Effects of Equipment Performance on Data

Quality from the National Atmospheric Deposition 

Program/National Trends Network and the 

Mercury Deposition Network

By Gregory A. Wetherbee and Mark F. Rhodes

Open-File Report 2013–1031

U.S. Department of the Interior

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

KEN SALAZAR, Secretary

U.S. Geological Survey

Suzette M. Kimball, Acting Director

U.S. Geological Survey, Reston, Virginia: 2013 

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Suggested citation:

Wetherbee, G.A., and Rhodes, M.F., 2013, Effects of equipment performance on data quality 

from the National Atmospheric Deposition Program/National Trends Network and the Mercury 

Deposition Network: U.S. Geological Survey Open-File Report 2013‒1031, 53 p. pamphlet 

Any use of trade, product, or firm names is for descriptive purposes only and does not imply 

endorsement by the U.S. Government.

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

copyright owners to reproduce any copyrighted material contained within this report.
iii

Contents

Terms and Abbreviations used in this report......................................................................................... viii

Acronyms ................................................................................................................................................ix

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

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

Precipitation Chemistry Quality Assurance.......................................................................................... 4

Purpose and Scope............................................................................................................................. 4

Study 1. Sample Evaporation in NTN Collector....................................................................................... 4

Background and Methods.................................................................................................................... 4

Results and Discussion ....................................................................................................................... 6

Conclusion........................................................................................................................................... 6

Study 2. MDN Sample Loss Study.......................................................................................................... 9

Background and MDN Data Analysis .................................................................................................. 9

Phase 1 of Study—Extent of MDN Sample Loss............................................................................... 10

Phase 2 of Study—Factors that Affect MDN Sample Loss................................................................ 13

Phase 2 Methodology........................................................................................................................ 13

Phase 3 of Study-Effects of Sample Loss on Mercury Concentrations.............................................. 18

Conclusions....................................................................................................................................... 21

Study 3. Mercury Adsorption in MDN Sample Trains ............................................................................ 21

Background and Methods.................................................................................................................. 21

Results and Discussion ..................................................................................................................... 25

Study 4. Sensitivity of NTN and MDN Collector Sensors ...................................................................... 25

Background and Methods.................................................................................................................. 25

Results and Discussion ..................................................................................................................... 27

Study 5. Catch Efficiency of NTN Collector with Wind Shield................................................................ 31

Background and Methods.................................................................................................................. 31

Results and Discussion ..................................................................................................................... 35

Summary and Conclusions ................................................................................................................... 42

References Cited .................................................................................................................................. 43

Figures

1. Map showing active and formerly active National Atmospheric Deposition Program/National 

Trends Network (NTN) sites, 2010............................................................................................. 2

2. Map showing active (2010) and formerly active National Atmospheric Deposition 

Program/Mercury Deposition Network (MDN) sites, 2010.......................................................... 3

3. Graph showing active National Atmospheric Deposition Program/National Trends Network and 

Mercury Deposition Network sites, 1978‒2009.......................................................................... 3

4. Graph showing weekly sample evaporation from a National Trends Network Aerochem Metrics 

Model 301 wet-deposition collector and weekly pan evaporation at Arvada, Colorado, May 

16–September 5, 2006............................................................................................................... 5

5. Graph showing weekly sample evaporation from a National Trends Network Aerochem Metrics 

Model 301 wet-deposition collector and weekly mean wind direction from north and wind 

speed at Arvada, Colorado, May 16–September 5, 2006 .......................................................... 7
iv

6. Graph showing weekly sample evaporation from a National Trends Network Aerochem Metrics 

Model 301 wet-deposition collector and weekly mean air temperature at Arvada, Colorado, 

May 16–September 5, 2006....................................................................................................... 8

7. Graph showing relation of weekly mean relative humidity and mean barometric pressure to 

weekly sample evaporation from a National Trends Network Aerochem Metrics Model 301 

wet-deposition collector at Arvada, Colorado, May 16–September 5, 2006............................... 8

8. Graph showing weekly sample evaporation from a National Trends Network Aerochem Metrics 

Model 301 wet-deposition collector and initial sample volumes at Arvada, Colorado, May 

16–September 5, 2006............................................................................................................... 9

9. Map showing Mercury Deposition Network samples with preservative volume loss in modified 

ACM and N-CON precipitation collectors during weeks with no precipitation, March 1996–

November 2010........................................................................................................................ 11

10. Map showing Mercury Deposition Network percent preservative volume loss in modified ACM 

and N-CON precipitation collectors during weeks with no precipitation, March 1996‒

November 2010........................................................................................................................ 12

11. Photographs of bad lid seal configuration for the modified ACM collector (top) and the N-CON 

collector (bottom) ..................................................................................................................... 14

12. Graph showing field sample volume lost (percent) over weekly periods in N-CON and modified 

Aerochem Metrics (ACM) precipitation collectors and maximum weekly temperatures of the 

air inside the collectors, December 1, 2009–May 7, 2010........................................................ 15

13. Graph showing percentages of initial sample volumes lost over weekly periods in N-CON and 

modified Aerochem Metrics (ACM) precipitation collectors and corresponding integrity of 

collector-lid seals, December 1, 2009–May 7, 2010................................................................. 16

14. Graph showing percentages of initial sample volumes lost over weekly periods in N-CON and 

modified Aerochem Metrics (ACM) precipitation collectors and corresponding 

configurations of air flow inside the collectors, March 1, 2010–October 29, 2010.................... 17

15. Graph showing percentages of initial sample volumes lost over weekly periods in N-CON and 

modified Aerochem Metrics (ACM) precipitation collectors and corresponding internal 

collector temperature, lid seal integrity, and internal air flow configurations for the 

collectors, December 1, 2009–November 17, 2010 ................................................................. 18

16. Graph showing relation of percent sample volume loss and mercury concentration difference 

for three MDN collector types: N-CON, modified Aerochem Metrics (ACM), and Loda 

Electronics ACM....................................................................................................................... 20

17. Graph showing relation of sample volume loss to percent mercury mass loss for three MDN 

collector types: N-CON, modified Aerochem Metrics (ACM), and Loda Electronics ACM........ 20

18. Thistle-tube configurations used with the modified N-CON collector and the ACM collector........... 22

19. Flowchart of the sample-train study for the Mercury Deposition Network........................................ 24

20. Mercury Deposition Network 11-grid sensor and National Trends Network 7-grid sensor for 

Aeorchem Metrics precipitation collectors................................................................................ 26

21. Graphs showing comparison of number of precipitation events when 7- and 11-grid sensors 

opened and closed their respective collectors first at 20 co-located National Trends 

Network (NTN) and Mercury Deposition Network (MDN) sites................................................. 28

22. Graphs showing comparison of wet- and dry-exposure differences and collector cycle 

differences for 7- and 11-grid sensors at 20 co-located National Trends Network and 

Mercury Deposition Network sites............................................................................................ 30

23. Co-located sampler installation at Marshall Field, Colorado showing placement of standard and 

wind-shielded ACM collectors and location of precipitation gage............................................. 33
v

24. Graphs showing time series of unshielded-minus-shielded collector catch differences for colocated wet-deposition collectors operated at Marshall Field, Colorado during water years 

2008‒2009 (WY08‒-WY09)..................................................................................................... 35

25. Graphs showing relation of shielded and unshielded collector catch for co-located wetdeposition collectors operated at Marshall Field, Colorado during water years 2008‒2009 

(WY08‒WY09)......................................................................................................................... 36

26. Graphs showing sample-volume differences for co-located standard and wind-shielded wetdeposition collectors, with maximum and average wind speed during precipitation at 

Marshall Field, Colorado during water years 2008‒2009 (WY08‒WY09)................................ 37

27. Graph showing catch efficiency and sample-volume differences, for co-located wind-shielded 

and standard wet-deposition collectors, related to average wind direction and wind 

direction relative standard deviation during precipitation at Marshall Field, Colorado during 

water years 2008‒2009 ........................................................................................................... 38

28. Graph showing sample-volume differences for co-located standard and wind-shielded wetdeposition collectors related to average and minimum air temperature during precipitation 

at Marshall Field, Colorado during water years 2008‒2009 (WY08‒WY09)............................ 40

29. Graph showing specific conductance of precipitation samples obtained by co-located windshielded and standard wet-deposition collectors at Marshall Field, Colorado during water 

years 2008‒2009 ..................................................................................................................... 41

30. pH of precipitation samples obtained by co-located wind-shielded and unshielded wetdeposition collectors at Marshall Field, Colorado during water years 2008‒2009 (WY08‒

WY09)...................................................................................................................................... 42
vi

Tables

1. Kendall’s Tau and associated statistical significance for correlation of meteorological data and 

weekly evaporation of synthetic precipitation samples sealed in an Aerochem Metrics 

Model 301 precipitation collector in Arvada, Colorado, May 16–September 5, 2006 ............... 46

2. Preservative volume loss for MDN samples collected between March 1996 and November 2010 ... 47

3. Weekly Mercury Deposition Network (MDN) samples with preservative volume loss and 

individual MDN sites where sample loss was observed, March 1996‒November 2010........... 47

4. Specifications of the cooling fan used in the original modified Aerochem Metrics (ACM) collector 

and the Loda Electronics version of the ACM collector ........................................................... 47

5. Results from evaporation tests with Aerochem Metrics version of the modified ACM collector......... 48

6. Results from evaporation tests with Loda Electronics version of the modified ACM collector........... 49

7. Results from evaporation tests with N-CON single-chimney collector............................................... 51

8. Total mercury concentration analyses for sample-train study samples processed after a week 

with rain or snow at selected Mercury Deposition Network sites.............................................. 52

9. Co-located National Trends Network (NTN) and Mercury Deposition Network (MDN) sites and 

periods of record for comparison of 7- and 11-grid Aerochem Metrics precipitation sensors... 53
vii

Conversion Factors

SI to Inch/Pound

Multiply By To obtain

Length

centimeter (cm) 0.3937 inch (in.)

millimeter (mm) 0.0394 inch (in.)

