National Water-Quality Assessment Program

Estimated Annual Agricultural Pesticide Use for Counties 

of the Conterminous United States, 2008–12

EXPLANATION

< 0.02

0.02–0.09

0.10–0.34

0.35–1.05

> 1.06

Estimated use on agricultural land, 

in pounds per square mile

No estimated use

2008

2012

Estimated Agricultural Use for Clothianidin EPest-Low

Data Series 907

U.S. Department of the Interior

U.S. Geological Survey
Cover: Maps showing Estimated Agricultural Use for Clothianidin EPest-Low in 2008 and 2012, as an example of data within report.
Estimated Annual Agricultural Pesticide 

Use for Counties of the Conterminous 

United States, 2008–12

By Nancy T. Baker and Wesley W. Stone

National Water-Quality Assessment Program

Data Series 907

U.S. Department of the Interior

U.S. Geological Survey
U.S. Department of the Interior

SALLY JEWELL, Secretary

U.S. Geological Survey

Suzette M. Kimball, Acting Director

U.S. Geological Survey, Reston, Virginia: 2015

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Suggested citation:

Baker, N.T., and Stone, W.W., 2015, Estimated annual agricultural pesticide use for counties of the conterminous 

United States, 2008–12: U.S. Geological Survey Data Series 907, 9 p., http://dx.doi.org/10.3133/ds907.

ISSN 2327-638X (online)
iii

Contents

Abstract...........................................................................................................................................................1

Introduction ....................................................................................................................................................1

Purpose and Scope ......................................................................................................................................1

Methods for Estimating Pesticide Use.......................................................................................................2

Pesticide-Use Data from Surveys......................................................................................................3

Harvested-Crop Acres .........................................................................................................................3

EPest Extrapolated Rates ....................................................................................................................4

EPest-Low and EPest-High ........................................................................................................4

Pesticide-Use Estimates for California .............................................................................................8

Estimated Annual Pesticide Use ................................................................................................................8

References Cited............................................................................................................................................8

Appendixes .....................................................................................................................................................9

Figures

1. Map showing county boundaries and U.S. Department of Agriculture Crop 

Reporting Districts and Farm Resources Regions of the conterminous 

United States .................................................................................................................................2

2. Graphs showing percentage of acres reported by the 2007 and 2012 Agricultural 

Censuses, County Agricultural Production Survey (2008–11), and acres derived 

from linear interpolation for each crop in the conterminous United States.......................5

3. Map showing an example decision process for calculating an estimated pesticide 

use (EPest) rate when a Crop Reporting District (CRD) rate is not reported or 

is considered missing ..................................................................................................................7

Appendixes 

Appendixes are available online at: http://dx.doi.org/10.3133/ds0907.

1. List of Crops and Pesticides for which Estimates Were Made 

2. EPest-Low and EPest-High Use Estimates
iv

Conversion Factors

 Inch/pound to International System of Units

Multiply By To obtain

Area

acre 4,047 square meter (m2

)

acre 0.4047 hectare (ha)

acre 0.4047 square hectometer (hm2

) 

acre 0.004047 square kilometer (km2

)

International System of Units to Inch/pound

Multiply By To obtain

Mass

kilogram (kg) 2.205 pound avoirdupois (lb)

Abbreviations

Ag Census Census of Agriculture

CAPS County Agricultural Production Survey

CRD Crop Reporting District

DPR-PUR Department of Pesticide Regulation-Pesticide Use Reports (California)

EPest estimated pesticide use

FIPS Federal Information Processing Standard

NAWQA National Water-Quality Assessment Program
Estimated Annual Agricultural Pesticide Use for Counties 

of the Conterminous United States, 2008–12

By Nancy T. Baker and Wesley W. Stone

Abstract

Annual county-level pesticide use was estimated for 423 

herbicides, insecticides, and fungicides applied to agricultural crops grown in the conterminous United States during 

2008–12. For all States except California, pesticide-use data 

were compiled from proprietary surveys of farm operations 

located within U.S. Department of Agriculture Crop Reporting 

Districts (CRDs). Surveyed pesticide-use data were used in 

conjunction with county annual harvested-crop acres reported 

by the U.S. Department of Agriculture 2007 and 2012 Censuses of Agriculture and the 2008–11 County Agricultural Production Survey to calculate use rates per harvested-crop acre, 

or an “estimated pesticide use” (EPest) rate, for each crop by 

year. County-use estimates were then calculated by multiplying EPest rates by harvested-crop acres for each pesticide crop 

combination. Use estimates for California were obtained from 

annual Department of Pesticide Regulation-Pesticide Use 

Reports. 

