U.S. Department of the Interior

U.S. Geological Survey

Scientific Investigations Report 2005–5061

External Quality-Assurance Results for the Nationa

Atmospheric Deposition Program/National Trends 

Network, 2002−03
External Quality-Assurance Results for the 

National Atmospheric Deposition Program/

National Trends Network, 2002–03

By Gregory A. Wetherbee, Natalie E. Latysh, and Kevin P. Burke

U.S. Department of the Interior

U.S. Geological Survey

Scientific Investigations Report 2005–5061
U.S. Department of the Interior

Gale A. Norton, Secretary

U.S. Geological Survey

Charles G. Groat, Director

U.S. Geological Survey, Reston, Virginia: 2005

For sale by U.S. Geological Survey, Information Services

Box 25286, Denver Federal Center

Denver, CO 80225

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Although this report is in the public domain, permission must be secured from the individual copyright owners to 

reproduce any copyrighted materials contained within this report.

Suggested citation:

Wetherbee, G.A., Latysh, N.E., and Burke, K.P., 2005, External quality-assurance results for the National Atmospheric 

Deposition Program/National Trends Network, 2002–03: U.S. Geological Survey Scientific Investigations Report 2005-

5061, 59 p.

Prepared by the U.S. Geological Survey in Denver, Colorado (http://bqs.usgs.gov)
 iii

Contents

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

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2

Statistical Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2

Intersite-Comparison Program . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

Results for Intersite-Comparison Studies 48–51. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

Intersite-Comparison Followup Studies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4

Sample-Handling Variability and Bias . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9

Blind-Audit Program Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12

Assessment of Variability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12

Relative and Absolute Percentage Differences . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12

Sample-Handling Evaluation (SHE) Program Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15

Assessment of Variability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15

Relative and Absolute Percentage Differences . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15

Comparison of Blind-Audit and SHE Program Variability and Bias Estimates . . . . . . . . . . . . . . . . . . . . . . . . . . 19

Field-Audit Program . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21

Assessment of Field-Audit Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23

Assessment of Variability and Bias . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26

Low-Level Contamination Detection in Ultrapure Deionized-Water Samples . . . . . . . . . . . . . . . . . . . . . . . . . 27

Relative and Absolute Percentage Differences . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29

Relation of Sample Volume and Field-Audit Data Variability and Bias . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29

Interlaboratory-Comparison Program . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30

Variability and Bias . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34

Median Absolute Error in Chemical Analyses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37

Control Charts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39

Collocated-Sampler Program . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51

Data Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51

Assessment of Absolute Error . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51

Comparison of Sources of Variability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52

Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55

References Cited . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58

Figures

1. Flowchart showing intersite-comparison program of U.S. Geological Survey External QualityAssuranceProject . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .4

2–6. Graphs showing:

 2. Distribution of pH and specific conductance values for intersite-comparison studies 48 

and 49. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .7

 3. Distribution of pH and specific conductance values for intersite-comparison studies 50 

and 51. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .8

 4. Summary of followup study results obtained during 2002 for intersite-comparison program . . .9

 5. Summary of followup study results obtained during 2003 for intersite-comparison program . 10
iv 

 6. Percentage of successful pH and specific conductance measurements in intersitecomparison program during 1998–2003 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

 7. Flowchart showing blind-audit program of U.S. Geological Survey. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13

 8. Flowchart showing sample-handling evaluation program of U.S. Geological Survey . . . . . . . . . . . . . . 14

9–13. Boxplots showing:

 9. Paired bucket-sample minus bottle-sample measurement differences for blind-audit 

programduring 2002. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18

 10. Comparison of distributions of bucket-minus-bottle concentration differences for 2002

blind-audit program and 2003 sample-handling evaluation program. . . . . . . . . . . . . . . . . . . . . . . . . 22

11. Comparison of distribution of bucket-minus-bottle differences for hydrogen-ion 

concentration and specific conductance for 2002 blind-audit program and 2003 samplehandling evaluation program . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23

 12. Relation of bucket-minus-bottle hydrogen-ion concentration differences and sample 

volume for 2002 blind-audit data and 2003 sample-handling evaluation data . . . . . . . . . . . . . . . . . 24

 13. Relation of paired bucket-minus-bottle specific conductance differences and sample 

volume for 2002 blind-audit data and 2003 sample-handling evaluation data . . . . . . . . . . . . . . . . . 25

14. Flowchart showing field-audit program of U.S. Geological Survey. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26

15–19. Boxplots showing:

 15. Bucket-minus-bottle concentration differences for 2002–03 field-audit major ions. . . . . . . . . . . .28

 16. Bucket-minus-bottle differences for hydrogen-ion concentration and specific 

conductancefor 2002–03 field-audit data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29

 17. Relation of paired bucket-minus-bottle major cation concentration differences and 

sample volumefor 2002–03 field-audit data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32

 18. Relation of paired bucket-minus-bottle ammonium and major anion concentration 

differences and sample volume for 2002–03 field-audit data. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33

 19. Relation of paired bucket-minus-bottle differences for hydrogen-ion concentration and 

specificconductance to sample volume for 2002–03 field-audit data . . . . . . . . . . . . . . . . . . . . . . . . 34

 20. Flowchart showing interlaboratory-comparison program of U.S. Geological Survey. . . . . . . . . . . . . . . .35

21–32. Graphs showing:

 21. Difference between measured calcium concentration values and median calcium 

concentration value calculated by solution for all participating laboratories in

interlaboratory-comparison program during 2002–03. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41

22. Difference between measured magnesium concentration values and median 

magnesiumconcentration value calculated by solution for all participating laboratories in 

interlaboratory-comparison program during 2002–03. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42

 23. Difference between measured sodium concentration values and median sodium 

concentration value calculated by solution for all participating laboratories in 

interlaboratory-comparison program during 2002–03. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43

 24. Difference between measured potassium concentration values and median potassium 

concentration value calculated by solution for all participating laboratories in 

interlaboratory comparison program during 2002–03. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44

 25. Difference between measured ammonium concentration values and median ammonium 

concentration value calculated by solution for all participating laboratories in 

interlaboratory-comparison program during 2002–03. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45

 26. Difference between measured chloride concentration values and median chloride 

concentration value calculated by solution for all participating laboratories in 

interlaboratory-comparison program during 2002–03. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46

27. Difference between measured nitrate concentration values and median nitrate 

concentration value calculated by solution for all participating laboratories in 

interlaboratory-comparison programduring 2002–03. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47
 v

28. Difference between measured sulfate concentration values and median sulfate concentration 

value calculated by solutionfor all participating laboratories in interlaboratory-comparison 

programduring 2002–03 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48

 29. Difference between measured pH values and median pH value calculated by solutionfor all 

participating laboratories in interlaboratory-comparison program during 

2002–03 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49

 30. Difference between measured specific conductance values and median specific 

conductance value calculated by solutionfor all participating laboratories in interlaboratorycomparison program during 2002–03 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50

 31. Median absolute error for analyte concentration and deposition for weekly samples from 

collocated precipitation collectors during2002–03 for selected analytes . . . . . . . . . . . . . . . . . . . . 53

 32. Median absolute error for hydrogen-ion concentration and deposition, specific conductance, 

and sample volume for weekly samples from collocated precipitation collectors and 

precipitationdepth from collocated rain gages during 2002–03. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54

33. Pie chart showing proportions of selected components of overall variability in National Atmospheric Deposition Program/National Trends Network measurements as estimated by U.S. 

Geological Survey external quality-assurance programs during 2002–03. . . . . . . . . . . . . . . . . . . . 58

Tables

1. Site-operator responses and summary statistics for 2002 intersite-comparison program 

studies 48and 49 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .5

 2. Site-operator responses and summary statistics for 2003 intersite-comparison program 

studies 50and 51 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .6

 3. Solutions used in 2002–03 blind-audit, sample-handling evaluation, field-audit, and 

interlaboratory-comparison programs. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15

 4. Target values for solutions used in 2002–03 U.S. Geological Survey blind-audit, samplehandling evaluation,field-audit, and interlaboratory-comparison programs . . . . . . . . . . . . . . . . . . . . . . . 16

 5. Selected statistics for paired bucket-sample minus bottle-sample concentration differences in 

blind-audit program during 2002 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17

 6. Relative and absolute bucket-minus-bottle differences calculated as a percentage of target 

concentration or value for each analyte during 2002 for blind-audit program . . . . . . . . . . . . . . . . . . . . . . 19

 7. Selected statistics for paired bucket-sample minus bottle-sample concentration differences 

for sample-handling evaluation program during 2003 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20

 8. Relative and absolute bucket-minus-bottle differences calculated as a percentage of target 

concentration or value for each analyte during 2003 for sample-handling evaluation program. . . . . 21

 9. Selected statistics for paired bucket-sample minus bottle-sample concentration differences for 

field-audit program during 2002–03 for wet- and dry-coded samples . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27

 10. Number of determinations exceeding minimum detection limit for 24 ultrapure deionized-water 

samples submitted in 2002 and for 18 ultrapure deionized-water samples submitted in 2003 as 

part of field-audit program . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30

 11. Relative and absolute bucket-minus-bottle differences calculated as a percentage of target 

concentration or value for each analyte in field-audit program during 2002–03 . . . . . . . . . . . . . . . . . . . . 31

 12. Most probable values for solutions used in 2002–03 U.S. Geological Survey interlaboratorycomparison program . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36

 13. Comparison of differences between reported concentrations and most probable values for 

syntheticprecipitation samples in interlaboratory-comparison program during 2002–03. . . . . . . . . . . 38

 14. Number of analyte determinations greater than minimum detection limits for each 

participatinglaboratoryand each ion for ultrapure deionized-water samples during 2002–03. . . . . . 39
vi 

 15. Summary of absolute differences for analysis of replicate, synthetic-precipitation solution 

samplesdetermined by eight laboratoriesparticipating in 2002–03 interlaboratory-comparison 

program. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40

 16. Comparison of median absolute differences determined for collocated-sampler sites 

OR02/02OR andWI98/98WI during water year 2002 to median values obtained during 2002 for 

allNational AtmosphericDeposition Program/National Trends Network sites and to median 

absolute differences for 41 collocated-sampler sites during 1989-2001 . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55

17. Comparison of median absolute differences determined for collocated-sampler sites 

OK00/00OK andWI98/98WI during water year 2003 to median values obtained during 2002 for 

allNational AtmosphericDeposition Program/National Trends Network sites and to median 

absolute differences for 41 collocated-sampler sites during 1989-2001 . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56

 18. Comparison of components of overall variability in National Atmospheric Deposition Program/

National Trends Network data as determined by U.S. Geological Survey external qualityassurance programs during 2002–03 for major ion concentrations and specific conductance. . . . . 57
 vii

Conversion Factors, Abbreviated Units, and 

Acronyms 

Temperature can be converted from degree Celsius(°C) to degree Fahrenheit (°F) by using the 

following equation:

°F = 9/5(°C) + 32.

Water year is the 12-month period October 1 through September 30 and is designated by the year 

in which it ends.

The following terms and abbreviations also are used in this report:

Multiply By To obtain

Length

centimeter (cm) 0.3937 inch (in.)

liter (L) 1.057 quart (qt)

milliliter (mL) 0.0338 ounce (oz), fluid

kilogram per hectare (kg/ha) 0.8924 pound per acre (lb/acre)

Abbreviation Full name

absolute value of x = |x| where x takes the form of numerical values or algebraic 

expressions

α alpha, maximum probability of rejecting the null hypothesis when 

it is true 

ADORC Acid Deposition and Oxidant Research Center, Niigata-shi, Japan

AIRMoN Atmospheric Integrated Research Monitoring Network

APD absolute percentage difference

CAL Illinois State Water Survey, Central Analytical Laboratory, 

Champaign, Illinois

CALNAT randomly collected natural wet-deposition samples collected at 

NADP/NTN sites for use in interlaboratory-comparison 

program

HPS High Purity Standards, Charleston, South Carolina

IQR interquartile range

MAD median absolute difference, in units of concentration or μS/cm

MAE median absolute error, in percent

MATEC MATEC, Inc., Gainesville, Florida

MΩ megohm

MDN Mercury Deposition Network

μeq/L microequivalents per liter

μS/cm microsiemens per centimeter at 25 degrees Celsius 

mg/L milligrams per liter

MDL minimum detection limit

MOEE Ontario Ministry of Environmental and Energy, Dorset Research 

Facility, Dorset, Ontario, Canada

MPV most probable value

MSC Meteorological Service of Canada, Downsview, Ontario, Canada

NADP/NTN National Atmospheric Deposition Program/National Trends 

Network

NILU Norwegian Institute for Air Research, Kjeller, Norway

NIST National Institute of Standards and Technology
viii 

NYSDEC New York State Department of Environmental Conservation, 

Albany, New York

QA quality assurance

QC quality control

RPD relative percentage difference

SA Shepard Analytical, Simi Valley, California

SHE sample-handling evaluation program

SOP standard operating procedure

Abbreviation Full name
External Quality-Assurance Results for the National 

Atmospheric Deposition Program/National Trends 

Network, 2002–03

By Gregory A. Wetherbee, Natalie E. Latysh, and Kevin P. Burke

Abstract

Six external quality-assurance programs were operated by 

the U.S. Geological Survey (USGS) External QualityAssurance (QA) Project for the National Atmospheric Deposition Program/National Trends Network (NADP/NTN) from 

2002 through 2003. Each program measured specific components of the overall error inherent in NADP/NTN wetdeposition measurements.

The intersite-comparison program assessed the variability 

and bias of pH and specific conductance determinations made 

by NADP/NTN site operators twice per year with respect to 

accuracy goals. The percentage of site operators that met the 

pH accuracy goals decreased from 92.0 percent in spring 2002 

to 86.3 percent in spring 2003. In these same four intersitecomparison studies, the percentage of site operators that met the 

accuracy goals for specific conductance ranged from 94.4 to 

97.5 percent. 

The blind-audit program and the sample-handling evaluation (SHE) program evaluated the effects of routine sample handling, processing, and shipping on the chemistry of weekly 

NADP/NTN samples. The blind-audit program data indicated 

that the variability introduced by sample handling might be 

environmentally significant to data users for sodium, potassium, chloride, and hydrogen ion concentrations during 2002. 

In 2003, the blind-audit program was modified and replaced by 

the SHE program. The SHE program was designed to control 

the effects of laboratory-analysis variability. The 2003 SHE 

data had less overall variability than the 2002 blind-audit data. 

The SHE data indicated that sample handling buffers the pH of 

the precipitation samples and, in turn, results in slightly lower 

conductivity. Otherwise, the SHE data provided error estimates 

that were not environmentally significant to data users.

The field-audit program was designed to evaluate the 

effects of onsite exposure, sample handling, and shipping on the 

chemistry of NADP/NTN precipitation samples. Field-audit 

results indicated that exposure of NADP/NTN wet-deposition 

samples to onsite conditions tended to neutralize the acidity of 

the samples by less than 1.0 microequivalent per liter. Onsite 

exposure of the sampling bucket appeared to slightly increase 

the concentration of most of the analytes but not to an extent 

that was environmentally significant to NADP data users.

An interlaboratory-comparison program was used to estimate the analytical variability and bias of the NADP Central 

Analytical Laboratory (CAL) during 2002–03. Bias was identified in the CAL data for calcium, magnesium, sodium, potassium, ammonium, chloride, nitrate, sulfate, hydrogen ion, and 

specific conductance, but the absolute value of the bias was less 

than analytical minimum detection limits for all constituents 

except magnesium, nitrate, sulfate, and specific conductance. 

Control charts showed that CAL results were within statistical 

control approximately 90 percent of the time. Data for the analysis of ultrapure deionized-water samples indicated that CAL 

did not have problems with laboratory contamination. 

During 2002–03, the overall variability of data from the 

NADP/NTN precipitation-monitoring system was estimated 

using data from three collocated monitoring sites. Measurement differences of constituent concentration and deposition 

for paired samples from the collocated samplers were evaluated 

to compute error terms. The medians of the absolute percentage 

errors (MAEs) for the paired samples generally were larger for 

cations (approximately 8 to 50 percent) than for anions (approximately 3 to 33 percent). MAEs were approximately 16 to 

30 percent for hydrogen-ion concentration, less than 10 percent 

for specific conductance, less than 5 percent for sample volume, 

and less than 8 percent for precipitation depth.

The variability attributed to each component of the sample-collection and analysis processes, as estimated by USGS 

quality-assurance programs, varied among analytes. Laboratory analysis variability accounted for approximately 2 percent 

of the overall variability in NADP/NTN measurements. Sample onsite exposure accounted for approximately 8 percent of 

the overall variability. Sample handling accounted for approximately 26 percent of the overall variability. The remaining 

variability, not accounted for by laboratory analysis, onsite 

exposure, and sample handling (approximately 64 percent), was 

attributed to the variable function of the onsite instrumentation 

and natural variability.
2 External Quality-Assurance Results for the National Atmospheric Deposition Program/National Trends Network, 2002–03

Introduction

A fundamental objective of the National Atmospheric 

Deposition Program (NADP) is to provide scientific investigators worldwide with a long-term, high-quality database of atmospheric wet-deposition information (Nilles, 2001). The NADP 

consists of three monitoring networks that are used to collect 

precipitation depth data and atmospheric deposition samples for 

chemical analysis—(1) National Trends Network (NTN), 

(2) Atmospheric Integrated Research Monitoring Network 

(AIRMoN), and (3) Mercury Deposition Network (MDN). 

NADP/NTN has monitored the effects of wet deposition across 

the United States since 1978 (Robertson and Wilson, 1985; 

Peden, 1986). Research scientists use NADP/NTN data to study 

the effects of atmospheric deposition on human health and the 

environment. All operators of NADP/NTN sites adhere to the 

same sample-collection and analysis procedures using identical 

wet-deposition collectors, described by Dossett and Bowersox 

(1999), and standard NADP/NTN sample-handling and shipping protocols are followed at the sites. Samples from 

NADP/NTN sites are sent to the Illinois State Water Survey, 

Central Analytical Laboratory (CAL), for analysis. A protocol 

report providing detailed information on the quality-assurance 

(QA) procedures and analytical methods is available (See and 

others, 1990). 

This report describes the results of the external QA programs operated by the U.S. Geological Survey (USGS) External QA Project in support of NADP/NTN during 2002–03 

(study period). These programs are designed to: (1) assess the 

variability and bias of onsite determinations of pH and specific 

conductance (intersite-comparison program); (2) evaluate 

effects of potential contamination due to handling, processing, 

and shipping of samples collected by NADP/NTN (blind-audit 

and sample-handling evaluation programs); (3) evaluate potential contamination introduced from onsite exposure of the samples, sample handling, and shipping (field-audit program); 

(4) estimate the variability and bias of analytical results determined by separate laboratories routinely measuring wet deposition (interlaboratory-comparison program); (5) estimate the 

overall variability of NADP/NTN data from the point of sample 

collection through laboratory data-quality control (collocatedsampler program); and (6) facilitate integration of data from 

various monitoring networks.

The term “major ions” in this text refers to calcium, magnesium, sodium, potassium, ammonium, chloride, nitrate, and 

sulfate. Throughout this report, concentration results are presented for cations first (calcium, magnesium, sodium, potassium, and ammonium), followed by anions (chloride, nitrate, 

and sulfate), followed, where appropriate, by hydrogen-ion 

concentration, specific conductance, sample volume, and precipitation depth. Hydrogen-ion concentrations are calculated 

from reported pH values. Conversion of the pH measurements 

to hydrogen-ion concentration allows for resolution of differences that would be masked by the nonlinear pH scale. 

Statistical Approach

Nonparametric rank-based alternatives to traditional 

hypothesis testing constitute the statistical analysis framework 

in this report. Nonparametric statistical tests were used because 

the datasets do not adhere to the normal distribution requirements of traditional parametric statistics. Hypothesis tests 

included the Wilcoxon signed-rank test, the Kruskal-Wallis 

test, and the Sign test (Kanji, 1993). The Wilcoxon signed-rank 

test (Hollander and Wolfe, 1999) was used to determine if there 

were shifts in data distributions due to the exclusion of samples 

identified as contaminated. The Kruskal-Wallis test (Iman and 

Conover, 1983) was used to compare two or more independent 

samples (SAS Institute Inc., 1989). The Sign test was used to 

identify bias in chemical analysis data from analytical 

laboratories.

All null hypotheses were tested at the 95-percent confidence level (α=0.05 statistical significance level), which 

implies that a 5-percent chance of rejecting the null hypothesis 

when it is true, is acceptable. For each test, the probability of 

rejecting the null hypothesis when it is true (p-value) is calculated. A p-value less than 0.05 indicates that there is less than a 

5-percent chance of rejecting the null hypothesis when it is true. 

