A Screening procedure to evaluate air pollution effects on Class I wilderness areas

Historic, Archive Document

Do not assume content reflects current
scientific knowledge, policies, or practices.

United States
Department of
Agriculture

Forest Service

Rocky Mountain
Forest and Range
Experiment Station

A Screening Procedure to Evaluate

Air Pollution Effects on
Class I Wilderness Areas

Fort Collins,
Colorado 80526

General Technical
Report RM-168

u4s(

Douglas G. Fox, Ann M. Bartuska,
James G. Byrne, Ellis Cowling,
Richard Fisher, Gene E. Likens,
Steven E. Lindberg, Rick A. Linthurst,
Jay Messer, and Dale S. Nichols

Base cations - Ca + Mg + K + Na (adjusted for marine influence)
jieq/l

917257

Fox, Douglas G.; Bartuska, Ann M.; Byrne, James G.; and others.
1989. A screening procedure to evaluate air pollution effects on
Class I wilderness areas. Gen. Tech. Rep. RM-168. Fort Collins,
CO: U.S. Department of Agriculture, Forest Service, Rocky
Mountain Forest and Range Experiment Station. 36 p.

This screening procedure is intended to help wilderness
managers conduct "adverse impact determinations" as part of
Prevention of Significant Deterioration (PSD) applications for sources
that emit air pollutants that might impact Class I wildernesses. The
process provides an initial estimate of susceptibility to critical
loadings for sulfur, nitrogen, and ozone. It also provides a basis for
requesting necessary additional information where potential adverse
impacts are identified.

Keywords: Prevention of Significant Deterioration, air pollution

On the Cover:

Foreground: The screening graph for determining effects of
atmospheric deposition on aquatic ecosystems (fig. 1, page 6).
Background: West Glacier Lake, part of the Glacier Lakes
Ecosystem Experiments Site (GLEES), a high-elevation area that,
while not a designated wilderness, is being used for research to
quantify atmospheric effects on wilderness. GLEES is instrumented
for meteorological, aerometric, deposition, snowmelt, and streamflow
measurements as part of a holistic ecosystem monitoring program
conducted by the air polution research unit at the Rocky Mountain
Station. GLEES is located on the Medicine Bow National Forest,
approximately 15 km west of Centennial, Wyoming, in the Snowy
Range Mountains.

USDA Forest Service

General Technical Report RM-168

January, 1989

A Screening Procedure to Evaluate
Air Pollution Effects on
Class I Wilderness Areas

Douglas G. Fox1, Ann M. Bartuska,
James G. Byrne, Ellis Cowling,
Richard Fisher, Gene E. Likens,
Steven E. Lindberg, Rick A. Linthurst,
Jay Messer, and Dale S. Nichols

'Rocky Mountain Forest and Range Experiment Station. The Station's headquarters is in
Fort Collins, in cooperation with Colorado State University. Supervision was provided by
Douglas G. Fox, Chief Meteorologist and Project Leader for The Research Work Unit,
Effects of Atmospheric Deposition on Natural Ecosystems in the Western United States.

Contents

Page

INTRODUCTION 1

Workshop Organization and Participants 1

Federal Land Managers' Responsibilities Concerning Protection of

Class I Area Wilderness 2

Wilderness Act 2

Clean Air Act 3

WORKSHOP RESULTS 4

The Green-Yellow-Red Screening Model 4

Terrestrial Green and Red Line Screening Numbers 5

Aquatic Green and Red Line Screening Graph 5

Implementing the Screening Technique 7

Information Needs 7

Monitoring Considerations 8

Meteorology 8

Ambient Air Concentration 8

Deposition 8

General Considerations for Data Collection 9

Quality Assurance and Quality Control 9

SPECIFIC FACTORS AND CONSIDERATIONS IN DEVELOPING THE

MODEL 9

Terrestrial Systems 9

Rationale Used in Selecting Ozone Values 10

Rationale Used in Selecting Sulfur Values 11

Rationale Used in Selecting Nitrogen Values 11

Aquatic Systems 12

Concept of Surface Water Sensitivity 12

Acidification Response Levels 13

S and N Loadings 14

Illustration of Graph Use 14

Information Needs 14

Cautions 15

LITERATURE CITED 15

APPENDIX A. MAP OF FOREST SERVICE CLASS I AREAS 18

APPENDIX B. BACKGROUND OF SAMPLE CLASS I AREAS 20

Alpine Lakes and Glacier Peak Wilderness - Washington 20

Hoover and Dome Land Wilderness - California 20

San Gorgonio Wilderness - California 21

Bob Marshall Wilderness - Montana 22

Bridger Wilderness - Wyoming 22

Superstition Wilderness - Arizona 23

Joyce Kilmer-Slickrock Wilderness - North Carolina, Tennessee 23

Otter Creek - West Virginia and Great Gulf - New Hampshire

Wildernesses 24

Boundary Waters Canoe Area Wilderness - Minnesota 25

APPENDIX C. OTHER AQUATIC MEASUREMENT METHODS 27

Loading/Response Relationships 27

Graph Construction 27

Detailed Information Needs 30

Conversion of Deposition Values 34

APPENDIX D. PARTICIPANTS AND THEIR AFFILIATIONS 35

PREFACE

ACKNOWLEDGMENTS

A group of scientists and land managers held a
cooperative workshop to help the Forest Service
develop a screening process tor evaluating Prevention
of Significant Deterioration (PSD) applications for
sources that might impact Class I area wildernesses.
The process described in this document provides an
initial estimate of the susceptibility of different Class I
areas to critical loadings for sulfur, nitrogen, and
ozone. Results should help Forest Service land
managers when conducting "adverse impact
determinations" of PSD permit applications and provide
a ready basis for requesting necessary additional
information where potential adverse impacts are
identified.

This document was prepared by the authors and
participants at the Workshop on Air Pollution Effects on
Wilderness, held May 2-5, 1988, at the Institute of
Ecosystem Studies, Millbrook, New York.

Dr. Gene Likens and his co-workers at the Institute
of Ecosystems Studies, New York Botanical Gardens,
hosted the workshop at the Mary Flagler Cary
Arboretum in Millbrook, NY. The participants at the
May 1988 meeting in Millbrook developed the concept
of this document, and the authors wrote the first draft.
All the participants reviewed a second draft. A final
step involved the review of 8 scientific peers who were
not at the meeting, but by virtue of both their research
and their positions with government, industry, and
interested groups, were able to substantially improve
the document. Finally, scientists at the Rocky Mountain
Station conducting research on effects of atmospheric
deposition on natural ecosystems, particularly Frank
Vertucci, Robert Musselman, and Anna Schoettle
added significantly to the final report by evaluating and
incorporating reviewers' comments, correcting
references, and providing the benefit of their
substantial knowledge and experience to the final
report.

USER NOTES

When implementing the PSD review process, line
officers and staff must understand the assumptions
and variables used to construct the screening model.
The model will help in PSD review only if the
assumptions and logic involved are fully understood. It
is critical that the user recognize the development
methodologies and limitations. For instance,
participating scientists and managers agreed on similar
numerical loadings for a pollutant in seemingly different
Class I areas. This agreement resulted because
similarly sensitive ecosystems occur in many different
Class I areas, although not to the same extent. For
example, alpine is the dominant ecosystem in Alpine
Lakes Wilderness in northern Washington, but a minor
portion of the San Gorgonio Wilderness in southern
California. However, the loading values for these two

wildernesses are the same because the alpine
ecosystem was considered most sensitive, and the
loadings were established to protect the most sensitive
ecosystems.

It should also be recognized that the loadings
suggested by this screening technique are likely to
overestimate potential impacts. As such, they may be
applicable for PSD permit review of effects on
designated Class I air quality areas, but are not
intended to suggest target loadings on ecosystems in
general.

Users should recognize that this document
represents the state of understanding in Spring 1988.
Science is very productive in this field, and it is
anticipated that this document will be upgraded
periodically.

A Screening Procedure to Evaluate
Air Pollution Effects on
Class I Wilderness Areas

Douglas G. Fox, Ann M. Bartuska,
James G. Byrne, Ellis Cowling,
Richard Fisher, Gene E. Likens,
Steven E. Lindberg, Rick A. Linthurst,
Jay Messer, and Dale S. Nichols

INTRODUCTION

Forest Service land managers need information
about the effects of air pollution on wilderness areas
that have been formally designated as Class I by the
Clean Air act (Public Law 95-95). Managers of Class I
areas are responsible for the review of preconstruction
applications termed "Prevention of Significant
Deterioration" (PSD) permits. Forest Service managers
must review PSD permits for major new emission
sources (more than 100 tons of a pollutant per year) or
the modification of an existing source that may cause
possible effects on Class I areas.

This introductory section describes a workshop of
Forest Service management leaders and prominent
scientists studying the biological effects of air pollution
and acid deposition. They worked together to identify
how best to merge the current state of science with
needs of Class I area managers. (Work group
participants are also identified.) It then briefly describes
Forest Service responsibilities under the Clean Air Act
and the Wilderness Act.

The second section summarizes the major results
of the workshop. Results are stated as proposed
maximum acceptable pollutant loadings on specific
ecosystems. These maximum loadings are intended
for use by federal land managers screening PSD
permits. The proposed screening process suggests
one of three decisions: recommend permit approval
(new pollutants will lead to loadings below Green Line),
recommend permit denial (new pollutants will lead to
loadings above Red line), and an intermediate zone
(Yellow Zone), where more data are needed before
deciding on a course of action.

The screening concept uses numerical values of
sulfur and nitrogen deposition and ozone
concentrations in nine different wildernesses
considered representative of the diversity of wilderness
ecosystems.

The third and fourth sections provide detailed
explanations, justifications, and cautions regarding the
screening approach as applicable to aquatic and
terrestrial ecosystems in wilderness landscapes.

Workshop Organization and Participants

A partnership between scientists and managers is
needed to protect air-quality-related values in Class I
area wildernesses. The form of such a partnership was
developed and approved by some 70 distinguished
scientists at the 1987 Cary Conference^ which
focused on long-term studies of ecosystems:

"Ecological understanding is required to develop
environmental policies and to manage resources for
the benefit of humankind. Sustained ecological
research is one of the essential approaches for
developing this understanding, and for predicting
the effects of human activities on ecological
processes. Sustained research is especially
important for understanding ecological processes
that vary over long periods of time. However, to
fulfill its promise, sustained ecological research
requires a new commitment on the part of both
management agencies and research institutions.
This new commitment should include longer funding
cycles, new sources of funding, and increased
emphasis and support from academic and research
institutions. Because they have common long-term
goals, we propose a new partnership between
scientists and resource managers. Elements of this
partnership include:

1. Agreement by scientists to answer the
questions asked by managers, while making
clear the level of uncertainty that exists and
what additional research needs to be done.

^Statement adopted at the Cary Conference in Millbrook, New
York, on May 1 3, 1987: revised July 4, 1987 (Likens in press).

1

2. Agreement by managers to give serious
consideration to these answers and to support
the continuing research toward better answers.

Sustained ecological research supported by this

new partnership can contribute significantly to the

resolution of critical environmental problems."

Such partnerships are essential to use scientific
information in an orderly and efficient manner for the
management of complex natural resources.

Organizers of this workshop invited a group of
prominent scientists, knowledgeable in the areas of
effects of air pollution (sulfur and nitrogen deposition
and ozone exposure) on ecosystems, to interact with a
group of Forest Service managers who have air
resource management responsibilities. The objectives
of this workshop were to establish communication
between these two groups of individuals, and to
develop a screening process for evaluating PSD
applications. This relationship was fostered by a 3-day
workshop at the Institute of Ecosystem Studies of the
New York Botanical Garden in Millbrook, New York.

The May 1988 workshop was to develop an air
pollution screening process for managers of Class I
areas. The participants decided that a screening
process that considered only the impacts of the
deposition of sulfur and nitrogen and ozone
concentration on specific ecosystems would be
appropriate. Other pollutants can adversely affect
ecosystems, but the chosen pollutants are those most
commonly of concern. Pollutant loadings are
determined by using air dispersion models and
estimates of deposition velocity to project the worst
case deposition of S and N from proposed industrial
emissions.

Four teams of scientists and managers (see table
1) were formed to determine independently the sulfur,
nitrogen, and ozone values to be used in answering
the following questions:

1. Below what magnitude of sulfur and nitrogen
deposition and ozone concentration, resulting from
proposed air pollution emissions, for each of the nine
Class I area wildernesses, can a land manager have a
high degree of confidence that no air-quality-related
values (AQRV's) would be adversely affected?

2. Above what magnitude of sulfur and nitrogen
deposition and ozone concentration for each of the
nine Class I area wildernesses can a land manager
have a high degree of confidence that at least one of
the selected air-quality-related values would be
adversely affected by the proposed air pollution
emissions?

The Forest Service managers present at the
Workshop picked tentative AQRV's (or reported those
already developed in Forest Plans) for the selected
wildernesses in their Regions. These AQRV's were
then used by the teams and working groups in the

development of their loading estimates. Also, each
Class I area wilderness was described. Appropriate
site data and first-hand knowledge were used to
estimate numerical loadings and identify problems in
applying these numbers to specific areas. Values were
chosen to protect the current condition of the selected
AQRV's in each Class I area.

Visibility is the only AQRV specifically mentioned in
the Clean Air Act, and it has been determined to be an
important AQRV in all class I areas except Bardwell
Bay (FL) and Rainbow Lake (Wl). However, this
workshop did not address visibility. The scientists,
known for their expertise in air pollution effects on
biotic systems, were invited to this workshop to
develop screening guidelines for only the terrestrial
and aquatic components of the ecosystem. The
absence of comments on visibility should not be
construed as a judgment of its relative value compared
to biotic systems. In fact, in some areas, visibility might
be considered adversely affected by air pollution
concentrations that were not considered adverse to the
biotic systems. For more discussion of visibility, the
Forest Service Air Resource Management Manual
(USDA 1987) should be consulted.

Federal Land Managers' Responsibilities
Concerning Protection of Class I Area
Wildernesses

Wilderness Act

The Wilderness Act of 1964 (Public Law 88-557)
established the National Wilderness Preservation
System "to secure for the American people an
enduring resource of wilderness." The Act states:

"A wilderness... is an area where the earth and
community of life are untrammeled by man, where
man himself is a visitor who does not remain...
Wilderness is. ..undeveloped Federal land retaining
its primeval character and influence, without
permanent improvements or human habitation,
which is protected and managed so as to preserve
its natural conditions and which generally appears
to have been affected primarily by the forces of
nature, with the imprint of man's work substantially
unnoticeable..."

Wilderness is a distinct resource with inseparable
parts. When possible, natural processes are allowed to
operate within wilderness; for example, lightning-
caused fires are allowed to burn under prescribed
conditions. Wilderness is managed to make it as wild
and natural as possible, including closing old roads,
restoring damaged trails and campsites, and removing
most structures. Managers use primitive tools to do the

2

Table 1 .-Work group assignments for participants.

