United States

Department of

Agriculture

Forest Service

Rocky Mountain

Research Station

General Technical

Report RMRS–GTR–52

May 2000

Determining Atmospheric

Deposition in Wyoming With

IMPROVE and

Other National Programs

Karl Zeller, Debra Youngblood Harrington,

Richard Fisher, and Evgeny Donev
Abstract

Zeller, Karl; Harrington, Debra Youngblood; Fisher, Richard; Donev, Evgeny. 2000. Determining

atmospheric deposition in Wyoming with IMPROVE and other national programs. Gen. Tech.

Rep. RMRS-GTR-52. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky

Mountain Research Station. 34 p.

Atmospheric deposition is the result of air pollution gases and aerosols leaving the atmosphere

as “dry” or “wet” deposition. Little is known about just how much pollution is deposited onto soils,

lakes and streams. To determine the extent and trends of forest exposure to air pollution,

various types of monitoring have been conducted. In this study, we evaluate data from different

rural air monitoring programs to determine whether or not they may have wider applications

in resource monitoring and protection. This report analyzes location-specific data collected by

three national programs: The CASTNET (NDDN) Network supported by the Environmental

Protection Agency, the IMPROVE (Interagency Monitoring of Protected Visual Environments)

network supported by federal land managers, and the NADP/NTN program supported by many

agencies.

Keywords: atmospheric deposition, sulfur and nitrogen deposition, dry deposition, wet deposition,

NADP/NTN, CASTNET, IMPROVE, air resource

The Authors

Karl Zeller is a micrometeorologist with the Rocky Mountain Research Station and an American

Meteorological Society certified consulting meteorologist (license #215).

Debra Youngblood Harrington is self-employed as a consultant, bookseller, and animal caretaker.

She assisted in developing a bimodal aerosol model at the Atmospheric Department of Colorado

State University. She continues to consult on results generated with this model.

Richard W. Fisher is an American Meteorological Society certified consulting meteorologist (license

#479) and Air Program Manager for the USDA Forest Service. He is assigned to the Washington

Office but works out of the Rocky Mountain Research Station in Fort Collins, CO. Rich advises

the Chief of the Forest Service on policy matters related to air quality and provides technical

leadership to field units on air quality issues. Rich holds an M.S. in earth sciences from Colorado

State University and an M.A. in international and strategic studies from the Naval War College,

Newport, RI.

Evgeny Donev is a professor in the Department of Meteorology at the University of Sofia in

Bulgaria. He is the Bulgaria Project Manager of cooperative agreement #RMRS-98006-MDU

between the Rocky Mountain Research Station, the Bulgarian Forest Research Institute, and

Sofia University, Department of Meteorology. He and Dr. Zeller have coauthored several

publications on N and S deposition and ozone behavior in the Rila Mountains of Bulgaria. Dr. Donev

was a visiting scientist at the Rocky Mountain Research Station during the summer of 1992 and

helped with GLEES research at that time.

You may order additional copies of this publication by sending

your mailing information in label form through one of the following

media. Please send the publication title and number.

Telephone (970) 498-1392

E-mail rschneider@fs.fed.us

FAX (970) 498-1396

Mailing Address Publications Distribution

Rocky Mountain Research Station

240 West Prospect Road

Fort Collins, CO 80526-2098
Contents

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

Methods ............................................................................................................ 1

Sites.............................................................................................................. 1

Wet Deposition ............................................................................................ 2

Dry Deposition ............................................................................................. 2

Results and Discussion ................................................................................... 4

Wet Deposition ............................................................................................ 4

Dry Deposition ............................................................................................. 8

Total Sulfur and Nitrogen Deposition ........................................................ 10

Conclusion ....................................................................................................... 11

References ........................................................................................................ 12

Appendix A. NO2 and SO2 Deposition Velocity (Vd ) Over Water ................... 13

Appendix B. NADP Statistics for , , Cl-, Na+, K+, Ca2+, Mg2+,

and Concentration and Deposition ......................................................... 21

Appendix C. NADP Weekly Concentration and Weekly Deposition and

Total Annual Deposition for , , Cl-

, Na+, K+, Ca2+, Mg2+,

and ............................................................................................................ 29

Appendix D. NADP Annual Statistics for , , Cl-, Na+, K+,

Ca2+, Mg2+, and .......................................................................................... 32

Appendix E. Recommendation: Use of IMPROVE Data to Assess

Air Pollution and Deposition .......................................................................... 33

Determining Atmospheric Deposition in Wyoming

With IMPROVE and Other National Programs

Karl Zeller, Debra Youngblood Harrington, Richard Fisher, and

Evgeny Donev

SO2-

4 NO3

-

NH4

+

NO3

- SO2-

4

NH4

+

SO2-

4 NO3

-

NH4

+
Acknowledgments

The authors thank Roger Ames, Cooperative Institute for Research, Colorado State

University Foothills Campus, for demonstrating the use of Glacier Lake National Park

as an IMPROVE comparison site; and the Rocky Mountain Research Station Statistics

Unit staff for their suggestions and timely review of this document.

Funding for this project was provided by the USDA Forest Service Watershed and Air

Management, Washington, DC; Rocky Mountain Research Station, Research Work Unit

4451; and the Department of Meterology, Sofia University, Bulgaria.
USDA Forest Service General Technical Report RMRS-GTR-52. 2000 1

Introduction

Air pollution can threaten visibility, aquatic ecosystems, and terrestrial ecosystems on national forests. Atmospheric deposition is the technical term for air pollution

gases and aerosols that come down or leave the atmosphere and deposit as (a) “wet” deposition through precipitation; (b) “dry” deposition by transportation through

the Earth’s atmospheric boundary layer to surfaces, stomate openings, etc.; and (c) “occult” or “cloud” deposition by becoming an aerosol with water vapor (i.e., becoming part of a cloud) then depositing upon impact

with surfaces. To determine the extent and trends of

forest exposure to air pollution, various types of monitoring have been conducted.

In response to the Clean Air Act of 1977, remote parts of

the national forests are monitored by the robust interagency ambient aerosol measurement program IMPROVE

(Interagency Monitoring of Protected Visual Environments). IMPROVE monitors background and adverse

changes to visibility, where visibility was the only measurable air quality related value (AQRV) specified for protection in the Clean Air Act. This report addresses the practical use of national monitoring program data and the

feasibility of applying IMPROVE Forest Service data to

atmospheric deposition. We provide information and recommendations specific to atmospheric deposition for land

manager applications through the example of determining nitrogen (N) and sulfur (S) deposition in the Snowy

Range of the Medicine Bow National Forest, Wyoming.

Cloud deposition is important for west coast and eastern

U.S. mountains, but because it has not been considered

important for the site area studied here and because data

are unavailable, it is not addressed.

Because ambient monitoring is expensive and because

the IMPROVE visibility monitoring program is of high

quality, the Forest Service is seeking ways to maximize the

usefulness of the aerosol visibility data that have been or

are now being collected. This report analyzes locationspecific data collected by three national programs:

1. The CASTNET (Clean Air Status and Trends

Network), a.k.a. National Dry Deposition Network (NDDN), supported by the Environmental

Protection Agency (http://www.epa.gov/

acidrain/castnet/). CASTNET measures “dry”

deposited pollutants, but few monitoring sites

exist.

2. The IMPROVE Module A (predecessor program:

SFU: stacked filter unit) supported by the

National Park Service (NPS), the United States

Dept. of Agriculture Forest Service (USDA FS),

and other cooperating agencies (http://

crocker.ucdavis.edu/CNL/RESEARCH/

AQG4.htm).

3. The NADP/NTN (National Atmospheric Deposition Program National Trends Network) (http:/

/nadp.sws.uiuc.edu/). This program, supported

by many governmental agencies, measures the

“wet” deposition of atmospheric pollutants to

the Earth’s surface in the form of precipitation.

All three programs have been and are currently conducted at or near the USDA FS Glacier Lakes Ecosystem

Experiments Site (GLEES) in the Snowy Range mountains

(Zeller et. al, 2000).

Little is known about just how much pollution is deposited onto soils, lakes, and streams. If this information were

available, we would be better able to relate pollutant

exposure to effects on AQRVs such as soils, flora, and

fauna. Measuring total atmospheric deposition is complicated because dry deposition cannot be accurately measured

directly and because the variety of measurement protocols

if used together reduce precision. Wet deposition measurements (Erisman et. al, 1994) are also sometimes difficult

to intercompare because proper siting is often compromised by access considerations. The adoption of NADP/

NTN protocols for most monitoring programs within the

United States, however, has helped to simplify wet deposition data analysis. In our study, three closely located

NADP sites are intercompared to address spatial representativeness. One of the sites is unusually rare due to its

alpine location and year round access. Spatial representativeness for dry deposition is partially addressed by comparing the sulfur concentration results from two NDDN

locations with SFU-IMPROVE results. Although IMPROVE

program protocols were designed to address visibility

and not deposition, the similarity in species monitored

potentially makes it useful for deposition assessments.

Scientists have been cautious about spatial representativeness of these data, especially in mountainous areas.

We will evaluate data from different rural air monitoring programs to determine whether or not they may have

wider applications in resource monitoring and protection.

Methods

Sites

The data presented here were taken from five separate

sites in Wyoming within or close to the GLEES area in the

Snowy Range of the Medicine Bow National Forest,
2 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-52. 2000

Wyoming, about 65 km west of Laramie, Wyoming. The

GLEES complex is described by Musselman (1994). The

major tree species in the GLEES forest are Picea engelmannii

(48%), Abies lasiocarpa (48%), and Pinus contorta (4%).

The Snowy Range (SR) NADP site, (WY00), is located

southwest of West Glacier Lake in the Snowy Range of

Wyoming at an elevation of 3286 meters, which is the

approximate tree line elevation for the forest. Samples

have been collected at this site from 1986 to the present.

The second NADP site, Nash Fork (NF), (WY96), is located 6.8 km southeast of the SR site at an elevation of

2856 m. Samples were collected at Nash Fork from 1987

to September 1992. In September of 1992, this site was

relocated and given a new name and NADP calcode. The

relocated NADP site, Brooklyn Lake, (BL), (WY95), is 2.4

km southeast of the SR site at an elevation of 3188 m.

Samples have been collected at this site from September

1992 to the present.

NADP data are compared by both linear regression

and paired difference. The paired difference analyses for

the total (T) data set (SR-NFT and SR-BLT) were made

because the regression offset is not always a good indication of bias for data comparisons with broad scatter.

Further, 25% trimmed paired differences (SR-NF50 and

SR-BL50) were calculated to eliminate the effect of large

outliers. The highest and lowest 25% of the data are culled

in this procedure; hence 50% of the data are trimmed.

GLEES area CASTNET NDDN monitoring commenced

July 1989 at an open dry meadow site near Centennial,

Wyoming (CNT169), 12.2 km southeast of GLEES. During

August 1991, CNT169 was relocated to GLEES in an opensloped dry meadow location 138 m west southwest of the

Brooklyn Lake tower IMPROVE site and approximately

50 m south-southeast of the Brooklyn Lake NADP site

(WY95). The USDA IMPROVE site, located about 130 m

east of BL NADP WY95, was not moved during the period

of this study. Table 1 gives the location and relative horizontal distance from the Snowy Range NADP site. The

three Brooklyn sites are all within 140 m horizontal distance of each other.

Wet Deposition

NADP was established in 1978 as a long-term atmospheric deposition monitoring network (CSU, 1991;

Sisterson, 1991). Today, the program has approximately

200 rural stations in the United States that monitor wet

deposition. The main goal of the program is to determine

the spatial patterns and temporal trends in chemical precipitation deposition to support studies of the impact of

chemical deposition on aquatic and terrestrial ecosystems.

Weekly precipitation samples are collected from each site

and sent to the Central Analytical Laboratory (CAL) for

analysis. The samples are analyzed for SO4

2− , NO3

− , Cl-

,

Na+

, K+, Ca2+, Mg2+, NH4

+ , H+

, pH, and conductivity.

The site comparisons in this study were completed for

each year (1987 through 1997) using the weekly data at

each site. The NADP data comparisons are made relative

to the Snowy Range site. This report analyzes weekly

deposition data in contrast to the NADP/NTN program,

which does not report weekly deposition rather seasonal

and yearly. The validity of weekly concentration samples,

however, is determined by NADP/NTN. NADP data may

be judged invalid for a number of reasons, including

contamination, short or long sampling period (< 6 days or

> 8 days), and laboratory error. Precipitation differences

between the study sites greatly affected the weekly intersite comparison of concentration and deposition values.

Hence a “filtered” or “reduced” dataset (i.e., a subset of the

valid weekly data) was also used. The data were reduced

by culling a weekly sample when precipitation at the site

was either less than 3 mm or when the precipitation

difference, Pd , between two sites was greater than 100%.

P P P

P d

SR i

i

=  −



 

 100  (1)

Here PSR is the precipitation measured at SR, and Pi

is the precipitation measured at either NF or BL. Table 2

shows the number of resulting data points used for each

year for the valid dataset and the reduced dataset.

The weekly deposition values for this study were calculated using the weekly concentration and precipitation values reported by NADP:

D C P

i i

i = 100

, (2)

where Di is the deposition of sample i in kg ha-1 wk-1, Ci is

the concentration of sample i in mg l-1, and Pi is the

Table 1. Monitoring sites, program, and location. 

Name Program Elevation Latitude Longitude Distance from SR 

SR: Snowy Range (WY00) NADP 3286 m 41o 22’ 34” 106o 15’ 34” 0.0 km 

NF: Nash Fork (WY96) NADP 2856 41o

 20’ 25” 106o 11’ 27” 6.8 

BL: Brooklyn Lake (WY95) NADP 3188 41o

 21’ 53” 106o 14’ 27” 2.4 

CNT:BL 169: Brooklyn Lake CASTNET (NDDN) 3180 41o

 21’ 50” 106o 14’ 27” 2.5 

CNT169: Centennial CASTNET (NDDN) 2591 41o

 18’ 30” 106o 09’ 10” 12.2 

BT: Brooklyn Tower IMPROVE 3186 41o

 21’ 53” 106o 14’ 15” 2.6 
USDA Forest Service General Technical Report RMRS-GTR-52. 2000 3

Dry Deposition

EPA CASTNET (NDDN). NDDN was established by

EPA to obtain routine weekly ambient concentration measurements and dry deposition estimates of O3

, SO4

−2 , NO3

− ,

NH4

+ , SO2

, and HNO3 and to obtain meteorological parameters. Weekly filter pack samples are exchanged on

Tuesday mornings in coordination with NADP protocol.

NDDN was expanded to incorporate similar programs

and is now called CASTNET although the NDDN sites

are still so named. The dry deposition component of

NDDN is a 3-stage serial filter pack: first, a 47 mm Teflon

filter (Zefluor, 1μm) for SO4

2− NH4

+ and NO3

− aerosols;

second, a 47 mm nylon filter (Nylasorb, 1μm) for HNO3

;

and third, a K2CO3 impregnated cellulose (Whatman no.

41) filter for SO2. Ambient air from 10m height is continuously drawn through the filter pack at 1.5 l m-1. Field and

laboratory procedures are provided by ESE (1990a,

1990b).

Estimating dry deposition is a two step analysis: step 1–

determine the vertical ambient concentration gradient,

( c z

 - c o), ( c z : above ground concentration; c o : surface

concentration) of the pollutant species of interest; step 2–

model the applicable deposition velocity (Bytnerowicz et

al., 1987; Hidy, 1999; Schmel, 1984; Wyers and Duyzer,

1997), Vd , and multiply it by ( c z

 - c o ) to determine

deposition, Fc

 (or vertical flux) equation 3 (Zeller and

Hehn, 1996):

Fc

 = ( c z – c o) Vd (3)

In practice the value of c o is often taken as 0.0. The

deposition velocity, provided within the CASTNET protocol, is a multiple function of chemical species, atmospheric

turbulence, vegetation, canopy structure, leaf wetness,

etc. Hidy (1999) has recently prepared a summary document on dry deposition determination techniques specifically for federal lands. Appendix A, “NO2

 & SO2 Deposition Velocity (Vd) Over Water,” gives more detail specifics on how to evaluate the deposition velocity parameter

and how to select specific values.

IMPROVE. The IMPROVE measurement program was

designed and implemented to address visibility (background, visibility impairment species and trends) for federal land management and regulatory agencies (Malm et

al. 1994; Sisler, 1996). An IMPROVE site can have up to

four separate modules sampling in parallel: module A—a

Teflon filter, for fine particulate (≤2.5μm diameter) mass;

module B—a denuded nylon filter, for sulfate (SO4

2− ) and

nitrate ( NO3

− ) (≤2.5μm); module C—a quartz filter, for

organic and light-absorbing carbon (C) (≤2.5μm); and

module D for particulate mass ≤10.0 μm diameter. Sample

measurements are made through 24-hour continuous

filter sampling on Wednesdays and Saturdays of each

week. The 2.5μm cutoff is achieved using a size selective

inlet in addition to a cyclone separator. Sample flow rate

is held at 22.7 l m-1 using a critical orifice. The IMPROVE

program was established in March 1988 having replaced

the earlier stacked filter unit (SFU) protocol originally

fielded in 1979. At sites where the fine particulate module A replaced the SFU, fine mass and sulfur monitoring

records are considered closely comparable to IMPROVE

and are analyzed as single records. At GLEES, SFU measurements commenced at the Brooklyn Lake tower site

(BRLA = BT), a 30 m diameter opening in the GLEES

forest (Zeller and Hehn, 1996) on 25 July 1989 and ended

29 June 1993. IMPROVE module A BT measurements

commenced 31 August 1993 through 20 August 1998

when it was relocated 10m northeast of the GLEES BL

NDDN site. For this study the sulfur analysis results of

Module A were used to estimate sulfate aerosol concentration.

The comparison “dry” results given below were obtained by assuming that the IMPROVE concentration

average of the Wednesday 24-hr sample plus the Saturday 24-hr sample (total 48-hr sample) would be the best

quantity to compare with the 7-day (168-hr sample)

Year Comparison 

sites 

Valid dataset Reduced 

dataset 

1987 SR-NF 31 24 

1988 SR-NF 22 17 

1989 SR-NF 34 25 

1990 SR-NF 27 22 

1991 SR-NF 41 29 

1992a SR-NF 28 23 

1992b SR-BL 3 3 

1993 SR-BL 31 27 

1994 SR-BL 27 24 

1995 SR-BL 35 32 

1996 SR-BL 28 24 

1997 SR-BL 38 32 

Table 2. Number of weekly data points in each dataset.

precipitation amount of sample i in mm. Extensive regression analyses were made between the SR site and the

other two sites by grouping the weekly data into separate

years and seasons as well as for the whole data set. The

differences in the concentration and deposition between

two sites ([SR-NF] and [SR-BL]) were calculated using

the reduced weekly dataset. The resulting differences

were analyzed two ways: sorting the data by year and

sorting the data by month. Using the data sorted by year

or month, the average differences and standard deviations were also calculated for each species and each year

or month.
4 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-52. 2000

concentration average measured Tuesday to Tuesday by

the NDDN sampler within the same sampled week. Sulfur concentration from module A is determined from a

proton-induced X-ray emission (PIXE) analysis of mass

divided by the total air volume passed through the filter

(Sisler, 1996). SO4

 from module A is determined using the

assumption that all the module A sulfur is sulfate:

SO4

 = 3 * S, using the ratio of molecular weights. Neither

a deposition velocity comparison analysis nor sulfate

deposition comparison analysis could be made separately for the IMPROVE site because edited site specific

meteorological parameters were not available for the

IMPROVE BT site from the GLEES FS program.