The hypothesis tests are based on two-sided rather than onesided alternatives, whereby the total acceptable uncertainty of 

5 percent (α=0.05) is split between the positive and negative 

ends of the data distribution. Huntsberger and Billingsley 

(1981) provide a detailed explanation of two-sided and onesided hypothesis testing.

The f-pseudosigma values are presented for many of the 

results in this report. The f-pseudosigma is used as a nonparametric analogue of the standard deviation of a statistical sample. 

The f-pseudosigma is calculated as the interquartile range (IQR, 

75th percentile value minus the 25th percentile value) divided 

by 1.349 (Hoaglin and others, 1983), as shown in equation 1.

. (1)

Relative and absolute percentage differences are calculated for each QA program as an estimation of the relative 

amount of error attributed to individual components of the datacollection process. The absolute percentage differences are 

used to quantify variability, whereas the relative percentage differences are used to quantify bias. The relative and absolute percentage differences are calculated for each paired difference as 

a percentage of the target sample concentration:

, 

and (2)

, (3)

f-pseudosigma 75th percentile – 25th percentile

1.349 = -----------------------------------------------------------------------------

Relative percentage difference (RPD) (C1-C2)/C3 = [ ] • 100

Absolute percentage difference (APD) (C1-C2)/C3 100 = •
Intersite-Comparison Program 3

where

C1 = sample concentration, in milligrams per liter 

(mg/L), for the sample exposed to the collection and 

processing steps of a normal weekly precipitation 

sample; 

C2 = sample concentration (in milligrams per liter) for 

the control sample subjected to minimal handling, 

and processing; and

C3 = target concentration (in milligrams per liter), which 

is the theoretically accepted concentration on the 

basis of laboratory preparation of performance evaluation samples from solutions of known concentration or determined experimentally as the median 

concentration on the basis of many independent 

analyses.

Concise graphical displays, such as boxplots, were used to 

depict data distributions and provide visual representations of 

NADP/NTN data quality. Tukey’s “schematic plot” version of 

the boxplot (Chambers and others, 1983) was used for all boxplots, whereby notches in the sides of the boxes are used to 

highlight the location of the median. The ends of the box are 

drawn at the lower and upper quartiles, which are the 25th and 

75th percentiles, respectively. The ends of the box depict the 

interquartile range (IQR). Whiskers are drawn from the quartiles to the last value that is located within a distance of 

1.5 times the IQR. Values greater than 1.5 times the IQR are 

graphed individually as asterisks and are called “outside values” (SAS Institute, 1989). In a normal distribution, there 

should be one outside value for every 100 data points (Helsel 

and Hirsch, 1992). Therefore, the occurrence of asterisks more 

frequently than expected indicates that the data are not normally 

distributed. The magnitude of measurement bias was quantified 

in several ways for the convenience of the reader, including 

units of concentration (for example, in mg/L), signed 

differences, and percentage differences. 

Intersite-Comparison Program

Intersite-comparison studies are completed by the USGS 

to assess the accuracy of onsite pH and specific conductance 

measurements made by NADP/NTN site operators. Measurement accuracy is defined herein as the combined evaluation of 

variability and bias. If measurements are not accurate, site operators are provided troubleshooting assistance by USGS. A flowchart depicting the chronological order of the intersite-comparison program is shown in figure 1. Due to the low ionic strength 

of precipitation, minor changes may occur between sample collection and laboratory analysis (Bigelow and others, 1989). 

Many authors have determined that onsite measurements (of pH 

in particular) are more representative of precipitation than subsequent laboratory determinations (Hem, 1985). 

In the intersite-comparison studies, site operators determined the pH and specific conductance of synthetic precipitation-check samples prepared by USGS. Protocols identical to 

NADP/NTN sample measurement methods were used (Gordon 

and others, 1991; Dossett and Bowersox, 1999). USGS prepared the synthetic precipitation-check samples by adding nitric 

acid and potassium chloride to deionized water to obtain solutions with pH and specific conductance similar to natural wetdeposition samples collected by NADP/NTN. The pH of the 

solution is adjusted to a target value ranging from 3.9 to 

5.3 standard units by adding nitric acid. Then, the specific conductance of the solution is adjusted to a target value using the 

potassium chloride. The pH and specific conductance target 

values for the solutions were verified by USGS before the solutions were mailed to the sites. The same unique check solution 

was sent to all NADP/NTN sites for each study. Each site’s 

ability to achieve the target pH and specific conductance values 

was evaluated. Operators also measured quality-control (QC) 

check standards provided by CAL (target pH: 4.19 + 0.15 standard units; and target specific conductance: 14 microsiemens 

per centimeter (μS/cm) + 2.0 μS/cm), prior to measuring the pH 

and specific conductance of precipitation samples and intersitecomparison samples, but those measurements are not evaluated 

herein.

Results for Intersite-Comparison Studies 48–51

Intersite studies 48 and 49 were completed during spring 

and fall 2002, respectively; studies 50 and 51 were completed 

during spring and fall 2003, respectively. From the day the samples were mailed, operators were allowed 45 days to perform 

the pH and specific conductance measurements. Sites were not 

included in the study’s performance evaluation if (1) they 

responded late, (2) the onsite equipment was completely inoperable, (3) the site was not in operation at the time of the study, 

or (4) the site did not perform onsite chemistry during the intersite-comparison study period.

Accuracy goals for pH were designed to address the 

increased difficulty of measuring pH in low-ionic-strength solutions as the hydrogen-ion concentration approaches neutrality 

(Gordon, 1999). Accuracy goals for pH measurements were 

based on a multiple-regression function that incorporated the 

solution’s hydrogen-ion concentration and the results from 

intersite studies 1–39 (John D. Gordon, U.S. Geological Survey, written commun., 1995). The accuracy goals were symmetrical in units of hydrogen-ion concentration and, therefore, 

were asymmetrical in units of pH. The specific conductance 

values for all of the intersite comparison solutions used during 

the study period were between 8 and 24 μS/cm. For specific 

conductance, if the most probable specific conductance was 

greater than 10 μS/cm but less than or equal to 60 μS/cm, the 

accuracy criterion was ± 4 μS/cm. If the most probable specific 

conductance was less than 10 μS/cm, then the accuracy criterion was + 2 μS/cm. 

The median values obtained from the site operators were 

used as the most probable values for intersite-comparison solutions. The median values from approximately 220 site-operator 

measurements were considered a more accurate representation 
4 External Quality-Assurance Results for the National Atmospheric Deposition Program/National Trends Network, 2002–03

Intersite-comparison study samples

prepared by U.S. Geological Survey

Samples analyzed for pH and specific

conductance by site operators

Response cards completed and mailed

to U.S. Geological Survey

Preliminary database compiled

Final database compiled

Site operator results during the

previous two studies analyzed

Site operator included

in followup program

Results sent to

site operators

Results sent to

NADP Program Office

Results presented to the NADP/

Network Operations Subsommittee

Results reported in publications

and on World Wide Web

USGS mails field-measurement

guidance letter to site operator

Did site operator meet

measurement accuracy goals?

Did site operator have difficulty meeting

accuracy goals in the previous two studies?

List of nonresponding site operators sent

to Quality Assurance Manager for the

National Atmospheric Deposition

Program (NADP)

Yes Yes

No

No

Figure 1. Intersite-comparison program of U.S. Geological Survey External Quality-Assurance Project.

of the most likely values for the intersite solutions than either a 

few in-house measurements or the theoretical values (Gordon, 

1999; See and others, 1989). Previous studies have found no 

appreciable deterioration of intersite solutions over the duration 

of the studies, which further supports the use of the median of 

the values obtained from site-operator measurements as the 

most probable values (Gordon and others, 1995). 

Table 1 contains a summary of the results for studies 48 

and 49. Table 2 summarizes the results for studies 50 and 51. 

The accuracy goals for each study also are provided (tables 1 

and 2). 

The pH and specific conductance measurement results for 

intersite-comparison studies 48–51 are plotted in figures 2 and 

3. The data in figures 2 and 3 indicate that a large majority of 

sites met measurement goals for both pH and specific conductance. Moreover, there was no relation between sites that did 

not meet pH measurement goals and sites that did not meet specific conductance measurement goals during 2002–03.

Intersite-Comparison Followup Studies

After the initial intersite-comparison results were tabulated for each study, the results from site operators that did not 

meet the pH accuracy goals were evaluated further in followup 

studies. The purpose of the followup studies was to help site 

operators identify and resolve sources of measurement difficulty and to produce better weekly data for NADP/NTN. Each 
Intersite-Comparison Program 5

Table 1. Site-operator responses and summary statistics for 2002 intersite-comparison program studies 48 and 49.

[μS/cm, microsiemens per centimeter at 25 degrees Celsius]

Site-operator responses

Study number

48 49

Number of site operators receiving samples 230 238

Number of site operators submitting pH values by closing date of study 199 197

Number of site operators submitting specific conductance values by closing date of study 199 195

Number of site operators responding late 16 10

Number of nonresponding site operators 14 29

Number of sites that were not in operation 1 2

Number of site operators reporting equipment problems:

 pH meter/electrode completely inoperable 0 2

 pH meter/electrode problems 0 0

 Specific conductance probe/meter completely inoperable 0 4

 Specific conductance probe/meter problems 0 0

Median pH, target pH 4.91, 4.90 4.72, 4.70

Number of responding sites that met the pH accuracy goals 183 174

Accuracy goals for pH: lower and upper acceptable values 4.72, 5.09 4.56, 4.86

Percentage of responding sites that met the pH accuracy goals 92.0 88.3

f-pseudosigma for pH .067 .052

Median specific conductance, target specific conductance, in μS/cm 23.8, 23.0 8.9, 8.4

Number of responding sites that met the specific conductance accuracy goals (+4 μS/cm) 194 184

Accuracy goals for specific conductance: lower and upper acceptable values, in μS/cm 19.8, 27.8 6.9, 10.9

Percentage of responding sites that met the specific conductance accuracy goals 97.5 94.4

f-pseudosigma for specific conductance .667 .445

operator that failed to meet the accuracy goals was placed into 

one of four followup categories on the basis of their performance in the current intersite-comparison program study and in 

the two preceding studies.

For the followup studies, the site operators’ reported values are converted into standardized z-values. Z-values are analogous to z-scores described by Iman and Conover (1983), 

whereby nonparametric estimators replace the traditional parametric estimators. Z-values indicate the number of standard 

deviations between a measured value and the median. The sign 

of the z-value denotes whether it is in the left or right tail of the 

distribution. For example, a z-value of +1 identifies the value 

to be approximately one standard deviation to the right of the 

median, whereas a z-value of -2 is two standard deviations to 

the left of the median. Z-values outside +3 standard deviations 

are considered to be outliers because approximately 99 percent 

of the data in a population is within three standard deviations of 

the median (Iman and Conover, 1983). The formulas for zscores and z-values are:

, and (4)

, (5)

where x = an individual observation,

= the mean of all observations,

= the median of all observations,

S = standard deviation of all observations, and 

fps = f-pseudosigma of all observations:

.

By using standardized z-values, each site operator’s performance, relative to all other site operators, was evaluated statistically. The standardized z-values take into account the 

amount by which pH-measurement accuracy goals are missed, 

given the relative difficulty of measuring the pH of the solution. 

The relative difficulty of measuring the pH of the low-ionicstrength solutions is inversely related to the hydrogenion concentration of the solution—the lower the hydrogen-ion 

concentration, the more difficult the measurement. A cumulative z-value total for the three most-recent studies was used to 

place each site operator failing to meet the accuracy goals into 

one of these followup study categories:

Level 1. Operators received a letter discussing common 

sources of measurement errors and were asked to 

voluntarily remeasure the intersite-comparison 

sample.

z-score x x –

S = ----------

z-value x x –  ̃

fps = ----------

x

x ̃

75th percentile 25th percentile –

1.349 -----------------------------------------------------------------------------
6 External Quality-Assurance Results for the National Atmospheric Deposition Program/National Trends Network, 2002–03

Table 2. Site-operator responses and summary statistics for 2003 intersite-comparison program studies 50 and 51.

[μS/cm, microsiemens per centimeter at 25 degrees Celsius]

Site-operator responses

Study number

50 51

Number of site operators receiving samples 239 242

Number of site operators submitting pH values by closing date of study 226 216

Number of site operators submitting specific conductance values by closing date of study 226 217

Number of site operators responding late 4 11

Number of nonresponding site operators 9 14

Number of sites that were not in operation 0 1

Number of site operators reporting equipment problems:

 pH meter/electrode completely inoperable 0 3

 pH meter/electrode problems 0 0

 Specific conductance probe/meter completely inoperable 0 1

 Specific conductance probe/meter problems 0 0

Median pH, target pH 4.56, 4.50 4.41, 4.35

Number of responding sites that met the pH accuracy goals 195 187

Accuracy goals for pH: lower and upper acceptable values 4.42, 4.67 4.29, 4.50

Percentage of responding sites that met the pH accuracy goals 86.3 86.6

f-pseudosigma for pH .044 .059

Median specific conductance, target specific conductance, in μS/cm 13.1, 13.3 18.3, 18.8

Number of responding sites that met the specific conductance accuracy goals (±4 μS/cm) 220 209

Accuracy goals for specific conductance: lower and upper acceptable values, in μS/cm 9.1, 17.1 14.3, 22.3

Percentage of responding sites that met the specific conductance accuracy goals 97.3 96.3

f-pseudosigma for specific conductance .667 .741

Level 2. Operators received a letter discussing common 

sources of measurement errors and were asked to 

reanalyze the remaining portion of the intersitecomparison sample.

Level 3. Operators received a letter discussing common 

sources of measurement errors and were asked to 

reanalyze the original intersite-comparison 

sample plus one additional intersite-comparison 

sample.

Level 4. Operators received a letter discussing common 

sources of measurement errors and were asked to 

reanalyze the original intersite-comparison 

sample plus two additional intersite-comparison 

samples of different pH and specific conductance 

target values.

The additional intersite-comparison samples sent to Level 

3 and 4 site operators were solutions that had been used in previous intersite-comparison studies and stored at 4oC in their 

original unopened bottles. Previous studies (Peden and Skowron, 1978; Gordon and others, 1995) indicated that the stability 

of hydrogen-ion concentration over time was sufficient to allow 

the use of previous intersite samples in the followup analysis.

During 2002 and 2003, the number of site operators that 

were required to participate in Level 1, Level 2, Level 3, and 

Level 4 intersite-comparison followup studies increased from 

32 in spring 2002 to 56 in fall 2003. Figure 4 summarizes the 

followup results for studies 48 and 49 during 2002, and figure 5 

summarizes the results for studies 50 and 51 during 2003. 

Before 2002, the followup studies proved to be effective in 

improving the quality of the onsite pH and specific conductance 

data (Wetherbee and others, 2004). However, the followup 

studies were not as effective during 2002–03, as indicated by a 

decrease in the percentage of successful intersite-comparison 

pH measurements during the study period as compared to 

results from 2000–2001 (fig. 6).

The 2002–03 intersite-comparison data were compared to 

data obtained in previous years to identify trends in operator 

performance. Site-operator performance for onsite pH and specific conductance measurement remained high over the years 

1998–2003 (fig. 6). However, the percentage of successful pH 

measurements for the intersite-comparison program fell from 

92.0 percent for study 48 to 86.3 percent for study 50, whereas 

94.4 to 97.5 percent of the site operators met accuracy goals for 

specific conductance. The data in figure 6 indicate a slight 

decrease in site-operator onsite-pH measurement performance 

during 2002–03. The data for intersite-comparison studies 48–

51 also indicate a decrease in site-operator participation for 

study number 50. The bottom graph in figure 6 indicates a 

decrease in the number of successful followup study 
Intersite-Comparison Program 7

These data pairs were off scale in study 48

Site pH Specific Site pH Specific

code conductance conductance

 These data pairs were off scale in study 49

 Site pH Specific Site pH Specific

 code conductance conductance

NE15

ME02

WY98

UT01

ND11

CA66

OK17

CA88

IN34

NM01 6.85 22.1

TX03 5.78 22.2 UT08 5.52 21.4

CAN5 4.65 16.4

OK08

TX02 & NC36

VA24

OH15

FL23

GA41

VA24

FL41

NY52 NC34

VA24

KS32

OH15

IL63

MN27

ID15 WY99

TX21 AL10

MT96

NC03

WY97

VA99

UT08

NV00

PR20

CO01

IL46

NDO8 5.60 8.70

TX39 4.85 18.1

OH49 4.72 25.4

MI48 NM07 ME02

CA88

NC29

FL05

WA19

MS19 4.86 17.0

FL23 4.75 11.0

VA24 Data point with four-character site code

Intersite-comparison study 49 − December 2002

Intersite-comparison study 48 − June 2002

Specific conductance, in microsiemens per centimeter at 25 degrees Celsius

pH, in standard units

EXPLANATION

Met National Atmospheric

Deposition Program / 

National Trends Network 

(NADP/NTN) goals for pH only

Met NADP/NTN goals for

pH and specific conductance

Met NADP/NTN goals for

specific conductance only

4.5

4.3 4.5 4.7 4.9 5.1 5.3 5.5

19

4

6

8

10

12

14

16

21

23

25

27

29

31

4.7 4.9 5.1 5.3

code

code

Figure 2. Distribution of pH and specific conductance values for intersite-comparison studies 48 and 49.
8 External Quality-Assurance Results for the National Atmospheric Deposition Program/National Trends Network, 2002–03

WV04

IL46

ME08

OH15

UT08

IL63

IN34

NC45

OK29

CO02 & CO94

MN27

NV05

SC06

NM08 5.71 2.2

MO05 7.10 10.8

WV05

KY35

OK17

MI99

NJ99

AR03

MO03

TX03

TX04

ME04

IA23

PR20

MN99

FL99, GA98, IA23,

MI26, ND08, WY99

CO91

SD04

ME95

UT09

ID15 4.40 4.4 ME09 4.56 24.1

ND11 3.45 13.7

MS10 12.3 12.3

TX39 4.41 64.2 WV04 5.25 26.2

MO05

ID03

AZ99

WY00&WY95

PA00

WI97

VA28IL11

SC05

TN04

MO03

CA99 IA23

WI35

OK29

AZ97

FL05 & KY35

WA99

TX03

WY08

WA19

KY10

CO00, CO10, CO93, CO96,

CT15, DE99, FL99, GA09,

GA98, KY10, ME04, MI29

MT98, NC35, OH71, TX02,

WY99

MT96

FL23

VA24

VA13

CO91

MS30

These data pairs were off scale in study 50

Site pH Specific Site pH Specific

code conductance conductance

These data pairs were off scale in study 51

Site pH Specific Site pH Specific

code conductance conductance

VA24 Data point with four-character site code

EXPLANATION

Met National Atmospheric

Deposition Program / 

National Trends Network 

(NADP/NTN) goals for pH only

Met NADP/NTN goals for

pH and specific conductance

Met NADP/NTN goals for

specific conductance only

code

code

Intersite-comparison study 51 − December 2003

Intersite-comparison study 50 − June 2003

Specific conductance, in microsiemens per centimeter at 25 degrees Celsius

pH, in standard units

4.1

6

5

10

15

20

25

30

8

10

12

14

16

18

20

4.0 4.2 4.4 4.6 4.8 5.0

4.3 4.5 4.7 4.9 5.1

Figure 3. Distribution of pH and specific conductance values for intersite-comparison studies 50 and 51.
Sample-Handling Variability and Bias 9

Level 1 Level 2 Level 3 Level 4

0

5

10

15

20

0

5

10

15

20

Followup results for intersite-comparison study 48

Combined number of site operators

participating in all levels: 32

Combined number of site operators

participating in all levels: 34

Followup results for intersite-comparison study 49

Number of site operators 

Participated in the followup study

Did not participate in the followup study

Successfully met the accuracy goals for 

 the followup study

EXPLANATION

Had mixed success meeting the accuracy

 goals for the followup study

Did not meet the accuracy goals for the 

 followup study

Level 1 followup :

(1) Letter discussing common sources of 

measurement errors

(2) Request for voluntary, additional 

measurement of the intersite- intersiteintersitecomparison 

-comparison sample 

sample

Level 2 followup :

(1) Letter discussing common sources of 

measurement errors

(2) Request that site operator reanalyze the 

remaining portion of the 

comparison sample

Level 3 followup :

(1) Letter discussing common sources of 

(2) Request that site operator reanalyze the 

remaining portion of the 

comparison sample

-comparison samples

(3) Request that site operator analyze one 

additional intersite

Level 4 followup :

(1) Letter discussing common sources of 

measurement errors

(2) Request that site operator reanalyze the 

remaining portion of the 

comparison sample

(3) Request that site operator analyze two 

additional intersite

:

:

intersite-

:

measurement errors

additional intersite

:

Figure 4. Summary of followup study results obtained during 2002 for intersite-comparison program.

measurements, on the basis of the total number of requested 

measurements, for study 50. Although the intersite-comparison 

program results indicate that a majority of NADP/NTN onsite 

measurements of pH and specific conductance were reliable for 

data users, the data obtained indicate lower onsite-data quality 

during 2003 than during 2001–02.

