Regional Haze and Visibility in the Northeast

and Mid-Atlantic States

prepared by

Northeast States for Coordinated Air Use Management

for the

Ozone Transport Commission

January 31, 2001
ii

NESCAUM

Northeast States for Coordinated Air Use Management

129 Portland Street

Boston, MA 02114

TEL: 617-367-8540

FAX: 617-742-9162

http://www.nescaum.org
iii

Regional Haze and Visibility in the Northeast

and Mid-Atlantic States

prepared by

Northeast States for Coordinated Air Use Management

for the

Ozone Transport Commission

January 31, 2001

Submitted to the United States Environmental Protection Agency, Region III

under EPA Agreement X98320801
iv

Regional Haze and Visibility in the Northeast 

and Mid-Atlantic States 

Northeast States for Coordinated Air Use Management

(NESCAUM) 

Project Manager

Gary Kleiman 

Editors

Marika Tatsutani, Gary Kleiman, Arthur Marin 

Principal Contributors (NESCAUM) 

Paul Miller, Ph.D. 

Gary Kleiman, Ph.D. 

Rawlings Miller, Ph.D. 

Lee Alter, M.S. 

Marika Tatsutani, M.S. 

Karen Fadely 

Ingrid Ulbrich 

U.S. EPA Project Officer

Russ S. Bowen (U.S. EPA Region III) 
v

Acknowledgements

We gratefully acknowledge the funding support provided by the United States

Environmental Protection Agency under cooperative agreement with the Ozone

Transport Commission.

This report was prepared by NESCAUM staff as listed on the opposite page under

“Principle Contributors.”

We thank numerous individuals for reviewing drafts of this report and providing

insightful comments:

Bruce Carhart, OTC

Tom Downs, ME DEP

Jennifer Galbraith, NH DES

John Graham, CT DEP

Wick Havens, PA DEP

John Kent, NY DEC

Kirsten King, U.S. FWS

Denis Lohman, U.S. EPA

Ralph Pasceri, NJ DEP

Rich Poirot, VT DEC

Bruce Polkowsky, U.S. NPS

Rosalina Rodriguez, U.S. EPA

James Salvaggio, PA DEP

Mark Scruggs, U.S. NPS

Nancy Seidman, MA DEP

Christian Seigneur, AER, Inc.

Gopal Sistla, NY DEC

Richard Valentinetti, VT DEC

John Vimont, U.S. NPS

Susan Wierman, MARAMA

Jeffrey West, NARSTO
vi
vii

Table of Contents

Acknowledgements.................................................................................vi

Table of Contents..................................................................................vii

Units, Symbols and Acronyms....................................................................x

Executive Summary................................................................................xiii

I. Introduction .............................................................................................................. I-1

II. The Basics of Haze.................................................................................................. II-1

A. How Haze Affects the View................................................................................ II-1

B. Characterizing and Measuring Haze ................................................................... II-3

C. Causes of Haze in the Northeast and Mid-Atlantic............................................. II-6

III. Anatomy of Regional Haze in the Northeast and Mid-Atlantic.............................III-1

A. Fine Particle Concentrations in the Northeast and Mid-Atlantic .......................III-1

B. Fine Particle Composition in the Northeast and Mid-Atlantic...........................III-4

C. Haze Characteristics at Nearby Class I Areas..................................................III-12

D. Seasonal Variations in Particle Concentration and Light Extinction...............III-15

E. The Link Between Haze and Other Air Quality Problems...............................III-20

F. The Regional Nature of Haze in the Eastern U. S............................................III-21

G. Anatomy of a Severe Haze Event ....................................................................III-22

IV. Federal Regional Haze Requirements....................................................................IV-1

A. Class I Areas in the Northeast and Mid-Atlantic Regions .................................IV-3

Requirements Under the First Phase of the Federal Haze Program (1980-1999)......IV-4

C. Requirements Under the New Regional Haze Rule (1999-2064)......................IV-5

C.1 Timeline for Regional Haze SIP Submittals ..................................................IV-6

C.2 Options for Regional Planning.......................................................................IV-8

C.3 Core Requirements of Regional Haze SIPs....................................................IV-9

C.4 Best Available Retrofit Technology (BART) Requirements .......................IV-10

C.5 Requirements for Comprehensive Periodic SIP Revisions..........................IV-12

C.6 Periodic Reporting on Achievement of Reasonable Progress Goals ...........IV-12

C.7 Adequacy Determination for Existing Implementation Plans......................IV-12

C.8 Coordination Between States and Federal Land Managers .........................IV-12

V. Building a Regional Haze Plan ...............................................................................V-1

A. Characterizing “Natural Background” and Current Visibility Conditions..........V-1

A.1 Calculating Light Extinction ...........................................................................V-1

A.2 Estimating “Natural Background” Reference Conditions...............................V-3

A.3 Estimating Visibility Impairment from Available Fine Particle Monitoring Data

.........................................................................................................................V-6

B. Recent Visibility Trends in the Northeast and Mid-Atlantic ............................V-10

C. Atmospheric Chemistry.....................................................................................V-14

C.1 Hygroscopic Nature of Sulfates and Nitrates................................................V-16

C.2 Potential Competition Between Ammonium Sulfate and Ammonium Nitrate.....

.......................................................................................................................V-17

C.3 Biogenic Hydrocarbon Influence on Regional Haze.....................................V-17
viii

VI. Haze Associated Pollutant Emissions ....................................................................VI-1

A. Sulfur Dioxide (SO2)..........................................................................................VI-1

A.1 Inventory ........................................................................................................VI-1

A.2 SO2 Control Programs....................................................................................VI-1

B. Volatile Organic Carbons (VOC).......................................................................VI-3

B.1 Inventory ........................................................................................................VI-4

B.2 VOC Control Programs..................................................................................VI-5

C. Oxides of Nitrogen (NOX)..................................................................................VI-5

C.1 Inventory ........................................................................................................VI-5

C.2 NOx Control Programs ...................................................................................VI-6

D. Elemental Carbon and Crustal Material.............................................................VI-7

E. Ammonia Emissions ..........................................................................................VI-8

VII. Review of Analytical Tools.............................................................................. VII-1

A. The Challenges of Modeling Regional Haze ................................................... VII-1

B. Available Analytical Tools............................................................................... VII-2

B.1 Meteorological Models ................................................................................ VII-4

B.2 Emissions Models ........................................................................................ VII-5

B.3 3-D Eulerian (Grid) Air Quality Models...................................................... VII-6

B.4 Source Dispersion Models ........................................................................... VII-9

B.5 Receptor Models .......................................................................................... VII-9

B.6 Trajectory Models ...................................................................................... VII-11

C. Comparison of Selected Aerosol Modules..................................................... VII-13

D. Recommended Approach for Modeling Activities ........................................ VII-14

VIII. Visibility Monitoring.......................................................................................VIII-1

A. Basic Monitoring Techniques .........................................................................VIII-1

B. USEPA Monitoring Guidance.........................................................................VIII-3

B.1 Additional USEPA Resources.....................................................................VIII-5

C. The IMPROVE Program.................................................................................VIII-5

C.1 Anatomy of an IMPROVE Monitoring Site ...............................................VIII-9

D. History, Status, and Future of Visibility Monitoring in the Northeast and MidAtlantic..................................................................................................................VIII-15

E. Monitoring Recommendations......................................................................VIII-20

IX. Social and Economic Considerations.....................................................................IX-1

A. Class I Areas in the Northeast and Mid-Atlantic ...............................................IX-1

A.1 National Parks ................................................................................................IX-2

A.2 Wilderness Areas Managed by the Forest Service.........................................IX-3

A.3 Wilderness Areas Managed by the Fish and Wildlife Service.......................IX-6

A.4 International Parks..........................................................................................IX-8

B. Economic Benefits of Outdoor Recreation ........................................................IX-8

C. Public Perceptions of Visual Air Quality.........................................................IX-10

D. Non-Valued Benefits of Visibility to Outdoor Recreation...............................IX-13

E. Valuation of Visibility and Related Attributes.................................................IX-14

F. Related Public Health and Ecosystem Benefits of Reducing Fine Particle

Pollution ...................................................................................................................IX-16
ix

X. Summary and Recommendations............................................................................X-1

A. The Problem ........................................................................................................X-1

B. The Importance of Visibility...............................................................................X-2

C. Recommendations ...............................................................................................X-3

C.1 Basic Science...................................................................................................X-4

C.2 Modeling and Data Analysis...........................................................................X-5

C.3 Air Quality Monitoring and Measurement......................................................X-6

C.4 Emission Inventories.......................................................................................X-8

C.5 Communication and Education .......................................................................X-9

C.6 Regulatory Efforts...........................................................................................X-9

D. Conclusion...........................................................................................................X-9

Appendix A Full Text of the Regional Haze Rule

Appendix B A Guide to Interpreting IMPROVE Monitoring Data

Appendix C IMPROVE Program Visibility Trend Tables
x

Unit, Symbols, Acronyms

Acronyms

ACM – Asymmetric Convective Model

AIRS – Aerometric Information Retrieval

System

ATAD – Atmospheric Transport and

Diffusion Model

ATDM – Aerosol and Toxics Deposition

Model (part of REMSAD)

ANC – acid neutralizing capacity

BACT – Best Available Control

Technology

BART – Best Available Retrofit

Technology

BLM – Bureau of Land Management

CAA – Clean Air Act

CALMET – California Meteorological

model

CALPUFF – California Puff model

CAMNET – Northeast Visibility Camera

Network

CAMx-AERO – Comprehensive Air

Quality Model with extensions-Aerosol

CASTNet – Clean Air States and Trends

Network

CCTM – CMAQ chemical transport

model

CenWRAP- Central West Regional Air

Partnership

CFR – Code of Federal Regulations

CIRA – Cooperative Institute for Research

in the Atmosphere

CMAQ – Community Multi-scale Air

Quality Model

CMB – chemical mass balance

CM – coarse mass

CUSTOMER – Customer Use and Survey

Techniques for Operations,

Management, Evaluations, and

Research

CVM – contigent valuation method

EDF – Environmental Defense Fund

EIA – Energy Information Administration

EGU – Electricity Generating Unit

ETS – Emission Tracking System

FAA – Federal Aviation Administration

FDDA – Four-Dimensional Data

Assimilation

FEM – Federal Equivalency Monitors

FGD – flue gas desulfurization

FIP – Federal Implementation Plan

FLAG – Federal Land Managers’ Air

Quality Related Values Workgroup

FLM – Federal Land Manager

FM – fine mass

FRM – Federal Reference Monitors

FWS – Fish and Wildlife Service

GCVTC – Grand Canyon Visibility

Transport Commission

GEMAP – Geocoded Modeling and

Projection System

GIS – Geographic Information System

IMPROVE – Interagency Monitoring of

Protected Visual Environments

HYSPLIT – Hybrid Single-Particle

Langrangian Integrated Trajectory

model

LADCo – Lake Michigan Air Directors

Consortium

LEV – low emission vehicle

MARAMA – Mid Atlantic Region Air

Management Association

MEPPS – Model-3 Emissions Processing

and Projection System

MM4 – Fourth Generation Mesoscale

Model

MM5 – Fifth Generation Mesoscale Model

MOU – Memorandum of Understanding

MRF – Medium Range Forecast model

MT – total mass (PM10)

MF – fine mass (PM2.5)

NAAQS – National Ambient Air Quality

Standards

NADP – National Atmospheric Deposition

Program
xi

NAPAP – National Acid Precipitation

Assessment Program

NARSTO – North American Research

Strategy for Tropospheric Ozone

NASA – National Aeronautics and Space

Administration

NEGC/ECP – New England Governors’

Conference/ Eastern Canadian Premiers

NEPA – National Environmental Policy

Act

NEPART– Northeast Particle Network

NESCAUM – Northeast States for

Coordinated Air Use Management

NET – National Emissions Trends (EPA)

NGM – Nested Grid Model

NOAA – National Oceanic and

Atmospheric Administration

NPS – National Park Service

NRC – National Research Council

NSPS – New Source Performance

Standard

NSR – New Source Review

NSRE – National Survey on Recreation

and the Environment

OMC – organic mass from carbon

OTC – Ozone Transport Commission

OTR – Ozone Transport Region

PMF – Positive Matrix Factorization

PSCF – Potential Source Contribution

Function

PSD – prevention of significant

deterioration

PVAQ – perceived visual air quality

QSSA – Quasi-Steady State

Approximation

RACT – Reasonably Available Control

Technology

RADM – Regional Acid Deposition Model

RAMS – Regional Atmospheric Modeling

System

RCFM – reconstructed particle fine mass

REMSAD – Regulatory Modeling System

for Aerosols and Deposition

RPO – regional planning organization

RV – recreational vehicle

SeSARM – Southeast States Air Resource

Managers

SIP – State Implementation Plan

SCR – selective catalytic reduction

SMOKE – Sparse Matrix Operator Kernel

Emissions model

SMVGEAR – Sparse Matrix Vectorized

Gear

SOA – secondary organic aerosol

SNCR – selective non-catalytic reduction

STAPPA/ALAPCO – State and Territorial

Air Pollution Program Administrators /

Association of Local Air Pollution

Control Offices

TEA-21 – Transportation Equity Act for

the 21st Century

TIP – Tribal Implementation Plan

UAM-AERO – Urban Airshed ModelAerosol

UAM-V – Urban Airshed Model –

Variable

URM – Urban-to-Regional Multiscale

model

USEPA – United States Environmental

Protection Agency

USFS – United States Forest Service

WESTAR-Western States Air Resources

Council

WRAP-Western Regional Air Partnership

WTP – willingness to pay

WTA – willingness to accept

compensation

Chemical Species

Al – aluminum

Ca – calcium

CO – carbon monoxide

ElemC, EC – elemental carbon

Fe – iron

HC – hydrocarbon

HSO4 – bisulfate

H2SO4 – sulfuric acid

HNO3 – nitric acid

LAC – light absorbing carbon
xii

NOx – oxides of nitrogen (NO2 and NO)

NO – nitric oxide

NO2 – nitrogen dioxide

NO3 – nitrate

NH3 – ammonia

NH4 – ammonium

(NH4)3H(SO4)2 – letovicite

NH4HSO4 – ammonium bisulfate

(NH4)2SO4 – ammmonium sulfate

(NH4NO3) – ammonium nitrate

O3 – ozone

OrgC, OC – organic carbon

PM2.5 – particle matter up to 2.5 μm in

size

PM10 – particle matter up to 10μm in size

Si – silicon

SO2 – sulfur dioxide

SO4 – sulfate

Ti – titanium

VOC – volatile organic carbon

Symbols

bext – light extinction coefficient (Mm-1 or km-1)

bscatt – light scattering coefficient (Mm-1 or km-1)

babs – light absorption coefficient (Mm-1 or km-1)

f(RH) – relative humidity adjustment factor

[ ] – concentrations

Units

Length

m – meter

nm – nanometer (0.000000001m; 10-9m)

μm – micrometer (0.000001m; 10-6m)

km – kilometer (1000 x m; 103

 m)

Mm – Megameter (1000000 x m; 106

 m)

Area

ha – hectare

m

2

 – square meter

km2

 – square kilometer

Volume

L – liter

m3

 – cubic meter

Mass

lb – pound

g – gram

ng – nanograms (0.000000001 x g; 10-9

g)

μg – micrograms (0.000001 x g; 10-6 g)

mg – milligram (0.001 x g; 10-3 g)

kg – kilograms (1000 x g; 103

 g)

Power

W – watt (Joules/sec)

kW – kilowatt (1000 x W; 103

 W)

MW – megawatt (1000000 x W; 106 W)

Energy

Btu – British Thermal Unit (= 1055

Joules)

mmBtu – million Btu

MWh – megawatt hour

kWh – kilowatt hour

Concentration

μg/m3 – micrograms per cubic meter

ng/m3

 – nanograms per cubic meter

ppb – parts per billion

ppm – parts per million

Scattering Efficiency

m2/g – square meters per gram

Visibility

dv – deciview
xiii

Executive Summary

In 1977, Congress added the goal of restoring pristine visibility conditions in national parks

and wilderness areas to the federal Clean Air Act (CAA). Section 169 of the CAA calls for the

prevention of any future, and the remedying of “any” existing, man-made visibility impairment in

so-called “Class I” areas.1 These are ambitious targets given that air pollution now reduces average

visual range in the eastern United States to just 15 to 30 miles, about one-third the visual range

typical of natural conditions.

Despite the lofty goal adopted in 1977, relatively modest steps were taken over the ensuing

two decades to remedy visibility impairment at Class I areas around the country. Control measures

undertaken to improve visibility were largely confined to addressing plume blight from specific

pollution sources near Class I areas; they did little to address the pervasive, regional nature of haze

throughout the eastern U.S. However, emissions reductions were realized through the

implementation of other sections of the CAA: most notably the adoption, in 1990, of a national acid

rain program aimed at substantially reducing sulfur dioxide emissions, a key contributor to visibility

impairment in the East.

On July 1, 1999, the U.S. Environmental Protection Agency (USEPA) issued a new set of

regulations aimed at achieving national visibility goals by 2064. Commonly known as the “regional

haze rule,” these regulations attempt, for the first time, to address the combined visibility effects of

numerous pollution sources over a wide geographic region. Significantly, all states – even those

without Class I areas – will be required to participate in haze reduction efforts.2

 To facilitate

interstate coordination and cooperation, USEPA has designated five regional planning organizations

(RPOs) covering all areas of the U.S. The Ozone Transport Commission (OTC), which includes all

states along the eastern seaboard from Washington, DC to Maine, was selected to serve as the

planning organization for the Northeast and Mid-Atlantic states.3 The OTC RPO will be

coordinating efforts to address visibility impairment at seven Class I areas: Acadia National Park,

ME; Brigantine Wilderness, NJ; Great Gulf Wilderness, NH; Lye Brook Wilderness, VT;

Moosehorn Wilderness, ME; Presidential Range – Dry River Wilderness, NH; and Roosevelt

Campobello International Park, New Brunswick.4

This report provides a comprehensive introduction to the problem of visibility impairment

and regional haze in the Northeast and Mid-Atlantic. It was undertaken by the Northeast States for

Coordinated Air Use Management (NESCAUM) as part of an effort, in partnership with the MidAtlantic Region Air Management Association (MARAMA), to assist the OTC in developing a

foundation for future haze planning and in identifying research priorities for the next several years.

 

1

 The Class I designation applies to national parks exceeding 6,000 acres; wilderness areas and national memorial parks

exceeding 5,000 acres; and all international parks that were in existence prior to 1977.

2

 Tribes may seek approval under 40 CFR 49 to assume the requirements of the regional haze program and be “treated

like states,” but are not required to do so.

3

 Specifically, the OTC RPO for visibility planning includes the District of Columbia, Maryland, Delaware,

Pennsylvania, New Jersey, New York, Connecticut, Rhode Island, Massachusetts, Vermont, New Hampshire, and

Maine. Note that the OTC as originally constituted to address ozone transport includes northern Virginia.

4

 Brigantine Wilderness is within the Edwin B. Forsythe National Wildlife Refuge and Moosehorn Wilderness is within

the Moosehorn National Wildlife Refuge.
xiv

A. The Basics of Haze

Small particles and certain gaseous molecules in the atmosphere cause poor visibility by

scattering and absorbing light, thereby reducing the amount of visual information about distant

objects that reaches an observer. Some light scattering by air molecules and naturally occurring

aerosols occurs even under natural conditions.5

The distribution of particles in the atmosphere depends on meteorological conditions and

leads to various forms of visibility impairment. When high concentrations of pollutants are well

mixed in the atmosphere, they form a uniform haze. When temperature inversions trap pollutants

near the surface, the result can be a sharply demarcated layer of haze. Plume blight — a distinct,

frequently brownish plume of pollution from a particular emissions source — occurs under stable

atmospheric conditions, when pollutants take a long time to disperse.

Visibility impairment can be quantified using three different, but mathematically related

measures: light extinction per unit distance (e.g., Mm-1);6

 visual range (i.e., how far one can see);

and deciviews (dv), a useful metric for measuring increments of visibility change that are just

 

5

 The fact that air molecules scatter more short wavelength (blue) light accounts for the blue color of the sky. The term

“aerosol” is defined as a suspension of particles in a gas. In this report we use the term to refer to particles suspended in

the atmosphere.

6

 In units of inverse length. An inverse megameter (Mm-1) is equal to one over one thousand kilometers.

Federal Class I Areas in the Northeast and Mid-Atlantic U.S.

Note: designations are shown with each Class I area. NP = National Park, WA=Wilderness Area,

WR = Wilderness Areas located within a Wildlife Refuge, and IP = International Park.
xv

perceptible to the human eye. Each can be estimated from the ambient concentrations of individual

particle constituents, taking into account their unique light-scattering (or absorbing) properties and

making appropriate adjustments for relative humidity. Assuming natural conditions, visibility in the

Northeast and Mid-Atlantic is estimated to be about 23 Mm-1, which corresponds to a visual range

of about 106 miles or 8 dv. Under current polluted conditions in the region, average visibility

ranges from 103 Mm-1 in the south to 55 Mm-1 in the north; these values correspond to a visual

range of 24 to 44 miles or 23 to 17 dv, respectively. On the worst 20 percent of days, visibility

impairment in Northeast and Mid-Atlantic Class I areas ranges from about 25 to 30 dv.

The small particles that commonly cause hazy conditions in the East are primarily composed

of sulfate, nitrate, organic carbon, elemental carbon (soot), and crustal material (e.g., soil dust, sea

salt, etc.). Of these constituents, only elemental carbon impairs visibility by absorbing visible light;

the others scatter light. Sulfate, nitrate, and organic carbon7

 are secondary pollutants that form in

the atmosphere from precursor pollutants; primarily sulfur dioxide (SO2), oxides of nitrogen (NOx),

and volatile organic compounds (VOCs), respectively. By contrast, soot and crustal material and

some organic carbon particles (see Footnote 7) are released directly to the atmosphere. Particle

constituents also differ in their relative effectiveness at reducing visibility. Sulfates and nitrates, for

example, contribute disproportionately to haze due to their chemical affinity for water. This

property allows them to grow rapidly, in the presence of moisture, to the optimal particle size for

scattering light (i.e., 0.1 to 1 micrometer).

B. Anatomy of Regional Haze

Monitoring data collected over the last decade show that fine particle8 concentrations, and

hence visibility impairment, are generally highest near industrial and highly populated areas of the

Northeast and Mid-Atlantic. Particle concentrations are lower, and visibility conditions are better, at

the more northerly Class I sites (such as Acadia and Moosehorn) where visibility on the 20 percent

best days9 is close to natural, unpolluted conditions. By contrast, visibility at the more southerly

Brigantine site in New Jersey is substantially impaired even on the 20 percent clearest days. On the

20 percent haziest days,9 visibility impairment is substantial throughout the region.

Sulfate is the dominant contributor to fine particle pollution throughout the eastern U.S. On

the haziest 20 percent of days, it accounts for one-half to two-thirds of total fine particle mass and is

responsible for about three-quarters of total light extinction at Class I sites in the Northeast and MidAtlantic. Even on the clearest 20 percent of days, sulfate typically constitutes 40 percent or more of

total fine particle mass in the region. Moreover, sulfate accounts for 60 to 80 percent of the

 

7

 The term “organic carbon” encompasses a large number of hydrogen and carbon containing molecules. Lightscattering secondary organic aerosols result from the oxidation of hydrocarbons that are emitted from many different

sources, ranging from automobiles and solvents, to natural vegetation. Organic carbon can be emitted as a primary

particle from sources such as wood burning, meat cooking, and automobiles and paved road dust.

8

 “Fine particles” refers throughout this study to particles less than or equal to 2.5 micrometers in diameter, consistent

with USEPA’s recently proposed fine particle NAAQS.

9

 “20 percent best visibility conditions” are defined throughout this report as the simple average of the lower 20th

percentile of a cumulative frequency distribution of available data (expressed in deciviews). Similarly, “20 percent worst

visibility conditions” represent the average of the upper 20th percentile of the same distribution of available data.
xvi

difference in fine particle mass concentrations on hazy versus clear days. Organic carbon

consistently accounts for the next largest fraction of total fine particle mass; its contribution typically

ranges from 20 to 30 percent on the haziest days. Notably, organic carbon accounts for as much as

40 to 50 percent of total mass on the clearest days, indicating that biogenic hydrocarbon sources (i.e.

vegetation) are important at Class I areas in the region. The relative contributions of nitrate,

elemental carbon, and fine soil are smaller (typically under 10 percent of total mass) and vary with

location. Nitrate plays a considerably larger role at a Washington DC site,10 pointing to the

importance of local NOx sources in urban settings.

The great majority of 20 percent worst visibility days at northeastern and mid-Atlantic Class

I sites occur in the summertime when meteorological conditions are more conducive to the formation

of sulfate from SO2 and to the oxidation of secondary organic aerosols. In addition, winter and

summer transport patterns are different, possibly leading to different contributions from upwind

pollutant source regions. In contrast to sulfate and organic carbon, the nitrate contribution is

typically higher in the winter months (especially at urban sites).11 The crustal and elemental carbon

fractions do not show a clear pattern of seasonal variation.

The basis for USEPA’s recent haze regulations is a recognition that visibility impairment is

fundamentally a regional phenomenon. Emissions from numerous sources over a broad geographic

area commonly create hazy conditions across large portions of the eastern U.S. as a result of the

long-range transport of airborne particles and precursor pollutants in the atmosphere. The key sulfate

precursor, SO2, for example, has an atmospheric lifetime of several days and is known to be subject

to transport distances of hundreds of miles. NOx and some organic carbon species are also subject to

long-range transport, as are small particles of soot and crustal material.

The importance of transport dynamics is well illustrated by a particularly severe haze episode

that occurred in mid-July of 1999. During this episode, unusually hot and humid conditions

coincided with the development of a high-pressure system over the Mid-Atlantic region that

produced atmospheric stagnation over the heavily urbanized, southern half of the OTC RPO region

(i.e., Philadelphia-DC-southern New Jersey). At the same time, wind patterns above the area of

stagnation brought a steady flow of air from the Midwest into the New England states. This resulted

in several days of unusually high fine particle concentrations throughout the region. At Acadia

National Park, ambient sulfate concentrations on July 17, 1999 were 40 percent higher than any

previous measurement at that site since the late 1980s; on the same day, visibility at the Burlington,

VT airport was limited to just 3 miles. As is often the case, very high ozone levels accompanied

these severe haze conditions. This is because haze and ozone – though they are fundamentally

different phenomena – tend to form and accumulate under similar meteorological conditions.

C. Federal Regional Haze Requirements

The USEPA’s July 1999 rule requires all states that contribute to visibility impairment in a

Class I area (whether or not they host a Class I area) to submit implementation plans or “SIPs” for

 

10 A Washington DC site is part of the IMPROVE monitoring network and was included for purposes of comparison.

11 This is largely because the ammonium nitrate bond is more stable at lower temperatures. The role of ammonia in

combination with both sulfate and nitrate is discussed further in later sections.
xvii

reducing regional haze. Similarly, tribes that choose to participate in the regional haze program (see

Footnote 2) would develop tribal implementation plans or “TIPs”. Because visibility impairment

and haze are directly linked to fine particle pollution, SIP submittal deadlines depend on states’

attainment status with respect to a proposed National Ambient Air Quality Standard (NAAQS) for

fine particle matter (PM2.5) and on whether they choose to participate in regional planning efforts.

The fact that the PM2.5 NAAQS is currently under review by the Supreme Court creates some

uncertainty about the exact timing of future haze requirements. As originally proposed, however,

most states (i.e., states that either have a PM2.5 non-attainment area and/or are participating in a

regional process) are required to submit haze SIPs at the same time that PM2.5 attainment SIPs are

due – that is, starting in 2007 and no later than the end of 2008. States free of PM2.5 non-attainment

that do not participate in regional efforts may have to submit haze SIPs as early as 2005-2006. In

addition, states planning to participate in regional efforts must indicate their intention to do so in a

“committal SIP” that will generally be due within a year of USEPA’s first PM2.5 attainment

designations (i.e. in the 2004-2006 timeframe).

Regional haze SIPs and TIPs must describe states’ (or tribes’) long-term strategies for

monitoring and reducing haze; they must also provide an inventory of relevant emissions and

describe plans for applying Best Available Retrofit Technology (BART) requirements to certain

point sources.12 Importantly, states can choose to implement emissions trading or other programs as

an alternative to the source-by-source BART approach, if this provides greater visibility benefits. In

addition, states with Class I areas must estimate natural visibility impairment and measure baseline

conditions for the 20 percent most and least impaired days (in deciviews) using monitoring data

collected between 2000-2004. Using this information they must establish reasonable progress goals,

taking into account the cost and feasibility of implementing emissions controls. Other requirements

include periodic reporting on reasonable progress goals (every five years); comprehensive periodic

SIP revisions (every 10 years); adequacy determinations for existing SIPs, and coordination between

states and federal land managers. USEPA expects to issue further guidance on many technical

aspects of the new rule in 2001.

D. Building a Regional Haze Plan

Quantifying existing visibility conditions, as well as “natural background” conditions, will be

central to developing regional haze SIPs. Current methods for making these calculations are

somewhat imprecise, particularly with respect to the treatment of humidity effects, although they

generally yield results that correspond reasonably well to direct visibility measurements. However,

further refinement of available methodologies, particularly in the estimation of “natural background”

conditions, may be necessary. For example, it will be essential to develop estimates of both 20

percent best and worst natural background impairment for comparison with baseline conditions13 in

the process of establishing reasonable progress goals.

 

12 BART requirements can be applied to 26 types of stationary sources (including power plants and other industrial

facilities), provided they began operation on or between August 7, 1962 and August 7, 1977.

13 Natural background conditions refer to visibility conditions that would prevail in the absence of any man-made

influence. These are contrasted against baseline conditions, or those visibility conditions currently experienced at Class I

areas in the region.
xviii

Besides quantifying the “gap” between actual and pristine visibility conditions, states will

need to consider recent visibility trends and understand the complex atmospheric chemistry of fine

particle formation. With the exception of Acadia, less than a decade of monitoring data are available

for most Northeast and Mid-Atlantic Class I areas. The available data do not indicate consistent

visibility trends over the last few years at most sites (with the possible exception of Acadia, where

there appears to have been some modest improvement since the late 1980s). This lack of progress

may seem surprising given the SO2 reductions that occurred during this period under the national

Acid Rain Program. Explanations may include the limited years of available data and the difficulty

of discerning small visibility changes against relatively polluted background conditions.

The processes by which precursor pollutants such as SO2, NOx, and organic compounds form

light-scattering particles in the atmosphere are complex. Particle constituents can move between

liquid and solid states; condense onto other particles, and react to form different chemical species.

Generally, haze does not consist of discrete particles of sulfate, nitrate, or organic carbon; rather

various combinations of these constituents adsorb onto existing nuclei moving through the

atmosphere, eventually becoming large enough to scatter light. An area of atmospheric chemistry

that bears further investigation is the role of ammonia. Implementing sulfate reductions alone may

mean that more ammonium ion would be available to bond with nitrate, possibly resulting in lessthan-anticipated visibility improvement, especially in the wintertime. Another area for future

research concerns the role of naturally occurring biogenic hydrocarbons emissions that may

contribute substantially to the organic carbon fraction at rural sites. It is important to note that the

biogenic contribution may be indirectly influenced by the presence of elevated levels of ozone,

which tends to promote the formation of secondary organic aerosols from all sources. Hence, efforts

to reduce regional ozone levels may have a beneficial impact on haze, even at more remote sites in

the Northeast and Mid-Atlantic.

E. Emissions Sources

As noted repeatedly in this study, SO2 is the dominant haze precursor pollutant in the

Northeast and Mid-Atlantic. Coal-burning power plants were responsible for two-thirds of total SO2

emissions nationwide in 1998; other sources of SO2 include fossil fuel combustion (by both

stationary and mobile sources) and certain industrial processes. At present, SO2 emissions are

primarily regulated under the national Acid Rain Program (Title IV of the 1990 CAA Amendments).

That program will eventually cut power plant SO2 emissions by roughly half from 1980 levels, to

just under 9 million tons annually.

Volatile organic compounds (VOCs), which contribute to the formation of light-scattering

secondary organic aerosols as well as ozone, are emitted primarily by transportation and area sources

(such as automobiles, trucks, solvents, architectural coatings, etc.) and to a lesser extent by certain

point sources. Substantial VOC reductions have been achieved to date through the regulation of

emissions from automobiles and transportation fuels. In addition, a variety of VOC reduction

strategies have been implemented in urban areas to address ozone non-attainment. The effects of

these programs on visibility conditions at Class I areas (taking into account the indirect impact of

ozone reductions on the oxidation of biogenic hydrocarbons) may need to be further investigated.
xix

NOx emissions are presently regulated primarily for purposes of ozone control and, to a much

more limited extent, under the national Acid Rain Program. New federal and California vehicle

standards will produce broad-based NOx reductions from the mobile source sector (including from

light and heavy-duty vehicles, construction equipment, marine vessels and locomotives) over the

next several years. Substantial additional NOX reductions from stationary sources are also due to be

implemented across much of the eastern U.S. under both the OTC’s 1994 NOx “Memorandum of

Understanding” and under the broader and more recent USEPA “NOx SIP call.” These initiatives

will reduce NOx emissions from power plants and large industrial sources by as much as 85 percent

from uncontrolled levels in the 2003-2004 timeframe.

Inventory data are generally less robust for elemental carbon (soot) and crustal material.

Soot emissions from diesel engines and wood stoves can be effectively reduced using particulate

control technologies. Future federal regulations will further limit soot emissions from new diesel

engines and states are undertaking a number of initiatives to reduce emissions from existing engines

using retrofit technology. While crustal material may be less amenable to control, there is some

experience with controlling dust and road-salt in a few areas of the Northeast and Mid-Atlantic that

have been in non-attainment of the PM10 NAAQS.

F. Review of Analytical Tools

Computer model simulations will play an important role in regional haze planning. A variety

of analytical tools are available including source apportionment models, source dispersion models,

three-dimensional Eulerian air quality models, and trajectory models. Operating these models can

be time and resource intensive and requires detailed inputs including ambient monitoring, emission

inventory, and meteorological data. States will need to carefully evaluate and coordinate their

modeling efforts, taking into account the strengths of available model platforms (many of which will

be refined further in coming years), as well as the availability and resolution of underlying input

data. NESCAUM will use USEPA’s REMSAD modeling system and the EPA Models-3

Community Multiscale Air Quality (Models-3/CMAQ) modeling system for preliminary regional

haze modeling. These two models should provide the flexibility and technical sophistication needed

to begin to assess modeling challenges for the regional haze program. Ultimately, a combination of

analytical tools and the coordination of individual state efforts will be needed to devise effective

visibility improvement strategies.

G. Visibility Monitoring

Visibility monitoring programs will need to incorporate a variety of techniques to adequately

characterize haze, including photography, optical monitoring (to measure light scattering and

absorption), and aerosol monitoring (to measure particle concentrations and composition). USEPA

is currently sponsoring a substantial expansion of existing monitoring networks in support of the

proposed PM2.5 NAAQS. Eventually over 1,000 fine particle monitoring sites will be deployed

nationwide for the purposes of PM2.5 non-attainment designations, characterizing background and
xx

transport conditions, and other informational needs. This network will include up to 300 routine

chemical speciation sites to assess trends in fine particle composition.

Much of the currently available data on visibility and particle pollution in the eastern U.S.

come from the IMPROVE (Interagency Monitoring of Protected Visual Environments) network,

which was established in the late 1980s by USEPA and the National Park Service. The IMPROVE

program is being expanded and will continue to provide crucial inputs to visibility planning efforts.

Visibility is currently monitored at five sites in or near Class I areas in the Northeast and MidAtlantic. Four existing, but no longer operative, sites in non-Class I rural areas are to be re-deployed

in 2001. In addition, six new sites will be monitored for the first time.

Meanwhile, an initiative known as CAMNET is making real-time pictures of visibility

conditions at three sites (Acadia, ME; Boston, MA; and the Great Gulf/Presidential-Dry River area,

NH) available on the Internet;14 additional CAMNET sites are planned for Hartford, CT and New

York City. Recommended objectives for future monitoring efforts include extending IMPROVEtype monitoring to other areas, providing specialized data for planning purposes and model

verification, expanding public outreach efforts, and tracking relative humidity and ammonia

concentrations at existing sites to refine current understanding of particle formation.

H. Social and Economic Considerations

Ultimately, the willingness of policymakers and the public to support effective regional haze

abatement strategies will depend, in large part, on the perceived benefits of improved visibility.

Class I areas in the Northeast and Mid-Atlantic include: one national park managed by the U.S.

National Park Service, three wilderness areas managed by the U.S. Forest Service, two wilderness

areas managed by the U.S. Fish and Wildlife Service and one international park managed by the

Roosevelt Campobello International Park Commission. While these agencies have somewhat

different missions, each promotes the public use and enjoyment of wilderness areas and the

protection of ecosystems and natural values (including natural scenery). Outdoor recreation is a

multi-billion dollar industry in the U.S. and is often of particular economic importance to

communities near protected federal lands.

Various surveys of perceived visual air quality (PVAQ) have been conducted in Class I areas

to assess the public’s response to different visibility conditions. They indicate that most individuals

are more sensitive to incremental changes in visibility when background conditions are relatively

clear. In other surveys, visitors have rated “clean, clear air” as among the most important features of

national parks and have overwhelmingly ranked scenic views and clean air as “extremely” or “very”

important. Although quantifying these inherently subjective value judgments is difficult, techniques

such as contingent valuation, in which the public is surveyed about its willingness to pay to protect a

resource, are available. Studies of this type have yielded estimates in the billions of dollars for the

visibility benefits associated with substantial national pollution reductions.15

 

14 http://www.hazecam.net

15 It should be noted that these results are highly sensitive to the specific survey instrument used.
xxi

Federal visibility goals cannot be achieved in the eastern U.S. without broad-based

reductions in fine particles and their precursors that will reach far beyond the borders of Class I areas

alone. Hence, the benefits of improved visibility are fundamentally intertwined with the benefits of

reducing fine particle pollution generally, and ambient sulfate levels in particular. Health benefits

are likely to be especially important, since fine particle pollution has been linked to premature

morbidity and mortality from respiratory and cardiovascular effects. Because there appears to be no

concentration threshold below which fine particles are harmless to human health, actions to improve

visibility are likely to produce substantial health benefits, even in areas where a future PM2.5

NAAQS is already being attained. Further SO2 and NOx reductions would also have multiple

ecosystem benefits in terms of addressing continued problems of acid deposition, as well as soil

nitrogen saturation and the eutrophication of sensitive aquatic environments. Finally, NOx and VOC

reductions can help alleviate ozone-related health impacts.

I. Summary and Recommendations

This report concludes with a number of recommendations for further research. Sorted into

six general categories, these include:

• Basic Science

3⁄4 Refining the characterization of natural background conditions to better address natural

variability, relative humidity, biogenic emissions, and marine aerosols.

3⁄4 Refining the characterization of baseline conditions through sensitivity analyses of

methodologies for reconstructing light extinction and further clarification of the role of

relative humidity.

3⁄4 Further study of the hygroscopicity and composition of secondary organic aerosols and

the relative contribution of man-made vs. biogenic sources.

• Modeling and Data Analysis

3⁄4 Developing a regional modeling strategy and “in-house” modeling capability by the OTC

RPO. Initial modeling goals should include establishing preliminary transport source

regions and assessing seasonal variability.

3⁄4 Assessing differences in source contributions on best and worst days and evaluating

source regions for Class I areas in the OTC RPO based on available data and trajectory

analysis techniques.

3⁄4 Mapping and displaying data using geographic information systems (GIS).

• Air Quality Monitoring and Measurement

3⁄4 Developing methods for dealing with incomplete monitoring data.
xxii

3⁄4 Re-sorting IMPROVE particle mass data using visibility measures

3⁄4 Compiling, updating, and evaluating additional PM2.5 monitoring data for haze planning

purposes.

3⁄4 Updating speciated aerosol and humidity data and translating it to deciviews.

3⁄4 Quantifying the role of marine aerosols with initial studies at coastal sites.

3⁄4 Maintaining and expanding the CAMNET program and maximizing the use of these

images for planning and outreach purposes.

• Emissions Inventories

3⁄4 Developing emission inventories for ammonia.

3⁄4 Improving emission inventories for VOC, SO2, and PM2.5, including better spatial and

temporal allocation of emissions and more detailed speciation.

3⁄4 Evaluating the visibility benefits of diesel and motor vehicle emission reductions,

especially with respect to SO2 and organics, and improving emission inventories for

mobile sources.

• Communication / Education

3⁄4 Developing programs to educate the public, policymakers and affected industry on

regional haze and its links to other important public health and environmental issues.

• Regulatory Efforts

3⁄4 Performing a technical analysis of the BART provisions of the regional haze rule as well

as USEPA’s proposed BART guidance to identify potential emission reduction

opportunities for improving visibility in Northeast and Mid-Atlantic Class I areas.

In conclusion, while several years of coordinated research will be needed to better understand

visibility problems and develop viable solutions, much is already known about the causes of haze in

the eastern U.S. It is clear, for example, from available monitoring data that SO2 emissions are an

obvious target for achieving reasonable progress toward improved visibility in the near term.

Another near term priority is for RPOs and states to begin educating policymakers, affected industry,

and the public about the adverse impacts of regional haze and its linkages to other important public

health and environmental issues. This will be crucial in building the understanding necessary for

achieving the aggressive visibility goals of the Clean Air Act.
I-1

I. Introduction

In 1977, Congress added the goal of restoring pristine visibility conditions in the nation’s

most cherished parks and wilderness areas to the federal Clean Air Act. Section 169 of the Act calls

for no less than the elimination of “any” man-made visibility impairment in so-called “Class I”

areas;16 an ambitious target given that air pollution now reduces average visual range in the eastern

United States to about one-third of that which would be possible under natural conditions.

Despite the lofty goal adopted in 1977, relatively modest steps were taken over the ensuing

two decades to address the substantial visibility impairment that was increasingly common at many

Class I areas around the country. To be sure, progress was made under other sections of the Clean

Air Act: notably the adoption, in 1990, of a national acid rain program aimed at substantially

reducing sulfur dioxide emissions, a key contributor to poor visibility in the eastern U.S. However,

control measures specifically undertaken to improve visibility were largely confined to addressing

“plume blight” from individual pollution sources near Class I areas. These requirements did little to

address the pervasive, regional nature of haze throughout the eastern half of the country.

On July 1, 1999, the U.S. Environmental Protection Agency (USEPA) issued new regulations

to address poor visibility in federally protected parks and wilderness areas. These regulations mark a

dramatic departure from past visibility improvement efforts in that they place a new emphasis on

regional strategies to address the cumulative effect of numerous air pollution sources distributed

over a wide geographic region. Significantly, the new regulations require even states that do not

have a Class I area within their borders to participate in efforts to reduce regional haze. The regional

haze rule sets a target date of 2064 for achieving the national visibility goals and requires regular

progress reports and implementation plan revisions to ensure reasonable progress toward achieving

these goals.

The USEPA has designated five regional planning organizations (RPOs) covering all areas of

the U.S to facilitate the development and implementation of cost-effective regional haze abatement

strategies and promote effective program coordination among states.17 The Ozone Transport

Commission (OTC) was selected to host the RPO for the Northeast and Mid-Atlantic regions. The

OTC RPO includes states along the eastern seaboard from Washington, DC to Maine. Interested

tribes in the Northeast and Mid-Atlantic can also join the RPO, giving them a first-ever opportunity

to directly participate in regional air quality planning. The OTC RPO will be coordinating efforts to

address visibility impairment at seven federal Class I areas within the Northeast/Mid-Atlantic region:

Acadia National Park, Maine; Brigantine Wilderness (within the Edwin B. Forsythe National

Wildlife Refuge), New Jersey; Great Gulf Wilderness, New Hampshire; Lye Brook Wilderness,

Vermont; Moosehorn Wilderness (within the Moosehorn National Wildlife Refuge), Maine;

Presidential Range – Dry River Wilderness, New Hampshire; and Roosevelt Campobello

International Park, New Brunswick.

The USEPA’s 1999 rule will require the submittal of regional haze state implementation

plans (SIPs) and tribal implementation plans (TIPs) in the 2006 to 2008 timeframe; deadlines may

be earlier for states that choose not to participate in regional efforts. Considerable upfront work will

 

16 The Class I designation applies to national parks exceeding 6,000 acres; wilderness areas and national memorial parks

exceeding 5,000 acres; and all international parks that were in existence prior to 1977.

17 A map of the five RPOs is provided in Chapter IV.
I-2

be needed to analyze the causes of haze in the Northeast and Mid-Atlantic, characterize the

contribution of different emissions sources, and devise effective control strategies that are consistent

with other efforts being undertaken under Clean Air Act requirements. Understanding the visibility

impacts of existing and future programs to address continuing acid deposition problems, new healthbased standards for ambient fine particle pollution, and ozone non-attainment will be of particular

relevance to future haze planning efforts.

To assist the OTC RPO in developing a foundation for future haze planning, the MidAtlantic Region Air Management Association (MARAMA) and the Northeast States for Coordinated

Air Use Management (NESCAUM) are partnering with the OTC to facilitate the needed technical

analyses, training and state support functions. NESCAUM has undertaken this study to provide a

detailed summary and evaluation of available information on the nature and scope of regional haze

in the Northeast and Mid-Atlantic region. It is hoped that this information will provide a

comprehensive introduction and common basis for understanding useful to states, tribal officials,

applicable federal agencies and others involved in the OTC RPO’s planning process. Further, the

technical recommendations provided in this report will serve to better define the work agenda of the

OTC RPO over the next several years.

This report is organized in two main sections: the first (Chapters II-IV) provides background

information necessary to understanding regional haze; the second (Chapters V-IX) introduces

technical tools and policy considerations that will be important in developing regional haze plans. In

the background section, Chapters II and III describe the phenomenon of haze and its basic causes

and characteristics in the Northeast and Mid-Atlantic, noting, in particular, the very important role

played by sulfates in determining visibility conditions throughout much of the eastern U.S. Chapter

IV provides further detail about the specific provisions of the 1999 regional haze rule, including its

planning requirements, key timelines, and Best Available Retrofit Technology (BART) provisions.

The second part of the report shifts to a discussion of topics that will be important in the

development of regional haze SIPs. Chapter V provides more technical detail about measuring

visibility and identifying baseline conditions; it also provides additional detail about some of the

basic atmospheric chemistry involved. Chapter VI discusses major emission sources of haze

associated precursor species. Chapters VII and VIII describe available modeling tools and

monitoring programs, respectively. Chapter IX describes Class I areas in the RPO region and

introduces, in largely qualitative terms, a discussion of the economic costs and benefits associated

with the achievement of visibility goals. Finally, Chapter X summarizes the report’s findings and

recommendations and points toward areas of inquiry for further research in the coming years.

The same fine particles that impair visibility also pose a significant risk to public health and

the environment. These pollutants can damage the lungs and exacerbate respiratory problems; they

may also contribute to heart attacks in people with existing cardiac problems. Numerous studies

have confirmed the relationship between elevated ambient atmospheric fine particle concentrations

and increased rates of mortality and morbidity. SO2 and NOX are also the primary causes of acid

rain, while NOX is implicated in the widespread eutrophication of sensitive marine bays and

estuaries. Thus, these haze precursors pose other, important threats to critical natural resources in

the Northeast and Mid-Atlantic region in addition to their visibility impacts. The linkages between

haze and other public health and environmental concerns are therefore a recurring theme in this

report.
II-1

II. The Basics of Haze

Under natural atmospheric conditions, the view in the eastern United States would

extend about 60 to 80 miles (100 to 130 kilometers) (Malm, 2000a). Unfortunately,

views of such clarity have become a rare occurrence in the East. As a result of man-made

pollution, average visual range in the eastern half of the country has diminished to about

15-30 miles, approximately one-third the visual range that would be observed under

unpolluted natural conditions. This chapter provides a brief primer on haze in the

Northeast and Mid-Atlantic: how haze affects the view, how the resulting visibility

impairment is measured, and what causes haze. A more detailed discussion of many of

these issues is provided in later Chapters, in particular Chapter V.

A. How Haze Affects the View

In general, the ability to see distant features in a scenic vista is determined less by

the amount of light reaching the observer than by the contrast between those features and

their surroundings. For example, the illumination of a light bulb in a greenhouse is

barely discernible on a sunny day but would be highly visible at night. Similarly, a

mountain peak is easily seen if it appears relatively dark against the sunlit sky. If, on the

other hand, a milky haze “fills” the space between the observer and the mountain peak,

the contrast between the mountain and its background is diminished as both take on a

similar hue (Figure II-1).

Figure II-1: View of a good visibility day (left) and a poor visibility day (right) at

Great Smoky Mountains National Park, North Carolina/Tennessee.

Source: U.S. EPA Visibility Improvement Program, http://www.epa.gov/oar/vis

In simple terms, this hazy effect occurs when small particles and certain gaseous

molecules in the atmosphere absorb or scatter visible light, thereby reducing the amount

of visual information that reaches the observer. This occurs to some extent even under

natural conditions, primarily as a result of the light scattering effect of individual air

molecules (known as Rayleigh scattering18) and of naturally occurring aerosols.19 The

 

18 Because air molecules more effectively scatter light of short wavelengths (i.e. blue light), Rayleigh

scattering explains the blue color of the sky.
II-2

substantial visibility impairment caused by manmade pollution, however, is almost

entirely attributable to the increased presence of very small particles in the atmosphere.20

Figure II-2 presents a simplified schematic of the way such small particles interact

with packets of light or “photons” as they travel from a distant object to an observer.

Along the way, particles suspended in the air can deflect or scatter some of the photons

out of the sight path. Intervening particles can also absorb photons, similarly removing

them from the total amount of light reaching the observer.

At the same time, particles in the air can scatter light into the sight path, further

diminishing the quality of the view. The extraneous light can include direct sunlight and

 19 Atmospheric aerosol is a more general term for fine particles suspended in the atmosphere that refers to

any particle (solid or liquid) which is suspended in the atmosphere. “Fine particles” refers to those aerosol

particles with a diameter ≤ 2.5μm.

20 The only light-absorbing gaseous pollutant present in the atmosphere at significant concentrations is

nitrogen dioxide (NO2) (USEPA, 1997a; Seinfeld and Pandis, 1998). However, the contribution of NO2 to

overall visibility impacts in the Northeast is negligible and hence its effects are not generally included in

this discussion or in standard calculations of visibility impairment (FLAG, 1999).

Figure II-2: Schematic of visibility impairment due to light scattering and absorption

(adapted from Malm, 2000a).

Light from clouds

scattered into

sight path

Sunlight

scattered

Light reflected

from ground

scattered into

sight path

Light absorbed

Image-forming

light scattered

out of sight path
II-3

light reflected off the ground or from clouds. Because it is not coming directly from the

scenic element, this light contains no visual “information” about that element. When the

combination of light absorption and light scattering (both in to and out of the sight path)

occurs in many directions due to the ubiquitous presence of small particles in the

atmosphere, the result is commonly described as “haze.”

B. Characterizing and Measuring Haze

The distribution of small particles in the atmosphere under different

meteorological conditions can lead to different manifestations of haze. Three common

types include uniform haze, layered haze, and plume blight. Table II-1 describes the

atmospheric conditions that commonly lead to each type of haze. Uniform haze is

characterized by an even degradation of visibility throughout the visible sky. It typically

occurs when pollutants from a large number of sources distributed over a broad area are

well mixed in the atmosphere. Hence, uniform haze tends to be regional in scope, often

extending over large areas of the eastern U.S. As the name implies, layered haze is

characterized by a distinct demarcation between clear and hazy air in the visible sky.

This type of haze event typically occurs when a temperature inversion or layer of stable

air traps pollutants near the earth’s surface and prevents them from mixing with air higher

in the atmosphere. A third type of haze, referred to as plume blight, is created when the

emissions from a particular pollution source are released into stable air. Under these

conditions the pollutants take more time to disperse and it is possible to discern a distinct

plume emanating from the emissions source. Sometimes the plume will appear brown,

an effect caused by the presence of nitrogen dioxide which can absorb significant

amounts of light when present in concentrated amounts. Over time, the pollution plumes

from multiple individual sources can contribute to layered haze conditions in a stable

atmosphere or to uniform haze conditions within a well-mixed atmosphere.

As described in the previous section, small particles in the atmosphere impair

visibility and create the effect of haze by attenuating light. Hence visibility impairment is

frequently measured as the proportion or fraction of light attenuated per unit distance and

is expressed in units of inverse length, typically inverse megameters21 (Mm-1) or inverse

kilometers (km-1) (Trijonis et al., 1990). The degree to which individual particles will

scatter or absorb visible light is a function of their geometric size and chemical make-up.

The total light extinction caused by a given mix of particles can be estimated by summing

the individual scattering and absorption coefficients for each type of particle present. It

can also be measured directly using specialized equipment such as transmissometers (to

measure light extinction) and nephelometers (to measure light scattering).22

While light extinction is the most useful measure of visibility impairment from a

scientific perspective, other measures are more intuitively accessible and are commonly

used in regulatory and policy contexts. Visual range, for example, is a measure of the

furthest distance a large object can be seen against the background sky taking into

 

21 One megameter is equal to one million meters or 1000 km.

22 See further discussion in Chapter V and VIII.
II-4

account the minimum or “threshold” level of contrast that is perceptible to the human

eye. Visual range is expressed in units of length (e.g., km) and is inversely proportional

to light extinction.23 As light extinction increases and conditions become hazier, visual

range decreases.

While visual range is useful in describing a given state of visibility impairment, a

different measure is helpful in describing changes in visibility. Humans perceive such

changes more readily when the view is relatively unimpaired; they are less sensitive to an

equivalent change in visibility when conditions are hazier to begin with. In other words,

a 10 km reduction in visual range is more noticeable when visual range declines from 60

km to 50 km than when visual range declines from 30 km to 20 km. A unit of measure

that accounts for this nuance is the deciview (dv). Like visual range, the deciview

measure is directly related to light extinction, though in this case the relationship is

logarithmic resulting in a more linear correspondence between the deciview and human

perception of visibility change.

The relationship between all three measures is illustrated by Figure II-3. As the

figure indicates, estimated visibility in the northeastern and mid-Atlantic U.S. under

natural, unpolluted conditions corresponds to a light extinction coefficient of

approximately 23 Mm-1 (of which roughly half is attributable to Rayleigh scattering and

half to naturally occurring particles). This corresponds to a visual range of approximately

170 km or 8 dv. (Note that estimating “natural, unpolluted” conditions is not

straightforward and will produce somewhat different results at different locations. These

issues are discussed further in Chapter V.) By comparison, average estimated light

extinction coefficients under current, polluted conditions range from 55 Mm-1 in the

Northeast to 103 Mm-1 in the Mid-Atlantic states (Malm, 2000b). These values

correspond to deciview measures of 17 and 23 dv, respectively and average visual range

of just 71 km in the Northeast and 38 km in the Mid-Atlantic.

 

23 For a more detailed description of how visual range corresponds to light extinction, see Chapter V.
II-5

Table II-1. The environmental elements leading to various haze conditions.View (provided byIMPROVE)

Haze Atmospheric Conditions Effects on Emitted

Pollutants

Clear Day Atmosphere is well mixed, Generally associated with

windy conditions

Pollutants mix verticallyand horizontally with sometransport away from source

Plume Blight(viewed as a thin line ofhaze) local in nature

Stable air and horizontalwind

Pollutants will stretch alonghorizontal plane fromsource emission level

Layered Haze(haze stretching from thesurface to a distinct height)generally local in nature

Stable air and no wind (i.e.stagnant conditions, novertical mixing, may be dueto a layer of stable air or aninversion layer)

Accumulation of pollutantsat source

Uniform Haze(stretches from the surfaceto well above anysurrounding vista)can extend across largeregional distances

Atmosphere is well mixed Pollutants are well-mixed

around source (verticallyand laterally)
II-6

C. Causes of Haze in the Northeast and Mid-Atlantic

The fine particles that impair visibility and contribute to haze in the eastern U.S.

include a variety of pollutants. They are primarily composed of the following

constituents:

• Sulfates

• Nitrates

• Organic carbon

• Elemental carbon

• Crustal material.

Most of these constituents (i.e., sulfates, nitrates, organic carbon, and crustal

particles) affect visibility by scattering light. By contrast, elemental carbon contributes to

visibility impairment chiefly by absorbing light (see Figure II-4).24

Particles are often characterized as either “primary,” meaning that they are

directly emitted from a pollution source, or as “secondary,” meaning that they are formed

in the atmosphere from precursor emissions. Elemental carbon (the main constituent of

soot) is emitted directly from diesel combustion and other sources and is an example of a

primary particle. Elemental carbon is distinguished from organic carbon by the fact that

 

24 As noted previously, nitrogen dioxide is a gaseous, manmade pollutant that can also absorb light.

However, its visibility impacts are not generally significant on a regional scale (see Footnote 20).

Figure II-3. Relationships between various measures of visibility conditions.

(adapted from Malm, 2000a).

Natural conditions in the Northeast

Extinction, bext (Mm-1)

Deciviews (dv)

Visual Range (km)

Typical day in Northeast

Typical day in Mid-Atlantic

14

100

40

42

670

6

35

330

12

49

1340

3

7

20

200

21

50

80

28

160

400 25

10

0
II-7

organic carbon is bound to hydrogen and other atoms in the form of more complex

molecules. The term organic carbon encompasses literally hundreds to thousands of

species of carbon and hydrogen containing molecules. Sulfates and nitrates are formed

in the atmosphere from emissions of sulfur dioxide (SO2) and nitrogen oxides (NOX),

respectively and are examples of secondary particles. To further complicate matters,

particles may exist as liquids or solids and may be composed of a mixture of the different

chemical species listed above. The size of particles also varies greatly. Very small or

“fine” particles are generally more efficient at scattering light and are hence of primary

concern from a regional haze perspective. In fact, per unit mass, particles with diameters

in the range of 0.1 to 1.0 micrometer25 are the most effective at scattering light. This

class of particles is within the 2.5 micrometer size designation used to distinguish fine

from coarse particles in proposed federal regulations to limit the health impacts of

particle pollution (see further discussion in Chapter IV).

Fine particles in the atmosphere come from both man-made and natural sources.

Sulfate particles are formed in the atmosphere primarily from SO2 emissions. The

dominant source of SO2 emissions in the eastern U.S. is fossil fuel combustion, primarily

at coal-fired power plants and industrial boilers. Similarly, nitrate particles are formed

 

25 One micrometer (μm) is equivalent to one-one millionth of a meter (10-6m), about the size of one

hundred molecules laid end-to-end.

Figure II-4: Principal components of light impairing particles in the atmosphere.

(adapted from Malm, 2000a).

Elemental Carbon

Organics

Sulfates Nitrates

Soil

Absorber

Scatterers
II-8

from the NOX emitted by power plants, automobiles, industrial boilers, and other

combustion sources. While human sources account for most nitrate precursors in the

atmosphere, there are some natural sources, including lightning, biological and

abiological processes in soils,26 and stratospheric intrusion (USEPA, 2000). Organic

carbon in the atmosphere is emitted by automobiles, trucks, and industrial processes, as

well by many types of vegetation. Elemental carbon (soot) is primarily caused by the

combustion of diesel, wood, and other fuels. Crustal material may include soil, salt, rock

and other material27 and has both natural and manmade sources (examples of the latter

include soil dust from roads, construction, and agriculture).

Particulate pollution is, as mentioned above and discussed more extensively in

later chapters of this report, directly targeted under existing and proposed air quality

regulations. To date, however, these regulations provide for the control of ambient

particle levels only on the basis of particle size and mass concentration, i.e. without

distinguishing between types of particles. When it comes to visibility impairment,

however, not all particles are created equal. Depending on their specific size, geometry,

chemical composition and – importantly – their ability to absorb water molecules in the

atmosphere,28 different particles will scatter light more or less effectively. Sulfates and

nitrates, for example, are highly hygroscopic (meaning they have a strong affinity for

water), a characteristic that tends to enhance their light scattering efficiency. As a result

these types of particles contribute disproportionately to visibility impairment in the

eastern U.S. Table II-2 summarizes the chief constituents of fine particle pollution in the

Northeast and Mid-Atlantic, their sources and relative contribution to visibility

impairment. Further discussion of the patterns and determinants of fine particle pollution

in the East may be found in Chapter III.

