- 06
--- Hydroly sis at pH 7 Stable MRID 4370 90
- 44
--- Aqueous Photolysis @ pH 7 and 25°C (days) Stable MRID 439084
- 22
--- Molecular Weight (g/mol) 225.29 Registrant Data
--- Vapor Pressure (torr) 3.80 x 10 - 6 MRID 437090
- 03 torr = mmHg Henry’s Law Constant (atm
- m 3 /mol) 7.04 x 10 - 8 Calculated from solubility and vapor pressure. --- Environment ir298.exv
--- Default for index reservoir, as opposed to pond scenario. Field Size Reservoir
--- Runoff Overall
--- Metfile Scenario CA almond w23232.dvf CA fruit w93193.dvf NY grape w 14860.dvf MI cherries w 14850.dvf OR snap bean w24232.dvf MO melon w13893.dvf NC sweet potato w 13722.dvf GA onion w03822.dvf FL straw berry w 12842.dvf PA tomato w14751.dvf --- As suggested by the shell (PE5).

CAM (Chemical Application Method) 2
--- 2 = linear foliar based on crop canopy IPSCND 1
--- 1 = pesticide remaining on foliage is converted to surface application to the top soil layer FEXTRC, Foliar extraction 0.5
--- --- PLDKRT, Decay rate on foliage (day - 1 ) 0
--- --- PLVKRT, Volatilization rate from foliage 0
--- --- UPTKF, Uptake factor 0
--- --- 1. Data were selected according to the Guidance for Selecting Input Parameters in Modeling the Environmental Fate and Transport of Pesticides ( Version 2.1 , dated October 22, 2009). 

### For CGA
- 249287, the same application dates as for cy prodinil were utilized. The application rates were adjusted as indicated in the example provided in the **Table 5** . The following parameters were estimated by the EPISUITE model: molecular weight, solubili ty in water, vapor

### 26

pressure and Henry ’s Law Constant. Other parameters such as the aerobic soil metabolism were derived from the decay

curve in the study

performed for cy

prodinil. In the absence of data, for the following processes CGA
- 249287 was assumed to be stable: h ydrol ys is, aqueous photoly sis and anaerobic aquatic metabolism. These assumptions are conservative. **Table 7b.**  **Input Parameters Utilized in PRZM/EXAMS for CGA -**  **249287 1**  

### PARAMETER **VALUE(S) SOURCES**  **COMMENTS** Output File Name CGA_249287
--- --- Chemical Name CGA
- 249287
--- --- Crop Names Same as for cyprodinil; refer to **Table 7a** 
. Proposed label for Vangard ® WG (EPA Reg. No. 100
- 828) --- PRZM Scenario Same as for cyprodinil; refer to **Table 7a** 
. --- --- Application Rate Crop/ Rate in kg a.i./ha CA almond/ 0.0367 CA fruit/ 0.0367 NY grape/ 0.0367 MI cherries/ 0.0179 OR snap bean/ 0.0257 MO melon/ 0.0257 NC sweet potato/ 0.0257 GA onion/ 1 @ 0.0280 + 2 @ 0.0367 FL straw berry/ 1 @ 0.0280 + 2 @ 0.0367 PA tomato/ 0.0257 Proposed label for Vangard ® WG (EPA Reg. No. 100
- 828) ; refer to **Table 5** for an example of the calculation of the application rate to be used in modeling. Crop/ Rate in lb a.i./A

CA almond/ 0.0327 CA fruit/ 0.0327 (in CA) NY grape/ 0.0327 MI cherries/ 0.0160 OR snap bean/ 0.0229 MO melon/ 0.0229 NC sweet potato/ 0.0229 GA onion/ 1 @ 0.0250 + 2 @ 0.0327 FL straw berry/ 1 @ 0.0250 + 2 @ 0.0327 PA tomato/ 0.0229 Number of Applications Allowed CA almond/ 3 CA fruit/ 3 NY grape/ 3 MI cherries/ 6 OR snap bean/ 4 MO melon/ 4 NC sweet potato/ 4 GA onion/ 3 FL straw berry/ 3 PA tomato/ 4 Proposed label for Vangard ® WG (EPA Reg. No. 100
- 828) ---

Interval between Applications (days) CA almond/ 21, 7 CA fruit/ 21, 7 NY grape/ 21, 7 MI cherries/ 7, 21, 7, 21, 7 OR snap bean/ 7, 21, 7 MO melon/ 7, 21, 7 NC sweet potato/ 7, 21, 7 GA onion/ 21, 7 FL straw berry/ 21, 7 PA tomato/ 7, 21, 7 Proposed label for Vangard ® WG (EPA Reg. No. 100
- 828) As per label requirement,

for resistance management, after two applications, alternate with a differ ent mode of action for two applications.

### 27

**Table 7b.**  **Input Parameters Utilized in PRZM/EXAMS for CGA -**  **249287 1**  

### PARAMETER **VALUE(S) SOURCES**  **COMMENTS** Day of Application Crop/ Day
- Month

CA almond/ 01
- 03 CA fruit/ 18
- 04 NY grape/ 15
- 08 MI cherries/ 05
- 05 OR snap bean/ 02
- 07 MO melon/ 30
- 05 NC sweet potato/ 22
- 07 GA onion/ 20
- 04 FL straw berry/ 02
- 01 PA tomato/ 01
- 07 Estimated from metadata file, meteorological files and label. Crop/ PHI (days)

