United States Department of Agriculture / Forest Service

Rocky Mountain Research Station

General Technical Report RMRS-GTR-230WWW

September 2009

U.S. Forest Service Region 1 

Lake Chemistry, NADP, and 

IMPROVE Air Quality Data Analysis

Jill Grenon

Mark Story
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Grenon, Jill; Story, Mark. 2009. U.S. Forest Service Region 1 Lake Chemistry, NADP, and 

IMPROVE air quality data analysis. Gen. Tech. Rep. RMRS-GTR-230WWW. Fort Collins, 

CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station. 42 p.

Abstract

This report was developed to address the need for comprehensive analysis of U.S. Forest 

Service (USFS) Region 1 air quality monitoring data. The monitoring data includes Phase 3 

(long-term data) lakes, National Atmospheric Deposition Program (NADP), and Interagency 

Monitoring of Protected Visual Environments (IMPROVE). Annual and seasonal data for the 

periods of record were evaluated for trends using non-parametric (SAS) protocols. The most 

significant trends were the consistent decrease in SO4

2– and increase in NH4+ at the NADP 

sites. Standard visual Range increased and extinction decreased at all the IMPROVE sites. 

Annual visibility was reduced during years of heavy wildland fire. In conclusion, considerations 

were listed regarding current and future monitoring and National Forest air quality protection 

including lake sampling protocols, and NADP and IMPROVE site continuation. 

Keywords: Northern Rocky Mountain air quality, NADP, IMPROVE, lake chemistry, SAS, 

air quality trends

Authors

Jill Grenon—Air Quality Specialist, USFS Region 1, Gallatin National Forest 

and USFS Region 4, Bridger Teton National Forest. 

Mark Story—Hydrologist, USFS Region 1, Gallatin National Forest.
Contents

Current Monitoring............................................................................1

Criteria Pollutants .............................................................................1

USFS R1 Air Pollution Sources ........................................................3

Analysis Methods .............................................................................7

Lake Chemistry and Trends..............................................................8

NADP Data and Trends ..................................................................13

IMPROVE Visibility Analysis and Trends........................................26

Overall Conclusions........................................................................39

Considerations................................................................................40

Acknowledgments ..........................................................................41

References .....................................................................................41

USDA Forest Service Gen. Tech. Rep. RMRS-GTR-230WWW. 2009 1

U.S. Forest Service Region 1 Lake Chemistry, 

NADP, and IMPROVE Air Quality Data Analysis

Jill Grenon and Mark Story

Current Monitoring ______________

The U.S. Forest Service (USFS) Region 1 Air Quality 

program has been actively monitoring air quality related 

values (AQRVs) and wilderness air quality values 

(WAQVs) since 1989. Formal AQRV monitoring plans 

for regional Class I Wilderness areas were developed 

between 1989 and 1996. For Class II Wilderness areas, 

formal WAQV plans were developed in 2007 and 2008 

in accordance with the Ten Year Wilderness Challenge. 

Towns and wilderness areas within USFS Region 1 are 

shown in figure 1. Table 1 summarizes the history of 

AQRV and WAQV planning for the region’s wilderness.

Class 1 plans are available in hard copy from Mark 

Story, Gallatin NF, Bozeman, Montana. Class II WAQV 

plans are posted on the USFS Air Quality website, (http://

www.fs.fed.us/r1/gallatin/resources/air/aq_plans/). The 

website also includes the USFS Region 1 AQRV/WAQV 

Monitoring Plan (Story and others 2008).

Criteria Pollutants _______________

The Clean Air Act designated that criteria pollutants 

are sulfur dioxide (SO2), nitrogen oxides (NOx), ozone 

(O3), carbon monoxide (CO), lead (Pb), and particulate 

matter (PM10 and PM2.5).

These pollutants are known to adversely affect plant 

life, water quality, aquatic species, health of humans 

and wildlife, and visibility. Sources of sulfur dioxide 

and lead are generally associated with urbanization 

and industrialization rather than with natural resource 

management activities or wildland fires. Wildland fires 

and natural resource management activities (such as timber 

harvest, road construction, site preparation, and mining) 

generate NOx, CO, O3, PM10, and PM2.5. A series of large 

wildland fires can generate NOx emissions comparable to 

the total annual statewide contributions by industry and 

vehicles. Ozone can be a by-product of fire, although high 

O3 exposures are infrequent (Sandberg and Dost 1990). 

Figure 1—Towns and wilderness areas within USFS Region 1.
2 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-230WWW. 2009

The EPA is recommending a secondary O3 standard 

that will protect vegetation and animals (http://www.

epa.gov/ttn/naaqs/standards/ozone/s_o3_cr_sp.html). 

Carbon monoxide is rapidly diluted at short distances 

from a burning area, as fires are generally spatially and 

temporally dispersed, and pose little or no risk to public 

health (Sandberg and Dost 1990).

The pollutant of most concern to public health and 

visibility impairment is particulate matter. The National 

Ambient Air Quality Standard (NAAQS) (http://www.

epa.gov/ttn/naaqs/) for PM2.5 is 35 μg/m3

 (micrograms 

Table 1—Information for Class I and II wilderness areas in USFS Region 1 and their corresponding air quality 

plans.

Wilderness area Class

Year of 

wilderness 

designation 

Size 

acres AQRV or WAQV plan Plan date 

Bob Marshall (BMW) 1 9/3/1964 1,009,356 Bob Marshall Wilderness Air 

Quality Related Values Management Plan 

6/5/1989

Cabinet Mountains 

(CMW)

1 9/3/1964 94,272 Air Quality Related Values Management Plan for the Cabinet 

Mountains Wilderness Area 

Montana

6/1/1993

Gates of the 

Mountains (GMW)

1 9/3/1964 28,562 Air Quality Related Values Management Plan for the Gates of 

the Mountains Wilderness Area 

12/31/1994

Selway-Bitterroot 

(SBW)

1 9/3/1964 1,340,502 Air Quality Related Values Management Plan for the SelwayBitterroot Wilderness Area 

Idaho-Montana

7/29/1994

Anaconda-Pintler 

(APW)

1 9/3/1964 158,615 Air Quality Related Values Management Plan for the AnacondaPintler Wilderness3/1/1995

Scapegoat (SGW) 1 9/3/1964 239,936 Air Quality Related Values 

Management Plan for Scapegoat 

Wilderness

12/1995

Mission Mountains 

(MMW)

1 9/3/1964 73,877 Air Quality Related Values Management Plan for the Mission 

Mountains Wilderness Area

6/1/1996

Absaroka- Beartooth 

(ABW)

2 3/27/1978 943,626 Wilderness Air Quality Value 

WAQV Class II Monitoring Plan

Absaroka Beartooth Wilderness

Lee Metcalf Wilderness

1/9/2008

Lee Metcalf (LMW) 2 10/21/1983 254,288

Rattlesnake (RW) 2 10/19/1980 32,976 Wilderness Air Quality Value 

WAQV Class II Monitoring Plan

Rattlesnake and Welcome Creek 

Wilderness Areas

12/20/2007

Welcome Creek 

(WCW)

2 2 /24/1978 28,135

Great Bear (GBW) 2 10//28/1978 286,700 Wilderness Air Quality Value 

WAQV Class II Monitoring Plan

Great Bear Wilderness

4/3/2007

Gospel Hump (GHW) 2 2 /24/1978. 206,053 Wilderness Air Quality Value 

WAQV Class II Monitoring Plan

Gospel Hump Wilderness Area

1/9/2008

per cubic meter) averaged over 24 hrs, and an average 

annual arithmetic PM2.5 concentration of 15 μg/m3. The 

Montana air quality State Implementation plan (SIP) 

for particulates is promulgated through the Montana 

Clean Air Act and implementing regulations. The 

regulations provide specific guidance on maintenance 

of air quality including restrictions on open burning. 

The Act created the Montana Air Quality Bureau (now 

the DEQ) and the regulatory authority to implement 

and enforce the codified regulations.
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-230WWW. 2009 3

residential wood burning, wood fires, and smoke from 

logging slash disposal, prescribed burns, and wildland 

fires. The Spanish Peaks unit of the LMW receives vehicle, 

residential, construction, and ski area emissions from 

the Big Sky area. Down valley airflow in the ABW and 

LMW drainages is frequently strong during nighttime 

and early morning hours.

The Billings and Laurel sources are currently permitted 

annual emissions of 1,928 tons of PM10 and 16,481 tons 

of S02. Laurel is in non-attainment for S02 (http://www.

deq.mt.gov/AirQuality/Planning/AirNonattainment.asp). 

Except for occasional upslope, high velocity, east winds, 

most of the Billings/Laurel emissions are carried to the 

east and away from the ABW by the predominant west-tosouthwest winds.The major sources of emissions affecting 

the ABW are the cities of Big Timber, Livingston, and 

Bozeman with vehicle exhaust, wood burning smoke, 

and road dust. These communities are in compliance 

with all NAAQS. Big Timber, Livingston, and Bozeman 

emissions do not visibly impact the ABW. These emissions 

are dispersed by predominant southern and southwestern 

winds that come from robust Yellowstone valley wind 

gradients that typically carry emissions north of the ABW. 

Other types of emissions in the Yellowstone valley that 

could affect the ABW include vehicle and agriculture 

equipment exhaust, road dust, smoke from residential 

wood burning, and smoke from pile burning, broadcast 

burning, and wildland fires.

The city of Bozeman is the major source of emissions 

from the Gallatin valley, north of the LMW. Smaller 

amounts of emissions occur from Belgrade and Three 

Forks/Willow Creek and from vehicles on Interstate 90 and 

Highways 191, 345, and 287. Bozeman emissions do not 

visibly impact LMW since these emissions are dispersed by 

predominant westerly and southwesterly wind direction. 

Table 2—Emission sources greater than 50 tons/year within 60 miles of USFS R1 

wildernesses.

Wilderness CO NOx PM10 SO2

Tons per year

Absaroka Beartooth (ABW) & Lee Metcalf (LMW) 2,038 5,442 1,259 13,521

Gates of the Mountains (GMW) 778 1,789 1,093 564

Bob Marshall (BMW), Scapegoat (SGW), Great 

Bear (GBW), Mission Mountains (MMW)

36,347 753 2,512 1,421

Cabinet Mountains (CMW) 1,191 52 303 6

Rattlesnake (RW), Welcome Creek (WCW), Eastern 

Selway Bitterroot (SBW) and Anaconda Pintler 

Wilderness (APW)

4,158 2,935 1,327 166

Gospel Hump (GHW) and Western (SBW) 1,150 392 204 22

USFS R1 Air Pollution Sources ____

Air quality in and around USFS R1 wilderness areas 

is generally good, impacted primarily by episodes of 

wildland fire smoke and long range transport. The EPA 

Aerometric Information Retrieval System (AIRS) data base 

(http://www.epa.gov/air/data/netemis.html) was queried 

for all stationary permitted sources of air emissions 

more than 50 tons/year. This database was last updated 

in 1999; emissions may now be higher or lower than 

initially recorded.

