U.S. Department of the Interior

U.S. Geological Survey

Data Series 630

National Water-Quality Assessment Program

Adjustment of Pesticide Concentrations for Temporal 

Changes in Analytical Recovery, 1992–2010

0

50

100

150

200

Recovery, in percent

Simazine groundwater matrix spikes: n: 999 Median: 96.3 Mean: 95.1 Standard deviation: 16.5

1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010

0

50

100

150

200

Recovery, in percent

Simazine stream−water matrix spikes: n: 1796 Median: 100.9 Mean: 100.5 Standard deviation: 19.3

1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010

0

50

100

150

200

Recovery, in percent

1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010

Comparison of lowess−modeled recovery

Groundwater matrix spikes

Stream−water matrix spikes
Cover image: Example graphs showing temporal changes in analytical recovery of simazine 

in groundwater and surface-water matrix spikes from 1992 through 2010. Similar graphs for 

43 other pesticides and 8 pesticide degradates are given in appendix 3 of this report.
Adjustment of Pesticide Concentrations for 

Temporal Changes in Analytical Recovery, 

1992–2010

By Jeffrey D. Martin and Michael Eberle

National Water-Quality Assessment Program

Data Series 630

U.S. Department of the Interior

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

KEN SALAZAR, Secretary

U.S. Geological Survey

Marcia K. McNutt, Director

U.S. Geological Survey, Reston, Virginia: 2011

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Suggested citation:

Martin, J.D., and Eberle, Michael, 2011, Adjustment of pesticide concentrations for temporal 

changes in analytical recovery, 1992–2010: U.S. Geological Survey Data Series 630, 11 p., 5 app.
iii

Foreword

The U.S. Geological Survey (USGS) is committed to providing the Nation with reliable scientific 

information that helps to enhance and protect the overall quality of life and that facilitates 

effective management of water, biological, energy, and mineral resources (http://www.usgs.

gov/). Information on the Nation’s water resources is critical to ensuring long-term availability 

of water that is safe for drinking and recreation and is suitable for industry, irrigation, and fish 

and wildlife. Population growth and increasing demands for water make the availability of that 

water, measured in terms of quantity and quality, even more essential to the long-term sustainability of our communities and ecosystems.

The USGS implemented the National Water-Quality Assessment (NAWQA) Program in 1991 

to support national, regional, State, and local information needs and decisions related to 

water-quality management and policy (http://water.usgs.gov/nawqa). The NAWQA Program 

is designed to answer: What is the quality of our Nation’s streams and groundwater? How are 

conditions changing over time? How do natural features and human activities affect the quality 

of streams and groundwater, and where are those effects most pronounced? By combining 

information on water chemistry, physical characteristics, stream habitat, and aquatic life, the 

NAWQA Program aims to provide science-based insights for current and emerging water issues 

and priorities. From 1991 to 2001, the NAWQA Program completed interdisciplinary assessments and established a baseline understanding of water-quality conditions in 51 of the Nation’s 

river basins and aquifers, referred to as Study Units (http://water.usgs.gov/nawqa/studies/

study_units.html).

National and regional assessments are ongoing in the second decade (2001–2012) of the 

NAWQA Program as 42 of the 51 Study Units are selectively reassessed. These assessments 

extend the findings in the Study Units by determining water-quality status and trends at sites 

that have been consistently monitored for more than a decade, and filling critical gaps in 

characterizing the quality of surface water and groundwater. For example, increased emphasis 

has been placed on assessing the quality of source water and finished water associated with 

many of the Nation’s largest community water systems. During the second decade, NAWQA is 

addressing five national priority topics that build an understanding of how natural features and 

human activities affect water quality, and establish links between sources of contaminants, the 

transport of those contaminants through the hydrologic system, and the potential effects of contaminants on humans and aquatic ecosystems. Included are studies on the fate of agricultural 

chemicals, effects of urbanization on stream ecosystems, bioaccumulation of mercury in stream 

ecosystems, effects of nutrient enrichment on aquatic ecosystems, and transport of contaminants to public-supply wells. In addition, national syntheses of information on pesticides, volatile organic compounds (VOCs), nutrients, trace elements, and aquatic ecology are continuing.
iv

The USGS aims to disseminate credible, timely, and relevant science information to address 

practical and effective water-resource management and strategies that protect and restore 

water quality. We hope this NAWQA publication will provide you with insights and information 

to meet your needs, and will foster increased citizen awareness and involvement in the protection and restoration of our Nation’s waters. 

The USGS recognizes that a national assessment by a single program cannot address all waterresource issues of interest. External coordination at all levels is critical for cost-effective management, regulation, and conservation of our Nation’s water resources. The NAWQA Program, 

therefore, depends on advice and information from other agencies—Federal, State, regional, 

interstate, Tribal, and local—as well as nongovernmental organizations, industry, academia, and 

other stakeholder groups. Your assistance and suggestions are greatly appreciated.

 William H. Werkheiser

 USGS Associate Director for Water
v

Contents

Foreword ........................................................................................................................................................iii

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

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

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

Analytical Method for Pesticides................................................................................................................2

Measurement of Recovery...........................................................................................................................2

Sources, Preparation, and Review of Recovery Data .............................................................................4

Temporal Changes in Recovery...................................................................................................................5

Magnitude of Temporal Changes in Recovery in Matrix Spikes...................................................5

Comparison of Groundwater and Stream-Water Matrix Spikes...................................................9

Adjustment of Pesticide Concentrations for Temporal Changes in Analytical Recovery.........9

Summary........................................................................................................................................................10

Acknowledgments.......................................................................................................................................10

References Cited..........................................................................................................................................10

Appendixes [available as separate files].................................................................................................11

Appendix 1. Data File of Pesticide Concentrations in Spike Solutions 

Appendix 2. Data File of Recovery of Pesticides in Matrix Spikes

Appendix 3. Comparison of Temporal Changes in Recovery of Pesticides in 

Groundwater Matrix Spikes and in Stream-Water Matrix Spikes

Appendix 4. Data File of Modeled Recovery of Pesticides in Groundwater, 1992–2010

Appendix 5. Data File of Modeled Recovery of Pesticides in Stream Water, 1992–2010

Figures

1. Explanation of boxplots used to depict distributions of recovery ........................................6

2. Example comparison of temporal changes (in the recovery of simazine) in 

groundwater matrix spikes and in stream−water matrix spikes ..........................................8

Tables

1. Pesticides analyzed by the GCMS method...............................................................................3

2. Summary statistics of temporal change in modeled recovery from the 

1992–2010 pesticide dataset.......................................................................................................6
vi

Conversion Factors and Abbreviations

Multiply By To obtain

Volume

liter (L) 0.2642 gallon (gal)

milliliter (mL) 0.03381 fluid ounce (oz) 

Mass

gram (g) 0.03527 ounce, avoirdupois (oz)

Concentrations of chemical constituents are given in micrograms per liter (μg/L) or micrograms 

per milliliter (μg/mL). 