Volume

milliliter (mL) 0.03381 ounce, fluid

liter (L) 1.057 quart (qt)

cubic meter (m3) 35.31 cubic foot (ft3)

Acceleration

meter per second (m/s) 2.237 miles per hour (mi/hr) 

Mass

gram (g) 0.03527 ounce, avoirdupois (oz)

micrograms per square meter (μg/m2) 2.049 × 10-10 pounds per square foot (lbs/ft2)

nanograms (ng) 3.527 × 10-11 ounce (oz)

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

°F=(1.8×°C)+32

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 either in milligrams per liter (mg/L) micrograms 

per liter (μg/L), or nanograms per liter (ng/L).
viii

Terms and Abbreviations Used in This Report

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

 expressions

cubic feet per minute (ft3/min)

decibel (dB)

gram (g)

grams per cubic centimeter (g/cm3)

grams per milliliter (g/mL)

maximum probability of incorrectly rejecting the null hypothesis when it is true (p)

meters per second (m/s)

microgram (μg)

microequivalents per liter (μeq/L)

microsiemens per centimeter at 25 degrees Celsius (μS/cm)

milligrams per liter (mg/L)

millimeter (mm)

nanograms per liter (ng/L)

revolutions per minute (rpm)

square centimeters (cm2

)

statistical significance level (α)

water year = October 1–September 30 of following year, designated by ending year
ix

Abbreviations and Acronyms

Abbreviation Full name

ACM Aerochem Metrics Model 301 collector

BQS Branch of Quality Systems

CAL Central Analytical Laboratory

CDPHE Colorado Department of Public Health and Environment

DC Direct Current

DFC Denver Federal Center

DFIR Dual Fence Inter-comparison Reference wind shield

HAL Mercury Analytical Laboratory at Frontier Global Sciences, Inc.

HCl Hydrochloric acid

Hg Mercury

MDN Mercury Deposition Network

Mod-ACM Modified Aerochem Metrics precipitation collector

MOF Mercury Observer Form

MPV most probable value

NADP National Atmospheric Deposition Program

NCAR National Center for Atmospheric Research

N-CON N-CON Systems, Incorporated

NTN National Trends Network

PCQA Precipitation Chemistry Quality Assurance

pH Negative log of hydrogen ion concentration in equivalents per liter

PO Program Office (of the National Atmospheric Deposition Program)

QC Quality control

SC Specific Conductance

URL Universal Resources Locator

USGS United States Geological Survey
Effects of Equipment Performance on Data

Quality from the National Atmospheric Deposition 

Program/National Trends Network and the 

Mercury Deposition Network

By Gregory A. Wetherbee1 and Mark F. Rhodes2

1 U.S. Geological Survey

2 University of Illinois, Prairie Research Institute

Abstract

The U.S. Geological Survey Branch of Quality Systems operates the Precipitation 

Chemistry Quality Assurance project (PCQA) to provide independent, external qualityassurance for the National Atmospheric Deposition Program (NADP). NADP is 

composed of five monitoring networks that measure the chemical composition of 

precipitation and ambient air. PCQA and the NADP Program Office completed five

short-term studies to investigate the effects of equipment performance with respect to the 

National Trends Network (NTN) and Mercury Deposition Network (MDN) data quality: 

sample evaporation from NTN collectors; sample volume and mercury loss from MDN 

collectors; mercury adsorption to MDN collector glassware, grid-type precipitation 

sensors for precipitation collectors, and the effects of an NTN collector wind shield on 

sample catch efficiency.

Sample-volume evaporation from an NTN Aerochem Metrics (ACM) collector 

ranged between 1.1–33 percent with a median of 4.7 percent. The results suggest that 

weekly NTN sample evaporation is small relative to sample volume. MDN sample 

evaporation occurs predominantly in western and southern regions of the United States 

(U.S.) and more frequently with modified ACM collectors than with N-CON Systems 

Inc. collectors due to differences in airflow through the collectors. Variations in mercury 

concentrations, measured to be as high as 47.5 percent per week with a median of 5 

percent, are associated with MDN sample-volume loss. Small amounts of mercury are

also lost from MDN samples by adsorption to collector glassware irrespective of collector 

type. MDN 11-grid sensors were found to open collectors sooner, keep them open longer, 

and cause fewer lid cycles than NTN 7-grid sensors. Wind shielding an NTN ACM 

collector resulted in collection of larger quantities of precipitation while also preserving 

sample integrity.
2

Introduction

The National Atmospheric Deposition Program (NADP) National Trends 

Network (NTN) was initiated in 1978 by the Association of State Agricultural 

Experiment Stations to monitor long-term atmospheric chemistry and the effects 

pollutants have on aquatic and terrestrial systems (Nilles, 2000). The number of sites 

increased from 21 in 1978 to 261 in 2006. As of 2010, precipitation samples were 

collected from a total of 251 sites in the United States (including Alaska, Puerto Rico,

U.S. Virgin Islands) and Canada (fig. 1). 

Figure 1. Active and formerly active National Atmospheric Deposition Program / National Trends 

Network (NTN) sites, 2010.

The NADP Mercury Deposition Network (MDN) was established in 1996 to 

monitor long-term atmospheric wet-deposition of mercury (Hg) and to aid in 

understanding the effects of mercury pollution on aquatic and terrestrial systems 

(Vermette and others, 1995). The number of sites increased from 18 in 1996 to a 

maximum of 117 in 2008. As of winter 2010, precipitation was being collected from 111

sites in the United States (including Alaska and Puerto Rico) and Canada (fig. 2). The 

chronology of the number of active sites in the NTN and MDN is shown in figure 3.
3

Figure 2. Active (2010) and formerly active National Atmospheric Deposition Program/Mercury 

Deposition Network (MDN) sites, 2010.

Figure 3. Active National Atmospheric Deposition Program/National Trends Network and Mercury 

Deposition Network sites, 1978‒2009.
4

Precipitation Chemistry Quality Assurance

The U.S. Geological Survey (USGS) Branch of Quality Systems (BQS) began 

operating external quality-assurance programs under the Precipitation Chemistry Quality 

Assurance Project (PCQA) for the NADP/NTN in 1978 and for the NADP/MDN in 2004

(Latysh and others, 2005 and 2007). In addition to long-term quality-assurance programs, 

PCQA implements short-term equipment performance studies. PCQA works closely with 

the NADP Program Office (PO) and Central Analytical Laboratory (CAL) located at the 

Illinois State Water Survey in Champaign, Illinois, and with the Mercury Analytical 

Laboratory (HAL) located at Frontier Global Sciences, Inc. in Bothell, Washington. CAL 

analyzes all weekly NTN precipitation samples, and HAL analyzes all weekly MDN 

precipitation samples.

Many technical questions about the integrity and representativeness of NTN 

measurements have been addressed by PCQA throughout the past 33 years of network 

operation. Results of studies to address NTN sample integrity were completed by Graham 

and others (1987 and 1990), See and others (1989), Willoughby and others (1989 and 

1990), Gordon (1997 and 1999), and Latysh and Gordon (2004). MDN has been the 

subject of quality assurance studies by Vermette and others (1995) and Wetherbee and 

others (2004, 2005, 2006, 2009, and 2010).

Purpose and Scope

The purpose of this report is to provide information about five studies of 

equipment performance effects on NADP data quality. Findings from these five studies 

have been presented at semi-annual NADP Technical Committee meetings, and may be 

accessed at http://nadp.isws.illinois.edu/committees/minutes.aspx. This report documents 

the information in a citable form.

The five studies of equipment performance effects on NADP data quality are:

1. Sample evaporation in NTN collector (2006),

2. MDN sample loss study (2009‒2011),

3. Mercury adsorption in MDN sample trains (2009‒2010),

4. Sensitivity of NTN and MDN collector sensors (2007‒2010), and 

5. Catch efficiency of NTN collector with wind shield (2008‒2009). 

Study 1. Sample Evaporation in NTN Collector

Background and Methods

This study evaluated sample evaporation from one model of NTN collector and 

compared the observed sample evaporation to nearby meteorological measurements of 

pan evaporation, wind direction, wind speed, air temperature, relative humidity, and 

barometric pressure. The hypothesis was that sample evaporation rate was related to one 

or more of these factors, in which case, algorithms could be developed to correct sample 

concentrations for evaporation using such measurements. This study did not address the 

effects of sample evaporation on sample chemistry. Tang and others (1987) measured 

weekly Aerochem Metrics Model 301 collector (ACM) sample evaporation ranging from 

0.6–5 percent with negligible effects on sample chemistry.
5

Synthetic precipitation samples were added to empty, pre-weighed NTN buckets 

and deployed in ACM collectors for one-week periods during May 16–September 5, 

2006 at a field site in Arvada, Colorado. Initial sample depth was determined 

immediately prior to field deployment of the buckets. Sample depth was calculated from 

the sample mass as:

Sample depth, in centimeters 













 × =

−

A

msample Ρ 1

, (1)

where, msample = mass of sample in grams,

P-1 = reciprocal of density of water (1 cubic centimeter / gram), and

A = area of bucket orifice (678.9 square centimeters).

The collector lid sealed the bucket orifice, and power was disconnected from 

the ACM collector so that it would not open during the week. At week's end, the 

bucket containing the sample was removed from the ACM collector, and the final 

sample mass and depth were once again determined immediately using the same 

balance. Sample evaporation depth was calculated as the initial depth minus the final 

depth. Calculated sample evaporation was compared to onsite measurement of pan 

evaporation, which was done using a Class-A evaporation pan monitored manually on 

a weekly basis and every 4 hours electronically using a float gage and Campbell 

Scientific CR‒10 data logger (fig. 4).

Figure 4. Weekly sample evaporation from a National Trends Network Aerochem Metrics Model 

301 wet-deposition collector and weekly pan evaporation at Arvada, Colorado, May 16–

September 5, 2006.
6

Hourly air temperature, wind speed, and wind direction were measured onsite 

using instrumentation operated by the Colorado Department of Public Health and 

Environment (CDPHE), Air Quality Control Division. Hourly CDPHE data for the 

Arvada site were provided by Frank Martelli (CDPHE, written commun., 2006). Relative 

humidity and barometric pressure were measured nearby at the Citizen Weather Observer 

Program site AR893 in Arvada, Colorado. Weekly mean wind direction ranged from 

southeast to southwest for this study, which was done during summer. The data were 

analyzed graphically to identify relations between the meteorological parameters and 

sample evaporation. Kendall’s Tau (T) correlation coefficients (Helsel and Hirsch, 1992)

were estimated to describe relations of sample evaporation to meteorological data using R 

software version 12.2.2 (available at URL: http://CRAN.R-project.org/). Statistically 

significant (α=0.05 significance level) correlations with T greater than 0.5 were 

considered relevant.

Results and Discussion

Sample evaporation correlated with pan evaporation (Kendall Tau =0.69, 

p=0.0003), but no evidence of correlation was found between sample evaporation and 

wind direction, wind speed, air temperature, or barometric pressure (figs. 5‒7), all with 

Kendall Tau less than 0.5 as indicated in table 1. However, figure 7 illustrates a 

significant (α=0.05), strong correlation (Kendall Tau =-0.77) between weekly sample 

evaporation and mean relative humidity whereby sample evaporation increases with 

decreasing relative humidity. Weekly sample evaporation depth is not correlated with the 

initial sample volume at the time of deployment to the field (fig. 8).

Weekly NTN sample-volume evaporation from the ACM collector ranged 

between 1.1–33 percent with a median of 4.7 percent. This is a site-specific study 

performed during summer at an altitude of approximately 1,660 meters (m). Results 

might not be representative of the entire NTN, but they are indicative of changes in NTN 

samples that occur after collection. 