Sample-Handling Variability and Bias

Routine handling and processing procedures applied to 

wet-deposition samples have been identified as sources of contamination (Nilles and others, 1995; Gordon, 1999). Constituent loss from solution, due to adsorption to the collection bucket 

or other reactions, is possible. The effects of routine sample 
10 External Quality-Assurance Results for the National Atmospheric Deposition Program/National Trends Network, 2002–03

Level 1 Level 2 Level 3 Level 4

0

5

10

15

20

0

5

10

15

20

Followup results for intersite-comparison study 50

Followup results for intersite-comparison study 51

Number of site operators 

Participated in the followup study

Did not participate in the followup study

Successfully met the accuracy goals for 

 the followup study

EXPLANATION

Had mixed success meeting the accuracy

 goals for the followup study

Did not meet the accuracy goals for the 

 followup study

Level 1 followup :

(1) Letter discussing common sources of 

measurement errors

(2) Request for voluntary, additional 

measurement of the intersite- intersiteintersitecomparison 

-comparison sample 

sample

Level 2 followup :

(1) Letter discussing common sources of 

measurement errors

(2) Request that site operator reanalyze the 

remaining portion of the 

comparison sample

Level 3 followup :

(1) Letter discussing common sources of 

(2) Request that site operator reanalyze the 

remaining portion of the 

comparison sample

-comparison samples

(3) Request that site operator analyze one 

additional intersite

Level 4 followup :

(1) Letter discussing common sources of 

measurement errors

(2) Request that site operator reanalyze the 

remaining portion of the 

comparison sample

(3) Request that site operator analyze two 

additional intersite

:

:

intersite-

:

measurement errors

additional intersite

:

Combined number of site operators

participating in all levels: 48

Combined number of site 

operators participating in 

all levels: 55

Figure 5. Summary of followup study results obtained during 2003 for intersite-comparison program.

handling, sample shipping, and chemical analysis of wetdeposition samples on analyte variability and bias were evaluated using the blind-audit program during 2002 and the samplehandling evaluation (SHE) program during 2003. 

In the blind-audit and SHE programs, site operators processed 

and submitted a USGS-prepared, synthetic wetdeposition sample to CAL for analysis. The operators poured 

75 percent of the synthetic sample into a clean bucket obtained 

from the operators’ stock supplied by CAL. The normal 

processing and handling steps of a regular weekly sample were 

applied to this “bucket portion” of the blind-audit and SHE samples. The remaining 25 percent of the synthetic sample in the 

bottle was subjected to minimal handling. This minimally handled “bottle sample” for the blind-audit program was sent to 

CAL for analysis in a separate mailer, but SHE bottle samples 

were shipped with the bucket samples. All bottle samples were 

analyzed independently of the bucket samples. Chemical 
Sample-Handling Variability and Bias 11

41 42 43 44 45 46 47 48 49 50 51

Intersite-comparison study

41 42 43 44 45 46 47 48 49 50 51

Intersite-comparison study

No data 

available

for studies 

42 and 43

0

10

20

30

40

50

60

70

80

90

100

0

10

20

30

40

50

60

70

80

90

100

Successful measurements, in percent Successful measurements, in percent

Year study completed

1998 1999 1999 2000 2000 2001 2001 2002 2002 2003 2003

Year study completed

1998 1999 1999 2000 2000 2001 2001 2002 2002 2003 2003

pH pH and specific conductance 

 combined

Specific conductance

EXPLANATION

Figure 6. Percentage of successful pH and specific conductance measurements in intersite-comparison program 

during 1998–2003.

analysis results for the bucket portion were compared to the 

results for the bottle portion to determine if significant addition 

or loss of constituents had occurred from sample handling and 

shipping.

The operation of the blind-audit and SHE programs was 

nearly identical, with two differences. The most important difference was that the blind-audit program bucket samples were 

received by CAL as double-blind samples, meaning that QA 

samples were disguised as environmental samples, whereas 

SHE samples were not disguised (single-blind samples). The 

second difference is that the volumes of QA samples used for 

the SHE program were larger than those used for the blind-audit 

program.
12 External Quality-Assurance Results for the National Atmospheric Deposition Program/National Trends Network, 2002–03

The SHE program replaced the blind-audit program in 2003 

with the objective to limit data variability to obtain a better measurement of the effects of sample handling and shipping on 

sample integrity. Paired blind-audit samples were received by 

CAL in separate shipments, which commonly caused the samples to be analyzed on different days. However, the paired SHE 

samples were received in the same shipment, which allowed 

them to be analyzed closer together in time, thus limiting analytical variability. Figures 7 and 8 outline the components of the 

blind-audit program and SHE program, respectively. The solutions used in the blind-audit and SHE programs were intended 

to replicate the range of analyte concentrations typically measured in natural NADP/NTN precipitation samples. The median 

analyte concentrations for the solutions used in the blind-audit 

and SHE programs (other than ultrapure deionized water) were 

between the 25th and 75th percentiles of all natural wet-deposition samples collected at NADP/NTN sites. Many of the solutions used in the blind-audit and SHE programs also were used 

in the field-audit and interlaboratory-comparison programs. 

Descriptions of each solution are listed in table 3. The target 

values for these solutions are presented in table 4.

Three different sample volumes of the solution matrices 

were distributed to operators of selected NADP/NTN sites to 

assess volume-related effects on biases. For the 2002 blindaudit program, sample volumes of 250, 500, and 1,000 mL of 

USGS solutions were used. For the 2003 SHE program, sample 

volumes of 250, 1,000, and 2,000 mL of USGS solutions were 

used. The volumes selected for the SHE program represent the 

interquartile range of NADP/NTN sample volumes. Larger 

volumes contact more surface area of the bucket and also dilute 

contaminants more than small volume samples. All 

NADP/NTN samples are filtered by CAL, and large volume 

samples flush the filters more thoroughly than small volume 

samples. These effects can be evaluated using the three different sample volumes for the blind-audit and SHE samples. 

Additional information regarding the blind-audit program is 

available in previous reports (See and others, 1990; Gordon and 

others, 1997; Gordon, 1999). 

Blind-Audit Program Results

Twenty-five blind-audit samples were sent to the operators 

of selected NADP/NTN sites each quarter during 2002. Complete bucket and bottle analyses are available for 83 of the 

100 blind-audit samples sent to site operators. Partial analyses 

are available for an additional 16 samples. Site operators were 

provided detailed blind-audit sample-processing instructions. 

The handling and processing steps of a regular weekly precipitation sample were duplicated as closely as possible. After a site 

successfully participated in the blind-audit program, the site 

was not selected again for the blind-audit program until the 

operators of all other NADP/NTN sites had a chance to 

participate.

Assessment of Variability

Paired bucket-minus-bottle differences were calculated to 

evaluate variability in the blind-audit data. Before determining 

paired bucket-minus-bottle differences, the bucket and bottle 

values reported as less than CAL’s minimum detection limit 

(MDL) were set equal to one-half the MDL. There is evidence 

that this substitution method is not as defensible as estimation 

of the distribution of values less than the MDL (Helsel, 1990); 

nonetheless it is a convenient substitution for purposes of capturing reasonable estimates of bias and variability. 

Table 5 contains summary statistics for the paired bucketminus-bottle differences for the 2002 blind-audit program. The 

median paired bucket-minus-bottle concentration differences 

for calcium, magnesium, potassium, and ammonium were consistently at or less than the MDLs. The median paired bucketminus-bottle concentration differences for sodium, chloride, 

and nitrate were slightly larger than two times the MDLs. The 

median bucket-minus-bottle difference for sulfate was larger 

than three times the MDL. Boxplots in figure 9 illustrate the 

distributions of the paired differences for the 2002 blindaudit data.

The environmental importance of the bucket-minus-bottle 

concentration differences was evaluated by comparing the 

median bucket-minus-bottle differences for each constituent to 

the median concentrations for all NADP/NTN weekly precipitation samples collected during 2002 (Rothert, 2004) (table 5). 

The absolute values of the median paired bucket-minus-bottle 

differences for the blind-audit results were less than 10 percent 

of the median of the measured NADP/NTN constituent concentrations for calcium, ammonium, nitrate, sulfate, and specific 

conductance. However, the median paired differences for magnesium, sodium, potassium, and chloride concentrations were 

slightly more than 10 percent of the median NADP/NTN constituent concentrations. The absolute value of the median 

paired difference for hydrogen-ion concentration was 19 percent of the median NTN hydrogen ion concentration for 2002. 

Therefore, error attributed to sample handling and shipping by 

the blind-audit program during 2002 was estimated to be environmentally important to data users.

Relative and Absolute Percentage Differences

Relative and absolute percentage differences were calculated for all of the paired blind-audit samples. The upper quartile, lower quartile, and median relative and absolute percentage 

differences during 2002 are listed in table 6. Bucket-bottle data 

pairs were excluded for a given analyte if the target concentration was less than or equal to the MDL. Otherwise, the percentage differences would be inflated by the effect of large bucketbottle differences when the known concentration was less than 

or equal to the MDL (Nilles and others, 1995).

The data in table 6 indicate that the median absolute errors 

(MAEs) were less than 7 percent for all constituents. The 

MAEs were less than 3 percent for sodium, chloride, nitrate, 
Blind-Audit Program Results 13

Stock solutions prepared by commercial vendors

and dilluted by the U.S. Geological Survey (USGS) Deionized water samples prepared by USGS

Samples packaged for distribution to selected National

Atmospheric Deposition Program (NADP) sites by USGS

Operators of selected sites receive 250-, 500-, or 1,000-milliliter samples

75 percent of blind-audit sample is poured into a

clean bucket (bucket sample) for 24-hour residence

Analytical results for the bucket and bottle

samples compiled by USGS

Dummy sample identification corrected in

database by NADP Program Office

USGS reports results to NADP/Network

Operations Subcommittee

Bucket sample is poured from bucket into a

1-liter shipping bottle

Site operators process blind-audit sample

25 percent of the blind-audit sample remains in

original bottle (bottle sample)

All blind-audit samples shipped to Illinois State

Water Survey, Central Analytical Laboratory (CAL)

Site operators collect natural weekly precipitation samples

Natural precipitation samples shipped to CAL as dummy samples

Samples analyzed by CAL

NADP Program Office presents 

results in annual summary reports

Figure 7. Blind-audit program of U.S. Geological Survey.
14 External Quality-Assurance Results for the National Atmospheric Deposition Program/National Trends Network, 2002–03

Samples prepared by diluting stock solutions from a commercial 

vendor and packaged for distribution to selected sites by the

U.S. Geological Survey (USGS)

Operators of selected National Atmospheric Deposition Program

(NADP) sites receive 250-, 1,000-, or 2,000-milliliter samples

75 percent of SHE sample is poured into a

clean bucket (bucket sample) for 24-hour residence

Analytical results for bucket and bottle

samples compiled by USGS

Natural sample processed and analyzed by

CAL as a normal NADP sample

USGS reports results to NADP/Network

Operations Subcommittee

Bucket sample is poured from bucket into a

1-liter shipping bottle

Site operators process SHE sample

25 percent of the SHE sample remains in original

bottle (bottle sample)

Paired bucket and bottle samples shipped together

to the Illinois State Water Survey, Central

Analytical Laboratory (CAL)

Site operators collect natural weekly precipitation samples

Samples analyzed by CAL

NADP Program Office presents 

results in annual summary reports

Natural precipitation sample shipped to CAL as a normal 

National Trends Network sample

Figure 8. Sample-handling evaluation (SHE) program of U.S. Geological Survey.

and sulfate. The upper and lower quartiles for the relative differences were negative values for hydrogen ion and specific 

conductance, indicating loss of hydrogen ion resulting in lower 

specific conductance from contact of the sample with the 

sample bucket. These data indicate that a small amount of 

hydrogen ion is buffered by contact with the bucket. Therefore, 

there is a slight positive bias in NADP/NTN laboratory and 

onsite pH measurements due to contact of the wet deposition 

with the sample buckets.

During 2002, the median relative percentage differences 

for the blind-audit data, defined herein as the median percentage 

bias, were positive for all analytes except hydrogen ion and specific conductance (table 6). Negative bias was indicated for 

hydrogen-ion concentration and specific conductance. A Wilcoxon signed-rank test was used to test for bias within the blindaudit samples for 2002. The null hypothesis for the test was: 

"The median of the blind-audit bucket-minus-bottle paired differences is zero." The Wilcoxon signed-rank test results 
Sample-Handling Evaluation (SHE) Program Results 15

Table 3. Solutions used in 2002–03 blind-audit, sample-handling evaluation, field-audit, and interlaboratory-comparison programs.

[DI, deionized; USGS, U.S. Geological Survey; MΩ, megohm; HPS, High Purity Standards, Charleston, South Carolina; stock solutions, concentrated solutions 

provided by vendor and diluted to specified concentrations by U.S. Geological Survey (USGS); CAL, Illinois State Water Survey, Central Analytical Laboratory, 

Champaign, Illinois; NADP/NTN, National Atmospheric Deposition Program/National Trends Network]

Solution Preparation Remarks

Ultrapure DI1, 2, 3, 4

1Solution used for the blind-audit program.

2Solution used for the interlaboratory-comparison program.

3Solution used for the sample-handling evaluation program.

4Solution used for the field-audit program.

USGS Deionized water with a measured resistivity greater 

than 16.7 MΩ.

SP11, 2, 3

SP21, 2, 3, 4

SP34

SP51, 2, 3

SP971, 2, 3

SP981, 3

SP98c1, 2, 3

HPS provides concentrated, stock solutions to USGS.

USGS dilutes and then bottles the diluted solutions.

Concentrations of stock solutions certified by HPS 

laboratory analysis against an independent source 

traceable to the National Institute of Standards and 

Technology.

CALNAT2 CAL blends excess, natural NADP/NTN precipitation samples 

and ships them to USGS. USGS prepares the samples for 

analysis by participating laboratories.

Most probable values for samples are the median 

results obtained from participating laboratories.

identified statistically significant (α=0.05) differences for 

hydrogen-ion concentration. No other statistically significant 

bias was identified for the other constituents. 

The median difference between bucket and bottle pairs for 

hydrogen ion during 2002 was -2.10 microequivalents per liter 

(μeq/L) (table 5). This bias was determined to be statistically 

significant at the 0.05 significance level by the Wilcoxon 

signed-rank test regardless of whether samples were qualified 

as contaminated (denoted by a "C" code in the NADP/NTN 

database) or not. The negative bias for hydrogen ion also was 

identified whether the buckets were dry or contained residual 

rinse water at the time that the blind-audit solution was added to 

the bucket.

Sample-Handling Evaluation (SHE) Program 

Results

Twenty-five SHE samples were sent to the operators of 

selected NADP/NTN sites each quarter during 2003. Complete 

bucket and bottle analyses were available for 80 of 100 SHE 

samples sent to the site operators. Partial analyses were available for an additional 16 SHE samples. SHE samples were processed in the same way as the blind-audit program samples with 

the exception that the processed bucket and bottle portions of 

SHE samples were shipped together to CAL for analysis, and 

they were labeled as QA samples (single blind samples). 

Latysh and Wetherbee (2005) provide a detailed description of 

SHE program protocols.

Assessment of Variability

Paired bucket-minus-bottle differences were calculated to 

evaluate variability in SHE data. Before determining paired 

bucket-minus-bottle differences, the bucket and bottle values 

reported as less than the MDL were set equal to one-half the 

MDL. As previously mentioned, this substitution method was 

convenient for the purposes of capturing reasonable estimates 

of bias and variability.

Table 7 contains summary statistics for the paired bucketminus-bottle differences for the 2003 SHE program. The 

median paired bucket-minus-bottle concentration differences 

for the SHE program were less than CAL’s MDLs for all 

constituents except sodium and sulfate. The absolute values of 

the median paired differences for SHE results were less than 

10 percent of the median measured NADP/NTN constituent 

concentrations for all constituents except for hydrogen-ion concentration, which was 10.5 percent of the median NADP/NTN 

hydrogen-ion concentration. 

Relative and Absolute Percentage Differences

Relative and absolute percentage differences were calculated for all of the SHE bucket-minus-bottle paired differences 

during 2003. The upper quartile, the lower quartile, and median 

relative and absolute percentage differences for SHE data 

obtained during 2003 are listed in table 8. Bucket-bottle data 

pairs were excluded for a given analyte if the target concentration was less than or equal to the MDL to control the effect of 

large bucket-bottle differences (Nilles and others, 1995).
Table 4. Target values for solutions used in 2002–03 U.S. Geological Survey blind-audit, sample-handling evaluation, field-audit, and interlaboratory-c[Target values are the theoretical concentrations that are based on dilution of stock solutions with certified concentrations; Ultrapure DI, deionized water with a resistivity great

assumed to have all constituent concentrations less than the minimum detection limit; pH, in standard units; specific conductance, in microsiemens per centimeter at 25 degrees 

value less than minimum detection limit; Ca2+, calcium; Mg2+, magnesium; Na+, sodium; K+, potassium; NH4+, ammonium; Cl-, chloride; NO3-, nitrate; SO42-, sulfate; significa

in laboratory precision; bold face indicates value was obtained as the median of all the field-audit, blind-audit, and interlaboratory-comparison samples]

Solution

Ca2+ Mg2+ Na+ K+ NH4+ Cl- NO3- SO42- 

1pH not certified by the National Institute of Standards and Technology.2At 25 degrees Celsius and 1 atmosphere pressure (Dean, 1979; Hem, 1985).

(milligrams per liter)

Ultrapure DI3, 4, 5, 6

3Solution used for the blind-audit program.4Solution used for the interlaboratory-comparison program.5Solution used for the sample-handling evaluation.6Solution used for the field-audit program.

<mdl <mdl <mdl <mdl <mdl <mdl <mdl <mdl 

SP13, 4, 5 0.460 0.092 0.420 0.076 0.680 0.590 2.10 3.850 SP23, 4, 5, 6 .460 .070 .360 .060 .560 .450 3.00 2.334 SP36 .159 .049 .111 .023 .140 .170 1.08 .960 SP53, 4, 5 .575 .168 .454 .083 .710 .720 2.55 4.510 SP973, 4, 5 .130 .019 .024 .017 .290 .054 1.18 1.140 SP983 .013 .024 .208 .056 .120 .230 .570 2.410 SP98c3, 4, 5 .016 .038 .208 .061 .120 .234 .570 2.428 
Table 5. Selected statistics for paired bucket-sample minus bottle-sample concentration differences in blind-audit program during 2002.[All units in milligrams per liter except hydrogen ion, in microequivalents per liter, and specific conductance, in microsiemens per centimeter at 25 degrees Celsius; N, number o

in the data distribution; Q3, the upper quartile in the data distribution; interquartile range, the difference between the upper and lower quartiles in the distribution (Q3 minus Q1); 

Analytical Laboratory; MDL, minimum detection limit; Median NADP/NTN concentration, median value of all National Atmospheric Deposition Program/National Trends N

concentrations for 2002 (Rothert, 2004)]

Analyte

Bucket-minus-bottle paired differences

Da

N Minimum Median

Quartiles

Maximum Interquartile range

Q1 Q3 CAL MDL 

Calcium 83 -0.058 0.003 -0.008 0.013 0.065 0.021 0.009 Magnesium 83 -.018 .003 .001 .007 .025 .006 .003 Sodium 83 -.097 .007 0 .012 .067 .012 .003 Potassium 84 -.027 .002 -.001 .005 .067 .006 .003 Ammonium 83 -.170 .020 0 .040 .090 .040 .020 Chloride 85 -.041 .011 .005 .021 .068 .016 .005 Nitrate 83 -.031 .024 .012 .048 .207 .036 .010 Sulfate 83 -.120 .037 .014 .086 .300 .072 .010 Hydrogen ion 99 -9.40 -2.10 -4.21 -.672 6.50 3.54 na Specific conductance 99 -5.1 -.50 -1.5 0 1.9 1.5 .05 
18 External Quality-Assurance Results for the National Atmospheric Deposition Program/National Trends Network, 2002–03

Largest value less than or 

 equal to the 75th percentile

 plus 1.5 times interquartile 

 range

Upper quartile

Median

Lower quartile

Smallest value less than or

 equal to the 25th percentile

 minus 1.5 times interquartile

 range

Data outside ±1.5 times the

 interquartile range.