Proprietary surveyed pesticide-use data were not available for all CRDs and years. When pesticide-survey data were 

unavailable for a CRD in a particular year, EPest extrapolated rates were calculated from adjoining or nearby CRDs to 

ensure that pesticide use was estimated for all counties where 

harvested-crop acres were reported. Two estimation methods were used—EPest-low and EPest-high—and differed in 

how they treated situations when a CRD was surveyed and 

pesticide use was not reported for a particular pesticide-bycrop combination. California pesticide-use estimates were 

not extrapolated; therefore, EPest-low and EPest-high are the 

same for counties in California.

This data series is a continuation of the 1992–2009 pesticide-use estimates reported by Stone (2013). It is an update of 

estimates for 2008–9 (Stone, 2013), as well as an update of the 

2010–11 preliminary estimates reported by Baker and Stone 

(2013). EPest values from these compilations (1992–2012) are 

suitable for making national, regional, and watershed assessments of annual pesticide use. County-level estimates are 

provided to make it easier to compile watershed assessments; 

however, users should be aware there is a greater degree of 

uncertainty in individual county-level estimates when compared to CRD or State-level estimates. This report provides 

EPest-low and EPest-high annual agricultural pesticide use for 

counties of the conterminous United States for 423 compounds 

during 2008–12 in tab-delimited files organized by compound, 

year, State Federal Information Processing Standard (FIPS) 

code, county FIPS code, and amount in kilograms (kg).

Introduction 

The U.S. Geological Survey National Water-Quality 

Assessment (NAWQA) Program, which began in 1991, conducts national-scale assessments of the occurrence and trends 

of pesticides in streams and groundwater of the United States. 

Direct measurement of pesticide concentrations in all of the 

Nation’s streams and aquifers would be ideal but the high cost 

of monitoring and analysis makes this not possible. Therefore, 

statistical models and other types of models are developed and 

used for predicting water-quality conditions for streams and 

groundwater that are not sufficiently monitored. Pesticide-use 

estimates are crucial predictive components of these models.

In addition, understanding changes in stream and groundwater pesticide concentrations over time (trend analysis) 

requires annual pesticide-use estimates that are compiled 

and developed with consistent methods. Annual county-level 

pesticide-use estimates have been used in conjunction with 

long-term pesticide trend analysis in streams (Ryberg and others, 2014) and groundwater (Toccalino and others, 2014).

Purpose and Scope 

The purpose of this report is to provide estimated annual 

pesticide use, referred to as EPest-low and EPest-high, for 

423 pesticides for each county in the conterminous United 

States. Methods used to compile EPest-low and EPest-high 

also are provided. This data series is a continuation of the 

1992–2009 pesticide-use estimates reported by Stone (2013). 

It is an update of estimates for 2008–9 (Stone, 2013), as well 

as an update of the 2010–11 preliminary estimates reported 

by Baker and Stone (2013). Estimates of annual agricultural 

pesticide use are provided via this report as downloadable, 
2

Estimated Annual Agricultural Pesticide Use for Counties of the Conterminous United States, 2008–12

tab-delimited files, which are organized by compound, year, 

State Federal Information Processing Standard (FIPS) code, 

county FIPS code, and amounts in kilograms (kg). 

Methods for Estimating Pesticide Use

For all States except California, pesticide-use data compiled by proprietary surveys of farm operations located within 

U.S. Department of Agriculture Crop Reporting Districts 

(CRDs)—a collection of contiguous counties within each 

State (fig. 1)—were used in conjunction with county annual 

harvested-crop acres reported by the U.S. Department of Agriculture (2009, 2014), 2007 and 2012 Censuses of Agriculture 

(Ag Census); and 2008–11 County Agricultural Production 

Survey (CAPS), (U.S. Department of Agriculture-National 

Agricultural Statistics Service, Various years) to calculate use 

rates per harvested-crop acre, or an ‘estimated pesticide use’ 

(EPest) rate, for each crop by year. County-use estimates were 

then calculated by multiplying EPest rates by harvested-crop 

acres for each pesticide crop combination. The methods documented in this report follow methods developed by Thelin and 

Stone (2013). 