There are other important differences between the study protocol and normal 

NTN samples. A fixed sample volume was added to the collector on the first day of each 

week of the study, and the collector did not open for the week. Many NTN samples are a 

composite of more than one rainfall event that does not always start on the first Tuesday 

of bucket deployment.; the collector may open and close several times during a week.

Conclusion

Sample evaporation is strongly correlated with mean relative humidity (Kendall 

Tau=-0.77 at α=0.0001 significance level), but not air temperature, wind speed, wind 

direction, or barometric pressure (figs. 5‒7). A weak correlation (Kendall Tau=-0.38 at 

α=0.041) between weekly percent sample evaporation and initial sample volume was 

observed despite the fact that evaporation occurs at the liquid-air interface of the sample

surface area, which is independent of volume in the cylindrical NTN bucket.
7

Figure 5. Weekly sample evaporation from a National Trends Network Aerochem Metrics Model 

301 wet-deposition collector and weekly mean wind direction from north and wind speed at 

Arvada, Colorado, May 16–September 5, 2006.
8

Figure 6. Weekly sample evaporation from a National Trends Network Aerochem Metrics Model 

301 wet-deposition collector and weekly mean air temperature at Arvada, Colorado, May 16‒

September 5, 2006.

Figure 7. Relation of weekly mean relative humidity and mean barometric pressure to weekly 

sample evaporation from a National Trends Network Aerochem Metrics Model 301 wetdeposition collector at Arvada, Colorado, May 16–September 5, 2006.
9

Figure 8. Weekly sample evaporation from a National Trends Network Aerochem Metrics Model 

301 wet-deposition collector and initial sample volumes at Arvada, Colorado, May 16–

September 5, 2006.

Study 2. MDN Sample Loss Study

Background and MDN Data Analysis

NADP/MDN weekly wet-deposition samples are analyzed for total mercury (Hg) 

and, in some instances, for methyl mercury. In order to preserve Hg in the collected 

sample, MDN sample bottles contain 20 mL of one-percent (volume/volume) 

hydrochloric acid (HCl) preservative when deployed to field sites.

The MDN glass sample-collection train and collector housings are designed to 

reduce exposure of the collected sample to the open atmosphere and thus minimize

sample loss by evaporation. Despite these efforts to minimize sample loss, field data 

suggest that sample loss does occur.

MDN site operators complete an MDN Observer Form (MOF) for each weekly 

sample to document sampling conditions and sample integrity. A review of MOFs for the 

period March 1996‒November 2010 revealed that some sample bottles were empty at the 

end of the 7-day sampling period. In other cases, liquid was present at the end of the 

sampling period, but the volume of liquid was less than 20 mL. In many instances this 

occurred during weeks with neither precipitation nor collector cycles (that is, collector 

not opening and closing again). These occurrences prompted investigation of the extent 

and cause(s) of MDN sample evaporation. 

The NADP PO and USGS BQS conducted a multi-phase study during 2010‒2012 

to: (1) assess the extent of MDN sample loss, (2) identify factors that impact MDN 
10

sample loss for both types of MDN collectors, modified ACM and N-CON Systems, Inc. 

(N-CON), and (3) determine the impact of sample volume loss on total Hg

concentrations. Results from each phase of this study are presented in this report.

Phase 1 of Study—Extent of MDN Sample Loss

The objective of this phase was to evaluate the extent of sample loss in MDN 

samples across the network. The MDN database was initially considered to determine the 

number of samples where volume was less than 20 mL. Samples met the following 

criteria:

• No leaks reported during transport from the laboratory to the site,

• No leaks reported during transport from the site to the laboratory, 

• Precipitation sensor and collector motor operated properly, 

• No precipitation reported during the sample period, and

• No quality assurance samples.

Evaporation probably occurs with all MDN samples, not just those that meet the 

criteria described above. However, the volumes of liquids in the sample bottles are not 

monitored during the course of the sampling period. In order to estimate potential effects 

on field samples, this study evaluated loss of preservative volume during dry weeks. 

Sample preservative loss cannot be quantified when precipitation occurs and is collected. 

For Phase 1, samples collected between March 1996 and November 2010 were 

considered. During that time 5,185 samples met the criteria of the study. Table 2 lists the 

number and the percentage of samples that had volumes less than 20 mL, the initial 

volume of preservative. Values shown are based on the amount of sample loss during the 

7-day, Tuesday to Tuesday, sampling period. Because at least some evaporation is 

demonstrated in over 84 percent of the samples meeting the study criteria, Phase 2 of the 

study was implemented to identify causes for the observed evaporation. 

Having determined the existence of MDN preservative loss, the next step was to 

evaluate the factors that contribute to evaporation of actual field samples. Identification 

of the factors was needed for NADP to take actions to help reduce sample loss. Toward 

this end, the following questions were evaluated:

• Are the two versions of the modified-ACM collector and the N-CON 

collector affected equally?

• Does geographic location contribute to sample loss?

• Does collector interior temperature contribute to sample loss?

• Does integrity of the lid seal contribute to sample loss?

• Does airflow through the collector contribute to sample loss?

To address the first two questions, the Phase 1 data were screened for preservative

volume loss (4,380 samples) and evaluated with respect to collector type: modified ACM 

versus N-CON. The N-CON MDN collector was approved for network use in October 

2006. As such, fewer sites have the N-CON collector, and fewer samples were collected 

with the N-CON collector. It is unknown whether equal use (that is, number of sites, and 

duration of use) of the two collectors would have yielded the same results. Figures 9 and 

10 illustrate the number and percentage of samples with measureable preservative 

evaporation loss at each site, respectively, by collector type.
11

Figure 9. Mercury Deposition Network samples with preservative volume loss in modified ACM and N-CON precipitation collectors during weeks 

with no precipitation, March 1996–November 2010.
12

Figure 10. Mercury Deposition Network percent preservative volume loss in modified ACM and N-CON precipitation collectors during weeks with no 

precipitation, March 1996‒November 2010.
13

Data in figures 9 and 10 indicate greater preservative loss with the modified ACM 

than with the N-CON collector. The greatest preservative volume loss occurred in the 

southwestern U.S. suggesting that geographic location affects sample loss. However, the 

majority of collectors used at these sites are the modified ACM type. Additional field 

experimentation is required to determine whether the increased volume loss at these sites 

is due to the collector characteristics or climatic conditions, such as wind speed, 

temperature, and relative humidity.

Phase 2 of Study—Factors that Affect MDN Sample Loss

Having demonstrated preservative loss in Phase 1, Phase 2 examined collector 

influence on field-sample evaporation. One modified ACM collector and one N-CON 

collector were specially configured for testing purposes and located outside the PO 

facility in Champaign, Illinois. Testing began on December 9, 2009, and continued 

through March 1, 2011. 

Phase 2 Methodology

Phase 2 field testing included:

• 1 modified ACM collector without a precipitation sensor to ensure no 

openings,

• 1 N-CON (standard, single-chimney version) collector without a

precipitation sensor,

• 2 sample bottles, one for each collector containing an initial 500 mL of 

preservative, and

• a sampling period of 7 days.

The collectors were deployed to the field with the lids tied in the closed position 

using bungee cords. This prevented the collectors from exposing the sample train and 

bottle during the course of the sampling period. It is likely that the bungee cords 

improved the seal between the lid pad and funnel. Therefore, actual evaporation observed 

in the field would likely be greater. Sample bottles were weighed at the start of each 7-

day sampling period (initial mass) and again at the end of the sampling period (final 

mass). Sample volume loss was determined as the difference between the initial mass and 

the final mass; assuming a density of 1 gram per cubic centimeter (1 g/cm3 or 1 g/mL) for 

water. All testing included the measurement of daily minimum and maximum 

temperatures inside each collector, visual observation of the collector lid seal, and 

recording whether the collector cooling fans were operational or not. During winter, the 

collector heaters ran continuously. Thus, internal temperature of the collector is not a 

reflection of ambient conditions.

Figure 11 shows each of the two MDN collector types configured to have a poor 

lid seal. For this configuration, a spacer was placed between the lid pad and the funnel, 

creating a gap between the two. Though the sample remains protected by the sample 

train, the gap likely allows a more direct path for evaporation.

Figures 12, 13, and 14 illustrate the sample loss data obtained for each of the 

parameters tested. Data in figure 12 suggest that field sample evaporation is not related to 

air temperature inside the collectors because measured evaporation amounts are generally 

constant over the range of measured maximum temperatures with the exception of four 
14

measurements for the modified ACM. More evaporation was observed from the modified 

ACM samples than from the N-CON samples.

Figure 11. Photographs of bad lid seal configuration for the modified ACM collector (top) and the 

N-CON collector (bottom).
15

Figure 12. Field sample volume lost (percent) over weekly periods in N-CON and modified 

Aerochem Metrics (ACM) precipitation collectors and maximum weekly temperatures of the air 

inside the collectors, December 1, 2009–May 7, 2010.

Data in figure 13 indicate that sample evaporation might have increased for 4 of 

15 weekly measurements for the modified ACM when the lid seal was compromised. 

However, the same effect was not observed for the N-CON.
16

Figure 13. Percentages of initial sample volumes lost over weekly periods in N-CON and modified 

Aerochem Metrics (ACM) precipitation collectors and corresponding integrity of collector-lid 

seals, December 1, 2009–May 7, 2010.
17

Figure 14. Percentages of initial sample volumes lost over weekly periods in N-CON and modified 

Aerochem Metrics (ACM) precipitation collectors and corresponding configurations of air flow 

inside the collectors, March 1, 2010–October 29, 2010.

Results in figure 14 indicate that field-sample evaporation was higher from 

samples in the modified ACM collector when the cooling fan was operated continuously. 

When both collectors were configured so that the cooling fans operated continuously, 

sample loss was consistently greater with the modified ACM collector (5 to 15 percent

sample loss). Figure 15 is a composite of figures 12, 13, and 14. Two conclusions may be 

drawn from the results of these tests. First, samples in the modified ACM collector are

affected to a greater extent than samples in the N-CON collector. Second, air flow within 

the collector is the most consistent factor affecting sample loss through evaporation. 

Having made these conclusions, the study entered into Phase 3 to evaluate the effect of 

field sample volume loss on actual Hg concentrations.
18

Figure 15. Percentages of initial sample volumes lost over weekly periods in N-CON and modified 

Aerochem Metrics (ACM) precipitation collectors and corresponding internal collector 

temperature, lid seal integrity, and internal air flow configurations for the collectors, December 

1, 2009–November 17, 2010.