CA almond/ CA fruit/ NY grape/ 7 MI cherries/ 2 OR snap bean/ 7 MO melon/ 1 NC sweet potato/ 7 GA onion/ 7 FL straw berry/ 0 PA tomato/ 0 Kd 3.97 MRID 43709047, 43908431 Average value of the

following Kd ‘s 0.31, 3.48, 3.88, 5.23, and 6.97, the Kd mo del describes the mo bility of the degradate better than the KOC mo del. Aerobic Soil Metabolism (days) 216 MRID: 43908425, 43908426, 43709045, and 43709046. 3X available value
Incorporation Depth 0.0 in Proposed label
--- Method of Application Ground or Aerial Proposed label
--- Buffer Zone (ft.) 75 ground/ 150 aerial Proposed label
--- Application Efficiency (fraction) 0.95 aerial
--- --- Spray Drift (fraction) 0.16 aerial
--- Included because the degradate forms under aerobic aquatic metabolism conditions. Solubility in Water (ppm) pH 7 @ 25°C 2,352 EPISuite From KOW . Aerobic Aquatic Metabolism (days) 432
--- 2X the aerobic soil metabolism input value Anaerobic Aquatic Metabolism (days) Stable MRID 43908427, 44186406 Assume stable Hydroly sis at pH 7 Stable MRID 43709044 Assume stable Aqueous Photolysis @ pH 7 and 25°C (days) Stable MRID 43908422 Assume stable Molecular Weight (g/mol) 149.20 EPISuite
--- Vapor Pressure (torr or mmHg, at 25°C) 0.00162 EPISuite
--- Henry’s Law Constant (atm
- m 3 /mol) 3.46x10 - 6 EPISuite Bond method. Environment ir298.exv
--- Default for index reservoir, as opposed to pond scenario. Field Size Reservoir
--- Runoff Overall
---

### 28

**Table 7b.**  **Input Parameters Utilized in PRZM/EXAMS for CGA -**  **249287 1**  

### PARAMETER **VALUE(S) SOURCES**  **COMMENTS** Metfile Scenario CA almond w23232.dvf CA fruit w93193.dvf NY grape w 14860.dvf MI cherries w 14850.dvf OR snap bean w24232.dvf MO melon w13893.dvf NC sweet potato w 13722.dvf GA onion w03822.dvf FL straw berry w 12842.dvf PA tomato w14751.dvf --- As suggested by the shell (PE5).

CAM (Chemical Application Method) 2
--- 2 = linear foliar based on crop canopy IPSCND 1
--- 1 = pesticide remaining on foliage is converted to surface application to the top soil layer FEXTRC, Foliar extraction 0.5
--- --- PLDKRT, D ecay rate on foliage (day - 1 ) 0
--- --- PLVKRT, Volatilization rate from foliage 0
--- --- UPTKF, Uptake factor 0
--- --- 1. Data were selected according to the Guidance for Selecting Input Parameters in Modeling the Environmental Fate and Transport of Pesticides ( Version 2.1 , dated October 22, 2009). 

### The percent cropped area (PCA) for all crops assessed was the Agency ’s national default of 0.87
. Options for Tier I are national scale cotton, wheat, corn, so ybeans, or default. Regional PCAs are a Tier II tool intended for more refined assessment. ( **Ref. 7** ) In the **Exposure Characterization**  section, the uncertainties surrounding the use of the PCA and the Index Reservoir are described. **Modeling Results** Once the parent cy

prodinil, and its degradate CGA
- 249287 were modeled separately using PRZM/ EXAMS, an output file is obtained that provides 1
- in
- 10 year exposure concentrations for each chemical. An example of an output file is provided in the **Appendix** f or reference purposes; however, these files were not utilized for the determination of the EDWCs. It is noted however, that the 1
- in
- 10 years exposure values may be used if it known that parent and its degradate have different toxicity and/ or mode of act ion. In this assessment it is assumed that parent and degradate are of similar toxicity and mode of action. Furthermore, there is another output file that provides daily concentrations, also called the time series or TS file. For each crop scenario one TS file is obtained for cy prodinil and another for CGA
- 249287. Post
- processing dail y exposure concentrations from the model results is performed to obtain daily EDWCs for the total residues (both stressor s) by combining daily concentrations from both chem icals b y simple addition of daily exposure concentrations. The

### 29

post - processing of total residue daily exposure concentrations is continued by calculating the required running averages and maxim a for each of the 30 years . This is followed by calculating the 90 th 

### percentiles which is considered to be the 1
- 10 year EDWCs for the total residues. In the post - processing, the PCA adjustment was also incorporated. Thus, the spreadsheet application yi elds directly

the PCA adjusted EDWCs. **Table 8** provides the re sults of the surface waters modeling and **Table 9** provides the results for the groundwater modeling. **Table 8**  **. Tier 2**  **Surface Waters Estimated Drinking Water Concentrations (EDWCs) of**  **the T**  **otal Residues of Concern of**  **C yprodinil**  **plus CGA**  **- 249287**  **1 DRINKING**  **WATER SOURCE**  **(MODEL USED) USE SCENARIO**  **National PCA (%)**  **EDWC ( ppb)**

1
- in
- 10
- year annual peak conc. 1
- in
- 10
- year

annual mean conc. Overall mean conc. 

### Surface water (PRZM/ EXAMS) CA almond 87 11.50 6.92 6.13

CA fruit 87 16.33 11.58 10.24 **NY grape 1**  

### 87 **34.79 24.65**  **16.38** MI cherries 87 21.29 15.59 12.12 OR snap bean 87 10.02 5.47 4.33 MO melon 87 22.07 7.21 5.66 NC sweet potato 87 28.25 12.91 10.07 GA onion 87 17.88 6.97 5.56 FL strawberry 87 21.22 6.63 5.10 PA tomato 87 21.05 10.76 8.10 1. The shaded and bolded row indicates the scenario that yielded the highest EDWCs. 

### The use scenario that yi elded the highest EDWCs was NY grape. The maximum acute concentration in surface water (EDWC) is 34.79 μg/Lof cy prodinil plus CGA
- 249287, using the NY grapes scenario. The maximum chronic EDWC in surface waters is 24.65 μg/L of cy prodinil plus CGA
- 249287, using the NY grapes scenario. Finally , the maximum cancer/ chronic EDWC in surface waters is 1 6.38 μg/L of cy prodinil plus CGA
- 249287, using the NY grapes scenario. **Table 9**  **. Groundwater**  **Estimated Drinking Water Concentrations (**  **EDWCs )**  **Modeled for the Use of Cyprodinyl and CGA**  **- 249287**  **1 Parameter** **\ Concentrations in ppb**  **C rop**  **Cyprodinil CGA**  **- 249287**  **Total Residues** 

### SCI
- GROW (Acute and Chronic) Grapes 3.60x10 - 2 

### 5.01x10 - 2 

### 8.61x10 **- 2**  1. The shaded and bolded cell indicates the EDWC for the total residues. 

### The SCI
- GROW generated EDWC for grapes are 0.0 360 μg/L for cy prodinil, 0.0 501 μg/Lfor CGA
- 249287 and 0. 0861 μg/Lfor the total residues of cy prodinil plus CGA
- 249287
. This value is suitable for acute and chronic exposures.