0 250 500 750 MILES

0 250 500 750 KILOMETERS

120°

70°

80°

90°

100°

110°

45°

40°

35°

30°

Figure 1. County boundaries and U.S. Department of Agriculture Crop Reporting Districts and Farm Resources Regions 

of the conterminous United States.

Eastern Uplands East

Eastern Uplands West

Fruitful Rim Northwest

Fruitful Rim Southeast

Fruitful Rim Texas

Fruitful Rim West

Basin and Range

Heartland

Mississippi Portal

Northern Crescent East

Northern Cresent West

Northern Great Plains

Prairie Gateway

Southern Seaboard East

Southern Seaboard West

EXPLANATION

Crop Reporting District

County

Farm Resources Region

1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

11

12

13 14

15

6

7

8

9

10

1

2

3

4

5

1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

11

12

13 14

15

6

7

8

9

10

1

2

3

4

5

Base from U.S. Geological Survey digital data, 2005, 1:2,000,000

Albers Equal-Area Conic projection

Standard parallels 29o30’N and 45o30’N, central meridian 96o00’W

Figure 1. County boundaries and U.S. Department of Agriculture Crop Reporting Districts and Farm Resources Regions of the 

conterminous United States.
Methods for Estimating Pesticide Use

3

Pesticide-survey data were not available for all CRDs and 

years. When data were unavailable for a CRD in a particular 

year, EPest extrapolated rates were calculated from adjoining 

or nearby CRDs to ensure that pesticide use was estimated 

for all counties within CRDs where harvested-crop acres 

were reported. Pesticide-survey data and EPest extrapolated 

rates are based on harvested-crop acres within a CRD, but 

many NAWQA modeling applications and analyses require 

pesticide-use estimates at the county scale. Therefore, EPest 

was disaggregated from CRDs to the individual counties and 

estimates were then calculated by multiplying EPest rates 

by annual county harvested-crop acres for each pesticide 

crop combination. EPest extrapolated rate determination and 

subsequent application to county harvested-crop acres differs 

between EPest-low and EPest-high methods. Use estimates for 

California were obtained from annual Department of Pesticide 

Regulation-Pesticide Use Reports (DPR-PUR) and used without extrapolation; therefore, EPest-low and EPest-high are the 

same for counties in California.

Pesticide-Use Data from Surveys

Methods for obtaining surveyed pesticide-use data for 

this compilation are the same as for the 1992–2009 compilation (Stone, 2013). Survey methods reported by Thelin and 

Stone (2013) are reiterated here for context in this (2008–12) 

compilation-method description. 

Proprietary data from GfK Kynetec, Inc., on the amounts 

of pesticides applied to individual crops by CRDs are the primary source of information used in this study and are referred 

to as “pesticide-survey” data in the remainder of this report. 

The pesticide-survey data are based on agricultural pesticideuse surveys of more than 20,000 farm operations distributed 

throughout the conterminous United States (GfK Kynetec, 

AgroTrak Quality Management Plan, written commun., 

August 2011). Data from the Ag Census on the size (in acres) 

and number of farms that grow individual crops and represent 

selected land uses, such as pasture, are used to stratify all 

farms in the United States by size and to allocate the number of farms that will be surveyed in each strata. The survey 

design allocates a greater proportion of the sample to larger 

farm operations so that a greater percentage of crop acres are 

represented, with the goal of more accurate characterization 

of farm operations and pesticide-use patterns. Surveys of farm 

operations within each CRD are extrapolated to represent total 

pesticide use for that CRD. The likelihood of underestimating 

or overestimating use for less widely used pesticides increases 

because not all farms within a CRD are surveyed. Use estimates for 423 pesticides that are applied to a variety of row, 

specialty, fruit, and nut crops are reported by multi-county 

areas, referred to as CRDs. The CRD to county geospatial 

relation is shown in figure 1. All surveyed pesticides and crops 

included in this compilation are listed in appendix 1, tables 

1–1 through 1–3.

Harvested-Crop Acres

County annual harvested-crop acres reported in the 2007 

and 2012 Ag Census (U.S. Department of Agriculture, 2009, 

2014) and 2008–11 CAPS (U.S. Department of AgricultureNational Agricultural Statistics Service, Various years) were 

used in this compilation. The Ag Census is the most uniform 

and complete source of crop-acre estimates for all counties in 

the United States. The Ag Census is published every 5th year 

with CAPS reporting crop-acre estimates for selected crops 

and counties for interim Ag Census years. 