 

26 Note that soil processes may be substantially influenced by fertilizer use, thereby creating another

potential man-made source of emissions.

27 A better understanding of crustal material and soil dust, which are likely to vary in composition

throughout the U.S., is needed. This class of particles may include silicon, aluminum, iron, calcium,

magnesium, sodium, potassium, titanium, manganese, chromium, vanadium, iron and cobalt constituents.

Generally, soil dust has lower concentrations of calcium, magnesium and sodium than crustal rock

(Seinfeld and Pandis, 1998) and is of greater concern with respect to visibility impacts in the western U.S.

28 As water condenses onto very small particles in the atmosphere, they grow in size and become more

effective at scattering light. This growth rate is directly proportional to the amount of available water (i.e.

relative humidity).
II-9

Table II-2. Characteristics of Particles Associated with Haze

Typical MassConcentration inthe Eastern U.S.

(μg/m3

)

Emission Sources Particle

Species

Effect onIncidentVisibleLight

AverageContributionto VisibilityImpairment inthe East1 Natural6 Natural + Anthro.

Primary orSecondaryPollutant

Natural Anthropogenic

Other

Environmental

and Health

Consequences

Sulfate Scatter 60% -80% 0.23 4.87 Secondary

pollutant,formed fromSO2

Sea Spray3

,

volcanoes3

,

wildfires3, marine

plankton2

,

bacteria2

Fossil-fuel burning1, notably at

coal-fired power plants; andsome industrial processes, suchas metal smelting1

Aciddeposition1,5,

respiratoryailments1,5

Nitrate Scatter 5% - 15% 0.1 0.37 Secondary

pollutant,formed fromNOX

Wildfires3, soil3

,

lightening3

,

stratosphericintrusion5, home

heating

Fossil-fuel burning3, notably

by mobile sources and powerplants, aircraft5

Aciddeposition1,5,

irritant to eyesand lungs2

,

eutrophication,ozone precursor5

OrganicCarbon* Scatter

10% - 30% 1.5 2.07 Primary and

secondarypollutant,formed fromhydrocarbons

Wildfires3, Plants Meat-cooking3, dust from

roads3, fireplaces3, gasoline

vehicles3, diesel vehicles3

,

surface coating3, cigarettes3

,

brake lining3,roofing tar pots3

,

tire wear3, natural gas

combust.3, petroleum

processing3, railroad (diesel

oil)3, refinery gas combust3

Enhanceformation ofground-levelozone5, toxic

chemicals2

ElementalCarbon*

Absorb 5% - 15% 0.02 0.47 Primary

Pollutant

Wildfires Wood combustion1,4, diesel 4 Toxic chemicals5

CrustalMaterial

Scatter 5% - 15% 0.5 0.37 Primary

Pollutant

Dust4 Unpaved roads, agriculture Respiratory

effects

Ammonia (ammonium ion chemically bonds with sulfates and nitrates): animal husbandry3, fertilizer use5, sewage3, mobile

sources3, forest fires5, combustion3, industrial processes3, vegetation5, wild animals5

Gases listed in blue; Particles in red. *Organic carbon consists of literally thousands of different molecules primarily consisting of carbon and hydrogen in various

configurations. Elemental carbon, also termed black, free or graphite carbon, consists of carbon alone.Sources: 1USEPA, 2000a; 2Hill, 1997; 3USEPA, 1997b; 4USEPA, 1997a; 5Seinfeld and Pandis, 1998; 6Trijonis et al., 1990; 7approximated from IMPROVE data at five

Northeast and Mid-Atlantic Class I sites (Acadia, Maine; Brigantine, NJ; Great Gulf, NH; Lye Brook, VT; Moosehorn, Maine), hence, represents rural concentrations.
II-10

References

FLAG (Federal Land Managers’ Air Quality Related Values Workgroup). Draft Phase I

Report. U.S. Forest Service, National Park Service, and U.S. Fish and Wildlife Service:

Oct. 1999.

Hill, M.K., Understanding Environmental Pollution, Cambridge University Press, NY,

NY: 1997.

Malm, William C., Introduction to Visibility, Cooperative Institute for Research in the

Atmosphere (CIRA), Colorado State University, Fort Collins, CO, 80523, 2000a.

Malm, William C., Spatial and Seasonal Patterns and Temporal Variability of Haze and

its Constituents in the United States, Cooperative Institute for Research in the

Atmosphere (CIRA), Colorado State University, Fort Collins, CO, 80523, 2000b.

Seinfeld, J.H. and S.N. Pandis. Atmospheric Chemistry and Physics: From Air

Pollution to Climate Change, John Wiley & Sons, Inc., NY, NY, 1998.

Trijonis, J.C., W.C. Malm, M. Pitchford, and W.H. White, Visibility: Existing and

Historical Conditions – Causes and Effects, State of Science and Technology Report 24,

Volume III of the National Acid Precipitation Assessment Program (NAPAP),

Washington: Oct. 1990.

USEPA. “National Air Quality and Emissions Trend Report, 1997,” EPA-454/R-98-016,

available online: http://www.epa.gov/oar/aqtrnd97/index.html, 1997a.

USEPA. “The Virtual Workgroup for the PM2.5 Analysis Workbook,” available online:

http://capita.wustl.edu/Database/UserDomains/PMFineAnalysisWB, 1997b.

USEPA. “Latest Findings on National Air Quality: 1999 Status and Trends,” EPA454/F-00-002, available online: http://www.epa.gov/oar/oaqps/efig, 2000.
III-1

III. Anatomy of Regional Haze in the Northeast and MidAtlantic

As described in the previous chapter, visibility impairment and haze in the

Northeast and Mid-Atlantic are caused by small, light-scattering and light-absorbing

particles in the atmosphere. This chapter begins by describing the geographic

distribution of fine particle pollution in the Northeast and Mid-Atlantic and the relative

contribution of different particle species to light extinction on the best and worst visibility

days in the region. A short section also describes particle concentrations and composition

at a few Class I sites just south and west of the Northeast/Mid-Atlantic region. The

chapter then goes on to describe seasonal variation in particle pollution and visibility

impairment, the link between regional haze and other air quality concerns, and the

regional nature of haze. Finally, the chapter concludes with a description of a particularly

extreme regional haze episode that occurred between July 15 and July 20 of 1999 in the

eastern U.S. A review of this episode helps to illustrate many of the factors that

contribute to severe visibility impairment in the eastern U.S.

A. Fine Particle Concentrations in the Northeast and Mid-Atlantic

Data on fine particle concentrations (in micrograms per cubic meter or μg/m3) in

the Northeast and Mid-Atlantic are available from a network of monitors that have

operated under various programs in the region since the late 1980s.29 Figure III-1a shows

average annual fine particle concentrations, while Figure III-1b exhibits average daily

high values30 for the period from 1991-98. Note that “fine particles” are defined

throughout this discussion as particles with a diameter less than or equal to 2.5 μm

(PM2.5) for consistency with current monitoring programs and proposed federal

regulations.

The geographic distribution of fine particle concentrations shown in Figures III-1a

and III-1b is consistent with the geographic distribution of pollutant sources in the East,

and with the movement of prevailing weather systems, which tend to flow from west and

south toward the north and east. Both annual average and maximum daily fine particle

concentrations are highest near heavily industrialized areas and population centers. Not

surprisingly, given the direct connection between fine particle pollution and haze, the

same pattern emerges when one compares measures of light extinction on the most and

least visibility impaired days at parks and wilderness areas subject to federal haze

regulations in the Northeast and Mid-Atlantic (see Figures III-2a and III-2b). Light

extinction from particles on the 20 percent most visibility impaired days31 ranges from

178 Mm-1 at Brigantine, NJ (the southernmost Class I site in the region) to 133.6 Mm-1 at

Lye Brook, VT to 86.2 Mm-1at Moosehorn, ME (the northernmost Class I site in the

 

29 Monitoring programs and technologies are discussed further in Chapter VIII.

30 Defined as the 98th percentile mass concentration measured over a 24-hour period in the course of a year. 31 See Footnote 9 for definition of twenty percent most/least visibility impaired days. See Figure III-2a and

2b for total light extinction (particle extinction plus rayleigh extinction) on the worst/best days.
III-2

region). The corresponding figures for the 20 percent least visibility impaired days31 at

these sites range from 41.5 Mm-1 at Brigantine to 16-17 Mm-1 at Lye Brook and

Moosehorn.

Notably, visibility values on the 20 percent least impaired days at the more remote

northeastern and mid-Atlantic Class I areas are comparable to estimates of visibility for

the region under natural, unpolluted conditions (on the order of 20 Mm-1, as noted in the

previous chapter). At the more southerly Brigantine site, by contrast, light extinction on

even the 20 percent least impaired days is well above that associated with natural

conditions. Equally striking, however, is the fact that substantial visibility impairment

occurs as frequently as every one day out of five at even the most remote sites in the

region. Measured light extinction of 96 Mm-1 at Moosehorn on the 20 percent most

Figure III-1a: Annual average fine particle concentrations in the northeastern U.S.

6.5

5.8

8.0

 8.0

7.5

10.4

9.4

11.4

11.3

6.9

4.1

 12.8 14.9

15.0

 7.3

 10.0 

 9.1

 7.2

14.6

16.2

13.0

14.1

 14.1

 11.2

11.6

24 - 34

13.7

16.5

16.3

Urban Sites

Rural Sites (mostly IMPROVE)

Rural Sites (mostly NEPART)

Note: Data are listed in μg/m3 and were obtained from a variety of sources including: the IMPROVE Program,

the NEPART network (see Chapter VIII), various state agencies, and other field studies (NESCAUM, 1999).
III-3

impaired days corresponds to a visual range of only 41 km; this is less than a quarter of

the visual range of 170 km estimated for natural conditions.

 In sum, the spatial distribution of fine particle concentrations and particle-related

light extinction in the Northeast and Mid-Atlantic points to the role played by

anthropogenic (manmade) sources of pollution, and more particularly to the atmospheric

transport of pollutants from regions to the south and west toward the north and east. It

also points to the fact that substantial visibility impairment is a frequent occurrence in

even the most remote and pristine areas of the Northeast and Mid-Atlantic.

Figure III-1b: 98th percentile fine particle concentrations in the northeastern U.S.

20.2

15.4

23.1

21.3

23.0

31.6

27.1

29.6

32.8

23.9

10.4

34.0 36.3

40.2

 21.6

 25.4 

 26.3

 27.6

31.5

37.8

28.7

32.9

34.7

57 - 62

37.7

41.2

39.9

Urban Sites

Rural Sites (mostly IMPROVE)

Rural Sites (mostly NEPART)

Note: Data are listed in μg/m3 and were obtained from a variety of sources including: the IMPROVE Program,

the NEPART network (see Chapter VIII), various state agencies, and other field studies (NESCAUM, 1999).
III-4

B. Fine Particle Composition in the Northeast and Mid-Atlantic

The chief constituents of fine particle pollution in the Northeast and Mid-Atlantic,

and hence the pollutants that are largely responsible for haze, were introduced in the

previous chapter. They include sulfates, nitrates, organic carbon, elemental carbon, and

material from the earth’s crust (e.g. soil, dust, sea salt, etc.). Figures III-3a and III-3b

provide more detail on the relative contribution of these constituents to fine particle mass

concentrations at northeastern and mid-Atlantic Class I sites on the 20 percent most and

least visibility impaired days in 1997.32 Data from Washington D.C. are included for

purposes of comparison with a more southern, urban site.

 

32 Fine particle mass concentrations were derived from monitoring data collected by the IMPROVE

monitoring network. IMPROVE stands for Interagency Monitoring of Protected Visual Environments. It

Figure III-2a: Extinction near Class I areas in the Northeast and Mid-Atlantic States

during the 20% worst visibility days in 1997.

Washington D.C.

242 Mm-1

(16 km/31.9 dv)

Brigantine

189 Mm-1

(21 km/29.4 dv)

Lye Brook

144 Mm-1

(27 km/26.7 dv)

Great Gulf

(Presidential Range)

140 Mm-1

(28 km/26.4 dv)

Moosehorn

(Roosevelt Campobello)

Acadia

110 Mm-1

(36 km/24 dv)

96 Mm-1

(41 km/22.6 dv)
III-5

The most striking observation to emerge from Figures III-3a and III-3b concerns

the dominant role of sulfate. Sulfate alone accounts for anywhere from one-half to twothirds of total fine particle mass on the 20 percent haziest days at all of the sites shown.

Even on the 20 percent clearest days, sulfate generally accounts for the largest fraction

(40 percent or more) of total fine particle mass at all the sites except Great Gulf, NH.33

 and other monitoring programs are described in greater detail in Chapter VIII. Appendix B of this report

details IMPROVE sampling techniques and data analysis; Appendix C presents more complete sampling

data from each IMPROVE site. The methodology used to analyze IMPROVE data for purposes of this

report is described in Chapter V. Note that mass concentrations derived for Figures III-3a and III-3b differ

slightly from those presented in Appendix C due to different sorting methodologies (i.e. particle extinction

vs. gravimetric fine mass). The year 1997 was selected because it was characterized by representative

meteorological conditions.

33 It is worth pointing out that there are no complete years of monitoring data for Great Gulf, which may

explain its divergence from the other IMPROVE sites. Data for this site only span the summer months of

Figure III-2b: Extinction near Class I areas in the Northeast and Mid-Atlantic States

during the 20% best visibility days in 1997.

Washington D.C.

70 Mm-1

(56 km/19.5 dv)

Brigantine

52 Mm-1

(75 km/16.5 dv)

Lye Brook

26 Mm-1

(150 km/9.6 dv)

Great Gulf

(PresidentialRange)

30 Mm-1

(130 km/11 dv)

Moosehorn

(Roosevelt Campobello)

Acadia

28 Mm-1

(140 km/10.3 dv)

27 Mm-1

(145 km/9.9 dv)
III-6

After sulfate, organic carbon consistently accounts for the next largest fraction of total

fine particle mass. Its contribution typically ranges from 20 to 30 percent on the haziest

days. On the 20 percent clearest days in 1997, the contribution from organic carbon was

as high as 40 percent at the more rural sites (and even reached as much as 50 percent at

Great Gulf34); this is likely to be indicative of the role played by organic emissions from

vegetation (so-called “biogenic hydrocarbons”). Relative contributions from nitrate,

elemental carbon, and fine soil are all smaller (typically under 10 percent), but the

relative ordering among the three species varies with location. Nitrate plays a noticeably

more important role at the Washington, DC site compared to northeastern and midAtlantic Class I locations, perhaps reflecting a greater contribution from vehicles and

other urban pollution sources.

Sulfate is not only the dominant contributor to fine particle mass in the region, it

accounts for anywhere from 60 to almost 80 percent of the difference between fine

particle concentrations on the clearest and haziest days at northeastern and mid-Atlantic

Class I sites. Notably, the exception is Washington DC, where sulfate accounted for only

41 percent of the difference in average fine particle concentrations for the 20 percent

most vs. least visibility impaired days in 1997.

As noted at the conclusion of the previous chapter, all particles are not created

equal when it comes to their effect on visibility. Because of the hygroscopic (water

attracting) properties of sulfate and nitrate, their relative contributions to total light

extinction are found to be disproportionately larger than their relative contributions to

total particle mass. By comparison, the light-scattering contribution of organic carbon,

which is assumed to be non-hygroscopic, becomes smaller. Figures III-4a and III-4b

present the same speciated monitoring data from 1997, this time in terms of contribution

to estimated light extinction. Note that these contributions are shown relative to total

particle-related light extinction, which does not include the background contribution

from Rayleigh scattering. These figures also group coarse particles (i.e., particles with a

diameter between 2.5 and 10 μm) with fine soil under the “crustal” category. Figures III3a and III-3b do not include coarse particles as their mass is not considered a contribution

to fine particle mass.

 May or June through September, and hence miss some of the hazy days that can occur during the cooler

months of the year in the Northeast. Moosehorn, ME is the only other site where the sulfate contribution

was matched by the organic carbon contribution (with each accounting for 40 percent of total mass) on the

20 percent clearest days in 1997. However, 1997 may have been slightly anomalous in this respect. As at

other Class I sites, in 1995, 1996, and 1998 the organic carbon contribution at Moosehorn was somewhat

below the sulfate contribution on even the 20 percent least impaired days.

34 As noted in Footnote 33, data for the Great Gulf site are limited to the summer months when natural

organic emissions from trees are likely to be highest. (Another factor in the summertime may be the

presence of higher ozone levels, which contribute to enhanced oxidation of organics regardless of origin.)

This may explain the especially high organic carbon contribution documented at this site. A comparison to

summer data from the nearby Lye Brook site tends to confirm this hypothesis. On the 20 percent least

impaired summer days at Lye Brook, relative mass concentrations for organic carbons were almost

identical to those found at Great Gulf, suggesting that hydrocarbons (a substantial portion of which may be

biogenic in origin) do contribute up to half of fine particle mass at rural sites on clear summer days in the

region.
III-7

The sulfate contribution, already dominant in terms of total fine particle mass,

becomes even larger when the differential visibility impacts of different particle species

are considered. Figure III-4a shows that in 1997, sulfate accounted for 70 to 82 percent

of estimated particle light extinction at northeastern and mid-Atlantic Class I sites, as

well as in Washington, DC. Organic carbon continues to be the second most important

contributor to particle light extinction at rural sites on the most impaired days, but slips to

third behind nitrate in Washington, DC.35

Figure III-4b indicates that on the 20 percent least impaired days, sulfate accounts

for over half of total particle light extinction at rural sites, followed in most cases by

organic carbon. Notably, crustal material plays a relatively more significant role on the

clearest days (especially at the Brigantine and Acadia sites), a result that may be due in

part to the inclusion of coarse particles in this category. The relative contribution of

elemental carbon and nitrate on the 20 percent clearest days is generally smaller at the

rural sites, but varies from location to location.

 

35 The monitoring data presented in Appendix C indicate that nitrate was often, though not always, the

second highest contributor to particle light extinction at the DC site over the sampling period from 1989 to

1998. It should be noted that the speciated data for 1997 in DC, when sorted by calendar year and light

extinction, depart from the relative ordering shown in Appendix C, although they are directionally

consistent with the data for previous years. Despite these discrepancies, the general finding that nitrate

plays a greater role in overall light extinction at the DC site appears robust when all sampling years are

taken into account.
III-8

Figure III-3a: Mass characteristics of fine particles (PM2.5) in or near Class I

areas in the Northeast and Mid-Atlantic States during the 20% worst visibility

days in 1997.

Washington D.C.

24.9 μg/m3

Brigantine

9.6 μg/m3

Lye Brook

14.0 μg/m3

Great Gulf

13.4 μg/m3

Moosehorn

9.6 μg/m3

Acadia

10.8 μg/m3

S ite S ulfate Nitrate OC Crus tal EC

Acadia 57 6 30 3 4

Brigantine 67 5 21 4 4

Great Gulf 69 1 22 3 5

Lye Brook 69 4 19 5 3

Moosehorn 56 5 32 3 5

Washington D.C. 59 9 23 4 5

pe rce nt contribution to particle mas s
III-9

Figure III-3b: Mass characteristics of fine particles (PM2.5) in or near Class I

areas in the Northeast and Mid-Atlantic States during the 20% best visibility

days in 1997.

Washington D.C.

6.7 μg/m3

Brigantine

3.9 μg/m3

Lye Brook

1.9 μg/m3

Great Gulf

2.5 μg/m3

Moosehorn

1.9 μg/m3

Acadia

2.0 μg/m3

S ite S ulfate Nitrate OC Crus tal EC

Acadia 42 5 38 8 6

Brigantine 53 10 25 7 5

Great Gulf 33 3 50 6 8

Lye Brook 44 8 37 7 5

Moosehorn 40 6 40 6 8

Washington D.C. 44 13 25 8 10

pe rce nt contribution to particle mas s
III-10

Figure III-4a: Particle extinction characteristics in or near Class I areas in the

Northeast and Mid-Atlantic States during the 20% worst visibility days in 1997.

Brigantine

189 Mm-1

Lye Brook

144 Mm-1

Great Gulf

140 Mm-1

Moosehorn

96 Mm-1

Acadia

110 Mm-1

S ite S O4 NO3 OC Crus ta l EC

Aca dia 70 7 13 5 4

Brigantine 76 5 8 7 4

Grea t Gulf 81 1 9 3 5

Lye Brook 82 5 8 2 3

Moose horn 71 6 14 4 5

Wa shington D.C. 71 12 10 2 6

pe rc e nt c o ntributio n to pa rtic le e xtinctio n

Washington D.C.

242 Mm-1
III-11

Figure III-4b: Particle extinction characteristics in or near Class I areas in the

Northeast and Mid-Atlantic States during the 20% best visibility days in 1997.

Brigantine

52 Mm-1

Lye Brook

26 Mm-1

Great Gulf

30 Mm-1

Moosehorn

27 Mm-1

Acadia

28 Mm-1

Washington D.C.

70 Mm-1

Site SO4 NO3 OC Crustal EC

Acadia 54 7 17 16 6

Brigantin 56 10 9 19 5

Great 48 4 26 12 11

Lye 60 11 18 7 5

Moosehorn 53 8 18 12 9

Washington 56 16 11 5 11

percent contribution to particle
III-12

C. Haze Characteristics at Nearby Class I Areas

As noted earlier in this report (and discussed in later sections of this chapter),

haze is a fundamentally regional problem and often affects large swaths of the eastern

U.S. at the same time. Hence, it is interesting to compare particle concentrations and

visibility impairment inside the Northeast/Mid-Atlantic region to values measured at

Class I areas just outside the region. Figures III-5a and III-5b show fine particle

concentrations and mass composition at Class I areas just to the south and west of the

OTC RPO, including Shenandoah National Park and James River Face Wilderness Area

in Virginia and the Dolly Sods and Otter Creek Wilderness Areas in West Virginia.36

(Note that there are no Class I areas to the immediate west in Ohio, Michigan, or

Indiana.) Figures III-6a and III-6b show the corresponding values in terms of light

extinction.

As these figures show, fine particle concentrations and visibility impairment at

Class I areas just to the south and west of the OTC RPO region are significantly higher

than concentrations at Class I areas within the region. The relative contribution of

different particle constituents is similar, though sulfate contributes an even larger fraction

of total particle extinction (from 65 to 85 percent on the best and worst visibility days

respectively). By contrast, nitrate plays a somewhat lesser role in overall light extinction

at these more southern sites relative to sites in the OTC RPO region.

Finally it should be noted that the Class I areas shown in Figures III-5 and III-6,

while not within the OTC RPO region, may be affected by emissions sources which are

within the region. As such these areas may need to be included in the regional haze

planning efforts of some OTC RPO states, especially those in the more southern portion

of the region.

 

36 Note that the maps are based on monitoring data from three IMPROVE sites and were generated using

the same methodology (described in detail in Chapter V) used to generate Figures III-3 and III-4.
III-13

Figure III-5a: Mass characteristics of fine particles (PM2.5) in or near Class I areas in

Virginia and West Virginia during the 20% worst visibility days in 1997.

Shenandoah

19.0 μg/m3

James River Face

23.5 μg/m3

Dolly Sods/Otter Creek

20.0 μg/m3

S ite S ulfa te Nitra te OC Crus ta l EC

Dolly Sods 77 1 16 3 2

James River 63 3 27 3 4

Shenandoah 72 1 21 3 3

pe rc e nt c o ntributio n to pa rtic le ma s s

Figure III-5b: Mass characteristics of fine particles (PM2.5) in or near Class I areas in

Virginia and West Virginia during the 20% best visibility days in 1997.

Shenandoah

3.7 μg/m3

James River Face

6.1 μg/m3

Dolly Sods/Otter Creek

4.4 μg/m3

S ite S ulfa te Nitra te OC Crus ta l EC

Dolly Sods 48 6 35 4 7

James River 50 6 31 6 7

Shenandoah 55 10 25 4 6

p e rc e nt c o ntrib utio n to p a rtic le ma s s
III-14

Figure III-6a: Extinction characteristics of fine particles (PM2.5) in or near Class I areas

in Virginia and West Virginia during the 20% worst visibility days in 1997.

Shenandoah

193 Mm-1

James River Face

201 Mm-1

Dolly Sods/Otter Creek

232 Mm-1

S ite S ulfa te Nitra te OC Crus ta l EC

Dolly Sods 90 1 6 1 2

James River 77 2 14 2 5

Shenandoah 85 2 9 2 3

pe rc e nt c o ntributio n to pa rtic le e xtinc tio n

Figure III-6b: Extinction characteristics of fine particles (PM2.5) in or near Class I areas

in Virginia and West Virginia during the 20% best visibility days in 1997.

Shenandoah

45 Mm-1

James River Face

56 Mm-1

Dolly Sods/Otter Creek

51 Mm-1

S ite S ulfa te Nitra te OC Crus ta l EC

Dolly Sods 66 8 15 4 7

James River 61 8 16 6 9

Shenandoah 66 12 11 5 7

pe rc e nt c o ntributio n to pa rtic le e xtinc tio n
III-15

D. Seasonal Variations in Particle Concentration and Light Extinction

The two digital camera views of the Boston city skyline shown in Figures III-7a

and III-7b on the opposing page suggest that hazy days in the summer and winter can

have significantly different visual characteristics in the Northeast. Indeed, the milky,

uniform visibility impairment shown in Figure III-7a is typical of summertime regional

haze events in the Northeast. During the winter, by comparison, reduced convection and

the frequent occurrence of shallow inversion layers often creates a layered haze with a

brownish tinge, as shown in Figure III-7b. This visual difference suggests seasonal

variation in the relative contribution of different gaseous37 and particle constituents

during the summer vs. winter months.

Figures III-8a through III-8e show seasonal variation in the relative contribution

of different particle species to estimated light extinction during the 20 percent most

impaired days from 1997 to 1998 at several northeastern and mid-Atlantic sites.38 Mass

concentrations (in μg/m3) are indicated by the numbers at the top of each column. To

generate these figures, those days which were among the 20 percent most impaired days

and occurred in the summer (June, July, and August) were grouped together as were

those which occurred in the winter (December, January, and February). Because some

poor visibility days occurred outside these months, 1998 data were included to increase

the sample size for each season.

Monitoring data from the Virginia and West Virginia sites discussed in the

previous section were also examined with respect to seasonal variation. However, the

results suggest that almost none of the 20 percent worst visibility days in 1997 and 1998

occurred in the wintertime in these areas, indicating that the most severe visibility

degradation occurs in the summer at these sites. Hence, similar seasonal figures for these

areas are not included here.

As the figures on the subsequent pages show, only a handful of the 20 percent

most visibility impaired days at each of the OTC RPO sites occurred between December

and February during the two-year period. In addition, total light extinction on the haziest

winter days was generally well below total light extinction during the haziest summer

days.

Figures III-8a through III-8e indicate that the overall difference in summer vs.

winter particle mass concentrations and light extinction is largely driven by seasonal

variation in sulfate mass concentrations. This is because winter meteorological

conditions are less conducive to the oxidation of sulfate from SO2. In addition, seasonal

differences in long-range transport patterns from upwind SO2 source regions may be a

factor.

 

37 The brownish tinge in Figure III-7b is caused by gas phase nitrogen dioxide which can accumulate to

high enough levels to contribute to light absorption in urban locations, especially when trapped by a

shallow inversion layer.

38 The Great Gulf site is excluded as only summer data are available from that site.
III-16

Figure III-7a: Hazy day in Boston, MA during the summer (July 16, 1999)

Figure III-7b: Hazy day in Boston, MA during the winter (January 21, 1999)

.
III-17

Figure III-8a: Summer/winter particle species contribution to reconstructed light

extinction during the 20 percent most impaired days at Acadia, ME.

0

20

40

60

80

100

120

Summer Winter

Extinction (Mm-1)

Sulfate

Nitrate

Org Carbon

Crustal

Elem Carbon

8.3 0.6

2.8 1.2

5.1

7.3 0.5

3.5

0.2

8.6

19 Days 6 Days

Note: Average mass concentration is indicated at the top of each column in units of μg/m3.

Figure III-8b: Summer/winter particle species contribution to reconstructed light

extinction during the 20 percent most impaired days at Brigantine, NJ.

0

20

40

60

80

100

120

140

160

180

Summer Winter

Extinction (Mm-1)

Sulfate

Nitrate

Org Carbon

Crustal

Elem Carbon

19 Days 4 Days

13.6

0.4

4.5

16.2 0.6

8.7

1.2 3.2

11.6 0.9

Note: Average mass concentration is indicated at the top of each column in units of μg/m3.
III-18

Figure III-8c: Summer/winter particle species contribution to reconstructed light

extinction during the 20 percent most impaired days at Lye Brook, VT.

0

20

40

60

80

100

120

140

Summer Winter

Extinction (Mm-1)

Sulfate

Nitrate

Org Carbon

Crustal

Elem Carbon

0.5 5.7

2.1

2.8 2.8

0.5 3.2

3.1

0.3

10.8

17 Days 3 Days

Note: Average mass concentration is indicated at the top of each column in units of μg/m3.

Figure III-8d: Summer/winter particle species contribution to reconstructed light

extinction during the 20 percent most impaired days at Moosehorn, ME.

0

10

20

30

40

50

60

70

80

Summer Winter

Extinction (Mm-1)

Sulfate

Nitrate

Org Carbon

Crustal

Elem Carbon

5.9

0.2

3.4

3.9

0.5

3.6

0.9

1.5 7.1 0.3

18 Days 2 Days

Note: Average mass concentration is indicated at the top of each column in units of μg/m3.
III-19

 Although sulfate accounts for a relatively smaller fraction of total light extinction

during the winter months, it nevertheless remains the dominant constituent species during

both seasons. The absolute contribution from organic carbon declines somewhat during

the winter, but generally not by a tremendous amount. Similarly, there does not appear to

be a consistent seasonal difference in the contribution from elemental carbon and crustal

material, although their average concentrations tend to be highest in summer.

Nitrate, by contrast, clearly contributes more in absolute and relative terms to

particle light extinction in the winter months. Indeed, the winter nitrate contribution to

light extinction almost equaled the winter sulfate contribution at Lye Brook during the

1997-98 period. The greater presence of nitrate during the cold season is a consequence

of the chemical properties of ammonium nitrate. Ammonia bonds more weakly to nitrate

than it does to sulfate and ammonium nitrate tends to dissociate at higher temperatures.

Consequently, ammonium nitrate becomes more stable at lower temperatures and hence

contributes more to overall light extinction during the winter months.

Figure III-8e: Summer/winter particle species contribution to reconstructed light

extinction during the 20 percent most impaired days at Washington, DC.

0

50

100

150

200

250

Summer Winter

Extinction (Mm-1)

Sulfate

Nitrate

Org Carbon

Crustal

Elem Carbon

17.3

19 Days 1 Day

2.2

8.4

5.9

2.9

8.0

1.2

5.1

5.7

0.6

Note: Average mass concentration is indicated at the top of each column in units of μg/m3.
III-20

E. The Link Between Haze and Other Air Quality Problems

As should be evident from the discussion in Chapter II and subsequent sections of

this report, haze and visibility impairment are very directly linked to fine particle

pollution. In fact, haze is particle pollution, though it is measured and regulated in

different ways and for different reasons. Particulate matter (PM) is among the so-called

“criteria pollutants” for which USEPA has established National Ambient Air Quality

Standards (NAAQS) to protect human health. At present, a NAAQS exists for particles

up to 10 micrometers in diameter (PM10); more recently, recognizing that smaller

particles pose particular health risks because they may be inhaled more deeply in the

lungs, USEPA promulgated separate NAAQS for particles up to 2.5 micrometers in

diameter (PM2.5). The new standards would limit annual average PM2.5 concentrations to

15 μg/m3 and peak (98th percentile) 24-hour concentrations to 65 μg/m3, based on

epidemiological evidence pointing to a number of health risks associated with both

chronic and short-term fine particle exposure. These risks include increased risk of

respiratory and cardiovascular illness (including chronic bronchitis and asthma) and

increased risk of premature death. The new PM standards (together with a new 8-hour

ozone standard) are currently under review by the U.S. Supreme Court; meanwhile

USEPA is reviewing possible future revisions to the PM2.5 NAAQS on the basis of new

epidemiological evidence.

The connection of haze to another prominent criteria pollutant, ozone, is more

complicated. Haze and ozone are fundamentally different phenomena: ozone, itself a

colorless pollutant, does not directly impair visibility and is formed from a different set of

chemical reactions. Thus, it is possible for fine particle levels, and hence visibility

impairment, to be high on days that are relatively free of ground-level ozone pollution.

On the other hand, ozone formation involves many of the same precursor pollutants

(notably NOx and VOCs) 39 and is enhanced by the same meteorological conditions

conducive to the formation of fine particles, including the presence of sunlight and

humidity. Consequently, researchers have found that high ozone levels are often

associated with hazy air masses in the summertime (Husar et al., 1976; Samson and

Ragland, 1977; Gillani and Wilson, 1980) and weather forecasters are most likely to issue

smog alerts on days described as “hazy, hot, and humid.”40 In addition, there is an

important, indirect link between ozone and haze. Ozone is an atmospheric oxidant and

therefore promotes the formation of secondary particles – including sulfate, nitrate, and

organic aerosols – from precursor emissions of SO2, NOx, and VOCs, respectively.

Finally, to the extent that haze is caused, in part, by precursor emissions of SO2

and NOx, efforts to reduce haze and improve visibility will have an important, if indirect

 

39 Note that optimal conditions for the formation of particles and ozone differ in terms of the relative

concentrations of precursor pollutants; in addition, NOX, is probably more important in ozone formation

than as a particle constituent in the eastern U.S. Conversely, SO2, which plays an important role in particle

formation, does not play a role in ozone formation.

40 Note that the combination of heat and humidity alone cannot cause “hazy” conditions and poor visibility,

absent the addition of particle-forming pollutants.
III-21

link to concerns in many eastern states about the ongoing ecosystem impacts of acid

deposition and nitrogen saturation/eutrophication. These ecosystem impacts affect

critical natural resources in the Northeast and Mid-Atlantic states; impacts that are not

confined to Class I areas.

F. The Regional Nature of Haze in the Eastern U. S.

The recent regulations promulgated by USEPA to address visibility impairment

throughout the nation are premised on the recognition that haze is a fundamentally

regional problem. Because pollutants can travel in the atmosphere, numerous emissions

sources dispersed over a broad geographic region often contribute to haze conditions over

large areas of the country. For example, the primary precursor pollutant for sulfate – a

key constituent of fine particle mass throughout the eastern U.S. – is SO2, a pollutant that

has an atmospheric lifetime of several days and is known to be capable of traveling

hundreds of miles before leaving the atmosphere.41 Other particle constituents and

precursors including NOX,

42 organic compounds,43 and primary particles such as crustal44

and elemental carbon, are also subject to long-range transport under certain

meteorological conditions.

The conditions that tend to create widespread haze and visibility impairment in

the OTC RPO region often start with high-pressure systems that bring pollutants from the

Midwest and Southeast (including ozone precursors, sulfates, and other secondary

pollutants) into the Northeast and Mid-Atlantic states, where they mix with pollutants

from major urban centers. Warm temperatures, abundant sunlight, and lack of ventilation

within the stable boundary layer of these high-pressure systems promote the production

and accumulation of ozone and visibility reducing particles as the systems slowly sweep

eastward and northward. The result can be a large-scale airmass, often blanketing major

portions of the eastern half of the country, with elevated concentrations of ozone and fine

particles.

Just such conditions occurred during the summer of 1999 between Thursday, July

15 and Tuesday, July 20. The result was one of the most severe regional haze events

recorded over the last decade in the eastern U.S. The final section of this chapter

concludes with a description of that event as a way of illustrating the various factors that

combine to create persistent problems of low visibility and regional haze in the Northeast

and Mid-Atlantic states.

 

41 Modeling by USEPA indicates that about two-thirds of total sulfur deposition from large power plants in

the Ohio River Valley occurs within 500 km to 700 km downwind (300-400 miles), with the remaining

third depositing at even greater distances from the emissions source (USEPA, 1995).

42 While NOX itself has a relatively short lifetime in the atmosphere, it has been shown that NOX can

quickly form peroxyacetyl nitrate (PAN) which is stable with respect to transport over large distances after

which the reverse reaction can occur, releasing NOX far downwind of its source (Seinfeld and Pandis,

1998).

43 Organic compounds, as discussed earlier, encompass a wide variety of molecular families with a range of

reactivities and thus can be transported over a correspondingly wide range of distances.

44 In fact, dust storms over the Sahara Desert in northern Africa commonly result in deposition of Saharan

dust over broad regions of the southeastern U.S. (Prospero and Nees, 1986).
III-22

G. Anatomy of a Severe Haze Event

It should be stressed at the outset of this section that the haze event that occurred

in mid-July of 1999 in the eastern U.S. was only unusual in its severity, not in its

underlying causes. Moreover, it bears emphasizing that regional haze is not necessarily

episodic in nature. Rather the conditions that create high haze levels in the East are

common, especially in the summertime, and often persist for long periods of time.

July of 1999 was unusually hot; indeed it was the ninth warmest July since 1895

for the Northeast and Mid-Atlantic as a whole. The stage was set for a major pollution

event when a high-pressure system began to build over the southeastern U.S on July 14-

15.45 Over the next several days, this area of high pressure began to move over the MidAtlantic region. As it built, a pool of cooler air lifted quickly to the Northeast, which is a

typical feature prior to the onset of a pollution transport event for the Northeast

(NESCAUM, 1998). Winds rotating clockwise around the high-pressure zone began

bringing air pollutants from source regions to the west into the Northeast. On Sunday,

July 18, an advancing cold front in the Great Lakes region began to distort the northern

edge of the high pressure ridge; over the next two days this shallow cold front pushed the

high pressure system southward and out of the Northeast (See Figure III-9).

 

45 The meteorological development of this episode has been extensively documented by Dr. William Ryan

at the University of Maryland (Ryan, 2000). This summary draws heavily from Dr. Ryan’s work.
III-23

Wind flows associated with the July 15-20 high pressure system exhibited a

complex pattern in parts of the Northeast. Back trajectory analysis of the air arriving

over Philadelphia on July 17 and 18 shows a circular pattern in which easterly air flow

near the surface cancelled the usual westerly trajectory of winds over the lower

(southern) parts of the Ozone Transport Region (Figure III-10). This area of

recirculation, which also appears in wind field maps from July 15-19 (Figure III-11),

allowed for the build-up of particle and ozone-forming pollutants over the heavily

urbanized areas of Washington DC, Baltimore, Philadelphia, and southern New Jersey.

Figure III-9: Upper air map of the evolution of a high pressure ridge

from July 15-20, 1999.

Colors correspond to upper air temperatures with blue shading indicating coolest and red shading

warmest. Note the relatively cooler air mass over the mid-Atlantic region on July 15 that moved to the

Northeast. This feature typically signals an incipient pollution transport episode for the Northeast region.
III-24

Figure III-10: 48-hour back trajectories for Philadelphia, PA (HYSPLIT, 2000).
III-25

Figure III-11: Average mean vector wind field map from July 15

through July 19, 1999.

Note the small white area near Washington, DC, indicating very low average wind speed vectors.

Recirculation around this area within the larger high pressure region over the southeastern United States

created a complex flow pattern in the lower Northeast.

Meanwhile, wind patterns above the area of recirculation produced a consistent

westerly flow of air into the more northern parts of the Ozone Transport Region on July

17 and 18. Back trajectory analysis for Hartford, CT during this period shows that the air

entering the New England states came from areas substantially to the west, including

Ohio, western Pennsylvania, and West Virginia (see Figure III-12). Having just

stagnated (as indicated by the looping structure at the back end of the trajectories) over an

area characterized by numerous large SO2 and NOX sources, the air reaching Hartford –

like the air recirculating in the Philadelphia-DC area –was likely to have higher than

normal concentrations of ozone and fine particle precursors. In sum, the July 1999

episode exhibited both local transport (in the southern part of the Ozone Transport

Region) and long-range transport (in the more northern part of the region).
III-26

Figure III-12: 48-hour back trajectories for Hartford, CT (HYSPLIT, 2000).
III-27

This complex pattern of intermittent transport and recirculation in the southern

portions of the OTC RPO region, combined with consistent westerly transport of air from

the industrial Midwest to the northern parts of the region resulted in some of the highest

ozone and fine particle concentrations recorded over the past decade. Figure III-13

shows daily maximum 8-hour ozone concentrations over the region from July 15 to July

20. The highest concentrations generally coincided with the development and movement

of the high pressure system: they occurred in the middle to northern portions of the

Northeast early in the episode, peaked across a large area spanning West Virginia to

Connecticut on July 18, and then began to shift south as the cold front pushed the high

pressure system out of the region toward the end of the episode. Notably, ozone

concentrations were already relatively high (greater than 85 parts per billion) in parts of

the Northeast and in areas to the west at the start of the episode on July 15. This reservoir

of ozone to the west set the stage for transport into the Northeast during the upcoming

days.

Figure III-13: Daily maps of maximum 8-hour averaged ozone concentrations

(in ppb) from July 15-20, 1999.

Note: Ozone maps are from U.S. EPA AIRNow (http://www.epa.gov/airnow/maparch.html). The maps are

based on spatial interpolations and may not represent actual measured values at some locations (e.g. the

Pittsburgh monitor only registered 121 ppb maximum concentrations on the 16th).

125 +

105 - 124

 85 - 104

 65 - 84

 0 - 64

ppb
III-28

A similar pattern characterizes PM2.5 monitoring data collected over this period

(see Figure III-14).46 As with ozone concentrations on July 17, the northernmost areas of

the Ozone Transport Region experienced higher fine particle concentrations than the

southern portions of the region (Poirot, 1999). Maximum 24-hour PM2.5 concentrations

on July 17 ranged from 46 μg/m3

 in Acadia National Park and 50 μg/m3 in Bennington,

VT47 to just 18 μg/m3

 in southern New Jersey’s Brigantine Wilderness and 29 μg/m3 in

Washington, DC.

 

46 Because fine particle concentrations were being measured on an every three day basis during 1999,

figures are only available for July 14, July 17, and July 20.

47 Data may be preliminary in some cases and subject to change. The consistency of the high

concentrations across the region, however, suggests that the preliminary data are reasonable indicators of

high concentrations during this time period.
III-29

Figure III-14 Fine particle mass concentrations during July, 1999 (Poirot, 2000a).
III-30

These unusually high fine particle concentrations resulted in extremely poor

visibility conditions across the Northeast and Mid-Atlantic, even at the most remote and

northerly sites. On July 17, visibility at the Burlington, VT airport was just 5 km (3

miles); at Acadia National Park it was just 13-16 km (8-10 miles). Figure III-15 shows

visibility conditions at Boston and Acadia on July 16 relative to clear conditions at both

sites. As the high pressure system shifted south, poor visibility conditions continued, with

airports from Washington to Philadelphia reporting visibility restricted to just a few miles

for several days.

Figure III-15: Digital camera views of Acadia National Park, Maine (upper row)

and the Boston, Massachusetts skyline (lower row).

The pictures on the left are examples of “good” visibility days at both locations. The pictures at the right

show poor visibility conditions at each site at 6:00 p.m. (eastern daylight time) on July 16, 1999.

The high levels of particulate pollution recorded in the Northeast and MidAtlantic during the 1999 mid-July episode provided stark images of haze that could even

be seen from outer space. Images from a satellite orbiting about 440 miles overhead

recorded a large trail of haze extending off the northeastern U.S. coast from Long Island

Sound to well off Cape Cod, MA on July 18, 1999 (Figure III-16).48 (Note that the false

color image on the right side of the figure helps identify the location of the haze plume,

which is circled in both images, relative to the coastline.)

 

48 Images came from a satellite in the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) Project,

http://seawifs.gsfc.nasa.gov/SEAWIFS.html. Figure III-16 is an adapted image from Westphal, 1999.

Acadia Nat’l Park

Boston skyline

Good visibility day July 16, 1999
III-31

Figure III-16: Satellite image from SeaWiFS on July 18, 1999.

Similar images were captured by a weather satellite in a geosynchronous orbit

22,000 miles above the Earth on that day.49 Researchers have since analyzed these

satellite images to identify plume features across large portions of the Northeast and out

over the Atlantic Ocean, including a particularly thick haze patch near the islands of

Martha’s Vineyard and Nantucket on the evening of July 16 (Husar, 1999; Westphal,

1999).

During the mid-July 1999 haze event, as during most poor visibility days in the

Northeast and Mid-Atlantic, sulfate accounted for a very large fraction of overall fine

particle mass. Figure III-17 shows speciated data for fine particle mass concentrations at

several northeastern and mid-Atlantic sites on July 17, 1999. The fact that sulfate levels

were higher at Acadia National Park on this occasion than at Brigantine in New Jersey is

reflective of the unique transport conditions that characterized this haze event. In fact,

the 24-hour ammonium sulfate concentrations measured at Acadia on July 17 were 40

 

49 A description of the Geostationary Operational Environmental Satellite program is on the internet at

http://goes1.gsfc.nasa.gov/.

Haze plume

July 18, 1999
III-32

percent higher than any other previous measurement at that site since monitoring began

in 1988. Monitoring data from Rye, NH during this period bear out the unusual “spike”

in sulfate concentrations that occurred on July 16 and 17 in the Northeast (see Figure III18).

Concentrations are in nanograms per cubic meter (ng/m3).50 Results are from IMPROVE monitors

at Acadia, Lye Brook, and Brigantine and from IMPROVE-type monitors operated by the State of

Connecticut at New Haven and Westport in 1999.

 

50 1000 ng/m3

 is equivalent to 1 μg/m3. These units are customarily used by the IMPROVE program from

which the figure was obtained.

Figure III-17: Average 24 hour total fine particle (PM2.5) mass concentrations in

the Northeast on July 17, 1999.
III-33

Figure III-18. Summer aerosol ionic concentrations at Rye, NH.

Measured ions include SO4, NO3, NH4, Na, Cl, Ca, Mg and K. Preliminary data provided

courtesy of University of New Hampshire Climate Change Research Center, AIRMAP Program.

Finally, researchers have modeled “forward trajectories” of SO2 plumes from

major sources across the region. The results indicate the spatial extent of a sulfate

particle plume passing through the Northeast during the 1999 episode (Figure III-19)

(Poirot, 2000b). While the trajectories do not take into account plume rise, deposition, or

transformation chemistry, their combined spatial pattern is consistent with the sulfate

monitoring data for this period. The modeled plume is also strikingly consistent in shape

and location with the satellite image shown in Figure III-16 (Husar, 1999) and with

another modeling effort that reproduced a sulfate plume extending from the Midwest

through the Northeast and out over the north Atlantic Ocean (Westphal, 1999).
III-34

Figure III-19: Forward trajectories from HYSPLIT model of SO2 plumes from

17 power plants in the Midwest during July 15-18, 1999 (Poirot, 2000b).

SO2 emission rates are based on 1998 continuous emission monitoring data. Concentrations correspond

to 24-hour averaging periods ending at 9 p.m. local time on the identified dates. The HYSPLIT model

did not calculate plume rise, deposition, or transformation chemistry, therefore the “SO2” plumes can be

thought of as precursor plumes for sulfate plumes.
III-35

References

Gillani, N.V., and W.E. Wilson. “Formation and Transport of Ozone and Aerosols in

Power Plant Plumes,” Annals N.Y. Academy of Sciences, 338, 276-296, 1980.

Husar, R.B., D. Patterson, C.C. Paley, and N.V. Gillani. “Ozone in Hazy Air Masses.”

Proceedings of Intl. Conf. on Photochemical Oxidant and its Control, Raleigh, NC, 12-

17 September 1976.

Husar, R.B. “Satellite and Haze Detection on July 16-18, 1999,” CAPITA, Washington

University, St. Louis, MO, available online:

http://capita.wustl.edu/CAPITA/CapitaReports/99071618Haze/99071618Haze/index.htm,

October 1999.

HYSPLIT, “HYbrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT-4)

Model.” NOAA Air Resources Laboratory, Silver Spring, MD, available online:

http://www.arl.noaa.gov/ready/hysplit4.html, 2000.

NESCAUM, 8-hr and 1-hr Ozone Exceedances in the NESCAUM Region (1993-1997),

Northeast States for Coordinated Air Use Management, Boston, MA, September, 1998.

Poirot, R. “7/16-17/99 Northeast Fine Particle and Ozone ‘Haze’ Episode.” Vermont

Department of Environmental Conservation, Waterbury, VT. Online. Internet. 1999.

Available: http://capita.wustl.edu/neardat/Activities/july99/july99.htm.

Poirot, R. Vermont Department of Environmental Conservation, Waterbury, VT.

Personal Communication. 12 September 2000a.

Poirot, R. Vermont Department of Environmental Conservation, Waterbury, VT.

Personal Communication. 31 March 2000b.

Prospero, J.M., and R.T. Nees, “Impact of the North African Drought and El Nino on

Mineral Dust in the Barbados Trade Winds,” Nature, 320, pg. 735-738, 1986.

Ryan, W. “Discussion of the 1999 Ozone Season: Summary of Weather Conditions,”

University of Maryland, Department of Meteorology, available online:

http://metosrv2.umd.edu/~ryan/summary99.htm, February 11, 2000.

Samson, P.J., and K.W. Ragland. “Ozone and Visibility Reduction in the Midwest:

Evidence for Large-Scale Transport.” J. Applied Meteorology, 16, 1101-1106, 1977.

Seinfeld, J.H. and S.N. Pandis. Atmospheric Chemistry and Physics, John Wiley &

Sons Inc., New York, New York: 1998.
III-36

USEPA. Acid Deposition Standard Feasibility Study Report to Congress. Washington,

DC: Acid Rain Division, Office of Air and Radiation, U.S. EPA, EPA 430-R-95-0001a,

p. 67, October 1995.

Westphal, D. “Environmental Conditions along Long Island Sound, July 16-17, 1999.”

Naval Research Laboratory, Monterey, CA, available online:

http://www.nrlmry.navy.mil/aerosol/Case_studies/19990717_jfk/, 1999.
IV-1

IV. Federal Regional Haze Requirements

Congress first adopted a national program aimed at protecting visibility and

reducing haze in national parks and wilderness areas over two decades ago. The

objectives of this program, as articulated in the 1977 Amendments to the federal Clean

Air Act, were:

“[T]he prevention of any future, and the remedying of any existing,

impairment of visibility in mandatory Class I Federal areas which impairment

results from manmade air pollution.”

In short, Congress was aiming for nothing less than the restoration of pristine, unpolluted

vistas in the nation’s most cherished natural areas.

Though the goal of the federal regional haze program, as adopted in 1977, was a

lofty one, the actual pollution control efforts it inspired over the ensuing two decades

were relatively modest. The specific regulations subsequently issued by USEPA in 1980

to implement national visibility goals focused largely on local sources of visibility

impairment and plume blight in Class I areas, and specifically deferred the more

controversial issue of regional haze. Thus, only emissions sources or groups of sources

to which specific visibility impairment could be “reasonably attributed” were subject to

pollution control requirements. (As it turned out, such a finding was made in only one

state and for only one Class I area throughout the 1980s.) Moreover, only those states

that hosted Class I federal areas were required to make haze reduction efforts and to

submit plans demonstrating “reasonable progress” toward the national goal. Congress

took some interim steps to address these shortcomings in the 1990 Clean Air Act

Amendments, which authorized additional research funds to study visibility impairment

and established a procedure for creating Visibility Transport Commissions. These

Commissions were to be made up of Governors from states with sources that contributed

to visibility impairment even in Class I areas outside their borders and represented a first

step toward addressing the problem of haze on a regional basis. Despite these efforts, by

the late 1990s, average visual range in eastern Class I areas remained less than a third of

what it would be under natural conditions.

In July of 1999, USEPA initiated a second phase of the federal haze program by

issuing a new set of federal requirements (64 Fed. Reg. 35,714 (July 1, 1999)). Known

as the 1999 regional haze rule, the new USEPA requirements seek to invigorate visibility

protection efforts by setting a specific deadline of 2064 for achieving national visibility

goals and by redirecting state and federal approaches toward reducing haze. Specifically,

the 1999 rule moves away from a localized approach and the concept of “reasonably

attributable” impairment from specific pollution sources to a more regional approach

which recognizes that visibility impairment is generally caused “by the emission of air

pollutants from numerous sources located over a wide geographic area.” Importantly, the

new rule requires that all states with sources that “may reasonably be anticipated to cause

or contribute” to poor visibility in a protected area (40 C.F.R. §51.300(b)(ii)) develop

regional haze implementation plans, regardless of whether those states themselves
IV-2

contain any mandatory Class I areas. In order to facilitate effective program coordination

among states and to effectively implement regional haze reduction strategies, USEPA has

designated five regional planning organizations (RPOs) covering all areas of the U.S. (see

Figure IV-1). The Ozone Transport Commission (OTC) was selected to serve as the

RPO for the Northeast and Mid-Atlantic regions. It includes all states along the eastern

seaboard from Washington, DC to Maine. Interested tribes can also join, giving them a

first-ever opportunity to participate directly in air quality planning in the OTC region.

RPOs for other regions include: Southeast States Air Resource Managers (SeSARM), the

Midwest RPO coordinated by Lake Michigan Air Directors Consortium (LADCo),

Central Regional Air Partnership (CenRAP), and the Western Regional Air Partnership

(WRAP).

This chapter describes the specific requirements that apply to states under the

original federal haze program and under USEPA’s more recent regional haze rule. The

first section identifies the states and Class I areas subject to federal haze requirements in

the Northeast and Mid-Atlantic regions. The second section summarizes key elements of

the first phase of the federal haze program and, in particular, its application of Best

Available Retrofit Technology (BART) requirements to certain emissions sources. The

third and lengthiest section describes in some detail the provisions of the 1999 rule,

including: regulatory timeline, regional planning options, State Implementation Plan

(SIP) requirements, BART requirements, SIP revisions, progress reporting, adequacy

determinations, and coordination between states and federal land managers.

Figure IV-1: USEPA designated Regional Planning Organizations (RPOs).

CenRAP

WRAP Midwest

SESARM

OTC
IV-3

A. Class I Areas in the Northeast and Mid-Atlantic Regions

Federal haze requirements are intended to restore pristine visibility conditions to

historical “Class I” areas. Historical (or “mandatory”) Class I areas are defined as

national parks over 6,000 acres, wilderness areas and memorial parks over 5,000 acres,

and all international parks established as of August 7, 1977. There are seven Class I

areas in the Northeast and Mid-Atlantic regions. They include:51

• Acadia National Park, ME

• Brigantine Wilderness, Edwin B. Forsythe National Wildlife Refuge, NJ

• Great Gulf Wilderness, White Mountain National Forest, NH

• Lye Brook Wilderness, Green Mountain National Forest, VT

• Moosehorn Wilderness, Moosehorn National Wildlife Refuge, ME

• Presidential Range–Dry River Wilderness, White Mountain National Forest,

NH

• Roosevelt Campobello International Park, New Brunswick

Figure IV-2 shows the location of each of these Class I areas.

 

51 A more complete description of each listed area appears in Chapter IX.
IV-4

B. Requirements Under the First Phase of the Federal Haze Program

(1980-1999)

Following the adoption of national visibility goals in the 1977 Clean Air Act

Amendments, USEPA issued a first set of haze regulations in 1980. These regulations

were largely aimed at addressing visibility impairment that was “reasonably attributable”

to a single source or small group of sources. Visibility planning requirements applied

only to states that had Class I areas; hence, in the Northeast and Mid-Atlantic regions,

only to Maine, New Hampshire, New Jersey, and Vermont. States with Class I areas

were required to submit implementation plans (SIPs) by September 2, 1981 that

contained the following planning elements:

1. Revision of existing SIPs for NAAQS attainment to assure reasonable

progress toward the national visibility goal of preventing any future, and

remedying any existing, impairment of visibility caused by manmade

pollution in mandatory Class I areas;

2. Determinations concerning which existing stationary facilities should be

required to install best available retrofit technology (BART) to reduce their

contribution to visibility impairment in Class I areas;

Figure IV-2: Map of federal Class I areas in the OTC RPO region.

Note: designations are shown with each Class I area. NP = National Park, WA=Wilderness

Area, WR = Wilderness Areas located within a Wildlife Refuge, and IP = International Park.
IV-5

3. Development, adoption, implementation, and evaluation of long-term

strategies (10-15 years) for making reasonable progress toward the national

visibility goal;

4. Adoption of certain measures to assess potential visibility impacts due to new

or modified major stationary sources, including measures to notify Federal

Land Managers (FLMs) of proposed new source permit applications, and

consideration of visibility analyses conducted by FLMs in new source

permitting decisions; and

5. Implementation of visibility monitoring in Class I areas.

In addition, states with Class I areas were required to review and revise their longterm visibility strategies every three years.

C. Requirements Under the New Regional Haze Rule (1999-2064)

In 1999, almost 20 years after its original 1980 haze rule, USEPA issued a new

set of regulations to address regional haze and visibility impairment in the nation’s Class

I areas [64 Fed. Reg. 35714 (July 1, 1999)]. At the time, USEPA stated that it had

deferred release of the new rule in order to integrate further refinements in the scientific

understanding of regional haze and to incorporate the results of several recent studies,

including a 1993 National Research Council report (NRC, 1993) and the 1996 Grand

Canyon Visibility Transport Commission report (GCVTC, 1996).

Unlike the 1980 regulations, the 1999 rule applies to all 50 states and the District

of Columbia and is not limited to states containing mandatory Class I areas. The goal

remains the restoration of pristine visibility conditions in Class I areas, though under the

new rules this goal is given a specific target date of 2064. As has already been noted, the

1999 rule introduces a regional approach that accounts for the contribution of numerous

emissions sources across a broad geographic area to visibility impairment and haze. The

following subsections describe specific elements of the new regional haze rule.

Requirements concerning SIP submittals and objectives are listed in 40 CFR sections

51.308(d) and 51.308(e). Provisions pertaining to the establishment of reasonable

progress goals, baseline and natural visibility conditions; development of long-term

visibility improvement strategies and monitoring strategies; and other SIP requirements

may be found in Section 51.308(d). Section 51.308(e) outlines best available retrofit

technology (BART) requirements.

Note that the synopsis provided in this chapter covers only the main elements of

the new regional haze rule. States52 may need to address other elements or planning

requirements in addition to those mentioned here. This synopsis does not include several

sections of the 1999 rule that specifically pertain to the Grand Canyon Visibility

Transport Commission and do not apply to Northeast and Mid-Atlantic planning efforts.

 

52Here “states” refers to states as well as tribes who successfully petition to be treated as a state for the

purposes of the regional haze rule under 40 CFR 49.
IV-6

States will need to consult the complete text of the regional haze rule (which is reprinted

in Appendix A of this report) for further detail and to ensure that they are complying with

all applicable requirements.

C.1 Timeline for Regional Haze SIP Submittals

USEPA’s 1999 regional haze rule links the timing of visibility SIP submissions to

the designation of fine particulate (PM2.5) nonattainment areas. These designations were

due to be completed by 2004 to 2005 under USEPA’s 1997 rule to establish a new

National Ambient Air Quality Standard (NAAQS) for PM2.5. As is discussed in Chapters

VI and IX, the PM2.5 NAAQS is currently under review by the Supreme Court. The

outcome of this review may or may not affect the timing of eventual PM2.5 attainment

designations.53 In any case, states that are working together in a regional planning effort

to address haze are allowed additional time to develop and submit SIPs. (Note that a

separate timeline option is available to the 16 Grand Canyon Visibility Transport

Commission states in the western U.S; but this option does not apply to states in the

East.)

Table VI-1 describes the SIP requirements and submittal deadlines specified in

the 1999 regional haze rule. Clearly, the timing and outcome of a Supreme Court

decision concerning the PM2.5 NAAQS has the potential to affect these deadlines. Under

the 1999 rule, states with areas that are in attainment or unclassifiable with respect to the

PM2.5 NAAQS will have one year after USEPA publishes their PM2.5 designation to

submit regional haze SIPs unless they commit to a multi-state regional planning process.

States with areas designated non-attainment for PM2.5 will be required to submit their

haze SIPs at the same time as they submit PM2.5 SIPs, generally 3 years after designation.

For states participating in a multi-state regional planning process (which may include

states with and without PM2.5 non-attainment areas), haze SIPs will be due at the same

time as the latest PM2.5 SIP due date applicable to any state in the regional planning

effort. Finally, states must notify USEPA of their commitment to a multi-state regional

haze planning effort within one year after USEPA publishes a PM2.5 designation for any

area of the state (the requirements for such a commitment are outlined in 40 CFR

§51.308(c)).