Phase 3 of Study—Effects of Sample Loss on Mercury Concentrations

The following experimental design was used for Phase 3 of the field study on the 

effects of sample volume loss on Hg concentrations:

• 2 collectors (1 modified ACM collector, 1 N-CON collector),

• 2 cooling fans (1 ACM cooling fan, 1 Loda Electronics cooling fan),

• Weekly pairs of sample bottles, one for each collector, each containing an 

initial 20 mL of preservative, 

• Quality Control (QC) samples of known total Hg concentration, 

• A sampling period of 7 days, and

• Total Hg analysis by the HAL 

Clean glassware and sample bottles containing preservative were provided by the 

HAL on a weekly basis. The HAL provides glassware, sample bottles, and all total Hg

analyses by Cold Vapor Atomic Fluorescence for the MDN.
19

At the start of each sampling period, the sample bottles were weighed. Then

approximately 100 mL of a QC sample of known Hg concentration was added to each 

bottle, and the sample bottles were weighed again before being installed in the collectors

with clean glassware (that is, funnel and thistle tube). The collectors were configured 

without sensors, and the collector lids were secured to prevent them from cycling during 

the sampling period. At the end of the sampling period the bottles were re-weighed to 

determine the mass loss during the sampling period, and were then shipped to the HAL 

for analysis.

In most cases, the sampling period was 7 days. In some cases, a longer sampling 

period was used due to the availability of personnel and clean glassware to support the 

study. As with Phase 2 of this study, samples were deployed using one modified ACM 

collector and one N-CON collector. One month into the study, the cooling fan in the 

modified ACM collector was replaced with a more powerful fan as used in the Loda 

Electronics version of the ACM collector due to failure of the original ACM fan. Table 4

contains specifications for the cooling fans used in the 2 versions of the ACM collector. 

Consistent with the Phase 2 experimental results, sample volume loss from the modified 

ACM collector was higher for the collector with a Loda Electronics cooling fan, which 

has a higher speed and moves more air through the collector. Results from the testing are 

presented for the modified ACM in tables 5 and 6 and for the N-CON collector in table 7. 

Figure 16 illustrates the results with “modified ACM1” being the Aerochem Metrics 

version of the modified ACM collector and “ Loda Electronics ACM” being the Loda 

Electronics version of the collector.

The QC samples used in this phase of the study were provided by the USGS and 

are from the USGS MDN Interlaboratory-Comparison Program (Wetherbee and others, 

2010). The chemistry of these samples is well defined. Nine different laboratories 

participate in the Interlaboratory-Comparison Program, including the HAL. Results from 

each of the participating laboratories were used to determine the most probable value 

(MPV) for Hg concentration in each of the QC solutions. The QC samples were 

preserved with 1-percent HCl and have Hg concentrations ranging from approximately 6 

to 22 nanograms per liter (ng/L). The concentration range was chosen as it spans the 

interquartile range of MDN field sample concentrations. Most probable value

concentrations for each QC sample were provided by USGS after the chemical analysis 

was complete. Hg concentrations for each the QC solutions were unknown to both PO 

staff and staff of the HAL during the study. As the samples evaporate, the acidity and 

associated preservation of the Hg in the samples can change. However, the acidity of the 

QC samples was not monitored. Tables 5‒7 present the results from each of the three 

collectors tested in Phase 3 of the study. Figures 16 and 17 illustrate these results. Hg

concentration differences were calculated as measured-minus-most probable value 

(MPV) for the QC solutions. Percent Hg mass gained (fig. 17) is probably from various 

sources including laboratory and field contamination.
20

Figure 16. Relation of percent sample volume loss and mercury concentration difference for three 

MDN collector types: N-CON, modified Aerochem Metrics (ACM), and Loda Electronics ACM.

Figure 17. Relation of sample volume loss to percent mercury mass loss for three MDN collector 

types: N-CON, modified Aerochem Metrics (ACM), and Loda Electronics ACM.
21

Conclusions

The following conclusions can be made from the three phases of this study:

• MDN samples in modified ACM collectors are subject to greater volume 

loss than those in an N-CON collector.

• MDN sample-volume loss occurs more frequently in low relative humidity 

regions of the USA, such as the western and southwestern regions of the 

country.

• Air flow through the collector housing increases MDN volume loss due to 

operation of the cooling fan.

• MDN samples deployed with the Loda Electronics version of the modified 

ACM collector undergo greater volume loss than those deployed with the 

original (Aerochem Metrics) version of the modified ACM collector. This 

difference is due to differences in the cooling fan used with the two 

versions of the collector.

• Sample chemistry is affected by MDN volume loss. In some instances Hg

is lost thus decreasing the total Hg concentration in the sample. In other 

instances, Hg is concentrated in the sample resulting in higher total Hg

concentrations.

• The rates of loss of sample volume, preservative volume, and Hg are not 

consistently proportional.

This study demonstrates that MDN sample evaporation has important 

implications for MDN data and field operations. Remediation of the modified ACM 

evaporation problem, including potential reconfiguration of the modified ACM 

collector’s glass sample train, could improve representativeness of MDN samples. 

Additional testing using an N-CON type thistle tube in the modified ACM collector and 

other potential solutions are needed.

Study 3. Mercury Adsorption in MDN Sample Trains

Background and Methods

MDN sample bottles are deployed containing 20 mL, 1-percent (volume/volume) 

HCl preservative pre-charge to prevent adsorption of Hg onto the glassware. Glass has 

the lowest adsorption rate (0.026‒1.13 micrograms per square meter (μg/m2

)) of 

commonly used materials for sample containers (Rosain and Wai, 1973). Adsorption can 

also be reduced by using HCl as a preservative (Rong and others, 2001). While deployed, 

some of the 1-percent HCl preservative refluxes within the sample train (Bob Brunette, 

Frontier Global Sciences, Inc., oral commun., 2009), which helps prevent adsorption of 

Hg to the walls of the MDN glassware.

The Modified ACM and N-CON MDN collectors use different glass thistle tubes 

to collect the precipitation sample (fig. 18). Both sample trains consist of a borosilicate 

glass funnel, thistle tube, and sample bottle, but the N-CON thistle tube extends down 

into the sample bottle, while the Modified ACM thistle tube does not. As the sample 

droplets travel from the less acidic funnel to the more acidic sample bottle, there is a

potential for loss of Hg to the walls of the thistle tube. Differences in the sample train 
22

configurations led to concern that Hg concentrations may be affected differently by 

adsorption between the two sample trains.

Figure 18. Thistle-tube configurations used with the modified N-CON collector (left) and the ACM 

collector (right).

To address these concerns, adsorption of Hg to the Modified ACM and N-CON 

sample trains was compared at 18 sites. First, 5 Modified ACM collectors in Florida, 

Indiana, Oklahoma (2 sites), and South Carolina were compared to 5 N-CON collectors 

in Georgia, Kansas, New York, Utah, and West Virginia for rain events. Then, 4 

Modified ACM collectors in Indiana, Minnesota, and Pennsylvania (2 sites) were 

compared to 4 N-CON collectors in Nebraska, New York, Idaho, and Utah for snow

events. Results were used to evaluate the dependence of precipitation type on Hg 

absorption. 

USGS provided each site operator with a cooler containing two standard MDN 

glass sample bottles and a 1-liter Teflon bottle. One of the MDN glass sample bottles was 

a “trip blank” sample containing either 170 mL or 320 mL of 1-percent HCl. The 

different volumes were used to help conceal the control sample. The “trip blank”

remained sealed until it was analyzed by the HAL. The second glass MDN sample bottle 

contained the standard 20 mL HCl pre-charge only. This bottle was used to collect 

rinseate from the used sample train. The 1-L Teflon bottle contained 1-percent HCl in a 

volume of either 250 mL or 500 mL, a portion of which was used to rinse the sample 

train in the field. The HCl remaining in the Teflon bottle was also analyzed for total Hg 

concentration and is referred to as the “bottle sample.”

After a week during which precipitation occurred, the field sample bottle was 

processed as usual, but the used sample train was left in place. This is different from 

standard MDN protocol whereby the complete sample train is replaced weekly. The 
23

second MDN sample bottle containing 20 mL of HCl was installed into the collector, and 

half of the 1-percent HCl solution in the 1-L Teflon bottle was poured through the glass 

sample train to create the “sample-train sample.” Both the sample-train sample and the 

bottle sample in the 1-L Teflon bottle were capped and placed in the cooler with the “trip 

blank”. All three test samples, plus the composite MDN sample from the previous week,

were shipped to the HAL for total Hg analysis. The identities of the sample-train and 

control samples were not revealed to the HAL and were known only by USGS and the 

site operators. The flowchart in figure 19 illustrates the study design.
24

Figure 19. Flowchart of the sample-train study for the Mercury Deposition Network.
25

Results and Discussion

Average Hg concentrations were calculated for the HCl solutions remaining in the 

original Teflon bottles. Hg adsorption to the sample trains is estimated by the median 

sample-train-minus-average control Hg concentration differences in table 8. The results 

indicate that there is a measureable amount of Hg that adsorbs to the glass sample trains 

in both the modified ACM and N-CON wet-deposition collectors.

There is no statistically significant difference between the collectors with respect 

to Hg adsorption as represented by Hg concentration differences per the Wilcoxon 

signed-rank test at the α=0.05 significance level. Hg concentration differences are 

significantly (α=0.05) higher for rain than for snow per the Wilcoxon rank sum test. 

Negative Hg concentration differences for GA33 and NE15 indicate potential 

contamination of the control samples with trace amounts of Hg, but the negative 

differences could also be due to analytical variability. Negative differences are

interpreted as zero values for the purposes of this study.

No correlation was observed between the mass of Hg collected in the previous 

week’s precipitation samples and the mass of Hg adsorbed to the sample trains (Kendall’s

Tau=0.238, p=0.17). However, the KS03 sample collected for the previous week (June 

10‒16, 2009) had the largest mass (18,154 ng) of Hg among all sites included in this

study, and it also exhibited the largest amount of adsorbed Hg to the sample train (1.384

ng/L). The results indicate that there is a small mass of Hg that absorbs to the sample 

trains during sample collection.

Study 4. Sensitivity of NTN and MDN Collector Sensors

Background and Methods

Sensors for ACM wet-deposition collectors are used to expose the collection 

bucket to the atmosphere at precipitation onset and then cover it again at cessation of 

precipitation events. The representativeness of the samples decreases with delay between 

precipitation onset and collector openings due to missed aerosol washout at precipitation 

onset (Raynor and McNiel, 1979; Pellett and others, 1984; Schroeder and others, 1986 

and 1987). Sample representativeness also decreases when collectors remain open after 

cessation of precipitation as contamination may be introduced from dry deposition or 

other foreign materials (Sisterson and others, 1985; Tang, 1987). Open collectors also 

increase the potential to affect sample integrity. Consequently, the sensitivity of the 

precipitation sensor is important for representative collection of wet-deposition samples. 