A microgram is one-millionth of a gram, and a milliliter is one-thousandth of a liter.

Abbreviations used in the report

DWH Data Warehouse

GCMS gas chromatography/mass spectrometry

lowess locally weighted scatterplot smooths

NASQAN National Stream Quality Accounting Network 

NAWQA National Water-Quality Assessment

NWIS National Water Information System

NWQL National Water Quality Laboratory 

QC quality control 

SPE solid-phase extraction

USGS U.S. Geological Survey
Adjustment of Pesticide Concentrations for Temporal 

Changes in Analytical Recovery, 1992–2010

Abstract

Recovery is the proportion of a target analyte that is 

quantified by an analytical method and is a primary indicator 

of the analytical bias of a measurement. Recovery is measured 

by analysis of quality-control (QC) water samples that have 

known amounts of target analytes added (“spiked” QC 

samples). For pesticides, recovery is the measured amount of 

pesticide in the spiked QC sample expressed as a percentage 

of the amount spiked, ideally 100 percent. Temporal changes 

in recovery have the potential to adversely affect time-trend 

analysis of pesticide concentrations by introducing trends 

in apparent environmental concentrations that are caused by 

trends in performance of the analytical method rather than by 

trends in pesticide use or other environmental conditions. 

This report presents data and models related to the 

recovery of 44 pesticides and 8 pesticide degradates (hereafter 

referred to as “pesticides”) that were selected for a national 

analysis of time trends in pesticide concentrations in streams. 

Water samples were analyzed for these pesticides from 1992 

through 2010 by gas chromatography/mass spectrometry. 

Recovery was measured by analysis of pesticide-spiked QC 

water samples. 

Models of recovery, based on robust, locally weighted 

scatterplot smooths (lowess smooths) of matrix spikes, were 

developed separately for groundwater and stream-water 

samples. The models of recovery can be used to adjust 

concentrations of pesticides measured in groundwater or 

stream-water samples to 100 percent recovery to compensate 

for temporal changes in the performance (bias) of the 

analytical method. 

Introduction

Analytical recovery is a primary indicator of the analytical 

bias of a measurement. Analytical recovery (hereafter referred 

to as “recovery”) is measured by analysis of quality-control 

(QC) water samples that have known amounts of target analytes 

added (“spiked” QC samples). For pesticides, recovery is 

the measured amount of pesticide in the spiked QC sample 

expressed as a percentage of the amount spiked, ideally 100 

percent. Recovery of pesticides in spiked QC water samples 

By Jeffrey D. Martin and Michael Eberle

is routinely measured by the U.S. Geological Survey (USGS) 

National Water Quality Laboratory (NWQL). Pesticide 

concentrations reported by NWQL are not corrected for 

recovery. Most environmental laboratories do not correct for 

recovery (Keith, 1991, p. 116).

Bexfield (2008, p. S228–S230) examined temporal 

changes in pesticide recovery for water samples analyzed by 

NWQL during 1993–5 and 2001–3 and found trends in the 

recovery of pesticides in laboratory reagent spikes. Bexfield 

noted that temporal changes in recovery had the potential to 

adversely affect time-trend analysis of pesticide concentrations 

by introducing trends in environmental concentrations that 

were caused by trends in performance of the analytical method 

rather than by trends in pesticide use or other environmental 

conditions. 

Subsequently, Martin and others (2009) did a detailed 

study of recovery of pesticides in laboratory reagent spikes and 

in groundwater and stream-water matrix spikes (environmental 

water samples spiked with known amounts of target analytes) 

analyzed by NWQL during 1992–2006. As part of that study, 

Martin and others (2009) developed models of recovery based 

on recovery in groundwater and stream-water matrix spikes that 

could be used to adjust pesticide concentrations measured in 

environmental water samples for temporal changes in recovery 

for that time period. Such models are needed for certain types of 

water-quality assessments, including time-trend analysis.

In January 2011, similar procedures were used to obtain, 

screen, and prepare pesticide data for the period 1992–2010. 

Models of recovery were developed similar to those reported 

by Martin and others (2009), and an updated pesticide-dataset 

trend analysis was developed similar to that reported by Martin 

(2009).

Purpose and Scope

This report updates and supplements Martin and others 

(2009) by providing datasets and recomputed models for 

1992–2010, an additional 4 years of data. These expanded 

datasets include analyses resulting from the USGS National 

Stream Quality Accounting Network (NASQAN), as well as 

the USGS National Water-Quality Assessment (NAWQA) 

Program; datasets and models in Martin and others (2009) 

were based on NAWQA data only. 
2 Adjustment of Pesticide Concentrations for Temporal Changes in Analytical Recovery, 1992–2010

The 44 pesticides and 8 pesticide degradates (hereafter 

referred to as “pesticides”) were initially selected for a 

national analysis of time trends in pesticide concentrations 

in streams (Martin, 2009). Water samples were analyzed 

for these pesticides from 1992 through 2010 by gas 

chromatography/mass spectrometry (referred to as the 

“GCMS” method in this report). Recovery of pesticides was 

measured by analysis of pesticide-spiked QC water samples 

prepared by field personnel of either the NAWQA Program or 

NASQAN. Temporal changes in recovery were examined by 

scatterplot smooths of time-series plots of pesticide recovery 

in 1,819 stream-water matrix spikes and 999 groundwater 

matrix spikes. Models of recovery, based on robust, locally 

weighted scatterplot smooths (lowess smooths) of matrix 

spikes, were developed separately for stream-water and 

groundwater samples. The models of recovery can be used 

to adjust pesticide concentrations to 100 percent recovery to 

compensate for temporal changes in the performance of the 

analytical method. 