Both Ag Census and CAPS report data for planted- and 

harvested-crop acres, but planted acres are only available 

for a limited number of crops and are not always available 

for all crops that are contained in the pesticide-survey data. 

Therefore, harvested acres, rather than planted acres, were 

used to develop annual pesticide-by-crop use rates. In taking 

this approach, it is recognized that use-rate estimates could 

be numerically greater than actual use rates on planted crops 

because not all planted acres are harvested. Annual harvestedcrop acres by county data were used to calculate the pesticideby-crop use rates for each crop and CRD surveyed, and to 

estimate pesticide use for all counties that report harvested 

acres in the conterminous United States. 

A list of the 58 crops for which EPest use rates were 

developed and the Ag Census and CAPS crop names for which 

acres data were obtained is given in table 1–1. For some crops, 

it was necessary to combine subcategories of Ag Census and 

CAPS acres to match pesticide-survey data. For example, Ag 

Census reports harvested acres for “BLACKBERRIES AND 

DEWBERRIES (INCLUDING MARIONBERRIES),” “BOYSENBERRIES,” “LOGANBERRIES,” and “RASPBERRIES, ALL,” while the pesticide-survey data contain the crop 

category “Caneberries.” In this instance, Ag Census harvestedcrop acres were summed to better match the pesticide-survey 

data. Conversely, the pesticide-survey data contain the crop 

categories “Grapes, Raisin,” “Grapes, Table,” and “Grapes, 

Wine,” while Ag Census reports only “GRAPES.” In this case, 

pesticide-survey data were summed to match the Ag Census 

report. Ag Census crop acres that were combined to match 

pesticide-survey data are given in table 1–1. 

In some cases, when a small number of farms within a 

county produce a crop, Ag Census and CAPS do not report 

county acres for that particular crop because of census nondisclosure rules that protect the identity of individual farm operations. Both Ag Census and CAPS include the nondisclosed 

county crop acres in State total acres. To estimate county crop 

acres in these cases, total reported county crop acres for each 

State were subtracted from total reported State crop acres to 

determine the number of nondisclosed crop acres for each 

State. To allocate those acres back to “nondisclosed” counties, 

crop acres were proportioned to individual counties based on 

the proportion of total agricultural land within each county. 

The proportion of total agricultural land within each county 

was determined from the 2011 National Land Cover Data (Jin 

and others, 2013). 
4

Estimated Annual Agricultural Pesticide Use for Counties of the Conterminous United States, 2008–12

CAPS data are used to supply crop-acre estimates for 

non-census years because Ag Census data are available only 

every 5th year. CAPS are conducted in 44 States for selected 

crops (http://www.nass.usda.gov/Surveys/Guide_to_NASS_

Surveys/County_Agricultural_Production). Crops selected for 

county surveys are specific to each State and may change from 

year to year. Crops included in CAPS are primarily field crops 

such as barley, corn, cotton, and rice. Only a few vegetables 

and no fruit crops are included in CAPS (all CAPS crops are 

listed in table 1–1). 

CAPS do not include acres for every crop/county/year 

combination used in this compilation; therefore, linear interpolation was used to fill gaps where county harvested crop acres 

were missing. Interpolation was done for each individual crop 

prior to combining subcategories of crops for every county. 

For many crops, CAPS data were not available for any county 

for the inter-Ag Census period (2008–11), and crop acres were 

interpolated entirely from Ag Census data. For crops where 

CAPS data were available, interpolation was done on those 

counties with missing data. The percentage of acres derived 

from interpolation for each crop is shown in figure 2. Interpolation is done for each county and crop before crops are 

combined into categories. For a small number of counties and 

crops, harvested acres were missing (indicated with a blank—

zero acres are indicated with a dash in Ag Census data) in 

either the 2007 or 2012 Ag Census. When this was the case, 

Ag Census acres for the missing data were interpolated from 

either U.S. Department of Agriculture-National Agricultural 

Statistics Service acres or the remaining available Ag Census 

value resulting in a small percentage of interpolated acres for 

Ag Census (see Caneberries graph in fig. 2). It is recognized 

that interpolation may overestimate or underestimate crop 

acres, especially in areas of the country where CAPS data are 

limited. 