NADP ACM wet-deposition collectors use two types of grid-design precipitation 

sensors: a 7-grid model for NTN and an 11-grid model for MDN (fig. 20). The MDN 

began deployment of modified ACM collectors using the 11-grid sensor instead of the 7-

grid NTN sensor in 1999. NTN continued to use the 7-grid sensor out of concern that a 

change to the 11-grid sensor might cause a shift in sample concentration bias. This study 

is part of renewed efforts to increase consistency between NTN and MDN field 

instrumentation. NADP approved optical sensors as an alternative to grid sensors in 2006. 

As N-CON collectors with optical sensors replace ACM collectors at NTN and MDN 

sites, differences in grid sensor performance also will need to be considered along with 

differences in optical and grid sensor performance. For this study, comparison of 7-grid 
26

and 11-grid sensor performance was accomplished by monitoring openings and closings 

of collector lid cycles recorded by a Campbell Scientific, Inc. data logger internal to a colocated ETI model NOAH-IV electronic rain gage (ETI Instrument Systems, Inc., Fort 

Collins, Colo.).

Figure 20. Mercury Deposition Network 11-grid sensor and National Trends Network 7-grid sensor 

for Aeorchem Metrics precipitation collectors.

NADP NOAH-IV rain gages are programmed to report precipitation when the 

gage’s optical sensor counts a minimum of 16 particles falling into the gage per minute. 

The data loggers count and store the number of seconds within each quarter hour when 

precipitation is detected and the collector lid is open. This parameter is called “wet 

exposure”. The number of seconds within each 15-minute period during which 

precipitation is not detected but the lid remains open is reported as “dry exposure”. 

A third NADP parameter, “missed exposure” is the number of seconds within the 

quarter hour when precipitation is detected, but the collector is closed. “Missed exposure” 

is arguably a more subjective parameter because the gage’s detection of precipitation is 

not confirmed by the collector sensor, which is triggered by precipitation completing an 

electrical circuit. Similarly, the rain gage’s optical sensor might detect particles that are 

not precipitation, such as blowing snow, dust, insects, and pollen. 

Comparison of the sensitivity of 7- and 11-grid sensors was done using data 

obtained from NADP sites with co-located NTN and MDN equipment. That is, ACM 
27

collectors with 7-grid sensors, and modified ACM collectors with 11-grid sensors, 

respectively. Data for the period May 22, 2007 to February 24, 2009 were obtained from 

the NADP website, http://nadp.isws.illinois.edu/precip/, on February 28, 2011. Table 9 is 

a list of the sites used in the analysis, and the associated periods of record.

Sensitivity of the 7-grid and 11-grid sensors to precipitation onset and cessation 

was compared. For each storm event in the record, the NTN or MDN collector that

opened first and closed first was determined. The times of day when wet exposure began 

to be recorded at the beginning of an event and when it stopped being recorded for the 

same event were compared for the co-located NTN and MDN collectors. This 

information is reported for each co-located NTN/MDN site.

Results and Discussion

The 11-grid sensors opened the collectors sooner than did the 7-grid sensors at 16 

of the 20 sites (fig. 21) after precipitation onset. The results in figure 21 also indicate that 

7-grid sensors closed the collectors sooner than did the 11-grid sensors at 12 of the 20 

sites.
28

Figure 21. Comparison of number of precipitation events when 7- and 11-grid sensors opened and 

closed their respective collectors first at 20 co-located National Trends Network (NTN) and 

Mercury Deposition Network (MDN) sites.
29

Daily wet-, dry-, and missed-exposure times were summed for each collector in 

the study, and 7-grid –minus- 11-grid differences were calculated for each of the three

exposure times. Figure 22 shows mean 7-grid –minus- 11-grid exposure differences on a 

monthly basis. More wet exposure was recorded for the 11-grid sensors than for the 7-

grid sensors for 10 months of the year, especially during the winter months of November 

-December. More dry exposure was recorded for the 11-grid sensors than for the 7-grid 

sensors for 7 months of the year. The 7-grid sensors caused the collector lids to cycle 

more during precipitation events than did the 11-grid sensors for all months except during 

February (fig. 22).
30

Figure 22. Comparison of wet- and dry-exposure differences and collector cycle differences for 

7- and 11-grid sensors at 20 co-located National Trends Network and Mercury Deposition 

Network sites.
31

The data obtained indicate that the 11-grid sensor, used with the MDN modified 

ACM collector, opens the collector sooner and keeps it open longer than does the 7-grid 

sensor, used with the NTN ACM collector. The 7-grid sensors cycle the collector lids

more than does the 11-grid sensor, which could be advantageous for limiting dry 

exposure.

Retrofit of NTN collectors with 11-grid sensors could be expected to increase 

constituent concentrations in NTN samples because the collectors would open sooner and 

catch more atmospheric washout at early onset of precipitation. The 11-grid sensor would 

also be expected to keep the NTN collectors open longer during periods with no 

precipitation. This could promote sample loss from evaporation or contamination from 

dry deposition. Retrofit of NTN ACM collectors with 11-grid sensors would lessen lid 

cycling by the motor and thus lower power consumption and save wear of the motor. This 

might be advantageous for sites that use direct current (DC) power, where power 

conservation can be important. A retrofit of 7-grid sensors with 11-grid sensors for NTN 

ACM collectors is not planned by NADP as of this writing.

Study 5. Catch Efficiency of NTN Collector with Wind Shield

Background and Methods

Wind-blown precipitation causes under-representation of precipitation depth

measurements by precipitation gages, especially for snow (Alter, 1937; Weiss, 1961, 

Brown and Peck, 1962; Bigelow and Denning, 1990; Yang and others, 1998 and 1999). 

Various wind shielding devices have been used to improve the catch of precipitation 

gages, such as the Alter wind shield, which is currently used at many NADP sites (Alter, 

1937). Wind shields are required for rain gages at NADP sites that receive at least 20 

percent of their annual precipitation as snow (see 

http://nadp.sws.uiuc.edu/newissues/newgages/windshields.aspx, accessed July 23, 2012). 

Similar types of wind shields have not been approved for use with precipitation 

collectors, due to concerns of potential sample contamination from rain splash from the 

surface of the wind shield. There is also the potential for birds to perch on the shields, 

thus creating another potential source of contamination. 

This study assessed a wind shield for ACM precipitation collectors at the National 

Center for Atmospheric Research (NCAR) Marshall Field Site near Marshall, Colorado

(fig. 23). The wind shield was designed in consultation with NCAR personnel 

experienced in testing various wind shields (Scott Landolt, NCAR, personal commun., 

2008). Made from materials commonly available in hardware stores, the wind shield is 

plastic construction mesh supported by 0.75-inch diameter electrical metal conduit poles 

attached to the ACM body using metal flagpole holders and self-tapping screws. The 

mesh is attached to the poles using locking plastic electrical ties. The flagpole holders 

keep the mesh shield angled away from the collector buckets. The wind shield is similar 

in shape to the Wyoming-type shield used with precipitation gages (Yang and others, 

2000). 

The porous wind shield creates self-canceling turbulent conditions over the top of 

the collector and prevents the shield from acting as a sail and catching too much wind, 

even though collectors are anchored to the ground with rebar stakes. From October 31, 

2007 to December 23, 2008, two ACM collectors were operated independently, each with 
32

its own standard NTN 7-grid sensor (see Study 4). One collector was shielded and the 

other was not. The ACM sensor is located inside and within a few inches of the shield. 

From December 23, 2008 to April 6, 2009, both collectors were operated by the same 

sensor on the unshielded collector so that both collectors opened within a few seconds of 

each other. The later configuration provided an additional control on the study so that the 

effects of the wind shield could be evaluated without shielding the sensor.
33

Figure 23. Co-located sampler installation at Marshall Field, Colorado showing placement of 

standard and wind-shielded ACM collectors and location of precipitation gage.
34

The two collectors were installed at Marshall Field; a windy, easily accessed, and 

secure site with many continuously operating meteorological instruments. Official 

precipitation depth is measured by the “Geonor North” gage installed inside a dual fence 

inter-comparison reference (DFIR) shield at Marshall Field (fig. 23). Meteorological data 

are collected at 2 meters above the land surface every minute and include air temperature, 

wind speed and direction, and relative humidity. Precipitation depth and meteorological 

data for Marshall Field were obtained from Scott Landolt of NCAR, (oral and written 

communs., 2009). Meteorological data for the site can also be obtained from the NCAR, 

Marshall Field web site at 

http://www.rap.ucar.edu/projects/winter/sites/marshall/?e10i4rljob9nfdsbdk4m4meud3, 

accessed February 28, 2011. 

Meteorological data were extracted from the continuous records for the 1-minute 

intervals during which precipitation was recorded by the Geonor North gage. It was 

assumed that the wet-side buckets on the collectors were most likely exposed to the 

atmosphere during these periods. Mean, minimum, and maximum values of temperature, 

wind speed, wind direction, and wind direction standard deviation for the periods with 

precipitation were computed for the weekly sample-collection intervals.

Weekly samples were collected from both the shielded and standard, unshielded 

ACM collectors for November 20, 2007, to March 25, 2008, and October 17, 2008, to 

April 6, 2009. Samples sealed in the original, pre-weighed collection buckets with preweighed lids were transported to the PCQA laboratory at the Denver Federal Center 

(DFC), where they were weighed on a balance. The previously determined empty bucket 

and lid weights were subtracted from the total weight to calculate the mass and volume of 

precipitation collected during the previous week. Shielded-minus-unshielded collector 

sample-volume differences were calculated. The mass of precipitation was converted to 

depth by equation (2), which incorporates the area of the bucket orifice (678.9 cm2

):

Depth (inches) = mass of liquid precipitation (grams) • 0.00058, (2)

where: 0.00058 = (1 gram/cm3 × 678.9 cm2 × 2.54 cm/inch)-1 .

The ability of a precipitation collector to catch a representative portion of the 

entire precipitation depth is characterized by catch efficiency. Catch efficiency is 

computed as the ratio of the precipitation depth measured by the collector, to the rain 

gage precipitation depth at the same location (equation 3).

Catch efficiency = ( )

( )

weekly rain gage precipitation depth inches

weekly collector catch depth inches

 (3)

Weekly samples were measured for pH and specific conductance in the PCQA 

laboratory in Building 95 at the DFC. Solution pH, a measure of acidity, is the negative 

base-10 logarithm of the hydrogen-ion concentration in equivalents per liter. pH was 

measured with a Beckman Phi-11 pH meter and ion-specific electrode calibrated with 

Orion low-ionic strength pH 4.0 and 7.0 buffers. Specific conductance was measured 

with a Radiometer CDM3 conductivity meter and type CDC 314 cell calibrated using a 

50 microSiemens per centimeter (μS/cm) aqueous potassium chloride standard. These 

measurements provided data to imply how potential differences in catch efficiency might 
35

affect sample chemistry without obtaining complete chemical analyses of solute 

concentrations in the samples. Only complete paired data, whereby sufficient volume was 

obtained for analysis by both collectors, were compared statistically. The unshielded 

collector did not obtain sufficient volume for analysis of specific conductance and pH for 

4 and 6 weekly samples, respectively. 

