National Park Service

U.S. Department of the Interior

Natural Resource Program Center

Federal Land Managers’ 

Air Quality Related Values Work Group (FLAG)

Phase I Report—Revised (2010)

Natural Resource Report NPS/NRPC/NRR—2010/232
ON THE COVER

Courthouse Towers, Arches National Park, Utah.

Photo by Debbie Miller.

THIS PAGE:

Jumping Cholla, Superstition Wilderness, Arizona.

Photo by Steve Boutcher 
Federal Land Managers’ 

Air Quality Related Values Work Group (FLAG)

Phase I Report—Revised (2010)

Natural Resource Report NPS/NRPC/NRR—2010/232

U.S. Forest Service

Air Quality Program

1400 Independence Ave, SW

Washington, DC 20250 

National Park Service

Natural Resource Program Center

Air Resources Division

PO Box 25287

Denver, Colorado 80225

U.S. Fish and Wildlife Service

National Wildlife Refuge System

Air Quality Branch

7333 W. Jefferson Ave., Suite 375 

Lakewood, CO 80235

October 2010
The National Park Service, Natural Resource Program Center publishes a range of reports that address natural 

resource topics of interest and applicability to a broad audience in the National Park Service and others in 

natural resource management, including scientists, conservation and environmental constituencies, and the 

public. 

The Natural Resource Report Series is used to disseminate high-priority, current natural resource management 

information with managerial application. The series targets a general, diverse audience, and may contain NPS 

policy considerations or address sensitive issues of management applicability.

All manuscripts in the series receive the appropriate level of peer review to ensure that the information is 

scientifically credible, technically accurate, appropriately written for the intended audience, and designed and 

published in a professional manner. 

This guidance document was jointly prepared by the National Park Service, U.S. Forest Service, and the U.S. Fish 

and Wildlife Service, in collaboration with the Environmental Protection Agency. Guidance contained herein 

has been reviewed by subject matter experts and the general public through formal public review and comment 

period. This guidance document provides information for Federal Land Managers, permitting authorities, and 

permit applicants to use when assessing air quality impacts to air quality related values. Mention of trade names 

or commercial products does not constitute endorsement or recommendation for use by the U.S. Government.

This report is available from the Air Resources Division of the NPS (http://www.nature.nps.gov/air) and the 

Natural Resource Publications Management Web site (http://www.nature.nps.gov/publications/NRPM) on the 

Internet. 

Please cite this publication as:

U.S. Forest Service, National Park Service, and U.S. Fish and Wildlife Service. 2010. Federal land managers’ 

air quality related values work group (FLAG): phase I report—revised (2010). Natural Resource Report NPS/

NRPC/NRR—2010/232. National Park Service, Denver, Colorado. 

NPS 999/105412, October 2010
 USFS–NPS–USFWS iii

United States Department of the Interior 

Dear FLAG User: 

OFFICE OF THE SECRETARY 

Washington, D.C. 20240 

OCT -7 2010 

We are pleased to provide the fmal revised FLAG report (FLAG 2010). FLAG was formed at the 

request of permit applicants and State permit review authorities to develop a more consistent and 

objective approach for the Federal Land Managers (FLMs), i.e., National Park Service, U.S. Fish 

and Wildlife Service, and U.S. Department of Agriculture Forest Service, to evaluate air pollution 

effects on their Air Quality Related Values (AQRVs). The FLAG effort focused on how air 

pollutants -primarily particulate matter, nitrogen dioxide, sulfur dioxide, nitrates, sulfates, ozone -

affect the health and status of resources in areas managed by the three agencies. FLAG subgroups 

concentrated on four key issues: (1) visibility; (2) aquatic and terrestrial effects of wet and dry 

pollutant deposition; (3) terrestrial effects of ozone; and ( 4) process and policy issues. In December 

2000, the FLMs published a final Phase I report (FLAG 2000). Based on knowledge gained and 

regulatory developments since FLAG 2000, the FLMs believe certain revisions to FLAG 2000 are 

now appropriate. The final revised FLAG 2010 report reflects those changes. 

The FLAG 2010 report contains a wealth of information and should continue to be a very useful 

tool; we support its recommendations. The FLAG report is guidance and reflects agency direction, 

but it is not a rule. Nevertheless, we encourage all FLMs, permitting .authorities, permit applicants, 

and other interested parties to take advantage of the helpful information contained in the FLAG 

report when assessing air pollution impacts on AQRVs. 

We want to thank the many people who contributed to this important and worthwhile project. 

Sincerely, 

itl_). 

Thomas L. Strickland 

Assistant Secretary for Fish and Wildlife and Parks 

Department of the Interior 

Harris Sherman, Under Secretary 

Natural Resources and the Environment 

Department of Agriculture 
iv FLAG Phase I Report—Revised (2010)
Contents

Figures ........................................................................................................................................................................... vii

Tables ............................................................................................................................................................................ viii

Preface to this Edition of the FLAG Phase I Report (New).......................................................................................... ix

Executive Summary (Revised)...................................................................................................................................... xii

1. Background ............................................................................................................................................................... 1

1.1. History (Revised)..................................................................................................................................................... 1

1.1.1. FLAG Approach (Revised)................................................................................................................................ 1

1.1.2. FLAG Organization ......................................................................................................................................... 2

1.2. Overview of Resource Issues (Revised) .................................................................................................................... 2

1.2.1. Visibility .......................................................................................................................................................... 2

1.2.2. Vegetation...................................................................................................................................................... 2

1.2.3. Soils and Surface Waters................................................................................................................................. 3

1.3. Legal Responsibilities (Revised) ............................................................................................................................... 3

1.4. Commonalities Among Federal Land Managers ..................................................................................................... 4

1.4.1. Identifying AQRVs (Revised) ............................................................................................................................ 4

1.4.2. Determining the Levels of Pollution that Trigger Concern for the Well-Being of AQRVs (Revised)..................... 4

1.4.3. Visibility .......................................................................................................................................................... 5

1.4.4. Biological and Physical Effects......................................................................................................................... 5

1.4.5. Determining Pollution Levels of Concern (Revised)........................................................................................... 5

1.4.6. FLM Databases (Revised) ................................................................................................................................. 5

1.5. Regulatory Developments Since FLAG 2000 (New)................................................................................................. 5

2. Federal Land Managers’ Approach to AQRV Protection ........................................................................................ 7

2.1. AQRV Protection and Identification (Revised) ......................................................................................................... 7

2.2. New Source Review (Revised)................................................................................................................................. 7

2.2.1. Roles and Responsibilities of FLMs (Revised) .................................................................................................... 7

2.2.2. Elements of Permit Review.............................................................................................................................. 9

2.2.3. FLM Permit Review Process ........................................................................................................................... 10

2.2.4. Criteria for Decision Making (Adverse Impact Considerations) (Revised)......................................................... 12

2.2.5. Air Pollution Permit Conditions that Benefit Class I Areas .............................................................................. 12

2.2.6. Reducing Pollution in Nonattainment Areas (Nonattainment Permit Process)................................................. 13

2.3. Other Air Quality Review Considerations (Revised) ............................................................................................... 13

2.3.1. Remedying Existing Adverse Impacts............................................................................................................. 13

2.3.2. Requesting State Implementation Plan (SIP) Revisions to Address AQRV Adverse Impacts (Revised)................ 14

2.3.3. Periodic Increment Consumption Review (Revised) ........................................................................................ 14

2.4. Managing Emissions Generated in and Near FLM Areas (Revised)......................................................................... 14

2.4.1. Prescribed Fire ............................................................................................................................................. 15

2.4.2. Strategies to Minimize Emissions from Sources In and Near FLM Areas (Revised)........................................... 15

2.4.3. Conformity Requirements in Nonattainment Areas........................................................................................ 16

3. Subgroup Reports: Technical Analyses and Recommendations........................................................................... 18

3.1. Subgroup Objectives and Tasks ............................................................................................................................ 18

3.2. Initial Screening Criteria (New) ............................................................................................................................. 18

 USFS–NPS–USFWS v
3.3. Visibility ............................................................................................................................................................... 19

3.3.1. Introduction (Revised) ................................................................................................................................... 19

3.3.2. Recommendations for Evaluating Visibility Impacts (Revised) ......................................................................... 20

3.3.3. Air Quality Models and Visibility Assessment Procedures (Revised)................................................................. 20

3.3.4. Summary (Revised)........................................................................................................................................ 25

3.3.5. Natural Visibility Conditions and Analysis Methods (New).............................................................................. 26

3.4. Ozone.................................................................................................................................................................. 54

3.4.1. Introduction (Revised) ................................................................................................................................... 54

3.4.2. Ozone Effects on Vegetation (Revised) .......................................................................................................... 54

3.4.3. Established Metrics to Determine Phytotoxic Ozone Concentrations (Revised) ............................................... 55

3.4.4. Identification of Ozone Sensitive AQRVs or Sensitive Receptors (Revised) ...................................................... 55

3.4.5. Review Process for Sources that Could Affect Ozone Levels or Vegetation in FLM Areas (Revised) ................ 55

3.4.6. Further Guidance to FLMs (Revised) .............................................................................................................. 56

3.4.7. Ozone Air Pollution Web Sites (Revised) ........................................................................................................ 58

3.5. Deposition .......................................................................................................................................................... 58

3.5.1. Introduction (Revised) ................................................................................................................................... 58

3.5.2. Current Trends in Deposition (Revised) .......................................................................................................... 59

3.5.3. Identification and Assessment of AQRVs (Revised) ........................................................................................ 59

3.5.4. Determining Critical Loads (Revised).............................................................................................................. 62

3.5.5. Other AQRV Identification and Assessment Tools (Revised) ........................................................................... 64

3.5.6. Recommendations for Evaluating Potential Effects from Proposed Increases in Deposition

 to an FLM Area (Revised) .............................................................................................................................. 65

3.5.7. Summary (Revised)........................................................................................................................................ 71

3.5.8. Web sites for Deposition and Related Information (Revised) ......................................................................... 71

4. Expansion of Discussion of Process for Adverse Impact Determination (New Chapter) .................................. 73

4.1. Background ....................................................................................................................................................... 73

4.2. Regulatory Factors ............................................................................................................................................... 73

4.3. Contextual Considerations................................................................................................................................... 74

4.4. Preliminary Adverse Impact Concerns................................................................................................................... 74

4.5. Adverse Impact Determination............................................................................................................................. 74

5. Future FLAG Work.................................................................................................................................................... 75

5.1. Implementing FLAG Recommendations (Revised) ................................................................................................ 75

5.2. Phase I Updates (Revised) .................................................................................................................................... 75

5.3. Phase II Tasks (Revised)......................................................................................................................................... 75

Appendix A: Glossary................................................................................................................................................... 76

Appendix B: Legal Framework for Managing Air Quality and Air Quality Effects on Federal Lands.................... 79

Appendix C: General Policy for Managing Air Quality Related Values in Class I Areas ......................................... 84

Appendix D: Best Available Control Technology (BACT) Analysis ............................................................................ 85

Appendix E: Maps of Federal Class I Areas................................................................................................................. 86

Appendix F: FLAG 2000 Participants ........................................................................................................................... 89

Appendix G: Bibliography (Revised) ........................................................................................................................... 91

vi FLAG Phase I Report—Revised (2010)
Figure 1. Procedure for Visibility Assessment for Distant/Multi-Source Applications (Revised) ........................................ xii

Figure 2. FLM Assessment of Potential Ozone Effects from New Emissions Source (Revised) ......................................... xiii

Figure 3. FLM Assessment of Potential Deposition Effects from New Emissions Sources (Revised) ................................. xiv

Figure 4. Procedure for Visibility Assessment for Distant/Multi-Source Applications (Revised)........................................ 26

Figure 5. IMPROVE Equation for Calculating Light Extinction........................................................................................ 29

Figure 6. FLM Assessment of Potential Ozone Effects from New Emissions Source (Revised) ........................................ 57

Figure 7. FLM Assessment of Potential Deposition Effects from New Emissions Sources (Revised) ................................. 67

Figure 8. National Park Services Class I Areas ............................................................................................................... 86

Figure 9. Fish and Wildlife Service Class I Areas............................................................................................................ 87

Figure 10. Forest Service Class I Wilderness Areas ........................................................................................................ 88

Figures

 USFS–NPS–USFWS vii
Tables

Table 1. FLAG 2000 vs. FLAG 2010 Analyses.................................................................................................................. xi

Table 2. Section of Table 6 Used for Step 1 Calculations of the Alpine Lakes Wilderness Example................................. 27

Table 3. Step 3 Calculation Results for the Alpine Lakes Wilderness Example ............................................................... 27

Table 4. Step 4 Calculation Results for the Alpine Lakes Wilderness Example................................................................ 28

Table 5. 20% Best Natural Conditions – Concentrations and Rayleigh Scattering By Class I Area.................................. 30

Table 6. Annual Average Natural Conditions - Concentrations and Rayleigh Scattering By Class I Area......................... 34

Table 7. Monthly fL(RH) – Large (NH4)

2

SO4 and NH4NO3 Relative Humidity Adjustment Factor ....................................... 38

Table 8. Monthly fS(RH) – Small (NH4)

2

SO4 and NH4NO3 Relative Humidity Adjustment Factor ....................................... 42

Table 9. Monthly fSS(RH) – Sea Salt Relative Humidity Adjustment Factor ...................................................................... 46

Table 10. Monthly Average Natural Conditions Visual Range In Kilometers................................................................... 50

Table 11. Indicators for monitoring and evaluating effects from deposition of S and N (Revised) .................................. 60

viii FLAG Phase I Report—Revised (2010)
Under the Clean Air Act, the Federal Land Manager 

(FLM) and the Federal official with direct responsibility 

for management of Federal Class I parks and wilderness 

areas (i.e., Park Superintendent, Refuge Manager, Forest 

Supervisor) have an affirmative responsibility to protect 

the air quality related values (AQRVs) (including visibility) 

of such lands, and to consider whether a proposed major 

emitting facility will have an adverse impact on such values. 

The FLM’s decision regarding whether there is an adverse 

impact is then conveyed to the permitting authority – usually 

a State agency – for consideration in its determinations 

regarding the permit. The permitting authority’s 

determinations generally consider a wide range of factors, 

including the potential impact of the new source or major 

modification on the AQRVs of Class I areas, if applicable. 

Both State permitting agencies and permit applicants 

requested that the FLMs provide better consistency 

pertaining to their role in the review of new source permit 

applications near Federal Class I areas. To address this 

concern, the FLMs formed the Federal Land Managers’ Air 

Quality Related Values Work Group (FLAG). The official 

“FLM” is the Secretary of the department with authority 

over the Federal Class I areas (or the Secretary’s designee). 

For the Department of the Interior, the Secretary has 

designated the Assistant Secretary for Fish and Wildlife and 

Parks as the FLM, whereas the Secretary of Agriculture has 

delegated the FLM responsibilities to the Regional Forester, 

and in some cases, the Forest Supervisor.

The purpose of FLAG is twofold: (1) to develop a more 

consistent and objective approach for the FLMs to 

evaluate air pollution effects on public AQRVs in Class I 

areas, including a process to identify those resources and 

any potential adverse impacts, and (2) to provide State 

permitting authorities and potential permit applicants 

consistency on how to assess the impacts of new and 

existing sources on AQRVs in Class I areas, especially in 

the review of Prevention of Significant Deterioration (PSD) 

of air quality permit applications. Under the Clean Air Act, 

the FLM formal ”affirmative responsibility” role in the 

permitting process is limited to the extent a proposed new or 

modified source may affect AQRVs in a Class I area.1

1. Nevertheless, the FLMs are also concerned about resources in 

Class II parks and wilderness areas because they have other mandates 

to protect those areas as well. The information and procedures outlined 

in this document are generally applicable to evaluating the effect of new 

or modified sources on the AQRVs in both Class I and Class II areas, 

including the evaluation of effects as part of Environmental Assessments 

and/or Environmental Impact Statements under the National 

Environmental Policy Act (NEPA). However, FLAG does not preclude 

more refined or regional analyses being performed under NEPA or 

other programs.

FLAG members include representatives from three of the 

federal land management agencies that administer Federal 

Class I areas: the U.S. Forest Service (USFS), under the 

Department of Agriculture, and the National Park Service 

(NPS) and U.S. Fish and Wildlife Service (FWS) under 

the Department of the Interior, hereafter referred to as 

“the Agencies” or the “FLMs.” In addition, five Tribal 

governments each administer their redesignated Class I 

areas, and the Bureau of Land Management (BLM) jointly 

administers four mandatory Federal Class I areas with the 

USFS. BLM is not a member of FLAG. However, because 

BLM does manage federal PSD Class I lands, as well as 

large amounts of acres in the vicinity of many FLAG 

Agencies’ Class I areas, they may apply, when appropriate, 

the assessment methodologies outlined in the FLAG report. 

Applicants with the potential to adversely impact visibility 

or other AQRVs at PSD Class I areas administered by the 

BLM should contact that agency directly to discuss their 

considerations. The Agencies review permit applications 

for projects that may impact their areas, and make 

recommendations to their respective FLM as to whether or 

not those impacts might be considered adverse. The FLM 

will then make the final decision regarding the nature of the 

potential impacts to AQRVs, which is then conveyed to the 

permitting authority for its consideration.

In December 2000, after undergoing a public review and 

comment process that included a 90 day public comment 

period announced in the Federal Register and a public 

meeting, the FLMs published a FLAG Phase I Report (FLAG 

2000), along with an accompanying “Response to Public 

Comments” document. The FLAG 2000 report described 

the work accomplished in Phase I of the FLAG effort. FLAG 

2000 provided State permitting authorities and potential 

permit applicants a consistent methodology for conducting 

Class I area impact analyses. At that time, the Agencies 

envisioned a FLAG Phase II to address unresolved issues 

Preface to this Edition of the FLAG Phase I Report (New)

Adult Brown Pelicans on Breton Island National Wildlife Refuge, 

Louisiana. 

Credit: USFWS 

 USFS–NPS–USFWS ix
including those that will require research and the collection 

of new data. However, resource constraints have prevented 

the Agencies from embarking on a formal FLAG Phase II 

process, but the Agencies have made significant progress 

in obtaining effects-based information as part of their 

resource-protection responsibilities. This information is 

included in this revised report.

The Agencies formed three separate subgroups to deal with 

area specific technical and policy issues associated with 

visibility impairment, ozone effects on vegetation, and effects 

of pollutant deposition on soils and surface waters. FLAG 

2000 consolidated the results of those three subgroups.

FLAG 2000 included recommendations for completing 

and evaluating New Source Review (NSR) projects that 

may affect federally protected areas. It was intended to be 

a screening tool to help the Agencies and permit applicants 

determine whether impacts would be negligible. It was 

not intended to provide a bright-line test that would allow 

one to determine whether or not a proposed source of air 

pollution would cause or contribute to an adverse impact 

on AQRVs. That determination remains a project-specific 

management decision of the FLM. Among other factors, 

the FLMs’ assessment of whether or not an adverse impact 

would occur is based on the sensitivity of the AQRVs at the 

particular federally protected area under consideration, and 

the magnitude, frequency, duration, timing, and geographic 

extent of the estimated new source impacts. This report 

(FLAG 2010) reaffirms these intentions.

FLAG 2000 has been a useful tool to the Agencies, State 

permitting authorities, and permit applicants. It was 

intended to be a working document that would be revised 

as necessary as the Agencies learn more about how to better 

assess the health and status of AQRVs. Based on knowledge 

gained and regulatory developments since FLAG 2000, the 

Agencies believe certain revisions to FLAG 2000 are now 

appropriate. This revised report (FLAG 2010) reflects those 

changes. However, it is important to emphasize that in this 

revision the Agencies have made certain changes to update 

specific information and data, but retain intact much of the 

background and general information contained in FLAG 

2000 (e.g., Appendices A through H). Therefore, while this 

version replaces FLAG 2000, FLAG 2010 does not constitute 

a comprehensive update of all the information and material 

contained in FLAG 2000. Instead, the Agencies have focused 

their efforts on those areas of FLAG 2000 that have received 

the most attention and concern from permit applicants 

and permitting authorities. In that regard, the Agencies 

have included substantial changes to the visibility analysis 

sections, as well as included a more detailed discussion of 

the factors that the FLMs will use in the decision making 

process for an adverse impact determination. The Agencies 

have also taken this opportunity to discuss some key 

regulatory developments since FLAG 2000, as well as update 

some information in the FLAG 2000 deposition and ozone 

sections. To aid the FLAG user wanting to focus on the most 

recent changes, the Agencies have identified those new and 

revised sections throughout the FLAG 2010 report. 

The most significant changes in this FLAG 2010 revision are 

summarized as follows:

•	 Adopts similar criteria derived from EPA’s 2005 Best 

Available Retrofit Technology (BART) guidelines for the 

Regional Haze Rule to screen out from AQRV review 

those sources with relatively small amounts of emissions 

located a large distance from a Class I area (i.e., Q/D ≤ 10, 

for sources located greater than 50 km away).

•	 Utilizes the most recent EPA estimates to determine 

annual average or 20% best natural visibility conditions 

for Class I areas, using the new EPA-approved visibility 

algorithm.

•	 Adopts criteria derived from the 2005 BART guidelines 

that utilizes monthly average relative humidity adjustment 

factors to minimize the effects of weather events (i.e., 

short-term meteorological phenomena) on modeled 

visibility impacts. 

•	 Adopts criteria derived from the 2005 BART guidelines 

that sets a 98th percentile value to screen out roughly 

seven days of haze-type visibility impairment per year.

•	 Includes deposition analysis thresholds and concern 

thresholds for nitrogen and sulfur deposition impacts on 

vegetation, soils, and water.

•	 Increases transparency and consistency of factors 

considered for adverse impact determinations.

A comparison of these FLAG 2010 changes to information 

contained in FLAG 2000 is provided in Table 1:

Other changes of note included in FLAG 2010 are:

•	 Clarifies the near field visibility analysis techniques for 

analyzing plumes or layers viewed against a background;

•	 Expands discussion of “Critical Loads” to reflect some 

significant developments in this area since FLAG 2000; 

•	 Updates ozone sensitive species lists contained in 

Appendix 3.A of the FLAG 2000 report, but now includes 

that information on individual agency web sites rather 

than in the FLAG 2010 report;

•	 Replaces Appendix 3.B of FLAG 2000 (W126 and N100 

ozone values) with current information on the individual 

agency web sites;

•	 Updates the information contained in Table D-2 of FLAG 

2000 to reflect current information, but now includes that 

information on individual agency web sites rather than in 

the FLAG 2010 report;

•	 Replaces the dated sulfate, nitrate, and ammonium ion 

concentration maps (Figures D-2, D-3, and D-4 of FLAG 

2000), with a reference to the NADP site for current 

trends data. 

x FLAG Phase I Report—Revised (2010)
Table 1. FLAG 2000 vs. FLAG 2010 Analyses

FLAG 2000 FLAG 2010

Annual emissions/Distance 

(Q/D) screening criteria. (Not 

applicable for Class I increment 

analyses).

None ≤10 (sum of certain pollutant emissions (TPY) divided 

by distance (km) from Class I area; applies to all AQRVs, 

not just visibility. See section 3.2.

Background Visibility Conditions. Based on annual average natural, using 

NAPAP estimates.

Based on annual average natural, or 20% best natural, 

using EPA data from Regional Haze Rule development. 

See section 3.3.3. 

Relative Humidity Adjustment 

Factor (f(RH)).

Hour-by-hour (with RH capped at 98%). Monthly average (with RH capped at 95%). See section 

3.3.3.

First Level Screening Model. CALPUFF or CALPUFF-lite. CALPUFF only. See section 3.3.3.

Visibility Assessment Criteria. Maximum modeled value. 98th percentile modeled value at any receptor. See 

section 3.3.3.

Deposition Analysis Thresholds/

Concern Thresholds 

None Provided for nitrogen and sulfur deposition. See section 

3.5.6.

Adverse Impact Determination 

Criteria.

“Likely to Object” if 10% threshold 

exceeded; regulatory factors implicitly 

considered.

Adverse impact determination process more explicit; 

considers regulatory and other factors. See sections 

4.2-4.4

 USFS–NPS–USFWS xi
The Federal Land Managers’ Air Quality Related Values 

Work Group (FLAG) formed to develop a more consistent 

approach for the Federal Land Managers (FLMs) to 

evaluate air pollution effects on resources. As discussed 

in the Preface, the FLAG Phase I Report (FLAG 2000) is 

being revised in part at this time. The primary—but not 

sole—focus of FLAG is the New Source Review (NSR) 

program, especially in the review of Prevention of Significant 

Deterioration (PSD) of air quality permit applications. The 

goals of FLAG have been to provide consistent policies 

and processes both for identifying air quality related values 

(AQRVs) and for evaluating the effects of air pollution on 

AQRVs, primarily in Federal Class I air quality areas, but also 

in some instances, in other national parks, national forests, 

national wildlife refuges, wilderness areas, and national 

monuments. Federal Class I areas are defined in the Clean 

Air Act as national parks over 6,000 acres and wilderness 

areas and memorial parks over 5,000 acres, established as of 

1977. All other FLM areas are designated Class II. Maps of 

the Agencies’ Federal Class I areas are provided in 

Appendix E. 

FLMs have an “affirmative responsibility” to protect AQRVs. 

In this respect, the FLM role consists of considering 

whether emissions from a new or modified source may 

have an adverse impact on AQRVs and providing comments 

to permitting authorities (States or EPA). FLMs have no 

permitting authority under the Clean Air Act, and they have 

no authority under the Clean Air Act to establish air qualityrelated rules or standards. It is important to emphasize that 

the FLAG report only explains factors and information the 

FLMs expect to use when carrying out their consultative 

role. It is separate from Federal regulatory programs. 

FLAG members include representatives from the three 

primary agencies that administer the nation’s Federal Class 

I areas: the U.S. Forest Service (USFS), the National Park 

Service (NPS), and the U.S. Fish and Wildlife Service (FWS). 

(Subsequently in this report, these three agencies collectively 

will be referred to as “the Agencies” or the “FLMs.” Class 

I and Class II air quality areas are called “FLM areas” in 

this report.) Appendix F contains a list of participants that 

worked on the original FLAG 2000 report.

This report describes the work accomplished in Phase I of 

the FLAG effort as revised to reflect current developments. 

That work includes identifying policies and processes 

common to the FLMs (herein called “commonalities”) 

and developing new policies and processes using readily 

available information. This report provides State permitting 

authorities and potential permit applicants a consistent and 

predictable process for assessing the impacts of new and 

existing sources on AQRVs, including a process to identify 

those AQRVs and potential adverse impacts. The report also 

discusses considerations unrelated to new source review 

and managing emissions in Federal areas. If and when the 

Agencies embark on Phase II, FLAG will address unresolved 

issues including those that will require research and the 

collection of new data.

This revised FLAG Phase I Report consolidates the results 

of the FLAG Visibility, Ozone, and Deposition subgroups. 

The chapters prepared by these subgroups contain issuespecific technical and policy analyses, recommendations 

for evaluating AQRVs, and information for completing and 

evaluating NSR permit applications. This information and 

the associated recommendations are intended for use by the 

FLMs, permitting authorities, NSR permit applicants, and 

other interested parties. The report includes background 

information on the roles and responsibilities of the FLMs 

under the NSR program.

This document includes recommendations for completing 

and evaluating NSR applications that may affect Class I FLM 

areas. This information can also be used to evaluate impacts 

on Class II parks and wilderness areas. It does not provide a 

universal formula that would, in all situations, allow one to 

determine whether or not a source of air pollution causes 

or contributes to an adverse impact. That determination 

remains a project-specific management decision, the 

responsibility for which remains with the FLM, as delegated 

by Congress. The FLM’s assessment of whether or not an 

adverse impact would occur is based on the sensitivity of the 

AQRVs at the particular FLM area under consideration, as 

well as the consideration of several other factors, including 

the magnitude, frequency, duration, timing, and geographic 

extent of the new source’s impacts.

To provide information for the FLM’s assessment of adverse 

impacts on AQRVs, the permit applicant should identify the 

potential impacts of the source on all applicable AQRVs of 

that area. An FLM may ask that an applicant address any or 

all of the areas of concern. The primary areas of concern 

to the FLMs with respect to air pollution emissions are 

Executive Summary (Revised)

Marble Mountain Wilderness, California. 

Credit: Steve Boutcher

xii FLAG Phase I Report—Revised (2010)
visibility impairment, ozone effects on vegetation, and effects 

of pollutant deposition on soils and surface waters. 

The FLAG Phase I Report also describes the FLAG effort, 

including the FLAG approach, organization, and plans for 

future FLAG work. Appendix A of the report contains a 

glossary of technical terms, abbreviations, and acronyms 

used in the report along with associated definitions. 

Appendix G provides a list of all references cited in the 

FLAG report.

The key recommendations developed by the Visibility, 

Ozone, and Deposition subgroups are summarized below, 

and updated in part in this FLAG 2010 revision. However, 

for all three subject matter areas, FLAG recommends that 

the permit applicant consult with the appropriate permitting 

authority and with the FLM for the affected area(s) for 

confirmation of preferred procedures. This consultation 

should take place in the early stages of the permit application 

process.

Recommendations for Evaluating Visibility 

Impacts (Revised)

FLAG provides recommendations, specific procedures, and 

interpretation of results for assessing visibility impacts of 

new or modified sources on Class I area resources.2

FLAG addresses assessments for sources proposed for 

locations near (generally within 50 km) and at large distances 

(greater than 50 km) from these areas. The key components 

of the recommendations are highlighted below.

In general, FLAG recommends that an applicant:

•	 Apply the Q/D test (see “INITIAL SCREENING TEST” 

below) for proposed sources greater than 50 km from 

a Class I area to determine whether or not any further 

visibility analysis is necessary. 

•	 Consult with the appropriate regulatory agency and with 

the FLM for the affected Class I area(s) or other affected 

area for confirmation of preferred visibility analysis 

procedures.

•	 Obtain FLM recommendation for the specified reference 

levels (estimate of natural conditions) and, if applicable, 

FLM recommended plume/observer geometries and 

model receptor locations.

2. Nevertheless, the FLMs are also concerned about resources in 

Class II parks and wilderness areas because they have other mandates 

to protect those areas as well. The information and procedures outlined 

in this document are generally applicable to evaluating the effect of new 

or modified sources on the AQRVs in both Class I and Class II areas, 

including the evaluation of effects as part of Environmental Assessments 

and/or Environmental Impact Statements under the National 

Environmental Policy Act (NEPA). However, FLAG does not preclude 

more refined or regional analyses being performed under NEPA or 

other programs.

•	 Apply the applicable EPA Guideline, steady-state models 

for regions within the Class I area that are affected by 

plumes or layers that are viewed against a background 

(generally within 50 km of the source).

- Calculate hourly estimates of changes in visibility, as 

characterized by the change in the color difference 

index (∆E) and plume contrast (C), with respect to 

natural conditions, and compare these estimates with 

the thresholds given in section 3.3.3.

•	 For regions of the Class I area where visibility impairment 

from the source would cause a general alteration of the 

appearance of the scene (generally 50 km or more away 

from the source or from the interaction of the emissions 

from multiple sources), apply a non-steady-state air 

quality model with chemical transformation capabilities 

(refer to EPA’s Guideline on Air Quality Models), which 

yields ambient concentrations of visibility-impairing 

pollutants. At each Class I receptor:

- Calculate the change in extinction due to the source 

being analyzed, compare these changes with the 

reference conditions, and then compare these results 

with the thresholds given in section 3.3.3.

- Utilize estimates of annual average natural visibility 

conditions for each Class I area as presented in 

Table 6, unless otherwise recommended by the 

FLM or permitting authority. Alternative estimates 

of visibility conditions are provided in Table 5 

for consistency with State agencies that elected to 

use 20% best visibility for regional haze or BART 

implementations, or when FLMs recommend using 

the 20% best visibility as natural background. 

•	 If first-level modeling results are above levels of concern, 

continue to consult with the Agencies to discuss other 

considerations (e.g., possible impact mitigation, more 

refined analyses). 

This review process for distant/multi-source applications is 

portrayed schematically in Figure 1.

Recommendations for Evaluating Ozone 

Impacts (Revised)

•	 FLM actions or specific requests on a permit application 

will be based on the existing air pollution situation at the 

area they manage. These conditions include (1) whether 

or not actual ozone damage has occurred in the area, and 

(2) whether or not ozone exposure levels occurring in 

the area are high enough to cause damage to vegetation 

(i.e., phytotoxic O3

 exposures). Figure 2 shows the FLM 

review process to assess ozone impacts for a project that 

exceeds the initial annual emissions over distance (Q/D) 

screening criteria. As noted in Figure 2, ambient ozone 

concentrations are considered along with data from 

exposure response studies (EPA 2007b) to determine 

whether a source will cause or contribute to phytotoxic 

 USFS–NPS–USFWS xiii
ozone levels (i.e., levels toxic to plants) at the affected site. 

The FLM may ask the applicant to calculate the ozone 

exposure values if these data are not already available. 

Ozone damage to vegetation is determined from field 

observations at the impacted site.

•	 Oxidant stipple necrosis on plant foliage and ozoneinduced senescence infer adverse physiological or 

ecological effects, and are considered to be damage if they 

are determined to have a negative impact on aesthetic 

value.

•	 Established ozone metrics to describe ozone exposure are 

referenced.

•	 NOx

 and VOC emissions are of concern because they are 

precursors of ozone. Current information indicates most 

FLM areas are NOx

 limited. Until we determine the VOC 

or NOx

 status of each area, we will focus on NOx emission 

sources. 

Recommendations for Evaluating Deposition 

Impacts (Revised) 

For a project that exceeds the initial annual emissions over 

distance (Q/D) screening criteria, the permit applicant 

should consult with the appropriate regulatory agency and 

FLM for the affected area(s) to determine if a deposition 

impact analysis should be done (i.e., expected sulfur and/

Figure 1. Procedure for Visibility Assessment for Distant/Multi-Source Applications (Revised) 

*Q/D test only applies to sources located greater that 50 km from a Class I area.

**Difference Change in the 98th percentile with respect to (wrt) the annual average Natural Condition (NC). Applicant should use the 20th percentile best natural condition background if recommended by the FLM or permitting authority.

xiv FLAG Phase I Report—Revised (2010)
or nitrogen deposition impacts are above the Deposition 

Analysis Threshold (DAT) or concern threshold (see 

section 3.5.6). Please note that although mercury and other 

toxic emissions are of interest to the FLM, the deposition 

impact analyses discussed here applies only to nitrogen 

and sulfur emissions. If an analysis is advised, the permit 

applicant should obtain available information on Class I 

AQRVs, critical loads, and concern thresholds from the 

FLM. In addition, the applicant should refer to section 3.5.6 

‘Recommendations for Evaluating Potential Effects from 

Proposed Increases in Deposition to an FLM Area’ section 

of the Deposition Chapter. The following steps summarize 

that process.

•	 From the respective Agency web sites, identify available 

on-site or representative wet and dry deposition data for 

the FLM area. 

•	 Estimate the future deposition rate by adding the existing 

rate, the new emissions’ contribution to deposition, 

and the contribution of sources permitted but not yet 

operating, while subtracting emission reductions that 

will occur before the proposed source begins operation. 

Modeling of new, reduced, and permitted but not yet 

operating emissions’ contribution to deposition should be 

conducted following EPA recommendations.

•	 Compare the future deposition rate with the 

recommended screening criteria (e.g., critical load, 

Figure 2. FLM Assessment of Potential Ozone Effects from New Emissions Source (Revised)

*Q/D test only applies to sources located greater that 50 km from a Class I area.

**Note: Ambient ozone concentrations are considered along with data from exposure response studies (EPA 2007b) to determine whether a source 

will cause or contribute to phytotoxic ozone levels (i.e., levels toxic to plants) at the affected site. 

 USFS–NPS–USFWS xv
concern threshold, or screening level value) for the 

affected FLM area. A list of documents summarizing 

these screening criteria, where available, can be found in 

Appendix G. 

- Information for USFS Class I areas is also available at:

http://www.fs.fed.us/air

- NPS and FWS Class I area information is available at:

http://www.nature.nps.gov/air

•	 Figure 3 shows the FLM review process to assess 

deposition impacts from new emission sources.

Figure 3. FLM Assessment of Potential Deposition Effects from New Emissions Sources (Revised)

*Q/D test only applies to sources located greater that 50 km from a Class I area.

xvi FLAG Phase I Report—Revised (2010)
1. Background 

1.1. History (Revised)

The Clean Air Act Amendments of 1977 give Federal Land 

Managers (FLMs) an “affirmative responsibility” to protect 

the natural and cultural resources of Class I areas from the 

adverse impacts of air pollution (see Appendix B: ‘Legal 

Framework for Managing Air Quality and Air Quality Effects 

on Federal Lands’). FLM responsibilities include the review 

of air quality permit applications from proposed new or 

modified major pollution sources near these Class I areas. 

If, in its permit review, an FLM demonstrates that emissions 

from a proposed source will cause or contribute to adverse 

impacts on the air quality related values (AQRVs) of a Class 

I area, the permitting authority, typically the State, can deny 

the permit. 

The FLMs’ role in the reviewing of permit applications 

focuses on impacts to Class I areas.3

 Individually, FLMs have 

developed different approaches to identifying AQRVs and 

defining adverse impacts on AQRVs in Class I areas. For 

example, in 1988, the U.S. Department of Agriculture Forest 

Service (USFS) conducted a national screening process 

to identify the AQRVs for each of its Class I areas. Using 

this national process as a starting point, each USFS Region 

refined the screening parameters and identified sensitive 

AQRVs for many Class I areas. However, this resulted in 

differences in the approaches and levels used by USFS 

Regions. The U.S. Department of the Interior National Park 

Service (NPS) and the U.S. Fish and Wildlife Service (FWS) 

have adopted a case-by-case approach to permit review, 

considering the most recent information available for each 

area. NPS and FWS have included lists of sensitive AQRVs 

for their Class I areas in their Air Resources Information 

System (ARIS) database. 

1.1.1. FLAG Approach (Revised)

Air resource managers from the USFS, NPS, and FWS 

recognized the need for a more consistent approach 

among their agencies with respect to their efforts to protect 

AQRVs. In April 1997, an interagency Work Group was 

formed whose objective was “to achieve greater consistency 

in the procedures each agency uses in identifying and 

evaluating AQRVs.” The Work Group named itself the 

3. Nevertheless, the FLMs are also concerned about resources in 

Class II parks and wilderness areas because they have other mandates 

to protect those areas as well. The information and procedures outlined 

in this document are generally applicable to evaluating the effect of new 

or modified sources on the AQRVs in both Class I and Class II areas, 

including the evaluation of effects as part of Environmental Assessments 

and/or Environmental Impact Statements under the National 

Environmental Policy Act (NEPA). However, FLAG does not preclude 

more refined or regional analyses being performed under NEPA or 

other programs. 

Federal Land Managers’ Air Quality Related Values Work 

Group, or FLAG. Although FLAG membership comprises 

air resource managers and subject matter experts from the 

three agencies, representatives from the Bureau of Land 

Management, the U.S. Environmental Protection Agency 

(EPA), U.S. Geological Survey, and State air agencies have 

also participated in FLAG efforts. 

FLAG participants have collaborated to:

- define sensitive AQRVs,

- identify the critical loads (or pollutant levels) that 

would protect an area and identify the criteria that 

define adverse impacts, and

- standardize the methods and procedures for 

conducting AQRV analyses.

To accomplish its objective, FLAG started with (and will 

continue to build on) the procedures, terms, definitions, and 

screening levels common to the three agencies. Many such 

“commonalities” were identified early in the FLAG planning 

sessions (see section 1.4, ‘Commonalities Among Federal 

Land Managers’).

FLAG’s “Action Plan” stipulates a phased approach. Phase 

I addressed issues that could be resolved without research 

or the collection of new data. When the Agencies embark 

on FLAG Phase II, they will address the more complex and 

unresolved issues from Phase I that may require additional 

data collection (see section 5, ‘Future FLAG Work’).

The FLAG effort focuses on the effects of the air pollutants 

that could affect the health of resources in Class I areas, 

primarily pollutants such as ozone, particulate matter, 

nitrogen dioxide, sulfur dioxide, nitrates, and sulfates. In 

Phase I, FLAG concentrated on four issues: (1) terrestrial 

effects of ozone; (2) aquatic and terrestrial effects of wet and 

dry pollutant deposition; (3) visibility impairment; and (4) 

process and policy issues. Four subgroups, one for each of 

UL Bend National Wildlife Refuge, Montana. 

Credit: Maribeth Oaks/The Wilderness Society

 USFS–NPS–USFWS 1
these issues, were formed and charged with developing a set 

of recommendations for consistent policies and processes. 

FLAG 2000’s findings and technical recommendations 

underwent scientific peer review, as well as review by agency 

decision-makers such as Class I area Park Superintendents, 

Refuge Managers, and Forest Supervisors; Regional 

Foresters; and the Assistant Secretary for Fish and Wildlife 

and Parks. (Note: USFS has designated the FLM as the 

Regional Foresters and, in some cases, Forest Supervisors.) 

FLAG products have also undergone public review and 

comment. A “notice of availability” of the draft FLAG 2000 

report was published in the Federal Register, and the FLMs 

conducted a public meeting to discuss the draft FLAG report 

and provided a 90 day public comment period. For the 

FLAG 2010 revisions, the FLMs announced the availability 

of the draft report in the Federal Register and provided a 60 

day public comment period. There was not sufficient public 

interest to conduct a public meeting to discuss the proposed 

revisions to the FLAG report.

1.1.2. FLAG Organization

In addition to the four subgroups (policy, deposition, 

ozone, and visibility), the FLAG organization included 

Leadership and Coordinating Committees and a Project 

Manager. The Leadership Committee, which includes the 

air quality program chiefs from the three FLM agencies, 

was responsible for providing direction to the Work Group 

and the resources necessary for FLAG to accomplish 

its objective. The Coordinating Committee, which also 

includes representatives from each agency, was responsible 

for communications within the Work Group, including 

coordination among the agencies and subgroups. The FLAG 

Project Manager coordinated FLAG activities, served as a 

single point-of-contact for the subgroups, and performed 

other administrative functions. 

1.2. Overview of Resource Issues (Revised)

Research conducted on Federal lands by FLMs and others 

has characterized natural resource effects associated with air 

pollution, and has helped identify those particular resources 

that are vulnerable to pollution in different areas. This 

effort does not address the impacts from air pollution on 

cultural resources. Documented effects include impairment 

of visibility, injury and reduced growth of vegetation, and 

acidification and fertilization of soils and surface waters. 

Air pollution effects on resources have been identified in a 

number of FLM areas; a few examples are provided below. 

It is important to note that similar, or even more serious, 

air pollution effects may be occurring on all Federal lands, 

but FLMs have not had the financial resources to perform 

the inventorying, monitoring, and/or research necessary 

to document such effects. Furthermore, the sensitivity of 

resources may vary from area to area because the nature of 

the resource, as well as geological, meteorological, biological, 

and other factors, vary from place to place.

1.2.1. Visibility

Visitors to national parks and wildernesses list the ability 

to view unobscured scenic vistas as a significant part of a 

satisfying experience. Unfortunately, visibility impairment 

has been documented in all Class I areas with visibility 

monitoring. Most visibility impairment is in the form of 

regional haze. The greatest visibility impairment due to 

regional haze occurs in the eastern United States and in 

southern California, while the least impairment occurs in 

the Colorado Plateau and Nevada Great Basin areas, and 

in Alaska. Ammonium sulfate contributes at least 50% to 

visibility impairment at most Class I areas in the eastern 

United States. The contribution to visibility impairment 

from ammonium nitrate is highest in central and southern 

California and in the Midwest. The largest region of 

high rural organic carbon visibility impairment is in the 

southeastern United States; impairment in this range is also 

present in the Sierra Nevada region of California and in the 

northern Rockies of Montana. The highest contribution 

to visibility impairment from fine soil is found in the arid 

Southwest. The highest coarse particle contribution to 

impairment is also in the arid Southwest and southern 

California. (DeBell et al. 2006) Visibility impairment on 

Federal lands can also result from plume intrusion and has 

been documented in Mount Zirkel Wilderness, Moosehorn 

National Wildlife Refuge, and Grand Canyon National Park.

1.2.2. Vegetation

While several components of air pollution (e.g., sulfur 

dioxide, nitrogen dioxide, and peroxyacyl nitrates) can 

affect vegetation, ozone is generally acknowledged as the air 

pollutant causing the greatest amount of injury and damage 

to vegetation. The most common visible effects are stipple 

(dark colored lesions on leaves resulting from pigmentation 

of injured cells), fleck (collapse of a few cells in isolated 

areas of the upper layers of the leaf, resulting in tiny lightcolored lesions), mottle (degeneration of the chlorophyll in 

certain areas of the leaf giving the leaf a blotchy appearance), 

necrosis (death of tissue), and in extreme cases, mortality. 

Aside from visible injury, ozone exposure can result in less 

obvious physiological impairment such as decreased growth 

or altered carbon allocation. 

Ozone fumigation experiments have identified a number 

of plant species that are sensitive to ozone. For example, 

fumigations were conducted in Great Smoky Mountains 

National Park (Tennessee and North Carolina) from 1987 

to 1992. On the basis of foliar injury, thirty species were 

rated as sensitive to ozone levels that occurred in the park. 

The species with foliar injury included black cherry (Prunus 

serotina) and American sycamore (Platanus occidentalis). 

Additional observations and physiological measurements 

2 FLAG Phase I Report—Revised (2010)
indicated elevated ozone concentrations reduced leaf, root, 

and total dry weights, and increased the severity of leaf 

stipple and premature leaf abscission in these two species 

(Neufeld and Renfro 1993a,b). Field observations have 

documented foliar injury of these species in other eastern 

United States areas such as Brigantine Wilderness (New 

Jersey) and Cape Romain Wilderness (South Carolina).

Ponderosa pine (Pinus ponderosa) and Jeffrey pine (Pinus 

jeffreyi) are recognized as good candidates for ozoneinjury surveys in the western United States, based on their 

documented sensitivity. For example, these species were 

examined for ozone injury in national parks and national 

forests in the California Sierra Nevada from 1991 to 1995. 

The sites surveyed included Lassen Volcanic, Yosemite, 

and Sequoia/Kings Canyon National Parks and the Tahoe, 

Eldorado, Stanislaus, Sierra, and Sequoia National Forests. 

Foliar injury attributable to ozone was found at all areas, 

and the extent of injury generally increased in a southward 

direction along the Sierra Nevada (Miller 1995). 

1.2.3. Soils and Surface Waters

Acidity in rain, snow, cloud water, and dry deposition 

can affect soil fertility and nutrient cycling processes in 

watersheds and can result in acidification of lakes and 

streams with low buffering capacity. Deposition of sulfate 

to sensitive watersheds results in leaching of base cations, 

soil acidification, and surface-water acidification. In some 

soils, sulfate adsorption results in “delayed” acidification of 

surface waters. Deposition of excess nitrogen species (nitrate 

and ammonium) to both terrestrial and aquatic systems 

can result in acidifying streams, lakes, and soils. There is 

also evidence that nitrogen deposition can cause shifts in 

phytoplankton composition in lakes in which biological 

activity is limited by nitrogen availability, i.e., increased 

nitrogen deposition can cause phytoplankton species that 

use nitrogen more efficiently to eventually dominate the lake. 

Water chemistry surveys and on-going monitoring show 

that many high elevation lakes on Federal lands in the Sierra 

Nevada, Cascades, and Rocky Mountains are sensitive to 

acid deposition. In general, these lakes are on bedrock that 

provides them with very little buffering capacity. Some of 

these lakes, for example, Loch Vale in Rocky Mountain 

National Park (Colorado) experience episodic acidification 

during Spring snow melt (Baron and Campbell 1997).

Through funding provided by the Southern Appalachian 

Mountains Initiative, Herlihy et al. (1996) compiled 

information on surface water sensitivity of streams in nine 

of the eleven Class I areas in the Southern Appalachians. 

The nine Class I areas were grouped according to geology, 

physiography, and stream chemistry, then the groupings were 

ranked in terms of effects. Class I areas in the West Virginia 

Plateau (Otter Creek and Dolly Sods Wildernesses) had 

the highest percentage of acidic stream length and lowest 

pH values. Class I areas in the Northern and Southern Blue 

Ridge (e.g., Shenandoah National Park in Virginia and Joyce 

Kilmer/Slickrock Wilderness in North Carolina) had a lower 

percentage of acidic stream length, however, streams with 

low buffering capacity were common. The Alabama Plateau 

Class I area (Sipsey Wilderness) had streams with the highest 

buffering capacity. (Note that the authors based their report 

on surveys conducted by others and did not account for 

potential differences in methods of data collection.)

A number of Federal areas contain estuarine and coastal 

areas that may experience eutrophication as a result of 

excess nitrogen deposition resulting from air pollution 

and other sources of nitrogen. For example, symptoms of 

eutrophication, including nutrient enrichment and algal 

blooms, have been observed in Everglades National Park and 

Chassahowitzka Wilderness (Florida).

1.3. Legal Responsibilities (Revised)

The specific legal responsibilities that Congress has given 

FLMs to protect natural, cultural, and scenic resources 

on the public lands from air pollution are identified in 

Appendix B. Statutes described in Appendix B include 

agency organic acts, the Wilderness Act, and the Clean Air 

Act (CAA).

The fundamental Congressional direction for managing 

public lands arises out of respective organic acts. Each 

of these laws is essentially a charter from Congress to 

the Executive Branch providing a purpose for parks, 

wildernesses, and refuges, respectively, and establishing 

broad management objectives for these areas. The 

Wilderness Act sets aside a subset of these public lands 

where natural processes are allowed to dominate. The 

agency stewards develop specific management objectives 

building on the organic acts using public involvement, 

regulations, best available science, and additional direction 

provided by Congress. 

Among this additional Congressional direction is the Clean 

Air Act (CAA). It further characterizes some of the public 

lands as “Class I” areas and bestows on the land managers 

an affirmative responsibility to protect these areas from 

air pollution. The CAA directs that the FLMs identify 

and protect air quality related values, including visibility. 

This direction is consistent with the underlying charters 

provided by the organic acts and the Wilderness Act. The 

similarities of management objectives, and of the policies 

and procedures necessary for protecting Class I areas, are 

at the core of the FLAG process. Please note that although 

all wilderness is not Class I, and the FLMs have not 

proposed that non-Class I wilderness be classified as Class 

I, management actions (e.g., limiting human activities) that 

satisfy wilderness management objectives for Class II areas, 

are often substantially the same as those used in Class I area 

management. 

 USFS–NPS–USFWS 3
In implementing laws, it is essential to understand the 

intent of Congress. In the case of the CAA, the FLM gleans 

additional insight from a passage in Senate Report No. 95-

127, 95th Congress, 1st Session, 1977 which states: 

The Federal Land Manager holds a powerful tool. He 

is required to protect Federal lands from deterioration 

of an established value, even when Class I [increments] 

are not exceeded. ... While the general scope of the 

Federal Government’s activities in preventing significant 

deterioration has been carefully limited, the FLM 

should assume an aggressive role in protecting the air 

quality values of land areas under their jurisdiction. In 

cases of doubt the land manager should err on the side 

of protecting the air quality-related values for future 

generations.

Although the FLMs have an “affirmative responsibility” to 

protect AQRVs, they have no permitting authority under the 

CAA, and they have no authority under the CAA to establish 

air quality-related rules or standards. The FLM role within 

the regulatory context consists of considering whether 

emissions from a new source, or emission increases from 

a modified source, may have an adverse impact on AQRVs 

and providing comments to permitting authorities (States 

or EPA). It is important to emphasize that the FLAG report 

only explains factors and information the FLMs expect to 

use when carrying out their consultative role. It is not a rule 

or standard. 

The FLAG report describes the steps and process that 

the FLMs intend to go through in order to perform their 

statutory duties. Consequently, the scope of the FLAG 

report is to provide a more consistent approach for the three 

FLM agencies to evaluate air pollution effects on resources, 

and to provide guidance to permitting authorities and permit 

applicants regarding necessary AQRV analyses. Although 

FLAG strives to be consistent with regulatory programs and 

initiatives such as the Regional Haze Rule and New Source 

Review Reform, no direct ties exist between FLAG and these 

regulatory requirements.

1.4. Commonalities Among Federal Land 

Managers

If a new source is proposed near two or more areas managed 

by different FLMs, the FLMs generally try to coordinate 

in their interactions with the permitting authority and with 

the applicant. For example, two or more FLMs involved 

in pre-application meetings typically try to minimize the 

workload for the applicant by reaching agreement on the 

types of analyses the application should contain. Beyond 

coordinating during permit review, FLMs currently base 

requests and decisions on similar principles regarding 

resource protection and FLM responsibilities. Listed below 

are the common principles in five areas of air resource 

management. In addition, Appendix C provides the FLM’s 

‘General Policy for Managing Air Quality Related Values in 

Class I Areas.’ 

1.4.1. Identifying AQRVs (Revised)

FLMs agree on the following definition of an AQRV: 

A resource, as identified by the FLM for one or more 

Federal areas that may be adversely affected by a change 

in air quality. The resource may include visibility or a 

specific scenic, cultural, physical, biological, ecological, 

or recreational resource identified by the FLM for a 

particular area.