EPest Extrapolated Rates

The following section describes methods developed by 

Thelin and Stone (2013) to estimate agricultural pesticide use 

for counties in the conterminous United States—except those 

in California—that were in unsurveyed CRDs but where crops 

were grown and pesticide use was likely. For all surveyed 

CRDs, pesticide-by-crop use rates were calculated from either 

surveyed pesticide use divided by surveyed crop acres, or 

surveyed pesticide use divided by Ag Census or CAPS crop 

acres. When a CRD was surveyed but harvested-crop acres 

from Ag Census and CAPS were greater than the surveyed 

crop acres, rates were calculated from the surveyed pesticide 

use and the total Ag Census and CAPS harvested acres for the 

CRD. For unsurveyed CRDs, EPest extrapolated rates were 

developed by using surveyed rates from nearby CRDs or from 

surveyed and extrapolated rates from CRDs in the same U.S. 

Department of Agriculture Farm Resources Region (fig. 1). A 

surveyed rate or an extrapolated rate, depending on the CRD, 

was then applied to county harvested acres to estimate pesticide use on individual crops grown in each county. 

To ensure that pesticide-use estimates accounted for all 

acreage that could have been treated, extrapolated use rates 

were developed for individual pesticides and crops in unsurveyed CRDs through a set of decision rules that depend on 

the availability of rates from surrounding CRDs (Thelin and 

Stone, 2013). The decision process included developing three 

types of extrapolated pesticide-by-crop use rates, referred 

to as tier 1, tier 2, and regional rates. Tier 1 CRDs are any 

contiguous CRD surrounding the unsurveyed CRD regardless 

of whether the tier 1 CRD is within the same Farm Resourc 

Regions(fig. 3). Tier 1 CRDs surrounding the unsurveyed 

CRD were searched, and if one or more surveyed pesticideby-crop use rate existed, the median rate was used from 

these surveyed rates to estimate pesticide-by-crop use for the 

counties in the unsurveyed CRD. If a tier 1 rate could not be 

established because there were no surveyed rates available, 

then tier 2 CRDs were searched to determine if three or more 

of the tier 2 CRDs had surveyed rates (fig. 3). If so, then the 

median value of these rates was applied to the unsurveyed 

CRD. Finally, if a tier 1 or tier 2 EPest rate could not be 

determined, then a regional rate was calculated for the Farm 

Resources Region and applied to county crop acres within 

the CRD. Regional rates were the median of all non-zero 

EPest rates, including surveyed, tier 1, and tier 2 EPest from 

the same Farm Resources Region. It is important to understand that the process is iterative, so that for each unsurveyed 

CRD within a region, tier 1 rates are calculated first, then tier 

2 rates, regardless of whether the CRD is within the Farm 

Resources Region. After the tier 1 and tier 2 rates have been 

established, a regional rate is calculated. Duplicate extrapolated rates were removed prior to the calculation to reduce the 

influence of duplicate extrapolated EPest rates on the calculation of regional rates because the same CRD may be used to 

calculate tier 2 rates within a region. 

EPest-Low and EPest-High

Two variations on the previously described method were 

developed to yield EPest-low and EPest-high for counties in 

the conterminous United States other than California (Thelin 

and Stone, 2013) because uncertainties are inherent in the 

EPest extrapolation. Calculating two values allows the user 

to select the method that best suits the application for which 

these estimates are used. Both methods incorporated surveyed 

and extrapolated rates to estimate pesticide use for counties, 

but EPest-low and EPest-high estimations differed in how they 

treated situations when a CRD was surveyed and pesticide use 

was not reported for a particular pesticide-by-crop combination. If use of a pesticide on a crop was not reported in a 

surveyed CRD, EPest-low reports zero use in the CRD for that 

pesticide-by-crop combination. EPest-high, however, treats 

the unreported use for that pesticide-by-crop combination in 

the CRD as unsurveyed, and pesticide-by-crop use rates from 

neighboring CRDs and, in some cases, CRDs within the same 

Farm Resources Region are used to calculate the pesticide-bycrop EPest-high rate for the CRD. 
Methods for Estimating Pesticide Use

5

Figure 2. Percentage of acres reported by the 2007 and 2012 Agricultural Censuses (U.S. Department of Agriculture, 2009, 2014), 

County Agricultural Production Survey (2008–11), and acres derived from linear interpolation for each crop in the conterminous 

