U.S. Department of the Interior

U.S. Geological Survey

Scientific Investigations Report 2020–5084

External Quality Assurance Project Report for the National 

Atmospheric Deposition Program’s National Trends Network 

and Mercury Deposition Network, 2017–18
Cover. National Atmospheric Deposition Program, National Trends Network sites CO86, Rocky Flats 

National Wildlife Refuge, Jefferson County, Colorado. (Photograph taken by Gregory A. Wetherbee, 

U.S. Geological Survey)
External Quality Assurance Project Report 

for the National Atmospheric Deposition 

Program’s National Trends Network and 

Mercury Deposition Network, 2017–18

By Gregory A. Wetherbee and RoseAnn Martin

Scientific Investigations Report 2020–5084

U.S. Department of the Interior

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

DAVID BERNHARDT, Secretary

U.S. Geological Survey

James F. Reilly II, Director

U.S. Geological Survey, Reston, Virginia: 2020

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Suggested citation:

Wetherbee, G.A., and Martin, R., 2020, External quality assurance project report for the National Atmospheric 

Deposition Program’s National Trends Network and Mercury Deposition Network, 2017–18: U.S. Geological Survey 

Scientific Investigations Report 2020–5084, 31 p., https://doi.org/10.3133/sir20205084.

Associated data for this publication:

Wetherbee, G.A., 2020, U.S. Geological Survey Precipitation Chemistry Quality Assurance Project Data 2017–2018: 

U.S. Geological Survey data release, https://doi.org/10.5066/P9ZKXD8N.

Wetherbee, G.A., 2019, Data for the U.S. Geological Survey Precipitation Chemistry Quality Assurance Project for the 

National Atmospheric Deposition Program, 1978–2017: U.S. Geological Survey data release, https://doi.org/10.5066/

P94RC4GD. 

ISSN 2328-0328 (online)
iii

Contents

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

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

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

Statistical Methods........................................................................................................................................2

National Trends Network Quality Assurance Programs .........................................................................3

Field Audit Program ..............................................................................................................................3

Network Maximum Contamination Levels ........................................................................................3

Analyte Losses ......................................................................................................................................4

National Trends Network Interlaboratory Comparison Program ..................................................4

Interlaboratory Comparison Program Bias and Variability ............................................................7

Interlaboratory Comparison Program Control Charts .....................................................................7

Colocated Sampler Program .............................................................................................................17

Mercury Deposition Network Quality Assurance Programs ................................................................22

System Blank Program.......................................................................................................................22

Network Maximum Contamination Levels for Mercury ...............................................................23

Mass of Mercury Contamination .....................................................................................................25

Mercury Deposition Network Interlaboratory Comparison Program ........................................25

Control Charts ......................................................................................................................................25

Interlaboratory Variability and Bias ........................................................................................25

Results for Blanks ...............................................................................................................................28

Summary........................................................................................................................................................28

National Trends Network ...................................................................................................................28

Mercury Deposition Network ...........................................................................................................29

References Cited..........................................................................................................................................29

Figures

1. Graph showing distributions of upper confidence limits for sodium 

contamination concentrations measured by the field audit program, 2016–18 .................5

2. Graph showing network maximum contamination levels for National Trends 

Network analytes calculated using 3-year moving increments, 1997–2018 .......................5

3. Graphs showing maximum loss of hydrogen ion and ammonium and nitrate 

from weekly National Trends Network samples calculated using 3-year moving 

increments, 1997–2018 .................................................................................................................6

4. Graphs showing differences between concentration values reported by the 

Central Analytical Laboratories and the median concentration values for all 

participating laboratories in the interlaboratory comparison program for the 

National Trends Network, 2017–18 ..........................................................................................19

5. Graph showing differences between total mercury concentrations reported 

by the Mercury Analytical Laboratory, Eurofins Frontier Global Sciences, Inc., 

and the median concentration values for all participating laboratories in the 

interlaboratory comparison program for the Mercury Deposition Network, 2017–18 ....26
iv

Tables

1. National Atmospheric Deposition Program’s National Trends Network method 

detection limits, network maximum contamination levels, and analyte losses 

estimated from field audit samples in addition to calculated concentration 

quartiles for all valid monitoring data, 2015–18 .......................................................................4

2. Analyte most probable values for synthetic precipitation solutions used in the 

2017–18 National Trends Network interlaboratory comparison program ...........................8

3. Analytical detection limits for laboratories participating in the U.S. Geological 

Survey interlaboratory-comparison program for the National Atmospheric 

Deposition Program, 2017–18 .....................................................................................................8

4. Median differences between reported constituent concentrations and most 

probable values for synthetic wet-deposition samples, 2017 interlaboratory 

comparison program ....................................................................................................................9

5. Median differences between reported constituent concentrations and most 

probable values for synthetic wet-deposition samples, 2018 interlaboratory 

comparison program ..................................................................................................................13

6. Number of analyte determinations greater than the method detection limits for 

deionized water samples, 2017–18 ..........................................................................................17

7. Number of analyte determinations outside ±3 f-pseudosigma statistical control 

limits, by participating laboratory, 2017–18 ............................................................................18

8. Overall median relative bias and sign test results for comparison of 75 National 

Atmospheric Deposition Program split samples analyzed by the former Central 

Analytical Laboratory at the Illinois State Water Survey (ICAL) and current 

Central Analytical Laboratory at the University of Wisconsin (WCAL) .............................22

9. Median weekly constituent concentration differences and annual deposition 

differences for colocated N–CON Systems Company, Inc. precipitation 

collectors at National Atmospheric Deposition Program sites CO11 and 11CO 

for all valid samples, water years 2017–18 .............................................................................23

10. Event recorder data summary for colocated N–CON Systems Company, Inc., 

precipitation collectors at National Atmospheric Deposition Program sites 

CO11 and 11CO, water years 2017–18 .....................................................................................24

11. Three-year moving network maximum contamination levels and 90-percent 

upper confidence limits at the 50th, 75th, and 90th percentiles of total mercury 

contamination mass in system blank samples, 2004–17 ......................................................24

12. Most probable values for total mercury in four solutions and hydrochloric 

acid blank samples used for the U.S. Geological Survey Mercury Deposition 

Network interlaboratory comparison program, 2017–18 .....................................................26

13. Differences between reported concentrations and most probable values for 

total mercury determinations, Mercury Deposition Network interlaboratory 

comparison program, 2017–18 ..................................................................................................27

14. Number of total mercury determinations greater than the method detection 

limits for blank samples, Mercury Deposition Network interlaboratory 

comparison program, 2017–18 ..................................................................................................28
v

Conversion Factors

International System of Units to Inch/Pound

Multiply By To obtain

Length

centimeter (cm) 0.3937 inch (in.)

Volume

liter (L) 1.057 quart (qt)

milliliter (mL) 0.03381 ounce, fluid (oz)

Application rate

kilogram per hectare (kg/ha) 0.8264 pound per acre (lb/acre)

Concentration

milligram per liter (mg/L) 3.34x10-5 ounce per quart (oz/qt)

nanogram per liter (ng/L) 3.34x10-11 ounce per quart (oz/qt)

microgram per liter (μg/L) 3.34x10-8 ounce per quart (oz/qt)

Temperature in degrees Celsius (°C) may be converted to degrees Fahrenheit (°F) as 

 °F = (1.8 × °C) + 32.

Temperature in degrees Fahrenheit (°F) may be converted to degrees Celsius (°C) as 

 °C = (°F–32) / 1.8.

Supplemental Information

Specific conductance is given in microsiemens per centimeter at 25 degrees Celsius (μS/cm 

at 25 °C).

Concentrations of chemical constituents in water are given in either milligrams per liter (mg/L), 

micrograms per liter (μg/L) or nanograms per liter (ng/L).

α, alpha, is the maximum probability of incorrect rejection of the null hypothesis.

100(p)th is the percentile equal to 100 times a value of p, for example, 100 × (.9) = 90th percentile.

Absolute value of x = |x|, where x takes the form of numerical values or algebraic expressions.

Study period, calendar year or water years 2017–18, depending on the program.

Water year (WY) is the 12-month period from October 1 through September 30 of the following 

year and is designated by the calendar year in which it ends.
vi

Abbreviations

ACM AeroChem Metrics Model 301 collector

ACAP Asia Center for Air Pollution Research

AIRMoN Atmospheric Integrated Research Monitoring Network

AMEC AMEC Foster Wheeler for 2014, formerly AMEC, Inc. in 2013

CAL Central Analytical Laboratory

CASIG Chinese Academy of Sciences, Institute of Geochemistry (People’s Republic 

of China)

CIES Carey Institute of Ecosystem Studies

CVAFS Cold vapor atomic fluorescence spectroscopy

DASNCU Department of Atmospheric Sciences, National Central University (Taiwan)

ECST Environment and Climate Change Canada (formerly [2015–16] Environment 

Canada) Science and Technology Branch

ETI Noah IV Environmental Technologies, Inc. Noah IV precipitation gage

f-psig f-pseudosigma

FRL Flett Research, Limited (Canada)

HAL Mercury Analytical Laboratory, Eurofins Frontier Global Sciences, Inc.

HCl hydrochloric acid

Hg mercury

ICAL Central Analytical Laboratory, University of Illinois, Illinois State Water Survey

ISWS Illinois State Water Survey

IVL IVL Swedish Environmental Research Institute (Sweden)

LEEQ Quebec Laboratory for Environmental Testing (Canada), also known as QLET

MDL method detection limit

MDN Mercury Deposition Network

MOECC Ministry of Environment and Climate Change—Dorset Chemistry 

Laboratory (Canada)

MPV most probable value

MRL minimum reporting level

NADP National Atmospheric Deposition Program

N–CON N–CON Systems Company, Inc.

NILU Norwegian Institute for Air Research (Norway)

NIST National Institute of Standards and Technology

NMCL network maximum contamination level

Noah IV Environmental Technologies, Inc. Noah IV precipitation gage
vii

NRS U.S. Department of Agriculture Forest Service, Northern Research Station, 

Durham, New Hampshire

NSA North Shore Analytical, Inc.

NTN National Trends Network

PCQA Precipitation Chemistry Quality Assurance project

PO Program Office for National Atmospheric Deposition Program

QA quality assurance

RTI Research Triangle Institute, International

RVP Readiness Verification Plan

UCL upper confidence limit

UNAM Universidad Nacional Autonoma de Mexico, Centro de Ciencias de la 

Atmosfera (University of Mexico, Center for Atmospheric Sciences, Mexico 

City, Mexico)

USGS U.S. Geological Survey

VITO Flemish Institute for Technological Research (Belgium)

WCAL Central Analytical Laboratory, University of Wisconsin, Wisconsin State 

Laboratory of Hygiene

WML U.S. Geological Survey Wisconsin Mercury Laboratory

WSLH Wisconsin State Laboratory of Hygiene, University of Wisconsin, Madison

External Quality Assurance Project Report for the National 

Atmospheric Deposition Program’s National Trends 

Network and Mercury Deposition Network, 2017–18

By Gregory A. Wetherbee and RoseAnn Martin

Abstract

The U.S. Geological Survey (USGS) Precipitation 

Chemistry Quality Assurance project (PCQA) operated five 

distinct programs to provide external quality-assurance monitoring for the National Atmospheric Deposition Program’s 

(NADP) National Trends Network and Mercury Deposition 

Network during 2017–18. The National Trends Network 

programs included (1) a field audit program to evaluate sample 

contamination and stability, (2) an interlaboratory comparison 

program to evaluate analytical laboratory performance, and (3) 

a colocated sampler program to evaluate variability attributed 

to automated precipitation samplers. The Mercury Deposition 

Network programs include the (4) system blank program and 

(5) an interlaboratory comparison program. The results indicate consistently low levels of sample contamination, generally strong analytical laboratory performance, and low overall 

variability in concentration data imparted by field equipment. 

The NADP operations moved from its 40-year home at the 

Illinois State Water Survey to the Wisconsin State Laboratory 

of Hygiene in June 2018. The PCQA programs were modified 

and (or) temporarily curtailed during the transition in 2018. 

Bias and variability of sample analysis results were evaluated for the two Central Analytical Laboratories, and ongoing 

monitoring will be helpful to differentiate true environmental 

signals from the effects of changing laboratory conditions and 

performance. Results of quality assurance sample analyses are 

provided to document that NADP data continue to be of sufficient quality for the analysis of spatial distributions and time 

trends for chemical constituents in wet deposition.

Introduction

The U.S. Geological Survey (USGS) Precipitation 

Chemistry Quality Assurance project (PCQA) ensures that the 

National Atmospheric Deposition Program (NADP) provides 

data users with long-term, known-quality atmospheric wetdeposition information. As of 2019, the project is administered by the USGS Observing Systems Division, Hydrologic 

Networks Branch in Denver, Colorado. Quality assurance 

(QA) results obtained by PCQA and presented in this report 

allow investigators to account for inherent variability and bias 

in NADP data potentially introduced by sample collection, 

processing, and laboratory analysis. The QA results obtained 

by PCQA also allow investigators to identify and quantify true 

environmental signals.

Purpose and Scope

The NADP incorporated three wet-deposition monitoring networks in 2017–18: (1) the National Trends Network 

(NTN), (2) the Mercury Deposition Network (MDN), and (3) 

the Atmospheric Integrated Research Monitoring Network 

(AIRMoN). This report updates the independent assessment of 

NADP data quality using PCQA results obtained for calendar 

years and water years 2017–18 (study period) for the NTN 

and MDN. Results obtained in previous years are used for 

comparison.

The field audit program and the system blank program 

assessed the effects of onsite exposure, sample handling, and 

shipping on the chemistry of NTN and MDN samples, respectively. Two interlaboratory comparison programs assessed the 

bias and variability of chemical analysis data from the Central 

Analytical Laboratories (CAL) at Illinois State Water Survey 

(ISWS), Champaign, Illinois, during 2017 and at Wisconsin 

State Laboratory of Hygiene (WSLH), Madison, Wisconsin, 

during 2018 and the Mercury Analytical Laboratory (HAL) at 

Eurofins Frontier Global Sciences, Inc., Bothell, Washington. 

The variability of NTN results was assessed using the colocated sampler program during water years 2017–18. Detailed 

information on USGS QA procedures and analytical methods 

for the NTN and MDN is available in Latysh and Wetherbee 

(2005, 2007) and Wetherbee and Martin (2016a).

Most of the PCQA programs are operated on a calendaryear basis, but the colocated sampler program is operated on 

a water-year basis. Each water year extends from October 1 

through September 30 of the following year and is designated 

by the calendar year in which it ends. Monitoring sites for the 

colocated sampler program consist of two precipitation-sample 

collectors and a continuously recording precipitation gage. 
2 External Quality Assurance Project Report for the National Trends Network and Mercury Deposition Network, 2017–18

During water years 2017–18, the colocated sampler program 

assessed the variability in NADP data obtained from N–CON 

collectors at the CO11 and 11CO sites colocated at the Arvada 

Community Gardens, Arvada, Colorado.