This report provides datasets of measured and modeled 

recoveries and a brief overview of methods. Additional details 

about the analytical methods, procedures used to investigate 

and model temporal changes in recovery, and regional or sitespecific variations in recovery can be found in Martin and 

others (2009).

Analytical Method for Pesticides

The recovery data discussed in this report are applicable 

to water-quality samples analyzed during 1992–2010 by 

NWQL using GSMS. Pesticides are isolated from filtered 

water samples by C-18 solid-phase extraction (SPE) and 

analyzed by capillary-column gas chromatography/mass 

spectrometry with selected-ion monitoring (Zaugg and others, 

1995; Lindley and others, 1996; Madsen and others, 2003). 

The GCMS method provides low-level analyses for as many 

as 44 commonly used pesticides and 8 pesticide degradates

(table 1). The pesticide acetochlor was added to the GCMS 

method in 1994 (Lindley and others, 1996), and the pesticide 

fipronil and four degradates of fipronil were added to the 

GCMS method in 1999 (Madsen and others, 2003). Analysis 

of pesticides by the GCMS method is obtained by requesting 

a NWQL analytical “schedule” (a suite of pesticides to be 

measured by one or more analytical methods). The recovery 

information provided in this report was obtained from samples 

analyzed by NWQL schedules 2001, 2010, 2003, and 2033. 

The GCMS analytical method does not have specified 

“detection limits” for each pesticide. All detections 

conclusively identified by retention time and spectral 

characteristics are quantified (Zaugg and others, 1995, p. 

19–21). Nondetections of pesticides (analyses that do not 

meet identification criteria based on retention time or spectral 

characteristics) are reported as less than the “reporting level” 

(for example: < 0.005 μg/L). The types and numerical values 

of reporting levels used to report nondetections of pesticides 

analyzed by the GCMS method have changed through time. 

Oblinger Childress and others (1999) and Martin (2009) give 

additional information on reporting procedures for GCMS 

analytical data.

Measurement of Recovery

Recovery, as used in this report, is the ratio of a measured 

value divided by a reference value.1 Measurements of recovery 

provide information on the bias and variability of measurements from the analytical method. Recovery of pesticides 

analyzed by the GCMS method of NWQL is measured by 

analysis of spiked QC water samples. Approaches and considerations in the measurement and use of recovery information 

are presented in Thompson and others (1999), whereas considerations for spiking water samples are given in American 

Society for Testing and Materials (2000, p. 770–774). Details 

of recovery procedures germane to the data in this report can 

be found in Martin and others (2009), but a brief discussion of 

spike solutions—matrix spikes in particular—is offered here.

Spike solutions of pesticides at known concentrations in 

solvents are prepared by NWQL personnel or by commercial 

vendors according to NWQL specifications and are certified 

by NWQL personnel prior to use (U.S. Geological Survey 

[n.d.]). Pesticide concentrations in most GCMS spike solutions are 1 μg/mL, and 0.1 mL of spike solution typically is 

added to spiked QC water samples. Pesticide concentrations 

in most spiked QC water samples are approximately 0.1 μg/L, 

but some QC samples are spiked at higher concentrations. A 

dataset of pesticide concentrations in spike solutions is provided in appendix 1.

In the original pesticide-recovery study by Martin and 

others (2009), matrix spikes (as opposed to laboratory-prepared 

spikes of reagent-grade blank water) were ultimately selected 

for recovery-model development. Matrix spikes are QC 

environmental water samples that typically are prepared by 

scientists responsible for the collection of stream-water and 

groundwater samples. Water is collected from the stream or 

well and processed by use of standard procedures to produce 

two samples (U.S. Geological Survey, variously dated; Shelton, 

1994; Koterba and others, 1995). Spike solution is added to only 

one of the two water samples, resulting in spiked and unspiked 

samples (the matrix spike and the “background” sample, respectively). Models of recovery based on matrix spikes are deemed 

more appropriate for adjusting concentrations of pesticides 

measured in groundwater and stream-water samples than models based on laboratory reagent spikes. Although there are many 

more laboratory reagent spikes than matrix spikes, the number 

and temporal distribution of matrix spikes is sufficient to model 

changes in recovery over a 6- to 12-month time scale. Models of 

recovery based on matrix spikes were selected because matrix 

1

 Burns and others (2002) prefer the term “apparent recovery.”
Measurement of Recovery 3

Table 1. Pesticides analyzed by the gas chromatography/mass spectrometry (GCMS) method.—Continued

[Parameter code, the number used to identify a pesticide in the U.S. Geological Survey National Water Information System; CAS, Chemical 

Abstracts Service (table contains CAS Registry Numbers®, a Registered Trademark of the American Chemical Society; CAS recommends 

the verification of CASRNs through CAS Client ServicesSM); LT-MDL, long-term method detection level; μg/L, microgram per liter; NA, not 

applicable; ND, not determined]

Figure 

number in 

appendix 3

Pesticide Parameter 

code CAS number Type of pesticide

Parent 

pesticide (if 

degradate)

Maximum 

LT-MDL 

(μg/L)