Results and Discussion

Wet Deposition

Site comparisons. For each chemical species, the NF

and BL annual, seasonal, and total (i.e., using data for all

years) weekly NADP data were linearly regressed against

the SR NADP data for both the complete valid data set

and for the precipitation-filtered data set. Linear regressions (slopes and offset) were calculated, including standard errors and coefficients of determination (correlation squared) r2 values. Paired differences, standard deviations of paired differences, and 25% trimmed paired

differences (i.e., top and bottom 25% of data trimmed)

were also calculated to evaluate bias. The complete results are presented in Appendix B. Figure 1 is an example

of the weekly deposition “filtered” NADP data for SO4 at

BL and SR. The coefficients of determination for the

filtered seasonal and annual concentration and deposition data from Appendix B are summarized in table 3.

Although the NADP program distinguishes four seasons in their data presentation, our site comparisons

demonstrated only two distinct seasons: winter and summer defined by the average precipitation type; winter

period - snow; and summer period - rain. The GLEES

summer season extends from May 1 to September 30

(although complete snow pack melt above 3150 m does

not typical occur until late June), while the winter season

extends from October 1 to April 30. Precipitation amounts

measured at NF were typically 70% of SR during the

summer and dropped to 50% during winter and at BL

they were 90% year round compared to SR.

The annual coefficients of determination for both concentration and deposition were not uniformly improved

by filtering the weekly data for high and low precipitation (see Appendix B). In such cases it was typical that the

specific culled data value(s) was significantly higher

than average and falsely improved the coefficient of

determination. We believe that the filtered data results

give more realistic statistics for the site comparisons.

From table 3, generally the BL site has better r2 values for

both concentration and deposition data; also the summer

season comparisons at both BL and NF do better than the

winter season. Interestingly, the deposition coefficients

of determination are generally slightly higher than concentration at BL and visa versa at SR. This was not

unexpected because BL is more similar to SR in both

elevation and precipitation amount. Since wet deposition measurements are precipitation quantity dependent, precipitation amount may account for the weaker

NF deposition coefficients compared to concentration.

Measured concentrations were often higher at the lower

sites but deposition is always greater at SR compared to

NF and BL (see Appendix C).

Comparisons of the annual averages (6 data points for

NF and 5 for BL) are also included (in parenthesis) in

table 3 for SR vs. NF and for SR vs. BL. In most cases, r2

values improve significantly when annual averages are

used. Cl concentration comparisons at both sites and the

annual averaged K concentration comparison at BL stand

out with lack of any correlation.

Annual weekly average concentration, annual weekly

average deposition, and annual total deposition amounts

as reported by NADP, including the averages of all years,

are given in Appendix C. Note that the values for 1992

are combined NF (January to September) and BL (September to December). The regression results of comparing the annual total depositions from Appendix C are

given in Appendix D. The r2

 values of the precipitation

filtered annual values in table 3 (in parenthesis) are for

the most part higher than those using NADP reported

data as listed in Appendix C.

y = 0.52x + 0.03

R2

 = 0.62

0.0

0.2

0.4

0.6

0.8

1.0

0.0 0.2 0.4 0.6 0.8 1.0

SR (kg ha-1 wk-1)

BL (kg ha-1 wk-1)

Figure 1. Scatter diagram of SO4 wet deposition data culled

for unrealistic values using precipitation quantity criteria.
USDA Forest Service General Technical Report RMRS-GTR-52. 2000 5

Figure 2. The average and standard deviation of weekly wet

concentration difference between Snowy Range (SR) and

Nash Fork (NF) or Brooklyn Lake (BL) NADP sites: (a) by

year; and (b) by month.

Figure 3. The average and standard deviation of weekly wet

concentration difference between Snowy Range (SR) and

Nash Fork (NF) or Brooklyn Lake (BL) NADP sites: (a) by

year; and (b) by month

Table 3. Coefficients of determination (r2

) for precipitation filtered seasonal weekly and

annual weekly data (and annual averaged weekly data in parenthesis) between NADP

sites (see Appendix B).

NH4 concentration differences

-0.1

-0.05

0

0.05

0.1

1986 1988 1990 1992 1994 1996 1998

Year

SR-NF

SR-BL

NH4 concentration differences

-0.1

-0.05

0

0.05

0.1

0 2 4 6 8 10 12

Month

SR-NF

SR-BL

NO3 concentration differences

-0.5

-0.4

-0.3

-0.2

-0.1

0

0.1

0.2

0.3

0.4

0.5

1986 1988 1990 1992 1994 1996 1998

Ye ar

SR-NF

SR-BL

NO3 concentration differences

-0.5

-0.4

-0.3

-0.2

-0.1

0

0.1

0.2

0.3

0.4

0.5

0 2 4 6 8 10 12

Month

SR-NF

SR-BL

 1987 to Sept. 1992 (SR vs. NF) 

concentration & deposition 

Sept. 1992 to 1997 (SR vs. BL) 

concentration & deposition 

Species Summer Winter 

All weeks 

(yearly averages) Summer Winter 

All weeks 

(yearly averages) 

+ NH4 (conc.) 0.54 0.07 0.45 (0.96) 0.59 0.31 0.47 (0.74) 

 “ (dep.) 0.47 0.12 0.16 (0.66) 0.71 0.48 0.49 (0.91) 

NO3

− (conc.) 0.64 0.51 0.47 (0.64) 0.81 0.55 0.72 (0.74) 

 “ (dep.) 0.41 0.32 0.19 (0.36) 0.84 0.54 0.60 (0.94) 

Cl− (conc.) 0.28 0.12 0.27 (0.06) 0.64 0.14 0.26 (0.00) 

 “ (dep.) 0.24 0.19 0.15 (0.80) 0.88 0.50 0.51 (0.36) 

SO4

2− (conc.) 0.61 0.43 0.45 (0.95) 0.82 0.51 0.70 (0.81) 

 “ (dep.) 0.38 0.43 0.33 (0.64) 0.78 0.60 0.62 (0.95) 

Ca2+ (conc.) 0.60 0.79 0.35 (0.17) 0.75 0.59 0.63 (0.92) 

 “ (dep.) 0.71 0.45 0.42 (0.93) 0.84 0.67 0.75 (0.92) 

Mg2+ (conc.) 0.67 0.61 0.42 (0.53) 0.77 0.70 0.73 (0.77) 

 “ (dep.) 0.65 0.37 0.37 (0.98) 0.79 0.71 0.73 (0.96) 

K+ (conc.) 0.34 0.19 0.22 (0.83) 0.45 0.06 0.38 (0.08) 

 “ (dep.) 0.27 0.08 0.13 (0.64) 0.46 0.18 0.26 (0.52) 

Na+ (conc.) 0.45 0.09 0.22 (0.59) 0.48 0.18 0.22 (0.44) 

 “ (dep.) 0.26 0.16 0.17 (0.54) 0.78 0.36 0.47 (0.34) 
6 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-52. 2000

Figure 4. The average and standard deviation of weekly wet

concentration difference between Snowy Range (SR) and

Nash Fork (NF) or Brooklyn Lake (BL) NADP sites: (a) by

year; and (b) by month.

Figure 5. The average and standard deviation of weekly wet

deposition difference between Snowy Range (SR) and Nash

Fork (NF) or Brooklyn Lake (BL) NADP sites: (a) by year; and

(b) by month.

Figures 2 through 7 present the trimmed paired average weekly difference concentration and deposition results distributed by (a) year (values plotted at end of

year) and (b) by month for NH4

+ , NO3− , and SO4

2− . The

concentration differences pattern (figures 2-4) for the

three species change in 1992 and show that NF concentrations tend to be greater than SR while BL concentrations are mostly lower but can also be higher. The concentration difference distribution by month also demonstrate the two-season annual cycle where concentrations

at SR compared to both NF and BL are likely to be higher

during the winter season and lower during the summer

season. The annual cycles (i.e., distributions by month) of

concentration differences between SR and BL are more

smoothly sinusoidal than those between SR and NF.

Deposition differences (figures 5 – 7) show that SR is

almost always higher than both NF and BL and that BL

deposition is closer to SR than NF. The deposition at both

NF and BL is closer to SR during the summer season. Note

the standard deviations are also smaller during the

summer season. In table 4, the results of the overall

annual average percent ratio of the 25% paired species

difference (i.e., all years SR-NF50 and SR-BL50) from Appendix B are compared to the all years’ average weekly

values for SR listed in Appendix C. Hence this ratio is a

measure of the average overall percent difference in

each species concentration and deposition between sites.

Except for Cl and Na concentrations (which are very

small), the BL site differences are much lower compared

to SR. While average concentration differences are typically less than 11% at both NF and BL (except for NO3

 at

SR), average species deposition differences are consistently much less at BL (7 to 21%) compared to NF (25 to

60%). These differences are similar to the difference in

total precipitation noted above.

Wet sulfur and nitrogen deposition. Wet deposited nitrogen and sulfur were calculated from the SR SO4

−2 , NO3−

and NH4

+ values based on molecular weight. Figure 8

shows the total wet sulfur and total wet nitrogen

SO4 concentration differences

-0.5

-0.4

-0.3

-0.2

-0.1

0

0.1

0.2

0.3

0.4

0.5

1986 1988 1990 1992 1994 1996 1998

Year

SR-NF

SR-BL

SO4 concentration differences

-0.5

-0.4

-0.3

-0.2

-0.1

0

0.1

0.2

0.3

0.4

0.5

0 2 4 6 8 10 12

Month

SR-NF

SR-BL

NH4 deposition differences

-0.01

0

0.01

0.02

0.03

0.04

0.05

0.06

0.07

0.08

0.09

0.1

1986 1988 1990 1992 1994 1996 1998

Year

SR-NF

SR-BL

NH4 deposition differences

-0.01

0

0.01

0.02

0.03

0.04

0.05

0.06

0.07

0.08

0.09

0.1

0 2 4 6 8 10 12

Month

SR-NF

SR-BL
USDA Forest Service General Technical Report RMRS-GTR-52. 2000 7

Figure 7. The average and standard deviation of weekly wet

deposition difference between Snowy Range (SR) and Nash

Fork (NF) or Brooklyn Lake (BL) NADP sites: (a) by year; and

(b) by month.

Figure 6. The average and standard deviation of weekly wet

deposition difference between Snowy Range (SR) and Nash

Fork (NF) or Brooklyn Lake (BL) NADP sites: (a) by year; and

(b) by month.

Table 4. Ratio of annual average paired concentration and annual average paired deposition 

differences to the SR annual average concentration and deposition for the 25% trimmed data.

 1987 to Sept. 1992 (SR - NF) Sept. 1992 to 1997 (SR – BL) 

Species Conc. (%) Dep. (%) Conc. (%) Dep. (%) 

NH4

+ -11 28 6 13 

NO3

− -17 60 3 21 

Cl− 1 32 3 14 

SO4

2− -6 40 4 13 

Ca2+ -6 25 -1 7 

Mg2+ -2 33 -1 10 

K+ -5 33 0 13 

Na+ 3 25 7 18 

SO4 deposition differences

-0.05

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

0.45

0.5

1986 1988 1990 1992 1994 1996 1998

Year

SR-NF

SR-BL

SO4 deposition differences

-0.05

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

0.45

0.5

0 2 4 6 8 10 12

Month

SR-NF

SR-BL

NO3 deposition differences

-0.1

0

0.1

0.2

0.3

0.4

0.5

1986 1988 1990 1992 1994 1996 1998

Year

SR-NF

SR-BL

NO3 deposition differences

-0.1

0

0.1

0.2

0.3

0.4

0.5

0 2 4 6 8 10 12

Month

SR-NF

SR-BL
8 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-52. 2000

Figure 8. Annual total wet and dry nitrogen and sulfur atmospheric deposition taken from available NADP and NDDN data from

1987 to 1997.

deposition at the GLEES area for the years, 1987 – 1997.

The dry deposition results in figure 8 are discussed below.

There is no clear trend to the wet S and N deposition data

except that there appears to be a maximum every four to

five years in both S and N and the two species seem to

track each other annually.

Dry Deposition

As presented in equation 3, the determination of dry

deposition is a measurement plus modeling exercise.

Concentration is the measurement portion of the dry

deposition assessment that both NDDN and IMPROVE

provide, hence the comparison of these two concentration measurements (not deposition), specifically for SO4,

is discussed here. Figure 9a, b, and c are scatter plots of the

weekly sulfate concentration data measured by SFU and

IMPROVE (average of Wednesday + Saturday) compared to NDDN for the three distinct sampling periods:

July 1989 through August 1991, August 1991 through

June 1993, and September 1993 through September 1996,

as explained previously. The coefficients of determination

(figure 9), 0.41, 0.63, and 0.72, improved when NDDN was

moved to the Brooklyn Lake area closer to the BT SFU/

IMPROVE site and improved again when the SFU protocols were replaced with the IMPROVE protocols. These

correlations are very good considering IMPROVE was

originally designed to only measure visibility parameters and that samples only include two-sevenths of the

period sampled by NDDN. The linear regression slopes

for SFU and IMPROVE located at Brooklyn were both

0.63 with similar offsets 0.09 and 0.11, indicating consistent results for both protocols at the same sites (138 m

distance). The slope for the period, October 1989 to August 1991, when NDDN was located in Centennial, WY,

(10 km southeast of BT) was 0.52. The SFU and IMPROVE

measurements were made in a forested opening while

the NDDN measurements were always made in open dry

meadows, hence it is possible that if the IMPROVE measurements were also taken in the open the regression

slope may become larger than 0.63. Figure 10 shows the

SO4

 concentration difference statistics between NDDN

and SFU/IMPROVE for each year separated by the three

periods. Figure 11a, b, and c shows the monthly difference distributions corresponding to figure 10. The 25%

trimmed analysis made for the difference data presented

in figure 11 did not produce different results as it did for

wet N

wet S

dry S

dry N

GLEES TOTAL S & N DEPOSITION

(wet & dry)

kg/ha

year
USDA Forest Service General Technical Report RMRS-GTR-52. 2000 9

Figure 9. Scatter plots of SO4 concentration: (a) SFU (BT) vs.

NDDN (Centennial, WY); (b) SFU (BT) vs. NDDN (BL); and

(c) IMPROVE module A. (BT) vs. NDDN (BL).

the NADP data, hence it is not shown. The overall average differences between NDDN and SFU/IMPROVE (averages of data shown in figure 10) compared to NDDN

were 31%, 26%, and 22% for the three distinct periods.

Only the BT SFU concentration data are available for

comparison to provide an insight of spatial separation

effects on dry deposition. Similar to the wet concentration data that were higher on the average at NF (the

lowest elevation NADP site), the dry concentration

differences also show that the NDDN data collected at

Centennial (lower elevation relative to BL) was slightly

higher (i.e., a larger average difference seen in figure 10)

compared to the NDDN data collected at BL. Unfortunately, without the meteorological information to calculate deposition velocities a spatial dry deposition cannot

be made. As an educated guess, however, greater wind

speeds at the higher elevations would yield larger deposition velocity values (equation 3 and see Appendix A);

hence calculated dry deposition values might be very

similar.

Table 5 gives the annual dry deposition results in kg

ha-1 yr-1 reported by EPA using the NDDN data. Nitric

acid, HNO3 , accounts for the greatest contribution to dry

nitrogen deposition. The annual dry deposition does not

appear to vary much from year to year, nor between the

Figure 10. SO4 annual monthly concentration difference

between GLEES area NDDN and SFU/IMPROVE for the

three distinct sampling periods.

Year SO4

−2 SO2 NH4+ NO3− HNO3

Centennial: CNT169 

1989 0.63 0.92 0.26 0.14 6.10 

1990 0.71 0.69 0.19 0.13 4.51 

1991* 0.56 0.53 0.22 0.14 4.98 

Brooklyn: CNT:BL169 

1992 0.64 0.47 0.22 0.13 4.93 

1993 0.57 0.62 0.19 0.10 5.06 

1994 0.59 0.59 0.19 0.14 5.45 

1995 0.47 0.53 0.19 0.10 5.76 

1996 0.65 0.55 0.24 0.19 6.54 

* combined Centennial, WY and BL locations

Table 5. NDDN site 169 Annual dry deposition (kg ha-1 yr-1).
10 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-52. 2000

Figure 11. a, b, and c. The monthly concentration differences

between GLEES area NDDN and SFU/IMPROVE difference

distributions corresponding to figure 10.

Figure 12. (a) SO4

 annual monthly concentration difference

between Glacier National Park, MT, NDDN and SFU/IMPROVE for the period 4/11/89 to 3/21/95; and (b) the monthly

concentration differences between Glacier National Park, MT,

NDDN and SFU/IMPROVE difference distributions for the

same period.

two sites. Unfortunately simultaneous dry deposition

assessments using IMPROVE were not possible.

Glacier National Park IMPROVE/NDDN comparison

How representative are the GLEES NDDN – IMPROVE

results? A similar analysis of NDDN and IMPROVE SO4

module A data collected at the collocated Glacier National Park sites is presented in figure 12a and b covering

the period April 11, 1989, to March 21, 1995. Glacier

National Park NDDN (GNP168) is located at Lat. 48o

 30’

36”; Long. 114o

 and IMPROVE (GLAC1) is located at Lat.

48o 30’ 38”; Long. 113o 59’ 44”; elevation 3213 m. Compared to the Brooklyn module A (figure 9c), there appears

to be slightly more data dispersion and r2

 = 0.57 compared

to 0.72. However, the overall difference for SO4

 between

the Glacier National Park programs is only 2.6% compared to 22% for Brooklyn. The regression slope, 0.8 for

Glacier National Park is much closer to 1:1; however, the

offset, 0.14, is similar to BL results. Figure 12b annual

difference statistics shows that for some years, IMPROVE

module A average concentrations actually exceed NDDN

averages. This never happened at Brooklyn, but the annual standard deviations for both locations (figures 10

and 12b) are very similar.

Total Sulfur and Nitrogen Deposition

Figure 13 displays the annual wet plus dry sulfur and

the annual wet plus dry nitrogen deposition at the GLEES

area for the years 1989-1996 when complete data sets
USDA Forest Service General Technical Report RMRS-GTR-52. 2000 11

were available. As stated above, wet deposited nitrogen

and wet deposited sulfur were calculated from

SO4

−2 , NO3− , and NH4

+ values at SR based on molecular

weight. Dry deposited nitrogen and dry deposited sulfur

were also calculated from the NDDN CNT169 SO4

−2 ,

NO3

− , SO2

, NH4

+ , and HNO3

 values based on molecular

weight. Different site locations were used for wet and for

dry deposition, based on the small average annual differences shown in figures 5, 6, and 7. Concentrations at

separate dry sites in table 5 are similar. Despite all of this,

figure 13 represents a reasonable characterization of the

total nitrogen and sulfur atmospheric deposition in the

surrounding GLEES subalpine area.

Conclusion

Deposition at separate sites within the Medicine Bow

National Forest in Wyoming have been analyzed for

spatial representativeness and to assess total annual

atmospheric nitrogen and sulfur deposition. The results

indicate that for both wet and dry deposition, spatial

differences are to be expected in the Snowy Range area

and higher elevation wet deposition is greater even though

higher elevation wet concentration values can be lower.

Wet deposition and wet concentration values between

sites are not comparable on a weekly basis and these

differences vary widely; but on an annual basis, results

are similar with greater wet deposition at higher elevations. The spatial comparison of dry deposition, limited

to concentrations, also showed that the measured concentrations tend to be slightly higher at the lower elevation. Data for a spatial comparison of dry deposition was

not available. Air resource managers can use results from

closely located NADP and NDDN sites to evaluate total

deposition on annual time scales with the caveat that

spatial variability is expected. A practical application

might be to use data from these programs to establish

historical deposition values prior to any new upwind

facility expected to impact AQRVs through increased

deposition.

Wet deposition assessed using SR NADP data accounts

for a little under 2 to 4 kg ha-1 yr-1 for nitrogen and a little

under 2 to a little over 3 kg ha-1 yr-1 for sulfur, but there are

no trends. Dry deposition assessed using CASTNET

Figure 13. Total wet and dry nitrogen and sulfur deposition at GLEES for 1989 to 1996.