Statistical Methods

In this report, nonparametric, rank-based statistical 

methods are used in place of traditional statistics and hypothesis testing. The sign test (Kanji, 2006) was used to evaluate 

whether the median of differences between two groups is 

significantly different from zero. Network maximum contamination levels were evaluated at the 90-percent significance 

level (alpha [α]=0.10). Other statistical tests were evaluated 

at the 95-percent significance level (α=0.05), unless otherwise noted. Statistical analysis was performed using SAS 

version 9.4 software (SAS Institute Inc., 2016) and R version 3.5.2 (R Development Core Team, 2018).

Bias was quantified using relative and absolute differences and percent differences (Wetherbee and others, 2010). 

These parameters are calculated for each program, as follows:

Relative difference = Cn-Cc, (1)

Absolute difference = |Cn-Cc|, (2)

Relative percentage difference (RPD) 

= [(Cn-Cc)/Ct] × 100, and (3)

Absolute percentage difference (APD) 

= |(Cn-Cc)/Ct| × 100 (4)

where

Cn is the sample concentration, in milligrams 

per liter or nanograms per liter, for the 

test sample, or precipitation depth in 

centimeters;

Cc is the sample concentration, in milligrams 

per liter or nanograms per liter, for the 

control sample or precipitation depth in 

centimeters; and

Ct is either Cc (field audit and system blank 

programs), a most probable target value 

(interlaboratory comparison programs), 

or the mean of Cn and Cc for replicate 

measurements using identical precipitation 

gages (colocated sampler program).

Variability was quantified in this report using 

f-pseudosigma (f-psig), a nonparametric analog of the standard

deviation of a statistical sample (Hoaglin and others, 1983):

f -pseudosigma = 75th percentile − 25th percentile

1 349. (5)

The f-pseudosigma ratio (f-psig ratio) was also used to compare the variability of an entire dataset with the variability of 

a subset:

f psig ratio fpsig

fpsigo

  



 



 subset (6)

where

fpsigsubset is the f-pseudosigma of the subset and

fpsigo is the overall f-pseudosigma of the 

entire dataset.

An f-psig ratio less than 1 indicates less variability in the 

subset than in the entire dataset, and an f-psig ratio greater 

than 1 indicates more variability in the subset than in the 

entire dataset.

Maximum contamination levels and precipitation-sample 

stability were determined by a calculation of upper confidence 

limits (UCL) on percentiles of concentration data using a 

binomial distribution (Hahn and Meeker, 1991). Their book 

describes a method for determining a distribution-free UCL 

for a percentile, which is appropriate for skewed data. This 

method uses order statistics, which are based on ranking the 

data from lowest to highest and applying binomial probability 

to determine the UCL. More detail is provided in Wetherbee 

and Martin (2016b).

Before determining contamination levels, concentrations 

less than the method detection limit (MDL) were changed to 

one-half the MDL. Helsel (2012) shows how such substitution 

leads to bias in hypothesis tests and calculation of statistical 

locations, but for this report, the substitution of one-half the 

detection limit had a minor effect on calculated percentiles 

because the percentage of censored values was typically less 

than 25 percent and was seen to have no discernable effect 

on quantification of the medians and interquartile ranges. 

Therefore, one-half the MDL was a convenient substitution 

for purposes of capturing reasonable estimates of bias and 

variability using the nonparametric methods described by 

Gibbons and Coleman (2001) for the Field Audit and System 

Blank data.

For the interlaboratory comparison program data, most 

probable values (MPVs) for concentrations of solutes in split 

samples of natural and synthetic rainwater solutions were 

calculated as the median concentrations for each analyte in 

each unique solution. The MPVs were calculated using the 

Not Above Detection Analysis (NADA) package in R to incorporate values below analytical detection limits. The NADA 
National Trends Network Quality Assurance Programs 3

package uses survival-analysis techniques, such as the KaplanMeier method, to properly include censored values reported as 

less than analytical detection limits. The Kaplan-Meier method 

uses the empirical distribution functions of the positively 

skewed datasets, which are flipped end-to-end to plot the 

probabilities of exceedance of the observations. The method 

calculates the survival function probability (S) of “surviving” 

to the next lowest uncensored concentration, given the number 

of data at or below that concentration. A complete explanation 

is provided by Helsel (2012).

Colocated precipitation collectors generated pairs of replicate measurements of the same parameters at the same time 

and place to assess the overall variability of NADP results. 

The variability estimates are useful for verification of trends 

in NADP data. More detailed descriptions can be found in 

Wetherbee and others (2005a, 2006, 2009, 2010).

Data used to support the conclusions presented in this 

report are publicly available through two USGS data releases 

(Wetherbee, 2019, 2020).

National Trends Network Quality 

Assurance Programs

Field Audit Program

The field audit program uses equipment-rinse samples 

(bucket samples) paired with corresponding deionized water 

or synthetic precipitation solutions (bottle samples) to identify 

changes to chemical concentrations in NTN wet-deposition 

samples resulting from field exposure of the sample-collection 

apparatus (Latysh and Wetherbee, 2005; Wetherbee and others, 

2010; Wetherbee and Martin, 2016a). After a week without 

wet deposition, site operators pour 75 percent of the volume 

of their field audit solution into the sample bucket and seal the 

bucket with a lid for 24 hours prior to decanting the solution 

to a clean sample bottle (bucket sample). The 25 percent of 

the field audit sample volume that remains in the sample bottle 

(bottle sample) never contacts any field sampling materials.

Contamination can be introduced to NADP samples 

by dissolution of materials residing on the bucket walls. In 

contrast, loss of dissolved constituents from the solution is 

possible through adsorption into the bucket walls. Dissolved 

constituents from the solution can also be lost through other 

chemical or biological processes. Contamination and sample 

stability are evaluated for network data by statistical analysis 

of paired “bucket-minus-bottle” concentration differences for 

field audit samples.

An NADP site operator who either processed and submitted a field audit sample to CAL or notified the USGS that an 

attempt was made to process the field audit sample during 

the year was considered to have participated in the field audit 

program. Field audit samples were shipped to 100 different 

sites in 2017. Shipment of field audit program samples was 

suspended in 2018 due to the transition of NADP operations 

from the ISWS to the WSLH. During 2017, 67 sites processed 

samples. During 2018, 9 sites processed samples that they 

received in 2016 or 2017. Data for a total of 76 complete pairs 

of field-audit samples were received from the CAL for the 

study period.

Network Maximum Contamination Levels

Using the binomial probability distribution function in 

SAS (SAS Institute, Inc., 2016) maximum concentrations of 

contaminants in NTN samples, with statistical confidence, 

were estimated using the 90-, 95-, and 99-percent UCLs for 

selected percentiles of the field audit, bucket-minus-bottle 

paired differences. As an example of the cumulative distributions for the UCLs, the 2016–18 results for sodium contamination concentrations are shown in figure 1. The 90-percent 

UCLs for the 90th percentiles of field-audit-paired concentration differences are calculated for each analyte, and these 

values are considered the network maximum contamination 

levels (NMCLs). The NMCLs serve as practical lower limits 

of quantitation for network-measured wet-deposition of 

chemical constituents (Wetherbee and others, 2010, 2013). The 

NMCLs are calculated for 3-year moving periods of time, but 

only 9 samples were processed and analyzed in 2018 (table 1).

The NMCL can be defined in three ways: (1) the NMCL 

is the maximum contamination expected in 90 percent of the 

samples with 90-percent confidence, (2) there is a 10-percent 

chance that contamination in NTN samples has been underestimated at the NMCL, or (3) there is 90-percent confidence 

that the contamination would exceed the NMCL in 10 percent 

of the NTN samples.

The 25th and 75th percentile values for all 2016–18 

NTN monitoring data (Robert Larson, NADP Program Office, 

Wisconsin State Laboratory of Hygiene, written commun., 

2019) are compared to estimated annual NMCLs in table 1. 

Trends in the NMCLs are illustrated for each analyte in 

figure 2. The NMCLs for calcium, magnesium, sodium, 

ammonium, and chloride have not changed appreciably since 

2014, whereas the NMCL for potassium decreased approximately -0.003 mg/L during 2015–18. The NMCLs for nitrate 

and sulfate increased by approximately 0.01 mg/L (2015–17) 

and then decreased again (2016–18) to levels lower than 

those measured during 2014–2016. These varying levels of 

sample contamination are small in terms of their absolute 

concentrations. However, the 2016–18 NMCLs for calcium, 

magnesium, sodium, and potassium were equivalent to the 

22nd, 26th, 20th, and 13th percentile concentrations, respectively, in NADP samples during the same period. Any NTN 

concentrations lower than the NMCLs cannot be differentiated from contamination. In other words, the lower 22 percent 

of all NTN calcium concentrations cannot be differentiated 

from contamination, and so on. The ammonium NMCL 

(0.030 mg/L) was at the 14th percentile of NTN data values. 

The NMCLs for chloride (0.022 mg/L), nitrate (0.071 mg/L), 
4 External Quality Assurance Project Report for the National Trends Network and Mercury Deposition Network, 2017–18

Table 1. National Atmospheric Deposition Program’s National Trends Network method detection limits, network maximum 

contamination levels, and analyte losses estimated from field audit samples in addition to calculated concentration quartiles for all valid 

monitoring data, 2015–18.

[NTN, National Trends Network; MDL, method detection limit; NMCL, network maximum contamination level; NADP NTN, National Atmospheric Deposition 

Program National Trends Network; Q1, 25th percentile; Q3, 75th percentile; all units in milligrams per liter except hydrogen ion (microequivalents per liter); 

n.d., no data; p>|M|], sign test p-value, probability of rejecting the null hypothesis: “The true median of the differences between laboratory results and the most 

probable value is zero,” when true]

Analyte

NTN Method 

detection limits 

(MDL)

Estimated 

network maximum contamination 

level (NMCL)2

2015–17

Estimated network maximum 

contamination 

level (NMCL)1, 2 

2016–18

Median 

concentration 

difference 

(units) 

2016–18

Sign test 

p>|M| 

2016–18

Maximum 

analyte 

loss3

2016–18

Valid 2016–18 NADP NTN 

data quartile values4

2017 12018 Q1 Median Q3

Calcium 0.002 0.011 0.041 0.042 0.005 <0.001 0.004 0.048 0.109 0.252

Magnesium 0.001 0.003 0.009 0.011 0.001 <0.001 0.002 0.010 0.023 0.048

Sodium 0.001 0.005 0.015 0.015 0.001 <0.001 0.005 0.019 0.051 0.151

Potassium 0.001 0.005 0.007 0.007 0.000 <0.001 0.001 0.011 0.021 0.041

Ammonium 0.008 0.009 0.030 0.030 0.004 0.072 0.020 0.113 0.256 0.514

Chloride 0.003 0.006 0.024 0.022 0.002 <0.001 0.006 0.041 0.089 0.250

Nitrate 0.005 0.008 0.095 0.071 0.003 <0.001 0.007 0.360 0.653 1.098

Sulfate 0.005 0.007 0.067 0.054 0.002 <0.001 0.013 0.226 0.411 0.694

Hydrogen ion n.d. n.d. 1.25 1.11 −0.320 <0.001 2.50 1.148 3.891 7.244

1Higher of the two MDLs reported by each Central Analytical Laboratory in 2018.

2Calculated as the 90-percent upper confidence limits for the 90th percentiles of 2016–18 field audit paired differences using the binomial distribution function 

in SAS (SAS Institute, Inc., 2001), where differences are calculated as bucket-minus-bottle.

3Calculated as the 90-percent upper confidence limits for the 90th percentiles of 2016–18 field audit paired differences using the binomial distribution function 

in SAS (SAS Institute, Inc., 2001), where differences are calculated as bottle-minus-bucket.

4Data for all valid 2016–18 NTN samples obtained from Robert Larson (Wisconsin State Laboratory of Hygiene, University of Wisconsin, written commun., 

2019).

and sulfate (0.054 mg/L), were at the 9th, 2nd, and 2nd NTN 

concentration percentiles, respectively. Therefore, contamination for anions is lower than for cations.

Analyte Losses

Maximum values for analyte losses were the same for the 

2015–17 and 2016–18 periods (fig. 3A and 3B). Nitrate loss 

was similar to the 2017–18 MDLs, which indicates that nitrate 

losses from NTN samples were small (table 1). Ammonium 

loss increased from 0.010 mg/L (2014–2016) to 0.020 mg/L 

(2015–2017), which is approximately 2.2 times the 2018 MDL 

for ammonium (0.009 mg/L). Hydrogen ion maximum loss 

was 2.50 microequivalents per liter (μeq/L), which has not 

changed since 2014. These values are considered to represent 

the maximum expected losses of ammonium, nitrate, and 

hydrogen ion from NTN samples with 90 percent confidence.

National Trends Network Interlaboratory 

Comparison Program

The standing objectives of the NTN interlaboratory comparison program are to (1) estimate the variability and bias in 

data reported by CAL and other participating laboratories and 

(2) facilitate integration of data from various wet-deposition 

monitoring networks without any attempt to account for 

the different onsite protocols used by different monitoring 

networks. Eleven laboratories participated in the interlaboratory comparison program during 2017–18: (1) Asia Center 

for Air Pollution Research (ACAP) in Niigata-shi, Japan; (2) 

NADP CAL, Illinois State Water Survey, in Champaign, Ill., 

(ICAL); (3) AMEC Foster Wheeler, Inc. (AMEC), renamed 

Wood Group, Inc. (WOOD), in Gainesville, Florida; (4) 

Ontario Ministry of Environment and Climate Change–Dorset 

Chemistry Laboratory (MOECC), in Dorset, Ontario, Canada; 

(5) Environment and Climate Change Canada, Science and 

Technology Branch (ECST) in Downsview, Ontario, Canada; 

(6) Norwegian Institute for Air Research (NILU) in Kjeller, 

Norway; (7) Carey Institute of Ecosystem Studies (CIES), 

in Millbrook, New York; (8) U.S. Department of Agriculture 
National Trends Network Quality Assurance Programs 5

Forest Service, Northern Research Station (NRS), in Durham, 

New Hampshire; (9) RTI International (RTI), in Research 

Triangle Park, North Carolina, (10) Universidad Nacional 

Autonoma de Mexico (UNAM), Centro de Ciencias de la 

Atmosfera, in Mexico City, Mexico; and (11) NADP CAL, 

Wisconsin State Laboratory of Hygiene, in Madison, Wisc. 