Team 1 Aquatic Ecosystems

Gene E. Likens (Chairperson)

Peter Dillon (Combined group chair)

Thomas Frost

Dale W. Johnson

Dale Nichols

Ed Brannon

Tom Thompson

Bill Carothers

Dave Unger

Jay Messer (Note Taker)

Team 2 Aquatic Ecosystems

Rick A. Linthurst (Chairperson)

Mike Pace

Richard Wright

Steve Mealey

Mike Edrington

Gray Reynolds

Anne Fege

Richard Fisher (Note Taker)

Team 3 Terrestrial Ecosystems

Ann M. Bartuska (Chairperson)
Jan Nilsson
John Reuss
Bill Mattson

Steve Lindberg (Combined group chair)

David F Karnosky

Chuck Wildes

John Butruille

Clif Benoit

Bob Loomis

Douglas G. Fox (Note Taker)

Team 4 Terrestrial Ecosystems

Ellis Cowling (Chairperson)

Gary M. Lovett

Dave Peterson

J. R. N. Jeffers

Peter B. Reich

Dave Radloff

Dick Stauber

Steve Harper

James G. Byrne (Note Taker)

1 Affiliations of participants are given in appendix D.

job. As with other National Forest resource
management efforts, public involvement is sought in
planning for wilderness management and use.

Many management activities and uses are
prohibited in wilderness: roads, motorized equipment
and mechanical transport, landing of aircraft, most
commercial enterprises, and permanent structures and
installations. The Wilderness Act allows certain
activities within wilderness, as long as the wilderness
character is preserved. These uses include livestock
grazing, hunting, fishing, exercising water rights, and
existing mineral claims. Special exceptions are made
in some wilderness legislation that permit mineral
exploration and exploitation, access to private land,
maintenance and use of airstrips, and, in Alaska,
native use for subsistence.

The scientific value of wilderness is recognized in
the 1964 Act. A decade or a century in the future,
wildernesses will serve as baseline or "control" areas,
since they are managed to preserve natural conditions
and generally will have been affected primarily by the
forces of nature. Permission to conduct scientific
studies is granted only if the studies require a
wilderness environment, and cannot be accomplished
outside the wilderness. Motorized equipment or
mechanical transport cannot be justified on the basis of
cost or efficiency, and are allowed only if a
comprehensive analysis shows there are no
alternatives.

Clean Air Act

The Clean Air Act (CAA) Amendments of 1977
included a program for prevention of significant
deterioration of air quality, generally referred to as the
"PSD" program. This PSD program is to prevent areas
currently having clean air from becoming too polluted.
Certain wilderness areas and National Parks
established before August 1977 were designated as
Class I areas. A Class I designation allows only very
small increments of new pollution above already
existing air pollution levels within the area.
Wildernesses established since August 7, 1977, are
Class II areas. Class II areas have a larger increment,
which is about 25 percent of the national ambient air
quality standard. Class I areas in the National Forest
System are identified in figure A-1 in the appendix to
this report.

The CAA charges the federal land manager (FLM)
of Class I areas with an affirmative responsibility to
protect the air-quality-related values (AQRV's) of these
areas from adverse air pollution impacts. AQRV's are
those values within the Class I area that could be
affected by air pollution such that the purpose for which
the area was established (biological diversity, water

3

quality, fish) would be adversely affected. Within the
Forest Service, the Regional Forester has been
delegated this affirmative responsibility. Managers
must minimize the conflicting human impacts of air
pollution, much as they manage other uses to limit their
impacts on the wilderness resource.

The PSD program is a preconstruction review and
permitting process for major new or expanding sources
of pollution. Any major facility seeking a new source
permit for location or expansion in a clean air area
must meet several requirements: Class I and/or II
increments, the AQRV impact analysis, and the Best
Available Control Technology (BACT) evaluation. In
the PSD permitting process, the FLM determines
whether a proposed source's emissions will have an
adverse impact on Class I area AQRV's.

New source permit applicants submit plans to the

permitting authority, who examines the proposed
location of the facility, its general design, projected air
pollution emissions, and potential impacts. When a
proposed source's emissions may have an impact on a
Class I area, the permitting authority (EPA, or the
State, if EPA has delegated PSD authority to that
State) alerts the FLM. The FLM then determines the
impact of the projected pollution level increases on the
Class I area AQRV's and recommends approval,
denial, or modification of the preconstruction permit.
When the air regulatory authority certifies that a permit
application is complete, the FLM might have as little as
30 days to review the permit application and respond
to the regulatory authority. The FLM's determination of
adverse impact must be completed within this period.
This reply is included in the required public
participation phase of the PSD program.

WORKSHOP RESULTS

The Green- Yellow-Red Screening Model

A conceptual framework was developed to
implement the partnership between scientists and
managers to help evaluate the potential impact of
proposed new air pollution sources on Class I areas.
This framework includes the idea of acceptable (Green
Line), unacceptable (Red Line), and intermediate
(Yellow Zone) levels of pollution. It is very important to
keep in mind that this framework represents a
screening tool. As such, it is intended to simplify the
decision process by providing guidelines for general
use rather than formulas for specific application. In all
circumstances, the magnitude of these screening
values, both Red and Green, are subject to change
based on better site specific information. In the
absence of such data, use of screening values should
advance the evaluation of PSD permits.

Pollutant doses less than the Green Line value
might be judged permissible by managers, and the
application recommended for approval without
additional data. Conversely, doses above the Red Line
value are likely to cause at least one AQRV to be
adversely affected. Thus they would result in a
recommendation for denial unless additional site-
specific data are provided to prove that the identified
AQRV of the Class I area would not be adversely
affected. Doses falling between the Green and Red
Lines (the Yellow Zone) would be evaluated on the
basis of additional information provided or gathered by
the applicant or the USDA Forest Service.

It is prudent for the Class I manager to have
AQRV's clearly identified, their current status
monitored, and specific limits of impact defined. To
avoid challenges, such information must be based
upon or include multiyear data, and scientific peer
review. Use of these screening techniques is also
based on the availability of accurate deposition and
concentration data at or near the Class I areas. These
data also should be quality assured. Suggestions from
long-term sustained ecological research will be useful
in this context.

Specifically, the Green Line denotes a total loading
(current deposition plus predicted additional deposition
from the new source) of sulfur and nitrogen and the
total dose of ozone that predicts, with a very high
degree of certainty, that no AQRV will be adversely
affected. The Red Line denotes a total loading of sulfur
and nitrogen and the total dose of ozone that predicts,
with a very high degree of certainty, that at least one
AQRV will be adversely affected. Sustained ecological
research, part of the partnership between managers
and scientists, will refine and modify these decision
points with new or better data.

Participants agreed that Green and Red Line
numbers need to be ecosystem-specific. The selected
numbers reflect the effects of pollutants on the AQRV's
identified within the nine example Class I areas.
Terrestrial and aquatic systems were considered
separately because the understanding of combined
impacts is not sufficiently developed to set numerical
levels. Ozone was considered only to affect terrestrial

4

ecosystems. Aquatic impacts were estimated by the
sensitivity of surface waters as measured by the
combined concentrations of calcium, magnesium,
potassium, and sodium (corrected for marine
influences) expressed in microequivalents per liter
(u.eq/1). Green and Red Line values for aquatic impacts
are presented graphically.

Terrestrial Green and Red Line Screening Numbers

Participating scientists familiar (to varying degrees)
with detailed data applicable to these Class I area
wildernesses agreed to the values in table 2. The
Green Line represents the total pollution loadings
(current plus proposed new source contribution)
pollution loadings below which a land manager can
recommend a permit be issued for a new source
unless data are available to indicate otherwise. The
Red Line represents an estimate of the total pollutant
loadings that each wilderness can tolerate. Total
loadings above these values suggest the land manager
recommend reduction of emissions from a new source
unless data are available to indicate that no AQRV of
the Class I area is likely to be adversely affected.

Pollutant loadings between these values require the
gathering of enough valid data to determine whether or
not a permit for a new source should be
recommended. General ideas for dealing with loadings
that fall between the values are described in the next
section.

Aquatic Green and Red Line
Screening Graph

Green and Red Line screening values associated
with effects on aquatic ecosystems are most
appropriately displayed graphically. The sensitivity of
aquatic ecosystems to S and N deposition is measured
by their acid-neutralizing capacity (ANC). The ANC
may already be reduced, however, in systems
subjected to significant deposition loading. A good
measure of sensitivity for fresh surface waters is the
sum of the concentrations of base cations (calcium,
magnesium, potassium and sodium ions) in the water.
Since Class I areas contain a diversity of lakes and
streams, the participants felt that Green and Red Line
values should be presented as a function of the ion
concentration. The manager will need loadings based
on knowledge of the surface waters in the Class I area
as well as the deposition environment.

The graph for aquatic systems shows Green and
Red Line values with total deposition loading (in kg of
S/ha-yr) on the vertical axis and concentration of
(nonmarine) Ca+Mg+K+Na (in u.eq/1) on the horizontal
axis. The significance of these concentrations is based
on the relative amount of water that is exported from
the watershed. Green and Red Line values are
presented in figure 1 for runoff estimated to be about
60-70% of the precipitation, and for 40-50% runoff.
Green and Red Line values for additional runoff
percentages are presented in appendix C in figures C-
1 and C-2.

Table 2.-Terrestrial Green and Red Line screening values.

Nitrogen deposition^

Ozone concentrations

Wilderness areal

Green Ln

Red Line

Green Ln

Red Line

Green Ln

Red Ln

— kg N/ha-y- —

— kg S/ha-y—

ppb-

Alpine Lakes, WA

5-7

15

3-5

20

35/75

55/110

Hoover, CA

3-5

10

3-5

20

35/75

55/110

San Gorgonio, CA

5

15

3-5

20

35/75

55/110

Bob Marshall, MT

3-5

10-15

5

20

35/75

55/110

Bridger, WY

3-5

10

5

20

35/75

55/110

Superstition, AZ

3-5

15

5-7

20

35/75

55/110

Joyce Kilmer, NC/Slick Rock, TN

7-10

15

5-7

20

35/75

55/110

Otter Creek, WV

7

10-15

5

20

35/75

55/110

Boundary Waters Canoe Area, MN

3-5

10

5

20

35/75

55/110

7 See appendix B for description of wildernesses.

^Nitrogen and sulfur deposition are total values including all forms, wet, dry, NH4-N and NOx-N, SO4-S,
SO2-S, etc.

^Growing season average/second highest 1 hour average value in a year.

5

60-70% Runoff

14

40-50%
Runoff

12

CO

c

o

'•4— '

CO

o

Q.
0
"D

10

8

iS 6

Red values - acidification
ikely

Green values - no
acidification likely

Yellow values - uncertain
whether or not acidification
occurs

40

Base cations

160

200

80 120
Ca + Mg + K + Na (adjusted for marine influence)
jLteq/l

Figure 1,-Green and Red Line va.ues for effects of deposition on freshwater systems.

Total

^deposition Is Z su7u, oep.s„,.„ —p. - ss^ed ,.oa,,o„s s, no.sd >„ ,Ko « whoro ,5%
of total Nitrogen deposition should be included.

6

Part of the water that falls on a watershed as
precipitation is lost as water vapor through evaporation
or through transpiration by plants. Depending on
geologic conditions, some may seep deep below
surface and be lost from the immediate watershed as
ground water. The rest leaves as surface runoff. High
mountain areas with cool temperatures, large amounts
of rain and snow, steep slopes, and thin soils have
high runoff percentages. Warm temperatures, deep
soils, level topography, and vigorous plant growth all
favor evapotranspiration and reduce runoff.

Participants considered that, with a few complex
exceptions, effects of N deposition on aquatic
resources are not likely to be significant because the N
is taken up by the watershed terrestrial and aquatic
biota and does not contribute to acidification.
Exceptions are very sensitive lakes and watersheds,
primarily at high-elevation sites in the western United
States, with base cation concentrations below 50 ueq/l.
Such systems can be acidified by addition of N
(Grennfelt and Hultberg 1986). For such
circumstances, we recommend adding 25% of the total
N deposition to the S deposition for use in the aquatic
graph. Thus, if the total deposition projected for a
western Class I area containing low base saturation
waters is 2 kg S/ha-yr and 4 kg N/ha-yr, the value of 2
+ .25x4 = 3 should be used in determining the Green
and Red Line loadings on the Graph.

Below a total deposition of 3 kg S/ha-yr, there are
no field data to develop the Green and Red lines.
Particularly in Class I areas in the western United
States, deposition levels are low and surface waters
have low ionic concentrations (10-40 ueq/l). No
evidence of chronic acidification has been reported.
However, snow melt has the potential to seasonally
acidify these surface waters. Another potential effect of
episodic snowmelt loading in lakes in the west is
eutrophication, a nutrient fertilization effect leading to
increased organic productivity. This effect would also
require additional study. Thus, these systems fall in the
Yellow zone.

Implementing the Screening Technique

Information Needs

Listed below are six types of data helpful to
managers for using the Green/Yellow/Red screening
technique. These data can be obtained from published
sources, or local scientists who may have access to
additional sources of information. It is also prudent for
managers to formulate recommendations for additional
research or assessment efforts which should be
undertaken by the permittee, Forest Service, state, or
by other organizations before or as a condition to the
permit.

Managers are encouraged to develop working
relationships with local university, state, federal, and
industrial research personnel to assist in identifying
already existing sources of information or
recommendations for further research. This workshop
report should be useful in initiating such
communication.

Data needed to responsibly evaluate a PSD permit
include:

1. Deposition and air concentrations to estimate
current loadings. --Current loading and exposure
conditions at wilderness sites must be estimated to
assess the impact of new deposition increments.
Measurements should take into account expected
higher fluxes at higher elevations. Some protocols for
these measurements have been established (Fox et al.
1987).

Ozone. Determine maximum hourly average values
and growing season average concentrations.

Sulfur. Determine total deposition by wet, dry, and
cloudwater processes. For some forest systems it
has been shown that measurements of throughfall
plus stemflow fluxes provide a simple but accurate
estimate of total deposition of the major S
components.

Nitrogen. Determine total deposition from
precipitation, cloudwater, and air chemistry
measurements (including HNO3 vapor and
ammonium ion) and appropriate dry deposition
models. Characterization of meteorologic and
climatologic parameters should also be considered.
These can be used to determine potential
climatologic stresses and to evaluate dry deposition
and cloudwater deposition.