GLEES TOTAL S & N DEPOSITION

(wet & dry)

1987 1988 1999 1990 1991 1992 1993 1994 1995 1996 1997

year

S

N

1

0

2

3

4

5

6

kg/ha
12 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-52. 2000

(NDDN) ranges from 1.2 to 1.7 kg ha-1 yr-1 and accounts

for about 30% of total deposition for nitrogen. It ranges

0.45 to 0.71 kg ha-1 yr-1 and accounts for about 20% of total

deposition for sulfur. There is no trend for either element.

The limited eight-year record (figure 13) wet plus dry for

nitrogen and sulfur does not show a trend but still reflects

the four- to five-year peak deposition in both elements.

Total nitrogen deposition ranges from 3.7 to 5.7 kg ha-1 yr-1

and sulfur ranges from 2 to 3.8 kg ha-1 yr-1.

Comparisons between NDDN and IMPROVE sulfur

concentrations suggest that IMPROVE data may be useful

for estimating the dry concentration component used for

estimating dry deposition. Although IMPROVE and

NDDN protocols are different, sulfate concentrations do

correlate well. However, there appears to be site specific

differences as shown by the comparison between the

Snowy Range sites and the Glacier National Park sites.

Additional research toward expanding the use of IMPROVE data may prove useful for dry atmospheric deposition assessments. For example, the limited analysis

presented here indicates that IMPROVE concentrations

could be used with valid deposition velocities to estimate

lower limits to dry deposition because IMPROVE concentrations are lower compared to NDDN. Appendix E

provides air resource managers with recommendations

specific to the use of IMPROVE module A data for SO4

concentration and deposition estimates.

References

Bytnerowicz, A., Miller, P, & Olyzyk, D. 1987. Dry deposition of nitrate, ammonium and sulfate to a Ceanothus

crassifolius canopy and surrogate surfaces, Atm. Envir.

21:8 1749-1757.

Colorado State University, NADP/NTN Annual Data

Summary. Precipitation chemistry in the United States

- 1991. Ft. Collins, CO: Nat’l Res. Ecology Labr., CSU.

1992.

Erisman, J.W., C. Beier, G.Draaijers, S. Lindberg. 1994.

Review of deposition monitoring methods, Tellus, 46

B, 79-93.

ESE, Inc. No. 86612-0212-3170. 1990a. National dry deposition network: Laboratory operations manual, EPA

Contract No. 68-02-4451, EPA/AREAL, RTP, NC 27791,

August 1990.

ESE, Inc. No. 86612-0108-2110. 1990b. National dry deposition network: Field operations manual, EPA Contract

No. 68-02-4451, EPA/AREAL, RTP, NC 27791, July 1990.

Hidy, G., Dry deposition relevant to National Parks and

wilderness, contract report to CIRA, CSU, Ft. Collins CO.

30p.

Malm, W.C., Sisler, J.F., Cahill, L., Eldred, R.A., and Pitchford,

M. 1994. Spatial and seasional trends in particle concentration and optical extinction in the U.S., JGR, 99 (D1),

1347-1370.

Musselman, R. C., (Ed.). 1994. The Glacier Lakes ecosystem

experiments site (GLEES): an alpine global change research study area. Gen. Tech. Rep. RM-249. Fort Collins,

CO: USDA Forest Service, Rocky Mountain Forest and

Range Experiment Station. 94 p.

Sisler, J.F., 1996. Spatial and seasonal patterns and long

term variability of the composition of the haze in the U.S.:

An analysis of data from the IMPROVE network, CIRA,

CSU, Ft. Collins, CO. July, ISSN: 0737-5352-32.

Sisterson, D.L., 1991. Report 6: Deposition monitoring:

methods and results, Acidic Deposition: state of science

and Technology ed. P. M. Irving, NAPAP 722 Jackson

Place NW, Wash. DC, 20503, Sept. 1991.

Schmel, G. 1984. Chapter 12: Deposition and resuspension,

In: D. Randerson ed., Atmospheric Science and Power

Production, DOE/TIC-27601 (DE84005177), 533-583.

Wyers, G.P., Duyzer, J.H. 1997. Micrometeorological measurement of the dry deposition flux of sulfate and nitrate

aerosols to coniferous forests, Atm. Envir. 31 (3), 333-343.

Zeller, K. and T. Hehn. 1996. Measurements of upward

turbulent ozone fluxes above a subalpine spruce-fir forest, GRL, 23 (8), 841-844.

Zeller, K., Cerny, M., Bytnerowicz, A., Smith, L., Sestak, M.,

Michalec, M., Pernegr, V. & Kucera, J. 1997. Air pollution

status of a representative site in the Czech Republic Brdy

mountains. Environmental Pollution, 98 (3), 291-297.

Zeller, K., Harrington, D., Riebau, A. and Donev, E. 2000.

Annual wet and dry deposition of sulfur and nitrogen

in the Snowy Range, Wyoming. Environmental Pollution 34(1) 1713-1722.
USDA Forest Service General Technical Report RMRS-GTR-52. 2000 13

Introduction: SO2 – NO2

Deposition

The discussion in this appendix was generated as a

result of a USDA FS Region 2 request for advice in

choosing a reasonable deposition velocity value for calculating NO2

 and SO2 deposition from their concentrations.

The NPS generally uses a value of 0.5 cm s-1 while the FS

Region 2 generally uses a suggested value of 0.7 cm s-1 for

over water NO2

 Vd. The NPS generally uses a value of 5.0

cm s-1 verses the FS Region 2 recommendation of 2.4 cm s-1 for

over water SO2 Vd. Unfortunately there is not just one

answer to the question “What is the best deposition

velocity for acid gases sulfur dioxide (SO2

) and nitrogen

dioxide (NO2)?” because it is a very variable parameter. The

term deposition is broadly used to account for the transfer

of trace gases or aerosols from the atmosphere to vegetation, soil, or other surfaces. Since NO2

 is photochemically

reactive (e.g., it can be converted to NO by reacting with

O3

 or other oxidants) (de Arellano, 1995), some of the

measured NO2 deposition may be due to chemical conversion in the atmosphere rather than to actual deposition to a surface. Deposition of NO2

 is not always downward. Depending on the ambient NO2

 concentration, NO2

may also be emitted from a vegetated surface (Rondo et

al., 1993). At Pawnee National Grassland, we (Stocker et

al., 1993; Padro, 1998) measured increasing upward NO2

fluxes immediately after rainstorms. SO2 also converts

chemically to a sulfate aerosol in the atmosphere. A trace

gas or aerosol flux, Fc , (or deposition) is a product of deposition velocity (Vd ) and the species concentration gradient between atmosphere and the surface. The concentration gradient, ( c z

 – c o ) may either be positive or negative,

while the deposition velocity is always positive. Typically the surface concentration, c o , is assumed to be zero.

Deposition Velocity

Deposition velocity (Vd ) is a parameter that quantifies

the rate of transfer of an aerosol or a trace gas molecule

between ambient air and the surface (such as vegetation

canopy, soil, etc.). As an example, for a molecule of NO2

to pass from free air into a leaf stomata, it will first meet

resistance from the turbulent air it travels through (ra ),

then it will meet a resistance from the laminar boundary

layer adjacent at the leaf surface (rb ) and finally it will

meet a resistance from the stomatal opening (rc ) on the

leaf surface. Mathematically:

Vd = (ra + rb + rc)-1. (A-1)

The above equation is an electrical resistance analogy

that applies better to gases than to aerosols, although in

practice it is used for both (Venkatram, 1999). Note that

this formulation will be more complicated for complex

canopies.

Resistances

There are different formulations for computing the

resistance, Equation A-2 (Hicks, 1991) is one, using standard meteorological measurements that are commonly

used for aerodynamic resistance, ra:

r u a = 9 2 /( ) σ θ for Rt

>10, (daytime) (A-2)

r u a = 4 2 /( ) σ θ for Rt

≤10, (nighttime)

where Rt

 is total solar radiation in Watts m-2; σ θ is the

standard deviation of wind direction in radians (i.e.,

degrees × π/180°); and u is the average wind speed in

m s-1. Equation A-3 can be used to calculate the boundary

layer resistance:

rb

 = 2 (1/ku*) (Sc/Pr)2/3 (A-3)

simplified: rb (NO2 ) = 6.4 u*

-1

rb (SO2 ) = 7.1u*

-1

where k = 0.4 is the von Karman constant; u ur * a = / is the

friction velocity in m s-1; Sc is the Schmidt number, the ratio

of air viscosity to molecular diffusivity (Sc = 1.25 for SO2 and

1.07 for NO2

) (note: Bill Massman [1998] has prepared a

useful review of diffusivities for typical atmospheric

trace gases); and Pr is the Prandlt number, a ratio between

momentum diffusivity and thermal diffusivity (Pr = 0.74

for air; Bird et al., 1960) (Massman [1999] recommends

Pr = 0.71). The canopy physiological resistance, rc , ranges

Appendix A. NO2 & SO2 Deposition Velocity (Vd) Over Water
14 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-52. 2000

from about 0.70 s cm-1 to infinity and is very site specific

and time specific. Over water, rc

 = 0.0 for SO2 . It is beyond

the scope of this short treatise to further describe rc .

Note on meteorological data for resistance calculation:

In the event σθ data is not available σθ can be estimated by

first selecting a Pasquill (1974) stability category from table

A1, then choosing a value for σθ from table A2 (Irwin, 1980).

Effect of Vegetation on

Deposition Velocity

Since plant stomates respond to diurnal changes in the

environment and NO2

 and SO2 are “sparingly soluble”

gases (Hidy, 1999)*, Vd rates will change throughout the

day (note: Hidy’s report on dry deposition is specifically

for air resource managers). For example, measurements

suggest that stomatal function is the most significant

factor controlling NO2 depositiontovegetation (Pilegaard

et al. 1998). Thus, the physiological resistance rc has been

found to be typically an order of magnitude larger than

other resistances in equation A-1. If stomates are controlling NO2

 deposition (and SO2), then the more stomates,

the more deposition. Another vegetation parameter that

has been found to strongly affect NO2 deposition on an

ecosystem level is the leaf area index (LAI). LAI is the

area of leaf surface above a unit area of ground: hence a

LAI of 2 m2 m-2 means that the ground is covered twice by

leaf surface and would have twice the number of stomates

compared to a LAI of 1 m2 m-2. LAI is used in biophysical

models of pollutant deposition (e.g., Nikolov 1997, Zeller

and Nikolov 2000) to scale leaf fluxes to a canopy and

landscape level. On a regional scale, spatial variation of

LAI is one of the most critical factors controlling landscape pattern of deposition velocity. Sometimes Vd is

reported as Vd per leaf surface. As an example we found

that a representative summertime midday Vd for NO2 at

the Pawnee Grassland was 0.07 cm s-1 (Stocker et al.,

1993) and that the LAI of the sparse grassland about the

same time was 0.6 m2 m-2 (Zeller and Hazlett, 1989)

giving a Vd per LAI of 0.07/0.6 = 0.12 cm s-1 LAI-1.

Table A1. Meteorological conditions defining Pasquill’s stability categories. 

Wind speed Daytime insolation Nighttime 

m s-1 Strong Moderate Slight >= 50% Clouds <= 38% clouds 

< 2 A* A-B B - - 

2 A-B B C E F 

4 B B-C C D E 

6 C C-D D D D 

> 6 C D D D D 

* A: extremely unstable; B: moderately unstable; C: slightly unstable; D: near neutral (heavy overcast day or 

night); E: slightly stable; F: moderately stable. 

Table A2. Conversion from Pasquill stability category to 

standard deviation of wind direction (σθ). 

Pasquill stability 

category 

σθ (degrees) 

A σθ >= 22.5 

B 17.5 <= σθ < 22.5 

C 12.5 <= σθ < 17.5 

D 7.5 <= σθ < 12.5 

E 3.8 <= σθ < 7.5 

F σθ < 3.8 
USDA Forest Service General Technical Report RMRS-GTR-52. 2000 15

Experimental NO2 & SO2

Deposition Velocities

Tables A3 and A4 give sample summaries of Vd from

some NO2

 and some SO2 deposition studies and experiments. The background on deposition velocity was

presented above to give air resource managers an idea of

what a Vd is and of just how tenuous the numbers in tables

1 and 2 really are. Simply selecting a value for Vd and

multiplying it by a concentration to estimate NO2

 or SO2

deposition might lead to an erroneous conclusion. For a

valid estimate, one must take into consideration vegetation type (e.g., species composition), canopy structure

(i.e. LAI), season, concentration gradient (not just concentration), and weather conditions.

Table A3. A summary of Vd from some NO2 deposition experiments. 

Lead author Canopy Technique NO2 Vd 

(cm s-1) 

NO2 Vd / LAI 

(cm s-1) 

NO2 rc 

(s cm-1)

Pilegaard ‘98 Agric. w/ forest 

patches 

EC 0.35 

(max) 

NA 200-1000 

Nielson ‘96 vegetation NA 0.2 NA NA 

Erisman ‘94 Elspectsche Veld NA 0.1 TO 0.4 NA NA 

Rondo ’93 

(2@forests) 

Spruce (F#1) 

Pine (F#1) 

Pine (F#2) 

CH NA 0.15 ± 0.13 

0.14 ± 0.11 

0.08 ± 0.07 

NA 

Coe ‘92 Dry heather moor EC 0.1 TO 0.35 NA 548 

(mean) 

Hicks ‘86 grassland EC 1.0 0.4 to 0.8 

Hesterberg ‘96 Meadow EC 0.11 TO 0.24 NA NA 

Stocker ‘93 Dry grassland EC 0.07 0.12 NA 

EC: eddy covariance; CH: chamber 

Table A4. A summary of Vd from some SO2 deposition experiments. 

Lead Author Canopy or 

surface 

Technique SO2 Vd 

(cm s-1) 

SO2 Vd / LAI 

(cm s-1) 

SO2 rc 

(s cm-1)

Sheih ‘79 Water estimate 0.2 to 0.3 NA 0.0 

Walcek ‘86 Conifer 

Water 

model 

 “ 

NA NA 0 0 to 1000 

0.0 

Wesely ‘77 All model 0.1 to 10 

depends on rc 

NA NA 

Hicks ‘86 Grassland EC 0.8 NA 1.0 

Matt ‘87 Deci. Forest EC 0.2 to 1.4 NA 50 to 150 

Davis ‘85 Field? GR <0.1 to 5.0 NA NA 

Granat ‘95 Pine CH 0.033 0.011 3 

Brueggemann 

‘99 

Melpitz site GR 0.16 to 0.37 NA NA 

Erismann ‘99 Speulder forest GR 1.5 (annual 

average) 

NA NA 

Xu ‘98 Forest 

Agric. 

Grassland 

Ocean 

Ocean 

model 0.4 

0.2 

0.5 

0.8 (summer) 

0.5 (winter) 

NA NA 

Brandy ‘96 Ocean GR 0.68 NA NA 

Houmand ‘96 Spruce TF 1.1 NA NA 

Padro ‘93 Deci. Forest EC 0.5 (day) 

0.1 (nite) 

NA NA 

EC: eddy covariance; CH: chamber; GR: gradient; TF: throughfall 
16 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-52. 2000

Discussion

Given that the NPS uses 0.5 cm s-1 vs. 0.7 cm s-1 for the

FS for over-water NO2

 Vd, and since table A3 does not

have an over-water example, and also assuming rc

 for

NO2 over water will be very small (possible zero), the best

approach would be to use equation A-1., assume rc

 = 0.0,

and calculate ra and rb from the actual meteorology and

model Vd as a varying value. Another approach would be

to calculate Vd for a small spectrum of likely meteorological scenarios and take an average value. The NPS and FS

values for SO2 over-water vd, 5.0 and 2.4 cm s-1, seem high

compared to the over ocean values in table A4; however,

fresh water most likely would have a higher Vd value.

JD HHMM WS θ σθ Temp Rad ra u* rb VdH2O Vdveg

 m s-1 Deg. Deg. oC Watt m-2 s cm-1 m s-1 s cm-1 cm s-1 cm s-1 

178 0 1.6 240 13 6.5 1 49 0.18 35 0.15 0.09 

178 30 1.3 239 15 6.5 1 45 0.17 38 0.16 0.09 

178 100 1 239 31 6.2 1 14 0.27 24 0.43 0.10 

178 130 1.8 244 20 5.8 1 18 0.31 20 0.37 0.10 

178 200 2.2 234 16 6.1 1 23 0.31 21 0.30 0.10 

178 230 2.2 236 15 6.1 1 27 0.29 22 0.27 0.10 

178 300 2.4 236 13 6.2 1 32 0.27 23 0.23 0.09 

178 330 2.8 234 14 6 1 24 0.34 19 0.30 0.10 

178 400 3.7 229 11 5.9 1 29 0.36 18 0.26 0.10 

178 430 4.4 227 12 5.8 1.5 21 0.46 14 0.36 0.10 

178 500 3.8 236 13 5.8 14 46 0.29 22 0.17 0.31 

178 530 3.3 236 11 6 75.7 74 0.21 30 0.11 0.28 

178 600 3.5 238 12 6.4 128.3 59 0.24 26 0.14 0.30 

178 630 3.2 245 15 6.5 165.6 41 0.28 23 0.19 0.32 

178 700 4.3 227 13 7 342.4 41 0.33 20 0.19 0.32 

178 730 4.9 221 14 7.4 440.2 31 0.40 16 0.25 0.34 

178 800 5.8 218 17 7.6 536.1 18 0.57 11 0.43 0.36 

178 830 5.4 217 18 7.8 627.7 17 0.57 11 0.44 0.36 

178 900 4.5 218 19 8.3 711.8 18 0.50 13 0.41 0.36 

178 930 4.3 209 19 8.7 792.5 19 0.48 13 0.39 0.35 

178 1000 4.7 209 20 9.2 857 16 0.55 12 0.47 0.36 

178 1030 4.5 202 24 9.6 916.5 11 0.63 10 0.62 0.37 

178 1100 4.7 200 22 9.8 906 13 0.60 11 0.56 0.37 

178 1130 5.1 187 18 10.1 840 18 0.53 12 0.42 0.36 

178 1200 4.5 197 16 10.5 1013 26 0.42 15 0.30 0.34 

178 1230 4.9 207 25 10.9 996.5 10 0.71 9 0.73 0.37 

178 1300 4.2 195 20 11.2 850.5 18 0.49 13 0.42 0.36 

178 1330 4.5 178 18 11.1 753.4 20 0.47 14 0.37 0.35 

178 1400 3.4 190 17 10.8 550.3 30 0.34 19 0.25 0.33 

178 1430 4.3 185 20 11.3 497.5 17 0.50 13 0.43 0.36 

178 1500 4.6 186 17 11.1 595.9 22 0.45 14 0.34 0.35 

178 1530 4 190 19 11.3 614.7 20 0.44 14 0.36 0.35 

178 1600 4 195 17 11.2 541.5 26 0.40 16 0.30 0.34 

178 1630 4.1 197 17 11.3 616.5 25 0.41 16 0.30 0.34 

178 1700 4.4 159 17 10.9 181.9 23 0.44 15 0.33 0.35 

178 1730 7.8 131 15 9 70.4 17 0.68 9 0.46 0.36 

178 1800 3.8 158 18 8.2 27.3 24 0.40 16 0.31 0.34 

178 1830 3.2 209 20 5.9 38.1 23 0.37 17 0.31 0.34 

178 1900 2.4 330 10 5.9 62.6 123 0.14 46 0.07 0.24 

178 1930 2.4 317 10 5.8 30.1 123 0.14 46 0.07 0.24 

178 2000 2.7 220 24 6.4 2 8 0.57 11 0.76 0.10 

178 2030 3.6 228 12 5.5 1 25 0.38 17 0.30 0.10 

178 2100 2.2 190 15 5.6 1 27 0.29 22 0.27 0.10 

178 2130 2.4 139 15 5.2 1 24 0.31 20 0.30 0.10 

178 2200 1.1 183 31 4.3 1 12 0.30 21 0.48 0.10 

178 2230 2.2 221 13 4.6 1 35 0.25 26 0.21 0.09 

178 2300 2.7 235 9 5 1 60 0.21 30 0.13 0.09 

178 2330 3.3 238 12 5.3 1 28 0.35 19 0.27 0.10 

Day 

178 

Avg. = 0.32 0.24 

Day 

179 

Avg. = 0.30 0.24 

Day 

180 

Avg. = 0.63 0.26 

Table A5. Meteorology and deposition velocity for NO2 over water (rc = 0; 30% σθ) and

vegetation [rc

 = 250 s cm-1 (day); 1000 s cm-1 (night)].
USDA Forest Service General Technical Report RMRS-GTR-52. 2000 17

The same approaches as recommended for NO2 above,

assuming rc

 = 0.0, would be the most credible.