According to USEPA, the PM2.5 designation process will begin after states collect

three years of PM2.5 monitoring data. This is expected to occur by December 31, 2001

for most areas, and no later than December 31, 2002 for the remaining areas. Allowing

up to six months for quality assurance and certification of the data, USEPA has indicated

that the data needed to make designations should be available between July 2002 and July

2003. The Transportation Equity Act for the 21st Century (TEA-21) statutorily requires

states to submit designations to USEPA within one year of data availability; hence

presumably between July 2003 and July 2004. However, USEPA also expects that some

states may submit designations sooner, perhaps as early as late 2002 or early 2003. Early

 

53 The Supreme Court is reviewing both EPA’s proposed new NAAQS for fine particle matter and a recent

EPA proposal to revise the existing ozone NAAQS. At the same time, EPA is engaged in a re-evaluation

of the health impacts of fine particles, which may result in a new NAAQS proposal for PM2.5.
IV-7

designations would move up the deadlines for regional haze SIP submittals. USEPA is

required to act within one year after receiving state designation submissions; assuming

that most submissions occur between July 2003 and July 2004, USEPA’s designations

should be released between July 2004 and July 2005.

Table IV-1: Options for submitting regional haze SIPs.

For the case... ...states must submit the

first regional haze SIPs no

later than:

... and the SIP must meet:

Areas designated as attainment

or unclassifiable for PM2.5.

One year after USEPA

publishes the designation

(generally 2004-2006).

All requirements of 40 CFR

§51.308(d) and (e) (unless

committing to multi-state

regional planning effort).

Areas designated as

nonattainment for PM2.5.

At the same time as PM2.5

SIPs are due under CAA §172

(3 years after publication of

designation, generally 2006-

2008).

All requirements of 40 CFR

§51.308(d) and (e).

Two phases:

Phase I: Commitment to

regional planning due one year

after USEPA publishes the

first designation for any area

within the state, and...

The regional planning

requirements listed in 40 CFR

§51.308(c).

States participating in multistate regional planning efforts

for combined attainment and

nonattainment areas.

Phase II: Complete

implementation plan due at the

same time as PM2.5 SIPs are

due under CAA §172 (3 years

after designation publication).

The “core requirements” listed

in 40 CFR §51.308(d) and

BART requirements in 40

CFR §51.308(e).

Table adapted from 64 Fed. Reg. 35,714 (July 1, 1999), at 35,725.

Figure IV-3 summarizes the regional haze SIP planning timeline for states

participating in regional planning activities.54 States that opt not to participate in the

regional process may have to submit haze SIPs between July 2005 and July 2006 (if they

do not have PM2.5 non-attainment areas). For most other states (i.e., those with PM2.5

non-attainment areas or states participating in a multi-state regional planning process),

haze SIPs should be submitted in the July 2007 to July 2008 timeframe, but in any case

no later than December 31, 2008.

 

54 This figure also assumes the timeline for monitoring data and PM2.5 designations described above.
IV-8

C.2 Options for Regional Planning

States that opt to participate in a multi-state regional planning effort must submit

a “committal SIP” to USEPA by the earliest date a regional haze SIP would otherwise

have been due for any area in the state. For states with PM2.5 attainment and

unclassifiable areas, this commitment would be due in the 2004-2006 timeframe (one

year after USEPA publishes the PM2.5 designation). The requirements for a committal

SIP are outlined in 40 CFR §51.308(c) and include the following:

1. A demonstration by the state of current participation in a regional planning process,

and an agreement to continue participating with other states in the development and

future revisions of the state’s regional haze SIP.

2. A showing that emissions within the state contribute to visibility impairment in a

Class I area outside the state, or that emissions from outside the state contribute to

visibility impairment in a Class I area within the state. The state may make its

showing using available inventory, monitoring, or modeling information.

Figure IV-3: Regional haze SIP timeline for states participating in regional planning

activities.

2001 2003-5 2008 2013 2018

PM2.5

 monitoring 

network

 in place

EPA designates

areas as being

 in attainment,

nonattainment,

or unclassifiable

with respect to 

PM2.5 NAAQS

2004-6

States committing 

to regional planning

process must submit

committal SIP and

haze plan within 1 yr

of designation

Regional planning states 

must submit complete

haze SIP 3 yrs after last

designation of any state

in the RPO

2011-13

Source specific

BART controls 

go into place

“Reasonable

Progress”

 report

 due 

(and every

5 years

 hereafter)

2016-18

New SIP

(and every

10 years

hereafter)

Emissions trading/

alternative control

measures must be

complete
IV-9

3. A description of the regional planning process, including a description of

participating states, goals, objectives, management, and the decision-making structure

of the planning group, deadlines for completing significant technical analyses and

developing emission management strategies, and a schedule for state review and

adoption of regulations implementing the regional group recommendations.

4. A commitment by the state to submit a regional haze SIP containing the core

requirements of 40 CFR §51.308(d) and §51.308(e) by the latest date an area within

the planning region would be required to submit a regional haze SIP, but no later than

December 31, 2008. The state must also commit to coordinate future plan revisions

with other states in the regional planning effort, and to fully address the

recommendations of the regional planning group.

5. A list of all BART-eligible sources within the state.

C.3 Core Requirements of Regional Haze SIPs

Whether a state develops a regional haze SIP on its own, or participates in a

multi-state regional planning effort, all states must submit a SIP that meets the core

requirements of 40 CFR §51.308(d) and the BART requirements of 40 CFR §51.308(e).

These requirements include:

1. For each Class I area within the state, the state must establish reasonable progress

goals (expressed in deciviews) for improving the most impaired days. The state must

also establish SIP requirements that ensure no degradation on the least impaired days.

As a starting point for determining the reasonable progress goals, USEPA has

established the presumption that such goals should return visibility to natural

conditions by 2064. The goal set for interim periods could be greater or less than this

presumptive rate based on costs of compliance, time necessary for compliance,

energy and non-air quality impacts of compliance, and the remaining useful life of

potentially affected sources. If the reasonable progress goals do not achieve a rate of

improvement consistent with attaining natural visibility conditions by 2064, then the

state must demonstrate its chosen rate of improvement is reasonable to USEPA.

2. In determining reasonable progress goals, the state must calculate baseline and natural

visibility conditions for each Class I area. Baseline conditions are the 20 percent

most impaired and 20 percent least impaired days (expressed in deciviews) in a

calendar year based on available monitoring data collected from 2000 to 2004.

3. Using the above calculations, the state must determine the uniform rate of

improvement (in deciviews) that would need to be maintained during each

implementation period to go from baseline conditions to natural conditions by 2064.

States must consider this rate of progress in setting their reasonable progress goals.

This uniform rate of progress goal may be adjusted downward (allowing for slower

progress), if compliance cost and other aforementioned factors dictate.
IV-10

4. All states must submit a long-term strategy for regional haze for each Class I area

within the state (if any) and for each Class I area outside the state that may be

affected by air pollution sources within the state.

5. The state must submit a monitoring strategy for measuring, characterizing, and

reporting visibility impairment in all Class I areas within the state. States without a

Class I area must submit procedures for using monitoring data and other information

to evaluate their contribution to visibility impairment at Class I areas in other states.

6. Each state must submit a statewide emissions inventory for pollutants reasonably

anticipated to cause or contribute to visibility impairment in any Class I area.

Each of these core requirements contains an additional subset of elements listed in

40 CFR §51.308(d) that states will need to review and address when developing their

regional haze SIPs.

C.4 Best Available Retrofit Technology (BART) Requirements

As part of their regional haze SIP submittals, each state must submit a list of all

BART-eligible sources within its boundaries and an inventory of the haze-related

pollutant emissions from these sources. BART-eligibility is defined under

40 CFR §51.301(hh) and is limited to “existing stationary sources” that went into

operation on or between August 7, 1962 and August 7, 1977 that have the potential to

emit 250 tons or more of any pollutant that may cause visibility impairment in a Class I

area. The 26 specific types of sources to which BART requirements may apply are listed

below:

(1) Fossil-fuel fired steam electric plants of more than 250 million Btu/hour heat input

(2) Coal cleaning plants (thermal dryers)

(3) Kraft pulp mills

(4) Portland cement plants

(5) Primary zinc smelters

(6) Iron and steel mill plants

(7) Primary aluminum ore reduction plants

(8) Primary copper smelters

(9) Municipal incinerators capable of charging more than 250 tons of refuse per day

(10) Hydrofluoric, sulfuric, and nitric acid plants

(11) Petroleum refineries

(12) Lime plants

(13) Phosphate rock processing plants

(14) Coke oven batteries

(15) Sulfur recovery plants

(16) Carbon black plants (furnace process)

(17) Primary lead smelters

(18) Fuel conversion plants

(19) Sintering plants

(20) Secondary metal production facilities
IV-11

(21) Chemical process plants

(22) Fossil-fuel boilers of more than 250 million Btu/hour heat input

(23) Petroleum storage and transfer facilities with a capacity exceeding 300,000

barrels

(24) Taconite ore processing facilities

(25) Glass fiber processing plants

(26) Charcoal production facilities

Each state SIP must include the emissions limits and compliance schedule to be

applied to each BART-eligible source that is found to cause or contribute to visibility

impairment in any Class I area. Detailed BART requirements and an enumeration of the

two supporting analyses that are required as part of the BART determination are provided

under 40 CFR §51.308(e)(1). These additional analyses include: (1) a technical analysis

to determine the best system of continuous emission control technology available and

associated emission reductions achievable for each BART-eligible source and (2) an

impact analysis to assess the degree of visibility improvement at affected Class I areas

expected to result from BART reductions. In the technology analysis, the state must

consider available control options, the costs of compliance, the energy and non-air quality

environmental impacts of compliance, any pollution control equipment in use at the

source, and the remaining useful life of the source. Reductions from BART measures

must be installed and operated as expeditiously as practicable but in no event later than

five years after approval of the SIP.

In addition, states have the option of pursuing an emissions trading program or

alternative measure if it can be demonstrated that this will result in greater reasonable

progress than a source-by-source application of BART requirements. Section

51.308(e)(2) outlines the elements of such a demonstration. Finally, any BART-eligible

source has the option of applying to USEPA for an exemption from BART requirements

subject to the provisions of 40 CFR §51.303(a)(2)-(h).

USEPA is currently preparing additional BART guidance to be added to

40CFR§51 as Appendix Y. The guidance should be available early in 200155 and is

intended to clarify BART requirements. It will cover applicability, engineering analysis,

cumulative air quality analysis and trading alternatives; in addition it will update the

“reasonably attributable” BART guidance issued in 1980. More specifically, the

guidance is expected to outline a potential trading program with emphasis on timelines

and budgets; but is not expected to address allocation, allowance tracking, or details of

program structure. At this point it is anticipated that USEPA will allow trading of haze

related emissions reductions across source sectors but not across pollutant species.

 

55 On September 22, 2000 the guidance report arrived at the White House Office of Management and

Budget for evaluation of the economic impact BART regulations will have on industry. After OMB

approval, the BART guidance will be published in the Federal Register. This will coincide with the public

comment period (Air Daily, volume 7, no. 185, 9/27/00).
IV-12

C.5 Requirements for Comprehensive Periodic SIP Revisions

Each state must revise and submit an updated regional haze SIP to USEPA by

July 31, 2018 and every ten years thereafter. These periodic SIP revisions must reassess

each of the core requirements described above in light of new monitoring data, haze

analyses, and any other relevant information. They must also provide updated

information on visibility conditions for the most impaired and least impaired days and

report on progress toward achieving natural background conditions. This update must be

based on the most recent five-year period for which data are available prior to the

revision submittal date. Finally, SIP revisions must evaluate the effectiveness of the

state’s long-term strategy for achieving reasonable progress goals and affirm or revise

these goals in light of available information from the prior implementation period(s).

C.6 Periodic Reporting on Achievement of Reasonable Progress Goals

The 1999 rule requires states to submit periodic reports every five years after

submitting an initial regional haze SIP. The periodic reports are intended to evaluate

progress towards meeting reasonable progress goals for any Class I areas affected by air

pollution sources within the state. Progress reports must be in the form of

implementation plan revisions and must comply with procedural requirements set forth in

sections 51.102 and 51.103. The regional haze rule lists a minimum set of elements in 40

CFR §51.308(g) that must be addressed in the periodic reports.

C.7 Adequacy Determination for Existing Implementation Plans

When states submit periodic reports under 40 CFR §51.308(g), they must also

take one of several actions listed in 40 CFR §51.308(h) based on the information

contained in these reports. The action options are:

1. A negative declaration that the state’s regional haze plan needs no further substantive

revision.

2. Notice to USEPA that the state’s regional haze plan is or may be inadequate due to

emissions from sources in another state(s). This action will re-initiate regional

planning efforts. The notifying state must then work with the other state(s) to

develop additional strategies.

3. Notice to USEPA that the state’s regional haze plan is or may be inadequate due to

emissions from sources in another country.

4. A determination by the state that its SIP is or may be inadequate due to emissions

from sources within the state. The state would then be required to revise its SIP to

address these deficiencies within one year.

C.8 Coordination Between States and Federal Land Managers

There are four requirements in the regional haze rule pertaining to coordination

between states and Federal Land Managers (FLMs) on regional haze planning.
IV-13

1. By November 29, 1999, states must notify FLMs in writing of the name of the state

official to whom FLMs may submit any recommendations concerning visibility

impairment, related monitoring strategy, and other implementation issues for Class I

areas.

2. States must give FLMs the opportunity to consult with state authorities in person at

least 60 days prior to any public hearing on regional haze SIPs or revisions thereto.

This consultation must include an opportunity for FLMs to discuss assessments of

visibility impairment in Class I areas and to make recommendations on reasonable

progress goals as well as on strategy implementation.

3. In developing or revising implementation plans, states must describe how they have

addressed any comments or recommendations from FLMs.

4. State SIPs and SIP revisions must provide for ongoing consultation with FLMs,

including consultation on the development and review of plan revisions, 5-year

progress reports, and any other programs with the potential to affect visibility

conditions in Class I areas.
IV-14

References

GCVTC, Recommendations for Improving Western Vistas, Report to the U.S. EPA,

Grand Canyon Visibility Transport Commission, 10 June 1996.

NRC, Protecting Visibility in National Parks and Wilderness Areas, National Research

Council Committee on Haze in National Parks and Wilderness Areas. National Academy

Press, Washington, DC: 1993.
V-1

V. Building a Regional Haze Plan

As discussed in the previous chapter, USEPA’s 1999 regional haze rule will

require states and interested tribes to develop implementation plans for reducing haze and

improving visibility at Class I sites. In response to these requirements, Northeast and

Mid-Atlantic states and tribes will need to define visibility goals, establish measures of

reasonable progress, and identify the relative contribution of different pollutant sources.

This chapter covers a number of analytical elements and technical considerations that will

be important in this effort. The first section begins by providing more detail on the

calculation of light extinction generally (a topic that was introduced in Chapter II). It

then discusses the estimation of “natural, background” visibility conditions and the

methodology used to quantify existing visibility impairment from available monitoring

data. The next section summarizes recent visibility trends at Class I sites in the Northeast

and Mid-Atlantic regions. A discussion of the atmospheric chemistry involved in particle

formation is deferred until the end of the chapter. Here we present basic information

regarding the chemical mechanisms involved with the formation of atmospheric aerosols

and additional considerations which may affect how control strategies are devised. These

include: (1) the hygroscopic nature of sulfates and nitrates, (2) the interaction of

ammonium with sulfates and nitrates and (3) the influence of biogenic hydrocarbons.

A. Characterizing “Natural Background” and Current Visibility

Conditions

A.1 Calculating Light Extinction

As noted in Chapter II, total light extinction is a function of the individual light

absorption and light scattering properties of particles present in the atmosphere. This total

is frequently expressed as a light extinction coefficient (bext) in units of inverse length

(such as Mm-1). In simple terms, the light extinction coefficient is a measure of the

proportion of light extinguished per unit of distance traveled through the atmosphere.

Bext can be empirically determined or “reconstructed” simply by summing the scattering

and absorption coefficients of the relevant particle constituents, as indicated by the

following equation (note that the equation includes Rayleigh scattering, bRay):56,57

bext = bSO4 + bNO3 + bOrgC + bSoil + bCoarse + bElemC + bRay

The calculation of extinction coefficients for each individual chemical species is

described by the following equations (FLAG, 1999):

 

56 As noted in Chapter II, absorption by nitrogen dioxide gas is not generally significant on a regional scale,

though it can play a role in coherent pollution plumes (FLAG, 1999). Hence the discussion in this chapter

considers elemental carbon as the only contributor to atmospheric light absorption.

57 Particles in the atmosphere may exist as an internal mixture of several chemical species. IMPROVE

assumes that the contribution of each particle constituent can be determined separately and summed to

determine total light extinction.
V-2

bSO4 = 3[(NH4)2SO4]f(RH)58

bNO3 = 3[NH4NO3]f(RH)

bOrgC = 4[OrgC]

bSoil = 1[Soil]

bCoarse = 0.6[Coarse]

bElemC = 10[ElemC].

The bracketed quantities represent ambient air concentrations expressed in micrograms

per cubic meter (μg/m3). The numeric coefficients represent “dry” scattering

efficiencies59 (m2/g), while the relative humidity adjustment factor f(RH) accounts for the

hygroscopic properties of sulfate and nitrate (i.e. their tendency to absorb water in the

atmosphere). As relative humidity increases this factor becomes larger, which in turn

produces a higher coefficient of light extinction for the hygroscopic particles. Provided

concentrations and humidity levels are known, the light extinction coefficients for

individual particle constituents can be straightforwardly calculated and summed to

estimate the overall light extinction coefficient, bext.

It should be noted that a number of uncertainties are embedded in these

calculations; hence reconstructions of light extinction may not be precise. For example,

the equations reflect simplified assumptions about the role of relative humidity and may

not adequately account for the non-linear relationship between humidity and particle

growth rate. Moreover, the values used for relative humidity generally represent an

average over a large geographic range and long periods of time. Ideally, relative

humidity should be recorded and stored with each concentration measurement so that an

appropriate factor can be calculated for each observation. Second, different humidity

adjustment factors should be used for the sulfate and nitrate fraction of aerosol particles

given differences in the rate at which particle size grows for these two constituents with

increasing relative humidity. Third, the above equations assume that organic carbons are

non-hygroscopic and do not require a relative humidity adjustment. In many instances

little information is available about the specific constituents of secondary organic aerosol

particles and of their potential affinity for water. Whether or not a relative humidity

adjustment factor should be applied to the organic fraction is therefore an issue of current

debate (Saxena et al., 1995). The sensitivity of reconstructed light extinction to each of

these assumptions is an area that warrants further investigation.

Reconstructed light extinction compares fairly well with light scattering as

measured by transmissometers and nephelometers; however, the level of agreement is

dependant on how relative humidity is treated in the calculation (Malm, 2000b). Choice

of humidity adjustment factors and decisions about how to average relative humidity,

both spatially and temporally, will therefore have a significant impact on the accuracy of

 

58 IMPROVE assumes that all sulfate is in the form ammonium sulfate ((NH4)2SO4) and that all nitrate is in

the form ammonium nitrate (NH4NO3). Other forms of these species exist in nature as detailed in Section

D of this chapter. These differing forms may have different scattering efficiencies and relative humidity

adjustment factors.

59 Dry scattering efficiencies were determined for 550 nm (0.55 μm) light (green light). There may be

discrepancies between this value and those determined by integrating over the entire visible spectrum (400-

700 nm).
V-3

reconstructed light extinction and on the relative contribution assigned to different

particle constituents. USEPA is currently planning to develop guidance on these issues by

2001.

Applying current methods to the pollutant concentrations measured by the

IMPROVE monitoring program over the last ten years yields average reconstructed light

extinction ranging from very low levels (i.e., near natural conditions) to greater than 150

Mm-1. Reconstructed values in the Northeast and Mid-Atlantic range from 70 Mm-1 to

over 90 Mm-1 (Fox et al., 1999).

As noted in Chapter II, light extinction is often expressed in terms of visual range,

a unit of measurement that is generally more accessible to the general public and to

policymakers. Visual range is inversely proportional to light extinction and can be readily

derived from total light extinction using the Koschmeider equation:

Visual Range (km) = 3.912/bext(km-1) = 3912/bext(Mm-1)

The deciview (dv) measure that is frequently used to measure perceptible changes

in visibility has a similarly direct, mathematical relationship to light extinction.

Specifically, it is proportional to the natural log (ln) of light extinction (in Mm-1) divided

by 10 Mm-1:

dv = 10·ln(bext/10 Mm-1)

The form of the deciview equation essentially sets dv = 0 for Rayleigh conditions

(no particles) at an altitude of about 1800 meters (bRay = 10 Mm-1). Increases in

deciviews above this zero threshold thus provide a measure of perceived haziness relative

to a particle-free atmosphere at 1800 meters of altitude (Pitchford and Malm, 1994).

Federal haze regulations require states to express baseline conditions and

reasonable progress goals in terms of deciviews (40 CFR §51.308). To derive these

values, states must use atmospheric light extinction coefficients calculated from aerosol

measurements (40 CFR §51.301(bb)). Therefore, states will need to calculate

reconstructed particle extinction coefficients and total light extinction using available

particle monitoring data and appropriate relative humidity factors. Current regulations do

not allow states to use visual range records from airports or other sources to derive light

extinction coefficients for purposes of developing regional haze implementation plans.

However, these sources may be useful in corroborating visibility trends analyses.

A.2 Estimating “Natural Background” Reference Conditions

Estimating “natural background” reference conditions is an important aspect of

compliance with the new regional haze rule since a return to these conditions is the

ultimate aim of the rule.

There are only two significant components to light extinction under natural

conditions: Rayleigh scattering and scattering by naturally present aerosols. The Federal

Land Managers’ Air Quality Related Values Workgroup (FLAG) uses a Rayleigh
V-4

scattering value of 10 Mm-1 for the entire U.S. (FLAG, 1999). This value corresponds to

Rayleigh conditions at about 1800 m in altitude (Sisler and Malm, 2000). However,

Rayleigh scattering varies with altitude and at sea level is estimated to be about 12 Mm-1

(Trijonis et al., 1990). To avoid understating “natural” background visibility impairment

at coastal sites (which could result in setting unrealistic goals for haze reduction efforts),

the analysis conducted for this report assumes a Rayleigh coefficient of 12 Mm-1 for the

Acadia, Brigantine, Moosehorn, and Roosevelt Campobello sites. This assumption

reduces calculated background extinction levels by 2 Mm-1 but leads to a change of only

0.3 dv in estimated natural background conditions on the deciview scale.60

For natural aerosol particle concentrations, this report utilizes annual average

values from the 1990 NAPAP visibility report, which FLAG also uses. These values

come from three information sources (Trijonis et al., 1990):

1. compilations of natural versus anthropogenic emissions,

2. ambient measurements in remote areas (especially in the southern

hemisphere), and

3. regression analyses using anthropogenic and/or natural tracers

Table V-1 lists the assumed “natural” concentrations of six major types of light

attenuating particles in the eastern United States.

Table V-1: Assumed natural aerosol particle concentrations in the eastern U.S. 

(Trijonis et al., 1990).

Particulate Aerosol Component Annual average concentration, Eastern U.S.

(μg/m3

)

Sulfates (as ammonium sulfate) 0.2

Ammonium nitrate 0.1

Organic Carbon 1.5

Elemental Carbon 0.02

Soil Dust 0.5

Coarse 3.0

A caveat applies to the natural ambient aerosol particle concentrations assumed

for some Class I areas in the Northeast and Mid-Atlantic. Because these values do not

include marine aerosols they may understate natural aerosol particle levels at coastal sites

(i.e., at Acadia, Brigantine, Moosehorn, and Roosevelt Campobello). Further

investigation of this issue is needed. However, it should also be noted that because

marine aerosol particles tend to be larger in size, they are less efficient than other

 

60 Due to the logarithmic relationship between deciviews and light extinction.
V-5

particles at scattering visible light.61 Hence, a substantially larger concentration of

marine aerosol particles would be necessary to achieve the same level of visibility

impairment as secondary fine particles. In the absence of site-specific information, this

report uses the values in Table V-1 as surrogates until better estimates for the marine

aerosol contribution become available.

Most areas experience significant variability in natural ambient aerosol particle

concentrations. This is due to variation in natural emissions of particulate forming

species as well as to variations in meteorology and relative humidity. Comparing

observed 20 percent best and worst days under current, actual conditions to a single

estimate of “natural” conditions based on annual average concentrations and humidity

values may result in inaccurate estimates of needed reductions. In some areas, it may be

necessary to develop estimates of both 20 percent best and 20 percent worst natural

background conditions for comparison with baseline conditions. USEPA is currently

working to develop guidance on estimating natural background haze conditions and is

expected to release its recommendations in 2001.

To calculate coefficients of natural background light extinction in the Northeast

and Mid-Atlantic, the concentrations shown in Table V-1 were combined with average

annual relative humidity factors from the 1999 FLAG draft report and subjected to the

calculations described in Section A.1 above. Table V-2 gives the resulting Rayleigh

coefficients, relative humidity factors, and calculated natural background visibility levels

for each Northeast and Mid-Atlantic Class I area.

Table V-2: Estimated natural background visibility conditions at Northeast and

Mid-Atlantic Class I areas.

Site bRay

(Mm-1)

F(RH) Particle

extinction

(Mm-1)

Total

extinction

(Mm-1)

Deciviews

Acadia 12 3.8 11.92 23.92 8.7

Brigantine 12 3.9 12.01 24.01 8.8

Great Gulf 10 3.9 12.01 22.01 7.9

Lye Brook 10 3.8 11.92 21.92 7.8

Moosehorn 12 3.9 12.01 24.01 8.8

Presidential

Range-Dry River 10 3.9 12.01 22.01 7.9

Roosevelt

Campobello 12 3.9 12.01 24.01 8.8

 

61 Specifically, marine aerosol dry scattering efficiencies are 0.4 m2

/g versus 3-5 m2/g for sulfate (Seinfeld

and Pandis, 1998).
V-6

A.3 Estimating Visibility Impairment from Available Fine Particle Monitoring

Data

USEPA’s 1999 regional haze rule requires states to establish baseline conditions

for Class I areas as part of the visibility planning process. These baseline conditions are

defined as the average of visibility impairment on the 20 percent most impaired and 20

percent least impaired days (expressed in deciviews) in a calendar year

(40 CFR §§51.301(dd), 51.301(ee)). The rule further requires that states determine

baseline conditions using five years of monitoring data collected from 2000 to 2004

(40 CFR §51.308).

As indicated in Chapter III,62 IMPROVE monitoring data are available for several

northeastern and mid-Atlantic Class I sites, including Acadia National Park and the

Moosehorn Wilderness Area in Maine; the Brigantine Wilderness Area in New Jersey;

the Great Gulf Wilderness Area in New Hampshire; and the Lye Brook Wilderness Area

in Vermont. There are no historical IMPROVE data for the Presidential Range – Dry

River Wilderness Area in New Hampshire and the Roosevelt Campobello International

Park in Maine, but the Great Gulf and Moosehorn sites, respectively, provide

representative conditions for these Class I areas due to their close proximity.

The IMPROVE web site provides speciated data for all sampling days at

IMPROVE monitors.63 Total particle light extinction can be calculated using this

information and the methodology discussed in previous sections of this chapter. Table V3 lists the particle species for which IMPROVE provides data and the formulae and

assumptions used to calculate their atmospheric concentrations. Ambient concentrations

are in turn used to calculate reconstructed particle light extinction coefficients.

 

62 A more detailed discussion of visibility and particle monitoring programs may be found in Chapter VIII.

63 Archival IMPROVE data are available via an ftp link located at the web address

http://alta_vista.cira.colostate.edu/. The website is part of a cooperative program on visibility in Class I

areas between the National Park Service Air Resources Division and the Cooperative Institute for Research

in the Atmosphere (CIRA) at Colorado State University in Ft. Collins.
V-7

The bracketed symbols in the second column of Table V-3 correspond to species

concentrations and to the labeling conventions used in the IMPROVE database. The

labeling convention is:

[S] = Elemental sulfur

[NO3] = Nitrate

[EC#] = Detailed elemental carbon species measured by

thermal optical reflectance (TOR) with three bins

(# = 1,2,3)

[OC#] & [OP] = Detailed TOR organic species with bins (# = 1,2,3,4)

[AL] = Aluminum

[SI] = Silicon

[CA] = Calcium

[FE] = Iron

[TI] = Titanium

[MT] = Total mass (PM10)

[MF] = Fine mass (PM2.5)

Table V-3: Formulae and assumptions used with IMPROVE sampling

measurements to derive reconstructed particle light extinction

(adapted from Sisler and Malm, 2000).

Species Formula Assumptions

SULFATE 4.125[S] All elemental S is from

sulfate. All sulfate is from

ammonium sulfate.

NITRATE 1.29[NO3]

Denuder efficiency is

close to 100%. All nitrate

is from ammonium nitrate.

LAC (Light absorbing

carbon)

[EC1] + [EC2] + [EC3] – [OP] All high temperature

carbon is elemental.

OMC (Organic mass

from carbon)

1.4{[OC1] + [OC2] + [OC3] +

[OC4] + [OP]}

Average organic molecule

is 71% carbon.

SOIL (Fine Soil) 2.2[AL] + 2.49[SI] + 1.63[CA] +

2.42[FE] + 1.94[TI]

[Soil K] = 0.6[Fe]. FeO

and Fe2O are equally

abundant. A factor of

1.16 is used for MgO,

Na2O, H2O, CO2.

RCFM (Reconstructed

fine mass)

[SULFATE] + [NITRATE] +

[LAC] + [OMC] + [SOIL]

Represents dry ambient

fine aerosol mass for

continental sites.

CM (Coarse Mass) [MT] – [MF] Consists only of insoluble

soil particles.
V-8

Because the IMPROVE database reports concentrations in units of nanograms per

cubic meter, the data must be divided by 1000 to convert to units of micrograms per

cubic meter (μg/m3

). The IMPROVE guide to interpreting data, which details

IMPROVE sampling techniques and data analysis, is included with this report as

Appendix B.

Summaries of the sampling data for each IMPROVE site are tabulated in

Appendix C of this report. The data are grouped into the 20 percent least impaired

(Group 10), the 40-60 percent mid-range (Group 50), and the 20 percent most impaired

(Group 90) visibility days aggregated by particle mass and light extinction for each

IMPROVE monitor.64 A minor discrepancy between the IMPROVE monitoring program

and new regional haze rules is that the former sorts data according to a “sample year”

which runs from March to February, whereas the federal rule specifies the use of data

from a calendar year (January – December) to determine baseline conditions.

The methodologies used to sort and average IMPROVE data also deserve some

mention. For example, the data can be sorted by total measured (gravimetric) fine

particle mass or by reconstructed fine particle mass, the latter being simply the sum of

measured mass for individual particle species (ammonium sulfate, ammonium nitrate,

organic carbon, elemental carbon, and fine soil). The two methods can yield different

results because mass measurements for certain species are occasionally missing. Hence,

sorting by reconstructed fine mass excludes sample days when speciated values are

missing, whereas sorting by gravimetric mass includes all sample days. Malm has noted

that this can lead to significantly different results, particularly for small data sets (Malm,

2000b).

Table V-4 provides an example, taken from Malm (2000b), of how this can

happen. The table presents five entries corresponding to the five highest gravimetric fine

mass (FM) samples in a hypothetical data set. Three of the entries have missing values

for some of the speciated components, so the reconstructed fine mass cannot be

calculated for these observations. Summing the average mass of each species and

including all samples yields a reconstructed fine mass average of 11.61 μg/m3

. Relative

to this total, the average organic carbon fraction is 22 percent (2.5 /11.61). If, however,

samples 2,3, and 5 are excluded because of missing data for certain constituent species,

the average reconstructed fine mass totals 10.75 μg/m3

. Based on samples 1 and 4 only,

the average organic carbon fraction would appear to be just 14 percent (1.5/10.75).

Currently, there is no preferred or standard approach to dealing with missing data

components and researchers continue to investigate the implications of different

approaches. The guidance currently being prepared by USEPA on how to track

“reasonable progress” is expected to address this issue (as noted previously, this guidance

is expected to be released in 2001).

 

64 It should be noted that the appendix lists the 10th and 90th percentile values as a surrogate for the average

of the upper and lower 20 percentiles of the complete distribution of data. These will not necessarily be

equal.
V-9

Table V-4: Hypothetical example of 20 percent highest fine particle observations

with missing speciated values.

Observations FM Sulfate Nitrate Organics

LightAbsorbing

Carbon

Soil RCFM

1 10 6 1 1 1 2 11

2 13 4 --- 6 0.8 1 ---

3 10 7 1.1 --- --- 1 ---

4 10 5 0.8 2 0.7 2 10.5

5 12 8 --- 1 0.5 1 ---

AVERAGE 11 6 0.96 2.5 0.75 1.4 10.75

(11.61)

This example is taken from Malm, 2000b. FM = gravimetric fine particle mass. RCFM = reconstructed

particle fine mass. As shown in the table, excluding observations with missing values leads to an average

RCFM of 10.75. Using the ensemble average of each species, and keeping observations with missing

values, sums to an ensemble average RCFM of 11.61.

The tables presented in Appendix C sort IMPROVE data according to gravimetric

fine particle mass, thus they do not exclude days with missing data for specific particle

species. For purposes of this report, however, the IMPROVE data were regrouped by

calendar year (January – December) and sorted on the basis of reconstructed light

extinction. Because light extinction could not be reconstructed for days with missing

speciated values, this approach excluded some samples. A further difference results from

the fact that, as noted in Chapter III, different particle species are more or less efficient at

scattering light. Thus visibility may be less impaired on a day when fine particle mass

concentrations are high due to an atypically large soil component than on a day when the

particle mass is made up of a higher proportion of sulfates and nitrates. In short, a

grouping of the 20 percent days with highest or lowest light extinction values may not

correspond exactly to a grouping of days according to undifferentiated particle mass

concentrations.

The results obtained by re-sorting the IMPROVE data, in terms of the relative

contribution by different particle species to total fine particle mass concentration and total

light extinction, are presented in Chapter III (see Figures III-3a/b and III-4a/b). A

comparison of these results to those tabulated in Appendix C suggests that either

methodology produces broadly consistent findings. Nor does the exclusion of some

sampling days appear to significantly alter the relative contributions attributed to

different particle species. This result is perhaps not surprising given the relatively large

sample size involved. About 100 samples per year are collected at the IMPROVE sites

of which generally a dozen or fewer are excluded because of missing values for particular

particle constituents.

Though it may not matter greatly which methodology is chosen to sort and

analyze fine particle monitoring data, it probably will be important to apply that

methodology consistently over time, especially since changes in visibility are likely to

occur in relatively small increments over the near term. Measures of progress, in other

words, may be considerably more sensitive to confounding by methodological
V-10

inconsistencies than measures of absolute particle concentration or visibility impairment

at any given point in time.

B. Recent Visibility Trends in the Northeast and Mid-Atlantic

Figure V-1 presents recent visibility trends (in annual average deciviews) at

northeastern and mid-Atlantic IMPROVE sites for the 20 percent most and least visibility

impaired days. The graphs also show reconstructed “natural background” levels at each

site, as estimated in Table V-2, to indicate the magnitude of the gap that will need to be

closed, especially in terms of the 20 percent haziest days, to attain national visibility

goals. These trends are presented only as qualitative indicators of baseline conditions.

Under the new regional haze rule, states will need to determine baseline conditions based

on monitoring data from 2000 to 2004 and choose their preferred method for sorting and

analyzing the 20 percent most and least impaired days.

The trend plots suggest that the 20 percent least impaired days at Class I areas in

the upper Northeast are near natural background levels. As was previously noted in

Chapter III, this is not the case for the more southern Brigantine site, perhaps due to the

closer proximity of this site to urban and industrial areas. In addition, it is possible that

marine aerosols play a greater role than assumed in these estimates, in which case natural

background visibility impairment could be slightly understated at Brigantine (this bias

could also affect natural background conditions at other northeastern sites, such as

Acadia and Moosehorn). If so, the actual gap between current visibility impairment and

natural background conditions would be somewhat narrower (though probably not

substantially so) than it appears in these plots.

As of 1999, there were no complete years of sampling data for the Great Gulf site,

so the trends at this site pertain only to the subset of summer months from May or June

through September. Since the haziest days typically occur in the warm months, average

deciview values for the 20 percent most impaired summertime days may be higher than

for the year as a whole. A comparison of the Great Gulf values to those found at the

nearby Lye Brook site (for which complete data are available) suggests that the

difference, if any, is not large.

Due to the short time length for most of the trend plots, it is difficult to draw

definitive conclusions about recent visibility trends in the Northeast and Mid-Atlantic.

The Acadia and Washington, DC sites have the longest data records and both seem to

show some level of visibility improvement in the 20 percent most impaired and least

impaired days. The apparent improvement at Acadia, however, is very modest. Sisler

and Malm have indeed found a negative slope in deciview values (indicating improved

visibility) at these sites through 1996, but the decline was statistically significant only for

the 20 percent least impaired days at Acadia (Sisler and Malm, 2000). More recently

Malm found a statistically significant visibility improvement trend at Acadia for the 20

percent most impaired days using IMPROVE data through 1998 (Malm, 2000b).
V-11

0.0

5.0

10.0

15.0

20.0

25.0

30.0

1990 1991 1992 1993 1994 1995 1996 1997 1998

Year

Deciviews (DV)

20% worst DV

20% best DV

"Natural background"

Lye Brook, VT

0.0

5.0

10.0

15.0

20.0

25.0

30.0

35.0

1990 1991 1992 1993 1994 1995 1996 1997 1998 1999

Year

Deciviews (DV)

20% worst DV

20% best DV

"Natural background"

Great Gulf, NH1

0.0

5.0

10.0

15.0

20.0

25.0

30.0

1990 1991 1992 1993 1994 1995 1996 1997 1998

Year

Deciviews (DV)

20% worst DV

20% best DV

"Natural background"

Moosehorn, ME

1

IMPROVE data are only available from May or June through

September during the 1995 to 1999 sampling period.

Therefore, the 20% trends reflect the influence of warmer

weather months, and may differ with the inclusion of colder

weather months.

Figure V-1: Visibility Trends in the Northeast and Mid-Atlantic
V-12

Figure V-1: Visibility Trends in the Northeast and Mid-Atlantic, continued.

2

Monitoring in 1988 began in March. To estimate a full calendar year for 1988,

data from January and February 1989 were used, which double counts the

contribution of these months because they are part of the 1989 calendar year

also. For purposes of the trendlines, the double counting has little effect.

3

A large number of speciated nitrate data were missing during the 1998 calendar

year from the IMPROVE data set. In general, sample days with missing

speciated values were excluded, but to do so in this situation would result in

omitting a disproportionately large number of sample days. Rather than

discarding all these sample days, the missing nitrate values were estimated as

10% of the gravimetric fine mass, which is significantly higher than the 1997

annual average contribution, but consistent with other previous years. Because

of the missing data, the estimated 1998 visibility values may not reflect actual

values.

0.0

5.0

10.0

15.0

20.0

25.0

30.0

35.0

40.0

1989 1990 1991 1992 1993 1994 1995 1996 1997 1998

Year

Deciviews (DV)

20% worst DV

20% best DV

"Natural background"

Washington, DC

Acadia, ME2

0.0

5.0

10.0

15.0

20.0

25.0

30.0

35.0

1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998

Year

Deciviews (DV)

20% worst DV

20% best DV

"Natural background"

0.0

5.0

10.0

15.0

20.0

25.0

30.0

35.0

1990 1991 1992 1993 1994 1995 1996 1997 1998

Year

Deciviews (DV)

20% worst DV

20% best DV

"Natural background"

Brigantine, NJ3
V-13

In fact, a closer examination of daily versus annual average ammonium sulfate

concentrations at Acadia suggests that while average concentrations have perhaps shown

some underlying decline, the highest concentrations experienced on peak days have

remained largely unchanged (Poirot, 2000). Figure V-2 superimposes a trend line

representing a rolling average of concentrations from the previous 100 sampling days

(representing about one year of monitoring data) on a graph of daily average ammonium

sulfate concentrations. Though there is some evidence for a downward trend in the

rolling 100-sample average, the highest 24-hour values actually occur after 1995.

Particularly striking is the 24-hour value recorded on July 17, 1999 – a day when much of

the Northeast and Mid-Atlantic experienced exceptionally poor visibility conditions (the

July 1999 haze episode is described in detail in Chapter III). In fact, the ammonium

sulfate levels recorded on that day were about 40 percent higher than any previous 24-

hour measurement at the Acadia site.

Figure V-2: Trends in 24-hour average ammonium sulfate concentrations and a

rolling average of 100 samples from 1988 to 1999 at Acadia National Park in Maine.

Interestingly, Malm’s most recent analysis of visibility trends on the 20 percent

most impaired days at Acadia from 1988 through 1998 finds statistically significant

decreasing slopes in organic carbon and nitrate mass concentrations but does not find a

statistically significant decline for sulfate mass concentration (Malm, 2000b). Like

sulfate, organic carbon and nitrate precursors might have been affected by pollution

control programs introduced in the 1990s. In particular, efforts to reduce summertime

ground-level ozone concentrations have led to a variety of initiatives to reduce

hydrocarbon and NOX emissions in the Ozone Transport Region. Reductions in these

pollutants could directly reduce organic carbon and nitrate concentrations at some Class I
V-14

sites. To the extent these control programs have succeeded in reducing regional ozone

levels, they could indirectly affect the formation of organic aerosols with a biogenic

component (e.g., terpenes emitted by vegetation), which may play an important role

especially at the more remote rural sites. Both ozone and nitrate serve to oxidize terpenes

(Finlayson-Pitts and Pitts, 2000) and thereby promote the formation of biogenically

derived organic particulate.

In general, however, the trend plots in Figure V-1 present a mixed picture and do

not suggest much discernible improvement in visibility at northeastern and mid-Atlantic

Class I sites over the second half of the 1990s. A clearer indication of current visibility

trends may emerge with additional years of monitoring data; meanwhile, the

implementation of planned additional NOX and SO2 emissions reductions starting in 2000

may begin to produce more pronounced visibility benefits.

C. Atmospheric Chemistry

The processes by which primary pollutants, such as sulfur dioxide (SO2), nitrogen

oxides (NOX) and volatile organic compounds (VOCs), are transformed into the visibility

impairing species which are observed at visibility monitoring sites (i.e. sulfates, nitrates,

and secondary organic aerosol) are complex. While a full description is not included in

this report, a general presentation of some basic information regarding these processes is

given here with appropriate references to other sources of information containing greater

detail.

The atmospheric residence time of emitted SO2 can range from as short as a few

minutes (e.g. in the presence of clouds and high relative humidity) to as long as 13 days

or more65 before it is chemically transformed into another form. SO2 is principally

removed by two chemical processes (gas phase reaction with the hydroxyl radical (OH)

and aqueous (or liquid) phase processes inside a droplet) as well as by dry deposition in

the gas phase (see Figure V-3).

Gas phase chemical reactions result when two or more molecules in the

atmosphere come into contact and chemically react to form different molecules. In this

case, SO2 can be transformed into sulfuric acid (H2SO4), which can further react to form

solids in the presence of ammonium ion. These solids include letovicite ((NH4)3H(SO4)2,)

ammonium bisulfate (NH4HSO4) and ammonium sulfate ((NH4)2SO4) (Seinfeld and

Pandis, 1998). All of these forms of sulfate have a high affinity for water. Sulfuric acid

will condense directly onto existing liquid droplets in the atmosphere. In the case of the

solid forms of sulfate, water will condense onto their surface up to the point of

deliquescence, defined by a phase change that results in a liquid particle. In the liquid

phase, letovicite, ammonium bisulfate and ammonium sulfate will dissociate to form the

 

65 The atmospheric lifetime (or residence time) of sulfur dioxide is defined as the length of time from

release until 36% (or 1/e) of released sulfur dioxide molecules remain. Thirteen days represents the

atmospheric lifetime of SO2 with respect to oxidation by OH and assumes no other loss processes

(Finlayson-Pitts and Pitts, 2000).
V-15

bisulfate ion (HSO4

-

) and sulfate ion (SO4

=

). Sulfuric acid in the liquid phase (H2SO4(aq))

along with these other ionic forms of sulfate are collectively termed “sulfate.”

SO2 is also a highly soluble gas (has a high affinity for water) and, in the presence

of liquid droplets, will readily condense onto their surface. In the aqueous phase, SO2 is

oxidized within the liquid to form sulfuric acid, the bisulfate ion or the sulfate ion. The

aqueous phase processes that lead to the transformation from SO2 to sulfate are highly

complex and remain a subject of current research (Seinfeld and Pandis, 1998; FinlaysonPitts and Pitts, 2000).

NOX emitted to the atmosphere follow much the same processes with even more

rapid gas phase oxidation of NO2 by the hydroxyl radical to form nitric acid (HNO3).

Nighttime oxidation of NO2 by O3 can also lead to HNO3 formation, and this path may be

important during winter when hydroxyl levels are lower and nights are longer. Nitric

acid can then further react with ammonium to form the solid ammonium nitrate, which

also has a high affinity for water and can attract enough water to deliquesce into a liquid

droplet. Nitric acid will also condense directly onto existing droplets (it too is highly

soluble) where it will dissociate to form aqueous phase nitrate ion (NO3

-

). The term

Figure V-3: Schematic representation of sulfate formation mechanisms

(adapted from Malm, 2000a).
V-16

“nitrate” is used to refer to aqueous phase nitrate ion as well as to dry deposited nitric

acid.66

The formation of secondary organic aerosols (SOA) from precursor emissions of

volatile organic species is similarly complex. As noted in Chapter II, organics consist of

literally thousands of different molecules (all containing carbon within their molecular

formula) with widely varying reactivities and lifetimes. These chemicals react with the

hydroxyl radical or other oxidants in the atmosphere to form new species which again

may have a wide range of physical properties. As these chemicals travel and

meteorological conditions (i.e. temperature and relative humidity) change, their tendency

to condense onto existing particles may be altered. The exact composition of the organic

fraction of SOA is not well understood and remains an area of active research (FinlaysonPitts and Pitts, 2000). It should be noted that there are many primary sources of organic

carbon fine particles, including automobile exhaust, meat cooking, wood smoke and

paved road dust. These sources emit organic carbon directly as a solid and thus no

subsequent phase change is necessary.

The condensational processes by which many organics are incorporated into fine

particles are no different that those governing the previously discussed forms of sulfate

and nitrate. Thus it is generally inaccurate to think of haze as being caused by discrete

particles of sulfate, nitrate, or organic compounds. Rather, various combinations of

sulfate, nitrate, and organic compounds will attach to tiny nuclei moving through the

atmosphere; eventually growing into particles of sufficient size to effectively scatter light.

By comparison, primary pollutants – such as elemental carbon (soot) or crustal material –

are generally present in the atmosphere as discrete particles. Encounters between other

particle constituents and ammonium sulfate are more frequent when ambient ammonium

sulfate concentrations are high: as a result, sulfate will tend to comprise a larger fraction

of total particle mass under these conditions.

C.1 Hygroscopic Nature of Sulfates and Nitrates

The hygroscopic nature of sulfate and nitrate containing aerosol particles has been

discussed already; however, given the fact that their ability to scatter visible light is

greatly enhanced as they grow in size, some details of this process bear mention.

Sulfate aerosol particles, composed of sulfuric acid and ammonium sulfate and

possibly other constituents as described above, typically have a diameter between 0.1 to

1.0 μm. Sulfate particles will grow substantially as relative humidity increases,

particularly when the relative humidity reaches or surpasses 90 percent. Pure ammonium

sulfate particles are rarely seen in natural conditions; however, in laboratory experiments,

these hygroscopic particles remain in the solid phase until the relative humidity reaches

80 percent, at which point the particle deliquesces and changes from solid to liquid

(Seinfeld and Pandis, 1998). Relative humidity in the summer months typically exceeds

80 percent in the eastern U.S.; hence, particles containing large amounts of ammonium

 

66 Dry deposited nitric acid will quickly dissociate to form nitrate ion when it comes into contact with moist

soils and vegetation.
V-17

sulfate often have greatly enhanced scattering. In sum, the substantial visibility

impairment common in the East is a function of both the high sulfate concentrations and

high humidity found in this part of the country.

Nitric acid is an extremely soluble gas that readily forms nitrate in the liquid

phase. Nitric acid may also react with ammonium to form ammonium nitrate.

Experiments with ammonium nitrate particles demonstrate that these particles will exist

as solids until the relative humidity reaches 60 percent, at which point they will

deliquesce to the liquid phase (Seinfeld and Pandis, 1998). With a deliquescence point

substantially below that of ammonium sulfate, particles containing a mixture of the two

may have a substantially lower deliquescence point than ammonium sulfate alone. These

particles will scatter substantially more visible light as they become larger.

C.2 Potential Competition Between Ammonium Sulfate and Ammonium Nitrate

As the discussion above indicates, there are interactions between ammonium

sulfate and ammonium nitrate in the atmosphere that will need to be considered in

establishing reasonable progress goals. Specifically, the competition between these two

chemical species may mean that a given reduction in sulfate precursors will not result in

expected visibility improvement because ammonium ion previously bound to sulfate will

be available to combine with gas-phase nitric acid and form ammonium nitrate (West et

al., 1999; Middleton and Laulainen, 2000).67 The result could be a non-linear response to

early emissions reduction efforts, particularly if these efforts focus solely on SO2.

An investigation by Carnegie Mellon University researchers indicates that in the

eastern U.S., replacement of sulfate particles by nitrate particles could be important

during colder winter months, but would be relatively uncommon during the warmer

summer months68 (West et al., 1999). This would suggest that an SO2-focused strategy

may indeed lead to expected haze reductions during the summer, when the great majority

of the 20 percent most impaired days in a given year occur at most northeastern and midAtlantic Class I areas. For the minority of days with poor visibility during the winter

months, however, competition from ammonium nitrate could partially offset the particle

reductions achieved by cutting SO2 emissions.

C.3 Biogenic Hydrocarbon Influence on Regional Haze

In general, organic carbon is the second most abundant particle species on poor

visibility days at northeastern and mid-Atlantic Class I areas. A number of laboratory

studies have shown that the semi-volatile oxidation products of higher molecular weight

hydrocarbons can form secondary organic aerosols (Pandis et al., 1991; Zhang et al.,

1992; Odum et al., 1996; 1997a, 1997b; Hoffmann et al., 1997). Due to analytical

challenges and the relatively large number of hydrocarbon species present in the air,

however, relatively little is known about the molecular composition of ambient organic

aerosols.

 

67 In general, sulfate has a stronger affinity for ammonia than does nitrate. This ensures that when enough

sulfate is available, it will preferentially scavenge any ammonia present in the atmosphere. If the amount

of sulfate is reduced, however, a greater amount of ammonia becomes available to react with nitrate.

68 This is due to the tendency for ammonium nitrate to thermally dissociate in warmer weather.
V-18

Precursor emissions for secondary organic aerosols come from both manmade

(anthropogenic) and natural (biogenic) sources. Anthropogenic sources include motor

vehicles, industrial processes, and consumer products. For areas influenced by mobile

sources (i.e., motor vehicles), research indicates that the quantity of so-called

“aromatics,” such as benzene, toluene, and xylenes, in the gasoline strongly determines

the potential for secondary aerosol formation from gasoline vapor (Odum et al., 1997a).

Biogenic sources include trees and other vegetation. In the forested sections of the

eastern U.S., which include most of the Class I areas, emissions of biogenic hydrocarbons

can be quite significant (Geron et al., 1994). The fact that organic carbons generally

account for the second largest fraction of fine particle mass and visibility impairment at

these sites (and up to 40 percent of total fine mass on the 20 percent least impaired days)

would appear to support this hypothesis.

The major biogenic hydrocarbons are isoprene, monoterpenes, and

sesquiterpenes, although oxygenated and sulfur-containing compounds also occur

(Griffin et al., 1999). The biogenic hydrocarbons differ in size, with isoprene containing

five carbons, monoterpenes containing ten, and sesquiterpenes having fifteen.

Secondary organic aerosols generally form from the oxidation of hydrocarbons

containing seven or more carbons (Grosjean, 1992; Grosjean and Seinfeld, 1989). The

smaller isoprene molecule — which plays a substantial role in ozone formation — is

therefore probably not an important precursor of secondary organic aerosols. In contrast,

many of the larger biogenic terpenes effectively form secondary aerosols (Pandis et al.,

1991; Zhang et al., 1992; Odum et al., 1996; Hoffmann et al., 1997). In fact, a number of

biogenic terpenes have a greater potential to form secondary aerosols than does gasoline

vapor (Griffin et al., 1999).

Although isoprene does not appear to be an important precursor of secondary

organic aerosols, it may have important indirect impacts on visibility by virtue of its role

in promoting ozone formation. Isoprene by itself does not produce ozone, but it can

greatly enhance ozone production in the presence of NOX. As noted previously in this

report, ozone in turn enhances the oxidation of biogenic hydrocarbons, thereby promoting

their transformation into light-scattering organic aerosol particles. Biogenic

hydrocarbons can also be oxidized by nitrate radical (NO3) formed from NOX, a process

that can produce large yields of secondary aerosol particles (Griffin, et al., 1999). Thus

oxidation by NO3 and ozone represent anthropogenic influences on biogenic secondary

organic aerosol formation, much as NOX is an anthropogenic influence on isoprene’s

ability to enhance ozone formation. In sum, it would be inaccurate to characterize the

biogenic contribution to aerosol particle concentrations at northeastern and mid-Atlantic

Class I as a purely “natural” component of visibility impairment. Rather, the presence of

biogenic aerosols may be substantially influenced by pollutants that are anthropogenic in

origin, including NOX and ozone.

Conifers such as pine, spruce, and fir trees are significant emitters of terpenes. In

the case of monoterpenes, forest emissions are relatively high in northern New England

(Geron et al., 1994). Unlike isoprene emissions from deciduous trees (e.g., oaks), terpene

emissions from coniferous forests occur year-round. Terpene emission rates are highly

temperature dependent, however; hence terpene emissions in June, July, and August
V-19

(when visibility conditions are generally worst) can be two to four times greater than

winter emissions (Lamb et al., 1993).

While sulfate accounts for the largest share of current levels of light extinction in

the northeastern and mid-Atlantic Class I areas, eventual achievement of national

visibility goals will require addressing the other contributors to regional haze. Organic

carbon is typically the second most important component of regional haze in the

Northeast and Mid-Atlantic. A better knowledge of its molecular constituents may be

necessary to determine the best strategies for reducing its contribution to poor visibility.

These may include both strategies aimed at directly reducing emissions of anthropogenic

hydrocarbons (such as gasoline vapor), and strategies aimed at reducing other

anthropogenic pollutants such as NOX that indirectly influence the formation of biogenic

secondary organic aerosols. In fact, NOX reductions could influence visibility through as

many as three separate mechanisms: first, by directly reducing the formation of aerosol

nitrate; second, by maximizing the visibility improvement achieved through sulfate

reductions (especially in the wintertime); and third, by reducing the formation of biogenic

secondary organic aerosols.
V-20

References

Finlayson-Pitts, B.J., and J.N. Pitts, Chemistry of the upper and lower atmosphere,

Academic Press, San Diego, CA, 969 pp., 2000.

FLAG (Federal Land Managers’ Air Quality Related Values Workgroup), Draft Phase I

Report, U.S. Forest Service, National Park Service, and U.S. Fish and Wildlife Service:

Oct. 1999.

Fox, D.G., W.C. Malm, B. Mitchell, and R.W. Fisher, “Where There’s Fire, There’s

Smoke: Fine Particle and Regional Haze,” Air and Waste Management Association’s

Magazine for Environmental Managers, pg. 15-24, November, 1999.

Geron, C.D., A.B. Guenther, and T.E. Pierce. “An Improved Model for Estimating

Emissions of Volatile Organic Compounds from Forests in the Eastern United States.” J.

Geophys. Res. 99, 12,773-12,79, 1994.

Griffin, R.J., D.R. Cocker III, R.C. Flagan, and J.H. Seinfeld. “Organic Aerosol

Formation from the Oxidation of Biogenic Hydrocarbons.” J. Geophys. Res., 104,

3555-3567, 1999.

Grosjean, D. “In Situ Organic Aerosol Formation During a Smog Episode: Estimated

Production and Chemical Functionality.” Atmos. Envt. 26A, 953-963, 1992.

Grosjean, D., and J.H. Seinfeld. “Parameterization of the Formation Potential of

Secondary Organic Aerosols.” Atmos. Envt. 23, 1733-1747, 1989.

Hoffman, T., J.R. Odum, F. Bowman, D. Collins, D. Klockow, R.C. Flagan, and J.H.

Seinfeld. “Formation of Organic Aerosols from the Oxidation of Biogenic

Hydrocarbons.” J. Atmos. Chem. 26, 189-222, 1997.

Lamb, B., D. Gay, H. Westberg, and T. Pierce. “A Biogenic Hydrocarbon Emission

Inventory for the U.S. A. Using a Simple Forest Canopy Model.” Atmos. Envt, 27A, pg.

1673-1690, (1993).

Malm, William C., Introduction to Visibility, Cooperative Institute for Research in the

Atmosphere (CIRA), Colorado State University, Fort Collins, CO, 80523, 2000a.

Malm, W.C. et al., Spatial and Seasonal Patterns and Temporal Variability of Haze and

Its Constituents in the United States: Report III, Cooperative Institute for Research in the

Atmosphere. Colorado State University, Ft. Collins, CO, 2000b.

Middleton, P., and N. Laulainen. “Examining Impacts of Visibility and PM Strategies

before Implementation.” J. Air & Waste Mgmt. Assn. 50, 875-880, 2000.
V-21

Odum, J.R., T. Hoffman, F. Bowman, D. Collins, R.C. Flagan, and J.H. Seinfeld.

“Gas/Particle Partitioning and Secondary Organic Aerosol Yields.” Environ. Sci.

Technol. 30, 2580-2585, 1996.

Odum, J.R., T.P.W. Jungkamp, R.J. Griffin, R.C. Flagan, and J.H. Seinfeld. “The

Atmospheric Aerosol-forming Potential of Whole Gasoline Vapor.” Science, 276, 96-99,

1997a.

Odum, J.R., T.P.W. Jungkamp, R.J. Griffin, H.J.L. Forstner, R.C. Flagan, and J.H.

Seinfeld. “Aromatics, Reformulated Gasoline, and Atmospheric Organic Aerosol

Formation.” Environ. Sci. Technol. 31, 1890-1897, 1997b.

Pandis, S.N., S.E. Paulson, J.H. Seinfeld, and R.C. Flagan. “Aerosol Formation in the

Photooxidation of Isoprene and β-Pinene.” Atmos. Envt. 25, 997-1008, 1991.

Pitchford, M.L., and W.C. Malm. “Development and Applications of a Standard Visual

Index.” Atmospheric Environment, 28,1049-1054, 1994.

Poirot, R. Vermont Department of Environmental Conservation, Waterbury, VT.

Personal Communication. 31 March 2000.

Saxena, P., L.M. Hildemann, P.H. McMurry, and J.H. Seinfeld, “Organics alter

hygroscopic behavior of atmospheric particles.”, Journal of Geophysical Research, 100,

18,755-18,770, 1995.

Seinfeld, J.H. and S.N. Pandis. Atmospheric Chemistry and Physics, John Wiley &

Sons Inc., New York, New York: 1998.

Sisler, J.F., and W.C. Malm. “Interpretation of Trends of PM2.5 and Reconstructed

Visibility from the IMPROVE Network.” J. Air & Waste Mgmt. Assn. 50, 775-789,

2000.

Trijonis, J.C., W.C. Malm, M. Pitchford, and W.H. White, Visibility: Existing and

Historical Conditions – Causes and Effects, State of Science and Technology Report 24,

Volume III of the National Acid Precipitation Assessment Program (NAPAP),

Washington: Oct. 1990.

West, J.J., A.S. Ansari, and S.N. Pandis. “Marginal PM2.5: Nonlinear Aerosol Mass

Response to Sulfate Reductions in the Eastern United States.” J. Air & Waste Mgmt.

Assn. 49, 1415-1424, 1999.