This definition is compatible with the general definition of 

AQRV that appears in the Federal Register (45 FR 43003, 

June 25, 1980). That definition includes visibility, flora, fauna, 

odor, water, soils, geologic features, and cultural resources. 

FLMs have the responsibility to identify specific AQRVs of 

areas they manage. To this end, FLMs further refine AQRVs 

beyond the above definition to be more site-specific (i.e., 

area specific) by using on-site information. To the extent 

possible, the FLMs have identified specific AQRVs for 

many Class I areas. Site-specific AQRV lists are available 

on the respective Agency web sites, or by contacting the 

Agencies directly. The FLMs also recognize that, ideally, 

inventories should be developed for all Class I areas. The 

FLMs may identify additional AQRVs in the future as 

more is learned through science about the sensitivity of 

resources to air pollution. A public process involving the 

regulated community and other interested members of 

the public is necessary and will be accomplished through 

participation in the land management planning process or 

reply to an announcement in the Federal Register. Finally, 

FLMs agree on the need for continued inventory, research, 

and monitoring to improve their ability to determine which 

AQRVs are most sensitive to air pollution and the sensitivity 

of these AQRVs. 

1.4.2. Determining the Levels of Pollution that 

Trigger Concern for the Well-Being of AQRVs 

(Revised)

FLMs acknowledge the importance of being able to agree 

among themselves on the levels of pollution that trigger 

concerns for AQRVs. FLMs recognize the need to assess 

cumulative impacts and the difficulties associated with 

this process. Difficulties arise when a large number of 

minor source impacts eventually lead to an unacceptable 

cumulative impact or when a new source applies for a PSD 

permit in an area that has a high background concentration 

of pollution from existing sources. The agencies will evaluate 

a proposed new source within the context of the total 

impacts that are occurring or that potentially could occur 

from permitted/existing sources on the AQRVs of the area 

and should consider the effects of both emission increases 

and decreases.

4 FLAG Phase I Report—Revised (2010)
1.4.3. Visibility

FLMs use EPA-approved models [Appendix W of Part 51 

(EPA’s Guideline on Air Quality Models, revised November 

2005), as required under the PSD regulations at 40 CFR 

51.166(1) and 52.21(1)] and the recommendations of 

the Interagency Work Group on Air Quality Modeling 

(IWAQM) to evaluate visibility impacts. The models use 

thresholds of visibility degradation measured in light 

extinction to evaluate source impacts to haze (far-field/

multi-source impacts), and EPA established criteria for 

coherent plume impacts (near-field impacts). Currently 

all FLMs use Interagency Monitoring of Protected Visual 

Environments (IMPROVE) monitoring data to determine 

current conditions for visibility in FLM areas.

1.4.4. Biological and Physical Effects

All FLMs rely on research, monitoring, models, and effects 

experts to identify and understand physical, biological, and 

chemical changes resulting from air pollution and relating 

them to changes in AQRVs. Further, they focus on sensitive 

AQRVs (defined as either species or processes) to assess this 

biological/physical/chemical change.

1.4.5. Determining Pollution Levels of Concern 

(Revised)

FLMs rely on the best scientific information available in 

the published literature and best available data to make 

informed decisions regarding levels of pollution likely to 

cause adverse impacts. FLMs re-evaluate, update, and 

assess this information as appropriate. They consider 

specific Agency and Class I area legislative mandates in 

their decisions and, in cases of doubt, “err on the side of 

protecting the AQRVs for future generations.” (Senate 

Report No. 95-127, 95th Congress, 1st Session, 1977)

For air quality dispersion modeling analyses, FLMs follow 

Appendix W of Part 51 (EPA’s Guideline on Air Quality 

Models, revised November 2005), as required under the 

PSD regulations at 40 CFR 51.166(1) and 52.21(1), and the 

recommendations of the Interagency Work Group on Air 

Quality Modeling (IWAQM). FLMs recommend protocols 

for modeling analyses to permit applicants on a case-by-case 

basis considering types and amount of emissions, location 

of source, and meteorology. When reviewing modeling 

and impact analysis results, all FLMs consider frequency, 

magnitude, duration, location of impacts, and other factors, 

in determining whether impacts are adverse.

1.4.6. FLM Databases (Revised)

Air Resources Information System (ARIS) (Formerly Air 

Synthesis) (Revised)

ARIS provides information on air quality related values in 

NPS and FWS Class I areas, as well as in many NPS Class 

II areas. ARIS identifies specific AQRVs, and provides 

information on air quality and its effects in parks and 

wildernesses. 

Natural Resource Information System – Air Module 

(NRIS-AIR) (Revised)

Publicly available USDA Forest Service Class I and II area 

information and related resource data can be linked to or 

found at http://www.fs.fed.us/air. If desired information and 

data cannot be found, contact any air program manager or 

specialist at national or regional offices for assistance.

1.5. Regulatory Developments Since FLAG 

2000 (New)

Several regulatory developments have occurred since the 

FLMs published the FLAG report in December 2000. Some 

of these regulatory developments may have a significant 

effect on air resource management in mandatory Class 

I areas, or how these effects are assessed. First, on April 

15, 2003, the Environmental Protection Agency (EPA) 

promulgated revisions to Appendix W of 40 C.F.R. 

§51 (Guideline on Air Quality Models). EPA revised the 

Guideline to adopt the CALPUFF model as a preferred 

long-range transport model for inclusion in Appendix A 

of that document. Prior to that date, FLAG 2000 relied on 

CALPUFF as the suggested model of choice for long-range 

transport assessments in accordance with recommendations 

of the Interagency Work Group on Air Quality Models 

(IWAQM). EPA’s adoption of CALPUFF substantiates 

the Agencies’ model choice. In addition, EPA’s action, 

combined with improved computer technology, has resulted 

in the availability of more meteorological data. These 

improvements have enhanced the ability of permitting 

authorities and applicants to perform the types of modeling 

analyses suggested in FLAG. However, the FLMs will 

continue to work with the EPA on recommendations for 

future long-range transport model development. 

On May 12, 2005, the EPA published the Clean Air 

Interstate Rule (CAIR) to reduce interstate transport of 

fine particulate matter and ozone. The CAIR applied to 28 

eastern states and the District of Columbia, and required 

those areas to significantly reduce emissions of sulfur 

dioxide (SO2

) and/or nitrogen oxides (NOx) from utilities. 

Although EPA developed the CAIR to address violations of 

the National Ambient Air Quality Standards (NAAQS) for 

fine particulates (PM2.5) and ozone, the associated SO2

 and 

NOx

 emission reductions would also benefit visibility and 

other AQRVs at many eastern Class I areas. The Agencies 

supported the CAIR, however, because it did not apply to 

western states, the majority of the Class I areas would not 

have directly benefited from the rule. Please note that at the 

time of this writing CAIR has been remanded to the EPA 

for revision to address various court challenges, and EPA 

has proposed a new transport rule as a replacement (EPA 

2010a).

 USFS–NPS–USFWS 5
On July 6, 2005, the EPA published a final rule and 

associated guidelines that detail the Best Available Retrofit 

Technology (BART) requirements of the Regional Haze 

Rule. Among other things, the BART guidelines advise 

States to rely on the CALPUFF model for long-range 

visibility impairment assessments, provide thresholds for 

what constitutes causing or contributing to regional haze 

visibility impairment, and includes screening level values that 

exempt certain sources from further analysis. As discussed 

in more detail below, the Agencies believe the assumptions 

and methodology included in the BART guidelines also 

have merit with respect to evaluating haze-like visibility 

impairment for New Source Review under the PSD and 

other programs. Consequently, the Agencies are paralleling 

some of those BART guidelines in this FLAG revision.

Please note that FLAG 2000 acknowledges the EPA’s July 

1999 Regional Haze Rule, and discusses possible changes 

to FLAG that may be necessary as States implement the 

Regional Haze Rule. Although the EPA promulgated the 

Regional Haze Rule before the FLMs published FLAG 2000, 

there were several improvements and differences in the 

associated EPA guidance documents (e.g., those related to 

Natural Conditions and Tracking Progress) that were not 

finalized until December 2003. Therefore, these documents 

were not reflected in FLAG 2000, but have been considered 

in this revision. Currently, State Implementation Plans 

(SIPs) under the Regional Haze Rule are being developed, 

and submitted to the EPA for approval. If the new visibility 

SIPs adequately account for new source growth, the 

Agencies may need to make further revisions to the FLAG 

recommendations to reflect progress made through the SIP 

process that could minimize the focus the FLMs place on 

individual sources.

EPA has also developed other regulations, standards, and 

policies that will help reduce air pollution and resulting 

impacts at FLM areas (e.g., revised ozone, sulfur dioxide, 

nitrogen dioxide, and particulate matter standards; mobile 

source controls).

6 FLAG Phase I Report—Revised (2010)
2. Federal Land Managers’ 

Approach to AQRV Protection 

FLM responsibilities for resource protection on Federal 

lands are clear and there should be no misunderstanding 

regarding the tools the FLM uses to fulfill these 

responsibilities. Opportunities to influence decisions 

regarding pollution sources external to the park or 

wilderness are limited. However, FLMs strive to minimize 

emissions from internal sources and their effects. 

Approaches for minimizing air pollution from external and 

internal sources are discussed in detail below.

2.1. AQRV Protection and Identification 

(Revised)

Congress assigned the FLMs an affirmative responsibility to 

protect AQRVs in Federal Class I areas. The FLMs interpret 

this assignment as a responsibility to:

•	 Identify AQRVs in each of the Class I areas.

•	 Establish inventorying and monitoring protocols for 

AQRVs.

•	 Prioritize AQRV inventorying and monitoring.

•	 Specify a process for evaluating air pollution effects on 

AQRVs, including the use of sensitive indicators.

•	 Specify adverse effects for each AQRV. 

To the extent possible, AQRVs have been identified for 

each Class I area. As noted above, the FLMs may identify 

additional AQRVs in the future as more is learned about 

the sensitivity of resources to air pollution. The FLMs will 

provide a public process involving the regulated community 

and other interested members of the public in order to seek 

public input regarding AQRV-identification issues. This 

desired public involvement will be accomplished through 

participation in the land management planning process or 

reply to an announcement in the Federal Register.

While the sensitivity of an AQRV to air pollution may be 

known, long-term monitoring of the health or status of 

the AQRV may not have been accomplished. The expense 

of monitoring all AQRVs simultaneously is prohibitive. 

Consequently, FLMs seek opportunities through the 

permitting process and through partnerships to gather more 

information about condition of AQRVs.

Because AQRVs themselves are often difficult to measure, 

surrogates are used as indicators, or sensitive indicators, of 

the health or status of the AQRV. A working process for Class 

I area management and AQRV protection is outlined ahead 

in this document. 

An adverse impact is determined for each AQRV. An adverse 

impact from air pollution results in a diminishment of 

the Class I area’s national significance, that is, the reason 

the Class I area was created. Adverse impacts can also 

be an impairment of the structure or functioning of the 

ecosystem, as well as an impairment of the quality of the 

visitor experience. The FLMs make an adverse impact 

determination on a case-by-case basis, based on technical 

and other information, which is then conveyed to the 

permitting authority.4

 The permitting authority then 

considers this, along with other factors, in its determination 

regarding the permit application.

2.2. New Source Review (Revised)

Section 165 of the CAA spells out the roles and 

responsibilities for FLMs in New Source Review, including 

the Prevention of Significant Deterioration (PSD) permitting 

program. Other laws, such as the respective agency organic 

acts and the Wilderness Act, provide the fundamental 

underpinning of land management direction to land 

managers. The following discussion merges this complex 

labyrinth of legal responsibilities as it relates to air resource 

management. 

2.2.1. Roles and Responsibilities of FLMs 

(Revised)

The federal officials directly responsible for the national 

parks, national wildlife refuges, and national forests 

(e.g., park superintendents, refuge managers, and forest 

supervisors, respectively) derive their responsibility from the 

respective agency organic acts. Furthermore, these officials, 

and the FLM for the respective agencies, have an affirmative 

responsibility under Section 165 of the CAA to protect and 

4. As discussed elsewhere in this report, if a proposed source’s 

impacts on AQRVs exceed established significance criteria, the FLMs 

will consider the magnitude, frequency, geographic extent, etc. of the 

impacts, and other relevant factors, in determining whether or not the 

impacts are adverse. 

Sipsey Wilderness, Alabama. 

Credit: Steve Boutcher

 USFS–NPS–USFWS 7
enhance the AQRVs of Class I areas from the adverse effects 

of air pollution. The FLM for the USFS is the Regional 

Forester or the Forest Supervisor depending on the specific 

location. The FLM for the NPS and FWS is the Department 

of the Interior’s Assistant Secretary for Fish and Wildlife and 

Parks. 

The FLMs have visibility protection responsibility under 

40 CFR §51.307 (New source review), which spells out 

the requirements for State Implementation Plan (SIP) 

visibility protection programs, as well as 40 CFR §52.27 

(Protection of visibility from sources in attainment areas) 

and 40 CFR §52.28 (Protection of visibility from sources 

in non-attainment areas). These three provisions, taken 

together along with the SIP-approved rules, establish the 

visibility protection program for new and modified sources 

throughout the country.

Notification

Section 165 (42 USC 7475) of the CAA requires the EPA, 

or the State/local permitting authority, to notify the FLM if 

emissions from a proposed project may impact a Class I area. 

The permitting authority should forward PSD applications 

to the FLM for review and analysis as soon as possible 

after receipt, giving the FLM an opportunity to review the 

application concurrently with the permitting authority. 

Generally, the permitting authority should notify the FLM 

of all new or modified major facilities proposing to locate 

within 100 km (62 miles) of a Class I area. In addition, the 

permitting authority should notify the FLM of “very large 

sources” with the potential to affect Class I areas proposing 

to locate at distances greater than 100 km. (Reference March 

19, 1979, memorandum from EPA Assistant Administrator 

for Air, Noise, and Radiation to Regional Administrators, 

Regions I - X). Given the multitude of possible size/distance 

combinations, the FLMs can not precisely define in advance 

what constitutes a “very large source” located more than 100 

km away that may impact a particular Class I area. However, 

as discussed elsewhere in this report, the Agencies have 

adopted a size (Q)/distance (D) criteria to screen out from 

AQRV review those sources with relatively small amounts 

of emissions located a large distance from a Class I area. 

Consequently, as a minimum, the permitting authority 

should notify the FLM of all sources that exceed this Q/D 

criteria. Nevertheless, the FLM and permitting authority 

should still work together to determine which other PSD 

applications the FLM is to be made aware of in excess of 100 

km. In making this determination, the FLM and permitting 

authority should consider, on a case-by-case basis, such 

factors as:

•	 Current conditions of sensitive AQRVs;

•	 Magnitude of emissions;

•	 Distance from the Class I area;

•	 Potential for source growth in an area/region;

•	 Existing/prevailing meteorological conditions;

•	 Cumulative effects of several sources to AQRVs, as well as 

changes in their emissions.

Additionally, such dialogue facilitates coordination between 

permitting authorities and the FLMs. The significance of 

the impact to AQRVs is more important than the distance 

of the source. Not all PSD permit applications that the 

FLM is notified of will be analyzed in-depth by the FLM. 

FLM notification of a PSD permit application for a project 

located greater than 100 km does not mean that the 

permit application will be reviewed by the FLM in detail. 

Notification of PSD permit applications in excess of 100 km 

by the permitting authority allows the FLM to gauge the level 

of potential cumulative effects. As indicated above, the FLM 

decides which PSD permit applications to review on a caseby-case basis depending on the potential impacts to AQRVs.

Pre-Application Meetings 

To expedite the PSD permit review process, the FLM 

encourages pre-application meetings with permitting 

authorities and permit applicants to discuss air quality 

concerns for a specific Class I area in question. Given 

preliminary information, such as the source’s location 

and the types and quantity of projected air emissions, the 

FLM can discuss specific AQRVs for an area and advise the 

applicant of the analyses needed to assess potential impacts 

on these resources. 

Completeness Determination

To further minimize delays, the FLMs encourage the 

permitting authority to use comments provided by the FLM 

concerning the completeness of the application, and to not 

deem the application complete until the applicant performs 

all necessary air quality impact analyses, including all 

relevant AQRV impact information. The permitting authority 

should then notify the FLM when they deem the application 

to be complete. 

Visibility Protection Procedures 

Additional procedural requirements apply when a proposed 

source has the potential to impair visibility in a Class I 

area (40 CFR §52.27(d)(2007); 40 CFR §51.307(a)(2007)). 

Specifically, the permitting authority must, upon receiving 

a permit application for a source that may affect visibility in 

any Class I area, notify the FLM in writing. Such notification 

shall include a copy of all information relevant to the permit 

application, including the proposed source’s anticipated 

impacts on visibility in a Class I area. The permitting 

authority shall notify the FLM within 30 days of receipt and 

at least 60 days prior to the close of the comment period.

If the FLM notifies the permitting authority that the 

proposed source may adversely impact visibility in a Class 

I area, or may adversely impact visibility in a previously 

identified integral (scenic) vista, then the permitting 

8 FLAG Phase I Report—Revised (2010)
authority is to work with the FLM to address their concerns. 

If the permitting authority agrees with the FLM’s finding 

that visibility in a Class I area may be adversely affected, 

the permit may not be issued. Even though the permitting 

authority may agree with the FLM’s adverse impact finding 

regarding integral vistas, the permitting authority may still 

issue a permit if the emissions from the source are consistent 

with reasonable progress toward the national goal of 

preventing or remedying visibility impairment. In making 

this decision, the permitting authority may take into account 

the costs of compliance, the time needed for compliance, 

the energy and non-air quality environmental impacts of 

compliance, and the useful life of the source.

The FLM will make a preliminary determination regarding 

possible adverse visibility impacts upon receipt of all 

relevant information, including the draft permit and any 

associated staff analysis. 

2.2.2. Elements of Permit Review

The FLM review of a PSD application for a proposed project 

that may impact a Class I area generally consists of three 

main analyses:

1. Air quality impact analysis to ensure that predicted 

pollutant levels in Class I areas do not exceed National 

Ambient Air Quality Standards (NAAQS) and PSD 

increments, and to provide sufficient information for the 

FLM to conduct an AQRV impact analysis. Ensuring that 

permit applicants meet these requirements is the direct 

responsibility of the permitting authority (see discussion 

below);

2. AQRV impact analysis to ensure that the Class I area 

resources (i.e., visibility, flora, fauna, etc.) are not 

adversely affected by the proposed emissions. The AQRV 

impact analysis includes interpreting the significance of 

the results from the applicant’s air quality impact analysis 

and is the responsibility of the FLM (see discussion 

below); and

3. Best Available Control Technology (BACT) analysis 

to help ensure that the source installs the best control 

technology to minimize emission increases from the 

proposed project (See Appendix D for a summary of 

this analysis). The final BACT determination is a direct 

responsibility of the permitting authority.

Air Quality Impact Analysis

The permit applicant must perform an air quality impact 

analysis for each pollutant subject to PSD review (40 CFR 

§51.166). This analysis must show the contribution of the 

proposed emissions to increment consumption and to 

the existing ambient pollution levels in a Class I park or 

wilderness area. The applicant must perform a cumulative 

increment analysis for each pollutant and averaging time for 

which the proposed source will have a significant impact. 

Because proposed sources are not yet operating, the air 

quality analysis should rely on mathematical dispersion 

models to estimate the air quality impact of the proposed 

emissions. The FLMs provide the applicants with guidance 

on where to place model receptors within the Class I area. 

The applicant is responsible to provide sufficient information 

for the FLM to make a decision about the acceptability 

of potential AQRV impacts as a consequence of the new 

source. 

The applicant must perform the air quality impact analysis 

using approved models and procedures as specified in 

Appendix W of Part 51 (EPA’s Guideline on Air Quality 

Models, revised November 2005), as required under the 

PSD regulations at 40 CFR 51.166(1) and 52.21(1). The 

applicant should explicitly state all assumptions for the 

analysis, and furnish sufficient information on modeling 

input so that the FLM can validate and duplicate the model 

results. FLMs encourage the permit applicant to submit a 

modeling protocol for review before performing the Class 

I modeling analyses. This protocol should include the 

proposed air quality analysis methodology and model input 

(i.e., emissions, stack data, meteorological data, etc.), and the 

proposed location of the receptors in the FLM area. 

AQRV Impact Analysis

 According to the CAA’s legislative history and current EPA 

regulations and guidance, the air quality impact analysis 

that provides sufficient information to enable the FLM to 

conduct the AQRV impact analysis is one part of a permit 

application just as are the BACT analysis and the air quality 

impact analysis relative to the increments and NAAQS. 

The applicant bears the entire cost of preparing the permit 

application including the complete air quality impact 

analysis.

It is important to highlight the distinction between the air 

quality impact analyses that the applicant performs and 

the AQRV impact analyses that FLMs perform. Whereas 

the permit applicant calculates changes in pollutant 

concentrations, deposition rates, or visibility extinction, 

the FLM assesses the extent to which these impacts affect 

sensitive visual, aquatic, or terrestrial resources. Given the 

FLM’s statutory responsibilities and expertise, the FLM 

must have responsibility to consider whether the amount 

of pollution dispersed into the air or deposited on the 

ground (or in water) would have an adverse impact on any 

AQRV, and if so, to demonstrate that claim to the permitting 

authority. In making an adverse impact finding, FLMs 

consider such factors as magnitude, frequency, duration, 

location, geographic extent, and timing of impacts, as well 

as current and projected conditions of AQRVs based on 

cumulative impacts.

The FLM uses the results from the applicant’s air quality 

impact analysis and other information to conduct the 

 USFS–NPS–USFWS 9
AQRV impact analysis and make an informed decision 

about whether or not AQRVs will be adversely affected. If 

the FLM concludes that AQRVs will be adversely affected, 

the FLM will so demonstrate to the permitting authority. 

The following sections of this document give guidance to 

applicants on how to conduct an air quality impact analysis 

and how the FLM uses this information to make an AQRV 

impact decision. 

Cumulative Impact Analysis 

The FLM will evaluate on a case-by-case basis both the 

permit applicant’s contribution to the AQRV impacts, as 

well as the cumulative source impacts on AQRVs, taking 

into account expected emission reductions. A cumulative 

air quality analysis in which the proposed source and any 

recently permitted (but not yet operating) sources in the 

area are modeled is an important part of any AQRV impact 

analysis. This cumulative modeled impact is then added to 

measured ambient levels (to the extent that such monitoring 

data are available) so that the FLM can assess the total effect 

of the anticipated ambient concentrations on AQRVs. If 

no representative monitoring data are available, the total 

pollutant concentrations should be estimated by modeling 

emissions from all contributing sources in the area.

Information Provided by the FLM to the Applicant 

To assist the permit applicant in performing air quality 

impact analyses, the FLMs will provide all available 

information about AQRVs for a particular Class I area that 

may be adversely affected by emissions from the proposed 

source. FLMs will recommend available methods the 

applicant should use to analyze the potential effects (i.e., 

pollutant concentration, deposition rates, and visibility 

extinction) in the Class I area. In addition to identifying 

AQRVs, FLMs will, to the extent possible:

- identify inventories, surveys, monitoring data, 

scientific studies, or other published reports that are 

the basis for identification of AQRVs;

- identify specific receptors known to be most sensitive 

to air pollution and the pollutant or pollutants 

that individually or in combination can cause or 

contribute to an adverse effect on each receptor;

- identify the critical pollutant concentrations above 

which adverse effects are known or suspected to 

occur;

- recommend methods the applicant should use for 

predicting ambient pollutant concentrations and 

other related impacts (e.g., deposition, visibility) 

which may cause or contribute to an adverse effect 

on each receptor; and

- suggest screening level values or criteria that would 

be used to assess whether a proposed emissions 

increase would have a de minimis impact on AQRVs.

2.2.3. FLM Permit Review Process

The FLM’s current permit review process for any 

application that may impact a FLM area is described below. 

1. Pre-application. If possible, participate in any preapplication meeting to learn specifics of the proposed 

project (size, emissions, location, etc.) and to provide 

information regarding recommended Class I analyses.

2. Modeling Protocol. The FLMs encourage the permit 

applicant to submit a modeling protocol for review 

before performing the Class I modeling analyses. This 

protocol should include the proposed air quality analysis 

methodology and model input (i.e., emissions, stack data, 

meteorological data, etc.), and the proposed location of 

the receptors in the FLM area.

3. Completeness Determination. Upon receipt, the FLM 

will review the application and provide comments to 

the permitting authority regarding the completeness of 

the application and the need for additional information 

regarding the BACT, Air Quality Impacts, and AQRV 

Impacts analyses. The FLM will coordinate with the 

permitting authority and the permit applicant to ensure 

that all the necessary information to enable the FLM to 

make an impact determination is included. 

4. Public Comment Period. After review of all relevant 

information, the FLM will provide pertinent comments 

to the permitting authority, before or during the official 

public comment period, and/or at scheduled public 

hearings.

5. No Class I Increment Violated and No Adverse 

Impacts. If no Class I increment is violated and no 

adverse impacts to AQRVs are expected, the FLM will 

inform the permitting authority of this determination and 

no further FLM action is necessary. The FLM may still 

provide BACT comments.

6. No Class I Increment Violated but AQRV Impacts 

Uncertain. If no Class I increment is violated but 

uncertainty exists regarding potential adverse impacts 

to AQRVs, the FLM may request that the permitting 

authority include a permit condition that requires the 

permittee to conduct relevant post-construction AQRV 

or air quality monitoring. The FLM may also request 

certain control technologies or methods to reduce 

impacts.

7. Class I Increment Violated, but No Adverse AQRV 

Impacts. If the Class I increment is violated, but no 

adverse AQRV impacts are anticipated, the applicant 

requests the FLM to “certify” no adverse impact under 

Section 165(d)(2)C)(iii) of the Clean Air Act [42 USC 

7475(d)(2)(C)(iii)(1998)]. If the FLM concurs, (s)he 

makes a preliminary determination that no adverse 

impacts will occur.

10 FLAG Phase I Report—Revised (2010)
- The FLM will inform the applicant, the State/local 

permitting authority, and EPA of the preliminary no 

adverse impact determination.

- The FLM will notify the public of its preliminary 

no adverse impact determination either through the 

permitting authority’s notice procedures, or through 

separate notice in the Federal Register. Such notice 

should include a statement as to the availability 

of supporting documentation for inspection and 

copying, and an announcement of at least a 30 day 

public comment period on issues directly relevant to 

the determination in question.

- The FLM will review and prepare response to public 

comments.

- The FLM will make a final determination regarding 

no adverse impacts, with a clear and concise 

statement of reasons supporting that determination.

- The FLM will inform the permit applicant, 

the permitting authority, and EPA of its final 

determination and if the final determination is “no 

adverse impact,” the FLM shall so “certify” in a letter 

to the affected parties.

- Simultaneous with above, the FLM will publish a final 

determination in the ‘Notice’ section of the Federal 

Register, including a clear and concise statement of 

reasons supporting that determination, statement 

as to availability of supporting documentation 

for inspection and copying, and statement as to 

immediate effective date (date signed) of final 

determination.

- The FLM will contact the permitting authority and 

request a revision to the State Implementation Plan 

(SIP) to eliminate the Class I increment violations.

8. Adverse Impact Determination. Regardless of 

increment status, the FLM may make a preliminary 

determination that the proposed project will cause, or 

contribute to, an adverse impact on AQRVs. Before 

officially declaring an adverse impact, the FLM will 

inform the proposed new source and the permitting 

authority that an adverse impact determination is 

imminent and suggest that the draft permit be modified. 

If the draft permit is modified to satisfy the concerns of 

the FLM, then an adverse determination is avoided.

- The FLM will inform the applicant, the permitting 

authority, and EPA of a preliminary adverse impact 

determination.

- The FLM will notify the public of the preliminary 

adverse impact determination either through the 

permitting authority’s notice procedures, or through 

separate notice in the Federal Register. Such notice 

should include a statement as to the availability 

of supporting documentation for inspection and 

copying, and an announcement of at least a 30 day 

public comment period on issues directly relevant to 

the determination in question.

- The FLM will review and prepare response to public 

comments.

- The FLM will make a final determination regarding 

adverse impacts, with a clear and concise statement 

of reasons supporting that determination.

- The FLM will inform the permit applicant, 

the permitting authority, and EPA of its final 

determination.

- Simultaneous with above, the FLM will publish a final 

determination in the ‘Notice’ section of the Federal 

Register, including a clear and concise statement of 

reasons supporting that determination, statement 

as to availability of supporting documentation 

for inspection and copying, and statement as to 

immediate effective date (date signed) of final 

determination.

- If the FLM makes a final determination that a source 

will have an adverse impact, the FLM will oppose 

the permit. However, the permit applicant may 

propose to mitigate any adverse impacts (via reducing 

emissions, obtaining emission offsets, etc.). If the 

applicant adequately mitigates the adverse impacts to 

the satisfaction of the FLM, the FLM will withdraw 

his objection to the permit. If the adverse impacts are 

not adequately mitigated and the permitting authority 

nevertheless issues the permit, the FLM may appeal 

the permit.

Note: If the permitting authority’s SIP makes execution 

of the above listed steps impossible (e.g., inadequate 

time allotments for the FLM’s determination or lack of 

timely FLM notice) the procedures shall be adjusted as 

appropriate. In addition, the above procedures (6 and 7) 

could also be modified to accommodate those situations 

when the FLM chooses to certify that existing impacts are 

adverse, absent a proposed new source. Such an action 

would alert potential permit applicants that adverse impacts 

exist and any new source would need to mitigate its potential 

impacts. Although each FLM may implement the above 

procedures somewhat differently, the FLAG goal is to reduce 

the differences in implementing the above steps. 

Furthermore, FLMs intend to coordinate on air permit 

modeling requirements for new or modified sources that 

are geographically near more than one FLM area. For 

example, a proposed source in eastern Tennessee that lies 

equidistant from NPS-administered Great Smoky Mountains 

National Park and the FS-administered Joyce Kilmer/

Slickrock Wilderness would receive coordinated guidance 

on modeling requirements from the FLMs. The FLMs 

may or may not have common AQRVs at different Class I 

areas, making coordination beneficial. The FLMs may also 

 USFS–NPS–USFWS 11
coordinate on potential permit conditions and mitigation 

strategies.

2.2.4. Criteria for Decision Making (Adverse 

Impact Considerations) (Revised)

As previously mentioned, the legislative history of the CAA 

provides direction to the FLM on how to comply with the 

affirmative responsibility to protect AQRVs in Class I areas, 

and in cases of doubt, the land manager should err on 

the side of protecting air quality-related values for future 

generations.

The FLMs define adverse impact on AQRVs as:

An unacceptable effect, as identified by an FLM that 

results from current, or would result from predicted, 

deterioration of air quality in a Federal Class I or Class 

II area. A determination of unacceptable effect shall be 

made on a case-by-case basis for each area taking into 

account existing air quality conditions. It should be 

based on a demonstration that the current or predicted 

deterioration of air quality will cause or contribute 

to a diminishment of the area’s national significance, 

impairment of the structure and functioning of the area’s 

ecosystem, or impairment of the quality of the visitor 

experience in the area.

Also, the Federal visibility protection regulations (40 CFR 

§51.300, et seq., §52.27) define adverse impact on visibility 

as:

[V]isibility impairment which interferes with the 

management, protection, preservation or enjoyment of 

the visitor’s visual experience of the Federal class I area. 

This determination must be made on a case-by-case 

basis taking into account the geographic extent, intensity, 

duration, frequency, and time of visibility impairment, 

and how these factors correlate with: (1) times of visitor 

use of the Federal class I area, and (2) the frequency and 

timing of natural conditions that reduce visibility. (Id. 

§51.301(a))

FLMs typically address adverse impacts on a case-by-case 

basis in response to PSD permit applications. The factors 

the FLMs will consider in making an adverse impact 

determination are discussed in more detail below (see 

section 4.3). When an adverse impact is predicted, FLMs 

recommend that permits either be modified to protect 

AQRVs or be denied. FLMs can also address adverse 

conditions outside of the PSD process. They do so through 

a variety of mechanisms: certify visibility impairment; 

participate in regional assessments; informally collaborate 

with States and EPA; review lease permits, SIP revisions, 

National Environmental Policy Act (NEPA) analyses, Park/

Refuge/Forest management plans, CERCLA (Comprehensive 

Environmental Response, Compensation, and Liability Act) 

reviews, and other documents.

In some States, FLMs use screening procedures or 

thresholds that indicate when the condition of an AQRV is 

acceptable or unacceptable. The pollutant concentration 

or loading rate that will adversely impact an AQRV 

can vary among Class I areas, and depends on current 

conditions. After a threshold is reached, an increase in 

pollutant concentrations is likely to be unacceptable. A 

concern threshold can be an adverse impact threshold or 

other quantifiable level in resource condition or pollutant 

exposure identified by the FLM.

2.2.5. Air Pollution Permit Conditions that 

Benefit Class I Areas

The FLM does not determine what permit conditions will 

be required or administer permit conditions; that is the 

responsibility of the permitting authority. However, the 

FLMs may request permit conditions or agree to withdraw 

objections to permit issuance if requested conditions are 

included. The FLMs view the inclusion of certain PSD 

permit conditions by the permitting authority as a means to 

help protect or enhance the condition of AQRVs when:

1. Air pollution source(s) may cause impacts that exceed 

protection thresholds for AQRVs;

2. Terrestrial resources, aquatic resources, and/or visibility 

are currently adversely impacted by air pollution and 

proposed emissions will exacerbate these adverse 

conditions;

3. FLM policies require improvement or restoration of 

AQRVs in parks and wildernesses; and

4. There is uncertainty on the extent and magnitude of air 

pollution effects on AQRVs.

Recommended permit conditions may include requiring 

emission offsets, AQRV and/or air quality monitoring, 

inventories, post-construction reassessment, LAER (or 

other improved control technologies), or other measures to 

protect, enhance, or restore resources and values of parks 

and wildernesses. Permit conditions may:

1. Result in net air quality benefits at a protected area or 

within a region; 

2. Contribute to a reduction of air pollution within a region; 

3. Promote ecosystem inventories and/or monitoring to 

evaluate physical and biological resource damage caused 

by air pollution emissions; and

4. Promote ecosystem restoration or improve the condition 

of resources that have been damaged by air pollution 

emissions.

The basis of an air permit condition should be identified in 

the public notice for the draft permit. To be effective, permit 

conditions must be federally enforceable and guaranteed. 

Air permit provisions may be temporary or permanent 

depending on the nature of the permit requirements. 

12 FLAG Phase I Report—Revised (2010)
Procedures to implement an air permit condition must be 

acceptable to the FLM (e.g., an agreement between parties 

[memorandum of understanding, interagency agreement] 

is an option to accomplish inventory, monitoring, or other 

requirements).

2.2.6. Reducing Pollution in Nonattainment 

Areas (Nonattainment Permit Process)

The PSD program does not apply with respect to a particular 

pollutant when the source locates in an area designated 

non-attainment for that pollutant. Instead, pollution sources 

are regulated by Non-attainment Area New Source Review 

(NNSR). NNSR includes air quality planning and regulation 

of stationary sources. Air quality planning addresses issues 

such as lowest achievable emission rate (LAER), offsets, 

reasonably available control technology (RACT), and 

mobile and stationary source control strategies. New major 

stationary sources and major modifications of sources in 

designated non-attainment areas must satisfy NNSR before 

construction begins. For visibility protection, SIPs must 

include either EPA-approved provisions to comply with 40 

CFR §51.307 for the non-attainment pollutant, otherwise, 

the federally promulgated visibility provisions at 40 CFR 

§52.28 would apply to all sources located in non-attainment 

areas. Therefore, FLMs can provide suggestions to the 

permitting authority regarding these conditions during the 

permitting and planning processes. 

SIPs provide a mechanism to address AQRV impacts when 

the source or the Class I area is located in a non-attainment 

area. FLMs may recommend that States adopt policies, rules, 

or regulations in their SIPs requiring a demonstration that 

offsets will result in a net air quality benefit within any Class 

I area likely to be impacted by emissions from the source to 

be permitted. FLMs may also request emissions reductions 

greater than 1:1, perhaps offset rates of 1.5 or 2.0 to 1, or 

higher, depending on the nature and magnitude of impacts 

to be offset. Such recommendations can be developed jointly 

in a meeting with the regulatory authority or in a letter from 

the FLM.

Mitigation measures recommended by FLMs may include 

stringent control technologies to minimize the increase 

in emissions and the impact on AQRVs. Monitoring can 

determine whether predicted resource conditions are 

observed. Offsets ensure that net emissions reductions 

from all sources will occur within a geographic area and 

their resulting air quality impacts at the Class I area will be 

mitigated. 

2.3. Other Air Quality Review 

Considerations (Revised)

At all Class I areas where visibility has been monitored, 

visibility conditions have been found to be impaired by 

human-caused pollution. The impairment comes primarily 

from older sources, not new sources. From a regional 

perspective, new or modified sources (using new/cleaner 

technologies) contribute far less to impaired AQRV 

conditions than old sources. EPA has implemented a call 

for reducing NOx

 emissions from older sources in the 

eastern U.S. to meet existing ozone standards. In addition 

to complying with national ambient standards, States are 

now developing plans to implement EPA’s Regional Haze 

Regulations. If these requirements are implemented, then 

progress toward remedying impaired AQRVs is likely. 

However, given the sensitivity of some AQRVs to low levels 

of pollution, programs focused on reaching national goals, 

such as the NAAQS or visibility, may not fully remedy 

impacts on AQRVs in all locations. It is for this reason that 

the FLM does pursue other strategies to protect AQRVs. The 

following sections discuss FLM issues that go beyond NSR.

2.3.1. Remedying Existing Adverse Impacts

Allowing the existence of adverse impacts would be 

inconsistent with the mandates of the FLM agencies. 

Consequently, FLMs may request or participate in regional 

assessments to protect AQRVs, and remedy any existing 

adverse impacts on AQRVs, as appropriate. Regional 

assessments often use a multi-faceted approach to remedy 

impairment. For example, categories addressed by the Grand 

Canyon Visibility Transport Commission (GCVTC) include 

air pollution prevention; clean air corridors; stationary 

sources; sources in and near Class I areas; mobile sources; 

road dust; fire; and future regional coordination.

Clean Air Act requirements for remedying existing visibility 

impairment provide a mechanism for addressing impacts 

from specific sources or groups of sources [42 USC 

7491). Negotiations at the Centralia Power Plant in the 

state of Washington provide an example of how to build 

partnerships and work collaboratively to obtain retrofit 

controls or more stringent control technologies for sources 

that affect a FLM area. Through a collaborative decision 

making process, owners of the Centralia plant agreed to 

reduce sulfur dioxide emissions at the plant by 90%. In 

another case, the FWS identified plume impacts from a 

pulp and paper mill located seven miles upwind of the 

Moosehorn Wilderness Area. Using cameras provided by the 

IMPROVE monitoring network, plumes from the mill were 

documented entering the Moosehorn Wilderness Area. In 

collaboration with the State of Maine, additional controls 

for nitrogen oxides and updated particulate controls were 

incorporated into the mill’s PSD permit to address the plume 

impacts. 

 USFS–NPS–USFWS 13
FLMs may also coordinate with others to ensure that 

emission reductions in nonattainment areas will improve 

air quality in FLM areas. Recommendations on urban 

planning were developed with FLM involvement to address 

nonattainment areas in California. Data documenting 

ozone effects on vegetation were provided to the planning 

authority.

2.3.2. Requesting State Implementation Plan 

(SIP) Revisions to Address AQRV Adverse Impacts 

(Revised)

A SIP is the mechanism that states use to develop the 

pollution control programs that will be used to achieve 

and maintain the NAAQS, as well as prevent significant 

deterioration of air quality. It is important for FLMs to be 

involved in SIP development, as participation provides 

an opportunity to influence planning of pollution control 

programs that can benefit air quality in FLM areas. Once a 

SIP is fully approved by EPA, it is legally enforceable under 

both State and Federal law. FLMs assist in the development 

of SIPs by providing analysis and comment to address 

existing impacts of concern. This approach is particularly 

useful for addressing impacts on AQRVs other than 

visibility, since the Clean Air Act does not provide specific 

requirements for other AQRVs. 

SIP revisions could be used to address multiple sources 

and regional pollution that adversely affect AQRVs in all 

Class I areas. For example, in South Coast and San Diego, 

California, SIP revisions included FLM recommendations 

to reduce the impact of minor sources on AQRVs. South 

Coast recommendations addressed visibility while the San 

Diego recommendations addressed all AQRVs. EPA’s NOx

SIP Call in the east is another example of obtaining emission 

reductions through the SIP revision process. The NOx

 SIP 

Call was directed at 20 eastern States and the District of 

Columbia to address NOx

 emissions from existing large 

sources. Significant reductions in ozone formation and 

nitrogen deposition have occurred as a result of these efforts.

2.3.3. Periodic Increment Consumption Review 

(Revised)

EPA has indicated its intention to establish a SIP revision 

requirement to address existing adverse impacts on AQRVs. 

The FLMs strongly support EPA exercising its authority 

in this way. In the interim, however, there are existing SIP 

revision requirements that are not being fully utilized. EPA’s 

current regulations require States to conduct a periodic 

review of the adequacy of their PSD plan and program. [40 

CFR §51.166(a)(4)] This would include an assessment of 

increment consumption in Class I and Class II areas. Few 

States have ever conducted a comprehensive, cumulative 

increment consumption analysis for one or more Class I 

areas. In addition, many PSD sources have not exceeded the 

significant impact levels for increment consumption; thus, 

few PSD permit applicants have had to perform a cumulative 

increment consumption analysis for Class I areas. Such a 

periodic increment consumption review would be beneficial 

given that the burden of proof for AQRV adverse impact 

determinations shifts from the FLM to the applicant when 

the increment has been consumed.

In its 1990 report, Air Pollution: Protecting Parks and 

Wilderness From Nearby Pollution Sources, the U.S. General 

Accounting Office (GAO) found that only 1 percent of 

the sources within 100 kilometers of five Class I areas 

it investigated were required to have permits under the 

PSD program, with 99 percent of the sources being minor 

or grandfathered sources. It also found that “non-PSD 

sources contribute from 53 to 90 percent of five of the six 

criteria pollutants emitted within a 100-kilometer radius of 

each of the five Class I areas.” As part of its investigation, 

GAO noted that “a significant portion of total emissions 

of volatile organic compounds generally comes from small 

sources...and suggested that as part of the overall control 

strategy, States may want to consider lowering thresholds 

for regulating new sources to 25 tons of volatile organic 

compounds a year.” According to the investigation, 55 

percent of anthropogenic VOC emissions come from new 

sources or modifications totaling five tons per year or less. 

In a review of PSD permit applications near Mesa Verde 

National Park (a Class I area in Colorado), a cumulative 

modeling analysis of increment-consuming sources found 

that approximately 80 percent of the NO2

 Class I increment 

at the park had been consumed, but much of it by minor 

sources.

The FLMs have encouraged EPA to provide clearer direction 

on how often these periodic reviews should occur as the lack 

of a prescribed time-frame for conducting such analyses has 

clearly led to noncompliance with this requirement over the 

past twenty years by States. 

2.4. Managing Emissions Generated in and 

Near FLM Areas (Revised)

Specific strategies need to be developed and implemented 

for reducing and preventing pollution from the many diverse 

sources and activities in communities surrounding FLM 

areas, including “gateway” communities (i.e., those adjacent 

to FLM areas). Accountability mechanisms are needed to 

ensure that appropriate actions are taken, reported and 

incorporated into SIPs, visibility protection plans, and 

Federal land management plans. Various forums (e.g., 

the Western Regional Air Partnership, and the Southern 

Appalachian Mountains Initiative) addressed some of 

the emissions sources of concern and developed regional 

strategies. In addition, EPA has formed other “regional 

planning organizations” for implementing its regional haze 

rule. FLMs participate in these forums, consistent with 

Federal law (e.g., Federal Advisory Committee Act), to the 

14 FLAG Phase I Report—Revised (2010)
maximum extent possible and coordinate their activities 

within those forums to ensure that comprehensive strategies 

are developed and implemented to address all the key 

emissions sources near FLM areas.

 A systematic assessment of emission sources in and near 

FLM areas would be extremely helpful for formulating 

strategies aimed at mitigating or eliminating adverse impacts 

on area resources, and the NPS has performed microemission inventories for several of its Class I areas. However, 

without this assessment for all areas it is not possible to 

accurately quantify the extent to which these emissions 

contribute to the overall problem. Nevertheless, FLMs can, 

and should, take steps to minimize emissions generated on 

FLM lands even without an accurate inventory of emissions 

sources.

2.4.1. Prescribed Fire 

Prescribed fire is a land management tool used for multiple 

landscape objectives. Prescribed fire allows the FLM 

to mimic natural fire return intervals under controlled 

conditions where smoke management can minimize air 

quality impacts. The alternative is wildfires, which can be 

very difficult to control and may cause much more severe 

air quality impacts. A modeling assessment suggests that 

using prescribed fire to minimize wildfires can result in a net 

reduction in fine particle (PM2.5) emissions in the long-term. 

In the Pacific Northwest wildfire emissions were found to 

be greater than prescribed fire emissions in the same airshed 

(Ottmar 1996).

Since the early 1900s, wildfire has been aggressively 

suppressed on most of the nation’s public lands to protect 

public safety, property, and to prevent what was thought 

to be the destruction of our natural and cultural resources. 

Fire-exclusion practices have resulted in forests, shrub 

lands, and grasslands plagued with a variety of problems, 

including overcrowding, resulting from the encroachment of 

species normally suppressed by fire; vulnerability of trees to 

insects and disease; and inadequate reproduction of certain 

species. In addition, heavy accumulation of fuels (such as 

dead vegetation on the forest floor) can cause fires to be 

catastrophic, which threatens firefighter and public safety, 

impairs forest and ecosystem health, destroys property and 

natural and cultural resources, and degrades air quality. 

The intense or extended periods of smoke associated 

with wildfires can also cause serious health effects and 

significantly decrease visibility. 

FLMs recognize prescribed fire as a valuable tool; they 

also recognize that emissions from prescribed fire can be a 

significant source of air pollution. Smoke particles are also 

in the size range (< 2.5 μm) that they play a significant role in 

visibility impairment. Particulate matter is the main pollutant 

of concern from smoke because it can cause serious health 

problems, especially for people with respiratory illness. 

The FLMs are committed to minimizing the impacts from 

smoke by following sound smoke management practices, 

and if practical, using non-burning alternatives (i.e., 

mechanical clearing, chipping, mulching) to achieve land 

management objectives. Each prescribed burn site will have 

unique characteristics, but in general, smoke impacts can 

be minimized by burning during weather conditions that 

provide optimal humidity levels and dispersion conditions 

for the type of materials being burned, in addition to limiting 

the amount of materials and acreage burned at one time.

EPA has worked in partnership with land management 

agencies in the U.S. Departments of Agriculture, Defense, 

and the Interior; State Foresters; State air regulators; Tribes; 

and others to obtain recommendations and develop a 

national policy that addresses how best to improve the 

quality of wildland ecosystems (including forests and 

grasslands) and reduce threats of catastrophic wildfires 

through the increased use of managed fire, while achieving 

national clean air goals (EPA 1998b). EPA’s interim air 

quality policy on fire describes criteria for wildland managers 

(federal, state, tribal, and private), and state and tribal air 

pollution agencies, to use in planning for and implementing 

prescribed fires, and recommends a variety of smoke 

management techniques that land managers can use to help 

reduce smoke impacts from prescribed fires. The policy is 

available at EPA’s web site: http://www.epa.gov/ttn/faca/

fa08.html. In addition, on March 22, 2007, EPA promulgated 

its Exceptional Events Rule that clarifies how ambient air 

quality standard exceedances from wildland fire will be 

treated in determining attainment and nonattainment status. 

In that rule, EPA committed to revising its 1998 wildland fire 

policy (72 FR 13560, March 22, 2007). 

2.4.2. Strategies to Minimize Emissions from 

Sources In and Near FLM Areas (Revised)

Aside from prescribed fire, other activities in and near 

FLM areas that generate air pollution include vehicle 

emissions, road building, operation of generators, oil and 

gas development, etc. Developing strategies for addressing 

natural resource impacts in or near an FLM area should not 

only take into consideration the type of activities generating 

the emissions and their amount, but also the existing 

condition of the resources of that area. More stringent 

measures should be recommended for sources in and near 

FLM areas that are already experiencing adverse effects from 

air pollution.

Examples of potential air pollution prevention practices 

that FLM agencies may encourage or develop and use are 

categorized under the following three strategies:

 USFS–NPS–USFWS 15
Pollution Prevention Strategies

•	 Review land management plans for affected FLM areas 

to assess whether they include strategies to limit and 

reduce air pollution emissions and incorporate protective 

measures into planning and decision documents.

•	 Place priority on pollution prevention.

•	 Encourage zero and near-zero emitting technologies.

•	 Promote energy conservation and the use of renewable 

energy sources.

•	 Promote use of clean fuels.

Mobile Source Strategies

•	 Promote the adoption of Low Emission Vehicle standards 

or the conversion of Federal fleets to alternative fuels.

•	 Improve control of evaporative emissions.

•	 Promote more stringent emission standards for the tour 

bus industry and other high-emitting vehicles used in 

federal areas (e.g., park shuttle vehicles).

•	 Considering restricting access of high emitting vehicles to 

sensitive areas.

•	 Retire high-emitting vehicles from Federal fleets as 

quickly as practicable and/or relocate high-emitting 

vehicles to less sensitive areas until they can be retired.

•	 Establish emission budgets from the transportation sector 

for selected FLM areas.

•	 Develop mass transit systems in some NPS units (e.g., 

light rail in Grand Canyon NP and a bus system in Zion 

NP).

Minor Source Strategies (Revised)

•	 Apply RACT, BACT, LAER, best and reasonably available 

control measures, etc., to existing federal sources, as 

appropriate.

•	 Recommend going beyond conformity requirements 

to include the protection of AQRVs in FLM areas, and 

ensure all actions FLMs can practicably control in and 

near FLM areas will not cause, or contribute to, an 

adverse impact on any AQRV.

Improved involvement with interested parties in gateway 

communities will likely be required to ensure growth in these 

communities occurs in a manner that mitigates the impact on 

natural resources. These communities may need to enhance 

their participation in the planning processes of FLMs. 

Similarly, FLMs should participate in planning activities 

for public lands located in the FLM area and communities 

adjacent to FLM areas to ensure air quality concerns are 

adequately addressed. Mechanisms should be identified 

and developed for community involvement in developing, 

implementing, and enforcing emission management 

strategies for sources near and in FLM areas.

Implementing strategies to achieve emission reductions 

in and near FLM areas will require efforts in at least three 

specific areas:

1. FLMs should ensure that sufficient emphasis is placed in 

agency planning documents requiring the minimization 

of air pollution emissions from new activities or practices. 

2. FLMs should inventory air pollution emissions within 

FLM areas. After emissions have been quantified, 

FLMs, States, and adjacent communities will be able 

to assess the impact of these emissions through the 

use of appropriate models. Knowledge of Class I area 

emissions will also improve FLM ability to consult with 

States during the development and review of their SIPs 

(especially visibility SIPs). The NPS has developed an 

emissions inventory tool, the Climate Leadership in Parks 

(CLIP) Tool, that can be utilized by FLMs to inventory 

both greenhouse gases and all criteria air pollutants. 

3. FLMs should cooperate with States and local 

communities in assessing the need for, and the 

development of, appropriate emission reduction 

strategies in and near FLM areas that address nonPSD sources. For Class I areas, the Regional Planning 

Organizations have completed analyses of emissions 

from nearby communities and activities that will serve as 

the basis for identifying strategies to reduce emissions. 

Without an acknowledgment from States and local 

communities that these sources may pose a threat to 

FLM areas and a systematic assessment of these potential 

impacts, current efforts to protect FLM area resources 

may be insufficient.

2.4.3. Conformity Requirements in 

Nonattainment Areas

Conformity criteria and procedures ensure that actions 

on lands administered by Federal agencies do not cause 

a violation of the NAAQS, increase the frequency of any 

standards violations, or delay attainment of a standard. 

Conformity to SIPs is only required for activities within 

nonattainment areas for non-transportation related sources 

if emissions are above de minimis levels and regionally 

significant. Any activity that represents 10 percent, or more, 

of the emission inventory for that pollutant in the nonattainment or maintenance area is regionally significant. 

Examples of actions that may require a conformity 

determination include road paving projects, ski area 

development, or mining. Activities such as prescribed fire, 

that are included in a conforming land management plan, 

are exempt from conformity requirements. Please note that 

conformity determinations must be made in accordance 

with applicable EPA regulations, are typically done before a 

project is approved, and are part of the NEPA process.

The FLM should define the process to be used in conformity 

determinations and perform the conformity analysis before 

16 FLAG Phase I Report—Revised (2010)
a project is implemented. A conformity analysis typically 

includes emission calculations, public participation, 

mitigation measures/implementation schedules, and 

reporting methods. The Pacific Southwest Region of the 

USFS has published a Conformity Handbook for FLMs to 

assist in conformity compliance. In an approved Plan of 

Operation, FLMs can require monitoring. For example, in 

the case of Carlota Mine, located on National Forest land in 

Arizona, the USFS requested additional mitigation measures 

to protect AQRVs in the Superstition Wilderness.