2. Expected deposition and air concentrations
due to proposed source. --Predicted loading and
exposure at each site must be estimated to assess the
change in current loading or air concentrations for
comparison with Red and Green Line values.
Estimates must account for elevational effects and for
important nearby sources that contribute to
background loading and concentration. The expected
worst case ambient loading or concentration should be
predicted. Modeling is generally conducted by the
proponent and/or the regulatory agency. Managers
should be aware that ozone is a secondary pollutant
(generated in the atmosphere) and must be predicted
with a model incorporating photo-chemical reactions.
Sulfur modeling should include any increased loading
due to all important sulfur species (SO2, particle
sulfate, cloudwater sulfate). Nitrogen modeling should
consider all species of N available for plant uptake
(HNO3 vapor, nitrate and ammonium ions in rain and
cloudwater, NH3).

7

3. Inventory of biological resources associated
with the identified AQRV's of the Class I area. -A
description of the vegetation communities (type, cover)
is needed to assess the relative response of the
ecosystem(s) to pollutants. Include in a general
assessment the identification of unique communities
(such as small bog in an otherwise forested system),
and the percentage cover of major ecosystem types.

Periodic remeasurement of stand composition and
integrity. Linkage to developing long-term monitoring
programs (EPA, FS) will assist in an evaluation of
change. A species list including relative frequencies of
occurrence is needed. An estimate of the biomass
increment for assessment of nitrogen demand and use
(for instance Douglas-fir require more than alpine
plants) must be made. Percent cover by major
vegetation type is useful for this purpose.

A full inventory of aquatic resources, including
water column and benthic sampling to determine
phytoplankton, zooplankton, and macroinvertebrates
as well as associated water chemistry is needed. A
quantitative sampling procedure for macroinvertebrates
and flowing waters should be followed. Fish
abundance, condition, age class, and other aspects of
community composition should be measured (Fox et
al. 1987).

4. Species response/biological effects data.-
Following the vegetation survey, the response of key
species to pollution loading must be evaluated. The
FLM should coordinate these needs with FS Research
and other research activities in the area of air pollution,
plant response, acid deposition, and aquatic resources.
One outcome of this might be the development of
bioindicators and key sensitive organisms in Class I
areas.

5. Lake, stream, and soil survey/geological
assessment. -Data needs for lake and stream water
chemistry are identified above. Information is
necessary to understand the relative ability of soil and
bedrock to buffer pollutant inputs for all subsystems
within the wilderness.

Lake and stream water. Care should be exercised
to ensure that appropriate guidelines are followed
(see Fox et al. 1987).

Soil survey. Identify major soil series, followed by
more detailed chemical characterizations of the
important series. (See for example the description
and protocols in the recent EPA Soil Survey; Fox et
al. 1987.)

Geological assessment. Parent material can be
assigned to one of several weathering as described
in the Swedish critical load document (Nilsson
1986). Ecosystem sensitivity to S inputs can then
be related to the percentages of the various classes
within the wilderness.

6. Snowpack chemistry and hydrologic
characteristics of the area.-Snowpacks in high-
elevation wilderness have large surface area to
capture S and N compounds. Thus pollution may
accumulate in the snowpack. Careful measurement of
snowpack chemistry (Fox et al. 1987) can provide
good deposition loading information. Snowmelt causes
a significant pulse of water which initially can release
concentrated chemicals to the ecosystem. Since
pollutants are not soluble in ice, they reside on the
surface of the ice. As the snowpack warms, these
chemicals are removed by the initial meltwater. This
may result in a chemical pulse more concentrated in
the initial runoff than in the snowpack itself. Managers
should assess the potential and the likely effects of this
process of pollutant storage and delivery.

Monitoring Considerations

A major consideration for all ecosystems is the
current condition of the atmospheric environment. This
requires measurement of meteorology and air quality in
sites representative of the wilderness.

Meteorology

Meteorological instrumentation can be operated
with battery power using microprocessors to record
and process the data. The details of these systems are
available in Fox et al. (1987).

Ambient Air Concentration

Air quality measurement is more problematical.
Ozone measurement requires a major investment in an
air-conditioned instrument shelter. The shelter and the
ozone monitor require line power, frequent calibration,
and standardization. Such instrumentation cannot be
put in a wilderness. Rather, the site selected for
monitoring ozone must be carefully selected to be
representative in exposure, elevation, and ground
cover (canopy, etc.) of the wilderness being monitored
(Fox et al. 1987).

Ambient air concentrations of SO2, NOx, and NH4
can be measured using filter packs. These filter packs
also collect aerosol SO4 and NO3. These instruments
also require power, although they need not be
sheltered. Again, siting must be representative of the
ecosystems being monitored. These techniques are
described in Fox et al. (1987).

Deposition

A major concern in assessing impacts is the
measurement of deposition. Dry deposition cannot
easily be measured except with research quality
instruments. However, it can be approximated by
measurements of surrogates, for example snowpack in
alpine areas. The snowpack can be monitored by

8

carefully digging a snowpit and collecting snow
samples along its depth (Fox et al. 1987). In a forest,
throughfall and streamflow together have proven a
useful measure of dry deposition of some chemical
elements.

Wet deposition should be measured using NADP-
type collectors and protocols for consistency and
comparison within the large national network. Other
data required should be collected using the guidelines
for wilderness measurements (Fox et al. 1987).

Cloud and fog water interception in certain locations
can add considerably to the total deposition. They
should be considered in mountain locations where
such events occur.

General Considerations for Data Collection

The land manager should be aware of the degree of
uncertainty in the numbers obtained, including those
used to establish Red and Green Line values. The
FLM should accept that some uncertainty is
unavoidable and does not negate use in decision
making. The following points are relevant.

1. The variance of certain measurements can be
quite high, increasing the uncertainty in estimates, and
decreasing confidence in prediction.

2. The level of resolution can increase
uncertainty. Finer temporal resolution of data (such as
hourly ozone averages) may be quite variable and
difficult to interpret, but when averaged over a longer
period of time (weekly), values are more stable and,
hence, certain.

3. Temporal patterns in water and soil chemistry
may or may not be greater than the magnitude of
differences among soil types in the same watershed.
The focus of the monitoring is on the most sensitive
component of the ecosystem, rather than any average
or representative condition.

4. Most wildernesses are comprised of several
ecosystems (such as alpine at high elevation; Douglas-
fir at lower elevation). The manager needs to evaluate
the sensitivity and the importance of identified AQRV's
in each ecosystem.

5. There may be mismatches between data sets.
For example, air quality data may be provided for a
region or large parcel of land (especially if derived from
a model); however, the soil chemistry or vegetation
type may be specific to a location. Also, microclimatic
effects might alter an air-quality and/or deposition
effect locally, reducing the representativeness of a
measurement.

Quality Assurance and Quality Control

The need for quality assurance and quality control
is implicit in the need for data upon which decisions
can be upheld in an appeal. The following items reflect
this need:

1. Utilize standardized quality assurance/quality
control guidelines where available; in particular, EPA
procedures and the QA Methods Manuals of the Forest
Response Program (Blair 1986).

2. Implement standard protocols across regions.
For soils, coordination with the Soil Conservation
Service is recommended.

3. For chemical analyses, evaluate laboratory
capability and performance prior to selecting a
laboratory. Evaluation is especially relevant for many
state and university laboratories where procedures
may be appropriate for agricultural but not forest soils,
and for lake and stream water but not necessarily
dilute surface waters and precipitation. Water
chemistry is particularly expensive and demanding on
laboratory resources. Laboratory procedures should be
carefully evaluated and monitored both prior to
receiving samples and during sample analysis.

SPECIFIC FACTORS AND CONSIDERATIONS IN
DEVELOPING THE MODEL

Terrestrial Systems

Effects of direct air pollution on terrestrial resources
have been the subject of considerable research over
the past 50 years. Many plant species have been
tested for direct phytotoxicity due to the so-called
criteria pollutants (03, S02, NOx) as well as other
reactive hydrocarbons. Concentrations necessary to
cause a noticeable impact are generally well above the
current loadings in many Class I areas, although ozone
routinely occurs at phytotoxic levels in California and
the eastern United States. The major problems
associated with ozone toxicity are: (1) plants respond

almost immediately to low concentrations of ozone, but
their response is not likely to be significant until
concentrations are somewhat higher than the response
level (Reich 1987), and (2) generally only economically
important plants have been studied. Other species may
or may not respond in the same manner.

In the 1980's there has been a growing awareness
of so called forest declines: large-scale reductions in
the health and vigor of trees. Declines are likely
associated with a host of interacting stress factors;
direct causes are hard to pin-point. Research has been
focused recently on determining the role of acidic
deposition in forest decline. This program is rapidly

9

accumulating quantitative and qualitative information
about the effects of addition of S, N, and associated
pollutants on forest health. Considerable research is
addressing the mechanisms of how S and N affects
forests, including soil influences, foliar leaching, carbon
allocation, winter injury, reproduction and regeneration,
and insect and pathogen influences. Finally, direct
dose-response relationships are being determined.

Workshop scientists considered the current state of
this rapidly moving field in developing the numerical
values in the Green and Red Line tables. In addressing
ozone impacts they needed to address the critical
question of what constitutes an ecosystem-level
impact, given that most experiments have dealt with
single species. An exception may be studies in
California by Miller and his coworkers (Miller 1973).

When considering the levels of S and N deposition,
the scientists focused on soil effects because soils
were presumed to be a very sensitive ecosystem
component, and clearly soil effects are an ecosystem-
level impact. Dealing with N in this context was difficult,
however, because most Class I area ecosystems are
likely to be N limited. In this case any increment of N is
likely to cause some effect. Scientists had to estimate
the significance of anticipated effects at an ecosystem
level in order to develop numerical values.

Rationale Used in Selecting Ozone Values

It has been well established that exposure of plant
leaves to air containing ozone results in a number of
quantifiable effects, including visible injury, reduced
photosynthetic capacity, increased respiratory rate,
briefer leaf retention time, and reduced growth (Barnes
1972, Hayes and Skelly 1977, Pye 1988). The
magnitude of these effects depends on several factors,
including the concentration of the pollutant, the
duration of exposure, and other environmental factors
(USEPA 1986). Sensitivity to ozone varies among and
within species because of inherent differences in
uptake rates (Reich 1987) and also because of other
unknown genetic factors (Karnosky and Steiner 1981).
Despite differences at the leaf level, responses of a
wide variety of species types can be effectively
characterized by taking into consideration exposure
dynamics and uptake characteristics (Reich 1987).

The immediate effect of elevated ozone levels in
wilderness areas would be decreased leaf longevity,
reduced net carbon gain of foliage, reduced growth of
individual plants, and foliar injury. Other adverse
effects could include alteration of plant allocation of
carbon; greater susceptibility to insects, pathogens,
water stress, winter injury, or other stress agents;
possible changes in species composition of plant
communities; and possible loss of genetic resources of
sensitive genotypes within a species.

The Green Line values for ozone for all wilderness
terrestrial plant ecosystems are set at 75 ppb (peak 1-
hour average) or 35 ppb (growing season average).3
We follow regulatory procedures established by the
Environmental Protection Agency, which define a peak
as the second-highest one hour average concentration
in a year (EPA 1986). Estimates of average ozone
concentrations in clean air range from 15 to 30 ppb.
However, estimates of background ozone
concentration are very difficult because measurements
do not exist, and models show complex nonlinear
interactions where ozone production depends on NOx
concentration, nonmethane hydrocarbon (NMHC)
concentration, and seasonality (Liu et al. 1987). NOx
background concentrations range from less than 1
ppbv (remote locations in the western United States) to
about 7 ppbv (remote locations in the eastern United
States) and about twice that in Europe (Fehnsenfeld et
al. 1988). Modeling estimates (Liu et al. 1987) would
then project background ozone concentrations of
approximately 20 ppb in the western United States and
70 ppb in the eastern United States. Of course, NOx
and ozone concentrations in the vicinity of urban areas
(such as Los Angeles, Phoenix, and Denver) are often
higher than the eastern background.

The Green Line values were chosen to give
reasonable certainty that no significant damage will
occur to the ecosystem. Based on available
information about plant response to ozone, we
conclude that any increase in ozone levels above
background (clean air) will have some adverse effect
on individual leaves of at least some species.
However, we believe that the integrity of the ecosystem
can be maintained with the slight amount of stress on
either sensitive individuals and/or sensitive species
that might occur below Green Line levels.

The Red Line values for ozone are set at 110 ppb
(peak 1-hour average) or 55 ppb (growing season
average). Species from all plant types suffer reduced
net photosynthesis and growth if exposed to 55 ppb for
the daylight hours every day of the growing season.
Although some of the data used in the development of
this value are based on average concentration during
daylight hours only (12 hours), the loading value
seasonal averages use 24 hours per day. While it is an
area of scientific controversy (Musselman et al. 1988)
whether a 12-hour or a 24-hour based ozone season
average is better correlated with effects, 12-hour data
are not available from regulatory agencies. Thus, 24-
hour data are recommended to calculate seasonal
averages.

3Growing season average may not be available in many
locations, and determination of growing season will be specific to
each species. Thus, it is likely that the peak values will be more
useful than the growing season average values (USEPA 1986,
Musselman et al. 1988).

10

Ambient ozone levels in Class I areas should not
exceed peak annual 1-hour average values of 110 ppb.
Data from numerous ozone monitoring stations
suggest that exceeding 110 ppb for the peak 1-hour
period of the year would be accompanied by 15 to 50
(or more) hours of exposure to ozone levels greater
than 80 ppb. Adverse effects are greater at higher
ozone concentrations.

Ozone effects are cumulative for each individual
plant, but the chemical itself is ephemeral and does not
accumulate in the plant or ecosystem. Also, ozone
does not enter the soil in sufficient quantities to be of
any significance. Finally, we conclude that some
individuals and species will be damaged in all
wilderness ecosystems at ozone levels between the
Red and Green Line values. In such Yellow Zones,
predicted damage must be evaluated on a case by
case basis. The PSD recommendation may depend on
the relative value of the plant community as an AQRV
within that particular wilderness area.

Rationale Used in Selecting Sulfur Values

Two criteria or effects have been considered to set
the Green and Red Line levels of deposition for sulfur:
(1) removal of base cation from soils in association
with the SO42- anion, a "capacity" effect, and (2) the
"intensity" effects resulting from the changes in soil
solution composition. This distinction becomes
important in areas affected by marine air masses
where natural SO42- levels may be well above our
proposed Green Line values. An approximate
correction can be made by subtracting the marine
component based on the S0427CI" ratio in seawater.
Marine sulfate is generally not considered deleterious
because it is normally accompanied by base cations,
particularly Na and to some extent Mg, and thus does
not contribute to acidification of the system. There may
be episodic exceptions to this.

For our basic capacity comparisons, we have
assumed a soil depth of 30 cm with a bulk density of
1.1 kg/liter. At a loading of 3 kg S/ha, it would require
approximately 175 years to achieve a reduction of 1
meq of base cations per 100 g soil. This reduction
would be at least partially offset by weathering of
primary minerals. Somewhat higher deposition levels
would be acceptable in areas where soils are deep or
are well supplied with bases, and these considerations
are reflected in the proposed values for some of the
particular ecosystems.