As an example for NO2

 using actual meteorology

data, table A5 gives a few days of half-hour average

summertime meteorology over a six-day period as

measured above an alpine forest canopy. The canopy

resistance term for the over-water calculation of

VdH2O(NO2) was taken as rc = 0.0, and since over-water

stability is usually classified below C (table A1), the σθ

values measured above trees were reduced by 70% to

simulate typical over-water σθ. The canopy resistance

for the vegetation was simply estimated as 250 s cm-1

during the day and 1000 s cm-1 at night. Table A5

demonstrates the different half hourly and daily average and six-day average for these two hypothetical

estimates. Table A5 is presented as an exercise to

demonstrate Vd variability and behavior for two different applications and not as a specific recommendation.

JD HHMM WS θ σθ Temp Rad ra u* rb VdH2O Vdveg

 m s-1 Deg. Deg. oC Watt m-2 s cm-1 m s-1 s cm-1 cm s-1 cm s-1 

181 0 7.1 297 13 0.8 0.9 11 0.81 8 0.68 0.10 

181 30 7.5 294 16 0.7 0.9 7 1.05 6 1.04 0.10 

181 100 6.7 291 15 0.6 0.9 9 0.88 7 0.83 0.10 

181 130 7.4 287 16 0.5 0.9 7 1.03 6 1.02 0.10 

181 200 7.6 281 18 0.7 0.9 5 1.19 5 1.30 0.10 

181 230 8.1 284 18 0.4 0.9 5 1.27 5 1.38 0.10 

181 300 9.4 286 15 0 0.8 6 1.23 5 1.16 0.10 

181 330 9.1 288 15 -0.5 0.9 6 1.19 5 1.12 0.10 

181 400 9.6 286 16 -0.6 0.8 5 1.34 5 1.33 0.10 

181 430 10 283 16 -0.6 1.4 5 1.40 5 1.38 0.10 

181 500 9.9 282 16 -0.7 13.2 12 0.92 7 0.66 0.37 

181 530 10.5 277 17 -0.5 73.4 10 1.04 6 0.78 0.38 

181 600 10.3 280 17 -0.5 162.1 10 1.02 6 0.76 0.38 

181 630 10.5 276 17 -0.3 254.2 10 1.04 6 0.78 0.38 

181 700 9.4 273 16 0.1 353.4 12 0.87 7 0.62 0.37 

181 730 8.9 273 19 0.6 453.3 9 0.98 6 0.81 0.38 

181 800 7.7 268 19 1.1 550.7 11 0.85 8 0.70 0.37 

181 830 7.5 268 20 1.6 645 10 0.87 7 0.75 0.37 

181 900 7.9 272 22 2 731.5 8 1.01 6 0.94 0.38 

181 930 6.7 268 21 2.7 810 10 0.82 8 0.73 0.37 

181 1000 7.1 252 20 2.8 878 10 0.83 8 0.71 0.37 

181 1030 7.7 260 17 3 933.5 13 0.76 8 0.57 0.37 

181 1100 7.6 253 17 3.5 978 13 0.75 9 0.56 0.37 

181 1130 7.6 250 19 3.8 1006.5 11 0.84 8 0.69 0.37 

181 1200 7.2 259 20 4.3 1022 10 0.84 8 0.72 0.37 

181 1230 6.4 245 19 4.7 1026.5 13 0.71 9 0.58 0.37 

181 1300 5.5 236 22 5.3 1020 11 0.70 9 0.65 0.37 

181 1330 6.1 245 21 5.8 1000.5 11 0.75 9 0.66 0.37 

181 1400 5.7 247 25 6.2 966 8 0.83 8 0.85 0.38 

181 1430 5.1 245 22 6.6 915.5 12 0.65 10 0.60 0.37 

181 1500 4.3 252 30 6.8 854.5 8 0.75 9 0.88 0.38 

181 1530 3.9 256 30 7.2 784 8 0.68 9 0.80 0.37 

181 1600 3.4 241 31 7.5 702.6 9 0.61 10 0.74 0.37 

181 1630 3.9 263 25 7.8 614.8 12 0.57 11 0.58 0.37 

181 1700 3.8 237 24 7.9 518.3 13 0.53 12 0.53 0.36 

181 1730 3 235 29 8.1 422.4 12 0.51 13 0.58 0.36 

181 1800 3.6 225 17 7.9 324.2 28 0.36 18 0.27 0.34 

181 1830 2.8 215 17 8 229 37 0.28 23 0.21 0.32 

181 1900 2.1 222 16 7.9 45.7 55 0.20 33 0.14 0.30 

181 1930 1.4 235 16 7.2 12.7 82 0.13 49 0.09 0.26 

181 2000 1.5 241 21 6 4.9 20 0.27 23 0.34 0.10 

181 2030 3.4 123 17 5.3 1 13 0.50 13 0.52 0.10 

181 2100 3.1 104 20 4.8 1 11 0.54 12 0.64 0.10 

181 2130 2.7 84 13 4.8 1 29 0.31 21 0.26 0.10 

181 2200 2.1 42 14 4.9 0.9 32 0.26 25 0.23 0.09 

181 2230 2.1 51 13 5.1 0.9 37 0.24 27 0.20 0.09 

181 2300 2 27 14 5.1 1 33 0.24 26 0.22 0.09 

181 2330 2.4 22 7 5.1 1 112 0.15 44 0.07 0.09 

Day 

181 

Avg. = 0.68 0.26 

Table A5. (Cont’d.)
18 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-52. 2000

Table A5. (Cont’d.)

JD HHMM WS θ σθ Temp Rad ra u* rb VdH2O Vdveg

 m s-1 Deg. Deg. oC Watt m-2 s cm-1 m s-1 s cm-1 cm s-1 cm s-1 

182 0 2.2 18 7 5.1 0.9 122 0.13 48 0.07 0.09 

182 30 1.5 7 9 5 0.9 108 0.12 54 0.07 0.09 

182 100 0.5 336 37 4.5 0.9 19 0.16 40 0.29 0.09 

182 130 0.7 286 22 4.3 0.9 39 0.13 48 0.17 0.09 

182 200 1.9 273 13 4.9 0.9 41 0.22 30 0.18 0.09 

182 230 3.2 272 7 5 0.9 84 0.20 33 0.10 0.09 

182 300 4.2 273 9 5 0.9 39 0.33 19 0.20 0.09 

182 330 4.6 278 8 5.3 0.9 45 0.32 20 0.18 0.09 

182 400 4.5 279 9 5.5 0.9 36 0.35 18 0.22 0.09 

182 430 3.7 277 9 5.5 1.3 44 0.29 22 0.18 0.09 

182 500 3.7 280 8 5.5 12.4 125 0.17 37 0.07 0.24 

182 530 2.9 245 11 5.5 70.9 84 0.19 34 0.10 0.27 

182 600 1.8 236 8 5.7 160.6 256 0.08 76 0.03 0.17 

182 630 2.9 226 13 6 251.7 60 0.22 29 0.13 0.29 

182 700 3.2 222 14 6 350.3 47 0.26 25 0.17 0.31 

182 730 2.6 238 23 6.7 449.8 21 0.35 18 0.33 0.34 

182 800 3.9 252 19 7.1 547.6 21 0.43 15 0.35 0.35 

182 830 4.6 254 21 7.4 640.3 15 0.56 11 0.50 0.36 

182 900 5.3 263 23 7.6 725.5 11 0.71 9 0.68 0.37 

182 930 4.7 259 24 7.9 803 11 0.66 10 0.65 0.37 

182 1000 4.4 256 27 8.1 872 9 0.69 9 0.75 0.37 

182 1030 5 254 20 8.3 925.5 15 0.58 11 0.50 0.36 

182 1100 4.7 266 31 8.9 970.5 7 0.85 8 1.02 0.38 

182 1130 4.7 255 25 8.9 997 10 0.68 9 0.70 0.37 

182 1200 5 258 24 9.2 1011.5 10 0.70 9 0.69 0.37 

182 1230 5.5 246 27 9.4 1022 7 0.86 7 0.94 0.38 

182 1300 5.1 251 30 9.7 1013 6 0.89 7 1.05 0.38 

182 1330 5.3 251 24 10.1 991 10 0.74 9 0.73 0.37 

182 1400 5.4 259 25 10.3 959.5 9 0.79 8 0.80 0.37 

182 1430 5.5 257 23 10.3 917 10 0.74 9 0.71 0.37 

182 1500 6.2 266 23 10.3 841.5 9 0.83 8 0.80 0.37 

182 1530 6 268 21 10.5 785.5 11 0.73 9 0.65 0.37 

182 1600 5.3 249 26 10.6 703 8 0.80 8 0.85 0.38 

182 1630 5.4 250 24 10.7 623.3 9 0.75 8 0.75 0.37 

182 1700 4.5 255 26 10.7 448.9 10 0.68 9 0.72 0.37 

182 1730 5.2 277 24 10.7 435.2 10 0.73 9 0.72 0.37 

182 1800 5.6 276 22 10.7 348.2 11 0.72 9 0.66 0.37 

182 1830 5.4 274 21 10.7 304.5 12 0.66 10 0.59 0.37 

182 1900 4.6 283 19 10.5 70.8 18 0.51 13 0.42 0.36 

182 1930 4.5 281 15 9.7 19.2 29 0.39 16 0.26 0.34 

182 2000 3.7 290 14 9 5 18 0.45 14 0.40 0.10 

182 2030 4 293 13 8.6 1 19 0.45 14 0.38 0.10 

182 2100 3.8 311 10 8.3 1 35 0.33 19 0.22 0.09 

182 2130 4 309 10 8.1 1 33 0.35 18 0.23 0.10 

182 2200 4 305 8 8.1 0.9 51 0.28 23 0.15 0.09 

182 2230 3.4 303 8 8.2 1 60 0.24 27 0.13 0.09 

182 2300 4.3 314 7 7.8 0.9 62 0.26 24 0.13 0.09 

182 2330 4.2 317 4 7.2 1 195 0.15 44 0.04 0.08 

Day 

182 

Avg. = 0.43 0.25 

Day 

183 

Avg. = 0.48 0.26 

6-Day Avg. = 

 

0.47 0.25 
USDA Forest Service General Technical Report RMRS-GTR-52. 2000 19

References

Bandy, A.; Thornton, D. C.; Blomquist, B. W.; Chen, S.;

Wade, T. P.; Ianni, J. C.; Mitchell, G. M.; Nadler, W.

1996, Chemistry of dimethyl sulfide in the equatorial

Pacific atmosphere. Geophysical Research Letters.

23(7): 741-744.

Bird, R. B.; Stewart, W. E.; Lightfoot, E. N. 1960. Transport

phenomena. New York: J. Wiley & Sons. 780 p.

Brueggemann, E.; Spindler, G. 1999. Wet and dry deposition

of sulphur at the site Melpitz in East Germany, in

memorium dedicated to Wolfgang Rolle. Water, Air, and

Soil Pollution. 109(1-4): 81-99.

Coe, H.; Gallagher, M. W. 1992. Measurements of dry deposition of NO2

 to a Dutch heathland using the eddycorrelation technique. Quarterly Journal of the Royal

Meteorological Society. 118(506): 767-786.

Davis, C.; Wright, R. 1985. Sulfur dioxide deposition velocity by a concentration gradient measurement system.

Journal of Geophysical Research. 90(D1): 2091-2095.

De Arellano, J. V-G.; Duynkerke, P.; Zeller, K. 1995. Atmospheric surface layer similarity theory applied to chemical reactive species. Journal of Geophysical Research.

100(D1): 1397-1408.

Erisman, J. W.; Hogenkamp, J. E. M.; Van Putten. E. M.;

Uiterwijk, J. W.; Kemkers, E.; Wiese, C. J.; Mennen, M. G.

1999. Long-term continuous measurements of SO2 dry

deposition over the Speulder forest. Water, Air, and

Soil Pollution. 109(1-4): 237-262.

Erisman, J. W.; Vanelzakker, B. G.; Mennen, M. G.;

Hogenkamp, J.; Zwart, E.; Vandenbeld, L.; Romer, F. G.;

Bobbink, R; Hheil, G.; Raessen, M.; Duyzer, J. H.; Verhage,

H.; Wyers, G. P.; Otjes, R. P.; Mols, J. J. 1994. The elspeetsche

veld experiment on surface exchange of trace gases -

summary of results. Atmospheric Environment. 28(3):

487-496.

Granat L.; Richter A. 1995. Dry deposition to pine of sulfurdioxide and ozone at low concentration. Atmospheric

Environment. 29(14): 1677-1683.

Hesterberg, R.; Blatter, A.; Fahrni, M.; Rosset, M.; Neftel, A.;

Eugster, W.; Wanner, H. 1996. Deposition of nitrogencontaining compounds to an extensively managed grassland in central Switzerland. Environmental Pollution.

91(1): 21-34.

Hicks, B.; Hosker, R.; Meyers, T.; Womack, J. 1991. Dry

deposition inferential measurement techniques-I. Design and tests of a prototype meteorological and chemical system for determining dry deposition. Atmospheric Environment. 25A: 2345-2359.

Hicks, B.; Wesely, M.; [and others]. 1986. An experimental

study of sulfur and NOx

 fluxes over grassland. Bdy. Lay.

Meteor. 34: 103-121.

Hidy, G. 1998. Dry deposition relevant to the national

parks and wilderness. Colorado State University Cooperative Institure for Research in the Atmosphere;

Fort Collins contract. November: 30 p.

Hovmand, M. F.; Kemp, K. 1996. Downward trends of

sulphur deposition to Danish spruce forest. Atmospheric

Environment. 30(17): 2989-2999.

Pasquill, F. 1974. Atmospheric diffusion. New York: John

Wiley & Sons.

Pilegaard, K.; Hummelshoj, P.; Jensen, N. O. 1998. Fluxes of

ozone and nitrogen dioxide measured by eddy correlation over a harvested wheat field. Atmospheric Environment. 32(7): 1167-1177.

Massman, W. 1998. A review of the molecular diffusivities

of H2

O, CO2, CH4, CO, O3, SO2, NH3, N2O, NO, and NO2,

in air, O2, and N2 near STP. Atmospheric Environment.

32(6): 1111-1127.

Massman, W. 1999. Molecular diffusivities of Hg vapor in

air, O2

, and N2 near STP and kinematic viscosity and

thermal diffusivity of air near STP. Atmospheric Environment. 33: 453-457.

Matt, D.; McMillen, R.; Womack, J.; Hicks, B. 1987. A

comparison of estimated and measured SO2

deposition velocities. Water, Air, and Soil Pollution.

36: 331-347.

Neubert, A.; Kley, D.; Wildt, J.; Segschneider, H. J.; Forstel, H.

1993. Uptake of NO, NO2 and O3 by sunflower (helianthusannuus l) and tobacco plants (nicotiana-tabacum-l) -

dependence on stomatal conductivity, Part A – General

Topics. Atmospheric Environment. 27(14): 2137-2145.

Nielsen, T.; Pilegaard, K.; Egelov, A. H.; Granby, K.;

Hummelshoj, P.; Jensen, N. O.; Skov, H. 1996. Atmospheric nitrogen compounds: occurrence, composition

and deposition. Science of the Total Environment. 190:

459-465.

Nikolov, N. T. 1997. Mathematical modeling of seasonal

biogeophysical interactions in forest ecosystems. Fort

Collins, CO: Colorado State University. 149 p. Dissertation.

Padro, J.; Zhang, L.; Massman, W. 1998. An analysis of

measurements and modelling of air-surface exchange of

NO-NO2-O3 over grass. Atmospheric Environment. 32(8):

1365-1375.

Padro J.; Neumann, H. H.; Denhartog, G. 1993. Dry deposition velocity estimates of SO2

 from models and measurements over a deciduous forest in winter. Water, Air,

and Soil Pollution. 68(3-4): 325-339.

Rondon,A.; Johansson, C.; Granat, L. 1993. Dry deposition

of nitrogen-dioxide and ozone to coniferous forests. Journal of Geophysical Research-Atmospheres. 98(D3):

5159-5172.

Stocker, D.; Stedman, D.; Zeller, K.; Massman, W.; Fox, D.

1993. Fluxes of NO2 and O3 measured by eddy correlation

over a shotgrass praire. Journal of Geophysical Research.

98(D7): 12,619-12,630.
20 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-52. 2000

Sheih, C.; Wesely, M.; 1979. Hicks, B. Estimated dry deposition velocities of sulfur over the eastern U.S. and

surrounding regions. Atmospheric Environment. 13:

1361-1368.

Venkatram, A.; Pleim, J. 1999. The electrical analogy does

not apply to modeling dry deposition of particals. Atmospheric Environment. 33: 3075-3076.

Walcek, C.; Brost, R.; Chang, J.; Wesely, M. 1986. SO2, sulfate

and HNO3 deposition velocities computed using regional landuse and meteorological data. Atmospheric

Environment. 20(5): 949-964.

Wesely, M.; Hicks, B. 1977. Some factors that affect the

deposition rates of sulfur dioxide and similar gases on

vegetation. Journal of the Air Pollution Control Association. 27(11): 1110-1116.

Xu, Y. W.; Carmichael, G. R. 1998. Modeling the dry

deposition velocity of sulfur dioxide and sulfate in

Asia, Part 1. Journal of Applied Meteorology. 37(10):

1084-1099.

Zeller, K.; Hazlett, D. 1989. O3

 deposition and leaf area index

at the Pawnee National Grassland for the 1988 growing

season. In: Olson, R.; LeFohn, A. (eds.). Trans.: Effects of

air pollution on western forests. AWMS ISBN 0-923204-

03-2: 177-192.

Zeller, K; Nikolov, N.T. 2000. Quantifying simultaneous

fluxes of ozone, carbon dioxide and water vapor above a

subalpine forest ecosystem. Environmental Pollution.