Total permitted emissions (>50 ton/year/source) in 

counties within approximately 60 miles of USFS R1 

wildernesses or wilderness complexes are recorded in 

table 2.

The Absaroka Beartooth (ABW) and Lee Metcalf 

(LMW) Wildernesses have the highest amount of 

permitted NOx, and SO2, due to the petroleum refineries 

in Billings and Laurel. Most of these emissions disperse 

to the east of the ABW. The Bob Marshall wilderness 

has the highest exposure to CO and PM10 emissions 

due to its proximity to the Columbia Falls aluminum 

plant. That facility is currently operating on a reduced 

schedule; therefore, emissions are currently lower than 

table 2 depicts. More detailed data regarding emissions 

within 60 miles of R1 wilderness areas or complexes 

are presented in tables 3 to 8.

Absaroka Beartooth and Lee Metchalf 

Emission Sources

Existing sources of emissions in the ABW and LMW 

wilderness areas (table 3) include dust from trails and 

campsites and smoke emissions from wildland fires 

and prescribed burns. Adjacent area emissions include 

occasional construction equipment, vehicles, road dust, 
4 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-230WWW. 2009

In the evenings, air flows down drainages from the north 

end of the Gallatin valley, carrying Bozeman emissions 

north and west. This process is particularly noticeable 

in the winter when frequent inversions constrain mixing 

heights over Bozeman and air pollutants drift down the 

Gallatin valley toward Belgrade.

Regional wildland fire smoke accumulated in the ABW 

and LMW area during periods of extensive wildland fire 

activity in 1988, 1994, 2000, 2003, 2006, and 2007. The 

primary sources of wildland fire emissions are central 

and southern Idaho and southwest Montana. Smoke from 

wildland fires in Yellowstone National Park can also impact 

the ABW and LMW area, as occurred in 1988.

Generally the ABW and LMW areas do not develop 

temperature inversions that trap smoke and reduce its 

dispersal. Dispersion of emissions within the ABW and 

LMW is very high due to the mountainous terrain and high 

wind activity. The Main Boulder Canyon, Gallatin Canyon, 

and the West Fork Gallatin (Big Sky) have some potential 

for inversion and cumulative concentrations of smoke and 

residential and transportation emissions. Visible inversion 

conditions occasionally occur in the Big Sky area, which 

has been designated as the Big Sky Impact Zone 

by the Montana DEQ (http://www.deq.state.mt.us/

AirQuality/Planning/MONTANA_SMOKE_MGNT_

impact_zone.htm).

Due to temperature and density differences, winds 

typically flow up valleys and up mountain slopes during 

the daytime and reverse direction during the cooler hours 

of the evening and night. Mountain winds in the ABW 

and LMW area are usually stronger than valley winds 

(NASA [n.d.])

Cabinet Mountains Wilderness Emission 

Sources

Air Quality in the Cabinet Mountains Wilderness (CMW) 

is generally good (table 4), with few upwind point source 

emissions and periodic strong wind dispersion. Libby is

in non-attainment for the PM2.5 annual standard and has 

some of the most persistent particulate-matter caused 

human health issues in Montana. These are documented 

in the Montana DEQ air monitoring network review 

(http://www.deq.mt.gov/AirMonitoring/networkRev/

network2003.pdf). The Libby PM2.5 issues are caused 

by reduced dispersion in Libby’s incised valley location. 

Conditions of reduced dispersion are atypical in CMW, 

which is located in a higher elevation mountainous area 

with considerably better air dispersion. CMW is also in 

the path of long distance transport of air pollutants from 

Washington and Oregon. Emission sources in CMW 

include dust from trails during dry conditions and smoke 

Table 3—Emission sources greater than 50 tons/year within 60 miles of the Absaroka Beartooth (ABW) and 

Lee Metcalf (LMW) Wildernesses.

CO NOx PM10 SO2 Facility name Location Industry type 

tons per year

542 11.9 1.52 1,137 Montana Sulfur & Chemical Billings inorganic chemicals

386 905 184 3,197 Centex Laurel petroleum refining

293 697 155 1,222 ConocoPhillips Billings petroleum refining

205 1,504 127 2,698 Pal, Montana - J.E. Curette Plant Billings electric services

191 324 60.3 74.7 Western Sugar Billings beet sugar

149 41.5 63.3 2.21 Louisiana-Pacific - Belgrade Belgrade sawmill

134 733 291 2,894 Exxon Billings petroleum refining

42.5 3.12 40.0 24.4 Jell Group Belgrade paving mixtures 

31.0 685 213 192 Holcim, Inc. Three Forks cement

29.8 448 22.8 2,073 Yellowstone Energy Limited Billings electric services

23.9 55.4 46.4 6.03 Stillwater Mining Co - E. Boulder Mcleod metal ores 

6.62 23.4 22.8 0.48 Barretts Minerals Inc. Dillon minerals

4.30 10.5 32.2 0.24 Luzenac America - Three Forks Three Forks talc

2,038 5,442 1,259 13,521 Total
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-230WWW. 2009 5

from wildland fires and prescribed burns. Adjacent area 

sources are primarily occasional construction equipment, 

vehicles, road dust, residential wood burning, wood 

fires, and smoke from logging emissions slash disposal, 

prescribed burns, and wildland fires. CMW also receives 

some vehicle, residential, and construction emissions from 

the Libby area and from the Highway 56 and Highway 2 

corridors.

Gates of the Mountains Wilderness 

Emission Sources

The southern edge of the Gates of the Mountains 

Wilderness (GMW) is about 14 miles from the ASARCO 

smelter in East Helena, which was the largest source of 

SO2 emissions in Montana before shutting down in 2001. 

Area emissions adjacent to the GMW (table 5) from the 

Helena valley and I-15 corridor include construction 

equipment, vehicles, road and agricultural dust, residential 

wood burning, wood fires, and smoke from logging slash 

disposal, prescribed burns, and wildland fires.

Bob Marshal, Scapegoat, Great Bear, 

and Mission Mountains Wildernesses 

Emission Sources

Air Quality in the Bob Marshall Wilderness (BMW) 

complex is good (table 6), with limited upwind emissions 

from large stationary local emission sources and periodic 

robust wind dispersion. Existing emissions sources in 

the wilderness complex include dust from trails during 

dry conditions and smoke emissions from wildland fires 

and prescribed burns. Adjacent area emissions include 

occasional construction equipment, vehicles, road dust, 

residential wood burning, wood fires, and smoke from 

logging emissions slash disposal, prescribed burns, and 

wildland fires. The BWM complex receives vehicle, 

residential, and construction emissions from the upper 

Flathead valley (Kalispell, Columbia Falls, Whitefish, 

Hungry Horse, and West Glacier).

The main permitted industrial sources in the Flathead 

valley include Columbia Falls Aluminum Company 

(currently only partially in operation) for sulfur dioxides 

(SOx) and particulates and two Plum Creek facilities 

Table 4—Emission sources near the Cabinet Mountains Wilderness (CMW).

CO NOx PM10 SO2 Facility name Location 

Industry 

type 

tons per year

1,052 36.6 69.8 3.70 Stimson Lumber - Libby Libby lumber

129 14.3 63.9 1.90 Plum Creek Mfg., Lp-Ksanka Libby lumber

10.1 2.20 57.1 0.37 Eureka Pellet Mills Eureka lumber

63.6 Owens & Hurst Lincoln County lumber

1,191 52 303 6 Total

Table 5—Emission sources near the Gates of the Mountains Wilderness (GMW).

CO NOx PM10 SO2 Facility name Location 

Industry 

type 

tons per year

355 367 924 40.4 Golden Sunlight Mine Whitehall gold ores

246 336 433 36.7 Montana Tunnels Mine Jefferson City gold ores

141 336 95.1 239 Continental Lime Townsend lime

23.0 697 199 241 Ash Grove Cement Clancy cement

10.8 26.5 29.4 1.91 Basin Creek Mine Basin gold ores

778 1,789 1,093 564 Total
6 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-230WWW. 2009

Table 6—Emission sources near the Bob Marshall (BMW), Scapegoat (SGW), Great Bear (GBW), 

and Mission Mountains (MMW) Wildernesses.

CO NOx PM10 SO2 Facility name Location Industry type 

tons per year

32,523 10.6 1,447 1,386 Columbia Falls Aluminum Kalispell aluminum plant

1,365 150 156 9.28 Plum Creek Evergreen Kalispell lumber

1,080 480 445 15.5 Plum Creek Manufacturing, 

L.P. Columbia Falls lumber

1,052 36.6 69.8 3.70 Stimson Lumber Libby lumber

129 14.3 63.9 1.90 Plue Creek Mfg., Lp-Ksanka Libby lumber

94.7 5.45 178 1.07 American Timber Company Olney lumber

58.8 23.3 1.54 0.08 MPC Cut Bank Mainline #1 Cut Bank natural gas

24.0 4.08 64.4 0.90 Stoltze Land and Lumber Columbia Falls lumber

10.8 26.5 29.4 1.91 Basin Creek Mine Lewis & Clark Co gold ores

10.1 2.20 57.1 0.37 Eureka Pellet Mills Lincoln Co lumber

36,347 753 2,512 1,421 Total 

(Kalispell and Columbia Falls) for nitrogen oxides (NOx) 

and PM10. Kalispell, Columbia Falls, and Whitefish are 

designated non-attainment areas by the Montana DEQ 

for PM10 (http://www.deq.mt.gov/AirQuality/Planning/

AirNonattainment.asp). East of the Great Bear Wilderness, 

there are several stationary sources of NOx emissions 

from natural gas processing and transportation facilities 

in Glacier and Teton Counties (primarily in Cut Bank). 

The very strong dispersion and predominantly westto-east wind direction transports most of these eastside 

emissions downwind of the GBW. The Mission Mountain 

Wilderness (MMW) receives emissions from the lower 

Flathead valley, including the Highway 93 corridor. The 

southern part of the MMW is subject to Missoula area 

emissions described for the RW.

Existing sources of emissions in the Rattlesnake 

Wilderness (RW), Welcome Creek Wilderness (WCW), 

and eastern Selway Bitterroot Wilderness (SBW) (table 7) 

include dust from trails during dry conditions and smoke 

from wildland fires and prescribed burns. Emissions from 

adjacent areas include occasional construction equipment, 

vehicles, road dust, residential wood burning, wood fires, 

and smoke from logging slash disposal, prescribed burns, 

and wildland fires. The RW receives vehicle, residential, 

and construction from the Missoula area. The WCW 

has very limited local sources. Down valley airflow in 

the RW and the WCW drainages is frequently strong 

during nighttime and early morning hours. The entire 

RW and WCW area is considered to be in attainment 

by the Montana DEQ. The eastern SBW receives valley 

emissions from Stevensville, Hamilton, and Darby and 

some agriculture burning emissions. The primary air 

pollution source for the eastern SBW is wildland fire 

smoke from Idaho.