Results and Discussion

During water year 2008 (October 1, 2007–September 30, 2008, WY08), 15

paired, weekly samples were collected, and an additional 4 weekly samples were

collected by the shielded collector that were missed by the unshielded collector. During 

water year 2009 (WY09), 13 paired, weekly samples were collected, and an additional 2 

weekly samples were collected only by the shielded collector (fig. 24). Collector catch

was significantly (α=0.05) greater for the shielded collector per the Wilcoxon Signed 

Rank Test on the paired sample volumes (p<0.0001). There was no significant difference 

(α=0.05) in shielded-minus-unshielded collector catch differences for the two different 

sensor configurations, independent versus single-sensor modes, per the Wilcoxon Rank 

Sum Test (p=0.1728). Excluding weeks with zero standard ACM collector catch, the 

shielded collector exhibited a +39 percent (median) increase in catch efficiency over the 

unshielded collector (fig. 25).

Figure 24. Time series of unshielded-minus-shielded collector catch differences for co-located 

wet-deposition collectors operated at Marshall Field, Colorado during water years 2008‒09 

(WY08‒WY09).
36

Figure 25. Relation of shielded and unshielded collector catch for co-located wet-deposition 

collectors operated at Marshall Field, Colorado during water years 2008‒09 (WY08‒WY09).

Results in figure 26 indicate no statistical correlation between shielded-minusunshielded collector catch difference and average or maximum wind speed during 

precipitation (Kendall’s Tau = -0.011 and 0.183, respectively). However, the distribution 

of the data indicate increasing effectiveness of the shield with increasing wind speed up 

to a maximum effectiveness at a mean wind speed of 5 m/s (meters per second). Then, 

the wind shield’s effectiveness decreases with further increasing wind speed to

approximately 9 m/s where the wind shield ceases to be effective. Collector catch 

efficiency tended to be greater when the 2-meter elevation wind direction was from the 

northeast to southwest. Mean relative standard deviation of wind direction (wind 

direction variability, also known as Sigma theta) during precipitation and shielded-minusunshielded collector catch difference are weakly correlated (Kendall’s Tau = 0.35, p = 

0.0103), but this is not evident in the scatterplot of the data in figure 27.
37

Figure 26. Sample-volume differences for co-located standard and wind-shielded wet-deposition 

collectors, with maximum and average wind speed during precipitation at Marshall Field, 

Colorado during water years 2008‒2009 (WY08-WY09).
38

Figure 27. Catch efficiency and sample-volume differences, for co-located wind-shielded and 

standard wet-deposition collectors, related to average wind direction and wind direction relative 

standard deviation during precipitation at Marshall Field, Colorado during water years 2008‒

2009.
39

The wind shield’s effect on snow catch is indicated by a weak negative 

correlation (Kendall’s Tau = -0.2796, p=0.041) between minimum temperature during 

precipitation and shielded-minus-unshielded catch difference (fig. 28). This implies that 

shielded-minus-unshielded collector catch differences are greater for frozen precipitation 

than for liquid precipitation. The catch differences are plotted versus mean temperature 

during precipitation in figure 28 for comparison. Additionally, there were 6 weeks when 

the shielded collector obtained a sample when the unshielded collector did not, and 5 of 

these samples were for snow.
40

Figure 28. Sample-volume differences for co-located standard and wind-shielded wet-deposition 

collectors related to average and minimum air temperature during precipitation at Marshall 

Field, Colorado during water years 2008‒2009 (WY08‒WY09).
41

Specific conductance was significantly (α=0.05) lower for samples from the 

shielded collector compared to the unshielded collector per the Wilcoxon Signed Ranks 

test (p=0.004). Results in figure 29 show that the shielded collector had lower specific 

conductance for 15 of 18 weekly sample pairs. The median shielded-minus-unshielded 

specific conductance difference is -2.6 μS/cm.

Figure 29. Specific conductance of precipitation samples obtained by co-located wind-shielded 

and standard wet-deposition collectors at Marshall Field, Colorado, during water years 2008‒

2009.

Results in figure 30 show that 13 of 17 samples from the shielded collector had 

higher pH than the unshielded collector. However, pH of the samples from the shielded 

and unshielded collectors were not significantly (α=0.05) different per the Wilcoxon 

Signed Ranks test (p=0.1475). The median shielded-minus-unshielded hydrogen-ion 

concentration difference (calculated from pH) is -0.08 microequivalents per liter (μeq/L).
42

Figure 30. pH of precipitation samples obtained by co-located wind-shielded and unshielded wetdeposition collectors at Marshall Field, Colorado during water years 2008‒2009 (WY08 to 

WY09).

The results indicate that sample pH and specific conductance are potentially 

affected by the wind shield in three ways: (1) the shielded collector could open later than 

the unshielded collector, thereby missing acidic atmospheric deposition at the onset of 

precipitation, (2) the unshielded collector could catch more dry deposition or windblown 

particulates that increase the specific conductance of the sample, or (3) the shielded 

collector could catch more dry deposition or windblown particulates that buffer sample 

acidity and thereby lower the specific conductance attributed to hydrogen ion. Collector 

lid actuation was only logged for the shielded collector. Therefore, data are incomplete 

for determination of how the wind shield affects sensitivity of the precipitation sensor. 

Summary and Conclusions

USGS/BQS and the NADP/PO conducted five studies to assess the effects of 

monitoring equipment performance on the quality of NADP/NTN and MDN 

measurements. Each study’s objectives and results are summarized.

Results of an NTN sample evaporation study indicate that weekly NTN samplevolume evaporated from ACM collector buckets ranged between 1.1–33 percent with a 

median of 4.7 percent. The results suggest that weekly NTN sample evaporation is small 

relative to sample volume. Effects of evaporation on sample solute concentrations were 

not evaluated. Sample evaporation was consistent with co-located pan evaporation 

measurements and was statistically correlated with relative humidity, but not sample 

volume, air temperature, wind speed, or wind direction.
43

Results of a study on weekly MDN sample evaporation and associated changes in 

Hg concentrations revealed that MDN sample evaporation is more prevalent in the 

western and southern portions of the United States, and the problem occurs more 

frequently with modified ACM collectors than with N-CON collectors. Field testing of 

MDN collectors revealed that airflow through the modified ACM is the dominant factor 

that influences sample evaporation. Modified ACM collectors with cooling fans 

manufactured by Loda Electronics are even more susceptible to sample evaporation, 

which was measured to be as high as 47.5 percent per week. Median evaporation was 5 

percent.

MDN Hg concentrations are affected by evaporation. In some instances Hg is lost 

from the sample and in other instances Hg is concentrated in the sample, with both 

scenarios resulting in changes to Hg concentrations in MDN samples. The rates of loss of 

sample volume, preservative volume, and Hg are not consistently proportional.

Results of a field evaluation of MDN glass sample trains in both modified ACM 

and N-CON collectors indicate that a small amount of Hg can be removed from MDN 

samples by adsorption to the glass sample trains. No statistically significant difference 

between the two collector types with respect to Hg adsorption was found. Median 

summer time Hg loss ranged from 0.238 ng/L to 0.489 ng/L for the N-CON and modified 

ACM, respectively. Median winter time Hg loss ranged from 0.056 ng/L to 0.076 ng/L 

for the modified ACM and N-CON, respectively.

A comparison of the relative sensitivity of 2 different ACM collector grid-type 

precipitation sensors indicates that the 11-grid MDN sensors open the collectors sooner 

than the 7-grid NTN sensors. The 7-grid sensors closed the collectors sooner than did the 

11-grid sensors. The 7-grid sensor also causes the collector lid to cycle more than the 11-

grid sensor. Retrofit of NTN ACM collectors with 11-grid sensors could reduce wear on 

collector motors. However, solute concentrations in NTN samples could be expected to 

increase because the collector would open earlier at the onset of precipitation with an 11-

grid sensor, and it would be more likely to stay open after precipitation stops.

Evaluation of a collector wind shield demonstrated that precipitation catch was 

significantly increased by the shield without significant differences in pH, and specific 

conductance was significantly lower for samples collected by the shielded collector. The 

results demonstrate that collector shields could be used to enhance the catch efficiency of 

the collector while preserving the integrity of sample chemistry. However, NADP has 

only approved the use of wind shields on precipitation gages, not collectors. Collector 

wind shields are typically prohibited by NADP and only approved on a case-by-case 

basis. This study is intended to inform and guide changes to this policy.

References Cited

Alter, J.C., 1937, Shielded storage precipitation gages, in Monthly Weather Review, July 

1937, 65, p. 262‒265.

Bigelow, D.S., and Denning, A.S., 1990, Differences between Nipher and Alter shielded 

universal Belfort precipitation gages at two Colorado deposition monitoring sites:

Environmental Science and Technology, v. 24, p. 758‒760.

Brown, M.J., and Peck, E.L., 1962, Reliability of precipitation measurements as related 

to exposure: Journal of Applied Meteorology, June 1962, v. 1, p. 203‒207.
44

Citizen Weather Observer Program, 2011, site AR893: Citizen Weather Observer 

program, accessed on March 4, 2011 at http://weather.gladstonefamily.net/site/AR893.

Gordon, J.D., 1999, External quality-assurance results for the National Atmospheric 

Deposition Program/National Trends Network, 1995‒96: U.S. Geological Survey 

Water-Resources Investigations Report 99‒4072, 69 p.

Gordon, J.D., Nilles, M.A., Polacsek, D.K., and Ratcliff, M.E., 1997, External qualityassurance results for the National Atmospheric Deposition Program/National Trends 

Network during 1994: U.S. Geological Survey Water-Resources Investigations Report 

97‒4201, 42 p.

Graham, R.C., and Robertson, J.K., 1990, An assessment of performance of wet 

atmospheric deposition samplers: U.S. Geological Survey Water-Resources 

Investigations Report 90‒4042, 101 p.

Graham, R.C., Robertson, J.K., and Obal, J., 1987, An assessment of the variability in 

performance of wet atmospheric deposition samplers: U.S. Geological Survey WaterResources Investigations Report 87‒4125, 152 p.

Helsel, D.R., and Hirsch, R.M., 1992, Statistical methods in water resources: New York, 

Elsevier Science Publishing Company, Inc., 522 p.

Latysh, N.E., and Gordon, J.D., 2004, Investigation of differences between field and 

laboratory pH measurements of National Atmospheric Deposition Program/National 

Trends Network precipitation samples: Water, Air, and Soil Pollution, v. 154, p. 249‒

270.