Zhang, S.H., M. Shaw, J.H. Seinfeld, and R.C. Flagan. “Photochemical Aerosol

Formation from α-Pinene and β-Pinene.” J. Geophys. Res. 97, 20,717-20,729, 1992.
V-22
VI-1

VI. Haze Associated Pollutant Emissions

This chapter discusses major sources and current emissions of haze-forming

pollutants in the eastern U.S., as well as anticipated changes in emissions due to existing

or pending control programs. Each of the chief haze constituents, including sulfate,

organic carbon, nitrate, elemental carbon, and crustal material are addressed. The final

section of this chapter describes on-going efforts to inventory ammonia emissions. As

discussed in Chapter V, ambient levels of ammonia in the atmosphere are important

given their role in the formation of light-scattering ammonium sulfate and ammonium

nitrate aerosol particles.

A. Sulfur Dioxide (SO2)

SO2 is the primary precursor pollutant for sulfate particles. Sulfate particles, as

noted in Chapter III, commonly account for more than 50 percent of particle-related light

extinction at northeastern Class I areas on the clearest days and for as much as 80 percent

on the haziest days. Hence, SO2 emissions are an obvious target of opportunity for

reducing regional haze in the eastern U.S. Fossil fuel combustion, of coal and to a

substantially lesser extent of petroleum products, accounts for most anthropogenic SO2

emissions. In fact, in 1998 a single source category — coal-burning power plants — was

responsible for two-thirds of total SO2 emissions nationwide (USEPA AIRS, 2000).

A.1 Inventory

Figure VI-1 shows the trend in national SO2 emissions over the ten-year period

between 1989 and 1998 (USEPA, 2000a). It indicates a decline in total emissions of

about 20 percent over this period, with a significant step-wise drop coinciding with the

implementation of Phase I of the federal Acid Rain Program in 1994-95 (see discussion

below). After 1995, emissions actually began to increase again slightly, a trend that

probably reflects increased electricity demand in the late 1990s combined with the

availability of excess emissions allowances that were banked as a result of substantial

initial over-compliance with Phase I requirements in the mid-90s. This led to relatively

low market prices for allowances later in the decade, which tended to encourage

allowance purchases rather than implementation of control measures as electricity output

continued to grow.

A.2 SO2 Control Programs

SO2 emissions from power plants were first regulated at the federal level under

the 1970 Amendments to the Clean Air Act. The 1970 Amendments directed USEPA to

establish a National Ambient Air Quality Standard (NAAQS) and New Source

Performance Standard (NSPS) for SO2. From the late-1970s through the 1980s, these

regulatory developments resulted in a gradual decline in SO2 emissions, but did not result

in major overall reductions. The primary strategy for avoiding NAAQS violations was to

dilute SO2 emissions through the use of tall smokestacks; this tactic, which, of course,

facilitated atmospheric transport, was regarded as acceptable at a time when the long-
VI-2

range impacts of pollution were not generally understood or considered. NSPS

requirements applied only to new or substantially modified power plants – a relatively

small number compared to the population of existing facilities.

In the mid-1990s, substantial SO2 emissions reductions from existing power

plants were implemented as a component of the national Acid Rain Program. This

program was introduced under Title IV of the Clean Air Act Amendments of 1990. Title

IV aimed to cut national SO2 emissions from power plants by 10 million tons from 1980

levels, to an eventual cap of just under 9 million tons annually. More modest reductions

in NOX emissions were also included in the program; these are discussed in Section C.2

of this chapter. The reductions were to be implemented using a national cap and trade

program in which sources were allocated an initial emissions allowance based on their

historic emission rates and were then free to trade allowances.

The first phase of the federal Acid Rain Program was implemented in 1995 with

110 of the highest emitting power plants subject to emissions limits. As indicated by

Figure VI-1, Phase I implementation resulted in net emissions reductions of

approximately 4 million tons, with total power plant emissions falling to just under 12

million tons. However, it is worth noting that the reductions achieved at Phase I plants

Figure VI-1: National SO2 emissions trend from 1989 to 1998 (USEPA, 2000a).
VI-3

between 1990 and 1995 actually totaled 4.7 million tons. This was a full 3.4 million tons

lower than required in 1995 and represented over-compliance of close to 40 percent with

Phase I requirements. After 1995, as noted previously, power plant emissions began to

rise again slightly and by 1998 had increased by nearly 1.3 million tons over the SO2

levels achieved in 1995, to a total of over 13 million tons.

The second phase of the Acid Rain Program went into effect in 2000. It further

reduced allowable emissions (to an average rate of 1.2 pounds of SO2 emissions per

million Btu of fuel input or lbs/mmBtu) and extended emissions limits to a larger group

of power plants (including all units with a generating capacity greater than 25

megawatts). Full implementation of the Phase II requirements should eventually limit

total SO2 emissions from power plants to just under 9 million tons per year. However,

power plant emissions for most of the 2000-2010 period are expected to remain closer to

9.5 million tons, in part because of the availability of bonus allowances to ease

compliance for certain sources and because of the carryover of excess allowance from

over-compliance in Phase I of the program. As of 2000, over 10 million tons of SO2

emissions allowances had been carried over from Phase I into Phase II (NESCAUM,

2000).

As indicated by Figure VI-1, fossil fuel combustion by large industrial facilities,

transportation sources and certain industrial processes account for a substantial portion of

the remaining national SO2 inventory. In 1995, sources other than power plants

contributed over 6 million tons to the national inventory.69 Roughly half this total was

attributable to fossil fuel combustion at large industrial facilities. The Acid Rain Program

encourages emission reductions at large industrial sources by giving them the option of

participating in allowance trading markets if they make reductions. Finally, new

regulations proposed by USEPA to limit the sulfur content of highway diesel fuel and

gasoline should, if implemented,70 provide important reductions in sulfur emissions from

the transportation sector. As currently proposed, fuel sulfur content limits would go into

effect by 2006 and would reduce sulfur emissions from cars and trucks by approximately

90 percent. Relative to power sector reductions, however, additional SO2 reductions

from the transportation sector will be fairly small. In sum, remaining sulfur emissions

from other industrial facilities, the transportation sector, and other sources are likely to

keep the total national inventory well above 10 million tons, even after Title IV emissions

caps are fully implemented.

B. Volatile Organic Carbons (VOC)

After sulfate, organic carbon generally accounts for the next largest share of fine

particle mass and particle-related light extinction at northeastern Class I sites. As

indicated in Chapter II, the term organic carbon encompasses a large number and variety

 

69 Note that this represents a decline of 2.1 million tons from the non-utility contribution of 8.4 million tons

in 1980.

70 EPA’s proposal for substantially limiting fuel sulfur content faces substantial political opposition; hence

there is still some question, at the time of this writing, as to whether it will be implemented as currently

proposed.
VI-4

of chemical compounds. The organic carbon present at Class I sites almost certainly

includes a mix of species attributable to manmade pollution sources and biogenic

hydrocarbons, which are emitted from vegetation. As this section indicates, efforts to

reduce manmade organic carbon emissions have been undertaken primarily to address

summertime ozone formation in urban centers. In the future, efforts to control fine

particle pollution both for visibility reasons and for public health protection may prompt

additional control efforts for this class of pollutants.

B.1Inventory

Inventory data on organic carbon emissions are available as a result of past and

ongoing ozone attainment planning efforts.71 Current inventories typically refer to

“volatile organic compounds”or VOCs, a term that designates those hydrocarbons whose

volatility in the atmosphere makes them particularly important from the standpoint of

ozone formation. Understanding transport dynamics and source regions for organic

carbon in northeastern Class I areas is likely to be more complex than for sulfate. This is

partly because of the large number and variety of organic carbon species, the fact that

their transport characteristics vary widely, and the fact that a given species may undergo

numerous complex chemical reactions in the atmosphere. Thus, the organic carbon

contribution to visibility impairment at most Class I sites in the East is likely to include

manmade pollution transported from a distance, manmade pollution from nearby sources,

and biogenic emissions, especially terpenes from coniferous forests.

The VOC inventory is dominated by transportation sources, including exhaust

from gasoline passenger vehicles and diesel-powered heavy-duty vehicles, as well as

evaporative emissions from transportation fuels. VOC emissions also come from a

variety of so-called area sources (this category includes sources such as solvents,

architectural coatings, dry cleaners, etc.) as well as some point sources, including

industrial facilities and petroleum refineries.

Biogenic VOCs may play an important role within the rural settings typical of

Class I sites. As discussed in Chapter V, the oxidation of hydrocarbons containing seven

carbons or more is generally the most significant pathway in the formation of light

scattering organic aerosol particles (Odum et al., 1997). Smaller reactive hydrocarbons

that may contribute significantly to urban smog (ozone) are less likely to play a role in

organic aerosol formation (though it should be noted that ozone levels can have an

indirect effect in terms of promoting the oxidation of other available hydrocarbons,

including biogenic emissions). 72

In short, further work is needed to characterize the organic carbon contribution to

regional haze in the Northeast and Mid-Atlantic regions and to develop inventories that

will be of greater value for visibility planning purposes.

 

71 Ozone is formed in the atmosphere from chemical reactions involving NOX and VOC in the presence of

sunlight. Because solar energy is a fundamental driver in this process, ozone is primarily a summertime air

quality concern.

72 See further discussion of the biogenic component of organic emissions in Chapter V, Section C.3.
VI-5

B.2 VOC Control Programs

To date, some of the most important VOC control efforts for purposes of ozone

mitigation have focused on mobile sources. Automobiles, in particular, have been

subject to increasingly stringent regulation of their tailpipe exhaust and evaporative

emissions since the early 1970s. These regulations have resulted in per mile reductions

of up to 98 percent in VOC emissions from light duty vehicles. At the same time fuel

modifications, such as the federal reformulated gasoline program, have been used to

reduce evaporative and other fuel-related emissions. Some of the resulting benefits have

been offset by a substantial increase in vehicle miles traveled and fuel consumed over the

same time period, but on the whole, VOC emissions from passenger vehicles have

declined significantly over the last three decades.

In addition, states in the ozone transport region (OTR) have undertaken a number

of initiatives aimed at reducing VOC emissions from non-mobile point and area sources

as part of their ozone attainment SIPs. By 2007, these initiatives will reduce VOC

emissions from solvent utilization by 33 percent from area sources and by 45 percent

from point sources relative to 1990 levels. Over the same time period, the storage and

transport sector will be required to reduce area source emissions by 45 percent and

facility (point source) emissions by 12 percent. Finally, by 2007, emissions from

chemical manufacturing facilities and “other industrial processes” are to be reduced by 46

and 58 percent, respectively, below 1990 levels.

C. Oxides of Nitrogen (NOX)

Nitrate generally accounts for a substantially smaller fraction of fine particle mass

and related light extinction than sulfate and organic carbon at northeastern Class I sites.

(Notably, it may play a more important role at urban sites and in the wintertime.)

Nevertheless, NOx emissions contribute directly to visibility impairment in the eastern

U.S. by forming light-scattering nitrate particles. In addition, NOx may have an indirect

effect on summertime visibility by virtue of its role in ozone formation, which in turn

promotes the formation of secondary organic aerosols.

C.1 Inventory

Power plants and mobile sources are the dominant source of NOx emissions.

Nationally, power plants account for more than one-quarter of all NOx emissions, over 6

million tons. Their relative contribution is much higher, however, in parts of the

industrial Midwest where high NOx emissions are associated with a significant power

plant contribution. By contrast, the NOx inventories for more urbanized Mid-Atlantic and

New England states are dominated to a far greater extent by mobile sources.

Since 1980,73 nationwide emissions of NOX from all sources have shown little

change. In fact, emissions increased by 2 percent between 1989 and 1998 (EPA, 2000a).

This increase is most likely due to industrial sources and the transportation sector, as

 

73 1980 is the base year for all control programs under the CAA’s Title IV requirements.
VI-6

power plant combustion sources have shown modest emissions reductions during this

same time period.

C.2 NOx Control Programs

Most current regulatory efforts to reduce NOx emissions from power plants and

mobile sources are motivated by ozone attainment needs; in addition, more limited

reductions are currently being required for purposes of mitigating the NOx contribution to

acid deposition. Because of the link to ozone, some of the most important NOx control

efforts – notably those involving major point sources – are seasonal; i.e. they require

emissions controls only during the summer months. Tailpipe NOX emissions standards

for automobiles, of course, provide year-round reductions. In addition, modest NOX

reductions from power plants (totaling approximately 2 million tons nationally) are

required under the federal Acid Rain Program; these reductions are similarly year-round.

NOx was first regulated at the federal level by the 1970 Clean Air Act

Amendments which directed USEPA to develop both a NAAQS for NO2 and NSPS

standards for NOx emissions from new or substantially modified stationary sources.

Because violations of the NO2 NAAQS were relatively uncommon (notably, Los Angeles

was one area in non-attainment of this standard in the 1970s) and because NSPS applied

to a relatively limited number of sources, these regulations did not result in broad-based

control efforts. In addition, they were largely met by the use of so-called low-NOx burner

technology, a form of emissions control that is based on combustion modifications rather

than smokestack controls. In the late 1970s and 1980s, low-NOx burner technology

tended to achieve emissions reductions on the order of 30 percent.

By 1990, the previously under-appreciated importance of NOx in ozone formation

was increasingly recognized. The 1990 Clean Air Act Amendments for the first time

required NOx controls at existing large stationary sources located in ozone nonattainment areas. As a result, most power plants in the Ozone Transport Region became

subject to Reasonably Available Control Technology (RACT) requirements in 1995.

Combustion modifications (such as low-NOx burners and overfire air) continued to

suffice for meeting most of these requirements; modern versions of these technologies are

capable of achieving control efficiencies of over 40 percent. The RACT requirements

introduced in the mid-1990s for purposes of ozone control overlapped to a considerable

degree with the NOx limits that were applied to certain units in 1996 under the Phase I

requirements of the Acid Rain Program.

Meanwhile, states within the Ozone Transport Region were recognizing that

additional NOx reductions would be necessary to address pervasive, regional ozone

problems in the Northeast and Mid-Atlantic regions. In 1994, the Ozone Transport

Commission (OTC) adopted a Memorandum of Understanding (MOU) that committed

participating states to go beyond existing RACT requirements to achieve total NOx

reductions of 55 to 65 percent by 1999 and 65 to 75 percent by 2003. Most OTC member

states are participating in Phase II of the OTC MOU and several have created a NOx

budget program to allow for trading of allowances among sources. More recently,
VI-7

following a two-year, multi-stakeholder process74 aimed at addressing the problem of

ozone transport over a broader area of the eastern U.S., USEPA proposed to extend

similar reduction requirements to a 22-state eastern region in an action widely known as

the Section 110 NOX “SIP call.”75 The NOx SIP call, which was recently upheld in

federal court after several legal challenges, will require emissions reductions of

approximately 85 percent from uncontrolled levels (equivalent to meeting an average

emissions rate of approximately 0.15 lb/mmBtu) at large industrial boilers and power

plants over a large portion of the eastern U.S. These reductions were originally to have

been implemented by 2003; because of subsequent litigation, however, the

implementation date may be delayed to 2004. Importantly, reduction requirements under

both the OTC MOU and USEPA’s broader NOX SIP call apply to emissions only during

the 5-month ozone season (from May to September).

Significant limits on NOX emissions from vehicle tailpipes, meanwhile, were first

introduced in the late 1970s (in California) and in the 1980s (nationally). On a per-mile

basis, current tailpipe standards for NOX represent a 98 percent reduction from pre-1970

uncontrolled levels; a further reduction of 50 percent will be achieved with the

implementation of new federal and California standards in 2005. As in the case of

VOCs, absolute emissions reductions from the mobile source sector have not been

equally dramatic, owing to the several-fold increase in total vehicle miles traveled over

the last four decades. Finally, additional NOX reductions from heavy-duty vehicles are

anticipated in the next decade as a result of new federal regulations for diesel engines.

D. Elemental Carbon and Crustal Material

Elemental carbon and crustal material generally account for a smaller portion of

fine particle mass and visibility impairment at northeastern Class I areas76. Because

ambient levels of these materials have not generally been regulated in the past, inventory

data and experience with control measures are generally less extensive than for the other

pollutants discussed in this Chapter. This section provides a brief overview of sources

and relevant control experience for these fine particle constituents; additional research in

this area may be appropriate as part of future haze planning efforts.

Elemental carbon, the chief constituent of soot, is primarily emitted from the

combustion of wood, and diesel fuel. Particulate emissions limits currently apply to

several combustion sources of elemental carbon, including newer wood stoves and diesel

engines. However, these limits frequently apply to larger particles in the 10 micrometer

 

74 The Ozone Transport Assessment Group (OTAG) process involved 27 states and provided the basis for

EPA’s subsequent Section 110 SIP call.

75 EPA’s action is authorized under Section 110 of the Clean Air Act, which allows the Agency to act to

address interstate pollution transport by requiring states to submit implementation plans (SIPs) to reduce

their contribution to ozone non-attainment in downwind states. In a separate but related action, several

individual northeastern states also petitioned EPA under Section 126 of the Clean Air Act to impose

upwind NOx reductions. 76 However it should also be noted that the relative fraction of total carbon that is considered elemental

versus organic is operationally defined and has large associated uncertainty. See Appendix B for more

detail regarding carbon analysis procedures.
VI-8

size range (PM10) and hence may provide less effective regulation of the smaller particles

that are susceptible to long-range atmospheric transport and play a more important role in

visibility impairment at Class I sites. Diesel engines are known to be a substantial source

of elemental carbon emissions in urban areas of the Northeast, while wood stoves can be

an important source of particulate pollution in some rural areas. Figure III-3a

demonstrates that while elemental carbon accounts for roughly the same percentage of

total fine particle mass in urban areas as in rural areas, the absolute contribution from

elemental carbon is two and a half times greater in Washington D.C. than it is in rural

areas like Acadia National Park. The evidence that woodsmoke contributes to elemental

carbon measurements in rural areas is shown later in this report in Figure VII-2, which

illustrates the results of source attribution studies for fine particle observations at

Underhill, VT. Particulate emissions from new woodstoves are presently regulated;

however, emissions from wood burned in older woodstoves and fireplaces are not.

Meanwhile, effective control technologies for other sources of elemental carbon

emissions are available, including particulate traps for diesel exhaust. Additional

reductions will be achieved by the future federal emissions limits for new diesel engines

and by retrofitting existing engines. Currently, a number of northeastern states are

initiating smoke testing and other programs to reduce particulate emissions from on-road

heavy-duty vehicles; states are also exploring means to reduce emissions from

construction equipment and other off-road sources.

Crustal material accounted for as much as 16 percent of particle-related light

extinction on the 20 percent of days with the best visibility in 1997 at the Brigantine and

Acadia sites. However, its role is generally much smaller in relative terms on the 20

percent worst visibility days. To the extent that the crustal fraction includes material of

natural origin (such as soil or sea salt), it may not be particularly amenable to control

efforts. However, the crustal fraction can be influenced by human activities, such as

construction, agricultural practices, and road maintenance (including wintertime salting).

To the extent that these types of activities are found to impact visibility at northeastern

Class I sites, control measures targeted at crustal material may prove beneficial. Some

experience may be available from the western U.S., where the crustal component has

generally played a more significant role in driving overall particulate levels; aspects of

this experience may or may not be relevant in the eastern context. In addition, a few

areas in the Northeast, such as New Haven, CT and Presque Isle, ME, have some

experience with the control of dust and road-salt as a result of their past non-attainment

status with respect to the PM10 NAAQS.

E. Ammonia Emissions

Knowledge of ammonia emission sources will be necessary in developing

regional haze reduction strategies because of the important roles of ammonium sulfate

and ammonium nitrate in fine particle mass and light scattering. Overall, it is estimated

that in 1998, livestock agriculture and fertilizer use contributed to about 85 percent of all

ammonia emissions to the atmospere (USEPA AIRS, 2000). However, better ammonia

inventory data are needed as an input to the photochemical models used to simulate fine

particle formation and transport in the eastern U.S. Because ammonia has not been
VI-9

regulated as a criteria pollutant or criteria pollutant precursor, these data do not presently

exist at the same level of detail or certainty as for NOx and SO2.

Ammonium ion (formed from ammonia emissions to the atmosphere) is an

important constituent of airborne particulate matter, typically accounting for 10 to 20

percent of total fine particle mass. Reductions in ammonium ion concentrations can be

extremely beneficial because a more than proportional reduction in fine particle mass can

result. Ansari and Pandis (1998) showed that a 1 μg/m3 reduction in ammonium ion

could result in up to a 4 μg/m3 reduction in fine particulate matter. However, the benefits

of ammonia reduction must be weighed against the significant role it plays in neutralizing

acidic aerosol77 and potentially decreasing dry scattering efficiency of fine particles.

To address the need for improved ammonia inventories, MARAMA, NESCAUM

and USEPA have funded researchers at Carnegie Mellon University (CMU) in Pittsburgh

to develop a regional ammonia inventory (Davidson et al., 1999). This study is focusing

on three issues with respect to current emissions estimates:

1. Wide range of ammonia emission factor values,

2. Inadequate temporal and spatial resolution of ammonia emissions, and

3. Lack of standardized ammonia source categories.

With respect to the first issue, currently available inventories list emission factors

that differ by more than an order of magnitude for several animal categories (Lee and

Dollard, 1994). These reflect uncertainties in the emission factors themselves as well as

variable emissions from some source categories. For example, animal wastes are a

source of ammonia in the atmosphere through volatilization from excrement. The rate of

volatilization is affected by wind speed, air and soil temperature, relative humidity, soil

moisture, and rainfall (Lee and Dollard, 1994; Sommer et al., 1991); as a result,

emissions factors are sensitive to the conditions under which they were measured. In

addition, current inventories typically do not account for the fact that ammonia emissions

are nearly an order of magnitude higher from confined cattle operations than from

grazing cattle operations (Roe and Strait, 1998).

The second issue, concerning spatial resolution, reflects the fact that current air

quality models require emissions input data at a spatial resolution sufficient for

computing air quality in a single grid cell, often 10 square kilometers or smaller. Activity

level data for some ammonia sources, however, are available only at the county level.

This introduces a level of uncertainty in converting county level emissions to grid-scale

emissions for model inputs. Meanwhile, the temporal resolution of ammonia emissions is

another area of uncertainty in model inputs. One example is the use of fertilizer. Model

inputs typically treat fertilizer emissions as if they are temporally constant (i.e., using a

constant yearly average), whereas actual fertilizer applications are episodic and occur at

 

77 SO2 reacts in the atmosphere to form sulfuric acid (H2SO4). In the presence of ammonia, this strong acid

can be partially neutralized to form ammonium bisulfate or fully neutralized to form ammonium sulfate. If

strategies are focused on ammonia without corresponding decreases in SO2 emissions, resulting fine

particles will be substantially more acidic than those presently observed.
VI-10

brief, specific times during the year. Real world ammonia emissions from fertilizer are

therefore characterized by large peaks, which then taper off to background levels, a

feature that is generally not captured by current air quality models (Davidson et al.,

1999).

The third area of investigation for the Carnegie Mellon researchers focuses on

discrepancies in classifying ammonia source categories by different inventories. For

example, the current national inventory for 1990 does not include emissions from soils

(E.H. Pechan, 1995), yet most other inventories show soil emissions to be significant

(Davidson et al., 1999). This discrepancy may be quite significant between inventories.

A recent inventory of emissions in the San Joaquin Valley in California ranks soil

emissions as second (40 percent of total) only to livestock emissions (50 percent of total)

(Roe and Strait, 1998).

One goal of this project is establish an inventory framework with source

categories, emissions factors, and activity data that are readily accessible to the user.

With such a framework, data can be obtained in a variety of formats78 and updates can be

made easily, allowing additional ammonia sources to be added or emissions factors to be

replaced as needed in the future (Strader et al., 1999).

It should be noted that the point source inventory being developed by CMU is

based on the USEPA Toxic Release Inventory (TRI) which may or may not be more

accurate than available state information. The resulting inventory should be compared to

state information for consistency.

 

78 For example, the user will have the flexibility to choose the temporal resolution of the output emissions

data or to spatially attribute emissions based on land-use data.
VI-11

 References

Ansari , A. S., and S.N. Pandis. “Response of inorganic PM to precursor

concentrations,” Environ. Sci. Technol., 32, 2706-2714, 1998.

Davidson, C., Strader, R., Pandis, S., and Robinson, A. Preliminary Proposal to

MARAMA and NESCAUM: Development of an Ammonia Emissions Inventory for the

Mid-Atlantic States and New England. Carnegie Mellon University, Pittsburgh, PA. 7

Jan. 1999.

E. H. Pechan & Associates, Inc. The National Particulates Inventory: Phase II

Emission Estimates, Draft. Prepared for U.S. EPA Office of Air Quality Planning and

Standards. Research Triangle Park, NC (June 1995).

Lee, D. S., and G.J. Dollard. “Uncertainties in Current Estimates of Emissions of

Ammonia in the United Kingdom.” Environmental Pollution, 86, 267-277, 1994.

NESCAUM, “Environmental Regulation and Technology Innovation: Controlling

Mercury Emissions from Coal-Fired Boilers.” September, 2000.

Odum, J.R., T.P.W. Jungkamp, R.J. Griffin, R.C. Flagan, and J.H. Seinfeld. “The

Atmospheric Aerosol-forming Potential of Whole Gasoline Vapor.” Science, 276, 96-99,

1997.

Roe, S. M., and R.P. Strait. “Methods for Improving National Ammonia Emission

Estimates.” Proceedings of the Air and Waste Management Association Emissions

Inventory Conference, New Orleans (December 8-10, 1998).

Sommer, S. G., J.E. Olesen, and B.T. Christensen, B. T. “Effects of Temperature,

Wind Speed and Air Humidity on Ammonia Volatilization from Surface Applied Cattle

Slurry.” J. Agricultural Sci., 117, 91-100, 1991.

Strader, R., N. Anderson, and C. Davidson, Development of an Ammonia Inventory for

the Mid-Atlantic States and New England, Progress Report, October 18,2000, available

online: http://marama.org/rt_center/MARAMAprogress10-18-00.pdf, 2000.

USEPA, National Air Quality and Emission Trends Report, 1998, EPA 454/R-00-003,

available online: http://www.epa.gov/oar/aqtrnd98/, 2000a.

USEPA, National Air Pollutant Trends, 1900 – 1998, EPA 454/R-00-002, available

online: http://www.epa.gov/ttn/chief/trends/trends98/trends98.pdf, 2000b.

USEPA AIRS. “AIRSData: Query – NET Tier Report.” U.S. Environmental Protection

Agency, Available Online: http://www.epa.gov/airsweb/nettier.htm, 2000.
VI-12
VII-1

VII. Review of Analytical Tools

To develop successful haze SIPs and TIPs, all states and interested tribes, whether

they host a Class I area or not, must develop long-term strategies for helping to achieve

natural visibility conditions in Class I areas by 2064. In addition, those states that do

have a Class I area will be required to establish visibility goals and demonstrate

reasonable progress toward these goals for each Class I area. To assess the effectiveness

of a particular control strategy and to produce satisfactory demonstrations of progress,

model simulations of “baseline” and future visibility conditions in Class I areas are

needed. These simulations will likely employ a number of analytical tools to portray the

meteorology, emissions, chemical transformations and other factors that ultimately affect

atmospheric light extinction and therefore visibility.

A. The Challenges of Modeling Regional Haze

Model simulations performed for purposes of understanding the contribution of

regional haze to visibility impairment in Class I areas will differ significantly from

modeling activities aimed at understanding episodic ozone concentrations in urban areas

and even episodic fine particle levels in urban areas. This is, in part, because conditions

leading to regional haze are geographically widespread and present for much of the year.

Because federal regional haze regulations are aimed at improving aggregate

visibility conditions over a 5-year period, it becomes necessary to consider the wide

variety of emissions levels and meteorological conditions (including humidity factors)

which are experienced over this time period. Simulations of visibility must be

representative of daily, seasonal, as well as year-to-year variations which are likely to be

experienced in each Class I area, and across the broader regions surrounding them. If

shorter time periods or “episodes” are modeled, they must be selected to represent the full

range of possible conditions. Performing a year-long model run (or longer) presents a

challenge in and of itself, simply in terms of the computation time required by many

detailed air quality models. Obtaining, validating and analyzing a year of meteorological

(as well as emissions) data for the entire eastern U.S. represents an additional burden

which could be significantly eased by the cooperative efforts of state, tribal, regional,

federal and academic modeling groups. Due to the nature of regional haze, large spatial

scales are also required. It may prove most efficient for some purposes to move from

mesoscale models to global models, for which archived meteorological data are already

being produced (e.g. NGM, MRF and Eta Model output).

Federal regional haze requirements specify two objectives; improving visibility

(eventually to unpolluted natural “background “ conditions) on the 20 percent of days

with the worst visibility and ensuring no degradation on the 20 percent of days with the

best visibility. Maintaining visibility conditions on the 20 percent least impaired days in

the more northern Class I areas where current conditions on those days are already quite

close to natural background (see Figure V-1) may be a challenge. In these areas, a single

major source could degrade visibility measurably on the 20 percent least impaired days.

Modeling activities will have to address this issue in developing strategies to comply with

the maintenance provisions of the regional haze rule. This may require detailed modeling
VII-2

studies using source dispersion techniques to assess the impacts of specific sources near

certain Class I areas.

The state of science in current aerosol models presents an additional challenge for

modeling specific regional haze episodes. This chapter discusses several models in use

or in development for the analysis of fine particle nucleation and growth mechanisms.

Several of these models contain deficiencies that are expected to be addressed in the near

future. As modeling tools are refined and expanded, more accurate simulations of fine

particle size and number distributions, as well as compositional information, should be

available. Such information is important in calculating reliable estimates of the visibility

degradation caused by different haze constituents. Emissions control measures,

meanwhile, need not be delayed to await such refinements since current models are

already able to provide reliable information about the aggregate determinants and

components of regional haze in the eastern U.S. (Huber et al., 2000).

As discussed in Chapter IV, states’ first regional haze SIPs will generally be due

in the 2007-2008 time frame (though a SIP committing states to regional planning efforts

will be due before this). Thus it would be reasonable to expect that significant modeling

activities will occur in the 2004-2007 time frame. Given the significant time required to

construct and run complex air quality models, states will be required to make choices

soon about modeling tools that may not be used for regulatory purposes for another four

to seven years. In making these choices, states will need to consider anticipated

improvements as well as the current attributes of available modeling platforms. Perhaps

even more important will be the need for early regional coordination to ensure that all

necessary modeling activities for regional haze SIP development are carried out.

In the following section, the structures of the various modeling platforms are

reviewed along with noted strengths or weaknesses. In section C we review comparison

studies focused on the performance of several of the particulate models presented here.

In section D we discuss how one might use the available tools in SIP development.

B. Available Analytical Tools

Figure VII-1 illustrates the relationship among a number of analytical tools

available for modeling regional haze and indicates how they can be of use in the SIP

development process. Meteorological and emissions models are required to generate

gridded inputs for 3-Dimensional Eulerian air quality models. These 3-D models, in turn,

can inform the SIP development process in two ways: first, to simulate average

conditions using simplified parameterizations over an extended period of time and

second, to simulate specific haze events, such as the mid-July 1999 event discussed in

Chapter III, using more sophisticated analysis and more specific parameters.
VII-3

Figure VII-1: Relationship of modeling tools for SIP development.

Ambient

PM Data

Emissions

Inventories

Met Data

Emissions

Model

Meteorological

Model

Trajectory

Model

 3-D Eulerian

Air Quality

Model

Source

Dispersion

Model

Source

Apportionment

Model

SIP Development Visibility

Goals

A different type of tool, the source dispersion model, can inform the SIP process

in a different way. This type of model allows the user to investigate the specific impact

of individual emission sources. Yet another tool, called factor analysis, uses receptorbased techniques that take into account speciated measurements of particle composition

(and in some cases, the source emission profiles of specific known sources) to determine

the individual contribution of known source types to the fine particle levels observed at a

particular site. In cases where emissions profiles are generic across a source type, (e.g., if

all smelters produce similar emissions) then factor analysis can be used to help identify

source categories and validate emission inventories. This technique is often used in

conjunction with trajectory models for source apportionment studies which identify the

origin of airmasses that correlate with a specific source profile.
VII-4

B.1 Meteorological Models

Two major types of analytical tools are available for generating meteorological

inputs to air quality models: diagnostic and prognostic models. Diagnostic models

typically analyze observed atmospheric states at discrete times and locations. These

models are usually computationally efficient and simple to apply; however, they can

produce large errors when attempting to interpolate over regions with sparse data.

Meteorological observations are limited by the existing network for collecting such data

and are frequently sparse over mountainous and marine areas. Observations of

conditions higher in the atmosphere are often similarly sparse, however, the spatial scales

of interest for accurate simulation of atmospheric dynamics aloft are often greater as well.

The interpolation of meteorological conditions is inherently imprecise and, when run with

insufficient data, can lead to physically unrealistic results. Diagnostic models cannot

produce results at a level of resolution finer than the underlying observation set; thus it is

important to select a level of modeling resolution that is consistent with available input

data.

CALMET (Scire et al., 1998a) is one of the most widely used air quality

diagnostic models. It includes specific modules for boundary layer meteorology and

complex terrain. This model is frequently used in conjunction with CALPUFF, a

dispersion model that was designed to calculate fine-scale pollutant transport over

complex terrain.

Prognostic models are based on primitive equations of motion for the atmosphere

in a finite-difference form. Thus, while they ensure internally consistent results, these

models are highly sensitive to the accuracy of the boundary conditions used to initialize

them. To avoid the accumulation of errors which can result from this situation,

prognostic models are frequently used in conjunction with Four-Dimensional Data

Assimilation (FDDA). This procedure “nudges” certain variables used in the theoretical

relationships to keep the results close to those observations which may be available. The

use of FDDA substantially reduces errors and is currently the best method for generating

reasonably accurate and dynamically consistent data sets (Seaman, 2000). Nevertheless,

prognostic models are more complex than diagnostic models and require skill and care

when adapted to individual situations.

Two prognostic models are widely used and readily available. They are the

Regional Atmospheric Modeling System (RAMS) (Pielke et al., 1992) produced by

Colorado State University and the Fifth Generation Mesoscale Model (MM5) (Grell et

al., 1994) developed by Pennsylvania State University in conjunction with the National

Center for Atmospheric Research. Both are non-hydrostatic models and can be

appropriately used at resolutions finer than 10 km; however, a number of considerations

must be given to selecting a grid resolution. In general, the finest resolution available

will give the most accurate results; however, many parameterizations included in

prognostic models (used to estimate variables such as cloud cover, precipitation or heat

flux) may break down at very fine resolutions. This occurs when the processes involved

are no longer accurately represented by parameterized relationships. In general, for

regional modeling purposes, it may be computationally prohibitive to perform a severalday simulation on scales finer than 12 km; additionally, when computation speeds are not
VII-5

an issue, care should be taken to ensure that embedded parameterizations remain valid at

these resolutions. Probably the most important consideration in selecting a resolution is

consistency with the chosen air quality model. An interface program designed to

transform the output of a meteorological model to the required input format for an air

quality model should be used with great care. Interpolation of meteorological fields,

spatially or temporally, onto a different grid for use in an air quality model has been

shown to introduce errors in maintaining mass consistency (Wang, 1997). This has been

identified as a major problem which can be diminished if the meteorological and air

quality models share exactly the same coordinate system both spatially and temporally.79

Trajectory models, which will be discussed in more detail later, can be thought of

as extensions of meteorological models and simply calculate the motion over time of a

specified airmass using meteorological data.

B.2 Emissions Models

Emissions information is a required input for air quality models. Emissions

inventories developed as part of a state’s SIP can be used as a foundation for generating

the detailed temporal and spatial emission information required for atmospheric

simulations. Emission models are used in conjunction with emission factors to transform

countywide emission inventory information to the requisite component-specific emission

information at the desired temporal frequency. For regional haze simulations, emissions

information will be needed for primary PM2.5 and PM10, NH3, SO2, NOX, VOC,

elemental carbon (e.g. diesel, wood smoke) and CO for each grid cell within the air

quality model’s domain for each timestep of the simulation.

Two available emission models are the EPS2.580 model and the EMS200081

model which are both new versions of older models (EPS2.0 (Causley et al., 1990) and

EMS95 (Alpine Geophysics, 1995)) which have been widely used for converting

stationary source emissions information. A newer emissions model has been developed

which is theoretically similar to the EMS95 model but is computationally more efficient.

This model, the Sparse Matrix Operator Kernel Emissions (SMOKE) model82 has had

limited use to date but is promising in its ability to consolidate gridded estimates of

stationary, mobile and biogenic sources.

In addition, the MEPPS emission modeling system (Byun and Ching, 1999) has

been developed for use with the Models-3/CMAQ framework (discussed later). This

model was based on the 1994 version of Geocoded Modeling and Projection System

(GEMAP) which has subsequently become known as EMS95. MEPPS has been

substantially revised from GEMAP/EMS95 to be more generic and efficient in its

operation. The advantages of this modeling system include its incorporation of

geographic information system (GIS) code which allows for the easy distribution of

emissions to geographic regions; however, the system does require SAS® and Arc/Info®

 

79 NARSTO Synthesis Team Draft Report, 2000

80 Systems Applications International, Ongoing work assignment with Tom Braverman of U.S. EPA, 2000.

81 LADCO, User’s guide and documentation forthcoming, 2000.

82 MCNC, A description of the SMOKE emissions model is available online at the following website:

http://envpro.ncsc.org/products/smoke/.
VII-6

software to run. While MEPPS is the currently available emissions processor used by the

Models-3/CMAQ system, a version of SMOKE for Models-3 is under development and

may be available for use soon.

B.3 3-D Eulerian (Grid) Air Quality Models

Gridded models are perhaps the most complex of the analytical tools explored

here. These models attempt to simulate atmospheric processes including meteorological

processes and aerosol formation mechanisms. These models, as with other air quality

models, all solve some form of the atmospheric mass conservation equation and the

atmospheric diffusion equation. These fundamental equations are used to mathematically

calculate the formation, transport and fate of chemical species in the atmosphere. Gridbased models are more complex in large part because they divide a geographical domain

into individual grid cells, both horizontally and vertically, which interact with each other

to simulate atmospheric processes affecting pollutant concentrations such as chemistry,

diffusion, advection, sedimentation (for particles), and deposition (wet and dry) (Russell

and Dennis, 2000). They then attempt to solve the fundamental equations for each of

these grid cells simultaneously.

Gridded Eulerian models vary in terms of their mechanistic complexity and

computational intensity. For example, the Regulatory Modeling System for Aerosols and

Deposition (REMSAD) (ICF Kaiser/ SAI, 1998) is a relatively simple three-dimensional

grid-based air quality model which has been reviewed by a panel of experts (Seigneur et

al., 1999a). It has a meteorological pre-processor which reformats MM4 or MM5 model

output for use in the REMSAD system. Emissions inputs must also be generated

externally.

The core Aerosol and Toxics Deposition Model (ATDM) included in REMSAD

is well suited for regional scale deposition modeling due to its grid structure which is

based on latitude and longitude in the horizontal and terrain-following sigma-pressure

coordinates in the vertical.

The REMSAD aerosol module calculates fine particle mass yields by assuming

that the concentrations of certain chemical species are always in the particulate form as

PM2.5. Though a kinematic treatment of aerosol formation is lacking (along with certain

properties such as particle size distribution and water content of particles), REMSAD

performs well in terms of calculating sulfate concentrations (sulfate is assumed to exist

entirely in the particulate phase). However, it is less successful at simulating total

organic PM, nitrate and crustal PM concentrations. Improvements in aerosol inventories

as well as aerosol formation mechanisms included in REMSAD may be necessary to

address these shortcomings.

A particularly useful feature of REMSAD from a regional haze perspective is the

inclusion of a postprocessor, XYVIS, which calculates visibility in deciviews (dv). This

calculation is performed using species-specific extinction efficiencies and a relative

humidity (RH) function developed by the National Park Service. The advantage of this

approach is that the calculations, while not scientifically rigorous, are consistent with the

federal regulations, easing the task of producing demonstrations of reasonable progress.
VII-7

Despite this apparent complexity, REMSAD’s extremely simplified chemistry in

significantly reduces computation time. The simplified chemistry and the lack of aerosol

dynamic modules severely limits REMSAD’s ability to accurately simulate specific

episodes, but this model may nevertheless be appropriate for simulating average

conditions over longer periods of time. It has been suggested (USEPA, 2000) that a yearlong simulation may be needed for regional haze purposes, although it is not clear that

generating a year of validated and properly formatted meteorological data is not an overly

ambitious task.

Currently available emissions inventories for the REMSAD modeling system are

based on USEPA 1996 base year national inventory. These inventories have been

updated at least to 1997 to include primary PM2.5 emissions estimates and speciation of

VOC emissions; however, a review performed for the REMSAD system (Seigneur et al.,

1999a) determined that better emissions inventories will be needed for testing emissions

control strategies related to fine particles.

In contrast to REMSAD, air quality models such as the EPA Models-3

Community Multiscale Air Quality (Models-3/CMAQ)83 modeling system (Byun and

Chin, 1999) or the Urban Airshed Model – Aerosol (UAM-AERO) (Lurmann et al.,

1997) are more appropriate for simulating episodic fine particle events. Due to their

complexity these models are far more computationally demanding and require many

hours of computer time to simulate a single day.

The Urban Airshed Model – Aerosol (UAM-AERO) is based on the Urban

Airshed Model – Variable (UAM-IV) (Scheffe and Morris, 1993) which has been

developed for episodic ozone events. It is an Eulerian, multilayer, nested grid model with

grid spacing typically from 4 to 50 km. The UAM-IV and UAM-AERO models do have

a plume-in-grid module which allows them to properly account for complex chemistry

that occurs immediately downwind of large point sources before diluting the resulting

species into an entire grid cell. UAM-AERO uses the CB-IV chemical mechanism which

contains a fairly complete treatment of gas phase chemistry. In terms of aerosol

dynamics, UAM-AERO uses a sectional representation of particle size distribution. This

approach has been shown to accurately reproduce major features of the particle size

distribution and should be sufficient for visibility studies (Wu et al., 1996) but may have

limited accuracy in terms of studying fine details of the distribution’s evolution (Zhang et

al., 1999).

Models-3/CMAQ is the result of USEPA’s efforts to develop and foster a

community modeling system. The Models-3 software system is intended to provide an

easy-to-use framework for air quality modeling applications and tools for analysis. The

initial release of a beta version of the software (June 1998) has been criticized for its less

than seamless installation and operation. However, the completed framework promises

 

83 USEPA has suggested that Models-3/CMAQ is appropriate for year-long simulations; however, we note

that this may represent a prohibitive task given the significant computation time required for CMAQ’s

more sophisticated chemical mechanisms and aerosol dynamics modules. The same restrictions in regard

to developing year-long meteorological and emissions inputs apply equally to Models-3/CMAQ and longterm models such as REMSAD.
VII-8

to be significantly more powerful than typical air quality models due to its sophisticated

user interface which attempts to simplify and organize the entire simulation process.

Deficiencies in some aspects of the science code for this modeling system have

been noted as well. In order to achieve some computational savings, Models-3/CMAQ

represents the particle size distribution by three gaussian distributions (one for each of the

three modes: nuclei, accumulation, and course) each with a fixed standard deviation.

Zhang et al. (1999) noted that the modal representation used in Models-3/CMAQ has

difficulty accurately representing coagulation and condensation processes due to the use

of a fixed standard deviation for each mode. This study also suggests that Models3/CMAQ (and other air quality models including UAM-AERO) may benefit from an

updated particle nucleation parameterization which is based on gas/particle partitioning

instead of calculated nucleation rates.

A newly released version of Models-3 (August, 2000) promises to rectify many of

these early deficiencies. The Models-3/CMAQ system is intended to evolve over time as

users contribute additional modules and make modifications; however, the current

version of Models-3 is compatible with the output of the MEPPS emission processor and

the MM5 meteorological model. A recent hands-on training of the Lake Michigan Air

Directors Consortium (LADCo) modeling staff left the impression that the Models-3

system offers exciting opportunities in the future and that the data input and output

visualization components are well developed now (LADCo, 2000). This same review,

however, faulted the graphical user interface for being “cumbersome and flawed” and

recommended using the Models-3 system without the interface.

The CMAQ Chemical Transport Model (CCTM) is the centerpiece of the CMAQ

framework. A choice of advection schemes is available for horizontal and vertical

advection. Vertical velocity can be handled either by eddy diffusion, or the Asymmetric

Convective Model (ACM) for convective conditions. Eddy diffusion is used for

horizontal diffusion. Gas phase chemistry is handled by either the RADM2 or CB-IV

mechanisms and can be used with either the Sparse Matrix Vectorized Gear

(SMVGEAR) or the Quasi-Steady State Approximation (QSSA) solver.

Models-3/CMAQ uses the Region Particulate Matter (RPM) aerosol model (based

on RADM) to calculate lognormal distributions of the three modes of particles, ultrafine,

accumulation and course. Cloud processes are also modeled borrowing algorithms from

RADM to model deep convective clouds and shallow clouds at the 36 and 12 km

resolutions. Models-3 does have plume-in-grid capability for gas phase species, and a

plume-in-grid mechanism for PM is under development.

Other Eulerian grid models are available for regional haze planning and may be

preferable to those discussed above. Environ is expected to release the latest version of

CAMx-AERO which some states may prefer to other models. Another model, the UrbanRegional Multiscale (URM) model, has been used in the Southern Appalachian Mountain

Initiative (SAMI) to look at haze in that region. Results so far have shown reasonable

agreement between modeled simulations and observations for aggregate visibility

characteristics averaged over several days (Huber, et al., 2000).
VII-9

B.4 Source Dispersion Models

Another type of model for understanding the distribution of haze forming

particulate matter in the atmosphere is the source dispersion model. CALPUFF (Scire et

al., 1998b, Strimaitis et al., 1998) is a Lagrangian puff model which has recently been

proposed as a USEPA Guideline model for regulatory applications involving long range

transport. This model was designed to assess the impacts of transport, dispersion,

chemical conversion, and wet and dry deposition of SO2 and NOX emissions from point

sources such as power plants (Scire, 2000). Emissions are advected as Gaussian puffs

according to specified meteorological inputs (the output of the CALMET meteorological

system which can be used in a diagnostic or prognostic mode). This is similar to the

approach used for trajectory modeling, but as these puffs are advected, various

parameterizations calculate concentration changes in the puff due to diffusion,

convection, wet and dry deposition, as well as movement over and around complex

terrain features. Impacts on specified receptors are calculated by summing the

contribution from each puff to the receptor site at a given time.

The variety of physical and chemical mechanisms available, including a

particulate module, and the flexibility with regard to the number of potential emission

sources and receptor sites, make this model adaptable for use over regional scales that

encompass a large number of point or area emission sources.

In comparisons with the USEPA’s ISCST3 model, another popular source

dispersion model, CALPUFF was better able to simulate SO2 concentrations due to

power plant emissions (Strimaitis et al., 1998).

Regardless of which source dispersion model is selected, this approach may

provide a powerful demonstration of the impact that emissions have on particulate

concentrations and visibility conditions in Class I areas.

B.5 Receptor Models

The fundamental difference between source models and receptor models is that

receptor models take monitored data as their input and try to determine characteristics of

the sources. Source models assume known sources and try to estimate the future

characteristics (e.g. pollutant levels) usually at monitored sites for comparison. Among

receptor techniques there are both mathematical techniques, predominantly factor

analysis, and ensemble trajectory techniques. Source apportionment modeling is a

mathematical approach to receptor based modeling. Based on monitored concentrations

of speciated PM mass, source apportionment models calculate the compositional profile

of sources which best fit with the observations. When used in conjunction with ensemble

trajectory techniques, location information can also be determined. Some of these

models may also require information regarding likely tracers or compositional profiles

for individual sources in order to isolate their specific contribution to a given observation.

The Chemical Mass Balance (CMB) model (Friedlander, 1973) is regarded as the

origin of this receptor based approach. CMB requires the input of source profiles, or a
VII-10

listing of the chemical composition of emissions due to each source to be investigated.

This technique calculates the contribution of each source to a specific measurement

which provides the best fit to the observed concentrations. While this process is straight

forward for PM2.5 derived from primary emission sources, the use of CMB modeling for

secondary PM constituents is problematic. Techniques are, however, being developed

which allow CMB to deal with this in a limited way that isolates the total mass of

secondary component but cannot apportion it to specific sources.

Though developing accurate source profiles can be a costly and time-consuming

process, the USEPA maintains an archive of source profiles (SPECIATE) on the internet

(http://www.epa.gov/ttn/chief). The most recent version of this model, CMB8, is

expected to be available from USEPA soon and will offer a graphical user interface that

should greatly ease the use of this tool.

A more recent technique employed by receptor models is that of factor analysis or

the closely related principle component analysis (Harmon, 1976). Simply stated, these

techniques calculate not only the best combination of sources needed to match the

observations, but also the individual compositional profiles of each source identified to

contribute to that observed measurement. By looking at all the data, these models can

identify correlations that occur between different species indicating origin from a

common source. Once sources have been identified, these models then proceed to

calculate the contribution of each source to individual measurements. Positive Matrix

Factorization (PMF) (Paatero, 1994) and UNMIX (Henry, 1997) are popular examples of

multivariate receptor models employing the factor analysis and principle component

analysis techniques.

When combined with ensemble trajectory techniques, those measurements that

are dominated by particular sources can be related to geographical source locations. An

example of how these techniques can work together is shown in Figure VII-2 where both

UNMIX and PMF were used to calculate the profiles for sources that affect the Underhill,

Vermont PM monitor. Residence time analysis was used with back trajectories to

determine the most likely geographical area of influence from each source identified by

UNMIX. Potential Source Contribution Function (PSCF) analysis was used with the

PMF results (Poirot et al. 2000). In this figure, seven source profiles were identified by

each of the models (PMF and UNMIX) as contributing substantially to the observed PM

data collected at Underhill. These source profiles have been associated with specific

sources based on the respective modelers’ interpretations of their characteristics:

Midwestern summer and winter coal, woodsmoke, East Coast oil, Canadian Mn

(manganese) sources, soil, and Canadian smelters. Trajectories were then used to

associate the upper 10 percent of daily source contribution for each source with a

geographical region of influence. In general, these two models agree quite well with each

other and have identified regions which likely contribute to the fine particles present in

northern Vermont.
VII-11

Figure VII-2: Factor analysis of 1988-1995 observations at Underhill, VT

(Poirot et al. 2000).

B.6 Trajectory Models

Trajectory models, including ATAD (Atmospheric Transport and Dispersion),

HYSPLIT (Hybrid Single-Particle Lagrangian Integrated Trajectory) and the CAPITA

Monte Carlo, can aid the SIP development process in several ways. These models can be

run in either a foreward direction (starting from source locations) or backward (from

receptor locations). The HYSPLIT and CAPITA models are configured to run from the

archived output of gridded eulerian meteorological models, while ATAD operates

directly from the archived meteorological observations. All three models allow inclusion

of dispersion estimates when run in a forward mode. The CAPITA model also allows

estimated influences of vertical mixing to be included in the backward mode. Large

numbers of backward trajectories from specified receptors can also provide useful input

for a variety of ensemble trajectory assessment techniques, such as cluster analysis and

residence- time analysis discussed in the preceding section.

In general, Lagrangian trajectories can be used to demonstrate the likely origin of

an airmass and, in conjunction with other monitored data, can build a solid case for the

origin of pollutants which contribute to haze. Trajectories can be calculated forward and

backward from multiple source (or receptor) points at different levels of the atmosphere.

Results of such analyses, using the HYSPLIT model (Draxler 1999) are cited earlier in

this report (See Figures III-10 and III-12 in Chapter III). HYSPLIT was also used in
VII-12

conjunction with a source dispersion option to illustrate the impact of 17 midwestern SO2

sources during the mid-July, 1999 episode discussed in Chapter III (see Figure III-19).

For regional haze purposes, it would be extremely useful to develop historical and

continuing archives of backward trajectories from one or more of these models, for each

Class I area for all IMPROVE sample days. This may be an area where the OTC haze

group could work closely with the National Park Service, which has considerable

expertise in the application of these trajectory models and ensemble trajectory assessment

techniques.

The accuracy of trajectory models is highly dependent on the accuracy and

resolution of input meteorological data as well as prevailing conditions (e.g. high vertical

shear is known to significantly reduce trajectory accuracy (Stunder, 1996)). Spatial

(temporal) resolution for currently available meteorological data sets used with the

HYSPLIT model is approximately 80km (1 hour). This may not account for complex

flows in mountainous or coastal areas. Hence, the development of high resolution

meteorological data for the entire domain of interest should be considered.

 A similar technique in an Eulerian framework, region of influence analysis, was

used during the OTAG (Ozone Transport Assessment Group; see footnote 74) process to

sort wind fields by measured pollutant level at a specific site. Averaging wind fields

from times of highest observed pollutant level identifies wind patterns which are most

likely to lead to high pollutant time periods. Figure VII-3 shows a averaged wind vectors

Figure VII-3: Transport vectors averaged over 20 percent highest daily average ozone

concentration as measured in New England.
VII-13

for the 20 percent of days with the highest daily average ozone concentrations as

measured in the New England Region between 1991 and 1995. The source region

associated with these high ozone days is shown in green and clearly reflects the role of

transport in these events.

C. Comparison of Selected Aerosol Modules

Several recent review articles have been written regarding the structure and

performance of air quality models and the aerosol modules used within them. Russell

and Dennis (2000) have just published a critical review of photochemical models in the

recent NARSTO (North American Research Strategy for Tropospheric Ozone)

assessment issue of the journal Atmospheric Environment. Although this article is

primarily focused on models designed for ozone applications, it provides a thorough

overview of model structures and identifies the major features of available aerosol

dynamics routines.

A more complete description of the types of particle models that are available is

given by Seigeur et al. (1999b). This work provides an overview of source models,

including episodic and long-term models, receptor models and other techniques such as

inverse modeling and speciated rollback. Seigneur concludes with recommendations

related to modeling fine particles, however these are more relevant to the proposed PM2.5

standard than to visibility planning as they focus on the modeling of high particulate mass

episodes.

Zhang et al. (1999, 2000) present two more detailed examinations of the aerosol

dynamics and inorganic aerosol thermodynamics modules included in many widely used

air quality models. Coagulation, condensation, nucleation and mass transfer are

compared for six different air quality models. Highly detailed aerosol models (which,

because of their continuous treatment of the particle size distribution, are too

computationally demanding to be used in 3-D air quality models) are taken as “exact” for

comparison purposes. In general, results indicate that the sectional size distribution (used

by models such as CIT, SAQM-AERO and UAM-AERO) is superior at simulating

coagulation and condensation to the modal size distribution representation with fixed

standard deviations. The modal representation (which is used by Models-3) can be

allowed to vary and it is not clear that these deficiencies remain when variable standard

deviations are used. Models produce divergent results when nucleation modules are

compared, suggesting that alternatives to the current parameterizations (which are based

on theoretical nucleation rates for all models) may be needed. An example given is a

parameterization based on relative rates of nucleation and condensation.

In reviewing thermodynamic equilibrium modules, Zhang and coworkers (2000)

found that results between models are generally consistent with two exceptions: during

high nitrate and chloride concentrations, and low to medium relative humidity conditions.

Given the relatively high humidity in the Northeast and Mid-Atlantic and generally lower

levels of nitrate than are found in the western U.S. we simply note that these

discrepancies should be considered when conditions in the region warrant.
VII-14

As the state of aerosol science is advancing rapidly and expected applications for

visibility compliance modeling are several years away, there is a tremendous need for

continued model development as well as for comparative assessments to ensure that

remaining deficiencies are addressed in the near future.

D. Recommended Approach for Modeling Activities

A successful demonstration of reasonable progress may include analyses

generated by one or more of these models (see Figure VII-1) and will, in fact, benefit

from the diversity of information provided by different techniques. Figure VII-4

demonstrates how the use of several different techniques can provide comprehensive

geographic information about the source regions that affect a particular Class I area.

For example, a long-term air quality model, such as REMSAD, might show how a

change over time in the emissions from a number of geographically dispersed sources

would lead to corresponding changes in visibility. A more detailed (and thus more

computationally intensive) air quality model, like UAM-AERO or Models-3/CMAQ,

may be needed to show precise linkages between known emissions and observed fine

particle measurements on shorter time scales. These types of air quality models are

represented by the black grid shown in Figure VII-4.

Figure VII-4: Complementary approach of various modeling techniques.

3-D Eulerian AQ Model Spatial Domain

✘

✘ Class I Area

 Domain for Annual

 or Episodic models

Source Dispersion

Modeling

Trajectory Analysis

Source 

Apportionment

Techniques
VII-15

A source apportionment model such as UNMIX, can be used in conjunction with

an ensemble trajectory approach, like residence time analysis, to identify sources or

source regions whose emissions are associated with a high proportion of particulate

matter observed at monitors in a Class I area. These techniques can effectively

demonstrate the link between specific source regions and fine particles observed in Class

I areas, as depicted by the yellow, red and orange borders shown in Figure VII-4.

Trajectory cluster analysis provides strong qualitative support for any conclusions drawn

from other air quality models by identifying the most common routes of origin for

airmasses which pass over Class I areas (see blue arrows in Figure VII-4).

The impacts of specific sources can be examined using a Lagrangian source

dispersion model, like CALPUFF or HYSPLIT (magenta border in Figure VII-4). This

may be needed to demonstrate the added visibility impairment that could potentially

result from new sources, especially near Class I areas that are already close to natural

visibility conditions on the 20 percent best days.

All of these techniques should be pursued for SIP development; however,

opportunities exist for distributing these activities amongst states to distribute the burden

of modeling activities. In addition to performing model simulations, development of

meteorological grids and emissions inventories should be included among the tasks to be

performed. States should adopt a role within the structure of the regional process

(coordinated through the RPO) to insure that the breadth of analytical techniques will be

explored. This combined effort will result in a comprehensive and robust

characterization of current visibility conditions in the Northeast and Mid-Atlantic regions

and will be necessary to demonstrate reasonable progress toward visibility goals.

The OTC Modeling Committee has developed a technical plan regarding

modeling, data analysis and policy issues related to national air quality standards. This

plan includes a collaborative effort with LADCO and the North Carolina Department of

Environment and Natural Resources to unify regional modeling efforts. Efforts to

develop modeling protocols (e.g. consistent time periods, geographical domains, and

meteorological and emissions input data) will aid states, tribes, FLMS and other RPOs to

work together in creating modeled simulations that are representative of visibility

conditions across the regions. These efforts are consistent with the approach described in

the preceding paragraph and lay the foundation for developing a complete modeling

strategy.
VII-16

References

Alpine Geophysics, The Emissions Modeling System (EMS-95) User’s Guide, Alpine

Geophysics, Inc., Boulder, CO, 1995.

Byun, D.W. and Ching, J.K. S. (Eds.), Science algorithms of the EPA Models-3

Community Multiscale Air Quality (CMAQ) Modeling System, Chapter 4. EPA Report

No. EPA-600/R-99/030, Office of Research and Development, US Environmental

Protection Agency, Washington, D.C., 1999.

Causley, M.C. et al., User’s guide for the Urban Airshed Model, Volume IV: User’s

Manual for the Emissions Preprocessor System, EPA-450/4-90-007D, U.S.

Environmental Protection Agency, Research Triangle Park, NC, 1990.

Draxler, R., HYSPLIT_4 user’s guide, NOAA Technical Memorandum ERL ARL-230,

NOAA Air Resources Laboratory, Silver Spring, MD, June, 1999.

Friedlander, S.K., Chemical element balances and identification of air pollution sources,

Environmental Science and Technology, 7, 235-240, 1973.

Grell, G.A. et al., “A description of the fifth generation Penn State/NCAR mesoscale

model (MM5),” NCAR Technical Note NCAR/TN-398 +STR, 138pp, 1994.

Harmon, H. H., Modern Factor Analysis, third edition revised, University of Chicago

Press, Chicago and London, 1976.

Henry, R.C., History and fundamentals of multivariate air quality receptor models,

Chemometrics and Intelligent Laboratory Systems, 37, 525-530, 1997.

Huber, C., P. Brewer and D. Ducharme, “Visibility Analyses for the Southern

Appalachian Mountains,” Abstracts of the 93rd Annual Conference and Exhibition of the

Air and Waste Management Association, Salt Lake City, Utah, June 18-22, 2000.