(WCAL). The WCAL began participation in October 2017.

Each of the participating laboratories received four 

samples from PCQA every month for chemical analysis. The 

three types of samples used in the interlaboratory comparison 

program included (1) synthetic standard reference samples 

prepared by PCQA, which are traceable to National Institute 

of Standards and Technology (NIST) reference materials 

(NIST-traceable materials); (2) de-ionized water blank samples 

prepared by PCQA; and (3) natural wet-deposition samples 

collected at NTN sites, blended by CAL, and sent to PCQA 

for shipping to the laboratories as blind samples (Wetherbee 

and Martin, 2016a). Synthetic precipitation samples used in 

the interlaboratory comparison program were made from stock 

solutions prepared by High Purity Standards, Charleston, 

South Carolina. Natural samples were filtered through 

0.45-micrometer filters; bottled in 60-, 125-, and 250-milliliter 

polyethylene bottles by CAL; and shipped in chilled, insulated containers to the PCQA to enhance stability of nutrient 

Upper confidence limits

90 percent

99 percent

95 percent

EXPLANATION

Detection limit, 0.004 mg/L

90 percent upper confidence 

limit on 90th percentile, 

considered the network 

maximum contamination 

level, 0.015 mg/L

Sodium concentration, in milligrams per liter (mg/L)

0

0.02 

0.04 

0.06 

0.08 

Percentile

10 20 30 40 50 60 70 80 90 100

Figure 1. Distributions of upper confidence limits for sodium 

contamination concentrations measured by the field audit 

program, 2016–18.

0

0.01

0.02

0.03

0.04

0.05

0.06

0.07

0.08

0.09

0.1

Network maximum contamination level, in milligrams per liter

Calcium Magnesium Sodium Potassium Ammonium Chloride Nitrate Sulfate

EXPLANATION

Each set of bars represents calendar years 1997–2018, in 3-year moving increments. Red bars are years 2015–2018

Figure 2. Network maximum contamination levels for National Trends Network analytes calculated using 3-year moving increments, 

1997–2018.
6 External Quality Assurance Project Report for the National Trends Network and Mercury Deposition Network, 2017–18

A

0.0

1997–991998–001999–012000–022001–032002–04

2003–05

2004–06

2005–07

2006–082007–09

2008–10

2009–11

2010–122011–132012–14

2013–15

2014–16

2015–17

2016–18

2016–18

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

Network maximum hydrogen ion loss, in microequivalents per liter

Date

B

EXPLANATION

Each set of bars represents calendar years 1997–2018, in 3-year moving increments. Red bars are years 2015–2018

Network maximum analyte loss, in milligrams per liter

2015–18

2015–18

1997–2018

0.000

0.025

0.075

Ammonium Nitrate

Figure 3. Maximum loss of A, hydrogen ion and B, ammonium and nitrate from weekly National Trends Network samples calculated 

using 3-year moving increments, 1997–2018. 
National Trends Network Quality Assurance Programs 7

analytes—ammonium, nitrate, and sulfate—in the samples 

(Tchobanoglous and Schroeder, 1987; U.S. Geological 

Survey, 2002).

Median concentrations of calcium, magnesium, sodium, 

potassium, ammonium, chloride, nitrate, sulfate, bromide, and 

hydrogen ion and median specific conductance were computed 

by solution from the data submitted by all participating laboratories. The median values were considered to be equal to the 

most probable values (MPVs). Censored concentration values 

reported as less than the MDL were included in the estimation 

of MPVs for each solution using the Kaplan Meier method 

(Helsel, 2012). The largest percentages of censored concentration values observed for this program during 2017–18 were 

for magnesium and potassium, most commonly with natural 

wet-deposition samples.

The MPVs for the synthetic precipitation solutions and 

the number of samples analyzed per solution are listed in 

table 2 by solution identifier: SP2B, SP21B, SP22B. Data 

from each laboratory were compared against these MPVs to 

evaluate bias. Only ICAL, NRS, CIES, and WCAL analyzed 

the samples for bromide. The RTI laboratory routinely analyzed the samples only for chloride, nitrate, and sulfate plus 

16 samples for sodium, potassium, and ammonium in 2018. 

The ECST, NRS, and RTI laboratories did not analyze the 

samples for specific conductance. The NRS and RTI laboratories did not measure pH for any of the samples. Data are missing for: AMEC in December 2017, ECST in September 2018, 

MOECC in November 2018, NRS in December of 2017 and 

2018, and UNAM in November and December 2018 due to 

shipping problems.

Interlaboratory Comparison Program Bias and 

Variability

Interlaboratory bias for the participating laboratories 

was evaluated using 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 de-ionized water samples. The arithmetic signs of the median differences indicate 

whether the reported results for each constituent are positively 

or negatively biased. The sign test null hypothesis is the true 

median of the reported-minus-MPV differences is zero. Test 

results were evaluated at the α=0.05 significance level for a 

two-tailed test.

Calculated variation between laboratories was compared 

using the f-psig ratios (eq. 6). Analytical detection limits 

are reported for each laboratory in table 3. Results for variability and bias within the analytical data reported by each of 

the participating laboratories are presented in tables 4 and 5. 

Shaded values in tables 4 and 5 identify analytes for which 

bias was found to be both statistically (α=0.05) and practically significant. For this program, statistically significant bias 

was determined to be of practical significance only when the 

absolute value of the median relative concentration difference was greater than the participating laboratory’s analytical 

method detection limit (table 3).

During 2017, significant bias above the detection limits 

was observed for ICAL (calcium, potassium, and ammonium), 

MOECC (nitrate), ECST (sodium), NILU (nitrate), NRS 

(sodium, chloride, and bromide), CIES (calcium, sodium, 

potassium, nitrate, and sulfate), RTI (nitrate), WCAL (chloride), and UNAM (nitrate and sulfate) (table 4). During 

2018, significant bias above the method detection limits was 

identified for ACAP (sodium), ICAL (calcium and potassium), 

MOECC (nitrate), ECST (sodium), NILU (nitrate), NRS 

(sodium, chloride, and bromide), CIES (calcium, sodium, 

bromide, and nitrate), RTI (ammonium), WCAL (chloride), 

and UNAM (nitrate and sulfate) (table 5). The ECST, ICAL, 

AMEC/WOOD, RTI, and WCAL laboratories had comparable, low overall variability among the participating laboratories during 2017–18 as indicated by most f-psig ratios less 

than 1.00 (tables 4 and 5).

Four de-ionized water blank samples were analyzed 

annually by each laboratory. A summary of results for the 

blanks is shown in table 6. No results were reported above 

analytical detection limits for blank samples for the ECST, 

NILU, RTI, UNAM, and AMEC/WOOD laboratories during 

2017–18. The ACAP laboratory reported detections for all 

constituents in 2018 for at least two blanks per analyte. The 

ICAL reported detections for potassium and ammonium in 

2 blanks in 2017 and for calcium (1), magnesium (1), potassium (2), ammonium (1), and chloride (1) in 2018. The ECST 

laboratory reported no detections of analytes in blanks for 

2017 and detections for calcium (1), sodium (1), and potassium (2) in 2018. The MOECC laboratory reported detections 

in blanks for calcium (4), potassium (2), ammonium (5), 

chloride (2), nitrate (3), and sulfate (2) during 2017–18. The 

NRS laboratory reported detections in blanks for calcium (2), 

magnesium (1), sodium (1), potassium (4), ammonium (1), 

chloride (2), nitrate (3), and sulfate (2) for 2017–18 combined. 

The WCAL reported a detection for magnesium in a blank 

during 2018 and analyzed no blanks in 2017.

Interlaboratory Comparison Program Control 

Charts

Each participating laboratory’s results were compared to 

the MPVs over time in control charts. Analyte determinations 

that exceeded the control limits (± 3 f-psig) during 2017–18 

are summarized in table 7. Each laboratory was provided with 

its own sets of control charts.

Control charts for ICAL and WCAL for 2017–18 are 

compared in figures 4A, 4B, and 4C. Points in the control 

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

a visual indication of potential solution-specific bias. A potential positive bias is observed for the SP2B solution, indicated 

by the green diamond symbols in figures 4A, 4B, and 4C. 

Control charts for base cation results are shown in figure 4A. 
8 External Quality Assurance Project Report for the National Trends Network and Mercury Deposition Network, 2017–18 Table 2. Analyte most probable values for synthetic precipitation solutions used in the 2017–18 National Trends Network interlaboratory comparison program. [Ca2+, calcium; Mg2+, magnesium; Na+, sodium; K+, potassium; NH4

+, ammonium; Cl-, chloride; Br-, bromide; NO3

-, nitrate; SO42-, sulfate; H+, hydrogen ion; all units in milligrams per liter except hydrogen 

ion (microequivalents per liter) and specific conductance (microsiemens per centimeter at 25 degrees Celsius)]

Solution 

identifier

Analytes Number of 

samples 

analyzed Ca2+ Mg2+ Na+ K+ NH4

+ Cl− Br− NO3− SO42− H+ Specific conductance

2017

SP21B 0.220 0.034 0.170 0.029 0.281 0.222 0.020 1.453 1.144 14.7233 12 74SP22B 0.110 0.017 0.082 0.013 0.140 0.110 0.009 0.720 0.562 7.7625 6.2 72SP2B 0.454 0.068 0.339 0.060 0.564 0.450 0.039 2.921 2.281 29.3432 23.4 62

2018

SP21B 0.230 0.034 0.177 0.030 0.280 0.225 0.021 1.485 1.143 15.4882 12.1 62SP22B 0.111 0.017 0.085 0.015 0.139 0.108 0.012 0.718 0.550 8.5114 6.3 62SP2B 0.456 0.070 0.350 0.060 0.560 0.442 0.039 2.930 2.266 29.5121 23.4 73

Table 3. Analytical detection limits for laboratories participating in the U.S. Geological Survey interlaboratory-comparison program for the National Atmospheric Deposition Program, 2017–18.[mg/L, milligram per liter; Participating laboratories: ACAP, Asia Center for Air Pollution Research; CIES, Carey Institute of Ecosystem Studies; ECST, Environment and Climate Change Canada Science and Technology Branch; ICAL, Central Analytical Laboratory, Illinois State Water Survey; MOECC, Ontario Ministry of Environment and Climate Change; NILU, Norwegian Institute for Air Research; NRS, U.S, Department of Agriculture Forest Service Northern Research Service; RTI, RTI International; UNAM, Universidad Nacional Autonoma de Mexico; WCAL, Central Analytical Laboratory, Wisconsin State Laboratory of Hygiene; WOOD, Wood Group, Inc; —, not calculated]

Analyte Method detection limits (mg/L) 2017/2018 ACAP CIES ECST ICAL MOECC NILU NRS RTI UNAM WCAL WOOD

Calcium 0.006/0.028 0.009/0.001 0.005 0.002/0.001 0.02 0.004 0.012/0.002

— 0.05 0.011 0.003

Magnesium 0.033 0.010/0.003 0.002 0.001/0.002 0.002/0.005 0.002 0.002

— 0.05 0.003 0.003

Sodium 0.095/0.003 0.001/0.005 0.003 0.001 0.005 0.024 0.008/0.006 0.003 0.04 0.004 0.005Potassium 0.036/0.001 0.003/0.040 0.004 0.001 0.005 0.03 0.01 0.003 0.05 0.005 0.005Ammonium 0.003/0.109 0.003/0.005 0.006 0.008/0.009 0.003 0.016 0.001 0.003 0.04 0.008 0.026Chloride 0.001 0.004/0.001 0.006 0.003 0.01 0.018 0.021 0.005 0.08 0.006 0.02Bromide 0.003/0.001 0.003/0.001

— 0.002/0.003

—

— 0.003

—

— 0.006

—

Nitrate 0.005/0.034 0.003 0.009 0.005/0.006 0.009/0.004 0.009 0.033 0.010/0.008 0.11 0.008 0.036Sulfate 0.003/0.055 0.01 0.016 0.005/0.006 0.050/0.040 0.017 0.033 0.008/0.011 0.11 0.007 0.04
National Trends Network Quality Assurance Programs 9

Table 4. Median differences between reported constituent concentrations and most probable values for synthetic wet-deposition 

samples, 2017 interlaboratory comparison program.

[ACAP, Asia Center for Air Pollution Research; ICAL, Central Analytical Laboratory, Illinois State Water Survey; AMEC/WOOD, AMEC Foster-Wheeler/

Wood Group; MOECC, Ontario Ministry of Environment and Climate Change; ECST, Environment and Climate Change Canada Science and Technology 

Branch; NILU, Norwegian Institute for Air Research; NRS, U.S. Forest Service Northern Research Station; CIES, Carey Institute of Ecosystem Studies; RTI, 

RTI International; WCAL, Central Analytical Laboratory, Wisconsin State Laboratory of Hygiene; UNAM, Universidad Nacional Autonoma de Mexico; all 

units in milligrams per liter, except hydrogen ion (microequivalents per liter) and specific conductance (microsiemens per centimeter at 25 degrees Celsius); 

overall f-psig, f-pseudosigma for all participating laboratories; median diff., median of differences between each laboratory's individual results and the most 

probable value during 2017; f-psig ratio, ratio of each individual laboratory's f-pseudosigma to the overall f-pseudosigma; sign test p-value, probability of rejecting the null hypothesis: “The true median of the differences between laboratory results and the most probable value is zero,” when true; values are shaded where 

median bias is greater than the method detection limit (table 3) and statistically significant (α=0.05) (Kanji, 2006); Spec. cond, specific conductance; —, not 

calculated; <, less than]

Analyte Overall f-psig Median diff. Sign test p-value f-psig ratio

ACAP Laboratory

Calcium 0.012 0.003 0.001 0.86

Magnesium 0.003 0.002 0.001 1.81

Sodium 0.013 0.06 <0.001 0.6

Potassium 0.005 0.002 0.18 1.38

Ammonium 0.009 0 0.182 1.67

Chloride 0.009 0 1 1.23

Bromide 0.002 — — —

Nitrate 0.024 0.001 0.434 0.77

Sulfate 0.024 0.001 0.44 0.92

Hydrogen ion 1.262 −1.073 <0.001 1.12

Spec. cond. 0.5 0.4 0.13 0.66

ICAL Laboratory

Calcium 0.012 0.003 <0.001 0.33

Magnesium 0.003 0 0.508 0.13

Sodium 0.013 0 0.345 0.17

Potassium 0.005 0.002 0.002 0.15

Ammonium 0.009 0.009 <0.001 0.77

Chloride 0.009 0.003 0.011 0.65

Bromide 0.002 −0.001 0.001 0.67

Nitrate 0.024 0.004 0.002 0.44

Sulfate 0.024 −0.005 0.012 0.41

Hydrogen ion 1.262 0.069 0.23 0.85

Spec. cond. 0.5 0.4 <0.001 0.88

AMEC/WOOD Laboratory

Calcium 0.012 −0.003 <0.001 0.47

Magnesium 0.003 0 0.016 0.25

Sodium 0.013 −0.004 0.002 0.19

Potassium 0.005 −0.002 0.227 0.15

Ammonium 0.009 −0.001 0.076 0.4

Chloride 0.009 −0.002 0.033 0.56

Bromide 0.002 — — —

Nitrate 0.024 −0.006 0.119 0.84

Sulfate 0.024 0.003 0.115 0.9

Hydrogen ion 1.262 0.401 <0.001 1.04

Spec. cond. 0.5 0.1 <0.001 0.44
10 External Quality Assurance Project Report for the National Trends Network and Mercury Deposition Network, 2017–18