Given these assumptions, the maximum allowable
(Red Line) values of 20 kg/ha of S could achieve the
reduction of 1 meq base cation within about 26 years.
This base cation reduction would generally be
unacceptable unless the system contains free CaC03.
However, with the possible exception of the
Superstition Wilderness, all of the specific ecosystems

considered here contain considerable areas of non-
calcareous soils.

For our evaluation of intensity effects, we have
assumed 1 m precipitation in excess of
evapotranspiration. The Green Line value of 3 kg/ha
would increase solution concentrations by about 19
u.eq/1, which is near the natural background for surface
waters in areas that do not contain significant amounts
of readily oxidizable sulfur-bearing minerals.
Furthermore, this concentration would be unlikely to
result in significant mobilization of soluble inorganic
forms of aluminum. The corresponding increase for the
maximum value of 20 kg/ha would increase solution
concentrations by about 125 u.eq/1. This concentration
is in the range where Al mobilization might occur in
acid soils, and with the possible exception of the
Sonoran systems, would probably not be acceptable.

Rationale Used in Selecting Nitrogen Values

The basic features of N cycling in forest
ecosystems are fairly well understood, and can provide
a broad conceptual outline for arriving at deposition
loadings to wilderness areas. The following is a brief
summary of some of the important features of N cycles
relevant to loading considerations.

Nitrogen is the only major plant nutrient that does
not accumulate to any significant extent in inorganic
forms in the soil. Although ammonium is strongly
adsorbed to soil cation exchange sites, ammonium
almost never significantly accumulates because of
biological uptake by plants, grazers, decomposers, and
nitrifying bacteria. Thus, forest ecosystems can
accumulate atmospherically deposited N only by
biological mechanisms; specifically through
incorporation into plants, plant feeders (herbivores),
and decomposers such as soil microorganisms and
invertebrates. Because N is the nutrient most
commonly limiting growth of forests in North America,
forested ecosystems usually show a net accumulation
of atmospherically deposited N.

Any increase in N deposition as nitrate or
ammonium ion to N-limited wilderness areas will most
probably result in some increase in growth, and may
actually improve the health of the ecosystem. Species
adapted to low N conditions might be replaced as a
result of fertilization. It is also possible that chronic N
enrichment may eventually predispose plants to
outbreaks of plant-feeding insects and fungal
pathogens because of changes in the plants' carbon
allocation to growth and defensive processes.

N deposited in excess of biological need almost
invariably leads to nitrification, microbially mediated
nitrate and nitrite formation in the soil, and increased
leaching of nitrate and associated cations. The nitrate
so produced may lead to surface- or groundwater

degradation unless it encounters anaerobic conditions.
Under these conditions, it may be microbially reduced
to N2O gas (denitrification), thus decreasing the
potentially deleterious effects of excessive N
deposition on water quality. These processes may still
leave the potential increases in soil acidification to be
considered.

The Green Line values (3-10 kg/ha-yr) for nitrogen,
across all the ecosystems considered, were selected to
give reasonable certainty that no significant change in
the forest ecosystem will occur below this amount of
nitrogen deposition.

The Red Line values (10-15 kg/ha-yr) for nitrogen,
across all the ecosystems considered, were selected to
give reasonable certainty that these amounts of
nitrogen deposition will result in significant cnanges in
the accumulation of nitrogen and in the species
composition or other important features of the
ecosystem.

While the fundamental elements of forest N cycles
are reasonably well understood, quantitative data on N
cycling in wilderness areas is quite scarce at best, and
in many areas completely lacking. Therefore, the Red
and Green Line loadings for N deposition in wilderness
areas are judgments based on a very limited database.
We strongly urge that relevant N cycling parameters be
measured in those wilderness areas for which there is
a potential concern about increased N deposition. It is
also important to note that atmospheric deposition at
the chosen target loadings may well have some effect
upon wilderness areas in terms of stimulating growth;
thus, there is no assertion that these levels will protect
the wilderness areas from all effects. In our judgment,
however, the Green Line levels are sufficiently low that
perceptible deleterious effects upon plant health,
changes in species composition, or degradation of
water quality are unlikely.

Aquatic Systems

Aquatic resources are important Air Quality Related
Values in most Class I areas. Determining how best to
prevent significant deterioration by atmospheric
pollutants, however, is not as straightforward as
establishing their importance.

This section provides general guidelines for all
surface waters relative to the amount of sulfur and
nitrogen that can be deposited on an annual basis.

Green Line values indicate levels below which it is
highly unlikely that the most sensitive aquatic
resources will be significantly affected, while Red Line
values indicate levels above which it is highly //7<e/ythat
the most sensitive aquatic resources will be
significantly affected.

The guidelines use the concentrations of base

cations: calcium (Ca), magnesium (Mg), potassium (K),
and sodium (Na), as a measure of sensitivity. The
sulfur and nitrogen loadings above which adverse
change is likely and below which change is unlikely are
based on the most sensitive waters.

Concept of Surface Water Sensitivity

Lakes and streams differ in their inherent sensitivity
to inputs of acidifying compounds from the
atmosphere. A number of factors affect lake sensitivity;
bedrock geology, soil and vegetation type, hydrologic
characteristics, lake chemistry and biology, and
precipitation volume are among the important factors.
Maps of bedrock geology are often used to indicate
areas with sensitive lakes and streams. Seepage
lakes, lakes which have no visible outlet, are likely to
be dominated by precipitation, while drainage lakes are
likely to be influenced by watershed base cation
supply. Seepage lakes, all other things being equal,
will be more sensitive to acidification. The lake or
stream chemistry itself provides a convenient measure
of sensitivity. The lake water integrates many
watershed factors that may be difficult to measure or
estimate in the field.

Any of several water chemistry parameters may be
used to estimate sensitivity. In pristine areas receiving
little or no acid deposition, acid neutralizing capacity
(ANC) provides a useful measure-the lower the ANC,
the more sensitive is the water body. In areas receiving
acid deposition, however, ANC may have decreased.
Since ANC changes with acid deposition, it cannot be
used directly to assess sensitivity. Acid neutralizing
capacity can be defined as the sum of the base cations
minus the sum of the strong acid anions (SO4-, NO3-,
Ch) in a water sample if concentrations of organic
acids and aluminum are insignificant. Because of the
principle of electroneutrality, changes in base cations
and/or acid anion concentrations must affect the ANC
of the sample.

Calcium and magnesium concentrations have been
used widely as a measure of inherent sensitivity.
Henriksen's (I979) empirical nomograph for lake
acidification uses Ca+Mg concentrations as a measure
of sensitivity and SO4 concentration (or alternatively
pH of precipitation) as a measure of acid deposition to
determine whether a given lake will be acidic (pH<4.7),
transitional (4.7-5.3), or bicarbonate dominated
(p(H>5.3). This empirical approach developed on the
basis of several hundred Norwegian lakes has been
shown to be of general applicability to lakes in many
regions of Europe and North America (Wright and
Henriksen 1983, Henriksen and Brakke 1988, Wright
1988, Reuss et al. 1986).

While Ca and Mg are the major cations usually

12

associated with alkalinity, the weathering of minerals
containing K and Na can also contribute significantly to
ANC. Given the geological diversity of the Class I
areas, we used the sum of the four major base cations
(adjusted to subtract any marine influences) as the
principal measure of inherent sensitivity.

The relationships between lake ANC, anions, base
cations (Ca+Mg+K+Na), pH, and conductivity can be
derived either empirically or from basic water chemistry
theory. The figures used for our screening technique
were constructed showing the relationships between
non-marine base cations and total S or S+N deposition
for sensitive lakes. Measured lake chemistry data from
the 1984 Eastern Lake Survey (Linthurst et al. 1986)
and the 1985 Western Lake Survey (Landers et al.

1987) were used. Total deposition for S and N were
estimated for eastern lakes from analysis of wet
deposition data done by Husar (1986) with 30 percent
added to account for dry deposition. For the western
lakes we averaged data from nearby high-elevation
National Atmospheric Deposition Program (NADP)
sites (NADP 1988) with data from high-elevation snow
chemistry studies (Brown and Skau 1975, Melack et al.
1982, Laird et al. 1986, Loranger 1986, Loranger and
Brakke 1988, Reddy and Classen 1985, Vertucci in
press). No additional correction was made for dry
deposition because not enough information is available
to estimate the potential contribution (Young et al.

1988) .

Acidification Response Levels

The effects of O3, N, and S can be assessed
directly for aquatic ecosystems. Ozone has no known
direct effects on aquatic systems, and therefore does
not warrant further consideration. For aquatic systems,
pollutant loadings by N and S exert their influence on
biotic communities primarily by changing pH conditions
rather than by a direct influence due to the chemical
species of N or S. Our focus, therefore, is on defining
threshold levels for N and S loading based on their
influence on pH. Again in very dilute, high-elevation N-
limited lakes, the addition of N can initiate
eutrophication.

Changes in lake or stream pH due to atmospheric
inputs of N and S can have a variety of direct and
indirect effects on aquatic communities and ecosystem
processes. Increased hydrogen ion concentrations can
have a direct, toxic effect on organisms. Such direct
effects on one or a group of organisms may exert,
subsequently, an indirect influence on the occurrence
of other organisms, primarily through food web
interactions. Changing pH may also influence the
solubility of nutrients or toxic compounds and elements
(such as aluminum) which in turn may affect the

occurrence of organisms either directly or indirectly. It
is important to note that small-scale changes in
chemical conditions are likely to affect physiological
processes or a particular life stage of an organism prior
to the disappearance of a taxon.

Information on the effects of a particular decrease
in pH on a lake or stream can be derived from four
types of sources (EPRI 1986): (1) laboratory
bioassays, (2) synoptic surveys of the distribution of
organisms across systems with a range of pH values
(Eilers et al. 1984, Confer et al. 1983, Haines 1981),
(3) manipulations of pH in mesocosms, and (4) whole-
system experimental manipulations of pH (Schindler et
al. 1985, Brezonik et al. 1986, Hall et al. 1980, Hall and
Likens 1981). Each of these sources can provide
useful information on the effects of changing pH
conditions. However, whole-system experiments
provide the best detailed information on the response
of aquatic systems to acid stress because they involve
a direct, controlled manipulation of pH conditions, and
they are conducted at a scale that encompasses a full
range of population and ecosystem processes
(Schindler 1988, Hall and Likens 1984). Specifically,
results from these studies indicate effects that could
not have been discovered with other approaches.

In general, considering information drawn from all of
the sources listed above, it is possible to conclude that
pH changes of less than 0.5 units are capable of
producing considerable change in the biotic
communities of either lakes or streams. In many cases,
fish populations would be expected to respond to a 0.5
unit pH change. Shifts of 1 pH unit can lead to major
changes in the occurrence of other organisms,
particularly sensitive ones such as mollusks. Workshop
participants suggested a 0.5 pH unit change as a Red
Line projection and a 0.1-0.2 unit projected change for
the Green Line, in sensitive systems with pH of order 6
or very low ANC.

Because many wilderness areas contain a diversity
of lakes and streams, it is important to target a subset
of lakes and streams as primary AQRV's. Generally,
lakes and streams with low base cation concentrations
(BCC) or acid neutralizing capacity (ANC) are most
likely to be affected by the lowest level of pollutant
input. The federal land manager should therefore
target the lowest BCC and ANC systems within a
wilderness area for evaluation. An inventory of the
BCC and ANC of aquatic resources in an area would
provide extremely valuable and cost-effective baseline
information. Among the low BCC lakes and streams,
those with pH values of around 6.0 may be the most
likely to change with an increased S or N loading, and
should be given the most detailed attention. Typical
symptoms of acidification for lakes and streams include
the development of extensive mats of filamentous
green algae, increased water clarity, and/or changes in

13

the proportional occurrence of macroinvertebrate
species (Schindler et al. 1985, Hall et al. 1985, 1987).
It is also important to note, however, that a shift in the
pH of a lake or stream with a current value of 7.0 is
also likely to cause changes in the biota.

In some wilderness areas, lakes or streams may
already have pH<6.0. In many cases these could be
naturally acid rather than anthropogenically altered
systems. Natural acidification is often the case where
sphagnum bogs occur and runoff waters are yellow-
brown stained. These waters can have high organic
carbon concentrations, and therefore the natural
contributions to acidity may be high. Although such
naturally acid systems may contain assemblages of
species that are adapted to low pH conditions, they
may still be sensitive to the effects of increased N and
S loading. These colored water systems require more
detailed consideration.

Although the graphs presented are based on S
deposition, N may, in some circumstances, also affect
lake acidification. To account for the acidifying effect of
N deposition, we again used an empirical approach.
Generally, most N inputs are retained in the terrestrial
ecosystem. The fraction that leaks out to surface water
depends on a variety of site factors such as vegetation
type, stage of ecosystem development, hydrology, and
history of acid deposition. Large leaks of N often result
from vegetation disturbance such as clearcutting, fire,
and windthrow (Likens et al. 1970, Bormann and
Likens 1979).

Henriksen and Brakke (1988) have shown from
empirical data for surface waters in Norway that the
percent of incoming N retained by the terrestrial
system is generally 75-100%. Many of these lakes and
streams are comparable chemically and biologically to
mountainous areas in the United States. Some
acidified areas have shown an increase in NO3-, while
unacidified areas have very low concentrations of
NO3- in runoff (Henriksen and Brakke 1988).

While there will be unusual situations where N can
be released from ecosystems, a general exception is
extremely sensitive high mountain lake watersheds.
For such high elevation systems (BCC<50 |ieq/l),
adding 25% N deposition to the S deposition is merely
a guideline because the uptake will vary from site to
site, and also over time at a given site. Our approach
here is based on current situations measured at lakes
and streams of varied sensitivity and receiving varied
amounts of acid deposition both as N and S.

S and N Loadings

Current S and N loadings are necessary to locate
the lake(s)/stream(s) on the nomograph (fig. 1). The S
loading should be total S (wet SO4 + dry particulate

SO4 + SO2 gas) and can probably be best estimated
from the NADP wet deposition fields + measured SO2
levels, combined with best estimates of deposition
velocity. N loading (NO3- + NH4+) can be calculated in
an analogous manner for cases (BCC<50 u.eq/1) where
N is to be considered.

Illustration of Graph Use

For example, assume that lake water quality has
been identified as an AQRV, and that pH was chosen
as a measurement to be monitored. Lake pH, identified
as an indicator of the health of the aquatic ecosystem,
needs to be maintained above 5.8. This is equivalent to
maintaining an ANC over 10 u.eq/1 in water. Data have
been collected that identify a particular lake whose
base cation concentration is 80 u.eq/1. The screening
concept in the Aquatic Graph (fig. 1) is to be applied to
this lake.