### 30

**Monitoring Data** The U.S. Geological Survey ’s (USGS) National Water Quality Assessment (NAWQA) Data Warehouse was checked for possible detections of cy prodinil, but it was found that the chemical was not monitored in the study units (basins) that are included in the database. In addition, STORET (short for STOrage RETrieval) Data Warehouse was checked. It appears that it contains data o n cy

prodinil. **Drinking Water Treatment** It is likel y that primary treatment may reduce the levels of cy prodinil due to its relatively high tendency to bind. Also it is possible that the chemical and/ or its degradate undergoes transformation. However, there is no information available at this time to determine the levels of reduction and/ or transformation, if any ( **Ref. 6** ). **EXPOSURE CHARACTERIZATION** The maximum EDWCs were obtained on the use of cy prodinil on grapes in NY. The following two crops with the next to the highest EDWCs were NC sweet potato and MO melon. Three crops modeled in the west coast (two in CA and one in OR) yielded the lowest EDWCs out of a total of 10 crop scenarios modeled. The range of peak EDWCs varied only b y a factor of ~3. 5. The range of peak EDWCs is 10.02 ppb for OR snap beans to 34.79 for NY grapes. Itappears that the obtained EDWCs are reasonable conservative values. In a previous assessment, the NY grapes scenario also yielded the highest EDWCs even though at the t ime, the application was modeled with ground methods (as compared to applications made aerially

in CA, which were also modeled in the DWA). Since the shell (PE5.pl) does not allow for changes in the method of application in the same modeling run, all the applications were assumed to be aerial. Thus, the results of this assessment are likel y to be conservative, since for all crops only

two aerial applications will be allowed per season. In the case of grapes, a total of three applications are made at the maximum application rate. In addition, for cy

prodinil, the label require s a buffer zone and a vegetated buffer strip to protect lakes, reservoirs, rivers, permanent streams, marshes or natural ponds, estuaries and commercial fish ponds. For aerial applic ations, the buffer zone is 150 ft. For this assessment, the level of drift was assumed to be 0.16 (16%), which is the standard value that has been derived for aerial applications that do not include a buffer zone; however, it is possible that the level of drift is an overestimate for aerial applications of cy prodinil because of the buffer zone restriction. It appears that the assumption of 16% drift could be conservative in this assessment. The crops selected for modeling [almond, fruit (for pome fruits) , grape, cherries (for stone fruits), snap beans (for beans), melons (for cucurbit vegetables), sweet potatoes (for various root and tuber vegetables), onions (for onions and garlic), strawberries and tomatoes] are representative of the maximum number of a pplications at the maximum single application rates at the minimum interval between applications (maximum seasonal application rate between 1.3 and 1.4 lb a.i./A/year). For grapes, which had the maximum EDWCs in PRZM/ EXAMS, the

### 31

range of application rates for a single application is 0.235 to 0.47 lb a.i./A (5
- 10 oz of product, containing 75% a.i., Vangard® 

### WG Fungicide), it is unknown if the maximum single or seasonal application rate are similar to the ty pical application rates. However, it is indicated in the label that the higher application rate for grapes is recommended for the use of cyprodinil alone, while the range of application rates (5
- 10 oz product) is recommended for tank mixtures with another fungicide registered on grapes for control of Botrytis bunch rot. The selected crop scenarios represent most regions and various major use areas of the continental US (CA, NY, MI, OR, MO, NC, GA, FL and PA). No new crops are proposed in this action. Rather, the use of aerial and chemigation application s are proposed. Grapes and almonds are the two major crops (as of 2002), which comprised >74% of the national use of cy prodinil, followed by

raspberries (not modeled), peaches and strawberries (5.3
- 5.9% of the national use each). The next crops in order of usage are apples, plums and prunes, nectarines, apricots and pears, in that order (0.58
- 3.6% of the national use). Crops which were not modeled in this assessment were tropical fruits, kiwi, citrus (lemon and lime), pistachios (usually modeled using th e CA almond scenario, which was modeled), berries, brassica (cole) vegetables, herbs, leafy vegetables and watercress. For citrus and watercress, only ground applications are allowed according to the proposed label. Tropical fruits, citrus, brassica (col e) vegetables and leafy vegetables are ty

pically modeled using crop scenarios located in FL or CA, for which other scenarios were modeled ( e.g. , FL avocado, FL citrus, CA citrus, FL cabbage and CA lettuce). For kiwi, berries and herbs, no standard scenari o was available. Despite the fact that these crops were not modeled, a variety of crops were modeled indeed, which cover major uses of cy prodinil and most regions of the continental U.S. where the chemical may

be used. These crops may be considered repre sentative of all uses of cy prodinil. One uncertainty related to the fate database is the aqueous photoly sis study. It resulted in a half
life of 22 day s, but the review concluded that there may be little aqueous photoly sis and that aqueous photoly sis is not a major route of dissipation for cy prodinil. The study

was conducted with an unsterilized solution. For modeling purposes, EFED assumed that the cy prodinil is stable to aqueous photolysis. This uncertainty is expected to alter both the peak and long term EDWCs (should the actual photoly sis rate was different); however, the assumption is conservative. The input parameters for PRZM/ EXAMS for cy prodinil have a relativel y low level of uncertainty. The dataset for the chemical was extensive. The chemical was found to be stable to hydrol ys is, aqueous photoly sis at pH 7 and anaerobic aquatic metabolism. A total of ten PRZM scenarios were run with PRZM/ EXAMS. In gene ral, conservative assumptions were made with respect to the input parameters in this assessment, as per the input guidelines dated 10/22/2009 ( **Ref. 10**). CGA
- 249287 had been selected b y the Me tabolism Assessment Review Committee (MARC) for modeling of EDWCs. The metabolite was modeled separatel y (as opposed to the use of the total residue approach), but using the residue summation method (RS). For CGA
- 249287, there is a higher degree of uncertainty in the input parameters. For this c hemical, only the mobility

study was available. The aerobic soil metabolism half
- life was derived from the study on the parent.