Table 4. Median differences between reported constituent concentrations and most probable values for synthetic wet-deposition 

samples, 2017 interlaboratory comparison program.—Continued

[ACAP, Asia Center for Air Pollution Research; ICAL, Central Analytical Laboratory, Illinois State Water Survey; AMEC/WOOD, AMEC Foster-Wheeler/

Wood Group; MOECC, Ontario Ministry of Environment and Climate Change; ECST, Environment and Climate Change Canada Science and Technology 

Branch; NILU, Norwegian Institute for Air Research; NRS, U.S. Forest Service Northern Research Station; CIES, Carey Institute of Ecosystem Studies; RTI, 

RTI International; WCAL, Central Analytical Laboratory, Wisconsin State Laboratory of Hygiene; UNAM, Universidad Nacional Autonoma de Mexico; all 

units in milligrams per liter, except hydrogen ion (microequivalents per liter) and specific conductance (microsiemens per centimeter at 25 degrees Celsius); 

overall f-psig, f-pseudosigma for all participating laboratories; median diff., median of differences between each laboratory's individual results and the most 

probable value during 2017; f-psig ratio, ratio of each individual laboratory's f-pseudosigma to the overall f-pseudosigma; sign test p-value, probability of rejecting the null hypothesis: “The true median of the differences between laboratory results and the most probable value is zero,” when true; values are shaded where 

median bias is greater than the method detection limit (table 3) and statistically significant (α=0.05) (Kanji, 2006); Spec. cond, specific conductance; —, not 

calculated; <, less than]

Analyte Overall f-psig Median diff. Sign test p-value f-psig ratio

MOECC Laboratory

Calcium 0.012 −0.002 0.645 3.34

Magnesium 0.003 0.001 1 0.75

Sodium 0.013 0.005 0.281 0.83

Potassium 0.005 0.003 0.18 0.85

Ammonium 0.009 0.01 <0.001 0.79

Chloride 0.009 −0.001 0.002 1.88

Bromide 0.002 — — —

Nitrate 0.024 0.027 <0.001 1.44

Sulfate 0.024 −0.008 0.141 1.36

Hydrogen ion 1.262 0.784 <0.001 2.38

Spec. cond. 0.5 −0.4 <0.001 0.84

ECST Laboratory

Calcium 0.012 0.004 <0.001 0.41

Magnesium 0.003 0.001 0.063 0.5

Sodium 0.013 0.008 <0.001 0.39

Potassium 0.005 0.002 0.063 0.27

Ammonium 0.009 0 1 0.71

Chloride 0.009 0 0.418 0.35

Bromide 0.002 — — —

Nitrate 0.024 0.002 0.105 0.41

Sulfate 0.024 −0.011 <0.001 0.88

Hydrogen ion 1.262 −0.2 0.002 0.35

Spec. cond. 0.5 — — —

NILU Laboratory

Calcium 0.012 −0.002 0.004 0.61

Magnesium 0.003 −0.002 0.119 1.38

Sodium 0.013 0.011 <0.001 0.57

Potassium 0.005 0 1 1.38

Ammonium 0.009 −0.001 0.002 1.19

Chloride 0.009 0.004 0.007 1.04

Bromide 0.002 — — —

Nitrate 0.024 0.014 <0.001 1.96

Sulfate 0.024 0.01 0.101 1.67

Hydrogen ion 1.262 0.289 0.021 1.17

Spec. cond. 0.5 0.1 0.135 0.74
National Trends Network Quality Assurance Programs 11

Table 4. Median differences between reported constituent concentrations and most probable values for synthetic wet-deposition 

samples, 2017 interlaboratory comparison program.—Continued

[ACAP, Asia Center for Air Pollution Research; ICAL, Central Analytical Laboratory, Illinois State Water Survey; AMEC/WOOD, AMEC Foster-Wheeler/

Wood Group; MOECC, Ontario Ministry of Environment and Climate Change; ECST, Environment and Climate Change Canada Science and Technology 

Branch; NILU, Norwegian Institute for Air Research; NRS, U.S. Forest Service Northern Research Station; CIES, Carey Institute of Ecosystem Studies; RTI, 

RTI International; WCAL, Central Analytical Laboratory, Wisconsin State Laboratory of Hygiene; UNAM, Universidad Nacional Autonoma de Mexico; all 

units in milligrams per liter, except hydrogen ion (microequivalents per liter) and specific conductance (microsiemens per centimeter at 25 degrees Celsius); 

overall f-psig, f-pseudosigma for all participating laboratories; median diff., median of differences between each laboratory's individual results and the most 

probable value during 2017; f-psig ratio, ratio of each individual laboratory's f-pseudosigma to the overall f-pseudosigma; sign test p-value, probability of rejecting the null hypothesis: “The true median of the differences between laboratory results and the most probable value is zero,” when true; values are shaded where 

median bias is greater than the method detection limit (table 3) and statistically significant (α=0.05) (Kanji, 2006); Spec. cond, specific conductance; —, not 

calculated; <, less than]

Analyte Overall f-psig Median diff. Sign test p-value f-psig ratio

NRS Laboratory

Calcium 0.012 0.001 0.477 0.83

Magnesium 0.003 0 0.453 0.56

Sodium 0.013 −0.062 <0.001 1.92

Potassium 0.005 −0.005 0.18 0.77

Ammonium 0.009 −0.001 0.815 0.81

Chloride 0.009 0.022 <0.001 4.9

Bromide 0.002 0.006 <0.001 3.67

Nitrate 0.024 −0.023 0.009 2.07

Sulfate 0.024 −0.001 1 2.85

Hydrogen ion 1.262 1.054 0.629 3.96

Spec. cond. 0.5 −0.9 0.016 2.53

CIES Laboratory

Calcium 0.012 −0.023 <0.001 0.97

Magnesium 0.003 −0.001 0.146 0.5

Sodium 0.013 −0.027 <0.001 0.94

Potassium 0.005 −0.002 0.002 0.69

Ammonium 0.009 −0.002 0.266 1.15

Chloride 0.009 0.004 <0.001 1.48

Bromide 0.002 −0.002 <0.001 2

Nitrate 0.024 0.016 <0.001 1.38

Sulfate 0.024 0.009 <0.001 1.34

Hydrogen ion 1.262 −1.943 <0.001 1.77

Spec. cond. 0.5 −1 <0.001 0.81

RTI Laboratory

Calcium 0.012 — — —

Magnesium 0.003 — — —

Sodium 0.013 — — —

Potassium 0.005 — — —

Ammonium 0.009 — — —

Chloride 0.009 0 1 0.21

Bromide 0.002 — — —

Nitrate 0.024 −0.014 <0.001 0.36

Sulfate 0.024 −0.001 0.661 0.3

Hydrogen ion 1.262 — — —

Spec. cond. 0.5 — — —
12 External Quality Assurance Project Report for the National Trends Network and Mercury Deposition Network, 2017–18

Table 4. Median differences between reported constituent concentrations and most probable values for synthetic wet-deposition 

samples, 2017 interlaboratory comparison program.—Continued

[ACAP, Asia Center for Air Pollution Research; ICAL, Central Analytical Laboratory, Illinois State Water Survey; AMEC/WOOD, AMEC Foster-Wheeler/

Wood Group; MOECC, Ontario Ministry of Environment and Climate Change; ECST, Environment and Climate Change Canada Science and Technology 

Branch; NILU, Norwegian Institute for Air Research; NRS, U.S. Forest Service Northern Research Station; CIES, Carey Institute of Ecosystem Studies; RTI, 

RTI International; WCAL, Central Analytical Laboratory, Wisconsin State Laboratory of Hygiene; UNAM, Universidad Nacional Autonoma de Mexico; all 

units in milligrams per liter, except hydrogen ion (microequivalents per liter) and specific conductance (microsiemens per centimeter at 25 degrees Celsius); 

overall f-psig, f-pseudosigma for all participating laboratories; median diff., median of differences between each laboratory's individual results and the most 

probable value during 2017; f-psig ratio, ratio of each individual laboratory's f-pseudosigma to the overall f-pseudosigma; sign test p-value, probability of rejecting the null hypothesis: “The true median of the differences between laboratory results and the most probable value is zero,” when true; values are shaded where 

median bias is greater than the method detection limit (table 3) and statistically significant (α=0.05) (Kanji, 2006); Spec. cond, specific conductance; —, not 

calculated; <, less than]

Analyte Overall f-psig Median diff. Sign test p-value f-psig ratio

WCAL Laboratory

Calcium 0.012 0.003 <0.001 0.84

Magnesium 0.003 0 0.219 0.69

Sodium 0.013 0 0.503 0.61

Potassium 0.005 −0.001 0.109 0.31

Ammonium 0.009 −0.001 0.144 0.17

Chloride 0.009 −0.008 <0.001 0.81

Bromide 0.002 0.003 0.078 1.17

Nitrate 0.024 −0.002 1 0.68

Sulfate 0.024 −0.004 0.058 0.34

Hydrogen ion 1.262 1.326 0.001 3.06

Spec. cond. 0.5 −0.1 0.401 0.81

UNAM Laboratory

Calcium 0.012 −0.005 0.154 2.47

Magnesium 0.003 0.006 0.004 4.63

Sodium 0.013 −0.002 0.442 1.83

Potassium 0.005 −0.002 1 2.46

Ammonium 0.009 −0.01 0.001 1.63

Chloride 0.009 −0.011 <0.001 1.65

Bromide 0.002 — — —

Nitrate 0.024 −0.024 <0.001 1.02

Sulfate 0.024 0.025 <0.001 1.17

Hydrogen ion 1.262 0.264 0.003 1.5

Spec. cond. 0.5 −0.2 0.002 0.49

The ICAL results indicate a slight positive bias for sodium 

and potassium in the latter half of 2018. The WCAL results 

indicate a slight negative bias for sodium in late 2018.

Control charts for ammonium, chloride, bromide, and 

nitrate are shown in figure 4B. No bias for ammonium results 

reported by ICAL and WCAL is evident. However, the WCAL 

control charts indicate a negative bias for chloride and a 

positive bias for bromide results through November 2018. 

In November 2018, the WCAL chloride results match the 

MPVs, and the bias for bromide results becomes negative. The 

WCAL nitrate results indicate a slight negative bias, except for 

solution SP2B, until July 2018 when the bias shifts positive 

with several analyses outside the statistical control limits. The 

ICAL nitrate results trend toward a positive bias at about the 

same time as the WCAL shift in bias for nitrate. Additionally, 

an ICAL result for solution SP21B was out of statistical control in November 2018. There were several laboratories that 

did not report data for November and December, and this may 

have adversely affected the MPVs for solutions analyzed in 

this time period.

The control charts in figure 4C indicate a positive 

bias in WCAL sulfate results, primarily for solution SP2B, 

but the same bias for SP2B is not observed in the ICAL 

results. Hydrogen-ion concentrations calculated from pH 
National Trends Network Quality Assurance Programs 13

Table 5. Median differences between reported constituent concentrations and most probable values for synthetic wet-deposition 

samples, 2018 interlaboratory comparison program.

[ACAP, Asia Center for Air Pollution Research; ICAL, Central Analytical Laboratory, Illinois State Water Survey; WOOD, Wood Group; MOECC, Ontario 

Ministry of Environment and Climate Change; ECST, Environment and Climate Change Canada Science and Technology Branch; NILU, Norwegian Institute 

for Air Research; NRS, U.S. Forest Service Northern Research Station; CIES, Carey Institute of Ecosystem Studies; RTI, RTI International; WCAL, Central 

Analytical Laboratory, Wisconsin State Laboratory of Hygiene; UNAM, Universidad Nacional Autonoma de Mexico; all units in milligrams per liter except 

hydrogen ion (microequivalents per liter) and specific conductance (microsiemens per centimeter at 25 degrees Celsius); overall f-psig, f-pseudosigma for all 

participating laboratories; median diff., median of differences between each laboratory's individual results and the most probable value during 2018; f-psig ratio, 

ratio of each individual laboratory's f-pseudosigma to the overall f-pseudosigma; sign test p-value, probability of rejecting the null hypothesis: “The true median 

of the differences between laboratory results and the most probable value is zero,” when true; values are shaded where median bias is greater than the method 

detection limit (table 3) and statistically significant (α=0.05) (Kanji, 2006); Spec. cond, specific conductance; —, not calculated; <, less than]

Analyte Overall f-psig Median diff. Sign test p-value f-psig ratio

ACAP Laboratory

Calcium 0.011 0.003 0.001 0.4

Magnesium 0.001 0.002 0.003 2.5

Sodium 0.008 0.006 <0.001 0.64

Potassium 0.003 0.002 0.18 0.89

Ammonium 0.013 0 0.182 1.12

Chloride 0.007 −0.013 1 1.05

Bromide 0.004 — — —

Nitrate 0.028 0.001 0.434 0.36

Sulfate 0.02 0.001 0.44 0.73

Hydrogen ion 0.832 −1.073 <0.001 3

Spec. cond. 0.5 0.01 0.13 0.89

ICAL Laboratory

Calcium 0.011 0.003 <0.001 0.38

Magnesium 0.001 0 0.508 0.75

Sodium 0.008 0 0.345 0.34

Potassium 0.003 0.002 0.002 1.06

Ammonium 0.013 0.009 <0.001 1.06

Chloride 0.007 0.003 0.011 1.03

Bromide 0.004 −0.001 0.001 0.25

Nitrate 0.028 0.004 0.002 0.93

Sulfate 0.02 −0.005 0.012 0.62

Hydrogen ion 0.832 0.069 0.23 0.6

Spec. cond. 0.5 0.43 <0.001 0.73

WOOD Laboratory

Calcium 0.011 −0.003 <0.001 0.45

Magnesium 0.001 0 0.016 0.5

Sodium 0.008 −0.004 0.002 0.45

Potassium 0.003 −0.002 0.227 0.5

Ammonium 0.013 −0.001 0.076 0.85

Chloride 0.007 −0.002 0.033 0.47

Bromide 0.004 — — —

Nitrate 0.028 −0.006 0.119 0.59

Sulfate 0.02 0.003 0.115 0.55

Hydrogen ion 0.832 0.401 <0.001 2.36

Spec. cond. 0.5 0.11 <0.001 0.44
14 External Quality Assurance Project Report for the National Trends Network and Mercury Deposition Network, 2017–18