Since the lake in this example has a measured non-
marine base cation sum of 80 ueq/l, the results are 3
kg S/ha/yr and 5.5 kg S/ha/yr for Green and Red Line
deposition loading, respectively, if runoff is between
40-50% of precipitation. If runoff is 60-70% of
precipitation, the Green Line deposition is 6 kg S/ha/yr
and Red Line is 1 1 kg S/ha/yr. That is, if the low runoff
lake would receive a total of <3 kg S/ha including
deposits from the new source, the pH of the lake would
not likely drop below 5.8. The AQRV would not be
adversely impacted, and the recommendation to the
state regulatory agency would be for permit approval. If
the low runoff lake would receive a total of >5.5 kg
S/ha/yr, including deposits from the new source, the
pH of the lake would certainly drop below 5.8 and
probably below 5.0. The AQRV would be adversely
impacted, and the recommendation to the state
regulatory agency would be for permit denial or permit
modification, to reduce deposition from the new source
to levels that would not adversely affect the lake.

Total deposition, including that from the proposed
new source, between 3 and 5.5 kg S/ha-yr would have
uncertain effects on the lake pH. The assessment
would then require additional site-specific information
indicating physical, chemical, and/or biological
response to sulfur input.

Information Needs

To use the Aquatic Graph (fig. 1), the following
information is needed:

o Distribution of cations, anions, ANC, and pH in
wilderness lakes and streams, collected after spring
runoff has receded.

14

o Estimates of annual runoff for watersheds
containing low base cation (sensitive) systems.

o Estimates of background annual average (wet plus
dry) sulfur and nitrogen deposition.

o Estimated total S and N deposition based on
modeling of the proposed new source emissions.

Cautions

The aquatic Green/Red model developed at this
workshop is based on an empirical relationship
involving a large number of lakes and streams. These
aquatic systems differ in watershed biogeochemistry
and hydrology, and in their specific response to
incremental additions of sulfur or nitrogen loading. The
loadings themselves are based, in most cases, on
estimated atmospheric values developed from models
that use regional assumptions and "rules of thumb."
Empirical models are best used as a screening
technique to estimate the probability of a water body or
group of water bodies responding to a given sulfur or
nitrogen deposition rate in cases where minimal data
are available. The terrestrial Green/Red Line model is
equally approximate.

Empirical models are not able to predict exact
results in any specific ecosystem. Because all of the
assumptions in this report are conservative, a loading
value below the Green Line has a low probability of
causing negative effects on AQRV. However, there
remain some sources of error that would cause an
underestimate of the potential for wilderness
acidification:

0 Failure to include the most sensitive lakes or
streams.

° Overestimation of average annual runoff.

0 Underestimation of background S or N deposition.

0 Underestimation of nitrogen assimilation and
storage by watershed vegetation and litter.

° Episodic acidification due to acidic snowmelt or
storm events (primarily in streams).

0 Higher than normal initial concentrations of SO4 in
lakes from natural sources other than marine
sources.

0 Failure to correct lake cation values for marine
influence or for other geological sources of CI and
associated anions.

The nitrogen loading data also do not consider
possible effects of increased nitrogen on eutrophication
(algal growth) and consequent low dissolved oxygen
content in lakes.

If a loading appears above the Green Line, the
graph indicates that the lake or stream may experience
a pH below 5.8. The following factors lead to an
overestimation of the effects of the predicted future
loadings.

o Overestimation of background sulfur loadings due
to:

--a large component of alkaline sulfate dust,
--overestimation of background dry deposition
rates.

0 Overestimation of background nitrogen loading due
to:

-overestimation of dry deposition rates,
-underestimation of nitrogen assimilation by
watershed vegetation.

o Delayed response to loadings because of:

-high sulfate adsorption capacity of watershed
soils.

-higher than average background weathering
rates.

If a loading falls above the Green Line criterion value,
the manager should request data from a proponent as
part of the PSD permit to determine if one or more of
the above cases may apply. Determinations would
involve deposition chemistry measurements (including
dry deposition), watershed element budgets, analyses
of watershed soils, and watershed simulation models.
Such studies should be suggested or approved
following consultation with scientists.

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15

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1987. Characteristics of lakes in the western United
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Fox, D. G.; Bernabo, J. C; Hood, B. 1987. Guidelines
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Hall, R. J.; Driscoll, C. T.; Likens, G. E. 1987.
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Hall, R. J.; Driscoll, C. T.; Likens, G. E.; Pratt, J. M.
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Hall, R. J.; Likens, G. E. 1984. Effect of discharge rate
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Hall, R. J.; Likens, G. E.; Fiance, S. B.; Hendry, G. R.
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to surface waters: estimating critical loads for

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1986. Characteristics of lakes in the eastern United
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Linthurst, R. A., Landers, D. H.; Eilers, J. M.; and
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1987. Ozone production in the rural troposphere
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17

18

WASHINGTON

1 Pasayten 505,524

2 Glacier Peak 464,258

3 Alpine Lakes 303,508

4 Goat Rocks 82,680

5 Mt. Adams 32,356

OREGON

6 Mt. Hood 14,160

7 Hells Canyon See ID

8 Eagle Cap 293,476

9 Mt. Jefferson 100,208

10 Strawberry Mtn. 33,003

11 Mt. Washington 46,116

12 Three Sisters 199,902

13 Diamond Peak 36,637

14 GearhartMtn. 18,709

15 Kalmiopsis 76,900

16 Mountain Lakes 23,071

CALIFORNIA

17 Marble Mtn. 213,743

18 South Warner 68,507

19 Thousand Lakes 15,695

20 Caribou 19,080

21 Yolla-Bolly-Middle Eel 109,091

22 Desolation 63,469

23 Mokelumne 50,400

24 Emigrant 104,311

25 Hoover 47,916

26 Minarets (Now Ansel Adams) 109,484

27 Kaiser 22,500

28 John Muir 484,673

29 Ventana 95,152

30 Dome Land 62,206

31 San Rafael 142,722

32 Cucamonga 9,022

33 San Gabriel 36,137

34 San Gorgonio 34,644

35 San Jacinto 20,564

36 Agua Tibia 15,934

NEVADA

37 Jarbridge 64,667

IDAHO

7 Hells Canyon 193,840

38 Sawtooth 216,383

39 Selway-Bitterroot 1,240,618

MONTANA

39 Selway-Bitterroot See ID

40 Anaconda-Pintler 157,803

41 Gates-of-the Mtn. 28,562

42 Scapegoat 239,295

43 Mission Mountains 73,877

44 Bob Marshall 950,000

45 Cabinet Mountains 94,272

WYOMING

46 North Absaroka 351,104

47 Washakie 686,584

48 Teton 557,31 1

49 Fitzpatrick 191,103

50 Bridger 392,160

COLORADO

51 Rawah 26,674

52 Mt. Zirkel 72,472

53 Flat Tops 235,230

54 Eagles Nest 133,910

55 Maroon Bells-Snowmass 71,060

56 West Elk 61,412

57 La Garita 48,486

58 Weminuche 400,907

ARIZONA

59 Sycamore Canyon 47,757

60 Pine Mtn. 20,061

61 Mazatzal 205,137

62 Mt. Baldy 6,975

63 Sierra Ancha 20,850

64 Superstition 124,117

65 Galiuro 52,717

66 Chiricahua 18,000

NEW MEXICO

67 Gila 433,690

68 White Mtn. 31,171

69 Pecos 167,416

70 San Pedro Parks 41,132

71 Wheeler Park 6,027

ARKANSAS

72 Caney Creek 14,344

73 Upper Buffalo 9,912

MISSOURI

74 Hercules-Glades 12,315

MINNESOTA

75 Boundary Waters Canoe Area 747,840

WISCONSIN

76 Rainbow Lake 6,388

NEW HAMPSHIRE

77 Great Gulf 5,552

78 Presidential Range-Dry River 20,000

VERMONT

79 Lye Brook 12,430

W. VIRGINIA

80 Dolly Sods 10,215

81 Otter Creek 20,000

VIRGINIA

82 James River Face 8,703

N. CAROLINA

83 Linville Gorge 7,575

84 Joyce Kilmer-Slickrock 14,033

85 Shining Rock 13,350

TENNESSEE

84 Joyce-Kilmer-Slickrock See NC
GEORGIA

86 Cohutta 33,776

ALABAMA

87 Sipsey 12,646

FLORIDA

88 Bradwell Bay 23,432

19

APPENDIX B. BACKGROUND OF SAMPLE CLASS I
AREAS

These descriptions were prepared jointly by
scientists and managers at this workshop. The
precision of these descriptions varies because the
amount of information available to workshop
participants was different. These Class I areas show
the breadth of AQRV's considered and the diversity of
approaches suggested by participants working
together. Terrestrial values given each area may be
the same because the different areas contain
ecosystems with similar sensitivities, such as alpine
areas. It is essential to consider the details of a specific
Class I area being screened when applying information
contained here.

Although visibility is an important AQRV in all these
Class I areas, this workshop focused on the effects of
air pollution on biotic systems and did not address
physical impacts on visibility. In no way should the
absence of visibility as an AQRV be construed as a
judgment of its relative value compared to biological
components.

Alpine Lakes and Glacier Peak Wildernesses -
Washington

Brief Description

The Alpine Lakes and Glacier Peak Wildernesses
are typical of the North Cascade mountains. The
vegetation is fir, Douglas-fir, and hemlock, and
precipitation is high. Soils are diverse in origin with
modest fertility and moisture. This is a high mountain
area with general elevation above 6,000 feet. Lakes
and large perennial snow fields are common at the
higher elevations. Streams peak during snowmelt
runoff, but abundant year round stream flow persists.

Air Quality Related Values

Water flowing from the Cascade crest has
significant value. The hydrologic system includes
snowfields, glaciers, high mountain streams, small
cirque lakes, cascading waterfalls, and larger streams
and rivers in lower systems. The water and aquatic
biota systems contribute greatly to these wildernesses.
Maintaining these systems and their natural water
clarity depends upon little chemical degradation or
change.

These wildernesses include a wide variety of
diverse plant communities and species typical of the
northern Cascade range. Maintaining natural diversity

is a critical component of general health and balance of
the ecosystem. Any significant change in plant
communities due to the effects of air pollution would
not only change the quality of wilderness experience,
but also ecosystem interrelationships which contribute
to wilderness values.

Much of the wilderness experience in the Cascades
is influenced by sights, sounds, feelings, experiences,
and even the smells the visitor encounters. In areas
close to metropolitan areas, one of the significant
changes for the city resident is the smell of the great
out-of-doors. Whether it is a whiff of pine forest, an
aroma of rain forest, or briskness of the clean, crisp
high mountain air rising up and over the Cascade
range, natural smell is a value only truly appreciated
when it's replaced with the odor of civilization.

Hoover and Dome Land Wildernesses - California
Brief Description

Hoover. This Wilderness lies along the eastern
slope of the Sierra Nevada Range in Mono County,
California. It is bounded on the west by Yosemite
National Park, which lies on the western slope of this
Range. The area is characterized by recently glaciated
canyons, composed of granitic and metavolcanic
rocks. The vegetation is scattered among the rocky
flats and ledges of the Sierra granite batholith.

Most soils are derived from granitic rock, are weakly
developed, and are low in productivity. They are
typically shallow over granitic parent material on the
sloping areas, and are deeper in the canyon bottoms.
They are sandy textured and low base saturation.
Water quality is good to excellent, with low sediment
loads in the streams. The many lakes in the high
country act as natural sinks in absorbing sediments
from the canyon uplands.

Scattered stands of timber grow on approximately
11 percent of the wilderness. Timber types generally
are mixed conifer, with Jeffery pine and white fir
dominating the lower elevations and lodgepole pine
and limber pine dominating the higher elevations.
Subalpine meadows occur throughout the area;
riparian areas exist along the stream courses, springs,
and other water influence zones. The higher elevations
are dominated by subalpine and alpine shrubs and
herbaceous vegetation, while elevations below the
forest zones are dominated by sagebrush, bitterbrush,
and mountainmahogany.

20

Air quality within the wilderness is excellent. Among
potential threats is the possibility for NOx, SOx, and
ozone to drift up the Toulumne valley, flow over the
crest, and influence the AQRV of the area and acidify
precipitation.

Dome Land: The Dome Land Wilderness is located
on the southeastern slopes of the Sierra Nevada
Range at the southern end of the Kern Plateau.
Granite domes and unique geologic formations are the
dominant features. Climatic conditions range from
montane to semi-arid to desert with elevations from
3,000 to 9,700 feet above sea level. The South Fork of
the Kern River flows through the wilderness.

Dome Land geography has been primarily
influenced by the South Fork Kern River drainage. The
wilderness is rimmed by high elevation peaks in a
horseshoe configuration. Pollution may be transported
up the Kern River drainage from the Bakersfield area
of the San Joaquin Valley.

The Dome Land is covered mainly by mixed conifer
forest. The higher elevations support primarily
lodgepole and Jeffrey pine, red and white fir, and small
amounts of oak and various shrubs. Small stands of
limber and foxtail pine are also found at the higher
elevations. A unique association of limber and foxtail
pine at the southern most ends of their ranges has
resulted in the establishment of a research natural
area. The lower elevations support mainly pinyon,
digger pine, oak, and shrubs.

Wildlife in the Dome Land is abundant. The
wilderness provides summer range for the Monache
and Kern River deer herds. A comprehensive species
list is lacking, but other wildlife observed include quail,
squirrels, chickaree, chipmunk, marten, marmot, black
bear, mountain lion, and bobcat. In the 1970's
California condors were sighted on several occasions.

There is light to moderate fishing within the
wilderness. The heaviest fishing area is located on the
South Fork of the Kern River. The rainbow trout found
in the wilderness are introduced.

The Dome Land contains six major tributary
streams of the South Fork of the Kern River. The
general character of the wilderness is dry during the
normal season of use, so these streams are very
important to visitors, livestock, and wildlife. Below the
wilderness, water from the South Fork is used for
agriculture, recreation, electrical power, and domestic
supplies. All of the Kern tributaries in the wilderness
drop to a low level or become dry in late summer.
Water becomes quite warm in creeks still flowing.

Soils within the Dome Land are derived form
weathered granite. Most of the soil consists of coarse,
sandy materials that have weathered from the barren,
exposed rock that dominates the wilderness. These
soils are very young, and lack the development
characteristic of older soils. They are very infertile due

to coarseness, shallowness, and lack of capacity to
store water. The soils are also susceptible to erosion.

Air Quality Related Values

Jeffery and ponderosa pines are prevalent above
5,000 feet. These sensitive tree species are subject to
damage by ozone, and can be used as indicators of
changes in plant communities. Needle retention and
natural color are needed to maintain the aesthetics of
these wildernesses. Limber, foxtail, and pinyon pine
are also important vegetative species.