The main source of air pollutants to RW and, to a lesser 

degree, WCW is the city of Missoula and surrounding 

Table 7—Emission sources near the Rattlesnake (RW), Welcome Creek (WCW), eastern 

Selway Bitterroot (SBW), and Anaconda Pintler (APW) Wildernesses.

CO NOx PM10 SO2 Facility name Location Industry type 

tons per acre

3,804 2,253 697 149 Stone Container Missoula paper mill

265 186 141 9.94 Stimson Lumber East Bonner sawmill

54.0 435 348 6.49 Louisiana-Pacific Missoula wood products

23.6 56.3 141 0.87 Pyramid Mtn Lumber Seeley Lake sawmill

11.1 4.42 Conoco, Inc. Bulk Terminal Missoula petroleum 

4,158 2,935 1,327 166 Total
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-230WWW. 2009 7

area (table 7). A chronological history of Missoula air 

quality issues and trends is available at Missoula County, 

2006 (http://www.co.missoula.mt.us/airquality/). The 

major source of emissions in the Missoula valley includes 

vehicle exhaust, wood burning smoke, and road dust, 

and industrial emissions. The main permitted industrial 

sources in the Missoula valley include Stone Container 

for NOx and PM10.

Air quality in the Gospel Hump Wilderness (GHW) 

and western Selway Bitterroot Wilderness (SBW) is 

generally good (table 8) with limited emissions from 

upwind large stationary sources and periodic strong 

wind dispersion. The GHW in particular is subject to 

long distance transport from Washington and Oregon 

(Graw personal communication). Existing emission 

sources in the GHW include dust from trails during dry 

conditions and smoke from wildland fires and prescribed 

burns. Area emission sources adjacent to the GHW and 

western SBW include construction equipment, vehicles, 

road dust, logging emissions, residential wood burning, 

wood fires, and smoke from slash disposal, prescribed 

burns, and wildland fires. The GHW receives some 

vehicle, residential, and construction emissions from 

the Grangeville to McCall corridor along Highway 95, 

adjacent logging, jet boat emissions on the Salmon river, 

and snowmobile emissions along the Buffalo Hump 

corridor. Local emission levels are low due to the sparsely 

populated area and vast areas for dispersion. Down valley 

airflow in the GHW drainages (Johns Creek and Crooked 

Creek on the north and Salmon River tributaries on the 

south—Wind River, Sheep Creek, and Crooked Creek) 

is frequently strong during nighttime and early morning 

hours. The entire GHW is considered to be in attainment 

by the Idaho DEQ.

Analysis Methods _______________

Methods for analysis followed the Data Analysis 

Protocol for Long-Term Lake Monitoring (DAP) (Gurrieri 

2006), which was derived from the statistical, graphical, 

and protocol development methods of Gilbert (1987), 

Helsel and Hirsch (1992), and Ward and others (1990). 

Trends were tested using the Kruskall-Wallis Test for 

seasonality, the Mann-Kendall, and the Seasonal MannKendall tests. These nonparametric tests work well 

with monotonic trends. They do not require normally 

distributed data and are much more resistant to outliers 

and missing data than parametric tests (Gurrieri 2006).

The null hypothesis (Ho) is that there is no significant 

trend (in lake, NADP, and IMPROVE parameters) over 

time. The alternative hypothesis (H1) means a significant 

increasing or decreasing trend (in the lake, NADP, or 

IMPROVE parameters) was found over time.

Figure 2 is used by the Data Analysis Protocol to 

analyze trends in long-term lake monitoring data and 

was used to guide the data analysis.

The data analysis for this paper was generated using 

SAS software, Version 9.1.3 of the SAS System for 

Windows. Copyright © 2008 SAS Institute Inc. SAS 

and all other SAS Institute Inc. product or service names 

are registered trademarks or trademarks of SAS Institute 

Inc., Cary, NC, USA.

After the data was imported into SAS, the KruskalWallis test was run for each parameter to see if there 

was a difference among seasons. If seasonality existed 

statistically at an α < 0.05 level then the Seasonal MannKendall test was run. If seasons were not statistically 

different, then the Mann-Kendall test was run on the annual 

data. The Mann-Kendall and Seasonal Mann-Kendall 

tests report whether or not a trend exists, they do not 

Table 8—Emission sources near the Gospel Hump Wilderness (GHW) and the western Selway 

Bitterroot SBW Wildernesses.

CO NOx PM10 SO2 Facility name Location 

Industry 

type 

tons per acre

807 275 24.1 8.88 Potlatch Corporation Wood Products Pierce lumber

246 110 59.2 10.5 Evergreen Forests & Tamarack Energy New Meadows sawmill

96.7 6.46 121 2.55 Shearer Lumber Products Elk City sawmill

1,150 392 204 22 Total
8 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-230WWW. 2009

Figure 2—Flow diagram depicting temporal trend analysis protocol 

(Gurrieri 2006).

evaluate the magnitude of the trend. The Mann-Kendall 

test was also run to look for trends among each season.

The Mann-Kendall and Seasonal Mann-Kendall use 

alpha (α) to quantify the probability that a trend exists. 

For this report the alpha level for statistical significance 

was set at α < 0.1. A value of α = 0.001 means there is a 

0.1% chance of making a mistake when rejecting the null 

hypothesis that no trend exists (Salmi and others 2002).

Lake data were downloaded from the National USDA 

Forest Service website for chemistry of lakes, streams, and 

bulk deposition on and near the National Forests, (USFS 

NRIS-Air database http://www.fs.fed.us/waterdata/). 

Protocols for lake sampling often call for three samples 

to be taken during three specific times of year so that 

differences due to seasonality can be detected. Lake 

sampling in the USFS Region 1 usually occurred only once 

or twice a year so any changes over and between seasons 

could not be compared. In the case when two or more 

samples did occur, only data from the samples that used 

the most common deep sampling method (Story 2008) 

was used. Data from samples closest to the most common 

date were selected to minimize seasonality differences 

in data. Samples with close dates were averaged. Only 

data that was contaminated (lab suggested contamination) 

were deleted. The revised data sets were used for the 

SAS analysis.

Six lakes in R1 undergo long-term Phase 3 monitoring: 

Lower Libby Lake and Upper Libby Lake, in the CMW, 

North Kootenai Lake and Shasta Lake, in the SBW, and 

Stepping Stone Lake and Twin Island Lake, in the ABW 

(Story 1999). Each lake was analyzed for trends in specific 

conductance (μS/cm), pH, ANC (mg/L), NH4

+

, NO3

–

, 

SO4

2–, Ca2+, and Cl–

.

The National Atmospheric Deposition Program 

(NADP) data were downloaded from the NADP website 

(http://nadp.sws.uiuc.edu). The following six sites were 

analyzed for trends in annual and seasonal concentrations 

(mg/L): Lost Trail Pass (MT97), Clancy (MT07), Glacier 

(MT05), Tower Junction (WY08), Craters of the Moon 

(ID03), and Little Bighorn Battlefield National Monument 

(MT00). Lost Trail Pass (MT97), Clancy (MT07), and 

Glacier (MT05) were also analyzed for trends in annual 

and seasonal deposition (kg/ha). Each site was analyzed 

for trends in specific conductance, pH, NO3

–

, NH4

+

, 

SO4

2–, Ca2+, Cl–

, Na+, K+, and Mg2+.

The IMPROVE (Interagency Monitoring or Protected 

Visual Environments) data were received from the 

Atmospheric Data Analyst for CIRA (Cooperative 

Institute for Research in the Atmosphere) because the 2006 

data were not yet available on the public website (http://

vista.cira.colostate.edu/improve/). Data were analyzed 

for seven IMPROVE sites: CABI1, GAM01, GLAC1, 

HECA1, MONT1, SULA1, and YELL2. Each site was 

analyzed for trends in the extinction coefficient (E) for the 

following parameters: ESO4, ENO3, EOMC (organic mass 

from carbon), Esoil (fine soil), ECM (coarse mass), ELAC 

(Light Absorbing Carbon), Esea_salt (sea salt), Rbext (sum 

aerosol extinctions), SVR (standard visibility range), dv 

(deciview), MF (PM2.5), and MT (PM10).

Lake Chemistry and Trends _______

The U.S. Forest Service Region 1 Air Resource 

Monitoring Program, encompassing approximately 1,750 

wilderness lakes, has emphasized the monitoring of 

lake chemistry, which provides diagnostic indicators of 
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-230WWW. 2009 9

atmospheric deposition since 1989. The lakes are a main 

attraction for wilderness recreation users but also provide 

a chemical record of air pollution impacts. Many alpine 

lakes are vulnerable to acid deposition because they are 

very dilute and have little acid buffering capacity. Dilute, 

poorly buffered lake water results from limited weathering, 

thin soils, sparse vegetation, and short groundwater flow 

paths (Campbell and others 1995). Lake chemistry also 

affects community composition of microorganisms, 

invertebrates, and other aquatic fauna and flora, which 

ultimately affects the health and productivity of fish. 

Since 1989, USFS R1 personnel—primarily wilderness 

rangers and volunteers from Yellowstone Ecosystem 

Studies—have sampled 176 lakes in R1 wildernesses. 

The sampling has consisted of a three-phase program 

(Story and Grenon 2008).

Six lakes were selected for long term Phase 3 

monitoring: Lower Libby Lake and Upper Libby Lake, 

in the CMW, North Kootenai Lake and Shasta Lake, in 

the SBW, and Stepping Stone Lake and Twin Island Lake, 

in the ABW (Story 1999). Figure 3 indicates the location 

of Phase 3 lakes. The lakes were selected due to their 

high sensitivity to acid precipitation and are considered 

representative of the R1 wilderness lakes. Figure 4 

shows a sensitive high alpine Phase 3 lake. The SBW, 

ABW, and parts of the CMW consist of granite, gneiss, 

or quartzite bedrock, which are chemically resistant and 

result in low alkalinity surface waters.

Phase 3 sample methods are described in detail in Story 

and Grenon (2008) and Story (2008). For each lake, 

duplicate samples were collected at 0.5 meters below the 

surface in the deepest part the lake. Samples were kept 

cool in field coolers with frozen gel packs and shipped to 

the Air Resource Management Laboratory (http://www.

fs.fed.us/waterlab/) as soon as possible. Filtering was done 

in the lab within 24 hours of samples arriving at the lab.

All analyses used QA/QC guidelines and EPA reference 

standards established in the Handbook of Methods for 

Acid Deposition Studies (EPA 1987) and Standard 

Methods (APHA 1989). The data were reviewed for 

conformance with quality assurance standards prior 

to use. All of the lake data is available from the USFS 

NRIS-Air database (http://www.fs.fed.us/waterdata/).