107:1-20.
USDA Forest Service General Technical Report RMRS-GTR-52. 2000 21

NF versus SR Sulfate concentration (mg/L) 

 Complete valid weekly dataset Precip-filtered weekly dataset 

Year Slope Offset R2 N Slope Offset SR–NFT SR-NF50 R2 N 

1987 0.42 ± 0.06 0.47 ± 0.08 0.63 31 0.28 ± 0.14 0.57 ± 0.13 -0.01 ± 0.54 -0.041 0.16 24 

1988 1.27 ± 0.29 -0.02 ± 0.31 0.48 22 1.10 ± 0.32 0.02 ± 0.31 -0.11 ± 0.58 0.01 0.44 17 

1989 1.01 ± 0.09 0.08 ± 0.11 0.78 34 0.83 ± 0.17 0.19 ± 0.15 -0.06 ± 0.33 -0.045 0.50 25 

1990 1.93 ± 0.28 -0.38 ± 0.26 0.66 27 1.41 ± 0.15 -0.19 ± 0.09 -0.04 ± 0.21 -0.005 0.83 22 

1991 1.13 ± 0.13 -0.01± 0.09 0.65 41 1.17 ± 0.18 -0.04 ± 0.12 -0.06 ± 0.30 -0.055 0.60 29 

1992 1.05 ± 0.12 0.03 ± 0.12 0.75 28 0.93 ± 0.18 0.16 ± 0.16 -0.11 ± 0.33 -0.08 0.56 23 

Summer 

87-92 

1.38 ± 0.13 -0.08 ± 0.13 0.55 89 1.02 ± 0.10 0.13 ± 0.09 -0.15 ± 0.29 -0.129 0.61 72 

Winter 

87-92 

1.04 ± 0.07 -0.02 ± 0.06 0.73 85 0.97 ± 0.15 0.02 ± 0.10 0.00 ± 0.40 0.055 0.43 61 

All years 

87-92 

0.90 ± 0.06 0.19 ± 0.07 0.52 183 0.81 ± 0.08 0.19 ± 0.06 -0.06 ± 0.38 -0.039 0.45 140 

BL versus SR Sulfate concentration (mg/L) 

Year Slope Offset R2 N Slope Offset SR–BLT SR-BL50 R2 N 

1992 1.07 ± 0.17 -0.07 ± 0.12 0.98 3 1.07 ± 0.17 -0.07 ± 0.12 0.03 ± 0.08 - 0.98 3 

1993 0.68 ± 0.15 0.15 ± 0.09 0.58 31 0.57 ± 0.13 0.22 ± 0.10 0.07 ± 0.29 0.03 0.43 27 

1994 1.00 ± 0.17 0.07 ± 0.13 0.59 27 0.85 ± 0.11 0.09 ± 0.08 0.00 ± 0.24 -0.034 0.74 24 

1995 0.92 ± 0.06 0.01 ± 0.04 0.87 35 0.92 ± 0.09 0.01 ± 0.05 0.03 ± 0.10 0.028 0.78 32 

1996 1.05 ± 0.08 -0.12 ± 0.06 0.86 28 0.85 ± 0.12 -0.01 ± 0.07 0.09 ± 0.14 0.073 0.71 24 

1997 1.39 ± 0.07 -0.17 ± 0.05 0.91 38 0.98 ± 0.07 0.00 ± 0.04 0.01 ± 0.11 0.006 0.88 32 

Summer 

92-97 

1.21 ± 0.08 -0.11 ± 0.07 0.78 75 0.95 ± 0.06 0.04 ± 0.04 -0.03 ± 0.15 -0.02 0.82 63 

Winter 

92-97 

0.53 ± 0.06 0.13 ± 0.03 0.51 79 0.53 ± 0.06 0.13 ± 0.03 0.09 ± 0.20 0.067 0.51 73 

All Years 

92-97 

1.04 ± 0.05 -0.04 ± 0.04 0.73 162 0.83 ± 0.05 0.06 ± 0.03 0.04 ± 0.18 0.022 0.70 142 

NF versus SR Sulfate deposition (kg/Ha) 

 Valid dataset Reduced dataset 

Year Slope Offset R2 N Slope Offset SR–NFT SR-NF50 R2 N 

1987 0.36 ± 0.10 0.04 ± 0.01 0.32 31 0.28 ± 0.12 0.06 ± 0.02 0.05 ± 0.08 0.032 0.20 24 

1988 0.27 ± 0.10 0.07 ± 0.03 0.26 22 0.28 ± 0.12 0.06 ± 0.04 0.12 ± 0.21 0.062 0.27 17 

1989 0.22 ± 0.04 0.04 ± 0.01 0.51 34 0.22 ± 0.04 0.06 ± 0.02 0.16 ± 0.27 0.08 0.54 25 

1990 0.25 ± 0.07 0.04 ± 0.01 0.35 27 0.25 ± 0.08 0.04 ± 0.02 0.09 ± 0.13 0.059 0.34 22 

1991 0.18 ± 0.10 0.05 ± 0.02 0.08 41 0.15 ± 0.11 0.06 ± 0.02 0.10 ± 0.14 0.065 0.07 29 

1992 0.67 ± 0.10 0.00 ± 0.02 0.62 28 0.70 ± 0.09 -0.01 ± 0.01 0.06 ± 0.04 0.057 0.75 23 

Summer 

87-92 

0.34 ± 0.05 0.06 ± 0.01 0.34 89 0.33 ± 0.05 0.06 ± 0.01 0.04 ± 0.10 0.021 0.38 72 

Winter 

87-92 

0.24 ± 0.03 0.02 ± 0.01 0.40 85 0.25 ± 0.04 0.02 ± 0.01 0.16 ± 0.20 0.106 0.43 61 

All years 

87-92 

0.25 ± 0.03 0.05 ± 0.01 0.30 183 0.25 ± 0.03 0.05 ± 0.01 0.10 ± 0.16 0.056 0.33 140 

BL versus SR Sulfate deposition (kg/Ha) 

Year Slope Offset R2 N Slope Offset SR–BLT SR-BL50 R2 N 

1992 1.14 ± 0.18 0.00 ± 0.01 0.98 3 1.14 ± 0.18 0.00 ± 0.01 0.09 ± 0.16 - 0.98 3 

1993 0.27 ± 0.11 0.08 ± 0.02 0.18 31 0.27 ± 0.09 0.07 ± 0.02 0.05 ± 0.13 0.016 0.26 27 

1994 0.47 ± 0.07 0.04 ± 0.01 0.62 27 0.45 ± 0.08 0.04 ± 0.01 0.02 ± 0.06 0.003 0.58 24 

1995 0.65 ± 0.09 0.03 ± 0.02 0.59 35 0.69 ± 0.10 0.02 ± 0.02 0.03 ± 0.06 0.018 0.59 32 

1996 0.62 ± 0.07 0.01 ± 0.01 0.75 28 0.60 ± 0.08 0.02 ± 0.01 0.04 ± 0.06 0.028 0.71 24 

1997 0.59 ± 0.05 0.03 ± 0.01 0.82 38 0.62 ± 0.04 0.01 ± 0.01 0.05 ± 0.07 0.022 0.91 32 

Summer 

92-97 

0.78 ± 0.07 0.03 ± 0.01 0.63 75 0.77 ± 0.05 0.02 ± 0.01 0.00 ± 0.03 0.002 0.78 63 

Winter 

92-97 

0.45 ± 0.05 0.03 ± 0.01 0.55 79 0.47 ± 0.05 0.02 ± 0.01 0.06 ± 0.10 0.045 0.60 73 

All years 

92-97 

0.51 ± 0.04 0.04 ± 0.01 0.56 162 0.52 ± 0.03 0.03 ± 0.01 0.04 ± 0.08 0.017 0.62 142 

Appendix B. NADP Statistics for , , Cl-, Na+, K+,

Ca2+, Mg2+, and Concentration and Deposition

SO2-

4 NO3

NH+

4
22 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-52. 2000

NF versus SR Nitrate concentration (mg/L) 

 Complete valid weekly dataset Precip-filtered weekly dataset 

Year Slope Offset R2 N Slope Offset SR–NFT SR-NF50 R2 N 

1987 0.34 ± 0.05 0.60 ± 0.08 0.60 31 0.27 ± 0.10 0.68 ± 0.12 -0.08 ± 0.70 -0.14 0.25 24 

1988 1.40 ± 0.15 -0.15 ± 0.18 0.80 22 1.17 ± 0.16 -0.06 ± 0.16 -0.08 ± 0.37 -0.106 0.78 17 

1989 1.24 ± 0.09 0.07 ± 0.12 0.85 34 0.74 ± 0.14 0.37 ± 0.12 -0.19 ± 0.32 -0.222 0.56 25 

1990 2.01 ± 0.25 -0.70 ± 0.30 0.73 27 1.23 ± 0.16 -0.15 ± 0.15 -0.05 ± 0.30 -0.035 0.74 22 

1991 1.34 ± 0.17 -0.11 ± 0.15 0.63 41 1.27 ± 0.20 -0.07 ± 0.16 -0.13 ± 0.38 -0.073 0.61 29 

1992 0.91 ± 0.17 0.32 ± 0.19 0.53 28 1.06 ± 0.21 0.22 ± 0.21 -0.27 ± 0.42 -0.192 0.55 23 

Summer 

87-92 

1.54 ± 0.13 -0.19 ± 0.15 0.61 89 1.14 ± 0.10 0.12 ± 0.10 -0.26 ± 0.35 -0.198 0.64 72 

Winter 

87-92 

1.25 ± 0.06 -0.09 ± 0.07 0.82 85 0.88 ± 0.11 0.13 ± 0.08 -0.04 ± 0.34 -0.017 0.51 61 

All years 

87-92 

0.92 ± 0.06 0.27 ± 0.08 0.53 183 0.76 ± 0.07 0.33 ± 0.07 -0.13 ± 0.44 -0.122 0.47 140 

BL versus SR Nitrate concentration (mg/L) 

Year Slope Offset R2 N Slope Offset SR–BLT SR-BL50 R2 N 

1992 1.05 ± 0.10 -0.15 ± 0.11 0.99 3 1.05 ± 0.10 -0.15 ± 0.11 0.012 ± 0.19 - 0.99 3 

1993 0.76 ± 0.10 0.18 ± 0.10 0.67 31 0.80 ± 0.18 0.18 ± 0.14 0.122 ± 0.20 -0.022 0.44 27 

1994 1.29 ± 0.22 -0.10 ± 0.22 0.58 27 0.93 ± 0.10 0.12 ± 0.10 0.042 ± 0.14 -0.066 0.79 24 

1995 0.86 ± 0.07 0.05 ± 0.06 0.70 35 0.85 ± 0.09 0.06 ± 0.06 -0.06 ± 0.26 0.038 0.76 32 

1996 1.04 ± 0.09 -0.16 ± 0.10 0.85 28 0.86 ± 0.09 -0.006 ± 0.09 -0.04 ± 0.35 0.101 0.79 24 

1997 1.30 ± 0.08 -0.22 ± 0.08 0.88 38 0.96 ± 0.08 0.01 ± 0.07 0.10 ± 0.05 -0.004 0.84 32 

Summer 

92-97 

1.14 ± 0.09 -0.08 ± 0.106 0.71 75 0.97 ± 0.06 0.07 ± 0.06 0.06 ± 0.22 -0.048 0.81 63 

Winter 

92-97 

0.65 ± 0.07 0.16 ± 0.05 0.52 79 0.66 ± 0.07 0.15 ± 0.05 0.08 ± 0.23 0.076 0.55 73 

All years 

92-97 

1.06 ± 0.05 -0.05 ± 0.05 0.71 162 0.89 ± 0.05 0.06 ± 0.04 0.02 ± 0.24 0.020 0.72 142 

NF versus SR Nitrate deposition (kg/Ha) 

 Valid dataset Reduced dataset 

Year Slope Offset R2 N Slope Offset SR–NFT SR-NF50 R2 N 

1987 0.42 ± 0.11 0.041 ± 0.017 0.34 31 0.29 ± 0.14 0.071 ± 0.023 0.035 ± 0.089 - 0.17 24 

1988 0.05 ± 0.11 0.085 ± 0.023 0.01 22 0.06 ± 0.10 0.081 ± 0.025 0.088 ± 0.165 0.003 0.33 17 

1989 0.16 ± 0.05 0.063 ± 0.017 0.27 34 0.17 ± 0.05 0.077 ± 0.020 0.138 ± 0.266 0.011 0.33 25 

1990 0.22 ± 0.08 0.066 ± 0.02 0.26 27 0.20 ± 0.09 0.074 ± 0.027 0.137 ± 0.178 0.006 0.22 22 

1991 0.21 ± 0.10 0.063 ± 0.025 0.10 41 0.26 ± 0.12 0.059 ± 0.033 0.113 ± 0.149 0.007 0.15 29 

1992 0.54 ± 0.12 0.025 ± 0.022 0.44 28 0.52 ± 0.13 0.026 ± 0.025 0.059 ± 0.071 0.011 0.45 23 

Summer 

87-92 

0.46 ± 0.06 0.060 ± 0.012 0.39 89 0.45 ± 0.07 0.059 ± 0.014 0.030 ± 0.088 0.018 0.41 72 

Winter 

87-92 

0.14 ± 0.03 0.046 ± 0.009 0.24 85 0.15 ± 0.03 0.053 ± 0.010 0.174 ± 0.207 0.122 0.32 61 

All years 

87-92 

0.19 ± 0.03 0.067 ± 0.008 0.17 183 0.20 ± 0.03 0.074 ± 0.009 0.096 ± 0.168 0.051 0.19 140 

BL versus SR Nitrate deposition (kg/Ha) 

Year Slope Offset R2 N Slope Offset SR–BLT SR-BL50 R2 N 

1992 -3.13 ± 1.8 0.462 ± 0.196 0.76 3 -3.13 ± 1.8 0.462 ± 0.196 0.099 ± 0.149 0.002 0.76 3 

1993 0.48 ± 0.18 0.081 ± 0.037 0.20 31 0.52 ± 0.19 0.065 ± 0.039 0.014 ± 0.133 0.003 0.23 27 

1994 0.48 ± 0.08 0.054 ± 0.013 0.56 27 0.43 ± 0.10 0.062 ± 0.016 0.013 ± 0.067 -0.0004 0.48 24 

1995 0.72 ± 0.10 0.030 ± 0.022 0.63 35 0.77 ± 0.10 0.014 ± 0.025 0.035 ± 0.070 0.005 0.66 32 

1996 0.69 ± 0.08 0.014 ± 0.021 0.74 28 0.68 ± 0.09 0.019 ± 0.027 0.055 ± 0.096 0.012 0.71 24 

1997 0.60 ± 0.06 0.045 ± 0.015 0.74 38 0.66 ± 0.05 0.020 ± 0.015 0.055 ± 0.079 0.006 0.84 32 

Summer 

92-97 

0.87 ± 0.06 0.025 ± 0.011 0.77 75 0.87 ± 0.05 0.021 ± 0.010 -0.004 ± 0.038 -0.001 0.84 63 

Winter 

92-97 

0.52 ± 0.06 0.045 ± 0.016 0.50 79 0.56 ± 0.06 0.030 ± 0.017 0.065 ± 0.109 0.060 0.54 73 

All years 

92-97 

0.61 ± 0.04 0.044 ± 0.010 0.57 162 0.64 ± 0.04 0.036 ± 0.011 0.036 ± 0.093 0.024 0.60 142 

Appendix B. (Cont’d.)
USDA Forest Service General Technical Report RMRS-GTR-52. 2000 23

NF versus SR Chlorine concentration (mg/L) 

 Complete valid weekly dataset Precip-filtered weekly dataset 

Year Slope Offset R2 N Slope Offset SR–NFT SR-NF50 R2 N 

1987 0.16 ± 0.03 0.08 ± 0.01 0.57 31 0.16 ± 0.02 0.07 ± 0.009 0.07 ± 0.36 0.0008 0.71 24 

1988 1.66 ± 0.11 -0.06 ± 0.02 0.91 22 1.23 ± 0.24 -0.02 ± 0.03 -0.006 ± 0.04 -0.007 0.63 17 

1989 0.73 ± 0.08 0.05 ± 0.03 0.72 34 0.27 ± 0.13 0.07 ± 0.02 0.02 ± 0.08 0.004 0.15 25 

1990 3.91 ± 2.17 -0.14 ± 0.41 0.12 27 -0.004 ± 0.08 0.10 ± 0.01 0.03 ± 0.13 0.009 0.00 22 

1991 0.52 ± 0.17 0.08 ± 0.03 0.20 41 0.50 ± 0.16 0.04 ± 0.02 0.002 ± 0.04 0.0007 0.26 29 

1992 0.50 ± 0.15 0.06 ± 0.02 0.30 28 0.46 ± 0.16 0.07 ± 0.03 0.006 ± 0.10 -0.007 0.28 23 

Summer 

87-92 

4.32 ± 1.09 -0.30 ± 0.15 0.15 89 0.47 ± 0.09 0.06 ± 0.01 -0.005 ± 0.06 -0.007 0.28 72 

Winter 

87-92 

0.68 ± 0.06 0.04 ± 0.02 0.59 85 0.22 ± 0.08 0.06 ± 0.01 0.03 ± 0.10 0.014 0.12 61 

All years 

87-92 

0.59 ± 0.20 0.10 ± 0.05 0.05 183 0.18 ± 0.03 0.08 ± 0.006 0.02 ± 0.17 0.001 0.27 140 

BL versus SR Chlorine concentration (mg/L) 

Year Slope Offset R2 N Slope Offset SR–BLT SR-BL50 R2 N 

1992 -1.6 ± 2.14 0.22 ± 0.14 0.34 3 -1.55 ± 2.1 0.22 ± 0.14 -0.05 ± 0.07 - 0.34 3 

1993 0.32 ± 0.06 0.05 ± 0.01 0.52 31 0.17 ± 0.07 0.06 ± 0.01 0.03 ± 0.10 0.005 0.20 27 

1994 0.57 ± 0.27 0.03 ± 0.02 0.16 27 0.47 ± 0.17 0.03 ± 0.01 0.009 ± 0.04 0.002 0.25 24 

1995 0.64 ± 0.10 0.016 ± 0.01 0.55 35 0.53 ± 0.11 0.02 ± 0.01 0.01 ± 0.03 0.007 0.42 32 

1996 3.41 ± 0.95 -0.24 ± 0.14 0.33 28 0.51 ± 0.13 0.03 ± 0.02 0.02 ± 0.04 0.010 0.40 24 

1997 1.76 ± 0.17 -0.05 ± 0.01 0.75 38 0.84 ± 0.13 0.01 ± 0.01 -0.002 ± 0.02 0.000 0.60 32 

Summer 

92-97 

1.51 ± 0.35 -0.03 ± 0.05 0.21 75 0.71 ± 0.07 0.02 ± 0.007 0.0005 ± 0.03 -0.003 0.64 63 

Winter 

92-97 

0.20 ± 0.05 0.05 ± 0.006 0.17 79 0.17 ± 0.05 0.05 ± 0.006 0.02 ± 0.07 0.011 0.14 73 

All years 

92-97 

0.99 ± 0.18 0.002 ± 0.02 0.16 162 0.32 ± 0.05 0.05 ± 0.005 0.012 ± 0.054 0.003 0.26 142 

NF versus SR Chlorine deposition (kg/Ha) 

 Valid dataset Reduced dataset 

Year Slope Offset R2 N Slope Offset SR–NFT SR-NF50 R2 N 

1987 0.12 ± 0.02 0.006 ± 0.001 0.47 31 0.10 ± 0.02 0.008 ± 0.001 0.014 ± 0.03 0.005 0.49 24 

1988 0.18 ± 0.06 0.008 ± 0.002 0.34 22 0.20 ± 0.06 0.007 ± 0.002 0.02 ± 0.03 0.010 0.45 17 

1989 0.07 ± 0.02 0.009 ± 0.002 0.20 34 0.08 ± 0.03 0.010 ± 0.002 0.04 ± 0.06 0.014 0.29 25 

1990 0.00 ± 0.04 0.016 ± 0.004 0.00 27 0.009 ± 0.03 0.014 ± 0.003 0.03 ± 0.08 0.014 0.00 22 

1991 0.01 ± 0.04 0.010 ± 0.002 0.00 41 0.14 ± 0.06 0.007 ± 0.002 0.02 ± 0.02 0.010 0.18 29 

1992 0.06 ± 0.04 0.009 ± 0.001 0.09 28 0.05 ± 0.04 0.010 ± 0.001 0.02 ± 0.03 0.008 0.09 23 

Summer 

87-92 

0.15 ± 0.05 0.01 ± 0.001 0.10 89 0.17 ± 0.04 0.010 ± 0.001 0.007 ± 0.04 0.003 0.24 72 

Winter 

87-92 

0.05 ± 0.01 0.008 ± 0.001 0.12 85 0.06 ± 0.02 0.009 ± 0.001 0.04 ± 0.06 0.020 0.19 61 

All years 

87-92 

0.05 ± 0.01 0.01 ± 0.0009 0.07 183 0.07 ± 0.01 0.010 ± 0.0008 0.022 ± 0.047 0.009 0.15 140 