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, 76 p.

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.

National Atmospheric Deposition Program (NADP), 2011:Accessed on Mar. 4, 2011at 

http://nadp.isws.illinois.edu/newissues/newgages/windshields.aspx.

National Center for Atmospheric Research (NCAR), 2011:, Accessed on Feb. 28, 2011at 

http://www.rap.ucar.edu/projects/winter/sites/marshall/?7b4701fa4bc533451f192615e

aa0263d.

Nilles, M.A., 2000, Atmospheric Deposition Program of the U.S. Geological Survey:

U.S. Geological Survey Fact Sheet 112‒00.

Pellett, G.L., Bustin, R.A., and Harris, R.C., 1984, Sequential sampling and variability of 

acid precipitation in Hampton, Virginia: Water, Air, and Soil Pollution, v. 21, p. 33–49.

Raynor, G.S., and Hayes, J.V., 1982, Variation in chemical wet deposition with 

meteorological conditions: Atmospheric Environment, v. 16, no. 7, p. 1647–1656.

Raynor, G.G., and McNeil, J.P., 1979, An automatic sequential precipitation sampler, in 

Atmospheric Environment, v. 13, pp. 149-155.

Rong, X., Waite, D., Huang, G.H., Tong, L., and Kybett, B., 2001, Materials selection for 

a dry atmospheric mercury deposits sampler, in Chemosphere, vol. 45, pp 1045-1051.

Rosain, R.M., and Wai, C.M., 1973, The rate of loss of mercury from aqueous solution 

when stored in various containers, in Analytical Chimica Acta, vol. 65, pp 279-284.
45

Schroeder, L.J., Brooks, M.H., and Garbarino, J.R., 1987, The influence of an urban 

environment in the chemical composition of precipitation, in Chemical Quality of 

Water and Hydrologic Cycle, chap. 3, Averett, R.C., and McKnight, D.M., eds.,: 

Chelsea, Mich., Lewis Publishers, Inc.

Schroeder, L.J., and Hedley, A.G., 1986, Variation in precipitation quality during a 40-

hour snowstorm in an urban environment—Denver, Colorado: International Journal of 

Environmental Studies, v. 28, p. 131‒138.

See, R.B., Schroder, L.J., and Willoughby, T.C., 1989, A quality-assurance assessment 

for constituents reported by the National Atmospheric Deposition Program and the 

National Trends Network: Atmospheric Environment, v. 23, no. 8, p. 1801–1806.

Sisterson, D.L., Wurfel, B.E., and Lesht, B.M., 1985, Chemical differences between 

event and weekly precipitation samples in northeastern Illinois: Atmospheric 

Environment, v. 19, no. 9, p. 1453‒1469.

Tang, A.J.S., Chan, W.H., Orr, D.B., Bardswick, W.S., and Lusis, M.A., 1987, An 

evaluation of the precision, and various sources of error, in daily and cumulative 

precipitation chemistry sampling: Water, Air, and Soil Pollution, v. 36, p 91‒102.

Vermette, S.J., Lindberg, S.E., and Bloom, N., 1995, Field tests for a regional mercury 

deposition network-sampling design and preliminary test results: Atmospheric 

Environment, v. 29, no. 11, p. 1247‒1251.

Weiss, L.L., 1961, Relative catches of snow in shielded and unshielded gages at different 

wind speeds: Monthly Weather Review, October 1961, p. 397‒400.

Wetherbee, G.A., Latysh, N.E., and Chesney, T.A., 2010, U.S. Geological Survey 

External Quality-Assurance Project Report to the National Atmospheric Deposition 

Program / National Trends Network and Mercury Deposition Network, 2007‒08: 

NADP QA Report 2010‒01, ISWS Miscellaneous Publication 190, University of 

Illinois, Institute of Natural Resource Sustainability, Illinois State Water Survey, 82 p.

Wetherbee, G.A., Latysh, N.E., Greene, S.M., and Chesney, T.A., 2009, U.S. Geological 

Survey external quality-assurance program results reported to the National 

Atmospheric Deposition Program / National Trends Network, and Mercury Deposition 

Network for 2005‒06: NADP QA Report 2009‒01, ISWS DCS 2009‒01, Illinois State 

Water Survey, Champaign, Ill., 54 p.

Wetherbee, G.A., Latysh, N.E., and Gordon, J.D., 2005, Spatial and temporal variability 

of the overall error of National Atmospheric Deposition Program measurements 

determined by the USGS co-located-sampler program, water years 1989–2001:

Environmental Pollution, v. 135, p. 407‒418.

Wetherbee, G.A., Latysh, N.E., and Gordon, J.D., 2004, External quality-assurance 

results for the National Atmospheric Deposition Program / National Trends Network, 

2000-2001, U.S. Geological Survey Scientific Investigations Report 2004‒5034, 

Denver, CO, 59 p.

Wetherbee, G.A., Latysh, N.E., and Greene, S.M., 2006, External quality-assurance 

results for the National Atmospheric Deposition Program / National Trends Network, 

and Mercury Deposition Network, 2004: U.S. Geological Survey Scientific 

Investigations Report 2006‒5067, 52 p.

Willoughby, T.C., Schroder, L.J., and See, R.B., 1990, Chemical stability of wetdeposition samples subsampled daily for one week: U.S. Geological Survey WaterResources Investigations Report 90‒4003, 19 p.
46

Willoughby, T.C., See, R.B., and Schroder, L.J., 1989, Stability of nitrate-ion 

concentrations in simulated deposition samples used for quality-assurance activities by 

the U.S. Geological Survey: U.S. Geological Survey Water-Resources Investigations 

Report 89‒4042, 15 p.

Yang, D., Goodison, B.E., and Metcalfe, J.R., 1998, Accuracy of NWS 8" standard 

nonrecording precipitation gauge—Results and application of WMO intercomparison: 

Journal of Atmospheric and Oceanic Technology, v. 15, p. 54‒68.

Yang, D., Goodison, B.E., Metcalfe, J.R., Louie, P., Leavesley, G.L., Emerson, D., 

Hanson, C.L., Golubev, E.E., Gunther, T., Pangburn, T., Kang, E., and Milkovic, J., 

1999, Quantification of precipitation measurement discontinuity induced by wind 

shields on national gauges: Water Resources Research, v. 35, no. 2, p. 491‒508.

Yang, D., Kane, D.L., Hinzman, L.D., Goodison, B.E., Metcalfe, J.R., Louie, P.Y.T., 

Leavesley, G.H., Emerson, D.G., and Hanson, C.L., 2000, An evaluation of the 

Wyoming gauge system for snowfall measurement: Water Resources Research, v. 36, 

no. 9, p. 2665‒2677.

Table 1. Kendall’s Tau and associated statistical significance for correlation of meteorological data 

and weekly evaporation of synthetic precipitation samples sealed in an Aerochem Metrics 

Model 301 precipitation collector in Arvada, Colorado, May 16–September 5, 2006. 

[mm, millimeters; p-values, probability of correctly deciding that two variables are not correlated; m/s, meters 

per second; deg. C, degrees Celsius; mmHg, millimeters of mercury; mL, milliliters ]

Weekly sample evaporation 

depth, mm

Weekly sample evaporation,

in percent

Parameters and units Kendall's Tau p-values Kendall's Tau p-values

Weekly pan evaporation, mm 0.69 0.0003 0.30 0.157

Weekly mean wind direction 0.07 0.757 0.08 0.690

Weekly mean wind speed, m/s 0.45 0.015 0.40 0.033

Weekly mean air temperature, deg. C 0.10 0.626 -0.12 0.564

Weekly mean relative humidity, percent -0.77 0.00001 - -

Weekly mean barometric pressure, mmHg -0.37 0.059 - -

Initial sample volume, mL 0.23 0.228 -0.38 0.041
47

Table 2. Preservative volume loss for MDN samples collected between March 1996 and 

November 2010.

Preservative volume loss1

(milliliters) Number of samples Percentage of samples2(Percent)

0 (no loss) 805 15.5

0- 1 1,052 20.3

1- 2 801 15.4

2- 5 1,072 20.7

5-10 670 12.9

10-15 293 5.7

15-19.9 336 6.5

20 156 3.0

1 Volume loss based on sampling period with no precipitation, no bottle leaks during shipment, and proper 

operation of both the collector’s motor and sensor. 

2 Based on the number of samples (5,185) that met the study criteria.

Table 3. Weekly Mercury Deposition Network (MDN) samples with preservative volume loss and 

individual MDN sites where sample loss was observed, March 1996 - November 2010. 

Collector type Number of samples with preservative 

volume loss1 Number of sites2

Modified ACM 3,820 125

N-CON 560 39

1 Total number (4,380) based on sampling periods with no precipitation, no bottle leaks during shipment, 

proper operation of both the motor and sensor, and preservative volume loss greater than 0 milliliters. 

2 Includes both presently and formerly active sites, and sites that changed collector type.

Table 4. Specifications of the cooling fan used in the original modified Aerochem Metrics (ACM) 

collector and the Loda Electronics version of the ACM collector. 

[ft3/min, cubic feet per minute; rpm, revolutions per minute; dB, decibels]

Parameter

Manufacturer

Aerochem Metrics Loda Electronics

Air flow (ft3/min) 70 100

Speed (rpm) 2,000 2,900

Power (Watts) 11 18

Noise (dB) 36 48
48

Table 5. Results from evaporation tests with Aerochem Metrics version of the modified ACM 

collector.

[%, percent; ng/L, nanograms per liter; MPV, most probably value; Hg, mercury] 

Dates 

samples 

deployed in 

collectors

Sampling 

Period

(days)

Mass 

Loss 

(grams)

Volume 

Loss 

(%)

MPV

(ng/L)

Measured total 

Hg 

concentration 

(ng/L)

Hg 

concentration 

difference1 

(%)

Hg mass 

loss2

(%)

 8/24/10 – 

8/31/10 7 0.6 0.4 15.3 9.56 -37.5 37.8

 8/31/10 – 

9/15/10 15 1.1 0.8 21.7 7.08 -67.4 67.7

11/11/10 –

11/23/10 12 9.7 3.6 9.26 10.2 10.4 -6.00

11/23/10 –

12/02/10 9 2.6 1.0 9.26 9.38 1.3 -0.20

12/02/10 –

12/09/10 7 2.2 1.4 6.26 7.33 17.1 -15.2

12/09/10 –

12/16/10 7 16.7 9.4 9.26 10.3 10.9 -0.80

12/16/10 –

12/23/10 7 8.3 4.8 15.2 6.59 -56.6 59.0

12/23/10 –

12/30/10 7 1.3 0.7 6.26 5.96 -4.80 5.50

12/30/10 – 

1/13/11 14 22.2 12.6 15.2 15.8 3.70 11.1

 1/13/11 – 

1/25/11 12 2.8 1.7 15.2 12.9 -15.0 16.6

 1/25/11 – 

2/01/11 7 9.0 10.0 15.2 12.0 -20.9 31.0

 2/01/11 – 

2/08/11 7 82.4 60.9 21.6 68.7 218 9.50

 2/08/11 – 

2/15/11 7 7.2 5.7 21.6 20.6 -4.60 11.0

 2/15/11 – 

2/22/11 7 6.8 4.2 21.6 17.5 -19.0 22.9

 2/22/11 – 

3/01/11 7 2.4 2.0 21.6 16.3 -24.4 26.2

 7/05/11 – 

7/12/11 7 6.6 4.9 15.2 16.4 8.10 -1.80

 7/12/11 – 

7/19/11 7 1.1 0.9 15.2 14.0 -7.60 8.60

 7/19/11 – 

7/26/11 7 1.2 0.7 20.8 17.1 -17.6 18.2

 7/26/11 – 

8/02/11 7 1.6 1.0 14.2 13.4 -5.80 6.90

1

((Measured – MPV)/MPV) × 100

2

(( MPV-Measured)/MPV) × 100
49

Table 6. Results from evaporation tests with Loda Electronics version of the modified ACM collector.