ICF Kaiser/SAI, User’s Guide to the Regulatory Modeling System for Aerosols and

Deposition (REMSAD), SYSAPP98-96/42r2, ICF Kaiser/SAI, San Rafael, CA, 1998.

LADCo, Models-3 Review, memorandum issued by Lake Michigan Air Directors

Consortium (LADCo), (Revised), September 25, 2000.

Lurmann, F. W. et al., “Modeling urban and regional aerosols – II. Application to

California’s south coast air basin.” Atmospheric Environment, 31, 2695-2715, 1997.

Paatero, P. and U. Tapper, “Positive Matrix Factorization: a non-negative factor model

with optimal utilization of error estimates of data values,” Environmetrics, 5, 111-126,

1994.
VII-17

Pielke, R.A. et al., “A comprehensive meteorological modeling system – RAMS,”

Meteorology and Atmospheric Physics, 49, 69-91, 1992.

Poirot, R., P. R. Wishinski, P.K. Hopke, and A.V. Polissar, “Sources of Fine Particle

Concentration and Composition in Northern Vermont,” Proceedings of the Air and Waste

Management Association’s International Symposium on Measurement of Toxic and

Related Air Pollutants, Research Triangle Park, NC, September 12-14, 2000.

Russell, A. and Dennis, R., “NARSTO critical review of photochemical models and

modeling,” Atmospheric Environment, 34, 2283-2324, 2000.

Scheffe, R. D. and R. E. Morris, “A review of the development and application of the

Urban Airshed Model,” Atmospheric Environment, 27B, 23-39, 1993.

Scire, J.S., F.R. Robe, M.E. Fernau, and R.J. Yamartino, “A user’s guide for the

CALMET meteorological model (Version 5),” Earth Tech, Inc, Concord, MA, 1998a.

Scire, J.S., D.G. Strimaitis, R.J. Yamartino, and E.M. Insley, “A user’s guide for the

CALPUFF dispersion model (Version 5),” Earth Tech, Inc, Concord, MA, 1998b.

Scire, J.S. “Preliminary Comments on the Report ‘Estimated Public Health Impacts of

Criteria Pollutant Air Emissions from the Salem Harbor and Brayton Point Power

Plants’,” Earth Tech, Inc., Concord, MA, 2000.

Seaman, N.L., “Meteorological modeling for air-quality assessments,” Atmospheric

Environment, 34, 2231-2259, 2000.

Seigneur, C., G. Hidy, I. Tomback, J. Vimont and P. Amar, Scientific Peer-Review of

the Regulatory Modeling System for Aerosols and Deposition (REMSAD), the KEVRIC

Company, October, 1999a.

Seigneur, C., P. Pai, P.K. Hopke, and D. Grosjean, “Modeling atmospheric particulate

matter,” Environmental Science and Technology, 33, 80A-86A, 1999b.

Strimaitis, D.G., J.S. Scire, J.C. Chang, “Evaluation of the CALPUFF Dispersion Model

with two power Plant Data Sets,” Proceedings of the 10th Joint Conference on the

Applications of Air Pollution Meteorology, Phoenix, AZ, 11-16 January, 1998.

Stunder, B.J., “An Assessment of the Quality of Forecast Trajectories,” Journal of

Applied Meteorology, 35, 1996.

USEPA, Guidance for Demonstrating Attainment of Air Quality Goals for PM2.5 and

Regional Haze (draft 1.1), Environmental Protection Agency , Research Triangle Park,

NC, March 2000.
VII-18

Wang, Z.S., Comparison of Three Vertical Diffusion Schemes in the SARMAP Air

Quality Model with Integrated Process Rate Analysis Method and Continuous Process

Copmposition and Source Receptor Methodology, Ph.D. Dissertation, University of

North Carolina, Chapel Hill, NC, 1997.

Wu, X., C. Seigneur, and R.W. Bergstrom, “Evaluation of a sectional representation of

size distributions for calculating aerosol optical properties,” Journal of Geophysical

Research, 101, 19277-19283, 1996.

Zhang, Y., C. Seigneur, J.H. Seinfeld, M.Z. Jacobson, and F.S. Binkowski,

“Simulation of aerosol dynamics: a comparative review of algorithms used in air quality

models,” Aerosol Science and Technology, 31, 487-514, 1999.

Zhang, Y., C. Seigneur, J.H. Seinfeld, M.Z. Jacobson, S.L. Clegg, and F.S. Binkowski

“A comparative review of inorganic aerosol thermodynamic equilibrium modules:

similarities, differences, and their likely causes,” Atmospheric Environment, 34, 117-137,

2000.
VIII-1

VIII. Visibility Monitoring

Visibility is typically thought of as “how far” one can see. However, the enjoyment of

scenic vistas also depends on “how well” one can see. This includes the ability to observe color,

texture, and contrast within the visual range. Given the many attributes of a scene, a variety of

monitoring techniques are used to characterize all aspects of a view, including scene, optical, and

aerosol monitoring. Effective visibility monitoring programs must incorporate aspects of each

technique.

A. Basic Monitoring Techniques

The most direct and comprehensive way to monitor visibility is with photographs and this

approach is often used as part of most visibility monitoring programs. However, given the

variety of air quality, meteorological and lighting conditions that can exist at an individual site, it

can take thousands of photographs to adequately characterize visibility conditions at a particular

location. The Interagency Monitoring of Protected Visual Environments (IMPROVE) program,

for example, recommends taking photographs three times per day for five years in order to

adequately characterize the range of visibility conditions at a single monitoring site. Digital, film

and time-lapse photography are all forms of scene monitoring. Major drawbacks of this

approach, however, are that it does not provide quantitative information regarding visibility and

it is cumbersome to assess, given the variety of conditions that must be subjectively

differentiated.

Optical monitoring provides a quantitative and continuous indicator of visibility

conditions. The most common forms of optical monitoring data are obtained by measuring the

amount of atmospheric scattering and/or absorption of an artificial light source (lamp) of known

luminescence. A major drawback of optical monitoring is that because it measures light and not

the particles affecting light, it provides limited information regarding the types of particles or

emission sources that contribute to visibility impairment.

Aerosol monitoring provides information on particle composition by making direct

measurements and conducting speciation analyses on collected samples. A major drawback of

most current aerosol monitoring programs is that they collect samples averaged over a 24-hour

period every three days, limiting the temporal resolution of subsequent analyses utilizing these

data. Aerosol monitoring also has higher annual operating (lab) costs and is subject to a variety

of biases stemming from the equations that are used to convert speciated quantities of particles to

estimates of visibility conditions. An advantage of both optical and aerosol monitoring

techniques is that natural factors, such as cloud cover and sun angle, do not affect their

measurement.84 In this manner, optical and aerosol instruments do not measure visibility per se,

but measure visual air quality, or that portion of visibility impairment due to air pollution. Since

these techniques typically utilize ground-based instruments, they are not well suited for

 

84 Most optical measurements are affected by rain, fog, and mist. For this reason, optical data collected during

periods with relative humidity in excess of 95 percent (as a surrogate for rain, fog, or mist) are usually flagged as

suspect or invalid.
VIII-2

distinguishing a uniform haze from a surface-level haze. In addition, they may not detect

elevated layers of haze or plume blight.

The transmissometer and nephelometer are the most common instruments used for

optical monitoring. Transmissometers operate over an open path of 1 km to 10 km and measure

total light extinction (bext) by determining the loss of light (due to scattering and absorption of

the intervening atmosphere) from an artificial light source of known luminescence at a fixed

distance. Nephelometers measure light scattering (bscat), which is responsible for most light

extinction in rural areas of the eastern U.S. Nephelometers operate over a very short open path

(few inches) and are easier to install and maintain than transmissometers. However, they

measure only a portion (albeit a large majority) of total light extinction. Light absorption (babs)

can be measured continuously by aethalometers, which measure the intensity of light transmitted

through a filter tape that ambient air has passed through and on which absorbing particles have

collected. Relatively few aethalometers have been deployed in the field, however, and

absorption is typically determined through aerosol measurements or by subtracting nephelometer

data (bscat) from transmissometer data (bext).

Several varieties of instruments are available for aerosol monitoring, but the one

historically used and recommended by USEPA is the IMPROVE monitoring method. This

method employs a set of four aerosol samplers that simultaneously collect a 24-hour sample

every third day onto a variety of filter media. Three of the samplers collect PM2.5 on teflon,

nylon, and quartz filters. This allows for a comprehensive analysis of PM2.5 species by different

laboratory techniques. The fourth sampler collects PM10 on a teflon filter to identify the amount

of coarse mass in the atmosphere, which can have a significant effect on visibility in dusty or

fire-prone areas in the western U.S. Non-IMPROVE aerosol samplers can be used for visibility

monitoring, but it is recommended that they collect samples on teflon, nylon, and quartz filters

and employ the same laboratory techniques (USEPA, 1999). Photographs of a transmissometer,

nephelometer, and IMPROVE aerosol sampling system are provided in Figure VIII-1 (schematic

diagrams of these instruments are shown later in Figure VIII-3, 4, and 5).
VIII-3

Figure VIII-1 Photographs (clockwise from top-left) of a transmissometer, nephelometer,

and IMPROVE aerosol sampling system.

B. USEPA Monitoring Guidance

In June 1999, USEPA issued guidance to provide a written reference for organizations

conducting monitoring of visibility and particulate matter for regulatory, planning, or research

purposes (USEPA, 1999). The guidance focuses on instruments and methods currently in use

and considered by USEPA and IMPROVE as best suited for use at this time. The guidance is

not meant to dictate USEPA monitoring requirements, to define policy, standards, or data

interpretation methods, or to address the human perception of visual air quality. Rather, it

provides a strategic framework for state monitoring programs.

The guidance is written primarily for individuals familiar with aerometric monitoring

principles and those responsible for designing and operating monitoring program to characterize

visibility and/or particulate matter. Table VIII-1 summarizes the seven major sections of the

guidance.
VIII-4

Table VIII-1: Organization and content of USEPA’s visibility monitoring guidance

Section 1 Introduction

Presents the purpose of the Guidance, the Guidance organization, and a summary

of legislative and regulatory requirements that provide the basis for visibility

protection and visibility monitoring.

Section 2 Monitoring program considerations and requirements

Presents visibility definitions and theory, outlines visibility protection goals and

monitoring objectives, how to design a site or network, and how to select and

apply appropriate monitoring, data handling, and analytical methods.

Section 3 Aerosol monitoring

Provides detailed examples of standard operating procedures, including monitoring

of PM10 and PM2.5 (including chemical composition analysis for sulfates, nitrates,

organic and elemental carbon, and primary PM).

Section 4 Optical monitoring

Provides detailed examples of optical monitoring protocols, including

transmissometer and nephelometer monitoring systems.

Section 5 Scene monitoring

Provides detailed examples of scene monitoring protocols, including 35mm and

time-lapse monitoring systems.

Section 6 References

Section 7 Glossary of terms and abbreviations

USEPA’s visibility monitoring guidance identifies six specific objectives to support the

visibility protection regulations for mandatory Class I areas. There are, however, other potential

applications and uses for visibility monitoring data including studies on PM2.5, climatological

effects of fine particles and model verification to name a few. The objectives identified in

USEPA guidance are to:

1. Ensure that high quality, nationally consistent, comparable data are collected by all

monitoring organizations through adoption of standard monitoring protocols;

2. Establish present visual air quality conditions;

3. Identify sources of existing man-made visibility impairment;
VIII-5

4. Document long-term spatial and temporal trends to track progress towards meeting

the long-term goal of no man-made impairment of protected areas;

5. Provide data for New Source Review (NSR) analyses; and

6. Provide data for Prevention of Significant Deterioration (PSD) analyses.

B.1 Additional USEPA Resources

In addition to supporting regional haze and visibility monitoring through the IMPROVE

program (whose role is described in the next section), USEPA has supported the deployment of a

fine particle monitoring network. While the primary purpose of this network is to aid in the

designation and enforcement of a PM2.5 standard (currently under review by the U.S. Supreme

Court), PM2.5 observations provide insights regarding the spatial and temporal patterns of

visibility impairment. An overview of the national PM2.5 monitoring network has been presented

by Sheffe and Bachmann (2000).

The fine particle network consists primarily of 850 Federal Reference Method (FRM) or

Federal Equivalency Method (FEM) samplers to monitor fine particle mass. Of these monitors,

750 are intended for use in determining NAAQS compliance, while another 100 samplers (2 per

state) are to be used in characterizing background and transport.

An additional 200 fine particle mass monitoring sites are to be deployed nationally for

spatial averaging purposes or special studies. Data from these monitors will not be considered

for purposes of NAAQS attainment designations, provided they operate for less than 2 years.

In addition to the FRM samplers, 100 continuous fine particle mass monitors are to be

deployed, of which 52 are to be co-located with FRM monitors in the largest cities (greater than

1,000,000 population). Continuous PM2.5 measurements are intended to provide real-time

estimates of fine particle levels as well as to provide input to public information systems (similar

to current ozone mapping efforts).

Finally, the PM2.5 network will include up to 300 routine chemical speciation sites to

assess long-term trends in the composition of PM2.5. Of these sites, 50 are required to follow a

protocol similar to that used in the IMPROVE program and will exist in mostly urban locations

as part of a “trends” network. States have significant flexibility using the funding for the

remaining 250 speciation sites and are exploring ways to enhance the current state-of-knowledge

regarding the magnitude and trends in fine particle constituents. However, it is expected that

many of these sites will operate in a manner similar to the 50 “trends” sites.

The final component of the national PM2.5 network is the expansion of the IMPROVE

program as described in detail in the following section.

C. The IMPROVE Program

Data from the IMPROVE program represent a crucial input to state and tribal planning

efforts under the 1999 regional haze rule. The IMPROVE program was established, in part, as a

result of a 1985 lawsuit brought by the Environmental Defense Fund (EDF) against the USEPA
VIII-6

which sought to force the Agency to develop Federal Implementation Plans (FIPs) for states

without approved visibility provisions in their SIPs. At that time, only seven SIPs with visibility

provisions were approved pursuant to the 1980 visibility rule.

Between 1986 and 1999 the IMPROVE program was funded jointly by the National Park

Service and USEPA, with USEPA funds coming directly from state Section 105 grants. Since

1999, federal funding has increased to support network expansion. The additional funds are

provided through state Section 103 grants.

The National Park Service manages the IMPROVE program with the support of several

contractors who perform specific components. These contractors include the University of

California at Davis (site selection, filter management, gravimetric and elemental analyses and

database management), the Desert Research Institute (elemental and organic carbon analyses),

the Research Triangle Institute (ion analyses), Atmospheric Resource Specialists, Inc. (optical,

scene and meteorological data collection), and the Cooperative Institute for Research in the

Atmosphere (data analysis and website support).

The IMPROVE program has been extremely successful in meeting its monitoring

objectives. Methods and procedures used in the network form the basis of USEPA’s visibility

monitoring guidance and have had a substantial influence on the design of the national PM2.5

speciation network. Another tribute to IMPROVE’s success is that, with heightened awareness

of particle-related health concerns in urban areas, it continues to be the nation’s best source of

PM2.5 trend and speciated data.

The IMPROVE program will play several important roles in the implementation of the

regional haze rule and PM2.5 standards. These include (Malm, 2000):

• Providing a standard suite of visibility monitoring data (in accordance with USEPA

visibility monitoring guidance) for each mandatory Class I area for establishing

baseline and natural visibility conditions, tracking progress, verifying predictive

models, and providing input for receptor models.

• Providing anchor points for additional routine monitoring, special studies, and

comparisons with other areas;

• Satisfying USEPA requirements for states to monitor PM2.5 at background and

transport locations; and

• Accommodating sites (protocol sites) outside Class I areas, which states may wish to

implement for enhanced visibility or other monitoring purposes. Approximately 10

protocol sites are planned for deployment in the Northeast and Mid-Atlantic states (in

ME, VT, MA, CT, NY and PA).

In addition to routine monitoring, IMPROVE sponsors research to verify measurements

and to improve quality control and operations. It has also provided support to several special

studies. These studies are typically done to improve the attribution of visibility impacts to

various emission sources and may involve time lapse photography, release and measurement of

tracer materials from suspected contributing sources, enhanced surface monitoring, and

measurements taken aboard aircraft. Special studies have involved the Mohave electric

generating station (1992), Shenandoah National Park (1991), northwest Washington (1990), the
VIII-7

Navajo electric generating station (1987-90), and the photographic monitoring of plume blight

from a pulp mill near the Moosehorn Wilderness Area in Maine.

The IMPROVE program is undergoing a significant expansion of its monitoring network,

including some operational changes to help implement the regional haze rule and proposed PM2.5

standards (Pitchford et al., 2000). These include:

• Distribution of new and improved samplers to all IMPROVE and IMPROVE protocol

sites.85 The new samplers have microprocessors and data loggers that will improve

quality control and data capture and enable the transition from Wednesday/Saturday

sampling to every third day sampling;

• Expansion from 30 IMPROVE sites and 40 protocol sites to 110 IMPROVE sites and

at least 23 protocol sites (10 in the Northeast, 8 in the Midwest, and 5 in Arizona).

IMPROVE protocol sites in Maine and New Hampshire will become full IMPROVE

sites as a result of this process;

• Accommodation of protocol sites outside Class I areas (e.g., urban areas);

• Accommodation on the Steering Committee of “associated members” (e.g., states

providing significant contributions to the program);

• Changing the sampling schedule from Wednesday and Saturday to every 3rd day to

coordinate data collection with the PM2.5, PAMS, and toxics networks;

• Providing data and reports on an Internet web site;

• Submitting data to AIRS; and

• Publishing new documents and videotapes for public education.

IMPROVE’s strategy for monitoring all 156 mandatory Class I areas is to cluster areas

that are located close to one another and share the same airshed. Two or more areas are clustered

together if a monitor can be located within 100 km of each area and at an altitude of within 100 ft

or 10% of the minimum and maximum altitudes in both areas (Pitchford, 1998). Some

exceptions to this rule are made on a case-by-case basis. There are two clusters in the Northeast.

The IMPROVE monitor in the Moosehorn Wilderness Area meets the cluster criteria, and

therefore provides valid data for purposes of visibility monitoring in the Roosevelt-Campobello

International Park. The IMPROVE monitor at Camp Dodge, NH slightly violates the elevation

criteria, but has been deemed valid by the IMPROVE Steering Committee to represent a cluster

for the Great Gulf Wilderness Area and the Presidential Range - Dry River Wilderness Area.

Clusters for all Class I areas in the U.S. are provided in Figure VIII-2. As of September 2000, 96

of the 110 clusters have received a new IMPROVE sampler, and most of these have changed

their sampling schedule to one in three days.

 

85 IMPROVE protocol sites use the same samplers and laboratories as IMPROVE sites but do not necessarily follow

the same schedule and siting criteria and may not conduct a full suite of chemical analyses.
VIII-8

Figure VIII-2: Clusters for IMPROVE monitoring of mandatory Class I areas.
VIII-9

Since its inception, the IMPROVE program has been governed by a steering committee

comprised of one representative from each of the following organizations: USEPA, the National

Park Service, the U.S. Forest Service, the U.S. Fish and Wildlife Service, and the Bureau of

Land Management. Efforts by the western states helped bring the Western States Air Rescources

Council (WESTAR), NESCAUM, and STAPPA/ALAPCO onto the Committee in 1990.

MARAMA joined the Committee in 1998 and Arizona was admitted as an associate member in

1999. Other states may also become associate members, depending on their contributions to the

program.

C.1 Anatomy of an IMPROVE Monitoring Site 

Table VIII-2 summarizes the suite of visibility measurements included in the IMPROVE

program. Ideally, a visibility monitoring site would include all such measurements. However,

due to financial and physical constraint, some sites do not host nephelometers and far fewer host

transmissometers. Only two Northeast sites host digital cameras due to the relatively recent

availability of this technology. All sites host aerosol monitors: they are generally easier to

maintain, their data on reconstructed light scattering and light extinction correlate well with

nephelometer and transmissometer data, and they provide additional information on the types of

sources contributing to visibility impairment.

Schematics of a transmissometer, nephelometer, and IMPROVE aerosol sampling system

are shown in Figures VIII-3, VIII-4, and VIII-5. (Photographs of these instruments are provided

above in Figure VIII-1.) The minimum clearance between aerosol sampler inlets and nearby

trees or structures is shown in Figure VIII-6.
VIII-10

Table VIII-2: Summary of visibility measurements at a fully-instrumented IMPROVE monitoring site.

Instrument Type of Visibility

Measurement

Sampling Frequency Notes (Underlines indicate the major components of the reconstructed light

extinction budget from aerosol monitoring.)

Scene Monitoring 35 mm camera Full visual condition

(color, texture, contrast,clarity, visual range)

At least 3 times per day(9 AM, 12 PM, 3 PM)

IMPROVE recommends 5 years of monitoring to capture full range ofconditions and to produce high quality “slide spectrums” to aid in thepresentation and interpretation of quantitative data. Cameras capture elevatedhaze layers and plumes that may be missed by ground-based instruments.

 Time lapse recorder Full visual condition

(color, texture, contrast,clarity, visual range)

At least once perminute

Same as above, except that time-lapse monitoring is done on a case-by-case,special-study basis and is specially suited for capturing the visual dynamics ofplume and meteorological events.

 Digital camera Full visual condition

(color, texture, contrast,clarity, visual range)

Approx every 15 min Same as above, except that resolution begins to degrade when printed at sizes

larger than 5 x 7 inches. Particularly well suited for real-time monitoring,public reporting, and image archival.

Optical Monitoring Transmissometer Light extinction (bext) Continuous Requires open path length of 1-10 km and more maintenance than other types

of visibility monitors. Can be affected by fog/mist/rain and atmosphericturbulence, especially if beam is close to ground. Absolute calibration notpossible.

 Nephelometer Light scattering (bscat) Continuous Easier to compare with aerosol data since both are point (rather than long-path)

measurements. Can be affected by fog/mist/rain. Absolute calibrationpossible.

Aerosol Monitoring Module A (PM2.5 on teflon)

Concentration of PM2.5 mass

Concentration of elements1

Light absorption (babs)2

24-hr average,every 3rd day

Elemental data are used to determine light extinction due to soil and sulfates.

They also indicate the type of sources contributing to impairment.Measurement of hydrogen provides a check on organic carbon assumptions.Light absorption measurements are being re-evaluated. Results are not beingreported until evaluation is complete. Filters are archived at room temperature.

 Module B (PM2.5 on nylon,

 preceded by denuder)

Concentration of ions3 24-hr average,

every 3rd day

Ion data are used to determine light extinction from ammonium nitrate. Sulfate

data provide a check on ammonium sulfate calculated from elemental S.Chloride data provide a check on salt calculated from elemental Na.Denuder removes nitric acid vapor and prevents a positive bias that wouldresult from its deposition on nylon filters. Filters are destroyed by analysis.
VIII-11

Instrument Type of Visibility

Measurement

Sampling Frequency Notes (Underlines indicate the major components of the reconstructed light

extinction budget from aerosol monitoring.)

 Module C (PM2.5 on quartz)

Concentration of elemental and organic carbon4

24-hr average,every 3rd day

Elemental carbon usually accounts for all light absorption in rural areas.

Organic carbon is assumed to comprise 71 percent of organic material by mass.A “punch” is taken from the filters for analysis. Remainder of filter isarchived.

 Module D (PM10 on teflon)

Concentration of PM10 mass

24-hr average,every 3rd day

PM10 data are used to calculate extinction from coarse particles. Filters are

archived at room temperature.

1 Elements with atomic weights from sodium through manganese are measured by Particle-Induced X-ray Emissions (PIXE). Elements with atomic weights

from iron through lead are measured by X-Ray Fluorescence (XRF). Hydrogen is measured simultaneously by Proton Elastic Scattering Analysis (PESA).

2 Light absorption is measured using a Hybrid Integrating Plate and Sphere (HIPS) method, which runs a laser over the filter.3 Ions are measured by ion chromatography.4 Elemental and organic carbon are determined by Thermal Optical Reflectance (TOR). Organic carbon is operationally defined as the amount of carbon

volatilized off the filter by heat in a helium atmosphere. The remaining carbon (volatilized at higher temperatures in the presence of oxygen) is assumed to beelemental carbon. During the heating process, some of the organic carbon may pyrolize (or char) on the filter and only volatilize in the elemental-carbon portionof the analysis. This portion of the “elemental carbon” which should be attributed to organic carbon is determined by monitoring the reflectance of the filter.When the reflectance returns to its initial value (taken prior to heating), then the last of the organic carbon is assumed to have volatilized. No elemental carbon isassumed to have volatilized up to this point.
VIII-12

Figure VIII-3: Schematic of a transmissometer transmitter and receiver station.
VIII-13

Figure VIII-4: Schematic of a nephelometer.
VIII-14

Figure VIII-5: Schematic of an IMPROVE aerosol monitor.
VIII-15

Figure VIII-6: Minimum clearance between aerosol sampler inlets and nearby trees or

structures.

D. History, Status, and Future of Visibility Monitoring in the Northeast and

Mid-Atlantic

Five visibility monitoring sites currently exist in or near mandatory Class I areas in the

Northeast and Mid-Atlantic; their status is summarized in Table VIII-3. Two of the five sites

have historically operated as IMPROVE protocol sites. For this reason, a 35 mm photographic

archive has not been developed for the cluster containing the Moosehorn and RooseveltCampobello areas, and only summertime monitoring has been performed for the cluster

containing the Great Gulf and Presidential-Dry River areas. These sites have recently become

full IMPROVE monitoring sites. All IMPROVE sites are expected to continue operating in

support of the regional haze program.

From 1988 to 1993, the NESCAUM states established a network of seven IMPROVE

protocol sites at non-Class I rural areas. This program, known as NEPART (for Northeast

particle network), included sites at Underhill, VT; Whiteface Mountain, NY; Bridgton, ME; Mt.

Sunapee, NH; Quabbin Reservoir, MA; Mohawk Mountain, CT; and Ringwood, NJ. NEPART

was initiated out of the realization that assessment of visibility and acid deposition was hindered

by a lack of standardized monitoring methods and by measurements that had been conducted

over short periods of time at a spatially limited number of sites. Each NEPART site hosted an

IMPROVE Module A sampler and a PM10 sampler, both of which operated on Wednesdays and

Saturdays (coincident with the IMPROVE schedule) and on every 6th day (coincident with state

criteria pollutant schedules). During the first year of NEPART, two sites (Quabbin Reservoir

and Whiteface Mountain) also hosted a Module C sampler. Initial funding was provided by the

USEPA, while the University of California at Davis provided laboratory analysis for the

remaining years as an in-kind service.
VIII-16

Table VIII-3: History and status of visibility monitoring at mandatory Class I areas in the

Northeast and Mid-Atlantic states.

Site /

Parameter Instrument

Start

Date

End

Date1

Data

Interval

Operating

Period2

Operating

Agency

Moosehorn Wildlife Refuge, ME and Roosevelt-Campobello International Park, NB

 Scene Timelapse 8mm camera 01/88 08/91 1 per min year-round FWS

 Scene Timelapse vid recorder 12/94 1 per min year-round FWS

 Aerosol IMPROVE module A 08/94 24-hr avg year-round FWS

 Aerosol IMPROVE module B 08/94 24-hr avg year-round FWS

 Aerosol IMPROVE module C 08/94 24-hr avg year-round FWS

 Aerosol IMPROVE module D 08/94 24-hr avg year-round FWS

Acadia National Park, ME

 Scene 35 mm camera 01/80 04/95 1+ per day year-round NPS

 Scene Realtime digital camera 07/99 4 per hr year-round NPS

 Standard visual range Teleradiometer 10/79 02/86 1+ per day year-round NPS

 Standard visual range 35 mm camera 03/86 03/87 1+ per day year-round NPS

 Extinction coefficient Transmissometer 11/87 06/93 1-hr avg year-round NPS

 Scattering coefficient Nephelometer 06/93 1-hr avg year-round NPS

 Aerosol Stacked filter unit 09/85 05/86 72-hr avg year-round NPS

 Aerosol Stacked filter unit 09/86 11/87 24-hr avg year-round NPS

 Aerosol IMPROVE module A 03/88 24-hr avg year-round NPS

 Aerosol IMPROVE module B 03/88 24-hr avg year-round NPS

 Aerosol IMPROVE module C 03/88 24-hr avg year-round NPS

 Aerosol IMPROVE module D 03/88 24-hr avg year-round NPS

 Meteorology Relative humidity 11/87 1-hr avg year-round NPS

Great Gulf and Presidential-Dry River Wilderness Areas, NH

 Scene 35 mm camera 09/85 08/96 1+ per day summer USFS

 Standard visual range 35 mm camera 09/85 08/96 1+ per day summer USFS

 Scattering coefficient Nephelometer 06/95 1-hr avg summer3 USFS

 Aerosol IMPROVE module A 06/95 24-hr avg summer3 USFS

 Aerosol IMPROVE module B 06/95 24-hr avg summer3 USFS

 Aerosol IMPROVE module C 06/95 24-hr avg summer3 USFS

 Aerosol IMPROVE module D 06/95 24-hr avg summer3 USFS

 Meteorology Relative humidity 06/95 1-hr avg summer3 USFS

Lye Brook Wilderness Area, VT

 Scene 35 mm camera 05/87 10/91 1+ per day summer USFS

 Standard visual range 35 mm camera 05/87 10/91 1+ per day summer USFS

 Scene 35 mm camera 06/92 04/95 1+ per day summer USFS

 Scattering coefficient Nephelometer 08/93 03/94 1-hr avg year-round USFS

 Scattering coefficient Nephelometer 05/96 1-hr avg summer USFS

 Aerosol IMPROVE module A 03/91 24-hr avg year-round USFS

 Aerosol IMPROVE module B 03/91 24-hr avg year-round USFS

 Aerosol IMPROVE module C 03/91 24-hr avg year-round USFS

 Aerosol IMPROVE module D 03/91 24-hr avg year-round USFS

 Meteorology Relative humidity 08/93 03/94 1-hr avg year-round USFS

 Meteorology Relative humidity 05/96 1-hr avg summer USFS

Brigantine Wildlife Refuge, NJ

 Scene 35 mm camera 01/97 12/93 1+ per day year-round NJ DEP

 Standard visual range 35 mm camera 01/87 12/93 1+ per day year-round NJ DEP

 Scene 35 mm camera 05/92 03/99 1+ per day year-round FWS

 Scattering coefficient Nephelometer 04/93 04/94 1-hr avg year-round FWS

 Aerosol IMPROVE module A 09/91 24-hr avg year-round FWS

 Aerosol IMPROVE module B 09/91 24-hr avg year-round FWS
VIII-17

In 2001, four NEPART sites (Underhill, Bridgton, Quabbin, and Mohawk Mtn.) will be

re-deployed as IMPROVE protocol sites. Six more IMPROVE protocol sites will be deployed

for the first time at Presque Isle, ME; Old Town, ME; Freeport, ME; Cape Cod National

Seashore (Truro), MA; Pinnacle State Park (Addison), NY; and Martha’s Vineyard, MA.

Whiteface Mtn. (a former IMPROVE site) will be another rural site for PM2.5 speciation,

although it won’t be an IMPROVE protocol site.

Upwind of the Northeast, visibility monitoring has occurred at IMPROVE sites located in

Washington, DC (protocol site); Shenandoah National Park, VA; James River Face Wilderness

Area (previously a protocol site), VA; Dolly Sods Wilderness Area, WV; Mammoth Cave

National Park, KY; Shining Rock Wilderness Area, NC; and Great Smoky Mountain National

Park, TN. Also upwind of the northeastern states, PM2.5 mass concentration and some PM2.5

speciation have been measured at seven Clean Air Status and Trends Network (CASTNet) sites.

These sites are located in rural areas of NY, PA, OH, KY, IL, and IN. In 2001, aerosol

monitoring at these sites will change from the CASTNet method (which takes week-long

composites of sulfate and nitrate, but not carbon) to the IMPROVE method (protocol sites). Colocated measurements will be made at one site for at least one year to assess comparability.

Real-time visibility cameras for enhanced monitoring and public outreach purposes are

being deployed at several sites. These sites are being chosen and maintained by NESCAUM as a

coordinated network known as CAMNET (http://www.hazecam.net). The first CAMNET sites

(Acadia National Park, ME and Boston, MA) were launched in the summer of 1999. The Great

Gulf/Presidential-Dry River area was brought on line in the summer of 2000. Plans are

underway to have sites deployed in Hartford, CT and New York City by 2001.

A map of the IMPROVE sites (for mandatory Class I areas), IMPROVE protocol sites

(mostly Midwest CASTNet and Northeast background/transport sites), NEPART sites, and

current and planned CAMNET sites is shown in Figure VIII-7.

Not shown on the map are historic and future visibility monitoring sites that may exist in

Canada. This needs to be further investigated as it is known that PM2.5 has been monitored at

several Canadian locations. Also not shown on the map are several urban speciated PM2.5 sites,

Table VIII-3: History and status of visibility monitoring at mandatory Class I areas in

the Northeast and Mid-Atlantic states, continued.

Site /

Parameter Instrument

Start

Date

End

Date1

Data

Interval

Operating

Period2

Operating

Agency

Aerosol IMPROVE module C 09/91 24-hr avg year-round FWS

 Aerosol IMPROVE module D 09/91 24-hr avg year-round FWS

 Meteorology Relative humidity 04/93 04/94 1-hr avg year round FWS

1

End dates are not provided if parameter is still being measured.

2

Summer typically indicates June - October

3

These parameters will be measured year-round beginning in 2000.

Other notes:

(a) Site histories provided Jim Wagner, Air Resource Specialists, Inc., Air Quality Monitoring History

Database.

(b) Other, non-visibility measurements are made at may of these sites which may be useful for visibility

assessments, such as ozone precursor concentrations, acid deposition, and meteorological variables.
VIII-18

which will be deployed in 2001 and later years. Data from these sites can be used to assess

urban visibility, further verify predictive models, and supplement regional haze analyses (e.g.,

enhance resolution of spatial gradients, distinguish in-region from out-of-region influences, etc.).

Urban PM2.5 speciation samplers are slated for Burlington, VT; Portsmouth, NH; Boston, MA;

Springfield, MA; Providence, RI; Hartford, CT; Rochester, NY; New York, NY; New

Brunswick, NJ; Pittsburgh, PA; Philadelphia, PA; Baltimore, MD; and Washington, DC.

Additional PM2.5 speciation monitors may be deployed depending on state/regional needs and

available resources. Special studies are under way by the USEPA and the IMPROVE program to

assess the comparability of data from these sites with those from IMPROVE sites. Initial results

from IMPROVE samplers co-located with other samplers are encouraging, as shown in

Figure VIII-8. However, the monitoring systems were not run completely independently of each

other – i.e., filters from different samplers were handled by the same operator, in the same

fashion, and analyzed by the same laboratory, whereas they would normally be handled slightly

differently and sent to different laboratories with slightly different machinery and procedures.

Results from completely independent co-located monitors should be available late in 2001.

Figure VIII-7: Visibility monitoring sites in the Northeast and Mid-Atlantic region.

IMPROVE

IMPROVE Protocol Sites

IMPROVE Protocol Sites (former NEPART sites)

IMPROVE Protocol Sites (former CASTNet sites)

Other Rural Speciation Sites

CAMNET sites

Presque

Isle

Moosehorn

Old Town

Acadia

Freeport Bridgton

Mt. Washington

Underhill

Lye Brook

Boston

Truro

Martha’s

Vineyard

Quabbin

Mohawk

Mountain

Seney

Connecticut Hill

(Note: About half these sites will not be operational until early

2001.)

New York

Brigantine

Whiteface Mtn.

Pinnacle Park

Goddard Park

Arendtsville

Quaker

City

Shenandoah

James River Face

Dolly Sods

Linville Gorge

Shining Rock

Cohutta

Great Smoky Mtns

Cadiz Mammoth Cave

Livonia

Bondville
VIII-19

Figure VIII-8: Concentrations of PM2.5 mass, sulfate, nitrate, ammonium, organic carbon, and

elemental carbon as measured by IMPROVE and other speciation samplers in Philadelphia.
VIII-20

E. Monitoring Recommendations

The Northeast and Mid-Atlantic states need to develop a regional monitoring strategy and

update or revise this strategy on an annual basis, as necessary to adequately characterize regional

haze. Specific recommendations are provided for the maintenance and enhancement of CAMNET,

since it is a likely component of any regional haze monitoring strategy.

Regional haze monitoring strategies should provide the following information:

• Track the history and status of visibility and visibility-related monitoring in the

Northeast, Mid-Atlantic, and upwind areas;

• Identify additional monitoring activities that may be warranted, their objectives, and

resource requirements;

• Help coordinate state and FLM monitoring programs to address these additional,

warranted activities; and

• Provide a basis for the monitoring portion of the SIPs.

Tracking the history and status of monitoring activities is accomplished to some extent in this

document. However, better documentation and detail would provide a more appropriate frame of

reference for current and future monitoring and would help in the planning of various air quality

modeling and data analyses.

Additional monitoring activities could extend IMPROVE-type monitoring into transport

corridors, urban vistas, and other locations with scenic resources; provide specialized data for model

verification, receptor model input, and other data analyses; garner such data from other organizations

(e.g., NOAA, NASA, and FAA); and support public outreach activities. The addition of relative

humidity monitoring at IMPROVE and IMPROVE protocol sites would significantly aid in reducing

the current uncertainties associated with this parameter and its effect on reconstructed light

extinction. Measurements of ammonia at select IMPROVE sites would allow researchers to

determine the acidity of deposited aerosol particles under some conditions and should be

investigated. Future field studies focused on understanding haze and its precursors should be sure to

include detailed measurements of indicator species, such as H2O2, HNO3, NOY, NOX and

formaldehyde. These measurements will (1) improve the conceptual model of regional haze in the

Northeast and (2) help evaluate computer models.

With respect to outreach activities, a recommendation can be made at this time to maintain

and enhance CAMNET. Specifically, some of the web site’s pages should be updated, additional

sites should be located in upstate New York and the Mid-Atlantic Region, the web site needs to be

further promoted to the public, and it should be incorporated into standard outreach materials and

activities among state, regional, and federal organizations. An effort should be made by the USEPA

to coordinate real-time visibility web cameras. A few currently exist outside CAMNET that are

oriented towards air pollution (e.g., Great Smoky Mountains and St. Louis), but they vary in quality,

objectives, messages, and geographic coverage. Given the trend in web camera use and burgeoning

activities in regional haze planning, now is the time for USEPA to encourage consistent and

effective use of real-time visibility cameras. Finally, an investigation should be made into making

CAMNET images more interesting and interactive. For example, some web sites merge
VIII-21

photographs from different directions and allow the visitor to “virtually” rotate the camera left and

right (360 degrees) and up and down.
VIII-22

References

Malm, William C., Spatial and Seasonal Patterns and Temporal Variability of Haze and its

Constituents in the United States, Cooperative Institute for Research in the Atmosphere (CIRA),

Colorado State University, Fort Collins, CO, 80523, 2000.

Pitchford, M., IMPROVE Steering Committee Chair, Letter to State and Local Air Quality Agencies,

c/o STAPPA/ALAPCO, dated August 31, 1998.

Pitchford, M., N. Frank, R. Damberg, M. Scruggs, W. Malm, S. Silva, R. Fisher, S. Archer, R.

Poirot, D. Ely, R. Lebens, T. Moore, R. Eldred, and L Ashbaugh, “Expanded IMPROVE Network

for Regional Haze Monitoring,” Abstracts of the 93rd Annual Conference and Exhibition of the Air &

Waste Management Association, Salt Lake City, Utah, June 18-22, 2000.

Scheffe, R. and J. Bachmann, “Overview of National PM2.5 Monitoring Networks,” Atmospheric

observations: helping build the scientific basis for decisions related to airborne particulate matter,

Report of the PM measurements research workshop, Chapel Hill, North Carolina, Eds. D. L.

Albritton and D.S. Greenbaum, Appendix A, July 1998.

USEPA, Visibility Monitoring Guidance, EPA-454/R-99-003, Office of Air Quality Planning and

Standards, Research Triangle Park, NC, June 1999.
IX-1

IX. Social and Economic Considerations

The long-term goal of remedying “any” manmade impairment of visibility in Class I

areas was adopted by Congress in 1977 without reference to technical feasibility or cost-benefit

calculations. Nevertheless, considerations of societal benefit, public welfare, and economic

cost will have an important and inevitable impact on the emission control strategies used to

attain this goal and on the timeliness with which they are implemented. Ultimately, the

willingness of policymakers and the public to support effective regional haze abatement

strategies will depend, in large part, on the perceived benefits associated with improved

visibility. This chapter provides a mostly qualitative overview of visibility-related social and

economic benefits and of available evidence on the public’s willingness to pay for them. It

does not address the economic costs of reducing pollution to achieve these benefits.

While this chapter is focused on the specific benefits of visibility improvement in

northeastern Class I areas, it should be clear from the foregoing chapters that there are

important links between regional haze, fine particle pollution, acid deposition, and (more

indirectly) ozone. Hence, a discussion of visibility benefits is to some extent inseparable from

a discussion of the benefits of addressing these related problems more generally. The final

section of this chapter touches briefly on some of the broader public health and ecosystem

concerns that, along with visibility concerns, are likely to drive fine particle reduction efforts in

the eastern U.S. in the coming years.

To provide context for a discussion of visibility benefits in northeastern Class I areas,

the Chapter turns first to a description of these areas and to the environmental and societal

value they currently provide.

A. Class I Areas in the Northeast and Mid-Atlantic

Federal mandatory Class I areas include: (1) national parks exceeding 6,000 acres; (2)

wilderness areas and national memorial parks exceeding 5,000 acres; and (3) all international

parks, in existence prior to August 7, 1977. The USEPA has identified 156 areas that meet

these criteria and for which visibility was determined to be an “important value.” These areas

include a vast array of ecosystems that are subject to somewhat different management

objectives. Class I areas in the Northeast and Mid-Atlantic include: one national park managed

by the U.S. National Park Service, three wilderness areas managed by the U.S. Forest Service,

two wilderness areas managed by the U.S. Fish and Wildlife Service and one international park

managed by the Roosevelt Campobello International Park Commission (see Table IX-1).

Distinctions between these agencies, and the areas they manage, are described below. In

addition, detailed descriptions of each of the Northeast/Mid-Atlantic Class I areas may be

found in boxed text within each category of management agency. These descriptions are

included to provide the reader with a more concrete sense of the value provided by each of

these areas to the broader Northeast/Mid-Atlantic region in terms of recreation, wildlife and

habitat protection, and other social, economic and environmental benefits.
IX-2

A.1 National Parks

President Woodrow Wilson established the National Park Service (NPS) in 1916 under

the Department of the Interior. At the time, 40 areas of historical, natural or recreational

significance were identified for protection under one managing agency. Today the national

park system encompasses more than 370 areas designated by Congress or the President. The

role of the NPS is:

“To promote and regulate the use of Federal areas known as national parks,

monuments and reservations... by such means and measures as conform to the

fundamental purpose of the said parks, monuments and reservations, which purpose is

to conserve the scenery and the natural and historic objects and the 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.” (National Park

Service Organic Act, 16 U.S.C.1.)

Table IX-1: Class I Areas in the Northeast and Mid-Atlantic.

Class I Area State Management

Agency

Federal

Designation

Year

Designated

Current

Size

(acres)

Acadia Maine National Park

Service

National Park 1919 46,784

Moosehorn Maine Fish and Wildlife

Service

Wilderness Area

of Wildlife

Refuge

1970 (Edmunds

Unit)

1975 (Baring

Unit)

2,780

4,680

Roosevelt

Campobello

New

Brunswick

Roosevelt

Campobello

International

Park

Commission

International

Park

1964 2,800

Great Gulf New

Hampshire

Forest Service Wilderness Area

of National

Forest

1975 5,552

Presidential

Range – Dry

River

New

Hampshire

Forest Service Wilderness Area

of National

Forest

1975 27,380

Brigantine New Jersey Fish and Wildlife

Service

Wilderness Area

of Wildlife

Refuge

1975 6,603

Lye Brook Vermont Forest Service Wilderness Area

of National

Forest

1975 15,680
IX-3

A wide range of recreational activities are permitted on NPS lands. The use of

motorized vehicles, prohibited in many wildlife refuge and wilderness areas, is allowed in

many national parks, which support the use of cars, snowmobiles, mountain bikes, and

recreational vehicle (RV) camping. Parks with sensitive natural and cultural areas may restrict

these activities if they adversely affect or threaten park resources.

Consistent with a national trend toward increased outdoor recreation, visits to national

parks rose from 246 million in 1987 to 275 million in 1996. In that same period, the number of

overnight visitors grew from 16.6 million to 18.3 million (Van Horne, 1999). As a result, some

of the more popular parks now require reservations for overnight visits, or limit the number of

visitors.

Acadia National Park in Maine is the only Class I areas in the Northeast under the

jurisdiction of the NPS. This area is described in Box IX-1. The scenic qualities of this park is

adversely affected by regional haze. For example, Acadia National Park has air pollution

levels similar to those found in Philadelphia, PA, during the summer months when visitation is

highest (Mardock et al, 1999).

Box IX-1: Class I National Parks in the Northeast.

A.2 Wilderness Areas Managed by the Forest Service

Wilderness areas are managed by the U.S. Forest Service, which is part of the

Department of Agriculture. The Forest Service is primarily responsible for managing national

forests and grasslands. It was established by Congress in 1905 to manage the multiple uses and

benefits of public lands. The self-described mission of the Forest Service is “Caring for the

Land and Serving People,” a formulation that suggests a balance between protecting

environmental values and managing commercial and recreational interests.

Acadia National Park, ME

When Acadia National Park was designated in 1919, it was called Lafayette

National Park and was the first national park designated east of the Mississippi River.

Created with 6,000 acres of land, the park changed its name in 1929 and now

encompasses about 40,000 acres of mixed ecology including Atlantic shoreline, mixed

hardwood forests, spruce and fir forests, mountains, lakes and islands. Facilities at the

park include 45 miles of carriage roads for walking and biking with 27 miles of scenic

driving, plus 120 miles of hiking only trails, 2 campgrounds, a restaurant and 3 gift

shops. Acadia averages 3 million visitors each year with the majority visiting during

July and August (almost 700,000 visitors per month) and the fewest during December,

January, and February (almost 38,000 visitors per month). Open year round, Acadia

provides an abundance of recreational opportunities. Fees are $10 per vehicle or $5

per motorbike for 7 days. Additional fees for camping apply and vary from $12-$18

per day throughout the year. The average park visitor stays at Acadia 1-4 days.

(http://www.nps.gov.acad)
IX-4

Any federally protected land can be designated as a wilderness area under the

guidelines of the Wilderness Act of 1964 which describes such areas as:

“Administered for the use and enjoyment of the American people in such

manner as will leave them unimpaired for future use and enjoyment as wilderness...A

wilderness, in contrast with those areas where man and his own works dominate the

landscape, is hereby recognized as an area where the earth and its community of life are

untrammeled by man, where man himself is a visitor who does not remain.” (The

Wilderness Act, 16 U.S.C. 1 1 21)

In wilderness areas, recreation is secondary to preservation. Only those activities that

do not threaten the wild integrity of the area are permitted. Travel is universally limited to

non-mechanical means such as on foot or by horseback. To protect ecosystems, groups are

limited to ten people and quotas or reservation systems may be imposed to limit visitor

impacts. Low-impact recreation is supported within wilderness areas with designated trails and

camping areas. People visit these areas to experience wilderness and to enjoy year-round

activities such as hiking, rock climbing, bird and wildlife watching, hunting, fishing, cross

country skiing and snow shoeing. Since wilderness areas are usually part of larger managed

areas, no direct fees are charged for their use (http://www.wilderness.net).

In the Northeast, the Forest Service manages three Class I wilderness areas: the Great

Gulf and Presidential-Dry River Wilderness areas in New Hampshire’s White Mountain

National Forest and the Lye Brook Wilderness area in Vermont’s Green Mountain National

Forest. Box IX-2 describes these areas.

Class I areas in the White Mountain National Forest are especially affected by poor

visibility. Mt. Washington, the highest mountain in the Northeast, attracts visitors (who can

climb, drive, or ride to the summit) in large part because of the breathtaking views from its

summit. Any action taken to improve visibility in the adjacent Great Gulf and Presidential-Dry

River wilderness areas will affect the vistas from the summit of Mt. Washington. The White

Mountain National Forest is the main tourist attraction in New Hampshire and ranks among the

most popular National Forests in the country with over 6 million visitors annually (U. S. Forest

Service, 2000).

Vermont’s rustic mountain landscapes and quaint New England towns also attract

throngs of visitors each year that support an important tourist-based economy. The Class I Lye

Brook Wilderness area is part of the Green Mountain National Forest, which attracts many of

Vermont’s visitors. Haze reductions targeted at Lye Brook will increase visibility throughout

the Green Mountain National Forest and beyond.
IX-5

Box IX-2: Class I Wilderness Areas Managed by the Forest Service.

Great Gulf Wilderness Area, NH

The Great Gulf Wilderness is located in a unique mountain valley surrounded by

the Presidential Mountain Range. The valley has steep walls rising from 1,100 feet to

1,600 feet above the valley floor. The area includes many rivulets that drain eastward

to the West Fork of the Peabody River. For visitors, the Great Gulf offers 21.3 miles

of marked trails, which offer some of the best views of the ridges and summits of the

Presidential Range -- including Mt. Washington, the tallest peak in the Northeast.

Great Gulf averages 20,128 visitors annually. The area is open for camping below the

tree line most of the year; however, camping is prohibited during the winter when

weather conditions make camping unsafe.

Presidential Range – Dry River Wilderness Area, NH

The Presidential Range-Dry River Wilderness is a rugged expanse of mountains

and valleys located south of Mt. Washington and other peaks in the Presidential

Range, including Mt. Eisenhower and Mt. Monroe. The Wilderness extends over and

beyond the central valley of the Dry River to the Saco River, encompassing numerous

brooks and smaller, heavily forested mountains. As the name suggests, the Dry River

is almost without water by late summer but swells quickly during heavy rains. There

are only ten trails in the wilderness area totaling 46.1 miles in length. This area

receives fewer visitors than Great Gulf (about 7,000 annually), mostly due to its more

remote location. Its southern portion has almost no trails, is very steep and rugged,

and offers a rare degree of solitude.

Lye Brook Wilderness Area, VT

At 15,680 acres, Lye Brook is the second largest wilderness area within the Green

Mountain National Forest. Its main attraction is the series of cascades that make up

Lye Brook Falls, but the surrounding area also has much to offer. Lye Brook features

a diversity of habitats from northern hardwood forests to grassy meadows, and a

scattering of lakes, streams, and bogs. Prospect Rock, a series of cliffs, is popular spot

offering breathtaking views of the whole wilderness. Intertwined with the pristine

natural beauty are remnants of the heavy logging that occurred in the area during the

early 1900s. Lye Brook offers a variety of recreational activities despite the

limitations of its wilderness designation. With only three hiking trails, much of the

land is available for backcountry exploring. Other popular activities are wildlife

watching, hunting (for wild turkey, white tailed deer, black bear and beaver) and, in

the winter, cross-country skiing and snowshoeing.
IX-6

A.3 Wilderness Areas Managed by the Fish and Wildlife Service

Wildlife refuges are managed by the Fish and Wildlife Service (FWS). FWS was

created when the Bureau of Fisheries and the Biological Survey merged in 1940. The Wildlife

Refuge System was established by the National Wildlife Refuge Administration Act of 1966 to

conserve, protect, and enhance fish and wildlife and their habitats. However, the specific

mission of FWS in managing the refuge system remained undefined for more than 30 years.

The National Wildlife Refuge System Improvement Act of 1997 finally defined the FWS’s role

as follows:

“To administer a national network of lands and waters for the

conservation, management, and where appropriate, restoration of

the fish, wildlife, and plant resources and their habitats within the

United States for the benefit of present and future generations of

Americans.” (NWRI Act 1997)

The National Refuge System has grown since its inception to include over 500 refuges,

several thousand Waterfowl Production Areas, and 50 Coordination Areas, that attract nearly

30 million visitors each year. In recent years, growing interest in these areas has prompted

debate over the role of recreation within the refuge system. The National Wildlife Refuge

Administration Act limits public use within refuges to activities “compatible” with the

management of the refuge, but does not clearly define “appropriate compatible use.” The

debate was addressed by the National Wildlife Refuge System Improvement Act of 1997,

which defined “compatible uses” as those that “will not materially interfere with or detract

from the fulfillment of the mission of the [Refuge] System or the purposes of a refuge.”

Recreation within a wildlife refuge is limited to “wildlife-dependent recreation” such as

hunting, fishing, wildlife observation and photography, and environmental education and

interpretation.

Because the primary purpose of the refuge system is to protect the habitat of plant and

animal species, recreational opportunities at specific refuges may be restricted. Two percent of

national wildlife refuges are closed to the public. The Class I areas within wildlife refuges in

the Northeast and Mid-Atlantic are free and open to the public and provide opportunities for

some of the most popular and visibility dependent recreational activities such as bird watching

(U.S. Fish and Wildlife Service, 2000).
IX-7

Box IX-3: Class I Wilderness Areas Managed by the Fish and Wildlife Service.

Moosehorn Wildlife Refuge, ME

Two units, the Baring Unit (17,200 acres) and the Edmunds Unit (7,200 acres),

make up the Moosehorn Wildlife Refuge, which was officially established in 1937.

Within the refuge, a combined 7,460 acres of land (2780 acres from the Edmunds Unit

and 4680 acres from the Baring Unit) are protected as Class I wilderness area. The

refuge includes rocky shores, rolling forested hills, lakes, bogs, and marshes that

provide protected habitat and breeding grounds for migratory land and water birds.

Moosehorn was the first migratory bird refuge to be established in what is now a chain

of refuges extending south to Florida. It features American bald eagles, and the

American woodcock among the more than 220 species of birds that have been spotted

here. While birding is the primary attraction of Moosehorn Refuge, visitors also

utilize over 50 miles of roads and trails for hiking, biking, cross country skiing, and

snowmobiling. Non-motorized boats are also allowed access to streams and lakes in

the refuge for fishing. In November, the refuge is open for white-tailed deer hunting.

Education programs also draw visitors to the refuge, where wildlife biologists invite

visitors to join them on bird banding operations

.(http://www.mainebirding.net/moosehorn/).

Brigantine – Edwin B. Forsythe Wildlife Refuge, NJ

Until 1984, the Brigantine – Edwin B. Forsythe Wildlife Refuge existed as two

distinct refuges. Today, the combined refuge encompasses 42,000 acres of coastal

habitat, over 90 percent of which consists of tidal marshes and meadows. About 6,600

acres of the refuge have been designated Class I wilderness area. The refuge serves as

an important resting and feeding spot for migratory waterfowl including the

endangered piping plover, black skimmer, and least tern; it also provides an ideal

spawning ground and nursery for native fish. The remaining area of the refuge is

dominated by pitch pine, oak forest, and white cedar-red maple swamps which are

home to songbirds, white-tailed deer, box turtles, and other woodland creatures.

The Forsythe Refuge is nationally recognized as one of the East Coast’s premier

birding spots, and hosts around 200,000 visitors each year. In addition, it supports

hiking, biking, and scenic driving with eight miles of roadway, and three groomed

trails. Saltwater fishing, crabbing, clamming from boats, surf fishing, and deer and

waterfowl hunting are allowed during appropriate seasons. The refuge’s visitor center

also serves as a community resource for environmental education programs. Plans

have been made to increase visitor access through the development of new foot trails,

docks, observation platforms, and an updated visitors’ center

(http://www2.nature.nps.gov/ard/fws/brig/forsyth.htm).
IX-8

A.4 International Parks

Only one international park exists and that is Roosevelt Campobello International Park

which is located in New Brunswick, Canada. Because this park is jointly administered by the

U.S. and Canada, its protection falls under the jurisdiction of both countries. International

parks are designated as Class I areas by statute in the regional haze rule and thus are afforded

the same protection as other Class I areas throughout the country. A description of Roosevelt

Campobello International Park is given in Box IX-4.

Box IX-4: International Parks.

B. Economic Benefits of Outdoor Recreation

Since its inception in 1960, the National Survey on Recreation and the Environment

(NSRE) has offered the most complete information regarding outdoor recreation trends in the

U.S. In 1960, the survey estimated that 131 million individuals over the age of 12 participated

in outdoor activities. By 1994-5, this number had increased by 65 percent to 216 million

Roosevelt Campobello International Park, ME

Roosevelt Campobello International Park is the only international park in the

world. The park is located on Campobello island in Canada, but is of historical

significance to the U.S. as the life-long summer home of President Franklin Delano

Roosevelt. U.S. President Lyndon Johnson and Canadian Prime Minister Lester

Pearson established the park on January 22, 1964 by international agreement. The

park remains a symbol of neighborly relations between the U.S. and Canada, and of

the importance of FDR’s achievements to both nations. The Roosevelt Campobello

International Commission manages the park. Commission members are appointed by

the Governor General of the Council of Canada and by the U.S. President. The

agreement splits equally all costs of development, operation, and management

(www.fdr.net).

The park itself is a mixture of historic cottages and scenic natural landscapes.

There are 8.4 miles of scenic roads in the park and 8 miles of walking paths. The

grounds of the park include coastal headlands, rocky shores, beaches, wetlands, fields,

forest, and the landscaped gardens of the cottages. The mix of habitat is excellent for

a variety of migratory and shore birds (Roosevelt Campobello International Park

Commission, 2000). While the historic cottages are only open from Memorial Day to

Columbus Day, the natural areas and visitor center are open year round. This unique

historic, natural area attracts approximately 150,000 visitors annually, with most

arriving in August. The National Park Service recommends visitors plan on 2 to 4

hours to view the cottages, and 8 or more hours for full appreciation of the natural

areas. In addition to the historic setting, several recreational activities are permitted

on the island. There are no admission fees for this park, although donations are

encouraged and accepted.
IX-9

people (Cordell et al., 1999). Of 29 activities covered by the NSRE survey, 23 reported

increased levels of participation since the last survey in 1982-3. For example, the number of

individuals bicycling and skiing more than doubled in a decade. Technology has encouraged

this trend with innovations in sporting equipment allowing people easier access to, and

enhanced enjoyment of, their favorite outdoor activities (Cordell et al., 1999).

Although the aggregate economic impact of outdoor recreation is difficult to calculate,

estimates for specific activities suggest overall trends. Bird watching, for example, has

experienced the greatest gain in participant days of all the activities surveyed in 1982-3 and

1994-5. Birders in the U.S. are estimated to spend $2.5 billion annually on feeders, seed,

baths, nest boxes, binoculars, and field guides. Although many may not leave their backyards,

an estimated 24.7 million birders travel to recreational and wilderness areas in an attempt to

catch glimpses of their favorite species. An avid birder is estimated to spend approximately

$2,000 annually on this hobby, of which half goes toward travel. With about 123,500 serious

birders in the U.S., this equates to a minimum “dedicated birder GNP” of $247 million

(Baicich et al., 1999). Recreational spending of this type can be significant to the economy of

localities near parks or refuge areas. For example, with the influx of 100,000 birders annually

to Cape May, NJ, “avitourism” contributes nearly $10 million dollars to the local economy. At

Hawk Mountain, PA, a “hotspot” for raptor migration viewing, some 500,000 visitors annually

bring $4 million into the local economy.

The following are estimates of activity-specific expenditures related to the use of public

lands (Stegner, 1999a):

 $67.9 billion spent by hunters and anglers in 1996

 $29 billion spent by bird watchers in 1996

 $17.8 billion retail spending on new and used boats and related goods and services

in 1996

 $9.4 billion spent on snow sport-related expenditures annually

 $6.5 billion spent on food and lodging while visiting national wildlife refuges

yearly

 $2.0 billion spent for rentals at commercial campgrounds in 1995

Communities surrounding protected areas often benefit tremendously from the jobs and income

created by the outdoor recreation industry. Non-resident visitors typically contribute to the

local economy in four distinct sectors: lodging, food, retail, and recreation/amusement

services. English and Marcoullier (1999) conducted a study to determine the benefits, by

region, that outdoor recreation contributes to jobs and income for each of these economic

sectors. In the Northeast, 3 percent of all jobs and 1.3 percent of income are related to

recreation. Of all non-local recreational visitor-supported jobs in the U.S., the Northeast

accounts for 40 percent of all jobs in eating and drinking establishments, 36 percent of all

lodging jobs, 38 percent of all retail jobs, and 41 percent of all jobs in recreation services.