BL versus SR Chlorine deposition (kg/Ha) 

Year Slope Offset R2 N Slope Offset SR–BLT SR-BL50 R2 N 

1992 -2.66 ± 3.3 0.04 ± 0.02 0.40 3 -2.66 ± 3.3 0.04 ± 0.02 0.001 ± 0.003 - 0.40 3 

1993 0.23 ± 0.06 0.01 ± 0.003 0.36 31 0.25 ± 0.05 0.010 ± 0.003 0.01 ± 0.03 0.003 0.48 27 

1994 0.34 ± 0.08 0.005 ± 0.001 0.45 27 0.32 ± 0.09 0.005 ± 0.002 0.005 ± 0.01 0.001 0.39 24 

1995 0.46 ± 0.11 0.007 ± 0.003 0.34 35 0.51 ± 0.11 0.005 ± 0.003 0.007 ± 0.01 0.003 0.43 32 

1996 0.57 ± 0.08 0.005 ± 0.003 0.64 28 0.59 ± 0.07 0.004 ± 0.003 0.008 ± 0.01 0.005 0.73 24 

1997 0.48 ± 0.06 0.006 ± 0.002 0.62 38 0.54 ± 0.06 0.004 ± 0.002 0.005 ± 0.01 0.002 0.74 32 

Summer 

92-97 

0.84 ± 0.06 0.003 ± 0.001 0.73 75 0.86 ± 0.04 0.001 ± 0.001 0.0005 ± 0.001 0.0004 0.88 63 

Winter 

92-97 

0.28 ± 0.04 0.009 ± 0.001 0.44 79 0.30 ± 0.03 0.008 ± 0.001 0.01 ± 0.02 0.007 0.50 73 

All years 

92-97 

0.37 ± 0.03 0.008 ± 0.001 0.44 162 0.39 ± 0.03 0.007 ± 0.001 0.007 ± 0.02 0.003 0.51 142 

Appendix B. (Cont’d.)
24 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-52. 2000

NF versus SR Sodium concentration (mg/L) 

 Complete valid weekly dataset Precip-filtered weekly dataset 

Year Slope Offset R2 N Slope Offset SR–NFT SR-NF50 R2 N 

1987 0.16 ± 0.05 0.07 ± 0.02 0.29 31 0.14 ± 0.05 0.07 ± 0.02 0.05 ± 0.31 0.002 0.28 24 

1988 1.02 ± 0.23 0.01 ± 0.04 0.49 22 1.06 ± 0.40 0.006 ± 0.05 -0.01 ± 0.09 -0.0003 0.33 17 

1989 0.62 ± 0.07 0.04 ± 0.04 0.69 34 0.05 ± 0.08 0.11 ± 0.03 0.07 ± 0.29 0.012 0.02 25 

1990 0.45 ± 0.17 0.04 ± 0.02 0.23 27 0.22 ± 0.12 0.04 ± 0.01 0.02 ± 0.08 0.003 0.14 22 

1991 0.53 ± 0.19 0.06 ± 0.03 0.16 41 0.22 ± 0.16 0.05 ± 0.01 0.01± 0.06 0.005 0.07 29 

1992 0.71 ± 0.11 0.02 ± 0.02 0.61 28 0.71 ± 0.12 0.02 ± 0.02 0.02 ± 0.09 0.007 0.63 23 

Summer 

87-92 

0.68 ± 0.08 0.04 ± 0.01 0.43 89 0.59 ± 0.08 0.04 ± 0.01 0.003 ± 0.07 -0.001 0.45 72 

Winter 

87-92 

0.62 ± 0.05 0.03 ± 0.02 0.62 85 0.16 ± 0.06 0.07 ± 0.02 0.04 ± 0.19 0.015 0.09 61 

All years 

87-92 

0.50 ± 0.04 0.05 ± 0.01 0.50 183 0.22 ± 0.05 0.06 ± 0.01 0.03 ± 0.19 0.004 0.22 140 

BL versus SR Sodium concentration (mg/L) 

Year Slope Offset R2 N Slope Offset SR–BLT SR-BL50 R2 N 

1992 0.40 ± 0.53 0.08 ± 0.06 0.36 3 0.40 ± 0.53 0.08 ± 0.06 -0.02 ± 0.05 - 0.36 3 

1993 0.49 ± 0.05 0.02 ± 0.01 0.78 31 0.11 ± 0.06 0.06 ± 0.01 0.04 ± 0.12 0.008 0.11 27 

1994 0.07 ± 0.15 0.04 ± 0.01 0.01 27 0.19 ± 0.12 0.03 ± 0.007 0.01 ± 0.03 0.004 0.11 24 

1995 0.29 ± 0.10 0.03 ± 0.008 0.21 35 0.29 ± 0.10 0.03 ± 0.008 0.02 ± 0.04 0.009 0.20 32 

1996 0.97 ± 0.11 -0.01 ± 0.01 0.73 28 0.44 ± 0.10 0.03 ± 0.01 0.02 ± 0.04 0.012 0.45 24 

1997 1.23 ± 0.21 -0.01 ± 0.01 0.48 38 0.57 ± 0.11 0.02 ± 0.007 0.003 ± 0.02 -0.0006 0.49 32 

Summer 

92-97 

0.64 ± 0.04 0.03 ± 0.007 0.79 75 0.51 ± 0.07 0.03 ± 0.005 0.004 ± 0.035 0.001 0.48 63 

Winter 

92-97 

0.15 ± 0.04 0.04 ± 0.004 0.16 79 0.16 ± 0.04 0.04 ± 0.005 0.024 ± 0.07 0.012 0.18 73 

All years 

92-97 

0.53 ± 0.03 0.02 ± 0.005 0.62 162 0.23 ± 0.04 0.04 ± 0.004 0.015 ± 0.06 0.005 0.22 142 

NF versus SR Sodium deposition (kg/Ha) 

 Valid dataset Reduced dataset 

Year Slope Offset R2 N Slope Offset SR–NFT SR-NF50 R2 N 

1987 0.16 ± 0.05 0.005 ± 0.002 0.26 31 0.15 ± 0.06 0.007 ± 0.002 0.011 ± 0.03 0.003 0.24 24 

1988 0.25 ± 0.10 0.007 ± 0.004 0.28 22 0.26 ± 0.11 0.006 ± 0.006 0.020 ± 0.03 0.011 0.29 17 

1989 0.06 ± 0.02 0.009 ± 0.002 0.22 34 0.05 ± 0.02 0.011 ± 0.003 0.062 ± 0.012 0.018 0.21 25 

1990 0.06 ± 0.04 0.006 ± 0.002 0.10 27 0.05 ± 0.04 0.007 ± 0.002 0.020 ± 0.05 0.007 0.07 22 

1991 0.06 ± 0.04 0.006 ± 0.002 0.05 41 0.13 ± 0.05 0.006 ± 0.002 0.017 ± 0.03 0.008 0.19 29 

1992 0.07 ± 0.03 0.006 ± 0.001 0.14 28 0.06 ± 0.04 0.007 ± 0.001 0.014 ± 0.03 0.006 0.13 23 

Summer 

87-92 

0.17 ± 0.03 0.006 ± 0.0007 0.27 89 0.16 ± 0.03 0.007 ± 0.001 0.007 ± 0.02 0.002 0.26 72 

Winter 

87-92 

0.07 ± 0.02 0.007 ± 0.001 0.15 85 0.07 ± 0.02 0.008 ± 0.002 0.04 ± 0.09 0.019 0.16 61 

All years 

87-92 

0.07 ± 0.01 0.007 ± 0.008 0.16 183 0.08 ± 0.01 0.008 ± 0.001 0.024 ± 0.062 0.007 0.17 140 

BL versus SR Sodium deposition (kg/Ha) 

Year Slope Offset R2 N Slope Offset SR–BLT SR-BL50 R2 N 

1992 -0.40 ± 2.3 0.018 ± 0.02 0.03 3 -0.40 ± 2.3 0.018 ± 0.02 -0.005 ± 0.007 - 0.03 3 

1993 0.22 ± 0.10 0.010 ± 0.003 0.15 31 0.26 ± 0.10 0.008 ± 0.003 0.008 ± 0.018 0.003 0.21 27 

1994 0.34 ± 0.07 0.003 ± 0.001 0.49 27 0.32 ± 0.08 0.003 ± 0.001 0.004 ± 0.008 0.001 0.44 24 

1995 0.43 ± 0.10 0.005 ± 0.003 0.34 35 0.42 ± 0.12 0.005 ± 0.003 0.007 ± 0.013 0.004 0.31 32 

1996 0.47 ± 0.06 0.004 ± 0.002 0.68 28 0.45 ± 0.07 0.005 ± 0.002 0.009 ± 0.014 0.006 0.64 24 

1997 0.46 ± 0.04 0.004 ± 0.001 0.77 38 0.47 ± 0.05 0.004 ± 0.001 0.005 ± 0.010 0.008 0.77 32 

Summer 

92-97 

0.75 ± 0.06 0.002 ± 0.001 0.72 75 0.75 ± 0.05 0.002 ± 0.001 0.001 ± 0.005 0.0006 0.78 63 

Winter 

92-97 

0.31 ± 0.04 0.006 ± 0.001 0.39 79 0.31 ± 0.05 0.006 ± 0.002 0.010 ± 0.016 0.007 0.36 73 

All years 

92-97 

0.41 ± 0.04 0.005 ± 0.0008 0.46 162 0.41 ± 0.04 0.005 ± 0.001 0.006 ± 0.013 0.003 0.47 142 

Appendix B. (Cont’d.)
USDA Forest Service General Technical Report RMRS-GTR-52. 2000 25

NF versus SR Potassium concentration (mg/L) 

 Complete valid weekly dataset Precip-filtered weekly dataset 

Year Slope Offset R2 N Slope Offset SR–NFT SR-NF50 R2 N 

1987 0.20 ± 0.07 0.02 ± 0.006 0.20 31 0.19 ± 0.09 0.019 ± 0.007 0.008 ± 0.07 -0.003 0.19 24 

1988 1.38 ± 0.23 -0.001 ± 0.006 0.65 22 1.40 ± 0.20 -0.006 ± 0.005 -0.001 ± 0.02 0.0004 0.77 17 

1989 1.15 ± 0.27 0.004 ± 0.007 0.37 34 0.81 ± 0.21 0.003 ± 0.004 0.0003 ± 0.01 0.000 0.40 25 

1990 63.2 ± 16.8 -0.66 ± 0.34 0.36 27 0.41 ± 0.17 0.005 ± 0.003 0.003 ± 0.01 -0.0005 0.23 22 

1991 0.63 ± 0.06 0.008 ± 0.004 0.71 41 0.76 ± 0.09 0.004 ± 0.002 -0.0007 ± 0.01 -0.0009 0.70 29 

1992 0.10 ± 0.10 0.02 ± 0.004 0.03 28 0.08 ± 0.11 0.02 ± 0.005 0.001 ± 0.04 -0.003 0.02 23 

Summer 

87-92 

3.67 ± 2.8 0.02 ± 0.11 0.02 89 0.56 ± 0.09 0.01 ± 0.003 -0.001 ± 0.03 -0.003 0.34 72 

Winter 

87-92 

0.54 ± 0.06 0.008 ± 0.002 0.50 85 0.60 ± 0.16 0.005 ± 0.003 -0.0004 ± 0.01 0.0005 0.19 61 

All years 

87-92 

1.27 ± 1.03 0.04 ± 0.05 0.01 183 0.27 ± 0.05 0.013 ± 0.002 0.002 ± 0.03 -0.0009 0.22 140 

BL versus SR Potassium concentration (mg/L) 

Year Slope Offset R2 N Slope Offset SR–BLT SR-BL50 R2 N 

1992 1.80 ± 0.09 0.002 ± 0.002 1.00 3 1.80 ± 0.09 0.002 ± 0.002 -0.013 ± 0.01 - 1.00 3 

1993 1.20 ± 0.29 -0.002 ± 0.004 0.57 31 0.93 ± 0.19 0.001 ± 0.003 -0.0002 ± 0.01 -0.0004 0.48 27 

1994 1.50 ± 0.24 -0.002 ± 0.006 0.61 27 1.48 ± 0.25 -0.002 ± 0.006 -0.007 ± 0.02 -0.0023 0.62 24 

1995 1.64 ± 0.25 -0.005 ± 0.006 0.56 35 2.05 ± 0.43 -0.01 ± 0.007 -0.003 ± 0.03 0.0003 0.43 32 

1996 0.80 ± 0.17 0.005 ± 0.005 0.45 28 0.44 ± 0.19 0.01 ± 0.005 0.0009 ± 0.02 0.002 0.20 24 

1997 2.66 ± 0.15 -0.02 ± 0.005 0.90 38 0.57 ± 0.21 0.005 ± 0.004 0.0008 ± 0.01 0.002 0.20 32 

Summer 

92-97 

2.17 ± 0.14 -0.016 ± 0.005 0.76 75 1.46 ± 0.20 -0.002 ± 0.005 -0.008 ± 0.03 -0.002 0.45 63 

Winter 

92-97 

0.25 ± 0.11 0.006 ± 0.002 0.06 79 0.25 ± 0.11 0.006 ± 0.002 0.003 ± 0.01 0.002 0.06 73 

All Years 

92-97 

1.95 ± 0.10 -0.012 ± 0.003 0.70 162 1.17 ± 0.13 -0.001 ± 0.003 -0.002 ± 0.02 0.000 0.38 142 

NF versus SR Potassium deposition (kg/Ha) 

 Valid dataset Reduced dataset 

Year Slope Offset R2 N Slope Offset SR–NFT SR-NF50 R2 N 

1987 0.11 ± 0.09 0.002 ± 0.0006 0.05 31 0.08 ± 0.10 0.002 ± 0.0008 0.001 ± 0.007 0.0004 0.03 24 

1988 0.25 ± 0.07 0.001 ± 0.0005 0.38 22 0.28 ± 0.06 0.001 ± 0.0005 0.003 ± 0.004 0.001 0.57 17 

1989 0.19 ± 0.06 0.001 ± 0.0003 0.25 34 0.21 ± 0.07 0.001 ± 0.0004 0.003 ± 0.004 0.002 0.32 25 

1990 -0.18 ± 0.4 0.005 ± 0.003 0.01 27 0.05 ± 0.04 0.001 ± 0.0004 0.004 ± 0.007 0.001 0.07 22 

1991 0.19 ± 0.07 0.001 ± 0.0004 0.17 41 0.20 ± 0.06 0.001 ± 0.0004 0.003 ± 0.005 0.001 0.30 29 

1992 0.17 ± 0.08 0.002 ± 0.0005 0.14 28 0.15 ± 0.09 0.002 ± 0.0006 0.002 ± 0.004 0.001 0.12 23 

Summer 

87-92 

0.09 ± 0.19 0.003 ± 0.001 0.00 89 0.20 ± 0.04 0.002 ± 0.0003 0.002 ± 0.004 0.0004 0.27 72 

Winter 

87-92 

0.12 ± 0.04 0.001 ± 0.0003 0.08 85 0.12 ± 0.05 0.001 ± 0.0004 0.003 ± 0.005 0.002 0.08 61 

All years 

87-92 

0.09 ± 0.08 0.002 ± 0.0006 0.01 183 0.14 ± 0.03 0.002 ± 0.0002 0.003 ± 0.005 0.001 0.13 140 

BL versus SR Potassium deposition (kg/Ha) 

Year Slope Offset R2 N Slope Offset SR–BLT SR-BL50 R2 N 

1992 1.84 ± 0.90 0.0006 ± 0.001 0.81 3 1.84 ± 0.90 0.0006 ± 0.001 0.0001 ± 0.002 - 0.81 3 

1993 0.93 ± 0.22 0.0004 ± 0.001 0.39 31 0.90 ± 0.13 0.000 ± 0.006 0.0009 ± 0.002 0.0002 0.66 27 

1994 0.70 ± 0.20 0.001 ± 0.0008 0.34 27 0.68 ± 0.22 0.001 ± 0.001 0.0003 ± 0.002 -0.0001 0.31 24 

1995 1.30 ± 0.26 -0.001 ± 0.001 0.44 35 1.35 ± 0.28 -0.001 ± 0.001 0.0008 ± 0.002 0.0003 0.44 32 

1996 0.31 ± 0.12 0.002 ± 0.0009 0.23 28 0.27 ± 0.13 0.003 ± 0.001 0.002 ± 0.006 0.0007 0.17 24 

1997 0.33 ± 0.10 0.001 ± 0.0006 0.23 38 0.34 ± 0.12 0.001 ± 0.0007 0.002 ± 0.004 0.0009 0.22 32 

Summer 

92-97 

1.04 ± 0.14 0.001 ± 0.0007 0.45 75 1.04 ± 0.14 0.0006 ± 0.001 -0.001 ± 0.004 -0.0002 0.46 63 

Winter 

92-97 

0.20 ± 0.05 0.001 ± 0.0003 0.19 79 0.20 ± 0.05 0.001 ± 0.0003 0.002 ± 0.004 0.001 0.18 73 

All years 

92-97 

0.56 ± 0.07 0.001 ± 0.0004 0.26 162 0.55 ± 0.08 0.001 ± 0.0004 0.0006 ± 0.004 0.0004 0.26 142 

Appendix B. (Cont’d.)
26 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-52. 2000

NF versus SR Calcium concentration (mg/L) 

 Complete valid weekly dataset Precip-filtered weekly dataset 

Year Slope Offset R2 N Slope Offset SR–NFT SR-NF50 R2 N 

1987 0.22 ± 0.03 0.16 ± 0.03 0.68 31 0.19 ± 0.03 0.15 ± 0.03 0.13 ± 0.86 -0.01 0.69 24 

1988 0.95 ± 0.16 0.06 ± 0.06 0.63 22 0.84 ± 0.15 0.05 ± 0.05 -0.006 ± 0.15 0.02 0.67 17 

1989 1.35 ± 0.08 -0.02 ± 0.04 0.90 34 1.42 ± 0.15 -0.05 ± 0.04 -0.06 ± 0.2 -0.006 0.89 25 

1990 1.39 ± 0.32 -0.01 ± 0.08 0.43 27 0.67 ± 0.23 0.05 ± 0.05 0.01 ± 0.13 -0.005 0.29 22 

1991 1.61 ± 0.15 -0.04 ± 0.04 0.76 41 1.50 ± 0.27 -0.04 ± 0.05 -0.042 ± 0.19 -0.005 0.54 29 

1992 0.96 ± 0.12 0.05 ± 0.04 0.72 28 0.96 ± 0.13 0.07 ± 0.04 -0.06 ± 0.15 -0.004 0.73 23 

Summer 

87-92 

1.09 ± 0.11 0.07 ± 0.03 0.53 89 0.93 ± 0.09 0.07 ± 0.03 -0.05 ± 0.15 -0.02 0.60 72 

Winter 

87-92 

1.34 ± 0.05 -0.03 ± 0.02 0.89 85 1.35 ± 0.09 -0.04 ± 0.02 -0.024 ± 0.175 0.001 0.79 61 

All years 

87-92 

0.50 ± 0.05 0.16 ± 0.03 0.39 183 0.36 ± 0.04 0.15 ± 0.02 -0.005 ± 0.4 -0.01 0.35 140 

BL versus SR Calcium concentration (mg/L) 

Year Slope Offset R2 N Slope Offset SR–BLT SR-BL50 R2 N 

1992 0.99 ± 0.01 0.005 ± 0.005 1.00 3 0.99 ± 0.01 0.005 ± 0.005 -0.003 ± 0.005 - 1.00 3 

1993 0.74 ± 0.15 0.04 ± 0.03 0.46 31 0.62 ± 0.20 0.06 ± 0.04 0 ± 0.13 -0.006 0.28 27 

1994 0.87 ± 0.19 0.04 ± 0.03 0.45 27 0.70 ± 0.12 0.05 ± 0.02 -0.008 ± 0.08 -0.025 0.61 24 