[%, percent; ng/L, nanograms per liter; MPV, most probably value; Hg, mercury] 

Dates 

samples 

deployed in 

collectors

Sampling 

Period

(days)

Mass 

Loss

(grams)

Volume 

Loss

(%)

MPV

(ng/L)

Measured 

total Hg 

concentration 

(ng/L)

Hg 

concentration 

difference1

(%)

Hg mass 

loss2

(%)

 8/24/10 – 

8/31/10 7 5.5 3.9 15.3 8.79 -42.5 45.2

 8/31/10 – 

9/15/10 15 6.0 4.2 21.7 11.0 -49.1 51.6

11/11/10 –

11/23/10 12 25.4 9.5 15.2 16.9 11.2 0.2

11/23/10 –

12/09/103 16 40.7 15.2 15.2 16.8 10.6 7.5

12/09/10 –

12/16/10 7 25.3 12.1 9.26 11.0 18.7 -2.7

12/16/10 –

12/23/10 7 41.7 22.7 15.2 8.25 -45.7 59.6

12/23/10 –

12/30/10 7 28.7 12.8 15.2 16.5 8.8 6.4

12/30/10 – 

1/13/11 14 35.1 23.2 15.2 20.3 33.5 2.3

 1/13/11 – 

1/25/11 12 67.6 42.6 15.2 26.2 72.6 11.7

 1/25/11 – 

2/01/11 7 20.7 13.1 15.2 13.6 -10.5 23.9

 2/01/11 – 

2/08/11 7 36.8 18.6 21.6 18.2 -15.6 33.1

 2/08/11 – 

2/15/11 7 60.7 54.4 21.6 39.1 81.0 39.1

 2/15/11 – 

2/22/11 7 7.9 4.7 21.6 15.4 -28.9 32.7

 2/22/11 – 

3/01/11 7 55.3 47.5 21.6 33.6 55.5 33.7

 8/02/11 – 

8/09/11 7 10.9 4.8 9.03 11.8 30.2 -23.3

 8/09/11 – 

8/16/11 7 5.6 3.1 9.03 8.92 -1.2 4.6

 8/16/11 – 

8/23/11 7 14.4 6.6 14.2 14.2 -0.1 7.4
50

Table 6. Results from evaporation tests with Loda Electronics version of the modified ACM 

collector.—Continued

[%, percent; ng/L, nanograms per liter; MPV, most probably value; Hg, mercury] 

Dates 

samples 

deployed in 

collectors

Sampling 

Period

(days)

Mass 

Loss

(grams)

Volume 

Loss

(%)

MPV

(ng/L)

Measured 

total Hg 

concentratio

n (ng/L)

Hg 

concentration 

difference1

(%)

Hg mass 

loss2

(%)

 8/23/11 – 

8/30/11 7 1.7 1.0 20.75 17.33 -16.5 17.5

 8/30/11 – 

9/06/11 7 23.5 14.7 9.03 10.16 12.5 6.3

 9/06/11 – 

9/13/11 7 17.8 7.2 15.5 15.66 1.0 6.9

 9/13/11 – 

9/20/11 7 0.4 0.2 14.2 13.05 -8.1 8.3

 9/20/11 – 

9/27/11 7 0.5 0.3 15.5 14.32 -7.6 8.0

 9/27/11 –

10/04/11 7 0.7 0.4 15.5 11.66 -24.8 25.1

10/04/11 –

10/11/11 7 6.8 3.2 6.02 6.35 5.5 -1.8

10/11/11 –

10/18/11 7 12.5 8.2 6.02 6.96 15.1 -4.3

10/18/11 –

11/01/11 14 31.0 13.6 6.02 7.56 25.6 -6.9

1

((Measured – MPV)/MPV) × 100

2

(( MPV-Measured)/MPV) × 100

3

Sample bottle left in place for extended duration. Bottle for 2nd week broke during shipment.
51

Table 7. Results from evaporation tests with N-CON single-chimney collector.

[%, percent; ng/L, nanograms per liter; MPV, most probably value; Hg, mercury] 

Dates 

samples 

deployed in 

collectors

Sampling 

Period

(days)

Mass 

Loss

(grams)

Volume 

Loss

(%)

MPV

(ng/L)

Measured total 

Hg 

concentration 

(ng/L)

Hg 

concentration 

difference1

(%)

Hg mass 

loss2

(%)

 7/05/11 – 

7/12/11 7 1.7 1.1 15.2 14.4 -5.3 6.5

 7/12/11 – 

7/19/11 7 2.4 1.6 15.2 12.7 -16.2 17.7

 7/19/11 – 

7/26/11 7 1.4 0.9 20.8 12.8 -38.3 38.9

 7/26/11 – 

8/02/11 7 0.9 0.5 14.2 13.5 -5.1 5.6

 8/02/11 – 

8/09/11 7 1.7 0.8 9.03 8.62 -4.5 5.4

 8/09/11 – 

8/16/11 7 0.8 0.5 9.03 8.16 -9.6 10.1

 8/16/11 – 

8/23/11 7 0.9 0.4 14.2 14.3 1.0 -0.5

 8/23/11 – 

8/30/11 7 0.9 0.5 20.8 19.8 -4.8 5.3

 8/30/11 – 

9/06/11 7 1.1 0.7 9.03 7.4 -18.1 18.7

 9/06/11 – 

9/13/11 7 0.8 0.4 15.5 14.3 -7.9 8.4

 9/13/11 – 

9/20/11 7 0.3 0.2 14.2 14.1 -0.6 0.8

 9/20/11 – 

9/27/11 7 0.7 0.4 15.5 13.8 -10.8 11.1

 9/27/11 –

10/04/11 7 1.6 1.1 15.5 15.1 -2.9 4.1

10/04/11 –

10/11/11 7 4.1 2.2 6.02 4.91 -18.4 20.5

10/11/11 –

10/18/11 7 0.6 0.5 6.02 5.32 -11.6 12.1

10/18/11 –

11/01/11 14 0.8 0.4 6.02 5.34 -11.3 11.7

1

((Measured – MPV)/MPV) × 100

2

(( MPV-Measured)/MPV) × 100
52

Table 8. Total mercury concentration analyses for sample-train study samples processed after a 

week with rain or snow at selected Mercury Deposition Network sites.

[Hg, mercury; ng, nanograms; ng/L, nanograms per liter; %, percent; HCl, hydrochloric acid; N-CON, NCON Systems, Inc.; Mod-ACM, Modified Aerochem Metrics; dry, no precipitation recorded for previous 

week; <0.005, less than detection value reported as 0.000 by laboratory; mean HCl control concentration= 

0.1 ng/L;]

MDN site 

ID

Hg wetdeposition

collector type

Hg mass 

collected in 

previous 

week’s sample 

(ng)

Sample train 

total Hg 

concentration (ng/L)

Control 

sample total 

Hg concentration

(ng/L)

Sample-trainminus-control 

total Hg 

concentration 

difference1

(ng/L)

Sample-trainminus-control 

total Hg 

concentration 

median 

difference 

(ng/L)

Rain Samples

GA33 N-CON 4,514 1.553 2.082 -0.530

KS03 N-CON 18,154 1.397 0.013 1.384 0.238

NY06 N-CON 999 0.557 0.320 0.238

UT97 N-CON 2,185 0.293 0.116 0.177

WV99 N-CON 1,397 0.666 0.007 0.659

FL34 Mod-ACM 16,025 0.545 <0.005 0.545

IN26 Mod-ACM 3,162 0.624 0.539 0.085

OK04 Mod-ACM 3,069 0.601 0.010 0.590 0.489

OK06 Mod-ACM 1,288 0.206 <0.005 0.206

SC03 Mod-ACM 8,981 0.529 0.039 0.489

Snow Samples

NE15 N-CON dry 0.004 0.012 -0.008

NY06 N-CON 272 0.170 0.063 0.107 0.076

ID98 N-CON 805 0.046 <0.005 0.046

UT97 N-CON 103 0.460 <0.005 0.460

IN28 Mod-ACM dry 0.269 0.051 0.217

MN23 Mod-ACM 37 0.059 <0.005 0.059 0.056

PA52 Mod-ACM 91 0.052 <0.005 0.052

PA60 Mod-ACM 3,339 0.077 0.061 0.016

1 Negative difference values are interpreted as zero for purposes of this study.
53

Table 9. Co-located National Trends Network (NTN) and Mercury Deposition Network (MDN) sites 

and periods of record for comparison of 7- and 11-grid AeroChem Metrics precipitation 

sensors.

NTN/MDN

site Period of record

Months of 

record 

evaluated

CA94 6/24/08 – 2/17/09 8

CO99 8/27/08 – 2/01/09 5

ID03 12/05/07 – 2/17/09 14

IL11 8/24/07 – 2/24/09 18

IN20 12/30/08 – 2/17/09 2

IN34 12/30/08 – 2/17/09 1.5

KY10 1/09/09 – 2/17/09 1.2

MD08 7/03/08 – 1/20/09 6.5

MD99 10/23/08 – 1/21/09 3

ME02 9/18/08 – 2/17/09 5

ME04 5/08/08 – 12/03/08 7

ME09 1/22/08 – 2/17/09 13

ME96 6/12/08 – 2/17/09 8

ME98 5/20/08 – 2/17/09 8

MT05 6/24/08 – 2/17/09 8

OK99 5/22/07 – 2/17/09 16

TN11 10/07/08 – 2/24/09 4.5

VA28 7/01/08 – 2/17/09 7

WI10 10/29/08 – 2/10/09 4

WY08 6/05/08 – 2/17/09 8