EXPLANATION

(for all boxplots) 

-0.2

10

Hydrogen ion Specific

conductance

5

0

-5

-10

2.5

0

-2.5

-5.0

-7.5

Calcium

Magnesium

Sodium

Potassium

Ammonium

Chloride

Nitrate

Sulfate

-0.1

0

Bucket-minus-bottle differences, in milligrams per liter Bucket-minus-bottle differences,

in microequivalents per liter

Bucket-minus-bottle differences,

in microsiemens per centimeter at 25 degrees Celsius

0.1

0.2

0.3

Figure 9. Paired bucket-sample minus bottle-sample measurement differences for blind-audit program during 2002.

The data in table 8 indicate that MAEs for the 2003 SHE 

program were less than or equal to 3 percent for all analytes 

except ammonium and hydrogen ion. The relative bucketminus-bottle differences expressed as percentages of the target 

concentrations were positive for most of the measured constituents except for hydrogen ion and specific conductance (table 8). 

Therefore, positive bias was indicated for all constituents 

except hydrogen-ion concentration and specific conductance. 

The negative bias for hydrogen ion and specific conductance 

indicate loss of hydrogen ion and decreased specific conductance from contact of the NADP/NTN samples with the bucket. 

Therefore, SHE results are similar to the blind-audit results, 

which indicate a slight positive bias in NADP/NTN pH 
Sample-Handling Evaluation (SHE) Program Results 19

Table 6. Relative and absolute bucket-minus-bottle differences calculated as a percentage of target concentration or value for each 

analyte during 2002 for blind-audit program.

Analyte

Relative bucket-minus-bottle differences

expressed as a percentage of corresponding

target bottle concentration 

(selected data pairs only)

Absolute bucket-minus-bottle differences

expressed as a percentage of corresponding

target bottle concentration 

(selected data pairs only)

Percentiles Percentiles

25th Median 75th 25th Median 75th

Calcium -1.8 1.1 4.0 1.4 3.7 8.0

Magnesium 1.4 4.3 8.7 2.4 4.8 8.9

Sodium 0 2.0 4.0 .96 2.6 4.1

Potassium -1.7 3.5 8.3 3.3 5.8 12

Ammonium 0 4.2 7.1 1.8 5.4 10

Chloride 1.4 2.4 4.2 1.8 2.4 4.3

Nitrate .43 1.3 2.4 .63 1.3 2.4

Sulfate .22 1.5 2.3 .86 1.5 2.3

Hydrogen ion -10 -6.4 -2.3 4.3 6.5 10

Specific conductance -7.5 -2.6 -.29 1.5 3.3 7.8

measurement due to contact of the wet deposition with the 

sample buckets.

A Wilcoxon signed-rank test was used to test for bias in the 

SHE data for 2003. The null hypothesis for the test was: "The 

median of the SHE bucket-minus-bottle paired differences is 

zero." The Wilcoxon signed-rank test results identified no 

statistically significant (α=0.05) bias for any SHE constituents 

in 2003. No statistically significant bias was identified by the 

Wilcoxon signed-rank test regardless of whether samples were 

qualified as contaminated (denoted by a "C" code in the 

NADP/NTN database) or not, nor whether the buckets were dry 

or contained residual rinse water at the time that the SHE solution was added to the bucket.

Comparison of Blind-Audit and SHE Program 

Variability and Bias Estimates

Boxplots in figure 10 graphically depict the paired bucketminus-bottle concentration differences for all the major ions for 

the 2002 blind-audit program and the 2003 SHE program. Boxplots in figure 11 depict the paired bucket-minus-bottle 

concentration differences for pH and specific conductance for 

the 2002 blind-audit program and the 2003 SHE program. The 

boxplots show that there generally is less variability in the SHE 

data than in the blind-audit data. A Kruskal-Wallis analysis of 

variance test was used to test the null hypothesis, "There is no 

difference between the bucket-minus-bottle differences for the 

blind-audit and SHE programs." The results indicate that the 

blind-audit and SHE bucket-minus-bottle differences are significantly (α=0.05) different for magnesium, chloride, nitrate, and 

sulfate. Less variability in the SHE data was suspected to be 

due to submittal of the SHE bucket and bottle samples to CAL 

together, which increased the likelihood that samples were analyzed together; thus limiting analytical variability. The blindaudit samples typically arrived at CAL on different days. Consequently, the SHE data were regarded as more 

representative of the variability and bias introduced by sample 

handling and shipping than the blind-audit data.

The blind-audit and SHE data were evaluated for constituent concentration effects on data variability. The paired bucketminus-bottle differences were grouped by target concentrations, 

and a Kruskal-Wallis analysis of variance test was used to test 

the null hypothesis, "There is no relation between constituent 

concentration and the variability of the paired differences." For 

the 2002 blind-audit data, a significant (α=0.05) relation 

between the paired differences and concentration was found for 

magnesium, chloride, nitrate, and sulfate. For the 2003 SHE 

data, a significant (α=0.05) relation between the paired differences and concentration was found for all constituents except 

calcium. For both the blind-audit and SHE data, variability in 

the paired bucket-minus-bottle differences increased with 

increasing concentration.

The blind-audit and SHE data were evaluated for sample 

volume effects on data variability. The paired bucket-minusbottle differences were grouped by target concentrations, and a 

Kruskal-Wallis analysis of variance test was used to test the 

null hypothesis, "There is no relation between sample volume 

and the variability of the paired differences." A significant 

(α=0.05) relation between sample volume and the variability of 

the paired differences was found for magnesium, nitrate, and 

sulfate in the 2002 blind-audit data. A significant (α=0.05) 
Table 7. Selected statistics for paired bucket-sample minus bottle-sample concentration differences for sample-handling evaluation program during [All units in milligrams per liter except hydrogen ion, in microequivalents per liter, and specific conductance, in microsiemens per centimeter at 25 degrees Celsius; N, number o

the data distribution; Q3, 75th percentile in data distribution; interquartile range, difference between upper and lower quartiles in distribution (Q3 minus Q1); na, not applicableLaboratory; MDL, minimum detection limit; median NADP/NTN concentration, median value of all National Atmospheric Deposition Program/National Trends Network (NA

concentrations for 2002 (Rothert, 2004)]

Analyte

Bucket-minus-bottle paired differences D

N Minimum Median

Quartiles

Maximum Interquartile range CAL MDL 

Q1 Q3

Calcium 82 -0.040 0.002 -0.009 0.011 0.113 0.020 0.009 Magnesium 81 -.032 .002 0 .004 .012 .004 .003 Sodium 82 -.009 .004 .001 .009 .328 .008 .003 Potassium 82 -.016 .001 -.001 .003 .065 .004 .003 Ammonium 81 -.130 .010 0 .030 .110 .030 .020 Chloride 80 -.046 .004 -.001 .010 .119 .011 .005 Nitrate 80 -.098 .009 -.002 .034 .124 .036 .010 Sulfate 80 -.093 .013 -.006 .037 .169 .043 .010 Hydrogen ion 96 -8.19 -1.15 -2.95 0 3.44 2.95 na Specific conductance 96 -5.8 -.5 -.9 -.1 1.4 .8 .05 
Field-Audit Program 21

Table 8. Relative and absolute bucket-minus-bottle differences calculated as a percentage of target concentration or value for each 

analyte during 2003 for sample-handling evaluation program.

Analyte

Relative bucket-minus-bottle differences expressed as a 

percentage of corresponding target bottle concentration 

or value

Absolute bucket-minus-bottle differences expressed as a 

percentage of corresponding target bottle concentration 

or value

Percentiles Percentiles

25th 50th 75th 25th 50th 75th

Calcium -1.7 0.52 3.8 1.3 2.8 6.3

Magnesium 0 2.2 5.7 1.2 3.0 7.1

Sodium .44 1.4 3.3 .88 1.8 3.6

Potassium -1.2 1.3 4.0 1.2 2.6 6.0

Ammonium 0 2.9 7.1 1.4 3.4 8.9

Chloride -.28 1.1 3.0 .68 1.2 3.7

Nitrate -.12 .43 1.6 .38 .76 1.8

Sulfate -.24 .38 1.3 .31 .70 1.4

Hydrogen ion -8.8 -5.2 -1.6 2.0 6.0 9.0

Specific conductance -4.6 -2.5 -.91 1.2 2.6 4.9

relation between the variability of the paired differences and 

sample volume was found for magnesium, potassium, ammonium, chloride, nitrate, hydrogen ion, and specific conductance 

in the 2003 SHE data.

Boxplots of the paired differences grouped by sample volume for hydrogen ion and specific conductance are shown in 

figures 12 and 13, respectively. The boxplots in figures 12 and 

13 show that similar results were obtained for the 2002 blindaudit data and the 2003 SHE data. Negative bias in hydrogen 

ion concentration paired differences and specific conductance 

paired differences were indicated for both programs (figs. 12 

and 13). Therefore, the blind-audit and SHE data infer that 

reported NADP/NTN hydrogen-ion concentrations and specific 

conductance are slightly underestimated due to contact of the 

samples with the buckets and subsequent sample handling. The 

median paired hydrogen-ion concentration differences are 

increasingly negative with increasing sample volume for the 

blind-audit data. These data imply that more acidity is neutralized when more of the sample contacts a larger surface area of 

the bucket. However, this result was not observed for the SHE 

data. 

The variability in the bucket-minus-bottle hydrogen-ion 

concentration differences increase with increasing sample volume for both the blind-audit and SHE data. Therefore, larger 

volume NADP/NTN samples inherently are prone to more variability from sample handling than smaller volume samples. 

Nonetheless, the SHE results indicate that the effects of sample 

handling and shipping do not appear to be environmentally significant and do not affect the analysis and interpretation of 

NADP/NTN data.

Field-Audit Program

The field-audit program is intended to help quantify chemical changes to NADP/NTN precipitation samples resulting 

from onsite exposure of the sample-collection apparatus. Estimates of variability and bias from the field-audit program data 

are assumed to represent the combined effects of onsite 

exposure of the sample plus sample handling and shipping. 

Every Tuesday morning at all sites across the NADP/NTN, 

the sample from the previous week is removed, and a new sample-collection bucket is installed in the Aerochem Metrics wetdeposition collector. The sample-collection bucket is covered 

with a foam pad attached to a rigid aluminum lid. The site operators’ standard operating procedures (SOPs) specify monthly 

cleaning of the foam pad and lids and lid replacement every 

12 months (Dossett and Bowersox, 1999). Nonetheless, when 

precipitation is not occurring, small amounts of windblown 

contamination can enter the bucket between the lid and the 

bucket. For example, small amounts of dust can enter the sample-collection bucket, particularly when the foam lid pad has 

started to wear and the seal between the bucket and lid is compromised. Small amounts of dust or debris can fall into the 

bucket when the lid is in motion. The net effect of these factors 

can change the chemistry of the precipitation sample. 

Like the blind-audit and SHE programs, the field-audit 

program uses a paired sample design to detect statistically significant differences in analyte concentrations between solutions 

that come in contact with collector buckets and solutions that 

are not exposed to collector buckets. But unlike the blind-audit 

and SHE programs, the field-audit program measures the added 

effects of onsite exposure of the buckets. Although the blindaudit and SHE programs used clean buckets from the site operators’ stock, the field-audit program uses buckets that have 
22 External Quality-Assurance Results for the National Atmospheric Deposition Program/National Trends Network, 2002–03

2002 Blind-audit program 

2003 SHE program 

-0.2

-0.1

0

Bucket-minus-bottle differences, in milligrams per liter

0.1

0.2

0.3

-0.2

-0.1

0

0.1

0.2

0.3

Calcium

Magnesium

Sodium

Potassium

Ammonium

Chloride

Nitrate

Sulfate

Figure 10. Comparison of distributions of bucket-minus-bottle concentration differences for 2002 blind-audit 

program and 2003 sample-handling evaluation (SHE) program (see figure 9 for explanation of boxplots).
Field-Audit Program 23

been installed in wet-deposition collectors for 1 week without 

precipitation. Field-audit samples were distributed to 

25 NADP/NTN sites quarterly. Tables 3 and 4 list the solutions 

used for the field-audit program. Figure 14 outlines the components of the field-audit program. NADP/NTN site operators 

were furnished special instructions to process the field-audit 

SPC samples. A number of prerequisite conditions must be met 

before proceeding with field-audit sample processing. In the 

field-audit program, the site operator is instructed to process 

and submit a QC sample after a standard 7-day, Tuesday-toTuesday sampling period when no precipitation occurred. The 

site operator is instructed to check the rain-gage chart to make 

sure the Aerochem Metrics collector lid did not open and 

uncover the wet-side bucket during the sampling period (Dossett and Bowersox, 1999). 

If all of the requirements are met for processing a fieldaudit sample, the operator pours approximately 75 percent of 

the field-audit solution, supplied by USGS, into the samplecollection bucket. The operator swirls the solution in the bucket 

and seals the bucket with its lid. The solution is left in the sealed 

bucket for at least 24 hours, and then the solution is transfered 

to a clean 1-L sample bottle for shipment to CAL. The 25-percent portion of the sample remaining in the original sample bottle and the sample that resided in the bucket are both shipped to 

CAL for separate analysis.

Three different sample volumes of the solution matrices 

were distributed to operators of selected NADP/NTN sites 

(Berthouex and Brown, 1995) to investigate a possible relation 

between sample volume collected weekly at NADP/NTN sites 

and the amount of contamination introduced through onsite 

exposure and shipping and handling procedures. The program 

design used sample volumes of 250, 500, and 1,000 mL during 

2002. The sample volumes were changed for 2003 to 250, 

1,000, and 2,000 mL to better represent the quartile values for 

NADP/NTN sample volumes. Three different solution matrices were used, including ultrapure deionized water, solution 

SP2, and solution SP3 (table 4).

Assessment of Field-Audit Data

Samples submitted as part of the field-audit program are 

referred to as field-audit samples. Site operators had 1 year 

from the time of sample receipt to process their field-audit samples. For example, an operator receiving a sample in the fourth 

quarter had until the end of the fourth quarter of the following 

year to submit a field-audit sample. If the site was located in an 

area with a wet climate and extremely high humidity, the probability of a week with no lid openings was very low. Therefore, 

some of the field-audit samples that were shipped to wet or 

humid regions were not processed because some of the samplers in these regions recorded precipitation every week during 

the field-audit sample-processing period.

Of the 100 field-audit samples mailed to site operators in 

2002, 58 were submitted for analysis by the end of the third 

quarter 2003. Of the 100 field-audit samples mailed to site operators in 2003, 58 were submitted for analysis by the second 

quarter of 2004. Overall, there were 116 complete sample pairs 

for the study period.

Prior to processing the field-audit sample, the site operators inspected the wet-side bucket to ensure that it was at least 

as dry as it was when it was installed the previous week; if there 

were a few drops of rinse water in the bucket when it was 

installed, it is conceivable that the water was still present. A 

bucket was considered "wet" if there was rinse water in the 

bucket when the bucket was installed and if the rinse water 

remained at the end of the week during which there were no lid 

10

5

0

-5

-10

2.5

0

-2.5

-5.0

-7.5

Bucket-minus-bottle differences, in microequivalents per liter

10

Hydrogen ion Specific

conductance

5

0

-5

-10

2.5

0

-2.5

-5.0

-7.5

Bucket-minus-bottle differences, in microsiemens per centimeter at 25 degrees Celsius

2002 Blindaudit program 

2003 SHE

program 

Figure 11. Comparison of distribution of bucket-minusbottle differences for hydrogen ion concentration and 

specific conductance for 2002 blind-audit program and 

2003 sample-handling evaluation (SHE) program (see 

figure 9 for explanation of boxplots).
24 External Quality-Assurance Results for the National Atmospheric Deposition Program/National Trends Network, 2002–03 Bucket-minus-bottle differences, in microequivalents per lietr

5.0

2.5

0

-2.5

-5.0

5.0

2.5

0

-2.5

-5.0

250 1,000

Sample volume, in milliliters

2,000

2002 Blind-audit program 

Not significantly different by volume

at α = 0.05 significance level 

Significantly different by volume

at α = 0.05 significance level 

2003 SHE program 

Figure 12. Relation of bucket-minus-bottle hydrogen-ion concentration differences and sample volume for 2002 

blind-audit data and 2003 sample-handling evaluation (SHE) data (see figure 9 for explanation of boxplots).

openings. A bucket was considered "dry" if no rinse water was 

present. Regardless of the final reported sample chemistry, 

bucket and bottle field-audit samples containing extrinsic material were assigned a "C" code by CAL to indicate samples with 

visible contamination, such as detritus, dust, or other materials. 

Eleven of the 116 field-audit samples were assigned "C" 

codes during the study period. Because field-audit samples can 

be poured either into a dry bucket or a bucket with rinse water, 

the data initially were separated depending on whether the sample data were coded as "wet" or "dry." Of the 116 samples analyzed, 14 were processed with rinse water present as "wet" 

buckets, and 102 were processed as "dry" buckets. 

Before determining paired bucket-minus-bottle differences for the field-audit program, bucket and bottle values 

reported as less than the MDLwere set equal to one-half
Field-Audit Program 25

Bucket-minus-bottle differences, in microsiemens per centimeter at 25 degrees Celsius

5.0

2.5

0

-2.5

-7.5

-5.0

5.0

2.5

0

-2.5

-7.5

-5.0

250 1,000

Sample volume, in milliliters

2,000

2002 Blind-audit program 

Not significantly different by volume

at α = 0.05 significance level 

Significantly different by volume

at α = 0.05 significance level 

2003 SHE program 

Figure 13. Relation of paired bucket-minus-bottle specific conductance differences and sample volume for 2002 

blind-audit data and 2003 sample-handling evaluation (SHE) data (see figure 9 for explanation of boxplots).
26 External Quality-Assurance Results for the National Atmospheric Deposition Program/National Trends Network, 2002–03

Samples prepared and packaged for distribution to operators of selected National

Atmospheric Deposition Program/National Trends Network (NADP/NTN) sites

by U.S. Geological Survey (USGS)

75 percent of the field-audit sample was poured into the samplecollection bucket that had been installed at the site the previous week 

Field-audit sample was poured from bucket into a 1-liter shipping

bottle (bucket sample)

Site operators process

field-audit sample

Data presented in reports and

publications

Operators of selected sites received 250-, 500-, or 1,000-milliliter samples in 2002

Operators of selected sites received 250-, 1,000-, or 2,000-milliliter samples in 2003

Conditions for field-audit sample submission are met; dry week with no

collector openings

25 percent of the field-audit sample remained in original bottle

(bottle sample)

All field-audit samples shipped to Illinois State Water Survey, Central Analytical

Laboratory (CAL)

USGS presents results to the NADP/

Network Operations Subcommittee

Analytical results for bucket and bottle samples compiled by USGS

Samples analyzed by CAL

Figure 14. Field-audit program of 

U.S. Geological Survey.

the MDL for computation of statistics. Only minor differences 

resulted from how the less than MDL values were treated, such 

as substituting values reported less than MDLs with zero or with 

the MDLs themselves. Therefore, all of the values less than the 

MDL were set equal to one-half the MDL, which was a convenient substitution for purposes of capturing reasonable estimates of bias and variability.

Assessment of Variability and Bias

The Wilcoxon signed-rank test was used to compare the 

ion concentrations and specific conductance of the two groups 

of field-audit samples (C-coded samples and samples without C 

codes). For all constituents, no statistically significant differences were found at the α=0.05 level during the study period for 

any of the analytes. Therefore, data from the 11 field-audit 

samples assigned C codes during the study period were 

included in the overall statistical analysis of field-audit samples. 

The Wilcoxon signed-rank test also was used to evaluate if 

there were statistically significant differences in the field-audit 

results on the basis of the presence or absence of rinse water in 

the sample-collection buckets. Unlike previous years, a statistically significant (α=0.05) difference was indicated between 

the paired bucket-minus-bottle analyses for hydrogen ion in 
Field-Audit Program 27

2002 for the wet-coded samples, but not in 2003, nor for any 

other analyte during the study period. 

A statistical summary of paired bucket-minus-bottle 

results for the "wet" and "dry" field-audit samples is shown in 

table 9. In most instances, the median values for the differences 

between bucket and bottle samples were similar for the "wet"-

coded samples where rinse water was present and for the "dry"-

coded samples where rinse water was absent. The differences 

between the two groups was small, and the interquartile ranges 

and median values also were similar for the "wet" and "dry" 

sample groups. The 2002–03 median bucket-minus-bottle 

paired differences obtained for the “dry”-coded field-audit data 

(table 9) were less than 10 percent of the median concentrations 

determined for all NADP/NTN concentration measurements 

made during 2002 (table 5).