### 32

Since only

one value was available, it was multiplied by three to account for the uncertainty due to the lack of additional half
- lives. The aerobic aquatic metabolism was assumed to be twice the aerobic soil metabolism input (as per the input guidelines). CGA
- 249287 was assumed to be stable to hydrol ys is, aqueous photolysis and anaerobic aquatic metabolism (because there was no data or the metabolite did not degrade under the stated conditions). The vapor pressure, Henry ’s Law constant and solubility were derived from the EPI SUITE ® 

### model because no empirical values were available. With the RS approach, both cy prodinil and CGA
- 249287 were assumed to be applied at time zero. Also, it is assumed that the maximum degradation of the parent and the maximum formation of degradates occur at application. This assumption constitutes an uncertainty of the RS method. The degradate was a ctually a maximum at 28 day s in the aerobic soil metabolism study
. The EDWC was comparativel y high er using the conventional approach to determine 1
- in
10 ye ar peak exposures ( e.g. , for the CA almond scenario, the peak EDWC is 13.48 ppb x 0.87 = 11.73 ppb for cy

prodinil and the peak EDWC is 0.827 ppb x 0.87 = 0.719 ppb for CGA
- 249287, see the **Appendix** for the example output file). The metabolite comprised only a maximum of ~12
- 14% in laboratory

studies. When the time series files were post
- processed, the peak EDWC for the same scenario was slightly lower than the sum of the individual values. For the example of the CA almond scenario, the final post
- processed EDWC is 11.50 ppb of cy prodinil plus CGA
- 249287. It is unknown if using the peak value derived u sing this approach may be an overestimation or underestimation of what reall y happens in the field. CGA
- 249287 was a major degradate only

under aerobic conditions (aerobic soil metabolism and aerobic aquatic metabolism) and in the field. The extent of th is assessment is national in scope, with the use of national percent crop areas (PCAs)
. For uncertainties regarding the use of a PCA, refer to the following section. In addition, the percent of the crop which is treated (PCT) with a pesticide can be an i mportant factor in determining the concentration level in drinking water in each basin. However, PCT can vary greatly from watershed to watershed, and generall y, pesticide use data is not collected below the statewide level, so this variability cannot cur

rentl y be characterized. Using state
- wide averages for PCT will underestimate for up to half the watersheds, or in cases where the usage is limited to a small portion of the state, significantl y underestimate for these watersheds, while overestimating for the rest. Because there is no currentl y acceptable method to estimate PCT on a watershed basis from existing data, and existing data sources are usually at too large a scale, OPP does not estimate drinking water concentrations be quantitatively adjusted to account for PCT. OPP currently

assumes 100% PCT for surface
- water - source drinking water assessments, as there is no way to objectively

defend the assumption of a lower PCT without appropriate data or estimation tools. Monitoring data were not utilized i n this assessment
.

### 33

**Uncertainties Related to the Use of a PCA** The PCA is a watershed
- based modification ( **Ref. 7** ) . Implicit in its application is the assumption that currentl y used field
- scale models reflect basin
- scale processes consistently for all pesticides and uses. In other words, it is assumed that the large field simulated b y the index reservoir models is a reasonable approximation of pesticide fate and transport within a watershed that contains a drinking water reservoir. If the models fail to capture pertinent basin
- scale fate and transport processes consistently for all pesticides and all uses, the application of a factor that reduces the concentrations estimated by modeling could, in some instances, result in underestimated EDWCs. Important basin scale processes that are not simulated by using PRZM and EXAMS with a PCA factor tend to reduce the peak concentration below the estimate, but may extend the duration of its occurrence. Examples of these processes include applications to different fi elds on different dates, non
- simultaneous entry of runoff into the water body at different locations in the watershed, and subsurface interflow through ground water. The spatial data used for the PCA came from readily available sources and have a number o f inherent limitations: 1. The size of the 8
- digit HUC [mean = 366,989 ha; range = 6.7
- 2,282,081 ha; n = 2,111] may not provide reasonable estimates of actual PCAs for smaller watersheds. The watersheds that drain into drinking water reservoirs are generally smaller than the 8
- digit HUC and may

be better represented by

watersheds defined for drinking water intakes. 2. The conversion of the county
- level data to watershed
- based percent cropped areas assumes the distribution of the crops within a county is uniform and homogeneous throughout the county area. Distances between the treated fields and the water body are not addressed. 3. PCA adjustment factors were generated using data from the 1992 and 1997 Census of Agriculture. The assumption that “yearl y changes in cro pping patterns will cause minimal impact” remains a source of uncertainty
. 4. The PCA adjustment factors do not consider the percent of the crop treated in the watershed because detailed pesticide usage data are extremely limited at this time and are currentl y available for only a few states. **Uncertainties Related to the Use of the Index Reservoir**  The index reservoir represents potential drinking water exposure from a specific area (Illinois) with specific cropping patterns, weather, soils, and other factors ( **Ref. 8** ) . Use of the index reservoir for areas with different climates, crops, pesticides used, sources of water ( e.g. , rivers instead of reservoirs), and hydrogeology creates uncertainties. In general, because the index reservoir represents a fairly vuln erable watershed, the exposure estimated with the index reservoir will likely

be higher than the actual exposure for most drinking water sources. However, the index reservoir is not designed to represent a worst case scenario. Communities that derive thei r drinking water from smaller bodies of water with minimal outflow, or with more runoff prone soils, would be likely to have higher drinking water exposure than estimated using the index reservoir. Areas with a more humid climate , that use a similar reserv oir and cropping

### 34

patterns may

also have higher concentrations of pesticides in their drinking water than predicted using this scenario. A single steady flow represents water flow through the reservoir. Because this steady discharge from the reservoir also removes chemicals, this assumption will underestimate removal from the reservoir during wet periods and will overestimate removal during dry periods. This assumption can both underestimate and overestimate the concentration of a pesticide remaining in the reservoir depending upon the annual precipitation pattern at the reservoir. The index reservoir scenario uses the characteristics of a single soil to represent soils in the watershed. Soils can vary substantially across even small areas and this variabil ity is not reflected in the scenario. The index reservoir scenario does not consider tile drainage. Tile drainage contributes additional water and, in some cases, additional pesticide loading to the reservoir. This may cause either an increase or decrease in the pesticide concentration in the reservoir. Tile drainage also causes the surface soil to dry

out faster, which will reduce runoff of the pesticide into the reservoir. The watershed used as the model for the index reservoir (Shipman City L ake) does n ot have tile drainage in the cropped areas. The index reservoir scenario assumes complete mixing of the chemical through the water column. However, thermal stratification can occur in reservoirs that inhibits mixing. Eventuall y, an overturn event will oc cur that eliminates the stratification and returns the water column to a completely

mixed state. Overturn occurs when the temperature drops in the fall and again in the spring when the reservoir warms up. EXAMS does not easily model stratification and spri ng and fall turnover. Because of this limitation with EXAMS, the Index Reservoir has been simulated without stratification. There are data to suggest that Shipman City L ake, upon which the Index Reservoir is based, does indeed stratify in the deepest parts of the lake at least in some years. This may result in both over and underestimation of the concentration in drinking water depending upon the time of the year and the depth of the drinking water intake.