Sampling in the six lakes chosen for analysis started 

between 1991 and 1993, and were typically sampled at 

least once each year. Due to infrequent sampling, trends 

were run using one sample per year with the Mann-Kendall 

test and Sen’s Slope estimator. Trends were run for 

Figure 3—USFS R1 Phase 3 lake locations.
10 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-230WWW. 2009

Figure 4—Stepping Stone Lake in the Absaroka-Beartooth Wilderness. 

concentrations (mg/L) of ANC (mg/L), NH4

+

, NO3

–

, pH, 

SO4

2–, Ca2+, and Cl–

, and conductivity (μS/cm) over time.

Significant trends in R1 Wilderness lake chemistry 

are presented in table 9 (p-values and trend direction). 

The direction of the Trend and Sen’s Slope estimator is 

indicated either by an upward/increase ↑ or downward/ 

decrease ↓ in the trend of the parameter analyzed. The 

closer the p-value to 0, the stronger the evidence of a trend.

Concentrations of SO4

2– decreased in Lower Libby 

Lake, CMW. No significant trends were observed in 

Upper Libby Lake for any of the measured parameters.

In the SBW, Cl– decreased in North Kootenai Lake. 

Specific conductance decreased and NO3

– concentrations 

increased in Shasta Lake.

In the ABW, ANC, specific conductance, and Cl– 

decreased in Stepping Stone Lake. The pH increased in 

both Stepping Stone Lake and Twin Island Lake.

Figures 5 to 10 illustrate lake chemistry trends in the 

six Phase 3 lakes. Data gaps occurred where sample 

contamination was suspected (lab suggested) or no 

samples were collected using the deep sampling method 

described in Story and Grenon (2008).

Table 9—Mann-Kendall p-values for annual lake data and trend direction. Highlighted cells indicate 

statistically significant trends when p < 0.1. 

Parameter (mg/L)

Lower 

Libby

Upper 

Libby N. Kootenai Shasta

Stepping 

Stone Twin Island

ANC 0.138 0.428 0.767 0.246 0.002 ↓ 0.381

ConductivityμS/cm 0.621 0.882 0.198 0.032 ↓ 0.042 ↓ 0.956

NH4+ 0.368 0.519 0.714 0.136 0.487 0.442

NO3– 0.686 0.725 0.313 0.030 ↑ 0.450 0.856

pH 0.620 0.843 0.373 0.219 0.038 ↑ 0.010 ↑

SO4= 0.047 ↓ 0.113 0.767 0.582 0.843 0.228

Ca2+ 0.552 1 0.692 0.246 0.656 0.274

Cl– 0.276 1 0.048 ↓ 0.583 0.003 ↓ 0.827
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-230WWW. 2009 11

Figure 5—Long-term trends in lake water ANC concentrations for Stepping 

Stone Lake.

Figure 6—Long-term trends in lake-water specific conductance.

Figure 7—Long-term trends in lake-water NO3

–

 concentrations.
12 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-230WWW. 2009

Figure 8—Long-term trends in lake-water pH.

Figure 9—Long-term trends in lake-water SO42– concentrations at Lower 

Libby Lake.

Figure 10—Long-term trends in lake-water Cl–

 concentrations.
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-230WWW. 2009 13

Lake Sampling Discussion

Nitrate trends in the R1 Phase 3 lakes are less evident 

than trends in the Bridger-Teton and Shoshone National 

Forest in the Wind River Range, Wyoming, where

increasing lake water NO3

–

 concentrations were detected 

in several lakes (Bevenger 2008; Svalberg and Mebane 

2006). In the Rocky Mountains, the largest trends have 

occurred in the Colorado Front Range (Williams and others 

1996) where several lake NO3

–levelshave increased from 

below detection limits to around 10 μeq/L (0.62 mg/L) 

and are considered at or near nitrogen saturation levels.

Of the R1 lakes sampled, only Shasta Lake shows a 

significant increasing trend in NO3

–

. The low nitrate 

concentrations in the Phase 3 lakes, which were below 

detection limits for most sampling events, are likely due to 

rapid assimilation of atmospherically deposited nitrogen 

by aquatic and terrestrial biota. The exception is Upper 

Libby Lake, which has very sparse soil development, 

is very oligotrophic, and has limited algae, which may 

limit nitrate assimilation rates (Story and Grenon 2008 ). 

Fenn and others (2003) and other findings indicate that 

many places in the Rocky Mountains may be at or near 

nitrogen saturation. Future sampling may provide better 

indications/continuation of trends in USFS R1.

Despite overall trends in the West of decreasing SO4

2– 

atmospheric deposition, only one of the lakes (Lower 

Libby) in this report showed a decreasing SO4

2– trend. 

The lack of lake water response may be masked by 

inputs of sulfate from internal weathering sources or the 

lakes may be too far from SO4

2–emission sources to be 

significantly affected by an emission decrease. The lack 

of a decreasing SO4

2– trend in the R1 lakes (except for 

Lower Libby Lake) contrasts with the Wind River lakes 

(Svalberg and Mebane 2006) and the Shoshone lakes 

(Bevenger 2008) where sulfate concentrations in Deep 

Lake and Hobbs Lake (Wind River), and Ross Lake 

(Shoshone) have decreased.The Wind River and Shoshone 

lakes have a longer and more frequent sampling record, 

which may increase the statistical power to detect trends.

Sulfate concentrations in North Kootenai Lake were 

higher than the other Phase 3 lakes, which Eilers (2003) 

speculates may be due to the presence of sulfur-bearing 

minerals (such as FeS2) in the bedrock.

The smaller the ANC the more sensitive the lake is to 

acid deposition from the atmosphere. The decrease in 

ANC and specific conductance in Stepping Stone Lake 

is not clearly related to an increase in acid deposition 

because no trends in lake water concentrations of NO3

–

and SO4

2– were detected. There is suggestive evidence 

that ANC increased in Twin Island Lake from 1999 to 

2007 but decreased in Lower Libby, Upper Libby, North 

Kootenai, and Stepping Stone Lakes (Story and Grenon 

2008). The Mann-Kendall test statistically validated an 

ANC decrease only at Stepping Stone Lake. Generally, 

a decrease in ANC coincides with a decrease in pH. 

Both Twin Island and Stepping Stone Lakes showed 

a significant increase in pH despite the decreasing 

trends in ANC at Stepping Stone Lake. In the Shoshone 

National Forest, Saddlebag and Ross Lakes (Fitzpatrick 

Wilderness) have also demonstrated decreased trends 

in ANC, which may be from a coinciding increase in 

NO3

–

 (Bevenger 2008).

The reduction in Cl–

 in both North Kootenai and 

Stepping Stone Lakes is not readily explainable, but 

it may be related to contamination in 1993 to 1995. 

Seasonality often plays an important role in data variation.

Since there was only one lake sample per year analyzed 

and the samples were not always taken during the same 

season, potential seasonality in the above data could be a 

factor. Variation in lake chemistry can also be influenced 

by weather patterns (rain events and predominant wind 

patterns during the several days preceding the sampling 

period) and the date and time of sampling.

NADP Data and Trends ___________

The National Atmospheric Deposition Program 

(NADP) was initiated in 1978 to monitor geographical 

and temporal trends in the chemical composition of rain 

and snow (wet deposition) with the primary purpose 

of acid rain benchmark monitoring. The program was 

prompted by scientific evidence and public concern 

in the 1970s that acid rain could be damaging aquatic 

ecosystems throughout the United States. The program 

grew steadily though the early 1980s and has stabilized 

at about 200 sites. The NADP network data is used by 

a wide variety of government administrators, resource 

specialists, and university scientists in monitoring the 

amounts of wet deposition and effects on agriculture, 

forests, rangelands, freshwater streams, lakes, and 

cultural resources. Atmospheric deposition is commonly 

referred as “acid rain” but can occur as acid snow, fog, or 

dry deposition. The NADP data from all sites is readily 

retrievable at the NADP web site at http://nadp.sws.uiuc.

edu. Figure 11 shows NADP site locations in Region 1.

The NADP site at Lost Trail Pass (MT97) on the Sula 

District of the Bitterroot National Forest is the only NADP 

site in Montana operated by the U.S. Forest Service and is 

the only high elevation NADP site in Montana and Idaho. 

Data for the MT97 site from 1990 to 2006 is summarized 

in Story and Grenon (2008). Other NADP sites are very 
14 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-230WWW. 2009

Figure 11—Active NADP site locations in and around MT.

useful for USFS R1 wilderness monitoring as shown in 

figure 11. Figure 12 shows a typical NADP site setup.

All of the NADP sites are operated according to NADP 

protocols (http://nadp.sws.uiuc.edu/documentation/

completeness.asp). Sample buckets (3.5 gallons) are 

exchanged each Tuesday. Sample weights are measured, 

daily precipitation is recorded on the site from the rain 

gage strip charts, and the samples are shipped to the Central 

Analytical Lab (CAL) at the University of Illinois in 

Champaign (Illinois State Water Survey). The CAL analyzes 

samples for pH, specific conductance, Ca2+, Mg2+, K+

, Na+, 

NH4

+

, NO3

–

, Cl–, and SO4

2–. The data is carefully evaluated 

at the NADP Coordination Office for quality control and 

consistency. Quality control throughout the CAL and 

NADP offices is very rigid and consistent. Data is available 

about 6 months after the samples are analyzed and quality 

control checked by the CAL. For deposition (or loading) in 

kg/ha, total inorganic N was analyzed but pH and specific 

conductance were not. The NADP concentration (mg/L) 

data are precipitation-weighted and the loading NADP 

data (kg/ha) are total wet deposition.

Data from the following six sites were analyzed for 

annual and seasonal trends: Lost Trail Pass (MT97), 

Clancy (MT07), Glacier (MT05), Tower Junction 

(WY08), Craters of the Moon (ID03), and Little Bighorn 

Battlefield National Monument (MT00). Lost Trail Pass 

(MT97), Clancy (MT07), and Glacier (MT05) were also 

analyzed for trends in annual and seasonal deposition. 

Each site was analyzed for trends in NO3

–

, NH4

+

, specific 

conductance, pH, SO4

2–, Ca2+, Cl–

, Na+, K+, and Mg+.

Annual NADP Concentration Trends

Statistically significant increase in annual NH4

+

concentration (mg/L) were present at Glacier, Craters 

of the Moon, Little Bighorn, and Tower Junction. For 

NO3

–

, only Tower Junction showed an increase. Specific 

conductance appears to be decreasing at Glacier, Craters 

of the Moon, Little Bighorn and Tower Junction. The 

only significant trend in lab pH was a decrease at Clancy. 

Downard trends in SO4

2– were statistically significant 

at all sites except Lost Trail Pass. Decreasing trends in 

Ca2+, Na+

, and Mg+ were detected at all sites except for 

Lost Trail Pass. Cl– and K+ exhibited decreasing trends 

at all sites. Table 10 and figures 13 to 15 should help 

visualize annual trends in concentration during the period 

of record evaluated.
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-230WWW. 2009 15

Figure 12—Lost Trail pass (MT97) NADP Site.