Transportation projects in FLM areas classified as 

nonattainment are subject to a more complicated 

transportation conformity process. Consultation with State 

and local air quality and transportation agencies will be 

required to comply with applicable regulations.

 USFS–NPS–USFWS 17
3. Subgroup Reports: Technical 

Analyses and Recommendations

3.1. Subgroup Objectives and Tasks

Subgroups were formed to address the four key issues 

relevant to AQRV identification and evaluation issues: policy 

(and procedures), visibility, ozone, and deposition. Each 

of these subgroups reviewed the commonalities among the 

FLMs then addressed the tasks assigned to them by FLAG. 

One of their first tasks was to differentiate between Phase 

I tasks, those which could be resolved in the short term 

without significant additional resources, and Phase II issues, 

those that would require a longer period or greater effort.

Subgroups were asked to reach common ground among the 

FLMs on the issues. The intent was to develop, to the extent 

possible, consistent policies, processes, and terminology 

that could be used when identifying AQRVs and evaluating 

impacts on AQRVs. This involves recommending consistent 

approaches for identifying air pollution effects on AQRVs, 

for determining adverse impacts, and for attributing adverse 

impacts to specific pollution sources. In addition, the FLMs 

consider that AQRV protection from visibility, ozone, and 

deposition impacts are equally important. However, we 

also recognize that given the current state of the science, 

attributing adverse impacts to specific sources are easier to 

document for visibility than for deposition and ozone, and 

easier for deposition than ozone. 

The individual subgroup reports document the common 

policies, procedures, and definitions identified or developed 

during Phase I activities. The Visibility, Ozone, and 

Deposition subgroup reports are included below. The 

FLAG Policy Subgroup Report was used as the basis for 

much of the rest of this FLAG Phase I Report, including 

much of section 1 ‘Background’ and section 2 ‘Federal Land 

Managers’ Approach to AQRV Protection’.

3.2. Initial Screening Criteria (New)

Experience with the FLAG 2000 recommendations in 

dealing with many new source review applications led 

the Agencies to believe that an initial screen that would 

exempt a source from AQRV impact review based on its 

annual emissions and distance from a Class I area may be 

appropriate in most situations. As part of its Regional Haze 

Regulation, the EPA has introduced a screening criteria in 

its BART guidelines based on a source’s annual emission 

strength and distance from a Class I area. The EPA stated 

that it would be reasonable to conclude that the following 

sources would not be considered to cause or contribute to 

visibility impairment:

- those located more than 50 km from any Class I area 

that emit less than 500 tons per year of NOx

 or SO2

(or combined NOx

 and SO2), and 

- those located more than 100 km from any Class I area 

that emit less than 1,000 tons per year of NOx

 or SO2

(or combined NOx

 and SO2).

In both cases, the annual emissions over distance factor 

equates to 10. 

The Agencies have concluded that a similar approach has 

merit with respect to new source impacts at Class I areas, 

for air pollution sources with relatively steady emissions 

throughout each year. However, the Agencies are modifying 

the size criteria to also include Particulate Matter less than 

10 microns in size (PM10) and sulfuric acid mist (H2

SO4) 

emissions because those pollutants also impair visibility and 

contribute to other resource impacts. In addition, rather 

than the two-step BART test, the Agencies are using a fixed 

Q/D factor of 10 as a screening criteria for sources locating/

located greater than 50 km from a Class I area. Furthermore, 

the Agencies are expanding the screening criteria to include 

all AQRVs, not just visibility. Therefore, the Agencies will 

consider a source locating greater than 50 km from a Class I 

area to have negligible impacts with respect to Class I AQRVs 

if its total SO2

, NOx, PM10, and H2SO4 annual emissions 

(in tons per year, based on 24-hour maximum allowable 

emissions), divided by the distance (in km) from the Class I 

Acadia National Park, Maine. 

Credit: National Park Service

18 FLAG Phase I Report—Revised (2010)
area (Q/D) is 10 or less. The Agencies would not request any 

further Class I AQRV impact analyses from such sources.

In cases where a source’s operations which generate 

visibility-affecting emissions are limited to time periods 

shorter than a year, the short-term potential to impact 

visibility may not be adequately expressed by the Q/D 

concept. For example, a source that is operated either 

seasonally or intermittently, and has zero emissions for 

substantial portions of a year, would have a total annual 

emission rate that under-represents its potential emission 

strength over a shorter time frame, such as a day or week. 

Because visibility is an air quality related value that is 

sensitive to immediate and short-term conditions, in order 

to apply the Q/D≤10 screening tool, these types of sources 

need to first adjust the tons-per-year emissions to reflect 

what the emissions would be if the source operated yearround. For instance, if operations are restricted to 3,000 

hours per year, then the annual steady-state-equivalent 

emission rate (Q) is found by multiplying the permitted total 

tons per year for SO2

, NOx, PM10 , and H2SO4 by the ratio of 

hours: 8,760 hours per year/3,000 hours operation.5

 Then, 

using this annual equivalent Q in the Q/D test, the Agencies 

will consider a source locating greater than 50 km and 

showing that its ratio of annual equivalent Q (tons per year) 

divided by distance from the Class I area (km) of 10 or less, 

as having negligible impacts with respect to Class I visibility 

impacts, and would not request any further Class I visibility 

impact analyses from such sources.

3.3. Visibility

3.3.1. Introduction (Revised)

This chapter describes methods for analyzing the impacts 

on visibility from new or modified air pollution sources. 

This includes sources that fall under the purview of the 

Prevention of Significant Deterioration (PSD) regulations 

and sources that are being analyzed for Environmental 

Assessments and/or Environmental Impact Statements 

under the National Environmental Policy Act (NEPA). The 

basis for some of the decisions outlined in this chapter is 

Section 169A of the Clean Air Act. The opening statement of 

this section states: “Congress hereby declares as a national 

goal the prevention of any future, and the remedying of 

any existing, impairment of visibility in mandatory class I 

Federal areas which impairment results from man made air 

pollution.” Under the regulations promulgated for visibility 

protection (40 CFR §51.301 (x)) visibility impairment is 

defined as “...any humanly perceptible change in visibility 

(visual range, contrast, coloration) from that which would 

have existed under natural conditions.” The remainder of 

this chapter describes methods that allow for new source 

growth to be analyzed against the constraint of preventing 

5. Or, an intermittent hourly emission limit could be annualized by 

multiplying by 8,760 hours per year/2,000 lb/ton (= 4.38).

visibility impairment as defined in 40 CFR §51.301 (x), 

that is, new source growth should not allow any humanly 

perceptible change in visibility as compared against natural 

conditions.

Visibility Impairment

Before proceeding with the discussion, it is useful to identify 

the ways that visibility impairment can manifest itself. 

First, the pollutant loading of a section of the atmosphere 

can become visible, by the contrast or color difference 

between a layer or plume and a viewed background, 

such as a landscape feature or the sky. The second way 

that visibility is impaired is a general alteration in the 

appearance of landscape features or the sky, changing the 

color or the contrast between landscape features or causing 

features of a view to disappear. The first phenomenon is 

commonly referred to as plume impairment, whereas the 

second phenomenon is sometimes referred to as uniform 

haze impairment. As plumes are transported within a 

stable atmospheric layer, they may become a layered haze. 

As plumes and other more diffuse emission sources are 

transported and become well mixed in the atmosphere, they 

may develop into a uniform haze.

Visibility Parameters (Revised)

The analysis methods for new source growth, described in 

this chapter, deal with the visibility effects of discrete plumes 

and the aggregation of discrete plumes into a uniform 

haze. The difference in these phenomena, as treated in this 

chapter, is whether the visibility effect is primarily seen 

as a section of the atmosphere which exhibits a change in 

contrast or color as compared with a viewed background, or 

whether the effect is due to an alteration of the appearance 

of the background features themselves. For the first 

situation, the contrast (C) and color difference index (∆E) 

of the plume and the viewing background are calculated. 

For the second situation, the change in atmospheric light 

extinction (∆bext), relative to natural conditions, is calculated. 

The light extinction is inversely proportional to “visual 

range.” An approximation for which situation applies is the 

distance from the point of emission. (Distance serves as an 

indicator of where steady state conditions may apply.) The 

visibility impairment from sources within 50 kilometers of a 

view is usually calculated using contrast and color difference, 

whereas visibility impairment from sources greater than 50 

kilometers from a view, or the aggregation of a number of 

plumes, regardless of distance, is usually calculated using 

the change in light extinction. The distance approximation 

is useful for distinguishing these two phenomena; the terms 

“near field” and “distant/multi-source” are sometimes used 

in the remainder of this document to make this distinction. 

 USFS–NPS–USFWS 19
3.3.2. Recommendations for Evaluating Visibility 

Impacts (Revised)

There are two fundamentally different approaches one 

could adopt to determine visibility impairment. One is 

a technically rigorous, complex, and situation-specific 

method, while the other is a more generalized approach. The 

more rigorous approach requires determination of particle 

concentrations and size distributions, calculation of particle 

growth dynamics, and application of elaborate physics (e.g., 

Mie Theory) to determine the optical characteristics of the 

aerosol distribution. Sophisticated radiative transfer models 

are then applied, using aerosol optical characteristics, 

lighting and scene characteristics, and spatial distribution of 

the pollutants to calculate the path and wavelength of imageforming and non-image-forming light that reaches a specific 

observer from all points in the scene being viewed.

While such a detailed analysis may be useful for assessing 

specific cases, it is usually impractical for situations in which 

visibility could be experienced in a nearly infinite variety 

of circumstances. Practical limitations frequently dictate 

that it is more reasonable to use a generalized approach to 

determine the change in extinction by using bulk-averaged 

aerosol-specific extinction efficiencies rather than trying to 

reproduce the complex optical phenomena that may occur 

in the atmosphere.

Consequently, as a first-level analysis, FLAG recommends 

the generalized approach for determining the effects on 

visibility from a proposed new source’s emissions. The 

procedure is to estimate the atmospheric concentrations of 

visibility impairing pollutants, apply representative visibility 

parameters, calculate the change from specified reference 

levels, and compare this change with prescribed threshold 

values. The more detailed analysis described above may be 

appropriate as a refined analysis in the event the source fails 

the first-level analysis.

FLAG is using EPA’s estimates of natural visibility conditions 

under its Regional Haze Rule as reference levels for Class 

I visibility analyses. Comparison with natural conditions 

will help ensure that those conditions will not be impaired 

in keeping with Section 169A of the CAA. Because of the 

different requirements of the two modeling approaches 

discussed below, natural conditions should be expressed 

using two different metrics:

•	 Standard visual range (visual range adjusted to a Rayleigh 

condition of 10 Mm-1), for near field modeling. Present 

EPA guideline visibility models traditionally accept 

visibility conditions expressed in these terms.

•	 Extinction, for distant/multi-source modeling. Visibility 

conditions should be expressed in terms of the averaged 

extinction efficiencies of the individual atmospheric 

constituents that comprise the total extinction. The 

relative humidity effects of the hygroscopic particles 

should be accounted for when the change in extinction is 

calculated.

Information needed to calculate the above indices for all 156 

Class I areas for which visibility is an important attribute is 

provided in Tables 5 through 10 at the end of this chapter. If 

estimates are needed for Class II areas, the FLM can provide 

them.

3.3.3. Air Quality Models and Visibility 

Assessment Procedures (Revised)

The modeling discussion will be divided into two parts to 

address the very different requirements for 1) near field 

modeling where plumes or layers are compared against a 

viewing background, and 2) distant/multi-source modeling 

for plumes and aggregations of plumes that affect the general 

appearance of a scene. Note that both of the above analyses 

might apply depending on the source’s proximity to all 

portions of the Class I area or multiple Class I areas.

FLAG 2000 provided information in the form of 

recommendations, specific processes, and interpretations 

of results for assessing visibility impacts of sources affecting 

Class I areas (although some of this information is generally 

applicable to Class II areas, as well). The information 

separately addressed assessments for sources proposing to 

locate relatively near (within 50 km) and at farther distances 

(greater than 50 km) from these areas. It also recommended 

impairment thresholds and identified the conditions for 

which cumulative analyses could be warranted. This revision 

(FLAG 2010) updates the Distant/Multi-source analysis 

discussed in FLAG 2000, and clarifies the recommendations 

regarding the near-field (within 50 km)/steady-state analysis. 

Near Field Analysis Technique for Analyzing Plumes or 

Layers Viewed Against a Background (Revised)

The Model (Near Field – Steady State Conditions 

Applicable) (Revised)

EPA has recommended a methodology to assess impacts due 

to coherent plumes. A guideline for when these steady state 

conditions apply is the distance from the source to the view 

of concern. This technique is usually applied for sources 

locating within 50 km of a Class I area. Applicants should 

first model their potential plume impacts using the screening 

model, VISCREEN (EPA 1992a), or, if the next level of 

analysis is called for, PLUVUE II (EPA 1992b and 1996a). 

Both of these models use steady-state, gaussian-based plume 

dispersion techniques to calculate one-hour concentrations 

within an elevated plume. These two models calculate the 

change in the color difference index (∆E) and contrast 

between the plume and the viewing background. Values 

of ∆E and plume contrast are based on the concentrations 

of fine primary particulates (including sulfates), nitrogen 

dioxide (NO2

), and the geometry of the observer, target, 

plume, and the position of the sun. PLUVUE II also allows 

20 FLAG Phase I Report—Revised (2010)
consideration of the effects of secondarily formed sulfates. 

Plume contrast results from an increase or decrease in light 

transmitted from the viewing background through the plume 

to the observer. The specifics of the emission scenarios and 

plume/observer geometries for modeling should be selected 

in consultation with the appropriate Agency representatives. 

At the present time there is no recommended procedure for 

conducting analyses of multiple sources with these modeling 

tools, so multiple coherent plumes should be treated 

individually, or combined into a representative single source 

if appropriate. Alternatively, the techniques outlined in the 

Distant/Multi-Source section below may be used on a caseby-case basis.

The Recommended Procedures (Near Field – Steady 

State Conditions) (Revised)

Until better modeling tools are available, FLAG recommends 

using the present EPA techniques for plume visual impact 

screening analyses (EPA 1992c). However, unlike those 

procedures, which suggest the use of current average annual 

visibility conditions, FLAG recommends that for Class I 

areas the visual range corresponding to natural conditions 

be used to generate the hourly estimates of ∆E and plume 

contrast. FLAG recommends this change in order for the 

analysis technique to be consistent with the national visibility 

goal. For plume analyses, FLAG recommends using the 

monthly average natural visual range conditions provided for 

each area in Table 10. 

If a screening analysis of a new or modified source can 

demonstrate that its emissions will not cause a plume with 

any hourly estimates of ∆E greater than or equal to 2.0, 

or the absolute value of the contrast values (|C|) greater 

than or equal to 0.05, the FLM is likely not to object to the 

issuance of the PSD permit based on near field visibility 

impacts and no further near field visibility analyses will be 

requested. More refined analyses (i.e., PLUVUE II) would be 

undertaken if the above conditions are not met and would 

be compared against lower levels of concern. For PLUVUE 

II analyses, the FLM would likely not object if ∆E < 1.0 and 

|C| < 0.02.

All analysis for Class I visibility impacts should include 

all visibility impairing emissions. This means that even if 

a facility is only considered a significant emitter of one 

pollutant, all pollutants that may contribute to impairment 

should be modeled together. Furthermore, since visibility 

is an instantaneous value, short-term (24-hour) maximum 

allowable emissions should be used.

•	 Level-1 Near Field Screening. Conducting a complete 

refined plume blight analysis can become rather 

complex, so three levels of evaluation are available to an 

applicant. The first, Level-1 screening, is the simplest and 

most conservative method. As described in the EPA’s 

Workbook for Estimating Visibility Impairment (EPA450/4-80-031):

Level-1 Screening: Level-1 screening is designed 

to provide a conservative estimate of plume visual 

impacts (i.e., impacts that would be larger than those 

calculated with more realistic input and modeling 

assumptions). This conservatism is achieved by the 

use within the screening model VISCREEN of worstcase meteorological conditions: extremely stable (F) 

atmospheric condition, coupled with a very low wind 

speed (1 m/s) persisting for 12 hours, with a wind that 

would transport the plume directly adjacent to the 

observer (as shown schematically in Figure 7).

Since little project specific information is used for a 

Level-1 screening analysis, documentation requirements 

are minimal. Basic information of emissions, 

meteorological parameters, and model results should be 

provided. Applicants are encouraged to supply electronic 

copies of all files necessary to reproduce the results. If 

an application shows estimated impact values within the 

thresholds, it is unlikely that additional evaluation will be 

necessary.

•	 Level-2 Near Field Screening. If Level-2 screening is 

necessary, more project specific information is now 

incorporated. Actual meteorology from the area and 

emission characteristics of the facility are used. Again, as 

described in the EPA’s Workbook for Estimating Visibility 

Impairment:

Level-2 Screening: As shown in Figure 1, Level-2 

plume visual impact screening is done if the Level-1 

results exceed the screening criteria. The objective of 

Level-2 screening is identical to that of Level-1—the 

estimation of worst-day plume visual impacts—but 

in Level-2 screening more realistic (less conservative) 

input, representative of the given source and the 

Class I area, is provided. This situation-specific input 

may include particle size distributions for plume and 

background that are different from those used in the 

default Level-1 analysis. Median background visual 

range based on on-site measurements rather than the 

map shown in Figure 9 might be used. However, the 

most important potential difference in input between 

Level-1 and Level-2 analysis centers on meteorology 

and plume transport and dispersion patterns. While 

the Level-1 analysis assumes F stability, a 1 m/s 

wind speed, and a wind direction that would carry 

plume material very close to the observer, in the 

Level-2 analysis, meteorological data and topography 

representative of the source area and Class I area may 

suggest that worst-case plume dispersion conditions 

are different.

It is important to note that the Agencies have maintained 

the recommendation that all applicants compare 

 USFS–NPS–USFWS 21
estimated modeled impacts from a facility against natural 

conditions. This is true for all analysis levels. The use of 

five years of site-representative meteorology and facilityspecific emission characteristics is what makes this 

analysis different. 

As a result of the increased project-specific information, 

documentation also should include summaries and/or 

tables describing the additional data sets and evaluation 

steps taken to conduct the analysis. 

Once again, meeting screening thresholds means that it 

is likely that the Agencies’ Class I air quality modeling 

procedures will have been satisfied.

•	 Level-3 Near Field Refined Analysis. A Level-3 analysis 

is the final assessment. An applicant can conduct a full 

refined analysis demonstrating estimates of frequency, 

magnitude, and spatial extent of a proposed project’s 

visibility impacts. The EPA’s Workbook for Estimating 

Visibility Impairment says:

Level-3 Analysis: In Level-3 analysis, the objective is 

broadened from conservative analysis of worst-case 

conditions to a realistic analysis of all conditions that 

would be expected to occur in a typical year in the 

region that includes both the emission source and 

the observer. Level-3 analysis is no longer considered 

screening because it is a comprehensive analysis of 

the magnitude and frequency of occurrence of plume 

visual impacts as observed at a sensitive Class I area 

vista.

It is important to determine the frequency of 

occurrence of visual impact because the adversity or 

significance of impact is dependent on how frequently 

an impact of a given magnitude occurs. For example, 

if a plume is perceptible from a Class I area a third of 

the time, the impact would be considered much more 

significant than if it were perceptible only one day 

per year. The assessment of frequency of occurrence 

of impact should be an integral part of Level-3 visual 

impact analysis.

As mentioned above, the threshold values for this 

analysis step changed. For this step, EPA’s PLUVUE II 

model is currently recommended. One main difference 

with PLUVUE II is its inability to evaluate more than 

one hour of impact per run. Because it is customary to 

evaluate five years of site-specific meteorology, it can 

become an extensive process. Applicants may want to 

develop and utilize tools to group hourly meteorological 

and post processing scenarios. The analysis identifies 

specific locations for plume/observer relationships. These 

observation points should be established within each 

potentially impacted Class I area. With each observer, 

potential impacts are calculated for all possible views. 

As with the meteorology, PLUVUE II is only able to 

assess one observer location per model run. Specific 

information on setup methods can be found in EPA’s 

Workbook for Estimating Visibility Impairment and 

PLUVUE II manual. 

Substantial documentation is needed for this more 

refined analysis. The discussion should summarize data 

sources, processing methods, and modeling utilities 

used, and information regarding all assumptions or 

consolidation criteria. In short, sufficient information and 

electronic files should be provided to the Agencies that 

will allow reviewers to reproduce the results. Due to the 

complexity of this refined analysis, the Agencies suggest 

that consultation occur between the applicant and the 

Agencies before working on the impact analysis begins. 

Furthermore, selection of model parameters and input 

data should be documented in a written protocol and 

agreed upon by the affected Agencies in advance of any 

modeling being conducted. 

If the estimated plume parameters exceed the 

aforementioned values, the FLM would rely on a case-bycase effects-based test (NPS 1993), taking into account 

magnitude, frequency, duration, and other factors, to decide 

whether to make an adverse impact determination. 

Distant/Multi-Source Techniques for Analyzing 

Whether a Plume or an Aggregation of Plumes Alters 

the General Appearance of a Scene (Revised)

This analysis is generally more complex than the near field, 

coherent plume modeling analyses and the guidance from 

EPA is less definitive, though it is evolving. The modeling 

system should include the capability to assess single and 

multiple sources in a temporally and spatially varying 

meteorological domain, accommodate modeling domains 

measuring hundreds of kilometers, include rough and 

complex terrain, provide pollutant concentration estimates 

for averaging times from one-hour to annual, and address 

inert and secondarily formed pollutants and dry and wet 

deposition. In the early 1990s the FLMs and the EPA 

recognized the need for a consistent, technically credible 

technique to estimate contributions to air quality of multiple 

new sources locating more than 50 km from Class I areas. 

Towards that end, on April 15, 2003, the EPA promulgated 

revisions to Appendix W of 40 C.F.R. §51 (Guideline on Air 

Quality Models). The EPA revised the Guideline to adopt 

the CALPUFF model as the preferred long-range transport 

model for inclusion in Appendix A of that document. This 

technique is usually applied when sources are located more 

than 50 kilometers from portions of a Class I area, when 

an aggregation of plumes may impact an area, or when the 

assumptions inherent in steady state visibility models do not 

apply.

The first-level analysis procedures discussed in this revision 

differ from FLAG 2000 in several discrete areas, but 

22 FLAG Phase I Report—Revised (2010)
generally remain the same. The primary differences are in the 

areas of the reference natural conditions that are used in the 

comparisons for thresholds of concern and using the average 

monthly relative humidity adjustment factors rather than the 

hour-by-hour factors identified in FLAG 2000. CALPUFF is 

still the preferred first-level air quality model for calculating 

pollutant concentrations, however, using “CALPUFF Lite” 

with single station meteorology is no longer recommended. 

We wish to emphasize that the first-level procedures defined 

herein are to be taken as a whole; any deviations from these 

procedures or ostensible refinements compromise the 

integrity of the analysis, and may warrant an hourly analysis 

for all hours in the analysis. Furthermore, the metric used for 

the first-level analysis (relative change in light extinction) is 

not necessarily the appropriate metric for a refined analysis. 

The procedures and metrics for refined analyses will need to 

be agreed upon by the affected Agencies. 

The initial step in conducting the first-level analysis is to run 

CALPUFF using a minimum of three years of mesoscale 

meteorological model output, and preferably five years, 

consistent with current EPA guidance. Selection of model 

parameters and input data should be documented in a 

written protocol and agreed upon by the affected Agencies 

in advance of any modeling being conducted. Please note 

emissions input considerations and model receptor grid data 

are discussed below. The indices for comparison with the 

Agencies’ levels of concern are calculated in CALPOST. The 

remainder of this discussion is focused on CALPOST.

After CALPUFF is run, CALPOST is used to evaluate 

whether the proposed source or modification will be below 

the Agencies’ threshold for concern (i.e., 5% change in light 

extinction). The CALPOST parameter MVISBK is set to eight 

(8), sub-mode five (M8_MODE = 5), and the background 

hygroscopic and non-hygroscopic aerosol levels are derived 

from the annual average natural conditions provided in Table 

6. The monthly relative humidity adjustment factors for the 

Class I area are input to the RHFAC array (Tables 7-9) in 

CALPOST. The 98th percentile test applies to the number 

of days that any model receptor in the Class I area exceeds 

the threshold. The visibility threshold for concern is not 

exceeded if the 98th percentile change in light extinction is 

less than 5% for each year modeled, when compared to the 

annual average natural condition value for that Class I area.

If this analysis indicates that the 98th percentile values for 

change in light extinction are equal to or greater than 5% 

for any year, then the Agencies will further scrutinize the 

applicant’s proposal. The Agencies will consider the full 

range of factors discussed below (in the “Expansion of 

Discussion of Process for Adverse Impact Determination” 

chapter) and any refined analyses provided by the applicant 

before making a recommendation to the FLM regarding 

potential adverse impacts. As noted above, these refined 

analyses should account for the relevant physicochemical 

processes that produce visibility impairing pollutants and 

accurately treat the relevant radiative transfer properties 

affecting visibility. This will likely entail using different 

meteorological and air quality models capable of producing 

hourly concentrations, or less, and using a three dimensional 

radiative transfer model (see refined analysis discussion 

below). 

For consistency with implementation of BART or the 

regional haze rule to specific Class I areas, the FLM or 

permitting authority may recommend use of the 20% best 

natural background values provided in Table 5 in lieu of 

annual averages on a case-by-case basis. 

Background Information on Thresholds

In its BART guidelines, EPA indicated that for regional haze, 

a source whose 98th percentile value of the haze index is 

greater than 0.5 deciview (dv) (approximately a 5% change in 

light extinction) is considered to contribute to regional haze 

visibility impairment. Similarly, a source that exceeds 1.0 

dv (approximately a 10% change in light extinction) causes 

visibility impairment. The 0.5 dv and 1.0 dv thresholds are 

similar to what the Agencies used in FLAG 2000. Therefore, 

for consistency between visibility protection programs and 

to address similar concerns, the Agencies will also use the 

98th percentile value as a threshold in the first-level visibility 

analyses for new source impacts. 

In its 2005 BART guidelines, the EPA also concluded that 

by using the 98th percentile of CALPUFF modeled impacts 

the sources that contribute 0.5 deciview to regional haze 

visibility impairment in a Class I area would effectively be 

captured, while minimizing the likelihood that the highest 

modeled visibility impacts might be caused by conservative 

assumptions in the model. Similarly, using the monthly 

average relative humidity adjustment factors, rather than 

the hour-by-hour factors, reduces some of the higher (e.g., 

weather –related) values seen in FLAG 2000.

Using the 98th percentile of modeled visibility values to 

compare to the 5% change in extinction threshold would 

exclude roughly seven days per year from consideration 

for each Class I area. However, consistent with the BART 

guidelines, the 98th percentile test applies to the number of 

days that any model receptor in the Class I area exceeds the 

threshold. Also, this test is limited to haze-like, first-level 

analyses. Therefore, all applicable sources locating within 

50 km of a Class I area would still need to assess coherent 

plume impacts in accordance with the procedure described 

above. Furthermore, applicable sources would need to assess 

sulfur and nitrogen deposition impacts at the Class I area. 

Natural Conditions

FLAG 2000 discussed assessing the change in visibility 

due to a proposed new source relative to annual average 

natural conditions. Therefore, it is important to define 

 USFS–NPS–USFWS 23
natural conditions for each Class I area. At the time of 

FLAG 2000, the Agencies acknowledged that the EPA 

was working on defining natural conditions in support of 

their visibility regulations. In the absence of more specific 

data, the FLMs at that time adopted the appropriate 

aerosol concentrations developed by the National Acid 

Precipitation Assessment Program (NAPAP) as estimates of 

natural conditions for each Class I area. The EPA has since 

published natural condition estimates for each Class I area. 

The natural condition values provided in FLAG 2000 and 

those developed by the EPA are based on similar underlying 

assumptions; consequently, the estimates are similar. 

Regardless, the EPA estimates should be used by applicants 

in future visibility impact assessments. Please note that 

Tables 5 and 6 contain estimates for the 20% best natural 

visibility and annual average natural visibility conditions for 

each Class I area, respectively. 

Relative Humidity Adjustment Factor

FLAG 2000 discussed the importance of the relative 

humidity adjustment factor (f(RH)) when calculating the 

sulfate and nitrate components of the visibility extinction 

coefficient. These aerosols are hygroscopic and the addition 

of water enhances their scattering efficiencies. FLAG 2000 

recommended using hour-by-hour f(RH) for the analysis. 

The EPA, in its 2005 BART guidelines, concluded that by 

using a monthly average f(RH) the likelihood that the highest 

modeled visibility impacts were caused by short-term and 

geographically different meteorological phenomena (e.g., 

weather events) would be minimized. The Agencies agree 

with the EPA that using the monthly f(RH) effectively 

neutralizes short-term weather events and are adopting a 

similar approach for Class I visibility impact analyses for new 

sources. Therefore, new sources performing Class I visibility 

analyses should use monthly average f(RH) values developed 

by EPA for large hygroscopic particles (Table 7), small 

hygroscopic particles (Table 8), and sea salt (Table 9), rather 

than the hourly values discussed in FLAG 2000.

Emissions Input

There are two other aspects of the visibility impact analysis 

that the Agencies would like to clarify at this time: (1) 

emissions input, and (2) the model receptor grid. Regarding 

the emission inputs, because applicants are assessing a 24-

hour average regional haze visibility impact, it is important 

that they model a corresponding maximum allowable 

24-hour mass emission rate, as opposed to monthly or 

annual average emissions. Using a 30 day average emission 

rate as input to the visibility modeling analyses does not 

restrict the facility from emitting pollution at a higher rate 

for shorter time periods (e.g., 24-hour average). A 30 day 

average emission rate smooths out days with high emissions, 

and therefore, would underestimate the predicted 24-hour 

visibility impacts. Because the emission rates and the 

corresponding averaging times influence the outcome of 

the analyses, it is critical that appropriate emissions are 

matched to the averaging time being assessed, and that these 

emission rates ultimately are included as enforceable permit 

conditions. This approach is consistent with the Guideline on 

Air Quality Models (Appendix W of 40 C.F.R. §51) and the 

EPA BART guidelines. Furthermore, if an applicant chooses 

to conduct any refined analyses, where visibility impairment 

is assessed at no more than an hourly basis, maximum 

hourly emissions should be analyzed.

Please note that all visibility impairing pollutants should 

be modeled from all modified or affected emission 

unit(s), regardless of which pollutants actually triggered 

NSR. Particulate Matter (PM) should also be speciated 

into filterable PM (coarse, fine, elemental carbon) and 

Condensable PM (organic carbon and sulfates) based on the 

best available information. Particulate speciation data for 

several source types can be found on the NPS Air Resources 

Division’s web site at:

- http://www.nature.nps.gov/air/permits/ect/index.cfm

Applicants should calculate the 24-hour average net 

emission increase for each pollutant from modified facilities 

as the maximum allowable 24-hour average minus the 

actual hourly rate averaged over the past two years (annual 

emissions over past two years/hours of operation over last 

two years).6

Model Receptor Grid

Since FLAG 2000 was published, the NPS Air Resources 

Division has developed a database of modeling receptors 

for all of the Class I areas in the contiguous United States. A 

file conversion program to convert the data from latitude/

longitude to other common mapping coordinates (currently 

Lambert Conformal and Universal Transverse Mercator 

(UTM)) has also been developed. Alaska and Hawaii are not 

yet complete, but will be included in the data sets when they 

are available. 

Permit applicants can download the Class I Receptor Data 

files, as well as the Conversion program, from the link below. 

For modeling consistency, the Agencies ask that permit 

applicants use the uniform receptor grids provided. Also 

available are the Class I boundary shape files that were used 

to create the receptor data files.

- http://www.nature.nps.gov/air/Maps/Receptors/

index.cfm

Receptor grids for FLM Class II areas should be dense 

enough to determine Class II increment consumption and 

6. Note that this is different from the emission change calculation used 

for short-term increment, which is calculated as the maximum allowable 

24-hour average minus the highest occurrence over the past two years.

24 FLAG Phase I Report—Revised (2010)
to perform any required “secondary impacts” (i.e., soils, 

vegetation and visibility) analyses. 

Refined Analysis

It is important to reiterate that the FLAG distant/multisource visibility analysis is only a first-level screening 

technique, primarily designed to identify those sources 

that are unlikely to significantly affect visibility and 

warrant no further analysis, and those that may adversely 

impact visibility and warrant further scrutiny. Visibility is 

experienced instantaneously, not on a 24-hour average 

basis. The 24-hour average visibility calculation in FLAG is 

acceptable because of a number of simplifying assumptions 

in the prescribed technique. Accepting certain EPA BART 

guideline procedures as an update to the FLAG techniques 

does not alter the first-level nature of the procedure. 

Modifying those simplifying assumptions negates the 

acceptability of using a 24-hour average. Consequently, 

any applicant whose visibility analysis deviates from the 

recommended FLAG screening procedures warrants 

performing an hour-by-hour analysis. 

Deviations from the first-level screening procedure 

should lead to refinements in the modeling and visibility 

analyses, not arbitrary adjustments to the prescribed firstlevel technique. This is especially important in dealing 

with weather-related events. The Agencies believe that 

by paralleling the BART guideline procedures they have 

adequately taken into account the effects of meteorological 

extremes, and model uncertainty. Therefore, given the 

Agencies’ desire to balance the positive and negative biases 

of the FLAG screening methodology, any modifications 

to the screening technique invalidate the Level 1 model 

results. Consequently, the Agencies do not expect permit 

applicants that exceed the visibility effects thresholds 

to scrutinize the data and attempt to disregard specific 

impact days due to weather. Under those circumstances, 

the permit applicant can accept the modeling results at 

face value, and then the FLM will decide whether or not 

those impacts are adverse. Alternatively, the applicant could 

conduct an hour-by-hour analysis (as opposed to using a 

24-hour average) by performing a refined analysis using 

a more sophisticated approach that requires determining 

particle concentrations and size distributions, calculation of 

particle growth dynamics, and application of Mie Theory 

to determine the optical characteristics of the aerosol 

distribution. Sophisticated radiative transfer models can 

then be applied, using aerosol optical characteristics, lighting 

and scene characteristics, and spatial distribution of the 

pollutants to calculate the path and wavelength of imageforming and non-image-forming light that reaches a specific 

observer from all points in the scene being viewed. The 

concept of this more refined approach is discussed in FLAG 

2000, and one possible approach is included in “Proposed 

FLAG Level II and III Visibility Assessment” (Schichtel et al. 

2006). However, if this situation arises, permit applicants 

are encouraged to consult with the Agencies and discuss the 

specifics of this refined analysis. 

3.3.4. Summary (Revised)

FLAG provides recommendations, specific procedures, and 

interpretation of results for assessing visibility impacts of 

new or modified sources on Class I area resources. Although 

FLMs only have a formal role in the permitting process for 

applications that affect Class I areas, this information can be 

used for Class II areas as well. FLAG addresses assessments 

for sources proposed for locations near (generally within 50 

km) and at large distances (greater than 50 km) from these 

areas. The key components of the recommendations are 

highlighted below.

In general, FLAG recommends that an applicant:

•	 Apply the Q/D test (see section 3.2, ‘Initial Screening 

Criteria’) for proposed sources greater than 50 km from 

a Class I area to determine whether or not any further 

visibility analysis is necessary. 

•	 Consult with the appropriate regulatory agency and with 

the FLM for the affected Class I area(s) or other affected 

area for confirmation of preferred visibility analysis 

procedures.

•	 Obtain FLM recommendation for the specified reference 

levels (estimate of natural conditions) and, if applicable, 

FLM recommended plume/observer geometries and 

model receptor locations.

•	 Apply the applicable EPA Guideline, steady-state models 

for regions within the Class I area that are affected by 

plumes or layers that are viewed against a background 

(generally within 50 km of the source).

- Calculate hourly estimates of changes in visibility, as 

characterized by the change in the color difference 

index (∆E) and plume contrast (C), with respect to 

natural conditions, and compare these estimates with 

the thresholds given in section 3.3.3. 

•	 For regions of the Class I area where visibility impairment 

from the source would cause a general alteration of the 

appearance of the scene (generally 50 km or more away 

from the source or from the interaction of the emissions 

from multiple sources), apply a non-steady-state air 

quality model with chemical transformation capabilities 

(refer to EPA guidance documents), which yields ambient 

concentrations of visibility-impairing pollutants. At each 

Class I receptor:

- Calculate the change in extinction due to the source 

being analyzed, compare these changes with the 

reference conditions, and then compare these results 

with the thresholds given in section 3.3.3. 

- Utilize estimates of annual average natural visibility 

conditions for each Class I area as presented in 

Table 6, unless otherwise recommended by the 

 USFS–NPS–USFWS 25
FLM or permitting authority. Alternative estimates 

of visibility conditions are provided in Table 5 

for consistency with State agencies that elected to 

use 20% best visibility for regional haze or BART 

implementations. 

•	 If first-level modeling results are above levels of concern, 

continue to consult with the Agencies to discuss other 

considerations (e.g., possible impact mitigation, more 

refined analyses). 

This review process for distant/multi-source applications is 

portrayed schematically in Figure 4.

3.3.5. Natural Visibility Conditions and Analysis 

Methods (New)

Both distant/multi-source applications and near-field 

analyses require an estimate of natural visibility conditions. 

The effects of visibility impairing emissions from a source are 

compared to the natural visibility conditions to determine 

the potential for unacceptable visibility impacts. The 

methods and data for calculating natural visibility conditions 

in FLAG are presented in this section. The calculation of 

visibility metrics under the distant/multi-source application 

is also described. For the distant/multi-source application, 

aerosol species components are provided for input to the 

CALPUFF modeling system, which is the suggested model 

Figure 4. Procedure for Visibility Assessment for Distant/Multi-Source Applications (Revised)

*Q/D test only applies to sources located greater that 50 km from a Class I area.

**Difference Change in the 98th percentile with respect to (wrt) the annual average Natural Condition (NC). Applicant should use the 20th percentile best natural condition background if recommended by the FLM or permitting authority.

26 FLAG Phase I Report—Revised (2010)
for most of these applications. For near-field analyses, visual 

ranges under natural conditions are provided for input to the 

VISCREEN and PLUVUE-II models.

Natural visibility 

conditions

Distant/Multi-source: 

Natural visibility conditions 

are affected by the light 

scattering of air molecules 

(Rayleigh scattering) and 

by naturally occurring 

aerosols. The majority 

of aerosols, both natural 

and anthropogenic, that 

affect light extinction can 

be categorized as sulfates ((NH4

)2SO4), nitrates (NH4NO3), 

organic mass (OM), elemental carbon (EC), soil, sea salt, 

and coarse mass (CM). The light scattering efficiency of 

aerosols is affected by the size of the aerosol relative to the 

wavelength of light. Sulfates, nitrates, and sea salt are all 

hygroscopic, which affects their size and their light scattering 

efficiency as they acquire or shed water molecules. The 

relationship between the aerosol components and light 

extinction is shown through the equations in Figure 5. The 

hygroscopic effects are accounted for through the relative 

humidity adjustment factors (f(RH)) terms in the equations 

in Figure 5. The aerosol concentrations and monthly relative 

humidity adjustment factors for calculating natural visibility 

conditions are found in Tables 5 through 10.

The aerosol concentrations for the 20% best natural 

conditions are found in Table 5 and the annual average 

natural concentrations are found in Table 6. 

Near-field: The near-field visibility analysis is generally 

performed using either VISCREEN or PLUVUE-II. For 

calculating the effect of a plume on visibility, a background 

visibility, expressed as a visual range, must be input to these 

models. Appropriate average natural conditions, by month 

and Class I area are listed in Table 10. The values in Table 

10 were determined by calculating the month by month 

light extinction values and calculating the visual range (VR) 

(VR=3912/bext). 

Example Calculation of Natural Conditions and 

Change in Light Extinction

The annual average concentration and the relative humidity 

adjustment factors (f{L,S,SS}(RH)) for the Alpine Lakes 

Wilderness for January will be used for illustration of the 

calculations.

1. Look up the Alpine Lakes Wilderness annual average 

concentration values in Table 6 for sulfate ((NH4

)2SO4), 

nitrate (NH4

NO3), organic mass (OM), Elemental Carbon 

(EC), soil, coarse mass (CM), sea salt, and Rayleigh 

scattering.

2. Look up the f(RH) factors for large sulfate/nitrate (table 

7), small sulfate/nitrate (table 8), and sea salt (table 9); 

January in this example. 

a. fL(RH) = 3.86

b. fS(RH) = 5.87

c. fSS(RH) = 5.35

3. Calculate the large and small sulfate, nitrate, and organic 

mass, as defined in Figure 5.

4.

Table 3. Step 3 Calculation Results for the Alpine Lakes 

Wilderness Example 

Total Large Small

Sulfate 0.12 0.00072 0.11928

Nitrate 0.10 0.0005 0.0995

Organic Mass 0.60 0.018 0.582

Apply to bext equation in Figure 5:

bext= 

2.2 × 5.87 × 0.11928 + 

4.8 × 3.86 × 0.00072

{Sulfate}

+ 2.4 × 5.87 × 0.0995 + 

5.1 × 3.86 × 0.0005

{Nitrate}

+ 2.8 × 0.582 + 6.1 × 

0.018 

{Organic Mass}

+ 10 × 0.02 {Elemental Carbon}

+ 1 × 0.23 {Soil}

+ 0.6 × 1.30 {Coarse Mass}

+ 1.7 × 5.35 × 0.06} {Sea Salt

+ 11 {Rayleigh}

 + 0.33 × 0 {NO2

}

 bext =17.46 Mm-1

 

Table 2. Section of Table 6 Used for Step 1 Calculations of the Alpine Lakes Wilderness 

Example

Class I Area

(NH4

)

2

SO4

μg/m3

NH4NO3

μg/m3

OM

μg/m3

EC

μg/m3

Soil

μg/m3

CM

μg/m3

Sea Salt

μg/m3

Rayleigh

Mm-1

Acadia NP 0.23 0.10 1.67 0.02 0.24 2.14 0.14 12

Agua Tibia 

Wilderness 0.12 0.10 0.60 0.02 0.50 3.00 0.14 11

Alpine Lakes 

Wilderness 0.12 0.10 0.60 0.02 0.23 1.30 0.06 11

... ... ... ... ... ... ... ... ...

 USFS–NPS–USFWS 27
To calculate the change in light extinction from the impacts 

from an air pollution source, the species concentrations 

from the source are added to the total species concentrations 

in steps 3 and 4 above and the new total light extinction is 

calculated. Therefore, if a source contributed 0.05 μg/m3

 of 

sulfate ((NH4

)2SO4) and 0.01 μg/m3 of nitrate (NH4NO3) at a 

receptor, the total, large and small sulfate and nitrate values 

would be:

Table 4. Step 4 Calculation Results for the Alpine Lakes 

Wilderness Example

Total Large Small

Sulfate 0.17 (0.12+0.05) 0.001445 0.168555

Nitrate 0.11 (0.10+0.01) 0.000605 0.109395

The other concentrations and the relative humidity 

adjustment factors would remain as in step 4 of the natural 

condition example. After recalculating the light extinction 

accounting for the effect of the source (bext(source+nat cond)), the 

new light extinction would be 18.25 Mm-1.

The change in light extinction (∆bext) would simply be:

∆bext = (bext(source+nat cond) – bext(nat cond)) / bext(nat cond) or:

∆bext = (18.25 – 17.46) / 17.46

∆bext = 0.045 (4.5%)

The example provided here is to illustrate the process. 

Usually the concentrations and relative humidity adjustment 

factors would be extracted from the appropriate tables 

and input to one of the air quality model post processing 

programs. 

28 FLAG Phase I Report—Revised (2010)
bext = 2.2 × fS(RH) × [Small Sulfate] + 4.8 × fL(RH) × [Large Sulfate] 

+ 2.4 × fS(RH) × [Small Nitrate] + 5.1 × fL(RH) × [Large Nitrate] 

+ 2.8 × [Small Organic Mass] + 6.1 × [Large Organic Mass] 

+ 10 × [Elemental Carbon] 

+ 1 × [Fine Soil] 

+ 0.6 × [Coarse Mass] 

+ 1.7 × fSS(RH) × [Sea Salt] 

+ Rayleigh Scattering (Site Specific) 

+ 0.33 × [NO2 (ppb)] {or as: 0.1755 × [NO2 (μg/m3

)]} 

Where: 

 [ ] indicates concentrations in μg/m3

 fS(RH) = Relative humidity adjustment factor for small sulfate and nitrate 

 fL(RH) = Relative humidity adjustment factor for large sulfate and nitrate 

 fSS(RH) = Relative humidity adjustment factor for sea salt 

 For Total Sulfate < 20 μg/m3

: 

 [Large Sulfate] = ([Total Sulfate] / 20 μg/m3

) × [Total Sulfate] 

 

 For Total Sulfate ≥ 20 μg/m3

: 

 [Large Sulfate] = [Total Sulfate] 

 And: 

 [Small Sulfate] = [Total Sulfate] – [Large Sulfate] 

To calculate large and small nitrate and organic mass, substitute ({Large, Small, Total} {Nitrate, 

Organic Mass}) for Sulfate. 