1 Acetochlor 49260 34256-82-1 Herbicide NA 0.005

2 Alachlor 46342 15972-60-8 Herbicide NA 0.004

3 Atrazine 39632 1912-24-9 Herbicide NA 0.004

4 Azinphos-methyl 82686 86-50-0 Insecticide NA 0.06

5 Benfluralin 82673 1861-40-1 Herbicide NA 0.007

6 Butylate 04028 2008-41-5 Herbicide NA 0.002

7 Carbaryl 82680 63-25-2 Insecticide NA 0.1

8 Carbofuran 82674 1563-66-2 Insecticide NA 0.03

9 Chlorpyrifos 38933 2921-88-2 Insecticide NA 0.005

10 Cyanazine 04041 21725-46-2 Herbicide NA 0.02

11 Dacthal 82682 1861-32-1 Herbicide NA 0.0038

12 p,p’-DDE 34653 72-55-9 Degradate DDT 0.0013

13 Deethylatrazine 04040 6190-65-4 Degradate Atrazine 0.007

14 Desulfinylfipronil 62170 ND Degradate Fipronil 0.006

15 Desulfinylfipronil amide 62169 ND Degradate Fipronil 0.015

16 Diazinon 39572 333-41-5 Insecticide NA 0.003

17 Dieldrin 39381 60-57-1 Insecticide NA 0.004

18 2,6-Diethylaniline 82660 579-66-8 Degradate Alachlor 0.003

19 Disulfoton 82677 298-04-4 Insecticide NA 0.02

20 EPTC 82668 759-94-4 Herbicide NA 0.0028

21 Ethalfluralin 82663 55283-68-6 Herbicide NA 0.005

22 Ethoprophos 82672 13194-48-4 Insecticide NA 0.008

23 Fipronil 62166 120068-37-3 Insecticide NA 0.02

24 Fipronil sulfide 62167 120067-83-6 Degradate Fipronil 0.006

25 Fipronil sulfone 62168 120068-36-2 Degradate Fipronil 0.012

26 Fonofos 04095 944-22-9 Insecticide NA 0.005

27 alpha-HCH 34253 319-84-6 Degradate gamma-HCH 0.004

28 gamma-HCH 39341 58-89-9 Insecticide NA 0.007

29 Linuron 82666 330-55-2 Herbicide NA 0.03

30 Malathion 39532 121-75-5 Insecticide NA 0.014

31 Metolachlor 39415 51218-45-2 Herbicide NA 0.01

32 Metribuzin 82630 21087-64-9 Herbicide NA 0.014

33 Molinate 82671 2212-67-1 Herbicide NA 0.002

34 Napropamide 82684 15299-99-7 Herbicide NA 0.009

35 Parathion 39542 56-38-2 Insecticide NA 0.01

36 Parathion-methyl 82667 298-00-0 Insecticide NA 0.008

37 Pebulate 82669 1114-71-2 Herbicide NA 0.008

38 Pendimethalin 82683 40487-42-1 Herbicide NA 0.011

39 cis-Permethrin 82687 54774-45-7 Insecticide NA 0.007

40 Phorate 82664 298-02-2 Insecticide NA 0.027

41 Prometon 04037 1610-18-0 Herbicide NA 0.007

42 Propachlor 04024 1918-16-7 Herbicide NA 0.012

43 Propanil 82679 709-98-8 Herbicide NA 0.007
4 Adjustment of Pesticide Concentrations for Temporal Changes in Analytical Recovery, 1992–2010

Table 1. Pesticides analyzed by the gas chromatography/mass spectrometry (GCMS) method.—Continued

[Parameter code, the number used to identify a pesticide in the U.S. Geological Survey National Water Information System; CAS, Chemical 

Abstracts Service (table contains CAS Registry Numbers®, a Registered Trademark of the American Chemical Society; CAS recommends 

the verification of CASRNs through CAS Client ServicesSM); LT-MDL, long-term method detection level; μg/L, microgram per liter; NA, not 

applicable; ND, not determined]

Figure 

number in 

appendix 3

Pesticide Parameter 

code CAS number Type of pesticide

Parent 

pesticide (if 

degradate)

Maximum 

LT-MDL 

(μg/L)

44

45

46

47

48

49

50

51

52

Propargite

Propyzamide

Simazine

Tebuthiuron

Terbacil

Terbufos

Thiobencarb

Triallate

Trifluralin

82685

82676

04035

82670

82665

82675

82681

82678

82661

2312-35-8

23950-58-5

122-34-9

34014-18-1

5902-51-2

13071-79-9

28249-77-6

2303-17-5

1582-09-8

Acaricide

Herbicide

Herbicide

Herbicide

Herbicide

Insecticide

Herbicide

Herbicide

Herbicide

NA

NA

NA

NA

NA

NA

NA

NA

NA

0.02

0.0021

0.006

0.014

0.02

0.009

0.008

0.003

0.009

spikes are expected to more closely match the matrix of environmental water samples than are reagent spikes, and method 

performance is often matrix dependent, as has been shown 

by higher recovery in matrix spikes for most of the pesticides 

(Martin and others, 2009).

Most matrix spikes analyzed by the NWQL were spiked 

at the field site (field matrix spikes). In general, approximately 

5 percent of the pesticide samples collected for the NAWQA 

and NASQAN Programs are field matrix spikes. 

Background concentrations of pesticides are measured 

by pesticide analysis of the unspiked sample. Nondetections 

of pesticides in the unspiked sample were assumed to be zero 

concentration for the calculation of recovery. Recovery in field 

matrix spikes is calculated as follows:

R = [(Cspiked – Cunspiked) / Cexpected] × 100 % (1)

where

R is pesticide recovery, in percent;

Cspiked is the measured concentration of the pesticide 

in the spiked sample, in micrograms per 

liter;

Cunspiked is the measured concentration of the pesticide 

in the unspiked sample, in micrograms per 

liter; and

Cexpected is the expected or theoretical concentration 

of the pesticide in the spiked sample, in 

micrograms per liter, and is calculated as

Cexpected = Csolution × Vsolution / Vsample (2)

where

Csolution is the concentration of the pesticide in the 

spike solution, in micrograms per milliliter;

Vsolution is the volume of spike solution added to the 

spiked sample, in milliliters; and

Vsample is the volume of water in the spiked sample, 

in liters.

Sources, Preparation, and Review of 

Recovery Data

Recovery in matrix spikes was calculated from 

concentration data for spiked environmental water samples 

and the associated unspiked water samples that are stored 

in the NAWQA Data Warehouse (DWH). Water-quality 

data were obtained from DWH data managers (Jessica 

L. Thompson, Information Technology Specialist, U.S. 

Geological Survey, written commun., January 19, 2011). Any 

water-quality sample in the DWH with analyses of one or 

more pesticides of interest was retrieved along with selected 

supporting sample information. Procedures for identification 

of the matrix spikes and associated ancillary information are 

described in Martin and others (2009). 