Table 10—Statistically significant annual NADP concentration trends found with the 

Mann-Kendall (light blue cells) and with Seasonal Mann-Kendall tests (yellow cells) 

are bolded. Highlighted cells indicate statistically significant trends using p < 0.1.

Parameter

(mg/L) Clancy Glacier

Lost Trail 

Pass

Craters of 

the Moon

Little 

Bighorn Tower

NO3

– 0.259 0.23 0.436 0.806 0.858 0.041 ↑

NH4

+ 0.291 <0.001 ↑ 0.146 <0.001 ↑ <0.001 ↑ <0.001 ↑

cond 0.689 0.002 ↓ 0.436 0.001 ↓ 0.054 ↓ 0.017 ↓

pH 0.029 ↓ 0.513 0.932 0.227 0.98 0.646

SO4

2– 0.022 ↓ <0.001 ↓ 0.488 <0.001 ↓ <0.001 ↓ <0.001 ↓

Ca2+ 0.015 ↓ <0.001 ↓ 0.23 0.001 ↓ 0.026 ↓ 0.033 ↓

Cl– 0.003 ↓ <0.001 ↓ 0.033 ↓ <0.001 ↓ <0.001 ↓ <0.001 ↓

Na+ 0.007 ↓ <0.001 ↓ 0.173 0.003 ↓ <0.001 ↓ <0.001 ↓

K+ 0.005 ↓ <0.001 ↓ 0.017 ↑ 0.001 ↓ 0.004 ↓ 0.013 ↓

Mg+ 0.043 ↓ <0.001 ↓ 0.401 <0.001 ↓ 0.001 ↓ <0.001 ↓
16 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-230WWW. 2009

Figure 13—Trends in annual volume-weighted mean (VWM) NO3–

concentrations at Tower Junction NADP site

Figure 14—Trends in annual VWM NH4

+ concentrations at NADP sites.

Figure 15—Trends in annual VWM SO42– concentrations at NADP sites.
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-230WWW. 2009 17

Annual NADP Deposition (Loading) 

Trends

Trends in annual wet deposition (or loading) are shown 

in table 11 and figures 16 to 20. Trends indicated increasing 

amounts of nitrogen. NO3

–

 shows an increasing loading 

trend only at Clancy. NH4

+

, Inorganic Nitrogen, SO4

2–, 

Cl–, Na+, and Mg+ exhibited increasing trends at Clancy 

and Glacier. Glacier also shows a decreasing trend in 

Ca2+ and K+

.

Seasonal Trends at NADP Sites

USFS R1 NADP sites were also analyzed for 

statistically significant trends in concentration for each 

parameter through each season (winter, spring, summer, 

and fall) to evaluate individual seasonal differences. 

The NADP sites closest to USFS R1 wilderness areas 

were analyzed for trends in deposition among each 

season. Results are presented in tables 12 to 17 and 

figures 21 to 35.

Table 11—Statistically significant annual NADP deposition 

trends found with the Mann-Kendall (light blue cells) 

and with Seasonal Mann-Kendall tests (yellow cells) 

are bolded. Highlighted cells indicate statistically 

significant trends using p < 0.1.

Parameter

kg/ha Clancy Glacier Lost Trail 

NO3

– 0.036 ↑ 0.739 0.24

NH4

+ <0.001 ↑ 0.002 ↑ 0.533

SO4

2– <0.001 ↓ <0.001 ↓ 0.16

Ca2+ 0.929 <0.001 ↓ 0.48

Cl– <0.001 ↓ <0.001 ↓ 0.71

Mg2+ <0.001 ↓ <0.001 ↓ 0.1509

K+ 0.732 <0.001 ↓ 0.112

Na+ <0.001 ↓ <0.001 ↓ 0.967

Inorganic N 0.001 ↑ 0.076 ↑ 0.59

Figure 16—Trend in annual nitrate deposition at Clancy 

NADP site.

Figure 17—Trend in annual NH4

+ deposition at NADP sites.

Figure 18—Trend in annual inorganic N deposition at NADP 

sites.

Figure 19—Trend in annual sulfate deposition at NADP sites.
18 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-230WWW. 2009

Figure 20—Trends in annual Cl– deposition at NADP sites.

Table 12—Clancy NADP site Mann-Kendall p-values for seasonal trends. Highlighted cells indicate statistically significant 

trends using p < 0.1. The grey cells indicate parameters that were not available. 

Parameter Winter Spring Summer Fall Winter Spring Summer Fall

mg/L kg/ha

NO3

– 1 0.193 0.756 0.640 0.106 0.233 0.901 0.245

NH4

+ 0.732 0.115 0.876 0.876 0.146 <0.001 ↑ 0.534 0.028 ↑

cond 0.451 0.373 0.755 0.756

pH 0.034 ↓ 0.304 0.696 0.161

SO4

2– 0.034 ↓ 0.451 0.436 0.533 0.003 ↓ 0.039 ↓ 0.053 ↓ 0.047 ↓

Ca2+ 0.039 ↓ 0.582 1 0.043 ↓ 0.046 ↓ 0.901 0.104 0.790

Cl– 0.016 ↓ 0.169 0.533 0.087 ↓ <0.001 ↓ 0.024 ↓ 0.154 0.097 ↓

Na+ 0.024 ↓ 0.028 ↓ 0.696 0.161 <0.001 ↓ 0.066 ↓ 0.442 0.053 ↓

K+ 0.032 ↓ 0.241 0.756 0.085 ↓ 0.122 0.901 0.862 0.613

Mg2+ <0.001 ↓ 0.071 ↓ 0.060 ↓ 0.004 ↓ <0.001 ↓ 0.072 ↓ 0.551 0.381

Inorganic N 0.018 ↑ 0.025 ↑ 0.534 0.067 ↑

Table 13—Glacier NADP site Mann-Kendall p-values for seasonal trends. Highlighted cells indicate statistically significant 

trends using p < 0.1. The grey cells indicate parameters that were not available. 

Parameter Winter Spring Summer Fall Winter Spring Summer Fall

mg/L kg/ha

NO3

– 0.588 0.008 ↑ 0.700 0.677 0.851 0.381 0.182 0.874

NH4

+ 0.428 <0.001 ↑ 0.123 0.196 0.883 0.003 ↑ 0.210 0.081 ↑

cond 0.632 0.708 0.003 ↑ 0.017 ↑

pH 0.162 0.843 0.103 0.182

SO4

2– <0.001 ↓ <0.001 ↓ <0.001 ↓ <0.001 ↓ <0.001 ↓ 0.004 ↓ <0.001 ↓ <0.001 ↓

Ca2+ 0.066 ↓ 0.098 ↓ 0.061 ↓ 0.020 ↓ 0.010 ↓ 0.017 ↓ 0.001 ↓ 0.034 ↓

Cl– 0.002 ↓ <0.001 ↓ <0.001 ↓ <0.001 ↓ 0.710 ↓ 0.008 ↓ <0.001 ↓ <0.001 ↓

Na+ 0.002 ↓ 0.047 ↓ <0.001 ↓ <0.001 ↓ 0.002 ↓ 0.083 ↓ <0.001 ↓ <0.001 ↓

K+ 0.024 ↓ 0.691 0.077 ↓ 0.009 ↓ 0.001 ↓ 0.404 0.014 ↓ 0.038 ↓

Mg2+ <0.001 ↓ 0.002 ↓ 0.003 ↓ <0.001 ↓ <0.001 ↓ <0.001 ↓ <0.001 ↓ <0.001 ↓

Inorganic N 0.786 0.037 ↑ 0.933 0.312
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-230WWW. 2009 19

Table 14—Lost Trail Pass NADP site Mann-Kendall p-values for seasonal trends. Highlighted cells indicate statistically significant trends using p < 0.1. The grey cells indicate parameters that were not available. 

Parameter Winter Spring Summer Fall Winter Spring Summer Fall

mg/L kg/ha

NO3

– 0.652 0.458 0.232 1 0.090 ↑ 0.364 0.009 ↓ 0.621

NH4

+ 0.031 ↑ 0.742 0.869 0.322 0.197 0.836 0.901 0.738

cond 0.500 0.387 0.091 ↓ 0.091 ↑

pH 0.718 0.432 0.083 ↑ 0.284

SO4

2– 0.500 0.902 0.077 ↓ 0.232 0.869 1 0.007 ↓ 0.967

Ca2+ 0.471 0.509 0.620 0.138 0.320 0.408 0.095 ↓ 0.227

Cl– 0.299 0.341 0.216 0.364 0.321 0.252 0.073 ↓ 0.181

Na+ 0.299 0.283 0.069 ↓ 0.216 0.230 0.187 0.026 ↓ 0.202

K+ 0.185 0.098 ↑ 0.901 0.055 ↑ 0.509 0.173 0.650 0.116

Mg2+ 0.534 0.835 0.096 ↓ 0.402 0.967 0.648 0.016 ↓ 0.933

Inorganic N 0.136 0.741 0.089 ↓ 0.618

Table 15—Craters of the Moon NADP site Mann-Kendall p-values for seasonal trends. Highlighted cells 

indicate statistically significant trends using p < 0.1. The grey cells indicate parameters that were 

not available. 

Parameter (mg/L) Winter Spring Summer Fall

NO3

– 0.518 0.491 1 0.843

NH4

+ 0.381 0.453 0.053 ↑ 0.016 ↑

cond 0.009 ↓ 0.026 ↓ 0.128 0.053 ↓

pH 0.127 0.738 0.277 0.363

SO4

2– <0.001 ↓ 0.005 ↓ 0.002 ↓ <0.001 ↓

Ca2+ <0.001 ↓ 0.217 0.040 ↓ 0.060 ↓

Cl– <0.001 ↓ 0.002 ↓ <0.001 ↓ <0.001 ↓

Na+ <0.001 ↓ 0.061 ↓ 0.002 ↓ <0.001 ↓

K+ <0.001 ↓ 0.103 0.285 0.034 ↓

Mg2+ <0.001 ↓ 0.002 ↓ 0.004 ↓ 0.002 ↓

Table 16—Little Bighorn NADP site Mann-Kendall p-values for seasonal trends. Highlighted cells indicate 

statistically significant trends using p < 0.1. The grey cells indicate parameters that were not 

available. 

Parameter (mg/L) Winter Spring Summer Fall

NO3

– 0.460 0.833 0.233 0.286

NH4

+ 0.009 ↑ 0.119 0.107 0.003 ↑

cond 1 0.187 0.040 ↓ 0.707

pH 0.153 0.597 0.519 0.941

SO4

2– 0.013 ↓ 0.009 ↓ 0.004 ↓ 0.027 ↓

Ca2+ 0.509 0.119 0.150 0.472

Cl– 0.012 ↓ <0.001 ↓ <0.001 ↓ <0.001 ↓

Na+ 0.010 ↓ 0.001 ↓ <0.001 ↓ 0.002 ↓

K+ 0.111 0.071 ↓ 0.345 0.188

Mg2+ 0.015 ↓ 0.011 ↓ 0.027 ↓ 0.041 ↓
20 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-230WWW. 2009

Table 17—Tower Falls NADP site Mann-Kendall p-values for seasonal trends. Highlighted cells indicate 

statistically significant trends using p < 0.1. The Grey cells indicate parameters that were not 

available. 