1995 0.92 ± 0.07 0.002 ± 0.01 0.84 35 0.90 ± 0.08 0.004 ± 0.01 0.007 ± 0.053 0.003 0.83 32 

1996 1.04 ± 0.11 -0.03 ± 0.04 0.77 28 0.53 ± 0.08 0.05 ± 0.02 0.03 ± 0.09 0.007 0.67 24 

1997 1.57 ± 0.11 -0.04 ± 0.02 0.86 38 1.06 ± 0.09 0.000 ± 0.01 -0.006 ± 0.04 -0.006 0.82 32 

Summer 

92-97 

1.19 ± 0.08 -0.01 ± 0.02 0.75 75 0.99 ± 0.07 0.02 ± 0.01 -0.02 ± 0.06 -0.012 0.75 63 

Winter 

92-97 

0.59 ± 0.06 0.02 ± 0.01 0.60 79 0.59 ± 0.06 0.03 ± 0.01 0.02 ± 0.09 0.004 0.59 73 

All Years 

92-97 

0.99 ± 0.05 0.005 ± 0.01 0.69 162 0.75 ± 0.05 0.03 ± 0.01 0.003 ± 0.08 -0.002 0.63 142 

NF versus SR Calcium deposition (kg/Ha) 

 Valid dataset Reduced dataset 

Year Slope Offset R2 N Slope Offset SR–NFT SR-NF50 R2 N 

1987 0.13 ± 0.04 0.015 ± 0.003 0.30 31 0.12 ± 0.04 0.017 ± 0.004 0.02 ± 0.08 0.004 0.29 24 

1988 0.37 ± 0.11 0.013 ± 0.008 0.36 22 0.41 ± 0.12 0.007 ± 0.01 0.03 ± 0.04 0.02 0.43 17 

1989 0.33 ± 0.05 0.008 ± 0.005 0.57 34 0.34 ± 0.06 0.011 ± 0.005 0.03 ± 0.06 0.013 0.62 25 

1990 0.54 ± 0.07 0.000 ± 0.006 0.68 27 0.55 ± 0.08 -0.002 ± 0.008 0.03 ± 0.04 0.016 0.69 22 

1991 0.37 ± 0.08 0.008 ± 0.006 0.33 41 0.38 ± 0.10 0.008 ± 0.008 0.02 ± 0.05 0.01 0.35 29 

1992 0.26 ± 0.09 0.013 ± 0.004 0.23 28 0.23 ± 0.10 0.015 ± 0.005 0.01 ± 0.03 0.01 0.20 23 

Summer 

87-92 

0.59 ± 0.04 0.008 ± 0.003 0.67 89 0.61 ± 0.05 0.007 ± 0.003 0.008 ± 0.03 0.004 0.71 72 

Winter 

87-92 

0.30 ± 0.04 0.005 ± 0.003 0.42 85 0.32 ± 0.04 0.004 ± 0.004 0.04 ± 0.05 0.02 0.45 61 

All years 

87-92 

0.31 ± 0.03 0.011 ± 0.002 0.40 183 0.32 ± 0.03 0.011 ± 0.003 0.03 ± 0.05 0.01 0.42 140 

BL versus SR Calcium deposition (kg/Ha) 

Year Slope Offset R2 N Slope Offset SR–BLT SR-BL50 R2 N 

1992 1.05 ± 0.01 0.001 ± 0.000 1.00 3 1.05 ± 0.01 0.001 ± 0.000 -0.002 ± 0.001 - 1.00 3 

1993 0.82 ± 0.18 0.006 ± 0.008 0.41 31 0.79 ± 0.14 0.003 ± 0.006 0.004 ± 0.02 0 0.57 27 

1994 0.37 ± 0.10 0.01 ± 0.003 0.37 27 0.34 ± 0.10 0.011 ± 0.004 0.004 ± 0.02 -0.002 0.33 24 

1995 0.96 ± 0.06 -0.002 ± 0.003 0.88 35 0.98 ± 0.07 -0.003 ± 0.003 0.004 ± 0.013 0.005 0.88 32 

1996 0.66 ± 0.05 0.005 ± 0.003 0.86 28 0.65 ± 0.06 0.006 ± 0.004 0.01 ± 0.022 0.005 0.85 24 

1997 0.73 ± 0.05 0.003 ± 0.002 0.88 38 0.74 ± 0.05 0.001 ± 0.002 0.006 ± 0.013 0.003 0.88 32 

Summer 

92-97 

0.83 ± 0.06 0.006 ± 0.003 0.73 75 0.81 ± 0.05 0.006 ± 0.002 -0.001 ± 0.01 -0.001 0.84 63 

Winter 

92-97 

0.63 ± 0.05 0.003 ± 0.002 0.67 79 0.64 ± 0.05 0.002 ± 0.003 0.01 ± 0.02 0.006 0.67 73 

All years 

92-97 

0.74 ± 0.04 0.004 ± 0.002 0.69 162 0.74 ± 0.04 0.003 ± 0.002 0.005 ± 0.02 0.002 0.75 142 

Appendix B. (Cont’d.)
USDA Forest Service General Technical Report RMRS-GTR-52. 2000 27

NF versus SR Magnesium concentration (mg/L) 

 Complete valid weekly dataset Precip-filtered weekly dataset 

Year Slope Offset R2 N Slope Offset SR–NFT SR-NF50 R2 N 

1987 0.28 ± 0.04 0.02 ± 0.004 0.62 31 0.24 ± 0.05 0.02 ± 0.004 0.008 ± 0.065 -0.001 0.54 24 

1988 1.10 ± 0.17 0.0004 ± 0.007 0.69 22 0.91 ± 0.15 0.002 ± 0.006 0.001 ± 0.015 0.002 0.71 17 

1989 1.33 ± 0.09 -0.006 ± 0.006 0.87 34 1.09 ± 0.11 -0.001 ± 0.005 -0.002 ± 0.016 0.0003 0.82 25 

1990 1.57 ± 0.31 -0.009 ± 0.01 0.51 27 0.67 ± 0.24 0.005 ± 0.007 0.004 ± 0.016 0.001 0.28 22 

1991 1.47 ± 0.14 -0.004 ± 0.005 0.73 41 1.04 ± 0.21 0.003 ± 0.005 -0.004 ± 0.016 -0.0009 0.48 29 

1992 0.91 ± 0.11 0.005 ± 0.005 0.73 28 0.88 ± 0.12 0.008 ± 0.005 -0.005 ± 0.017 -0.003 0.72 23 

Summer 

87-92 

1.19 ± 0.11 0.004 ± 0.005 0.57 89 0.89 ± 0.07 0.008 ± 0.003 -0.004 ± 0.016 -0.0018 0.67 72 

Winter 

87-92 

1.29 ± 0.06 -0.006 ± 0.003 0.85 85 1.00 ± 0.10 -0.001 ± 0.003 0.000 ± 0.018 0.0018 0.61 61 

All years 

87-92 

0.71 ± 0.05 0.014 ± 0.003 0.49 183 0.46 ± 0.05 0.016 ± 0.002 0.000 ± 0.03 -0.0004 0.42 140 

BL versus SR Magnesium concentration (mg/L) 

Year Slope Offset R2 N Slope Offset SR–BLT SR-BL50 R2 N 

1992 1.31 ± 0.04 -0.002 ± 0.002 1.00 3 1.31 ± 0.04 -0.002 ± 0.002 -0.005 ± 0.009 - 1.00 3 

1993 1.10 ± 0.11 -0.003 ± 0.003 0.77 31 1.04 ± 0.16 -0.001 ± 0.004 0.0006 ± 0.010 0.0006 0.63 27 

1994 1.13 ± 0.24 0.002 ± 0.005 0.48 27 0.94 ± 0.11 0.003 ± 0.002 -0.002 ± 0.007 -0.002 0.75 24 

1995 0.80 ± 0.08 0.002 ± 0.002 0.74 35 0.75 ± 0.08 0.002 ± 0.002 0.002 ± 0.007 0.0008 0.73 32 

1996 1.30 ± 0.06 -0.01 ± 0.003 0.94 28 0.71 ± 0.08 0.003 ± 0.002 0.003 ± 0.008 0.0016 0.78 24 

1997 1.64 ± 0.09 -0.007 ± 0.002 0.89 38 1.00 ± 0.08 0.0007 ± 0.001 -0.001 ± 0.004 -0.0007 0.82 32 

Summer 

92-97 

1.31 ± 0.06 -0.004 ± 0.002 0.87 75 0.97 ± 0.07 0.003 ± 0.002 -0.003 ± 0.007 -0.0013 0.77 63 

Winter 

92-97 

0.73 ± 0.06 0.0008 ± 0.001 0.69 79 0.73 ± 0.06 0.001 ± 0.001 0.002 ± 0.007 0.0012 0.70 73 

All years 

92-97 

1.21 ± 0.04 -0.003 ± 0.001 0.84 162 0.88 ± 0.05 0.0015 ± 0.001 0.0004 ± 0.007 0.0001 0.73 142 

NF versus SR Magnesium deposition (kg/Ha) 

 Valid dataset Reduced dataset 

Year Slope Offset R2 N Slope Offset SR–NFT SR-NF50 R2 N 

1987 0.15 ± 0.07 0.002 ± 0.0006 0.13 31 0.13 ± 0.08 0.003 ± 0.0007 0.002 ± 0.007 0.0008 0.11 24 

1988 0.23 ± 0.10 0.002 ± 0.0009 0.21 22 0.26 ± 0.11 0.002 ± 0.001 0.004 ± 0.006 0.003 0.26 17 

1989 0.26 ± 0.04 0.001 ± 0.0006 0.51 34 0.26 ± 0.05 0.002 ± 0.0007 0.006 ± 0.009 0.003 0.56 25 

1990 0.40 ± 0.08 0.0006 ± 0.001 0.52 27 0.41 ± 0.09 0.0003 ± 0.001 0.005 ± 0.007 0.003 0.51 22 

1991 0.23 ± 0.08 0.002 ± 0.0006 0.19 41 0.24 ± 0.08 0.002 ± 0.0008 0.003 ± 0.006 0.001 0.23 29 

1992 0.27 ± 0.10 0.001 ± 0.0005 0.24 28 0.26 ± 0.10 0.002 ± 0.0006 0.002 ± 0.003 0.001 0.26 23 

Summer 

87-92 

0.53 ± 0.05 0.001 ± 0.0003 0.60 89 0.54 ± 0.05 0.001 ± 0.0004 0.001 ± 0.003 0.0006 0.65 72 

Winter 

87-92 

0.22 ± 0.03 0.001 ± 0.0004 0.33 85 0.23 ± 0.04 0.001 ± 0.0005 0.006 ± 0.008 0.004 0.37 61 

All years 

87-92 

0.26 ± 0.03 0.01 ± 0.0003 0.34 183 0.27 ± 0.03 0.002 ± 0.0003 0.004 ± 0.007 0.002 0.37 140 

BL versus SR Magnesium deposition (kg/Ha) 

Year Slope Offset R2 N Slope Offset SR–BLT SR-BL50 R2 N 

1992 1.43 ± 0.02 -0.0003 ± 0.00 1.00 3 1.43 ± 0.02 -0.0003 ± 0.00 0.0001 ± 0.002 - 1.00 3 

1993 0.65 ± 0.19 0.001 ± 0.001 0.30 31 0.73 ± 0.12 0.0004 ± 0.001 0.0009 ± 0.002 0.0004 0.59 27 

1994 0.60 ± 0.11 0.001 ± 0.0003 0.55 27 0.58 ± 0.12 0.001 ± 0.0004 0.0003 ± 0.002 0.000 0.51 24 

1995 0.81 ± 0.08 0.000 ± 0.001 0.74 35 0.83 ± 0.09 0.000 ± 0.0005 0.0008 ± 0.002 0.000 0.73 32 

1996 0.57 ± 0.05 0.001 ± 0.0004 0.82 28 0.56 ± 0.06 0.001 ± 0.0005 0.002 ± 0.003 0.0006 0.81 24 

1997 0.74 ± 0.04 0.000 ± 0.000 0.89 38 0.77 ± 0.05 0.000 ± 0.000 0.0007 ± 0.001 0.0008 0.91 32 

Summer 

92-97 

0.75 ± 0.07 0.001 ± 0.0004 0.62 75 0.72 ± 0.05 0.001 ± 0.0003 0.000 ± 0.001 0.000 0.79 63 

Winter 

92-97 

0.57 ± 0.04 0.000 ± 0.000 0.71 79 0.58 ± 0.04 0.000 ± 0.000 0.001 ± 0.002 0.001 0.71 73 

All years 

92-97 

0.66 ± 0.04 0.001 ± 0.0002 0.63 162 0.67 ± 0.03 0.001 ± 0.0002 0.0008 ± 0.002 0.0004 0.73 142 

Appendix B. (Cont’d.)
28 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-52. 2000

NF versus SR Ammonium concentration (mg/L) 

 Complete valid weekly dataset Precip-filtered weekly dataset 

Year Slope Offset R2 N Slope Offset SR–NFT SR-NF50 R2 N 

1987 1.10 ± 0.16 0.004 ± 0.02 0.62 31 1.19 ± 0.25 -0.004 ± 0.03 -0.018 ± 0.083 -0.01 0.50 24 

1988 0.52 ± 0.19 0.06 ± 0.03 0.28 22 0.36 ± 0.09 0.04 ± 0.01 0.008 ± 0.082 -0.003 0.50 17 

1989 0.68 ± 0.25 0.05 ± 0.05 0.19 34 0.80 ± 0.23 0.03 ± 0.04 -0.008 ± 0.124 -0.002 0.35 25 

1990 0.88 ± 0.26 0.08 ± 0.06 0.31 27 0.38 ± 0.20 0.09 ± 0.04 -0.001 ± 0.13 -0.022 0.16 22 

1991 0.46 ± 0.14 0.08 ± 0.02 0.22 41 0.57 ± 0.16 0.06 ± 0.02 -0.019 ± 0.102 -0.023 0.31 29 

1992 0.58 ± 0.11 0.09 ± 0.03 0.52 28 0.58 ± 0.12 0.09 ± 0.03 0.000 ± 0.13 0.000 0.54 23 

Summer 

87-92 

0.90 ± 0.10 0.06 ± 0.02 0.48 89 0.73 ± 0.08 0.07 ± 0.02 0.004 ± 0.12 -0.026 0.54 72 

Winter 

87-92 

0.18 ± 0.10 0.09 ± 0.02 0.04 85 0.22 ± 0.10 0.07 ± 0.01 -0.023 ± 0.11 -0.004 0.07 61 

All years 

87-92 

0.70 ± 0.07 0.06 ± 0.01 0.34 183 0.64 ± 0.07 0.06 ± 0.01 -0.008 ± 0.108 -0.012 0.45 140 

BL versus SR Ammonium concentration (mg/L) 

Year Slope Offset R2 N Slope Offset SR–BLT SR-BL50 R2 N 

1992 -0.68 ± 3.5 0.12 ± 0.19 0.04 3 -0.68 ± 3.5 0.12 ± 0.19 -0.037 ± 0.097 - 0.04 3 

1993 0.76 ± 0.17 0.02 ± 0.03 0.41 31 0.73 ± 0.18 0.02 ± 0.03 0.018 ± 0.091 -0.003 0.40 27 

1994 0.55 ± 0.19 0.07 ± 0.04 0.25 27 0.54 ± 0.14 0.06 ± 0.03 0.005 ± 0.094 -0.008 0.41 24 

1995 0.65 ± 0.09 0.03 ± 0.01 0.62 35 0.62 ± 0.10 0.03 ± 0.01 0.018 ± 0.051 0.011 0.58 32 

1996 0.57 ± 0.10 0.02 ± 0.02 0.55 28 0.62 ± 0.11 0.02 ± 0.02 0.046 ± 0.072 0.048 0.61 24 

1997 1.29 ± 0.13 -0.03 ± 0.02 0.73 38 0.76 ± 0.12 0.02 ± 0.02 0.007 ± 0.054 -0.002 0.59 32 

Summer 

92-97 

0.85 ± 0.11 0.03 ± 0.02 0.47 75 0.78 ± 0.08 0.03 ± 0.02 0.000 ± 0.07 -0.005 0.59 63 

Winter 

92-97 

0.33 ± 0.06 0.05 ± 0.008 0.30 79 0.33 ± 0.06 0.05 ± 0.008 0.03 ± 0.07 0.021 0.31 73 

All years 

92-97 

0.72 ± 0.06 0.03 ± 0.01 0.45 162 0.63 ± 0.06 0.03 ± 0.009 0.017 ± 0.074 0.008 0.47 142 

NF versus SR Ammonium deposition (kg/Ha) 

 Valid dataset Reduced dataset 

Year Slope Offset R2 N Slope Offset SR–NFT SR-NF50 R2 N 

1987 0.65 ± 0.11 0.001 ± 0.003 0.53 31 0.65 ± 0.14 0.001 ± 0.005 0.008 ± 0.018 0.005 0.49 24 

1988 0.12 ± 0.08 0.008 ± 0.003 0.09 22 0.14 ± 0.05 0.006 ± 0.002 0.012 ± 0.033 0.003 0.33 17 

1989 0.12 ± 0.06 0.011 ± 0.005 0.10 34 0.11 ± 0.07 0.015 ± 0.007 0.032 ± 0.073 0.011 0.09 25 

1990 0.10 ± 0.07 0.018 ± 0.005 0.08 27 0.10 ± 0.07 0.018 ± 0.006 0.026 ± 0.060 0.006 0.09 22 

1991 0.24 ± 0.11 0.010 ± 0.005 0.11 41 0.27 ± 0.13 0.010 ± 0.006 0.015 ± 0.037 0.007 0.15 29 

1992 0.43 ± 0.10 0.007 ± 0.005 0.43 28 0.41 ± 0.10 0.007 ± 0.006 0.018 ± 0.030 0.011 0.44 23 

Summer 

87-92 

0.53 ± 0.07 0.009 ± 0.003 0.44 89 0.54 ± 0.07 0.008 ± 0.003 0.008 ± 0.026 0.004 0.47 72 

Winter 

87-92 

0.07 ± 0.02 0.007 ± 0.002 0.10 85 0.07 ± 0.02 0.009 ± 0.002 0.017 ± 0.029 0.011 0.12 61 

All years 

87-92 

0.19 ± 0.03 0.011 ± 0.002 0.15 183 0.19 ± 0.04 0.012 ± 0.002 0.019 ± 0.046 0.007 0.16 140 

BL versus SR Ammonium deposition (kg/Ha) 

Year Slope Offset R2 N Slope Offset SR–BLT SR-BL50 R2 N 

1992 -1.25 ± 1.7 0.013 ± 0.010 0.37 3 -1.25 ± 1.7 0.013 ± 0.010 -0.003 ± 0.009 - 0.37 3 

1993 0.31 ± 0.11 0.014 ± 0.005 0.20 31 0.32 ± 0.11 0.012 ± 0.005 0.010 ± 0.028 0.003 0.24 27 

1994 0.25 ± 0.04 0.011 ± 0.002 0.62 27 0.24 ± 0.04 0.012 ± 0.002 0.008 ± 0.031 0.000 0.61 24 

1995 0.66 ± 0.10 0.007 ± 0.005 0.55 35 0.69 ±0.11 0.005 ± 0.005 0.007 ± 0.019 0.005 0.57 32 

1996 0.59 ± 0.08 0.002 ± 0.004 0.69 28 0.57 ± 0.09 0.004 ± 0.005 0.015 ± 0.021 0.012 0.65 24 

1997 0.44 ± 0.06 0.008 ± 0.003 0.59 38 0.45 ± 0.07 0.008 ± 0.004 0.013 ± 0.024 0.006 0.61 32 

Summer 

92-97 

0.76 ± 0.06 0.005 ± 0.002 0.70 75 0.75 ± 0.06 0.005 ± 0.003 0.001 ± 0.011 0.000 0.71 63 