The interquartile ranges of the field-audit hydrogen ion 

concentration differences were between -1.36 and -0.18 μeq/L 

for the wet-coded samples and between -1.30 and 0 μeq/L for 

dry-coded samples (table 9). The interquartile ranges for hydrogen ion concentration differences for wet and dry samples were 

slightly larger for the study period than for 2000–2001 

(Wetherbee and others, 2004). The field-audit program data for 

hydrogen-ion concentrations for the study period indicated that 

exposure of NADP/NTN wet-deposition samples to onsite conditions generally tended to neutralize the acidity of the samples 

but typically by less than 1.0 μeq/L as indicated by the median 

bucket-minus-bottle differences in table 9.

Boxplots graphically depict the paired bucket-minusbottle concentration differences for all the major ions (fig. 15) 

and for hydrogen ion and specific conductance (fig. 16) for the 

field-audit program during 2002–03. Figure 15 shows that the 

median bucket-minus-bottle differences for all major-ion concentrations were greater than zero and near zero, indicating that 

onsite exposure of the samples tended to slightly increase the 

concentration of most of the analytes. The estimated increase 

in major-ion concentration was typically less than 10 μg/L for 

all analytes. The median differences were less than 10 percent 

of NADP/NTN median values for 2002 data.

Results of a Kruskal-Wallis analysis of variance test indicated a statistically significant (α=0.05) relation between the 

solution target values and the magnitude of paired field-audit 

bucket-minus-bottle differences for nitrate, sulfate, and specific 

conductance during 2002 and for magnesium, sodium, nitrate, 

sulfate, and specific conductance during 2003. The KruskalWallis analysis of variance results combined with the boxplots 

of the paired differences in figures 15 and 16 indicate that onsite 

exposure, sample handling, and shipping caused less than 

a +20-μg/L change to nitrate and sulfate concentrations and a 

less than -1-μS/cm change to specific conductance during the 

study period.

Low-Level Contamination Detection in Ultrapure 

Deionized-Water Samples

The number of ultrapure deionized-water (DI) samples 

processed and analyzed as part of the field-audit program was 

24 in 2002 and 18 in 2003 (table 10). The most common analyte 

detected greater than the MDL during 2002 in DI samples was 

chloride, which was detected in 75 percent of the onsiteexposed bucket samples and in 13 percent of the minimally handled bottle samples. During 2003, the most common analyte 

detected greater than the MDL in DI samples was ammonium, 

which was detected in 44 percent of the onsite-exposed bucket 

samples but not in the minimally handled bottle samples 

(table 10). Calcium was the second-most detected constituent 

Table 9. Selected statistics for paired bucket-sample minus bottle-sample concentration differences for field-audit program during

2002–03 for wet- and dry-coded samples.

[All units in milligrams per liter except hydrogen ion, in microequivalents per liter, and specific conductance, in microsiemens per centimeter at 25 degrees 

Celsius; Q1, the lower quartile in the data distribution; Q3, the upper quartile in the data distribution]

Analyte

Wet samples Dry samples

Median

Quartiles

Median

Quartiles

Q1 Q3 Q1 Q3

Calcium 0.010 0 0.018 0.008 0.003 0.015

Magnesium 0 -.001 .001 .001 0 .003

Sodium .003 0 .007 .002 0 .005

Potassium 0 -.001 .004 .001 0 .004

Ammonium .005 0 .010 0 0 .010

Chloride .008 .001 .016 .007 0 .015

Nitrate .002 0 .026 .010 0 .032

Sulfate .012 0 .032 0 -.001 .012

Hydrogen ion -.473 -1.36 -.180 -.372 -1.30 0

Specific conductance 0 -.4 .3 -.1 -.8 .2
28 External Quality-Assurance Results for the National Atmospheric Deposition Program/National Trends Network, 2002–03

2002 Field-audit program 

2003 Field-audit program 

-0.2

-0.1

0

Bucket-minus-bottle differences, in milligrams per liter

0.1

0.2

-0.3

-0.2

-0.1

0

0.1

0.2

-0.3

Number of samples = 58

Number of samples = 58

Calcium

Magnesium

Sodium

Potassium

Ammonium

Chloride

Nitrate

Sulfate

Figure 15. Bucket-minus-bottle concentration differences for 2002–03 field-audit major ions (see figure 9 for 

explanation of boxplots).

in the onsite-exposed bucket samples in 2003, occurring in 

39 percent of the samples. 

The number of detections of each analyte in the minimally 

handled bottle samples during 2002 was similar to the number 

of detections in the bottle samples during 2003, but slightly less 

contamination was indicated during 2003 than 2002 except for 

ammonium. There were more detections of all major-ion constituents in the onsite-exposed bucket samples than in the minimally handled bottle samples during the study period, which 

indicates that differences in the number of detections in the 

onsite-exposed bucket samples collected during 2002 and 2003 
Field-Audit Program 29

were not due to laboratory analysis but rather to onsite conditions and sample handling.

Relative and Absolute Percentage Differences

During the study period, the median percentage bias, estimated by the relative bucket-minus-bottle paired differences for 

all analytes, was within a range of -3.7 to 3.1 percent (table 11). 

MAEs, estimated by the absolute values of the bucket-minusbottle differences, were smaller for the field-audit data obtained 

during 2002–03 than during 2000–2001 (Wetherbee and others, 

2004) for all analytes except calcium, ammonium, and specific 

conductance. The analyte with the largest MAE for the fieldaudit program during the study period was ammonium 

(5.4 percent) (table 11). 

As in previous years, a minor positive bias was measured 

for the bucket samples for all analytes except for hydrogen ion 

and specific conductance during the study period. The negatively biased results for conductivity appear counterintuitive 

because addition of the major ions should increase the specific 

conductance of the solution. However, hydrogen-ion activity 

can account for a substantial portion of specific conductance, 

especially in low ionic strength solutions.

Relation of Sample Volume and Field-Audit Data 

Variability and Bias

To determine if there was a statistically significant relation 

between paired field-audit differences and sample volume, a 

Kruskal-Wallis analysis of variance test was performed. The 

null hypothesis, "There is no difference in the variability of the 

paired bucket-minus-bottle concentration differences between 

samples pooled by sample volume for the field-audit data," was 

tested using the Kruskal-Wallis analysis of variance. The analysis of variance results for the study period indicate a significant 

(α=0.05) relation between paired field-audit sample 

concentration or value differences and sample volume for magnesium, nitrate, and sulfate during 2002 and for calcium, magnesium, sodium, chloride, nitrate, sulfate, and specific conductance during 2003. When paired differences for major ions 

were converted to units of mass by multiplying the concentration by the sample volume, the outcome of the Kruskal-Wallis 

analysis of variance indicated a significant (α=0.05) difference 

only for nitrate during 2003.

The results obtained for the 2002 data were similar to the 

results obtained for the field-audit program from 1997 to 2001 

(Gordon and others, 2003; Wetherbee and others, 2004). However, during 2003, a significant (α=0.05) relation between the 

magnitude of the paired differences and sample volume was 

observed for calcium and sodium for the first time in the 7-year 

history of the field-audit program. The sample-volume range 

increased to include 2,000-mL samples in 2003. The 2,000-mL 

sample volume contacted a larger surface area of the bucket 

than the smaller sample volumes. Therefore, presumably more 

contaminants could be incorporated into the 2,000-mL sample. 

Boxplots of the paired field-audit bucket-minus-bottle differences for all analytes indicate that the data for the largest sample 

volumes (1,000 mL in 2002 and 2,000 mL in 2003) generally 

had the greatest variability, except for specific conductance 

(figs. 17, 18, and 19). Because median sample volumes are site 

specific due to climatic differences throughout NTN (Nilles and 

others, 1993; Gordon, 1999; Wetherbee and others, 2005), it 

is reasonable to expect that sample-volume differences 

could affect the spatial distribution in data variability 

throughout NTN.

In general, the boxplots of the paired bucket-minus-bottle 

differences coupled with the results of the Kruskal-Wallis analysis of variance show that minor amounts of contaminant 

10

5

0

-5

-10

5.0

2.5

0

-2.5

-5.0

5.0

2.5

0

-2.5

-5.0

10

Hydrogen ion Specific

conductance

5

0

-5

-10

Bucket-minus-bottle differences, in microequivalents per liter

Bucket-minus-bottle differences, in microsiemens per centimeter at 25 degrees Celsius

2002 Fieldaudit program 

2003 Fieldaudit program 

Number of 

samples = 58

Number of 

samples = 58

Figure 16. Bucket-minus-bottle differences for hydrogen ion 

concentration and specific conductance for 2002–03 field-audit data 

(see figure 9 for explanation of boxplots).
30 External Quality-Assurance Results for the National Atmospheric Deposition Program/National Trends Network, 2002–03

Table 10. Number of determinations exceeding minimum detection limit for 24 ultrapure deionized-water samples submitted in 2002 and 

for 18 ultrapure deionized-water samples submitted in 2003 as part of field-audit program.

[CAL MDL, Central Analytical Laboratory minimum detection limit obtained from Rothert (2004); mg/L, milligrams per liter]

Analyte

Onsite-exposed bucket sample Minimally handled bottle sample

CAL

MDL 

(mg/L)

Number of 

determinations greater 

than MDL

Percentage of total

Number of 

determinations greater 

than MDL

Percentage of total

2002

Calcium 8 33 3 13 0.009

Magnesium 4 17 0 0 .003

Sodium 11 46 1 4 .003

Potassium 8 33 0 0 .003

Ammonium 4 17 0 0 .020

Chloride 18 75 3 13 .005

Nitrate 7 29 0 0 .010

Sulfate 8 33 0 0 .010

2003

Calcium 7 39 2 11 .009

Magnesium 1 6 0 0 .003

Sodium 3 17 0 0 .003

Potassium 6 33 1 6 .003

Ammonium 8 44 0 0 .020

Chloride 5 28 0 0 .005

Nitrate 5 28 0 0 .010

Sulfate 2 11 1 6 .010

material were entrained into the solutions from the onsiteexposed buckets. The data also show some loss of constituents 

by virtue of the negative values for the bucket-minus-bottle concentration differences. It is unclear how much of the apparent 

loss was due to adsorption to the buckets and (or) other chemical reactions. Analytical variability for hydrogen-ion concentrations is estimated herein to be less than 1 percent (see 

"Interlaboratory-Comparison Program" section).

Constituents that appear to be introduced to the precipitation samples by onsite exposure of the sample buckets, evidenced by positive bucket-minus-bottle differences, are calcium, magnesium, sodium, potassium, chloride, nitrate, and 

sulfate. The positive bias that results from the minor amount of 

contamination appears to affect the chemical results by as much 

as +11 percent, which is the 75th percentile relative percentage 

difference shown in table 11 for calcium. Despite this evidence 

of apparent addition of contaminants to the samples from onsite 

exposure, the median relative bucket-minus-bottle difference 

for specific conductance is negative, indicating loss of ions 

from solution (table 11), which might be associated with 

hydrogen-ion loss. Hydrogen-ion loss due to onsite exposure 

and sample handling also appears to impart a bias of approximately -3.7 percent, as indicated by the median relative percentage bias shown in table 11. Like all environmental data, fieldaudit data contain a portion of the variability introduced by 

laboratory analysis.

Interlaboratory-Comparison Program

The two objectives of the interlaboratory-comparison program are (1) to estimate the analytical variability and bias of 

CAL and (2) to help facilitate integration of data from various 

monitoring networks—not accounting for the different onsite 

protocols used by different monitoring networks. A flowchart
Interlaboratory-Comparison Program 31

Table 11. Relative and absolute bucket-minus-bottle differences calculated as a percentage of target concentration or value for each 

analyte in field-audit program during 2002–03.

Analyte

Relative bucket-minus-bottle differences, expressed as a 

percentage of corresponding target bottle concentration 

or value 

Absolute bucket-minus-bottle differences, 

expressed as a percentage of corresponding 

target bottle concentration or value

Percentiles Percentiles

25th 50th 75th 25th 50th 75th

Calcium 0.22 3.1 11 1.7 4.1 13

Magnesium 0 2.0 6.1 1.4 2.9 6.1

Sodium -.9 .4 3.6 .28 1.4 3.6

Potassium -4.4 1.7 10 0 4.4 13

Ammonium -1.8 0 7.1 1.8 5.4 7.1

Chloride 1.1 2.7 5.8 1.2 2.9 6.0

Nitrate .17 .93 2.0 .46 1.1 2.0

Sulfate -.30 .26 1.6 .30 .94 2.0

Hydrogen ion -8.8 -3.7 0 2.2 5.0 9.9

Specific conductance -6.1 -1.2 1.7 1.6 5.3 13

of the interlaboratory-comparison program is shown in 

figure 20. Eight laboratories participated in the interlaboratorycomparison program during the study period. Each of the eight 

participating laboratories received four samples from USGS 

every 2 weeks for chemical analysis, except for Shepard Analytical (Simi Valley, California), which received one-half of the 

sample load. The samples were synthetic precipitation solutions, ultrapure deionized water, or natural precipitation. The 

laboratories submitted chemical-analysis data to USGS for 

evaluation and reporting. Data from each laboratory were compared against most probable values (MPVs) and evaluated 

within statistical limits using control charts. The medians of all 

of the concentration values obtained from the eight laboratories 

were considered to be the MPVs for solutions used in the interlaboratory-comparison program. MPVs for the synthetic precipitation solutions are listed in table 12. Control charts and 

other data summaries are posted on the World Wide Web for 

each laboratory’s use at http://bqs.usgs.gov/precip/ 

project_overview/interlab/ilab_intro.htm

The following laboratories participated in the interlaboratory-comparison program during 2002 through 2003: (1) Acid 

Deposition and Oxidant Research Center (ADORC) in Niigatashi, Japan; (2) Illinois State Water Survey, Central Analytical 

Laboratory (CAL) in Champaign, Illinois; (3) MACTEC, Inc. 

(formerly ESE) in Gainesville, Florida; (4) Ontario Ministry of 

Environment and Energy, Dorset Research Facility (MOEE) in 

Dorset, Ontario, Canada; (5) Meteorological Service of Canada 

(MSC) in Downsview, Ontario, Canada; (6) Norwegian Institute for Air Research (NILU) in Kjeller, Norway; (7) New York 

State Department of Environmental Conservation (NYSDEC) 

in Albany, New York; and (8) Shepard Analytical (SA) in Simi 

Valley, California. Many of the major global atmosphericdeposition monitoring networks are united into this single 

program designed to measure laboratory data quality, which 

aids in data comparison between monitoring networks worldwide.

Many of the samples used in the interlaboratorycomparison program were made from stock solutions prepared 

by High Purity Standards (HPS), Charleston, South Carolina, 

which were diluted, bottled, labeled, and shipped by USGS to 

the participating laboratories. Three sources of samples were 

used in the interlaboratory-comparison program during 2002 

through 2003: (1) natural wet-deposition samples collected at 

NADP/NTN sites and blended by CAL, which were sent to 

USGS for bottling and shipping to the interlaboratorycomparison laboratories (Latysh and Wetherbee, 2005); 

(2) synthetic precipitation standard reference samples prepared 

by HPS and diluted and bottled by USGS; and (3) ultrapure 

deionized-water samples prepared by USGS. Table 3 contains 

information on the preparation of the solutions made either by 

HPS, USGS, or CAL, as well as the names of solutions with 

concentrations traceable to NIST reference materials (NISTtraceable samples).

Natural wet-deposition samples collected at NADP/NTN 

sites with sufficient volume (samples in excess of 750 mL) were 

selected randomly by CAL for use in the interlaboratorycomparison program. These samples, collectively called CALNAT samples, were bottled in 60- and 125-mL polyethylene 

bottles and shipped in chilled, insulated containers to USGS in 

Denver, Colorado. USGS keeps CALNAT samples refrigerated and ships the samples on ice to participating laboratories 

within a few weeks of receiving them. CALNAT samples are 

not preserved, and a maximum sample hold time is not specified 

for the nutrient constituents in these samples. Variability in 

hold times among the different laboratories could have an effect 

on the variability in the nutrient data among laboratories analyzing CALNAT samples because the nutrients may be used by 
32 External Quality-Assurance Results for the National Atmospheric Deposition Program/National Trends Network, 2002–03

40

20

0

-20

40

60

20

0

-20

10

5

0

-10

250 500 1,000

Sample volume, in milliliters

250 1,000 2,000

-5

10

5

0

-5

20

-10

0

10

20

30

40

50

60

-5

0

5

10

15

-20

0

20

40

60

10

0

-10

Bucket-minus-bottle differences, in micrograms per liter

Calcium

SD @ 0.05

SD @ 0.05—Significant difference between different volumes with 95-percent confidence

SD @ 0.05

SD @ 0.05 SD @ 0.05

2002 2003

Calcium

Magnesium

Sodium

Potassium Potassium

Sodium

Magnesium

EXPLANTION

Figure 17. Relation of paired bucket-minus-bottle major cation concentration differences and sample volume for 2002–03 

field-audit data (see figure 9 for explanation of boxplots).
Interlaboratory-Comparison Program 33

40

20

0

-20

-40

40

80

60

20

0

-20

-40

-60

50

25

0

-50

250 500 1,000

Sample volume, in milliliters

250 1,000 2,000

-25

20

0

-20

-40

60

0

30

-30

60

-10

0

10

20

30

-40

-20

0

20

40

30

0

-30

Bucket-minus-bottle differences, in micrograms per liter

Ammonium Ammonium

SD @ 0.05—Significant difference between different volumes with 95-percent confidence

SD @ 0.05 SD @ 0.05

SD @ 0.05 SD @ 0.05

SD @ 0.05

2002 2003

Chloride Chloride

Nitrate Nitrate

Sulfate Sulfate

EXPLANTION

Figure 18. Relation of paired bucket-minus-bottle ammonium and major anion concentration differences and sample 

volume for 2002–03 field-audit data (see figure 9 for explanation of boxplots).
34 External Quality-Assurance Results for the National Atmospheric Deposition Program/National Trends Network, 2002–03

4

2

0

-2

-4

4

2

0

-2

-4

4

2

0

-2

-4

4

2

0

-2

-4

250 500 1,000

Sample volume, in milliliters

250 1,000 2,000

Bucket-minus-bottle differences,

in microsiemens per centimeter

at 25 degrees Celsius

Bucket-minus-bottle differences,

in microequivalents per liter

Hydrogen ion Hydrogen ion

SD @ 0.05—Significant difference between different volumes with 95-percent confidence

SD @ 0.05

2002 2003

Specific conductance Specific conductance

EXPLANTION

Figure 19. Relation of paired bucket-minus-bottle differences for hydrogen-ion concentration and specific conductance to 

sample volume for 2002–03 field-audit data (see figure 9 for explanation of boxplots).

bacteria, which can affect ammonium, nitrate, and sulfate 

concentrations in the samples (Tchobanoglous and Schroeder, 

1987).

During 2002–03, seven of the eight participating 

laboratories received 104 samples annually. Of the 104 samples, 52 were CALNAT samples. Of the remaining samples, 

44 were synthetic precipitation solutions made by HPS and 

diluted by USGS, which were referred to as: SP1 solution; 

(9 samples); SP2 solution, (9 samples); SP5 solution, (8 samples); SP97 solution, (9 samples); and SP98c solution, (9 samples). Eight samples were ultrapure deionized-water samples 

bottled by USGS. SA received only the synthetic precipitation 

solution samples and ultrapure deionized-water samples.

Variability and Bias

Variability was evaluated for each laboratory and each 

analyte by comparing the distributions of the differences 

between reported results and MPVs. Analyte concentrations 

reported as less than MDL were set equal to one-half MDL 

before computing differences for each laboratory.

Evaluation of the interlaboratory variability was done in 

several steps. First, the differences between the reported results 

and MPVs were calculated as follows:

, (6)

where Clab = concentration reported by a laboratory for an 

analyte in a test solution, and

MPV = most probable value, which is the median of 

all concentration analyses submitted by participating laboratories for a test solution during 

2002–03.

