### Chlor o picrin ( 08 1501 )

Screening Level Usage Analysis (SLUA)

Date: April 20

, 2012

What is a Screening Level Usage Analysis (SLUA)?

• Available estimates of pesticide usage data for a particular active ingredient that is used on

agricultural crops in the Un ited States.

• Pesticide usage data obtained from various sources. The data are then merged, averaged, and rounded

so that the presented information is not proprietary, business confidential, or trade secret.

What does it contain?

• Pesticide usage data for a single active ingredient only.

• Agricultural use sites (crops) that the pesticide is reported to be used on.

• Available pesticide usage information from U.S. states that produce 80% or more of a crop, in most

cases, or less than 80%, in rare cases, depend ing on the scope of the survey and available resources.

• Annual percent of crop treated (average & maximum) for each agricultural crop.

• Average annual pounds of the pesticide applied for each agricultural crop (i.e., for the states surveyed,

not for the ent ire United States).

What assumptions can I make about the reported data?

• Average pounds of active ingredient applied

- Values are calculated by merging pesticide usage data

sources together; averaging across all observations, then rounding. Note: If the estimated value is

less than 500, then that value is labeled <500. Estimated values between 500 & <1,000,000 are

rounded to 1 significant digit. Estimated values of 1,000,000 or greater are rounded to 2 significant

digits.)

• Average percent of crop treate d

- Values are calculated by merging data sources together; averaging

by year, averaging across all years, & rounding to the nearest multiple of 5. Note: If the estimated

value is less than 2.5, then the value is labeled <2.5. If the estimated value is less than 1, then the

value is labeled <1.

• Maximum percent of crop treated

- Value is the single maximum value reported across all data

sources, across all years, & rounded up to the nearest multiple of 5. Note: If the estimated value is

less than 2.5, t hen the value is labeled <2.5.

What are the data sources used?

• USDA

- NASS (United States Department of Agriculture’s National Agricultural Statistics Service)

– pesticide usage data from 2003 to 20 10

.

• Private pesticide market research

– pesticide usage data from 2003 to 2010.

• California Department of Pesticide Regulation (DPR) Pesticide Use Reporting (PUR) data for

2003 to 20 10

. What are the limitations to the data?

• Additional registered uses may exist but are not included because the available surveys do no t report

usage (e.g., small acreage crops).

• Lack of reported usage data for the pesticide on a crop does not imply zero usage.

• Usage data on a particular site may be noted in data sources, but not quantified . In these instances,

the site would not be repo rted in the SLUA.

• Non

- agricultural use sites (e.g., turf, post

- harvest, mosquito control, etc.) are not reported in the SLUA.

A separate request must be made to receive these estimates.

• Some sites show some use, even though they are not on the label. Thi s usage could be due to various

factors, including, but not limited to Section 18 requests, existing stocks of the chemical, data

collection errors, and experimental use permits (EUPs).

### January 30 , 2012

Screening Lev el Estimates of Agricultural Uses of Chlor o picrin (081501 )

Sorted Alphabetically

Crop

Lbs. A.I. Percent Crop Treated

Average Maximum

1 Almonds 20,000 <1 <2.5



### 2 Apples 3,000 <1 <2.5



### 3 Apricots * 3,000 <1 <2.5



### 4 Beans, Green 20,000 <1 <2.5



### 5 Broccoli 30,000 <2.5 <2.5



### 6 Cabbage 2,000 <1 <2.5



### 7 Caneberries 200,000 5 15



### 8 Cantaloupes 100,000 5 15



### 9 Carrots 50,000 <2.5 10



### 10 Celery 50,000 <2.5 <2.5



### 11 Cherries 30,000 <1 <2.5



### 12 Co rn 50,000 <1 <2.5



### 13 Cotton 60,000 <1 <2.5



### 14 Cucumbers 300,000 5 10



### 15 Dates * 1,000 <1 <2.5



### 16 Dry Beans/Peas 8,000 <1 <2.5



### 17 Garlic * 5,000 <1 <2.5



### 18 Grapes 50,000 <1 <2.5



### 19 Lemons 60,000 <1 <2 .5



### 2 0 Lettuce 60,000 <1 <2.5



### 2 1 Nectarines * 8,000 <1 <2.5



### 2 2 Onions 300,000 5 10



### 2 3 Oranges 10,000 <1 <2.5



### 2 4 Peaches 3,000 <1 <2.5



### 2 5 Peanuts 40,000 <1 <2.5



### 2 6 Pears 1,000 <1 <2.5



### 2 7 Pecans 10,000 <1 <2.5



### 2 8 Peppers 1,200,000 20 30



### 29 Pistachios * <500 <1 <2.5



### 3 0 Plums/Prunes <500 <1 <2.5



### 3 1 Pomegranates * <500 5 10



### 3 2 Potatoes 400,000 <2.5 <2.5



### 3 3 Pumpkins 30,000 <1 <2.5



### 3 4 Squash 100,000 5 20



### 3 5 Strawberries 3,100,000 55 75



### 3 6 Sugar Beets 30,000 <1 <2.5



### 3 7 Tobacco 1,800,000 20 25



### 38 Tomatoes 2,200,000 15 50

### 39 Walnuts 7,000 <1 <2.5



### 4 0 Watermelons 300,000 5 10



### 4 1 Wheat 90,000 <1 <2.5



### All numbers rounded.

< 500 Less than 500 pounds of active ingredient

<2.5 Less than 2.5 percent of crop treated

<1 Less than 1 percent of crop treated

* Based on CA DPR data only (valid because 80 % or more of U.S. acres grown are in California)

SLUA data sources include:

USDA

- NASS (United States Department of Agriculture's National Agricultural Statistics Service)

Private Pesticide Market Research

California DPR (Department of Pesticide Regulation)

These results reflect amalgamated data developed by the Agency and are r eleasable to the public.