Figure 5. IMPROVE Equation for Calculating Light Extinction

http://vista.cira.colostate.edu/improve/Publications/GrayLit/019_RevisedIMPROVEeq/RevisedIMPROVEAlgorithm3.doc

 USFS–NPS–USFWS 29
Table 5. 20% Best Natural Conditions – Concentrations and Rayleigh Scattering By Class I Area

Class I Area

(NH4

)

2

SO4

μg/m3

NH4

NO3

μg/m3

OM

μg/m3

EC

μg/m3

Soil

μg/m3

CM

μg/m3

Sea Salt

μg/m3

Rayleigh

Mm-1 Type

Acadia NP 0.09 0.03 0.68 0.01 0.10 0.94 0.03 12 B20%

Agua Tibia Wilderness 0.03 0.04 0.26 0.01 0.26 1.20 0.04 11 B20%

Alpine Lakes Wilderness 0.04 0.03 0.15 0.01 0.05 0.30 0.02 11 B20%

Anaconda Pintler Wilderness 0.04 0.03 0.12 0.01 0.07 0.31 0.00 10 B20%

Ansel Adams Wilderness 0.02 0.01 0.12 0.01 0.07 0.44 0.01 9 B20%

Arches NP 0.07 0.06 0.23 0.01 0.14 0.89 0.01 9 B20%

Badlands NP 0.05 0.05 0.23 0.01 0.22 0.99 0.00 11 B20%

Bandelier NM 0.07 0.06 0.31 0.01 0.16 0.91 0.00 9 B20%

Bering Sea Wilderness B20%

Big Bend NP 0.05 0.04 0.24 0.01 0.11 0.80 0.00 10 B20%

Black Canyon of the Gunnison NP 0.06 0.04 0.24 0.01 0.13 0.88 0.00 9 B20%

Bob Marshall Wilderness 0.05 0.04 0.19 0.01 0.08 0.37 0.00 10 B20%

Bosque del Apache Wilderness 0.08 0.06 0.30 0.01 0.15 0.97 0.02 10 B20%

Boundary Waters Canoe Area 

Wilderness

0.11 0.02 0.50 0.01 0.13 0.86 0.01 11 B20%

Breton Wilderness 0.14 0.05 0.73 0.01 0.27 2.26 0.07 11 B20%

Bridger Wilderness 0.05 0.04 0.14 0.01 0.07 0.33 0.00 9 B20%

Brigantine Wilderness 0.12 0.04 0.86 0.01 0.24 1.73 0.04 12 B20%

Bryce Canyon NP 0.04 0.05 0.18 0.01 0.10 0.60 0.00 9 B20%

Cabinet Mountains Wilderness 0.05 0.05 0.13 0.01 0.09 0.42 0.01 10 B20%

Caney Creek Wilderness 0.07 0.06 0.68 0.01 0.14 1.51 0.02 11 B20%

Canyonlands NP 0.07 0.06 0.23 0.01 0.14 0.89 0.01 9 B20%

Cape Romain Wilderness 0.14 0.06 0.88 0.01 0.24 1.99 0.04 12 B20%

Capitol Reef NP 0.06 0.07 0.26 0.01 0.15 0.79 0.01 9 B20%

Caribou Wilderness 0.03 0.02 0.12 0.01 0.08 0.24 0.01 10 B20%

Carlsbad Caverns NP 0.06 0.05 0.26 0.01 0.12 0.82 0.00 9 B20%

Chassahowitzka Wilderness 0.14 0.08 1.02 0.01 0.28 2.46 0.02 11 B20%

Chiricahua NM 0.06 0.05 0.27 0.01 0.13 0.81 0.00 10 B20%

Chiricahua Wilderness 0.06 0.05 0.27 0.01 0.13 0.81 0.00 10 B20%

Cohutta Wilderness 0.09 0.08 0.69 0.01 0.15 1.06 0.01 11 B20%

Crater Lake NP 0.02 0.02 0.08 0.01 0.07 0.23 0.01 9 B20%

Craters of the Moon NM 0.06 0.05 0.19 0.01 0.12 0.69 0.01 10 B20%

Cucamonga Wilderness 0.03 0.03 0.15 0.01 0.14 0.67 0.01 9 B20%

Denali NP & Pres 0.04 0.02 0.08 0.01 0.05 0.31 0.01 11 B20%

Desolation Wilderness 0.04 0.03 0.15 0.01 0.09 0.51 0.01 9 B20%

Diamond Peak Wilderness 0.02 0.02 0.08 0.01 0.07 0.23 0.01 9 B20%

Dolly Sods Wilderness 0.10 0.05 0.80 0.01 0.17 0.96 0.01 10 B20%

Dome Land Wilderness 0.03 0.02 0.18 0.01 0.08 0.43 0.01 10 B20%

Eagle Cap Wilderness 0.05 0.02 0.17 0.01 0.10 0.50 0.01 10 B20%

Eagles Nest Wilderness 0.04 0.03 0.14 0.01 0.08 0.36 0.00 8 B20%

Emigrant Wilderness 0.03 0.02 0.10 0.00 0.08 0.50 0.01 10 B20%

Everglades NP 0.16 0.07 0.77 0.01 0.16 1.86 0.12 11 B20%

Fitzpatrick Wilderness 0.05 0.04 0.14 0.01 0.07 0.33 0.00 9 B20%

Flat Tops Wilderness 0.04 0.03 0.14 0.01 0.08 0.36 0.00 8 B20%

Galiuro Wilderness 0.06 0.05 0.27 0.01 0.13 0.81 0.00 10 B20%

30 FLAG Phase I Report—Revised (2010)
Table 5. 20% Best Natural Conditions – Concentrations and Rayleigh Scattering By Class I Area

Class I Area

(NH4

)

2

SO4

μg/m3

NH4

NO3

μg/m3

OM

μg/m3

EC

μg/m3

Soil

μg/m3

CM

μg/m3

Sea Salt

μg/m3

Rayleigh

Mm-1 Type

Gates of the Mountains Wilderness 0.04 0.04 0.13 0.01 0.07 0.49 0.00 9 B20%

Gearhart Mountain Wilderness 0.02 0.02 0.08 0.01 0.07 0.23 0.01 9 B20%

Gila Wilderness 0.06 0.04 0.22 0.01 0.09 0.45 0.00 9 B20%

Glacier NP 0.05 0.03 0.17 0.01 0.11 0.57 0.00 11 B20%

Glacier Peak Wilderness 0.02 0.03 0.09 0.00 0.04 0.28 0.01 11 B20%

Goat Rocks Wilderness 0.02 0.01 0.06 0.00 0.04 0.21 0.01 10 B20%

Grand Canyon NP 0.04 0.03 0.12 0.01 0.10 0.59 0.00 9 B20%

Grand Teton NP 0.06 0.05 0.17 0.01 0.08 0.33 0.00 9 B20%

Great Gulf Wilderness 0.09 0.04 0.56 0.01 0.10 1.05 0.02 11 B20%

Great Sand Dunes NP & Pres 0.06 0.05 0.29 0.01 0.15 0.90 0.00 9 B20%

Great Smoky Mountains NP 0.09 0.06 0.78 0.01 0.16 1.47 0.01 11 B20%

Guadalupe Mountains NP 0.06 0.05 0.26 0.01 0.12 0.82 0.00 9 B20%

Haleakala NP 0.05 0.04 0.24 0.01 0.11 1.59 0.13 10 B20%

Hawaii Volcanoes NP 0.03 0.04 0.27 0.01 0.06 0.64 0.11 10 B20%

Hells Canyon Wilderness 0.06 0.02 0.19 0.01 0.14 0.81 0.01 11 B20%

Hercules-Glades Wilderness 0.09 0.06 0.78 0.01 0.16 1.86 0.02 11 B20%

Hoover Wilderness 0.03 0.02 0.08 0.01 0.06 0.55 0.00 9 B20%

Isle Royale NP 0.10 0.02 0.34 0.01 0.09 0.79 0.01 12 B20%

James River Face Wilderness 0.11 0.06 0.71 0.01 0.20 1.39 0.01 11 B20%

Jarbidge Wilderness 0.05 0.03 0.14 0.01 0.05 0.33 0.00 10 B20%

John Muir Wilderness 0.02 0.01 0.12 0.01 0.07 0.44 0.01 9 B20%

Joshua Tree NP 0.04 0.02 0.20 0.01 0.17 0.94 0.02 10 B20%

Joyce Kilmer-Slickrock Wilderness 0.09 0.06 0.78 0.01 0.16 1.47 0.01 11 B20%

Kaiser Wilderness 0.02 0.01 0.12 0.01 0.07 0.44 0.01 9 B20%

Kalmiopsis Wilderness 0.03 0.02 0.31 0.01 0.05 0.99 0.04 12 B20%

Kings Canyon 0.03 0.03 0.18 0.01 0.08 0.73 0.02 11 B20%

La Garita Wilderness 0.06 0.04 0.24 0.01 0.13 0.88 0.00 9 B20%

Lassen Volcanic NP 0.03 0.02 0.12 0.01 0.08 0.24 0.01 10 B20%

Lava Beds NM 0.03 0.03 0.14 0.01 0.06 0.46 0.00 10 B20%

Linville Gorge Wilderness 0.08 0.06 0.67 0.01 0.14 1.04 0.01 11 B20%

Lostwood Wilderness 0.06 0.04 0.23 0.01 0.22 1.05 0.01 11 B20%

Lye Brook Wilderness 0.05 0.03 0.36 0.01 0.09 0.63 0.01 11 B20%

Mammoth Cave NP 0.11 0.08 0.86 0.01 0.24 1.54 0.01 11 B20%

Marble Mountain Wilderness 0.03 0.02 0.12 0.01 0.06 0.36 0.01 10 B20%

Maroon Bells-Snowmass Wilderness 0.04 0.03 0.14 0.01 0.08 0.36 0.00 8 B20%

Mazatzal Wilderness 0.06 0.05 0.30 0.01 0.14 0.80 0.00 10 B20%

Medicine Lake Wilderness 0.06 0.05 0.24 0.01 0.20 1.13 0.00 11 B20%

Mesa Verde NP 0.06 0.05 0.24 0.01 0.17 0.67 0.00 9 B20%

Mingo Wilderness 0.12 0.04 0.88 0.01 0.21 1.49 0.01 12 B20%

Mission Mountains Wilderness 0.05 0.04 0.19 0.01 0.08 0.37 0.00 10 B20%

Mokelumne Wilderness 0.04 0.03 0.15 0.01 0.09 0.51 0.01 9 B20%

Moosehorn Wilderness 0.11 0.04 0.76 0.01 0.12 1.25 0.02 12 B20%

Mount Adams Wilderness 0.02 0.01 0.06 0.00 0.04 0.21 0.01 10 B20%

Mount Baldy Wilderness 0.05 0.04 0.19 0.01 0.11 0.53 0.00 9 B20%

Mount Hood Wilderness 0.02 0.02 0.06 0.00 0.05 0.15 0.01 10 B20%

 USFS–NPS–USFWS 31
Table 5. 20% Best Natural Conditions – Concentrations and Rayleigh Scattering By Class I Area

Class I Area

(NH4

)

2

SO4

μg/m3

NH4

NO3

μg/m3

OM

μg/m3

EC

μg/m3

Soil

μg/m3

CM

μg/m3

Sea Salt

μg/m3

Rayleigh

Mm-1 Type

Mount Jefferson Wilderness 0.02 0.02 0.08 0.00 0.03 0.31 0.01 11 B20%

Mount Rainier NP 0.03 0.02 0.18 0.01 0.06 0.83 0.02 11 B20%

Mount Washington Wilderness 0.02 0.02 0.08 0.00 0.03 0.31 0.01 11 B20%

Mount Zirkel Wilderness 0.06 0.04 0.16 0.01 0.09 0.60 0.00 8 B20%

Mountain Lakes Wilderness 0.02 0.02 0.08 0.01 0.07 0.23 0.01 9 B20%

North Absaroka Wilderness 0.05 0.04 0.16 0.00 0.11 0.82 0.00 9 B20%

North Cascades NP 0.02 0.03 0.09 0.00 0.04 0.28 0.01 11 B20%

Okefenokee Wilderness 0.13 0.07 0.92 0.01 0.22 1.69 0.03 11 B20%

Olympic NP 0.04 0.03 0.23 0.01 0.03 0.50 0.04 11 B20%

Otter Creek Wilderness 0.10 0.05 0.80 0.01 0.17 0.96 0.01 10 B20%

Pasayten Wilderness 0.04 0.03 0.07 0.00 0.07 0.24 0.01 10 B20%

Pecos Wilderness 0.04 0.03 0.16 0.01 0.08 0.67 0.00 8 B20%

Petrified Forest NP 0.06 0.06 0.28 0.01 0.15 0.75 0.00 9 B20%

Pine Mountain Wilderness 0.06 0.05 0.30 0.01 0.14 0.80 0.00 10 B20%

Pinnacles NM 0.06 0.04 0.31 0.01 0.16 1.50 0.06 11 B20%

Point Reyes NS 0.12 0.04 0.33 0.01 0.13 1.08 0.25 12 B20%

Presidential Range-Dry River 

Wilderness

0.09 0.04 0.56 0.01 0.10 1.05 0.02 11 B20%

Rawah Wilderness 0.06 0.04 0.16 0.01 0.09 0.60 0.00 8 B20%

Red Rock Lakes Wilderness 0.06 0.05 0.17 0.01 0.08 0.33 0.00 9 B20%

Redwood NP 0.05 0.03 0.28 0.01 0.06 1.02 0.10 11 B20%

Rocky Mountain NP 0.04 0.02 0.15 0.01 0.09 0.68 0.00 9 B20%

Roosevelt Campobello International 

Park

0.11 0.04 0.76 0.01 0.12 1.25 0.02 12 B20%

Saguaro NP 0.07 0.05 0.32 0.01 0.22 1.15 0.03 10 B20%

Saint Marks Wilderness 0.14 0.06 0.81 0.01 0.24 2.17 0.04 11 B20%

Salt Creek Wilderness 0.05 0.06 0.31 0.01 0.17 1.00 0.02 10 B20%

San Gabriel Wilderness 0.03 0.03 0.15 0.01 0.14 0.67 0.01 9 B20%

San Gorgonio Wilderness 0.03 0.02 0.15 0.01 0.10 0.62 0.02 10 B20%

San Jacinto Wilderness 0.03 0.02 0.15 0.01 0.10 0.62 0.02 10 B20%

San Pedro Parks Wilderness 0.05 0.04 0.14 0.01 0.09 0.34 0.01 8 B20%

San Rafael Wilderness 0.03 0.04 0.22 0.01 0.11 0.79 0.02 10 B20%

Sawtooth Wilderness 0.05 0.04 0.23 0.01 0.10 0.37 0.00 10 B20%

Scapegoat Wilderness 0.05 0.04 0.19 0.01 0.08 0.37 0.00 10 B20%

Selway-Bitterroot Wilderness 0.04 0.03 0.12 0.01 0.07 0.31 0.00 10 B20%

Seney Wilderness 0.08 0.01 0.38 0.01 0.09 0.80 0.01 12 B20%

Sequoia NP 0.03 0.03 0.18 0.01 0.08 0.73 0.02 11 B20%

Shenandoah NP 0.08 0.07 0.56 0.01 0.14 1.20 0.01 10 B20%

Shining Rock Wilderness 0.05 0.05 0.51 0.01 0.13 0.56 0.01 10 B20%

Sierra Ancha Wilderness 0.06 0.05 0.33 0.02 0.14 0.73 0.01 10 B20%

Simeonof Wilderness 0.06 0.05 0.25 0.02 0.04 1.18 0.25 12 B20%

Sipsey Wilderness 0.11 0.10 0.81 0.01 0.25 1.66 0.01 11 B20%

South Warner Wilderness 0.03 0.03 0.14 0.01 0.06 0.46 0.00 10 B20%

Strawberry Mountain Wilderness 0.05 0.02 0.17 0.01 0.10 0.50 0.01 10 B20%

Superstition Wilderness 0.07 0.05 0.31 0.01 0.16 0.84 0.00 10 B20%

32 FLAG Phase I Report—Revised (2010)
Table 5. 20% Best Natural Conditions – Concentrations and Rayleigh Scattering By Class I Area

Class I Area

(NH4

)

2

SO4

μg/m3

NH4

NO3

μg/m3

OM

μg/m3

EC

μg/m3

Soil

μg/m3

CM

μg/m3

Sea Salt

μg/m3

Rayleigh

Mm-1 Type

Swanquarter Wilderness 0.12 0.06 0.65 0.01 0.23 2.38 0.05 12 B20%

Sycamore Canyon Wilderness 0.06 0.05 0.28 0.01 0.12 0.62 0.00 9 B20%

Teton Wilderness 0.06 0.05 0.17 0.01 0.08 0.33 0.00 9 B20%

Theodore Roosevelt NP 0.07 0.04 0.26 0.01 0.21 1.20 0.01 11 B20%

Thousand Lakes Wilderness 0.03 0.02 0.12 0.01 0.08 0.24 0.01 10 B20%

Three Sisters Wilderness 0.02 0.02 0.08 0.00 0.03 0.31 0.01 11 B20%

Tuxedni Wilderness 0.03 0.04 0.09 0.01 0.03 0.52 0.05 12 B20%

UL Bend Wilderness 0.05 0.03 0.18 0.01 0.15 0.93 0.01 11 B20%

Upper Buffalo Wilderness 0.08 0.06 0.68 0.01 0.16 1.33 0.01 11 B20%

Ventana Wilderness 0.06 0.04 0.31 0.01 0.16 1.50 0.06 11 B20%

Virgin Islands NP 0.18 0.07 0.21 0.01 0.12 1.53 0.26 11 B20%

Voyageurs NP 0.12 0.02 0.56 0.01 0.10 0.86 0.01 12 B20%

Washakie Wilderness 0.05 0.04 0.16 0.00 0.11 0.82 0.00 9 B20%

Weminuche Wilderness 0.06 0.04 0.24 0.01 0.13 0.88 0.00 9 B20%

West Elk Wilderness 0.04 0.03 0.14 0.01 0.08 0.36 0.00 8 B20%

Wheeler Peak Wilderness 0.04 0.03 0.16 0.01 0.08 0.67 0.00 8 B20%

White Mountain Wilderness 0.05 0.03 0.24 0.01 0.08 0.67 0.01 9 B20%

Wichita Mountains Wilderness 0.03 0.04 0.28 0.01 0.15 1.52 0.01 11 B20%

Wind Cave NP 0.05 0.04 0.20 0.01 0.19 1.05 0.00 10 B20%

Wolf Island Wilderness 0.13 0.07 0.92 0.01 0.22 1.69 0.03 11 B20%

Yellowstone NP 0.06 0.05 0.17 0.01 0.08 0.33 0.00 9 B20%

Yolla Bolly-Middle Eel Wilderness 0.03 0.02 0.12 0.01 0.06 0.36 0.01 10 B20%

Yosemite NP 0.03 0.02 0.10 0.00 0.08 0.50 0.01 10 B20%

Zion NP 0.05 0.06 0.28 0.01 0.10 0.60 0.01 10 B20%

 USFS–NPS–USFWS 33
Table 6. Annual Average Natural Conditions - Concentrations and Rayleigh Scattering By Class I Area

Class I Area

(NH4

)

2

SO4

μg/m3

NH4NO3

μg/m3

OM

μg/m3

EC

μg/m3

Soil

μg/m3

CM

μg/m3

Sea Salt

μg/m3

Rayleigh

Mm-1 Type

Acadia NP 0.23 0.10 1.67 0.02 0.25 2.14 0.14 12 Annual

Agua Tibia Wilderness 0.12 0.10 0.60 0.02 0.50 3.00 0.14 11 Annual

Alpine Lakes Wilderness 0.12 0.10 0.60 0.02 0.23 1.30 0.06 11 Annual

Anaconda Pintler Wilderness 0.12 0.10 0.60 0.02 0.39 1.79 0.02 10 Annual

Ansel Adams Wilderness 0.12 0.10 0.58 0.02 0.46 2.88 0.03 9 Annual

Arches NP 0.12 0.10 0.60 0.02 0.50 2.92 0.01 9 Annual

Badlands NP 0.12 0.10 0.60 0.02 0.50 3.00 0.01 11 Annual

Bandelier NM 0.12 0.10 0.60 0.02 0.50 2.86 0.02 9 Annual

Bering Sea Wilderness Annual

Big Bend NP 0.12 0.10 0.60 0.02 0.50 3.00 0.03 10 Annual

Black Canyon of the Gunnison NP 0.12 0.10 0.60 0.02 0.49 2.59 0.01 9 Annual

Bob Marshall Wilderness 0.12 0.10 0.60 0.02 0.44 2.34 0.01 10 Annual

Bosque del Apache Wilderness 0.12 0.10 0.60 0.02 0.50 3.00 0.04 10 Annual

Boundary Waters Canoe Area 

Wilderness

0.23 0.10 1.71 0.02 0.31 2.53 0.02 11 Annual

Breton Wilderness 0.23 0.10 1.78 0.02 0.48 3.01 0.19 11 Annual

Bridger Wilderness 0.12 0.10 0.60 0.02 0.44 1.88 0.01 9 Annual

Brigantine Wilderness 0.23 0.10 1.80 0.02 0.47 3.00 0.22 12 Annual

Bryce Canyon NP 0.12 0.10 0.60 0.02 0.50 2.87 0.01 9 Annual

Cabinet Mountains Wilderness 0.12 0.10 0.60 0.02 0.41 2.31 0.02 10 Annual

Caney Creek Wilderness 0.23 0.10 1.80 0.02 0.50 3.00 0.03 11 Annual

Canyonlands NP 0.12 0.10 0.60 0.02 0.50 2.92 0.01 9 Annual

Cape Romain Wilderness 0.23 0.10 1.80 0.02 0.45 3.00 0.20 12 Annual

Capitol Reef NP 0.11 0.10 0.58 0.02 0.50 2.78 0.00 9 Annual

Caribou Wilderness 0.12 0.10 0.60 0.02 0.44 1.82 0.01 10 Annual

Carlsbad Caverns NP 0.12 0.10 0.60 0.02 0.50 3.00 0.02 9 Annual

Chassahowitzka Wilderness 0.23 0.10 1.81 0.02 0.50 3.00 0.08 11 Annual

Chiricahua NM 0.12 0.10 0.60 0.02 0.50 3.00 0.02 10 Annual

Chiricahua Wilderness 0.12 0.10 0.60 0.02 0.50 3.00 0.02 10 Annual

Cohutta Wilderness 0.23 0.10 1.71 0.02 0.50 2.45 0.02 11 Annual

Crater Lake NP 0.12 0.10 0.60 0.02 0.39 1.67 0.02 9 Annual

Craters of the Moon NM 0.12 0.10 0.60 0.02 0.50 2.92 0.01 10 Annual

Cucamonga Wilderness 0.12 0.10 0.60 0.02 0.50 3.00 0.04 9 Annual

Denali NP & Pres 0.12 0.05 0.60 0.02 0.14 1.12 0.04 11 Annual

Desolation Wilderness 0.12 0.10 0.60 0.02 0.43 1.92 0.01 9 Annual

Diamond Peak Wilderness 0.12 0.10 0.60 0.02 0.39 1.67 0.02 9 Annual

Dolly Sods Wilderness 0.23 0.10 1.80 0.02 0.43 2.19 0.02 10 Annual

Dome Land Wilderness 0.12 0.10 0.60 0.02 0.50 3.00 0.03 10 Annual

Eagle Cap Wilderness 0.12 0.10 0.60 0.02 0.50 2.99 0.04 10 Annual

Eagles Nest Wilderness 0.12 0.10 0.60 0.02 0.48 2.12 0.00 8 Annual

Emigrant Wilderness 0.12 0.10 0.60 0.02 0.44 3.00 0.02 10 Annual

Everglades NP 0.23 0.10 1.79 0.02 0.50 3.00 0.31 11 Annual

Fitzpatrick Wilderness 0.12 0.10 0.60 0.02 0.44 1.88 0.01 9 Annual

Flat Tops Wilderness 0.12 0.10 0.60 0.02 0.48 2.12 0.00 8 Annual

Galiuro Wilderness 0.12 0.10 0.60 0.02 0.50 3.00 0.02 10 Annual

34 FLAG Phase I Report—Revised (2010)
Table 6. Annual Average Natural Conditions - Concentrations and Rayleigh Scattering By Class I Area

Class I Area

(NH4

)

2

SO4

μg/m3

NH4NO3

μg/m3

OM

μg/m3

EC

μg/m3

Soil

μg/m3

CM

μg/m3

Sea Salt

μg/m3

Rayleigh

Mm-1 Type

Gates of the Mountains 

Wilderness

0.12 0.10 0.60 0.02 0.35 1.55 0.01 9 Annual

Gearhart Mountain Wilderness 0.12 0.10 0.60 0.02 0.39 1.67 0.02 9 Annual

Gila Wilderness 0.12 0.10 0.60 0.02 0.50 2.54 0.01 9 Annual

Glacier NP 0.11 0.10 0.59 0.02 0.50 3.00 0.01 11 Annual

Glacier Peak Wilderness 0.11 0.10 0.60 0.02 0.19 1.32 0.02 11 Annual

Goat Rocks Wilderness 0.12 0.10 0.60 0.02 0.23 1.23 0.03 10 Annual

Grand Canyon NP 0.12 0.10 0.60 0.02 0.50 2.88 0.02 9 Annual

Grand Teton NP 0.12 0.10 0.60 0.02 0.41 1.92 0.01 9 Annual

Great Gulf Wilderness 0.23 0.10 1.70 0.02 0.25 2.65 0.03 11 Annual

Great Sand Dunes NP & Pres 0.12 0.10 0.60 0.02 0.50 2.99 0.01 9 Annual

Great Smoky Mountains NP 0.23 0.10 1.80 0.02 0.48 2.92 0.02 11 Annual

Guadalupe Mountains NP 0.12 0.10 0.60 0.02 0.50 3.00 0.02 9 Annual

Haleakala NP 0.12 0.10 0.57 0.02 0.23 2.93 0.25 10 Annual

Hawaii Volcanoes NP 0.12 0.10 0.45 0.02 0.16 1.42 0.29 10 Annual

Hells Canyon Wilderness 0.12 0.10 0.60 0.02 0.48 2.97 0.01 11 Annual

Hercules-Glades Wilderness 0.23 0.10 1.80 0.02 0.50 3.00 0.02 11 Annual

Hoover Wilderness 0.12 0.10 0.60 0.02 0.50 2.97 0.01 9 Annual

Isle Royale NP 0.23 0.10 1.55 0.02 0.24 2.89 0.03 12 Annual

James River Face Wilderness 0.23 0.10 1.80 0.02 0.48 3.00 0.02 11 Annual

Jarbidge Wilderness 0.12 0.10 0.60 0.02 0.50 3.00 0.02 10 Annual

John Muir Wilderness 0.12 0.10 0.58 0.02 0.46 2.88 0.03 9 Annual

Joshua Tree NP 0.12 0.10 0.60 0.02 0.50 3.00 0.03 10 Annual

Joyce Kilmer-Slickrock Wilderness 0.23 0.10 1.80 0.02 0.48 2.92 0.02 11 Annual

Kaiser Wilderness 0.12 0.10 0.58 0.02 0.46 2.88 0.03 9 Annual

Kalmiopsis Wilderness 0.12 0.10 0.60 0.02 0.20 2.24 0.23 12 Annual

Kings Canyon 0.11 0.10 0.60 0.02 0.50 3.00 0.04 11 Annual

La Garita Wilderness 0.12 0.10 0.60 0.02 0.49 2.59 0.01 9 Annual

Lassen Volcanic NP 0.12 0.10 0.60 0.02 0.44 1.82 0.01 10 Annual

Lava Beds NM 0.12 0.10 0.60 0.02 0.44 2.36 0.01 10 Annual

Linville Gorge Wilderness 0.23 0.10 1.80 0.02 0.45 2.60 0.02 11 Annual

Lostwood Wilderness 0.12 0.10 0.60 0.02 0.50 3.00 0.03 11 Annual

Lye Brook Wilderness 0.23 0.10 1.59 0.02 0.28 1.79 0.02 11 Annual

Mammoth Cave NP 0.23 0.10 1.80 0.02 0.50 2.73 0.02 11 Annual

Marble Mountain Wilderness 0.12 0.10 0.52 0.02 0.42 2.08 0.04 10 Annual

Maroon Bells-Snowmass 

Wilderness

0.12 0.10 0.60 0.02 0.48 2.12 0.00 8 Annual

Mazatzal Wilderness 0.12 0.10 0.60 0.02 0.50 3.00 0.02 10 Annual

Medicine Lake Wilderness 0.12 0.10 0.60 0.02 0.48 3.00 0.01 11 Annual

Mesa Verde NP 0.12 0.10 0.60 0.02 0.50 2.88 0.00 9 Annual

Mingo Wilderness 0.23 0.10 1.83 0.02 0.51 3.05 0.04 12 Annual

Mission Mountains Wilderness 0.12 0.10 0.60 0.02 0.44 2.34 0.01 10 Annual

Mokelumne Wilderness 0.12 0.10 0.60 0.02 0.43 1.92 0.01 9 Annual

Moosehorn Wilderness 0.23 0.10 1.79 0.02 0.23 2.56 0.11 12 Annual

Mount Adams Wilderness 0.12 0.10 0.60 0.02 0.23 1.23 0.03 10 Annual

 USFS–NPS–USFWS 35
Table 6. Annual Average Natural Conditions - Concentrations and Rayleigh Scattering By Class I Area

Class I Area

(NH4

)

2

SO4

μg/m3

NH4

NO3

μg/m3

OM

μg/m3

EC

μg/m3

Soil

μg/m3

CM

μg/m3

Sea Salt

μg/m3

Rayleigh

Mm-1 Type

Mount Baldy Wilderness 0.12 0.10 0.57 0.02 0.50 2.82 0.01 9 Annual

Mount Hood Wilderness 0.12 0.10 0.60 0.02 0.29 1.58 0.05 10 Annual

Mount Jefferson Wilderness 0.12 0.10 0.60 0.02 0.26 1.98 0.05 11 Annual

Mount Rainier NP 0.12 0.10 0.60 0.02 0.24 2.27 0.07 11 Annual

Mount Washington Wilderness 0.12 0.10 0.60 0.02 0.26 1.98 0.05 11 Annual

Mount Zirkel Wilderness 0.12 0.10 0.60 0.02 0.45 2.69 0.00 8 Annual

Mountain Lakes Wilderness 0.12 0.10 0.60 0.02 0.39 1.67 0.02 9 Annual

North Absaroka Wilderness 0.12 0.10 0.60 0.02 0.43 2.84 0.01 9 Annual

North Cascades NP 0.11 0.10 0.60 0.02 0.19 1.32 0.02 11 Annual

Okefenokee Wilderness 0.23 0.10 1.80 0.02 0.50 3.00 0.08 11 Annual

Olympic NP 0.12 0.10 0.60 0.02 0.15 1.88 0.14 11 Annual

Otter Creek Wilderness 0.23 0.10 1.80 0.02 0.43 2.19 0.02 10 Annual

Pasayten Wilderness 0.12 0.10 0.60 0.02 0.33 1.50 0.01 10 Annual

Pecos Wilderness 0.12 0.10 0.60 0.02 0.50 2.29 0.03 8 Annual

Petrified Forest NP 0.12 0.10 0.60 0.02 0.50 3.00 0.01 9 Annual

Pine Mountain Wilderness 0.12 0.10 0.60 0.02 0.50 3.00 0.02 10 Annual

Pinnacles NM 0.12 0.10 0.60 0.02 0.35 3.00 0.19 11 Annual

Point Reyes NS 0.12 0.10 0.60 0.02 0.24 3.00 2.11 12 Annual

Presidential Range-Dry River 

Wilderness

0.23 0.10 1.70 0.02 0.25 2.65 0.03 11 Annual

Rawah Wilderness 0.12 0.10 0.60 0.02 0.45 2.69 0.00 8 Annual

Red Rock Lakes Wilderness 0.12 0.10 0.60 0.02 0.41 1.92 0.01 9 Annual

Redwood NP 0.12 0.10 0.60 0.02 0.16 3.00 0.96 11 Annual

Rocky Mountain NP 0.12 0.10 0.60 0.02 0.50 2.90 0.00 9 Annual

Roosevelt Campobello 

International Park

0.23 0.10 1.79 0.02 0.23 2.56 0.11 12 Annual

Saguaro NP 0.12 0.10 0.60 0.02 0.50 3.00 0.06 10 Annual

Saint Marks Wilderness 0.23 0.10 1.80 0.02 0.50 3.00 0.10 11 Annual

Salt Creek Wilderness 0.12 0.10 0.60 0.02 0.50 3.00 0.04 10 Annual

San Gabriel Wilderness 0.12 0.10 0.60 0.02 0.50 3.00 0.04 9 Annual

San Gorgonio Wilderness 0.12 0.10 0.60 0.02 0.50 3.00 0.05 10 Annual

San Jacinto Wilderness 0.12 0.10 0.60 0.02 0.50 3.00 0.05 10 Annual

San Pedro Parks Wilderness 0.12 0.10 0.60 0.02 0.50 2.19 0.01 8 Annual

San Rafael Wilderness 0.11 0.10 0.60 0.02 0.50 3.00 0.11 10 Annual

Sawtooth Wilderness 0.12 0.08 0.60 0.02 0.41 1.64 0.01 10 Annual

Scapegoat Wilderness 0.12 0.10 0.60 0.02 0.44 2.34 0.01 10 Annual

Selway-Bitterroot Wilderness 0.12 0.10 0.60 0.02 0.39 1.79 0.02 10 Annual

Seney Wilderness 0.23 0.10 1.74 0.02 0.26 1.95 0.02 12 Annual

Sequoia NP 0.11 0.10 0.60 0.02 0.50 3.00 0.04 11 Annual

Shenandoah NP 0.23 0.10 1.80 0.02 0.41 2.88 0.02 10 Annual

Shining Rock Wilderness 0.23 0.10 1.76 0.02 0.50 1.76 0.02 10 Annual

Sierra Ancha Wilderness 0.12 0.10 0.60 0.02 0.50 3.00 0.02 10 Annual

Simeonof Wilderness 0.12 0.10 0.46 0.02 0.13 3.00 1.26 12 Annual

Sipsey Wilderness 0.23 0.10 1.80 0.02 0.50 3.00 0.04 11 Annual

South Warner Wilderness 0.12 0.10 0.60 0.02 0.44 2.36 0.01 10 Annual

36 FLAG Phase I Report—Revised (2010)
Table 6. Annual Average Natural Conditions - Concentrations and Rayleigh Scattering By Class I Area

Class I Area

(NH4

)

2

SO4

μg/m3

NH4

NO3

μg/m3

OM

μg/m3

EC

μg/m3

Soil

μg/m3

CM

μg/m3

Sea Salt

μg/m3

Rayleigh

Mm-1 Type

Strawberry Mountain Wilderness 0.12 0.10 0.60 0.02 0.50 2.99 0.04 10 Annual

Superstition Wilderness 0.11 0.10 0.59 0.02 0.50 3.00 0.02 10 Annual

Swanquarter Wilderness 0.23 0.10 1.63 0.02 0.41 3.00 0.14 12 Annual

Sycamore Canyon Wilderness 0.12 0.10 0.60 0.02 0.50 3.00 0.03 9 Annual

Teton Wilderness 0.12 0.10 0.60 0.02 0.41 1.92 0.01 9 Annual

Theodore Roosevelt NP 0.12 0.10 0.60 0.02 0.50 3.00 0.01 11 Annual

Thousand Lakes Wilderness 0.12 0.10 0.60 0.02 0.44 1.82 0.01 10 Annual

Three Sisters Wilderness 0.12 0.10 0.60 0.02 0.26 1.98 0.05 11 Annual

Tuxedni Wilderness 0.12 0.09 0.60 0.02 0.10 2.06 0.38 12 Annual

UL Bend Wilderness 0.12 0.10 0.60 0.02 0.45 3.00 0.00 11 Annual

Upper Buffalo Wilderness 0.23 0.10 1.80 0.02 0.50 3.00 0.03 11 Annual

Ventana Wilderness 0.12 0.10 0.60 0.02 0.35 3.00 0.19 11 Annual

Virgin Islands NP 0.23 0.10 0.35 0.02 0.50 3.00 0.84 11 Annual

Voyageurs NP 0.23 0.10 1.75 0.02 0.26 2.73 0.04 12 Annual

Washakie Wilderness 0.12 0.10 0.60 0.02 0.43 2.84 0.01 9 Annual

Weminuche Wilderness 0.12 0.10 0.60 0.02 0.49 2.59 0.01 9 Annual

West Elk Wilderness 0.12 0.10 0.60 0.02 0.48 2.12 0.00 8 Annual

Wheeler Peak Wilderness 0.12 0.10 0.60 0.02 0.50 2.29 0.03 8 Annual

White Mountain Wilderness 0.12 0.10 0.60 0.02 0.50 3.00 0.03 9 Annual

Wichita Mountains Wilderness 0.12 0.10 0.60 0.02 0.50 3.00 0.03 11 Annual

Wind Cave NP 0.12 0.10 0.60 0.02 0.49 2.98 0.01 10 Annual

Wolf Island Wilderness 0.23 0.10 1.80 0.02 0.50 3.00 0.08 11 Annual

Yellowstone NP 0.12 0.10 0.60 0.02 0.41 1.92 0.01 9 Annual

Yolla Bolly-Middle Eel Wilderness 0.12 0.10 0.52 0.02 0.42 2.08 0.04 10 Annual

Yosemite NP 0.12 0.10 0.60 0.02 0.44 3.00 0.02 10 Annual

Zion NP 0.12 0.10 0.60 0.02 0.50 3.00 0.01 10 Annual

 USFS–NPS–USFWS 37
Table 7. Monthly fL

(RH) – Large (NH4)

2

SO4 and NH4NO3 Relative Humidity Adjustment Factor

Class I Area Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Acadia NP 2.74 2.46 2.45 2.66 2.67 2.73 2.99 3.03 3.16 2.91 2.89 2.96

Agua Tibia Wilderness 2.10 2.08 2.11 1.98 1.98 1.93 1.93 2.01 2.02 1.99 1.87 1.95

Alpine Lakes Wilderness 3.86 3.58 3.04 2.92 2.99 2.58 2.62 2.67 2.97 3.60 4.00 3.99

Anaconda Pintler Wilderness 2.75 2.46 2.24 2.08 2.06 2.01 1.76 1.72 1.88 2.22 2.66 2.74

Ansel Adams Wilderness 2.56 2.34 2.20 1.88 1.79 1.59 1.52 1.52 1.59 1.70 2.01 2.34

Arches NP 2.28 2.12 1.73 1.57 1.50 1.28 1.34 1.47 1.51 1.56 1.90 2.13

Badlands NP 2.31 2.31 2.31 2.21 2.34 2.25 2.08 2.05 2.02 2.05 2.38 2.33

Bandelier NM 2.10 1.90 1.72 1.51 1.53 1.38 1.63 1.87 1.80 1.59 1.87 2.04

Bering Sea Wilderness 3.02 3.17 3.20 3.19 3.23 3.34 3.78 4.16 3.64 3.19 3.12 3.13

Big Bend NP 1.72 1.61 1.44 1.38 1.47 1.48 1.58 1.74 1.83 1.63 1.63 1.70

Black Canyon of the Gunnison NP 2.15 2.05 1.83 1.75 1.74 1.51 1.59 1.78 1.80 1.68 1.96 2.06

Bob Marshall Wilderness 2.82 2.54 2.35 2.22 2.21 2.19 1.98 1.92 2.15 2.43 2.78 2.81

Bosque del Apache Wilderness 2.03 1.82 1.55 1.37 1.36 1.27 1.61 1.79 1.73 1.54 1.73 2.00

Boundary Waters Canoe Area Wilderness 2.50 2.25 2.28 2.09 2.20 2.43 2.57 2.71 2.78 2.38 2.64 2.64

Breton Wilderness 2.91 2.76 2.74 2.72 2.83 2.94 3.10 3.07 2.97 2.82 2.83 2.90

Bridger Wilderness 2.22 2.10 2.04 1.95 1.95 1.67 1.46 1.44 1.68 1.83 2.19 2.16

Brigantine Wilderness 2.49 2.32 2.38 2.28 2.50 2.56 2.69 2.81 2.82 2.71 2.45 2.50

Bryce Canyon NP 2.31 2.16 1.82 1.56 1.47 1.26 1.30 1.46 1.46 1.55 1.87 2.15

Cabinet Mountains Wilderness 3.07 2.73 2.45 2.26 2.24 2.21 1.98 1.92 2.19 2.53 3.03 3.11

Caney Creek Wilderness 2.77 2.53 2.37 2.43 2.68 2.71 2.59 2.60 2.71 2.69 2.67 2.79

Canyonlands NP 2.32 2.16 1.78 1.58 1.51 1.28 1.36 1.53 1.55 1.58 1.93 2.17

Cape Romain Wilderness 2.66 2.47 2.42 2.32 2.56 2.80 2.82 3.04 3.03 2.86 2.65 2.70

Capitol Reef NP 2.36 2.22 1.84 1.63 1.54 1.31 1.36 1.52 1.55 1.61 1.95 2.22

Caribou Wilderness 2.96 2.58 2.35 2.10 2.01 1.85 1.79 1.82 1.88 2.03 2.50 2.82

Carlsbad Caverns NP 2.07 1.81 1.50 1.42 1.51 1.48 1.72 1.90 2.03 1.64 1.76 2.00

Chassahowitzka Wilderness 3.03 2.82 2.74 2.65 2.63 3.00 3.02 3.15 3.14 3.03 2.97 3.09

Chiricahua NM 1.87 1.79 1.52 1.24 1.22 1.13 1.64 1.87 1.66 1.45 1.55 1.89

Chiricahua Wilderness 1.84 1.76 1.49 1.22 1.20 1.12 1.64 1.86 1.64 1.43 1.53 1.87

Cohutta Wilderness 2.84 2.61 2.49 2.36 2.72 2.97 3.00 3.07 3.08 2.89 2.72 2.85

Crater Lake NP 3.71 3.25 3.07 2.91 2.70 2.50 2.31 2.33 2.49 2.99 3.67 3.74

Craters of the Moon NM 2.58 2.34 2.03 1.84 1.83 1.65 1.40 1.39 1.52 1.80 2.35 2.54

Cucamonga Wilderness 2.21 2.14 2.13 1.96 1.95 1.90 1.91 1.96 1.98 1.96 1.90 2.02

Denali NP & Pres 2.48 2.44 2.15 1.96 1.98 2.13 2.47 2.90 2.95 2.84 2.69 2.68

Desolation Wilderness 2.73 2.42 2.18 1.84 1.74 1.56 1.47 1.49 1.58 1.73 2.12 2.54

Diamond Peak Wilderness 3.82 3.38 3.18 3.04 2.79 2.60 2.33 2.35 2.58 3.18 3.80 3.86

Dolly Sods Wilderness 2.53 2.39 2.38 2.20 2.63 2.65 2.74 2.90 2.94 2.65 2.45 2.61

Dome Land Wilderness 2.26 2.07 2.00 1.79 1.73 1.63 1.61 1.64 1.68 1.71 1.81 2.01

Eagle Cap Wilderness 3.44 3.02 2.54 2.31 2.28 2.01 1.78 1.75 1.97 2.61 3.34 3.56

Eagles Nest Wilderness 2.02 2.01 1.87 1.87 1.92 1.69 1.68 1.83 1.86 1.73 1.96 1.97

Emigrant Wilderness 2.67 2.42 2.26 1.92 1.81 1.59 1.49 1.50 1.58 1.72 2.08 2.45

Everglades NP 2.43 2.31 2.26 2.16 2.15 2.38 2.32 2.49 2.55 2.42 2.34 2.39

Fitzpatrick Wilderness 2.22 2.10 2.04 1.95 1.94 1.68 1.47 1.44 1.68 1.83 2.18 2.16

Flat Tops Wilderness 2.09 2.04 1.87 1.84 1.86 1.62 1.59 1.70 1.79 1.72 1.97 2.03

Galiuro Wilderness 1.80 1.67 1.47 1.21 1.18 1.10 1.43 1.66 1.53 1.42 1.57 1.87

Gates of the Mountains Wilderness 2.46 2.25 2.15 2.05 2.02 2.00 1.81 1.77 1.91 2.15 2.37 2.41

38 FLAG Phase I Report—Revised (2010)
Table 7. Monthly fL

(RH) – Large (NH4)

2

SO4 and NH4NO3 Relative Humidity Adjustment Factor

Class I Area Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Gearhart Mountain Wilderness 3.30 2.89 2.62 2.45 2.29 2.13 1.88 1.90 2.03 2.47 3.09 3.27

Gila Wilderness 1.93 1.78 1.52 1.31 1.28 1.23 1.72 1.76 1.68 1.50 1.67 1.96

Glacier NP 3.21 2.84 2.69 2.55 2.58 2.56 2.24 2.22 2.57 2.81 3.08 3.13

Glacier Peak Wilderness 3.69 3.39 2.97 2.85 2.79 2.54 2.49 2.59 2.91 3.45 3.83 3.84

Goat Rocks Wilderness 3.83 3.44 3.10 2.97 2.82 2.60 2.48 2.55 2.88 3.49 3.91 3.98

Grand Canyon NP 2.13 2.01 1.74 1.46 1.36 1.19 1.29 1.49 1.47 1.50 1.75 1.98

Grand Teton NP 2.27 2.14 2.01 1.91 1.90 1.68 1.48 1.44 1.64 1.84 2.16 2.24

Great Gulf Wilderness 2.51 2.32 2.36 2.41 2.45 2.55 2.72 2.87 2.98 2.80 2.67 2.60

Great Sand Dunes NP & Pres 2.11 2.04 1.85 1.77 1.80 1.62 1.70 1.97 1.92 1.72 2.04 2.09

Great Smoky Mountains NP 2.85 2.57 2.51 2.35 2.72 2.98 2.98 3.08 3.10 2.87 2.71 2.85

Guadalupe Mountains NP 2.14 1.82 1.49 1.38 1.48 1.47 1.78 1.98 2.10 1.60 1.78 2.08

Haleakala NP 2.34 2.27 2.25 2.20 2.13 2.09 2.16 2.14 2.10 2.19 2.33 2.30

Hawaii Volcanoes NP 2.56 2.45 2.47 2.47 2.47 2.45 2.53 2.59 2.55 2.57 2.78 2.55

Hells Canyon Wilderness 3.05 2.65 2.22 1.97 1.91 1.81 1.55 1.52 1.68 2.15 2.90 3.15

Hercules-Glades Wilderness 2.70 2.48 2.30 2.30 2.57 2.59 2.56 2.60 2.69 2.54 2.57 2.72

Hoover Wilderness 2.63 2.38 2.21 1.88 1.77 1.56 1.46 1.47 1.55 1.69 2.05 2.42

Isle Royale NP 2.53 2.21 2.26 2.07 1.99 2.32 2.65 2.69 2.82 2.28 2.76 2.74

James River Face Wilderness 2.44 2.30 2.29 2.12 2.47 2.58 2.65 2.78 2.82 2.57 2.36 2.51

Jarbidge Wilderness 2.51 2.28 1.90 1.92 1.97 1.82 1.51 1.37 1.34 1.56 2.14 2.42

John Muir Wilderness 2.51 2.29 2.20 1.95 1.86 1.65 1.60 1.61 1.69 1.78 2.03 2.28

Joshua Tree NP 2.06 1.99 1.97 1.82 1.81 1.74 1.68 1.82 1.83 1.81 1.75 1.87

Joyce Kilmer-Slickrock Wilderness 2.86 2.58 2.51 2.36 2.71 2.97 2.98 3.06 3.08 2.87 2.72 2.85

Kaiser Wilderness 2.58 2.35 2.22 1.90 1.80 1.62 1.56 1.57 1.64 1.75 2.03 2.36

Kalmiopsis Wilderness 3.57 3.17 3.03 2.88 2.75 2.60 2.52 2.53 2.60 2.92 3.51 3.55

Kings Canyon 2.47 2.26 2.18 1.94 1.85 1.65 1.59 1.60 1.68 1.77 2.01 2.24

La Garita Wilderness 2.14 2.03 1.81 1.70 1.69 1.49 1.63 1.87 1.83 1.67 1.98 2.08

Lassen Volcanic NP 2.99 2.61 2.38 2.13 2.03 1.86 1.81 1.84 1.90 2.06 2.54 2.86

Lava Beds NM 3.31 2.88 2.64 2.44 2.29 2.13 1.98 1.99 2.10 2.43 3.03 3.26

Linville Gorge Wilderness 2.71 2.54 2.48 2.31 2.70 2.96 3.00 3.20 3.19 2.84 2.62 2.74

Lostwood Wilderness 2.51 2.45 2.54 2.06 2.03 2.21 2.23 2.05 2.02 2.13 2.69 2.67

Lye Brook Wilderness 2.46 2.30 2.34 2.31 2.42 2.47 2.60 2.76 2.84 2.70 2.54 2.51

Mammoth Cave NP 2.79 2.57 2.47 2.56 3.29 3.76 3.67 2.92 2.95 2.71 2.61 2.82

Marble Mountain Wilderness 3.48 3.08 2.95 2.78 2.67 2.53 2.50 2.52 2.55 2.78 3.32 3.42

Maroon Bells-Snowmass Wilderness 2.02 1.99 1.84 1.84 1.83 1.59 1.69 1.90 1.89 1.71 1.94 1.96

Mazatzal Wilderness 1.91 1.80 1.59 1.32 1.25 1.13 1.38 1.61 1.51 1.45 1.63 1.89

Medicine Lake Wilderness 2.53 2.46 2.46 2.02 2.00 2.13 2.12 1.95 1.98 2.10 2.63 2.65

Mesa Verde NP 2.45 2.25 1.98 1.57 1.61 1.31 1.62 1.87 1.75 1.66 2.01 2.30

Mingo Wilderness 2.73 2.52 2.34 2.28 2.53 2.60 2.64 2.67 2.71 2.56 2.56 2.73

Mission Mountains Wilderness 2.93 2.62 2.37 2.20 2.21 2.19 1.98 1.92 2.15 2.46 2.91 2.96

Mokelumne Wilderness 2.72 2.42 2.20 1.86 1.75 1.57 1.48 1.50 1.58 1.73 2.11 2.52

Moosehorn Wilderness 2.65 2.39 2.38 2.52 2.49 2.57 2.83 2.95 3.07 2.83 2.77 2.78

Mount Adams Wilderness 3.78 3.40 3.10 2.98 2.78 2.60 2.43 2.52 2.84 3.45 3.87 3.92

Mount Baldy Wilderness 2.00 1.86 1.62 1.34 1.29 1.18 1.50 1.73 1.60 1.51 1.73 2.01

Mount Hood Wilderness 3.71 3.33 3.08 2.96 2.74 2.55 2.34 2.42 2.72 3.35 3.81 3.84

Mount Jefferson Wilderness 3.89 3.48 3.27 3.16 2.89 2.66 2.35 2.35 2.63 3.34 3.92 3.95

 USFS–NPS–USFWS 39
Table 7. Monthly fL

(RH) – Large (NH4)

2

SO4 and NH4NO3 Relative Humidity Adjustment Factor

Class I Area Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Mount Rainier NP 3.93 3.54 3.23 3.12 2.96 2.75 2.61 2.69 3.04 3.66 4.04 4.07

Mount Washington Wilderness 4.09 3.63 3.49 3.41 3.06 2.80 2.37 2.34 2.62 3.41 4.07 4.10

Mount Zirkel Wilderness 2.00 1.99 1.89 1.92 1.98 1.72 1.63 1.70 1.81 1.75 1.97 1.95

Mountain Lakes Wilderness 3.51 3.03 2.80 2.62 2.44 2.25 2.08 2.09 2.23 2.65 3.37 3.52

North Absaroka Wilderness 2.16 2.05 2.01 1.95 1.94 1.77 1.58 1.50 1.67 1.87 2.12 2.14

North Cascades NP 3.60 3.32 2.99 2.88 2.74 2.59 2.49 2.63 2.97 3.43 3.77 3.76

Okefenokee Wilderness 2.94 2.73 2.73 2.65 2.74 3.11 3.00 3.17 3.16 3.05 2.96 3.03

Olympic NP 3.80 3.50 3.30 3.21 2.76 2.89 2.61 2.94 3.23 3.73 3.99 3.95

Otter Creek Wilderness 2.55 2.41 2.40 2.23 2.64 2.69 2.80 2.96 3.00 2.69 2.48 2.63

Pasayten Wilderness 3.65 3.34 2.97 2.84 2.72 2.53 2.45 2.56 2.88 3.39 3.78 3.81

Pecos Wilderness 2.09 1.93 1.73 1.57 1.58 1.44 1.65 1.90 1.84 1.63 1.90 2.05

Petrified Forest NP 2.11 1.95 1.64 1.40 1.32 1.18 1.46 1.72 1.58 1.53 1.81 2.09

Pine Mountain Wilderness 1.96 1.86 1.64 1.35 1.28 1.15 1.38 1.62 1.53 1.48 1.66 1.93

Pinnacles NM 2.84 2.86 2.87 2.27 2.15 1.99 1.91 1.97 1.98 2.10 2.16 2.46

Point Reyes NS 2.96 2.73 2.61 2.28 2.20 2.04 2.12 2.16 2.18 2.23 2.47 2.75

Presidential Range-Dry River Wilderness 2.52 2.32 2.37 2.42 2.49 2.61 2.78 2.93 3.03 2.83 2.68 2.59

Rawah Wilderness 1.91 1.96 1.89 1.96 2.04 1.79 1.71 1.78 1.86 1.75 1.94 1.90

Red Rock Lakes Wilderness 2.39 2.20 2.06 1.95 1.92 1.80 1.60 1.54 1.69 1.93 2.30 2.37

Redwood NP 3.31 3.10 3.16 3.04 3.11 3.08 3.26 3.28 3.11 2.99 3.20 3.12

Rocky Mountain NP 1.77 1.85 1.84 1.95 2.04 1.80 1.73 1.77 1.84 1.70 1.84 1.76

Roosevelt Campobello International Park 2.66 2.39 2.38 2.53 2.49 2.57 2.82 2.93 3.05 2.83 2.78 2.79

Saguaro NP 1.69 1.56 1.40 1.13 1.12 1.05 1.37 1.62 1.47 1.38 1.50 1.83

Saint Marks Wilderness 2.98 2.78 2.73 2.69 2.74 3.04 3.17 3.21 3.10 2.96 2.94 3.06

Salt Creek Wilderness 2.01 1.79 1.51 1.45 1.55 1.48 1.64 1.80 1.91 1.64 1.72 1.91

San Gabriel Wilderness 2.25 2.17 2.14 1.96 1.95 1.90 1.91 1.95 1.98 1.97 1.91 2.04

San Gorgonio Wilderness 2.21 2.23 2.13 1.90 1.90 1.69 1.62 1.71 1.72 1.70 1.73 1.92

San Jacinto Wilderness 2.12 2.09 2.06 1.90 1.90 1.81 1.71 1.88 1.89 1.87 1.80 1.92

San Pedro Parks Wilderness 2.14 1.97 1.73 1.55 1.53 1.38 1.59 1.83 1.77 1.61 1.91 2.08

San Rafael Wilderness 2.50 2.37 2.34 2.12 2.10 2.05 2.10 2.15 2.20 2.15 2.07 2.25

Sawtooth Wilderness 2.79 2.44 2.05 1.83 1.80 1.66 1.37 1.35 1.43 1.77 2.47 2.75

Scapegoat Wilderness 2.74 2.47 2.30 2.18 2.16 2.14 1.93 1.87 2.07 2.35 2.70 2.72

Selway-Bitterroot Wilderness 2.90 2.57 2.26 2.05 2.03 1.95 1.67 1.63 1.81 2.19 2.76 2.91

Seney Wilderness 2.75 2.42 2.49 2.35 2.30 2.55 2.75 3.01 3.03 2.78 2.88 2.85

Sequoia NP 2.40 2.22 2.21 2.05 1.95 1.67 1.60 1.59 1.69 1.78 2.04 2.17

Shenandoah NP 2.44 2.28 2.29 2.12 2.45 2.56 2.65 2.79 2.81 2.53 2.34 2.55

Shining Rock Wilderness 2.78 2.56 2.48 2.33 2.72 2.98 3.02 3.17 3.18 2.91 2.68 2.79

Sierra Ancha Wilderness 1.92 1.81 1.59 1.32 1.25 1.13 1.42 1.65 1.54 1.47 1.66 1.93

Simeonof Wilderness 3.39 3.40 3.15 3.26 3.40 3.69 4.00 4.14 3.61 3.09 3.21 3.44

Sipsey Wilderness 2.79 2.58 2.42 2.36 2.64 2.86 2.94 2.92 2.93 2.78 2.64 2.80

South Warner Wilderness 3.06 2.67 2.39 2.16 2.05 1.90 1.68 1.69 1.79 2.11 2.67 2.97

Strawberry Mountain Wilderness 3.55 3.10 2.69 2.47 2.37 2.10 1.82 1.81 2.05 2.73 3.45 3.65

Superstition Wilderness 1.84 1.72 1.53 1.26 1.20 1.11 1.36 1.56 1.46 1.40 1.58 1.85

Swanquarter Wilderness 2.48 2.35 2.31 2.18 2.38 2.55 2.67 2.72 2.64 2.55 2.40 2.49

Sycamore Canyon Wilderness 2.01 1.93 1.70 1.40 1.33 1.17 1.38 1.67 1.58 1.52 1.70 1.97

Teton Wilderness 2.22 2.09 2.01 1.92 1.91 1.72 1.52 1.47 1.65 1.86 2.15 2.19

40 FLAG Phase I Report—Revised (2010)
Table 7. Monthly fL

(RH) – Large (NH4)

2

SO4 and NH4NO3 Relative Humidity Adjustment Factor

Class I Area Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Theodore Roosevelt NP 2.47 2.42 2.45 2.12 2.14 2.21 2.14 1.99 1.99 2.10 2.58 2.57

Thousand Lakes Wilderness 3.04 2.63 2.42 2.17 2.06 1.88 1.82 1.85 1.91 2.08 2.61 2.91

Three Sisters Wilderness 4.03 3.59 3.43 3.34 3.02 2.78 2.40 2.38 2.65 3.39 4.02 4.04

Tuxedni Wilderness 2.97 2.83 2.47 2.40 2.38 2.50 2.96 3.19 3.18 2.91 2.91 3.03

UL Bend Wilderness 2.33 2.20 2.19 2.03 1.96 1.95 1.80 1.66 1.76 2.00 2.31 2.32

Upper Buffalo Wilderness 2.71 2.48 2.31 2.33 2.61 2.64 2.57 2.59 2.71 2.58 2.59 2.72

Ventana Wilderness 2.80 2.67 2.63 2.20 2.10 1.96 1.97 2.01 2.05 2.11 2.21 2.51

Virgin Islands NP 2.04 2.00 1.94 2.03 2.06 2.04 2.05 2.14 2.14 2.18 2.20 2.12

Voyageurs NP 2.46 2.22 2.22 2.07 2.09 2.46 2.46 2.59 2.70 2.35 2.58 2.55

Washakie Wilderness 2.16 2.05 2.01 1.94 1.93 1.74 1.54 1.48 1.66 1.86 2.12 2.14

Weminuche Wilderness 2.19 2.05 1.81 1.65 1.64 1.44 1.60 1.85 1.79 1.65 1.97 2.11

West Elk Wilderness 2.11 2.04 1.84 1.77 1.77 1.54 1.63 1.83 1.83 1.69 1.96 2.04

Wheeler Peak Wilderness 2.14 2.00 1.78 1.65 1.67 1.52 1.66 1.94 1.89 1.68 1.98 2.10

White Mountain Wilderness 2.00 1.79 1.51 1.40 1.44 1.37 1.64 1.82 1.85 1.59 1.72 1.95

Wichita Mountains Wilderness 2.39 2.25 2.10 2.11 2.39 2.24 2.02 2.13 2.35 2.22 2.28 2.41

Wind Cave NP 2.23 2.22 2.22 2.18 2.32 2.18 2.00 1.97 1.95 2.00 2.30 2.24

Wolf Island Wilderness 2.86 2.67 2.61 2.54 2.63 2.96 2.94 3.13 3.12 2.99 2.88 2.95

Yellowstone NP 2.24 2.11 2.03 1.95 1.94 1.78 1.59 1.53 1.69 1.91 2.19 2.22

Yolla Bolly-Middle Eel Wilderness 3.12 2.76 2.60 2.37 2.29 2.13 2.14 2.18 2.21 2.33 2.75 2.98

Yosemite NP 2.61 2.45 2.34 1.99 1.88 1.61 1.48 1.46 1.54 1.69 2.06 2.38

Zion NP 2.32 2.18 1.83 1.56 1.45 1.26 1.24 1.38 1.40 1.51 1.84 2.14

 USFS–NPS–USFWS 41
Table 8. Monthly fS

(RH) – Small (NH4)