### 35

**REFERENCES** 1. U.S. Environmental Protection Agency (2006). Guidance for Developing a Tier I Drinking Water Exposure Assessment 2. U.S. Environmental Protection Agency . Guidance on Characterization of Drinking Water Exposure for Dietary

Risk Assessment. December 13, 2007
. 3. U.S. Environmental Prote ction Agency (1999) Estimating the Drinking Water Component of a Dietary Exposure Assessment. http://www.epa.gov/oppfead1/trac/science/#drinking 4. U.S. Environmental Protection Agency (2000a). Development and Use of Distributions of Pesticide Concentrations in Drinking Water for FQPA Exposure Assessments. FIFRA SAP Meeting

– February

29

– March 3, 2000. http://www.epa.gov/oscpmont/sap/meetings/2000/index.htm
. 5. June 2000 : Monitoring Strategies for Pesticides in Surface
- Derived Drinking Water. FIFRA SAP Meetin g - http://www.epa.gov/oscpmont/sap/meetings/2000/june/finwateronl y.pdf 6. U.S. Environmental Protection Agency (2000b). Progress Report on Estimating Pesticide Concentrations in Drinking Water and Assessing Water Treatment Effects on Pesticide Removal and Transformation. http://www.epa.gov/oscpmont/sap/meetings/2000/index.htm 7. Jones, R.D., K. Costello, J. Hetrick, J. L in, R. Parker, N. Thurman, C. Peck and G. Orrick. 2010. Development and Use of Percent Cropped Area Adjustment Factors in Drinking Water Exposure Assessments. Office of Pesticide Programs, USEPA. September 9, 2010 8. Jones, R.D., K. Costello, J. Hetrick, J. L in, R. Parker, N. Thurman and C. Peck. 2010. Dev elopment and Use of the Index Reservoir in Drinking Water Exposure Assessments. Office of Pesticides Programs, USEPA. April 15, 2010 9. SCI
- GROW Description http://www.epa.g ov/oppefed1/models/water/scigrow_description.htm 1 0 . Guidance for Selecting Input Parameters in Modeling the Environmental Fate and Transport of Pesticides, Version 2.1 (October 22, 2009) . Available at http://www.epa.gov/oppefed1/models/water/input_parameter_guidance.htm 11. U.S. Environmental Protection Agency (2007). Guidance for Developing a Tier II Drinking Water Exposure Assessment
. 12. Food and Agriculture Organization of the United Nations. FAO PESTICIDE DISPOSAL SERIES 8. Assessing Soil Contamination: A Reference Manual. Appendix 2. Parameters of pesticides that influence processes in the soil. Editorial Group, FAO Information Division: Rome, 2000. http://www.fao.org/DOCREP/003/X2570E/X2570E00.htm

### APPENDIX

**Structure of Cyprodinil** (4
- cycloprop yl

**Structure of CGA -**  **249287** (4
- cyclopropyl

**EPISUITE Output File for CGA** SMILES : c1c(C)nc(N)nc1(C2CC2) CHEM : MOL FOR : C8 H11 N3 **MOL WT : 149.20**

------------------------------ Physical Property Inputs: Water Solubility (mg/L): Vapor Pressure (mm Hg) : Henry LC (atm - m3/mole) : Log Kow (octanol - water): Boiling Point (deg C) : Melting Point (deg C) : Log Octanol - Water Partitio n Coef (SRC): Log Kow (KOWWIN v1.67 estimate) = 1.77 Boiling Pt, Melting Pt, Vapor Pressure Estimations (MPBPWIN v1.41): Boiling Pt (deg C): 277.53 (Adapted Stein & Brown method) Melting Pt (deg C): 86.92 (Mean or Weighted MP) **VP(mm Hg,25 deg C): 0.00162 (Modified Grain method)** 



### N N NH 2



### 36

cycloprop yl
- 6
- methyl
-N
- phenyl
- 2
- py rimidinamine )

cyclopropyl
- 6
- methylpy

rim idin
- 2
- amine)

**EPISUITE Output File for CGA -**  **249287** SMILES : c1c(C)nc(N)nc1(C2CC2)

------------------------------ EPI SUMMARY (v3.12)
-------------------------- Water Solubility (mg/L):
------ Vapor Pressure (mm Hg) : ------

m3/mole) :
------ water): ------ Boiling Point (deg C) :
------ Melting Point (deg C) :
------ n Coef (SRC): Log Kow (KOWWIN v1.67 estimate) = 1.77 Boiling Pt, Melting Pt, Vapor Pressure Estimations (MPBPWIN v1.41): Boiling Pt (deg C): 277.53 (Adapted Stein & Brown method) Melting Pt (deg C): 86.92 (Mean or Weighted MP) **Hg,25 deg C): 0.00162 (Modified Grain method)** 