The buffering effect of meadows on water quality
and quantity makes these areas very valuable for
protecting the Class I areas' aquatic systems,
especially the rainbow trout fisheries. Meadow
condition and water quality should be maintained within
current biological variability. Water quality needs to be
maintained in the river and its tributaries.

The selected loadings for these wildernesses are
lower than in some other wildernesses because of the
presence of alpine ecosystems with limited ability to
buffer additional S and N. The desire to maintain
current ecosystem structure and function were primary
considerations in the selection of threshold values.

The granitic domes characteristic in this wilderness
should be protected.

San Gorgonio Wilderness - California

Brief Description

Geology of this wilderness is highly diverse and
typical of southern California mountains. Climate is
Mediterranean, and the soils are dry with base
saturations about 50%. Water resources are scarce.
Vegetation varies with elevation from chaparral through
a pinyon-juniper and pine forest to alpine.

Air Quality Related Values

Ponderosa pine and Jeffery pine are dominant
species known to be susceptible to air pollutants,
especially O3. Symptoms of ozone injury (needle
chlorosis and premature needle senescence) can be
readily identified. The ponderosa pine forests in
southern California often have high concentrations of
pollutants present. West of the San Gorgonio
Wilderness, ozone concentrations are high from May
through September, with moderate concentrations at
other times. Nitrogen deposition is very high, and
although poorly quantified, may be an important
component of the ecosystem (Riggan et al. 1985).

21

Water quality is important as it relates to pH, ANC,
and productivity. The pH and ANC values are related
to changes in acidity, which affect chemical processes
and ultimately biological processes. Productivity is a
general term that refers to the amount of carbon fixed
on an annual basis; more N-rich systems are generally
more productive. Productivity should be maintained.

Meadows are critical areas to maintain in subalpine
and alpine ecosystems.

Bob Marshall Wilderness - Montana
Brief Description

The Bob Marshall Wilderness is nearly one million
acres in size, located in northwest Montana in the
Rocky Mountain Province. The bedrock is mostly
precambrian meta-sedimentary argillites, quartzites,
and limestones. Glaciation influenced the shape of the
land and the composition of the soil. Soils are cool,
moist, with base saturation of 25 to 50% with a
volcanic ash surface ranging from 4 to 8 inches. The
terrain has been influenced by glaciation, which formed
high alpine basins and broad u-shaped valleys.

Precipitation ranges from 16 inches in the valley
bottoms to more than 100 inches on the mountain
peaks. Snow comprises over 80 percent of the
precipitation at the higher elevations and 50 percent in
the valley bottoms. Elevation within the area varies
from 3,000 feet in the valleys to nearly 10,000 feet at
the highest peaks.

Habitat types range from warm-dry ponderosa
pine/bunchgrass to cool-moist whitebark pine.
Subalpine fir is the dominant habitat type. The country
is known for a mixture of big, open meadows and
dense forest. Uncontrolled natural fire played a large
part in producing a mosaic of different even-aged
communities.

About 250 wildlife species and 22 fish species are
found in the wilderness and surrounding national forest
lands. Native fish species include bull trout, west slope
cutthroat trout, mountain whitefish, and several non-
game species. Big game species include elk, mule
deer, white-tailed deer, moose, Rocky Mountain goat,
grizzly bear, black bear, and cougar. Endangered
species include the gray wolf, bald eagle, and
peregrine falcon. Threatened species include the
grizzly bear.

Lakes and streams are common and dependent on
snowmelt. The Middle Fork and South Fork of the
Flathead River flow out of the Bob Marshall. These
rivers are designated Wild and Scenic and are
important for rafting, fishing, photography, and
domestic and other consumptive needs. Water quality
is considered excellent, although water quality has not
been extensively sampled.

Air Quality Related Values

Grizzly bear and west slope cutthroat trout are the
key air quality related values in this wilderness. Effects
of air pollutants on forage species and other critical
grizzly habitat plant communities and on meadow
vegetation that could change trout habitat must to be
determined. This wilderness provides one of only two
major grizzly bear population centers in the lower 48
states. The cutthroat is classified as a species of
special concern in Montana because of declines in
abundance and distribution. It is important to the
wilderness visitor for both consumptive and non-
consumptive uses.

Alpine and subalpine plant communities were
thought to be the most sensitive to increases in N,
because they are naturally stressed ecosystems and
are likely to be naturally low N-consuming systems.
The Bob Marshall Wilderness is in a very clean air
region. Current deposition rates for N and S are
probably 1 kg/ha-yr or less for each of these elements.
Therefore, increases of N and S could represent large
percentage increases in the quantity of these
elements. This implies that tolerable increase levels
are likely to be in the low end of the Yellow Zone.

Bridger Wilderness - Wyoming

Brief Description

The Bridger Wilderness is located on the west side
of the continental divide in the Wind River Mountain
Range. The elevation ranges from about 8,000 to over
13,000 feet on Gannet Peak, with most of wilderness
above 9,000 feet. Almost all of the area is precambrian
crystalline granite except for a small section of
sedimentary rock in the northwest part. The area was
glaciated in the past, and still contains the largest
glaciers in the continental United States. Lakes are
very common (roughly 1 ,300) and have been stocked
since 1907 with all major species of trout found in
North America. Since a large portion of the wilderness
is above timberline, the vegetation is primarily alpine
and subalpine in character. Precipitation is primarily
snow, and the annual snow pack is deep. The soils are
cold, wet, and shallow with base saturation below 25%.
Granite or quartz rock outcrops and talus slopes are
common. Perennial streams are fed by snowmelt.
Groundwater flow is minimal.

Air Quality Related Values

This wilderness was originally designated as a
Primitive Area in 1930 because of its unique alpine

22

ecosystem, with numerous cirque lakes. These lakes
are the primary AQRV needing protection.

Because of the large amount of alpine vegetation,
this area is potentially very sensitive to the effects of
increased nitrogen deposition. The harsh climate,
shallow soils, and presumed low nitrogen uptake rates
of the alpine plants suggest significant changes in
growth rates and species composition under conditions
of even small atmospheric N deposition. The problem
would be exacerbated because the exposed bedrock in
the watersheds will focus large amounts of deposition
into small areas of alpine meadow.

The effects of air pollution on alpine vegetation are
not well known, and the interaction of pollutants with
the other severe stresses acting on alpine vegetation
make the problem especially complex. To improve the
knowledge base, the response of species
characteristic of this wilderness to ozone exposure and
N and S loading should be determined. Such
determinations should be performed in natural field
settings which incorporate the rigor of the alpine
environment. Plant communities of special concern are
the primary successional plant communities near
glacial margins. The chemistry and hydrology of the
snowpack needs special attention because of its
crucial role in maintaining the diverse plant
communities.

palo verde, saguaro cactus, cholla cacti, ocotillo,
catclaw, beargrass, agave, yucca, mesquite,
mountainmahogany, hopbush, turbinella and Emory
oaks, pinyon pine, and junipers.

Air Quality Related Values

Water is scarce in the Superstitions and its
availability and quality are critical to sustaining the
diverse faunal populations, as well as providing water
for recreationists.

Riparian species are important to the visual quality
of this unique wilderness, as well as furnishing perhaps
one of the most valuable wildlife habitats found in the
Upper Sonoran Desert. The ability of the wilderness to
support the diverse wildlife species found here would
be greatly diminished without riparian areas. Riparian
species include cottonwood, willow, sycamore, and
numerous others.

Both the number and uniqueness of Upper Sonoran
Desert plants give this wilderness its special character.
To lose any of these species would be a serious loss to
the wilderness. Vegetation in this type is thought to be
quite resistant to environmental stress, except that
vegetation growing in riparian areas may be more
sensitive to O3, SO2, and other pollutant effects.

Superstition Wilderness - Arizona
Brief Description

The Superstition Wilderness is located south of the
Mazatzal Mountains about 65 miles east of Phoenix.
Elevation is approximately 1,000 to 4,000 feet. The
rugged, dissected landscape that rises spectacularly
out of the desert has deep canyons with steep sonoran
relief. Streams are ephemeral, and there are no lakes.
Hydrographs are storm-dominated.

Climate is warm semi-arid and arid, with summer
convection storms and occasional winter rain. Annual
precipitation is 10 to 20 inches, but can vary as much
as 40 percent annually. The growing season is about
280 days. Average annual temperature is 60 to 75°F.

Soils are deep, dry forest soils with base
saturations above 50%. The geology includes highly
diverse rock types and complex geological structures,
including metamorphic, sedimentary, and intrusive and
extrusive igneous rocks. The east half is proterozoic
rocks that have been pervasively faulted. The west half
is tertiary volcanic rocks of many different types.

Vegetation is typically open, with sonoran desert
shrubs at lower elevations to interior chaparral and
juniper woodland at higher elevations. Upland plants
include grama grasses, creosote bush, yellow and blue

Joyce Kilmer - Slickrock Wilderness - North
Carolina, Tennessee

Brief Description

Cove and upland hardwoods are the dominant
forest types typical of this warm, humid climate that
has abundant, uniform precipitation. Soils range from
deep, moist, and well-developed to shallow, poorly
developed, and with base saturation less than 25%.
The low mountains underlain by sedimentary geology
vary from 2,000 to 5,300 feet in elevation. Intermittent
and perennial mountain streams are common.

Air Quality Related Values

Flora, water quality, and trout fisheries all had
important roles in the designation of the Joyce Kilmer-
Slickrock Wilderness, and continue to be important
characteristics of the wilderness, and the experiences
valued by visitors.

The floral diversity is great, with more than 60
species of trees. Most of the flora is of tertiary origin,
and a number of plant species are close relatives to
species in eastern Asia. Wildflowers are abundant
throughout the wilderness. The Joyce Kilmer Memorial

23

Forest portion of the wilderness has many trees over
300 years old, some more than 20 feet in
circumference and 100 feet tall. This part of the
wilderness is a remnant virgin forest preserved by the
Forest Service since 1935. Approximately 30% of the
Slickrock portion of the wilderness is also
representative of a forest in its primeval condition.

The high-quality mountain streams found in the
wilderness, free of sediment with clean bottoms, cool
and clear, with deep pools and numerous riffles, are
rare in this part of the country. These streams have
been rated by the State of North Carolina as type "C
Trout" and have met State standards for use as a
public water supply. Slickrock Creek is a highly
productive trout stream yielding about twice as much
poundage per acre as neighboring streams. "Native"
(reproducing naturally in the stream) brook trout are
abundant in the upper reaches of Slickrock Creek.
Brown and rainbow trout are prominent in the lower
reaches. Little Santeelah Creek and its tributaries are
habitat for brown, brook, and rainbow trout. The trout
fisheries in these streams represent a major recreation
opportunity in the wilderness.

The location of the Slickrock area in the southern
Appalachians and the locations of some portions of the
area at elevations above 4,800 feet suggest that parts
of this system currently receive relatively high loadings
of S and N, as well as high concentrations of O3
(NADP 1988). Any added loading due to new sources
will move pollutant levels into the Yellow Zone or
above the Red Line where granting of PSD Permits is
not automatic. At the high-elevation sites, minor
loadings may move pollutant levels into values above
the Red Line.

Slickrock's diverse forest systems of high and low
elevations require that the target loading values (Green
Line values) cover a somewhat higher range than other
wilderness areas. Over 90% of the area is
characterized by a capacity to utilize higher loadings of
N because of deep, well-developed soils of moderate
sulfate absorption capacity that can tolerate higher S
loadings. The remaining 10% of the area is boreal
forest, which receives higher loadings due to
elevational effects, and has soils, tree species, and
age classes of trees sensitive to low loadings of S and
N. The effect of the loss of the relatively small area of
high-elevation boreal forest on downslope ecosystems
is currently unknown, but hydrologic and chemical
disturbances might result.

Otter Creek - West Virginia and Great Gulf - New
Hampshire Wildernesses

Brief Description

Otter Creek: This 20,000 acre wilderness is located

in northeast West Virginia in an area with a cool, humid
climate and abundant, uniform precipitation averaging
50 to 55 inches annually. It is located in the
unglaciated Allegheny Plateau; mountainous, with
elevations ranging between 1,800 feet near the mouth
of Otter Creek, to 3,900 feet on McGowan Mountain.
Otter Creek, a perennial stream, bisects the wilderness
and a number of perennial tributaries occur throughout
the area.

Waters are generally acid and low in productivity.
There is a small native brook trout population in the
upper reaches of Otter Creek, made possible by a
demonstration project being conducted by the West
Virginia Department of Natural Resources in which
ground limestone is continuously added to Otter Creek
just outside the wilderness boundary. Trout may also
occur in the lower reaches of Otter Creek, below its
confluence with Turkey Run, where limestone bedrock
borders the stream. Otter Creek drains from a 6-acre
open acid fen, and some tributaries (Yellow Creek and
Moore Run) drain from open sphagnum/sedge/spruce
swamps.

Soils are moderately deep to deep, with base
saturation less than 35% (Utisols), and 35 to 50%
(Inceptosols). They are high in iron and aluminum.
Forest vegetation is a mixture of northern hardwoods
and Allegheny mixed hardwoods, including a
component of yellow poplar, and with red spruce at the
higher elevations. Rhododendron makes up understory
vegetation over extensive areas. Ground and
herbaceous vegetation is somewhat depauperate over
most of the wilderness compared to other low-elevation
mesic sites, with the exception of limited areas of
limestone bedrock in which vegetation richness
increases and spring wildflowers may be abundant.
The area was logged between 1890 and 1915, and
200 acres of Norway spruce was later planted on the
top of Green Mountain.

Great Gulf. This gulf and its tributary gulfs were
hollowed out by the action of glaciers before the last
ice age. One of the distinctive features of the eastern
slopes of the Presidential Range, this glacial valley
between Mount Washington and the Northern Peaks is
from 1,100 to 1,600 feet deep. It extends easterly from
Mount Washington some 3-1/2 miles as a narrow,
steep-sided gulf before broadening gradually to more
open terrain. It contains a number of remarkable
cascades, and the views from the walls and from
points on the floor are among the best in New England.

Many of the older trees have been damaged by
hurricanes, but a few scattered stands of large virgin
spruce remain. A small portion of the eastern part of
the area, in the lower slope type, was cut over for large
spruce late in the 19th century. Northern hardwoods
are the typical forest at lower elevations. Alpine plants
and lichens abound above treeline. Stunted spruce and

24

fir provide the transition between the alpine and
forested areas.

A weather observatory on the 6,262-foot summit of
Mount Washington, the highest point in the Northeast,
just outside the southwest corner of the wilderness,
has recorded the highest wind speed (231 mph) of any
weather station world-wide. Wind speeds in excess of
100 mph are not uncommon. The weather is severe
most of the year, and approximates conditions
encountered at a much higher latitude. The summit of
Mount Washington is in the clouds approximately 55
percent of the time. The effects and extent of acid
cloud/fog water (pH generally less than 3.0) are
currently being studied.