Rural counties near Acadia National Park, White Mountain National Forest, and Green
IX-10

Mountain National Forest owe more than 6 percent (double the national average) of jobs in the

area to recreational visitors. A recent study by Abt Associates (2000) estimates that a 10

percent increase in park visitation at Acadia would lead to a $20 million increase in local sales,

$2 million in increased tax revenue and approximately 800 new jobs.

Outdoor recreation on federally managed lands also draws foreign visitors to the U.S.

Surveys of international travelers identified “outdoor-related activities,” and particularly

“visiting parks and forests” as common reasons for coming to the U.S. International travelers

ranked parks, forests, and historic places as highly important factors to consider when planning

their trip, with responses ranging from 91 percent of Venezuelan visitors to 70 percent of

Japanese visitors. International travel to the U.S. has grown 66 percent in the past decade to

become an $89 billion industry (O’Leary, 1999). Interest in natural areas and outdoor

recreation plays an important role in the growth of the tourist industry. In the northeastern

U.S., states with Class I areas attract large numbers of international visitors. In 1995, Maine

ranked 14th in the nation for attracting international visitors with Vermont, New Jersey, and

New Hampshire ranking 15th, 17th and 27th, respectively (O’Leary, 1999).

As interest in outdoor activities grows, demands on public land increase. Between

1986 and 1996, there was a 40 percent increase in visitors to federally managed public lands

(Stenger, 1999b). This increase reflects not only additional people seeking outdoor settings,

but also the expectation visitors have of the quality of the environment managed by federal

agencies. The role of Federal Land Managers (FLMs) is to maintain or improve the quality of

the lands they manage, thereby enhancing park enjoyment and use.

C. Public Perceptions of Visual Air Quality

The benefits of improved visibility in Class I areas depend in part on the public’s ability

to perceive such improvements. Conditions such as object/sky contrast, solar angle, sky color,

cloud cover, and landscape features can all affect an individual’s ability to perceive changes in

visual quality. A layered haze with defined edges affecting only part of the view may be easier

to detect than a uniform haze that has no boundaries and uniformly impairs visibility.

Effective means to quantify discernible visibility change and communicate the link between

pollution levels and visual air quality are needed to generate public support and appreciation of

efforts to address regional haze.

As described in Chapter III, the deciview (dv) is a unit of measure which tends to be

linear with perceived changes in visibility; thus a 1 dv change in visibility reflects a change in

visibility that is just perceptible to the human eye.86 However, the measure itself does not

quantify human responses to perceived visibility changes. For example, studies have shown

that a 1 dv reduction in visibility elicits a different response on hazy days, when overall

contrast is low, than when the same change occurs on a clear day with high overall contrast.

Human judgments about scenic quality are often referred to as perceived visual air quality

(PVAQ). Studies of PVAQ can help researchers to understand those aspects of haze that most

 

86 There is some controversy, however, whether this statement holds for all distances. Certainly there is evidence

that a 1 dv change is perceptible for a target at the distance of the visual range.
IX-11

influence an individual’s assessment of scenic quality and assess the level of visibility change

needed to affect visitor enjoyment.

PVAQ can be measured using a series of photographs and a ranking scale (e.g., from 1

to 10) to rate visual air quality. The pictures show the same scene under various pollutant

levels and different background conditions. This technique allows researchers to relate

perceptions of visibility to quantifiable differences in pollutant levels, relative humidity,

lighting conditions, etc. Ideally, such studies would allow researchers to define one parameter

that would produce equal PVAQ, regardless of other background conditions.

In a study by the National Park Service (Malm, 2000), multiple slides representing best,

worst, and intermediate levels of air quality with various conditions of cloud, snow cover, and

sun angle were shown to volunteer visitor participants. The 10 slides in random order were

shown once to the participant in order to become familiar with the slides and then shown again

to evaluate them. Participants used a scale from poor (1) to good (10) to evaluate the scenes.

As a control to test for accuracy, 15 identical slides were mixed with the evaluation slides. The

results were controlled for factors such as the participant’s education level, age, sex and

location of residence.

The results show a simple linear relationship between the level of scenic contrast and

PVAQ (See Figure IX-1) regardless of the size of the distant feature. This same relationship

held under different lighting conditions (e.g. cloud cover and sun angle). Visitors are just as

likely to notice changes in air quality in the morning as in the afternoon, or on a cloudy day as

on a clear day although ratings of the scenery are generally lower for mornings and cloudy

periods.

When PVAQ is compared to actual particulate concentrations, perceptions of visual

impairment appear to be most sensitive to low concentrations, or when the air is cleaner (see

Figure IX-2). As the air gets dirtier, the PVAQ rating changes little. When distance to the

viewed object is taken into account, the sensitivity of the PVAQ rating in a cleaner

environment is even higher. This suggests that maintaining current visibility conditions on the

20 percent best days may be a challenge, given that some Class I areas experience near pristine

conditions on these days. While comprising only 10 to 15 percent of all people who participate

in outdoor activities, outdoor enthusiasts account for 60 to 90 percent of all visitor days in

federal lands (English et al, 1999). Enthusiasts who repeatedly visit the same area for

recreation may perceive small changes in visibility more readily, and may find anything less

than the visual quality typical of the 20 percent best days to be unacceptable.

PVAQ ratings for photographs of layered haze and plumes show that the color and

position of haze in relation to scenic features can affect perceptions of visual air quality. The

position of plumes in the sky, however, tends to affect perception only when the haze is dark in

color (Malm, 2000).
IX-12

Figure IX-1: Perceived Visual Air Quality (PVAQ) versus contrast (Malm, 2000).

Figure IX-2: Sensitivity of PVAQ to different pollutant levels (Malm 2000).
IX-13

Information garnered by PVAQ surveys regarding human perception of visible air

quality can assist researchers in designing studies to value these changes. Researchers can use

photographs of the same view at the same time of day to control for external factors that may

affect PVAQ, thus limiting the possibility that the value assigned to specific visibility

improvements (e.g. in willingness to pay studies) is representative of anything but air quality.

These studies also give federal land managers information on how visitors perceive the 20

percent best visibility days. The best visibility days tend to get poorer ratings when conditions

are cloudy or when features are shaded.

D. Non-Valued Benefits of Visibility to Outdoor Recreation

The preferences people have for clean air and unhindered visibility represent the kind

of social value that is difficult to translate into dollar figures. Nevertheless, such preferences

play an important role in decisions to visit, stay, or return to Class I areas. The NSRE

identified the most popular outdoor activities as walking/hiking (66.7 percent), viewing a

beach or waterside (62.1 percent), family gatherings (61.8 percent), and sightseeing (56.6

percent). Three of these top four activities are directly affected by visibility. In choosing an

“ideal” outdoor setting for their recreation, almost 80 percent of Americans surveyed

responded that the “quality of scenery” is extremely important. The majority of Americans

(almost 90 percent) agree that scenic beauty is an “important” or “extremely important” value

of wilderness (Cordell et al., 1997). These statistics support the notion that visual quality is a

fundamental component of the value placed by society on maintaining national parks and

wilderness areas.

The Customer Use and Survey Techniques for Operations, Management, Evaluations,

and Research (CUSTOMER) study (Tarrant et al, 1999) measures visitor preferences and

perceptions at a variety of recreational sites in terms of demographic and trip characteristics

(day vs. overnight, first time or repeat visit, etc). Northeastern and mid-Atlantic Class I areas

include the range of settings surveyed in this study, including developed areas (i.e., areas with

services for RVs, picnics, and driving), dispersed areas (i.e., areas that are primarily roadless),

water areas (i.e., lakes, rivers and streams), roadside areas (i.e., areas within 0.5 mile of roads),

and winter settings (i.e., areas with snow and ice-based recreational opportunities). When

asked about visibility (or other visibility related characteristics such as “quality of the

scenery”) respondents consistently identified visibility attributes as among the most important

characteristics of their visit. This finding was independent of trip characteristics or

demographic group (although individuals with high income/education levels tended to give the

highest ratings to visual quality).

Multiple studies at individual national parks corroborate these findings. A survey of

summer visitors to the Grand Canyon, Mesa Verde, Mount Rainier, Great Smoky Mountains,

and Everglades National Parks between 1983 and 1985 asked respondents to rank the

importance of a list of both general and site specific park features (USNPS, 2000). “Clean,

clear air” was rated among the four most important features at all five parks. Additionally,

other scenery related features were rated as “very important.” Overall, the study pointed out

that the visitors to national parks expect first to experience a natural setting, free of pollution,
IX-14

and second, to enjoy the unique features of that park. If park attributes such as “clean, clear

air” deteriorate, so presumably would visitor satisfaction and ultimately visitor attendance.

This NPS 2000 study also asked visitors if they noticed any haze during their stay at the

park and if so, how much. Researchers found that on days when visual range was impaired (as

measured by teleradiometer readings), visitors reported they did notice haze. Visitors who

reported the view to be “very” or “extremely” hazy ranked their satisfaction with the view and

their overall park experience lower than those who noticed only “slight” to “moderate” haze.

Studies of the Great Gulf Wilderness (Hill et al, 2000) found that there is a level at which

visitors find the haze to be “unacceptable.” Most respondents indicated that visibility of 20

deciviews or greater was “unacceptable” for the view from Mt. Jefferson. Researchers have

postulated that the deciview level of unacceptability is relatively high at this site because the

scene depth at Mt. Jefferson is comparatively short at five miles. Visitors at areas with views

spanning a greater distance may have a lower tolerance for haze since distant features would

disappear into the haze much sooner than a scenic feature at close range.

Recently, Acadia National Park conducted a visitor study to: (1) determine visitor

demographics and activity preferences; (2) identify favorable features or qualities of the park;

and (3) solicit public input on Acadia’s primary mission (Littlejohn, 1999). Among other

questions, visitors were asked which activities they had participated in during their visit. Not

unlike the previous studies mentioned, park visitors overwhelmingly cited sightseeing/pleasure

driving (86 percent) and hiking (72 percent). Visitors were asked to rank scenic views, native

plants and animals, recreational opportunities, solitude/quiet, wildness, cultural/historical sites

and resources, clean air, and clean water on a scale from 1 to 5 representing varying levels of

importance from “extremely important” to “not important.” Scenic views (99 percent), clean

air (97 percent), and clean water (96 percent) received the highest ratings of “extremely” or

“very” important. Respondents also indicated that “scenic views” were the most enjoyed

features of their visit from a long list that included both park amenities and specific natural

features. Furthermore, visitors consistently replied that they thought the mission of Acadia

National Park is to “preserve, protect, and maintain the natural beauty.”

Finally, this study also found that most visitors receive information about the park from

previous visits (51 percent), travel/guide books (41 percent), and from friends (40 percent).

This suggests that perceptions of poor visibility can affect not only return trips by the visitors

who experience haze, but their recommendations to friends. This finding is especially

troubling for parks such as Acadia, where the peak visitor season coincides with the worst

season for regional haze.

E. Valuation of Visibility and Related Attributes

Various methods have been developed to assess the economic value of resources such

as forests, biodiversity, clean air and clean water. For example, the worth of a forest could be

calculated as the total market value of the timber it contains. This method is helpful in

measuring the potential use value of an environmental resource, but it is less helpful in

quantifying the value of non-use goods (such as species protection) or indirect use goods (such

as clean air). A technique that is frequently used to quantify the economic value of such goods
IX-15

is called the Contingent Valuation Method (CVM). CVM studies frequently rely on surveys of

the public’s willingness to pay (WTP) to keep a resource or, alternatively, its willingness to

accept compensation (WTA) for the loss of the resource. The results of these surveys can be

highly sensitive to the formulation of survey questions; hence survey instruments must be

carefully designed and tested to limit uncertainties and potential biases. Lack of familiarity

with the resource to be valued, difficulty in understanding the questions, or lack of effort on the

part of respondents can all distort survey results. Despite these difficulties, USEPA, the

Interior Department, and the U.S. Court of Appeals have supported CVM as a viable and

legitimate method for calculating the value of societal benefits associated with environmental

protection (McClelland et al., 1993). Moreover, researchers have found that willingness to pay

estimates generated by the CVM approach are comparable to estimates produced through other

non-use and/or indirect use valuation techniques and can successfully predict actual purchase

behavior (McClelland et al., 1993).

Various CVM studies have been conducted to value changes in air quality, including

the specific attribute of visibility. These studies have been closely scrutinized to assess

uncertainties associated with the survey methods. Chestnut and Rowe (1990) designed a study

to value visibility at different national parks, across multiple regions. The study focuses on

national parks in the Southwest, California, and the Southeast. Participants were asked about

national parks and their personal experiences with them, general attitudes toward

environmental issues, and the importance of visibility specifically. They were also asked how

different visibility conditions would affect their enjoyment of national parks and whether they

would be willing to pay higher prices or taxes to support specific measures to improve

visibility.

Protecting visibility from further degradation ranked as a “high priority” for 72 percent

of respondents. The study also found that 95 percent of respondents believed that their

enjoyment of national parks would increase with improved visibility conditions. The findings

of this study suggest a high level of public support for protecting and preserving “non-use”

resources such as visibility. The following ranked highest among reasons to protect visibility

and other natural values:

• “So there will be areas preserved in their natural condition, even if no one ever

goes there.”

• “To preserve our national heritage.”

• “So there is not development everywhere.”

The study found that the individuals willing to pay for visibility improvement was

correlated with their income level and past or expected visits to the park. The mean per

household value for all of the visibility improvement scenarios presented was $40-$60

annually. The mean is higher for residents of the state where the park is located. The Chestnut

and Rowe study suggests that visual quality is important, not only to park visitors but also to

those who never plan to visit a park themselves. This finding is important, since the economic

burden of implementing control measures is likely to be borne equally by all citizens or

ratepayers in a given region, regardless of whether they use Class I areas or not.
IX-16

A similar study specific to the Great Gulf Wilderness in New Hampshire was

conducted during the summer of 1998 (Hill et al., 2000). Individuals both on and off-site were

surveyed to determine their willingness to accept compensation for worse visibility conditions.

Only 20 percent of the respondents were willing to accept lower electricity costs for hazier

conditions, suggesting that they placed a high value on visual quality. Significantly, 66 percent

of respondents reported that they would cancel future plans to visit the White Mountains if

visibility conditions worsened significantly.

USEPA used Chestnut and Rowe’s estimates of visibility values to calculate the

economic benefits associated with SO2 emission reductions being considered by the Western

Regional Air Partnership (WRAP)(USEPA, 2000). These emissions represent the total

reductions that could be achieved by applying BART controls to all eligible sources in the

WRAP region in order to achieve the region’s 2018 visibility goals. The results of the

Chestnut and Rowe study were transferred to Class I areas in other parts of the country using a

“benefits transfer methodology” that adjusted WTP measures for other populations using

baseline visibility, magnitude of visibility improvement, and household income. The results

suggested that a 170,000 ton reduction in SO2 emissions in the WRAP region would translate

to an annual national willingness to pay of $320 million (1997 dollars). This estimate assumed

higher reported WTP values for states with a Class I area, and lower estimates for states

without a Class I area. USEPA’s conclusions acknowledge that total economic benefit may be

higher because this estimate did not include the benefits of improved visibility in residential

areas around the Class I areas. The analysis also did not account for potential benefits in terms

of reduced damage to structures and materials or ecosystem benefits. Therefore, the total

economic benefit would be likely to exceed $320 million.

Abt Associates (2000) recently completed a study using WTP valuations and an

economic utility function (which balances the tradeoff between household income and

willingness to pay for visibility improvements) to assess the benefit of eliminating emissions

from electric utility generators in terms of visibility improvement. The study found that the

elimination of SO2 and NOX emissions from U.S. power plants would produce $7.7 billion in

national visibility benefits alone. The economic benefit to Maine specifically was estimated to

be $327.8 million, to New Hampshire, $6.0 million, and to Vermont, $600,000 (Abt

Associates, 2000). These figures were based on enhanced recreational value, they do not take

into account other indirect benefits, such as the increase in property values that may accrue to

regions with improved visibility.

F. Related Public Health and Ecosystem Benefits of Reducing Fine Particle

Pollution

As noted in the introduction to this chapter, the potential benefits of improving

visibility in the eastern U.S. are fundamentally intertwined with the benefits of reducing fine

particle pollution more generally, and ambient sulfate levels in particular. Federal visibility

goals cannot be practically achieved – given the regional nature of haze in the eastern U.S. –

without broad-based reductions in fine particles and their precursors. Such reductions will

affect a much larger area than the Class I areas alone, both in terms of human exposure to fine

particle pollution and in terms of ecosystem exposure to acid deposition, nitrogen-related
IX-17

eutrophication, and other environmental impacts associated with haze-forming pollutants.

Further, visibility improvements will accrue at other treasured areas of the region that are not

designated as Class I areas including the Adirondack Mountains, the Allegheny Mountains, the

Cape Cod National Seashore, and beach resorts throughout the region.

Fine particle pollution has been linked by a variety of epidemiological studies to direct

impacts on human health, including premature mortality and morbidity. A number of studies

have demonstrated that elevated levels of fine particle pollution are associated with increased

emergency room and hospital visits, increased respiratory and cardiovascular illness (including

chronic bronchitis and asthma), and increased risk of death. These studies formed the basis of

USEPA’s recent proposal to establish a new NAAQS for fine particulate matter, specifically

particles with a diameter less than 2.5 micrometers or PM2.5. That standard is now under

review by the Supreme Court. Meanwhile, additional studies continue to add weight to the

existing evidence for a direct and substantial relationship between health risks and fine particle

pollution (HEI, 2000).

Importantly, the available epidemiological evidence suggests that there is no

concentration threshold below which fine particle pollution is harmless to human health.

Rather, the relationship between fine particle concentrations and health risks appears to be

linear over the range of concentrations commonly experienced in the eastern U.S. In other

words, a given increase or decrease in fine particle concentrations produces a commensurate

increase or decrease in associated health risks. This finding suggests that any additional

reductions in fine particle pollution that result from efforts to improve visibility conditions in

Class I areas will produce public health benefits, even in areas where particulate levels are

below a future PM2.5 NAAQS. In short, broader public health benefits could add substantially,

in economic terms, to the value placed on visibility improvement at Class I sites per se.

For example, USEPA’s examination of the economic benefits of achieving a 170,000-

ton reduction in SO2 emissions in the WRAP region included an assessment of associated

health benefits. Using concentration-response functions from published epidemiological

studies to estimate the resulting avoidance of premature mortality, chronic bronchitis,

respiratory and cardiovascular hospital admissions, asthma-related emergency room visits,

lower and upper respiratory symptoms and care, asthma attacks, and lost days of work, the

Agency arrived at a figure of roughly $1.3 billion in avoided health costs.87

Another recent study by Abt Associates for the Clean Air Task Force examined the

health benefits of achieving substantial additional reductions in SO2 and NOx emissions from

power plants nationwide (Clean Air Task Force, 2000). The study concluded that reducing

these emissions by 75 percent from 1997 levels could reduce the annual number of premature

deaths associated with current levels of fine particle pollution in the U.S. by 18,000.

Further SO2 and NOx reductions would also have multiple ecosystem benefits. There is

evidence that acid deposition continues to be a problem for sensitive ecosystems in several

northeastern states and that the acid neutralizing capacity (ANC) of soils is continuing to

 

87 Note that possible effects on infant mortality, low birth weight, changes in pulmonary function, chronic

respiratory diseases other than chronic bronchitis, morphological changes, altered host defense mechanisms,

cancer, and non-asthma related respiratory emergency room visits were not considered.
IX-18

decline in many parts of the region (Likens et al., 1996). Meanwhile, nitrate deposition has

been associated with increases in nitrogen-saturated soils, increased toxicity of fish habitats,

impaired health of several plant and tree species, and the proliferation of oxygen-depleting

algae in sensitive bays and estuaries. Finally, further reductions in both NOx and VOC

emissions can help to reduce ozone formation and transport. Ozone has its own human health

and ecosystem impacts; these include decreased lung function and eye irritation in humans, as

well as damage to structures and vegetation.
IX-19

References

Abt Associates, Out of Sight: The Science and Economics of Visibility Impairment, Prepared

for Clean Air Task Force, Boston, MA; Project Manager: Bruce Hill; Abt Associates Inc.

Bethesday, MD, 2000.

Baicich, Paul J., Gregory S. Butcher, and Paul Green, “Trends and Issues in Birding,” Outdoor

Recreation in American Life: A National Assessment of Demand and Supply Trends, H. Ken

Cordell Ed., pg. 242-245, Sagamore Publishing, 1999.

Chestnut, Lauraine G., and Robert D. Rowe, “Preservation Values for Visibility Protection at

the National Parks,” US EPA, CR 813686, 1990.

Clean Air Task Force, Death, Disease & Dirty Power: Mortality and Health Damage Due to

Air Pollution from Power Plants. Boston, MA. October 2000.

Cordell, H. Ken, Jeff Teasley, Greg Super, John C. Berstrom, and Barbara McDonald, Outdoor

Recreation in the United States: Results from the National Survey on Recreation and the

Environment, U.S. Forest Service, 1997.

Cordell, H. Ken, Barbara L. McDonald, R. Jeff Teasley, John C. Bergstrom, Jack Martin, Jim

Bason, and Vernon R. Leeworthy, “Outdoor Recreation Participation Trends,” Outdoor

Recreation in American Life: A National Assessment of Demand and Supply Trends, H. Ken

Cordell Ed., pg. 220-242, Sagamore Publishing, 1999.

English, D. B. K. and D. Marcoullier, “Local Jobs and Income from Outdoor Recreation,”

Outdoor Recreation in American Life: A National Assessment of Demand and Supply Trends,

H. Ken Cordell Ed., pg. 291-294, Sagamore Publishing, 1999.

English, Donald B.K., H. Ken Cordell, and J.M. Bowker, “Implications of this Assessment,”

Outdoor Recreation in American Life: A National Assessment of Demand and Supply Trends,

H. Ken Cordell Ed., pg. 434-440, Sagamore Publishing, 1999.

Health Effects Institute, The National Morbidity, Mortality, and Air Pollution Study (NMAPS),

J. Samet, ed., Health Effects Institute, Cambridge, MA, 2000

Hill, Bruce L., Wendy Harper, John M. Halstead, Thomas H. Stevens, Ina Porras, Kenneth D.

Kimball, “Visitor Perceptions and Valuation of Visibility in the Great Gulf Wilderness, New

Hampshire,” Proceedings : Wilderness Science in a Time of Change, D.N. Cole and S. F.

McCool, Ed. U.S. Department of Agriculture, Forest Service, Rocky Mountain Research

Station, Ogden, UT. Vol. RMRS-P-000, 2000.

Likens, G.E., C.T. Driscoll, and D.C. Busco, “Long Term Effects of Acid Rain: Response and

Recovery of a Forest Ecosystem,” Science, 272, pg. 244-246, 1996.

Littlejohn, Margaret, “Visitor Study” Acadia National Park, Visitor Services Project, 1999.
IX-20

Malm, William C., Introduction to Visibility, Cooperative Institute for Research in the

Atmosphere (CIRA), Colorado State University, Fort Collins, CO, 80523, 2000.

Mardock, Jayne E., Conrad Schneider, and Gina Porreco, “No Escape: Can You Ever Really

‘Get Away’ from the Smog?” Clean Air Network, Clean Air Task Force, 1999.

McClelland, G., William Schulze, Donald Waldman, David Schenk, Julie Irwin, Thomas

Stewart, Leland Deck, and Mark Thayer, “Valuing Eastern Visibility: A Field Test of the

Contingent Valuation Method,” US EPA, CR 815183, 1993.

O’Leary, Joseph, “International Tourism in the United States,” Outdoor Recreation in

American Life: A National Assessment of Demand and Supply Trends, H. Ken Cordell Ed., pg.

294-298, Sagamore Publishing, 1999.

Roosevelt Campobello International Park Commission, “Birds of Campobello,” available

online: http://www.fdr.net, 2000.

Stenger, Richard, “Recent Trends in Consumer Spending and Industry Sales,” Outdoor

Recreation in American Life: A National Assessment of Demand and Supply Trends, H. Ken

Cordell Ed., pg. 287-290, Sagamore Publishing, 1999a.

Stenger, Richard, “Trends in Visits to Federal Areas,” Outdoor Recreation in American Life:

A National Assessment of Demand and Supply Trends, H. Ken Cordell Ed., pg. 282-284,

Sagamore Publishing, 1999b.

Tarrant, Michael A., Erin Smith, and H. Ken Cordell, “Recreation Visitor Preferences for and

Perceptions of Outdoor Recreation Setting Attributes,” Outdoor Recreation in American Life:

A National Assessment of Demand and Supply Trends, H. Ken Cordell Ed., pg. 412-431,

Sagamore Publishing, 1999.

USEPA, 2018 Milestone Benefits Assessment of BART Reductions in 9 Western States, draft,

U.S. Environmental Protection Agency, Office of Air Quality Planning and Standards,

Research Triangle Park, NC, 2000.

U.S. Fish and Wildlife Service, pamphlet, “National Wildlife Refuge System, Profile of the

Refuge System,” 2000.

U.S. Forest Service, available online: http://www.fs.fed.us/r9/white/about_us/index.html, 2000.

USNPS, “Effects of Visual Air Quality on Visitor Experience,” National Park

Service,www2.nature.nps.gov/ard/vis/visitesp.html, 08/15/2000.

Van Horne, Merle, “The National Park Service and Outdoor Recreation in the United States,”

Outdoor Recreation in American Life: A National Assessment of Demand and Supply Trends,

H. Ken Cordell Ed., pg. 55-58, Sagamore Publishing, 1999.
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X. Summary and Recommendations

A. The Problem

Visibility is impaired when particles in the atmosphere scatter and absorb light. A

new regional haze rule issued by the USEPA in 1999 addresses visibility impairment

caused by air pollutants from numerous sources located over a wide geographic area.

The goal of the program is to reduce manmade emissions and incrementally restore

visibility in national parks and wilderness areas to natural conditions no later than 2064.

There are seven Class I areas in the Northeast and Mid-Atlantic covered under the

regional haze rule: Acadia National Park, ME; Brigantine Wildlife Refuge, NJ; Great

Gulf Wilderness Area, NH; Lye Brook Wilderness Area, VT; Moosehorn Wildlife

Refuge, ME; Presidential Range – Dry Gulf Wilderness Area, NH; and the Roosevelt

Campobello International Park, ME. Under natural atmospheric conditions, visibility in

the East would be about 8 deciviews, which is equivalent to a visual range of 60 to 80

miles. Currently, on the worst 20 percent days, visibility at the Class I areas in New

England is about 25 deciviews and about 30 deciviews at the New Jersey site, which is

equivalent to visual range of about 15 to 30 miles. The deciview is the metric used in

USEPA’s regional haze rule to characterize visual quality and track reasonable progress

due to its mostly linear relationship to perceived changes in visibility.

Due to the relatively short length of time that visibility data have been collected in

most areas, it is difficult to determine whether visibility is improving or worsening at

Class I areas in the Northeast and Mid-Atlantic. Acadia National Park, where data has

been collected for the longest period, shows a modest level of improvement for both the

20 percent best and worst visibility days. A similar trend has been observed at the

Washington, DC IMPROVE site.

Sulfates, organic carbon, nitrates, elemental carbon and crustal material are the

main constituents of light-attenuating particles in the atmosphere. Particles can be

directly emitted from industrial, transportation and agricultural sources or formed in the

atmosphere by precursor species that are chemically transformed into the building blocks

of fine particulate matter. In the East, sulfates are the predominant contributor to haze.

Power plants and other industrial facilities are the primary sources of SO2 and NOx, the

precursors for sulfates and nitrates. Highway vehicles and non-road equipment are a

significant source of NOx, organic matter and elemental carbon. Natural contributions to

visibility include crustal materials (e.g., soil dust and sea salt) and biogenic organic

hydrocarbons emitted by vegetation.

The presence of ammonia in the atmosphere aids the formation of sulfate and

nitrate particles and increases the efficiency with which they grow in size. On a per mass

unit basis, sulfates and nitrates are much greater contributors to visibility degradation

than other haze constituents due, in part, to their affinity for water vapor. Under high

relative humidity conditions, these particles can grow rapidly and change from solid to
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liquid phase, significantly enhancing their ability to scatter light and degrade visibility.

Ammonium sulfate accounts for 70 percent to 80 percent of the light extinction occurring

at Class I areas on the worst visibility days in the Northeast and Mid-Atlantic. Under

certain winter conditions, ammonium ion can be preferentially attracted to NOx rather

than SO2, resulting in increased nitrate formation. Even under such winter conditions,

however, sulfates remain the most important source of light extinction at all Class I

locations in the Northeast and Mid-Atlantic.

Organic compounds comprise a significant mass fraction of aerosol particles and

are an important contributor to visibility impairment even though they are assumed to

have a low affinity for water vapor. Better understanding of the composition of organic

aerosol particles remains a key focus for further research and may have a significant

impact on the selection of haze control strategies depending on whether the majority of

organic aerosols found at Class I sites are related to emissions from the transportation

sector or from biogenic sources. Organic aerosol is more prevalent in urban locations, as

evidenced by results from the IMPROVE monitor located in Washington D.C. where the

relative contribution of organics to overall particulate matter is greater than at any of the

Class I areas in the Northeast or Mid-Atlantic. This suggests an important anthropogenic

contribution in urban areas.88

The long range transport of pollutants such as SO2 and NOx in the atmosphere is a

well-established phenomenon with important implications for the regional haze program.

As exemplified by the haze event described in Chapter III, visibility impairment can be

exacerbated by the transport of SO2 and NOx emissions into the Northeast, where they are

chemically transformed into haze constituents.

B. The Importance of Visibility

The sweeping views from the summit of Stratton Mountain in Vermont

(overlooking the Lye Brook Wilderness area to the west) are said to have inspired Benton

MacKaye when he conceived the idea of a scenic hiking route spanning the length of the

Appalachian Mountains along the East Coast (Green Mountain Club, 1999). While the

Appalachian Trail, which extends from Georgia to Maine, might have been created

without the pristine views MacKaye must have experienced that day, this anecdote

speaks to the importance of preserving and improving visibility conditions across the

northeastern U.S.

Over $150 billion are spent annually in the U.S. on recreational activities in or

near federally protected lands. National surveys indicate that 80 percent of Americans

feel that the “quality of scenery” is an extremely important factor in choosing locations

for their outdoor recreational activities. In addition to the psychological impact on

 

88 Note that in the summertime, anthropogenic organic carbon emissions in urban areas combine with NOx

to create tropospheric ozone (smog). Ozone promotes the oxidation of biogenic hydrocarbons into lightscattering secondary organic aerosols. In this way, anthropogenic organic carbon emissions can also have

an indirect effect on the biogenic contribution to visibility impairment in more rural Class I areas.
X-3

visitors at parks and wilderness areas, efforts to improve visibility will provide attendant

public health and environmental benefits throughout the region. Reducing visibility

impairing particulate matter will decrease the incidence of heart and respiratory ailments

and associated premature morbidity and mortality across broad regions of the country

(HEI, 2000). The USEPA estimates that $1.4 billion in public health-related savings

would be realized in the western U.S. if BART controls were implemented consistent

with the 2018 visibility milestone targets for that region (USEPA, 2000). Given higher

pollutant levels and population density, far greater health benefits would be expected

from similar controls on large stationary sources affecting visibility in the East.

Contributors to regional haze including NOx and VOCs, also contribute to

photochemical smog, a pollutant with significant health and welfare implications in the

eastern U.S. The same meteorological processes responsible for secondary aerosol

formation can lead to the photochemical transformation of these precursor species into

ozone and other smog constituents. Even after three decades of emission control

programs, the Northeast and Mid-Atlantic states still suffer from unacceptably high levels

of ozone under certain meteorological conditions. Due to the predominance of

photochemical smog events during summer months, NOx controls for many large point

sources are currently in place from May to September. Nitrates represent a more

significant source of visibility impairment during the winter months in the East. Since

some of the 20 percent worst days occur during the winter at Class I areas in the

Northeast and Mid-Atlantic, examination of conditions leading to wintertime visibility

impairment will have to be considered in order to achieve visibility goals.

The benefits of controlling pollutants that degrade visibility are significant in

terms of other air pollution-related environmental problems. Sulfates and nitrates cause

acid rain which results in: (1) the acidification of surface waters and soils through wet

and dry deposition processes; (2) the depletion of soils’ acid neutralizing capacity as

stored base cations are replaced with acidic ions; and (3) soils suffering from nitrogen

saturation, where the supply of nitrates received through atmospheric deposition

overwhelms the natural ability of plants and microorganisms to utilize it. Dry and wet

nitrate deposition also contributes to nitrification, algal blooms and eutrophication in

critical marine bays and estuaries. For example, Chesapeake Bay receives almost 6

kilograms per hectare per year of wet nitrate deposition from airborne NOx to the serious

detriment of the ecosystem and wildlife within the bay (Cimorelli, 1999).

C. Recommendations

One of the primary goals of this analysis was to identify haze-related issues

needing further research prior to the development of state and tribal implementation

plans. This section summarizes the technical recommendations made in the body of this

report and will help inform the research agenda of the OTC regional planning

organization in the coming years. The recommendations are sorted into the following

categories: basic science, modeling and data analysis, air quality monitoring and

measurement, emission inventories, communication and education, and regulatory
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efforts. It should be noted that these recommendations reflect the views of NESCAUM

and MARAMA staff as members of the OTC RPO and may not accurately represent the

views of individual state agencies or tribes within the RPO.

C.1 Basic Science

Natural background visibility conditions

In order to adequately characterize natural background conditions at Class I areas

and establish viable rate-of-progress goals, forthcoming USEPA guidance on the subject

should address natural variability in a more precise manner. Estimates in this report are

largely based on a study by Federal Land Managers that do not account for the natural

range of particulate forming emissions, meteorological conditions, and relative humidity

experienced in the Northeast and Mid-Atlantic. We encourage the USEPA to develop a

method for calculating the 20 percent best and worst natural visibility conditions for each

Class I area based on monitored relative humidity over an extended period of time. A 20

percent best and 20 percent worst relative humidity value for each season should be

considered. Additional work is also recommended to explore the magnitude of seasonal

changes in biogenic emissions under natural conditions and the resulting impact on

visibility. Finally, further research is needed to better assess the visibility impacts of

marine aerosols on natural conditions at Class I areas in coastal locations.

 Calculating baseline conditions

USEPA also plans to release guidance on tracking reasonable progress toward

visibility goals. This guidance should contain a sensitivity analysis that details the range

of potential errors introduced by the various assumptions that go into the calculation of

reconstructed light extinction.

For example, in calculating visibility conditions from monitored data, it is

recognized that relative humidity plays a significant role in the determination of the 20

percent best and worst visibility days. Monthly relative humidity values should be

developed for each Class I area for both the 20 percent best and worst monitored days.

Data from within the region suggest that using a single monthly average relative humidity

value may bias the selection of the 20 percent best visibility days. Given the strong

influence that humidity has on the optical properties of fine particles, further research

should be focused on determining the accuracy of the relative humidity adjustment factor

assumed in the forthcoming guidance.

Uncertainties also exist with regard to the relationship between the operationally

defined term “organic carbon” (OC) and total organic mass as determined by organic

carbon (OMC). The factor of 1.4 currently used by the IMPROVE program to define this

relationship is based on empirical data. USEPA should evaluate the validity of this factor.

USEPA should also look at the uncertainty introduced by assuming a constant size

distribution, fixed dry scattering coefficients, and a single representative wavelength.
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Secondary Organic Aerosols

Further study is needed to resolve the current uncertainty regarding the

composition of secondary organic aerosol (SOA) and the relative fraction from

anthropogenic versus biogenic sources. The USEPA, through the RPO structure, should

encourage research into the role of biogenic organic compounds in SOA formation. This

may include supporting basic research as well as emission inventory/emission factor

work. Research in this area should also address the affinity of organic fine particulate

matter for water vapor. The hygroscopicity of organic aerosol particles strongly

influences their optical properties and, as the second most abundant constituent of fine

particles in the East, warrant attention. During summer in rural eastern locations,

organics may contribute up to 50 percent of fine particle mass; however, the current

assumption that this fraction of aerosol composition is non-hygroscopic may

underestimate its contribution to visibility degradation during these time periods.

C.2 Modeling and Data Analysis

Computer modeling

Computer model simulations of future fine particle levels will serve as the basis

of state planning efforts. In order to ascertain as much useful information as possible, a

regional modeling strategy is recommended that takes advantage of the multiple

analytical techniques that are or will be available and is coordinated in cooperation with

other regional planning organizations. This strategy is consistent with the approach used

by the OTC modeling committee who, therefore, may be the appropriate group to

develop a regional modeling strategy for haze.

An initial goal of the RPO’s modeling effort will be to establish preliminary

transport source regions for each of the relevant pollutants with regard to each of the

Class I areas in or affected by the Northeast and Mid-Atlantic States. Work is also

needed to evaluate seasonal variability caused by differences in weather patterns, sunlight

and the availability of reactants. While similar work has been done to quantify transport

of acid rain and ozone precursors, this work needs to be updated and refined for the

purposes of the regional haze program.

REMSAD is appropriate for this preliminary work based on the availability of

input data and the relatively short computational time required by this tool compared to

other available models. The computational efficiency of REMSAD is critical given that

the annual, as opposed to episodic, nature of the regional haze problem will require

analyzing entire seasons. In addition, the RPO should develop “in-house” modeling

capabilities with technically superior models (e.g. Models-3/CMAQ) in order to support

the future needs of the member states. This effort will complement fine particle work

being conducted or contemplated by participating states using other models such as

UAM-V, CAMx-AERO, URM, CALPUFF, etc.
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Assess differences in source contributions on best and worst days

Standard trajectory techniques (such as HYSPLIT) should be investigated and

utilized to bundle air trajectories associated with good and poor visibility days as part of

the effort to identify source regions for visibility-impairing pollutants. The National Park

Service has previously performed such an analysis for Acadia National Park. This work

needs to be updated to reflect changes in source region emissions due to new regulatory

requirements and the closure of major sources such as the nickel smelter in Sudbury

Ontario. A similar analysis is needed for other Class I areas in the Northeast and MidAtlantic that may be affected by different source regions than Acadia. Given its location

as the southern-most Class I area in the OTC RPO region, future work should focus on

the Brigantine Wildlife Refuge in New Jersey. The combined source regions for Acadia

and Brigantine should reasonably bound the area of influence for haze-forming pollutants

that affect visibility in Class I areas of the Northeast and Mid-Atlantic. This information

is critical to establishing appropriate modeling domains.

GIS mapping of haze-related data

To make haze related data more accessible, this information should be mapped

and displayed using geographic information systems. This approach will: (1) enable

assessments of spatial and temporal variation in emissions and ambient fine particle

concentrations; (2) provide a means for displaying a range of visibility metrics

simultaneously and provide a better understanding of the relationship among the different

ways of quantifying visual quality; and (3) make these data more accessible to both

policymakers and the public. Ultimately, this technique should prove useful in

explaining the linkages between regional haze and related public health and

environmental issues.

C.3 Air Quality Monitoring and Measurement

A regional monitoring strategy must be developed which focuses on maintaining

existing visibility records and identifying new monitoring activities that can add to these

records. The regional monitoring strategy will necessarily address coordination with the

FLM monitoring programs and provide the basis for SIP development in the future.

Dealing with incomplete monitoring data

Due to instrumentation problems with nitrate measurement, IMPROVE data on

some high particle days is “thrown out” as incomplete. These days are not subsequently

included in the 20 percent worst day calculations. Since nitrates are a relatively small

contributor on most worst-case days, a weighted average nitrate concentration should be

used and the resulting data should be retained as valid. Weighted average nitrate values

can be derived from measured nitrate values on high mass particle days for which valid

data exist.

Sorting IMPROVE data

Total particle weight is not always the best indicator of light extinction.

IMPROVE data should be sorted according to reconstructed total particle light extinction
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rather than gravimetric or reconstructed fine mass. Because of the disproportionate

visibility impairment caused by sulfates and nitrates, a grouping of the best and worst

visibility days may not correspond exactly to a grouping based on mass concentrations.

For example, even though sulfate is the generally the dominant contributor to haze on the

20 percent worst days, sulfate mass on some of those days may be less than that of other

particle constituents, such as organic carbon. In this case, a grouping based on mass

sorting may miss some of the poorest visibility days.

Compile and evaluate regional PM2.5 monitoring data for haze purposes

The IMPROVE network provides a wealth of particulate data for assessing source

contributions and long-term trends. In addition, states are now collecting new PM2.5 data

from an extensive monitoring network, and researchers are establishing new “supersites”

for assessing particulate health impacts in New York City, Baltimore and Pittsburgh. All

these data collection efforts will serve as important sources of information for assessing

speciated particulate compositions, source contributions, and visibility improvement

trends. As such, they will be part of a continuing effort by the RPO to assess PM2.5 in the

context of regional haze. Our regional database should be enhanced by adding these

additional data.

Translate PM-fine data into deciview increments

The OTC RPO’s database of speciated aerosol and relative humidity data in the

Northeast and Mid-Atlantic states should be updated to include calendar year 2000 data.

Sources of relative humidity data and procedures for using those data to calculate

visibility metrics should continue to be explored. Adding relative humidity sensors to the

required instrumentation package at each IMPROVE site is highly recommended.

Deciviews and visual ranges need to be calculated for each aerosol sampling day and

averaged into the appropriate time periods.

Assessment of marine aerosols

A field study is needed to better quantify the role of marine aerosols in haze

formation. The information from such a study would aid in more accurately calculating

natural background conditions at Class I areas at or near the coast. Initial studies should

focus on Acadia National Park, Maine, Moosehorn Wilderness, Maine or Brigantine

Wilderness, New Jersey.

Visibility cameras

The CAMNET initiative involves placing cameras at locations where visual

quality is important. The pictures from these cameras provide an important resource for

educating the public about regional haze. This network must be maintained and should

be expanded to cover all Class I areas in the Northeast and Mid-Atlantic. Additional

effort is needed to maximize the use of the images available from the network. At a

minimum, these sites must be linked to the OTC RPO website. The data from continuous

fine particle monitors should be used in conjunction with the camera images to evaluate

and illustrate the relationship between ambient fine particle concentrations and visibility

throughout the region.
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C.4 Emission Inventories

Ammonia

Given the important role that it plays in the transformation of SO2 and NOx into

sulfate and nitrate, better estimates of ammonia emissions are needed. The regional

ammonia inventory being developed by researchers at Carnegie Mellon University, under

a grant from NESCAUM and MARAMA, is a critical first step in overcoming this

deficiency. The results from this analysis need to be translated into a format useful for

SIP inventories and modeling purposes. State and local air quality agencies should

compare available information for point sources to the CMU inventory and update the

inventory with the most accurate information.

SO2, VOC, and PM2.5

In order to improve modeled estimates of SOA, as discussed above, emission

inventories of VOC, SO2 and PM2.5 must be improved. This report demonstrates the

dominant role of sulfates on both worst and best days. Inventories will need to be

especially sensitive and accurate for modeling the 20 percent best visibility days when

PM2.5 concentrations are only about 2-4 μg/m3 in the Northeastern Class I areas. Given

the importance of sulfate aerosols (for both worst and best days), refinements in SO2

emissions (especially quality assuring the 1999 NET emissions) will be needed.

Similarly, improving biogenic and anthropogenic VOC emissions estimates, improving

primary PM2.5 emissions estimates, and obtaining speciated organic carbon (OC)

measurements will be required.

It appears that better spatial and temporal allocation of emissions as well as more

detailed speciation will be important for regional haze analysis. These aspects of the

inventory are often handled in the emissions modeling or preprocessing phase of air

quality modeling. Increased capability in this area is needed and a distributed approach

may be the best model. As recommended for modeling activities, various states (or

possibly the OTC RPO) should share the responsibility of developing the capability for

emissions modeling and preprocessing.

The OTC RPO should stay abreast of efforts by EPA and other states and regions

to improve estimates of biogenic emissions so that we have access to the best data

available. This can be achieved through coordination with other regional planning

organizations to develop a work plan for improving emissions inventories for regional

planning purposes.

Mobile sources

Highway vehicles and nonroad equipment are significant sources of haze

precursor species. The benefits of the Tier II motor vehicle emission control program,

the 2004 heavy-duty engine rule, and the low sulfur gasoline and diesel regulations with

regard to regional haze must be evaluated and quantified. While the NOx, VOC and PM

benefit projections have been quantified, the impact of these future controls on SO2 and

organic emissions from mobile sources must be better understood.
X-9

Quantification of current emission inventories should be improved by using

MOBILE6 and by improving estimates of particulate emissions from mobile sources.

Improvements in calculation and allocation of vehicle miles traveled (VMT) also need to

be addressed in a regionally coordinated manner.

C.5 Communication and Education

The OTC RPO and states will need to develop communication programs to

educate policymakers, affected industry and the public about the adverse impacts of

regional haze and its linkages with other important public health and environmental

issues. Such outreach will be important to build the political support necessary to achieve

the aggressive visibility goals established by Congress.

C.6 Regulatory Efforts

A detailed technical analysis of USEPA’s proposed BART guidance should be

performed. This analysis should include: (1) a preliminary assessment of source regions

influencing visibility at one or more of Class I areas in the Northeast; (2) an initial

identification of potentially BART-eligible sources; (3) a summary of existing

information regarding SO2 and NOX emissions from these sources; (4) an assessment of

potential control options; and (5) a preliminary analysis of the reductions that might be

achieved from these sources.

D. Conclusion

While regional haze is a new regulatory initiative in the eastern U.S. with

relatively long planning and compliance horizons, much is already known about the

causes of visibility impairment at Class I areas. As detailed in this report, sulfates are far

and away the most significant component of regional haze in this part of the country and

coal-fired utility boilers are the predominant source of sulfate precursor emissions.

The OTC RPO and its counterparts in other regions are tasked with orchestrating

the technical assessment needed to develop cost-effective state and tribal implementation

plans to comply with the regional haze rule. The RPOs, states, and tribes will need

several years of coordinated research to better understand visibility problems and develop

viable solutions. Nevertheless, we start with a reasonably strong understanding of the

major causes of visibility impairment throughout the Northeast and Mid-Atlantic region

and regulatory actions that will likely be needed to remedy the problem. Preliminary

efforts to control SO2 sources that contribute to sulfate aerosol formation in the Northeast

and Mid-Atlantic should not be constrained by the relatively small uncertainties in

quantifying secondary causes of visibility impairment in the region. At the same time,

achieving the ultimate goal of eliminating the impact of manmade pollutants on visibility

in all Class I areas will necessitate a far deeper understanding of the multitude of sources

and the complicated chemistry at play. Developing this level of understanding represents

a significant technical challenge to the RPOs and the individual states and tribes.

Similarly, RPOs and states must effectively educate policymakers, affected industry and
X-10

the public about the adverse impacts of regional haze and its linkages with other

important public health and environmental issues in order to build the understanding

necessary to achieve the aggressive goals established by Congress.
X-11

References

Cimorelli, A. J., C.H. Stahl, A.H., Chow and C. Fernandez, Decision Consequence

Model (DCM): Integrating Environmental Data and Analysis into Real Time Decision

Making, USEPA Region III document number 99-741, 1999.

Green Mountain Club, The Long Trail Guide, twenty-fourth edition, Leahy Press, Inc.

Montpelier, VT, 1999.

Health Effects Institute, The National Morbidity, Mortality, and Air Pollution Study

(NMAPS), J. Samet, ed., Health Effects Institute, Cambridge, MA, 2000

USEPA, 2018 Milestone Benefits Assessment of BART Reductions in 9 Western States,

Draft Report, Office of Air Quality Planning and Standards, U.S. Environmental

Protection Agency, Research Triangle Park, NC, August, 2000.

USEPA. Acid Deposition Standard Feasibility Study Report to Congress. Washington,

DC: Acid Rain Division, Office of Air and Radiation, U.S. EPA, EPA 430-R-95-0001a,

p. 67, October 1995.

Appendix A – Full Text of the Regional Haze Rule

1

[Code of Federal Regulations]

[Title 40, Volume 2, Parts 50 to 51]

[Revised as of July 1, 1997]

From the U.S. Government Printing Office via GPO Access

[CITE: 40CFR51]

 TITLE 40--PROTECTION OF ENVIRONMENT

 CHAPTER I--ENVIRONMENTAL PROTECTION AGENCY

PART 51--REQUIREMENTS FOR PREPARATION, ADOPTION, AND SUBMITTAL OF

IMPLEMENTATION PLANS--Table of Contents

Subpart P--Protection of Visibility

 Authority: Secs. 110, 114, 121, 160-169, 169A, 169B, 301,

and 302 of the Clean Air Act, (42 U.S.C. 7410, 7414, 7421, 7470-

7479, 7491, 7492, 7601, and 7602).

Sec. 51.300 Purpose and applicability.

 (a) Purpose. The primary purposes of this subpart are (1) to

require States to develop programs to assure reasonable progress

toward meeting the national goal of preventing any future, and

remedying any existing, impairment of visibility in mandatory

Class I Federal areas which impairment results from man-made air

pollution, and (2) to establish necessary additional procedures

for new source permit applicants, States, and Federal Land

Managers to use in conducting the visibility impact analysis

required for new sources under §51.166. This subpart sets forth

requirements addressing visibility impairment in its two

principal forms: “reasonably attributable” impairment (i.e.,

impairment attributable to a single source or small group of

sources) and regional haze (i.e. widespread haze from a multitude

of sources which impairs visibility in multiple direction over a

large area).

 (b) Applicability. (1) General Applicability. The provisions

of this subpart are applicable to:

 (i) Each State which has a mandatory Class I Federal area
2

identified in part 81, subpart D, of this title, and 

 (ii) Each State in which there is any source the emissions

from which may reasonably be anticipated to cause or contribute

to any impairment of visibility in any such area.

 (2) The provisions of this subpart pertaining to

implementation plans to address reasonably attributable

visibility impairment are applicable to the following States:

 (i) Alabama

 (ii) Alaska

 (iii) Arizona

 (iv) Arkansas

 (v) California

 (vi) Colorado

 (vii) Florida

 (viii) Georgia

 (ix) Hawaii

 (x) Idaho

 (xi) Kentucky

 (xii) Louisiana

 (xiii) Maine

 (xiv) Michigan

 (xv) Minnesota

 (xvi) Missouri

 (xvii) Montana

 (xviii) Nevada

 (xix) New Hampshire

 (xx) New Jersey

 (xxi) New Mexico

 (xxii) North Carolina

 (xxiii) North Dakota

 (xxiv) Oklahoma

 (xxv) Oregon

 (xxvi) South Carolina

 (xxvii) South Dakota

 (xxviii) Tennessee

 (xxix) Texas

 (xxx) Utah

 (xxxi) Vermont

 (xxxii) Virginia

 (xxxiii) Virgin Islands

 (xxxiv) Washington

 (xxxv) West Virginia

 (xxxvi) Wyoming

(3) The provisions of this subpart pertaining to implementation
3

plans to address regional haze visibility impairment are

applicable to all States as defined in section 302(d) of the

Clean Air Act except Guam, Puerto Rico, American Samoa, and the

Northern Mariana Islands. 

Sec. 51.301 Definitions.

 For purposes of this subpart:

 (a) Adverse impact on visibility means, for purposes of

section 307, visibility 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 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. This term does not include effects on integral

vistas.

 (b) Agency means the U.S. Environmental Protection Agency.

 (c) Best Available Retrofit Technology (BART) means an

emission limitation based on the degree of reduction achievable

through the application of the best system of continuous emission

reduction for each pollutant which is emitted by an existing

stationary facility. The emission limitation must be established,

on a case-by-case basis, taking into consideration the technology

available, the costs of compliance, the energy and nonair quality

environmental impacts of compliance, any pollution control

equipment in use or in existence at the source, the remaining

useful life of the source, and the degree of improvement in

visibility which may reasonably be anticipated to result from the

use of such technology.

 (d) Building, structure, or facility means all of the

pollutant-emitting activities which belong to the same industrial

grouping, are located on one or more contiguous or adjacent

properties, and are under the control of the same person (or

persons under common control). Pollutant-emitting activities must

be considered as part of the same industrial grouping if they

belong to the same Major Group (i.e., which have the same twodigit code) as described in the Standard Industrial

Classification Manual, 1972 as amended by the 1977 Supplement

(U.S. Government Printing Office stock numbers 4101-0066 and 003-

005-00176-0 respectively).
4

 (e) Existing stationary facility means any of the following

stationary sources of air pollutants, including any reconstructed

source, which was not in operation prior to August 7, 1962, and

was in existence on August 7, 1977, and has the potential to emit

250 tons per year or more of any air pollutant. In determining

potential to emit, fugitive emissions, to the extent

quantifiable, must be counted. 

 (1) Fossil-fuel fired steam electric plants of more than 250

million British thermal units per hour heat input,

 (2) Coal cleaning plants (thermal dryers),

 (3) Kraft pulp mills,

 (4) Portland cement plants,

 (5) Primary zinc smelters,

 (6) Iron and steel mill plants,

 (7) Primary aluminum ore reduction plants,

 (8) Primary copper smelters,

 (9) Municipal incinerators capable of charging more than 250

tons of refuse per day,

 (10) Hydrofluoric, sulfuric, and nitric acid plants,

 (11) Petroleum refineries,

 (12) Lime plants,

 (13) Phosphate rock processing plants,

 (14) Coke oven batteries,

 (15) Sulfur recovery plants,

 (16) Carbon black plants (furnace process),

 (17) Primary lead smelters,

 (18) Fuel conversion plants,

 (19) Sintering plants,

 (20) Secondary metal production facilities,

 (21) Chemical process plants,

 (22) Fossil-fuel boilers of more than 250 million British

thermal units per hour heat input,

 (23) Petroleum storage and transfer facilities with a

capacity exceeding 300,000 barrels,

 (24) Taconite ore processing facilities,

 (25) Glass fiber processing plants, and

 (26) Charcoal production facilities.

 (f) Federal Class I area means any Federal land that is

classified or reclassified Class I.

 (g) Federal Land Manager means the Secretary of the

department with authority over the Federal Class I area (or the

Secretary’s designee) or, with respect to Roosevelt-Campobello

International Park, the Chairman of the Roosevelt-Campobello

International Park Commission.
5

 (h) Federally enforceable means all limitations and

conditions which are enforceable by the Administrator under the

Clean Air Act including those requirements developed pursuant to

parts 60 and 61 of this title, requirements within any applicable

State Implementation Plan, and any permit requirements

established pursuant to §51.163 of this chapter or under

regulations approved pursuant to part 51, 52, or 60 of this

title.

 (i) Fixed capital cost means the capital needed to provide

all of the depreciable components.

 (j) Fugitive Emissions means those emissions which could not

reasonably pass through a stack, chimney, vent, or other

functionally equivalent opening.

 (k) In existence means that the owner or operator has

obtained all necessary preconstruction approvals or permits

required by Federal, State, or local air pollution emissions and

air quality laws or regulations and either has (1) begun, or

caused to begin, a continuous program of physical on-site

construction of the facility or (2) entered into binding

agreements or contractual obligations, which cannot be canceled

or modified without substantial loss to the owner or operator, to

undertake a program of construction of the facility to be

completed in a reasonable time.

 (l) Installation means an identifiable piece of process

equipment.

 (m) In operation means engaged in activity related to the

primary design function of the source.

 (n) Integral vista means a view perceived from within the

mandatory Class I Federal area of a specific landmark or panorama

located outside the boundary of the mandatory Class I Federal

area.

 (o) Mandatory Class I Federal Area means any area identified

in part 81, subpart D of this title.

 (p) Major Stationary Source and major modification mean major

stationary source and major modification, respectively, as

defined in §51.166.

 (q) Natural conditions includes naturally occurring phenomena

that reduce visibility as measured in terms of light extinction,

visual range, contrast, or coloration.
6

 (r) Potential to emit means the maximum capacity of a

stationary source to emit a pollutant under its physical and

operational design. Any physical or operational limitation on the

capacity of the source to emit a pollutant including air

pollution control equipment and restrictions on hours of

operation or on the type or amount of material combusted, stored,

or processed, shall be treated as part of its design if the

limitation or the effect it would have on emissions is federally

enforceable. Secondary emissions do not count in determining the

potential to emit of a stationary source.

 (s) Reasonably attributable means attributable by visual

observation or any other technique the State deems appropriate.

 (t) Reconstruction will be presumed to have taken place where

the fixed capital cost of the new component exceeds 50 percent of

the fixed capital cost of a comparable entirely new source. Any

final decision as to whether reconstruction has occurred must be

made in accordance with the provisions of Sec. 60.15 (f) (1)

through (3) of this title.

 (u) Secondary emissions means emissions which occur as a

result of the construction or operation of an existing stationary

facility but do not come from the existing stationary facility.

Secondary emissions may include, but are not limited to,

emissions from ships or trains coming to or from the existing

stationary facility.

 (v) Significant impairment means, for purposes of section

303, visibility impairment which, in the judgment of the

Administrator, interferes with the management, protection,

preservation, or enjoyment of the visitor's visual experience of

the mandatory Class I Federal area. This determination must be

made on a case-by-case basis taking into account the geographic

extent, intensity, duration, frequency and time of the visibility

impairment, and how these factors correlate with (1) times of

visitor use of the mandatory Class I Federal area, and (2) the

frequency and timing of natural conditions that reduce

visibility.

 (w) Stationary Source means any building, structure,

facility, or installation which emits or may emit any air

pollutant.

 (x) Visibility impairment means any humanly perceptible

change in visibility (light extinction, visual range, contrast,

coloration) from that which would have existed under natural

conditions.
7

 (y) Visibility in any mandatory Class I Federal area includes

any integral vista associated with that area.

 (z) Reasonably attributable visibility impairment means 

visibility impairment that is caused by the emission of air

pollutants from one, or a small number of sources. 

 (aa) Regional haze means visibility impairment that is caused

by the emission of air pollutants from numerous sources located

over a wide geographic area. Such sources include, but are not

limited to, major and minor stationary sources, mobile sources,

and area sources. 

 (bb) Deciview means a measurement of visibility impairment. 

A deciview is a haze index derived from calculated light

extinction, such that uniform changes in haziness correspond to

uniform incremental changes in perception across the entire range

of conditions, from pristine to highly impaired. The deciview

haze index is calculated based on the following equation:

 deciview haze index = 10 lne(bext/10 Mm ). -1

where bext = atmospheric light extinction coefficient 

For the purposes of calculating deciview for this regulation, the

atmospheric light extinction coefficient must be calculated from

aerosol measurements.

 (cc) State means “State” as defined in section 302(d) of the

Clean Air Act.

 (dd) Most impaired days means the average visibility

impairment (measured in deciviews) for the twenty percent of

monitored days in a calendar year with the highest amount of

visibility impairment.

 (ee) Least impaired days means the average visibility

impairment (measured in deciviews) for the twenty percent of

monitored days in a calendar year with the lowest amount of

visibility impairment. 

 (ff) Implementation plan means, for the purposes of this

part, any State Implementation Plan, Federal Implementation Plan,

or Tribal Implementation Plan.

 (gg) Indian tribe or Tribe means any Indian tribe, band,

nation, or other organized group or community, including any

Alaska Native village, which is federally recognized as eligible

for the special programs and services provided by the United

States to Indians because of their status as Indians.
8

(hh) BART-eligible source means an existing stationary

facility as defined in section 51.301(e). 

(ii) Geographic enhancement for the purpose of section 308

means a method, procedure, or process to allow a broad regional

strategy, such as an emissions trading program designed to

achieve greater reasonable progress than BART for regional haze,

to accomodate BART for reasonably attributable impairment.

Sec. 51.302 Implementation control strategies for reasonably

attributable visibility impairment.

 (a) Plan Revision Procedures. (1) Each State identified in

section 300(b)(2) must have submitted, not later than September

2, 1981, an implementation plan meeting the requirements of this

subpart pertaining to reasonably attributable visibility

impairment.

 (2) (i) The State, prior to adoption of any implementation

plan to address reasonably attributable impairment required by

this subpart, must conduct one or more public hearings on such

plan in accordance with §51.102.

 (ii) In addition to the requirements in §51.102, the State

must provide written notification of such hearings to each

affected Federal Land Manager, and other affected States, and

must state where the public can inspect a summary prepared by the

Federal Land Managers of their conclusions and recommendations,

if any, on the proposed plan revision.