### )

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

### 37

Water Solubility Estimate from Log Kow (WSKOW v1.41): **Water Solubility at 25 deg C (mg/L): 2352** log Kow used: 1.77 (estimated) no - melting pt equation used Water Sol Estimate from Fragme nts: Wat Sol (v1.01 est) = 4921.5 mg/L ECOSAR Class Program (ECOSAR v0.99h): Class(es) found: Aromatic Amines Henrys Law Constant (25 deg C) [HENRYWIN v3.10]: **Bond Method : 3.46E -**  **006 atm -**  **m3/mole** Group Method: Incomplete Henrys LC [VP/WSol estimate using EPI values]: 1.352E
- 007 atm
- m3/mole Probability of Rapid Biodegradation (BIOWIN v4.02): Biowin1 (Linear Model) : 0.5521 Biowin2 (Non
- Linear Model) : 0.5343 Expert Survey Biodegradation Results: Biowin3 (Ultimate Survey Model): 2.5848 (weeks
- months) Biowin4 (Primary Survey Model) : 3.3870 (days
- weeks ) Readily Biodegradable Probability (MITI Model): Biowin5 (MITI Linear Model) : 0.1900 Biowin6 (MITI Non
- Linear Model): 0.13 65 Ready Biodegradability Prediction: NO Atmospheric Oxidation (25 deg C) [AopWin v1.91]: Hydroxyl Radicals Reaction: OVERALL OH Rate Constant = 78.8956 E
- 12 cm3/molecule
- sec Half - Life = 0.136 Days (12
- hr day; 1.5E6 OH/cm3) H alf - Life = 1.627 Hrs Ozone Reaction: No Ozone Reaction Estimation Soil Adsorption Coefficient (PCKOCWIN v1.66): Koc : 47.33 Log Koc: 1.675 Aqueous Base/Acid
- Catalyzed Hydrolysis (25 deg C) [HYDROWIN v1.67]: Rate constants can NOT be estimated for this structure! BCF Estimate from Log Kow (BCFWIN v2.15): Log BCF = 0.663 (BCF = 4.607) log Kow used: 1.77 (estimated) Volatilization from Water: Henry LC: 3.46E
- 006 atm
- m3/mole (estimated by Bond SAR Method) Half - Life from Model River: 207.9 hours (8.664 days) Half - Life from Model Lake : 2371 hours (98.78 days) Removal In Wastewater Treatment: Total removal: 2.27 percent Total biodegradation : 0.09 percent Total sludge adsorption: 1.98 percent Total to Air: 0.20 percent (using 10000 hr Bio P,A,S) Removal In Wastewater Treatment: Total removal: 22.64 percent Total biodegradation : 20.84 percent Total sludge adsorption: 1.65 percent Total to Air: 0.16 percent

### 38 (using Biowin/EPA draft method) Level III Fugacity Model:

Mass Amount Half - Life Emissions (percent) (hr) (kg/hr) Air 0.235 3.25 1000 Water 36.1 900 1000 Soil 63.6 1.8e+003 1000 Sediment 0.11 8.1e+003 0 Persistence Time: 710 hr 

### SCi **- GROW Output Files (output for the parent, followed by output for the degradate):**  SCIGROW VERSION 2.3 ENVIRONMENTAL FATE AND EFFECTS DIVISION OFFICE OF PESTICIDE PROGRAMS U.S. ENVIRONMENTAL PROTECTION AGENCY

SCREENING MODEL FOR AQUATIC PESTICIDE EXPOSURE SciGrow version 2.3 chemical :Cyprodinil time is 9/24/2010 15: 6:21

------------------------------------------------------------------------ Application Number of Total Use Koc Soil Aerobic rate (lb/acre) applications (lb/acre/yr) (ml/g) metabolism (days)

------------------------------------------------------------------------ 0.421 3.0 1.263 1.70E+03 35.5

---------------------------------------- -------------------------------- groundwater screening cond (ppb) = 3.60E
- 02 ************************************************************************

### 39 SCIGROW VERSION 2.3 ENVIRONMENTAL FATE AND EFFECTS DIVISION OFFICE OF PESTICIDE PROGRAMS U.S. ENVIRONMENTAL PROTECTION AGENCY

SCREENING MODEL FOR AQUATIC PESTICIDE EXPOSURE SciGrow version 2.3 chemical:CGA
- 249287 ti me is 9/24/2010 15: 8:20

------------------------------------------------------------------------ Application Number of Total Use Koc Soil Aerobic rate (lb/acre) applications (lb/acre/yr) (ml/g) metabolism (days)

---------- -------------------------------------------------------------- 0.033 3.0 0.098 1.73E+02 72.0

------------------------------------------------------------------------ groundwater screening cond (ppb) = 5.01E
- 02 *** ********************************************************************* 

### Sample PRZM/EXAMS Output Files (Note that the Time Series or TS files were used **instead of the usual output files in determining the results): Cyprodinil:**  **CA almond** stored as CYPRODIN.out Chemical: Cyprodinil PRZM environment: CAalmond_WirrigSTD.txt modified Wedday, 13 June 2007 at 12:17:16 EXAMS environment: ir298.exv modified Tueday, 26 August 2008 at 06:14:07 Metfile: w23232.dvf modified Tueday, 26 August 2008 at 06:15:38 Wa ter segment concentrations (ppb) Year Peak 96 hr 21 Day 60 Day 90 Day Yearly 1961 6.773 6.6 6.018 5.027 4.564 2.583 1962 8.793 8.525 7.842 6.87 6.352 4.79 1963 13.92 13.53 12.7 11.28 10.41 7.162 1964 11.73 11.46 10.82 9.827 9.253 6.902 1965 11.58 11.3 10. 58 9.53 9.006 6.692 1966 11.53 11.25 10.48 9.515 8.956 6.616 1967 11.76 11.48 10.86 9.676 9.069 6.665 1968 11.6 11.32 10.46 9.485 8.905 6.534 1969 11.48 11.2 10.36 9.38 8.849 6.494 1970 11.52 11.36 10.68 9.571 8.952 6.564 1971 11.68 11.4 10.6 9.544 9.024 6 .675 1972 11.61 11.45 10.54 9.539 8.975 6.575 1973 11.28 11.01 10.39 9.418 8.838 6.472 1974 11.43 11.15 10.22 9.267 8.743 6.45 1975 11.81 11.57 10.65 9.564 8.975 6.494 1976 11.6 11.31 10.4 9.444 8.946 6.505 1977 11.51 11.22 10.5 9.436 8.87 6.526 1978 12 11.71 10.69 9.552 9.006 6.636 1979 11.61 11.32 10.44 9.385 8.858 6.522 1980 11.48 11.2 10.54 9.462 8.884 6.513 1981 11.49 11.21 10.45 9.386 8.826 6.499 1982 18.51 17.95 16.8 14.35 13.06 8.653 1983 13.6 13.29 12.4 11.62 11.02 8.212 1984 12.43 12.14 11.47 10 .47 9.889 7.39 1985 11.78 11.51 10.82 9.798 9.223 6.901 1986 12.07 11.77 10.98 9.876 9.276 6.833