Parameter (mg/L) Winter Spring Summer Fall

NO3

– 0.851 0.021 ↑ 0.287 0.374

NH4

+ 0.035 ↑ <0.001 ↑ 0.004 ↑ 0.018 ↑

cond 0.070 ↓ 1 0.039 ↓ 0.385

pH 0.008 ↓ 0.348 0.234 0.285

SO4

2– <0.001 ↓ 0.087 ↓ 0.013 ↓ 0.038 ↓

Ca2+ 0.001 ↓ 1 0.661 0.594

Cl– <0.001 ↓ 0.009 ↓ <0.001 ↓ 0.002 ↓

Na+ <0.001 ↓ 0.039 ↓ <0.001 ↓ 0.072 ↓

K+ 0.004 ↓ 0.917 0.491 0.213

Mg2+ <0.001 ↓ 0.478 ↓ 0.055 ↓ 0.005 ↓

Figure 22—Trends in seasonal sulfate deposition at Glacier 

NADP site.

Figure 21—Trends in VWM concentrations during spring at Glacier 

NADP site.
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-230WWW. 2009 21

Figure 23—Trends in winter VWM NH4

+ concentrations at Lost Trail Pass 

NADP site.

Figure 24—Trends in sulfate deposition during summer at Lost Trail Pass 

NADP site.

Figure 25—Seasonal trends in NH4

+ loading at Clancy NADP site.
22 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-230WWW. 2009

Figure 26—Seasonal trends in NH4

+ at Little Bighorn NADP site.

Figure 27—Seasonal trends in sulfate at Little Bighorn NADP site.

Figure 28—Seasonal summer trend in conductivity at Little Bighorn 

NADP site. 
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-230WWW. 2009 23

Figure 29—Seasonal trends in NH4

+ at Craters of the Moon 

NADP site.

Figure 30—Seasonal trends in sulfate at Craters of the Moon 

NADP site.

Figure 31—Seasonal trends in conductivity at Craters of the Moon 

NADP site.
24 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-230WWW. 2009

Figure 32—Seasonal trends in NH4

+ at Tower Falls NADP site. 

Figure 33—Spring nitrate trend at Tower Falls NADP site.

Figure 34—Seasonal trends in sulfate concentration at Tower Falls 

NADP site.
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-230WWW. 2009 25

Figure 35—Seasonal trends in conductivity at Tower Falls NADP site.

NADP Data Discussion

The NADP data evaluated only accounts for wet 

deposition (total deposition also includes dry and fog 

deposition). In the Northern Rocky Mountains, dry 

deposition can be a substantial component of total 

deposition. Data from CASTNet samplers estimate total 

nitrogen dry deposition in this area to be about 25 to 33 

percent of total deposition (Ingersoll and others 2008).

The NADP samplers (Airochem Metrics) were designed 

to collect rainfall in relatively calm environments; harsher 

environments (commonly found in mountains) often pose 

difficulties for data collection. The NADP equipment 

limitation in winter environments (Goodison and others 

1998; Yang and others 2000), and the inefficient NADP 

sample buckets and rain gage can compromise data 

collection from high elevation sites, particularly at the 

MT97 Lost Trail Pass.

The most significant result of the NADP data analysis 

is the increase trend in ammonia (either concentration 

or deposition) present within at least one season of the 

year for all sites. Fenn and others (2003) and the NADP 

data report (NADP 2007) document consistent increases 

in ammonia deposition and concentration over much of 

the western United States. Ingersoll and others (2008) 

and Bevenger (2008) also documented a moderately 

significant upward trend in ammonium concentration 

at NADP sites in the Northern Rockies subregion. In an 

intensive analysis of NADP trends from 1985 to 2002, 

Lehman (2004) documents a nationwide NH4

+ increase, 

particularly in agriculture areas of the Midwest. The 

percent increase in NH4

+ concentration during the 1985 

to 2002 period was 30 percent at the Glacier NP NADP site, 

57 percent at Clancy, and 46 percent at Yellowstone NP. 

Lehmann and others (2007) found increases in ammonium 

concentrations at NADP stations over most of the United 

States with trends in ammonium to sulfate ratios exceeding 

1.0, creating an ammonia rich environment for more than 

one half of the United States from 2002 to 2004. Fenn 

and others (2003) found that concentrations of N03

–

 and 

NH4

+

 at NADP sites in Oregon and Washington have 

been increasing since monitoring began in 1980. The 

NH4

+

 increase is attributable to increasing fertilizer and 

animal feedlot operations. Campbell (2004) indicates 

that for the Intermountain West, ammonia makes up 

about one third of the total nitrogen deposition at many 

sites. Concentrated animal feedlot operations are a large 

source of NH4

+through volatilization from feedlots, waste 

lagoons, and land-based waste application. Fertilizer 

production is another large source of atmospheric nitrogen. 

Galloway (1995) suggests that N03

– fertilizer production 

has resulted in NH3 emissions and in time can cause 

delayed ecosystem acidification.

The less pronounced nitrate trend (mg/L) found at 

Tower Junction and Glacier during spring is consistent 

with Lehmann and others (2005). They found that in 

the northeast United States, N03

– concentration trends 

have decreased by 25 percent due to the 1990 Clean Air 

Act amendments that mandated emission reductions 

for stationary sources. Lehmann and others (2005), 

however, have also found that N03

–

 concentrations in the 

Rocky Mountains have generally increased, particularly 
26 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-230WWW. 2009

around urban areas with large transportation sources. 

In the western United States, nitrate increases are most 

closely associated with proximity to urban areas (Fenn 

and others 2003). Particularly notable is the Colorado 

Front Range (Nanus and others 2008), where N03

– in 

wet deposition and lakes are elevated. Nanus and 

others (2008) also reported a statistical correlation in 

N03

–

 (p < 0.05) from lakes and N0x emissions within 

300 km from Rocky Mountain NP, Grand Teton NP, 

Great Sand Dunes NP, and Yellowstone NP with the 

strongest correlations in the central and southern 

Rockies in Colorado.

This NADP analysis has documented consistent 

decreasing trends in SO4

2– deposition SO2 emissions 

dissolve in atmospheric water vapor forming sulfurous 

acid (H2SO3), which is rapidly oxidized by dissolved 

O2 to H2SO4 allowing SO4

2– deposition (Kellogg and 

others 1972). This trend is consistent with a 43 percent 

decrease in national SO2 emissions from 1990 to 2007 

and a 24 percent decrease from 2001 to 2007 (EPA 2008). 

The EPA (2008) also documented statistically significant 

decreases in net SO2 emissions found in Glacier NP and 

Yellowstone NP from 1990 to 1999 with at 27 percent 

decrease at both sites. This widespread decrease in SO4

2–

deposition is also a result of the Clean Air Act 1990 

amendment provisions as well as closure and/or emission 

reductions of several smelters and coal burning power 

plants in the western United States. Lehmann and others 

(2005) documented sulfate reduction in the 1985 to 2002 

period at all of the western U.S. NADP sites including 

Glacier NP (47 percent reduction), Clancy (49 percent 

reduction), Yellowstone NP (39 percent reduction), Priest 

Lake (45 percent reduction), and Craters of the Moon 

(66 percent reduction).

Several of the NADP sites showed statistically 

significant decreasing trends in Ca2+, Cl–

, Na+, K+, and 

Mg2+ deposition (p ≤ 0.1). Recent trends in Colorado 

report 9 of 10 high elevation NADP sites had statistically 

significant decreasing Na+ and Cl– (p ≤ 0.01) (Mast, 

personal communication). These findings are also 

consistent with reported declines in base cations for the 

eastern United States and parts of Europe (Hedin and 

others 1994). In 1990 the Clean Air Act Amendments 

put stronger restrictions on emissions. In 1994 a change 

was made in the type of filter used for NADP protocol/

procedures at the CAL (Lynch and others 1996). Both of 

these changes may account for a portion of the cation and 

anion decreases observed, but not all. Other environmental 

factors contributing to cation and anion decreases may 

be due to overall emission decreases but are not readily 

explained.

IMPROVE Visibility Analysis 

and Trends _____________________

Air pollution has significantly impacted visibility 

throughout many National Parks and Wilderness areas. 

Visibility in USFS R1 has been monitored in coordination 

with the Interagency Monitoring of Protected Visual 

Environments (IMPROVE) program (http://vista.cira.

colostate.edu/improve/) since 1988. Many IMPROVE 

monitors were established in MT during 2000, figure 36 

shows locations of IMPROVE sites in R1 and figure 37 

shows an example of an IMPROVE station. Trend data 

can be graphed using this website but the data was only 

available through 2004 at the time of this report.

The USFS currently operates four IMPROVE sites in 

Region 1: CABI1 (which monitors visibility for the 

CMW), GAMO1 (GMW), MONT1 (Wilderness Class I 

areas: BMW, MMW, and SGW, and Wilderness Class II 

areas: RW and WCW), and SULA1 (APW and SBW). 

Three additional IMPROVE sites are in close proximity and 

can also be used for wilderness airshed analysis: GLAC1 

(located at Glacier National Park and closest to the GBW), 

YELL2 (located at Yellowstone National Park and closest 

to the ABW and LMW), and HECA1 (located in the Hells 

Canyon National Recreation Area and closest to the GHW). 

Data was analyzed for the following seven IMPROVE sites 

mentioned above: CABI1, GAM01, GLAC1, HECA1, 

MONT1, SULA1, and YELL2. All of these sites are valley 

bottom to lower slopes except for GAM01 and SULA1, 

which are on the summit of small peaks.

Fine particulate matter is a major contributor to 

reduced visibility (haze). Particulates can occur from 

natural sources such as volcanoes, dust, and wildland 

fires or from anthropogenic sources including industrial, 

agricultural, vehicles, municipalities, prescribed fire and 

agricultural burning. Fine particles both absorb and reflect 

light. Absorption and scattering of light affects haze color 

and visibility reduction. The type (sulfates, nitrates, etc.) 

and the condition (humid, dry, etc.) of the pollution particle 

affect how much light is scattered.

The deciview unit (dv) is a haze index that is a measure 

of visibility derived from calculated light extinction 

measurements. Uniform changes in the haze index correspond to uniform incremental changes in visual perception across the entire range of conditions from pristine to 

highly impaired. The haze index (dv) is calculated directly 

from the total light extinction (best expressed in inverse 

megameters, Mm-1): HI = 10 in (bext/10). Deciview decreases 

as standard visual range (SVR) increases. Examples of 

high and low visibility days and corresponding dv and 

SVR for Yellowstone NP (YELL2) are shown in figure 38.
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-230WWW. 2009 27

Figure 36—IMPROVE monitoring site locations relative to wilderness areas in USFS R1.