Winter 

92-97 

0.33 ± 0.04 0.010 ± 0.002 0.44 79 0.34 ± 0.04 0.008 ± 0.002 0.031 ± 0.062 0.011 0.48 73 

All years 

92-97 

0.45 ± 0.04 0.010 ± 0.002 0.48 162 0.45 ± 0.04 0.009 ± 0.002 0.01± 0.024 0.004 0.49 142 

Appendix B. (Cont’d.)
USDA Forest Service General Technical Report RMRS-GTR-52. 2000 29

Sulfate concentration (mg/L) and deposition (kg/Ha) reported by NADP 

Concentration weekly averages Deposition annual totals Deposition weekly 

averages 

Year SR NF SR NF SR NF 

1987 0.60 0.68 5.24 3.73 0.10 0.07 

1988 0.72 0.77 8.65 4.28 0.17 0.08 

1989 0.77 0.80 9.72 4.00 0.19 0.08 

1990 0.49 0.56 6.39 3.35 0.12 0.06 

1991 0.51 0.58 6.40 3.40 0.12 0.07 

1992 0.63 0.72 6.79 2.62 0.13 0.07 

average 0.62 0.69 7.20 3.56 0.14 0.07 

Year SR BL SR BL SR BL 

1992 0.63 0.40 6.79 1.20 0.13 0.09 

1993 0.59 0.53 8.41 6.77 0.16 0.13 

1994 0.55 0.47 4.58 3.50 0.09 0.07 

1995 0.46 0.41 6.53 5.82 0.13 0.11 

1996 0.52 0.35 6.83 4.91 0.13 0.09 

1997 0.53 0.43 6.34 5.16 0.12 0.10 

average 0.55 0.43 6.58 4.56 0.13 0.10 

Nitrate concentration (mg/L) and deposition (kg/Ha) reported by NADP 

Concentration weekly averages Deposition annual totals Deposition weekly 

averages 

Year SR NF SR NF SR NF 

1987 0.63 0.79 5.48 4.28 0.11 0.12 

1988 0.51 0.59 6.08 3.25 0.12 0.06 

1989 0.77 0.89 9.73 4.48 0.19 0.09 

1990 0.76 0.82 9.95 4.90 0.19 0.09 

1991 0.67 0.79 8.38 4.57 0.16 0.09 

1992 0.87 0.91 9.43 3.30 0.18 0.06 

average 0.70 0.80 8.18 4.13 0.16 0.08 

Year SR NF SR NF SR NF

1992 0.87 0.67 9.43 2.04 0.18 0.15 

1993 0.59 0.63 8.44 8.02 0.16 0.15 

1994 0.71 0.68 5.94 5.06 0.11 0.10 

1995 0.63 0.56 8.95 8.05 0.17 0.15 

1996 0.80 0.54 10.65 7.67 0.20 0.15 

1997 0.76 0.67 9.20 8.06 0.18 0.16 

average 0.73 0.63 8.77 6.48 0.17 0.12 

Appendix C. NADP weekly concentration

and weekly deposition and total annual

deposition for , , Cl-

, Na+, K+, Ca2+,

Mg2+, and

SO2-

4 NO3

NH+

4
30 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-52. 2000

Chlorine concentration (mg/L) and deposition (kg/Ha) reported by NADP 

Concentration weekly averages Deposition annual totals Deposition weekly 

averages 

Year SR NF SR NF SR NF 

1987 0.13 0.08 1.17 0.41 0.023 0.011 

1988 0.11 0.10 1.33 0.55 0.026 0.011 

1989 0.16 0.11 1.98 0.57 0.038 0.011 

1990 0.13 0.11 1.73 0.67 0.033 0.013 

1991 0.10 0.08 1.31 0.48 0.025 0.009 

1992 0.12 0.09 1.28 0.31 0.025 0.006 

average 0.13 0.10 1.47 0.50 0.028 0.010 

Year SR NF SR NF SR NF

1992 0.12 0.06 1.28 0.19 0.025 0.014 

1993 0.10 0.07 1.39 0.93 0.027 0.018 

1994 0.07 0.06 0.60 0.42 0.012 0.008 

1995 0.06 0.06 0.93 0.89 0.018 0.017 

1996 0.11 0.07 1.46 1.03 0.028 0.020 

1997 0.07 0.06 0.85 0.76 0.016 0.015 

average 0.09 0.06 1.09 0.70 0.021 0.013 

Sodium concentration (mg/L) and deposition (kg/Ha) reported by NADP 

Concentration weekly averages Deposition annual totals Deposition weekly 

averages 

Year SR NF SR NF SR NF 

1987 0.15 0.07 1.30 0.39 0.025 0.011 

1988 0.12 0.12 1.39 0.64 0.027 0.012 

1989 0.21 0.11 2.61 0.57 0.050 0.011 

1990 0.09 0.06 1.16 0.36 0.022 0.007 

1991 0.09 0.06 1.11 0.34 0.021 0.007 

1992 0.10 0.07 1.08 0.24 0.021 0.005 

average 0.12 0.08 1.44 0.42 0.028 0.008 

Year SR NF SR NF SR NF

1992 0.10 0.06 1.08 0.18 0.021 0.013 

1993 0.08 0.07 1.07 0.95 0.021 0.018 

1994 0.05 0.04 0.43 0.30 0.008 0.006 

1995 0.06 0.05 0.87 0.75 0.017 0.014 

1996 0.10 0.06 1.30 0.83 0.025 0.016 

1997 0.06 0.05 0.68 0.62 0.013 0.012 

average 0.07 0.06 0.90 0.60 0.017 0.012 

Potassium concentration (mg/L) and deposition (kg/Ha) reported by NADP 

Concentration weekly averages Deposition annual totals Deposition weekly 

averages 

Year SR NF SR NF SR NF 

1987 0.02 0.02 0.17 0.10 0.003 0.003 

1988 0.02 0.01 0.22 0.08 0.004 0.002 

1989 0.01 0.02 0.17 0.08 0.003 0.002 

1990 0.01 0.03 0.18 0.16 0.003 0.003 

1991 0.01 0.02 0.18 0.09 0.003 0.002 

1992 0.02 0.02 0.21 0.07 0.004 0.001 

average 0.02 0.02 0.18 0.10 0.003 0.002 

Year SR NF SR NF SR NF

1992 0.02 0.01 0.21 0.04 0.004 0.003 

1993 0.01 0.01 0.14 0.14 0.003 0.003 

1994 0.01 0.02 0.12 0.11 0.002 0.002 

1995 0.01 0.01 0.14 0.19 0.003 0.004 

1996 0.02 0.01 0.31 0.20 0.006 0.004 

1997 0.01 0.01 0.17 0.14 0.003 0.003 

average 0.02 0.01 0.18 0.14 0.003 0.003 

Appendix C. (Cont’d.)
USDA Forest Service General Technical Report RMRS-GTR-52. 2000 31

Calcium concentration (mg/L) and deposition (kg/Ha) reported by NADP 

Concentration weekly averages Deposition annual totals Deposition weekly 

averages 

Year SR NF SR NF SR NF 

1987 0.20 0.17 1.74 0.93 0.03 0.03 

1988 0.19 0.20 2.23 1.11 0.04 0.02 

1989 0.19 0.26 2.46 1.28 0.05 0.02 

1990 0.19 0.18 2.44 1.07 0.05 0.02 

1991 0.14 0.18 1.75 1.06 0.03 0.02 

1992 0.17 0.18 1.81 0.64 0.03 0.01 

average 0.18 0.20 2.07 1.02 0.04 0.02 

Year SR NF SR NF SR NF

1992 0.17 0.09 1.81 0.27 0.03 0.02 

1993 0.11 0.13 1.61 1.68 0.03 0.03 

1994 0.12 0.11 0.98 0.81 0.02 0.02 

1995 0.11 0.10 1.52 1.48 0.03 0.03 

1996 0.19 0.11 2.47 1.61 0.05 0.03 

1997 0.11 0.11 1.35 1.27 0.03 0.02 

average 0.14 0.11 1.62 1.19 0.03 0.02 

Magnesium concentration (mg/L) and deposition (kg/Ha) reported by NADP 

Concentration weekly averages Deposition annual totals Deposition weekly 

averages 

Year SR NF SR NF SR NF 

1987 0.03 0.02 0.25 0.13 0.005 0.004 

1988 0.03 0.03 0.30 0.14 0.006 0.003 

1989 0.03 0.03 0.36 0.17 0.007 0.003 

1990 0.03 0.02 0.35 0.14 0.007 0.003 

1991 0.02 0.02 0.23 0.13 0.004 0.003 

1992 0.02 0.02 0.24 0.08 0.005 0.002 

average 0.02 0.02 0.29 0.13 0.006 0.003 

Year SR NF SR NF SR NF

1992 0.02 0.01 0.24 0.03 0.005 0.002 

1993 0.02 0.02 0.23 0.22 0.004 0.004 

1994 0.01 0.01 0.11 0.09 0.002 0.002 

1995 0.01 0.01 0.19 0.19 0.004 0.004 

1996 0.02 0.01 0.32 0.20 0.006 0.004 

1997 0.01 0.01 0.16 0.15 0.003 0.003 

average 0.02 0.01 0.21 0.15 0.004 0.003 

Ammonium concentration (mg/L) and deposition (kg/Ha) reported by NADP 

Concentration weekly averages Deposition annual totals Deposition weekly 

averages 

Year SR NF SR NF SR NF 

1987 0.09 0.12 0.78 0.65 0.015 0.018 

1988 0.05 0.06 0.57 0.36 0.011 0.007 

1989 0.15 0.14 1.93 0.73 0.037 0.014 

1990 0.12 0.15 1.56 0.90 0.030 0.017 

1991 0.09 0.13 1.14 0.74 0.022 0.014 

1992 0.16 0.20 1.69 0.71 0.033 0.014 

average 0.11 0.13 1.28 0.68 0.025 0.013 

Year SR NF SR NF SR NF

1992 0.16 0.04 1.69 0.13 0.033 0.009 

1993 0.10 0.09 1.48 1.18 0.028 0.023 

1994 0.14 0.10 1.14 0.77 0.022 0.015 

1995 0.11 0.10 1.59 1.42 0.031 0.027 

1996 0.15 0.08 2.04 1.10 0.039 0.021 

Appendix C. (Cont’d.)
32 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-52. 2000

Deposition (kg/Ha): comparison of annual totals as reported by NADP 

 NF versus SR 1987 – 1992* BL versus SR 1993 - 1997 

Species Slope Offset R2 Slope Offset R2

Ca 0.30 ± 0.12 0.43 ± 0.26 0.60 0.48 ± 0.24 0.62 ± 0.40 0.56 

Mg 0.24 ± 0.09 0.07 ± 0.03 0.64 0.49 ± 0.23 0.07 ± 0.05 0.60 

K -0.09 ± 0.69 0.12 ± 0.13 0.00 0.33 ± 0.20 0.10 ± 0.04 0.49 

Na 0.12 ± 0.08 0.28 ± 0.13 0.34 0.66 ± 0.19 0.12 ± 0.18 0.79 

NH4 0.27 ± 0.11 0.35 ± 0.15 0.60 0.34 ± 0.37 0.58 ± 0.58 0.22 

NO3 0.26 ± 0.12 2.32 ± 1.04 0.53 0.62 ± 0.25 2.01 ± 2.20 0.67 

Cl 0.21 ± 0.09 0.23 ± 0.14 0.55 0.57 ± 0.17 0.21 ± 0.19 0.78 

SO4 0.15 ± 0.08 2.70 ± 0.57 0.47 0.83 ± 0.18 -0.19 ± 1.17 0.88 

* The 1992 NF deposition value is the sum of the measurements made at NF (37 weeks) and BL (14 weeks). 

Appendix D. NADP annual statistics for , , Cl-,

Na+, K+, Ca2+, Mg2+, and

SO2-

4 NO3

NH+

4
USDA Forest Service General Technical Report RMRS-GTR-52. 2000 33

As demonstrated in this report, the initial evaluation

of Snowy Range, WY, module A (IMPROVE) concentrations compare reasonably well with concentrations from

EPA’s National Dry Deposition Network (NDDN) site.

Each program however, has a different protocol, each

designed for a different purpose. Although comparisons

may be reasonable, several factors should be addressed

when using IMPROVE data to either estimate concentrations directly or calculate deposition amounts:

1. Physical site characteristics: Location and emission

frequency of upwind sources may preclude an accurate

estimate of site concentration and deposition. For example, because IMPROVE protocol allows for 24-hr

samples only on Wednesdays and Saturdays, an operation that emits pollution only on Fridays would be

missed.

2. Sample intake, orientation, and filter chemistry:

The physical dimensions and placement of the air

sample collection head and flow rate will determine

aerosol (particulate) size cutoff. The type of filter(s)

used, pore size, and pre-treatment for specific gaseous

species collection also vary and must be considered.

IMPROVE modules A, B, & C are designed to collect

aerosols equal to and less than 2.5 micrometers in

diameter only. Assuming the presence of aerosols

larger than 2.5μm, concentrations and deposition derived from IMPROVE would be biased on the low side.

The exact amount of bias would be site, season, and

species specific.

3. Support data for deposition estimates: While wet

deposition can be measured directly, dry deposition is

estimated from programs like NDDN (and potentially

IMPROVE) by multiplying measured concentrations

by modeled deposition velocities or by choosing a

“best guess” single deposition velocity value for a

specific site. For modeled deposition velocity, detailed

site meteorology, canopy characteristics, and leafarea-index (LAI) are required. To choose a single value,

canopy characteristics and LAI are needed. To select

or compute a deposition velocity, either review the

literature to justify a selection or solicit the recommendation of an expert. As an example Zeller et al. (1997a)

chose the value 0.4 cm s-1 to apply to aerosols in the Rila

mountain area of Bulgaria (pine, spruce, and fir forest)

based on matching site characteristics with available

literature at the time: Bytnerowicz et al. (1987) and the

general information on deposition velocities given by

Sehmel (1984). Calculations made for the Brdy

Mountains, Czech Republic (Zeller et al. 1996 & 1997b),

used an approach similar to Appendix A.

Based on this report, given a new average annual

Brooklyn IMPROVE SO4

 concentration of

0.7 μg m-3 and given an average aerosol deposition velocity of 0.2 cm s-1 selected for the estimate:

(1) Convert 0.7 to an equivalent NDDN value by

either using the Figure 9c regression equation

(y = 0.63 x + 0.11) where y (IMPROVE) = 0.7 and

solve for x (NDDN) = 0.94 μg m-3, or

(2) Convert 0.7 to an equivalent NDDN value by

using the 22% overall average difference cited

in the dry deposition results discussion:

0.7 + 0.22 (0.7) = 0.85 μg m-3. Manager’s choice.

(3) Use equation 3, Fc

 = ( c z – c o) Vd, to calculate

deposition (vertical flux): Fc = (0.94 – 0.0) 0.2

(μg m-3 cm s-1) = 0.002 μg m-2 s-1 = 0.6 kg ha-1 yr-1.

4. Site location and averaging periods: Based on this

study of Snowy Range, WY, NADP wet deposition data

analyses with adjacent sites, site comparisons improve

with longer averaging periods (yearly concentration

averages, and total annual deposition compare better

than seasonal and weekly) and closer sites, as one

would expect. If sites are in the same general geographical area, one might use the same approach climatologists use for applying rain gage data to areas within

25 kilometers (i.e., use annual values as spatially representative and seasonal or shorter period values only to

understand potential variability).

In general, the use of IMPROVE data for estimating

sulfate concentration and deposition is defendable. The

same anion and cation aerosols are measured by both

IMPROVE and NDDN but diameter size for IMPROVE is

limited to 2.5μm, hence results will be biased toward lower

than actual. Results will also be dependent on both the site

and the specific species of interest. Module A does not

measure nitrate so it wasn’t evaluated; however, there are

additional gas to aerosol phase changes for nitrate that

affect filter collection systems that would have to be taken

into account.

Appendix E. Recommendation: Use of IMPROVE Data to

Assess Air Pollution and Deposition
34 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-52. 2000

References

Bytnerowicz, A., Miller, P, & Olyzyk, D., 1987. Dry deposition of nitrate, ammonium and sulfate to a Ceanothus

crassifolius canopy and surrogate surfaces, Atm. Envir.

21:8 1749-1757.

ESE, Inc. No. 86612-0212-3170, 1990a. National dry deposition network: Laboratory operations manual, EPA

Contract No. 68-02-4451, EPA/AREAL, RTP, NC 27791,

August 1990.

ESE, Inc. No. 86612-0108-2110, 1990b. National dry deposition network: Field operations manual, EPA Contract

No. 68-02-4451, EPA/AREAL, RTP, NC 27791, July

1990.

Sisler, J.F., 1996. Spatial and seasonal patterns and long

term variability of the composition of the haze in the U.S.:

An analysis of data from the IMPROVE network, CIRA,

CSU, Ft. Collins, CO. July, ISSN: 0737-5352-32.

Schmel, G. 1984. Chapter 12: Deposition and resuspension,

In: D. Randerson ed., Atmospheric Science and Power

Production, DOE/TIC-27601 (DE84005177) pp 533-583.

Zeller, K., Cerny, M., Smith, L. et al. 1996. Weekly dry

deposition of and at Brdy Mountain, Czech Republic.

Proceedings of NATO-Advanced Research Workshop:

Atmospheric Deposition and Forest Management. 23-

26 April, 1996. Spindleruv Mlyn, Krkonose Mtn., Czech

Republic.

Zeller, K., Cerny, M., Bytnerowicz, A., Smith, L., Sestak,

M., Michalec, M., Pernegr, V. & Kucera, J., 1997b. Air

pollution status of a representative site in the Czech

Republic Brdy mountains. Environmental Pollution, 98

(3), 291-297.

Zeller, K., Donev, E., Bojinov, H., Nikolov, N., 1997a. Air

pollution status of the Bulgarian Govedartsi Ecosystem. Environmental Pollution, 98 (3), 281-289.

Zeller. K. 1993. BLM IWAES filter pack monitoring: what

does it really do? USDA FS RMFRES IAG K910-A1-0008

T01. project report. March.

The Rocky Mountain Research Station develops scientific information

and technology to improve management, protection, and use of forests

and rangelands. Research is designed to meet the needs of National

Forest managers, federal and state agencies, public and private

organizations, academic institutions, industry, and individuals.

Studies accelerate solutions to problems involving ecosystems,

range, forests, water, recreation, fire, resource inventory, land

reclamation, community sustainability, forest engineering technology,

multiple use economics, wildlife and fish habitat, and forest insects and

diseases. Studies are conducted cooperatively, and applications can

be found worldwide.

Research Locations

Flagstaff, Arizona

Fort Collins,

Colorado*

Boise, Idaho

Moscow, Idaho

Bozeman, Montana

Missoula, Montana

Lincoln, Nebraska

* Station Headquarters, 2150 Centre Avenue, Building A, Fort Collins, CO

80526

The U.S. Department of Agriculture (USDA) prohibits discrimination in all its

programs and activities on the basis of race, color, national origin, sex, religion,

age, disability, political beliefs, sexual orientation, or marital or family status. (Not

all prohibited bases apply to all programs.) Persons with disabilities who require

alternative means for communication of program information (Braille, large print,

audiotape, etc.) should contact USDA’s TARGET Center at (202) 720-2600

(voice and TDD).

To file a complaint of discrimination, write USDA, Director, Office of Civil

Rights, Room 326-W, Whitten Building, 1400 Independence Avenue, SW,

Washington, D.C. 20250-9410 or call (202) 720-5964 (voice and TDD).

USDA is an equal employment opportunity provider and employer.

Reno, Nevada

Albuquerque, New

Mexico

Rapid City, South Dakota

Logan, Utah

Ogden, Utah

Provo, Utah

Laramie, Wyoming

Printed on recycled paper