 (3) Submission of plans as required by this subpart must be

conducted in accordance with the procedures in §51.103.

 (b) State and Federal Land Manager Coordination. (1) The

State must identify to the Federal Land Managers, in writing and

within 30 days of the promulgation of these regulations, the

title of the official to which the Federal Land Manager of any

mandatory Class I Federal area can submit a recommendation on the

implementation of this subpart including, but not limited to:

 (i) A list of integral vistas that are to be listed by the

State for the purpose of implementing section 304,

 (ii) Identification of impairment of visibility in any

mandatory Class I Federal area(s), and

 (iii) Identification of elements for inclusion in the

visibility monitoring strategy required by §51.305.
9

 (2) The State must provide opportunity for consultation, in

person and at least 60 days prior to holding any public hearing

on the plan, with the Federal Land Manager on the proposed SIP

revision required by this subpart. This consultation must include

the opportunity for the affected Federal Land Managers to discuss

their:

 (i) Assessment of impairment of visibility in any mandatory

Class I Federal area, and

 (ii) Recommendations on the development of the long-term

strategy.

 (3) The plan must provide procedures for continuing

consultation between the State and Federal Land Manager on the

implementation of the visibility protection program required by

this subpart.

 (c) General Plan Requirements for reasonably attributable

visibility impairment. 

 (1) The affected Federal Land Manager may certify to the

State, at any time, that there exists reasonably attributable

impairment of visibility in any mandatory Class I Federal area.

 (2) The plan must contain the following to address reasonably

attributable impairment:

 (i) A long-term (10-15 years) strategy, as specified in

section 305 and section 306, including such emission limitations,

schedules of compliance, and such other measures including

schedules for the implementation of the elements of the long-term

strategy as may be necessary to make reasonable progress toward

the national goal specified in section 300(a).

 (ii) An assessment of visibility impairment and a discussion

of how each element of the plan relates to the preventing of

future or remedying of existing impairment of visibility in any

mandatory Class I Federal area within the State.

 (iii) Emission limitations representing BART and schedules

for compliance with BART for each existing stationary facility

identified according to paragraph (c)(4) of this section.

 (3) The plan must require each source to maintain control

equipment required by this subpart and establish procedures to

ensure such control equipment is properly operated and

maintained.
10

 (4) For any existing reasonably attributable visibility

impairment the Federal Land Manager certifies to the State under

paragraph (c)(1) of this section, at least 6 months prior to plan

submission or revision:

 (i) The State must identify and analyze for BART each

existing stationary facility which may reasonably be anticipated

to cause or contribute to impairment of visibility in any

mandatory Class I Federal area where the impairment in the

mandatory Class I Federal area is reasonably attributable to that

existing stationary facility. The State need not consider any

integral vista the Federal Land Manager did not identify pursuant

to section 304(b) at least 6 months before plan submission.

 (ii) If the State determines that technological or economic

limitations on the applicability of measurement methodology to a

particular existing stationary facility would make the imposition

of an emission standard infeasible it may instead prescribe a

design, equipment, work practice, or other operational standard,

or combination thereof, to require the application of BART. Such

standard, to the degree possible, is to set forth the emission

reduction to be achieved by implementation of such design,

equipment, work practice or operation, and must provide for

compliance by means which achieve equivalent results.

 (iii) BART must be determined for fossil-fuel fired

generating plants having a total generating capacity in excess of

750 megawatts pursuant to ``Guidelines for Determining Best

Available Retrofit Technology for Coal-fired Power Plants and

Other Existing Stationary Facilities'' (1980), which is

incorporated by reference, exclusive of appendix E, which was

published in the Federal Register on February 6, 1980 (45 FR

8210). It is EPA publication No. 450/3-80-009b and is for sale

from the U.S. Department of Commerce, National Technical

Information Service, 5285 Port Royal Road, Springfield, Virginia

22161. It is also available for inspection at the Office of the

Federal Register Information Center, 800 North Capitol NW., suite

700, Washington, DC.

 (iv) The plan must require that each existing stationary

facility required to install and operate BART do so as

expeditiously as practicable but in no case later than five years

after plan approval or revision.

 (v) The plan must provide for a BART analysis of any existing

stationary facility that might cause or contribute to impairment

of visibility in any mandatory Class I Federal area identified
11

under this paragraph (c)(4) at such times, as determined by the

Administrator, as new technology for control of the pollutant

becomes reasonably available if:

 (A) The pollutant is emitted by that existing stationary

facility,

 (B) Controls representing BART for the pollutant have not

previously been required under this subpart, and

 (C) The impairment of visibility in any mandatory Class I

Federal area is reasonably attributable to the emissions of that

pollutant.

Sec. 51.303 Exemptions from control.

 (a) (1) Any existing stationary facility subject to the

requirement under §51.302 to install, operate, and maintain BART

may apply to the Administrator for an exemption from that

requirement.

 (2) An application under this section must include all

available documentation relevant to the impact of the source's

emissions on visibility in any mandatory Class I Federal area and

a demonstration by the existing stationary facility that it does

not or will not, by itself or in combination with other sources,

emit any air pollutant which may be reasonably anticipated to

cause or contribute to a significant impairment of visibility in

any mandatory Class I Federal area.

 (b) Any fossil-fuel fired power plant with a total generating

capacity of 750 megawatts or more may receive an exemption from

BART only if the owner or operator of such power plant

demonstrates to the satisfaction of the Administrator that such

power plant is located at such a distance from all mandatory

Class I Federal areas that such power plant does not or will not,

by itself or in combination with other sources, emit any air

pollutant which may reasonably be anticipated to cause or

contribute to significant impairment of visibility in any such

mandatory Class I Federal area.

 (c) Application under this §51.303 must be accompanied by a

written concurrence from the State with regulatory authority over

the source.

 (d) The existing stationary facility must give prior written

notice to all affected Federal Land Managers of any application

for exemption under this §51.303.
12

 (e) The Federal Land Manager may provide an initial

recommendation or comment on the disposition of such application.

Such recommendation, where provided, must be part of the

exemption application. This recommendation is not to be construed

as the concurrence required under paragraph (h) of this section.

 (f) The Administrator, within 90 days of receipt of an

application for exemption from control, will provide notice of

receipt of an exemption application and notice of opportunity for

public hearing on the application.

 (g) After notice and opportunity for public hearing, the

Administrator may grant or deny the exemption. For purposes of

judicial review, final EPA action on an application for an

exemption under this §51.303 will not occur until EPA approves or

disapproves the State Implementation Plan revision.

 (h) An exemption granted by the Administrator under this

§51.303 will be effective only upon concurrence by all affected

Federal Land Managers with the Administrator's determination.

Sec. 51.304 Identification of integral vistas.

 (a) On or before December 31, 1985 the Federal Land Manager

may identify any integral vista. The integral vista must be

identified according to criteria the Federal Land Manager

develops. These criteria must include, but are not limited to,

whether the integral vista is important to the visitor's visual

experience of the mandatory Class I Federal area. Adoption of

criteria must be preceded by reasonable notice and opportunity

for public comment on the proposed criteria.

 (b) The Federal Land Manager must notify the State of any

integral vistas identified under paragraph (a) of this section,

and the reasons therefor.

 (c) The State must list in its implementation plan any

integral vista the Federal Land Manager identifies at least six

months prior to plan submission, and must list in its

implementation plan at its earliest opportunity, and in no case

later than at the time of the periodic review of the SIP required

by section 306(c), any integral vista the Federal Land Manager

identifies after that time.

 (d) The State need not in its implementation plan list any

integral vista the identification of which was not made in

accordance with the criteria in paragraph (a) of this section. In

making this finding, the State must carefully consider the
13

expertise of the Federal Land Manager in making the judgments

called for by the criteria for identification. Where the State

and the Federal Land Manager disagree on the identification of

any integral vista, the State must give the Federal Land Manager

an opportunity to consult with the Governor of the State.

Sec. 51.305 Monitoring for Reasonably Attributable Visibility

Impairment.

 (a) For the purposes of addressing reasonably attributable

visibility impairment, each State containing a mandatory Class I

Federal area must include in the plan a strategy for evaluating

reasonably attributable visibility impairment in any mandatory

Class I Federal area by visual observation or other appropriate

monitoring techniques. Such strategy must take into account

current and anticipated visibility monitoring research, the

availability of appropriate monitoring techniques, and such

guidance as is provided by the Agency.

 (b) The plan must provide for the consideration of available

visibility data and must provide a mechanism for its use in

decisions required by this subpart.

Sec. 51.306 Long-term strategy requirements for reasonably

attributable visibility impairment.

 (a) (1) For the purposes of addressing reasonably

attributable visibility impairment, each plan must include a

long-term (10-15 years) strategy for making reasonable progress

toward the national goal specified in section 300(a). This

strategy must cover any existing impairment the Federal Land

Manager certifies to the State at least 6 months prior to plan

submission, and any integral vista of which the Federal Land

Manager notifies the State at least 6 months prior to plan

submission. 

 (2) A long-term strategy must be developed for each mandatory

Class I Federal area located within the State and each mandatory

Class I Federal area located outside the State which may be

affected by sources within the State. This does not preclude the

development of a single comprehensive plan for all such areas.

 (3) The plan must set forth with reasonable specificity why

the long-term strategy is adequate for making reasonable progress

toward the national visibility goal, including remedying existing

and preventing future impairment.

 (b) The State must coordinate its long-term strategy for an
14

area with existing plans and goals, including those provided by

the affected Federal Land Managers, that may affect impairment of

visibility in any mandatory Class I Federal area.

 (c) The plan must provide for periodic review and revision,

as appropriate, of the long-term strategy for addressing

reasonably attributable visibility impairment. The plan must

provide for such periodic review and revision not less frequently

than every three years until the date of submission of the

State’s first plan addressing regional haze visibility impairment

in accordance with sections 51.308(b) and (c). On or before this

date, the State must revise its plan to provide for review and

revision of a coordinated long-term strategy for addressing

reasonably attributable and regional haze visibility impairment,

and the State must submit the first such coordinated long-term

strategy. Future coordinated long-term strategies must be

submitted consistent with the schedule for periodic progress

reports set forth in section 51.308(g). Until the State revises

its plan to meet this requirement, the State must continue to

comply with existing requirements for plan review and revision,

and with all emission management requirements in the plan to

address reasonably attributable impairment. This requirement

does not affect any pre-existing deadlines for State submittal of

a long-term strategy review (or element thereof) between [the

date of promulgation of regional haze rules] and the date

required for submission of the State’s first regional haze plan. 

In addition, the plan must provide for review of the long-term

strategy as it applies to reasonably attributable impairment, and

revision as appropriate, within 3 years of State receipt of any

certification of reasonably attributable impairment from a

Federal land manager. The review process must include

consultation with the appropriate Federal Land Managers, and the

State must provide a report to the public and the Administrator

on progress toward the national goal. This report must include

an assessment of:

 (1) The progress achieved in remedying existing impairment of

visibility in any mandatory Class I Federal area;

 (2) The ability of the long-term strategy to prevent future

impairment of visibility in any mandatory Class I Federal area;

 (3) Any change in visibility since the last such report, or,

in the case of the first report, since plan approval;

 (4) Additional measures, including the need for SIP

revisions, that may be necessary to assure reasonable progress

toward the national visibility goal;
15

 (5) The progress achieved in implementing BART and meeting

other schedules set forth in the long-term strategy;

 (6) The impact of any exemption granted under §51.303;

 (7) The need for BART to remedy existing visibility

impairment of any integral vista listed in the plan since the

last such report, or, in the case of the first report, since plan

approval.

 (d) The long-term strategy must provide for review of the

impacts from any new major stationary source or major

modifications on visibility in any mandatory Class I Federal

area. This review of major stationary sources or major

modifications must be in accordance with §51.307, §51.166, and

§51.160 and any other binding guidance provided by the Agency

insofar as these provisions pertain to protection of visibility

in any mandatory Class I Federal areas.

 (e) The State must consider, at a minimum, the following

factors during the development of its long-term strategy:

 (1) Emission reductions due to ongoing air pollution control

programs,

 (2) Additional emission limitations and schedules for

compliance,

 (3) Measures to mitigate the impacts of construction

activities,

 (4) Source retirement and replacement schedules,

 (5) Smoke management techniques for agricultural and forestry

management purposes including such plans as currently exist

within the State for these purposes, and

 (6) Enforceability of emission limitations and control

measures.

 (f) The plan must discuss the reasons why the above and other

reasonable measures considered in the development of the longterm strategy were or were not adopted as part of the long-term

strategy.

 (g) The State, in developing the long-term strategy, must

take into account the effect of new sources, and the costs of

compliance, the time necessary for compliance, the energy and
16

nonair quality environmental impacts of compliance, and the

remaining useful life of any affected existing source and

equipment therein.

Sec. 51.307 New source review.

 (a) For purposes of new source review of any new major

stationary source or major modification that would be constructed

in an area that is designated attainment or unclassified under

section 107(d)(1)(D) or (E) of the Clean Air Act, the State plan

must, in any review under §51.166 with respect to visibility

protection and analyses, provide for:

 (1) Written notification of all affected Federal Land

Managers of any proposed new major stationary source or major

modification that may affect visibility in any Federal Class I

area. Such notification must be made in writing and include a

copy of all information relevant to the permit application within

30 days of receipt of and at least 60 days prior to public

hearing by the State on the application for permit to construct.

Such notification must include an analysis of the anticipated 

impacts on visibility in any Federal Class I area,

 (2) Where the State requires or receives advance notification

(e.g. early consultation with the source prior to submission of

the application or notification of intent to monitor under §

51.166) of a permit application of a source that may affect

visibility the State must notify all affected Federal Land

Managers within 30 days of such advance notification, and

 (3) Consideration of any analysis performed by the Federal

Land Manager, provided within 30 days of the notification and

analysis required by paragraph (a)(1) of this section, that such

proposed new major stationary source or major modification may

have an adverse impact on visibility in any Federal Class I area.

Where the State finds that such an analysis does not demonstrate

to the satisfaction of the State that an adverse impact will

result in the Federal Class I area, the State must, in the notice

of public hearing, either explain its decision or give notice as

to where the explanation can be obtained.

 (b) The plan shall also provide for the review of any new

major stationary source or major modification:

 (1) That may have an impact on any integral vista of a

mandatory Class I Federal area, if it is identified in accordance

with §51.304 by the Federal Land Manager at least 12 months

before submission of a complete permit application, except where
17

the Federal Land Manager has provided notice and opportunity for

public comment on the integral vista in which case the review

must include impacts on any integral vista identified at least 6

months prior to submission of a complete permit application,

unless the State determines under section §51.304(d) that the

identification was not in accordance with the identification

criteria, or

 (2) That proposes to locate in an area classified as

nonattainment under section 107(d)(1)(A), (B), or (c) of the

Clean Air Act that may have an impact on visibility in any

mandatory Class I Federal area.

 (c) Review of any major stationary source or major

modification under paragraph (b) of this section, shall be

conducted in accordance with paragraph (a) of this section, and

§51.166(o), (p) (1) through (2), and (q). In conducting such

reviews the State must ensure that the source's emissions will be

consistent with making reasonable progress toward the national

visibility goal referred to in §51.300(a). The State may take

into account the costs of compliance, the time necessary for

compliance, the energy and nonair quality environmental impacts

of compliance, and the useful life of the source.

 (d) The State may require monitoring of visibility in any

Federal Class I area near the proposed new stationary source or

major modification for such purposes and by such means as the

State deems necessary and appropriate.

§51.308 Regional Haze Program Requirements

 (a) What is the purpose of this section? This section

establishes requirements for implementation plans, plan

revisions, and periodic progress reviews to address regional

haze.

 (b) When are the first implementation plans due under the

regional haze program? Except as provided in sections 51.308(c)

and 51.309(c), each State identified in section 51.300(b)(3) must

submit an implementation plan for regional haze meeting the

requirements of sections 51.308(d) and (e) by the following

dates: 

 (1) For any area designated as attainment or unclassifiable

for the national ambient air quality standard (NAAQS) for fine

particulate matter (PM2.5), the State must submit a regional haze

implementation plan to EPA within 12 months after the date of

designation.
18

 (2) For any area designated as nonattainment for the PM2.5

NAAQS, the State must submit a regional haze implementation plan

to EPA at the same time that the State’s plan for implementation

of the PM2.5 NAAQS must be submitted under section 172 of the

Clean Air Act, that is, within 3 years after the area is

designated as nonattainment, but not later than December 31,

2008.

(c) Options for regional planning. If at the time the SIP

for regional haze would otherwise be due, a State is working with

other States to develop a coordinated approach to regional haze

by participating in a regional planning process, the State may

choose to defer addressing the core requirements for regional

haze in section 51.308(d) and the requirements for BART in

section 51.308(e). If a State opts to do this, it must meet the

following requirements:

 (1) The State must submit an implementation plan by the

earliest date by which an implementation plan would be due for

any area of the State under section 51.308(b). This

implementation plan must contain the following:

 (i) A demonstration of ongoing participation in a regional

planning process to address regional haze, and an agreement by

the State to continue participating with one or more other States

in such a process for the development of this and future

implementation plan revisions;

 (ii) A showing, based on available inventory, monitoring, or

modeling information, that emissions from within the State

contribute to visibility impairment in a mandatory Class I

Federal Area outside the State, or that emissions from another

State contribute to visibility impairment in any mandatory Class

I Federal area within the State. 

 (iii) A description of the regional planning process,

including a list of the States which have agreed to work together

to address regional haze in a region (i.e. the regional planning

group), the goals, objectives, management, and decisionmaking

structure of the regional planning group, deadlines for

completing significant technical analyses and developing emission

management strategies, and a schedule for State review and

adoption of regulations implementing the recommendations of the

regional group; 

 (iv) A commitment by the State to submit an implementation

plan revision addressing the requirements in sections 51.308(d)

and(e) by the date specified in section 51.308(c)(2). In
19

addition, the State must commit to develop its plan revision in

coordination with the other States participating in the regional

planning process, and to fully address the recommendations of the

regional planning group.

(v) A list of all BART-eligible sources within the State.

 (2) The State must submit an implementation plan revision

addressing the requirements in sections 51.308(d) and (e) by the

latest date an area within the planning region would be required

to submit an implementation plan under section 51.308(b), but in

any event, no later than December 31, 2008.

 (d) What are the core requirements for the implementation

plan for regional haze? The State must address regional haze in

each mandatory Class I Federal area located within the State and

in each mandatory Class I Federal area located outside the State

which may be affected by emissions from within the State. To

meet the core requirements for regional haze for these areas, the

State must submit an implementation plan containing the following

plan elements and supporting documentation for all required

analyses:

 (1) Reasonable progress goals. For each mandatory Class I

Federal area located within the State, the State must establish

goals (expressed in deciviews) that provide for reasonable

progress towards achieving natural visibility conditions. The

reasonable progress goals must provide for an improvement in

visibility for the most impaired days over the period of the

implementation plan and ensure no degradation in visibility for

the least impaired days over the same period. 

 (i) In establishing a reasonable progress goal for any

mandatory Class I Federal area within the State, the State must:

 (A) Consider the costs of compliance, the time necessary for

compliance, the energy and non-air quality environmental impacts

of compliance, and the remaining useful life of any potentially

affected sources, and include a demonstration showing how these

factors were taken into consideration in selecting the goal.

 (B) Analyze and determine the rate of progress needed to

attain natural visibility conditions by the year 2064. To

calculate this rate of progress, the State must compare baseline

visibility conditions to natural visibility conditions in the

mandatory Federal Class I area and determine the uniform rate of

visibility improvement (measured in deciviews) that would need to

be maintained during each implementation period in order to
20

attain natural visibility conditions by 2064. In establishing

the reasonable progress goal, the State must consider the uniform

rate of improvement in visibility and the emission reduction

measures needed to achieve it for the period covered by the

implementation plan.

 (ii) For the period of the implementation plan, if the State

establishes a reasonable progress goal that provides for a slower

rate of improvement in visibility than the rate that would be

needed to attain natural conditions by 2064, the State must

demonstrate, based on the factors in section 51.308(d)(1)(i)(A)

above, that the rate of progress for the implementation plan to

attain natural conditions by 2064 is not reasonable; and that the

progress goal adopted by the State is reasonable. The State must

provide to the public for review as part of its implementation

plan an assessment of the number of years it would take to attain

natural conditions if visibility improvement continues at the

rate of progress selected by the State as reasonable.

(iii) In determining whether the State’s goal for visibility

improvement provides for reasonable progress towards natural

visibility conditions, the Administrator will evaluate the

demonstrations developed by the State pursuant to sections

51.308(d)(1)(i) and 51.308(d)(1)(ii). 

 (iv) In developing each reasonable progress goal, the State

must consult with those States which may reasonably be

anticipated to cause or contribute to visibility impairment in

the mandatory Class I Federal area. In any situation in which

the State cannot agree with another such State or group of States

that a goal provides for reasonable progress, the State must

describe in its submittal the actions taken to resolve the

disagreement. In reviewing the State’s implementation plan

submittal, the Administrator will take this information into

account in determining whether the State’s goal for visibility

improvement provides for reasonable progress towards natural

visibility conditions.

 (v) The reasonable progress goals established by the State

are not directly enforceable but will be considered by the

Administrator in evaluating the adequacy of the measures in the

implementation plan to achieve the progress goal adopted by the

State.

 (vi) The State may not adopt a reasonable progress goal that

represents less visibility improvement than is expected to result

from implementation of other requirements of the Clean Air Act

during the applicable planning period. 
21

 (2) Calculations of baseline and natural visibility

conditions. For each mandatory Class I Federal area located

within the State, the State must determine the following

visibility conditions (expressed in deciviews):

 (i) Baseline visibility conditions for the most impaired and

least impaired days. The period for establishing baseline

visibility conditions is 2000 to 2004. Baseline visibility

conditions must be calculated, using available monitoring data,

by establishing the average degree of visibility impairment for

the most and least impaired days for each calendar year from 2000

to 2004. The baseline visibility conditions are the average of

these annual values. For mandatory Class I Federal areas without

onsite monitoring data for 2000-2004, the State must establish

baseline values using the most representative available

monitoring data for 2000-2004, in consultation with the

Administrator or his or her designee;

(ii) For an implementation plan that is submitted by 2003,

the period for establishing baseline visibility conditions for

the period of the first long term strategy is the most recent 5-

year period for which visibility monitoring data are available

for the mandatory Class I federal areas addressed by the plan. 

For mandatory Class I Federal areas without onsite monitoring

data, the State must establish baseline values using the most

representative available monitoring data, in consultation with

the Administrator or his or her designee;

 (iii) Natural visibility conditions for the most impaired and

least impaired days. Natural visibility conditions must be

calculated by estimating the degree of visibility impairment

existing under natural conditions for the most impaired and least

impaired days, based on available monitoring information and

appropriate data analysis techniques; and

 (iv)(A) for the first implementation plan addressing the

requirements of section 51.308(d) and (e),the number of deciviews

by which baseline conditions exceed natural visibility conditions

for the most impaired and least impaired days; or

(B) for all future implementation plan revisions, the number

of deciviews by which current conditions, as calculated under

section 51.308(f)(1), exceed natural visibility conditions for

the most impaired and least impaired days.

 (3) Long-term strategy for regional haze. Each State listed

in §51.300(b)(3) must submit a long-term strategy that addresses

regional haze visibility impairment for each mandatory Class I
22

Federal area within the State and for each mandatory Class I

Federal area located outside the State which may be affected by

emissions from the State. The long-term strategy must include

enforceable emissions limitations, compliance schedules, and

other measures as necessary to achieve the reasonable progress

goals established by States having mandatory Class I Federal

areas. In establishing its long-term strategy for regional haze,

the State must meet the following requirements:

(i) Where the State has emissions that are reasonably

anticipated to contribute to visibility impairment in any

mandatory Class I Federal area located in another State or

States, the State must consult with the other State(s) in order

to develop coordinated emission management strategies. The State

must consult with any other State having emissions that are

reasonably anticipated to contribute to visibility impairment in

any mandatory Class I Federal area within the State.

 (ii) Where other States cause or contribute to impairment in

a mandatory Class I Federal area, the State must demonstrate that

it has included in its implementation plan all measures necessary

to obtain its share of the emission reductions needed to meet the

progress goal for the area. If the State has participated in a

regional planning process, the State must ensure it has included

all measures needed to achieve its apportionment of emission

reduction obligations agreed upon through that process.

 (iii) The State must document the technical basis, including

modeling, monitoring and emissions information, on which the

State is relying to determine its apportionment of emission

reduction obligations necessary for achieving reasonable progress

in each mandatory Class I Federal area it affects. The State may

meet this requirement by relying on technical analyses developed

by the regional planning organization and approved by all State

participants. The state must identify the baseline emissions

inventory on which its strategies are based. The baseline

emissions inventory year is presumed to be the most recent year

of the consolidate periodic emissions inventory.

 (iv) The State must identify all anthropogenic sources of

visibility impairment considered by the State in developing its

long-term strategy. The State should consider major and minor

stationary sources, mobile sources, and area sources. 

 (v) The State must consider, at a minimum, the following

factors in developing its long-term strategy:

(A) Emission reductions due to ongoing air pollution control
23

programs, including measures to address reasonably attributable

visibility impairment; 

 (B) Measures to mitigate the impacts of construction

activities;

 (C) Emissions limitations and schedules for compliance to

achieve the reasonable progress goal

 (D) Source retirement and replacement schedules

 (E) Smoke management techniques for agricultural and forestry

management purposes including plans as currently exist within the

State for these purposes;

 (F) Enforceability of emissions limitations and control

measures; and

 (G) The anticipated net effect on visibility due to projected

changes in point, area, and mobile source emissions over the

period addressed by the long-term strategy.

 (4) Monitoring strategy and other implementation plan

requirements. The State must submit with the implementation plan

a monitoring strategy for measuring, characterizing, and

reporting of regional haze visibility impairment that is

representative of all mandatory Class I Federal areas within the

State. This monitoring strategy must be coordinated with the

monitoring strategy required in section 51.305 for reasonably

attributable visibility impairment. Compliance with this

requirement may be met through participation in the Interagency

Monitoring of Protected Visual Environments network. The

implementation plan must also provide for the following:

 (i) The establishment of any additional monitoring sites or

equipment needed to assess whether reasonable progress goals to

address regional haze for all mandatory Class I Federal areas

within the State are being achieved.

 (ii) Procedures by which monitoring data and other

information are used in determining the contribution of emissions

from within the State to regional haze visibility impairment at

mandatory Class I Federal areas both within and outside the

State.

 (iii) For a State with no mandatory Class I Federal areas,

procedures by which monitoring data and other information are

used in determining the contribution of emissions from within the

State to regional haze visibility impairment at mandatory Class I

Federal areas in other States.

(iv) The implementation plan must provide for the reporting

of all visibility monitoring data to the Administrator at least

annually for each mandatory Class I Federal area in the State. 
24

To the extent possible, the State should report visibility

monitoring data electronically.

 (v) A statewide inventory of emissions of pollutants that are

reasonably anticipated to cause or contribute to visibility

impairment in any mandatory Class I Federal area. The inventory

must include emissions for a baseline year, emissions for the

most recent year for which data are available, and estimates of

future projected emissions. The State must also include a

commitment to update the inventory periodically.

(vi) Other elements, including reporting, recordkeeping, and

other measures, necessary to assess and report on visibility.

 (e) Best Available Retrofit Technology (BART) requirements for 

regional haze visibility impairment. The State must submit an

implementation plan containing emission limitations representing

BART and schedules for compliance with BART for each BARTeligible source that may reasonably be anticipated to cause or

contribute to any impairment of visibility in any mandatory Class

I Federal area, unless the State demonstrates that an emissions

trading program or other alternative will achieve greater

reasonable progress toward natural visibility conditions. 

(1) To address the requirements for BART, the State must

submit an implementation plan containing the following plan

elements and include documentation for all required analyses:

(i) A list of all BART-eligible sources within the State.

(ii) A determination of BART for each BART-eligible source

in the State that emits any air pollutant which may reasonably be

anticipated to cause or contribute to any impairment of

visibility in any mandatory Class I Federal area. All such

sources are subject to BART. This determination must be based on

the following analyses:

(A) An analysis of the best system of continuous emission

control technology available and associated emission reductions

achievable for each BART-eligible source within the State subject

to BART. In this analysis, the State must take into

consideration the technology available, the costs of compliance,

the energy and nonair quality environmental impacts of

compliance, any pollution control equipment in use at the source,

and the remaining useful life of the source; and

(B) An analysis of the degree of visibility improvement that

would be achieved in each mandatory Class I Federal area as a
25

result of the emission reductions achievable from all sources

subject to BART located within the region that contributes to

visibility impairment in the Class I area, based on the analysis

conducted under section 51.308(e)(1)(ii)(A).

(iii) If the State determines in establishing BART that

technological or economic limitations on the applicability of

measurement methodology to a particular source would make the

imposition of an emission standard infeasible, it may instead

prescribe a design, equipment, work practice, or other

operational standard, or combination thereof, to require the

application of BART. Such standard, to the degree possible, is

to set forth the emission reduction to be achieved by

implementation of such design, equipment, work practice or

operation, and must provide for compliance by means which achieve

equivalent results.

(iv) A requirement that each source subject to BART be

required to install and operate BART as expeditiously as

practicable, but in no event later than 5 years after approval of

the implementation plan revision. 

(v) A requirement that each source subject to BART maintain

the control equipment required by this subpart and establish

procedures to ensure such equipment is properly operated and

maintained.

(2) A State may opt to implement an emissions trading

program or other alternative measure rather than to require

sources subject to BART to install, operate, and maintain BART. 

To do so, the State must demonstrate that this emissions trading

program or other alternative measure will achieve greater

reasonable progress than would be achieved through the

installation and operation of BART. To make this demonstration,

the State must submit an implementation plan containing the

following plan elements and include documentation for all

required analyses:

(i) A demonstration that the emissions trading program or

other alternative measure will achieve greater reasonable

progress than would have resulted from the installation and

operation of BART at all sources subject to BART in the State. 

This demonstration must be based on the following:

(A) A list of all BART-eligible sources within the State.

(B) An analysis of the best system of continuous emission

control technology available and associated emission reductions
26

achievable for each source within the State subject to BART. In

this analysis, the State must take into consideration the

technology available, the costs of compliance, the energy and

nonair quality environmental impacts of compliance, any pollution

control equipment in use at the source, and the remaining useful

life of the source. The best system of continuous emission

control technology and the above factors may be determined on a

source category basis. The State may elect to consider both

source-specific and category-wide information, as appropriate, in

conducting its analysis. 

(C) An analysis of the degree of visibility improvement that

would be achieved in each mandatory Class I Federal area as a

result of the emission reductions achievable from all such

sources subject to BART located within the region that

contributes to visibility impairment in the Class I area, based

on the analysis conducted under section 51.308(e)(2)(i)(B).

(ii) A demonstration that the emissions trading program or

alternative measures will apply, at a minimum, to all BARTeligible sources in the State. Those sources having a federally

enforceable emission limitation determined by the State and

approved by EPA as meeting BART in accordance with section

51.302(c) or 51.308(e)(1) do not need to meet the requirements of

the emissions trading program or alternative measure, but may

choose to participate if they meet the requirements of the

emissions trading program or alternative measure. 

(iii) A requirement that all necessary emission reductions

take place during the period of the first long-term strategy for

regional haze. To meet this requirement, the State must provide

a detailed description of the emissions trading program or other

alternative measure, including schedules for implementation, the

emission reductions required by the program, all necessary

administrative and technical procedures for implementing the

program, rules for accounting and monitoring emissions, and

procedures for enforcement. 

(iv) A demonstration that the emission reductions resulting

from the emissions trading program or other alternative measure

will be surplus to those reductions resulting from measures

adopted to meet requirements of the Clean Air Act as of the

baseline date of the SIP.

(v) At the State’s option, a provision that the emissions

trading program or other alternative measure may include a

geographic enhancement to the program to address the requirement

under §51.302(c) related to BART for reasonably attributable
27

impairment from the pollutants covered under the emissions

trading program or other alternative measure.

(3) After a State has met the requirements for BART or

implemented emissions trading program or other alternative

measure that achieve more reasonable progress than the

installation and operation of BART, BART-eligible sources will be

subject to the requirements of section 51.308(d) in the same

manner as other sources.

(4) Any BART-eligible facility subject to the requirement

under section 51.308(e) to install, operate, and maintain BART

may apply to the Administrator for an exemption from that

requirement. An application for an exemption will be subject to

the requirements of section 51.303(a)(2)-(h). 

(f) Requirements for comprehensive periodic revisions of

implementation plans for regional haze. Each State identified in

section 51.300(b)(3) must revise and submit its regional haze

implementation plan revision to EPA by July 31, 2018 and every

ten years thereafter. In each plan revision, the State must

evaluate and reassess all of the elements required in section

51.308(d), taking into account improvements in monitoring data

collection and analysis techniques, control technologies, and

other relevant factors. In evaluating and reassessing these

elements, the State must address the following:

 (1) Current visibility conditions for the most impaired and

least impaired days, and actual progress made towards natural

conditions during the previous implementation period. The period

for calculating current visibility conditions is the most recent

five year period preceding the required date of the

implementation plan submittal for which data are available. 

Current visibility conditions must be calculated based on the

annual average level of visibility impairment for the most and

least impaired days for each of these five years. Current

visibility conditions are the average of these annual values.

 (2) The effectiveness of the long-term strategy for achieving

reasonable progress goals over the prior implementation

period(s); and

 (3) Affirmation of, or revision to, the reasonable progress

goal in accordance with the procedures set forth in section

51.308(d)(1). If the State established a reasonable progress

goal for the prior period which provided a slower rate of

progress than that needed to attain natural conditions by the

year 2064, the State must evaluate and determine the
28

reasonableness, based on the factors in section

51.308(d)(1)(i)(A), of additional measures that could be adopted

to achieve the degree of visibility improvement projected by the

analysis contained in the first implementation plan described in

section 51.308(d)(1)(i)(B).

 (g) Requirements for periodic reports describing progress

towards the reasonable progress goals. Each State identified in

section 51.300(b)(3) must submit a report to the Administrator

every 5 years evaluating progress towards the reasonable progress

goal for each mandatory Class I Federal area located within the

State and in each mandatory Class I Federal area located outside

the State which may be affected by emissions from within the

State. The first progress report is due 5 years from submittal

of the initial implementation plan addressing sections 51.308(d)

and (e). The progress reports must be in the form of

implementation plan revisions that comply with the procedural

requirements of sections 51.102 and 51.103. Periodic progress

reports must contain at a minimum the following elements:

 (1) A description of the status of implementation of all

measures included in the implementation plan for achieving

reasonable progress goals for mandatory Class I Federal areas

both within and outside the State.

 (2) A summary of the emissions reductions achieved throughout

the State through implementation of the measures described in

section 51.308(g)(1). 

 (3) For each mandatory Class I Federal area within the State,

the State must assess the following visibility conditions and

changes, with values for most impaired and least impaired days

expressed in terms of five-year averages of these annual values.

 (i) the current visibility conditions for the most impaired

and least impaired days;

 (ii) the difference between current visibility conditions for

the most impaired and least impaired days and baseline visibility

conditions;

 (iii) the change in visibility impairment for the most

impaired and least impaired days over the past five years; 

 (4) An analysis tracking the change over the past 5 years in

emissions of pollutants contributing to visibility impairment

from all sources and activities within the State. Emissions

changes should be identified by type of source or activity. The
29

analysis must be based on the most recent updated emissions

inventory, with estimates projected forward as necessary and

appropriate, to account for emissions changes during the

applicable 5-year period. 

 (5) An assessment of any significant changes in anthropogenic

emissions within or outside the State that have occurred over the

past 5 years that have limited or impeded progress in reducing

pollutant emissions and improving visibility. 

 (6) An assessment of whether the current implementation plan

elements and strategies are sufficient to enable the State, or

other States with mandatory Federal Class I areas affected by

emissions from the State, to meet all established reasonable

progress goals. 

(7) A review of the State’s visibility monitoring strategy

and any modifications to the strategy as necessary.

 (h) Determination of the adequacy of existing implementation

plan. At the same time the State is required to submit any 5-

year progress report to EPA in accordance with section 51.308(g),

the State must also take one of the following actions based upon

the information presented in the progress report: 

(1) If the State determines that the existing implementation

plan requires no further substantive revision at this time in

order to achieve established goals for visibility improvement and

emissions reductions, the State must provide to the Administrator

a negative declaration that further revision of the existing

implementation plan is not needed at this time. 

(2) If the State determines that the implementation plan is or

may be inadequate to ensure reasonable progress due to emissions

from sources in another State(s) which participated in a regional

planning process, the State must provide notification to the

Administrator and to the other State(s) which participated in the

regional planning process with the States. The State must also

collaborate with the other State(s) through the regional planning

process for the purpose of developing additional strategies to

address the plan’s deficiencies. 

(3) Where the State determines that the implementation plan is

or may be inadequate to ensure reasonable progress due to

emissions from sources in another country, the State shall

provide notification, along with available information, to the

Administrator.
30

(4) Where the State determines that the implementation plan is

or may be inadequate to ensure reasonable progress due to

emissions from sources within the State, the State shall revise

its implementation plan to address the plan’s deficiencies within

one year. 

 (i) What are the requirements for State and Federal Land

Manager coordination?. 

 (1) By [insert date 90 days from the effective date of these

regulations], the State must identify in writing to the Federal

Land Managers the title of the official to which the Federal Land

Manager of any mandatory Class I Federal area can submit any

recommendations on the implementation of this subpart including,

but not limited to:

 (i) Identification of impairment of visibility in any

mandatory Class I Federal area(s), and

 (ii) Identification of elements for inclusion in the 

visibility monitoring strategy required by sections 51.305 and

51.308.

 (2) The State must provide the Federal Land Manager with an

opportunity for consultation, in person and at least 60 days

prior to holding any public hearing on an implementation plan (or

plan revision) for regional haze required by this subpart. This

consultation must include the opportunity for the affected

Federal Land Managers to discuss their:

 (i) Assessment of impairment of visibility in any mandatory

Class I Federal area, and

 (ii) Recommendations on the development of the reasonable

progress goal and on the development and implementation of

strategies to address visibility impairment.

 (3) In developing any implementation plan (or plan revision),

the State must include a description of how it addressed any

comments provided by the Federal Land Managers. 

 (4) The plan (or plan revision) must provide procedures for

continuing consultation between the State and Federal Land

Manager on the implementation of the visibility protection

program required by this subpart, including development and

review of implementation plan revisions and 5-year progress

reports, and on the implementation of other programs having the

potential to contribute to impairment of visibility in mandatory
31

Class I Federal areas.

 

§51.309 Requirements Related to the Grand Canyon Visibility

Transport Commission.

(a) What is the purpose of this section?. This section

establishes the requirements for the first regional haze

implementation plan to address regional haze visibility

impairment in the 16 Class I areas covered by the Grand Canyon

Visibility Transport Commission Report. For the years 2003 to

2018, certain States (defined below as Transport Region States)

may choose to implement the Commission’s recommendations within

the framework of the national regional haze program and

applicable requirements of the Act by complying with the

provisions of this section, as supplemented by an approvable

Annex to the Commission Report as required by section 51.309(f). 

If a transport region state submits an implementation plan which

is approved by EPA as meeting the requirements of this section,

it will be deemed to comply with the requirements for reasonable

progress for the period from approval of the plan to 2018.

(b) Definitions. For the purposes of this section:

(1) “16 Class I areas” means the following mandatory Class I

Federal areas on the Colorado Plateau: Grand Canyon National

Park, Sycamore Canyon Wilderness, Petrified Forest National Park,

Mount Baldy Wilderness, San Pedro Parks Wilderness, Mesa Verde

National Park, Weminuche Wilderness, Black Canyon of the Gunnison

Wilderness, West Elk Wilderness, Maroon Bells Wilderness, Flat

Tops Wilderness, Arches National Park, Canyonlands National Park,

Capital Reef National Park, Bryce Canyon National Park, and Zion

National Park.

(2) “Transport Region State” means one of the States that is

included within the Transport Region addressed by the Grand

Canyon Visibility Transport Commission (Arizona, California,

Colorado, Idaho, Nevada, New Mexico, Oregon, Utah, and Wyoming).

(3) “Commission Report” means the report of the Grand Canyon

Visibility Transport Commission entitled “Recommendations for

Improving Western Vistas,” dated June 10, 1996. 

(4) “Fire” means wildfire, wildland fire (including

prescribed natural fire) , prescribed fire, and agricultural

burning conducted and occurring on Federal, State, and private

wildlands and farmlands.
32

(5) “Milestone” means an average percentage reduction in

emissions, expressed in tons per year, for a given year or for a

period of up to five years ending in that year, compared to a

1990 actual emissions baseline. 

(6) “Mobile Source Emission Budget” means the lowest level

of VOC, NOX, SO2 elemental and organic carbon, and fine particles

which are projected to occur in any area within the transport

region from which mobile source emissions are determined to

contribute significantly to visibility impairment in any of the

16 Class I areas. 

(7) “Geographic enhancement” means a method, procedure, or

process to allow a broad regional strategy, such as a milestone

or backstop market trading program designed to achieve greater

reasonable progress than BART for regional haze, to accommodate

BART for reasonably attributable impairment.

(c) Implementation Plan Schedule. Each Transport Region

State may meet the requirements of section 51.308(b)-(e) by

electing to submit an implementation plan that complies with the

requirements of section 51.309. Each Transport Region State must

submit an implementation plan addressing regional haze visibility

impairment in the 16 Class I areas no later than December 31,

2003. A Transport Region State that elects not to submit an

implementation plan that complies with the requirements of

section 51.309 (or whose plan does not comply with all of the

requirements of 51.309) is subject to the requirements of section

51.308 in the same manner and to the same extent as any State not

included within the Transport Region.

(d) Requirements of the first implementation plan for States

electing to adopt all of the recommendations of the Commission

Report. Except as provided for in §51.309(e), each Transport

Region State must submit an implementation plan that meets the 

following requirements:

(1) Time period covered. The implementation plan must be

effective for the entire time period between December 31, 2003

and December 31, 2018.

(2) Projection of visibility improvement. For each of the

16 mandatory Class I areas located within the Transport Region

State, the plan must include a projection of the improvement in

visibility conditions (expressed in deciviews, and in any

additional ambient visibility metrics deemed appropriate by the

State) expected through the year 2018 for the most impaired and

least impaired days, based on the implementation of all measures
33

as required in the Commission report and the provisions in

§51.309. The projection must be made in consultation with other

Transport Region States with sources which may be reasonably

anticipated to contribute to visibility impairment in the

relevant Class I area. The projection may be based on a

satisfactory regional analysis.

(3) Treatment of clean-air corridors. The plan must

describe and provide for implementation of comprehensive emission

tracking strategies for clean-air corridors to ensure that the

visibility does not degrade on the least-impaired days at any of

the 16 Class I areas. The strategy must include:

(i) An identification of clean-air corridors. The EPA will

evaluate the State’s identification of such corridors based upon

the reports of the Commission’s Meteorology Subcommittee and any

future updates by a successor organization;

(ii) Within areas that are clean-air corridors, an

identification of patterns of growth or specific sites of growth

that could cause, or are causing, significant emissions increases

that could have, or are having, visibility impairment at one or

more of the 16 Class I areas.

(iii) In areas outside of clean-air corridors, an

identification of significant emissions growth that could begin,

or is beginning, to impair the quality of air in the corridor and

thereby lead to visibility degradation for the least-impaired

days in one or more of the 16 Class I areas.

(iv) If impairment of air quality in clean air corridors is

identified pursuant to subsections 51.309(d)(3)(ii) and (iii), an

analysis of the effects of increased emissions, including

provisions for the identification of the need for additional

emission reductions measures, and implementation of the

additional measures where necessary.

(v) A determination of whether other clean air corridors

exist for any of the 16 Class I areas. For any such clean air

corridors, an identification of the necessary measures to protect

against future degradation of air quality in any of the 16 Class

I areas.

(4) Implementation of Stationary Source Reductions. The

first implementation plan submission must include:

(i) Monitoring and reporting of sulfur dioxide emissions. 

The plan submission must include provisions requiring the
34

monitoring and reporting of actual stationary source sulfur

dioxide emissions within the State. The monitoring and reporting

data must be sufficient to determine whether a 13 percent

reduction in actual stationary source sulfur dioxide emissions

has occurred between the years 1990 and 2000, and whether

milestones required by section 51.309(f)(ii) have been achieved

for the transport region. The plan submission must provide for

reporting of these data by the State to the Administrator. Where

procedures developed under section 51.309(f)(2) and agreed upon

by the State include reporting to a regional planning

organization, the plan submission must provide for reporting to

the regional planning body in addition to the Administrator.

(ii) Criteria and Procedures for a Market Trading Program. 

The plan must include the criteria and procedures for activating

a market trading program or other program consistent with section

51.309(f)(2) if an applicable regional milestone is exceeded,

procedures for operation of the program, and implementation plan

assessments of the program in the years 2008, 2013, and 2018. 

(iii) Provisions for activating a market trading program.

Provisions to activate the market trading program or other

program within 12 months after the emissions for the region are

determined to exceed the applicable emission reduction milestone,

and to assure that all affected sources are in compliance with

allocation and other requirements within 5 years after the

emissions for the region are determined to exceed the applicable

emission reduction milestone.

(iv) Provisions for market trading program compliance

reporting. If the market trading program has been activated, the

plan submission must include provisions requiring the State to

provide annual reports assuring that all sources are in

compliance with applicable requirements of the market trading

program.

(v) Provisions for stationary source NOx and PM. The plan

submission must include a report which assesses emissions control

strategies for stationary source NOx and PM, and the degree of

visibility improvement that would result from such strategies. 

In the report, the State must evaluate and discuss the need to

establish emission milestones for NOx and PM to avoid any net

increase in these pollutants from stationary sources within the

transport region, and to support potential future development and

implementation of a multipollutant and possibly multisource

market-based program. The plan submission must provide for an

implementation plan revision, containing any necessary long-term

strategies and BART requirements for stationary source PM and NOx
35

(including enforceable limitations, compliance schedules, and

other measures) by no later than December 31, 2008.

 

(5) Mobile Sources. The plan submission must provide for:

(i) Statewide inventories of current annual emissions and

projected future annual emissions of VOC, NOX, SO2,elemental and

organic carbon, and fine particles from mobile sources for the

years 2003 to 2018. The future year inventories must include

projections for the year 2005, or an alternative year that is

determined by the State to represent the year during which mobile

source emissions will be at their lowest levels within the State. 

(ii) A determination whether mobile source emissions in any

areas of the State contribute significantly to visibility

impairment in any of the 16 Class I Areas, based on the statewide

inventory of current and projected mobile source emissions.

(iii) For States with areas in which mobile source emissions 

are found to contribute significantly to visibility impairment in

any of the 16 Class I areas:

(A) The establishment and documentation of a mobile source

emissions budget for any such area, including provisions

requiring the State to restrict the annual VOC, Nox, SO2,

elemental and organic carbon, and/or fine particle mobile source

emissions to their projected lowest levels, to implement measures

to achieve the budget or cap, and to demonstrate compliance with

the budget.

(B) An emission tracking system providing for reporting of

annual mobile source emissions from the State in the periodic

implementation plan revisions required by section 51.309(d)(10).

The emission tracking system must be sufficient to determine the

States’ contribution toward the Commission’s objective of

reducing emissions from mobile sources by 2005 or an alternate

year that is determined by the State to represent the year during

which mobile source emissions will be at their lowest levels

within the State, and to ensure that mobile source emissions do

not increase thereafter. 

(iv) Interim reports to EPA and the public in years 2003,

2008, 2013, and 2018 on the implementation status of the regional

and local strategies recommended by the Commission Report to

address mobile source emissions.

(6) Programs Related to Fire. The plan must provide for:
36

(i) Documentation that all Federal, State, and private

prescribed fire programs within the State evaluate and address

the degree visibility impairment from smoke in their planning and

application. In addition the plan must include smoke management

programs that include all necessary components including, but not

limited to, actions to minimize emissions, evaluation of smoke

dispersion, alternatives to fire, public notification, air

quality monitoring, surveillance and enforcement, and program

evaluation.

(ii) A statewide inventory and emissions tracking system

(spatial and temporal) of VOC, NOx, elemental and organic carbon,

and fine particle emissions from fire. In reporting and tracking

emissions from fire from within the State, States may use

information from regional data-gathering and tracking

initiatives.

(iii) Identification and removal wherever feasible of any

administrative barriers to the use of alternatives to burning in

Federal, State, and private prescribed fire programs within the

State.

(iv) Enhanced smoke management programs for fire that

consider visibility effects, not only health and nuisance

objectives, and that are based on the criteria of efficiency,

economics, law, emission reduction opportunities, land management

objectives, and reduction of visibility impact.

(v) Establishment of annual emission goals for fire,

excluding wildfire, that will minimize emission increases from

fire to the maximum extent feasible and that are established om 

cooperation with States, tribes, Federal land management

agencies, and private entities.

(7) Area Sources of Dust Emissions from Paved and Unpaved

Roads. The plan must include an assessment of the impact of dust

emissions from paved and unpaved roads on visibility conditions

in the 16 Class I Areas. If such dust emissions are determined

to be a significant contributor to visibility impairment in the

16 Class I areas, the State must implement emissions management

strategies to address the impact as necessary and appropriate.

(8) Pollution Prevention. The plan must provide for: 

(i) An initial summary of all pollution prevention programs

currently in place, an inventory of all renewable energy

generation capacity and production in use, or planned as of the

year 2002 (expressed in megawatts and megawatt-hours), the total
37

energy generation capacity and production for the State, the

percent of the total that is renewable energy, and the State’s

anticipated contribution toward the renewable energy goals for

2005 and 2015, as provided in section 51.309(d)(8)(vi).

(ii) Programs to provide incentives that reward efforts that

go beyond compliance and/or achieve early compliance with airpollution related requirements.

(iii) Programs to preserve and expand energy conservation

efforts.

(iv) The identification of specific areas where renewable

energy has the potential to supply power where it is now lacking

and where renewable energy is most cost-effective.

(v) Projections of the short- and long-term emissions

reductions, visibility improvements, cost savings, and secondary

benefits associated with the renewable energy goals, energy

efficiency and pollution prevention activities.

(vi) A description of the programs relied on to achieve the

State's contribution toward the Commission's goal that renewable

energy will comprise 10 percent of the regional power needs by

2005 and 20 percent by 2015, and a demonstration of the progress

toward achievement of the renewable energy goals in the years

2003, 2008, 2013, and 2018. This description must include

documentation of the potential for renewable energy resources,

the percentage of renewable energy associated with new power

generation projects implemented or planned, and the renewable

energy generation capacity and production in use and planned in

the State. To the extent that it is not feasible for a State to

meet its contribution to the regional renewable energy goals, the

State must identify in the progress reports the measures

implemented to achieve its contribution and explain why meeting

the State's contribution was not feasible.

(9) Implementation of Additional Recommendations. The plan

must provide for implementation of all other recommendations in

the Commission report that can be practicably included as

enforceable emission limits, schedules of compliance, or other

enforceable measures (including economic incentives) to make

reasonable progress toward remedying existing and preventing

future regional haze in the 16 Class I areas. The State must

provide a report to EPA and the public in 2003, 2008, 2013, and

2018 on the progress toward developing and implementing policy or

strategy options recommended in the Commission Report. 
38

(10) Periodic Implementation Plan Revisions. Each Transport

Region State must submit to the Administrator periodic reports in

the years 2008, 2013, and 2018. The progress reports must be in

the form of implementation plan revisions that comply with the

procedural requirements of §51.102 and §51.103. 

(i) The report will assess the area for reasonable progress

as provided in §51.309 for mandatory Class I Federal area(s)

located within the State and for mandatory Class I Federal

area(s) located outside the State which may be affected by

emissions from within the State. This demonstration may be based

on assessments conducted by the States and/or a regional planning

body. The progress reports must contain at a minimum the

following elements:

 (A) A description of the status of implementation of all

measures included in the implementation plan for achieving

reasonable progress goals for mandatory Class I Federal areas

both within and outside the State.

 (B) A summary of the emissions reductions achieved throughout

the State through implementation of the measures described in

§51.309(d)(10)(i)(A).

 (C) For each mandatory Class I Federal area within the State,

an assessment of the following: the current visibility

conditions for the most impaired and least impaired days; the

difference between current visibility conditions for the most

impaired and least impaired days and baseline visibility

conditions; the change in visibility impairment for the most

impaired and least impaired days over the past five years. 

 (D) An analysis tracking the change over the past 5 years in

emissions of pollutants contributing to visibility impairment

from all sources and activities within the State. Emissions

changes should be identified by type of source or activity. The

analysis must be based on the most recent updated emissions

inventory, with estimates projected forward as necessary and

appropriate, to account for emissions changes during the

applicable 5-year period. 

 (E) An assessment of any significant changes in anthropogenic

emissions within or outside the State that have occurred over the

past 5 years that have limited or impeded progress in reducing

pollutant emissions and improving visibility. 

(F) An assessment of whether the current implementation plan

elements and strategies are sufficient to enable the State, or
39

other States with mandatory Federal Class I areas affected by

emissions from the State, to meet all established reasonable

progress goals. 

(G) A review of the State’s visibility monitoring strategy

and any modifications to the strategy as necessary.

(ii) At the same time the State is required to submit any 5-

year progress report to EPA in accordance with section

51.309(d)(10)(i), the State must also take one of the following

actions based upon the information presented in the progress

report: 

(A) If the State determines that the existing

implementation plan requires no further substantive revision at

this time in order to achieve established goals for visibility

improvement and emissions reductions, the State must provide to

the Administrator a negative declaration that further revision of

the existing implementation plan is not needed at this time. 

(B) If the State determines that the implementation plan is

or may be inadequate to ensure reasonable progress due to

emissions from sources in another State(s) which participated in

a regional planning process, the State must provide notification

to the Administrator and to the other State(s) which participated

in the regional planning process with the States. The State must

also collaborate with the other State(s) through the regional

planning process for the purpose of developing additional

strategies to address the plan’s deficiencies. 

(C) Where the State determines that the implementation plan

is or may be inadequate to ensure reasonable progress due to

emissions from sources in another country, the State shall

provide notification, along with available information, to the

Administrator.

(D) Where the State determines that the implementation plan

is or may be inadequate to ensure reasonable progress due to

emissions from within the State, the State shall develop

additional strategies to address the plan deficiencies and revise

the implementation plan no later than one year from the date that

the progress report was due.

(11) State Planning and Interstate Coordination. In

complying with the requirements of section 309, States may

include emission reductions strategies that are based on

coordinated implementation with other States. Examples of these

strategies include economic incentive programs and transboundary
40

emissions trading programs. The implementation plan must include

documentation of the technical and policy basis for the

individual State apportionment (or the procedures for

apportionment throughout the trans-boundary region), the

contribution addressed by the State's plan, how it coordinates

with other State plans, and compliance with any other appropriate

implementation plan approvability criteria. States may rely on

the relevant technical, policy and other analyses developed by a

regional entity (such as the Western Regional Air Partnership) in

providing such documentation. Conversely, States may elect to

develop their own programs without relying on work products from

a regional entity.

(12) Tribal Implementation. Consistent with 40 CFR Part 49,

Tribes within the Transport Region may implement the required

visibility programs for the 16 Class I areas, in the same manner

as States, regardless of whether such tribes have participated as

members of a visibility transport commission. 

(e) States Electing Not to Implement the Commission

Recommendations. Any Transport Region State may elect not to

implement the Commission recommendations set forth in paragraph

(d) of this section. Such States are required to comply with the

timelines and requirements of section 51.308. Any Transport

Region state electing not to implement the Commission

recommendations must advise the other states in the Transport

Region of the nature of the program and the effect of the program

on visibility-impairing emissions, so that other States can take

this information into account in developing programs under

section 51.309. 

(f) Annex to the Commission Report. 

(1) A Transport Region State may choose to comply with the

provisions of this section and by doing so shall satisfy the

requirements of section 51.308(b)-(e) only if the Grand Canyon

Visibility Transport Commission (or a regional planning body

formed to implement the Commission recommendations) submits a

satisfactory annex to the Commission Report no later than October

1, 2000. To be satisfactory, the Annex must contain the

following elements:

(i) The annex must contain quantitative emission reduction

milestones for stationary source sulfur dioxide emissions for the

reporting years 2003, 2008, 2013 and 2018. The milestones must

provide for steady and continuing emission reductions for the

2003-2018 time period consistent with the Commission’s definition

of reasonable progress, its goal of 50 to 70 percent reduction in
41

sulfur dioxide emissions from 1990 actual emission levels by

2040, applicable requirements under the Clean Air Act, and the

timing of implementation plan assessments of progress and

identification of deficiencies which will be due in the years

2008, 2013, and 2018. The emission reduction milestones must be

shown to provide for greater reasonable progress than would be

achieved by application of best available retrofit technology

(BART) pursuant to section 51.308(e)(2) and would be approvable

in lieu of BART.

(ii) The annex must contain documentation of the market

trading program or other programs to be implemented pursuant to

51.309(d)(4)if current programs and voluntary measures are not

sufficient to meet the required emission reduction milestones. 

This documentation must include model rules, memoranda of

understanding, and other documentation describing in detail how

emission reduction progress will be monitored, what conditions

will require the market trading program to be activated, how

allocations will be performed, and how the program will operate.

(2) The Commission may elect, at the same time it submits

the annex, to make recommendations intended to demonstrate

reasonable progress for other mandatory Class I areas (beyond the

original 16) within the Transport Region States, including the

technical and policy justification for these additional mandatory

Class I Federal areas in accordance with the provisions of

section 51.309(g).

(3) The EPA will publish the annex upon receipt. If EPA

finds that the annex meets the requirements of §51.309(f)(1) and

assures reasonable progress, then EPA, after public notice and

comment, will amend the requirements of §51.309(d)(4) to

incorporate the provisions of the annex within one year after EPA

receives the annex. If EPA finds that the annex does not meet

the requirements of §51.309(f)(1), or does not assure reasonable

progress, or if EPA finds that the annex is not received, then

each Transport Region State must submit an implementation plan

for regional haze meeting all of the requirements of section

51.308.

(4) In accordance with the provisions under §51.309(f)(1),

the annex may include a geographic enhancement to the program

provided for in §51.309(d)(4) to address the requirement under

§51.302(c) related to Best Available Retrofit Technology for

reasonably attributable impairment from the pollutants covered by

the milestones or the backstop market trading program. The

geographic enhancement program may include an appropriate level

of reasonably attributable impairment which may require
42

additional emission reductions over and above those achieved

under the milestones defines in §51.309(f)(1)(i).

(g) Additional Class I Areas. The following submittals must

be made by Transport Region States implementing the provisions of

this section as the basis for demonstrating reasonable progress

for additional Class I areas in the Transport Region States. If

a Transport Region State submits an implementation plan which is

approved by EPA as meeting the requirements of this section, it

will be deemed to comply with the requirements for reasonable

progress for the period from approval of the plan to 2018.

(1) In the plan submitted for the 16 Class I areas no later

than December 31, 2003, a declaration indicating whether other

Class I areas will be addressed under §51.308 or 51.309(g)(2) and

(3).

(2) In a plan submitted no later than December 31, 2008,

provide a demonstration of expected visibility conditions for the

most impaired and least impaired days at the additional mandatory

Class I Federal area(s) based on emissions projections from the

long-term strategies in the implementation plan. This

demonstration may be based on assessments conducted by the States

and/or a regional planning body.

(3) In a plan submitted no later than December 31, 2008, 

provide revisions to the plan submitted under section 51.309(c),

including provisions to establish reasonable progress goals and

implement any additional measures necessary to demonstrate

reasonable progress for the additional mandatory Federal Class I

areas. These revisions must comply with the provisions of

section 51.308(d)(1)-(4). 

(4) The following provisions apply for Transport Region

States establishing reasonable progress goals and adopting any

additional measures for Class I areas other than the 16 Class I

areas under section 51.309(g)(2)and(3).

(i) In developing long-term strategies pursuant to section

308(d)(3), the State may build upon the strategies implemented

under section 51.309(d) and take full credit for the visibility

improvement achieved through these strategies.