### 40

1987 12.33 12.09 11.22 10.07 9.415 6.871 1988 11.72 11.56 10.78 9.805 9.24 6.766 1989 12.06 11.76 10.87 9.756 9.145 6.771 1990 11.62 11.42 10.66 9.63 9.123 6.7 62 Sorted results Prob. Peak 96 hr 21 Day 60 Day 90 Day Yearly 0.032258064516129 18.51 17.95 16.8 14.35 13.06 8.653 0.0645161290322581 13.92 13.53 12.7 11.62 11.02 8.212 0.0967741935483871 13.6 13.29 12.4 11.28 10.41 7.39 0.129032258064516 12.43 12.14 11. 47 10.47 9.889 7.162 0.161290322580645 12.33 12.09 11.22 10.07 9.415 6.902 0.193548387096774 12.07 11.77 10.98 9.876 9.276 6.901 0.225806451612903 12.06 11.76 10.87 9.827 9.253 6.871 0.258064516129032 12 11.71 10.86 9.805 9.24 6.833 0.290322580645161 11.81 11.57 10.82 9.798 9.223 6.771 0.32258064516129 11.78 11.56 10.82 9.756 9.145 6.766 0.354838709677419 11.76 11.51 10.78 9.676 9.123 6.762 0.387096774193548 11.73 11.48 10.69 9.63 9.069 6.692 0.419354838709677 11.72 11.46 10.68 9.571 9.024 6.675 0.451612903225806 11.68 11.45 10.66 9.564 9.006 6.665 0.483870967741936 11.62 11.42 10.65 9.552 9.006 6.636 0.516129032258065 11.61 11.4 10.6 9.544 8.975 6.616 0.548387096774194 11.61 11.36 10.58 9.539 8.975 6.575 0.580645161290323 11.6 11.32 10.54 9.53 8. 956 6.564 0.612903225806452 11.6 11.32 10.54 9.515 8.952 6.534 0.645161290322581 11.58 11.31 10.5 9.485 8.946 6.526 0.67741935483871 11.53 11.3 10.48 9.462 8.905 6.522 0.709677419354839 11.52 11.25 10.46 9.444 8.884 6.513 0.741935483870968 11.51 11.22 10.4 5 9.436 8.87 6.505 0.774193548387097 11.49 11.21 10.44 9.418 8.858 6.499 0.806451612903226 11.48 11.2 10.4 9.386 8.849 6.494 0.838709677419355 11.48 11.2 10.39 9.385 8.838 6.494 0.870967741935484 11.43 11.15 10.36 9.38 8.826 6.472 0.903225806451613 11.28 1 1.01 10.22 9.267 8.743 6.45 0.935483870967742 8.793 8.525 7.842 6.87 6.352 4.79 0.967741935483871 6.773 6.6 6.018 5.027 4.564 2.583 0.1 13.483 13.175 12.307 11.199 10.3579 7.3672 Average of yearly averages: 6.60093333333333 Inputs generated by pe5.p l - Novemeber 2006 Data used for this run: Output File: CYPRODIN Metfile: w23232.dvf PRZM scenario: CAalmond_WirrigSTD.txt EXAMS environment file: ir298.exv Chemical Name: Cyprodinil Description Variable Name Value Units Comments Molecular weight mwt 225.29 g/mol Henry's Law Const. henry 7.04e
- 8 atm - m^3/mol Vapor Pressure vapr 3.80e
- 6 torr Solubility sol 13 mg/L Kd Kd mg/L Koc Koc 1745 mg/L Photolysis half
- life kdp 0 days Half - life Aerobic Aquatic Metabolism kbacw 382.3 days Halfife Anaerobic Aquatic Metabolism kbacs 0 days Halfife Aerobic Soil Metabolism asm 44.3 days Halfife Hydrolysis: pH 7 0 days Half - life Method: CAM 2 integer See PRZM manual Incorporation Depth: DEPI 0.0 cm

### 41

Application Rate: TAPP 0.472 kg/ha Application Efficiency: APPEFF 0.95 fr action Spray Drift DRFT 0.16 fraction of application rate applied to pond Application Date Date 01
- 03 dd/mm or dd/mmm or dd
- mm or dd - mmm Interval 1 interval 21 days Set to 0 or delete line for single app. app. rate 1 apprate 0.472 kg/ha Interval 2 interval 7 days Set to 0 or delete line for single app. app. rate 2 apprate 0.472 kg/ha Record 17: FILTRA

IPSCND 1 UPTKF 0 Record 18: PLVKRT 0

PLDKRT 0 FEXTRC 0.5 Flag for Index Res. Run IR Reservoir Flag for runoff calc. RUNOFF total none, monthly or total(average of entire run)