Figure 37—Monture Guard Station 

IMPROVE site (MONT1), Lolo National 

Forest. This site is slightly influenced 

by emission sources in the Bitterroot 

valley, particularly Missoula. This site 

houses four modules that pump air in 

24 hour periods on Wednesdays and 

Saturdays. Filters are changed each 

Tuesday then sampled for a wide variety 

of chemical air quality constituents. A 

visibility camera associated with the site 

is located at Ovando, Montana.
28 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-230WWW. 2009

GLAC1 (all parameters), YELL2 (all parameters), and 

SULA1 (SO4

2– , Esoil, Salt, and MF only) are the only 

IMPROVE sites with >8 years of data. Data collection at 

CAB1, GAMO1, HECA1, and MONT1 began in 2000. 

Eight observations are the minimal number suggested in 

the Data Analysis Protocol to run the Mann-Kendall and 

Seasonal Mann-Kendall tests, though more observations 

Figure 38—Yell2 IMPROVE Spectrum Series photos in Yellowstone National Park on a 

clear day (top photo) and on a hazy day (bottom photo). The clear day photo has a dv = 0, 

Bext = 10, SVR = 390, and the hazy day has a dv = 17, Bext = 52, SVR = 75.

increase the confidence of the test. Trends in ESO4, 

ENO3, EOMC (organic mass from carbon), Esoil (fine 

soil), ECM (coarse mass), ELAC (light absorbing carbon), 

Esea_salt (documented as salt in tables), Rbext (sum aerosol 

extinctions), SVR, dv, MF (PM2.5), MT (PM10) were tested 

(table 18).
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-230WWW. 2009 29

Table 18—IMPROVE parameter symbols and definitions. 

Parameter Definition

ESO4 Sulfate extinction Mm-1

ENO3 Nitrate extinction Mm-1

EOMC Organic Mass from Carbon Mm-1

Esoil Fine Soil Mm-1

ECM Coarse Mass Mm-1

ELAC Light Absorbing Carbon Mm-1

Esea_salt Sea salt Mm-1 

Rbext Sum aerosol extinctions Mm-1

SVR Standard Visibility Range km

dv Deciview dv

MF PM2.5 μg/m3

MT PM10 μg/m3

E prefix Extinction coefficient Mm-1

*Esoil is referred to as SOIL in graphs, tables and text.

*Esea_salt is referred to as salt in graphs, tables, and text.

Annual IMPROVE Site Trends

SVR increased significantly at GLAC1 and YELL2. 

Significant decreases in sulfate and nitrate were present 

at GLAC1. EOMC, ECM, salt Rbext, dv, MF, MT, and 

ELAC had decreased trends at GLAC1. YELL2 had 

decreased trends in EOMC, Esoil, ECM, MF and MT. 

MF decreased at SULA1. Trend direction and p-values 

are recorded in table 19. The values based on less than 

eight observations are displayed in pink cells to qualify the 

values as provisional until the database receives sufficient 

additional monitoring data to achieve eight observations. 

Selected graphs are illustrated in figures 39 to 42.

Seasonal Trends at IMPROVE Sites With 

at Least 8 Years of Data

GLAC1, YELL2, and SULA1 were analyzed with the 

Mann-Kendall test to evaluate statistically significant 

trends for each parameter through each season (winter, 

spring, summer, and fall). Results are presented in 

tables 20 to 22 and figures 43 to 56. Figures 57 to 62 

show the 25 percent best and worst SVR and dv days at 

GLAC1, YELL2, and SULA1.

Table 19—Statistically significant annual IMPROVE trends found with the Mann-Kendall light blue cells and with 

Seasonal Mann-Kendall tests yellow cells are bolded. The grey cells indicate parameters that were 

not available. Pink cells are possible trends run with the Mann-Kendall test that are not validated/statistically sound because there are less then eight observations. P values < 0.1 signify a trend, ↑ and ↓

signifies increasing and decreasing trends/Sen’s Slope direction. IMPROVE parameter units are listed 

in table 18.

Parameter CABI1 GAMO1 GLAC1 MONT1 SULA1 YELL2 HECA1

 ESO4 0.23 1 0.035 ↓ 0.764 0.2 0.798 0.368

 ENO3

– 0.036 ↓ 0.016 ↓ 0.044 ↓ 0.016 ↓ <0.001 ↓ 0.199 0.23

 EOMC 0.548 1 0.018 ↓ 0.764 <0.001 ↓ 0.033 ↓ 0.764

 Esoil 1 1 0.766 0.548 0.629 0.073 ↓ 0.548

 ECM 0.368 0.548 0.006 ↓ 0.23 0.002 ↓ 0.087 ↓ 0.764

 Salt 0.133 1 0.041 ↓ 0.23 0.428 0.756 0.072 ↓

 Rbext 0.368 0.764 0.012 ↓ 0.133 <0.001 ↓ 0.124 0.764

 SVR 0.133 0.072 ↑ 0.022 ↑ 0.036 ↑ 0.003 ↑ 0.040 ↑ 0.133

 dv 0.133 0.23 0.004 ↓ 0.133 <0.001 ↓ 0.123 0.23

 MF 0.23 0.23 <0.001 ↓ 0.133 0.0572 ↓ 0.003 ↓ 0.764

 MT <0.001 ↓ 0.133 <0.001 ↓ 0.016 ↓ 0.548

 ELAC 1 1 0.011 ↓ 0.548 <0.001 ↓ 0.392 0.764
30 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-230WWW. 2009

Figure 39—Trends in annual NO3

–

 at IMPROVE sites. *Only GLAC1 site is statistically 

validated with at least 8 observations.

Figure 40—Trends in annual ECM at IMPROVE sites.

Figure 41—Trends in annual SVR at IMPROVE sites.
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-230WWW. 2009 31

Figure 42—Trends in annual MT and MF at IMPROVE sites.

Table 20—GLAC1 IMPROVE site Mann-Kendall p-values for each season. Highlighted cells indicate 

statistically significant trends using p < 0.1.

Parameter Winter Spring Summer Fall 

 ESO4 0.363 1 0.003 ↓ 0.050 ↓

 ENO3 0.442 0.002 ↓ 0.093 ↓ 0.944

 EOMC 0.006 ↓ 0.142 0.401 0.184

 Esoil 0.025 ↓ 1 0.093 ↑ 0.944

 ECM 0.003 ↓ 0.401 0.726 0.050 ↓

 ELAC 0.030 ↓ 0.401 0.442 0.005 ↓

 salt 0.142 0.294 0.889 0.184

 Rbext 0.025 ↓ 0.142 0.675 0.093 ↓

 SVR 0.624 0.069 ↑ 0.944 0.021 ↑

 dv 0.042 ↓ 0.059 ↓ 0.889 0.050 ↓

 MF 0.003 ↓ 0.036 ↓ 1 0.080 ↓

 MT 0.030 ↓ 0.401 0.442 0.005 ↓
32 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-230WWW. 2009

Table 22—SULA1 IMPROVE site Mann-Kendall p-values for each season. Highlighted cells indicate 

statistically significant trends using p < 0.1.

Parameter Winter Spring Summer Fall 

 ESO4 0.115 0.304 0.077 ↓ 0.200

 Esoil 0.537 1 0.760 1

 salt 0.837 0.016 ↓ 0.855 0.300

 MF 0.064 ↓ 0.115 0.855 0.502

Table 21—YELL2 IMPROVE site Mann-Kendall p-values for each season. Highlighted cells indicate 

statistically significant trends using p < 0.1.

Parameter Winter Spring Summer Fall

 ESO4 1 0.152 0.161 0.756

 ENO3 0.466 0.283 0.756 0.276

 EOMC 0.076 ↓ 0.210 1 0.160

 Esoil 1 1 0.120 0.120

 ECM 1 1 0.213 0.062 ↓

 ELAC 0.917 0.721 0.756 0.161

 salt 0.754 0.858 0.276 0.436

 Rbext 0.917 0.721 0.436 0.013 ↓

 SVR 0.917 1 0.161 0.013 ↑

 dv 0.754 0.721 0.276 0.020 ↓

 MF 0.048 ↓ 0.474 0.350 0.029 ↓

 MT 0.118 0.721 0.436 0.062 ↓

Figure 43—Seasonal trends in Rbext at GLAC1 IMPROVE site.
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-230WWW. 2009 33

Figure 44—Seasonal trends in SO4

2– at GLAC1 IMPROVE site.

Figure 45—Seasonal trends in NO3

–

 at GLAC1 IMPROVE site.

Figure 46—Winter trend in EOMC at GLAC1 IMPROVE site.
34 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-230WWW. 2009

Figure 47—Seasonal trends in Esoil at GLAC1 IMPROVE site.

Figure 48—Seasonal trends in ECM at GLAC1 IMPROVE site.

Figure 49—Seasonal winter trend in EOMC at YELL2 IMPROVE site.
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-230WWW. 2009 35

Figure 52—Seasonal trends in MF at YELL2 IMPROVE site.

Figure 50—Seasonal fall trend in ECM at YELL2 IMPROVE site.

Figure 51—Seasonal fall dv trend at YELL2 IMPROVE site. 
36 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-230WWW. 2009

Figure 53—Seasonal fall MT trend at YELL2 IMPROVE site.

Figure 54—Seasonal summer trend in SO4

2– at SULA1 IMPROVE site.

Figure 55—Seasonal spring trend in salt at SULA1 IMPROVE site.
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-230WWW. 2009 37

Figure 56—Seasonal winter trend of MF at SULA1 IMPROVE site.

Figure 57—SULA1 SVR 20% best and 

worst days. *Not statistically validated 

because only 6 observations are 

available (at least 8 observations are 

needed for statistical significance). For 

this graph summer includes the months 

of July, August, and September.

Figure 58—SULA1 dv 20% best and 

worst days. *Not statistically validated 

since only 5 observations are available 

(at least 8 observations are needed for 

statistical significance). For this graph 

summer includes the months of July, 

August, and September.
38 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-230WWW. 2009

Figure 59—GLAC1 SVR 20% best and worst days. For this graph summer includes the 

months of July, August, and September.

Figure 60—GLAC1 dv 20% best and worst days. For this graph summer includes the 

months of July, August, and September.

Figure 61—YELL2 SVR 20% best and worst days. For this graph summer includes the 

months of July, August, and September.
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-230WWW. 2009 39

IMPROVE Data Discussion

The USFS R1 IMPROVE data provided evidence 

of improving visibility through the period of record. A 

consistent reduction in dv and increase in SVR occurred 

at all sites and for all seasons analyzed. The analysis also 

documented a general decrease in SO4

2–, NO3–

, ECM, fine 

soil, EOMC, MF (PM2.5), and MT (PM10). Generally the 

lowest visibility (highest RBext and highest dv) occurred 

in 2000 and 2003, which were robust wildland fire years 

in Idaho and Montana. IMPROVE data from the massive 

wildland fire years of 2006 and 2007 in Montana and 

Idaho were not available at the time of this report.