2

SO4 and NH4NO3 Relative Humidity Adjustment Factor

Class I Area Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Acadia NP 3.80 3.28 3.30 3.71 3.72 3.81 4.28 4.34 4.58 4.10 4.06 4.19

Agua Tibia Wilderness 2.68 2.61 2.63 2.42 2.40 2.33 2.33 2.45 2.49 2.46 2.29 2.42

Alpine Lakes Wilderness 5.87 5.35 4.34 4.13 4.30 3.50 3.61 3.69 4.27 5.43 6.15 6.08

Anaconda Pintler Wilderness 3.72 3.23 2.87 2.62 2.60 2.52 2.14 2.07 2.33 2.87 3.60 3.71

Ansel Adams Wilderness 3.51 3.11 2.87 2.34 2.18 1.86 1.75 1.76 1.88 2.05 2.55 3.12

Arches NP 2.96 2.70 2.09 1.84 1.75 1.40 1.49 1.69 1.76 1.83 2.33 2.69

Badlands NP 2.94 2.96 3.01 2.87 3.10 2.91 2.64 2.59 2.56 2.58 3.11 2.98

Bandelier NM 2.66 2.36 2.10 1.77 1.80 1.55 1.93 2.30 2.21 1.87 2.32 2.60

Bering Sea Wilderness 4.16 4.48 4.52 4.50 4.64 4.86 5.71 6.43 5.40 4.52 4.36 4.37

Big Bend NP 2.11 1.92 1.65 1.56 1.67 1.67 1.83 2.07 2.22 1.92 1.92 2.04

Black Canyon of the Gunnison NP 2.71 2.56 2.23 2.12 2.12 1.75 1.87 2.17 2.21 2.00 2.42 2.57

Bob Marshall Wilderness 3.84 3.35 3.06 2.86 2.86 2.84 2.49 2.39 2.77 3.22 3.81 3.83

Bosque del Apache Wilderness 2.56 2.23 1.83 1.54 1.54 1.39 1.90 2.16 2.09 1.79 2.09 2.53

Boundary Waters Canoe Area Wilderness 3.23 2.81 2.93 2.63 2.89 3.22 3.44 3.71 3.83 3.08 3.49 3.49

Breton Wilderness 4.08 3.82 3.79 3.74 3.94 4.12 4.41 4.37 4.18 3.92 3.93 4.06

Bridger Wilderness 2.78 2.60 2.55 2.43 2.45 1.99 1.65 1.63 2.03 2.25 2.78 2.68

Brigantine Wilderness 3.34 3.07 3.17 2.99 3.37 3.45 3.68 3.90 3.91 3.73 3.27 3.36

Bryce Canyon NP 3.02 2.77 2.23 1.84 1.70 1.38 1.42 1.67 1.67 1.81 2.30 2.75

Cabinet Mountains Wilderness 4.30 3.69 3.23 2.91 2.91 2.87 2.50 2.40 2.84 3.40 4.26 4.37

Caney Creek Wilderness 3.85 3.44 3.14 3.24 3.66 3.71 3.49 3.51 3.73 3.72 3.68 3.88

Canyonlands NP 3.03 2.77 2.17 1.86 1.76 1.40 1.52 1.78 1.81 1.87 2.38 2.77

Cape Romain Wilderness 3.66 3.33 3.24 3.07 3.46 3.88 3.91 4.31 4.30 4.00 3.62 3.73

Capitol Reef NP 3.10 2.86 2.27 1.94 1.81 1.45 1.52 1.77 1.81 1.91 2.43 2.86

Caribou Wilderness 4.17 3.50 3.11 2.68 2.54 2.28 2.21 2.26 2.36 2.60 3.39 3.93

Carlsbad Caverns NP 2.70 2.25 1.75 1.63 1.77 1.70 2.06 2.34 2.59 1.95 2.16 2.57

Chassahowitzka Wilderness 4.31 3.92 3.79 3.62 3.57 4.22 4.26 4.50 4.49 4.29 4.18 4.43

Chiricahua NM 2.29 2.19 1.75 1.34 1.31 1.18 1.94 2.28 1.95 1.64 1.79 2.34

Chiricahua Wilderness 2.25 2.14 1.71 1.30 1.28 1.17 1.95 2.26 1.93 1.61 1.75 2.31

Cohutta Wilderness 3.99 3.59 3.38 3.16 3.76 4.19 4.24 4.37 4.41 4.09 3.77 4.00

Crater Lake NP 5.58 4.73 4.37 4.09 3.70 3.37 3.05 3.08 3.38 4.26 5.52 5.64

Craters of the Moon NM 3.40 3.00 2.52 2.22 2.23 1.94 1.56 1.55 1.76 2.17 3.04 3.32

Cucamonga Wilderness 2.87 2.73 2.68 2.40 2.37 2.29 2.31 2.38 2.43 2.42 2.34 2.54

Denali NP & Pres 3.21 3.19 2.71 2.39 2.46 2.69 3.27 4.05 4.17 3.90 3.59 3.58

Desolation Wilderness 3.77 3.22 2.82 2.26 2.09 1.80 1.67 1.71 1.84 2.08 2.72 3.44

Diamond Peak Wilderness 5.79 4.97 4.61 4.35 3.90 3.55 3.08 3.12 3.55 4.63 5.75 5.88

Dolly Sods Wilderness 3.39 3.16 3.17 2.87 3.63 3.62 3.78 4.06 4.15 3.63 3.27 3.53

Dome Land Wilderness 2.97 2.64 2.51 2.17 2.08 1.91 1.89 1.93 2.01 2.06 2.23 2.56

Eagle Cap Wilderness 5.05 4.28 3.45 3.05 3.02 2.56 2.20 2.15 2.53 3.62 4.89 5.26

Eagles Nest Wilderness 2.48 2.48 2.29 2.32 2.42 2.03 2.02 2.24 2.31 2.09 2.42 2.42

Emigrant Wilderness 3.69 3.25 2.98 2.39 2.21 1.86 1.71 1.73 1.85 2.07 2.68 3.32

Everglades NP 3.14 2.93 2.83 2.67 2.63 3.03 2.91 3.22 3.33 3.12 2.95 3.08

Fitzpatrick Wilderness 2.78 2.60 2.54 2.43 2.44 1.99 1.66 1.63 2.02 2.25 2.77 2.68

Flat Tops Wilderness 2.61 2.53 2.28 2.26 2.31 1.91 1.86 2.04 2.19 2.06 2.42 2.51

Galiuro Wilderness 2.17 1.99 1.68 1.30 1.26 1.14 1.62 1.96 1.75 1.60 1.82 2.31

Gates of the Mountains Wilderness 3.20 2.85 2.71 2.57 2.53 2.50 2.21 2.14 2.37 2.74 3.09 3.12

42 FLAG Phase I Report—Revised (2010)
Table 8. Monthly fS

(RH) – Small (NH4)

2

SO4 and NH4NO3 Relative Humidity Adjustment Factor

Class I Area Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Gearhart Mountain Wilderness 4.80 4.05 3.60 3.30 3.04 2.76 2.37 2.39 2.62 3.36 4.45 4.76

Gila Wilderness 2.40 2.16 1.77 1.45 1.41 1.33 2.11 2.12 2.00 1.73 1.99 2.45

Glacier NP 4.53 3.87 3.63 3.39 3.51 3.48 2.91 2.87 3.47 3.86 4.29 4.37

Glacier Peak Wilderness 5.53 4.98 4.21 3.99 3.90 3.43 3.35 3.54 4.14 5.12 5.80 5.80

Goat Rocks Wilderness 5.81 5.08 4.46 4.23 3.97 3.57 3.35 3.48 4.11 5.22 5.98 6.09

Grand Canyon NP 2.73 2.53 2.12 1.69 1.52 1.27 1.42 1.72 1.69 1.74 2.11 2.49

Grand Teton NP 2.88 2.66 2.48 2.35 2.34 2.00 1.68 1.62 1.94 2.25 2.73 2.82

Great Gulf Wilderness 3.34 3.02 3.12 3.23 3.31 3.46 3.76 4.03 4.22 3.90 3.64 3.50

Great Sand Dunes NP & Pres 2.66 2.55 2.27 2.16 2.22 1.92 2.04 2.47 2.41 2.07 2.57 2.63

Great Smoky Mountains NP 4.01 3.52 3.43 3.14 3.76 4.20 4.21 4.39 4.45 4.05 3.76 3.99

Guadalupe Mountains NP 2.85 2.28 1.74 1.57 1.73 1.69 2.16 2.48 2.74 1.90 2.20 2.71

Haleakala NP 2.98 2.85 2.81 2.72 2.60 2.53 2.65 2.63 2.56 2.69 2.95 2.89

Hawaii Volcanoes NP 3.35 3.10 3.14 3.13 3.14 3.11 3.24 3.42 3.34 3.38 3.76 3.34

Hells Canyon Wilderness 4.28 3.56 2.83 2.42 2.34 2.19 1.80 1.75 2.01 2.75 4.03 4.45

Hercules-Glades Wilderness 3.70 3.33 3.01 3.01 3.47 3.48 3.41 3.51 3.67 3.43 3.46 3.73

Hoover Wilderness 3.63 3.18 2.89 2.33 2.16 1.82 1.66 1.68 1.81 2.02 2.62 3.25

Isle Royale NP 3.26 2.74 2.87 2.58 2.46 3.00 3.59 3.68 3.92 2.88 3.72 3.67

James River Face Wilderness 3.25 3.03 3.02 2.72 3.31 3.48 3.59 3.83 3.91 3.48 3.11 3.38

Jarbidge Wilderness 3.29 2.92 2.31 2.34 2.44 2.22 1.73 1.51 1.48 1.80 2.70 3.13

John Muir Wilderness 3.42 3.02 2.86 2.44 2.29 1.94 1.86 1.87 2.01 2.16 2.60 3.03

Joshua Tree NP 2.62 2.49 2.44 2.19 2.16 2.05 1.97 2.18 2.21 2.19 2.11 2.31

Joyce Kilmer-Slickrock Wilderness 4.02 3.54 3.42 3.15 3.74 4.19 4.21 4.35 4.41 4.04 3.77 4.00

Kaiser Wilderness 3.55 3.13 2.89 2.36 2.21 1.90 1.81 1.83 1.95 2.12 2.59 3.16

Kalmiopsis Wilderness 5.32 4.56 4.30 4.02 3.79 3.54 3.43 3.44 3.56 4.12 5.21 5.28

Kings Canyon 3.35 2.97 2.82 2.42 2.28 1.93 1.85 1.87 2.01 2.15 2.56 2.96

La Garita Wilderness 2.71 2.54 2.21 2.04 2.05 1.72 1.93 2.31 2.26 2.00 2.46 2.62

Lassen Volcanic NP 4.24 3.55 3.16 2.73 2.58 2.31 2.24 2.29 2.39 2.64 3.46 4.00

Lava Beds NM 4.84 4.05 3.63 3.28 3.04 2.76 2.53 2.55 2.75 3.29 4.35 4.75

Linville Gorge Wilderness 3.76 3.46 3.37 3.07 3.74 4.18 4.24 4.62 4.61 4.00 3.59 3.80

Lostwood Wilderness 3.21 3.15 3.36 2.60 2.54 2.86 2.89 2.60 2.53 2.72 3.60 3.52

Lye Brook Wilderness 3.25 2.99 3.10 3.06 3.24 3.30 3.52 3.80 3.95 3.71 3.42 3.35

Mammoth Cave NP 3.86 3.47 3.32 3.54 4.90 5.77 5.58 4.09 4.15 3.73 3.54 3.91

Marble Mountain Wilderness 5.15 4.40 4.15 3.84 3.67 3.44 3.41 3.44 3.50 3.89 4.87 5.04

Maroon Bells-Snowmass Wilderness 2.48 2.44 2.23 2.25 2.25 1.87 2.02 2.35 2.35 2.04 2.36 2.38

Mazatzal Wilderness 2.36 2.20 1.88 1.46 1.36 1.18 1.54 1.89 1.74 1.66 1.91 2.33

Medicine Lake Wilderness 3.25 3.15 3.21 2.52 2.49 2.71 2.71 2.42 2.46 2.65 3.48 3.48

Mesa Verde NP 3.32 2.96 2.55 1.88 1.96 1.46 1.94 2.35 2.13 2.04 2.57 3.06

Mingo Wilderness 3.74 3.38 3.07 2.97 3.39 3.52 3.57 3.64 3.72 3.47 3.43 3.74

Mission Mountains Wilderness 4.03 3.51 3.08 2.82 2.84 2.83 2.49 2.40 2.78 3.28 4.04 4.08

Mokelumne Wilderness 3.75 3.23 2.86 2.29 2.12 1.81 1.68 1.72 1.84 2.08 2.71 3.41

Moosehorn Wilderness 3.59 3.14 3.16 3.44 3.38 3.49 3.98 4.18 4.40 3.94 3.82 3.82

Mount Adams Wilderness 5.71 5.00 4.46 4.23 3.89 3.55 3.26 3.41 4.02 5.13 5.89 5.98

Mount Baldy Wilderness 2.51 2.30 1.92 1.51 1.43 1.25 1.73 2.08 1.88 1.76 2.08 2.54

Mount Hood Wilderness 5.56 4.87 4.40 4.19 3.79 3.44 3.07 3.22 3.79 4.93 5.76 5.81

Mount Jefferson Wilderness 5.95 5.16 4.78 4.57 4.09 3.65 3.10 3.11 3.63 4.91 5.98 6.05

 USFS–NPS–USFWS 43
Table 8. Monthly fS

(RH) – Small (NH4)

2

SO4 and NH4NO3 Relative Humidity Adjustment Factor

Class I Area Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Mount Rainier NP 6.01 5.29 4.71 4.51 4.23 3.82 3.59 3.73 4.39 5.55 6.23 6.27

Mount Washington Wilderness 6.35 5.47 5.22 5.07 4.42 3.93 3.16 3.09 3.63 5.07 6.31 6.35

Mount Zirkel Wilderness 2.43 2.44 2.31 2.37 2.51 2.07 1.92 2.02 2.23 2.12 2.41 2.37

Mountain Lakes Wilderness 5.20 4.32 3.90 3.58 3.26 2.96 2.69 2.70 2.94 3.67 4.96 5.24

North Absaroka Wilderness 2.68 2.51 2.50 2.42 2.40 2.13 1.83 1.72 1.98 2.31 2.65 2.65

North Cascades NP 5.37 4.86 4.24 4.04 3.80 3.51 3.34 3.61 4.23 5.08 5.68 5.66

Okefenokee Wilderness 4.16 3.79 3.80 3.65 3.79 4.46 4.24 4.55 4.55 4.35 4.18 4.33

Olympic NP 5.76 5.20 4.81 4.64 3.81 4.04 3.52 4.16 4.70 5.63 6.11 6.02

Otter Creek Wilderness 3.41 3.20 3.20 2.91 3.64 3.70 3.88 4.18 4.26 3.72 3.32 3.56

Pasayten Wilderness 5.46 4.89 4.20 3.96 3.77 3.42 3.28 3.49 4.08 5.00 5.72 5.74

Pecos Wilderness 2.65 2.40 2.10 1.85 1.88 1.65 1.96 2.34 2.27 1.94 2.36 2.60

Petrified Forest NP 2.67 2.43 1.96 1.59 1.46 1.26 1.67 2.06 1.85 1.79 2.20 2.66

Pine Mountain Wilderness 2.44 2.29 1.95 1.51 1.41 1.20 1.54 1.91 1.77 1.70 1.96 2.39

Pinnacles NM 4.02 4.05 4.09 3.01 2.81 2.54 2.40 2.52 2.54 2.74 2.82 3.36

Point Reyes NS 4.16 3.74 3.53 2.96 2.80 2.55 2.69 2.77 2.80 2.90 3.30 3.80

Presidential Range-Dry River Wilderness 3.36 3.02 3.15 3.26 3.37 3.56 3.86 4.14 4.33 3.96 3.68 3.50

Rawah Wilderness 2.31 2.39 2.32 2.44 2.61 2.19 2.05 2.16 2.31 2.12 2.37 2.29

Red Rock Lakes Wilderness 3.09 2.76 2.57 2.41 2.38 2.17 1.86 1.77 2.01 2.39 2.96 3.05

Redwood NP 4.81 4.41 4.51 4.27 4.40 4.37 4.73 4.76 4.46 4.24 4.62 4.45

Rocky Mountain NP 2.09 2.24 2.24 2.45 2.62 2.22 2.09 2.15 2.29 2.04 2.23 2.08

Roosevelt Campobello International Park 3.61 3.14 3.16 3.45 3.37 3.49 3.95 4.15 4.36 3.93 3.84 3.85

Saguaro NP 1.99 1.80 1.56 1.18 1.16 1.07 1.51 1.89 1.66 1.54 1.72 2.25

Saint Marks Wilderness 4.24 3.89 3.79 3.72 3.79 4.32 4.56 4.63 4.43 4.19 4.16 4.39

Salt Creek Wilderness 2.57 2.19 1.75 1.67 1.82 1.69 1.93 2.16 2.37 1.94 2.07 2.38

San Gabriel Wilderness 2.94 2.78 2.72 2.41 2.37 2.29 2.32 2.39 2.44 2.44 2.36 2.58

San Gorgonio Wilderness 2.94 2.94 2.74 2.36 2.34 2.00 1.88 2.02 2.05 2.04 2.10 2.43

San Jacinto Wilderness 2.73 2.65 2.59 2.33 2.30 2.16 2.02 2.26 2.30 2.28 2.19 2.38

San Pedro Parks Wilderness 2.73 2.45 2.10 1.81 1.80 1.55 1.87 2.24 2.16 1.91 2.36 2.65

San Rafael Wilderness 3.38 3.13 3.07 2.68 2.64 2.57 2.66 2.74 2.84 2.77 2.63 2.94

Sawtooth Wilderness 3.78 3.18 2.55 2.20 2.17 1.95 1.51 1.50 1.61 2.11 3.26 3.70

Scapegoat Wilderness 3.70 3.24 2.97 2.79 2.78 2.75 2.41 2.31 2.65 3.09 3.67 3.68

Selway-Bitterroot Wilderness 3.99 3.41 2.90 2.56 2.54 2.43 2.00 1.93 2.21 2.82 3.78 4.01

Seney Wilderness 3.69 3.10 3.30 3.10 3.03 3.45 3.80 4.27 4.31 3.82 3.97 3.87

Sequoia NP 3.25 2.91 2.87 2.59 2.46 1.97 1.85 1.84 2.02 2.18 2.64 2.85

Shenandoah NP 3.26 2.99 3.02 2.72 3.28 3.46 3.59 3.85 3.91 3.41 3.08 3.44

Shining Rock Wilderness 3.89 3.51 3.37 3.11 3.77 4.22 4.29 4.58 4.60 4.12 3.69 3.88

Sierra Ancha Wilderness 2.38 2.21 1.87 1.46 1.36 1.19 1.60 1.95 1.78 1.69 1.96 2.41

Simeonof Wilderness 4.86 4.88 4.44 4.64 4.92 5.46 6.08 6.35 5.30 4.29 4.52 4.98

Sipsey Wilderness 3.89 3.52 3.23 3.13 3.60 3.99 4.13 4.09 4.12 3.87 3.61 3.89

South Warner Wilderness 4.36 3.67 3.20 2.81 2.64 2.39 2.04 2.07 2.24 2.76 3.71 4.20

Strawberry Mountain Wilderness 5.26 4.45 3.71 3.32 3.18 2.70 2.26 2.24 2.66 3.84 5.11 5.44

Superstition Wilderness 2.25 2.06 1.77 1.38 1.29 1.15 1.52 1.81 1.66 1.58 1.83 2.28

Swanquarter Wilderness 3.31 3.09 3.01 2.78 3.09 3.39 3.57 3.68 3.55 3.40 3.14 3.33

Sycamore Canyon Wilderness 2.52 2.41 2.05 1.59 1.47 1.23 1.53 1.98 1.85 1.77 2.03 2.45

Teton Wilderness 2.78 2.59 2.49 2.37 2.36 2.06 1.75 1.67 1.96 2.28 2.70 2.73

44 FLAG Phase I Report—Revised (2010)
Table 8. Monthly fS

(RH) – Small (NH4)

2

SO4 and NH4NO3 Relative Humidity Adjustment Factor

Class I Area Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Theodore Roosevelt NP 3.17 3.11 3.22 2.71 2.74 2.85 2.73 2.49 2.48 2.66 3.42 3.37

Thousand Lakes Wilderness 4.34 3.60 3.22 2.79 2.62 2.34 2.26 2.31 2.41 2.69 3.58 4.11

Three Sisters Wilderness 6.22 5.38 5.09 4.92 4.35 3.89 3.21 3.17 3.68 5.02 6.20 6.24

Tuxedni Wilderness 4.11 3.89 3.26 3.14 3.11 3.31 4.13 4.57 4.57 4.04 4.04 4.23

UL Bend Wilderness 2.94 2.75 2.77 2.55 2.44 2.41 2.19 1.97 2.12 2.50 2.96 2.95

Upper Buffalo Wilderness 3.73 3.33 3.03 3.07 3.54 3.57 3.43 3.50 3.71 3.51 3.52 3.74

Ventana Wilderness 3.92 3.69 3.61 2.86 2.69 2.46 2.46 2.55 2.61 2.72 2.89 3.43

Virgin Islands NP 2.41 2.36 2.27 2.39 2.44 2.40 2.43 2.57 2.58 2.63 2.68 2.54

Voyageurs NP 3.16 2.77 2.82 2.59 2.65 3.28 3.25 3.48 3.66 3.02 3.37 3.32

Washakie Wilderness 2.68 2.52 2.49 2.40 2.40 2.09 1.77 1.68 1.98 2.29 2.66 2.65

Weminuche Wilderness 2.80 2.58 2.22 1.97 1.97 1.64 1.89 2.28 2.20 1.97 2.45 2.69

West Elk Wilderness 2.64 2.53 2.24 2.15 2.16 1.79 1.92 2.24 2.26 2.02 2.41 2.53

Wheeler Peak Wilderness 2.72 2.50 2.17 1.97 2.02 1.76 1.98 2.42 2.36 2.01 2.48 2.66

White Mountain Wilderness 2.54 2.19 1.76 1.58 1.65 1.53 1.94 2.20 2.29 1.87 2.07 2.45

Wichita Mountains Wilderness 3.17 2.94 2.69 2.68 3.15 2.86 2.49 2.70 3.07 2.87 2.97 3.20

Wind Cave NP 2.81 2.81 2.86 2.82 3.06 2.81 2.50 2.46 2.44 2.52 2.97 2.83

Wolf Island Wilderness 4.02 3.68 3.58 3.45 3.59 4.17 4.13 4.47 4.46 4.23 4.05 4.18

Yellowstone NP 2.82 2.61 2.53 2.42 2.41 2.16 1.86 1.76 2.02 2.36 2.78 2.80

Yolla Bolly-Middle Eel Wilderness 4.48 3.82 3.53 3.13 3.00 2.75 2.81 2.87 2.93 3.11 3.84 4.24

Yosemite NP 3.62 3.32 3.13 2.52 2.34 1.89 1.69 1.67 1.78 2.04 2.65 3.22

Zion NP 3.05 2.81 2.26 1.84 1.67 1.37 1.33 1.54 1.58 1.75 2.25 2.72

 USFS–NPS–USFWS 45
Table 9. Monthly fSS(RH) – Sea Salt Relative Humidity Adjustment Factor

Class I Area Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Acadia NP 3.90 3.48 3.40 3.66 3.71 3.81 4.19 4.27 4.44 4.13 4.10 4.19

Agua Tibia Wilderness 2.94 2.95 3.02 2.85 2.88 2.81 2.78 2.90 2.90 2.83 2.56 2.69

Alpine Lakes Wilderness 5.35 4.96 4.27 4.11 4.18 3.64 3.68 3.73 4.12 4.98 5.51 5.53

Anaconda Pintler Wilderness 4.00 3.56 3.18 2.90 2.85 2.75 2.33 2.25 2.52 3.10 3.81 3.97

Ansel Adams Wilderness 3.55 3.25 3.04 2.54 2.38 2.05 1.91 1.91 2.03 2.21 2.72 3.21

Arches NP 3.25 2.99 2.26 1.97 1.86 1.48 1.59 1.82 1.88 1.96 2.60 3.02

Badlands NP 3.37 3.33 3.27 3.05 3.25 3.15 2.89 2.81 2.74 2.82 3.41 3.38

Bandelier NM 2.91 2.59 2.22 1.87 1.90 1.67 2.11 2.54 2.37 2.00 2.49 2.78

Bering Sea Wilderness 4.39 4.57 4.60 4.58 4.57 4.70 5.26 5.73 5.11 4.59 4.52 4.54

Big Bend NP 2.20 2.03 1.75 1.67 1.84 1.87 2.03 2.34 2.47 2.09 2.10 2.22

Black Canyon of the Gunnison NP 3.05 2.89 2.47 2.31 2.28 1.89 2.04 2.36 2.37 2.18 2.71 2.92

Bob Marshall Wilderness 4.08 3.66 3.35 3.11 3.08 3.04 2.68 2.59 2.94 3.42 3.98 4.05

Bosque del Apache Wilderness 2.77 2.43 1.95 1.62 1.62 1.47 2.06 2.40 2.29 1.92 2.27 2.71

Boundary Waters Canoe Area Wilderness 3.73 3.35 3.29 2.91 3.00 3.44 3.68 3.88 3.98 3.45 3.89 3.91

Breton Wilderness 4.10 3.89 3.87 3.85 4.02 4.21 4.44 4.38 4.23 3.99 4.01 4.11

Bridger Wilderness 3.25 3.05 2.90 2.67 2.62 2.17 1.81 1.79 2.17 2.43 3.15 3.17

Brigantine Wilderness 3.53 3.24 3.30 3.15 3.49 3.63 3.84 4.02 4.02 3.82 3.48 3.55

Bryce Canyon NP 3.24 3.00 2.40 1.96 1.80 1.45 1.52 1.80 1.78 1.93 2.52 2.99

Cabinet Mountains Wilderness 4.42 3.93 3.50 3.18 3.13 3.06 2.67 2.59 3.01 3.58 4.33 4.46

Caney Creek Wilderness 3.90 3.52 3.31 3.41 3.83 3.88 3.69 3.68 3.82 3.76 3.77 3.93

Canyonlands NP 3.30 3.04 2.33 1.99 1.87 1.48 1.63 1.90 1.94 2.00 2.64 3.07

Cape Romain Wilderness 3.74 3.44 3.37 3.23 3.62 3.99 4.04 4.32 4.29 4.03 3.74 3.81

Capitol Reef NP 3.35 3.11 2.45 2.08 1.93 1.54 1.62 1.90 1.94 2.05 2.68 3.13

Caribou Wilderness 4.16 3.63 3.28 2.89 2.75 2.47 2.33 2.37 2.49 2.74 3.48 3.97

Carlsbad Caverns NP 2.75 2.36 1.86 1.72 1.89 1.86 2.27 2.59 2.75 2.09 2.29 2.68

Chassahowitzka Wilderness 4.29 3.99 3.89 3.76 3.77 4.29 4.34 4.51 4.49 4.33 4.23 4.38

Chiricahua NM 2.53 2.38 1.91 1.41 1.38 1.21 2.12 2.55 2.18 1.78 1.99 2.56

Chiricahua Wilderness 2.48 2.33 1.86 1.37 1.35 1.20 2.12 2.54 2.16 1.75 1.94 2.52

Cohutta Wilderness 3.97 3.62 3.44 3.26 3.82 4.20 4.24 4.35 4.35 4.05 3.82 4.02

Crater Lake NP 5.15 4.56 4.31 4.12 3.80 3.52 3.20 3.23 3.44 4.17 5.10 5.19

Craters of the Moon NM 3.78 3.41 2.86 2.51 2.48 2.16 1.72 1.69 1.93 2.43 3.38 3.72

Cucamonga Wilderness 3.07 3.01 3.03 2.79 2.80 2.72 2.72 2.80 2.81 2.76 2.58 2.77

Denali NP & Pres 3.68 3.57 3.07 2.74 2.74 3.01 3.53 4.13 4.19 4.09 3.92 3.94

Desolation Wilderness 3.85 3.39 3.02 2.48 2.32 2.01 1.84 1.87 2.02 2.28 2.94 3.58

Diamond Peak Wilderness 5.29 4.72 4.45 4.27 3.92 3.65 3.23 3.26 3.56 4.43 5.26 5.34

Dolly Sods Wilderness 3.60 3.35 3.31 3.03 3.66 3.76 3.91 4.12 4.16 3.72 3.47 3.72

Dome Land Wilderness 3.10 2.86 2.75 2.42 2.33 2.15 2.11 2.16 2.22 2.26 2.40 2.71

Eagle Cap Wilderness 4.84 4.27 3.57 3.22 3.14 2.74 2.33 2.27 2.60 3.61 4.68 4.99

Eagles Nest Wilderness 2.86 2.82 2.54 2.52 2.57 2.20 2.20 2.44 2.46 2.27 2.73 2.79

Emigrant Wilderness 3.70 3.37 3.13 2.60 2.42 2.05 1.88 1.88 2.01 2.24 2.84 3.39

Everglades NP 3.60 3.44 3.37 3.22 3.21 3.58 3.50 3.72 3.78 3.61 3.50 3.55

Fitzpatrick Wilderness 3.25 3.05 2.88 2.66 2.62 2.18 1.82 1.79 2.16 2.43 3.13 3.18

Flat Tops Wilderness 2.99 2.88 2.54 2.47 2.47 2.07 2.03 2.23 2.35 2.25 2.75 2.89

Galiuro Wilderness 2.42 2.19 1.82 1.35 1.31 1.16 1.76 2.18 1.94 1.73 2.00 2.52

Gates of the Mountains Wilderness 3.62 3.27 3.05 2.85 2.80 2.74 2.43 2.35 2.58 2.99 3.41 3.52

46 FLAG Phase I Report—Revised (2010)
Table 9. Monthly fSS(RH) – Sea Salt Relative Humidity Adjustment Factor

Class I Area Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Gearhart Mountain Wilderness 4.63 4.06 3.67 3.40 3.16 2.90 2.49 2.50 2.70 3.39 4.31 4.60

Gila Wilderness 2.63 2.35 1.91 1.52 1.48 1.36 2.22 2.36 2.19 1.87 2.17 2.65

Glacier NP 4.61 4.12 3.87 3.64 3.63 3.59 3.11 3.11 3.63 4.03 4.43 4.51

Glacier Peak Wilderness 5.14 4.73 4.19 4.03 3.93 3.60 3.51 3.63 4.04 4.79 5.31 5.34

Goat Rocks Wilderness 5.30 4.79 4.32 4.15 3.94 3.65 3.46 3.55 3.99 4.83 5.40 5.51

Grand Canyon NP 2.93 2.73 2.26 1.78 1.61 1.32 1.50 1.85 1.79 1.84 2.29 2.70

Grand Teton NP 3.34 3.10 2.82 2.59 2.56 2.21 1.85 1.78 2.12 2.48 3.10 3.29

Great Gulf Wilderness 3.60 3.29 3.29 3.34 3.41 3.58 3.85 4.07 4.20 3.96 3.81 3.73

Great Sand Dunes NP & Pres 2.98 2.84 2.48 2.33 2.36 2.08 2.24 2.66 2.56 2.26 2.82 2.94

Great Smoky Mountains NP 4.01 3.57 3.47 3.22 3.82 4.23 4.24 4.37 4.38 4.03 3.81 4.02

Guadalupe Mountains NP 2.82 2.35 1.84 1.64 1.82 1.83 2.36 2.72 2.85 2.01 2.28 2.76

Haleakala NP 3.52 3.43 3.40 3.35 3.25 3.18 3.29 3.27 3.22 3.33 3.52 3.47

Hawaii Volcanoes NP 3.80 3.68 3.71 3.72 3.72 3.69 3.79 3.83 3.79 3.83 4.08 3.80

Hells Canyon Wilderness 4.39 3.81 3.15 2.75 2.63 2.44 1.97 1.90 2.19 3.00 4.13 4.51

Hercules-Glades Wilderness 3.86 3.51 3.23 3.22 3.66 3.72 3.69 3.73 3.81 3.57 3.65 3.88

Hoover Wilderness 3.66 3.31 3.05 2.53 2.36 2.00 1.82 1.82 1.96 2.18 2.79 3.34

Isle Royale NP 3.78 3.34 3.28 2.93 2.78 3.31 3.83 3.87 4.06 3.40 4.05 4.04

James River Face Wilderness 3.43 3.19 3.16 2.90 3.46 3.69 3.79 3.97 4.00 3.61 3.31 3.56

Jarbidge Wilderness 3.65 3.28 2.62 2.69 2.71 2.44 1.95 1.67 1.60 2.01 3.03 3.51

John Muir Wilderness 3.46 3.18 3.07 2.68 2.51 2.17 2.06 2.08 2.20 2.35 2.75 3.12

Joshua Tree NP 2.83 2.76 2.75 2.52 2.53 2.41 2.28 2.53 2.53 2.48 2.32 2.54

Joyce Kilmer-Slickrock Wilderness 4.01 3.58 3.46 3.24 3.81 4.22 4.23 4.35 4.35 4.03 3.82 4.02

Kaiser Wilderness 3.58 3.27 3.08 2.58 2.42 2.10 1.99 2.00 2.12 2.29 2.75 3.24

Kalmiopsis Wilderness 4.98 4.45 4.28 4.09 3.89 3.66 3.49 3.51 3.60 4.08 4.90 4.96

Kings Canyon 3.40 3.13 3.03 2.66 2.50 2.16 2.05 2.07 2.20 2.33 2.71 3.05

La Garita Wilderness 3.03 2.83 2.41 2.21 2.19 1.86 2.10 2.50 2.42 2.16 2.72 2.93

Lassen Volcanic NP 4.21 3.66 3.33 2.93 2.78 2.50 2.36 2.40 2.51 2.78 3.54 4.02

Lava Beds NM 4.64 4.04 3.68 3.37 3.15 2.89 2.62 2.65 2.82 3.32 4.21 4.56

Linville Gorge Wilderness 3.80 3.52 3.43 3.18 3.80 4.20 4.25 4.51 4.48 3.97 3.67 3.86

Lostwood Wilderness 3.77 3.66 3.67 2.86 2.79 3.07 3.11 2.82 2.80 2.99 3.93 3.95

Lye Brook Wilderness 3.53 3.26 3.27 3.20 3.36 3.48 3.70 3.93 4.04 3.82 3.63 3.61

Mammoth Cave NP 3.99 3.63 3.45 3.50 4.52 5.19 5.08 4.16 4.17 3.81 3.73 4.03

Marble Mountain Wilderness 4.85 4.32 4.16 3.92 3.76 3.53 3.44 3.46 3.51 3.86 4.63 4.78

Maroon Bells-Snowmass Wilderness 2.89 2.82 2.52 2.49 2.45 2.04 2.22 2.57 2.54 2.26 2.71 2.80

Mazatzal Wilderness 2.60 2.40 2.03 1.53 1.42 1.21 1.66 2.06 1.90 1.77 2.10 2.55

Medicine Lake Wilderness 3.79 3.66 3.56 2.80 2.75 2.94 2.93 2.66 2.73 2.95 3.85 3.92

Mesa Verde NP 3.40 3.10 2.61 1.95 2.00 1.53 2.04 2.45 2.28 2.05 2.69 3.15

Mingo Wilderness 3.92 3.58 3.30 3.19 3.58 3.72 3.80 3.82 3.85 3.61 3.66 3.90

Mission Mountains Wilderness 4.24 3.79 3.38 3.10 3.08 3.04 2.68 2.59 2.96 3.48 4.17 4.26

Mokelumne Wilderness 3.81 3.38 3.04 2.51 2.34 2.02 1.86 1.88 2.02 2.27 2.91 3.52

Moosehorn Wilderness 3.80 3.42 3.32 3.50 3.47 3.60 3.98 4.15 4.31 4.02 3.97 3.99

Mount Adams Wilderness 5.24 4.74 4.34 4.18 3.91 3.66 3.41 3.51 3.93 4.78 5.36 5.44

Mount Baldy Wilderness 2.74 2.50 2.05 1.58 1.50 1.29 1.87 2.28 2.06 1.87 2.26 2.74

Mount Hood Wilderness 5.16 4.67 4.33 4.18 3.87 3.61 3.29 3.38 3.78 4.67 5.29 5.33

Mount Jefferson Wilderness 5.38 4.84 4.55 4.42 4.05 3.74 3.27 3.28 3.63 4.64 5.41 5.46

Mount Rainier NP 5.42 4.92 4.50 4.36 4.13 3.86 3.67 3.76 4.20 5.05 5.56 5.62

 USFS–NPS–USFWS 47
Table 9. Monthly fSS(RH) – Sea Salt Relative Humidity Adjustment Factor

Class I Area Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Mount Washington Wilderness 5.61 5.03 4.81 4.71 4.24 3.91 3.31 3.25 3.60 4.73 5.59 5.62

Mount Zirkel Wilderness 2.85 2.83 2.61 2.61 2.67 2.24 2.10 2.23 2.38 2.31 2.75 2.78

Mountain Lakes Wilderness 4.89 4.26 3.93 3.67 3.40 3.11 2.82 2.83 3.04 3.67 4.68 4.91

North Absaroka Wilderness 3.18 2.97 2.83 2.66 2.64 2.35 2.02 1.89 2.16 2.53 3.03 3.13

North Cascades NP 5.03 4.65 4.22 4.08 3.88 3.68 3.53 3.70 4.13 4.78 5.24 5.25

Okefenokee Wilderness 4.13 3.83 3.82 3.69 3.85 4.38 4.28 4.51 4.48 4.31 4.18 4.27

Olympic NP 5.27 4.87 4.61 4.51 3.94 4.12 3.76 4.16 4.51 5.17 5.51 5.46

Otter Creek Wilderness 3.63 3.40 3.34 3.06 3.67 3.82 3.98 4.19 4.23 3.78 3.51 3.76

Pasayten Wilderness 5.09 4.67 4.18 4.00 3.84 3.58 3.45 3.58 3.99 4.71 5.25 5.30

Pecos Wilderness 2.91 2.64 2.25 1.97 2.00 1.78 2.15 2.57 2.44 2.09 2.56 2.83

Petrified Forest NP 2.93 2.66 2.11 1.66 1.53 1.30 1.81 2.26 2.03 1.91 2.40 2.88

Pine Mountain Wilderness 2.69 2.50 2.11 1.60 1.47 1.24 1.67 2.09 1.92 1.82 2.16 2.62

Pinnacles NM 3.94 3.97 3.99 3.12 2.94 2.67 2.54 2.63 2.65 2.80 2.96 3.36

Point Reyes NS 4.20 3.88 3.72 3.25 3.12 2.88 2.96 3.01 3.05 3.12 3.48 3.90

Presidential Range-Dry River Wilderness 3.60 3.28 3.31 3.36 3.45 3.66 3.92 4.14 4.27 3.99 3.83 3.72

Rawah Wilderness 2.70 2.74 2.58 2.65 2.76 2.36 2.23 2.37 2.45 2.31 2.69 2.66

Red Rock Lakes Wilderness 3.51 3.18 2.91 2.67 2.63 2.41 2.06 1.94 2.20 2.63 3.29 3.46

Redwood NP 4.66 4.38 4.48 4.34 4.41 4.35 4.56 4.59 4.34 4.19 4.51 4.44

Rocky Mountain NP 2.44 2.56 2.47 2.64 2.75 2.37 2.26 2.36 2.41 2.20 2.51 2.41

Roosevelt Campobello International Park 3.82 3.43 3.32 3.52 3.47 3.61 3.96 4.13 4.29 4.02 3.99 4.01

Saguaro NP 2.24 2.00 1.69 1.21 1.20 1.08 1.67 2.13 1.86 1.65 1.89 2.44

Saint Marks Wilderness 4.18 3.89 3.82 3.76 3.85 4.30 4.49 4.54 4.39 4.19 4.15 4.30

Salt Creek Wilderness 2.72 2.37 1.88 1.77 1.96 1.87 2.15 2.44 2.59 2.12 2.26 2.56

San Gabriel Wilderness 3.12 3.04 3.04 2.77 2.78 2.69 2.69 2.77 2.79 2.74 2.59 2.79

San Gorgonio Wilderness 2.97 3.06 2.93 2.60 2.63 2.28 2.13 2.30 2.31 2.24 2.25 2.55

San Jacinto Wilderness 2.92 2.91 2.91 2.67 2.69 2.55 2.33 2.64 2.64 2.57 2.40 2.60

San Pedro Parks Wilderness 3.00 2.71 2.25 1.94 1.91 1.66 2.04 2.45 2.33 2.05 2.57 2.88

San Rafael Wilderness 3.49 3.35 3.34 3.00 2.99 2.90 2.97 3.04 3.09 3.00 2.86 3.12

Sawtooth Wilderness 4.05 3.53 2.89 2.53 2.44 2.18 1.66 1.61 1.76 2.38 3.55 4.00

Scapegoat Wilderness 3.97 3.57 3.27 3.04 3.01 2.96 2.60 2.51 2.83 3.30 3.86 3.93

Selway-Bitterroot Wilderness 4.20 3.71 3.21 2.86 2.80 2.66 2.18 2.09 2.39 3.06 3.96 4.20

Seney Wilderness 4.05 3.60 3.60 3.30 3.20 3.58 3.91 4.28 4.30 4.00 4.19 4.16

Sequoia NP 3.27 3.07 3.10 2.84 2.66 2.21 2.06 2.05 2.21 2.35 2.75 2.93

Shenandoah NP 3.44 3.17 3.17 2.90 3.42 3.66 3.78 3.97 3.98 3.56 3.28 3.62

Shining Rock Wilderness 3.90 3.55 3.43 3.21 3.82 4.22 4.28 4.48 4.48 4.06 3.76 3.92

Sierra Ancha Wilderness 2.62 2.42 2.02 1.53 1.42 1.22 1.73 2.14 1.95 1.81 2.15 2.62

Simeonof Wilderness 4.83 4.85 4.54 4.68 4.83 5.20 5.57 5.72 5.11 4.48 4.62 4.89

Sipsey Wilderness 3.94 3.60 3.36 3.28 3.72 4.06 4.18 4.14 4.13 3.91 3.74 3.96

South Warner Wilderness 4.32 3.75 3.31 2.94 2.77 2.51 2.13 2.15 2.31 2.83 3.71 4.19

Strawberry Mountain Wilderness 4.97 4.37 3.77 3.44 3.28 2.88 2.41 2.38 2.73 3.77 4.82 5.10

Superstition Wilderness 2.49 2.27 1.92 1.44 1.34 1.17 1.64 1.98 1.82 1.69 2.01 2.49

Swanquarter Wilderness 3.52 3.30 3.25 3.09 3.42 3.71 3.88 3.96 3.83 3.67 3.43 3.55

Sycamore Canyon Wilderness 2.78 2.62 2.22 1.68 1.55 1.27 1.67 2.17 2.00 1.90 2.25 2.69

Teton Wilderness 3.26 3.04 2.83 2.61 2.59 2.27 1.93 1.83 2.14 2.50 3.07 3.21

Theodore Roosevelt NP 3.67 3.56 3.51 2.93 2.97 3.09 2.96 2.72 2.72 2.93 3.75 3.78

48 FLAG Phase I Report—Revised (2010)
Table 9. Monthly fSS(RH) – Sea Salt Relative Humidity Adjustment Factor

Class I Area Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Thousand Lakes Wilderness 4.27 3.70 3.38 2.99 2.82 2.52 2.37 2.42 2.53 2.82 3.62 4.08

Three Sisters Wilderness 5.53 4.97 4.74 4.63 4.20 3.89 3.35 3.31 3.65 4.70 5.53 5.56

Tuxedni Wilderness 4.28 4.06 3.53 3.46 3.44 3.64 4.26 4.56 4.51 4.17 4.17 4.37

UL Bend Wilderness 3.44 3.22 3.12 2.79 2.70 2.67 2.42 2.18 2.35 2.77 3.34 3.40

Upper Buffalo Wilderness 3.85 3.47 3.23 3.27 3.72 3.78 3.69 3.70 3.84 3.64 3.67 3.86

Ventana Wilderness 3.91 3.76 3.70 3.08 2.93 2.69 2.69 2.75 2.80 2.87 3.06 3.48

Virgin Islands NP 3.17 3.12 3.04 3.15 3.19 3.17 3.18 3.31 3.30 3.36 3.39 3.28

Voyageurs NP 3.69 3.31 3.20 2.90 2.89 3.46 3.55 3.71 3.87 3.42 3.83 3.80

Washakie Wilderness 3.18 2.98 2.83 2.64 2.62 2.31 1.96 1.85 2.15 2.50 3.04 3.14

Weminuche Wilderness 3.08 2.85 2.39 2.11 2.09 1.77 2.05 2.46 2.36 2.12 2.69 2.95

West Elk Wilderness 3.00 2.87 2.49 2.36 2.33 1.94 2.10 2.44 2.43 2.20 2.72 2.89

Wheeler Peak Wilderness 3.00 2.76 2.35 2.11 2.15 1.92 2.17 2.63 2.52 2.18 2.71 2.93

White Mountain Wilderness 2.71 2.37 1.89 1.68 1.76 1.66 2.14 2.46 2.49 2.02 2.25 2.63

Wichita Mountains Wilderness 3.35 3.12 2.91 2.94 3.40 3.21 2.84 3.01 3.32 3.10 3.20 3.40

Wind Cave NP 3.25 3.20 3.13 3.01 3.22 3.06 2.75 2.68 2.63 2.75 3.28 3.24

Wolf Island Wilderness 4.03 3.74 3.66 3.55 3.72 4.20 4.20 4.46 4.42 4.22 4.08 4.15

Yellowstone NP 3.29 3.05 2.87 2.66 2.65 2.39 2.05 1.93 2.21 2.59 3.14 3.25

Yolla Bolly-Middle Eel Wilderness 4.38 3.89 3.66 3.31 3.18 2.92 2.89 2.94 3.00 3.20 3.84 4.19

Yosemite NP 3.58 3.38 3.23 2.71 2.54 2.08 1.84 1.79 1.93 2.18 2.78 3.25

Zion NP 3.26 3.03 2.44 1.96 1.78 1.44 1.41 1.66 1.67 1.88 2.48 2.98

 USFS–NPS–USFWS 49
Table 10. Monthly Average Natural Conditions Visual Range In Kilometers

Class I Area Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Acadia NP 173 177 177 174 174 173 170 169 167 171 171 170

Agua Tibia Wilderness 226 227 226 228 228 229 229 228 228 228 230 229

Alpine Lakes Wilderness 224 228 236 238 236 243 242 242 237 227 222 222

Anaconda Pintler Wilderness 256 259 262 267 268 271 273 272 271 269 265 259

Ansel Adams Wilderness 258 263 266 269 269 270 274 275 272 267 259 258

Arches NP 265 268 274 276 277 281 280 278 277 276 271 268

Badlands NP 233 233 233 234 232 233 235 236 236 236 232 233

Bandelier NM 269 272 276 280 281 283 278 274 276 277 274 269

Bering Sea Wilderness

Big Bend NP 236 234 233 234 233 231 225 220 227 233 235 235

Black Canyon of the Gunnison NP 278 280 282 283 282 282 281 278 276 280 280 278

Bob Marshall Wilderness 257 259 262 263 263 266 265 262 262 264 260 258

Bosque del Apache Wilderness 249 252 256 259 259 260 255 252 253 256 253 249

Boundary Waters Canoe Area Wilderness 184 187 189 190 190 191 193 194 191 188 184 184

Breton Wilderness 173 176 176 179 177 174 172 170 169 174 171 171

Bridger Wilderness 278 280 286 290 292 296 295 292 292 291 285 280

Brigantine Wilderness 159 161 161 161 160 158 156 157 158 160 160 159

Bryce Canyon NP 268 269 270 271 271 275 279 279 275 273 268 268

Cabinet Mountains Wilderness 252 254 253 255 251 251 249 247 247 248 252 251

Caney Creek Wilderness 174 177 180 183 183 183 186 186 183 179 174 173

Canyonlands NP 257 261 264 263 259 259 260 260 258 258 259 257

Cape Romain Wilderness 167 169 174 177 178 181 180 178 177 177 172 169

Capitol Reef NP 269 271 277 280 281 285 284 281 281 280 275 271

Caribou Wilderness 250 256 259 263 264 267 267 267 266 264 257 252

Carlsbad Caverns NP 266 271 276 277 275 276 272 270 267 274 271 267

Chassahowitzka Wilderness 171 173 174 175 175 171 171 169 169 171 171 170

Chiricahua NM 253 254 258 261 262 263 256 253 256 259 257 252

Chiricahua Wilderness 253 254 258 262 262 263 256 253 256 259 258 252

Cohutta Wilderness 181 184 185 187 183 180 180 179 179 181 183 181

Crater Lake NP 255 263 266 269 273 276 280 279 276 267 256 255

Craters of the Moon NM 245 248 252 255 255 257 261 261 259 255 248 246

Cucamonga Wilderness 263 264 264 267 267 268 268 267 267 267 268 266

Denali NP & Pres 257 257 261 263 263 261 257 251 250 252 254 254

Desolation Wilderness 270 275 279 285 287 290 292 292 290 287 280 273

Diamond Peak Wilderness 253 261 264 267 271 275 279 279 275 264 254 253

Dolly Sods Wilderness 197 200 201 203 204 206 206 205 205 204 203 200

Dome Land Wilderness 242 244 244 247 241 241 239 237 236 241 243 241

Eagle Cap Wilderness 229 234 241 245 245 249 252 253 249 240 230 227

Eagles Nest Wilderness 302 302 304 304 303 308 308 305 304 307 303 303

Emigrant Wilderness 242 245 248 253 254 258 259 259 258 256 250 245

Everglades NP 168 170 171 172 172 169 170 167 166 168 169 168

Fitzpatrick Wilderness 280 282 283 284 284 289 292 293 288 286 280 281

Flat Tops Wilderness 301 302 305 305 304 309 310 307 306 307 303 302

Galiuro Wilderness 254 255 258 262 262 263 259 256 258 259 257 252

Gates of the Mountains Wilderness 281 285 287 288 289 289 292 293 291 286 283 282

50 FLAG Phase I Report—Revised (2010)
Table 10. Monthly Average Natural Conditions Visual Range In Kilometers

Class I Area Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Gearhart Mountain Wilderness 262 269 274 277 280 283 287 287 285 277 266 263

Gila Wilderness 275 278 282 285 285 286 278 278 279 282 279 275

Glacier NP 224 228 230 231 231 231 235 235 231 228 225 225

Glacier Peak Wilderness 233 237 243 245 245 249 250 248 244 236 231 231

Goat Rocks Wilderness 243 249 254 256 259 263 265 263 258 248 241 241

Grand Canyon NP 267 269 273 278 280 282 281 277 278 277 273 269

Grand Teton NP 274 278 277 276 275 273 270 268 266 269 272 273

Great Gulf Wilderness 192 192 195 195 195 197 196 193 193 196 192 192

Great Sand Dunes NP & Pres 255 260 260 263 257 254 253 252 251 255 257 255

Great Smoky Mountains NP 184 185 187 188 188 190 192 193 190 188 185 184

Guadalupe Mountains NP 265 270 276 278 276 276 271 268 266 274 271 266

Haleakala NP 232 234 234 235 237 238 236 236 237 235 232 233

Hawaii Volcanoes NP 243 246 246 246 246 246 244 243 244 243 238 243

Hells Canyon Wilderness 224 229 234 237 238 239 242 243 241 235 226 223

Hercules-Glades Wilderness 178 180 182 182 179 179 180 179 178 180 179 178

Hoover Wilderness 259 263 265 271 273 276 278 277 276 274 268 262

Isle Royale NP 182 185 184 186 187 183 179 179 177 184 179 179

James River Face Wilderness 181 183 187 187 186 188 192 193 193 191 185 182

Jarbidge Wilderness 245 246 246 249 244 243 242 240 239 243 246 243

John Muir Wilderness 256 260 261 264 258 254 254 253 252 255 258 256

Joshua Tree NP 242 246 247 251 252 255 256 256 255 253 249 246

Joyce Kilmer-Slickrock Wilderness 186 187 187 189 189 190 190 189 188 189 189 188

Kaiser Wilderness 260 264 266 272 273 277 278 278 276 274 269 264

Kalmiopsis Wilderness 194 200 202 205 207 209 211 210 209 204 195 195

Kings Canyon 229 232 233 236 237 240 240 240 239 238 235 232

La Garita Wilderness 252 259 263 266 268 271 273 273 271 266 256 253

Lassen Volcanic NP 263 264 267 269 269 272 270 266 267 269 265 263

Lava Beds NM 244 250 253 257 258 261 261 261 260 258 251 246

Linville Gorge Wilderness 180 182 183 185 180 177 177 175 175 178 181 180

Lostwood Wilderness 229 230 228 234 235 232 232 234 235 233 227 227

Lye Brook Wilderness 196 198 197 197 196 195 194 192 191 192 195 195

Mammoth Cave NP 187 188 189 189 189 192 191 188 188 191 188 188

Marble Mountain Wilderness 251 255 256 254 242 235 237 249 248 252 254 250

Maroon Bells-Snowmass Wilderness 274 281 284 287 289 291 292 291 291 286 276 275

Mazatzal Wilderness 252 253 256 260 261 263 259 256 258 258 256 252

Medicine Lake Wilderness 231 232 231 236 237 235 235 237 237 236 230 229

Mesa Verde NP 264 267 271 277 276 281 276 272 275 275 270 266

Mingo Wilderness 166 169 172 174 173 173 176 176 174 171 166 166

Mission Mountains Wilderness 249 252 254 255 251 250 250 249 249 251 251 249

Mokelumne Wilderness 252 259 263 266 269 272 275 273 268 257 251 250

Moosehorn Wilderness 159 163 166 167 170 172 174 173 170 162 158 157

Mount Adams Wilderness 242 248 251 253 258 262 267 267 262 250 241 241

Mount Baldy Wilderness 261 266 269 275 276 280 281 281 279 277 271 264

Mount Hood Wilderness 241 249 253 256 259 262 265 265 262 255 243 241

Mount Jefferson Wilderness 237 240 240 238 239 238 234 232 230 234 235 235

 USFS–NPS–USFWS 51
Table 10. Monthly Average Natural Conditions Visual Range In Kilometers

Class I Area Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Mount Rainier NP 215 220 224 226 228 231 233 232 227 218 213 213

Mount Washington Wilderness 216 223 224 225 230 234 240 241 237 225 217 216

Mount Zirkel Wilderness 296 296 297 296 295 300 301 300 298 299 296 296

Mountain Lakes Wilderness 284 285 286 287 287 290 294 295 292 288 284 284

North Absaroka Wilderness 246 251 256 258 260 262 264 261 256 249 244 244

North Cascades NP 243 246 246 247 246 241 243 240 240 242 243 242

Okefenokee Wilderness 162 166 168 169 174 173 176 172 169 163 160 161

Olympic NP 233 235 235 238 231 230 228 226 225 230 234 231

Otter Creek Wilderness 180 183 188 190 191 194 195 193 189 183 178 178

Pasayten Wilderness 269 271 274 277 276 279 276 272 272 276 272 269

Pecos Wilderness 294 297 303 308 310 313 307 302 304 305 300 294

Petrified Forest NP 269 271 274 279 280 282 278 275 276 277 274 270

Pine Mountain Wilderness 238 238 238 247 248 251 252 251 251 249 248 244

Pinnacles NM 211 215 216 222 223 226 225 224 224 223 219 214

Point Reyes NS 128 134 133 132 130 127 122 119 117 121 124 126

Presidential Range-Dry River Wilderness 186 188 189 191 192 192 192 191 190 191 192 190

Rawah Wilderness 297 296 297 296 294 298 300 299 297 299 296 297

Red Rock Lakes Wilderness 261 264 263 266 264 265 261 261 264 266 262 264

Redwood NP 176 182 187 191 192 196 204 206 201 192 180 177

Rocky Mountain NP 261 265 265 262 263 262 258 256 254 258 259 259

Roosevelt Campobello Int Pk 170 173 173 175 172 169 169 166 166 168 171 170

Saguaro NP 252 250 250 248 247 251 252 251 250 252 250 252

Saint Marks Wilderness 182 185 189 190 188 189 187 185 184 187 186 184

Salt Creek Wilderness 245 247 247 250 250 251 251 250 250 250 251 249

San Gabriel Wilderness 262 262 264 268 268 272 273 271 271 271 271 267

San Gorgonio Wilderness 253 255 258 262 262 263 258 254 257 258 256 251

San Jacinto Wilderness 247 247 248 250 250 252 253 251 250 251 252 250

San Pedro Parks Wilderness 280 284 285 286 285 279 277 276 278 281 281 279

San Rafael Wilderness 243 246 250 253 253 256 252 248 249 252 247 244

Sawtooth Wilderness 259 263 269 272 272 274 278 278 277 273 263 259

Scapegoat Wilderness 249 253 255 257 257 257 260 261 258 254 249 249

Selway-Bitterroot Wilderness 251 256 261 264 265 266 270 271 268 262 253 251

Seney Wilderness 179 182 181 182 183 180 178 175 175 178 177 177

Sequoia NP 230 232 232 234 236 239 240 240 239 238 234 233

Shenandoah NP 191 193 193 195 191 190 189 187 186 190 192 190

Shining Rock Wilderness 193 196 197 199 194 191 190 188 188 192 195 193

Sierra Ancha Wilderness 252 253 256 260 261 263 259 256 257 258 256 252

Simeonof Wilderness 138 138 143 141 138 133 128 127 135 144 142 138

Sipsey Wilderness 176 178 180 181 178 175 174 174 174 176 178 176

South Warner Wilderness 243 249 253 256 258 260 263 263 261 257 249 245

Strawberry Mountain Wilderness 227 233 239 242 244 248 252 252 248 238 228 226

Superstition Wilderness 254 256 259 262 263 264 261 258 259 260 258 254

Swanquarter Wilderness 172 174 174 176 174 171 170 169 170 171 173 172

Sycamore Canyon Wilderness 267 268 272 277 278 281 277 273 274 275 272 268

Teton Wilderness 280 282 283 285 285 288 291 292 289 286 281 281

52 FLAG Phase I Report—Revised (2010)
Table 10. Monthly Average Natural Conditions Visual Range In Kilometers

Class I Area Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Theodore Roosevelt NP 223 228 231 234 235 238 238 238 237 235 229 225

Thousand Lakes Wilderness 258 259 258 263 262 261 262 265 265 263 256 257

Three Sisters Wilderness 217 223 225 227 231 234 240 240 236 226 217 217

Tuxedni Wilderness 195 198 205 206 206 204 195 192 192 196 196 194

UL Bend Wilderness 235 236 236 237 238 238 240 242 241 238 234 235

Upper Buffalo Wilderness 177 180 182 182 178 178 179 179 177 179 179 177

Ventana Wilderness 213 215 216 223 225 227 227 227 226 225 223 218

Virgin Islands NP 188 189 190 188 187 188 187 185 185 184 183 185

Voyageurs NP 177 179 179 181 180 176 176 175 174 178 175 176

Washakie Wilderness 270 272 272 273 273 276 279 280 277 274 270 270

Weminuche Wilderness 272 273 276 277 277 281 280 276 276 279 275 273

West Elk Wilderness 298 301 305 308 308 312 309 305 306 308 303 300

Wheeler Peak Wilderness 296 300 306 308 307 309 303 300 299 304 301 297

White Mountain Wilderness 265 267 271 273 272 275 273 268 269 272 267 265

Wichita Mountains Wilderness 232 233 232 233 231 233 235 235 236 235 231 232

Wind Cave NP 246 248 250 250 247 249 252 250 247 249 248 246

Wolf Island Wilderness 173 175 176 177 176 172 172 170 170 171 173 172

Yellowstone NP 280 282 283 284 284 287 290 291 288 285 280 280

Yolla Bolly-Middle Eel Wilderness 246 251 254 258 259 262 261 260 260 258 251 248

Yosemite NP 243 245 246 252 253 257 259 259 258 256 251 246

Zion NP 247 249 254 257 259 262 262 260 260 258 254 250

 USFS–NPS–USFWS 53
3.4. Ozone

3.4.1. Introduction (Revised)

Ozone is an air pollutant that forms on warm, sunny days 

when precursor emissions—nitrogen oxides (NOx

) and 

volatile organic compounds (VOCs)—react in the presence 

of sunlight. Because ozone is a regional pollutant, precursor 

sources both near and far from FLM areas can contribute to 

ozone formation.