Air Quality Related Values

Otter Creek: Three isolated freshwater wetlands
occur, with some sphagnum vegetation most
commonly associated with more northern wetland
areas. A 59-acre stand of virgin red spruce and
hemlock remains on Shavers Mountain. Spring
ephemerals, especially on the more productive sites,
provide some very desirable diversity and richness. A
large number of tree, shrub, and herbaceous species
within the area have known sensitivity to various air
pollutants (black cherry, yellow poplar, red spruce,
etc.). Change in the native plant communities and
associated fauna resulting from air pollution would be
undesirable.

Water quality is important for drinking water by
wilderness users, and for the limited cold water fishery
in Otter Creek. However, water quality in Otter Creek is
being artificially improved for fishery purposes by the
continuous addition of ground limestone, raising the pH
and alkalinity of the stream. Therefore, water quality
measurements in Otter Creek are not representative of
natural conditions. Without such limestone treatment,
Otter Creek water in its natural condition is acid (pH
5.0) and very low in productivity (alkalinity much less
than 2 milligrams per liter, and conductivity 25 u,S/cm)
where it enters the wilderness. Water quality further
deteriorates going downstream due to even poorer
quality tributary inputs, until the neutralizing influence
of limestone bedrock is encountered near the mouth of
Otter Creek, where water quality improves somewhat
for a fairly short reach of the stream (pH 5.8 to 6.0,
alkalinity 3.1 mg/l and conductivity 31). Tributaries to
Otter Creek have pH less than 4.0 and alkalinities less
than 0.2 mg/l.

Great Gulf: Water quality is important for trout
fisheries, and for hikers to drink and enjoy its scenic
quality. Alpine flowers are rare in the Northeast and
they exist in a harsh environment probably susceptible
to damage from changes in soil chemistry.

Boundary Waters Canoe Area Wilderness -
Minnesota

Brief Description

This second largest wilderness area (798,458
acres) under Forest Service administration sits astride
the border between Minnesota and Ontario, Canada.
The elevation averages 1,150 feet above sea level.

The climate is continental polar, with long cold
winters and cool summers that provide only 95 frost-
free days per year. Annual precipitation varies from 20
to 30 inches per year.

The bedrock underlying the Boundary Waters
Canoe Wilderness is precambrian metamorphic and
intrusive igneous rock, which has been glaciated only
recently. The bedrock is overlaid with very thin,
nutrient-poor spodosol soils of low cation exchange
capacity, high in iron and aluminum, with moderately
low acid neutralizing capacity, and are essentially
neutral in pH.

This wilderness contains over 1,000 lakes larger
than 10 acres. Three-fourths of these lakes are slightly
to heavily stained a brown color from organic materials
draining from the abundant peatlands in the
wilderness. The pH of most of the lakes falls in the 6.6
to 8.3 range, with a mean of about 7.3. A few of the
highly stained lakes have pH's as low as 5.6. Many of
the lakes are sensitive, and could become acidified if
acid deposition were to increase. About half have
ANC's less than 130 u.eq/1 and base cation
concentrations below 215 |ieq/l. About 5% of the lakes
in this wilderness have ANC's less than 50 and base
cation concentrations below 140 jieq/l.

Air quality at present is very good since the BWCA
sits on the eastern fringe of the Canadian and United
States Great Plains, which have so far sustained little
industrial development. Also, the air quality standards
of the State of Minnesota are substantially more
stringent than the United States federal ambient air
quality standards. As a result, in 1985 the Boundary
Waters Canoe Wilderness sustained a measured wet
deposition of only 1.4 to 2.3 kg of nitrate nitrogen, 0.2
to 0.3 kg of ammonium nitrogen, 2.3 to 3.5 kg of
sulfate, and a hydrogen ion deposition of generally less
than 0.1 kg per hectare per year. The annual average
pH of precipitation was about 5.0. The average ozone
concentration during the growing season is about 35
ppb.

Air Quality Related Values

o High-quality waters that support a highly diverse
fishery.

25

o Coniferous and mixed coniferous forests that
provide the critical habitat for one of the last
remaining and viable eastern timber wolf
populations in the continental United States.

o Bird populations, especially bald eagles and loons.

o Native American pictographs and buried sites.

The relatively lower than usual Green Line and Red
Line values recommended for total sulfur and nitrogen
deposition in this Wilderness are justified because of
the substantial sensitivity of the shallow soils, the hard
crystalline bedrock, and the low alkalinity of the surface
waters.

Suggested factors to be considered in making a
determination of Green Line (or better) conditions:

o Based on current knowledge of species sensitivity,
modelled increases in pollutant loads will, with a

high degree of certainty, result in no reduction in
distribution of known pollutant sensitive tree or
lesser vegetation species.

o With a high degree of certainty, modelled increases
in pollutant loads will have negligible or no impact
on acid neutralizing capacity of any BWCA lake.

Suggested factors to be considered in making a
determination of Red Line (or worse) conditions:

o Based on current knowledge of species sensitivity,
modelled increases in pollutant loads will result in
either complete elimination or reduce distribution of
at least one tree or lesser vegetation species.

o Modelled increases in sulfate or nitrate deposition
will result in complete elimination of acid
neutralizing capacity from one or more lakes.

26

APPENDIX C. OTHER AQUATIC MEASUREMENT
METHODS

Loading/Response Relationships

The acidification of lakes has been considered to be
analogous to the titration of a bicarbonate solution
(acid neutralizing capacity, ANC) with acidic (sulfuric
acid) atmospheric deposition (Henriksen 1979). When
additions of acid consume ANC, pH decreases slowly
at first, then more markedly as ANC is depleted (Small
et al. 1988). Acidic deposition may also increase the
weathering of base cations and not result in an
equivalent consumption of ANC for each equivalent of
acid deposited (Henriksen 1984). Lake ANC is
produced from watershed weathering and exchange
reactions. These reactions generate equivalent
amounts of bicarbonate and base cations. Lake ANC
can also be produced from in-lake processes, such as
Ca exchange with sediments, and biologically
mediated removal of nitrate and sulfate (Schindler
1986). The relative importance of in-lake versus
watershed sources of alkalinity and the relationship
between acid deposition and enhanced weathering of
base cations is known for only a few ecosystems.
These additional mechanisms, which act to reduce the
effect of acidic deposition, cannot be included in a
conservative estimate of the relationship between
deposition amount and ecosystem impacts.

Our approach is analogous to the Henriksen
empirical model where deposition amount, lake
sensitivity (sum of base cations), and the results of
lakes surveys are used to empirically derive, for lakes
of a given sensitivity and deposition level, where the
system will experience ANC decline and pH
depression. We assume that in-lake alkalinity
generation and enhanced weathering of base cations
is negligible.

Graph Construction

Figures C-1 and C-2 show, for various deposition
levels, the concentrations of non-marine Ca+Mg+K+Na
in lakes having ANC of 1 0 to 25 |ieq/l and pH values of
about 5.9 to 6.2, and in lakes with ANC between -20
and -5 and pH of about 4.8 to 5.2. Figure C-1 shows
the Green Lines for these. The Green Lines indicate
the deposition level below which lakes with various
base cation concentrations should maintain ANC of at
least 10 to 25 u.eq/1 and pH of at least 5.8 to 6.2. Figure
C-2 shows Red Lines. If subjected to a particular
deposition level, lakes with base cation concentrations

less than those indicated by the Red Lines can be
expected to become acidic with ANC falling below zero
and pH reaching 5.2 or less.

The graphs are based on the assumption that, while
lake HCO3 decreases and is replaced by SO4 in
response to increasing S deposition, base cation
concentrations do not change. In fact, as deposition
increases, mineral weathering of base cations from the
watershed may increase somewhat (Henriksen 1984).
As a result, lakes with a given base cation
concentration may be able to withstand a somewhat
greater increase in S deposition than indicated by the
nomographs. In-lake alkalinity production may also
reduce the impact of S deposition (Schindler 1986).
Because these effects are uncertain in magnitude and
probably do not occur in all lakes, we have taken the
conservative approach of protecting the lakes and
have assumed that these processes are not significant.

The amount of runoff relative to the amount of
precipitation on a watershed affects how lake
chemistry responds to acid loadings. As more
precipitation is lost to evapotranspiration and less is
yielded as runoff, acid deposition is, in effect,
concentrated, and its impact on a lake is greater.
Consequently, the graphs show several Red and
Green Lines for various amounts of runoff, expressed
as percentages of annual precipitation.

N deposition is included for very low ANC (<50
u.eq/1) waters in the western United States. The
rationale for including N is based on observations that
most N deposited on a watershed is retained in the
watershed. At most, about 20% can be seen in surface
waters. This is explained in the text. Deposition loading
was determined as outlined in the surface water
sensitivity section, page 12. Essentially, total
deposition was determined by combining wet
deposition data with dry deposition estimates. In the
east, dry deposition was estimated to be 30% of wet
deposition, while in the west dry deposition was
assumed to be zero.

Within about 125 miles of the sea coast,
precipitation contains significant amounts of sodium,
magnesium, chloride, and sulfate and lesser amounts
of other ions of marine origin. These ions increase the
base cation concentration of lakes in these areas
without adding HCO3 or ANC. To correct for this effect,
we assume that all chloride (CI) in such lake water is
from marine sources, and subtract from the base
cation concentration an amount in proportion to the
relative concentrations of CI and base cation in
seawater (Hem 1970).

27

60-70% Runoff
/

14

12

40-50%
Runoff

/

/

10

8

4 -

2 -

Adirondack Mountains, runoff=60-70%
of precipitation
o ANC = 10 to 25^eq/l

• ANC = -5 to -20

Pocono and Catskill Mountains, runoff=:60-70%
O ANC = 10 to 25

• ANC = -5 to -20

New England, includes southern New England,
central New England, and Maine, runoff=60-70%
a ANC = 10 to 25
a ANC = -5 to -20

Northern Wisconsin and upper Michigan,
runoff=40-50%
□ ANC = 10 to 25
■ ANC = -5 to -20

Western Mountains, ANC = 10-25 ^eq/l
o Runoff = 80-90%

• Runoff = 50-70%
® Runoff = 25-35%

I s

40

80

120

160

200

Base cations, /ieq/l (adjusted for marine influence)

Figure C-1.--Base cations/deposition relationship for Green Lines. Lakes to the right of the
appropriate runoff lines are not considered to be acidic. (Data from Kanciruk et al. 1986 and Eilers
et al. 1987.)

28

80-90% Runoff

60-70% Runoff

40-50% Runoff

14

12

10

8

2 -

25-35%
Runoff

- Adirondack Mountains, runoff=60-70%
of precipitation
o ANC = 10 to 25Meq/l

• ANC = -5 to -20

- Pocono and Catskill Mountains, runoff=60-70%
O ANC = 10 to 25

• ANC = -5 to -20

- New England, includes southern New England,
central New England, and Maine, runoff=60-70%
a ANC = 10 to 25
a ANC = -5 to -20

- Northern Wisconsin and upper Michigan,
runoff=40-50%
o ANC = 10 to 25
■ ANC = -5 to -20

- Western Mountains, ANC = 10-25 ^eq/l
o Runoff = 80-90%

• Runoff = 50-70%
® Runoff = 25-35%

1

1

1

40 80 120 160 200

Base cations, pteq/l (adjusted for marine influence)

Figure C-2.--Base cations/deposition relationship for Red Lines. Lakes to the left of the appropriate
runoff lines are likely acidic. (Data from Kanciruk et al. 1986 and Eilers et al. 1987.)

29

Inland lakes generally have low concentrations of CI
and Cl-associated base cations, but natural geologic
sources and contamination by road salt may increase
them. The base cation concentration of these lakes
also must be corrected for this influence. This is done
by assuming:

Non-marine Ca+Mg+K+Na = Total
Ca+Mg+K+Na - (CI x 1.115)

Concentrations of all ions are expressed in u.eq/1.

Lake SO4 generally increases with increasing S
deposition, but natural geologic sources also contribute
variable amounts of SO4 to lakes (Loranger and
Brakke 1988, Eilers et al. 1987). Base cations
associated with geologic SO4 add significant variability
to the ANC:base cation relationship. In figures C-1 and
C-2, much of the scattering of data points for any given
deposition level and runoff percentage can be
attributed to geologic SO4 and associated base
cations.

This approach is similar to the so-called Hendriksen
model, which has been shown to have limitations
(Reuss et al. 1986, Vertucci in press). However, the
Red Line values used here are based on an empirical
fit to the data on acidified lakes. The Green Line values
essentially represent a simple balance of increased
sulfate (and nitrate) against ANC. This is an
approximation that Wright (1988), among others,
suggests can be improved by the introduction of a
factor "f" representing the ratio of change in base
cation concentration to net sulfate (that attributable to
anthropogenic sources). The model here assumes f to
be zero. A nonzero f would make the Green Lines
steeper. Since this is intended as a worst case
screening technique that errs on the side of
conservatism, and actual f values are unknown, we felt
it was appropriate to use an f factor of zero.

In cases where little cation data exist, conductivity
was considered as an alternate measure of sensitivity.
Since conductivity is easily and cheaply measured in
the field, conductivity data may be more widely
available for surface waters than are cation data. Easy
and cheap don't necessarily equate with accurate,
however, and field conductivity data must be closely
screened to ensure reliability. Electrical conductivity
(usually expressed as u.Siemens/cm at 25 degrees C)
is a measure of the total amount of ions dissolved in
the water. Consequently, conductivity is related to the
sum of the base cations and anions. Waters that are
inherently sensitive to acid deposition have little
buffering or acid neutralizing capacity, low
concentrations of base cations, and low conductivity.

Figures C-3 and C-4 are similar to C-1 and C-2, but
show lake conductivity in place of base cation
concentration as a measure of lake sensitivity.
Because conductivity is an indicator of the total

concentration of ions dissolved in the waters, it is used
as a substitute for the base cation concentration. Since
the contribution of SO4 and HCO3 to conductivity are
about the same, we assume that the conductivity of a
lake does not change with increasing S deposition. As
with figures C-1 and C-2, we ignore the fact that base
cations, and consequently conductivity, may increase
somewhat at greater deposition levels, due to
increased mineral weathering.

As with base cations, conductivity must be
corrected for marine influences. This correction is even
more critical for conductivity, because conductivity is
influenced not only by the ocean-derived base cations,
but also by the CI and SO4. In addition to the
adjustments for marine contributions, conductivity must
also be corrected for hydrogen ion (pH) influences. In
acidic waters, hydrogen contributes heavily to
conductivity, and this contribution must be subtracted.
All the lake conductivity data in figures C-3 and C-4 are
corrected for both pH and marine influences. This is
done by assuming:

Non-marine conductivity = measured
conductivity - (CI x 0.1422)

with CI expressed in u.eq/1 and conductivity in
liSiemens.