The USFS R1 analysis is generally consistent with 

EPA (2008) findings that no Class 1 IMPROVE sites 

had statistically significant upward trends for any of the 

extinction parameters evaluated. Visibility during the 

20 percent best, median, and worst days improved at all 

sites except at Glacier NP, where visibility deteriorated 

during the worst 20 percent of days, presumably due 

to the massive Glacier NP wildfires in 2000 and 2003. 

Green and Xu (2006) concluded that Glacier NP had 

reduced extinction coefficients for the 20 percent best 

visibility days and middle 60 percent days, but increased 

extinction coefficients for the 20 percent worst days. 

The Green and Xu (2006) analysis also concluded that 

Glacier NP had an increasing trend in organic carbon, 

fine soil, and nitrate on the 20 percent worst days. The 

EPA (1996) indicated that the greatest concentration of 

organic carbon and associated particulate extinction that 

occurred in the northwestern United States (with 50 to 

60 percent of extinction due to carbon) was at SULA1 

and MONT1.

Decreasing seasonal Rbext trends were present during 

winter and fall at GLAC1 and fall at YELL2. The EPA 

(1996) reported that the Rbext in the northwestern United 

States urban regions peaked in the winter due to increased 

light scattering from ammonium nitrite and organics 

(presumably due to winter inversions). The ammonium 

sulfate light scattering in the northwestern United States 

is unique in that it does not peak in the summer months; 

in Boise, Idaho, and Missoula, Montana, sulfate light 

scattering peaks in the coldest months (Debelle 2006). 

These general decreasing Rbext trends are consistent with 

the overall pattern of increasing SVR and decreasing dv 

in the northwestern United States.

Overall Conclusions _____________

Due to limited sampling dates, period of record, 

and/or lack of seasonal data, trend interpretation is 

difficult for much of the USFS R1 lake monitoring. Lake 

ANC decrease was not statistically validated except at 

Stepping Stone Lake. The pH increasing trend and decrease 

in lake cation trends are not readily explained. Continued 

monitoring and expansion of the period of record may allow 

clearer trend definitions of lake chemistry in the future.

The most consistent finding in the data analysis was 

the consistent ammonia increase trend at NADP sites. 

This trend is occurring over much of the western United 

States and may be partially due to increased agriculture 

emissions such as feedlots in Montana, Idaho, eastern 

Washington, and eastern Oregon. The nitrate increases 

at the NADP sites and in the lakes is not as consistent as 

the ammonia increase at the NADP sites.

Figure 62—YELL2 dv 20% best and worst days. For this graph summer includes the 

months of July, August, and September.
40 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-230WWW. 2009

The decrease in SO4

2– at NADP sites in R1 is consistent 

with overall U.S. trends during the last two decades 

coinciding with reduced industrial sulfate, largely due 

to reductions in powerplant emissions.

Visbility improvements, evidenced by increased 

SVR, decreased dv, and reduced light extinction were 

observed at most of the IMPROVE sites. The decreasing 

SVR at some of the sites on the 20 percent worst days 

corresponded to years with large wildland fires (regional 

and local) since 2000 and periodic significant visibility 

reduction due to smoke. Overall, IMPROVE chemistry 

and visibility trend data correlated well with wildland 

fire emissions.

The trends reported above should be used only as 

indicators of possible current and future changes in air 

quality, water chemistry, and ecosystem health. Because 

the periods of record for the datasets are short, the trends 

identified may change in the future as more data is 

collected. Continued analysis will be required to monitor 

current trends and help determine their causes.

Considerations _________________

High elevation lakes in USFS R1 may remain frozen 

through much of the year and initial ice-free conditions 

can vary from mid-June to early August. This, along 

with difficult access, makes multiple sampling during 

different hydroperiods each year logistically difficult. 

A recommended solution to deal with seasonality that 

affects lake chemistry is to sample each lake once 

during the same hydroperiod each year. To gain a more 

comprehensive and accurate knowledge of lake chemistry 

flux dynamics, samples of each lake’s inlet, outlet, and 

hypolimnion could be added to the current sampling 

protocol. This would be most physically appropriate 

for North Kootenai Lake, Lower Libby Lake, and the 

NE inlet and outlet of Twin Island Lake. Coring of lake 

sediments shows promise to understanding trends of metal 

accumulation from atmospheric deposition sources and 

nitrogen critical loads (Baron and others 1986). Recent 

research has explored the utility of high-elevation lake 

sediment coring and the relationship between shifting 

diatom communities, hindcasting nitrogen emissions 

and population growth, and then deriving critical loads 

(Baron 2006). Coring of at least one of the Phase 3 lakes 

in each of the ABW, CMW, and SBW for metal, diatom, 

and nitrogen analysis could be diagnostic of long-term 

air quality trends and help determine critical load values 

for sensitive ecosystems in USFS R1.

In USFS R1, NADP provides the largest dataset for 

air-quality analysis. Although trends were analyzed, there 

is much analysis that could be done with the data at the 

site and regional level. For example, NADP deposition 

(kg/ha) data can be used in conjunction with critical load 

levels of nitrogen and sulfur for R1 to better identify 

and predict ecosystem health and anthropogenic threats. 

Continued monitoring of the Lost Trail Pass NADP site 

is recommended since the site is the only high elevation 

NADP site in Idaho or Montana and a key atmospheric 

deposition site for several R1 Class I and Class II 

wilderness areas. Although not directly tied to USFS R1 

funding, the other NADP sites evaluated in this report are 

particularly valuable to the USFS R1 air quality program.

IMPROVE monitoring provides an invaluable historic 

and current look at visibility conditions (including 

wildland fire smoke) that can be useful in assessing 

impacts on and visibility violations of Class I and II 

airsheds and for regional haze analysis. Currently most of 

the IMPROVE sites do not have enough data to undergo 

rigorous statistical analysis. It is highly recommended 

that all the USFS R1 IMPROVE sites continue to be 

operated. In 2010, the data from R1 IMPROVE sites 

should be re-analyzed for statistically validated trends. 

IMPROVE is a very important tool to monitor forest 

ecosystem health, especially in the R1 Wilderness areas 

where visibility is the main AQRV.

This report did not review the USFS R1 air quality 

(AQRV) lichen monitoring (Story and others 2008) or 

the USGS snow chemistry sampling network along the 

Rocky Mountains (Ingersoll and others 2008). Lichens 

are useful indicators of long term pollution impacts, and 

are typically sampled every 5 to 8 years. Lichens were 

initially sampled from 1992 to 1994, were re-sampled 

from 2000 to 2003, and are currently (2007 to 2010) 

being re-sampled again. Lichens can provide useful air 

quality information, specifically on sulfur and nitrogen 

compounds and metals. The lichen data are a valuable 

addition to the lake chemistry, deposition, and visibility 

information in this report.

The USFS Snow Chemistry sampling network provides 

the only air quality related sampling directly adjacent 

to some of the USFS Wilderness areas and is useful for 

winter bulk deposition analysis. It is recommended the 

USFS R1 continue support of and coordination with the 

USGS Snow Chemistry sampling program (Ingersoll 

and others 2008).

Additional information for both programs can be found 

at USFS R1 air quality website (http://www.fs.fed.us/r1/

gallatin/resources/air/aq_plans/).
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-230WWW. 2009 41

Acknowledgments_______________

Many people helped shape and make this report possible: 

Greg Bevenger (USFS Shoshone NF), Scott Copeland 

(CIRA, Lander), Thomas Dzomba(USFS R1), Linda 

Geiser (USFS R6), Rick Graw (USFS R6) , Joe Gurrieri 

(USFS R4), Alisa Mast (USGS-CWSC, Denver), Laurie 

Porth (USFS-RMRS), Terry Svalberg (USFS BridgerTeton NF), John Zachariassen (USFS-RMRS), and Peter 

Landis (USFS-RMRS).

References _____________________

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Methods for the Examination of Water and Wastewater, 

17th Ed. American Public Health Association, Washington, DC.

Baron, J.S. 2006. Hindcasting nitrogen deposition to determine an 

ecological critical load. Ecological Applications. 16(2): 433-439.

Baron, J.S.; Norton S.A.; Beeson D.R.; Herrmann R. 1986. Sediment 

diatom and metal stratigraphy from Rocky Mountain Lakes with 

special reference to atmospheric deposition. Can. J. Fish. Aquat. 

Sci. 43: 1350-1362.

Bevenger, G. 2008. Shoshone National Forest. Comprehensive 

Evaluation Report, Version 2.0: 1-104.

Campbell, D.H. 2004. Atmospheric Deposition and Its Effects in the 

Intermountain West. Session V. North American Regional Impacts 

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N.E.; Turk J.T. 1995. Processes controlling the chemistry of two 

snowmelt-dominated streams in the Rocky Mountains. Water 

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DeBell, L.J. 2006. Spatial and Seasonal Patterns and Temporal 

Variability of Haze and its Constituents in the United States. 

Report IV. CIRA ISSN 0737-5352-74, Colorado State University, 

Fort Collins, Colorado.

Downing, D.; Clark, J. 1997. Statistics: The Easy Way. Baron’s 

Educational Series Inc. USA. pg. 194-200.

Eilers, J.M. 2003. Water Quality Review of Selected Lakes in the 

Northern Rocky Mountains. J.C. Headwaters, Bend, OR. http://

www.fs.fed.us/r1/gallatin/resources/air/monitoring/lakes/.

EPA. 1987. Handbook of Methods for Acid Deposition Studies: 

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026. Washington, DC: Environmental Protection Agency.

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EPA. 2008. National Air Quality, Status and Trends through 2007. 

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Agency. Online: http://www.epa.gov/airtrends/2008/index.html.

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Fenn, M.E.; Haeuber, R.; Tonnesen, G.S.; Baron, J.S.; GrossmanClarke, S.; Hope, D.; Jaffe, D.A.; Copeland, S.; Geiser, L.; Rueth, 

H.M.; Sickman, J.O. 2003. Nitrogen Emeisssions, Deposition, 

and Monitoring in the Western United States. Bioscience. Vol. 53 

(4): 391-404.

Galloway, J.N. 1995. Acid Deposition: Perspectives in Time and 

Space. Water, Air and Soil Pollution 85: 15-24.

Gilbert, R.O. 1987. Statistical Methods for Environmental Pollution 

Monitoring. John Wiley & Sons, Inc., New York.

Goodison, B.E.; Louie, B.Y.T.; Yang, D. 1998. WMO solid Precipitation 

intercomparison, Final Report, world Meteorological organization, 

Geneva, Switzerland, WMO/TD 872: 212.

Graw, R. (Personal communication). 2008. Phone calls June 2008. 

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OR 97204.

Green, M.; Xu J. 2006. Visibility Trends Analysis for IMPROVE Sites 

in the Western U.S. Desert Research Institute. http://coha.dri.edu/

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