 A total of 2,902 matrix spike samples were identified in 

the 1992–2010 dataset. Of these, 42 were removed from the 

dataset because no matching unspiked environmental sample 

was identified, 7 were removed because the spiked-sample 

volume was less than 400 mL, 5 were removed because of 

the use of an unidentified high-concentration spike solution, 

2 were removed because too few pesticides were detected in 

the sample, 15 were removed because recoveries of pesticides 
Temporal Changes in Recovery 5

were 2 to 20 times less than the expected recovery, and 13 

were removed because recoveries of pesticides were 3 to 

7 times greater than the expected recovery. Recoveries of 

pesticides much greater than or less than expected were 

assumed to be caused by improper spiking techniques. These 

sample deletions resulted in a dataset of 2,818 matrix spikes.

High background concentrations of pesticides resulted in 

invalid estimates of recovery for some matrix spikes. In the 

presence of high background concentrations, the additional 

concentration from spiking may be indistinguishable from the 

normal analytical variability of measurements at high concentrations. Recoveries calculated from matrix spikes under these 

conditions may be much higher or lower (even negative) than 

is typical for the method. Review of plots of recovery versus 

background concentrations showed that occurrences of very 

high (greater than 200 percent) or low (less than 50 percent) 

recoveries were more frequent at background concentrations 

of 0.3 μg/L or higher than at concentrations lower than 0.3 

μg/L. Recoveries were deleted from the dataset if background 

concentrations were greater than or equal to 0.3 μg/L and 

recovery was less than 50 percent or greater than 200 percent.2

This criterion resulted in removal of 164 recoveries from the 

dataset (22 for groundwater and 142 for surface water). 

Recoveries for several pesticides were 5 or more times 

greater than expected. Fifty-three recoveries in excess of 

500 percent were assumed to be unrepresentative of method 

performance and were removed from the dataset.3 Forty 

recoveries less than 0 percent were set to 0 percent. The final 

reviewed matrix spike dataset comprises 2,818 samples and 

125,374 estimates of pesticide recovery and spans the period 

May 1992 through August 2010. The date value reported or 

plotted for matrix spikes is the sample-collection date. For 

matrix spikes, the sample preparation/extraction date typically is 2 to 6 days after the sample-collection date. The final 

reviewed matrix spike dataset is provided in appendix 2.

Temporal Changes in Recovery

Temporal changes in pesticide recovery were investigated 

by calculating lowess smooths for the time series of pesticide 

recoveries. Lowess smooths were used to model changes 

in recovery as a function of time and to compare the timing 

and magnitude of temporal changes in recovery groundwater 

and stream-water matrix spikes. Details about the lowess 

procedure and its application to the previous 1992–2006 

dataset are given in Martin and others (2009). The remainder 

2

 The 50- and 200-percent recovery thresholds were subjectively selected to 

retain typical values of recovery (those apparently not adversely affected by 

high background concentrations). Recovery thresholds of 25 and 100 percent 

were used for deethylatrazine because deethylatrazine typically has about 50 

percent recovery.

3

 Removal of recoveries in excess of 500 percent had negligible effects on 

models of recovery.

of this section focuses on pesticide recovery for the expanded 

1992–2010 dataset.

Recovery was modeled by using PROC LOESS of 

SAS/STAT version 8, typically with a 10-percent smoothing 

window (SAS Institute Inc. [n.d.]). A smoothing window 

of 10 percent means that 10 percent of the data points 

in the time series of recoveries were used for the locally 

weighted regression. The length of the smoothing window 

is subjectively chosen depending on the use of the smooth 

(Helsel and Hirsch, 2002, p. 288). The 10-percent window 

was used to model broad changes in recovery over a 6- to 

12-month time scale for 48 of the 52 pesticides. A 25-percent 

window was used to model similar changes for fipronil and 

the four fipronil degradates because of a much reduced period 

of data. The 10-percent smoothing window is appropriate for 

modeling changes in recovery over a 6- to 12-month time scale 

but has no implications for the frequency of environmental 

samples that can be analyzed for time trends. Trend analysis 

of weekly, monthly, or annual time series of recovery-adjusted 

concentrations all are appropriate—depending on the trendanalysis technique and the characteristics of the time series. 

Boxplots (Helsel and Hirsch, 2002, p. 25) are used to 

show the distributions of measured recovery in figure 2 and 

appendix 3. Boxplots are explained in figure 1. Whiskers for 

boxplots shown in this report are drawn from the quartiles (the 

25th and 75th percentiles) to the most distant value that does 

not exceed 1.5 times the interquartile range from the quartile. 

Values that exceed 1.5 times the interquartile range from the 

quartile (commonly termed “outliers”) are omitted in order to 

emphasize statistics of central tendency in these figures.

Magnitude of Temporal Changes in Recovery in 

Matrix Spikes

The magnitude of temporal change in recovery during 

1992–2010 was quantified for each pesticide by calculating 

the range of lowess-modeled recovery for all days within the 

time period of the first matrix spike to the last matrix spike, 

inclusive. The magnitude of temporal change in modeled 

recovery in groundwater matrix spikes ranged from 14.6 

percent for fipronil sulfone to 159.0 percent for cis-permethrin 

(table 2). The median amount of temporal change was 30.0 

percent. The magnitude of temporal change in modeled 

recovery in stream-water matrix spikes ranged from 10.6 

percent for p,p’-DDE to 126.3 percent for carbaryl (table 2). 

The median amount of temporal change was 37.2 percent.

Results of the temporal-change analysis are depicted for 

each pesticide in appendix 3; figure 2 is a sample illustration 

(for simazine) from that appendix.
6 Adjustment of Pesticide Concentrations for Temporal Changes in Analytical Recovery, 1992–2010

Table 2. Summary statistics of temporal change in modeled recovery from the 1992–2010 pesticide dataset.