Next, the differences were pooled for all eight laboratories to 

obtain the overall f-pseudosigma of the differences (fpso), 

which is the (75th percentile of all concentration differences – 

25th percentile of all concentration differences) divided by 

1.349. Then, the f-pseudosigma for the differences was 

calculated for each laboratory’s data (fpslab), which is the 

Concentration difference C = lab – MPV
Interlaboratory-Comparison Program 35

60- and 125-milliliter interlaboratorycomparison program samples

prepared by Illinois State Water

Survey, Central Analytical Laboratory 

60- and 125-milliliter interlaboratorycomparison program samples

prepared by U.S. Geological Survey

Natural wetdeposition samples

ADORC MACTEC

NIST:

ADORC:

CAL:

MACTEC:

MOEE:

MSC:

NILU:

NYSDEC:

SA:

CAL

MSC

MOEE

NYSDEC

NILU SA

Synthetic wetdeposition samples

Ultrapure deionizedwater samples 

Synthetic standard 

NIST-traceable

reference samples

Mailed to participating

laboratories for analysis

(no natural samples for SA) 

Analytical results reported to the U.S. Geological Survey

Results presented to National

Atmospheric Deposition Program/

Network Operations Subcommittee 

Data posted on the World Wide

Web for participating laboratories

Results presented in

reports and journals

National Institute of Standards and Technology

Acid Deposition and Oxidant Research Center, Niigata-shi, Japan

Central Analytical Laboratory, Illinois State Water Survey, Champaign, Illinois

MACTEC, Inc., Gainesville, Florida

Ontario Ministry of Environment and Energy, Dorset Research Facility, Dorset, Ontario, Canada

Meteorological Service of Canada, Downsview, Ontario, Canada

Norwegian Institute for Air Research, Kjeller, Norway

New York State Department of Environmental Conservation, Albany, New York

Shepard Analytical, Simi Valley, California

EXPLANATION

Figure 20. Interlaboratory-comparison program of U.S. Geological Survey.

(75th percentile of concentration differences – 25th percentile 

of concentration differences) divided by 1.349. Finally, the 

ratio of f-pseudosigma of differences for each laboratory to the 

overall f-pseudosigma (fps ratio) was computed and expressed 

as a percentage for each analyte:

. (7)

An fps ratio larger than 100 percent indicated that the results 

provided by a laboratory had more variability than the overall 

variability, whereas an fps ratio smaller than 100 percent indicated less variability than overall.

Table 13 shows the fps ratios obtained for each laboratory 

and for each constituent for data obtained during the study 

period. The results in table 13 show that the fps ratio for CAL’s 

ammonium data was 189 percent, indicating that variability in 

fps ratio( ) % fpslab

fps0

------------- ⎝ ⎠ ⎛ ⎞ = x100
Table 12. Most probable values for solutions used in 2002–03 U.S. Geological Survey interlaboratory-comparison program.[Most probable values are the median values of reported results from eight laboratories. Ca2+, calcium; Mg2+, magnesium; Na+, sodium; K+, potassium; NH4+, ammonium; Cl-, 

sulfate; pH, in standard units; specific conductance, in microsiemens per centimeter at 25 degrees Celsius]

Solution Ca2+ Mg2+ Na+ K+ NH4+ Cl- NO3- SO42- 

SP1 0.456 0.090 0.413 0.077 0.673 0.580 2.071 3.79 SP2 .452 .070 .352 .060 .551 .442 2.980 2.30 SP5 .574 .167 .445 .082 .700 .710 2.526 4.46 SP97 .130 .019 .025 .019 .290 .052 1.150 1.11 SP98c .014 .038 .209 .060 .120 .226 .562 2.40 
Interlaboratory-Comparison Program 37

CAL’s ammonium data was nearly double the overall variability. CAL’s ammonium data were more variable than ammonium 

data for any other participating laboratory during the study 

period. CAL’s ammonium data had considerable variability 

during 2000–2001 as well (Wetherbee and others, 2004).

The fps ratios for all constituents were less than 100 percent for MSC, indicating slight variability relative to the other 

participating laboratories. MACTEC also showed consistent, 

slight variability for all constituents with a maximum fps ratio 

of 106 percent for ammonium. Data obtained from NYSDEC 

had the most overall variability, especially for sodium, potassium, and sulfate. The 2002–03 results for MOEE indicated a 

considerable reduction in analytical variability compared to 

2000–2001 results (Wetherbee and others, 2004). The 2002–03 

results for SA indicated more variability than the results 

obtained for SA during 2000–2001 (Wetherbee and others, 

2004).

Intralaboratory bias (bias within a single laboratory) is 

defined as a systematic difference between the measured and 

expected values arising from sample handling and analysis procedures within a specific laboratory. Potential intralaboratory 

bias for the participating laboratories was evaluated by the following methods: (1) comparison of the medians of the differences between laboratory results and MPVs, (2) hypothesis testing using the Sign test, and (3) comparison of laboratory results 

for ultrapure deionized-water samples. 

The median differences between reported concentrations 

and MPVs are presented in table 13. The arithmetic signs of the 

median differences indicate whether the reported results for 

each constituent were positively or negatively biased. The 

absolute values of the median differences reported by CAL 

were all less than or equal to MDLs (table 5) except for nitrate, 

sulfate, and specific conductance. The median differences for 

data reported by CAL for nitrate and sulfate were approximately three and five times their respective MDLs. The median 

differences for CAL were comparable to those computed for the 

other participating laboratories. 

The Sign test for a median (Kanji, 1993) was used to evaluate bias for each laboratory. The null hypothesis for the test is, 

"The median of the differences between laboratory-reported 

values and MPVs is zero." The test results shown in table 13 

were evaluated at the α=0.05 significance level for a two-tailed 

test. Rejection of the null hypothesis, as indicated by the shaded 

values in the table, implies that laboratory results were biased. 

The results in table 13 indicate that the calcium, magnesium, 

and ammonium data reported by CAL during the study period 

were negatively biased and that the sodium, potassium, chloride, nitrate, sulfate, hydrogen ion, and specific conductance 

data were positively biased. As shown in table 13, significant 

(α=0.05) bias was identified for selected constituents for all of 

the participating laboratories, but in nearly all cases, the magnitude of the biases was small compared to MPVs (table 12).

To detect possible low-level sample contamination resulting from laboratory analyses, eight ultrapure deionized-water 

samples were included among the samples submitted to the participating laboratories each year during the study period. The 

results obtained for the ultrapure deionized-water samples, 

which are not expected to contain detectable analyte concentrations, were compared to each laboratory’s MDLs. Table 14 lists 

the number of times each laboratory reported a concentration 

greater than MDL for the ultrapure deionized-water samples. 

The small number of detections (one in 2002 and two in 2003) 

in the ultrapure deionized-water samples indicates that contamination was not a problem for CAL, which infers that laboratory 

contamination was not a problem for NADP/NTN data during 

the study period. The number of detections in ultrapure deionized-water samples obtained by MOEE decreased from eight in 

2002 to four in 2003. The number of detections in ultrapure 

deionized-water samples obtained by NILU increased from 2 in 

2002 to 15 in 2003. ADORC, MACTEC, and MSC reported no 

detections greater than their MDLs for ultrapure deionizedwater samples during the study period.

Median Absolute Error in Chemical Analyses

Chemical analysis error is only one component of the overall error in NADP/NTN data, which also are affected by other 

error sources such as sampling equipment, contamination from 

onsite exposure, and sample handling, to name a few. Comparison of the chemical analysis error to the overall error in 

NADP/NTN measurements requires computation of errors in 

absolute terms. Therefore, median absolute differences 

(MADs) were calculated for replicate chemical analyses of 

synthetic precipitation solutions. The f-pseudosigma of the 

absolute differences also was computed as a measure of variability about the median (table 15).

Overall, the MAD values computed for the analysis of replicate samples for the study period were comparable to 2000–

2001 results for the interlaboratory-comparison program 

(Wetherbee and others, 2004). During the study period, cation 

precision estimates were similar among laboratories, with 

nearly all MAD less than or equal to 0.005 mg/L, but anion precision estimates exhibited greater variability among laboratories. During 2002–03, all of the participating laboratories had 

MAD values less than or equal to 0.030 mg/L for the anions. By 

comparison, the maximum MAD value for anions among participating laboratories during 2000–2001 was 0.020 mg/L 

(Wetherbee and others, 2004).

MAD values for hydrogen-ion concentration exhibited 

slight variability during 2002 ranging from 0 to 0.886 μeq/L for 

all participating laboratories. Variability in MAD values for 

hydrogen-ion concentration increased during 2003, ranging 

from 0 to 1.539 μeq/L for all participating laboratories. During 

the study period, MADs for CAL’s hydrogen-ion concentrations were less than 10 percent of the median hydrogen-ion 

concentration for NADP/NTN data (table 5). 

Seven laboratories routinely reported specific conductance 

results during the study period. The MSC laboratory did not 

report specific conductance measurements. Overall, there was 

little variability among laboratories in their reported specific 

conductance measurements as MAD values ranged from 0 to 
Table 13. Comparison of differences between reported concentrations and most probable values for synthetic precipitation samples in interlaboratory-

2002–03.

 [Overall f-psig., f-pseudosigma calculated for all results from all participating laboratories; Median diff., median of differences between each laboratory's individual results and t

which is defined as the median of all results from all participating laboratories during 2002–03; Sign test p-value, probability of rejecting the null hypothesis, "The true median o

tory results and the most probable value is zero," when true; shaded values identify bias per the Sign test for a two-tailed test at 95-percent confidence (α=0.05) (Kanji, 1993); fps oratory's f-pseudosigma to the overall f-pseudosigma, expressed as a percentage; ADORC, Acid Deposition and Oxidant Research Center; CAL, Central Analytical Laboratory, IMACTEC, MACTEC, Inc.; MOEE, Ontario Ministry of Environment and Energy; MSC, Meteorological Service of Canada; NILU, Norwegian Institute for Air Research; NYSDof Environmental Conservation; SA, Shepard Analytical; mg/L, milligrams per liter; %, percent; <, less than; --, not calculated]

Analyte

Overall 

f-psig. (mg/L)

Laboratory

ADORC CAL MACTEC 

Median 

diff. 

(mg/L)

Sign test 

p-value

fps ratio 

(%)

Median diff. 

(mg/L)

Sign test 

p-value

fps ratio 

(%)

Median 

diff. 

(mg/L)

Sign test 

p-value

fps ratio 

(%)

Calcium 0.021 -0.002 0.0088 107 -0.003 <0.0001 54 0.005 <0.0001 50 Magnesium .004 -.002 .0067 133 -.002 <.0002 67 -.001 .0344 67 Sodium .010 .003 .1284 108 .002 .0049 77 -.005 <.0001 69 Potassium .005 -.001 .3261 186 .001 .0103 43 0 .9122 86 Ammonium .013 .007 .0021 128 -.008 .0003 189 .004 .0314 106 Chloride .010 -.012 <.001 150 .003 <.0001 64 -.001 .0845 36 Nitrate .040 -.003 .5900 167 .030 <.0001 96 -.017 <.0001 41 Sulfate .059 .006 .2723 110 .050 <.0001 79 -.010 .0073 63 Hydrogen ion 3.08 -1.80 .0003 81 .820 <.0001 51 -2.11 .0821 54 Specific conductance 1.8 -.2 <.0001 30 1.0 .0073 29 .3 <.0001 84 

MSC NILU NYSDEC 

Calcium .021 -.003 .1093 79 .006 <.0001 79 .026 <.0001 161 Magnesium .004 0 .4095 67 .003 <.0001 100 .005 <.0002 167 Sodium .010 .003 <.0001 38 0 .8264 85 -.014 <.0003 238 Potassium .005 .002 .0014 71 .001 .0005 100 .006 .0034 371 Ammonium .013 -.004 .0002 44 -.003 .0008 117 -.004 .0040 72 Chloride .010 .004 <.0001 71 -.003 .0007 107 -.003 .1606 207 Nitrate .040 -.011 .2345 74 -.009 .3318 74 -.003 .9152 196 Sulfate .059 -.013 .0178 60 .060 <.0001 134 -.091 <.0001 478 Hydrogen ion 3.08 -2.09 <.0001 82 -.120 <.0001 98 .650 <.0001 55 Specific conductance 1.8 No data -- -- 1.0 .8304 21 -2.0 .0011 157 
Interlaboratory-Comparison Program 39

Table 14. Number of analyte determinations greater than minimum detection limits for each participating laboratory and each ion 

for ultrapure deionized-water samples during 2002–03.

[Eight determinations per year per laboratory; ADORC, Acid Deposition and Oxidant Research Center; CAL, Central Analytical Laboratory, Illinois State 

Water Survey; MACTEC, MACTEC, Inc.; MOEE, Ontario Ministry of Environment and Energy; MSC, Meteorological Service of Canada; NILU, Norwegian Institute for Air Research; NYSDEC, New York State Department of Environmental Conservation; SA, Shepard Analytical]

Analyte ADORC CAL MACTEC MOEE MSC NILU NYSDEC SA 

2002

Calcium 0 0 0 0 0 2 1 0

Magnesium 0 0 0 0 0 0 0 0

Sodium 0 1 0 1 0 0 0 0

Potassium 0 0 0 1 0 0 0 0

Ammonium 0 0 0 4 0 0 0 0

Chloride 0 0 0 0 0 0 1 0

Nitrate 0 0 0 2 0 0 0 0

Sulfate 0 0 0 0 0 0 0 0

2003

Calcium 0 0 0 0 0 4 1 0

Magnesium 0 0 0 0 0 1 0 0

Sodium 0 1 0 0 0 2 0 1

Potassium 0 1 0 0 0 3 0 0

Ammonium 0 0 0 0 0 2 3 0

Chloride 0 0 0 0 0 1 1 0

Nitrate 0 0 0 4 0 1 4 0

Sulfate 0 0 0 0 0 1 4 0

0.3 μS/cm in 2002 and from 0 to 0.8 μS/cm in 2003 for all participating laboratories. 

Control Charts

A visual comparison of interlaboratory differences 

between each laboratory’s analyte concentrations and MPVs 

are presented in the control charts shown in figures 21–30. The 

control limits are placed at + 3 f-pseudosigmas from the zero 

difference line. The f-pseudosigma was defined previously 

(equation 1) and is assumed to be a nonparametric analogue of 

the standard deviation (Hoaglin and others, 1983). Control limits (3-sigma) define the bounds of virtually all values (99 percent) produced by a system in statistical control. Modern control charts commonly have additional limits called warning 

limits (2-sigma) within which most (95 percent) of the values 

should lie (Taylor, 1987). The warning limits are positioned at 

+ 2 f-pseudosigmas from the zero difference line. The independent axis for the control charts is time of sample analysis, in this 

report January 1, 2002, to December 31, 2003.

Graphs in figures 21–30 depict the control charts for each 

analyte for the eight participating laboratories. The plotted 

points are color- and symbol-coded by solution type to provide 

visual indication of potential bias for specific solutions. No 

such solution-specific bias was identified in the data for any of 

the participating laboratories. The data for the CAL in figures 

22 through 29 indicate brief time periods when CAL’s analytical precision for magnesium, sodium, potassium, ammonium, 

chloride, nitrate, sulfate, and hydrogen ion was not within the 

control limits. However, CAL data were within statistical control approximately 90 percent of the time during the study 

period. The control chart data indicate that CAL’s precision is 

consistent with that of other laboratories performing analysis of 

low-ionic strength environmental samples. 

Visual comparison of the control charts for the eight laboratories indicates that CAL, MACTEC, and MSC exhibited 

similar, consistent statistical control characteristics for all analytes. ADORC, NILU, NYSDEC, and SA laboratories reported 

a small number of data outside of statistical control for magnesium. MOEE and NYSDEC produced a number of data outside 

of statistical control for chloride, and NYSDEC data for sulfate 

was not within statistical control for approximately 2 months in 

early 2002 and for approximately 4 months during middle to 

late 2003. SA produced specific conductance data outside of 

statistical control in middle to late 2002, which was uncharacteristic of past SA performance.
40 External Quality-Assurance Results for the National Atmospheric Deposition Program/National Trends Network, 2002–03

Table 15. Summary of absolute differences for analysis of replicate, synthetic-precipitation solution samples determined by eight 

laboratories participating in 2002–03 interlaboratory-comparison program.

[All units in milligrams per liter except hydrogen ion, in microequivalents per liter, and specific conductance, in microsiemens per centimeter at 25 degrees Celsius; MAD, median absolute difference; f-psig., f-pseudosigma; ADORC, Acid Deposition and Oxidant Research Center; CAL, Illinois State Water Survey, Central Analytical Laboratory; MACTEC, MACTEC, Inc.; MOEE, Ontario Ministry of Environment and Energy; MSC, Meteorological Service of Canada; NILU, 

Norwegian Institute for Air Research; NYSDEC, New York State Department of Environmental Conservation; SA, Shepard Analytical; --, not calculated]

Analyte

ADORC CAL MACTEC MOEE

MAD f-psig. MAD f-psig. MAD f-psig. MAD f-psig.

2002

Calcium 0.002 0.001 0.002 0.001 0.002 0.001 0 0.015

Magnesium 0 .001 .001 .001 0 0 0 0

Sodium .001 .001 .002 .007 .001 .002 0 .004

Potassium .001 .001 .001 .001 .001 .001 0 .004

Ammonium 0 0 0 0 .006 .004 0 .007

Chloride 0 0 .003 .002 .002 .003 .010 .007

Nitrate .010 .007 .005 .006 .004 .006 .020 .044

Sulfate .010 .007 .009 .008 .010 .007 0 0

Hydrogen ion .642 1.178 0 .641 .777 1.325 .886 1.560

Specific conductance .2 .2 0 .1 .3 .1 .2 .6

2003

Calcium .002 .002 .004 .007 .003 .002 0 .015

Magnesium 0 .001 .001 .001 0 .001 0 .004

Sodium .002 .002 .004 .003 .001 .003 .005 .007

Potassium .001 .001 .001 .001 .001 .001 0 .004

Ammonium .010 .007 0 .007 .003 .002 .010 .007

Chloride 0 .007 .004 .002 .003 .003 .010 .022

Nitrate .010 .007 .008 .007 .009 .009 .020 .041

Sulfate .010 .015 .007 .007 .010 .007 .025 .037

Hydrogen ion 1.539 1.650 .720 .728 .836 .632 .680 .672

Specific conductance .3 .4 .1 .1 .8 1.0 .4 .6

Analyte

MSC NILU NYSDEC SA

MAD f-psig. MAD f-psig. MAD f-psig. MAD f-psig.