United States. Estimated crop area, in percent

Alfalfa Almonds Apples Apricots Artichoke

Asparagus Barley Beans (Snap, Bush, 

Pole, String)

Broccoli Cabbage

Caneberries Canola (oilseed rape) Cantaloupes Carrots Cauliflower

Celery

07 08 09 10 11 12 07 08 09 10 11 12 07 08 09 10 11 12 07 08 09 10 11 12 07 08 09 10 11 12 0

20

40

60

80

100

20

40

60

80

100

20

40

60

80

100

0

20

40

60

80

100

20

40

60

80

100

0

20

40

60

80

100

Figure 2. Percentage of acres reported by the 2007 and 2012 Agricultural Censuses (U.S. Department of Agriculture, 2009, 2014), 

County Agricultural Production Survey (2008-11), and acres derived from linear interpolation for each crop in the 

conterminous United States.

Dry Beans/Peas Fallow Garlic Grapefruit Grapes

Hazelnuts Lemons Lettuce Lima Beans Onions

Reported acres

EXPLANATION

Interpolated acres

Cherries Corn Cotton Cucumbers
6

Estimated Annual Agricultural Pesticide Use for Counties of the Conterminous United States, 2008–12

07 08 09 10 11 12 07 08 09 10 11 12

07 08 09 10 11 12 07 08 09 10 11 12 07 08 09 10 11 12

Percentage of acres reported by the 2007 and 2012 Agricultural Censuses (U.S. Department of Agriculture, 

2009, 2014), County Agricultural Production Survey (2008-11), and acres derived from linear interpolation for each 

crop in the conterminous United States.

Figure 2 cont.-- 

Reported acres Interpolated acres

EXPLANATION

Estimated crop area, in percent

0

20

40

60

80

100

0

20

40

60

80

100

0

20

40

60

80

100

0

20

40

60

80

100

0

20

40

60

80

100

0

20

40

60

80

100

Oranges Pastureland Peaches Peanuts Pears

Peas (Fresh/

Green/Sweet)

Pecans Peppers Pistachios Plums/Prunes

Potatoes Pumpkins Rice Sorghum (Milo) Soybeans

Spinach Squash Strawberries Sugar Beets Sugarcane

Sunflowers Sweet Corn Tobacco

Tomatoes Walnuts

Watermelons Wheat, Spring Wheat, Winter

Figure 2. Percentage of acres reported by the 2007 and 2012 Agricultural Censuses (U.S. Department of Agriculture, 2009, 2014), 

County Agricultural Production Survey (2008–11), and acres derived from linear interpolation for each crop in the conterminous 

United States.—Continued
Methods for Estimating Pesticide Use

7

Figure 3. An example decision process for calculating an estimated pesticide use (EPest) rate when a Crop Reporting District (CRD) 

rate is not reported or is considered missing. In this example, a surveyed rate for Missouri 70 was not reported; therefore, surveyed 

rates for all tier 1 CRDs (median) were used to calculate a rate for the unsurveyed CRD. If there are no surveyed tier 1 rates available for 

Missouri 70, then available surveyed rates for all tier 2 CRDs (median) are evaluated. When neither tier 1 nor tier 2 rates are available, 

regional rates a calculated from all unique surveyed tier 1 and tier 2 CRD rates (median) within a Farm Resources Region.

Kansas 40

Oklahoma 40

Missouri 70

Arkansas 10

Iowa 80

Tennessee 20

Iowa 90 Iowa 70

Mississippi 40

Illinois 90

Louisiana 

10

Kentucky 10

Nebraska 50

Nebraska 80 Nebraska 90

Nebraska 60

Kansas 50 Kansas 80

Kansas 10 Kansas 70

Kansas 20

Kansas 40

Kansas 90 Kansas 60

Oklahoma 50

Oklahoma 10

Oklahoma 20

Oklahoma 60

Oklahoma 30

Oklahoma 90

Oklahoma 80

Oklahoma 70

Texas 40 Texas 30

Texas 51

Texas 21

Texas 22

Louisiana 20 Louisiana 30

Mississippi 50

Mississippi 20

Mississippi 10 

Mississippi 70 Mississippi 

80

Mississippi 90 Mississippi 60 Mississippi 30

Tennessee 10

Arkansas 40

Arkansas 20

Arkansas 30

Arkansas 50 Arkansas 60

Arkansas 

Arkansas 80 90

Arkansas 70

Missouri 80

Missouri 90

Missouri 40 Missouri 50 Missouri 60

Missouri 10 Missouri 20

Missouri 30

Illinois 80

Illinois 60

Illinois 70

Illinois 30 Illinois 40

Illinois 50

Nebraska 70

Eastern Uplands West

Heartland

Mississippi Portal

Prairie Gateway

Southern Seaboard East

Southern Seaboard West

EXPLANATION

Tier 1 CRD extent

Tier 2 CRD extent

Farm Resources Region

Locator map with 

example extent

Crop Reporting District (CRD)