Table 5. Median differences between reported constituent concentrations and most probable values for synthetic wet-deposition 

samples, 2018 interlaboratory comparison program.—Continued

[ACAP, Asia Center for Air Pollution Research; ICAL, Central Analytical Laboratory, Illinois State Water Survey; WOOD, Wood Group; MOECC, Ontario 

Ministry of Environment and Climate Change; ECST, Environment and Climate Change Canada Science and Technology Branch; NILU, Norwegian Institute 

for Air Research; NRS, U.S. Forest Service Northern Research Station; CIES, Carey Institute of Ecosystem Studies; RTI, RTI International; WCAL, Central 

Analytical Laboratory, Wisconsin State Laboratory of Hygiene; UNAM, Universidad Nacional Autonoma de Mexico; all units in milligrams per liter except 

hydrogen ion (microequivalents per liter) and specific conductance (microsiemens per centimeter at 25 degrees Celsius); overall f-psig, f-pseudosigma for all 

participating laboratories; median diff., median of differences between each laboratory's individual results and the most probable value during 2018; f-psig ratio, 

ratio of each individual laboratory's f-pseudosigma to the overall f-pseudosigma; sign test p-value, probability of rejecting the null hypothesis: “The true median 

of the differences between laboratory results and the most probable value is zero,” when true; values are shaded where median bias is greater than the method 

detection limit (table 3) and statistically significant (α=0.05) (Kanji, 2006); Spec. cond, specific conductance; —, not calculated; <, less than]

Analyte Overall f-psig Median diff. Sign test p-value f-psig ratio

MOECC Laboratory

Calcium 0.011 −0.002 0.645 3.5

Magnesium 0.001 0.005 1 4

Sodium 0.008 0.005 0.281 0.91

Potassium 0.003 0.003 0.18 2.22

Ammonium 0.013 0.01 <0.001 0.65

Chloride 0.007 −0.009 0.002 2.74

Bromide 0.004 — — —

Nitrate 0.028 0.027 <0.001 1.23

Sulfate 0.02 −0.008 0.141 1.2

Hydrogen ion 0.832 0.784 <0.001 0.9

Spec. cond. 0.5 −0.35 <0.001 0.73

ECST Laboratory

Calcium 0.011 0.014 0.109 0.47

Magnesium 0.001 0.001 0.063 0.5

Sodium 0.008 0.008 <0.001 0.45

Potassium 0.003 0.002 0.063 0.33

Ammonium 0.013 0 1 0.53

Chloride 0.007 0 0.418 0.42

Bromide 0.004 — — —

Nitrate 0.028 0.002 0.105 0.31

Sulfate 0.02 −0.011 <0.001 0.67

Hydrogen ion 0.832 −0.209 0.002 0.56

Spec. cond. 0.5 — — —

NILU Laboratory

Calcium 0.011 −0.002 0.004 1.42

Magnesium 0.001 −0.002 0.119 2.5

Sodium 0.008 0.011 <0.001 1.45

Potassium 0.003 0 1 1.39

Ammonium 0.013 −0.001 0.002 0.65

Chloride 0.007 0.004 0.007 1.26

Bromide 0.004 — — —

Nitrate 0.028 0.014 <0.001 1.03

Sulfate 0.02 0.01 0.101 2.29

Hydrogen ion 0.832 0.289 0.021 0.42

Spec. cond. 0.5 0.05 0.135 0.56
National Trends Network Quality Assurance Programs 15

Table 5. Median differences between reported constituent concentrations and most probable values for synthetic wet-deposition 

samples, 2018 interlaboratory comparison program.—Continued

[ACAP, Asia Center for Air Pollution Research; ICAL, Central Analytical Laboratory, Illinois State Water Survey; WOOD, Wood Group; MOECC, Ontario 

Ministry of Environment and Climate Change; ECST, Environment and Climate Change Canada Science and Technology Branch; NILU, Norwegian Institute 

for Air Research; NRS, U.S. Forest Service Northern Research Station; CIES, Carey Institute of Ecosystem Studies; RTI, RTI International; WCAL, Central 

Analytical Laboratory, Wisconsin State Laboratory of Hygiene; UNAM, Universidad Nacional Autonoma de Mexico; all units in milligrams per liter except 

hydrogen ion (microequivalents per liter) and specific conductance (microsiemens per centimeter at 25 degrees Celsius); overall f-psig, f-pseudosigma for all 

participating laboratories; median diff., median of differences between each laboratory's individual results and the most probable value during 2018; f-psig ratio, 

ratio of each individual laboratory's f-pseudosigma to the overall f-pseudosigma; sign test p-value, probability of rejecting the null hypothesis: “The true median 

of the differences between laboratory results and the most probable value is zero,” when true; values are shaded where median bias is greater than the method 

detection limit (table 3) and statistically significant (α=0.05) (Kanji, 2006); Spec. cond, specific conductance; —, not calculated; <, less than]

Analyte Overall f-psig Median diff. Sign test p-value f-psig ratio

NRS Laboratory

Calcium 0.011 0.001 0.477 0.63

Magnesium 0.001 0 0.453 1

Sodium 0.008 −0.062 <0.001 4

Potassium 0.003 −0.005 0.18 1.56

Ammonium 0.013 −0.001 0.815 0.51

Chloride 0.007 0.022 <0.001 3.13

Bromide 0.004 0.006 <0.001 1.08

Nitrate 0.028 −0.023 0.009 2.4

Sulfate 0.02 −0.001 1 3.95

Hydrogen ion 0.832 — — —

Spec. cond. 0.5 — — —

CIES Laboratory

Calcium 0.011 −0.023 <0.001 1.22

Magnesium 0.001 −0.001 0.146 0.88

Sodium 0.008 −0.027 <0.001 1.41

Potassium 0.003 −0.003 0.002 2.72

Ammonium 0.013 −0.002 0.266 4.94

Chloride 0.007 0.004 <0.001 0.68

Bromide 0.004 −0.002 <0.001 0.42

Nitrate 0.028 0.016 <0.001 0.66

Sulfate 0.02 0.009 <0.001 1.01

Hydrogen ion 0.832 −1.943 <0.001 4.44

Spec. cond. 0.5 −0.97 <0.001 1.38

RTI Laboratory

Calcium 0.011 — — —

Magnesium 0.001 — — —

Sodium 0.008 0.002 0.07 0.23

Potassium 0.003 — — —

Ammonium 0.013 −0.005 0.012 0.24

Chloride 0.007 0 1 0.37

Bromide 0.004 — — —

Nitrate 0.028 −0.014 <0.001 0.51

Sulfate 0.02 −0.001 0.661 0.6

Hydrogen ion 0.832 — — —

Spec. cond. 0.5 — — —
16 External Quality Assurance Project Report for the National Trends Network and Mercury Deposition Network, 2017–18

Table 5. Median differences between reported constituent concentrations and most probable values for synthetic wet-deposition 

samples, 2018 interlaboratory comparison program.—Continued

[ACAP, Asia Center for Air Pollution Research; ICAL, Central Analytical Laboratory, Illinois State Water Survey; WOOD, Wood Group; MOECC, Ontario 

Ministry of Environment and Climate Change; ECST, Environment and Climate Change Canada Science and Technology Branch; NILU, Norwegian Institute 

for Air Research; NRS, U.S. Forest Service Northern Research Station; CIES, Carey Institute of Ecosystem Studies; RTI, RTI International; WCAL, Central 

Analytical Laboratory, Wisconsin State Laboratory of Hygiene; UNAM, Universidad Nacional Autonoma de Mexico; all units in milligrams per liter except 

hydrogen ion (microequivalents per liter) and specific conductance (microsiemens per centimeter at 25 degrees Celsius); overall f-psig, f-pseudosigma for all 

participating laboratories; median diff., median of differences between each laboratory's individual results and the most probable value during 2018; f-psig ratio, 

ratio of each individual laboratory's f-pseudosigma to the overall f-pseudosigma; sign test p-value, probability of rejecting the null hypothesis: “The true median 

of the differences between laboratory results and the most probable value is zero,” when true; values are shaded where median bias is greater than the method 

detection limit (table 3) and statistically significant (α=0.05) (Kanji, 2006); Spec. cond, specific conductance; —, not calculated; <, less than]

Analyte Overall f-psig Median diff. Sign test p-value f-psig ratio

WCAL Laboratory

Calcium 0.011 0.003 0.002 0.43

Magnesium 0.001 0 0.219 1

Sodium 0.008 0 0.503 0.36

Potassium 0.003 −0.001 0.109 0.67

Ammonium 0.013 −0.001 0.144 0.47

Chloride 0.007 −0.008 <0.001 0.95

Bromide 0.004 0.006 0.078 0.83

Nitrate 0.028 −0.002 1 1.33

Sulfate 0.02 −0.004 0.058 0.67

Hydrogen ion 0.832 1.326 0.001 3.37

Spec. cond. 0.5 −0.05 0.401 0.36

UNAM Laboratory

Calcium 0.011 −0.005 0.154 3.63

Magnesium 0.001 0.006 0.004 10.13

Sodium 0.008 −0.012 0.442 3.55

Potassium 0.003 −0.002 1 6.44

Ammonium 0.013 −0.01 0.001 2.47

Chloride 0.007 −0.011 <0.001 3.71

Bromide 0.004 — — —

Nitrate 0.028 −0.023 <0.001 1.13

Sulfate 0.02 0.025 <0.001 1.54

Hydrogen ion 0.832 0.264 0.003 0.72

Spec. cond. 0.5 −0.15 0.002 0.77

measurements indicate generally consistent agreement with 

MPVs for the ICAL results, but there appears to be a solutionspecific bias only for the synthetic precipitation samples for 

the WCAL results. The WCAL results for pH indicate little 

to no bias for the natural precipitation samples. Meanwhile, 

specific conductance results for ICAL appear positively biased 

across all solutions, especially for solution SP2B, while the 

WCAL specific conductance results indicate no bias. These 

seemingly solution-specific effects had never been observed in 

this interlaboratory-comparison program’s results.

Analyte determinations that exceeded the control limits 

(± 3 f-psig) for ICAL during 2017–18 include ammonium (1), 

nitrate (2), sulfate (1), specific conductance (7), and hydrogen 

ion (5). Analyte determinations that exceeded the control 

limits for WCAL during 2017–18 include calcium (1), magnesium (1), sodium (1), potassium (1), chloride (1), bromide (1), 

nitrate (10), sulfate (3), and hydrogen ion (21). Determinations 

of bias and variability in bromide results are less reliable than 

for other analytes because MPVs for bromide were determined 

from results of only 4 participating laboratories, compared 

to 8–10 laboratories for other analytes. Missing data due to 

samples lost in shipment and partial participation by some 

laboratories were problematic, especially in 2018.

Results from the interlaboratory comparison program 

indicate differences in performance for ICAL and WCAL 

primarily for analysis of nitrate, specific conductance, and pH. 
National Trends Network Quality Assurance Programs 17

Table 6. Number of analyte determinations greater than the method detection limits for deionized water samples, 2017–18.

[Participating laboratories: ACAP, Asia Center for Air Pollution Research; CIES, Carey Institute of Ecosystem Studies; ECST, Environment and Climate 

Change Canada Science and Technology Branch; ICAL, Central Analytical Laboratory, Illinois State Water Survey; MOECC, Ontario Ministry of Environment 

and Climate Change; NILU, Norwegian Institute for Air Research; NRS, U.S, Department of Agriculture Forest Service Northern Research Service; RTI, RTI 

International; UNAM, Universidad Nacional Autonoma de Mexico; AMEC/WOOD, AMEC Foster-Wheeler/Wood Group, Inc.; WCAL, Central Analytical 

Laboratory, Wisconsin State Laboratory of Hygiene; NP, laboratory not participating in 2017; —, no data]

Analyte

Number of determinations greater than analytical detection limits for four blank samples

2017 Participating laboratories

ACAP CIES ECST ICAL MOECC NILU NRS RTI UNAM WCAL AMEC/WOOD

2017 participating laboratories

Calcium 0 0 0 0 1 0 0 — 0 NP 0

Magnesium 2 2 0 0 0 0 0 — 0 NP 0

Sodium 0 0 0 0 0 0 0 — 0 NP 0

Potassium 0 0 0 2 1 0 0 — 0 NP 0

Ammonium 0 0 0 2 2 0 0 — 0 NP 0

Chloride 2 3 0 0 0 0 3 0 0 NP 0

Bromide — 0 — 0 — — 0 — — NP —

Nitrate 1 3 0 0 1 0 2 0 0 NP 0

Sulfate 1 4 0 0 0 0 4 0 0 NP 0

2018 participating laboratories

Calcium 4 0 1 1 3 0 0 — 0 0 0

Magnesium 4 0 0 1 0 0 0 — 0 1 0

Sodium 3 0 1 0 0 0 0 0 0 0 0

Potassium 3 0 2 2 1 0 1 0 0 0 0

Ammonium 2 0 0 1 3 0 0 0 0 0 0

Chloride 2 1 0 1 2 0 3 0 0 0 0

Bromide — 0 — 0 — — 0 — — 0 —

Nitrate 2 4 0 0 2 0 4 0 0 0 0

Sulfate 2 2 0 0 2 0 4 0 0 0 0

However, a special study was conducted by the NADP Quality 

Assurance Advisory Group with assistance from the PCQA 

to compare ICAL and WCAL performance and verify readiness of the WCAL to assume the role of the CAL for NADP. 

Results of that study are contained in the internal NADP 

Central Analytical Laboratory Readiness Verification Report 

(RVP). Results for 75 spiked natural matrix split samples 

analyzed by the ICAL and WCAL are summarized in table 8. 

Median absolute percent differences for the split samples 

were less than 10 percent for all analytes except potassium 

(12 percent). Furthermore, the RVP results indicated a negative bias for WCAL results relative to ICAL results for nitrate 

and hydrogen ion concentrations, which is opposite of the 

results presented in this report. Therefore, control charts for 

2018 shown herein should be used with caution as representative indicators of laboratory bias relative to the MPVs. 

Nonetheless, continued monitoring of the potential differences 

in ICAL and WCAL relative bias is required to ensure that 

potential shifts in the precipitation chemistry record can be 

appropriately attributed to either true environmental signals or 

shifts in sample collection and analysis methodology.