Adjusted conductivity = measured
conductivity - (H x 0.34965)

where H is the hydrogen ion concentration in jieq/l
(H=10 raised to the -pH power, then that quantity
multiplied by 1,000,000).

Differences in natural sources of SO4 add much
variation to the ANC:conductivity relationship. This
effect is greater than that on ANC:base cations
because both SO4 and the associated base cations
contribute to conductivity. For any particular deposition
level and runoff percentage, the scatter among the
data points and the overlap between groups of acidic
and non-acidic lakes is greater in figures C-3 and C-4
than in C-1 and C-2. Therefore, base cations rather
than conductivity should be used as a measure of lake
sensitivity where cation data are available. Conductivity
is useful as a rough tool to separate lakes into non-
sensitive and possibly sensitive groups.

Detailed Information Needs

Surface water chemistry data can be collected by
means of special purpose surveys, by census, or by
estimating values based on previous surveys in similar
geographic terrains. As an example of the last
approach, an approximate characterization of the
surface water chemistry of seven of the nine
wilderness ecosystem types is presented in table C-1.

30

80-90% Runoff

~ 14

CD
O

c

0)

12

10

8

6 -

Adirondack Mountains, runoff=60-70%

of precipitation

o ANC = 10 to 25ixeq/\

• ANC = -5 to -20

Pocono and Catskill Mountains, runoff=60-70%
O ANC = 10 to 25

• ANC = -5 to -20

New England, includes southern New England,
central New England, and Maine, runoff=60-70%
a ANC = 10 to 25
a ANC = -5 to -20

Northern Wisconsin and upper Michigan,
runoff=40-50%
o ANC = 10 to 25
■ ANC = -5 to -20

Western Mountains, ANC = 10-25 j^eq/l
o Runoff = 80-90%

• Runoff = 50-70%
© Runoff = 25-35%

1

1

1

1

5 10 15 20 25

Conductivity, juS/cm (adjusted for marine influences and H+)

Figure C-3. --Conductivity/deposition relationships for Green Lines. Lakes to the right of the
appropriate runoff lines are not considered acidic. (Data from Kanciruk et al. 1986 and Eilers et al.
1987.)

31

80-90% Runoff

60-70% Runoff

-77T 14

12

10

^ 8

4 -

2 -

40-50%
Runoff

25-35%
Runoff

Adirondack Mountains, runoff=60-70%
of precipitation
o ANC = 10 to 25^eq/l

• ANC = -5 to -20

Pocono and Catskill Mountains, runoff=60-70%
O ANC = 10 to 25

• ANC = -5 to -20

New England, includes southern New England,
central New England, and Maine, runoff=60-70%
a ANC = 10 to 25
a ANC = -5 to -20

Northern Wisconsin and upper Michigan,
runoff=40-50%
□ ANC = 10 to 25
■ ANC = -5 to -20

Western Mountains, ANC = 10-25 ^eq/l
o Runoff = 80-90%

• Runoff = 50-70%
© Runoff = 25-35%

1

1

1

5 10 15 20 25

Conductivity, nS/cm (adjusted for marine influences and H+)

Figure C-4.~Conductivity/deposition relationships for Red Lines. Lakes to the left of the appropriate
runoff lines are likely acidic. (Data from Kanciruk et al. 1986 and Eilers et al. 1987.)

32

Table C-1 .--Conductivity and neutralizing capacity, and pH statistics for geographic regions represented by seven wilderness

ecosystem types.

Wilderness area

Chemical factor

and
NSWS region

Conductivity

ANC

pH

Min.

Q1

Med.

Min.

Qi

Med.

Min.

Q1

Med.

liS/cm

\xeq/l

Alnino I al^oc
AM|JIIIC L_cmUo,

1 AIA

OH/ \JC.

fi 0,

r^U^Ior Danle /DM\A/1\

oiacier reals ^riNvv 1 )

Hoover, Dome Land

>2

5

8

7/13

34

60

>5.8

6.6

7.0

(SNM2)

Bob Marshall (NR3)

>3

9

39

72

77

342

6.3

6.9

7.1

Bridger (ALP4)

>7

12

15

39

74

109

>5.8

6.9

7.1

Joyce Kilmer,

10

14

21

16

87

120

6.4

6.8

7.0

Slickrock (EHW5)

Otter Creek, Great

19

33/22

69/35

-48

20/52

110/119

4.4

5.7/6.3

6.6/6.8

Gulf (NH6)

Boundary Waters Canoe

18

22

30

34

98

185

5.6

6.6

6.9

Water Area (C?)

1 WLS Pacific NW, Middle Washington and Wenatchee Mtns.

2WLS California, Sierra Nevada.

3WLS Northern Rockies, Lewis Range.

4WLS Central Rockies, Wind River.

5NSS Southern Blue Ridge.

6NSS N. Appalachians, ELS C. New England.

7ELS NE Minnesota.

WLS = EPA Western Lake Survey.
ELS = EPA Eastern Lake Survey.
NSS = National Stream Survey.

These data are based on the National Surface Water
Survey (NSWS), which measured the chemistry of a
large statistical sample of lakes and streams in regions
of the United States, expected to have surface water
with low acid neutralizing capacity. In several cases
(such as the Bridger Wilderness), many lakes were
sampled. In most cases, however, only a few lakes or
streams were actually included. As an approximation,
the chemical data in table C-1 were aggregated to
include the geographic units nearest to exact
wilderness that approximate the geology of the
corresponding regions, based on the NSWS data. No
data were collected in southern California nor in
Arizona.

Half of the lakes or streams in each region are
expected to fall below the median value for each
region. Twenty percent of the systems are expected to
fall below the first quintile (Q-|). Minimum values
represent the lowest value observed in the sample,
and do not necessarily represent the lowest lake or

stream in the region. Lake chemistry was measured
following fall overturn. Stream chemistry was sampled
in the spring between snowmelt and leaf-out, avoiding
rain storms. Streams affected by acid mine drainage
and polluted lakes were avoided.

These data are statistically valid randomly selected
samples of water quality in all areas. To obtain a better
estimate of the true chemistry distributions in a
particular wilderness, a random sample of
approximately 50 lakes can generally give acceptable
confidence bounds if the area is not too
heterogeneous. If 50 represents less than 5% of the
total population of lakes, or if the area is highly diverse,
a larger sample size may be needed to reduce
uncertainties in the estimates. Field sampling, while
inexpensive, must follow protocols for wilderness areas
(Fox et al. 1987).

Annual runoff can be calculated from estimated
precipitation and evapotranspiration measurements on
site, or measured at a gauged stream site in the region

33

of interest. In the absence of such data, published
values of mean annual runoff from state and federal
agencies in state water atlases and other publications
can be used. Annual variations in runoff are not a
significant concern in using figure 1 , provided long term
data are available.

Dry deposition of sulfate and nitrate are often
estimated from obtaining wet deposition data from the
nearest National Acid Deposition Program (NADP) site.
As a rule of thumb, in rural areas removed from point
sources of pollution, dry deposition of sulfur can be
assumed to equal 30% of the wet deposition value. Dry
nitrogen deposition may be somewhat greater than the
wet value. These factors are subject to considerable
local variations, including impaction of particles on dry
surfaces, and adsorption of gaseous species (SO2 and
HNO3) by moist surfaces, including lakes and the open
stomata of vegetation. If air concentration data of S
and N are available, dry deposition can be calculated
using assumed values of deposition velocity taken from
the Air Resource Handbook. Still more desirable are
dry deposition estimates from a nearby NDDN
(National Dry Deposition Network) site. These are
currently being installed throughout the United States.

Conversion of Deposition Values

Deposition loadings are presented in kg/ha-yr of S
and N. Deposition measurements are often reported as
deposition of SO4 and NO3 in mg/m2/yr. Land
managers may also be familiar with applications of S
and N in Ib/A/yr. The following conversion factors may
be useful:

Multiply S deposition by 3.0 to determine SO4
deposition

Multiply N deposition by 4.43 to determine NO3
deposition

Multiply kg/ha by 0.89 to determine lb/A
Multiply kg/ha by 100 to determine mg/m2

Multiply kg/ha by 0.1 to determine g/m2

To convert from mg/l to u.eq/1, multiply mg/l of Ca by
49.90, Mg by 83.26, K by 25.57, Na by 43.50, CI by
28.21, and SO4 by 20.82.

34

APPENDIX D. PARTICIPANTS AND THEIR
AFFILIATIONS

Ann M. Bartuska
Research Plant Physiologist
USDA-Forest Service
NC State University
1509 Varsity Drive
Raleigh, NC 27607

Clif R. Benoit

Regional Air Resource Specialist
USDA/FS R-4 RWM
324 25th Street
Ogden, UT 84401

Edgar B. Brannon
Forest Supervisor
Flathead National Forest
1935 3rd Ave. E.
Kalispell, MT 59901

John Butruille

Director, Recreation Management
USDA/Forest Service
P.O. Box 96090
Washington, DC 20090-6090

James G. Byrne
Air Resource Program Manager
USDA/Forest Service
Watershed and Air Management
Rm. 1210, RPE
Washington, DC 20090-6090

William A. Carothers
Regional Air Resource Specialist
USDA/Forest Service, R-8, SW&A
1720 Peachtree Rd. N.W.
Atlanta, GA 30367

Ellis Cowling

Associate Dean

North Carolina State University

1509 Varsity Drive

Raleigh, NC 27606

Peter Dillon

Supervisor, Limnology Unit
Ontario Ministry of the Environment
P.O. Box 39
Dorset, Ontario
Canada POA 1EO

Michael Edrington
Forest Supervisor
Williamette National Forest
P.O. Box 10607
Eugene, OR 97440

Anne Fege

Wilderness Program Manager
USDA/Forest Service
P.O. Box 96090
Washington, DC 20090-6090

Richard Fisher

Air Resource Management Specialist
USDA/Forest Service

Rocky Mountain Forest and Range Experiment Station
240 West Prospect
Fort Collins, CO 80526

Douglas G. Fox
Chief Meteorologist

Rocky Mountain Forest and Range Experiment Station
240 West Prospect
Fort Collins, CO 80526

Professor Thomas Frost
Center for Limnology
University of Wisconsin-Madison
608 N. Park Street
Madison, Wl 53706

Stephen C. Harper
Forest Supervisor

Green Mountain and Finger Lakes National Forest
P.O. Box 519
Rutland, VT 05701

Professor J. R. N. Jeffers
Institute of Terrestrial Ecology
Ellerhow, Lindale
Grange-Over-Sands
Cumbria LA1 1 6JU
United Kingdom

Dale W. Johnson

Research Ecologist

Environmental Sciences Division

Oak Ridge National Lab

P.O. Box X

Oak Ridge, TN 37831

Professor David F. Karnosky
Michigan Technological University
School of Forestry and Wood Products
A11030

Houghton, Ml 49931

Gene E. Likens, Director
Institute of Ecosystem Studies
The New York Botanical Gardens
Mary Flagler Cary Arboretum, Box AB
Millbrook, NY 12545

35

Steve Lindberg

Research Ecologist

Oak Ridge National Laboratory

Environmental Sciences Division

Oak Ridge, TN 37831

Rick A. Linthurst

Director, EPA Aquatics Effects Research
MD-39, EPA/EMSL (Annex)
Research Triangle Park, NC 2771 1

Robert C. Loomis

Ecologist, Forest Pest Management
USDA/Forest Service, FPM
P.O. Box 96090
Washington, DC 20090-6090

Gary M. Lovett

Research Ecologist

Institute of Ecosystem Studies

The New York Botanical Gardens, Box AB

Millbrook, NY 12545

William J. Mattson
Research Entomologist
USDA, Forest Service
Michigan State University
1407 S. Harrison Road
East Lansing, Ml 48823

Steve Mealey, Assistant Chief
USDA, Forest Service
P.O. Box 96090
Washington, DC 20090-6090

Jay Messer, Ecologist
EPA Aquatic Effects Research
MD-39, EPA/EMSL (Annex)
Research Triangle Park, NC 2771 1

Dale Nichols

Research Forester

USDA, Forest Service

NC Station, Forestry Sciences Lab

1831 Highway 169 E.

Grand Rapids, MN 55744

Jan Nilsson, Director

Department of Research & Development

SNV (National Environmental Protection)

Box 1302

S-171 25 Solna

Sweden

Dave Peterson
Research Forester
USDA, Forest Service
Forest Fire Lab
4955 Canyon Crest Drive
Riverside, CA 92507

David L. Radloff

Assistant Director, Forest Fire and Atmospheric
Sciences Research
USDA, Forest Service
P.O. Box 96090
Washington, DC 20090-6090

Professor Peter B. Reich
Department of Forestry
University of Wisconsin
121 Russell Lab, 1630 Linden Drive
Madison, Wl 53706

Professor John Reuss
Department of Agronomy
Colorado State University
Fort Collins, CO 80521

Gray F. Reynolds

Director, Watershed and Air Management
USDA, Forest Service
P.O. Box 96090
Washington, DC 20090-6090

William T. Sommers

Director, Forest Fire and Atmospheric Sciences
Research

USDA, Forest Service
P.O. Box 96090
Washington, DC 20090-6090

Richard L. Stauber

Forest Supervisor

San Bernardino National Forest

1824 S. Commercenter Circle

San Bernardino, CA 92408-3430

Tom L. Thompson
Forest Supervisor
Siuslaw National Forest
P.O. Box 1148
Corvallis, OR 97339

David G. Unger, Associate Deputy Chief
USDA, Forest Service, National Forest System
P.O. Box 96090
Washington, DC 20090-6090

Charles C. Wildes
Deputy Forest Supervisor
Tonto National Forest
P.O. Box 5348
Phoenix, AZ 85010

Richard Wright
Limnologist

NIVA, Norwegian Institute, Water Res.
P.O. Box 333, Blindern
Oslo 3, Norway

36

Rocky
Mountains

Great
Plains

U.S. Department of Agriculture
Forest Service

Rocky Mountain Forest and
Range Experiment Station

The Rocky Mountain Station is one of eight
regional experiment stations, plus the Forest
Products Laboratory and the Washington Office
Staff, that make up the Forest Service research
organization.

RESEARCH FOCUS

Research programs at the Rocky Mountain
Station are coordinated with area universities and
with other institutions. Many studies are
conducted on a cooperative basis to accelerate
solutions to problems involving range, water,
wildlife and fish habitat, human and community
development, timber, recreation, protection, and
multiresource evaluation.

RESEARCH LOCATIONS

Research Work Units of the Rocky Mountain
Station are operated in cooperation with
universities in the following cities:

Albuquerque, New Mexico

Flagstaff, Arizona

Fort Collins, Colorado*

Laramie, Wyoming

Lincoln, Nebraska

Rapid City, South Dakota

Tempe, Arizona

'Station Headquarters: 240 W. Prospect St., Fort Collins, CO 80526