### CGA **- 249287: CA almond**  stored as CGA_249287.out Chemical: CGA
- 249287 PRZM environment: CAalmond_WirrigSTD.txt modified Wedday, 13 June 2007 at 12:17:16 EXAMS environment: ir298.exv modified Tueday, 26 August 2008 at 06:14:07 Metfile: w23232.dvf modified Tueday, 26 August 2008 at 06:15:38 Water segment concentrations (ppb) Year Peak 96 hr 21 Day 60 Day 90 Day Yearly 1961 0.6052 0.5873 0.558 0.4729 0.4133 0.1633 1962 0.8305 0.8112 0.736 0.6165 0.5223 0.305 1963 1.228 1.196 1.14 3 0.9996 0.8743 0.4069 1964 0.6063 0.5869 0.5643 0.4817 0.4191 0.179 1965 0.6013 0.5838 0.5521 0.4713 0.4092 0.1609 1966 0.6408 0.6214 0.5773 0.5006 0.4381 0.184 1967 0.6925 0.6738 0.6241 0.5325 0.4708 0.1998 1968 0.6391 0.6217 0.5719 0.4895 0.4266 0.1726 1969 0.6136 0.5957 0.5542 0.4803 0.4205 0.167 1970 0.661 0.6416 0.6092 0.5116 0.4416 0.1867 1971 0.6365 0.6171 0.5764 0.4928 0.4336 0.1824 1972 0.6708 0.6513 0.5871 0.503 0.4414 0.1736 1973 0.5761 0.5576 0.539 0.4588 0.3994 0.1619 1974 0.6202 0.6028 0.5446 0.475 0.4176 0.17 1975 0.6732 0.6504 0.583 0.4888 0.4208 0.165 1976 0.6512 0.6318 0.5767 0.4953 0.428 0.1661 1977 0.611 0.5906 0.5616 0.471 0.4123 0.1661 1978 0.7302 0.7112 0.6421 0.5429 0.4841 0.1975 1979 0.6531 0.6371 0.592 0.5137 0.4537 0.1843 1980 0.6534 0.634 0.5806 0.4911 0.4268 0.1684 1981 0.6244 0.6071 0.5845 0.5061 0.4483 0.1851 1982 1.586 1.539 1.416 1.119 0.9401 0.3598 1983 0.7002 0.6798 0.6318 0.5672 0.5034 0.2042 1984 0.6017 0.5822 0.5525 0.4743 0.4141 0.1669 1985 0.5896 0.5727 0.5457 0.470 2 0.4094 0.174 1986 0.6866 0.6674 0.6356 0.5473 0.479 0.1977 1987 0.7964 0.7747 0.7235 0.6156 0.5479 0.2197 1988 0.6774 0.6595 0.6241 0.564 0.501 0.2028 1989 0.6747 0.6552 0.6159 0.5347 0.4695 0.1987 1990 0.6648 0.6452 0.6036 0.5147 0.4565 0.1884 Sorted r esults Prob. Peak 96 hr 21 Day 60 Day 90 Day Yearly

### 42

0.032258064516129 1.586 1.539 1.416 1.119 0.9401 0.4069 0.0645161290322581 1.228 1.196 1.143 0.9996 0.8743 0.3598 0.0967741935483871 0.8305 0.8112 0.736 0.6165 0.5479 0.305 0.129032258064516 0.7964 0.7747 0.7235 0.6156 0.5223 0.2197 0.161290322580645 0.7302 0.7112 0.6421 0.5672 0.5034 0.2042 0.193548387096774 0.7002 0.6798 0.6356 0.564 0.501 0.2028 0.225806451612903 0.6925 0.6738 0.6318 0.5473 0.4841 0.1998 0.258064516129032 0.6866 0.6674 0.6241 0.5429 0.4 79 0.1987 0.290322580645161 0.6774 0.6595 0.6241 0.5347 0.4708 0.1977 0.32258064516129 0.6747 0.6552 0.6159 0.5325 0.4695 0.1975 0.354838709677419 0.6732 0.6513 0.6092 0.5147 0.4565 0.1884 0.387096774193548 0.6708 0.6504 0.6036 0.5137 0.4537 0.1867 0.419354838709677 0.6648 0.6452 0.592 0.5116 0.4483 0.1851 0.451612903225806 0.661 0.6416 0.5871 0.5061 0.4416 0.1843 0.483870967741936 0.6534 0.6371 0.5845 0.503 0.4414 0.184 0.516129032258065 0.6531 0.634 0.583 0.5006 0.4381 0.1824 0.548387096774194 0.65 12 0.6318 0.5806 0.4953 0.4336 0.179 0.580645161290323 0.6408 0.6217 0.5773 0.4928 0.428 0.174 0.612903225806452 0.6391 0.6214 0.5767 0.4911 0.4268 0.1736 0.645161290322581 0.6365 0.6171 0.5764 0.4895 0.4266 0.1726 0.67741935483871 0.6244 0.6071 0.5719 0.4 888 0.4208 0.17 0.709677419354839 0.6202 0.6028 0.5643 0.4817 0.4205 0.1684 0.741935483870968 0.6136 0.5957 0.5616 0.4803 0.4191 0.167 0.774193548387097 0.611 0.5906 0.558 0.475 0.4176 0.1669 0.806451612903226 0.6063 0.5873 0.5542 0.4743 0.4141 0.1661 0.83 8709677419355 0.6052 0.5869 0.5525 0.4729 0.4133 0.1661 0.870967741935484 0.6017 0.5838 0.5521 0.4713 0.4123 0.165 0.903225806451613 0.6013 0.5822 0.5457 0.471 0.4094 0.1633 0.935483870967742 0.5896 0.5727 0.5446 0.4702 0.4092 0.1619 0.967741935483871 0.57 61 0.5576 0.539 0.4588 0.3994 0.1609 0.1 0.82709 0.80755 0.73475 0.61641 0.54534 0.29647 Average of yearly averages: 0.198593333333333 Inputs generated by pe5.pl - Novemeber 2006 Data used for this run: Output File: CGA_249287 Metfile: w23232.dvf P RZM scenario: CAalmond_WirrigSTD.txt EXAMS environment file: ir298.exv Chemical Name: CGA - 249287 Description Variable Name Value Units Comments Molecular weight mwt 149.20 g/mol Henry's Law Const. henry 3.46e
- 6 atm - m^3/mol Vapor Pressure vapr 1.62e
- 3 torr Solubility sol 2352 mg/L Kd Kd 3.97 mg/L Koc Koc mg/L Photolysis half
- life kdp 0 days Half - life Aerobic Aquatic Metabolism kbacw 432 days Halfife Anaerobic Aquatic Metabolism kbacs 0 days Halfife Aerobic Soil Metabolism asm 216 days Halfife Hydrolysis: pH 7 0 days Half - life Method: CAM 2 integer See PRZM manual Incorporation Depth: DEPI 0.0 cm Application Rate: TAPP 0.0367 kg/ha Application Efficiency: APPEFF 0.95 fraction Spray Drift DRFT 0.16 fraction of application rate applied to pond Application Date Date 01
- 03 dd/mm or dd/mmm or dd
- mm or dd - mmm Interval 1 interval 21 days Set to 0 or delete line for single app. app. rate 1 apprate 0.0367 kg/ha Interval 2 interval 7 days Set to 0 or delete line for single app.

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app. rate 2 apprate 0.0367 kg/ha Record 17 : FILTRA

IPSCND 1 UPTKF 0 Record 18: PLVKRT 0

PLDKRT 0 FEXTRC 0.5 Flag for Index Res. Run IR Reservoir Flag for runoff calc. RUNOFF total none, monthly or total(average of entire run)