Colocated Sampler Program

For water years 2017–18, the colocated sampler program 

evaluated the variability of NTN data obtained with N–CON 

collectors. Colocated N–CON collectors were operated 

at NTN sites CO11 and 11CO at the Arvada Community 

Gardens, Arvada, Colorado. A single OTT Pluvio-2 precipitation gage measured and recorded precipitation depth as well as 

the operation of the N–CON collectors. Colocated sites were 

operated using identical field and laboratory sample-collection 

and sample-analysis procedures (Wisconsin State Laboratory 

of Hygiene, 2019).

Weekly precipitation chemistry data from colocated 

sites were analyzed for differences between the CO11 

and 11CO weekly analyte concentrations. Only valid data 
18 External Quality Assurance Project Report for the National Trends Network and Mercury Deposition Network, 2017–18

Table 7. Number of analyte determinations outside ±3 f-pseudosigma statistical control limits, by participating laboratory, 2017–18.

[n, number of samples analyzed; Ca, calcium; Mg, magnesium; Na, sodium; K, potassium; NH4, ammonium; Cl, chloride; NO3, nitrate; SO4, sulfate; Br, 

bromide, Sc, specific conductance at 25 degrees Celsius; H, hydrogen ion concentration from pH; ACAP, Asia Center for Air Pollution Research; CIES, Carey 

Institute of Ecosystem Studies; ECST, Environment and Climate Change Canada Science and Technology Branch; ICAL, Central Analytical Laboratory, Illinois 

State Water Survey; MOECC, Ontario Ministry of Environment and Climate Change; NILU, Norwegian Institute for Air Research; NRS, U.S. Department of 

Agriculture Forest Service Northern Research Service; RTI, RTI International; UNAM, Universidad Nacional Autonoma de Mexico; WCAL, Central Analytical 

Laboratory, Wisconsin State Laboratory of Hygiene; AMEC/WOOD, AMEC Foster-Wheeler / Wood Group, Inc.; —, no data; *, n=9 ]

Laboratory n Ca Mg Na K NH4 Cl NO3 SO4 Br Sc H

2017

ACAP 44 5 18 1 8 1 4 4 6 — 0 4

CIES 44 4 0 14 3 2 5 6 5 0 10 29

ECST 44 2 2 1 1 1 2 1 3 — 1 1

ICAL 44 0 0 0 0 0 0 1 1 0 6 0

MOECC 42 13 1 4 4 1 15 0 5 — 0 19

NILU 44 2 3 0 3 0 0 7 7 — 2 5

NRS 40 1 1 12 2 2 26 2 11 0 1 3

RTI 44 — — — — — 0 1 0 — — —

UNAM 40 7 35 9 34 5 4 2 3 — — 8

WCAL 9 1 1 0 1 0 0 0 0 0 0 7

AMEC/WOOD 40 0 0 2 0 0 0 1 1 0 0 4

2018

ACAP 43 0 8 0 0 3 2 0 4 — 0 13

CIES 44 10 0 6 8 16 2 1 3 3 17 6

ECST 41 0 0 0 0 1 0 0 3 — 2 0

ICAL 44 0 0 0 0 1 0 1 0 0 1 5

MOECC 41 16 9 1 4 2 0 8 3 — 2 5

NILU 44 1 4 1 6 3 4 7 8 — 0 0

NRS 34 0 1 9 4 1 12 14 14 3 2 1

RTI 44 8* 4* 0* 0* 0* 0 1 1 — — —

UNAM 32 17 21 6 14 8 14 2 4 — — 2

WCAL 44 0 0 1 0 0 2 10 3 1 0 14

WOOD 44 0 2 2 3 2 4 0 3 — 0 8

(quality rating codes “A” and “B”) identified in the NADP 

by a laboratory-type code “W” (sufficient volume for complete analysis) and “WI” (volume for incomplete analysis) 

were used (National Atmospheric Deposition Program, 

http://nadp.slh.wisc.edu/data/ntn/meta/ntnDataValidation.pdf, 

last accessed September 20, 2019). Samples flagged as 

contaminated by NADP were considered prone to a greater 

error component. For this reason, valid contaminated samples 

were eliminated from statistical analysis in previous reports. 

However, eliminating the contaminated samples for water 

years 2017–18 would have resulted in a limited dataset with 

only 26 pairs of samples and incomplete seasonal representation for the 2-year period of record. Therefore, all of the 

52 valid sample pairs were used for this report regardless of 

contamination flagging by NADP.

Because annual summaries of NTN data describe wetdeposition chemistry in terms of concentration and deposition, statistical summaries for colocated concentration and 

deposition measurements are provided. The weekly precipitation depth from the precipitation gage was used to calculate deposition values at the colocated sites by multiplying 

precipitation-weighted mean concentrations for each analyte in 

milligrams per liter (mg/L) by 0.10 multiplied by the precipitation depth in centimeters (cm) to yield deposition in kilograms 

per hectare (kg/ha) (Wetherbee and others, 2010).

Concentration differences from paired weekly samples 

obtained from the colocated collectors were calculated to 

evaluate variability, which was described by Wetherbee and 

others (2005b) as the overall error in NTN data. Relative 

concentration differences were calculated as the CO11 concentrations minus the 11CO concentrations. Results from 

these calculations are shown in table 9. The median weekly 
National Trends Network Quality Assurance Programs 19

Calcium–ICAL Calcium–WCAL

Concentration difference, in milligrams per liter

A

−0.20

−0.15

−0.10

−0.05

0.00

0.05

0.10

0.15

0.20

−0.20

−0.15

−0.10

−0.05

0.00

0.05

0.10

0.15

0.20

−0.05

−0.04

−0.03

−0.02

−0.01

0.00

0.01

0.02

0.03

0.04

0.05

−0.05

−0.04

−0.03

−0.02

−0.01

0.00

0.01

0.02

0.03

0.04

0.05

−0.10

−0.08

−0.06

−0.04

−0.02

0.00

0.02

0.04

0.06

0.08

0.10

−0.10

−0.08

−0.06

−0.04

−0.02

0.00

0.02

0.04

0.06

0.08

0.10

−0.06

−0.04

−0.02

0.00

0.02

0.04

0.06

−0.06

−0.04

−0.02

0.00

0.02

0.04

0.06

Magnesium–ICAL

Sodium–ICAL

Potassium–ICAL

Magnesium–WCAL

Sodium–WCAL

Potassium–WCAL

2017 2018 2019 2017 2018 2019

Year Year

Warning limit—± 2 f-pseudosigma from zero difference line

Control limit—± 3 f-pseudosigma from zero difference line

Zero difference line

EXPLANATION

SP21B

DI

SP22B

SP2B

Natural precipitation

Solution type

Figure 4. Differences between concentration values reported by the Central Analytical Laboratories and the median concentration 

values for all participating laboratories in the interlaboratory comparison program for the National Trends Network, 2017–18.
20 External Quality Assurance Project Report for the National Trends Network and Mercury Deposition Network, 2017–18 Concentration difference, in milligrams per liter

Chloride–ICAL

−0.100

−0.075

−0.050

−0.025

0.000

0.025

0.050

0.075

0.100

Bromide–ICAL

−0.03

−0.02

−0.01

0.00

0.01

0.02

0.03

Ammonium–WCAL

−0.3

−0.2

−0.1

0.0

0.1

0.2

0.3

Chloride–WCAL

−0.100

−0.075

−0.050

−0.025

0.000

0.025

0.050

0.075

0.100

Bromide–WCAL

−0.03

−0.02

−0.01

0.00

0.01

0.02

0.03

Nitrate–ICAL

−0.30

−0.25

−0.20

−0.15

−0.10

−0.05

0.00

0.05

0.10

0.15

0.20

0.25

0.30

Nitrate–WCAL

−0.30

−0.25

−0.20

−0.15

−0.10

−0.05

0.00

0.05

0.10

0.15

0.20

0.25

0.30

Ammonium–ICAL

−0.3

−0.2

−0.1

0.0

0.1

0.2

0.3

2017 2018 2019 2017 2018 2019

Year Year

B

Warning limit—± 2 f-pseudosigma from zero difference line

Control limit—± 3 f-pseudosigma from zero difference line

Zero difference line

EXPLANATION

SP21B

DI

SP22B

SP2B

Natural precipitation

Solution type

Figure 4. Differences between concentration values reported by the Central Analytical Laboratories and the median concentration 

values for all participating laboratories in the interlaboratory comparison program for the National Trends Network, 2017–18.—

Continued
National Trends Network Quality Assurance Programs 21

Concentration difference,

in milligrams per liter

Specific Conductance–ICAL

 Specific conductance difference, in micro

siemens per centimeter at 25 degrees celcius

−5.0

−2.5

0.0

2.5

5.0

Hydrogen ion–ICAL

Concentration difference,

in microequivalents per liter

−15

−12

−9

−6

−3

0

3

6

9

12

15

Sulfate–ICAL

−0.4

−0.3

−0.2

−0.1

0.0

0.1

0.2

0.3

0.4

Sulfate–WCAL

−0.4

−0.3

−0.2

−0.1

0.0

0.1

0.2

0.3

0.4

Hydrogen ion–WCAL

−15

−12

−9

−6

−3

0

3

6

9

12

15

Specific Conductance–WCAL

−5.0

−2.5

0.0

2.5

5.0

2017 2018 2019 2017 2018 2019

Year Year

Warning limit—± 2 f-pseudosigma from zero difference line

Control limit—± 3 f-pseudosigma from zero difference line

Zero difference line

EXPLANATION

SP21B

DI

SP22B

SP2B

Natural precipitation

Solution type

C

Figure 4. Differences between concentration values reported by the Central Analytical Laboratories and the median concentration 

values for all participating laboratories in the interlaboratory comparison program for the National Trends Network, 2017–18.—

Continued

relative differences were small and ranged 0.000–0.005 mg/L 

for calcium, magnesium, sodium and potassium (cations), 

and 0.003–0.020 mg/L for chloride, nitrate, and sulfate 

(anions). Median relative differences for both ammonium 

(0.008–0.022 mg/L) and hydrogen ion (0.009–0.010 microequivalents per liter [μeq/L]) as well as specific conductance 

values (0.3–1.0 microseimens per centimeter [μS/cm]) were 

also considered small (table 9). Median weekly absolute percent differences ranged 7–22 percent for cations, 4–10 percent 

for anions, 6–9 percent for ammonium, and 9.2–32 percent for 

hydrogen ion. Median weekly absolute percent differences for 

sample volume catch were low at 4–5 percent.

Annual deposition absolute percent differences (APD) 

ranged 8–18 percent for calcium, and were zero for magnesium, sodium, and potassium. Ammonium annual deposition APD ranged 0–12 percent. Annual deposition APD for 

anions ranged as follows: chloride (12–29 percent), nitrate 

(2–15 percent), and sulfate (0–7 percent). Annual hydrogenion deposition APD ranged 0–51 percent. Hydrogen-ion 
22 External Quality Assurance Project Report for the National Trends Network and Mercury Deposition Network, 2017–18 Table 8. Overall median relative bias and sign test results for comparison of 75 National Atmospheric Deposition Program split samples analyzed by the former Central Analytical Laboratory at the Illinois State Water Survey (ICAL) and current Central Analytical Laboratory at the University of Wisconsin (WCAL). [Ca, calcium; Mg, magnesium; Na, sodium; K, potassium; NH4, ammonium; Cl, chloride; Br, bromide with values less than the detection limit excluded; NO3, nitrate; SO4, sulfate; H, hydrogen ion concen- tration; SC, specific conductance; <, less than; %, percent; mg/L, milligrams per liter; μEq/L, microequivalents per liter; μS/cm, microsiemens per centimeter; 

p>=|M|, sign test result indicating probability 

of incorrectly deciding that the median WCAL-ICAL concentration difference is zero when true; shaded values indicate statistically significant difference between median difference and zero; APD, absolute percent difference; RPD, relative (to ICAL measurement) percent difference; %, percent; differences were calculated as WCAL value minus ICAL value; N, number of samples with both WCAL and ICAL values above their respective detection limits]

Statistic Ca (mg/L) Mg (mg/L) Na (mg/L) K (mg/L) NH4 (mg/L) Cl (mg/L) Br (mg/L) NO3 (mg/L) SO4 (mg/L) H (μEq/L) SC (μS/cm)

Median difference 

(units) 0.005 0 0.004 0.003 −0.008 −0.009 0.0015 −0.029 −0.003 −0.175 −0.3

p-value for 

p>=|M| <0.0001 0.3742 <0.0001 <0.0001 0.0027 <0.0001 0.375 <0.0001 0.2954 0.0002 <0.0001

Median APD (%) 4.7 6.2 3.9 12 7.3 5.9 33 5.2 3 10 6.1Median RPD (%) 3.9 0 3.7 12 −4.4 −3.7 21 −5.3 −0.3 −12 −5.1

N samples 75 71 73 74 73 75 8 75 75 75 75

concentrations were low with 35 of the 46 pH measurements 

greater than pH=6, and percent differences of small hydrogenion concentrations are relatively large.

The event-recorder data for actuation of the collector 

lids on the colocated N–CON collectors are shown in table 10

and include the number of times that the collector lids opened 

and closed (lid cycles). Table 10 also shows the amount of 

time that the collectors were open while the precipitation gage 

detected precipitation (wet exposure) and how long they were 

open when it did not (dry exposure). The collector sensors 

play a large role in the data variability and bias (Wetherbee, 

2017; Wetherbee and Rhodes, 2013). Dry exposure of NTN 

samples can lead to sample contamination with dry deposited 

materials. More than 6 hours of dry exposure causes invalidation of NTN samples.

The APDs for counted lid cycles at CO11/11CO ranged 

20–26 percent, indicating that the 11CO collector cycled 

20–26 percent more than the CO11 collector. Wet exposure 

APD was 1.2–2.1 percent, but dry exposure APD ranged 

1.4 percent (2017)–14 percent (2018). The 11CO samples 

received 13 percent more dry exposure in 2018 than in 2017. 

The cause of this is unknown. By comparison, the water year 

2015–2016 studies at NTN sites OH71/71OH and SD08/08SD 

indicated APDs of 8–22 percent for lid cycles, 3–10 percent for wet exposure, and 0–26 percent for dry exposure 

(Wetherbee and Martin, 2018). Despite differences in 2018 

performance of the collectors, overall differences in chemical 

solute concentrations were small.