2002

Calcium 0.003 0.004 0.010 0.007 0.003 0.004 0.002 0.004

Magnesium 0 .001 0 .007 .002 .002 0 .001

Sodium .001 .001 0 .007 .002 .001 .001 .001

Potassium .001 .001 0 0 .003 .003 .001 .001

Ammonium .001 .001 0 .007 .004 .003 0 0

Chloride .001 .001 .010 .007 .003 .003 0 0

Nitrate .002 .004 .010 .033 .011 .012 .010 .007

Sulfate .005 .004 .030 .026 .017 .016 .010 .007

Hydrogen ion .858 .662 .618 .580 .562 .696 0 .646

Specific conductance -- -- .1 .1 .3 .7 .1 .1

2003

Calcium .005 .004 0 .007 .006 .007 .002 .003

Magnesium 0 .001 0 .007 .001 .001 0 .001

Sodium .002 .004 .010 .022 .002 .002 .002 .001

Potassium .001 .001 0 .007 .002 .004 .001 .001

Ammonium .001 .001 0 .015 .003 .005 0 .007

Chloride .002 .002 0 .007 .007 .013 0 0

Nitrate .009 .009 .020 .022 .027 .041 .010 .007

Sulfate .008 .006 .020 .015 .030 .034 .010 .011

Hydrogen ion .766 .904 .768 .774 0 .597 .720 .827

Specific conductance -- -- .1 .2 .3 .7 .1 .1
Interlaboratory-Comparison Program 41

ADORC MSC

CAL NILU

MACTEC NYSDEC

MOEE SA

-0.4

-0.2

0

0.2

0.4

-0.4

-0.2

0

0.2

0.4

-0.4

-0.2

0

0.2

0.4

-0.4

-0.2

0

0.2

0.4

2002 2003 2004 2002 2003 2004

Calcium concentration difference, in milligrams per liter

Natural precipitation (CALNAT)

SP5

SP97

SP98c

Warning limits (+2 and -2 f-pseudosigmas from zero difference line)

Control limits (+3 and -3 f-pseudosigmas from zero difference line)

SP2

Solutions:

ADORC:

CAL:

MACTEC:

MOEE:

MSC:

NILU:

NYSDEC:

SA:

Acid Deposition and Oxidant Research Center, Niigata-shi, Japan

Central Analytical Laboratory, Champaign, Illinois

MACTEC Inc., Gainesville, Florida

Ontario Ministry of Environment and Energy, Dorset Research Facility, Dorset, Ontario, Canada

Meteorological Service of Canada, Downsview, Ontario, Canada

Norwegian Institute of Air Research, Kjeller, Norway

New York State Department of Environmental Conservation, Albany, New York

Shepard Analytical, Simi Valley, California

SP1

Laboratories:

EXPLANATION

Figure 21. Difference between measured calcium concentration values and median calcium concentration value 

calculated by solution for all participating laboratories in interlaboratory-comparison program during 2002–03.
42 External Quality-Assurance Results for the National Atmospheric Deposition Program/National Trends Network, 2002–03

ADORC MSC

CAL NILU

MACTEC NYSDEC

MOEE SA

-0.050

-0.025

0

0.025

0.050

-0.050

-0.025

0

0.025

0.050

-0.050

-0.025

0

0.025

0.050

-0.050

-0.025

0

0.025

0.050

2002 2003 2004 2002 2003 2004

Magnesium concentration difference, in milligrams per liter

Natural precipitation (CALNAT)

SP5

SP97

SP98c

Warning limits (+2 and -2 f-pseudosigmas from zero difference line)

Control limits (+3 and -3 f-pseudosigmas from zero difference line)

SP2

Solutions:

ADORC:

CAL:

MACTEC:

MOEE:

MSC:

NILU:

NYSDEC:

SA:

Acid Deposition and Oxidant Research Center, Niigata-shi, Japan

Central Analytical Laboratory, Champaign, Illinois

MACTEC Inc., Gainesville, Florida

Ontario Ministry of Environment and Energy, Dorset Research Facility, Dorset, Ontario, Canada

Meteorological Service of Canada, Downsview, Ontario, Canada

Norwegian Institute of Air Research, Kjeller, Norway

New York State Department of Environmental Conservation, Albany, New York

Shepard Analytical, Simi Valley, California

SP1

Laboratories:

EXPLANATION

Figure 22. Differences between measured magnesium concentration values and median magnesium concentration 

value calculated by solution for all participating laboratories in interlaboratory-comparison program during 2002–03.
Interlaboratory-Comparison Program 43

ADORC MSC

CAL NILU

MACTEC NYSDEC

MOEE SA

-0.2

-0.2

-0.1

0

0.2

0.1

0.3

-0.2

-0.2

-0.1

0

0.2

0.1

0.3

-0.2

-0.2

-0.1

0

0.2

0.1

0.3

-0.2

-0.2

-0.1

0

0.2

0.1

0.3

2002 2003 2004 2002 2003 2004

Sodium concentration difference, in milligrams per liter

Natural precipitation (CALNAT)

SP5

SP97

SP98c

Warning limits (+2 and -2 f-pseudosigmas from zero difference line)

Control limits (+3 and -3 f-pseudosigmas from zero difference line)

SP2

Solutions:

ADORC:

CAL:

MACTEC:

MOEE:

MSC:

NILU:

NYSDEC:

SA:

Acid Deposition and Oxidant Research Center, Niigata-shi, Japan

Central Analytical Laboratory, Champaign, Illinois

MACTEC Inc., Gainesville, Florida

Ontario Ministry of Environment and Energy, Dorset Research Facility, Dorset, Ontario, Canada

Meteorological Service of Canada, Downsview, Ontario, Canada

Norwegian Institute of Air Research, Kjeller, Norway

New York State Department of Environmental Conservation, Albany, New York

Shepard Analytical, Simi Valley, California

SP1

Laboratories:

EXPLANATION

Figure 23. Difference between measured sodium concentration values and median sodium concentration value 

calculated by solution for all participating laboratories in interlaboratory-comparison program during 2002–03.
44 External Quality-Assurance Results for the National Atmospheric Deposition Program/National Trends Network, 2002–03

ADORC MSC

CAL NILU

MACTEC NYSDEC

MOEE SA

-0.30

-0.15

0

0.30

0.15

-0.30

-0.15

0

0.30

0.15

-0.30

-0.15

0

0.30

0.15

-0.30

-0.15

0

0.30

0.15

2002 2003 2004 2002 2003 2004

Potassium concentration difference, in milligrams per liter

Natural precipitation (CALNAT)

SP5

SP97

SP98c

Warning limits (+2 and -2 f-pseudosigmas from zero difference line)

Control limits (+3 and -3 f-pseudosigmas from zero difference line)

SP2

Solutions:

ADORC:

CAL:

MACTEC:

MOEE:

MSC:

NILU:

NYSDEC:

SA:

Acid Deposition and Oxidant Research Center, Niigata-shi, Japan

Central Analytical Laboratory, Champaign, Illinois

MACTEC Inc., Gainesville, Florida

Ontario Ministry of Environment and Energy, Dorset Research Facility, Dorset, Ontario, Canada

Meteorological Service of Canada, Downsview, Ontario, Canada

Norwegian Institute of Air Research, Kjeller, Norway

New York State Department of Environmental Conservation, Albany, New York

Shepard Analytical, Simi Valley, California

SP1

Laboratories:

EXPLANATION

Figure 24. Difference between measured potassium concentration values and median potassium concentration value 

calculated by solution for all participating laboratories in interlaboratory-comparison program during 2002–03.
Interlaboratory-Comparison Program 45

ADORC MSC

CAL NILU

MACTEC NYSDEC

MOEE SA

-0.30

-0.15

0

0.30

0.15

-0.30

-0.15

0

0.30

0.15

-0.30

-0.15

0

0.30

0.15

-0.30

-0.15

0

0.30

0.15

2002 2003 2004 2002 2003 2004

Ammonium concentration difference, in milligrams per liter

Natural precipitation (CALNAT)

SP5

SP97

SP98c

Warning limits (+2 and -2 f-pseudosigmas from zero difference line)

Control limits (+3 and -3 f-pseudosigmas from zero difference line)

SP2

Solutions:

ADORC:

CAL:

MACTEC:

MOEE:

MSC:

NILU:

NYSDEC:

SA:

Acid Deposition and Oxidant Research Center, Niigata-shi, Japan

Central Analytical Laboratory, Champaign, Illinois

MACTEC Inc., Gainesville, Florida

Ontario Ministry of Environment and Energy, Dorset Research Facility, Dorset, Ontario, Canada

Meteorological Service of Canada, Downsview, Ontario, Canada

Norwegian Institute of Air Research, Kjeller, Norway

New York State Department of Environmental Conservation, Albany, New York

Shepard Analytical, Simi Valley, California

SP1

Laboratories:

EXPLANATION

Figure 25. Difference between measured ammonium concentration values and median ammonium concentration 

value calculated by solution for all participating laboratories in interlaboratory-comparison program during 2002–03.
46 External Quality-Assurance Results for the National Atmospheric Deposition Program/National Trends Network, 2002–03

ADORC MSC

CAL NILU

MACTEC NYSDEC

MOEE SA

-0.18

-0.09

0

0.18

0.09

-0.18

-0.09

0

0.18

0.09

-0.18

-0.09

0

0.18

0.09

-0.18

-0.09

0

0.18

0.09

2002 2003 2004 2002 2003 2004

Chloride concentration difference, in milligrams per liter

Natural precipitation (CALNAT)

SP5

SP97

SP98c

Warning limits (+2 and -2 f-pseudosigmas from zero difference line)

Control limits (+3 and -3 f-pseudosigmas from zero difference line)

SP2

Solutions:

ADORC:

CAL:

MACTEC:

MOEE:

MSC:

NILU:

NYSDEC:

SA:

Acid Deposition and Oxidant Research Center, Niigata-shi, Japan

Central Analytical Laboratory, Champaign, Illinois

MACTEC Inc., Gainesville, Florida

Ontario Ministry of Environment and Energy, Dorset Research Facility, Dorset, Ontario, Canada

Meteorological Service of Canada, Downsview, Ontario, Canada

Norwegian Institute of Air Research, Kjeller, Norway

New York State Department of Environmental Conservation, Albany, New York

Shepard Analytical, Simi Valley, California

SP1

Laboratories:

EXPLANATION

Figure 26. Difference between measured chloride concentration values and median chloride concentration value 

calculated by solution for all participating laboratories in interlaboratory-comparison program during 2002–03.
Interlaboratory-Comparison Program 47

ADORC MSC

CAL NILU

MACTEC NYSDEC

MOEE SA

-1.2

-0.6

0

1.2

0.6

-1.2

-0.6

0

1.2

0.6

-1.2

-0.6

0

1.2

0.6

-1.2

-0.6

0

1.2

0.6

2002 2003 2004 2002 2003 2004

Nitrate concentration difference, in milligrams per liter

Natural precipitation (CALNAT)

SP5

SP97

SP98c

Warning limits (+2 and -2 f-pseudosigmas from zero difference line)

Control limits (+3 and -3 f-pseudosigmas from zero difference line)

SP2

Solutions:

ADORC:

CAL:

MACTEC:

MOEE:

MSC:

NILU:

NYSDEC:

SA:

Acid Deposition and Oxidant Research Center, Niigata-shi, Japan

Central Analytical Laboratory, Champaign, Illinois

MACTEC Inc., Gainesville, Florida

Ontario Ministry of Environment and Energy, Dorset Research Facility, Dorset, Ontario, Canada

Meteorological Service of Canada, Downsview, Ontario, Canada

Norwegian Institute of Air Research, Kjeller, Norway

New York State Department of Environmental Conservation, Albany, New York

Shepard Analytical, Simi Valley, California

SP1

Laboratories:

EXPLANATION

Figure 27. Difference between measured nitrate concentration values and median nitrate concentration value 

calculated by solution for all participating laboratories in interlaboratory-comparison program during 2002–03.
48 External Quality-Assurance Results for the National Atmospheric Deposition Program/National Trends Network, 2002–03

ADORC MSC

CAL NILU

MACTEC NYSDEC

MOEE SA

-1.0

-0.5

0

1.0

0.5

-1.0

-0.5

0

1.0

0.5

-1.0

-0.5

0

1.0

0.5

-1.0

-0.5

0

1.0

0.5

2002 2003 2004 2002 2003 2004

Sulfate concentration difference, in milligrams per liter

Natural precipitation (CALNAT)

SP5

SP97

SP98c

Warning limits (+2 and -2 f-pseudosigmas from zero difference line)

Control limits (+3 and -3 f-pseudosigmas from zero difference line)

SP2

Solutions:

ADORC:

CAL:

MACTEC:

MOEE:

MSC:

NILU:

NYSDEC:

SA:

Acid Deposition and Oxidant Research Center, Niigata-shi, Japan

Central Analytical Laboratory, Champaign, Illinois

MACTEC Inc., Gainesville, Florida

Ontario Ministry of Environment and Energy, Dorset Research Facility, Dorset, Ontario, Canada

Meteorological Service of Canada, Downsview, Ontario, Canada

Norwegian Institute of Air Research, Kjeller, Norway

New York State Department of Environmental Conservation, Albany, New York

Shepard Analytical, Simi Valley, California

SP1

Laboratories:

EXPLANATION

Figure 28. Difference between measured sulfate concentration values and median sulfate concentration value 

calculated by solution for all participating laboratories in interlaboratory-comparison program during 2002–03.
Interlaboratory-Comparison Program 49

ADORC MSC

CAL NILU

MACTEC NYSDEC

MOEE SA

-1.8

-0.9

0

1.8

0.9

-1.8

-0.9

0

1.8

0.9

-1.8

-0.9

0

1.8

0.9

-1.8

-0.9

0

1.8

0.9

2002 2003 2004 2002 2003 2004

pH difference, in in standard units

Natural precipitation (CALNAT)

SP5

SP97

SP98c

Warning limits (+2 and -2 f-pseudosigmas from zero difference line)

Control limits (+3 and -3 f-pseudosigmas from zero difference line)

SP2

Solutions:

ADORC:

CAL:

MACTEC:

MOEE:

MSC:

NILU:

NYSDEC:

SA:

Acid Deposition and Oxidant Research Center, Niigata-shi, Japan

Central Analytical Laboratory, Champaign, Illinois

MACTEC Inc., Gainesville, Florida

Ontario Ministry of Environment and Energy, Dorset Research Facility, Dorset, Ontario, Canada

Meteorological Service of Canada, Downsview, Ontario, Canada

Norwegian Institute of Air Research, Kjeller, Norway

New York State Department of Environmental Conservation, Albany, New York

Shepard Analytical, Simi Valley, California

SP1

Laboratories:

EXPLANATION

Figure 29. Difference between measured pH values and median pH value calculated by solution for all participating 

laboratories in interlaboratory-comparison program during 2002–03.
50 External Quality-Assurance Results for the National Atmospheric Deposition Program/National Trends Network, 2002–03

ADORC MSC

CAL NILU

MACTEC NYSDEC

MOEE SA

-16

-8

0

16

8

-16

-8

0

16

8

-16

-8

0

16

8

-16

-8

0

16

8

2002 2003 2004 2002 2003 2004

Specific conductance difference, in microsiemens per centimeter at 25 degrees Celsius

MSC does not analyze

interlaboratorycomparison samples for

specific conductance

Natural precipitation (CALNAT)

SP5

SP97

SP98c

Warning limits (+2 and -2 f-pseudosigmas from zero difference line)

Control limits (+3 and -3 f-pseudosigmas from zero difference line)

SP2

Solutions:

ADORC:

CAL:

MACTEC:

MOEE:

MSC:

NILU:

NYSDEC:

SA:

Acid Deposition and Oxidant Research Center, Niigata-shi, Japan

Central Analytical Laboratory, Champaign, Illinois

MACTEC Inc., Gainesville, Florida

Ontario Ministry of Environment and Energy, Dorset Research Facility, Dorset, Ontario, Canada

Meteorological Service of Canada, Downsview, Ontario, Canada

Norwegian Institute of Air Research, Kjeller, Norway

New York State Department of Environmental Conservation, Albany, New York

Shepard Analytical, Simi Valley, California

SP1

Laboratories:

EXPLANATION

Figure 30. Difference between measured specific conductance values and median specific conductance value 

calculated by solution for all participating laboratories in interlaboratory-comparison program during 2002–03.
Collocated-Sampler Program 51

Collocated-Sampler Program

The collocated-sampler program was established in October 1988 to provide a method of estimating the overall variability of the precipitation-monitoring system used by NADP/NTN. 

Included in this estimate of NADP/NTN precision is the variability from the point of sample collection through laboratory 

analysis and quality control (Gordon, 1999). Nilles and others 

(1991) provide a detailed description of the collocated-sampler 

program. Since 1988, collocated sites have been operated on a 

water-year (October 1–September 30) basis every year except 

1994 (Gordon, 1999; Wetherbee and others, 2005). 

The two sites selected for the collocated-sampler program 

in water year 2002 (WY2002)–October 1, 2001, through September 30, 2002–were OR02 (Alsea Guard Ranger Station, 

Benton County, Oregon) and WI98 (Wildcat Mountain State 

Park, Vernon County, Wisconsin). In water year 2003 

(WY2003)–October 1, 2002, through September 30, 2003–the 

WI98 site remained in the collocated-sampler program to collect data for 2 consecutive years at the same location. Running 

a collocated site at WI98 for 2 consecutive years allowed for 

more long-term evaluation of precipitation variability. The single new site selected for participation in the collocated-sampler 

program in WY2003 was OK00 (Salt Plains National Wildlife 

Refuge, Alfalfa County, Oklahoma). 

NADP/NTN guidelines for site selection and installation 

(Dossett and Bowersox, 1999) are used in the establishment of 

each collocated site. Site selection is made with the goal of distributing sites among diverse ecoregions with different precipitation regimes. In an effort to minimize data loss due to changes 

in personnel, sites with stable operational histories are given 

priority consideration. At each collocated site, the original site’s 

equipment—Aerochem Metrics Model 310 collector, Belfort 

Model 5–780 rain gage, and the power supply (solar panel, battery, alternating current, and so forth)—are duplicated. The 

duplicate instruments are installed such that they are no more or 

less affected by surrounding objects than the original site equipment. Snow platforms, rain-gage shielding, and other accessories also are duplicated. Both the original and collocated sets of 

equipment are calibrated and tested by USGS before starting 

sample collection at the collocated sites to ensure that differences between the two sites are not attributable to differences in 

collection equipment efficiencies.

Over the course of the water year, the site operators process samples from each pair of collectors using standard 

NADP/NTN procedures (Dossett and Bowersox, 1999). Site 

operators are given the option of forgoing onsite pH and 

specific conductance measurements of samples from the collocated samplers. Regardless of whether the pH and specific conductance measurements are made, a 20-mL aliquot is removed 

from samples with volumes greater than 70 mL to ensure equivalent handling of both samples from the collocated-sampler site. 

CAL analyzes the samples from the collocated sites following 

NADP/NTN SOPs.

Data Analysis

For the purpose of comparing an original and collocated 

site, the data from the original and collocated sites were analyzed for differences. Data from the original and collocated site 

were formally referred to by the four-character site code of the 

original site followed by the four-character site code of the collocated site. For example, the Wildcat Mountain site was formally referred to as WI98/98WI. For this analysis, the data used 

were from wet-deposition samples with volumes greater than 

35 mL. These samples were identified in the NADP database 

by a laboratory-type-code "W" to indicate that the samples were 

of sufficient volume for analysis and did not require dilution. 

Samples requiring dilution were inherently prone to a greater 

error component. Samples identified as contaminated with 

debris, bird droppings, insects, dirt or soot particles, or due to 

errant sample handling, were eliminated from statistical 

analysis.

Because annual summaries of NADP/NTN data describe 

precipitation chemistry in terms of concentration and deposition 

(National Atmospheric Deposition Program, 2001; 2002), statistical summaries for both the concentration and deposition of 

constituents are provided in this report. The weekly precipitation depth associated with each Belfort recording rain gage was 

used to calculate deposition values at the collocated sites. To 

calculate deposition, concentration in milligrams per liter 

(mg/L) was multiplied by 10-1 times the precipitation depth in 

centimeters to yield deposition in kilograms per hectare (kg/ha). 

The variability in deposition, due to differences in collection 

efficiencies of rain gages and precipitation collectors at collocated sites, provided an estimate of the variability in deposition 

amounts at other NADP/NTN sites.

Assessment of Absolute Error

In the analysis of collocated data, statistical analyses that 

(1) were useful for describing overall sampling precision and 

(2) were not overly sensitive to a few extreme values were 

selected. Precision estimates for each site were calculated from 

the absolute differences between the pairs of collocated samplers and were expressed as median absolute error (MAE) for a 

given site and analyte. The equations used to estimate relative 

and absolute errors from collocated data were:

, (8)

,

and (9)

, (10)

Absolute difference C2 C1 = –

Absolute error (percent) (C2 C1)/(C2 – C1 = [ ] + /2 • 100

Median absolute error (percent) =

M C2 C1 ( ) – / C2 C1 [ ] ( ) + /2 • 100
52 External Quality-Assurance Results for the National Atmospheric Deposition Program/National Trends Network, 2002–03

where

M = median of all paired differences;

C1 = sample concentration, in milligrams per liter, from 

the collocated precipitation sampler, or deposition, 

in kilograms per hectare, from the collocated precipitation sampler and rain gage; and

C2 = sample concentration, in milligrams per liter, from 

the original precipitation sampler, or deposition, in 

kilograms per hectare, from the original precipitation sampler and rain gage.

Graphical depictions of all MAEs for collocated sites are 

shown for concentration, for deposition, and for the physical 

measurements of specific conductance, sample volume, and 

precipitation depth in figures 31 and 32. For clarity, only the 

four-character codes of the original sites are shown in figures 31 

and 32.

MAE was estimated to be approximately 10 percent or less 

for concentrations of nitrate and sulfate and for specific conductance, sample volume, and precipitation depth at all of the collocated sites during the study period. MAEs for calcium, 

magnesium, sodium, ammonium, chloride, nitrate, and sulfate 

were estimated to be less than 10 percent for WI98/98WI during 

WY2002. Larger MAEs were calculated for nearly every analyte at WI98/98WI during WY2003 as compared to WY2002. 

Only the precipitation depth MAE was smaller during WY2003 

than during WY2002 at WI98/98WI. Many samples collected 

at WI98/98WI were eliminated from statistical analysis for 

WI98/98WI during WY2003 due to sample contamination, primarily from bird droppings. The small sample number might 

have contributed to the increase in MAE observed at 

WI98/98WI during WY2003. During WY2002, MAEs for 

OR02/02OR were less than 20 percent for all analytes except 

potassium and ammonium. During WY2003, MAEs for 

OK00/00OK were less than 20 percent for all analytes. 