Example unsurveyed CRD

0 50 100 25 MILES

0 50 100 25 KILOMETERS

Base from U.S. Geological Survey digital data, 2005, 1:2,000,000

Albers Equal-Area Conic projection

Standard parallels 29°30’N and 45°30’N, central meridian 96°00’W

Figure 3. Example decision process for calculating an estimated pesticide use (EPest) rate when a Crop Reporting District (CRD) rate 

is not reported or is considered missing. In this example, a surveyed rate for Missouri 70 was not reported; therefore, surveyed rates 

for all tier 1 CRDs (median) were used to calculate a rate for the unsurveyed CRD. If there are no surveyed tier 1 rates available for 

Missouri 70, then available surveyed rates for all tier 2 CRDs (median) are evaluated. When neither tier 1 nor 2 rates are available, 

regional rates are calculated from all unique surveyed, tier 1 and tier 2 CRD rates (median) within a Farm Resources Region. 35° 40°

100° 90°
8

Estimated Annual Agricultural Pesticide Use for Counties of the Conterminous United States, 2008–12

Pesticide-Use Estimates for California

EPest-low and EPest-high estimates for California were 

not calculated using the method described in the previous 

section; instead, county totals were obtained from the online 

DPR-PUR database (California Department of Pesticide Regulation, 2014). Since 1990, California has required reporting of 

all agricultural pesticide use. DPR-PUR includes information 

on the pesticide applied, location and time of application, and 

the agricultural crop treated. Annual pesticide-use estimates 

by crop were retrieved from the online DPR-PUR database 

and merged with the EPest-low and EPest-high county data 

after the estimation process was completed for the rest of the 

country. A list of the 117 crops for which agricultural pesticide-use data were available is given in table 1–2. EPest-low 

and EPest-high estimates for counties in California are the 

same because California data were not extrapolated. Estimates 

are included in both EPest-low and EPest-high data tables to 

facilitate ease of use.

Estimated Annual Pesticide Use 

EPest-low and EPest-high annual agricultural pesticide 

use for counties of the conterminous United States for 423 

compounds during 2008–12 are provided in tab-delimited files 

organized by compound, year, State FIPS code, county FIPS 

code, and kg. Data files are available in appendix 2, tables 2–1 

through 2–14. This data series is a continuation of the 1992–

2009 pesticide-use estimates reported by Stone (2013). It is 

an update of Stone’s reported estimates for 2008–9, as well as 

an update of the 2010–11 preliminary estimates reported by 

Baker and Stone (2013).

EPest values from this study are suitable for making 

national, regional, and watershed assessments of annual pesticide use during 2008–12. Although estimates are provided by 

county to facilitate estimation of watershed pesticide use for a 

wide variety of watersheds, there is a greater degree of uncertainty in individual county-level estimates when compared 

to CRDs or State-level estimates because (1) EPest crop-use 

rates were developed on the basis of pesticide use on harvested acres in multi-county areas (CRDs) and then allocated 

to county harvested cropland; (2) pesticide-by-crop use rates 

were not available for all CRDs in the conterminous United 

States, and extrapolation methods were used to estimate pesticide use for those counties; and (3) it is possible that surveyed 

pesticide-by-crop use rates do not reflect all agricultural use on 

all crops grown. 

References Cited

Baker, N.T., and Stone, W.W., 2013, Preliminary estimates of 

annual agricultural pesticide use for counties of the conterminous United States, 2010–11: U.S. Geological Survey OpenFile Report 2013–1295, 2-p. pamphlet, 14 tables, http://pubs.

usgs.gov/of/2013/1295/.

California Department of Pesticide Regulation, Various years, 

Pesticide use reporting (PUR): Sacramento, Calif., Department of Pesticide Regulation, accessed April 2014 at 

http://www.cdpr.ca.gov/docs/pur/purmain.htm.