[SW, surface water; GW, groundwater]

Figure 

number 

in 

appendix 3

Parameter 

code

Pesticide

Temporal change in modeled recovery (percent) Median 

difference 

in 

modeled 

recovery 

(SW−GW, 

in percent)

Groundwater Surface water

Median Mini- Maxi- Range mum mumMedian Range Minimum

Maximum

1 49260 Acetochlor 102.8 19.0 93.2 112.2 113.0 31.0 102.1 133.1 9.8

2 46342 Alachlor 103.0 15.8 95.9 111.7 111.3 30.4 99.4 129.8 8.0

3 39632 Atrazine 100.6 24.1 87.4 111.6 102.4 26.9 85.9 112.8 2.2

4 82686 Azinphos-methyl 102.5 95.5 49.3 144.8 139.9 92.8 78.5 171.4 38.8

5 82673 Benfluralin 77.0 31.8 57.9 89.7 84.6 37.7 59.8 97.5 8.7

6 04028 Butylate 96.5 19.5 84.0 103.5 101.1 24.7 82.6 107.3 4.0

7 82680 Carbaryl 116.5 126.1 63.3 189.5 125.7 126.3 74.5 200.9 10.0

8 82674 Carbofuran 116.9 79.1 76.3 155.5 126.2 56.1 101.4 157.4 10.6

9 38933 Chlorpyrifos 92.5 15.6 86.0 101.6 99.1 23.3 80.9 104.2 5.6

10 04041 Cyanazine 103.8 32.9 83.2 116.2 108.2 56.2 86.2 142.4 7.7

11 82682 Dacthal 103.7 41.6 96.5 138.0 105.6 15.8 99.2 115.0 2.3

12 34653 p,p’-DDE 68.7 29.7 59.8 89.5 61.7 10.6 56.9 67.6 −7.3

Figure 1. Explanation of boxplots used to depict distributions of recovery. The number of 

measurements is shown at the top or bottom of the boxplot. Values more extreme than the 

whiskers are not shown.

0

50

100

150

Recovery, in percent

Figure 1. Explanation of boxplots used to depict distributions of recovery. The number of measurements

is shown at the top or bottom of the boxplot. Values more extreme than the whiskers are not shown.

<−−− 75th percentile (p75th)

<−−− Median

<−−− 25th percentile (p25th)

<−−− Whisker drawn to largest data value not more than

 1.5 * (p75th − p25th) distance from the 75th percentile

<−−− Whisker drawn to smallest data value not more than

 1.5 * (p75th − p25th) distance from the 25th percentile
Temporal Changes in Recovery 7

Table 2. Summary statistics of temporal change in modeled recovery from the 1992–2010 pesticide dataset.—Continued

Figure 

number 

in 

appendix 3

Parameter 

code

Pesticide

Temporal change in modeled recovery (percent) Median 

difference 

in 

modeled 

recovery 

(SW−GW, 

in percent)

Groundwater Surface water

Median Range Minimum

Maximum

Median Range Minimum

Maximum

13 04040 Deethylatrazine 46.7 62.4 24.0 86.4 41.2 84.2 11.3 95.5 −1.9

14 62170 Desulfinylfipronil 99.7 23.5 90.4 114.0 107.8 31.4 97.0 128.4 9.2

15 62169 Desulfinylfipronil amide 94.1 25.0 78.1 103.1 116.8 81.1 80.5 161.6 24.8