Mercury Deposition Network Quality 

Assurance Programs

The USGS operated a system blank program and an 

interlaboratory comparison program for the MDN during 

2017–18. Protocols for the PCQA external QA programs 

for MDN are described in detail by Wetherbee and Martin 

(2016a). The MDN system blank program is similar to the 

NTN field audit program, whereby the effects of onsite 

environmental exposure, handling, and shipping on sample 

contamination are evaluated. The MDN interlaboratory 

comparison program quantified variability and bias of MDN 

analytical data provided by the Mercury Analytical Laboratory 

(HAL) of Eurofins Frontier Global Sciences, Inc., in Bothell, 

Washington, for 2017–18.

System Blank Program

The MDN site operators received system blank samples 

from PCQA during 2017, but no samples were shipped to 

MDN sites in 2018 to allow for transfer of NADP operations 

from the Illinois State Water Survey to the Wisconsin State 

Laboratory of Hygiene. After a week without wet deposition at 

a site, operators poured one-half of the volume of the system 
Mercury Deposition Network Quality Assurance Programs 23

Table 9. Median weekly constituent concentration differences and annual deposition differences for colocated N–CON Systems 

Company, Inc. precipitation collectors at National Atmospheric Deposition Program sites CO11 and 11CO for all valid samples, water 

years 2017–18.

[mg/L, milligram per liter; μeq/L, microequivalent per liter; μS/cm, microsiemens per centimeter at 25 degrees Celsius; mL, milliliter; NA, not applicable]

Analyte (units)

Water year 2017 Water year 2018

Median 

weekly 

relative 

difference

Median 

weekly 

absolute 

percent 

difference

Annual 

deposition

absolute 

percent 

difference

Range of 

measured 

values

Median 

weekly 

relative 

difference

Median 

weekly 

absolute 

percent 

difference

Annual 

deposition 

absolute 

percent 

difference

Range of 

measured 

values

Calcium 

(mg/L) 0.002 4.9 18 0.058–1.78 0.005 7.6 8 0.080–2.03

Magnesium 

(mg/L) 0.001 7.2 0 0.007–0.183 0.001 10 0 0.008–0.260

Sodium 

(mg/L) 0.002 11 0 0.003–1.29 0.002 7 0 0.005–2.44

Potassium 

(mg/L) 0 22 0 0.006–0.164 0 22 0 0.010–0.179

Ammonium 

(mg/L) 0.008 9.3 12 0.070–5.86 0.022 6.1 0 0.023–2.74

Chloride 

(mg/L) 0.003 10 29 0.013–2.42 0.005 10 12 0.032–3.65

Nitrate 

(mg/L) 0.02 4.3 15 0.253 –10.7 0.02 3.8 2.2 0.356–3.85

Sulfate 

mg/L) 0.012 9 7.4 0.097–4.88 0.006 5.2 0 0.182 –11.77

Hydrogen-ion 

(μeq/L) 0.01 9.2 51 0.158–7.08 0.009 32 0 0.112–3.72

Specific conductance 

(μS/cm) 0.3 7.5 NA 2.8–37 1 5.3 NA 5.6–37

Sample volume 

(mL) 4.2 5.4 NA 8.7–3,766 −5.8 3.9 NA 73–7,707

blank solution through the glass sample train. The glass 

sample train consists of the collector funnel, which collects 

the precipitation sample, and a thistle tube, which drains the 

precipitation into the sample bottle. The solution that washed 

through the sample train is called the system blank sample, 

and the solution remaining in the original sample bottle is 

called the bottle sample. Both system blank and bottle samples 

were sent together to HAL for total mercury (Hg) analysis.

Of the 91 active MDN sites that received system blank 

samples in 2017, 55 sites either processed samples or returned 

a postcard to PCQA indicating no dry weeks during the year. 

In all, 41 system blank samples were processed with accompanying bottle samples, and four sites with no dry weeks submitted unopened bottle samples, which served as trip blanks. The 

trip blanks were analyzed by the HAL for total Hg concentrations, all of which were less than the detection limit. The 

HAL provided the system blank data to the PCQA, and system 

sample minus bottle sample differences were calculated by the 

USGS. Data for 123 system blank sample pairs were received 

by PCQA from the HAL during 2015–18.

Network Maximum Contamination Levels for 

Mercury

The NMCLs for total Hg were calculated from the 

system blank data using a 3-year moving window starting 

with 2004–06. MDN NMCL for total Hg decreased from 

1.098 ng/L for the 2014–16 period to 1.023 ng/L for the 

2015–17 period (table 11). Thus, the maximum contamination in MDN samples during 2015–17 was not greater than 

1.023 ng/L with 90-percent confidence, and no more than 

10 percent of the MDN samples had contamination concentrations exceeding 1.023 ng/L with 90-percent confidence. This 
24 External Quality Assurance Project Report for the National Trends Network and Mercury Deposition Network, 2017–18

Table 10. Event recorder data summary for colocated N–CON Systems Company, Inc., precipitation collectors at National Atmospheric 

Deposition Program sites CO11 and 11CO, water years 2017–18.

[Lid cycle, number of times collector opened and then closed; Wet exposure, time that collector is open to collect precipitation when rain gage confirms 

measurement of precipitation; Dry exposure, time that collector is open when rain gage does not indicate measurement of precipitation; cm, centimeter; APD, 

absolute percent difference]

Water year Site identifier Lid cycles Wet exposure 

(hours)

Dry exposure 

(hours)

Precipitation depth 

(cm)

2017 CO11 1,917 239.7 174.4 34.04

11CO 2,480 236.8 172

APD: 26 1.2 1.4

2018 CO11 1,937 221.3 161.2 33.15

11CO 2,369 216.7 140

APD: 20 2.1 14

Table 11. Three-year moving network maximum contamination levels and 90-percent upper confidence limits at the 50th, 75th, and 

90th percentiles of total mercury contamination mass in system blank samples, 2004–17.

[%, percent; UCL, upper confidence limit; Hg, total mercury; ng Hg, nanogram of mercury; ng Hg/L, nanogram of mercury per liter; nd, no data collected in 

2018]

3-year period

Network maximum 

contamination level1

(ng total Hg/L)

90% UCLs on percentiles of total Hg contamination mass in 

system blank samples (ng Hg)

Percentiles

50th 75th 90th2

2004–06 0.412 0.005 0.095 0.095

2005–07 1.067 0.018 0.067 0.136

2006–08 2.17 0.04 0.1 0.233

2007–09 3.476 0.06 0.12 0.325

2008–10 4.26 0.07 0.152 0.325

2009–11 1.588 0.068 0.14 0.285

2010–12 1.771 0.065 0.12 0.26

2011–13 1.871 0.052 0.097 0.47

2012–14 1.871 0.045 0.095 0.536

2013–15 1.787 0.036 0.068 0.115

2014–16 1.098 0.034 0.064 0.094

2015–17 1.023 0.034 0.068 0.101

2016–18 nd nd nd nd

1Defined as the 90-percent UCL on 90th percentile of system-blank Hg contamination concentrations.

2Defined as the maximum contamination mass per sample.
Mercury Deposition Network Quality Assurance Programs 25

concentration is approximately equal to the first percentile of 

all MDN weekly Hg concentrations from 2016 to 18 (Robert 

Larson, NADP Program Office, Wisconsin State Laboratory of 

Hygiene, written commun., 2019).

Mass of Mercury Contamination

The mass of Hg contamination in each system blank 

sample was calculated as follows:

Hg contamination (nanograms) = ([HgSB] 

× VolumeSB)–([HgBot] × VolumeBot) (7)

where

[HgSB] is the total Hg concentration in system blank 

sample, in nanograms per liter;

VolumeSB is the volume of system blank sample, 

in liters;

[HgBot] is the total Hg concentration in the bottle 

sample, in nanograms per liter; and

VolumeBot is the volume of the bottle sample, in liters.

Next, the UCLs of the percentiles of the system sample 

minus bottle sample Hg mass differences were calculated. 

Based on the 90 percent UCL on the 90th percentile of total 

Hg contamination mass, the maximum estimated contaminant 

mass per sample increased slightly from 0.094 ng Hg during 

2014–16 to 0.101 ng Hg during 2015–17 (table 11).

Mercury Deposition Network Interlaboratory 

Comparison Program

The objective of the MDN interlaboratory comparison 

program is to estimate the variability and bias of HAL analytical data in comparison with results from analytical laboratories supporting various monitoring networks, not accounting 

for the different onsite protocols used by different monitoring networks. Eight laboratories participated in the program 

during the study period: (1) HAL at Eurofins Frontier Global 

Sciences, Inc., in Bothell, Washington; (2) Chinese Academy 

of Sciences, Institute of Geochemistry (CASIG), in Guiyang, 

People’s Republic of China; (3) Department of Atmospheric 

Science, National Central University (DASNCU), in Jhong-Li 

District, Taoyuan City, Taiwan; (4) Flett Research, Ltd. (FRL), 

in Winnipeg, Manitoba, Canada; (5) Swedish Environmental 

Institute (IVL) in Goteborg, Sweden; (6) Quebec Laboratory 

for Environmental Testing (LEEQ or QLET) in Montreal, 

Quebec, Canada; (7) North Shore Analytical, Inc., (NSA) 

in Duluth, Minnesota; and (8) USGS Mercury Research 

Laboratory (WML) in Middleton, Wisconsin. During 2018, 

the scope of the program was reduced to 6 laboratories, which 

included HAL, DASNCU, FRL, IVL, and WML to accommodate transfer of NADP operations from the ISWS to the 

WSLH. All laboratories analyzed the water samples for low 

levels of Hg using atomic fluorescence spectrometry methods 

similar to U.S. Environmental Protection Agency Method 

1631 (U.S. Environmental Protection Agency, 2002).

During 2017, each participating laboratory received two 

samples per month consisting of 1-percent (volume:volume) 

hydrochloric acid blanks and mercuric nitrate spiked at four 

different concentrations in a 1-percent hydrochloric acid 

matrix. During 2018, each participating laboratory received 

two to four samples quarterly. The laboratories were instructed 

to analyze the samples as soon as they were received to 

promote accurate time representation of the data. All samples 

were single-blind samples, where the chemical analyst knew 

that the sample was a quality-control sample but did not know 

the total Hg concentrations of the samples. The medians of 

all the concentration values obtained from the participating 

laboratories were considered to be MPVs, which are listed in 

table 12.

Control Charts

Total Hg analysis data submitted by each laboratory 

were compared to MPVs for each of the four solutions. 

Differences between reported results and MPVs were plotted on annual control charts, which were delivered to each 

laboratory by PCQA. Control charts include warning limits 

placed at ±2 f-psig and control limits at ±3 f-psig from the 

zero-difference line during the study period. Values outside the 

control limits represent periods when a laboratory’s analyses 

were considered to be out of statistical control.

The HAL’s control chart for the 2017–18 interlaboratory 

comparison analyses shows that all results are within statistical 

control (±3 f-psig) except for one result for MP4 in the fourth 

quarter of 2018. One result for MP2 was outside the positive 

warning limit (+2 f-psig) during 2017 (fig. 5). No bias in the 

HAL results was evident from the control chart.

Interlaboratory Variability and Bias

Each laboratory’s results for variability and bias are 

summarized in table 13. Methods for evaluation of the interlaboratory variability and bias for the MDN interlaboratory 

comparison program are analogous to those for the NTN interlaboratory comparison program. The f-psig ratio was computed 

as shown in equation 6 and expressed as a percentage for each 

laboratory, whereby an f-psig ratio larger than 100 percent 

indicates that results provided by a laboratory exhibited higher 

variability than the overall variability among the participating 

laboratories; a ratio smaller than 100 percent indicates less 

variability than overall. The arithmetic signs of the median differences indicate whether total mercury analysis results were 

positively or negatively biased. Interlaboratory bias was evaluated for statistical significance using the sign test for location 

of a median (Kanji, 2006; Wetherbee and others, 2013).
26 External Quality Assurance Project Report for the National Trends Network and Mercury Deposition Network, 2017–18

Table 12. Most probable values for total mercury in four solutions and hydrochloric acid blank 

samples used for the U.S. Geological Survey Mercury Deposition Network interlaboratory 

comparison program, 2017–18. 

[Hg, total mercury; MPV, most probable value; ng/L, nanogram per liter; %, percent; HCl, hydrochloric acid; 

BLANK, mercury-free de-ionized water with 1% HCl by volume; MP1–MP4, mercuric nitrate standard diluted 

to target concentrations in 1% HCl; Blank MPVs estimated by Kaplan-Meier method in R–NADA package 

because of large number of censored values]

Solution identifier Total Hg concentration MPV 

(ng/L)

2017

1% HCl BLANK 0.02

MP1 5.9

MP2 8.7

MP3 14.3

MP4 20.4

2018

1% HCl BLANK 0.05

MP1 5.41

MP2 8.33

MP3 14.44

MP4 19.9

 Total mercury concentration difference, in nanograms per liter 

3.5

2.5

1.5

0.5

0

−0.5

−1.5

−2.5

−3.5

2017 2018 2019

Year

Warning limit—± 2 f-pseudosigma from zero difference line

Control limit—± 3 f-pseudosigma from zero difference line

Zero difference line

EXPLANATION

MP3

MP1

MP4

MP2

Solution type

Figure 5. Differences between total mercury concentrations reported by the Mercury Analytical Laboratory, Eurofins Frontier 

Global Sciences, Inc., and the median concentration values for all participating laboratories in the interlaboratory comparison 

program for the Mercury Deposition Network, 2017–18. Data are for test solutions MP1, MP2, MP3, and MP4.
Mercury Deposition Network Quality Assurance Programs 27

Table 13. Differences between reported concentrations and most probable values for total mercury determinations, Mercury 

Deposition Network interlaboratory comparison program, 2017–18.

[ng/L, nanogram per liter; overall f-psig, f-pseudosigma for all participating laboratories; median diff., median of differences between each laboratory's individual results and the most probable values for each solution; sign test p-value, probability of rejecting the null hypothesis: “The true median of the differences between laboratory results and the most probable value is zero,” when true; f-psig ratio, ratio of each individual laboratory's f-pseudosigma to the overall 

f-pseudosigma; sign test p-value, probability of rejecting the null hypothesis: “The true median of the differences between laboratory results and the most 

probable value is zero,” when true; HAL, Mercury Analytical Laboratory at Eurofins Frontier Global Sciences, Inc.; CASIG, Chinese Academy of Sciences, 

Institute of Geochemistry; DASNCU, Department of Atmospheric Sciences, National Central University (Taiwan); FRL, Flett Research, Ltd.; IVL, Swedish 

Environmental Research Institute; LEEQ, Quebec Laboratory of Environmental Testing; NSA, North Shore Analytical, Inc.; WML, U.S. Geological Survey 

Wisconsin Mercury Laboratory; n.d., no data; <, less than; statistical warning limits are ±2 overall f-psig, statistical control limits are ±3 overall f-psig]

Year Overall f-psig 

(ng/L)

Median diff.