Ozone is phytotoxic, causing damage to vegetation 

throughout the world (Ashmore et al. 2004). Some plant 

species are more sensitive to ozone than are humans (EPA 

2007b). Ozone pollution has been shown to reduce plant 

growth, alter species composition, and predispose trees to 

insect and disease attack. Ozone also causes direct foliar 

injury to many plant species. Affected leaves are often 

marked with discoloration and lesions, and they age more 

rapidly than normal leaves (EPA 2007b). 

FLAG is intended to provide information to assist the 

FLMs in identifying ozone impacts to vegetation on lands 

they manage. Therefore, the objectives of this chapter 

are to document information currently known about 

vegetation response to ozone exposure, and to describe 

FLM procedures for responding to new source review 

(NSR) permit applications. If the FLMs have evidence that 

ozone is adversely impacting an area they manage, they will 

recommend that additional emissions of ozone precursors 

are minimized until those adverse impacts are mitigated. 

3.4.2. Ozone Effects on Vegetation (Revised)

Most ozone effects research has focused on agricultural 

crops. However, research has identified many native 

plants in natural ecosystems that are sensitive to ozone 

(EPA 1996e). Some of these ozone-sensitive plant species 

have been used as “bioindicators” of ozone to document 

phytotoxicity of ozone in the field due to ambient ozone. A 

listing of key literature describing known ozone effects on 

native vegetation is provided in Appendix G.

The definitions for ozone injury and damage used by FLMs 

are based on the classical definitions (for example, see 

Guderian 1977). Injury is all physical or biological responses 

to pollutants, such as change in metabolism, reduced 

photosynthesis, leaf necrosis, premature leaf drop, and 

chlorosis. Damage is reduction in the intended use or value 

of the biological or physical resource; for example, economic 

production, ecological structure and function, aesthetic 

value, and biological or genetic diversity that may be altered 

through the impact of pollutants. 

Ozone enters plants through leaf stomata. It oxidizes plant 

tissue, causing changes in biochemical and physiological 

processes. These biochemical and physiological changes 

occur within the leaf long before visible necrotic symptoms 

appear (Guderian et al. 1985). Plants must expend energy to 

detoxify ozone and repair injured tissue that could otherwise 

be used for growth or for maintenance of plant health. 

The injured plant cells eventually die if detoxification and 

repair cannot keep up with ozone uptake. The mesophyll 

cells under the upper epidermis of leaves are the most 

sensitive to ozone, and those are the first cells to die. The 

adjacent epidermal cells then die, forming a small black 

or brown interveinal necrotic lesion that becomes visible 

on the upper surface of the leaf. These visible lesions 

most frequently begin to develop on leaves that have just 

become fully matured, with older leaves on a stem showing 

increased amounts of injury. These lesions, termed oxidant 

stipple7

, are quite specific indicators that the plant has been 

exposed to ozone. Other plant symptoms that can result 

from exposure to ozone, with or without the presence of 

oxidant stipple, include chlorosis, premature senescence, 

and reduced growth. However, these symptoms are nonspecific for ozone since other stressors (e.g., disease, insects) 

can also cause them to occur. Further, these non-specific 

symptoms are difficult to quantify in natural ecosystems, 

although limited data are available from exposure response 

experiments to estimate growth losses from specific ozone 

exposures. In general, the only indicator that a FLM has 

to document that ozone has impacted vegetation is visible 

symptoms of injury such as oxidant stipple. 

In addition to affecting individual plants, ozone can also 

affect entire ecosystems. Research shows that plants growing 

in areas with high exposure to ambient ozone may undergo 

natural selection for ozone tolerance (EPA 2007b). The final 

result could be the elimination of the most ozone-sensitive 

genotypes from the area. Regardless of the amount of 

ozone exposure, the magnitude of plant response may vary 

depending on the geographic area because of changes in 

meteorological and climatic conditions, and differences 

in plant conditions in space and time. Factors of most 

importance that influence plant response to ozone are the 

species/genotype, soil moisture, and nitrogen availability. 

Other factors influencing plant response to ozone include 

nutrient status, atmospheric humidity, temperature, solar 

radiation, phenological stage of development, carbon 

dioxide concentrations, day length, regional climatic 

differences, other pollutant interactions, and population/

ecosystem interactions (EPA 2007b).

Changes in growth, ecosystem form or function, or 

biological or genetic diversity caused by ozone have been 

difficult to document in natural ecosystems. However, 

recent research in Great Smoky Mountains National Park 

showed that in years with high ozone, tree growth was 

7. Specific symptoms of ozone injury in some plant species are 

different. A few species develop white or tan rather than brown or black 

lesions. This is termed “fleck” or “weather fleck” instead of oxidant 

stipple. In conifers, ozone causes banding of necrotic and green tissue 

near the tips of older needles, termed “chlorotic mottle.” 

54 FLAG Phase I Report—Revised (2010)
significantly reduced and trees had increased rates of 

water loss (McLaughlin et al. 2007a). Increased water loss 

resulted in soil moisture depletion and reduced late-season 

streamflows (McLaughlin et al. 2007b). The experiment was 

conducted over a range of forest types and included several 

different tree species. These findings may have implications 

for climate change. Climate change is predicted to increase 

temperatures and drought conditions in some areas. Ozone 

may exacerbate the effects of drought by increasing water 

loss from trees. 

Given the difficulty in determining ozone-induced 

physiological or growth changes in natural ecosystems, 

FLMs will utilize as indicators of ozone effects on vegetation 

(1) symptoms that are clearly ozone induced such as oxidant 

stipple, and (2) ozone exposures that have been shown to be 

phytotoxic. 

3.4.3. Established Metrics to Determine 

Phytotoxic Ozone Concentrations (Revised)

EPA has set primary and secondary ozone standards to 

protect human health and welfare. On March 12, 2008, 

EPA revised the primary and secondary ozone standards 

to 0.075 ppm (8-hour standard). On January 6, 2010, the 

EPA proposed further strengthening of the primary (human 

health) ozone standard and establishing a new secondary 

ozone standard to protect ecosystems and sensitive plants 

(EPA 2010b). For questions regarding site specific issues 

the applicant is encouraged to consult with the FLM. More 

detailed discussions regarding other ozone metrics may 

be available on the respective agency web sites provided in 

section 3.4.7. 

3.4.4. Identification of Ozone Sensitive AQRVs or 

Sensitive Receptors (Revised)

FLMs have determined that given the high ecological, 

aesthetic, and intrinsic value of federal lands, special 

attention should be given to native species. Ideally, 

protection efforts would focus on the identification and 

protection of at risk native species in an area. Unfortunately, 

AQRV identification is limited by incomplete species 

inventories and/or lack of exposure/response data for most 

species of native vegetation. Sensitive species identification 

will improve as more information becomes available. In the 

meantime, the Agencies are providing lists of sensitive plant 

species for each Class I area, i.e., those species that have 

been observed to exhibit ozone symptoms at ambient ozone 

exposures. This information is available at the respective 

agency web sites (see below). However, those ambient levels 

have not necessarily occurred at the specific Class I area 

where the plants occur. 

Since FLAG 2000, the FLMs have acquired additional 

information regarding ozone effects to vegetation, including 

lists of ozone sensitive species. Much of this information is 

included in the NPS and FWS ARIS data base referenced 

previously, and will be updated as necessary. The ARIS web 

site is as follows:

- http://www.nature.nps.gov/air/permits/aris/index.

cfm

In addition, the NPS has evaluated the risk to vegetation 

from ozone exposure at approximately 270 park units. The 

ozone risk assessment can be found at:

- http://www.nature.nps.gov/air/Permits/ARIS/

networks/ozonerisk.cfm

Forest Service pertinent ozone information, including a list 

of ozone sensitive species, can be found at: 

- http://www.fs.fed.us/air

3.4.5. Review Process for Sources that Could 

Affect Ozone Levels or Vegetation in FLM Areas 

(Revised)

As mentioned above, NOx and VOC are ozone precursors. 

States and the EPA have based ozone control strategies 

in various parts of the country on the determination of 

which precursor is most likely to influence the formation 

of ozone. Information suggests that in areas where ozone 

formation is driven by VOC emissions, i.e., VOC-limited 

areas, VOC to NOx

 ratios are less than 4:1. In VOClimited areas, minimizing or reducing VOC emissions is 

the most effective means of limiting or lowering ozone 

concentrations. Conversely, in NOx

-limited areas, where 

VOC to NOx

 ratios are greater than 15:1, controlling NOx

emissions is most effective. It is generally thought that 

most rural areas of the U.S. are NOx

-limited, most or all of 

the time, with the possible exception of the rural areas of 

southern California. The FLMs do not have current data 

to show that all areas are not NOx

 limited, nor do they 

consider VOCs to be unimportant as ozone precursors. 

However, until there is enough information available for 

FLAG to determine whether ozone formation in each FLM 

area is primarily limited by NOx

 or VOC emissions, we will 

assume all FLM areas are NOx

-limited and will focus on 

control of NOx

 emissions. Where FLMs have information 

indicating a specific area is VOC limited, they will shift the 

ozone protection strategy to focus on VOC rather than NOx

emissions. 

The FLMs recognize that oxidant stipple can occur at 

hourly ozone concentrations that can be considered natural 

background levels (Singh et al. 1978). Many of the high 

hourly background concentrations can be attributed to 

stratospheric intrusions or stratospheric mixing in the upper 

troposphere (Singh et al. 1978); but stratospheric intrusions 

rarely occur in the middle and southern latitudes after May 

(Singh et al. 1980, Wooldridge et al. 1997), and thus do not 

coincide with the major portion of the growing season. 

 USFS–NPS–USFWS 55
However, oxidant stipple has been observed on foliage in 

the spring when these intrusions can occur. In general, 

oxidant stipple observed on foliage from June through 

September cannot be attributed to natural background 

ozone from stratospheric sources. Low levels of ambient 

ozone may occasionally occur in the troposphere from nonanthropogenic and non-stratospheric sources. 

The occurrence of oxidant stipple necrosis on plant foliage 

may indicate further ozone induced physiological and 

growth impacts. Point sources emit precursors that could 

produce ozone at the FLM area, and increased ozone could 

induce further injury or damage to vegetation. However, we 

assume that restriction on increases in ozone precursors will 

prevent additional ambient ozone and subsequent increases 

in injury or damage to vegetation in FLM managed areas. It 

is important that ambient ozone monitoring be conducted 

by the State or Local air pollution control agency or by the 

FLM to determine the seasonal ozone exposure. 

FLM actions or specific requests on a permit application will 

be based on the existing air pollution situation at the FLM 

area(s) that may be affected by the source. Some FLMs may, 

with appropriate documentation, rely on growth loss rather 

than foliar necrosis to make an adverse impact finding. 

Each FLM will determine if actions are warranted to limit 

emissions that might lead to increased ambient ozone, based 

on the expected impact of ozone in their particular area.

FLM response will depend on whether or not:

- ozone specific vegetation effects have been 

documented in the area (as evidenced by foliar injury 

or damage to vegetation); 

- ozone exposure levels occurring in the area are high 

enough that they could affect vegetation (i.e., ozone 

exposures are at levels shown to be phytotoxic).

For a project that exceeds the initial annual emissions over 

distance (Q/D) screening criteria, Figure 6 outlines the 

general FLM review process for responding to NSR permit 

applications based on ozone exposure and vegetation 

effects at the receptor site. As noted in Figure 6, ambient 

ozone concentrations are considered along with data from 

exposure response studies (EPA 2007b) to determine 

whether a source will cause or contribute to phytotoxic 

ozone levels (i.e., levels toxic to plants) at the affected site. 

The FLM may ask the applicant to calculate the ozone 

exposure values if these data are not already available. Ozone 

damage to vegetation is determined from field observations 

at the impacted site.

Management decisions regarding acceptance of an existing 

or future ozone exposure will be area-specific and may differ 

significantly between agencies, or even regionally within 

agencies. Each FLM will determine if injury and/or damage 

are necessary to warrant action, based on the expected 

impact in the area they manage. The decisions are based on 

the FLM interpretation of regulations, past experience in the 

NSR arena, availability of ozone effect exposure/response 

information for species that occur in the area, and other 

factors. The FLM may also consider current trends in ozone 

exposures and meteorological conditions during peak ozone 

exposures (because dry soil conditions may induce plants 

to close stomates to limit water loss, thus limiting ozone 

uptake), as well as expected reductions in ozone precursor 

emissions. The FLM will negotiate with the NSR permit 

applicant and the permitting authority regarding possible 

mitigation strategies (e.g., using more efficient emissions 

control technologies, obtaining emission offsets, etc.). 

3.4.6. Further Guidance to FLMs (Revised)

As mentioned above, limited information about ozone 

exposure/response relationships in plants and lack of an 

ozone source/receptor model make it difficult to protect 

FLM areas from the effects of ozone from new sources. 

However, there are other area-specific gaps in information 

that also limit protection efforts. It is important for local 

land managers to attempt to collect the missing information. 

This section provides guidance specifically to FLMs on what 

types of data should be collected and how the data could be 

collected.

Identifying and Monitoring Ozone-sensitive AQRVs

Although many FLM areas have identified ozone-sensitive 

plant species in their areas, most areas need more details 

regarding plant species location and abundance. FLAG 

recommends FLMs gather this information, where needed, 

and refine their lists of area-specific ozone-sensitive plants. 

The FLMs have placed ozone sensitive plant species lists 

for many of their areas in the NRIS-AIR or Air Resources 

Information System databases.

FLAG recommends that once local FLMs have developed 

lists of potentially sensitive AQRVs specific for their site, they 

conduct surveys to detect the presence of ozone-induced 

foliar injury on the selected species. The USFS Forest Health 

Monitoring (FHM) Program and the National Park Service 

Inventory and Monitoring Program have developed foliar 

injury survey protocols and QA/QC procedures that can 

be used to collect this information. Another resource is 

the foliar injury training module developed by the NPS Air 

Resources Division and The Pennsylvania State University, 

available at http://www.nature.nps.gov/air/edu/O3Training/

index.cfm. This module helps field staff identify and quantify 

ozone injury symptoms on plant foliage. Field crews should 

obtain proper training and field experience in identifying 

foliar injury symptoms before surveys can be conducted. 

Ideally, to verify ozone-induced foliar injury symptoms in 

the field, exposure/response fumigation studies should be 

conducted on these species, using concentrations that reflect 

current ambient exposure. Plants should also be tested at 

56 FLAG Phase I Report—Revised (2010)
higher exposures, simulating increased levels of ambient 

ozone that might occur in the future. Due to the expense 

of constructing and operating such systems, it would be 

most appropriate for agencies to join resources and develop 

regional fumigation facilities. At a minimum, such facilities 

should be constructed both in the eastern and western U.S., 

since ambient conditions at an eastern facility might not be 

appropriate for western species and vice versa. 

Ambient Ozone Monitoring

Many FLM areas do not currently have either on-site or 

nearby ambient ozone monitoring data. FLAG recommends 

that local FLMs make every effort to collect this information 

and that they use quality-assured ambient ozone monitoring 

protocols developed by the EPA and the state air quality 

agency. Continuous monitoring is desirable to determine 

the temporal dynamics of ozone exposure for vegetation. 

Unfortunately, continuous monitoring is expensive and 

requires electric power that is often not available in or near 

remote FLM areas. When installing a continuous monitor is 

not an option, FLAG recommends use of passive monitors. 

Passive monitors give total exposure loading values (SUM00) 

for a specified period of time. The data are useful for 

indicating year-to-year changes in total ozone exposure 

at an individual site, and for indicating where continuous 

monitors should be installed. However, FLMs recognize the 

limitation of passive samplers in relating ozone exposure to 

plant response.

Figure 6. FLM Assessment of Potential Ozone Effects from New Emissions Source (Revised) 

*Q/D test only applies to sources located greater that 50 km from a Class I area.

**Note: Ambient ozone concentrations are considered along with data from exposure response studies (EPA 2007b) to determine whether a source 

will cause or contribute to phytotoxic ozone levels (i.e., levels toxic to plants) at the affected site. 

 USFS–NPS–USFWS 57
3.4.7. Ozone Air Pollution Web Sites (Revised)

EPA ozone information:

- http://www.epa.gov/ozone

- http://www.epa.gov/castnet

NPS ozone information:

- http://www.nature.nps.gov/air/permits/aris/index.

cfm

- http://www.nature.nps.gov/air/Monitoring/network.

cfm

- http://www.nature.nps.gov/air/studies/ecoOzone.cfm

FWS Information:

- http://www.fws.gov/refuges/whm/AirQuality/index.

html

U.S. Forest Service information:

- http://www.fs.fed.us/air 

- http://www.fs.fed.us/psw/programs/atdep

Ozone effects research, USDA ARS, North Carolina: 

- http://www.ars.usda.gov/Main/docs.htm?docid=8453

 Ozone exposure metrics for vegetation:

- http://www.asl-associates.com/

3.5. Deposition 

3.5.1. Introduction (Revised)

Atmospheric deposition has been studied extensively 

throughout the world, beginning in the 1800’s in England, 

Sweden, Norway, and Germany. Research has primarily 

focused on the deposition of acidic pollutants and long-term 

acidification. Many publications describe current conditions, 

monitoring and modeling methods, and the results of 

acidification experiments. In the United States, research on 

acidification was first begun in 1962 at Hubbard Brook, New 

Hampshire. Subsequent work in the Adirondack lakes and 

other areas furthered the understanding of acid deposition 

effects. It is now recognized that, in addition to causing 

acidification, deposition of pollutants can affect many 

ecosystem characteristics, including nutrient cycling and 

biological diversity. 

Although much progress has been made to control sulfur 

dioxide and nitrogen oxide emissions, deposition of sulfur 

(S) and nitrogen (N) compounds continues to be a problem 

in North America and Europe (EPA 2007a). As a result, 

certain sensitive freshwater lakes and streams continue to 

lose acid-neutralizing capacity (ANC) and sensitive soils 

continue to be acidified. Other ecosystems, including forests, 

grasslands, estuaries, and N-limited lakes exhibit unwanted 

fertilization and other effects from excess N deposition. 

In this section, the Agencies focus on S and N deposition 

and associated effects to ecosystems, but other potentially 

damaging pollutants are routinely deposited. For example, 

mercury emitted from coal-fired powerplants, incinerators, 

and other sources deposits into ecosystems and accumulates 

to sometimes toxic levels in fish and wildlife (EPA 1997). 

EPA sampled fish from over 75,000 lakes nationwide and 

found that mercury concentrations in large predatory fish 

exceeded the human health screening value for mercury in 

nearly half the lakes (EPA 2009b). The Great Waters Program 

found that, in addition to mercury, airborne toxics including 

dioxins, furans, polycyclic organic matter, polychlorinated 

biphenyls (PCBs), and pesticides are deposited widely across 

the Great Lakes, the Chesapeake Bay, Lake Champlain, 

and many coastal estuaries, posing ecological and human 

health risks (EPA 2000a). Even in relatively remote western 

and Alaska national parks, deposition has increased 

concentrations of certain toxic compounds in fish and 

wildlife above health thresholds (Landers et al. 2008).

Federal Land Managers (FLMs) have documented the 

effects of S and N deposition on many air quality related 

values (AQRVs). Documented effects include acidification 

of lakes, streams, and soils; leaching of nutrients from soils; 

injury to high-elevation spruce forests; changes in terrestrial 

and aquatic species composition and abundance; changes 

in nutrient cycling; unnatural fertilization of terrestrial 

ecosystems; and eutrophication of estuarine and some lake 

systems. FLMs recognize that other undocumented effects 

may also be occurring. 

The FLAG deposition subgroup was formed to identify 

common approaches among these agencies for evaluating 

atmospheric deposition and its effects on AQRVs. In 

addition, the subgroup was directed to recommend methods 

for establishing critical deposition loading values (“critical 

loads”) and, where possible, recommend such critical loads 

for specific areas. These tasks were assigned to Phase I or 

Phase II, depending on their degree of difficulty.

During the scoping process, the FLAG Deposition 

Subgroup determined that Phase I tasks would include the 

summarization of information currently available about 

deposition and its effects on FLM areas and the development 

of recommendations on methods to model and evaluate 

current and future deposition and its effects on AQRVs. In 

addition, critical load values, where available from previous 

FLM guidance documents, would be referenced. FLMs 

agreed that site-specific AQRV and critical load information 

would be maintained on FLM web sites, rather than 

included in the Phase I report. In this way, the information 

can be updated and the most recent versions made quickly 

available to the public. Some of this information is already 

available on FLM web sites, and the FLMs are committed to 

entering remaining available information as soon as possible.

58 FLAG Phase I Report—Revised (2010)
The subgroup recognizes that the development and 

refinement of site-specific critical load values for all FLM 

areas are crucial for AQRV protection. However, because 

of the complexity of this undertaking, and the lack of 

information for many areas, it was deferred to future FLAG 

development. 

Future deposition effects work will involve developing 

methods for establishing critical deposition loading values 

for FLM areas, and establishing critical loads for areas 

with adequate information. For areas lacking sufficient 

information to determine critical loads, strategies will 

be developed to obtain needed information. Previously 

established critical loads will be reviewed and refined 

as necessary. The subgroup will also explore alternative 

methods for estimating background deposition rates, 

including extrapolation techniques or modeling that 

considers the spatial scale of ecosystems and differences 

in elevation. Methods for addressing problems with dry 

deposition and cloud and fog deposition measurements will 

also be considered. In addition, future work may provide 

research or monitoring recommendations to improve our 

understanding of deposition and its effects, including effects 

on cultural resources.

3.5.2. Current Trends in Deposition (Revised)

Title IV of the Clean Air Act was passed by Congress as 

part of the 1990 Clean Air Act Amendments to reduce 

emissions of sulfur dioxide and nitrogen oxides from fossil 

fuel-burning power plants in order to reduce deposition of S 

and N compounds and protect ecosystems suffering damage 

from acid deposition. Since the implementation of Title IV, 

wet sulfate deposition, a major component of acid rain, has 

significantly decreased. Average annual sulfate deposition in 

the Northeast in 2000–2002 was 40% lower than it was in 

1989–1991, deposition in the mid-Atlantic and Midwest was 

35% lower, and deposition in the Southeast was 25% lower 

(NAPAP 2005).

Wet nitrate deposition, on the other hand, has not decreased 

regionally from historical levels because of the relatively 

moderate reduction in nitrogen oxides from power plants 

and the continuing large contribution (over 50% of total 

nitrogen oxides emissions) from other sources of nitrogen 

oxides such as vehicles and nonroad vehicles (NAPAP 2005). 

Deposition monitoring data can be used to identify 

decreases in S and N deposition due to decreases in 

emissions. The National Atmospheric Deposition Program 

(NADP) provides one of the best and most comprehensive 

long-term records of wet deposition chemistry in the 

U.S. Annual reports on deposition nationwide as well as 

deposition trend plots for all NADP sites are available at 

http://nadp.sws.uiuc.edu/. An analysis of long-term trends 

(1985-2004) in precipitation chemistry from NADP sites 

across the U.S. found that concentrations of sulfate have 

decreased in nearly all parts of the country. Nitrate, however, 

has increased in many areas and ammonium, another 

component of N deposition, has also increased significantly 

in many areas, particularly in the West (Lehmann et al. 

2005). Publications on trends in deposition are available 

from NADP at:

- http://nadp.sws.uiuc.edu/lib/

In this chapter, it is assumed that S is deposited into the 

environment primarily as sulfate ion and N is deposited 

primarily as inorganic nitrate and ammonium ions. Other 

ionic forms of S and N occur in the atmosphere, but 

information on their deposition into ecosystems is limited. 

For example, organic N in deposition is not routinely 

measured because of the expense and complexity of the 

measurements. Organic N includes peroxyacetyl nitrate 

(PAN) (produced in the atmosphere by nitrogen oxides 

and hydrocarbon reactions), urea, and amino acids. Both 

natural and anthropogenic processes contribute to organic 

N formation, including industry, agriculture, biomass 

burning, and biological activity. Limited monitoring suggests 

that organic N deposition varies widely, but on average 

constitutes about 30 percent of total N (Neff et al. 2002)

3.5.3. Identification and Assessment of AQRVs 

(Revised) 

AQRVs sensitive to pollutant deposition have been identified 

in various documents published by the USFS, NPS, and 

FWS, which are listed in the ‘General References’ of 

Appendix G of this report. The FLMs have previously used 

a combination of approaches to identify AQRVs, including 

national and regional workshops, regional reviews, and 

site-specific studies. AQRV identification was based on 

information from peer-reviewed scientific literature and 

expert judgment. Because information on AQRVs may 

change as new data become available, the FLMs agree that 

AQRV information will be made available on FLM web sites 

to allow for updating and improve accessibility, as discussed 

in the Introduction to this chapter.

Information on AQRVs for many USFS Class I areas can be 

found at

- http://www.fs.fed.us/air

The USFS is currently adding to and updating this 

information. 

Information on AQRVs for NPS Class I areas and some FWS 

Class I areas is available from NPS Air Web at: 

- http://www.nature.nps.gov/air

Information on AQRVs for FWS Class I areas is under 

development at: 

- http://www.fws.gov/refuges/whm/AirQuality/index.

html

 USFS–NPS–USFWS 59
FLMs recommend that permit applicants consult with 

the appropriate FLM to determine the need for an AQRV 

analysis and, if applicable, the methods for the analysis.

All FLMs use a similar conceptual approach to identify 

AQRVs that reflects the FLMs’ interest in maintaining the 

integrity of ecosystem structure and function and protecting 

the most sensitive ecosystem components. AQRVs can 

be categorized by the type of ecosystem in which they 

are found, such as terrestrial, freshwater, and estuarine 

ecosystems. Each ecosystem and its AQRVs responds 

somewhat differently to deposition and approaches to 

evaluating deposition effects must therefore be developed 

accordingly. In terrestrial ecosystems, detection of changes 

in production, decomposition, and nutrient cycling 

processes provide information on deposition stress. In 

aquatic and estuarine ecosystems, detection of changes in 

water chemistry and aquatic community composition and 

structure provide similar information. Table 11 summarizes 

AQRV indicators that may be used to assess effects in various 

ecosystems. 

Terrestrial, freshwater, and estuarine AQRVs are discussed 

below. In addition, methods to evaluate S- and N-induced 

deposition stress are discussed. 

Terrestrial Ecosystems

Terrestrial ecosystem AQRVs include flora, fauna, and 

soils. FLMs have identified, where possible, AQRVs, or 

characteristics of AQRVs, most likely to be sensitive to S 

and N deposition (“sensitive receptors”). For example, 

high-elevation spruce forests may be sensitive receptors. 

FLMs assess the condition of these sensitive receptors 

by evaluating some aspect of the receptor (the “sensitive 

receptor indicator” or “indicator”). For example, an 

indicator for high-elevation red spruce forests is the 

occurrence and extent of winter foliar injury. In general, 

the FLM has focused on deposition effects to vegetation 

and chemical receptors in terrestrial ecosystems, with little 

emphasis on fauna. In addition, there is increasing awareness 

among FLMs that certain soil fauna (e.g., microorganisms 

and invertebrates) are very sensitive to deposition and can be 

used as sensitive receptors. 

In terrestrial ecosystems, sulfate production is regulated 

primarily by chemical processes (Johnson et al. 1983) 

and it is rarely a limiting nutrient. Soil response to acidic 

deposition can be evaluated by monitoring the leaching of 

essential soil cations, soil acidification, and mobilization of 

ionic aluminum. These processes have been studied both in 

field and laboratory experiments, and are defined in detail 

in the literature (Mollitor and Raynal 1983; Richter et al. 

1983; Johnson et al. 1983; Reuss and Johnson 1986). Effects 

of S deposition can be detected by monitoring calcium 

and magnesium ions and S in the litter layer and surface 

soils; calcium, magnesium, potassium, and sulfate ions in 

soil solution; cation exchange capacity (CEC); and base 

saturation. 

In general, biological AQRVs do not provide reliable 

indicators of S deposition in terrestrial ecosystems except 

under extreme S deposition. Lichens have been used in 

some areas as biomonitors to demonstrate spatial trends 

in S deposition, particularly in areas with pronounced S 

deposition gradients. For example, isotopic analysis of 

lichens from Mt. Zirkel Wilderness, Colorado, indicated that 

power plants in the nearby Yampa Valley were the source of 

elevated S in the lichens (Jackson et al. 1996).

Unlike S, the production and mobility of N in ecosystems 

is regulated almost entirely by biological processes. N is a 

limiting nutrient in many terrestrial ecosystems. In these 

ecosystems, growth of plants is limited by N availability; 

additional N from atmospheric inputs increases plant 

growth. Most ecosystems can retain and process significant 

additions of N, with resulting increases in production and 

changes in species diversity, biomass, and nutrient cycling. 

However, these changes are usually considered to be 

inconsistent with desired ecosystem conditions for natural 

areas. The ability to retain and process N varies significantly 

Table 11. Indicators for monitoring and evaluating effects from deposition of S and N (Revised)

Ecosystem Indicators for Sulfur Deposition

Freshwater Chemical change (ANC depression), changes in phytoplankton and benthic community composition, species 

diversity, biomass

Terrestrial Leaching of soil cations, soil acidification, mobilization of aluminum ions; Lichen species and vitality

Estuarine Saltwater not sensitive to S deposition; leaching of nutrients may occur in sandy nearshore soils

Ecosystem Indicators for Nitrogen Deposition

Freshwater Chemical change (ANC depression), changes in phytoplankton and benthic community composition, species 

diversity, biomass

Terrestrial Changes in: litter and soil carbon and N dynamics; biomass; soil N processes; litter decomposition rates; soil 

microbe functional groups; soil organic matter quality and quantity; soil water chemistry; Lichen species and 

vitality

Estuarine Changes in: phytoplankton species composition and biomass; aquatic invertebrates; seagrass health and 

distribution; nutrient ratios; dissolved oxygen; trophic status

60 FLAG Phase I Report—Revised (2010)
depending on watershed successional status, site and fire 

history, soil conditions, vegetation, and other non-human 

factors. When N inputs exceed an ecosystem’s assimilation 

capacity, N is lost or leached, usually as nitrate, from the soil 

and can be detected in adjacent streams or lakes. This may 

occur following a major disturbance such as fire, logging, 

land use change, grazing, agriculture, or where atmospheric 

N deposition or experimental inputs exceed what the 

ecosystem can assimilate (Fenn and Dunn 1989; Fenn 1991, 

Fenn et al. 1996; Adams et al. 1997). 

Studies in northern Europe (Dise and Wright 1995) found 

that European forests leached detectable levels of nitrate at 

inputs of about 10-25 kilograms N per hectare per year (kg 

N ha1yr-1

). Tundra and high-elevation alpine sites may leach 

N at much lower levels of input. Mountain watersheds in 

the western U.S. show signs of N leakage at wet deposition 

levels of 3-5 kg N ha-1yr-1 (Eilers et al. 1994; Williams et al. 

1996; Williams and Tonnessen, in review). However, even 

high elevation, poorly vegetated ecosystems with limited soil 

development can process more than 80% of the atmospheric 

N input before it reaches the aquatic system (Campbell et 

al. 1995, Kendall et al. 1995). Although nitrogen leaching 

has often been used as an indicator of excess N deposition, 

major changes occur in below- and above-ground biomass, 

species diversity, and nutrient cycling long before N input 

levels are sufficient to cause nitrate leaching (NAPAP 1993; 

Tilman et al. 1997; Vitousek et al. 1997). For example, with 

ambient deposition rates of 7-10 kg N ha-1

yr-1, a Minnesota 

Long-Term Ecological Research (LTER) grassland study 

observed shifts from native, warm-season grasses to low 

diversity mixtures dominated by cool-season grasses and 

a greater than 50% decline in species richness (Wedin 

and Tilman 1996; Tilman et al. 1997). Significant losses 

in terrestrial diversity may have already occurred over 

extensive areas of the U.S., particularly in forest understories, 

shrublands, grasslands, and in soil microbial communities. 

(Suding et al. 2005; Weiss 2006).

Because significant ecological changes may occur before 

nitrate loss can be detected, more sensitive indicators than 

nitrate leaching are needed to evaluate N deposition effects. 

Such indicators include changes in carbon and N dynamics 

of litter and soil and biomass (Aber and Driscoll 1997; 

Magill et al. 1997). With knowledge of inputs and smallscale N fertilization studies, changes in soil organic matter 

quality and quantity in response to N deposition can be 

evaluated. Soil microbial communities control the quantity 

and quality of N available to ecosystems and may be very 

sensitive indicators of N deposition. Changes in soil microbe 

functional groups or biomass may provide good estimates 

of ecosystem critical loads and incremental effects. Soil N 

mineralization, small root growth, and carbon:nitrogen 

ratios of soil and microbial biomass are also sensitive to 

N deposition. Evidence suggests that current deposition 

rates may alter the production of dissolved organic carbon 

and organic N compounds in soils, which are important 

nutrient and energy sources for both terrestrial and aquatic 

ecosystems (Grandy et al. 2008; Aber et al. 1995; Sinsabaugh 

et al. 2005). These could also be used as indicators of N 

deposition effects. However, because there are many other 

variables that also affect soil processes, it may be very 

difficult to discern effects on any soil indicators that are 

solely attributable to N. 

Freshwater Ecosystems

AQRVs in freshwater ecosystems include lakes and streams 

and their associated flora and fauna. Sensitive receptors 

include water chemistry and clarity, phytoplankton, 

zooplankton, fish, amphibians, macroinvertebrates, 

and benthic organisms. Water chemistry indicators that 

respond to deposition include pH, ANC, conductance, 

cations and anions, metals, and dissolved oxygen. Physical 

indicators, such as water clarity, and biological indicators, 

including species diversity, abundance, condition factor 

and productivity of fish, amphibians, macroinvertebrates, 

and plankton can also be used to detect deposition effects 

in aquatic ecosystems. Much research has been done on 

the sensitivity of aquatic species to deposition, many of 

which are discussed in the 1990 National Acid Precipitation 

Assessment Program (NAPAP) State of Science report 

(NAPAP 1991a) and the 1998 NAPAP report (NAPAP 1998).

Sulfur is not a limiting nutrient in freshwater ecosystems. 

However, there are regions of the U.S. where a relatively 

high percentage of surface water is sensitive to current acidic 

inputs. These include portions of the Northeast (particularly 

Maine and the Adirondack and Catskill Mountains), 

southeastern streams, and some high elevation western 

lakes, particularly in the Rocky Mountains (NAPAP 2005). 

There are a number of FLM areas in acid-sensitive regions, 

including national parks, national forests, and wilderness 

areas. In these areas, S deposition can cause decreases 

in ANC and pH. For these sensitive or low-ANC waters, 

the best approach to quantify S deposition effects is the 

procedure currently used, monitoring changes in ANC and 

pH. 

Nitrogen deposition, like S deposition, can cause episodic 

acidification of surface water in certain sensitive highelevation ecosystems that have low-ANC headwater lakes 

and streams. Episodic acidification occurs in these areas 

when deposition is as low as 3-5 kg N ha-1yr-1 (Williams et al. 

1996).

Estuarine Ecosystems

AQRV sensitive receptors in estuarine ecosystems include 

plankton, sea grasses, and water chemistry and clarity. 

Associated coastal forest and dune soils may also be useful as 

sensitive receptors. Water and soil nutrient concentrations, 

phytoplankton species composition and abundance, sea 

 USFS–NPS–USFWS 61
grass health, and dissolved oxygen concentrations can be 

used to evaluate deposition effects. 

In estuaries, S is not a limiting nutrient. In addition, 

estuarine waters are highly buffered and, therefore, not 

subject to acidification. However, many coastal forest and 

dune soils are dominated by sandy soils that are sensitive 

to leaching of limiting nutrients because of very low cation 

exchange capacity (Au 1974). Monitoring for change in 

estuarine areas with high S deposition should therefore focus 

on soil ion mobility. As soil calcium and magnesium levels 

are generally adequate because of deposition from marine 

sources, potassium is likely the only limiting nutrient subject 

to significant loss by sulfate leaching. 

The role of N in estuaries is probably the best-documented 

example of anthropogenic alteration with a literature record 

dating back to the 1950s. Production and use of fertilizers, 

land use changes, and fossil fuel combustion have greatly 

increased the available N, normally a limiting nutrient, 

which enters coastal waters (Galloway et al. 2003). This has 

increased estuarine production and accelerated the process 

of eutrophication. Eutrophication can result in dramatic 

algae blooms, anoxia, the production of toxic hydrogen 

sulfide gas, and species extirpation in estuarine ecosystems. 

Human induced eutrophication has been documented for 

many areas along the Atlantic and Gulf coasts, including the 

Chesapeake Bay, Tampa Bay, Sarasota Bay, Florida Bay, and 

Long Island Sound.

A number of FLM areas along the Atlantic and Gulf coasts 

contain significant coastal waters that may be sensitive 

to eutrophication. Little is known about excess N effects 

in most of these areas, although eutrophication is well 

documented in Florida Bay, located in Everglades National 

Park. Also, recent evidence indicates that coastal waters in 

Chassahowitzka Wilderness (Florida) experience N-induced 

algal blooms (Dixon and Estevez in draft). In most coastal 

waters, 10-45% of the N entering the system is atmospheric, 

either from direct deposition to surface water or deposition 

to the watershed. Complete elimination of atmospheric 

N inputs would not entirely mitigate ecosystem change 

due to N because of the substantial contributions from 

agricultural and urban runoff. However, for most estuaries, 

any reduction in N input would be beneficial in restoring 

ecosystem structure and function.

The monitoring procedures recommended, and currently 

used, in estuaries are similar to those used in freshwater, 

with emphasis on incremental changes in plankton, aquatic 

plant, benthic, and invertebrate community composition; 

species diversity, distribution, and biomass; and ecosystem 

trophic status.

Significance of Long-Term Monitoring to Evaluate 

Trends and Validate Modeling

Long-term monitoring is critical to evaluate trends in 

deposition and deposition effects. Monitoring programs 

should concentrate not only on areas with high past and/or 

present sulfate, nitrate, or ammonium deposition, but also in 

areas that are very sensitive to deposition and in areas where 

deposition is expected to increase. For selected monitoring 

sites, the FLM should (1) obtain ion deposition data for 

the site, as from NADP or CASTNet, (2) identify sensitive 

AQRVs and appropriate variables to monitor, (3) evaluate 

the present condition of the sensitive AQRVs, (4) determine 

the degree to which results from one site can be extrapolated 

to other FLM areas in the region, and lastly (5) implement 

a long-term monitoring program, using carefully selected 

variables. 

Long-term monitoring data are also needed to support and 

validate models used to predict deposition and deposition 

effects, including the effects of increases or decreases of S 

and N on ecosystems. Long term studies in both aquatic 

and terrestrial ecosystems such as Hubbard Brook, Lake 

Tahoe, and the Experimental Lakes Area have provided 

useful information for modeling (Bormann and Likens 

1967; Holm-Hanson et al. 1976; Likens and Bormann 1977, 

Leonard et al. 1979; Byron and Eloranta 1984; Schindler et 

al. 1985; Schindler 1987; Schindler et al. 1990; Jassby et al. 

1995). NAPAP and the National Science Foundation LTER 

program have addressed monitoring to meet modeling needs 

in both terrestrial and aquatic ecosystems.

Data requirements to support models vary, but the quality 

of input data will determine the quality of a model’s 

predictions. Modeling is further discussed in the ‘Other 

AQRV Identification and Assessment Tools’ (see section 

3.5.5).

3.5.4. Determining Critical Loads (Revised)

FLAG 2000 introduced the concept of critical loads as it 

relates to air resource management in Class I areas. Since 

FLAG 2000 was published, the Agencies have adopted the 

widely used definition of critical load, “the quantitative 

estimate of an exposure to one or more pollutants below 

which significant harmful effects on specified sensitive 

elements of the environment do not occur according to 

present knowledge” (Nilsson and Grennfelt 1988). Critical 

loads have been widely accepted in Europe and Canada as a 

basis for negotiating control strategies for transboundary air 

pollution (Posch et al. 1997). 

In Canada, researchers have estimated the critical loads of S 

in wet deposition necessary to protect moderately sensitive 

lakes in eastern provinces. That value, equivalent to 6.7 kg 

ha-1yr-1 of S in wet deposition, was used by Canada to argue 

for the U.S. to implement the Clean Air Act Amendments of 

1990, which call for the initial reduction of sulfur dioxide 

62 FLAG Phase I Report—Revised (2010)
emissions in the eastern U.S. and later from all electric 

utilities nationwide. With additional data on lake and stream 

chemistry available for sensitive systems in Nova Scotia, 

Ontario, and Quebec, the Canadians are now recommending 

a more stringent critical load, equivalent to 2.7 kg ha-1yr-1 of 

wet deposition S.

In both European countries and in North America, attention 

has expanded beyond ecosystem damage caused by S 

deposition to ecosystem damage caused by N deposition. 

In some European forests, chronically high N deposition 

has exceeded the assimilation capacity of local ecosystems, 

resulting in the release of nitrate into surface waters (Dise 

and Wright 1995). Watersheds that are leaking nitrate into 

surface waters during the growing season, are referred to 

as “N saturated” (Aber et al. 1989). Nitrogen saturation 

has been linked to forest decline in Europe (Schulze 

1989). Based on a set of regional N addition experiments 

conducted at sites in northern Europe (NITREX), Wright 

(1995) recommended a N critical load of less than 10 kg 

ha-1yr-1 to protect European forests and fresh waters from 

N saturation. However, this critical load does not protect 

ecosystems from the changes caused by N deposition prior 

to actual N saturation, including shifts in composition 

and abundance of soil fauna species and alterations in soil 

chemistry. (Fenn et al. 2003; Driscoll et al. 2003)

In the United States, two states have attempted to set 

deposition standards or critical loads to protect sensitive 

ecosystems. In 1982, the State of Minnesota passed the 

Acid Deposition Control Act to limit wet sulfate deposition 

to 11 kg ha-1yr-1, which is equivalent to 3.7 kg S ha-1yr-1. 

At this sulfate level, precipitation pH was likely to remain 

above 4.7, which would protect lakes with ANC less than 50 

microequivalents per liter (μeq l-1). 

In 1989, the California legislature adopted the Atmospheric 

Acidity Protection Act, which required the Air Resources 

Board (CARB) to “develop and adopt standards, to the 

extent supportable by scientific data, at levels which are 

necessary and appropriate to protect public health and 

sensitive ecosystems from adverse effects resulting from 

atmospheric acidity” (CARB 1993). An assessment of 

existing data identified the high elevation watersheds, 

surface waters, and mixed conifer forests of the Sierra 

Nevada and the Los Angeles Basin as sensitive ecosystems. 

CARB analyses suggested that appropriate standards would 

include a critical load value for inorganic N to protect 

forests, and critical loads for both N and S to protect poorly 

buffered lakes and streams. However, no acidity standards to 

protect human health or critical loads to protect ecosystems 

have been set in California to date.

The Clean Air Act Amendments of 1990, Title IV, section 

404, called on the Environmental Protection Agency (EPA) 

to prepare a report on the feasibility and effectiveness of 

setting deposition standards nationwide to protect sensitive 

aquatic and terrestrial resources. The completed report 

includes a number of modeling analyses that project the 

effect of reductions in both S and N deposition in areas 

studied during NAPAP. EPA concluded that deposition 

standards could not be set at this time because of 1) the lack 

of clearly defined policy regarding appropriate or desired 

goals for protecting sensitive aquatic or terrestrial resources, 

and 2) key scientific uncertainties, particularly regarding 

nitrogen watershed processes. In addition, EPA recognized 

that a national deposition standard might be inappropriate 

because of differences among ecosystems. However, in 

response to public comments on the report, EPA stated that 

“Given an adequate level of monitoring and assessment data, 

Class I areas could serve as potential targets for standard 

setting activities.” (EPA 1995) 

Since FLAG 2000, other U.S. agencies and organizations 

have started considering how to work with critical loads. 

A National Academy of Sciences Report, Air Quality 

Management in the United States (2004), recognized the 

potential of critical loads for establishing standards to 

protect ecosystems, prompting the EPA to explore critical 

loads as an accountability tool to assess ongoing programs. 

Also, in the 2005 Prevention of Significant Deterioration for 

Nitrogen Oxides Final Rule, EPA stated it would consider 

critical loads information from any state as part of their air 

quality management approach, including whether such an 

approach satisfies PSD requirements. (EPA 2005.) The U.S. 

has signed, but not ratified, the European Union’s protocol 

for establishing critical loads, contained in the 1999 Protocol 

to Abate Acidification, Eutrophication and Ground-level 

Ozone (AKA The Gothenburg Protocol), available at: 

- http://www.unece.org/env/lrtap/multi_h1.htm

In 2006, EPA held the Multiagency Critical Loads Workshop 

to share information on critical loads and to develop a broad 

federal strategy for planning, executing, and evaluating 

critical loads projects, and to consider critical load use 

in a policy or management framework. As a result of 

recommendations from the workshop, the Critical Loads 

Ad-Hoc Committee (CLAD) was formed to foster critical 

loads science and development. Information on CLAD 

and the Multiagency Critical Loads Workshop Report are 

available at:

- http://nadp.sws.uiuc.edu/clad/

In 2008, EPA used critical loads to assess progress under 

the Acid Rain and related programs. For the analysis, EPA 

compared critical loads exceedances in Adirondack lakes 

before and after implementation of acid rain controls (EPA 

2009a).

Critical Loads in FLM Areas (Revised)

In the Clean Air Act, as amended in 1977, Congress gave 

FLMs an “affirmative responsibility” to protect AQRVs 

in Class I areas from the adverse effects of air pollution. 

 USFS–NPS–USFWS 63
Congress’ intent was, “...In cases of doubt the land manager 

should err on the side of protecting the air quality-related 

values for future generations...” (Senate Report No. 95-127, 

95th Congress, 1st Session 1977). In an effort to ensure AQRV 

protection, FLMs have established critical loads for many 

FLM areas. FLMs agree that a critical load should protect 

the most sensitive AQRVs within each FLM area and should 

be based on the best science available. As new scientific 

information becomes available, critical loads should be 

reviewed and updated. Critical loads should ensure that no 

unacceptable change occurs to the resource.