16 39572 Diazinon 95.3 25.3 81.0 106.4 99.8 26.7 86.9 113.6 5.1

17 39381 Dieldrin 94.2 18.1 82.2 100.3 95.9 20.9 86.5 107.4 2.5

18 82660 2,6-Diethylaniline 91.8 17.2 85.3 102.5 88.9 36.2 62.7 98.9 −2.2

19 82677 Disulfoton 72.7 88.7 37.0 125.7 68.3 72.7 31.2 103.9 −4.9

20 82668 EPTC 94.2 18.7 84.3 103.0 94.9 33.1 69.3 102.4 0.7

21 82663 Ethalfluralin 85.8 30.9 68.7 99.6 94.7 29.4 82.0 111.4 10.5

22 82672 Ethoprophos 97.1 31.0 82.1 113.1 103.7 54.4 85.9 140.3 9.4

23 62166 Fipronil 101.5 23.9 89.3 113.2 130.6 116.0 67.3 183.4 30.1

24 62167 Fipronil sulfide 98.6 17.0 91.4 108.4 114.5 39.1 103.6 142.7 18.6

25 62168 Fipronil sulfone 84.3 14.6 79.5 94.1 97.9 39.9 87.9 127.8 14.8

26 04095 Fonofos 91.4 20.0 78.3 98.2 96.4 28.9 79.6 108.5 5.1

27 34253 alpha-HCH 93.7 23.5 79.1 102.6 95.7 17.0 86.9 103.9 2.2

28 39341 gamma-HCH 97.0 23.3 84.2 107.4 99.3 21.7 85.8 107.5 1.6

29 82666 Linuron 108.6 119.4 28.6 148.0 114.9 123.0 13.4 136.4 4.4

30 39532 Malathion 98.1 37.9 72.2 110.1 106.3 63.6 60.7 124.4 8.6

31 39415 Metolachlor 104.5 14.7 100.7 115.4 110.5 23.6 97.7 121.2 5.3

32 82630 Metribuzin 88.1 44.5 54.6 99.2 91.2 76.0 45.5 121.5 6.4

33 82671 Molinate 98.4 20.3 83.9 104.2 100.5 29.5 80.0 109.5 3.0

34 82684 Napropamide 96.7 15.5 90.3 105.8 106.6 36.5 94.7 131.2 9.0

35 39542 Parathion 96.3 31.8 78.8 110.6 112.5 31.0 93.5 124.5 14.6

36 82667 Parathion-methyl 90.7 27.3 75.4 102.6 104.2 53.9 70.7 124.7 16.5

37 82669 Pebulate 95.0 15.2 85.7 100.9 97.9 35.3 73.4 108.7 2.8

38 82683 Pendimethalin 87.5 41.1 62.8 104.0 104.5 48.9 76.8 125.7 15.7

39 82687 cis-Permethrin 67.5 159.0 50.0 209.1 54.1 46.6 41.0 87.6 −10.3

40 82664 Phorate 74.3 31.8 57.2 89.0 73.6 27.9 54.0 82.0 −2.6

41 04037 Prometon 95.5 30.9 80.6 111.5 102.0 48.4 70.8 119.2 6.7

42 04024 Propachlor 106.0 36.5 81.1 117.6 116.8 35.3 93.7 129.0 10.6

43 82679 Propanil 108.1 32.5 84.4 116.9 116.9 62.7 86.5 149.2 10.4

44 82685 Propargite 93.2 36.7 69.3 106.1 109.4 56.1 84.2 140.4 17.3

45 82676 Propyzamide 96.2 26.8 76.9 103.8 103.6 38.7 80.2 119.0 7.8

46 04035 Simazine 98.2 37.9 72.1 110.0 101.0 51.2 67.5 118.7 2.7

47 82670 Tebuthiuron 115.3 72.0 74.4 146.4 123.3 98.5 78.5 177.0 9.6

48 82665 Terbacil 93.3 111.6 47.9 159.6 97.7 84.5 56.7 141.2 13.7

49 82675 Terbufos 78.7 32.3 65.7 97.9 84.2 27.7 71.1 98.8 4.8

50 82681 Thiobencarb 105.8 23.8 94.1 117.8 105.4 36.7 87.5 124.2 2.9

51 82678 Triallate 94.3 18.9 81.6 100.5 98.3 32.9 83.8 116.7 3.9

52 82661 Trifluralin 80.7 30.2 63.3 93.5 90.4 39.1 66.4 105.4 9.8
8 Adjustment of Pesticide Concentrations for Temporal Changes in Analytical Recovery, 1992–2010

0

50

100

150

200

Recovery, in percent

Simazine groundwater matrix spikes: n: 999 Median: 96.3 Mean: 95.1 Standard deviation: 16.5

1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010

0

50

100

150

200

Recovery, in percent

Simazine stream−water matrix spikes: n: 1796 Median: 100.9 Mean: 100.5 Standard deviation: 19.3

1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010

0

50

100

150

200

Recovery, in percent

1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010

Comparison of lowess−modeled recovery

Groundwater matrix spikes

Stream−water matrix spikes

0

50

100

150

200

Recovery, in percent

16 50 88 37 68 153 120 187 162 151 131 144 132 71 75 53 63 51 44

0 76 86 65 78 63 56 77 83 87 61 42 49 43 35 38 23 21 16

1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010

Figure 2. Comparison of temporal changes in the recovery of simazine in groundwater matrix spikes and in

stream−water matrix spikes. In the bottom graph, boxplots for groundwater matrix spikes are plotted in the first half of the year,

and boxplots for stream−water matrix spikes are plotted in the last half of the year. The number of groundwater spikes is shown

at the top of the plot and the number of stream−water spikes is shown at the bottom of the plot. Boxplots are explained in figure 1.

(Recoveries greater than 200 percent are not shown.)

Figure 2. Example comparison of temporal changes (in the recovery of simazine) in groundwater matrix spikes and in streamwater matrix spikes. In the bottom graph, boxplots for groundwater matrix spikes are plotted in the first half of the year and boxplots 

for stream-water matrix spikes are plotted in the second half of the year. The number of groundwater spikes is shown at the top of 

the plot and the number of stream-water spikes is shown at the bottom of the plot. Boxplots are explained in figure 1. (Recoveries 

greater than 200 percent are not shown.)
Temporal Changes in Recovery 9

Comparison of Groundwater and Stream-Water 

Matrix Spikes

Recovery was modeled separately for groundwater and 

stream-water matrix spikes. As was seen in the modeling 

of the 1992–2006 dataset (Martin and others, 2009), the 

pattern of increases and decreases in modeled recovery for 

groundwater and stream-water matrix spikes was temporally 

in phase for most pesticides. (See, for example, appendix 

figs. 3–13 (deethylatrazine), 3–19 (disulfoton), and 3–47 

(tebuthiuron).) Temporal changes in recovery were less in 

phase for some pesticides—especially for pesticides with 

highly variable recovery—most likely because of differences 

in data density (the number of spikes) between groundwater 

and stream-water matrix spikes for some periods of time. 

(See, for example, appendix figs. 3–4 (azinphos-methyl), 3–7 

(carbaryl), and 3–8 (carbofuran).) In general, relatively more 

groundwater spikes than stream-water spikes were collected 

during June through October, whereas relatively more 

stream-water than groundwater spikes were collected during 

December through April.

As noted in the results from the original analysis 1992–

2006 data (Martin and others, 2009) recovery in stream-water 

matrix spikes was greater than recovery in groundwater spikes 

for nearly every pesticide (appendix 3). The medians of the 

differences in modeled recovery in stream-water spikes were 

more than 5 percent larger for 32 of the 52 pesticides and more 

than 10 percent larger for 14 of the 52 pesticides (table 2). The 

smallest median difference in recovery (−10.3 percent) was 

for cis-permethrin, and largest median difference in recovery 

(38.8 percent) was for azinphos-methyl (table 2). Given the 

systematic differences in recovery between groundwater 

and stream-water matrix spikes for most pesticides, models 

of recovery used to adjust pesticide concentrations in 

environmental water samples should be matrix specific. 

Adjustment of Pesticide Concentrations for 

Temporal Changes in Analytical Recovery

Pesticide recovery in groundwater and stream water 

was modeled by lowess for each day in the 1992–2010 

period. Recovery for dates prior to the first matrix spike was 

modeled by assigning the lowess-modeled recovery for the 

date of the first spike to all previous dates. Recovery for dates 

after the last matrix spike was modeled by assigning the 

lowess-modeled recovery for the date of the last spike to all 

subsequent dates. Modeled recovery was extrapolated beyond 

the period of record for spikes in order to provide an estimate 

of the recovery for environmental samples collected beyond 

the period of record for matrix spikes. 

Data files of modeled recovery in groundwater and 

stream-water matrix spikes are provided in appendixes 4 and 

5, respectively. Data files of modeled recovery may be used to 

adjust concentrations of pesticides measured in groundwater 

or stream-water samples to 100 percent recovery. The samplecollection date of the water sample should be matched with the 

“dates” variable in the data files in appendixes 4 and 5. 