 (ng/L) Sign test p-value f-psig ratio Number of values outside limits (warning/control)

HAL Laboratory

2017 0.69 −0.09 0.481 0.79 1/0

2018 0.275 −0.08 0.25 0.93 0/1

CASIG Laboratory

2017 0.69 0.324 0.359 1.29 3/3

2018 0.275 (1) (1) (1) (1)

DASNCU Laboratory

2017 0.69 −0.6 0.019 2.77 2/7

2018 0.275 0.03 0.25 1.04 0/0

FRL Laboratory

2017 0.69 −0.04 0.824 0.44 0/0

2018 0.275 0.07 0.251 0.33 0/0

IVL Laboratory

2017 0.69 0.3 0.096 0.72 0/1

2018 0.275 0.06 0.25 1.84 1/0

LEEQ Laboratory

2017 0.69 1.3 <0.001 1.99 6/7

2018 0.275 (1) (1) (1) (1)

NSA Laboratory

2017 0.69 −0.215 0.0636 0.86 2/0

2018 0.275 (1) (1) (1) (1)

WML Laboratory

2017 0.69 −0.08 0.238 0.68 0/0

2018 0.275 0.07 0.25 0.75 0/0

1Laboratory did not participate in limited 2018 interlaboratory-comparison program.

Annual overall f-psig values were 0.690 ng/L and 

0.275 ng/L for 2017 and 2018, respectively, for the concentration ranges indicated by the MPVs in table 12. Results in 

table 13 indicate that the HAL’s performance was similar to 

that of FRL, NSA, and WML during the study period. The 

HAL’s total Hg analyses were characterized by less variability than overall in 2017 and 2018 with f-psig ratios of 79 and 

93 percent, respectively. The HAL results indicated small 

median differences (-0.090 and 0.080 ng/L) that were not 

statistically significant from zero (p=0.481 and 0.250) during 

2017 and 2018, respectively (table 13). Median differences 

from the MPVs were less than or equal to the second percentile of all weekly MDN total Hg concentrations of 1.41 ng/L. 

Therefore, the annual bias estimates for all of the laboratories 

are negligible compared to total Hg concentrations determined 

by the MDN during 2016 and 2018 (Robert Larson, NADP 

Program Office, Wisconsin State Laboratory of Hygiene, written commun., 2019).
28 External Quality Assurance Project Report for the National Trends Network and Mercury Deposition Network, 2017–18

Table 14. Number of total mercury determinations greater than the method detection limits for blank samples, Mercury Deposition 

Network interlaboratory comparison program, 2017–18.

[Four determinations per year per laboratory; HAL, Mercury Analytical Laboratory at Eurofins Frontier Global Sciences, Inc.; CASIG, Chinese Academy of 

Sciences, Institute of Geochemistry; DASNCU, Department of Atmospheric Sciences, National Central University (Taiwan); FRL, Flett Research, Ltd.; IVL, 

Swedish Environmental Research Institute; LEEQ, Quebec Laboratory of Environmental Testing; NSA, North Shore Analytical, Inc.; WML, U.S. Geological 

Survey Wisconsin Mercury Laboratory; ng/L, nanogram per liter; N/A, not applicable]

HAL CASIG1 DASNCU FRL IVL LEEQ1 NSA WML

2017

0 4 1 0 0 2 0 1

2018

0 N/A 1 2 3 N/A N/A 3

Minimum reporting limits (ng/L)

0.08 0.05 0.03 0.04 0.04 0.03 0.10 0.009

1Laboratory did not participate in limited 2018 interlaboratory-comparison program.

Results for Blanks

Interlaboratory comparison results for 2017–18 blank 

samples are shown in table 14. Four blind blank samples were 

shipped to each laboratory annually. Minimum reporting levels 

(MRLs) vary between laboratories and were less than or equal 

to 0.10 ng/L during 2017–18. The HAL had no values reported 

above the detection limit of 0.08 ng/L for blank samples.

As shown for results in previous years, results of blank 

analyses indicate that HAL Hg contamination during the study 

period was low (Wetherbee and Martin, 2016b). Therefore, 

most Hg contamination in MDN samples, which was estimated using the system blanks, was likely introduced in 

the field.

Summary

The U.S. Geological Survey (USGS) used three programs to provide external quality assurance monitoring for 

the National Atmospheric Deposition Program’s (NADP) 

National Trends Network (NTN) and two programs to provide 

external quality assurance monitoring for the NADP Mercury 

Deposition Network (MDN) during 2017–18. The field audit 

program assessed the effects of onsite exposure, sample 

handling, and shipping on the chemistry of NTN samples; 

the system blank program assessed the same effects for MDN 

samples. Two interlaboratory comparison programs assessed 

the bias and variability of the chemical analysis data from the 

Central Analytical Laboratory (CAL), Mercury Analytical 

Laboratory (HAL), and other participating laboratories that 

analyze precipitation samples for major ions, nutrients, and 

trace levels of mercury (Hg). A colocated sampler program 

was used to quantify the variability of NADP data collected 

with N–CON sample collectors. During 2018, the CAL moved 

from the Illinois State Water Survey (ICAL) to the Wisconsin 

Laboratory of Hygiene (WCAL). The field audit and system 

blank programs were not operated in 2018 and the MDN interlaboratory comparison program was reduced in scope during 

2018 both to provide support and avoid potential complications for the CAL transition. Due to the change in CAL operations during the study period, ICAL and WCAL performance 

is compared in this report.

National Trends Network

Field audit results for 2017–18 indicate that network 

maximum contamination levels for calcium, magnesium, 

sodium, ammonium, and chloride, in NTN samples, have not 

changed appreciably since 2014, but the Network Maximum 

Contamination Level (NMCL) for potassium decreased 

approximately -0.003 mg/L. The NMCLs for nitrate and 

sulfate increased by approximately 0.01 mg/L (2015–17) and 

then decreased again (2016–18) to levels lower than those 

measured during 2014–16. Variable levels of sample contamination over the past 10 years are small in terms of their 

absolute concentrations. However, the 2016–18 calcium, 

magnesium, sodium, and potassium NMCLs were equivalent 

to the 22nd, 26th, 20th, and 13th percentile concentrations, 

respectively, in NADP samples during the same period. The 

NMCLs for chloride (0.022 mg/L), nitrate (0.071 mg/L), 

and sulfate (0.054 mg/L), were at the 9th, 2nd, and 2nd NTN 

concentration percentiles, respectively. This program also estimated the maximum loss of ammonium, nitrate, and hydrogen 

ion in weekly NTN samples. Ammonium loss increased from 

0.010 mg/L (2014–2016) to 0.020 mg/L (2015–2017), which 

is approximately 2.2 times the 2018 MDL for (0.009 mg/L). 

Hydrogen ion maximum loss was 2.50 microequivalents per 

liter (μeq/L), which has not changed since 2014.

During 2017, statistically significant bias was observed 

for ICAL (calcium, potassium, and ammonium) and WCAL 

(chloride) results. During 2018, statistically significant bias 

was identified for ICAL (calcium and potassium) and WCAL 

(chloride). The ECST, ICAL, AMEC/WOOD, RTI, and 
References Cited 29

WCAL laboratories had comparable, low overall variability 

among the participating laboratories during 2017–18 as indicated by most f-psig ratios less than 100.

No results were reported above analytical detection 

limits for blank samples for the ECST, NILU, RTI, UNAM, 

and AMEC/WOOD laboratories during 2017–18. The ACAP 

laboratory reported detections for all constituents in 2018 for 

at least two blanks per analyte. The ICAL reported detections 

for potassium and ammonium in two of four blanks analyzed 

in 2017 and for calcium (1), magnesium (1), potassium (2), 

ammonium (1), and chloride (1) in 2018. The ECST laboratory reported no detected analytes in blanks for 2017 and 

detections for calcium (1), sodium (1), and potassium (2) in 

2018. The MOECC laboratory reported detections in blanks 

for calcium (4), potassium (2), ammonium (5), chloride (2), 

nitrate (3), and sulfate (2) during 2017–18. The NRS laboratory reported detections in blanks for calcium (2), magnesium 

(1), sodium (1), potassium (4), ammonium (1), chloride (2), 

nitrate (3), and sulfate (2) for 2017–18 combined. The WCAL 

reported a detection for magnesium in a blank during 2018 and 

analyzed no blanks in 2017.

Analyte determinations that exceeded statistical control 

limits (± 3 f-pseudosigma) for ICAL during 2017–18 include 

ammonium (1), nitrate (2), sulfate (1), specific conductance (7), and hydrogen ion (5). Analyte determinations 

that exceeded the control limits for WCAL during 2017–18 

include calcium (1), magnesium (1), sodium (1), potassium 

(1), chloride (1), bromide (1), nitrate (10), sulfate (3), and 

hydrogen ion (21). The interlaboratory-comparison program 

results indicate differences in performance for ICAL and 

WCAL primarily for analysis of nitrate, specific conductance, 

and pH. However, in an independent study in 2018, results for 

75 spiked natural matrix split samples analyzed by the ICAL 

and WCAL revealed median absolute percent differences less 

than 10 percent for all analytes except potassium (12 percent). 

Furthermore, the Readiness Verification Plan (RVP) results 

indicated a negative bias for WCAL results relative to ICAL 

results for nitrate and hydrogen ion concentrations, which is 

the opposite of the comparison presented in this report.

Weekly wet-deposition data for colocated N–CON collectors at NTN sites CO11 and 11CO at the Arvada Community 

Gardens were collected in water years 2017 and 2018. 

Concentration differences for the paired weekly samples were 

calculated to evaluate overall variability in NTN measurements. The median weekly absolute concentration differences 

were small and ranged 0.000–0.005 mg/L for calcium, magnesium, sodium and potassium (cations), and 0.003–0.020 mg/L 

for chloride, nitrate, and sulfate (anions). Median absolute 

differences for ammonium (0.00–0.022 mg/L); and hydrogen ion (0.009–0.010 μeq/L) and specific conductance 

(0.3–1.0 μS/cm) were also considered small. Median weekly 

absolute percent differences ranged 7–22 percent for cations, 

4–10 percent for anions, 6–9 percent for ammonium, and 

9.2–32 percent for hydrogen ion. Median weekly absolute 

percent differences for sample volume catch were low at 

4–5 percent.

Annual deposition absolute percent differences (APD) 

ranged 8–18 percent for calcium and were zero for magnesium, sodium, and potassium. Ammonium annual deposition 

APD ranged 0–12 percent. Ranges of annual deposition APD 

for anions were: chloride (12–29 percent); nitrate (2–15 percent); and sulfate (0–7 percent). Annual hydrogen-ion deposition APD ranged 0–51 percent. Hydrogen-ion concentrations 

were low with 35 of the 46 pH measurements greater than 

pH=6, and percent differences of small hydrogen-ion concentrations were relatively large.

Mercury Deposition Network

The MDN NMCL for total Hg decreased from 1.098 ng/L 

during 2014–16 to 1.023 ng/L during 2015–17. Thus, the maximum contamination in MDN samples during 2015–17 was 

not greater than 1.023 ng/L with 90-percent confidence, and no 

more than 10 percent of the MDN samples had contamination 

concentrations exceeding 1.023 ng/L with 90-percent confidence. This concentration is approximately equal to the first 

percentile of all MDN weekly Hg concentrations from 2016 

to 18. The maximum estimated contaminant mass per sample 

increased slightly from 0.094 ng Hg during 2014–16 to 0.101 

ng Hg during 2015–17.

The HAL’s control chart for the 2017–18 interlaboratory 

comparison analyses shows that all results are within statistical control (±3 f-psig) except for one result for solution MP4 

in the fourth quarter of 2018. One result for MP2 was outside 

the positive warning limit (+2 f-psig) during 2017. No bias 

in the HAL results was evident from the control chart. The 

HAL’s total Hg analyses were characterized by less variability than overall in 2017 and 2018 with f-psig ratios of 79 and 

93 percent, respectively. The HAL results indicated small 

median differences (−0.090 and 0.080 ng/L) that were not 

significantly different from zero (p=0.481 and 0.250) during 

2017 and 2018, respectively. Median differences from the 

MPVs were less than or equal to the second percentile of all 

weekly MDN total Hg concentrations of 1.41 ng/L. The HAL 

had no values reported above the detection limit of 0.08 ng/L 

for blank samples.

References Cited

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for detection and quantification of environmental contamination: New York, John Wiley & Sons, p. 139–146.

Hahn, G.J., and Meeker, W.Q., 1991, Statistical intervals—A 

guide for practitioners: New York, John Wiley & 

Sons, 392 p. [Also available at https://doi.org/10.1002/

9780470316771.]
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Helsel, D.R., 2012, Statistics for censored environmental data 

using Minitab and R 2nd ed.: Hoboken, N.J., John Wiley & 

Sons, p. 70–77.

Hoaglin, D.C., Mosteller, Frederick, and Tukey, J.W., 1983, 

Understanding robust and exploratory data analysis: New 

York, John Wiley & Sons, p. 38–41.

Kanji, G.K., 2006, 100 statistical tests 3rd ed.: New 

Delhi, Sage Publications Ltd., 242 p. [Also available at 

https://doi.org/10.4135/9781849208499.]

Latysh, N.E., and Wetherbee, G.A., 2005, External quality assurance programs managed by the U.S. Geological 

Survey in support of the National Atmospheric Deposition 

Program/National Trends Network: U.S. Geological Survey 

Open-File Report 2005–1024, 66 p., accessed January 31, 

2018 at https://pubs.er.usgs.gov/publication/ofr20051024.

Latysh, N.E., and Wetherbee, G.A., 2007, External quality assurance programs managed by the U.S. Geological 

Survey in support of the National Atmospheric Deposition 

Program/Mercury Deposition Network: U.S. Geological 

Survey Open-File Report 2007–1170, 33 p., accessed 

January 31, 2018, at https://pubs.er.usgs.gov/publication/

ofr20071170.

Morris, K., Mast, A., Clow, D., Wetherbee, G., Baron, J., 

Taipale, C., Blett, T., Gay, D., and Heath, J., 2014, 2012 

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Publishing support provided by the Science Publishing Network, 

Denver Publishing Service Center and Rolla Publishing Service Center

For more information concerning the research in this report, contact:

Director, Observing Systems Division

Buildings 2101, 2204 HIF

Hydrologic Instrumentation Facility, Stennis Space Center, MS 39529

(228) 688-1501

Or visit the Precipitation Chemistry Quality Assurance Project website 

at https://bqs.usgs.gov/PCQA/
Wetherbee and Martin—External Quality Assurance Project Report for the National Trends Network and Mercury Deposition Network, 2017–18—SIR 2020–5084

ISSN 2328-0328 (online)

https://doi.org/10.3133/sir20205084