Constituent deposition was calculated from the precipitation depth, which made the estimated MAE for deposition rates 

sensitive to error in precipitation depth measurements. Upon 

converting concentrations to deposition amounts, MAEs for 

most constituents increased for all of the collocated sites except 

for calcium at OR02/02OR and for sodium, potassium, and 

chloride at WI98/98WI during WY2003 (figs. 31 and 32).

MAEs were approximately 16 to 30 percent for hydrogen 

ion concentration and less than 10 percent for specific conductance. Contrary to past years, MAEs obtained for sample volume for the collocated sites (measured from the Aerochem 

Metrics wet-deposition collectors) were slightly larger than 

MAEs obtained for precipitation depth (measured from the Belfort rain gages), except for WI98/98WI during WY2002. MAEs 

for sample volume were uniformly small (ranging from 2 to 5 

percent). MAEs for precipitation depth ranged from less than 

1 percent to approximately 8 percent during the study period. 

Substantial variability was expected for concentrations 

approaching MDLs because laboratory percentage error usually 

increases as analyte concentration decreases. Estimates of network precision covering several years of collocated sampling 

are given in Nilles and others (1993), and the spatial and 

temporal variations in collocated-sampler estimated errors are 

presented by Wetherbee and others (2005). 

A comparison of WY2002 and WY2003 MAD values and 

MAD values determined for 41 collocated-sampler sites during 

1989–2001 is shown in tables 16 and 17. The data in tables 16 

and 17 indicate that the results for WY2002 and WY2003 generally are consistent with results for the collocated-sampler program for previous water years (Wetherbee and others, 2004). In 

tables 16 and 17, MAD data for each collocated-sampler site are 

expressed as percentages of the median values for all 

NADP/NTN data collected during 2002. MAD values for 

OR02/02OR expressed as a percentage of the 2002 median 

NADP/NTN values for magnesium (30 percent), sodium 

(72 percent), potassium (24 percent), and chloride (64 percent) 

might be environmentally significant to NADP/NTN data users. 

As in past years, MAEs were generally larger for cations 

(approximately 8 to 50 percent) than for anions (approximately 

3 to 33 percent) (fig. 31). Sample volume MAEs were less than 

5 percent. Precipitation depth MAEs were less than 8 percent 

(fig. 32) during the study period. 

Comparison of Sources of Variability

Two types of QC data are generated by the USGS External 

QA Project: (1) basic QC data and (2) topical QC data (Jeff 

Martin, USGS, written commun., 2003). Basic QC data are 

used to document the quality of NADP/NTN data and identify 

data-quality problems. Topical QC data are used to make 

"yes/no" decisions about data quality and to locate the causes of 

data-quality problems. Basic QC data are obtained from the 

collocated-sampler program. The goal of the collocatedsampler program is to measure the sum total of as many components of the overall variability (also known as overall error) in 

NADP/NTN measurements as possible. Topical QC data are 

obtained from the blind-audit, SHE, field-audit, and interlaboratory-comparison programs. These latter programs are used to 

measure selected components of the overall variability.

MAE data for each program are shown in table 18 to compare the relative amounts of the overall variability in 

NADP/NTN measurements attributable to different sources. 

The variability terms in table 18 compound from right to left 

across the table. For example, the variability term in column D 

is a component of the variability term in column C, and both 

variability terms in columns C and D are components of the 

variability term in column B, which is a component of the overall variability in column A. The laboratory analysis variability, 

defined earlier as the median absolute error (MAE), is shown in 

column D.

To determine the proportion of the overall variability 

attributed to each component, the following computational procedure was used. First, the proportion of variability attributed 

to laboratory analysis was calculated as column D divided by 

column A for each constituent and year. Next, the proportion of 

variability attributed to sample handling was calculated as the 
Comparison of Sources of Variability 53

Calcium Magnesium

Sodium Potassium

Ammonium Chloride

Nitrate Sulfate

20

30

40

60

50

0

10

20

30

40

60

50

0

10

20

30

40

60

50

0

10

20

30

40

60

50

0

10

OK00 OR02 WI98

2002

WI98

2003

OK00 OR02 WI98

2002

WI98

2003

Median absolute error, in percent

Error calculated from original and collocated

 concentration values Error calculated from original and collocated deposition amounts

EXPLANATION

Data are from the original and collocated sites. For clarity, only the four-digit codes of the

original National Atmospheric Deposition Program/National Trends Network sites are displayed.

Figure 31. Median absolute error for analyte concentration and deposition for weekly samples from collocated 

precipitation collectors during 2002–03 for selected analytes.
54 External Quality-Assurance Results for the National Atmospheric Deposition Program/National Trends Network, 2002–03

Hydrogen ion Specific conductance

Sample volume Precipitation depth

20

30

0

10

20

30

0

10

Median absolute error, in percent

Error calculated from original and collocated

 concentration values Error calculated from original and collocated deposition amounts

EXPLANATION

Data are from the original and collocated sites. For clarity, only the four-digit codes of the

original National Atmospheric Deposition Program/National Trends Network sites are displayed.

OK00 OR02 WI98

2002

WI98

2003

OK00 OR02 WI98

2002

WI98

2003

Figure 32. Median absolute error for hydrogen-ion concentration and deposition, specific conductance, and sample 

volume for weekly samples from collocated precipitation collectors and precipitation depth from collocated rain gages 

during 2002–03.

difference between column C and column D divided by column 

A for each individual analyte and year. Then, the proportion of 

variability attributed to onsite exposure was calculated as 

column B minus column C divided by column A for cases 

where column B is more than column C. Where the column B 

values are less than column C, the proportion of variability 

attributed to onsite exposure was set equal to zero. Finally, the 

proportion of variability attributed to both onsite instrumentation and natural variability was computed for each analyte and 

year as follows:

(11)

.

For each proportional variability term, the values for each analyte for 2002 and 2003 were averaged. The results of these 

computations provided an estimate of the proportion of 

variability attributed to laboratory analysis, onsite exposure, 

sample handling, and onsite instrumentation and natural variability combined (fig. 33).

Figure 33 shows that laboratory analysis variability, as 

estimated by the interlaboratory-comparison program, 

accounted for approximately 2 percent of the overall variability 

during the study period. Variability attributed to onsite exposure, as measured by the field-audit program, accounted for 

approximately 8 percent of the overall variability, whereas sample handling, as measured by the blind-audit and SHE programs, accounted for approximately 26 percent of the overall 

variability. The remaining variability (approximately 64 percent) not accounted for by onsite exposure, sample handling, 

and laboratory analysis was attributed to onsite instrumentation 

and natural variability. Overall average variability values for 

2002 and 2003 combined are represented in figure 33, whereas 

the data in table 18 indicate that the estimated variability attributed to each component of the sample-collection and analysis 

processes varied among analytes.

Proportion of variability attributed to onsite

instrumentation and natural variability =

1 0 or (B-C)/A – { } [ ] + + [ ] (C-D)/A ( ) D/A
Summary 55

Table 16. Comparison of median absolute differences determined for collocated-sampler sites OR02/02OR and WI98/98WI during water 

year 2002 to median values obtained during 2002 for all National Atmospheric Deposition Program/National Trends Network sites and to 

median absolute differences for 41 collocated-sampler sites during 1989–2001.

[NADP/NTN, National Atmospheric Depsition Program/National Trends Network; mg/L, milligrams per liter; MAD, median absolute difference between collocated-sampler values; μeq/L, microequivalents per liter; μS/cm, microsiemens per centimeter at 25 degrees Celsius; mL, milliliters; cm, centimeters; --, no data]

Analyte

(units)

Median 2002 

NADP/NTN 

values1 (mg/L 

unless specified)

1

Median values obtained for NADP/NTN during 2002 from Rothert (2004).

MAD results for 

OR02 

(mg/L unless 

specified)

OR02 MAD as a 

percentage of 

2002 median 

NADP/NTN 

values1

MAD results for 

WI98 

(mg/L unless 

specified)

WI98 MAD as a 

percentage of 

2002 median 

NADP/NTN 

values1

Median MAD for 

41 collocated 

sites 1989–20012

(mg/L unless 

specified)

2Data provided for comparison to MAD results from Wetherbee and others (2005).

Calcium 0.111 0.011 9.9 0.025 23 0.013

Magnesium .023 .007 30 .004 17 .003

Sodium .053 .038 72 .004 7.5 .013

Potassium .017 .004 24 .003 18 .004

Ammonium .240 .010 4.2 .043 18 .030

Chloride .108 .069 64 .007 6.5 .020

Nitrate 1.08 .010 .9 .056 5.2 .068

Sulfate .998 .025 2.5 .041 4.1 .060

Hydrogen ion (μeq/L) 11 .62 5.6 .52 4.7 1.7

Specific conductance (μS/cm) 12 .60 5.0 .60 5.0 .95

Sample volume (mL) 960 34 3.5 17 1.8 26

Precipitation depth (cm) -- .01 -- .04 -- .51

Summary

The U.S. Geological Survey (USGS) used six programs to 

provide external quality-assurance monitoring for NADP/NTN 

during 2002–03. An intersite-comparison program was used to 

estimate the accuracy and precision of onsite pH and specific 

conductance determinations. A blind-audit program was used in 

2002 and the SHE program was used in 2003 to assess the 

effects of routine sample handling, processing, and shipping of 

wet-deposition samples on the variability and bias of 

NADP/NTN wet-deposition data. A field-audit program 

assessed the effects of onsite exposure, sample handling, and 

shipping of sample-collection surfaces on precipitation chemistry. An interlaboratory-comparison program assessed the bias 

and variability of the chemical analysis data from CAL and 

seven other laboratories. A collocated-sampler program was 

used to determine the overall variability applicable to 

NADP/NTN wet-deposition data. 

Four intersite-comparison studies were conducted during 

the study period. The percentage of site operators responding 

on time that met the pH measurement accuracy goals decreased 

from 92.0 percent in spring 2002 to 86.3 percent in spring 2003. 

For these intersite-comparison studies, 94.4 to 97.5 percent of 

the site operators met the accuracy goals for specific 

conductance. Although performance for specific conductance 

remained consistent with historical levels, the data indicated a 

continuing decrease in the quality of onsite pH measurements 

compared to previous years.

Variability and bias in NADP/NTN data due to sample 

handling and shipping were estimated from paired sample concentration and specific conductance differences obtained for the 

blind-audit and SHE programs. For the 2002 blind audit, the 

median percentage bias for all analytes was within the range of 

-6.4 to 4.3 percent. The median percentage bias decreased for 

the SHE program during 2003 to a range of -5.2 to +2.9 percent, 

representing an approximate 2-percent decrease from the 2002 

blind-audit range.

The blind-audit results indicate that positive bias was 

introduced by sample handling, processing, and shipping at a 

level that was less than 10 percent of the median of the measured NADP/NTN constituent concentrations for calcium, 

ammonium, nitrate, sulfate, and specific conductance and at a 

level that was slightly more than 10 percent of the median 

NADP/NTN constituent concentrations for magnesium, 

sodium, potassium, and chloride concentrations. The blindaudit data also indicated that the absolute variability in 

hydrogen-ion concentration was 19 percent of the median NTN 

hydrogen-ion concentration for 2002. Negative bias in 

hydrogen-ion concentration and specific conductance measurements was attributed to hydrogen-ion buffering due to sample 

handling and shipping.
56 External Quality-Assurance Results for the National Atmospheric Deposition Program/National Trends Network, 2002–03

Table 17. Comparison of median absolute differences determined for collocated-sampler sites OK00/00OK and WI98/98WI during water 

year 2003 to median values obtained during 2002 for all National Atmospheric Deposition Program/National Trends Network sites and to 

median absolute differences for 41 collocated-sampler sites during 1989–2001.

[NADP/NTN, National Atmospheric Depsition Program/National Trends Network; mg/L, milligrams per liter; MAD, median absolute difference between collocated-sampler values; μeq/L, microequivalents per liter; μS/cm, microsiemens per centimeter at 25 degrees Celsius; mL, milliliters; cm, centimeters; --, no data]

Analyte

(units)

Median 2002 

NADP/NTN 

values1 (mg/L 

unless specified)

1Median values obtained for NADP/NTN during 2002 from Rothert (2004).

MAD results for 

OK00 

(mg/L unless 

specified)

OK00 MAD as a 

percentage of 

2002 median 

NADP/NTN 

values1

MAD results for 

WI98 

(mg/L unless 

specified)

WI98 MAD as a 

percentage of 

2002 median 

NADP/NTN 

values1

Median MAD for 

41 collocated 

sites 1989–20012

(mg/L unless 

specified)

2Data provided for comparison to MAD results from Wetherbee and others (2005).

Calcium 0.111 0.065 59 0.027 24 0.013

Magnesium .023 .004 17 .004 17 .003

Sodium .053 .008 15 .003 5.7 .013

Potassium .017 .006 35 .006 35 .004

Ammonium .240 .037 15 .045 19 .030

Chloride .108 .014 13 .011 10 .020

Nitrate 1.08 .124 11 .079 7.3 .068

Sulfate .998 .105 11 .076 7.6 .060

Hydrogen ion (μeq/L) 11 .34 3.1 .55 5.0 1.7

Specific conductance (μS/cm) 12 .90 7.5 .90 7.5 .95

Sample volume (mL) 960 17 1.8 9.5 1.0 26

Precipitation depth (cm) -- .01 -- .01 -- .51

Less variability attributed to sample handling, processing, 

and shipping was estimated by the SHE program than by the 

blind-audit program. The median paired differences for the 

SHE results were less than 10 percent of the median 

NADP/NTN values for 2002 except for hydrogen ion 

(10.5 percent). Error attributed to sample handling and shipping 

during 2003 was estimated to not be environmentally important 

to data users as indicated by the SHE results.

During the 2002–03 field-audit program, the median relative percentage bias for all analytes was within a range of -3.7 to 

+3.1 percent. Overall, positive bias was indicated for most constituents except hydrogen-ion concentration and specific conductance, which displayed negative bias. The negative bias in 

the paired difference data for hydrogen-ion concentration indicated that buffering of hydrogen ion occurred from onsite exposure of the sample and that the loss of hydrogen ion from 

solution was accompanied by a decrease in specific conductance. Therefore, NADP/NTN data tend to overestimate pH 

and underestimate specific conductance.

Analysis of field-audit ultrapure deionized-water sample 

results indicated potential low-level contamination of 

NADP/NTN samples with most of the major ions from onsite 

exposure and sample handling during the study period. A statistically significant (α=0.05) relation between the paired differences and sample volume was determined from the fieldaudit data for magnesium, nitrate, and sulfate during 2002 and 

for calcium, magnesium, sodium, chloride, nitrate, and sulfate 

concentration and specific conductance during 2003. Slightly 

less contamination was indicated during 2003 than during 2002 

except for ammonium. 

Variability and bias in NADP/NTN data from laboratory 

analysis of wet-deposition samples were evaluated during the 

study period by the interlaboratory-comparison program. CAL 

reported results with generally less variability than the other 

participating laboratories for all constituents except ammonium. The absolute values of the median differences reported 

by CAL were all less than or equal to MDLs (table 5) except for 

nitrate, sulfate, and specific conductance. The median differences for data reported by CAL for nitrate and sulfate were 

approximately three and five times their respective MDLs. The 

calcium, magnesium, and ammonium data reported by CAL 

were slightly negatively biased, and the sodium, potassium, 

chloride, nitrate, sulfate, hydrogen ion, and specific 

conductance data were slightly positively biased compared to 

other laboratories participating in the interlaboratorycomparison program. A small number of detections (one in 

2002 and two in 2003) in the ultrapure deionized-water samples 

indicated that contamination was not a problem for CAL, which 

implies that laboratory contamination did not affect 

NADP/NTN data during the study period.
Summary 57

Table 18. Comparison of components of overall variability in National Atmospheric Deposition Program/National Trends Network data as 

determined by U.S. Geological Survey external quality-assurance programs during 2002–03 for major ion concentrations and specific 

conductance.

Analyte

Variability as determined by median absolute error

Estimated overall 

variability1 

(percent)

(A)

1

Average median absolute error (MAE) values for sites OR02 and WI98 in 2002 and average MAEs for sites OK00 and WI98 in 2003 obtained from 

the collocated-sampler program (figs. 31–32).

Variability attributed to onsite 

exposure, sample handling, and 

laboratory analysis2 

(percent)

(B)

2

Combined onsite exposure, sample handling, and laboratory analysis MAEs obtained from the field-audit program (results for 2002 and 2003 

combined are reported in table 11).

Variability attributed to 

sample handling and 

laboratory analysis3 

(percent)

(C)

3

Combined sample handling and laboratory analysis MAEs obtained from the blind-audit program in 2002 (table 6) and from the sample-handling 

evaluation program in 2003 (table 8).

Variability attributed to 

laboratory analysis4 

(percent)

(D)

4

Median laboratory analysis variability calculated from analysis of synthetic precipitation sample replicates for the interlaboratory-comparison 

program. 

2002

Calcium 14.0 3.1 3.7 0.2

Magnesium 11.0 3.5 4.8 .3

Sodium 10.0 1.8 2.6 .2

Potassium 20.0 3.8 5.8 .4

Ammonium 20.0 4.5 5.4 0

Chloride 8.3 2.8 2.4 .2

Nitrate 4.9 1.3 1.3 .1

Sulfate 5.5 1.3 1.5 .1

Hydrogen ion 18.0 4.9 6.5 0

Specific conductance 6.7 5.4 3.3 0

2003

Calcium 10.0 5.0 2.8 .6

Magnesium 12.0 2.0 3.0 .2

Sodium 14.0 .9 1.8 .3

Potassium 34.0 6.9 2.6 .3

Ammonium 7.5 5.4 3.4 0

Chloride 14.0 2.9 1.2 .2

Nitrate 4.9 1.0 .76 .1

Sulfate 5.4 .4 .70 .1

Hydrogen ion 23.0 5.2 6.0 .6

Specific conductance 7.2 5.2 2.6 .1

MAD results obtained for replicate samples analyzed for 

hydrogen ion concentrations and specific conductance by CAL 

were less than 10 percent of the median values for 2002 

NADP/NTN concentration and specific conductance measurements. On the basis of this comparison, the absolute error introduced by laboratory analysis of hydrogen-ion concentration and 

specific conductance for NADP/NTN samples is not likely to be 

environmentally important to NADP/NTN data users. MAD 

results for all of the participating laboratories for cations generally were less than 0.005 mg/L during the study period, which 

is consistent with results for 2000–2001. However, MAD 

results for all participants for anions were less than 0.030 mg/L 

during the study period, compared to 0.020 mg/L during 2000–

2001.

Control charts indicate that most of the constituent concentration data reported by CAL were in statistical control approximately 90 percent of the time. CAL’s performance included 

brief time periods when magnesium, sodium, potassium, 

ammonium, chloride, nitrate, sulfate, and hydrogen-ion data 

were outside of the statistical control limits. The control chart 
58 External Quality-Assurance Results for the National Atmospheric Deposition Program/National Trends Network, 2002–03

Onsite instrumentation

and natural variability

64 percent

Laboratory analysis

2 percent Onsite exposure

8 percent

Sample handling

26 percent

Figure 33. Proportions of selected components of overall 

variability in National Atmospheric Deposition Program/ 

National Trends Network measurements as estimated by 

U.S. Geological Survey external quality-assurance 

programs during 2002–03.

data indicate that CAL’s precision was consistent with that of 

other laboratories performing analysis of low-ionic strength 

environmental samples. 

Overall variability of NADP/NTN measurements was 

evaluated from data collected in the collocated-sampler program. Weekly wet-deposition sample concentrations and precipitation measurements from three collocated NADP/NTN 

sites were compared. Estimates of precision were calculated in 

terms of MAE for concentration and deposition of ionic constituents of wet deposition. As in past years, MAEs were generally 

larger for cations (approximately 8 to 50 percent) than for 

anions (approximately 3 to 33 percent). MAEs were approximately 16 to 30 percent for hydrogen-ion concentration, less 

than 10 percent for specific conductance, less than 5 percent for 

sample volume, and less than 8 percent for precipitation depth. 

MAEs for constituent concentrations at collocated sites 

WI98/98WI generally increased between water years 2002 

and 2003.

The variability attributed to each component of the sample-collection and analysis processes, as estimated by USGS 

QA programs, varied among analytes. Laboratory analysis 

variability accounted for approximately 2 percent of the overall 

variability in NADP/NTN measurements. Sample onsite 

exposure accounted for approximately 8 percent of the overall 

variability. Sample handling accounted for approximately 

26 percent of the estimated overall variability. The remaining 

variability not accounted for by laboratory analysis, onsite 

exposure, and sample handling (approximately 64 percent) was 

attributed to onsite instrumentation and natural variability.

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