Jin, S., Yang, L., Danielson, P., Homer, C., Fry, J., and Xian, G., 

2013, A comprehensive change detection method for updating the National Land Cover Database to circa 2011: Remote 

Sensing of Environment, v. 132, p. 159–175, accessed April 

2014 at http://www.mrlc.gov/nlcd2011.php.

Ryberg, K.R., Vecchia, A.V., Gilliom, R.J., and Martin, J.D., 

2014, Pesticide trends in major rivers of the United States, 

1992–2010: U.S. Geological Survey Scientific Investigations Report 2014–5135, 63 p., http://pubs.usgs.gov/

sir/2014/5135/.

Stone, W.W., 2013, Estimated annual agricultural pesticide use 

for counties of the conterminous United States, 1992–2009: 

U.S. Geological Survey Data Series 752, 1-p. pamphlet, 

14 tables, http://pubs.usgs.gov/ds/752/.

Thelin, G.P., and Stone, W.W., 2013, Estimation of annual 

agricultural pesticide use for counties of the conterminous 

United States, 1992–2009: U.S. Geological Survey Scientific 

Investigations Report 2013–5009, 54 p., http://pubs.usgs.gov/

sir/2013/5009/. 

Toccalino, P.L., Gilliom, R.J., Lindsey, B.D., and Rupert, M.G., 

2014, Pesticides in groundwater of the United States—

Decadal-scale changes, 1993–2011: Groundwater, v. 52, p. 

112–125, http://pubs.er.usgs.gov/publication/70127095.

U.S. Department of Agriculture, 2009, 2007 Census of Agriculture, State and County Data, Volume 1, Geographic Area 

Series Part 1-50, AC-07-A-1—AC-07-A-50: Washington 

D.C., U.S. Department of Agriculture, National Agricultural 

Statistics Service, accessed May 2013 at http://www.agcensus.usda.gov/Publications/2007/. 

U.S. Department of Agriculture, 2014, 2012 Census of Agriculture, State and County Data, Volume 1, Geographic Area 

Series Part 1-50, AC-12-A-1—AC-12-A-50: Washington 

D.C., U.S. Department of Agriculture, National Agricultural 

Statistics Service, accessed May 2013 at http://www.agcensus.usda.gov/Publications/2012/.

U.S. Department of Agriculture-National Agricultural Statistics 

Service, Various years, Quick-Stats—Field crops: Washington D.C., U.S. Department of Agriculture, accessed May 

2014 at http://www.nass.usda.gov/Quick_Stats/.
Appendix

9

Appendixes

Appendixes are available online at: http://dx.doi.org/10.3133/ds0907.

Appendix 1. List of Crops and Pesticides for Which Estimates Were Made

1–1. Crops for which proprietary surveyed pesticide-use data were provided to U.S. 

Geological Survey for EPest compilation and matching Agricultural Census and County 

Agricultural Survey Program crop names. 

1–2. Crops for which California Department of Pesticide Regulation-Pesticide Use Reports 

were used for EPest compilation.

1–3. Pesticides for which proprietary surveyed pesticide-use data were provided to 

U.S. Geological Survey for EPest compilation. 

Appendix 2. EPest-Low and EPest-High Use Estimates

EPest-high county pesticide-use estimates, by pesticide name: 

2–1. 2, 4-D through Chlorantraniliprole 

2–2. Chlorethoxyfos through Diflufenzopyr 

 2–3. Dimethenamid through Gibberellic acid 

2–4. Glufosinate through Metiram 

2–5. Metolachlor through Propazine 

2–6. Propiconazole through Triasulfuron 

 2–7. Tribenuron methyl through Zoxamide 

EPest-low county pesticide-use estimates, by pesticide name: 

2–8. 2, 4-D through Chlorantraniliprole 

2–9. Chlorethoxyfos through Diflufenzopyr 

2–10. Dimethenamid through Gibberellic acid 

2–11. Glufosinate through Metiram 

2–12. Metolachlor through Propazine 

2–13. Propiconazole through Triasulfuron 

2–14. Tribenuron methyl through Zoxamide


Baker and Stone—Estimated Annual Agricultural Pesticide Use for Counties of the Conterminous United States, 2008–12—Data Series 907

ISSN 2327-638X (online)

http://dx.doi.org/10.3133/ds0907