A journal article published in the July 2005 issue of 

BioScience, entitled “Protecting Resources on Federal Lands: 

Implications of Critical Loads for Atmospheric Deposition 

of Nitrogen and Sulfur” (Porter, Blett, Potter, Huber 2005) 

provides an update on the Agencies’ perspectives with 

respect to critical loads. Among other things, the article 

describes the history of critical loads, the advances in science 

related to critical loads, and how to apply the concept 

of critical loads (including some specific case studies). 

Subsequent articles provide additional information and 

perspectives on critical loads (Burns et al. 2008; Dennis et al. 

2007). These and other articles and reports on critical loads 

are available from:

- http://www.nature.nps.gov/air/Studies/criticalLoads/

index.cfm

- http://www.nrs.fs.fed.us/clean_air_water/clean_

water/critical_loads/

FLMs have used a combination of approaches to establish 

critical loads, including national and regional workshops, 

regional reviews, and site-specific studies (see Appendix G). 

In all cases, the FLMs have used peer-reviewed scientific 

literature and expert judgment to make their decisions. For 

example, the NPS has compiled regional reviews that have 

evaluated existing information on air quality, deposition, 

and effects on AQRVs in national parks. For these reviews, 

NPS grouped parks by region and ecosystem type, including 

the Pacific Northwest, the Colorado Plateau, and the Rocky 

Mountains, and conducted an empirical assessment of the 

status of aquatic and terrestrial resources. An analysis of 

deposition effects was done, using current deposition data 

for S and N and effects information from field observations 

and research. These reviews provide the basis for critical 

load development by identifying sensitive resources and 

impacts to those resources. Park-specific information on 

sensitive resources, impacts, and critical loads is available at:

- http://www.nature.nps.gov/air/permits/aris/index.

cfm

The USFS has conducted a series of national and regional 

workshops to establish critical loads and concern thresholds. 

In the late 1980s, the USFS published prototype methods 

for evaluating the effects of acid deposition on AQRVs (Fox 

et al. 1989; Fox et al. 1987). Subsequently, the USFS held 

regional workshops to develop updated and more areaspecific screening procedures for new air pollutant emissions 

sources (Adams et al. 1991; Peterson et al. 1992; Haddow 

et al. 1998; Peterson et al. 1993; Stanford et al. 1997). These 

workshops were comprised of national and regional USFS 

land managers, deposition experts from the academic and 

air pollution research community, and agency air quality 

professionals. Dependent on the workshop leadership, each 

regional workshop followed a slightly different process 

and a variety of outputs and formats resulted. However, all 

workshops used a collaborative process to determine S and 

N deposition rates that would pose a risk to the aquatic 

and terrestrial ecosystems protected in FLM areas, while 

addressing the scientific uncertainty inherent in ecosystem 

response to acidic deposition. Critical load guidelines for 

many USFS Class I areas are published in the regional 

workshop reports (see Appendix G) and are available at:

- http://www.fs.fed.us/air

As resources permit, the Agencies will develop methods 

and a process for establishing critical deposition loading 

values for all FLM areas and for recommending critical 

loads for areas where adequate information exists. For areas 

lacking sufficient information to determine critical loads, 

the Agencies are developing strategies to obtain needed 

information. 

Current information and links on critical loads work being 

done by the U.S. Forest Service can be found at the following 

web site:

- http://www.fs.fed.us/air

The Agencies anticipate using critical loads as they are 

developed as an assessment tool, and, in concert with the 

Deposition Analysis Thresholds and Concern Thresholds 

(see below), a tool for assessing new source impacts. The 

Agencies also intend to continue to consult with States and 

the EPA as critical load development work progresses.

3.5.5. Other AQRV Identification and Assessment 

Tools (Revised) 

In addition to AQRV monitoring, there are several tools 

available to the FLM for identifying AQRVs and assessing 

the response of sensitive AQRVs to pollutant deposition. 

These include the Air Resources Information System 

(ARIS), the Natural Resource Information System – Air 

Module (NRIS-Air), and deposition models such as the 

Model of Acidification of Groundwater in Catchments 

(MAGIC) and MAGIC-With Aggregated Nitrogen Dynamics 

(MAGIC-WAND).

64 FLAG Phase I Report—Revised (2010)
Air Resources Information System (ARIS)

FLAG 2000 also introduced “Air Synthesis” as an 

information management and decision-support computer 

system under development by NPS and FWS. The NPS 

and FWS have since redesigned and renamed Air Synthesis, 

now called Air Resources Information System (ARIS). ARIS 

provides information on air quality related values in NPS 

and FWS Class I areas, as well as in many NPS Class II areas. 

Information can be accessed for specific areas or for all units 

within NPS Inventory & Monitoring (I & M) networks.8

 

ARIS identifies specific AQRVs, and provides information 

on air quality and its effects in parks and wildernesses. 

ARIS maintains information for all 48 NPS Class I air 

quality areas and several FWS Class I areas. Information is 

being developed for the remaining FWS Class I areas, and 

additional Class II areas. Additional information on ARIS 

can be found at:

- http://www.nature.nps.gov/air/permits/aris/index.

cfm

Information for FWS Class I areas is under development at: 

- http://www.fws.gov/refuges/whm/AirQuality/index.

html

Natural Resource Information System – Air Module 

(NRIS-Air)

Publicly available USDA Forest Service Class I and II area 

information and related resource data can be linked to or 

found at http://www.fs.fed.us/air. If desired information and 

data cannot be found, contact any air program manager or 

specialist at national or regional offices for assistance.

Information from NRIS-Air, including USFS Class I area 

AQRV information, is available at:

- http://www.fs.fed.us/air

Deposition Effects Models

A number of watershed process models have been 

developed and tested in an attempt to simulate the effects 

of S and N on soils, forests, and surface waters. These 

models are used by FLMs to predict effects from increases 

in deposition and vary from detailed, compartment models 

of watersheds to lumped parameter models that do not track 

different ions through each soil compartment. For a review 

of models developed under NAPAP see NAPAP 1991.

A commonly applied watershed model is MAGIC. MAGIC 

was first developed for eastern U.S. watersheds and then 

extensively tested and validated throughout Europe and 

North America (Cosby et al. 1985, 1995, 1996). The model 

8. The NPS I & M program consists of over 270 park units organized 

into 32 networks to conduct long-term natural resource monitoring 

on park “vital signs,” that is, selected physical, chemical, and biological 

elements and processes of park ecosystems that represent the overall 

health or condition of the park.

was used by NAPAP in its 1990 Integrated Assessment 

to project surface water chemistry resulting from various 

deposition scenarios (NAPAP 1991b). In another application 

in the eastern U.S., MAGIC has been linked with a simple, 

empirical, dose/response fish model developed at University 

of Virginia that makes it possible to predict changes in fish 

productivity based on modeled changes in stream water 

chemistry. 

As a result of NAPAP, there was increased awareness of the 

potential impacts of inorganic N deposition on watersheds 

and surface waters. In response, the MAGIC model was 

updated with a module called With Aggregated Nitrogen 

Dynamics (WAND). MAGIC-WAND is a process-based 

model that uses site-specific information on hydrology, soils, 

and hydrochemistry. The model predicts changes through 

time in lake or stream chemistry. These time-series of 

changes in pH and ANC can subsequently be used by FLMs 

to calculate critical S or N loads for watersheds. 

MAGIC-WAND has been extensively tested in the 

Adirondacks and at watersheds in Maine. For example, the 

Bear Brook Watershed Manipulation Project uses MAGICWAND to predict the effects of experimentally added N and 

S on a test watershed. MAGIC-WAND has also been applied 

to watersheds in FLM areas in the Cascades, the Sierra 

Nevada, the Rocky Mountains, and the Wind River Range 

in an effort to quantify critical S and N loads to aquatic and 

terrestrial resources. In the southeastern U.S., MAGICWAND is being used under the auspices of the Southern 

Appalachian Mountains Initiative (SAMI) to predict the 

effects of future deposition scenarios on FLM areas. Future 

SAMI modeling efforts will link watershed model results 

with fish dose/response models. The ultimate goal is to 

calibrate MAGIC-WAND with landscape level data in order 

to set regional critical loads.

Other models are also in use. For example, the USFS Rocky 

Mountain Region recommends using either CALPUFF or 

AERMOD (or other approved models) to estimate S and N 

deposition. The Screening Methodology for Calculating ANC 

Change to High Elevation Lakes (USDA Forest Service 2000) 

summarizes procedures for estimating total deposition of S 

and N. The document also recommends computations for 

estimating alkalinity changes in lakes caused by increases in 

S and N deposition. Another model, the Nutrient Cycling 

Model (NuCM) has been used in the East to predict the 

effect of changes in deposition on nutrient concentrations in 

soils and vegetation.

3.5.6. Recommendations for Evaluating Potential 

Effects from Proposed Increases in Deposition to 

an FLM Area (Revised) 

 FLAG 2000 described a process to help the Agencies and 

permit applicants assess the total sulfur and/or total nitrogen 

deposition impacts of proposed new or modified sources. 

 USFS–NPS–USFWS 65
Since that time, the Agencies have refined the concept 

of using concern thresholds, pollutant exposures, and 

deposition analysis thresholds in the permit review process. 

The approaches used by the respective agencies may vary 

somewhat, but in essence are all similar.

Deposition Analysis Thresholds (DATs) 

The NPS and FWS have introduced and developed the 

concept of Deposition Analysis Thresholds (DATs) to use as 

screening level values for the additional modeled amount of 

sulfur and nitrogen deposition within FLM areas from new 

or modified PSD sources. A DAT is defined as the additional 

amount of nitrogen or sulfur deposition within an FLM area, 

below which estimated impacts from a proposed new or 

modified source are considered negligible. In other words, 

if the new or modified source has a predicted nitrogen or 

sulfur deposition impact below the respective DAT, the NPS 

and FWS will consider that impact to be negligible, and no 

further analysis would be required for that pollutant. In 

cases where a source’s impact equals or exceeds the DAT, 

the NPS/FWS will make a project specific assessment of 

whether the projected increase in deposition would likely 

result in an “adverse impact” on resources considering 

existing AQRV conditions, the magnitude of the expected 

increase, and other factors.

The DATs are based on “naturally occurring deposition” 

that park and wilderness ecosystems may have experienced 

prior to anthropogenic influences and are scaled to enable 

assessment of the impacts of individual sources of air 

pollution. The DAT established for both nitrogen and sulfur 

in eastern and western FLM areas and wildernesses is 0.010 

and 0.005 kilograms/hectare/year (kg/ha/yr), respectively. 

More information regarding the sulfur and nitrogen DATs 

can be found at:

- http://www.nature.nps.gov/air/Pubs/pdf/flag/

nsDATGuidance.pdf

While DATs are a tool to assess the impact of a single new 

source, these levels may not be protective in areas that are 

already impaired or where there are multiple new sources 

impacting a single area. The critical load concept, discussed 

above, may be a more effective tool for assessing cumulative 

impacts.

Concern Thresholds and Pollutant Exposures

The Forest Service has continued to develop AQRV concern 

thresholds and pollutant exposure(s) thresholds (for sulfur 

or nitrogen deposition) that when exceeded may indicate 

an adverse impact to one or more AQRVs. These thresholds 

are very similar to the NPS/FWS Deposition Analysis 

Thresholds (DATs) in that they establish a point below 

which adverse impacts are not expected. Impacts above 

the thresholds may or may not cause an adverse impact; 

depending on current levels of deposition and resource 

condition. The values for these thresholds vary between FS 

Class I areas; therefore an applicant will need to check for 

Class I area-specific thresholds on the following Internet site: 

- http://www.fs.fed.us/air/technical/class_1/alpha.php

FLM Response to Potential Deposition Impacts

For a project that exceeds the initial annual emissions over 

distance (Q/D) screening criteria, the permit applicant 

should consult with the appropriate regulatory agency and 

FLM for the affected area(s) to determine if a deposition 

impact analysis should be done (e.g., expected sulfur and/

or nitrogen deposition impacts are above the DAT) or 

respective concern threshold). For such cases, FLMs request 

that proponents provide sufficient information for the FLM 

to evaluate the potential effects of emissions increases on 

AQRVs. FLMs have provided information to applicants 

through guidance documents, correspondence, meetings, 

and phone consultations. This chapter summarizes current 

information for evaluating new emissions on deposition and 

sensitive AQRVs and includes recommendations for:

- the types of data, information, and analysis needed 

before a permit application can be considered 

complete, including analytical and modeling 

protocols for a proponent’s use in conducting an 

AQRV impact analysis;

- approaches and sources of appropriate values for 

estimating wet and dry deposition; and

- permit conditions to mitigate source impacts.

The process begins with the question “Q/D ≤ 10?” as 

the first level screening criteria (see Figure 7). The next 

question is whether or not the DAT/concern threshold is 

exceeded. If not, no adverse impacts are expected. If so, the 

Agencies will determine if the contextual considerations (see 

section 4.3) or any refined analyses alleviate any deposition 

concerns. If not, the Agencies will defer to the FLM to make 

a case-by-case adverse impact finding. In determining if 

the proposed action will cause or contribute to an adverse 

effect to AQRVs, the FLM will consider information on 

deposition-sensitive AQRVs, deposition loads at which these 

AQRVs are affected (i.e., critical loads), the current pollutant 

deposition rates in the area, and the expected impacts from 

the proposed source. Procedures for estimating the source’s 

impacts are found in ‘Estimation of Current and Future 

Deposition Rates’ section of this report. In areas where 

no information is available, information from a nearby, or 

ecologically similar area, may be used. An adverse effect may 

occur if the critical load is exceeded for an area, and the 

new source impact is above the levels of concern (i.e., DAT/

concern threshold). AQRV and critical load information are 

discussed earlier in this report. 

If the available information is insufficient for the FLM to 

determine if the proposed action will cause or contribute 

to an adverse effect to AQRVs, the FLM may ask for 

deposition and deposition effects monitoring and/or 

66 FLAG Phase I Report—Revised (2010)
research in the FLM area. If the proposed action will 

likely cause or contribute to an adverse effect to AQRVs, 

the FLM may recommend permit conditions that ensure 

mitigation, including stricter emissions controls and effective 

emissions offsets. If no mitigation is possible, the FLM may 

recommend denial of the permit. 

Available Deposition Monitoring Data

Atmospheric pollutants are deposited to ecosystems 

primarily through wet deposition and dry deposition. FLMs 

participate in national monitoring programs to monitor wet 

and dry deposition, including the National Atmospheric 

Deposition Program (NADP) and the Clean Air Status and 

Trends Network (CASTNet). A 1999 report, “The Role of 

Monitoring Networks in the Management of the Nation’s 

Air Quality,” (CENR, 1999) identified these two networks as 

being critical for characterizing baseline air quality data in 

the U.S.

Wet Deposition (Revised)

Wet deposition includes rain, snow, fog, cloud water, and 

dew. In most FLM areas, rain and snow are the primary 

contributors to wet deposition. However, in some high 

elevation areas, fog, cloud water, and dew are significant 

contributors, as discussed below. 

Because rain and snow are the primary constituents of wet 

deposition at most FLM areas, the FLM generally relies on 

data from NADP to evaluate wet deposition of pollutants. 

NADP samplers collect rain and snow and NADP has 

documented deposition for many years in a nationwide 

network that currently includes over 220 monitoring 

Figure 7. FLM Assessment of Potential Deposition Effects from New Emissions Sources (Revised)

*Q/D test only applies to sources located greater that 50 km from a Class I area.

 USFS–NPS–USFWS 67
sites. The network collects data to evaluate spatial and 

temporal long-term trends in precipitation chemistry. The 

precipitation at each site is collected weekly and sent to 

a central analytical laboratory for analysis of hydrogen 

(acidity as pH), sulfate, nitrate, ammonium, chloride, and 

base cations, including calcium, magnesium, potassium, and 

sodium. Data and isopleth maps of pollutant concentrations 

and deposition are available on the NADP web site at:

- http://nadp.sws.uiuc.edu/ 

FLMs agree that it is preferable to obtain NADP data from 

the web site, rather than summarizing wet deposition data in 

this report. In this way, current data can be easily accessed 

by FLMs and the public.

Approximately 50 FLM areas have NADP samplers in 

or immediately adjacent to them. Because some of these 

areas are classified as wilderness, FLMs install sampling 

equipment in adjacent non-wilderness areas in order to 

preserve the wilderness character of the area. Ambient air in 

these adjacent areas is considered representative of air in the 

wilderness area. 

A number of FLM areas do not have an NADP sampler in 

or adjacent to them. Where possible, the FLM has identified 

an NADP site whose data may be used to characterize 

deposition at the area. Deposition rates generally increase 

with elevation and deposition in high-elevation areas may 

be difficult to characterize with data from a lower-elevation 

NADP site. FLM consultation may be necessary to estimate 

deposition in these areas.

 Areas that experience significant deposition from fog 

and cloud water or large amounts of snow may need to 

use alternate sampling methods and data in addition to 

NADP protocols and NADP data to characterize them. 

Wet deposition in these areas may need to be sampled 

with alternate methods, including cloud water samplers 

and snowpack sampling or estimated by modeling. At sites 

where such data or modeled estimates are available, they 

should be used to calculate total deposition. At mountain 

sites frequented by clouds and fog, deposition from clouds 

may equal or exceed that from precipitation. Cloud water 

is generally more acidic and contains higher concentrations 

of base cations than rain water; therefore, it can contribute 

significantly to total loadings of S and N (Hemmerlein and 

Perkins 1992). Various methods have been developed to 

measure deposition from cloud water. The Mountain Acid 

Deposition Program (MADPro) used automated cloud 

water collectors to sample at three high-elevation eastern 

sites (Anderson et al. 1999). Forests covered by fog for 

significant periods of time may be especially susceptible 

to injury from acid deposition. Acidic cloud water has 

predisposed red spruce in the high elevations of the 

northeast U.S. Appalachians to winter injury and cumulative 

impacts with other biotic and abiotic stresses have caused 

mortality. The contribution of clouds and fog to deposition 

at high elevations may overshadow both deposition from 

precipitation and dry deposition (Hidy 1998). The EPA 

estimated that as a result of cloud cover, high elevation 

forests might experience four times the amount of total 

pollutant deposition as lower elevation forests without cloud 

cover (NAPAP 1991). High elevation lakes are also impacted 

by fog and clouds, as well as rain and snow. Measurements 

in high elevation areas that do not include all contributions 

to wet deposition will result in under-estimates. 

Modeling has been used to estimate total wet deposition 

in some areas. For example, the Southern Appalachian 

Man and the Biosphere Cooperative (as part of the 

Southern Appalachian Assessment) has used NADP data, 

topographical data, and meteorological data to model wet 

deposition loading at locations in the southeastern U.S. 

Dry Deposition (Revised)

 Dry deposition includes gases, aerosols and particles. 

The primary gases involved with N and S deposition are 

ammonia (NH3

), nitric oxide (NO), nitrogen dioxide (NO2), 

nitric acid (HNO3

), and sulfur dioxide (SO2), while the 

primary particles are nitrate (NO3

-

), ammonium (NH4

+), and 

sulfate (SO4

2-) ions (Hanson and Lindberg 1991). Ammonia, 

NO, NO2

 and SO2 are taken up by plants through stomata, 

while HNO3

, due to its high deposition velocity, is deposited 

to plant surfaces in addition to being taken up by stomata. 

Nitrate, ammonium, and sulfate particles deposit to surfaces 

(Bytnerowicz and Fenn 1996).

Dry deposition is much more difficult to estimate than 

wet deposition. The estimation of dry deposition rates 

requires information on the ambient concentrations of 

pollutants, meteorological data, and information on land 

use, vegetation, and surface conditions, all of which are 

site-specific. Because of this site-specificity, it is difficult to 

spatially extrapolate dry deposition data as is often done for 

wet deposition data. 

In general, FLMs rely on data from CASTNet for estimates 

of dry deposition in FLM areas (http://www.epa.gov/

castnet). CASTNet was developed by EPA, as a result of the 

Clean Air Act Amendments of 1990, and currently includes 

over 70 sites. These include a combination of former 

National Dry Deposition Network sites, Park Research 

and Intensive Monitoring of Ecosystems Network sites 

(PRIMENet), and others. Dry deposition is measured at 26 

NPS areas and 2 USFS areas. FLMs agree that it is preferable 

to obtain CASTNet data from the web site, rather than 

summarizing dry deposition data in this report. In this way, 

current data can be easily accessed by FLMs and the public.

Other methods for measuring dry deposition are 

available. For example, information on vertical changes in 

concentrations of major gases and particles of interest over 

plant canopies can be used for calculation of deposition of 

68 FLAG Phase I Report—Revised (2010)
these compounds to forests and other ecosystems (Hicks 

et al. 1987). Models, such as “Big-Leaf” (Baldocchi et al. 

1987) allow estimating dry deposition to uniform canopies, 

such as agricultural crops or lowland forests. However, no 

models have been developed so far for reliable estimates 

of deposition of gases and particles to forests and other 

ecosystems in complex mountain terrain (Bytnerowicz et 

al. 1997). Therefore, no good large-scale estimates of dry 

deposition are available for western U.S. forests.

Another approach to evaluating dry deposition is net 

throughfall technique. By measuring concentrations of ions 

in throughfall (bulk precipitation) and after subtracting 

concentrations of the same ions in precipitation in an 

open area, fluxes of ions such as nitrate, ammonium, and 

sulfate can be calculated. A branch washing technique 

is similar to the net throughfall approach and is used 

when no wet precipitation is present. The pre-washed 

branches are exposed to ambient air for a certain time 

period and then carefully rinsed with water (Lindberg 

and Lovett 1985). Information about amounts of nitrate, 

ammonium and sulfate rinsed from branches of a known 

surface area, time of exposure, and leaf area index of a 

given forest stand allow the calculation of fluxes of the 

measured ions to trees. Adding stomatal uptake of gases 

(calculated from information on gas concentration and 

stomatal conductance), and estimates of deposition to other 

landscape forms (such as soils and rocks) allow for quite 

reliable estimates of dry deposition at a forest stand level 

(Bytnerowicz et al. 2000). Such estimates have been made 

for the subalpine zone of the eastern Sierra Nevada and 

mixed conifer forests on the western Sierra Nevada and 

the San Bernardino Mountains (Bytnerowicz and Fenn 

1996; Bytnerowicz et al. 1999). Both the net throughfall and 

branch washing techniques, although providing relatively 

accurate estimates of deposition to certain ecosystems, 

cannot be applied to every type of vegetation. These 

techniques work well for conifers with relatively thick 

cuticles. For plants with thinner cuticle, extraction of ions 

from plant interior or transcuticular uptake of deposited ions 

may not allow for making good estimates of dry deposition 

to plant surfaces.

Recent developments, such as passive samplers that allow 

for relatively inexpensive determinations of nitric oxide, 

nitrogen dioxide, ammonia, nitric acid and sulfur dioxide 

concentrations, provide some promising opportunities for 

large-scale estimates of distribution of these pollutants. This, 

together with information on landscape-level vegetation 

coverage, leaf area index, and deposition velocity of the 

monitored pollutants, will allow calculating deposition of the 

measured gases to various landscape forms. Although this 

approach would not include deposition fluxes of particulate 

pollutants, a large portion of dry N and S deposition 

(gases) would be covered. Information on fluxes of the 

N and S particulate component (nitrate, ammonium, and 

sulfate ion concentrations) can be estimated based on their 

concentrations from annular denuder/filter pack systems 

or other comparable techniques and literature values of 

deposition velocities of these ions.

For many FLM areas, detailed site-specific information and 

monitoring needed for dry deposition measurements are not 

available. Therefore, the FLM may choose to recommend 

a reasonable estimate of dry deposition. NAPAP’s 1991 

summary report concluded that dry deposition of sulfur is 

30-60% of the total (wet plus dry) deposition at regionally 

representative sites; dry deposition of nitrogen is 30-

70% of the total (wet plus dry) deposition at regionally 

representative sites (NAPAP 1991a). An analysis of one year 

(1991) of NADP, CASTNet, and IMPROVE (Interagency 

Monitoring of Protected Visual Environments) data from 

national parks and wildernesses found that wet deposition 

dominated total deposition in both the East and the West. 

Dry deposition of sulfur was 20-50% of the total; dry 

deposition of nitrogen was 30-60% of the total (Hidy 1998). 

These estimates, and similar ones, have led to the common 

assumption that dry deposition is approximately 50% of the 

total deposition. Therefore, for many FLM areas without 

on-site or nearby representative dry deposition sampling, the 

FLM may recommend that dry deposition is equal to wet 

deposition. The FLM recommends this as a “best available 

estimate,” recognizing that in some areas it may result in 

under- or over-estimating total deposition. Total deposition, 

which is the sum of wet plus dry deposition, therefore equals 

twice the wet deposition.

In summary,

Total Deposition = Wet Deposition + Dry Deposition

Or,

Total Deposition = 2 x Wet Deposition (assuming Dry 

Deposition = Wet Deposition)

There are numerous monitoring stations in or near FLM 

areas for estimating wet and dry deposition values. For 

some areas the FLM assumes that dry deposition equals 

wet deposition, recognizing that this may result in under- or 

over-estimates of total deposition. Deposition monitoring 

data and information on the appropriate dry deposition data 

to use at sites where data are available are included on the 

respective Agencies web sites referenced previously.

FLMs will continue to participate in monitoring and 

research to further our understanding of dry deposition 

dynamics and improve our measurements of dry deposition.

Other Deposition Measurement Methods

Pollutant deposition, particularly in areas where traditional 

wet and dry deposition sampling is impractical, can also 

be estimated by other methods. These methods include 

bulk samplers that collect both wet and dry deposition and 

snowpack measurements that estimate the total amount of 

 USFS–NPS–USFWS 69
pollutants in the snow column at the time of maximum snow 

accumulation. Special methods have also been developed for 

collecting fog and cloud water (Anderson et al. 1999).

In addition, methods are being developed to estimate dry 

deposition rates from pollutant concentrations obtained 

by IMPROVE fine particle samplers. IMPROVE samplers 

are located at many FLM areas and expanded coverage is 

planned for 1999. 

Modeling Deposition Rates

Deposition from existing sources can be estimated from 

deposition monitoring data, but contributions to deposition 

from the proposed source and other sources permitted but 

not yet operating should be modeled. 

Modeling should be done in accordance with 

recommendations developed by the Interagency Work 

Group on Air Quality Modeling (IWAQM) Phase 2: 

- http://www.epa.gov/scram001/7thconf/calpuff/

phase2.pdf

IWAQM provides the procedures that can be used to 

estimate S and N deposition from a proposed source and 

other sources permitted but not yet operating. The FLMs 

propose that these procedures be used to estimate S and 

N deposition. For S deposition, the wet and dry fluxes 

of sulfur dioxide and sulfate are calculated, normalized 

by the molecular weight of S, and expressed as total S. 

For N deposition, IWAQM recommends that the wet 

and dry fluxes of nitric acid (HNO3

) and nitrate (NO3

-

) 

and the dry flux of nitrogen oxides (NOx

) be calculated, 

normalized by the molecular weight of N, and expressed 

as total N. In addition, the FLMs agree that wet and dry 

fluxes of ammonium sulfate ((NH4

)2SO4) and ammonium 

nitrate (NH4

NO3) should be calculated, normalized by the 

molecular weight of N, and added to the estimate of total N. 

Therefore, total N deposition is the sum of N contributed by 

dry and wet fluxes of HNO3

, NO3

-

, (NH4)2SO4, and NH4NO3

and the dry flux of NOx

.

The FLMs recognize that the ammonia (NH3

) in these 

compounds is derived from both man-made and natural 

sources. Free gaseous NH3

 has a high deposition velocity 

and tends to deposit quickly. However, if sulfates and 

nitrates (which are primarily man-made) are present in the 

atmosphere, free NH3

 quickly reacts to form (NH4)2SO4 and 

NH4

NO3. These compounds, because of their fine particle 

size and slower deposition velocity than free gaseous NH3

, 

can be transported long distances and deposited in a FLM 

area, adding to the total N deposition loading. 

 An appropriate estimate of ambient free gaseous NH3

is needed for the modeling analysis. IWAQM refers to 

Langford et al. (1992), who suggest that typical (within a 

factor of 2) background values of NH3

 are: 10 parts per 

billion (ppb) for grasslands, 0.5 ppb for forest, and 1 ppb 

for arid lands at 20°C. Langford et al. (1992) provide strong 

evidence that background levels of NH3

 show strong 

dependence with ambient temperature (variations of a 

factor of 3 or 4) and a strong dependence on the soil pH. 

However, given all the uncertainties in NH3

 data, IWAQM 

recommends use of the background levels provided above, 

unless better data are available for the specific modeling 

domain. IWAQM notes that in areas where there are high 

ambient levels of sulfate, values such as 10 ppb might 

overestimate the formation of particulate nitrate from a given 

source, for these polluted conditions. IWAQM further notes 

that areas in the vicinity of strong point sources of NH3

, 

such as feed lots or other agricultural areas, may experience 

locally high levels of background NH3

.

Questions regarding these recommendations should be 

resolved through consultation with the appropriate FLM and 

the appropriate State and/or EPA modeling representative. 

Applicants should provide a modeling protocol to the 

appropriate FLM prior to conducting modeling analyses.

Estimation of Current and Future Deposition Rates 

(Revised)

In order to evaluate a proposed source’s contribution to 

total (wet + dry) deposition in a FLM area, it is necessary 

to first estimate current pollutant deposition rates. The 

current rate is a result of deposition from all existing natural 

and anthropogenic sources. FLMs use two approaches to 

estimating the current rate of deposition. One approach 

estimates the current rate by averaging data from an 

appropriate monitoring site for the pollutant of interest, 

using all years with complete data records. The second, 

more conservative, approach assumes that the current rate is 

equivalent to the highest rate for the pollutant of interest in 

the data record.

The method for estimating future total deposition rates is:

•	 From the respective Agency web sites, identify available 

on-site or representative wet and dry deposition data 

for the FLM area. Wet deposition data can be obtained 

through NADP (http://nadp.sws.uiuc.edu/). For NPS 

sites without an NADP sampler, use estimates of total 

wet nitrogen and total wet sulfur from the Air Quality 

Estimates for 1999-2003 at http://www.nature.nps.gov/

air/Maps/AirAtlas/index.cfm.

Dry deposition data can be obtained through CASTNet at 

(http://www.epa.gov/castnet). 

Verify if dry deposition is assumed to equal wet 

deposition for the site. For high-elevation sites, consult 

with the FLM to determine if deposition from cloud 

water, fog, dew, or snowpack should be considered. 

For sites without on-site data, consult FLM for further 

guidance.

•	 After consulting with the FLM, estimate either: 

70 FLAG Phase I Report—Revised (2010)
- the average annual or seasonal wet and dry 

deposition rates for the appropriate pollutant using 

all years with complete data records; or

- the highest annual or seasonal wet and dry deposition 

rates for the appropriate pollutant using all years with 

complete data records. 

•	 Calculate current total deposition (wet + dry = total).

•	 Estimate, using the appropriate dispersion model as 

described in the ‘Modeling Deposition Rates’ section 

above, the proposed source’s contribution to future total 

deposition on an annual or seasonal basis.

•	 Estimate, using appropriate dispersion model as described 

in the ‘Modeling Deposition Rates’ section above, 

the contribution of any sources permitted but not yet 

operating to future total deposition and the affect of any 

enforceable emission reductions. This estimate may be 

available from the State permitting authority.

•	 The current pollutant deposition rate plus the proposed 

source’s contribution to deposition plus the contribution 

from other sources permitted but not yet operating minus 

credit for enforceable emission reductions equals the 

future total deposition rate.

Current + Proposed + Permitted (not yet operating) – credit 

for enforceable reductions = Future Total Deposition

This future total deposition rate for a given pollutant can 

then be used to determine the potential for adverse effects 

to AQRVs. If appropriate, the change in deposition rate can 

be used to estimate changes in pH or ANC in an ecosystem. 

If the future total deposition rate is expected to cause an 

adverse effect to AQRVs and/or exceeds the critical load 

established for a FLM area, the FLM may recommend 

mitigation. If no critical load has been established for the 

FLM area, the FLM will use the best information available in 

determining whether to recommend mitigation.

3.5.7. Summary (Revised)

•	 Deposition of S and N has the potential to affect 

terrestrial, freshwater, and estuarine ecosystems on FLM 

lands.

•	 The FLM has identified, where possible, AQRVs sensitive 

to deposition of S and N on FLM lands and the critical 

loads associated with those AQRVs. 

•	 A proponent of a source of new emissions with the 

potential to contribute to S or N deposition in an FLM 

area should consult with the FLM to determine what 

analyses are needed to assess AQRV effects. The FLM 

may request a deposition impact analysis, described in 

detail in this chapter and summarized below.

- Estimate the current deposition rate to the FLM 

area. A list of monitoring sites providing data to 

characterize deposition in FLM areas is included on 

the respective Agencies web sites.

- Estimate the future deposition rate by adding the 

existing rate, the new emissions’ contribution to 

deposition, the contribution of sources permitted 

but not yet operating, and then subtracting the credit 

for enforceable emission reductions. Modeling of 

new, reduced, and permitted but not yet operating 

emissions’ contribution to deposition should 

be conducted following current EPA modeling 

guidance.

- Compare the future deposition rate with the 

recommended screening criteria (e.g., critical load, 

concern threshold, or screening level value) for the 

affected FLM area. A list of documents summarizing 

these screening criteria, where available, can be 

found in Appendix G. 

Information for USFS Class I areas is also available at:

http://www.fs.fed.us/air

Information for NPS and FWS Class I areas is 

available at:

http://www.nature.nps.gov/air/Permits/

ARIS/ 

Information for FWS Class I areas is under 

development at:

http://www.fws.gov/refuges/whm/

AirQuality/index.html

The appropriate FLM should be contacted for 

additional information.

3.5.8. Web sites for Deposition and Related 

Information (Revised) 

Clean Air Status and Trends Network (CASTNet) dry 

deposition data:

- http://www.epa.gov/castnet

National Acid Precipitation Assessment Program 2005 

Report:

- http://www.esrl.noaa.gov/csd/AQRS/reports/

napapreport05.pdf

 USFS–NPS–USFWS 71
National Atmospheric Deposition Program (NADP) wet 

deposition data: 

- http://nadp.sws.uiuc.edu/

National Park Service Airweb: 

- http://www.nature.nps.gov/air/

Natural Resources Conservation Service, Snow Water 

Equivalent Information (SNOTEL): 

- http://www.wcc.nrcs.usda.gov/snow

Southern Appalachian Mountain Initiative: 

- http://www.tva.gov/sami

USDA Forest Service National Air Resource Management 

Web Site:

- http://www.fs.fed.us/air/

EPA Office of Air and Radiation:

- http://www.epa.gov/oar

EPA, Deposition to Estuaries:

- http://epa.gov/owow/airdeposition/

EPA, STOrage and RETrieval System for Water and 

Biological Monitoring Data (STORET): 

- http://www.epa.gov/storet

U.S. Fish and Wildlife Service Air Quality Branch: 

- http://www.fws.gov/refuges/whm/AirQuality/index.

html

U.S. Geological Survey, National Water-Quality Assessment 

(NAWQA) Program: 

- http://water.usgs.gov/nawqa

U.S. Geological Survey, Acid Rain Program:

- http://bqs.usgs.gov/acidrain

U.S. Geological Survey, Water Data Storage and Retrieval 

System (WATSTORE): 

- http://water.usgs.gov/owq/data.html

72 FLAG Phase I Report—Revised (2010)
4. Expansion of Discussion 

of Process for Adverse Impact 

Determination (New Chapter)

Based on feedback from permit applicants and State 

permitting authorities, the Agencies are providing a more 

detailed description of the adverse impact decision making 

process once a source analysis has raised concerns during a 

first-level and any subsequent analyses.

If the first-level analysis yields impacts above the 

defined threshold(s), the applicant may propose to 

address preliminary FLM concerns directly through 

proposed emission reductions for the project, or through 

implementation of other measures to mitigate emission 

impacts. Alternatively, the applicant may undertake a more 

refined analysis to potentially alleviate preliminary concerns. 

Of course, this refined analysis should occur in a timeframe that enables permitting authorities to adhere to their 

regulatory guidelines. 

Additional emission reductions, mitigation proposals, or 

more refined analysis are not legal requirements. They are 

options that can be utilized to help alleviate preliminary 

FLM concerns about emission impacts on Class I areas. 

Permit applicants can request that FLMs conduct their 

evaluation based on information provided in the application.

4.1. Background 

The FLAG visibility thresholds have been interpreted by 

some as a one-dimensional or bright line test that inevitably 

leads to an adverse impact determination. This, however, is 

not the intent; these screening-levels were envisioned as a 

“visibility analysis threshold” similar to the newer deposition 

analysis thresholds (DATs) discussed above for sulfur and 

nitrogen deposition. 

The Agencies want to emphasize that the FLAG report 

provides criteria as to when the FLMs will definitively not 

object to, or declare an adverse impact for, a proposed new 

source. FLAG assures an applicant that, if they conduct their 

analyses correctly and demonstrate that change in extinction 

or deposition falls below the specified thresholds, the FLMs 

will not raise concerns regarding the project. However, the 

converse does not necessarily apply — a FLAG threshold 

exceedance does not mean the FLM will certainly find that 

a project will adversely affect air quality related values. If a 

threshold is exceeded, the FLMs will consider the factors 

discussed below and make a project-specific determination 

as to whether or not the impacts are adverse. 

4.2. Regulatory Factors

According to the EPA definition of “adverse impact on 

visibility,” the FLM must determine whether the proposed 

source’s predicted impact “interferes with the management, 

protection, preservation, or enjoyment of the visitor’s 

visual experience” taking into account the “geographic 

extent, intensity, duration, frequency and time of visibility 

impairments, and how these factors correlate with (1) 

times of visitor use of the Federal Class I area, and (2) the 

frequency and timing of natural conditions that reduce 

visibility.” (40 C.F.R. §51.301).

Considering the regulatory factors is inherent in the firstlevel modeling exercise. The model describes the geographic 

area predicted to be impacted. The visibility extinction 

values describe the intensity of the impact. Similarly, the 

model provides some level of assessment regarding duration, 

frequency, and time of impact. A more refined modeling 

analysis should further inform consideration of these 

factors. Regarding how these factors correlate with visitor 

use, the responsibilities of the Agencies include protecting 

the resources for all visitors. Visitor data show that nearly 

all Class I areas have some level of visitation each month. 

Regarding correlation with the frequency and timing of 

natural conditions that reduce visibility, the first-level 

modeling analysis will not provide this information directly, 

but, by using the percentile approach and monthly relative 

Seney National Wildlife Refuge, Michigan. 

Credit: Atlee Hart

 USFS–NPS–USFWS 73
humidity values, the Agencies have attempted to provide a 

reasonable approach to addressing weather impacts. 

Similarly, if the sulfur or nitrogen DAT is exceeded, or if high 

ozone levels are anticipated, the FLMs should determine if 

those impacts would adversely affect sensitive AQRVs. This 

adverse impact determination should be made on a projectspecific basis and will be largely driven by management 

objectives for the area. 

4.3. Contextual Considerations

The Agencies recognize that the context within which new 

source permitting occurs is shifting. Many older major 

stationary sources will be installing pollution controls over 

the next 10 to 15 years (e.g., in response to the Regional 

Haze Rule). New motor vehicle emission and fuel standards 

will reduce tailpipe pollution from mobile sources gradually, 

but significantly, over a similar time frame. States are 

developing visibility protection plans that ensure “reasonable 

progress” toward natural conditions, pursuant to the EPA’s 

Regional Haze Rule. These plans will be reviewed and 

revised every five to ten years, and thus provide a mechanism 

for revisiting sources as better technology becomes available 

or as otherwise needed to maintain progress toward visibility 

goals. The location and effect of pending pollution control 

programs on specific Class I areas remains somewhat 

uncertain; however, the Agencies recognize and appreciate 

that significant emission reductions are anticipated, 

especially in the eastern U.S. 

As part of the discussions with permitting authorities or 

permit applicants when screening level thresholds are 

exceeded, the Agencies will consider contextual information, 

including, for example:

•	 Current pollutant concentrations and AQRV impacts in 

the Class I area

•	 Air quality trends in the Class I area 

•	 Emission changes that have occurred or would occur (i.e., 

enforceable) by the time the new source begins operation

•	 Whether there are approved SIPs that account for new 

source growth and demonstrate attainment of national 

ambient air quality standards and “reasonable progress” 

toward visibility goals 

•	 The expected useful life of the source

•	 The stringency of the emission limits (e.g., Best Available 

Control Technology)

•	 Other considerations such as options put forth by the 

applicant that would produce ancillary environmental 

benefits to AQRVs (e.g., reductions in toxic air 

contaminants, pollution prevention investments)

•	 Comments received from the public or other agencies 

during the comment period prior to issuing the permit.

4.4. Preliminary Adverse Impact Concerns

After considering the regulatory factors and contextual 

considerations listed above, the Agencies, in consultation 

with the FLM, will evaluate, on a project-specific basis, 

whether the evidence supports a finding that the new source 

would possibly cause or contribute to an adverse impact 

on air quality related values. If so, the Agencies will notify 

the permit applicant and the permitting agency and provide 

the permit applicant the opportunity to consider mitigation 

strategies that will alleviate the potential adverse impact 

concerns. These strategies may include: 

•	 Obtaining emission offsets for pollutants that cause or 

contribute to the potential adverse impacts on Class I area 

resources; 

•	 Reducing emission rates through more stringent pollution 

control technology or operational or design changes; and 

•	 Monitoring or special studies that increase understanding 

of how Class I area resources or visitors are affected by air 

pollution, which may serve as a basis for revisiting permit 

conditions in future years. (Note: monitoring and study 

alone does not constitute mitigation.) 

 Again, proposing any such mitigation strategy is voluntary. 

Nevertheless, if the FLMs deem a proposed mitigation 

strategy as adequate to protect AQRVs, and the mitigation 

strategy is made enforceable via the PSD permit or some 

other mechanism, the FLM will not make an adverse impact 

finding with respect to the issues addressed by the mitigation 

strategy. 

4.5. Adverse Impact Determination

If an applicant is unable or unwilling to implement an 

appropriate mitigation strategy to alleviate potential adverse 

impact concerns, the FLM will determine whether or not 

the potential impacts of the project as proposed should be 

formally deemed adverse to air quality related values in the 

affected Class I areas. If the FLM concludes that there are 

potential adverse impacts, he will inform the permitting 

authority of this decision.

Historically, the FLMs have made adverse impact findings 

for less that one percent of the permit applications that the 

Agencies review. In those rare cases, the FLMs will strive 

to provide the permitting authority with an ample technical 

and policy/management-related foundation, including a 

discussion of the analysis results and the regulatory and 

contextual factors discussed above. The FLMs’ ability to 

provide this foundation will depend on the completeness 

and adequacy of information provided by the permit 

applicant. Where information is lacking, or uncertain, the 

FLMs will err on the side of protecting air quality related 

values. 

74 FLAG Phase I Report—Revised (2010)
5. Future FLAG Work

5.1. Implementing FLAG Recommendations 

(Revised) 

FLAG participants believe that the recommendations in 

this revised document should be implemented as soon as 

possible. Therefore, an attempt has been made to present 

thorough and clear information on the processes that will be 

used to protect and improve AQRVs in FLM areas. 

Many of the issues and recommendations discussed 

herein are complex and require specialized knowledge. 

Consequently, State agencies and others who intend to use 

this information in NSR/PSD permitting, land planning 

and use, and other activities, may want or require further 

guidance and implementation assistance. The Agencies 

anticipate that much of this guidance and assistance will be 

provided locally through established formal and informal 

links between FLMs, States, EPA and others. For example, 

the Agencies intend to provide further information through 

their respective web sites, and through participating in 

related training sessions and/or workshops. 

5.2. Phase I Updates (Revised) 

This revised FLAG Phase I Report is intended to clearly state 

FLM positions regarding NSR/PSD as it currently exists. As 

the FLMs learn more about how to better assess the health 

and status of AQRVs, and as EPA produces new modeling 

tools, the FLAG report may be revised again. Any such 

revisions to the report will be announced on the Agencies’ 

web sites. 

5.3. Phase II Tasks (Revised)

FLAG Phase I focused on issues that could be resolved 

relatively quickly, without extensive research or the 

collection of new data. The FLMs envisioned a Phase II 

that would address the more complex issues and concerns, 

including those that may require additional data collection. 

Unfortunately, lack of available resources has prevented 

the Agencies from embarking on a formal FLAG Phase 

II process. Nevertheless, the Agencies continue to gather 

effects-based information as part of their ongoing resource 

protection responsibilities. The new information gathered 

since FLAG 2000 is reflected in this revision. As the Agencies 

generate additional data or information, they will make that 

available to interested parties via their respective web sites.

Denali National Park and Preserve, Alaska. 

Credit: National Park Service/Trey Simmons. 

 USFS–NPS–USFWS 75
Appendix A: Glossary

The list below contains definitions for some of the terms 

used in the FLAG Phase I Report. These terms are defined 

in the sense that they relate to the work of the Federal Land 

Managers (FLMs) in protecting air resources. 

For terms whose definition is lengthy or complex, the 

associated Code of Federal Regulations (CFR) section or 

other reference is cited.

Air Quality Related Value (AQRV). A resource, as identified 

by the FLM for one or more Federal areas, that may be 

adversely affected by a change in air quality. The resource 

may include visibility or a specific scenic, cultural, physical, 

biological, ecological, or recreational resource identified by 

the FLM for a particular area.

Adverse Impact on an AQRV. An unacceptable effect, as 

identified by an FLM, that results from current, or would 

result from predicted, deterioration of air quality in a Federal 

Class I or Class II area. A determination of unacceptable 

effect shall be made on a case-by-case basis for each area 

taking into account existing air quality conditions. It should 

be based on a demonstration that the current or predicted 

deterioration of air quality will cause or contribute to a 

diminishment of the area’s national significance, impairment 

of the structure and functioning of the area’s ecosystem, or 

impairment of the quality of the visitor experience in the 

area. 

Adverse Impact on Visibility. Visibility impairment which 

interferes with the management, protection, preservation, 

or enjoyment of a visitor’s visual experience of a Federal 

Class I or Class II area. This determination must be made 

on a case-by-case basis taking into account the geographic 

extent, intensity, duration, frequency and time of visibility 

impairments, and how these factors correlate with (1) times 

of visitor use of the Class I area, and (2) the frequency and 

timing of natural conditions that reduce visibility. This 

term does not include effects on integral vistas. [40 CFR 

§51.301(a)]

Absorption. The process by which incident light is removed 

from the atmosphere and retained by a particle. 

Absorption Coefficient. A number that is proportional 

to the “amount” of light removed from a sight path by 

absorption per unit distance.

Acidification. The decrease of acid neutralizing capacity 

in water or base saturation in soil caused by natural or 

anthropogenic processes.

Aerosol. A mixture of microscopic solid or liquid particles 

in a gaseous medium. Smoke, haze, and fog are aerosol 

examples.

Airshed. A geographic area that, because of topography, 

meteorology, and/or climate, is frequently affected by the 

same air mass.

AOT40. Sum of all hourly average concentrations after 

subtracting 40 ppb from each hourly value.

BACT (Best Available Control Technology). The control 

level (or control measures) required for sources subject to 

PSD. (See 40 CFR §52.21(b)(12), or 40 CFR §51.166(b)(12)).

Class I Area. As defined in the Clean Air Act, the following 

areas that were in existence as of August 7, 1977: national 

parks over 6,000 acres, national wilderness areas and 

national memorial parks over 5,000 acres, and international 

parks. 

Critical Load. The quantitative estimate of an exposure to 

one or more pollutants below which significant harmful 

effects on specified sensitive elements of the environment do 

not occur according to present knowledge.

Cumulative. The impact on an AQRV resulting from the 

total pollutant loading from all sources including the 

contributing effects of known and reasonably foreseeable 

new and modified sources of air pollution. A single source 

may cause individually minor, but cumulatively significant, 

effects on AQRVs.

Damage. Any reduction in the intended use or value of 

a biological or physical resource. For example, economic 

production, ecological structure or function, aesthetic value, 

or biological or genetic diversity that may be altered by a 

pollutant.

Deposition Analysis Threshold. A screening threshold 

developed by NPS and FWS that defines the additional 

amount of nitrogen or sulfur deposition within an FLM area, 

below which estimated impacts from a proposed new or 

modified source are considered negligible. 

Emission Offset. A Federally enforceable reduction in 

emissions from an existing source that mitigates the impacts 

of a proposed new or modified source on AQRVs, PSD 

increments, and/or NAAQS. Also, Federally enforceable 

reductions in actual emissions from existing sources in a 

nonattainment area such that the total allowable emissions 

from a new or modified source and existing sources will 

be sufficiently less than the total emissions from existing 

sources before the application for a permit to construct so as 

to represent reasonable further progress towards attainment 

of the NAAQS. (See 42 U.S.C. § 7503(a)(1)(A))

Extinction. The attenuation of light due to scattering and 

absorption as it passes through a medium.

Fugitive Emissions. Emissions which do not pass through 

a stack, chimney, vent, or other functionally equivalent 

opening.

76 FLAG Phase I Report—Revised (2010)
Federal Land Manager (FLM). The Secretary of the 

Department with authority over such lands. [40 CFR 

§51.166(b)(24)] The FLM for the Department of the 

Interior has been delegated to the Assistant Secretary for 

Fish and Wildlife and Parks; the FLM for the Department 

of Agriculture has been delegated to the Forest Service, and 

has been redelegated to the Regional Forester or individual 

Forest Supervisor.

Flux. Gaseous uptake into plant tissue.

Green Line. The total pollutant loading (contributions from 

existing and proposed sources) below which there is a very 

high degree of certainty that no AQRV will be adversely 

affected. 

Haze. An atmospheric aerosol of sufficient concentration 

to be visible. The particles are so small that they cannot be 

seen individually, but are still effective attenuating light and 

reducing visual range. 

Hydrocarbons. Compounds containing only hydrogen and 

carbon. Examples: methane, benzene, and decane.

Hygroscopic. Readily absorbing moisture, as from the 

atmosphere.

Injury. Any physical or biological response to pollutants, 

such as a change in metabolism, reduced photosynthesis, 

leaf necrosis, premature leaf drop, or chlorosis.

LAER (Lowest Achievable Emissions Rate. The control 

level required of a source subject to nonattainment review. 

(See 40 CFR §51.165(a)(1)(xiii))

Limit of Acceptable Change. The amount of change that 

could occur without significantly altering an AQRV or 

sensitive receptor.

Micrometer. A unit of length equal to one millionth of a 

meter; the unit of measure for particle size.

Mie Theory. A complex mathematical model that allows the 

computation of the amount of energy (light) scattered by 

spherical particles.

N100. Number of hourly average concentrations ≥100 ppb. 

Natural Conditions. Conditions substantially unaltered 

by humans or human activities. As applied in the context 

of visibility, natural conditions include naturally occurring 

phenomena that reduce visibility as measured in terms of 

light extinction, visual range, contrast, or coloration.

Natural Visibility Conditions. Visibility conditions 

attributable to Rayleigh scattering and aerosol associated 

with natural processes. 

Nephelometer. An instrument that measures the amount of 

light scattered.

Nitrates. Those gases and aerosols that have origins in the 

gas-to-aerosol conversion of nitrogen oxides, e.g., NO2

 ; 

of primary interest are nitric acid and ammonium nitrate. 

Ammonium nitrate is very hygroscopic so its contribution to 

visibility impairment is magnified in the presence of water 

vapor.

Nitrogen Dioxide (NO2

). A gas consisting of one nitrogen 

and two oxygen atoms It absorbs blue light and therefore 

has a reddish-brown color associated with it.

Nonattainment Area. An area designated by the EPA 

Administrator pursuant to Section 107(d) of the Clean Air 

Act as having air quality which does not meet one or more 

National Ambient Air Quality Standard (NAAQS). For a list 

of nonattainment areas, see 40 CFR Part 81, Subpart C.

Oxidant Stipple. Small brown or black interveinal necrotic 

lesions on the adaxial surface of leaf tissue that can be 

attributed to exposure to ozone.

Phytotoxic. Poisonous to plants. 

Post-Construction Monitoring. Monitoring required as 

a permit condition that the permitting authority considers 

necessary to determine the effect emissions from a stationary 

source may have, or are having, on the air quality or on the 

AQRVs of an area. Such monitoring includes both “ambient” 

monitoring and “AQRV” monitoring and may involve 

short-term and long-term measurements made at locations 

representative of the greatest expected impacts.

PSD Increments. The maximum increases in ambient 

pollution concentrations allowed over baselines 

concentrations. See 40 CFR §51.166 (c) for increments for 

specific pollutants.

RACT (Reasonable Available Control Technology). The 

lowest emissions limit that a particular source can meet 

by the application of control technology that is reasonably 

available considering technological and economic feasibility.

Rayleigh Scattering. The scattering of light by particles 

much smaller than the wavelength of the light, e.g., 

molecular scattering in the natural atmosphere. 