Martin (2009, p. 15–17) presents an example application 

of recovery adjustment for trend analysis. All detected 

concentrations were adjusted for recovery. Recovery 

adjustment for nondetected concentrations was dependent 

on the class of nondetection. Two classes of nondetections 

were identified: “routine” and “raised.” The large majority 

of nondetections in the data set were routine nondetections 

that result when pesticide identification criteria based on 

retention time and spectral characteristics were not met. These 

nondetections were reported as censored concentrations at 

the “routine” reporting level (for example, <0.005 μg/L). 

A small number of samples, however, had matrix effects 

or other analytical difficulties that interfered with pesticide 

identification. These nondetections were reported as censored 

concentrations at a “raised” reporting level (for example, 

<0.03 μg/L, six times greater than the routine reporting level). 

None of the nondetections at “routine” reporting levels were 

adjusted for recovery. Nondetections at “raised” reporting 

levels were adjusted for recovery. Detected concentrations 

that were downward adjusted to concentrations less than the 

routine reporting level were not censored at the concentration 

of the routine reporting level. 

Concentrations should be adjusted as follows:

Cadjusted = [Cmeasured / (Rpredicted / 100)] (3)

where

Cadjusted is the recovery-adjusted concentration of 

the pesticide in the water sample, in 

micrograms per liter;

Cmeasured is the measured concentration of the pesticide 

in the water sample, in micrograms per 

liter; and

Rpredicted is the lowess-modeled recovery, in percent 

(the “predict” variable in the data files in 

appendixes 4 and 5).

Users of the recovery-adjustment models should review 

the “Model Performance” and “Limitations of Modeled 

Recovery” sections of Martin and others (2009). Model users 

should clearly state in their reports that concentration data 

have been adjusted for modeled recovery in matrix spikes and 

should consider publishing both unadjusted and recoveryadjusted data, as was done in Martin (2009, appendix 5a). 

Recovery-adjusted concentrations should not be stored in 

USGS National Water Information System (NWIS) databases. 
10 Adjustment of Pesticide Concentrations for Temporal Changes in Analytical Recovery, 1992–2010

Summary

Recovery is a primary indicator of the analytical bias 

of a measurement. For pesticides, recovery is measured by 

analysis of quality-control (QC) water samples that have 

known amounts of pesticides added (“spiked” QC samples). 

Recovery is the measured amount of pesticide in the spiked 

QC sample expressed as a percentage of the amount spiked, 

ideally 100 percent. Temporal changes in recovery have 

the potential to adversely affect time-trend analysis of 

pesticide concentrations by introducing trends in apparent 

environmental concentrations that are caused by trends in 

performance of the analytical method rather than by trends in 

pesticide use or other environmental conditions. 

This report (1) examines temporal changes in the 

recovery of 44 pesticides and 8 pesticide degradates 

(“pesticides”) that were selected for a national analysis of time 

trends in pesticide concentrations in streams (Martin, 2009) 

and (2) provides updates for datasets previously compiled for 

1992–2006 by Martin and others (2009). The data source for 

the current compilation is water samples analyzed for these 

pesticides from 1992 through 2010 by gas chromatography/

mass spectrometry. Recovery of pesticides was measured 

by analysis of pesticide-spiked QC water samples (“matrix 

spikes”) prepared by field personnel of the U.S. Geological 

Survey’s National Water Quality Assessment Program and 

National Stream Quality Accounting Network. Temporal 

changes in pesticide recovery were investigated by calculating 

robust, locally weighted scatterplot smooths (lowess smooths) 

for the time series of pesticide recoveries in 1,819 streamwater matrix spikes and 999 groundwater matrix spikes. A 

10-percent smoothing window was selected to show broad 

changes in recovery over a 6- to 12-month time scale for most 

of the 52 pesticides. 

Models of recovery, based on lowess smooths of 

matrix spikes, were developed separately for groundwater 

and stream-water samples. Temporal changes in recovery 

were similarly distributed in groundwater and surface water 

for most pesticides but less in phase for some pesticides—

especially for pesticides with highly variable recovery—most 

likely because of differences in data density (the number of 

spikes) between groundwater and stream-water matrix spikes 

for some periods of time. 

The models of recovery can be used to adjust 

concentrations of pesticides measured in groundwater or 

stream-water samples to 100 percent recovery to compensate 

for temporal changes in the performance (bias) of the 

analytical method. Model users should clearly state in their 

reports that concentration data have been adjusted for modeled 

recovery and should consider publishing both unadjusted and 

recovery-adjusted data.

Acknowledgments

Many USGS employees contributed to this report. Jessica 

L. Thompson provided water-quality data for matrix spikes 

and background samples; Sonja R. Abney, Jana Iverson, Leslie 

K. Kanagy, Janece C. Koleis, Chris E. Lindley, James E. 

Madsen, Dennis J. Markovchick, Lucinda K. Murtagh, Mary 

C. Olson, Scott D. Oppenheimer, Carmen G. Reed-Parker, 

Rhiannon C. Revello, Steven G. Smith, Max E. Stroppel, and 

Frank W. Wiebe analyzed the spiked water samples; David 

C. Reutter and Timothy C. Willoughby provided technical 

reviews of early drafts of the report; and Bonnie Stich Fink 

edited the report.

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Appendixes

Appendixes are separate online documents, accessible at 

http://pubs.usgs.gov/ds/630/.

Appendix 1. Data File of Pesticide 

Concentrations in Spike Solutions 

Appendix 2. Data File of Recovery of Pesticides 

in Matrix Spikes

Appendix 3. Comparison of Temporal Changes 

in Recovery of Pesticides in Groundwater 

Matrix Spikes and in Stream-Water Matrix 

Spikes

Appendix 4. Data File of Modeled Recovery of 

Pesticides in Groundwater, 1992–2010

Appendix 5. Data File of Modeled Recovery of 

Pesticides in Stream Water, 1992–2010
Martin and Eberle—Adjustment of Pesticide Concentrations for Temporal Changes in Analytical Recovery, 1992–2010—Data Series 630