Reconstructed Extinction. Extinction estimate that results 

from summing up the product of the mass of each measured 

particle species and the appropriate absorption or extinction 

coefficient. 

Red Line. The total pollutant loading (contributions from 

existing and proposed sources) at which there is a very high 

degree of certainty that at least one AQRV will be adversely 

affected. 

 USFS–NPS–USFWS 77
Regional Haze Visibility Impairment. Any humanly 

perceptible change in visibility (light extinction, visual 

range, contrast, coloration) from that which would have 

existed under natural conditions, caused predominantly by 

a combination of many sources from, and occurring over, a 

wide geographic area. 

Re-opener. A permit condition that requires the permitting 

authority, at a specified time after permit issuance, to 

review and revise, if necessary, the permit based on new 

information such as the findings from post-construction 

monitoring, updated emissions inventories, updated 

modeling, research, or information on air pollution effects to 

terrestrial, aquatic, and visibility resources.

Scattering. An interaction of a light with an object (e.g., a 

fine particle) that causes the light to be redirected in its path. 

Scattering Coefficient. Measure of the ability of particles 

to scatter light; measured in number proportional to the 

“amount” of light scattered per unit distance.

Screening Level or Screening Level Value (SLV). The 

concentration or dose of air pollution below which 

estimated impacts from a proposed new or modified source 

are considered insignificant. The SLV is dependent on 

existing air quality and on the condition of the AQRV of 

concern.

Sensitive Receptor. The AQRV, or part thereof, that is the 

most responsive to, or the most easily affected by the type 

of air pollution in question. For example, at Great Smoky 

Mountains National Park, spruce-fir forest is a sensitive 

receptor of the AQRV flora.

Sensitive Receptor Indicator. A measurable physical, 

chemical, biological, or social (e.g., odor) characteristic of 

a sensitive receptor. For example, for the sensitive receptor, 

Crater Lake, water clarity is a sensitive receptor indicator.

Stationary Source. A source of pollution that is well 

defined, such as the smokestack of a coal-fired power plant 

or smelter.

Sulfates. Those aerosols that have origins in the gas-toaerosol conversion of sulfur dioxide; of primary interest 

are sulfuric acid and ammonium sulfate. Sulfuric acid 

and ammonium sulfate are very hygroscopic so their 

contribution to visibility impairment is magnified in the 

presence of water vapor.

Sulfur Dioxide (SO2

). A gas consisting of one sulfur and two 

oxygen atoms. Of interest because sulfur dioxide converts to 

an aerosol.

SUM00. The sum of all hourly average concentrations above 

0 ppb.

SUM06. The sum of all hourly average concentrations at or 

above 60 ppb.

Target Load. The acceptable concentration or dose of an air 

pollutant that provides a reasonable margin of safety below 

the critical load. The target load should be achievable under 

existing conditions.

Transmissometer. An instrument that measures the amount 

of light extinction over a fixed, specified path length. 

Visibility Impairment. Any humanly perceptible change 

in visibility (visual range, contrast, coloration) from that 

which would have existed under natural conditions. [40 CFR 

§51.301(x)]

Visual Range. The distance at which a large black object 

would just disappear from view.

Volatile Organic Compound (VOC). Any compound of 

carbon, except those excluded by EPA that participates 

in atmospheric photochemical reactions. (See 40 CFR 

§51.100(s))

W126. An ozone index that multiplies each specific 

concentration by a sigmoidal weighted function, then 

sums all values. Wi = 1/[1 + Me-(A x Ci)], where M and A 

are constants 4403 and 126 ppm-1, respectively, wi

 is the 

weighting factor for ci

, and ci is concentration in ppm.

78 FLAG Phase I Report—Revised (2010)
Appendix B: Legal Framework 

for Managing Air Quality and Air 

Quality Effects on Federal Lands

Introduction 

The regulation of air pollution sources has clearly been 

delegated to EPA, and as applicable, the States. However, 

Federal Land Managers (FLMs) have the responsibility to 

protect the particular values of the lands over which they 

have jurisdiction, to the extent they have been delegated the 

authority, from the adverse impacts of activities inside and 

outside these areas.

This Appendix sets out the basic legal authorities and 

responsibilities with which the FLMs comprising FLAG 

must comply, in addition to those authorities which they can 

utilize to protect AQRVs on public lands.

For the purposes of this Appendix only, the term “public 

lands” is defined to include units of the National Park, 

National Wildlife Refuge, and National Forest Systems. 

Agency Organic Acts

Department of the Interior: National Park Service 

(NPS): 

This Organic Act is very specific in that it mandates national 

park unit managers: 

[T]o conserve the scenery and the natural and historic 

objects and wild life therein and to provide for the 

enjoyment of the same in such manner and by such means 

as will leave them unimpaired for the enjoyment of future 

generations. 

16 U.S.C. §1(1997); and 

[T]he authorization of activities shall be construed and 

the protection, management, and administration of these 

areas shall be conducted in light of the high public value 

and integrity of the National Park System and shall not be 

exercised in derogation of the values and purposes for which 

these various areas have been established, except as may 

have been or shall be directly and specifically provided for by 

Congress.

16 U.S.C. § 1a-1 (1997)

Department of the Interior: Fish and Wildlife 

Service (FWS): 

With respect to National Wildlife Refuge System lands 

(Refuge System lands under the jurisdiction of the United 

States Fish and Wildlife Service (FWS)), FWS managers are 

required to manage Refuge System lands so to: 

[E]nsure that the biological integrity, diversity, and 

environmental health of the System are maintained for the 

benefit of present and future generations of Americans. 

16 U.S.C. §668dd(a)(4)(B)(1997) 

Department of Agriculture: Forest Service (Forest 

Service) 

National Forest System lands are defined as: 

[A]ll National Forests reserved or withdrawn from the public 

domain of the United States, all national forests acquired 

through purchase, exchange, donation, or other means, all 

national grasslands and land utilization projects...and all 

lands waters, and other interests administered by the Forest 

Service. 

16 U.S.C. §1609(a)(1997) 

The Forest Service’s Organic Administration Act of 1897 

directs the Secretary of Agriculture to: 

[M]ake provisions for the protection against destruction by 

fire and depredations upon the public forests and national 

forests... 

16 U.S.C. Sec. §551(1997) 

The National Forest units are managed consistent with 

Land and Resource Management Plans (LRMPs) under the 

provisions of the National Forest Management Act (NFMA). 

16 §U.S.C. 1604 (1997). Any measures addressing AQRVs on 

National Forest System lands will be implemented through, 

and be consistent with, the provisions of an applicable 

LRMP or its revision (16 U.S.C. §1604(i)). 

The Secretary of Agriculture is required by law to prepare a 

Renewable Resource Assessment by 1979, and every 10 years 

thereafter. By law this Assessment is required to address: 

•	 A description of Forest Service programs in research, 

cooperative programs and management of the National 

Forest System, their relationships, and the relationships of 

these programs and responsibilities to public and private 

activities; and 

•	 An analysis of the potential effects of global climate 

change on the condition of renewable resources on the 

Forests and rangelands of the United States; and 

•	 An analysis of the rural and urban forestry opportunities 

to mitigate the buildup of atmospheric carbon dioxide 

and reduce the risk of global climate change. 

16 U.S.C. §1601(a) (1997)

In addition, the Secretary of Agriculture is required to 

prepare and transmit to the President, a Renewable Resource 

Program (the Program) every 5 years. This Program must 

include program recommendations which recognize the 

fundamental need to protect, and where appropriate, 

 USFS–NPS–USFWS 79
improve the quality of ... air resources. 16 U.S.C. §1602(5)

(C). 

The Forest Service’s implementing regulations for NFMA 

are found at 36 C.F.R. §219 et seq. LRMPs are, in part, 

specifically based on: 

[R]ecognition that the National Forests are ecosystems 

and their management for goods and services requires an 

awareness and consideration of the interrelationships among 

plants, animals, soil, water, air, and other environmental 

factors within such ecosystems. 

36 C.F.R. §219.1(b)(3)

The Wilderness Act. 16 U.S.C. §1131 (1997) 

AQRVs in Wilderness areas may receive further protection 

by the language of the Wilderness Act itself which states: 

Wilderness areas... shall be administered for the use of 

the American people in such a manner as will leave them 

unimpaired for future use and enjoyment as wilderness .... 

(16 U.S.C. Sec. §1131). 

For Wilderness Areas in the National Forest System, the 

Act’s implementing regulations are found at 36 C.F.R. §293. 

These Wilderness Areas shall be administered: 

...[For] such other purposes for which it may have been 

established in such a manner as to preserve and protect 

[their] wilderness character. In carrying out such purposes, 

National Forest Wilderness resources shall be managed 

to promote, perpetuate, and, where necessary, restore the 

wilderness character of the land... 

36 C.F.R. §293.2 (1997) 

The Clean Air Act, 42 U.S.C. §7401 et seq. 

Because of a perceived need for national and regional air 

quality research to support State programs, Congress passed 

its first federal air quality initiative in 1955. (Air Pollution 

Control Act of 1955, Ch. 360, 69 Stat. 322). In response 

to increasing harm to public health and welfare and to 

inadequate controls and enforcement, Congress has slowly 

but steadily expanded and refined the law, now known as the 

Clean Air Act (CAA), to cover more types of pollutants and 

emitters; e.g., stationary and mobile sources of pollution. 

These efforts have culminated in the 1990 Amendments 

to the CAA, which represent the most comprehensive and 

detailed set of measures to date to both prevent and curtail 

air pollution. 

The declaration of purpose, as revised in 1990 states in part: 

The purposes of this subchapter are: to protect and enhance 

the quality of the Nation’s air resources so as to promote the 

public health and welfare and the productive capacity of its 

population.

42 U.S.C. § 7401(b)(1); and 

A primary goal of this Act is to encourage or otherwise 

promote reasonable Federal, State, and local government 

actions, consistent with the provisions of this Act, for 

pollution prevention. 

42 U.S.C. §7401(c) 

The CAA provides an additional legal framework for FLMs 

to preserve and protect AQRVs from pollution sources 

emanating both within and outside National Park, Forest, 

and Refuge boundaries. 

National Ambient Air Quality Standards (NAAQS) 

and State Implementation Plans (SIPs): 

The CAA establishes a regulatory program with the goal 

of achieving and maintaining “national ambient air quality 

standards” (NAAQS) through state or, if necessary, federal 

implementation plans (SIPs or FIPs).1

 

The U.S. Environmental Protection Agency (EPA) is charged 

with promulgating: 

•	 “primary” NAAQS for “criteria” pollutants “to protect the 

public health,” allowing an adequate margin of safety;” 

and 

•	 “secondary” NAAQS “to protect the public welfare from 

any known or anticipated adverse effects associated with 

the presence of such air pollutant in the ambient air.”2

The above secondary standards may help protect public 

land AQRVs.3

 To date, EPA has promulgated NAAQS for 

six criteria pollutants: sulfur dioxide, particulate matter, 

nitrogen dioxide, carbon monoxide, ozone and lead. In 2006, 

EPA issued revised, and more stringent NAAQS for “fine 

particulate matter.” In 2008 EPA revised the ozone standard, 

to address human health and welfare concerns. In 2010, EPA 

promulgated one-hour standards for nitrogen dioxide and 

sulfur dioxide. However, EPA openly acknowledged that 

these revised NAAQS were not fully adequate to protect 

the above “secondary” values, in particular those sensitive 

AQRVs on public lands. EPA proposed further revisions 

to the primary and secondary ozone standards in January 

2010 and is currently developing a proposal for secondary 

NOx

 and SOx standards that are intended to address aquatic 

acidification due to acid deposition.

Prevention of Significant Deterioration (PSD): 

The CAA, as amended in 1977, includes the following 

major purposes regarding the “prevention of significant 

deterioration” (PSD) provisions: 

[T]o protect public health and welfare from any actual 

or potential adverse effect . . . from air pollution . . . 

80 FLAG Phase I Report—Revised (2010)
notwithstanding attainment and maintenance of all national 

ambient air quality standards.

42 U.S.C. § 7470(1)

[T]o preserve, protect, and enhance the air quality 

in national parks, national wilderness areas, national 

monuments, national seashores, and other areas of special 

national or regional natural, recreational, scenic, or historic 

value. 

42 U.S.C. §7470(2) 

The PSD section provides some protection for park and 

wilderness AQRVs through establishment of ceilings on 

additional amounts of air pollution over baseline levels in 

clean air areas (increments). It requires EPA or the State to 

provide to the FLM notice of any proposed major emitting 

facility4

 whose emissions may affect a Class I area (42 U.S.C. 

§7475(d)(2)(A), and also by charging: 

[T]he Federal Land Manager 1 and the Federal official 

charged with direct responsibility for management of such 

lands with “an affirmative responsibility to protect the air 

quality related values (including visibility) of any such lands 

within a class I area and to consider, in consultation with the 

Administrator, whether a proposed major emitting facility 

will have an adverse impact on such values. 

42 U.S.C. §7475(d)(2)(B). 

Class I areas include national parks larger than 6,000 acres 

and national wilderness areas and national memorial parks 

which exceed 5,000 acres, in existence on August 7, 1977. 

The 1990 Amendments provided that subsequent additions 

to the boundaries of such areas are also Class I areas. 

Currently, 48 areas in the National Park system, 21 Refuge 

System units, and 88 areas under the administration of the 

Forest Service are designated as Class I. 

Under the PSD provisions and implementing regulations 

(40 C.F.R. §51.166(p)), for Class I areas, once baseline 

concentrations come under review by submission of a 

PSD preconstruction permit application for a major new 

or modified emissions source, only the smallest increment 

of certain pollutants — sulfur dioxide, nitrogen oxide 

and particulate matter — may be added to the air by the 

proposed new source, and other “increment consuming” 

sources. 

Under the PSD provisions a FLM has several tools he/she 

may use to protect AQRVs. 

A state may not issue a PSD permit to allow construction or 

modification of a major emitting facility when the applicable 

Federal Land Manager files a notice alleging the facility 

may cause or contribute to a change in the Class I area’s air 

quality and by identifying the potential adverse impact of 

such a change, unless: 

The facility owner demonstrates that the facility’s emissions 

of particulate matter, sulfur dioxide, and nitrogen oxides will 

not cause or contribute to concentrations which will exceed 

the maximum allowable increases for that Class I area.

42 U.S.C. §7475(d)(2)(C)(i)(paraphrased) and 42 U.S.C. 

§7476. 

Even if no increment violation is predicted, 

[T]he state may not issue a PSD permit, if the Federal Land 

Manager demonstrates to the satisfaction of the State that 

the emissions from such facility will have an adverse impact 

on the air quality-related values (including visibility) of Class 

I lands. 

42 U.S.C. §7475(d)(2)(C)(ii)(paraphrased) 

Neither the CAA nor the implementing regulations specify 

criteria for the FLM to “satisfy” state permitting agencies. 

Consequently, some states have taken a liberal view of their 

discretion to reject an FLM’s adverse impact determination. 

However, EPA’s Environmental Appeals Board (the 

Board) has ruled that state discretion in rejecting a FLM’s 

finding of adverse impacts is not “unfettered” (see the 

Board’s decisions regarding the permit appeals for the Old 

Dominion Electric Cooperative and Hadson Power projects 

in Virginia). Nevertheless, the appropriate role of the FLM 

in the PSD permit process was addressed in EPA’s 1996 

proposed New Source Review Reform regulations. The final 

regulations have not yet been promulgated. 

Visibility Protection. Subpart II, 42 U.S.C. §7491 

et seq. (1997) 

The Visibility portion of the CAA: 

“... [D]eclares as a national goal the prevention of any future, 

and the remedying of any existing, impairment of visibility 

in mandatory class I Federal areas which impairment results 

from man made air pollution.” 

42 U.S.C. §7491(a)(1). 

To help carry out this goal, the Secretaries of the Interior and 

Agriculture are charged with identifying Class I areas where 

visibility is an important value. EPA is charged with reporting 

to Congress on methods to implement the national goal and 

with promulgating regulations to ensure reasonable progress 

toward meeting the goal. 

In 1980, EPA issued enforceable regulations for visibility 

impairment “reasonably attributable” to a specific source 

or small group of sources. In particular, major stationary 

sources emitting any pollutant which may “reasonably 

be anticipated to cause or contribute to any impairment 

of visibility” is required to install best available retrofit 

technology (BART). In addition, in April 1999 EPA 

promulgated final regulations addressing regional haze. 

 USFS–NPS–USFWS 81
The regional haze rule protects air quality in Class I areas 

by requiring States to plan to achieve “natural” visibility 

conditions over a 60-year time frame.

The 1990 Amendments added a new section on visibility, 

which authorizes EPA in conjunction with NPS and other 

federal agencies, to conduct visibility research and to 

evaluate clean air corridors and emissions sources and 

source regions causing visibility impairment in Class I areas. 

In this regard, EPA was required to establish the Grand 

Canyon Visibility Transport Commission (GCVTC) by 1991 

and consider the recommendations GCVTC would make 

(42 U.S.C. §7492(f). NPS, FS, FWS, and BLM played a vital 

role in the work of the GCVTC and committees in an effort 

to improve air quality in the Grand Canyon and other parks 

and wilderness areas in the “Golden Circle” on the Colorado 

Plateau. 

As part of the visibility protection process, states are 

required to promulgate a plan to prevent any future, and 

remedy any existing impairment of visibility in Class I 

areas... 40 C.F.R. §51.300 (1997). EPA has defined “visibility 

impairment” as: 

[A]ny humanly perceptible change in visibility (visual range, 

contrast, coloration) from that which would have existed 

under natural conditions. 

40 C.F.R. §51.301(x)(1997).7 

However, EPA has promulgated its visibility regulations 

to allow FLMs to use their existing authorities to 

address “visibility impairment” (rather than “significant 

impairment”) so that “the affected Federal Land Manager 

may certify to the State, at any time, that there exists 

impairment of visibility in any mandatory Class I Federal 

area.” 40 C.F.R. §51.302(c). 

Nonattainment Areas, 42 U.S.C. §7501 et seq.: 

Areas that have failed to meet NAAQS for one or more 

criteria pollutants are designated as “nonattainment” areas. 

Under the 1990 Amendments, Congress provides for further 

classification of nonattainment areas based on severity of the 

nonattainment and availability and feasibility of appropriate 

pollution control measures and for a compliance schedule 

ranging from 1993 in marginal nonattainment areas to 2010 

for Los Angeles. 

The 1990 Amendments authorize EPA to issue control 

technique guidance documents (CTGs) covering a variety 

of topics, such as control of idling vehicles and voluntary 

removal of pre-1980 model year light duty vehicles (cash 

for clunker programs). (42 U.S.C. §7408.) EPA is authorized 

to issue CTGs, in lieu of regulations, to reduce “volatile 

organic compounds” (VOC) emissions from any consumer 

or commercial product. (42 U.S.C. §7511b.) 

Proposed new or modified major stationary sources within 

nonattainment areas are required to meet emissions limits 

based on “lowest achievable emission rate” technology 

(LAER) and may be constructed only if their emissions are 

sufficiently offset by reductions in emissions from other 

sources. The 1990 Amendments also require analysis of 

alternative sites, sizes, production processes, and control 

techniques and a finding that the benefits of the source 

outweigh its environmental and social costs. (42 U.S.C. 

§7501-15.) 

General 

CAA Subchapter III 42 U.S.C. §7601 et seq. contains 

definitions, requirements for reports to Congress, 

authorizations for appropriations, and procedures for EPA 

rule making and judicial review. Citizen suits are authorized: 

1) against EPA for failure to perform a nondiscretionary duty 

under the CAA, or 2) against others for alleged violations of 

an emission limitation, standard, or order. (42 U.S.C.§7601 et 

seq.) 

Acid Deposition 

The 1990 Amendments add Title IV, which contains 

requirements for electric utilities to reduce emissions 

associated with acid rain. To reduce the adverse effects of 

acid deposition, Title IV requires a reduction in annual 

emissions of sulfur dioxide of ten million tons from 1980 

emission levels and a reduction of nitrogen oxides emissions 

of approximately two million tons from 1980 emission levels, 

in the 48 contiguous states and the District of Columbia. (42 

U.S.C. §7651.) The Title creates a system of market-based 

emission allowances, which can be traded among sources. 

See (42 U.S.C. §7651a-o.) 

Operating Permits 

The 1990 Amendments add Subchapter V, 42 U.S.C. §7661 

et seq., which establishes a nation-wide permit program for 

existing stationary sources. Permit requirements will include 

emission limitations. EPA may veto state permits, which do 

not comply with provisions of the CAA. (42 U.S.C. §7661a-f.) 

Conformity, 42 U.S.C. §7506 (1997) 

(Paraphrased) No federal agency may engage in, support 

in any way,... license or permit, or otherwise approve any 

activity which does not conform to an approved state 

(or federal) implementation plan. Conformity shall be 

an affirmative responsibility of the head of each agency. 

Conformity means: 

•	 Conforming to the SIP’s purpose of eliminating or 

reducing the number of NAAQS violations; 

•	 That any such activities will not: 

- Cause or contribute to new violations in any area; or 

82 FLAG Phase I Report—Revised (2010)
- Increase the frequency or severity of any existing 

standard violation... 

EPA, in its “criteria and procedures” for implementing 

“conformity” has decided that only those activities that “a 

federal agency can practicably control, and will maintain 

control over due to a continuing program responsibility” are 

subject to same. 40 C.F.R. §93.152. 

Although required to comply with the conformity provisions 

(42 U.S.C. §7618(1997)), the FLM cannot use these 

provisions to protect AQRVs from adverse impacts from off 

site sources. 

Impact on Federal Land Managers

The CAA reinforces the FLMs’ Organic Act and Wilderness 

Act roles as protectors of AQRVs on public lands.

The CAA also imposes on FLMs an obligation to comply 

with the Act’s many provisions regarding the abatement of 

air pollution to the same extent as any private person (42 

U.S.C. §7418). 

Thus, under various authorities, FLMs are responsible for 

protecting AQRVs within their respective unit boundaries 

and taking appropriate action to do so, when reviewing 

emission sources both within units, and in proximity to unit 

boundaries. 

FLMs, under the CAA, have an affirmative responsibility 

for protecting AQRVs (including visibility) in reviewing 

proposed PSD permits. However, because of the uncertainty 

involved in “satisfying” State permitting agencies in the PSD 

process, and the appropriate delegated role for FLMs in 

non-PSD situations, the existing framework may provide an 

inadequate means for FLMs to protect AQRVs from adverse 

impacts caused by sources outside unit boundaries. 

Endnotes

1) Clean Air Act, 42 U.S.C. §7401-7671q (as amended 1990). 

2) Clean Air Deskbook, The Environmental Law Reporter, 

Environmental Law Institute, 1992. 

3) Managing National Park System Resources: A Handbook on 

Legal Duties, Opportunities, and Tools, Chap. 4 “The Clean 

Air Act” by Molly Ross at pp. 51-65, The Conservation 

Foundation, 1990. 

4) Atmospheric Environment Vol. 27B, No. 1, “The 20-Year 

History of the Evolution of Air Pollution Control Legislation 

in the U.S.A.” by Richard H. Schulze at pp. 15-25., 1993 

5) Wilderness Act of 1964, 16 U.S.C. §1131 et seq, P.L. 577, 

78 stat 890 as amended. 

6) The Principal Laws Relating to Forest Service Activities, 

USDA - Forest Service ISBN 0-16-041927-1, 1993 

7) Organic Administration Act of 1897, 16 U.S.C. §473-475, 

§477-482, §551.

 USFS–NPS–USFWS 83
Appendix C: General Policy for 

Managing Air Quality Related 

Values in Class I Areas 

Most Federal Land Manager (FLM) enabling legislation 

and regulations developed to implement Federal Laws 

do not directly address air quality, or air pollution effects 

on Parks or Wildernesses. They do, however, provide 

broad direction on what should be protected in Parks and 

Wildernesses (the earth and its community of life) and 

to what degree (preserve natural conditions or conserve 

resources unimpaired). Accordingly, FLMs have developed 

the following policies related to air quality and Class I areas:

1. Class I areas are not merely a commodity for human use 

and consumption. Park and Wilderness ecosystems have 

intrinsic values other than user/public concerns.

2. A principal objective of FLM management is to offer a 

natural user experience, rather than strictly an enjoyable 

one. The amount of enjoyment is purely a personal 

matter for the individual user to decide.

3. All Class I components are equally important; none is of 

lesser value than another.

4. A Class I component is important even if users of the area 

are unaware of its existence.

5. All life forms are equally important. For example, 

microorganisms are as essential as elk, wild flowers, or 

grizzly bears.

6. The goal of Class I management is to protect not only 

resources with immediate aesthetic appeal (i.e., sparkling 

clean streams) but also unseen ecological processes (such 

as natural biodiversity and gene pools).

7. The most sensitive Class I components are to be 

emphasized more than those of “average” or “normal” 

sensitivity. Sensitivity is generally determined by inertia 

(resistance to change), elasticity (how far the component 

can be stretched from its natural condition without 

being permanently modified), and resiliency (the number 

of times it can revert to its natural condition after 

experiencing human-caused change).

8. Each Class I component is important in itself; as well as 

in terms of how it interacts with other components of 

the ecosystem. That is, the individual parts of the Class I 

ecosystem are as significant as the sum of the parts.

9. The physical components of the ecosystem (for 

instance, lake chemistry) are as essential as its biological 

constituents (i.e., salamanders). That is, the earth is as 

essential as the community of life.

10. Class I components are to be protected from “humancaused change” rather than from “damage.” Terms 

such as “damage” and “harm” are prejudicial, whereas 

“human-caused change” is value-neutral. (For example, 

deposits of nitrogen in a lake from nitrogen oxide, a 

common air pollutant, might result in more plant growth 

and larger fish. This would, however, be an unnatural 

- and therefore unacceptable - change in the aquatic 

ecosystem).

11. The goal of Class I management is to protect natural 

conditions, rather than the conditions when first 

monitored. That is, if initial monitoring in a Class I area 

identifies human-caused changes, appropriate actions 

should be taken to remedy them, in order to move 

towards a more natural condition.

12. The designation of a Park or Wilderness as Class I or II 

does not dictate the management goals for it; these are 

identified in the enabling legislation. The designation 

only determines which options are available to meet 

the goals. Class I Parks or Wildernesses, for instance, 

can be protected through AQRV analysis, whereas the 

protection of Class II Parks and Wildernesses can be 

achieved using BACT requirements.

13. The FLMs will do their best to manage and protect 

resources at every area that they administer. 

14. Although monitoring is critical to many air resource 

management decisions, it must not interfere needlessly 

with Park or Wilderness. Where possible, the most 

intrusive monitoring and instrumentation should be 

conducted adjacent to the Class I area - if such areas 

adequately represent the area of concern.

84 FLAG Phase I Report—Revised (2010)
Appendix D: Best Available 

Control Technology (BACT) 

Analysis

Given the need to minimize emissions and their resulting 

air quality impacts, the FLMs recommend that the applicant 

conduct the BACT analysis using EPA’s top-down approach. 

In brief, a top-down process ranks all available control 

technologies in descending order of control effectiveness. 

All of the available control systems for the source, including 

the most stringent, must be considered. The applicant 

first examines the most effective, or top, alternative. That 

alternative is established as the BACT unless the applicant 

demonstrates, and the permitting authority agrees, that 

technical considerations, or energy, environmental, or 

economic impacts justify a conclusion that the most 

stringent technology is not achievable in that case. FLMs 

utilize EPA’s BACT/RACT/LAER Clearinghouse, and other 

information, for assessing control technologies proposed by 

permit applicants.

If the most stringent technology is eliminated in this fashion, 

then the next most stringent alternative is considered, and so 

on. Permit applicants should refer to chapter B of the EPA 

Draft New Source Review Workshop Manual for a detailed 

discussion of the top-down policy (EPA 1990). 

The FLM reviews the applicant’s BACT analysis to 

determine if the best available pollution control technology 

is being proposed, thereby minimizing the proposed 

emission increases and their corresponding impact on the 

FLM area in question. The FLM does this by comparing 

the proposed controls to recent BACT determinations for 

similar facilities. If the FLM disagrees with the applicant’s 

BACT analysis, technical comments are submitted to the 

permitting authority that has the ultimate responsibility to 

make the BACT determination and issue the permit. 

The environmental impacts analysis of the BACT review is 

not to be confused with the air quality-related analysis. The 

environmental impacts analysis of the BACT review should 

concentrate on impacts other than ambient air quality 

impacts of the regulated pollutant in question, such as 

solid or hazardous waste generation, discharges of polluted 

water from a control device, or emissions of unregulated 

pollutants. Thus, the fact that a given control alternative 

would result in only a slight improvement in ambient 

concentrations of the pollutant in question when compared 

with a less stringent control alternative, should not be 

viewed as a basis for rejecting the more stringent control 

alternative.

Regarding the economic impact analysis, given the special 

protection Class I areas are afforded under the Clean Air Act, 

FLMs believe that the need to minimize potential impacts 

on a Class I area should be a major consideration in the 

BACT determination for a project proposed near such an 

area. Therefore, if a source proposes to locate near a Class 

I area, additional costs to minimize impacts on sensitive 

Class I resources may be warranted, even though such costs 

may be considered economically unjustified under other 

circumstances.

 USFS–NPS–USFWS 85
Appendix E: Maps of Federal 

Class I Areas

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Bryce

Canyon NP

TX

MT

AZ

ID

NV IL

NM

CA

CO

KS

UT NE

SD

WY IA

OR

MN

ND

OK

WI

FL

AL

AR

MO

GA

LA

PA

IN

WA

MI

NY

NC TN

MS

KY

VA

OH

SC

WV

VT

NJ

MDDE

MA

CT

ME

NH

RI

Bandelier NM

Acadia NP

Big

Bend NP

Canyonlands NP

Capitol

Reef

NP

Crater

Lake NP

Craters of

the Moon NM

Everglades NP

Grand

Canyon NP

Grand

Teton NP

Great Smoky

Mountains NP

Guadalupe

Mountains NP

Isle

Royale NP

Mount

Rainier NP

North

Cascades NP

Olympic NP

Pinnacles

NM

Redwood NP

Rocky

Mountain NP

Saguaro NP

Shenandoah NP

Chiricahua NM

Mammoth

Cave NP

Yosemite NP

Sequoia /

Kings Canyon NP

Great Sand

Dunes NP & Pres

Point

Reyes NS

Wind

Cave NP

Glacier NP

Arches NP

Joshua

Tree NP

Voyageurs NP

Theodore

Roosevelt NP

Petrified

Forest NP

Lava

Beds NM

Zion NP

Badlands NP

Carlsbad

Caverns NP

Lassen

Volcanic NP

Yellowstone NP

Mesa

Verde NP

Black Canyon of the Gunnison NP

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AK Denali

NP & Pres

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Haleakala NP

Hawaii

Volcanoes NP

PR ! VI

Virgin

Islands NP

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0 250 500 1,000 Kilometers

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Figure 8. National Park Service Class I Areas

Map produced by the National Park Service Air Resources Division March 2010.

86 FLAG Phase I Report—Revised (2010)
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NM

CA

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SD

WY IA

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MN

ND

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88 FLAG Phase I Report—Revised (2010)
Appendix F: FLAG 2000 Participants

The individuals listed in the attached table participated in the development of the FLAG Phase I Report (December 2000). 

The contact information was not updated as part of this FLAG 2010 revision. The abbreviations for the FLAG subgroup or 

committee on which participants served are shown below.

LC = Leadership Committee

CC = Coordinating Committee

P = Policy Subgroup

V = Visibility Subgroup

O = Ozone Subgroup

D = Deposition Subgroup

T = Terminology (Glossary) Subgroup

FLAG 2000 Participants

Name Subgroup Organization Work Phone Fax Email Address

Acheson, Ann* V Forest Service (406) 329-3493 (406) 329-3132 aacheson@fs.fed.us

Ahuja, Suraj O,V,D Forest Service (530) 934-3316 (530) 934-7384 sahuja@fs.fed.us

Bachman, Bob* CC,V,D,T Forest Service (503) 808-2918 (503) 808-2973 rbachman@fs.fed.us

Bayle, Bruce* P Forest Service (404) 347-3872 (404) 347-6197 bbayle@fs.fed.us

Benoit, Clif* V,P Forest Service -- -- --

Blanchard, Karen* EPA (919) 541-5503 (919) 541-5509 blanchard.karen@epamail.epa.gov

Blett, Tamara* Forest Service -- -- --

Boutcher, Steve Forest Service (503) 326-5434 (503) 808-2973 sboutcher@fs.fed.us

Bray, David T,V EPA (206) 553-4253 (206) 553-0110 bray.dave@epamail.epa.gov

Breitenfeld, Dale* Park Service -- -- --

Bunyak, John P,T Park Service (303) 969-2818 (303) 969-2822 john_bunyak@nps.gov

Bytnerowicz, A. O Forest Service (909) 680-1562 (909) 680-1501 andrzej@deltanet.com

Carriero, Joe* CC,T Fish and Wildlife -- -- --

Copeland, Scott V CIRA (CSU) (970) 491-3315 (970) 491-8598 copeland@cira.colostate.edu

Fisher, Rich* CC,V,P,O,T Forest Service (970) 498-1232 (970) 498-1010 rfisher@lamar.colostate.edu

Flores, Miguel* P,O Park Service -- -- --

Haddow, Dennis* P,V,T Forest Service (303) 275-5759 (303) 275-5759 dhaddow@fs.fed.us

Hogsett, Bill O EPA (541) 754-4632 (541) 754-4739 bill@heart.cor.epa.gov

Huber, Cindy V Forest Service (540) 265-5156 (540) 265-5145 chuber@fs.fed.us

Irwin, John V EPA (919) 541-5682 (919) 541-0044 irwin.john@epamail.epa.gov

Jackson, Bill O Forest Service (704) 257-4815 (704) 257-4263 bjacksono2@fs.fed.us

Lamb, Donna* LC Forest Service (202) 205-0800 (202) 205-1096 dlamb@fs.fed.us

Malm, Bill V Park Service (970) 491-8292 (970) 491-8598 malm@cira.colostate.edu

Maniero, Tonnie* CC,O Park Service (303) 969-2806 (303) 969-2822 tonnie_maniero@nps.gov

Morris, Kristi Park Service (303) 987-6941 (303) 969-2822 kristi_morris@nps.gov

Morse, Dee CC,V Park Service (303) 969-2817 (303) 969-2822 dee_morse@nps.gov

Musselman, Bob O,D Forest Service (970) 498-1239 (970) 498-1010 bobm@lamar.colostate.edu

Notar, John V Park Service (303) 969-2079 (303) 969-2822 john_notar@nps.gov

*No longer works for the agency or now works for a different office.

 USFS–NPS–USFWS 89
FLAG 2000 Participants

Name Subgroup Organization Work Phone Fax Email Address

Parker, Kim* D,O Forest Service -- -- --

Peterson, Dave O BRD (206) 543-1587 (206) 695-0790 wild@u.washington.edu

Peterson, Janice O,D Forest Service (425) 744-3425 (425) 744-3255 jpeterson@fs.fed.us

Pitchford, Mark V NOAA (702) 895-0432 (702) 895-0507 MarcP@snsc.dri.edu

Pitt, Ken P USDA/OGC (303) 275-5539 (303) 275-5557 kenneth.pitt@usda.gov

Porter, Ellen* CC,D Fish and Wildlife (303) 969-2617 (303) 969-2822 ellen_porter@nps.gov

Potter, Debby* P,D Forest Service (505) 842-3143 (505) 842-3800 dapotter@fs.fed.us

Procter, Trent O Forest Service (559) 784-1500 (559) 781-4744 tprocter@fs.fed.us

Renfro, Jim O Park Service (423) 436-1708 (423) 436-5598 jim_renfro@nps.gov

Riebau, Al D Forest Service (202) 205-1524 (202) 205-1054 ariebau@fs.fed.us

Rocchio, Judy O Park Service (415) 427-1431 (415) 427-1487 judy_rocchio@nps.gov

Rolofson, Bud* V Fish and Wildlife (303) 969-2804 (303) 969-2822 bud_rolofson@nps.gov

Scruggs, Mark* V Park Service (303) 969-2077 (303) 969-2822 mark_scruggs@nps.gov

Shaver, Chris LC Park Service (303) 969-2074 (303) 969-2822 chris_shaver@nps.gov

Shepherd, Don Park Service (303) 969-2075 (303) 969-2822 don_shepherd@nps.gov

Silva, Sandra LC Fish and Wildlife (303) 969-2814 (303) 969-2822 sandra_silva@nps.gov

Stottlemyer, Bob D USGS/BRD (970) 498-1017 (970) 498-1010 crhoades@lamar.colostate.edu

Thomas, Jerome Forest Service (803) 561-4000 (803) 561-4004 jthomas@fs.fed.us

Tonnessen, Kathy* D Park Service -- -- --

Vimont, John V Park Service (303) 969-2808 (303) 969-2822 john_vimont@nps.gov

*No longer works for the agency or now works for a different office.

90 FLAG Phase I Report—Revised (2010)
Appendix G: Bibliography 

(Revised)

Some of the documents cited below were referenced in 

this FLAG Phase I Report. Others are listed to provide 

background information.

Aber, J.D., K.J. Nadelhoffer, P. Steudler and J.M. Melillo. 

1989. Nitrogen saturation in northern forest ecosystems: 

excess nitrogen from fossil fuel combustion may stress the 

biosphere. BioScience 39:378-386.

Aber, J.D., Magill A, McNulty SG, Boone RD, Nadelhoffer 

KJ, Downs M, Hallett R. 1995. Forest biogeochemistry 

and primary production altered by nitrogen saturation. 

Water, Air and Soil Pollution 85: 1665–1670.

Adams, M.B., D.S. Nichols, C.A. Federer, K.F. Jensen and 

H. Parrott. 1991. Screening Procedure to Evaluate Effects 

of Air Pollution on Eastern Region Wildernesses Cited as 

Class I Air Quality Areas. General Technical Report NE151. U.S. Department of Agriculture, Forest Service, 

Northeastern Forest Experiment Station. Radnor, 

Pennsylvania.

Adams, M.B., T.R. Angradi and J.N. Kochenderfer. 1997. 

Stream water and soil solution responses to 5 years of 

nitrogen and sulfur additions at the Fernow Experimental 

Forest, West Virginia. Forest Ecology and Management

95:79-91.

Ames, R.B., and Malm, W.C. 2001.Chemical Species’ 

Contributions to the Upper Extremes of Aerosol Fine 

Mass. Atmospheric Environment. 35:5193-5201.

Anderson, J.B., R.E. Baumgardner, V.A. Mohnen and J.J. 

Bowser. 1999. Cloud chemistry in the eastern United 

States, as sampled from three high-elevation sites along 

the Appalachian Mountains. Atmospheric Environment 

33:5105-5114.

Ashmore, M., Emberson, L., Karlsson, P. E., Pleijel, H. 

2004. New directions: a new generation of ozone 

critical levels for the protection of vegetation in Europe 

(correspondence). Atmospheric Environment. 38: 2213-

2214.

Ashmore, M.R. and A.W. Davison. 1996. Towards a critical 

level of ozone for natural vegetation. In: Kaerenlampi, L. 

and L. Skaerby, eds. Critical Levels for Ozone in Europe: 

Testing and Finalizing the Concepts. UN-ECE Workshop 

Report. University of Kuopio, Department of Ecology 

and Environmental Science. p. 58-71.

Au, S. 1974. Vegetation and Ecological Processes on 

Shackleford Bank, North Carolina. Scientific Monograph 

Series No. 6. U.S. Department of the Interior, National 

Park Service. Washington, D.C. 86 pp.

Baldocchi, D. D., B. B. Hicks and P. Camara. 1987. A canopy 

stomatal resistance model for gaseous deposition to 

vegetated surfaces. Atmospheric Environment. 21, 91-101.

Baron, J.S. and D.H. Campbell. 1997. Nitrogen fluxes 

in a high elevation Colorado Rocky Mountain basin. 

Hydrological Processes 11:783-799.

Binkley, D., C. Giardina, I. Dockersmith, D. Morse, M. 

Scruggs and K. Tonnessen. 1997. Status of Air Quality and 

Related Values in Class I National Parks and Monuments 

of the Colorado Plateau. U.S. Department of the Interior, 

National Park Service, Air Resources Division. Denver, 

Colorado.

Bormann, F. H. and G. E. Likens. 1967. Nutrient cycling. 

Science 155:424-429.

Brace, S., D.L. Peterson and D. Horner. 1998. Diagnosing 

Ozone Injury in Vascular Plants of the Pacific Northwest. 

PNW-GTR-xxx (In Press). U.S. Department of Agriculture, 

Forest Service, Pacific Northwest Research Station.

Bunyak, J. 1993. Permit Application Guidance for New 

Pollution Sources. Natural Resources Report NPS/

NRAQD/NRR-93. U.S. Department of the Interior, 

National Park Service, Air Quality Division. Denver, 

Colorado.

Burns, Douglas A.; Blett, Tamara; Haeuber, Richard; Pardo, 

Linda H. 2008. Critical Loads as a Policy Tool for 

Protecting Ecosystems from the Effects of Air Pollutants. 

Frontiers in Ecology and the Environment: 6(3) 156-159.

Byron, E. R. and P. Eloranta. 1984. Recent historical 

changes in the diatom community of Lake Tahoe, 

California-Nevada, U.S.A. Verh. Internat. Verin. Limnol. 

22:1372-1376.

Bytnerowicz, A., J. J. Carroll, B. K. Takemoto, P. R. Miller, 

M. E. Fenn, R. C. Musselman. 2000. Distribution and 

transport of air pollutants to vulnerable California 

ecosystems. In: K. M. Scow, G. E. Fogg, M. L. Johnson. 

Integrated Assessment of Ecosystem Health. Lewis 

Publishers, Boca Raton, 93-118.

Bytnerowicz, A., M. E. Fenn 1996. Nitrogen deposition in 

California forests: a review. Environmental Pollution, 92, 

127-146.

 USFS–NPS–USFWS 91
Bytnerowicz, A., M. E. Fenn, P. R. Miller, M. J. Arbaugh. 

1999. Wet and dry pollutant deposition to the mixed conifer 

forest. In: P. R. Miller and J. R. McBride (eds.) Oxidant 

Air Pollution Impacts in the Montane Forests of Southern 

California. Springer, New York, 235-269.

Bytnerowicz, A., S. Ferguson, F. Fujioka, R. Ottmar, M. 

Poth. 1997. Simulation modeling: role and status. In: 

A. Bytnerowicz (tech. ed.) Atmospheric and Biospheric 

Interactions of Gases and Energy in the Pacific Region of 

the United States, Mexico and Brazil. USDA FS, Pacific 

Southwest Research Station, General Technical Report, 

PSW-GTR-161, 27-30.

California Air Resources Board (CARB). 1993. The 

Atmospheric Acidity Protection Program: Annual Report 

to the Governor and Legislature, 1992. Sacramento, 

California.

Campbell, D.H., D.W. Clow, G.P. Ingersoll, M.A. Mast, 

N.E. Spahr and J.T. Turk. 1995. Processes controlling 

the chemistry of two snowmelt-dominated streams 

in the Rocky Mountains. Water Resources Research

31(11):2811-2821.

CENR. 1999. The role of monitoring networks in the 

management of the Nation’s air quality. Report of the 

National Science and Technology Council Committee on 

Environment and Natural Resources. Washington, D.C. 

Chappelka, A.H., L.J. Samuelson, J.M. Skelly, A.S. Lefohn 

and D. Nesdill. 1995. Effects of Ozone on Vegetation 

in Southern Appalachians: an Annotated Bibliography. 

Auburn University, School of Forestry. Auburn, Alabama.

Chow, J.C., Bachmann, J.D., Wierman, S.S.G., Mathai, C.V., 

Malm, W.C., White, W.H., Mueller, P.K., Kumar, N., 

Watson, J.G. 2002. Critical Review Discussion: Visibility: 

Science and Regulation. Journal of the Air and Waste 

Management Association. 52:973-999

Colorado State University. Cooperative Institute for 

Research in the Atmosphere. 1996. IMPROVE, 

Interagency Monitoring of Protected Environments. Spatial 

and Seasonal Patterns and Long Term Variability of the 

Composition of the Haze in the United States: An Analysis of 

Data from the IMPROVE Network.

Cosby, B.J., R.F. Wright and E. Gjessing. 1995. An 

acidification model (MAGIC) with organic acid evaluated 

using whole-catchment manipulations in Norway. J. 

Hydrol. 170:101-122.

Cosby, B.J., R.F. Wright, G.M. Hornberger and J.N. Galloway. 

1985. Modeling the effects of acid deposition: assessment 

of a lumped parameter model of soil water and stream 

water chemistry. Water Resources Research 21:51-63.

Cosby, B.J., S.A. Norton and J.S. Kahl. 1996. Using a pairedwatershed manipulation experiment to evaluate a 

catchment-scale biogeochemical model. Science of the 

Total Environment 183:49-66.

Davis, D.D. 1995. Evaluation of Ambient Ozone Injury on 

the Foliage of Vegetation in the Edwin B. Forsythe National 

Wildlife Refuge, Brigantine, New Jersey. Final Report.

Davis, D.D. 1998a. Evaluation of Ambient Ozone Injury on the 

Foliage of Vegetation in the Cape Romain National Wildlife 

Refuge, South Carolina. 1997 Observations.

Davis, D.D. 1998b. Evaluation of Ozone Injury on Vegetation 

in the Okefenokee National Wildlife Refuge, Georgia. 1997 

Observations.

Dennis, R.L., R. Haeuber, T. Blett, J. Cosby, C. Driscoll, 

J. Sickles and J.M. Johnston. 2007. Sulfur and nitrogen 

deposition on terrestrial and freshwater ecosystems in 

the United States. Air & Waste Management Association 

Environmental Manager. pp 12-17.

Dise, N. and R.F. Wright. 1995. Nitrogen leaching from 

European forests in relation to nitrogen deposition. Forest 

Ecology and Management 71:153-161.

Dixon, L.K. and E.D. Estevez. 2000. Reservoirs of nitrogen 

and phosphorus across a multiple source, nitrogen-enriched, 

estuarine gradient. Draft report to the Air Quality Branch, 

U.S. Fish and Wildlife Service, Denver, Colorado.

Driscoll CT, Whitall D, Aber J, Boyer E, Castro M, Cronan 

C, Goodale CL, Groffman P, Hopkinson C, Lambert 

K, Lawrence G, Ollinger S. 2003. Nitrogen pollution 

in the northeastern United States: sources, effects, and 

management options. BioScience 53:357-374.

Eckert, R., R. Kohut, J. Laurence, P. King, T. Lee, B. Rock, 

D. Moss and A. Theisen. 1991. Studies to Assess the Effects 

of Ozone on Native Vegetation of Acadia National Park. 

Annual Report. University of New Hampshire. Durham, 

New Hampshire.

Ecological Society of America. 2000. Acid deposition: the 

ecological response. Workshop Report. March 1-3, 1999. 

Washington, D.C.

Eilers, J. M., C.L. Rose and T.J. Sullivan. 1994. Status of 

Air Quality and Effects of Atmospheric Pollutants on 

Ecosystems in the Pacific Northwest Region of the National 

Park Service. Technical Report NPS/NRAQD/NRTR94/160. U.S. Department of the Interior, National Park 

Service, Air Quality Division. Denver, Colorado.

92 FLAG Phase I Report—Revised (2010)
Environmental Protection Agency (EPA). 1990. Draft New 

Source Review Workshop Manual; Prevention of Significant 

Deterioration and Nonattainment Area Permitting. Office 

of Air Quality Planning and Standards. Research Triangle 

Park, North Carolina. 322 pp.

Environmental Protection Agency (EPA). 1992a. Summary 

of Selected New Information on Effects of Ozone on Health 

and Vegetation: Supplement to 1986 Air Quality Criteria 

for Ozone and Other Photochemical Oxidants. EPA/600/8-

88/105F. Research Triangle Park, NC: US Environmental 

Protection Agency, Office of Health and Environmental 

Assessment.

Environmental Protection Agency (EPA). 1992b. User’s 

Manual for the Plume Visibility Model, PLUVUE II 

(Revised). EPA-454/B-92-008.

Environmental Protection Agency (EPA). 1992c. Workbook 

for Visual Impact Screening and Analysis (Revised). EPA450/R-92-023

Environmental Protection Agency (EPA). 1995. Acid 

Deposition Standard Feasibility Study Report to Congress. 

EPA 430-R-95-001a.

Environmental Protection Agency (EPA). 1996a. Addendum 

to the User’s Manual for the Plume Visibility Model, 

PLUVUE II (Revised). EPA-454/B-95-001.

Environmental Protection Agency (EPA). 1996b. Air Quality 

Criteria for Ozone and Related Photochemical Oxidants. 

Vol. 2. EPA/600/P-93/004bF. EPA, Office of Research and 

Development. Research Triangle Park, North Carolina.

Environmental Protection Agency (EPA). 1996c. CALMET, 

CALPUFF, and CALPOST Modeling System. PB 96-502-

083INC.

Environmental Protection Agency (EPA). 1996d. Proposed 

Rule, New Source Review Reform, Federal Register/Vol. 61, 

No. 142/Tuesday, July 23, 1996.

Environmental Protection Agency (EPA). 1996e. Review 

of National Ambient Air Quality Standards for Ozone 

Assessment of Scientific and Technical Information. OAQPS 

Staff Paper. EPA-452/R-96-007. EPA, Office of Air Quality 

Planning and Standards. Research Triangle Park, North 

Carolina.

Environmental Protection Agency (EPA). 1997. Mercury 

Study Report to Congress. EPA-452/R-97-003. U.S. 

Environmental Protection Agency, Office of Air, 

Washington, DC.

Environmental Protection Agency (EPA). 1998a. Interagency 

Work Group on Air Quality Modeling (IWAQM) Phase 

2 Summary Report and Recommendations for Modeling 

Long-Range Transport and Impacts on Regional Visibility. 

EPA-454/R-98-019.

Environmental Protection Agency (EPA). 1998b. Interim Air 

Quality Policy on Wildland and Prescribed Fires. Office of 

Air Quality Planning and Standards. Research Triangle 

Park, North Carolina. 39 pp.

Environmental Protection Agency (EPA). 2000a. Deposition 

of Air Pollutants to the Great Waters: Third Report to 

Congress. EPA-453/R-00-005. U.S. Environmental 

Protection Agency, Office of Air Quality Planning and 

Standards, Research Triangle Park, NC.

Environmental Protection Agency (EPA). 2000b. National 

Air Quality and Emissions Trends Report, 1998. EPA 454/

R-00-003.

Environmental Protection Agency (EPA). 2005. 70 FR 59582, 

October 12, 2005, at p.59614.

Environmental Protection Agency (EPA). 2007a. Integrated 

Science Assessment for Oxides of Nitrogen and Sulfur – 

Environmental Criteria. EPA/600/R-07/145A.

Environmental Protection Agency (EPA). 2007b. Review of 

the National Ambient Air Quality Standards for Ozone: 

Policy Assessment of Scientific and Technical Information. 

EPA-452/R-07-007.

Environmental Protection Agency (EPA). 2009a. Acid Rain 

and Related Programs: 2007 Progress Report. 

Environmental Protection Agency (EPA). 2009b. The 

National Study of Chemical Residues in Lake Fish Tissue. 

EPA-823-R-09-006. U.S. Environmental Protection 

Agency, Office of Water, Washington, DC

Environmental Protection Agency (EPA). 2010a. Proposed 

Rule, Federal Implementation Plans to Reduce Interstate 

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Rule, National Ambient Air Quality Standards for Ozone. 

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2010.

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Geiser L, Bowman WD, Sickman JO, Meixner T, Johnson 

DW, Neitlich P. 2003a. Ecological effects of nitrogen 

deposition in the western United States. BioScience 53: 

404-420.

 USFS–NPS–USFWS 93
Fenn, M.E. 1991. Increased site fertility and litter 

decomposition rate in high-pollution sites in the San 

Bernardino Mountains. For. Sci. 37(4):1163-1181.

Fenn, M.E. and P.H. Dunn. 1989. Litter decomposition 

across an air-pollution gradient in the San Bernardino 

Mountains. Soil Sci. Soc. Am. J. 53(5):1560-1566.

Fenn, M.E., M.A. Poth and D.W. Johnson. 1996. Evidence 

for nitrogen saturation in the San Bernardino Mountains 

in southern California. Forest Ecology and Management

82:211-230.

Fox, D., G.J.C. Bernabo and B. Hood. 1987. Guidelines for 

Measuring the Physical, Chemical, and Biological Condition 

of Wilderness Ecosystems. General Technical Report RM146. U.S. Department of Agriculture, Forest Service, 

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Fisher, G.E. Likens, S.E. Lindberg, R.A. Linthurst, J. 

Messer and D.S. Nichols. 1989. A Screening Procedure to 

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General Technical Report RM-168. U.S. Department of 

Agriculture, Forest Service, Rocky Mountain Forest and 

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Howarth, R.W., Cowling, E.B., Cosby, B.J., 2003. The 

nitrogen cascade. BioScience 53, 341-356.

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Other Airborne Pollutants in the Forests of Eastern 

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Zak. 2008. Nitrogen deposition effects on soil organic 

matter chemistry are linked to variation in enzymes, 

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