(ii) The requirement under section 51.308(e) related to Best

Available Retrofit Technology for regional haze is deemed to be

satisfied for pollutants addressed by the milestones and backstop

trading program if, in establishing the emission reductions

milestones under section 51.309(f), it is shown that greater
43

reasonable progress will be achieved for these Class I areas than

would be achieved through the application of source-specific BART

emission limitations under section 51.308(e)(1). 

(iii) The Transport Region State may consider whether any

strategies necessary to achieve the reasonable progress goals

required by 51.309(g)(3) are incompatible with the strategies

implemented under section 51.309(d) to the extent the State

adequately demonstrates that the incompatibility is related to

the costs of the compliance, the time necessary for compliance,

the energy and no air quality environmental impacts of

compliance, or the remaining useful life of any existing source

subject to such requirements.

University of California, Davis page 1 August 1995

Appendix B - A Guide to Interpreting IMPROVE Monitoring Data
University of California, Davis page 2 August 1995
University of California, Davis page 3 August 1995

A GUIDE TO INTERPRETING IMPROVE MONITORING DATA

(The following text was provided by the University of California at Davis

 for the IMPROVE program.)

Introduction

The National Park Service (NPS) and other Federal Land Managers are required by the Clean Air

Act to protect visibility at Class I areas, which include most national parks and wilderness areas.

This is being accomplished through the Interagency Monitoring of Protected Visual

Environments (IMPROVE) program, which has representatives from the NPS, the Forest Service

(USFS), the Bureau of Land Management, the Fish and Wildlife Service (FWS), the

Environmental Protection Agency, and regional-state organizations. The IMPROVE program

includes the characterization of the haze by photography, the measurement of optical extinction

with transmissometers and nephelometers, and the measurement of the composition and

concentration of the fine particles that produce the extinction and the tracers that identify

emission sources.

Figure 1 shows the locations of all particulate monitoring sites using IMPROVE samplers

through August 1995. Funding agencies include the IMPROVE committee, the NPS, the USFS,

the FSW, the Tahoe Regional Planning Agency, the Department of Energy, the Northeast States

for Coordinated Air Use Management, the state of Vermont, and the Regional District of Fraser

Cheam (British Columbia). All sites are operated by the University of California, Davis. Table 1

gives the start and end months for each site.

. Glacier

. . .

.

.

.

.

.

.

.

. .

.

.

.

. .

.

.

. .

.

.

.

.

.

..

.

. .

.

. .

.

.

.

.

.

. . . .

. .

.

Mt. Rainier

Crater Lake

Lassen

Volcanic

Point

Reyes

Jarbidge

Denali

Dunes

Yellowstone

Tonto

Saguaro

Bandelier

Guadalupe Mountains

Big Bend 

Upper

Badlands

Boundary Waters Canoe Area

Voyageurs

Great Smoky

Sipsey

Okefenokee

Chassahowitzka

Everglades

Shenandoah

Washington

Brigantine

Virgin Islands

Haleakala

Scoville

Bridger

.

.

.

Buffalo

Mountains

Mammoth Cave

Chiricahua

Mesa Verde

Great Sand

Rocky Mountain

White River

Bryce Canyon

San Gorgonio

Three Sisters

Columbia River Gorge

Snoqualamie

Petrified Forest

Weminuche

. .

. Lone

Bliss So Lake Tahoe Peak Brooklyn Lake

Great Basin

.

. Craters of

Salmon

 the Moon

.

Sawtooth . Proctor Maple

Lye Brook

.Gila

.

.

..

.

.

Mt. Zirkel

.Sula

. Dome Land

Pinnacles

.

.

.

Shining Rock

Cape Romain

Jefferson

Dolly Sods

Redwood

Abbottsford..Chilliwack

.

.

.

.

.

Ringwood.

Bridgton

Mohawk Mtn

Quabbin

Sunapee Mtn

Whiteface Mtn

Reservoir

.Isle Royale

Arches. Canyonlands

Hawaii Volcanoes

.

Acadia

Moosehorn

.

Yosemite

Sequoia Valley

Death

.

. Grand Canyon

Sycamore

Canyon

Joshua Tree

Meadview

Great Gulf.

Figure 1. Particulate sampling sites using IMPROVE samplers through August 1995.
University of California, Davis page 4 August 1995

Table 1: Start and end dates of IMPROVE particulate sampling.

site name start end site name start end

Abbotsford, British Columbia.............. 4/94...... 6/95

Acadia National Park ........................... 3/88

Arches National Park ........................... 3/88...... 5/92

Badlands National Park........................ 3/88

Bandelier National Monument ............ 3/88

Big Bend National Park ....................... 3/88

Bliss State Park, CA........................... 11/90

Boundary Waters Canoe Area ............. 3/91

Bridger Wilderness .............................. 3/88

Bridgton, ME ....................................... 9/88.... 11/93

Brigantine National Wildlife Refuge ... 3/91

Brooklyn Lake, WY............................. 4/94

Bryce Canyon National Park................ 3/88

Canyonlands National Park ................. 3/88

Cape Romain NWR ............................. 8/94

Chassahowitzka NWR ......................... 3/93

Chilliwack, British Columbia............... 4/94...... 6/95

Chiricahua National Monument ........... 3/88

Columbia River Gorge NSA ................ 6/93

Crater Lake National Park ................... 3/88

Craters of the Moon NM...................... 5/92

Death Valley National Monument ..... 10/93

Denali National Park............................ 3/88

Dolly Sods /Otter Creek Wilderness ... 3/91

Dome Lands Wilderness ...................... 8/94

Everglades National Park..................... 9/88

Gila Wilderness.................................... 4/94

Glacier National Park .......................... 3/88

Grand Canyon National Park

 Hopi Point......................................... 3/88

 Indian Gardens................................ 10/89

Great Basin National Park .................. 5/92

Great Gulf Wilderness ........................ 6/95

Great Sand Dunes NM ......................... 5/88

Great Smoky Mountains NP ............... 3/88

Guadalupe Mountains National Park .. 3/88

Haleakala National Park ..................... 2/91

Hawaii Volcanoes National Park ......... 3/88...... 4/93

Isle Royale National Park ................... 6/88...... 8/91

Jarbidge Wilderness............................. 3/88

Jefferson/James River Face Wild......... 8/94

Joshua Tree National Monument ........ 9/91...... 9/92

Lassen Volcanic National Park ........... 3/88

Lone Peak Wilderness ........................11/93

Lye Brook Wilderness..........................3/91

Mammoth Cave National Park ............3/91

Meadview National Recreation Area....9/91 ......9/92

Mesa Verde National Park....................3/88

Mohawk Mountain, CT ........................9/88 ....11/93

Moosehorn NWR ...............................12/94

Mount Rainier National Park................3/88

Mount Zirkel Wilderness....................11/93

Okefenokee NWR ................................3/91

Petrified Forest National Park ..............3/88

Pinnacles National Monument .............3/88

Point Reyes National Seashore ............3/88

Proctor Maple Research Farm, VT.....09/88

Quabbin Reservoir, MA .....................12/88 ....11/93

Redwood National Park .......................3/88

Ringwood State Park, NJ......................9/88 ....11/93

Rocky Mountain National Park ............3/88

Saguaro National Monument ...............6/88

Salmon National Forest ......................11/93

San Gorgonio Wilderness ....................3/88

Sawtooth National Forest .....................1/94

Scoville, ID...........................................5/92

Sequoia National Park .........................9/92

Shenandoah National Park....................3/88

Shining Rock Wilderness .....................8/94

Sipsy Wilderness ..................................2/92

Snoqualamie National Forest................7/93

South Lake Tahoe, CA .........................3/89

Sula (Selway Bitteroot Wilderness)......8/94

Sunapee Mountain, NH ......................12/88 ....11/93

Sycamore Canyon Wilderness ..............9/91 ......9/92

Three Sisters Wilderness ......................7/93

Tonto National Monument ..................3/88

Upper Buffalo Wilderness....................6/91

Virgin Islands National Park ..............10/90

Voyageurs National Park .....................3/88

Washington D.C. ................................3/88

Weminuche Wilderness........................3/88

Whiteface Mountain, NY .....................9/88 ....11/93

White River National Forest.................7/93

Yellowstone National Park ..................3/88

Yosemite National Park........................3/88
University of California, Davis page 5 August 1995

Sample Collection and Analysis

The standard IMPROVE sampler has four sampling modules, listed in the Table 2: A, B, and C

collect fine particles (0-2.5 μm), and D collects PM10 particles (0-10 μm). Module A Teflon is

the primary filter, providing most of the fine particle data. Module B, with a denuder before the

nylon filter to remove acidic gases, is used primarily for nitrate. Module C, with tandem quartz

filters, measures carbon in eight temperature fractions. At many sites, the Module A or D Teflon

filter is followed by a quartz filter impregnated with K2CO2 that converts SO2 gas to sulfate on

the filter. Some sites have a single Module A Teflon.

Table 2: Measurements by full IMPROVE sampler.

module: A B C D A2 or D2

size: fine fine fine PM10 gas

filter: Teflon nylon quartz Teflon impregnated

analysis: gravimetric

PIXE/PESA

XRF

absorption

IC TOR combustion gravimetric IC

variables: mass

H, Na - Pb

babs

nitrate

sulfate

chloride

carbon in

8 temperature

fractions

PM10 mass SO2

Each module is independent, with separate inlet, sizing device, flow measurement system,

critical orifice flow controller, and pump. All modules have a common controller clock. The

flow rate is measured before and after the collection by a primary method using an orifice meter

system and a secondary method using the pressure drop across the filter and the equation of flow

rate through a critical orifice. The particle sizing depends on the flow rate; the standard deviation

of annual flow rates is 2% to 3%. The average particle cut point for the fine modules has

averaged 2.6 μm, with a standard deviation of 0.2 μm. All concentrations are based on local

volumes. Two 24-hour samples are collected each week, on Wednesday and Saturday (recently

changed to 24-hour sample every three days). The filter cassettes are changed weekly by on-site

personnel and shipped to Davis for processing and analysis. All filter handling is done in clean

laboratory conditions. The recovery rate for validated data since 1991 has been 96%.

Teflon A and D: The five analytical methods used at Davis to analyze the Teflon A filters are

listed in Table 3. All PM10 (Teflon D) filters were analyzed by gravimetric analysis; 4% were

analyzed by all five methods. The elemental concentrations (H, Na-Pb) are obtained by PIXE,

PESA and XRF. XRF was added for samples collected after May 1992; this affected the

precision, MDLs and fraction found for elements between Fe and Pb.

The coefficient of absorption (babs) was measured either by an integrating plate or an integrating

sphere system. Comparisons between the two methods verify that they accurately determine the

absorption for the filter. However, because of shielding by other particles, this is less than the

atmospheric coefficient. Based on separate experiments, an empirical equation has been derived

using the areal density of all particles on the filter that corrects for the effect. The reported babs
University of California, Davis page 6 August 1995

and the precision include this correction factor. Collocated samplers with differing collection

areas verify that the expression is reasonable. The coefficient of absorption is an optical

measurement with units of 10-8 m-1 in the database. To convert to inverse megameters (10-6 m1), divide the value by 100. (For the seasonal summaries, the units are written in inverse

megameters.)

Because of volatilization of nitrate and organics during sampling, the gravimetric mass

measurements on Teflon filters may be slightly less than the actual mass. Studies comparing

nitrate collected on Teflon filters with that collected on nylon indicate that one-half to threequarters of the nitrate volatilizes from the Teflon filter during sampling. At most sites and

seasons, ammonium nitrate is approximately 5% of the fine mass, so this loss is only a small

fraction of the mass. At some western sites near major cities, such as San Gorgonio, the

ammonium sulfate may be one-half of the fine mass in summer, resulting in major

underestimates of fine mass.

Table 3. Analytical methods used for A and D Teflon filters.

gravimetric (electromicrobalance) mass

LIPM: Laser Integrating Plate Method coefficient of absorption (babs)

PIXE: Particle Induced X-ray Emission

XRF: X-ray Fluorescence

Na, Mg, Al, Si, P, S, Cl, K, Ca, Ti, V, Cr,

Mn, Fe, Co, Ni, Cu, Zn, As, Se, Br, Rb, Sr,

Zr, Mo, Pb

PESA: Proton Elastic Scattering Analysis H

Nylon B: The nylon filters were analyzed by ion chromatography (IC) at Research Triangle

Institute or Global GeoChemical for nitrate (NO3-), chloride (CL-), sulfate (BSO4), and nitrite

(NO2-). Nitrate vapors are removed prior to collection, so that the measured nitrate

concentration represents only particulate nitrate. Chloride ion (CL-) is useful for sites near

marine sources, but elsewhere the ambient concentrations are below the minimum detectable

limit (MDL). Sulfate on nylon (BSO4) is used as a quality assurance check of the sulfur

measured by PIXE on the Teflon A filter. However, we strongly recommend using the Teflon

sulfur as the measurement of ambient sulfate, because of possible adsorption of SO2 on the nylon

filter. The nitrite concentrations are generally below the MDL.

Quartz C: The quartz filters were analyzed at Desert Research Institute for carbon using the

Thermal Optical Reflectance (TOR) combustion method. The sample is heated in steps and the

evolved CO2 measured. The atmosphere is 100% He until part way through the 550°C step,

when 2% O2 is introduced. The reflectance of the sample is monitored throughout. It decreases

at 120°C and returns to the initial value during the 550°C step after oxygen is added. All carbon

before this return of initial reflectance is considered organic carbon and the remainder elemental

carbon. The eight carbon fractions in the database are defined in Table 4. OP is the portion of

E1, E2, or E3 before the reflectance returns to the initial value.
University of California, Davis page 7 August 1995

Table 4. Carbon components as a function of temperature and added oxygen.

Fraction pyrolized

fraction

temperature

range

atmosphere reflectance

vs. initial

O1 ambient to 120°C at initial

O2 120 - 250°C 100% He

O3 250 - 450°C under initial

O4 450 - 550°C

E1 OP remains at

550°C 98% He

E2 550 - 700°C 2% O2 over initial

E3 700 - 800°C

The primary interest is in two fractions, organic carbon and elemental or light-absorbing carbon

(LAC). The equations are:

total organic carbon = OC1+OC2+OC3+OC4+OP

total elemental carbon = EC1+EC2+EC3-OP

Preliminary statistical comparisons between the coefficient of absorption and the carbon

measured by TOR suggest that the carbon evolved at 550°C without added oxygen (OC4) may be

light-absorbing. The comparison also suggests that much of the OP may not be pyrolized

organic. The carbon in question (OC4+OP) could be either light-absorbing organic carbon or

elemental carbon. If it is organic, then the current organic and elemental measurements are

correct, but there is approximately three times as much absorbing carbon than would be

estimated by elemental carbon alone. If it is elemental, then the current organic carbon

concentrations are approximately 30% too large. Until we determine otherwise, we will assume

that the equations above correctly determine the organic and elemental fractions.

SO2 gas: The sulfate on the impregnated quartz filter following a Teflon filters were analyzed by

ion chromatography at Desert Research Institute or Research Triangle Institute to give the

concentration of SO2.

Concentration and Precision of Measured Variables

The general equation for the concentration of a given variable is

c

A B

V = − ,
University of California, Davis page 8 August 1995

where A is the measured mass of the variable, B is the artifact mass determined from field blanks

or secondary filters , and V is the volume determined from the average flow rate and the sample

duration. The artifact B may be produced by contamination in the filter material, and in handling

and analysis, and by adsorption of gas during collection. The artifact is negligible for all Teflon

measurements, including gravimetric analysis. It is determined from designated field blanks for

ions and from secondary filters for carbon.

The precision in each concentration is included in the data base. The overall precision is a

quadratic sum of four components of precision. These are:

(1) Fractional volume precision, fv, primarily from the flow rate measurement. A

value of 3% is used, based on third-party audits.

(2) Fractional analytical precision associated with calibration or other factors, fa.

This is zero for gravimetric analysis. The values for all other methods are

determined from replicate analyses. Most variables have an fractional analytical

precision of around 4%, so that the combined volume and analytical precision is

around 5%.

For the eight carbon fractions, the primary source of fractional uncertainty is the

separation into temperature fractions. This may be associated with temperature

regulation, but it may also be from inherent variability of the species involved.

The fractional uncertainty of the sum of all carbon species is around 3% to 4%.

The fractional uncertainty for the fractions range from 11% to 40%, averaging

22%. Thus for sums of fractions, such as total organic, the uncertainties are less

than would be estimated from the individual fractions. This will be discussed in

the section of carbon composites.

(3) Constant mass per filter precision, σa, from either the analysis or artifact

subtraction. These are determined from the standard deviations in the

designated field blanks, secondary filters, or system control filters. For large

concentrations, this is small compared to the fractional terms. This is zero for

XRF, PIXE, and PESA.

(4) Statistical precision based on the number of counts in the spectrum, σstat. This

is used for XRF, PIXE, and PESA. For large concentrations, this is small

compared to the fractional terms.

The equation for the total precision is:

[ ] σ [][] σ σ ( ) c fc fc V V v a

2 a stat 2 2

2 2

=++





 



 +





 





The relative precision depends on the concentrations. For large concentrations, only the

fractional terms (1 and 2) are important, so the relative precision is around 5%. For small

concentrations, the constant analysis/artifact term (3) or the statistical term (4) is important. At

the MDL, the precision increases to 50%.
University of California, Davis page 9 August 1995

Table 5 separates the relative precisions of key measured variables into three groups. This is

defined as the ratio of the mean precision from all sources divided by the mean concentration.

Most variables are in the most precise group, 4% to 7%.

The average MDLs are provided with each concentration in the database. A concentration is

assumed to be statistically significant only is if is larger than the MDL. For ion chromatography

and carbon the MDL corresponds to twice the precision of the field blanks or secondary filters.

For mass and absorption, the MDL corresponds to twice the analytical precision determined by

controls. For PIXE, XRF, and PESA, the MDL is based on the background under the peaks in

the spectrum and is calculated separately for each case. The assumption for all elements except

As is that there are no interference from other elements. Because the measurement for arsenic

requires subtracting the value for lead, the MDL for As depends on the Pb concentration, and is

generally larger than the value estimated from the background. When calculating averages, if the

value is below the MDL, we use one-half of the MDL as the concentration and the precision in

the concentration. In all cases, the relative precisions are around 50% at the MDL.

Table 5: Relative precision of key measured variables. Ratio of mean

precision divided by mean concentration.

range before 6/1/92 after 6/1/92

4% to 6% PM2.5, PM10, H, S, Si, K, Ca, Fe, Zn,

SO4

=, NO3-, SO2

PM2.5, PM10, S, Si, K, Ca, Fe, Cu, Zn,

SO4

=, NO3-, SO2

8% to 15% Na, Al, Ti, Cu, Br, Pb H, Na, Ti, Se, As, Br, Sr, Pb, O4, E1

> 15% V, Mn, Se, As, Sr, all carbon fractions V, Mn, O1, O2, O3, OP, E2, E3

The MDLs of many elements changed in June 1992, with the addition of XRF. Figure 2 shows

the MDLs for each season for sulfur and selenium. The MDL for Fe decreased by a a factor of

nearly 10, The MDLs for elements below Fe increased slightly, because of a reduction in

cyclotron time to compensate for the extra cost of XRF analysis.

The MDLs of standard network samples for elements measured by PIXE and XRF are given in

Table 6. Arsenic is not included because the MDL depends on the lead concentration. Also

important is the fraction of cases with statistically significant concentrations (above the MDL).

This depends on the relationship between the MDL and the ambient concentrations. Table 7

separates these into four ranges. A significant change for aluminum occurred with samples

beginning 2/93. Because of detector problems, Al, which is on the shoulder of the Si peak, was

often not detected. Before this date, Al was observed on 65% of all samples; afterwards it was

found on almost every sample. Sodium, chlorine, and chloride ion were observe in significant

amounts only at sites with marine influences.
University of California, Davis page 10 August 1995

year

mdl (ng/m3)

0.01

0.1

1

10

1988 1989 1990 1991 1992 1993 1994 1995

S

Se

Figure 2: Minimum detectable limits (MDLs) of sulfur and selenium by season.

Table 6: Minimum detectable limits (MDLs) of elements in ng/m3.

 dates Na Mg Al Si P S Cl K Ca Ti V Cr Mn

6/88-5/92 8.7 2.9 1.8 1.4 1.3 1.2 1.3 0.83 0.64 0.57 0.50 0.41 0.39

6/92-5/94 13. 4.8 3.0 2.2 1.9 1.9 2.0 1.2 0.90 0.81 0.69 0.57 0.52

Fe Ni Cu Zn Ga Se Br Rb Sr Zr Pb

6/88-5/92 0.34 0.24 0.24 0.21 0.20 0.22 0.25 0.37 0.42 0.65 0.57

6/92-5/94 0.11 0.05 0.05 0.05 0.03 0.03 0.03 0.06 0.07 0.11 0.06

Table 7: Fraction of cases with statistically significant concentrations.

range before 6/1/92 after 6/1/92

90% to 100% PM2.5, PM10,

S, H, Si, K, Ca, Ti, Fe, Zn, Br,

SO4

=, NO3-, SO2, OP, E1

PM2.5, PM10, S, H, Si, K, Ca,

Fe, Cu, Zn, Br, Pb,

SO4

=, NO3-, SO2, O4, OP, E1

70% to 90% Cu, Pb, O2, O3, O4, E2 Ti, Se, Sr, O2, O3, E2

60% to 70% Mn Mn, As, Rb

less than 40% P, V, Ni, Se, As, Rb, Sr, Zr, O1, E3 P, V, Ni, Zr, O1, E3

Level I validation procedures for sample collection include comparison of the two measurements

of flow rate. Level I validation procedures for sample analysis include comparison to recognized

standards and periodic replicate measurements. Level II validation procedures include

comparison of selected variables measured by different methods. This includes comparison of

the PIXE and XRF measurements, comparison of sulfur by PIXE on Teflon with sulfate by ion

chromatography on nylon, comparison of OMC and OMH, comparison of LAC and BABS, and

comparison of MF with RCMA and RCMC.

Collocated sampling is an important part of the quality assurance program. These are conducted

routinely at Davis and periodically at field locations. All collocated sampling has indicated that

the precision estimates in the database are accurate representations of the actual differences.
University of California, Davis page 11 August 1995

Composite Variables

The database contains only measured variables. The composite variables listed in Table 8 can be

derived from the measured variables based on reasonable assumptions.

Table 8: Composite Variables

NHSO ammonium sulfate, (NH4)2SO2: 4.125 * S

NHNO ammonium nitrate, (NH4)NO3: 1.29 * NO3-

OC total organic carbon (quartz): OC1+OC2+OC3+OC4+OP

OMC organic mass by carbon (quartz): 1.4 * OC

OMH organic mass by hydrogen (Teflon): assumes all sulfur is ammonium sulfate

and no there is hydrogen from nitrate 13.75 * (H - 0.25 * S)

LAC light absorbing carbon (quartz): EC1+EC2+EC3-OP

TC total carbon (quartz): OC1+OC2+OC3+OC4+EC1+EC2+EC3

SOOT light absorbing carbon from optical measurement: If BABS in 10-8 m-1, and

SOOT and SOIL in ng/m3, SOOT = BABS - 0.11 * SOIL

SOIL soil: 2.20*Al + 2.49*Si + 1.63*Ca + 2.42*Fe + 1.94*Ti

KNON nonsoil potassium: K - 0.6 * Fe

RCMC reconstructed mass without nitrate, carbon from quartz filter C:

NHSO + SOIL + 1.4*KNON + 2.5*Na + LAC + OMC

RCMA reconstructed mass without nitrate, carbon from Teflon filter A:

NHSO + SOIL + 1.4*KNON + 2.5*Na + BABS/2 + OMH

For the uncertainty in all composites except for the four involving the quartz measurements, we

recommend quadratically adding the uncertainties of the constituent terms times the appropriate

multiplicative constant. For example, the uncertainty for soil would be:

[σ(SOIL)]2 = [2.20 σ(Al)]2 +[2.49 σ(Si)]2 +[1.63 σ(Ca)]2 +[2.42 σ(Fe)]2 +[1.94 σ(Ti)]2

Because of the fact that temperature separation plays a much larger role for carbon fractions than

for the composites, and because the factions are not independent, we cannot follow the above

method for OC, OMC, LAC, and TC. For these we recommend the following equations for 24-

hour samples:

σ() ()( ) OC OC = + 120 0 05 2 2 . * σ( ) ()( ) OMC OMC = + 168 0 05 2 2 . *

σ( ) () ( ) LAC LAC = + 34 0 07 2 2 . * σ() ( ) ( ) TC TC = + 133 0 05 2 2 . *

The constant terms (120, 168, 34, 133) are appropriate for volumes near 32.4 m3, which is typical

for 24-hour samples. For other volumes they should be multiplied by (32.4/V). For typical 12-

hour samples, the constant terms should be multiplied by 2.

ammonium sulfate (NHSO): The sulfur on the Teflon filter is always present as sulfate. In most

cases the sulfate is fully neutralized ammonium sulfate, which is 4.125 times the sulfur

concentration. The sulfate at eastern sites during the summer is not always fully neutralized, but

overall the occurrences are rare. If 100% of the sulfur were sulfuric acid, the correct sulfate mass
University of California, Davis page 12 August 1995

would be 74% of the calculated NHSO. The uncertainty in NHSO is 1.4 times the uncertainty in

S. To calculate sulfate ion from sulfur, multiply by 3.0.

ammonium nitrate (NHNO): As with sulfate, the nitrate is expected to be fully neutralized

ammonium nitrate. This is 1.29 times the nitrate ion concentration. The uncertainty in NHNO is

2.9 times the uncertainty in NO3

-

.

total organic carbon (OC) and organic mass by carbon (OMC): The total organic carbon

concentration is assumed to be the sum of the four organic fractions plus the pyrolized fraction,

OP. To obtain organic mass, we recommend multiplying the total carbon by 1.4, which assumes

that carbon accounts for 71% of the organic mass. The ratios for various typical compounds

range from 1.2 to 1.8.

organic mass by hydrogen (OMH): The hydrogen on the Teflon filter is associated with sulfate,

organics, nitrate, and water. Since the analysis is done in vacuum, all water will volatilize. We

also assume that no significant hydrogen from nitrate remains. If we assume that the sulfate is

fully neutralized ammonium sulfate, we can estimate the organic concentration by subtracting the

hydrogen from sulfate and multiplying the difference by a constant representing the fraction of

hydrogen. (We suggest a constant of 13.75. This gives the best comparison with OMC for the

network samples. However, a value near 10 is suggested by various typical organic compounds.)

The OMH variable is defined only when both H and S are valid measurements.

The OMH calculation is invalid when (1) there is high nitrate relative to sulfate, as at sites near

Los Angeles and San Francisco, and (2) the sulfur is not present as ammonium sulfate. This

latter includes sites with marine sulfur, and sites in the eastern United States with unneutralized

sulfate. For the western sites except San Gorgonio, Sequoia, Pinnacles, Point Reyes, Redwoods,

and Hawaii Volcanoes, the correlation coefficient (r2) between OMH and OMC for the first two

years was 0.89 and the slope was 0.98 ± 0.02. For 1992, r2 was 0.87 and the slope was

1.07±0.01. The main advantage of using OMH at these sites is that its precision is better than

that for OMC during periods of low organic, as winter in the West. At sites in the East, OMH is

often low because of unneutralized sulfate, and imprecise because of the high sulfate relative to

organic. For 10 eastern sites in 1992, the average OMH was one-half the average OMC, and

one-half of the OMH values were less than the minimum quantifiable limit.

An organic artifact was found on a batch of Teflon filters used between September 1990 and

November 1991. Approximately 7% of the samples had OMH significantly larger than OMC.

The artifact was apparently completely organic (there was no elevated sulfur) and appeared

during collection. For these samples, both H and MF (fine mass) were invalidated. These

variables were not invalidated on the remaining 93%, but flagged as less reliable than normal.

No other variables were invalidated.

light-absorbing carbon (LAC): This is the sum of elemental carbon fractions. The pyrolized

fraction is subtracted. Preliminary analyses indicate that some of the O4 fraction may absorb

light, and that OP may overestimate the pyrolytic mass.

light-absorbing carbon (SOOT): This is estimated from the coefficient of absorption assuming

absorption efficiencies of 10 m2/g for elemental carbon and 0.11 m2/g for soil.
University of California, Davis page 13 August 1995

soil (SOIL): This is a sum of the soil derived elements (Al, Si, K, Ca, Ti, Fe) along with their

normal oxides. The variable does not depend on the type of soil, such as sediment, sandstone, or

limestone. One fine element, K, however, may partly derive from smoke as well as soil. We

have eliminated this from the calculation and used Fe as a surrogate. This is discussed in nonsoil

potassium below.

nonsoil potassium (KNON): Fine potassium has two major sources, soil and smoke, with the

smoke potassium on much smaller particles than the soil potassium. The potassium in coarse

particles will be solely produced from soil. The soil potassium is estimated from the measured

concentration of Fe and the ratio of K/Fe of 0.6 measured on coarse samples ( 2.5 to 15 μm)

collected between 1982 and 1986. This ratio depends on the soil composition and varies slightly

from site to site. If the ratio were slightly smaller (say 0.5), the KNON values will be negative

when there is no smoke influence. The residual potassium, K - 0.6*Fe, is then assumed to be

produced by smoke. The burning of most organic fuels will produce potassium vapor. During

transport, this vapor will transform into fine particles. The KNON parameter is not a quantitative

measure of the total smoke mass, since the ratio of nonsoil potassium to total smoke mass will

vary widely, depending on the fuel type and the transport time. However, the KNON parameter

can be used as an indicator of a nonsoil contribution for samples with large KNON. In some

situations there may be some fine Fe from industrial sources which could cause occasional

smoke episodes to be lost.

reconstructed mass (RCMC and RCMA): We use two estimates of reconstructed mass, which

differ only in the estimation of organic mass and light-absorbing carbon. RCMC uses the quartz

C measurements, while the RCMA uses the Teflon A measurements. The RCMC estimate

should be used at sites where the OMH calculation is invalid, while the RCMA estimate should

be used when the organic and LAC concentrations are small. It can also be used when there is no

quartz measurement, as with a single Module A sampler.

Neither reconstructed mass estimate includes nitrates. The Teflon filter does not collect any

nitrate in the vapor state, and loses one-half to three-quarters of the particulate nitrate by

volatilization during sampling. At most sites this is a few percent the reconstructed mass.

Precision: The precisions of the composite variables are estimated by quadratically adding the

precisions of the components. This assumes that the precisions are independent. Since this is

not quite valid, the calculated precisions for composites formed by adding (SOIL, OMC, LAC,

RCMC, RCMA) are slightly smaller than they should be. For example, the average calculated

precision for SOIL of 4% should probably be closer to 5%. The composite formed by subtraction

(OMH) may have a slightly smaller precision than reported.
University of California, Davis page 14 August 1995

Major Components of Fine Mass

ammonium sulfate: Sulfate is generally the major component of the fine mass throughout the

United States, accounting for 20-40% of the mass in the West to 45-60% in the East. (It is less

than organic at most sites in the Northwest and less than nitrate at San Gorgonio.) Sulfur

primarily enters the atmosphere as SO2 gas. The SO2 converts in the atmosphere to sulfuric acid,

which reacts with ammonia gas to form ammonium sulfate. There are periods at some sites

when there is too much sulfuric acid to be neutralized by ammonia; some of it may remain as

sulfuric acid. The rate of transformation and the size of the resulting particle depends on the

relative humidity. This has a significant impact on visibility, because in high humidity the

sulfate particles are larger and scatter light much more efficiently relative to the mass of sulfur.

That is, the scattering per unit mass of sulfur is greater at high humidity than at low humidity.

This growth can occur anytime during the lifetime of the particle. If the relative humidity later

decreases the particle will shrink, but not immediately. Therefore the particle size and scattering

efficiency depends on the relative humidity of the past as well as the present. The scattering

efficiency for a small sulfate particle is less than that for a large one, but still significant.

Because sulfate is such an efficient scatterer of light, its contribution to the extinction budget is

even larger than its contribution to the mass budget.

ammonium nitrate: Nitrate is generally a minor component of the particulate mass and the

extinction budget. At half of the sites, ammonium nitrate is less than 6% of the mass, compared

to 32% for ammonium sulfate. The main exceptions are on the West Coast, where the average

nitrate concentration can be more than the average sulfate concentration. In the east, it is 15% of

ammonium sulfate.

soil: Most of this component is produced by soil dust. At some sites in the West, soil can be one

of the largest components of the mass. Its effect on visibility is less per unit mass than sulfate,

because the particles are generally larger than the optimum size. Soil emission is significantly

enhanced by disturbances to the soil: off-road and dirt-road vehicular traffic, agricultural

activities, bison stampedes. A smaller source of these elements can come from industrial and

mining activities.

organic: Organic material is the largest component at most sites in the northwest, and elsewhere

the second largest component. Possible sources are fires (wildfires, controlled burns, slash and

field burning, incineration, household heating), industrial emissions, and biogenic emissions.

elemental carbon or light-absorbing carbon: This component accounts for 5% to 10% of the fine

mass, depending on whether LAC or BABS is used.

reconstructed mass: The reconstructed mass by either definition generally correlates well with

the gravimetric mass, accounting for almost all of the fine mass. About 20% of the unaccounted

mass may be nitrate, with the remainder primarily residual water on the particles.

 v:\cnl\requests\sendout\dataguid.doc
Appendix C – IMPROVE Program Visibility Trend Tables
1
1

Table C-1. Annual trends of particle ambient mass for the 20% least impaired, 40-60% mid-range, and 20% most impaired days at

Northeast IMPROVE monitor sites.

Acadia National Park, ME-------------------------------------------------- SITE=ACAD GROUP=10 --------------------------------------------------

SYEAR TMASS CM FMASS SO4 F_SO4 NO3 F_NO3 OC F_OMC LAC F_LAC SOIL1 F_SOIL

88 7.57 5.23 2.34 1.02 0.44 0.16 0.07 0.76 0.33 0.23 0.10 0.16 0.0789 7.79 5.26 2.53 1.32 0.52 0.18 0.07 0.70 0.28 0.22 0.09 0.11 0.0490 8.26 5.59 2.67 1.39 0.52 0.16 0.06 0.83 0.31 0.18 0.07 0.10 0.0491 5.25 2.72 2.53 1.20 0.48 0.18 0.07 0.84 0.33 0.20 0.08 0.10 0.0492 5.06 3.05 2.01 0.98 0.49 0.13 0.06 0.66 0.33 0.16 0.08 0.08 0.0493 5.79 3.35 2.44 1.13 0.46 0.15 0.06 0.85 0.35 0.17 0.07 0.14 0.0694 5.46 3.41 2.04 0.90 0.44 0.15 0.07 0.71 0.35 0.17 0.08 0.12 0.0695 6.01 4.02 2.00 1.06 0.53 0.14 0.07 0.57 0.28 0.13 0.07 0.10 0.0596 5.16 3.29 1.87 0.88 0.47 0.10 0.05 0.67 0.36 0.12 0.06 0.10 0.0597 7.96 5.74 2.23 1.05 0.47 0.12 0.05 0.78 0.35 0.12 0.05 0.15 0.0798 5.61 3.24 2.36 1.01 0.43 0.12 0.05 0.88 0.37 0.12 0.05 0.22 0.09

-------------------------------------------------- SITE=ACAD GROUP=50 --------------------------------------------------

SYEAR TMASS CM FMASS SO4 F_SO4 NO3 F_NO3 OC F_OMC LAC F_LAC SOIL1 F_SOIL

88 7.14 2.26 4.88 2.41 0.49 0.46 0.09 1.36 0.28 0.40 0.08 0.25 0.0589 8.41 2.55 5.86 3.24 0.55 0.65 0.11 1.31 0.22 0.45 0.08 0.21 0.0490 8.82 4.06 4.76 2.89 0.61 0.26 0.06 1.11 0.23 0.31 0.06 0.19 0.0491 10.87 5.90 4.97 2.72 0.55 0.34 0.07 1.42 0.29 0.30 0.06 0.18 0.0492 7.68 3.05 4.63 2.39 0.52 0.32 0.07 1.37 0.30 0.39 0.08 0.16 0.0493 8.46 3.74 4.71 2.48 0.53 0.38 0.08 1.40 0.30 0.26 0.06 0.19 0.0494 9.68 4.92 4.77 2.40 0.50 0.44 0.09 1.46 0.31 0.27 0.06 0.20 0.0495 9.05 4.95 4.10 2.09 0.51 0.41 0.10 1.19 0.29 0.21 0.05 0.20 0.0596 9.13 4.89 4.25 2.41 0.57 0.30 0.07 1.15 0.27 0.21 0.05 0.18 0.0497 7.99 3.96 4.03 2.34 0.58 0.24 0.06 1.08 0.27 0.19 0.05 0.17 0.0498 7.73 3.70 4.03 2.01 0.50 0.24 0.06 1.34 0.33 0.21 0.05 0.23 0.06

-------------------------------------------------- SITE=ACAD GROUP=90 --------------------------------------------------

SYEAR TMASS CM FMASS SO4 F_SO4 NO3 F_NO3 OC F_OMC LAC F_LAC SOIL1 F_SOIL

88 21.59 8.02 13.58 7.25 0.53 0.91 0.07 4.01 0.30 0.80 0.06 0.61 0.0589 17.65 3.39 14.26 8.31 0.58 0.82 0.06 4.09 0.29 0.68 0.05 0.36 0.0390 18.60 7.49 11.11 6.53 0.59 0.69 0.06 2.90 0.26 0.68 0.06 0.32 0.0391 17.61 5.68 11.92 6.40 0.54 0.76 0.06 3.80 0.32 0.60 0.05 0.36 0.0392 15.70 2.72 12.98 8.36 0.64 0.72 0.06 3.03 0.23 0.58 0.04 0.29 0.0293 19.06 5.45 13.61 7.98 0.59 0.93 0.07 3.57 0.26 0.58 0.04 0.56 0.0494 21.73 8.20 13.53 8.20 0.61 0.73 0.05 3.55 0.26 0.57 0.04 0.48 0.0495 18.14 7.09 11.05 6.00 0.54 0.68 0.06 3.61 0.33 0.42 0.04 0.35 0.0396 17.24 6.25 10.99 7.09 0.64 0.52 0.05 2.69 0.24 0.44 0.04 0.26 0.0297 17.19 6.85 10.34 5.89 0.57 0.46 0.04 3.28 0.32 0.42 0.04 0.29 0.0398 16.02 5.44 10.58 6.81 0.64 0.39 0.04 2.49 0.24 0.44 0.04 0.46 0.04
2

Brigantine Wilderness Area, NJ-------------------------------------------------- SITE=BRIG GROUP=10 --------------------------------------------------

SYEAR TMASS CM FMASS SO4 F_SO4 NO3 F_NO3 OC F_OMC LAC F_LAC SOIL1 F_SOIL

92 9.99 5.63 4.36 2.25 0.52 0.50 0.11 1.17 0.27 0.26 0.06 0.18 0.0493 12.73 7.13 5.60 2.90 0.52 0.64 0.11 1.45 0.26 0.34 0.06 0.26 0.0594 14.33 9.48 4.85 2.08 0.43 0.65 0.13 1.36 0.28 0.38 0.08 0.38 0.0895 20.95 16.65 4.29 2.25 0.52 0.57 0.13 0.98 0.23 0.26 0.06 0.23 0.0596 16.36 11.40 4.96 2.44 0.49 0.55 0.11 1.32 0.27 0.34 0.07 0.31 0.0697 16.67 12.67 4.00 2.03 0.51 0.42 0.11 1.05 0.26 0.27 0.07 0.22 0.0698 13.18 8.76 4.41 2.15 0.49 0.35 0.08 1.27 0.29 0.32 0.07 0.33 0.07

-------------------------------------------------- SITE=BRIG GROUP=50 --------------------------------------------------

SYEAR TMASS CM FMASS SO4 F_SO4 NO3 F_NO3 OC F_OMC LAC F_LAC SOIL1 F_SOIL

92 14.55 5.59 8.96 5.07 0.57 1.00 0.11 2.13 0.24 0.54 0.06 0.23 0.0393 18.16 7.96 10.20 5.59 0.55 1.25 0.12 2.43 0.24 0.55 0.05 0.38 0.0494 21.03 10.61 10.42 4.99 0.48 1.76 0.17 2.45 0.24 0.64 0.06 0.58 0.0695 19.85 11.32 8.52 4.24 0.50 1.55 0.18 1.79 0.21 0.50 0.06 0.45 0.0596 22.19 13.12 9.07 5.30 0.58 0.91 0.10 2.08 0.23 0.45 0.05 0.32 0.0497 20.97 12.73 8.23 4.81 0.58 0.71 0.09 1.90 0.23 0.45 0.05 0.36 0.0498 21.65 13.79 7.86 4.06 0.52 0.70 0.09 2.18 0.28 0.51 0.06 0.41 0.05

-------------------------------------------------- SITE=BRIG GROUP=90 --------------------------------------------------

SYEAR TMASS CM FMASS SO4 F_SO4 NO3 F_NO3 OC F_OMC LAC F_LAC SOIL1 F_SOIL

92 27.32 7.85 19.47 12.68 0.65 1.39 0.07 3.99 0.21 0.84 0.04 0.56 0.0393 27.57 9.08 18.49 10.01 0.54 2.24 0.12 4.76 0.26 0.88 0.05 0.59 0.0394 32.85 14.01 18.84 10.38 0.55 1.81 0.10 4.52 0.24 0.87 0.05 1.25 0.0795 32.10 13.61 18.49 11.84 0.64 1.57 0.08 3.80 0.21 0.67 0.04 0.62 0.0396 30.07 12.89 17.19 11.25 0.65 1.08 0.06 3.48 0.20 0.80 0.05 0.57 0.0397 36.68 17.91 18.78 12.48 0.66 0.84 0.04 4.20 0.22 0.60 0.03 0.65 0.0398 32.99 11.88 21.11 13.65 0.65 0.40 0.02 5.42 0.26 0.94 0.04 0.71 0.03
3

Lye Brook Wilderness Area, VT-------------------------------------------------- SITE=LYBR GROUP=10 --------------------------------------------------

SYEAR TMASS CM FMASS SO4 F_SO4 NO3 F_NO3 OC F_OMC LAC F_LAC SOIL1 F_SOIL

92 3.32 1.84 1.48 0.74 0.50 0.11 0.07 0.50 0.34 0.08 0.05 0.05 0.0493 4.65 2.90 1.75 0.82 0.47 0.18 0.10 0.58 0.33 0.07 0.04 0.09 0.0594 5.23 3.48 1.75 0.68 0.39 0.17 0.10 0.66 0.37 0.12 0.07 0.12 0.0795 3.01 1.16 1.85 0.93 0.50 0.30 0.16 0.40 0.22 0.12 0.06 0.10 0.0596 3.60 1.60 2.01 1.19 0.59 0.15 0.07 0.43 0.21 0.11 0.06 0.14 0.0797 3.55 1.50 2.04 0.92 0.45 0.25 0.12 0.69 0.34 0.09 0.04 0.10 0.0598 4.34 2.19 2.15 0.86 0.40 0.18 0.09 0.79 0.37 0.12 0.06 0.19 0.09

-------------------------------------------------- SITE=LYBR GROUP=50 --------------------------------------------------

SYEAR TMASS CM FMASS SO4 F_SO4 NO3 F_NO3 OC F_OMC LAC F_LAC SOIL1 F_SOIL

92 6.36 1.91 4.45 2.33 0.52 0.56 0.13 1.15 0.26 0.23 0.05 0.17 0.0493 7.12 3.34 3.78 1.84 0.49 0.39 0.10 1.16 0.31 0.19 0.05 0.19 0.0594 9.88 5.24 4.64 2.16 0.47 0.59 0.13 1.32 0.28 0.26 0.06 0.32 0.0795 6.69 2.41 4.27 2.27 0.53 0.51 0.12 1.05 0.25 0.24 0.06 0.20 0.0596 6.80 2.01 4.79 2.83 0.59 0.38 0.08 1.15 0.24 0.22 0.05 0.22 0.0597 7.01 2.84 4.17 2.27 0.55 0.34 0.08 1.19 0.29 0.19 0.05 0.18 0.0498 7.74 2.26 5.47 2.46 0.45 0.66 0.12 1.61 0.29 0.26 0.05 0.49 0.09

-------------------------------------------------- SITE=LYBR GROUP=90 --------------------------------------------------

SYEAR TMASS CM FMASS SO4 F_SO4 NO3 F_NO3 OC F_OMC LAC F_LAC SOIL1 F_SOIL

92 15.92 3.23 12.69 8.32 0.66 0.88 0.07 2.65 0.21 0.47 0.04 0.37 0.0393 17.90 4.29 13.61 8.45 0.62 0.95 0.07 3.11 0.23 0.58 0.04 0.52 0.0494 20.39 5.98 14.41 8.93 0.62 0.99 0.07 3.02 0.21 0.55 0.04 0.91 0.0695 16.88 3.33 13.56 8.73 0.64 0.56 0.04 3.27 0.24 0.54 0.04 0.45 0.0396 15.07 3.23 11.84 7.04 0.59 0.82 0.07 3.03 0.26 0.49 0.04 0.47 0.0497 15.30 2.53 12.76 8.80 0.69 0.48 0.04 2.44 0.19 0.41 0.03 0.62 0.0598 18.67 3.31 15.36 10.28 0.67 0.60 0.04 3.24 0.21 0.59 0.04 0.65 0.04
4

Moosehorn Wilderness Area, ME-------------------------------------------------- SITE=MOOS GROUP=10 --------------------------------------------------

SYEAR TMASS CM FMASS SO4 F_SO4 NO3 F_NO3 OC F_OMC LAC F_LAC SOIL1 F_SOIL

95 4.59 2.21 2.38 1.03 0.43 0.20 0.09 0.87 0.36 0.15 0.06 0.12 0.0596 5.12 3.04 2.08 0.93 0.45 0.11 0.06 0.79 0.38 0.14 0.07 0.11 0.0597 4.87 2.99 1.88 0.77 0.41 0.12 0.06 0.78 0.42 0.12 0.06 0.09 0.0598 5.53 3.10 2.43 0.96 0.40 0.11 0.04 0.95 0.39 0.17 0.07 0.25 0.10

-------------------------------------------------- SITE=MOOS GROUP=50 --------------------------------------------------

SYEAR TMASS CM FMASS SO4 F_SO4 NO3 F_NO3 OC F_OMC LAC F_LAC SOIL1 F_SOIL

95 7.39 2.87 4.52 2.20 0.49 0.38 0.08 1.48 0.33 0.25 0.05 0.21 0.0596 9.22 4.87 4.36 2.04 0.47 0.24 0.06 1.63 0.37 0.27 0.06 0.18 0.0497 9.33 5.04 4.29 2.08 0.48 0.26 0.06 1.53 0.36 0.23 0.05 0.19 0.0598 8.81 4.56 4.25 1.87 0.44 0.30 0.07 1.54 0.36 0.26 0.06 0.29 0.07

-------------------------------------------------- SITE=MOOS GROUP=90 --------------------------------------------------

SYEAR TMASS CM FMASS SO4 F_SO4 NO3 F_NO3 OC F_OMC LAC F_LAC SOIL1 F_SOIL

95 14.05 3.81 10.24 5.36 0.52 0.67 0.07 3.48 0.34 0.39 0.04 0.34 0.0396 13.58 4.01 9.57 5.14 0.54 0.53 0.06 3.16 0.33 0.46 0.05 0.28 0.0397 14.39 4.42 9.97 5.34 0.54 0.33 0.03 3.64 0.37 0.37 0.04 0.28 0.0398 12.13 2.52 9.62 5.77 0.60 0.41 0.04 2.71 0.28 0.39 0.04 0.34 0.04
5

Washington, DC-------------------------------------------------- SITE=WASH GROUP=10 --------------------------------------------------

SYEAR TMASS CM FMASS SO4 F_SO4 NO3 F_NO3 OC F_OMC LAC F_LAC SOIL1 F_SOIL

89 16.80 7.82 8.98 3.69 0.41 1.20 0.13 2.45 0.27 1.15 0.13 0.49 0.0590 30.72 22.31 8.40 3.55 0.42 1.15 0.14 2.21 0.26 1.07 0.13 0.42 0.0591 13.88 5.17 8.71 3.89 0.45 1.33 0.15 2.19 0.25 0.87 0.10 0.43 0.0592 13.91 4.96 8.95 4.30 0.48 0.95 0.11 2.31 0.26 0.89 0.10 0.49 0.0693 15.88 5.26 10.62 4.95 0.47 1.34 0.13 2.78 0.26 0.92 0.09 0.62 0.0694 16.55 7.63 8.92 3.49 0.39 1.45 0.16 2.35 0.26 0.97 0.11 0.65 0.0795 11.11 4.56 6.55 3.23 0.49 0.78 0.12 1.50 0.23 0.62 0.10 0.42 0.0696 13.87 6.27 7.60 3.61 0.48 0.98 0.13 1.83 0.24 0.71 0.09 0.47 0.0697 11.64 4.64 7.00 3.64 0.52 0.56 0.08 1.66 0.24 0.63 0.09 0.51 0.0798 11.37 4.18 7.19 2.93 0.41 0.73 0.10 2.08 0.29 0.77 0.11 0.68 0.09

-------------------------------------------------- SITE=WASH GROUP=50 --------------------------------------------------

SYEAR TMASS CM FMASS SO4 F_SO4 NO3 F_NO3 OC F_OMC LAC F_LAC SOIL1 F_SOIL

89 25.93 10.16 15.77 6.63 0.42 2.45 0.16 4.10 0.26 1.69 0.11 0.91 0.0690 41.66 27.09 14.57 5.94 0.41 2.44 0.17 3.83 0.26 1.72 0.12 0.63 0.0491 24.00 6.06 17.93 8.98 0.50 2.42 0.13 4.27 0.24 1.54 0.09 0.73 0.0492 24.00 6.81 17.19 8.20 0.48 2.65 0.15 4.06 0.24 1.51 0.09 0.77 0.0493 26.79 8.30 18.49 8.62 0.47 2.81 0.15 4.80 0.26 1.52 0.08 0.75 0.0494 24.13 7.69 16.44 6.99 0.43 2.25 0.14 4.49 0.27 1.71 0.10 0.99 0.0695 19.04 6.23 12.81 6.05 0.47 2.01 0.16 3.02 0.24 1.07 0.08 0.66 0.0596 20.03 6.44 13.58 5.99 0.44 1.91 0.14 3.69 0.27 1.08 0.08 0.91 0.0797 16.77 3.90 12.87 5.88 0.46 2.00 0.16 3.37 0.26 1.00 0.08 0.62 0.0598 16.38 4.20 12.18 5.71 0.47 1.47 0.12 3.19 0.26 1.05 0.09 0.76 0.06

-------------------------------------------------- SITE=WASH GROUP=90 --------------------------------------------------

SYEAR TMASS CM FMASS SO4 F_SO4 NO3 F_NO3 OC F_OMC LAC F_LAC SOIL1 F_SOIL

89 37.35 13.50 23.85 11.62 0.49 3.20 0.13 5.47 0.23 2.17 0.09 1.38 0.0690 58.77 35.92 22.85 9.24 0.40 3.00 0.13 6.89 0.30 2.72 0.12 1.01 0.0491 40.24 9.08 31.16 18.58 0.60 2.87 0.09 6.78 0.22 1.91 0.06 1.01 0.0392 41.17 9.30 31.87 18.47 0.58 3.74 0.12 6.20 0.19 2.04 0.06 1.42 0.0493 43.08 10.39 32.69 15.34 0.47 4.12 0.13 8.93 0.27 2.33 0.07 1.97 0.0694 37.44 9.26 28.18 14.43 0.51 2.56 0.09 7.62 0.27 2.34 0.08 1.23 0.0495 31.61 7.29 24.32 12.72 0.52 2.79 0.11 6.20 0.26 1.69 0.07 0.92 0.0496 30.88 5.97 24.90 15.17 0.61 1.51 0.06 5.59 0.22 1.74 0.07 0.90 0.0497 30.08 5.72 24.36 13.61 0.56 2.49 0.10 5.90 0.24 1.36 0.06 1.00 0.0498 27.80 2.94 24.87 14.94 0.60 0.41 0.02 6.67 0.27 1.74 0.07 1.11 0.04
6

Key:GROUP 10 = 20% least impaired visibility daysGROUP 50 = 40 – 60% mid-range visibility daysGROUP 90 = 20% most impaired visibility daysSYEAR = Sample year (March – February)TMASS = Total mass (μg/m3)

CM = Coarse mass (PM10 – PM2.5) (μg/m3)

FMASS = Reconstructed fine particle mass (μg/m3)

SO4 = Ammonium sulfate (μg/m3)

NO3 = Ammonium nitrate (μg/m3)

OC = Organic carbon (μg/m3)

LAC = Light absorbing carbon (μg/m3)

SOIL1 = Fine soil (μg/m3)

F_*** = Mass fraction of speciated particle relative to reconstructed fine particleData from IMPROVE, http://alta_vista.cira.colostate.edu/NOTE: Great Gulf Wilderness Area data tables not available from IMPROVE web site.
7

Table C-2. Annual trends of particle light extinction for the 20% least impaired, 40-60% mid-range, and 20% most impaired days at

Northeast IMPROVE monitor sites.

Acadia National Park, ME-------------------------------------------------- SITE=ACAD GROUP=10 --------------------------------------------------

SYEAR SVR DV TBEXT ESO4 F_ESO4 ENO3 F_ENO3 EOC F_EOC ELAC F_ELAC ECM F_ECM

88 126 11 21.04 10.66 0.51 1.70 0.08 3.06 0.15 2.33 0.11 3.30 0.1689 115 12 23.91 13.75 0.58 1.93 0.08 2.80 0.12 2.17 0.09 3.27 0.1490 112 13 24.77 14.48 0.58 1.67 0.07 3.32 0.13 1.84 0.07 3.46 0.1491 124 12 21.55 12.53 0.58 1.87 0.09 3.37 0.16 2.04 0.09 1.73 0.0892 141 10 17.75 10.26 0.58 1.32 0.07 2.64 0.15 1.63 0.09 1.91 0.1193 128 11 20.59 11.73 0.57 1.59 0.08 3.40 0.17 1.71 0.08 2.15 0.1094 141 10 17.65 9.42 0.53 1.51 0.09 2.82 0.16 1.73 0.10 2.17 0.1295 137 11 18.56 11.00 0.59 1.46 0.08 2.28 0.12 1.31 0.07 2.51 0.1496 149 10 16.16 9.17 0.57 1.05 0.07 2.66 0.16 1.21 0.07 2.08 0.1397 130 11 20.12 10.98 0.55 1.23 0.06 3.12 0.16 1.19 0.06 3.60 0.1898 136 11 18.80 10.58 0.56 1.28 0.07 3.54 0.19 1.24 0.07 2.16 0.12

-------------------------------------------------- SITE=ACAD GROUP=50 --------------------------------------------------

SYEAR SVR DV TBEXT ESO4 F_ESO4 ENO3 F_ENO3 EOC F_EOC ELAC F_ELAC ECM F_ECM

88 77 16 40.97 25.14 0.61 4.78 0.12 5.44 0.13 4.00 0.10 1.61 0.0489 63 18 52.02 33.80 0.65 6.76 0.13 5.22 0.10 4.50 0.09 1.74 0.0390 74 17 43.00 30.14 0.70 2.74 0.06 4.43 0.10 3.06 0.07 2.63 0.0691 72 17 44.33 28.38 0.64 3.55 0.08 5.70 0.13 2.98 0.07 3.72 0.0892 79 16 39.60 24.96 0.63 3.30 0.08 5.49 0.14 3.86 0.10 1.99 0.0593 77 16 40.49 25.82 0.64 4.00 0.10 5.62 0.14 2.63 0.06 2.43 0.0694 76 16 41.33 25.04 0.61 4.61 0.11 5.83 0.14 2.70 0.07 3.14 0.0895 85 15 36.10 21.83 0.60 4.25 0.12 4.74 0.13 2.11 0.06 3.17 0.0996 81 16 38.01 25.07 0.66 3.14 0.08 4.59 0.12 2.09 0.06 3.12 0.0897 85 15 35.74 24.43 0.68 2.51 0.07 4.31 0.12 1.94 0.05 2.55 0.0798 90 15 33.32 20.93 0.63 2.49 0.07 5.36 0.16 2.08 0.06 2.46 0.07

-------------------------------------------------- SITE=ACAD GROUP=90 --------------------------------------------------

SYEAR SVR DV TBEXT ESO4 F_ESO4 ENO3 F_ENO3 EOC F_EOC ELAC F_ELAC ECM F_ECM

88 31 25 114.4 75.58 0.66 9.44 0.08 16.04 0.14 7.96 0.07 5.42 0.0589 30 26 120.8 86.61 0.72 8.55 0.07 16.37 0.14 6.84 0.06 2.39 0.0290 36 24 98.40 68.04 0.69 7.18 0.07 11.60 0.12 6.76 0.07 4.81 0.0591 36 24 99.59 66.67 0.67 7.91 0.08 15.22 0.15 6.02 0.06 3.77 0.0492 31 25 114.5 87.12 0.76 7.52 0.07 12.12 0.11 5.78 0.05 1.92 0.0293 31 25 116.7 83.13 0.71 9.65 0.08 14.29 0.12 5.81 0.05 3.82 0.0394 30 26 118.4 85.50 0.72 7.58 0.06 14.22 0.12 5.67 0.05 5.40 0.0595 38 23 92.78 62.54 0.67 7.05 0.08 14.43 0.16 4.16 0.04 4.61 0.0596 36 24 98.36 73.85 0.75 5.40 0.05 10.74 0.11 4.35 0.04 4.01 0.0497 40 23 87.88 61.35 0.70 4.84 0.06 13.13 0.15 4.15 0.05 4.40 0.0598 38 23 93.03 70.95 0.76 4.04 0.04 9.96 0.11 4.36 0.05 3.72 0.04
8

Brigantine Wilderness Area, NJ-------------------------------------------------- SITE=BRIG GROUP=10 --------------------------------------------------

SYEAR SVR DV TBEXT ESO4 F_ESO4 ENO3 F_ENO3 EOC F_EOC ELAC F_ELAC ECM F_ECM

92 78 16 40.22 24.02 0.60 5.32 0.13 4.68 0.12 2.64 0.07 3.56 0.0993 63 18 51.62 31.00 0.60 6.82 0.13 5.80 0.11 3.45 0.07 4.54 0.0994 72 17 44.53 22.23 0.50 6.97 0.16 5.45 0.12 3.81 0.09 6.07 0.1495 69 17 46.92 24.09 0.51 6.05 0.13 3.92 0.08 2.64 0.06 10.22 0.2296 68 18 47.75 26.06 0.55 5.89 0.12 5.27 0.11 3.37 0.07 7.15 0.1597 77 16 40.95 21.73 0.53 4.52 0.11 4.22 0.10 2.65 0.06 7.83 0.1998 77 16 40.54 22.97 0.57 3.75 0.09 5.08 0.13 3.15 0.08 5.59 0.14

-------------------------------------------------- SITE=BRIG GROUP=50 --------------------------------------------------

SYEAR SVR DV TBEXT ESO4 F_ESO4 ENO3 F_ENO3 EOC F_EOC ELAC F_ELAC ECM F_ECM

92 42 22 82.27 54.15 0.66 10.66 0.13 8.50 0.10 5.37 0.07 3.59 0.0493 38 23 93.47 59.74 0.64 13.35 0.14 9.74 0.10 5.49 0.06 5.16 0.0694 37 24 95.32 53.30 0.56 18.83 0.20 9.81 0.10 6.43 0.07 6.95 0.0795 43 22 81.25 45.31 0.56 16.57 0.20 7.15 0.09 4.99 0.06 7.24 0.0996 40 23 87.44 56.63 0.65 9.77 0.11 8.32 0.10 4.53 0.05 8.20 0.0997 44 22 79.10 51.42 0.65 7.54 0.10 7.61 0.10 4.52 0.06 8.00 0.1098 47 21 73.37 43.35 0.59 7.51 0.10 8.73 0.12 5.10 0.07 8.68 0.12

-------------------------------------------------- SITE=BRIG GROUP=90 --------------------------------------------------

SYEAR SVR DV TBEXT ESO4 F_ESO4 ENO3 F_ENO3 EOC F_EOC ELAC F_ELAC ECM F_ECM

92 21 29 180.1 135.5 0.75 14.89 0.08 15.97 0.09 8.43 0.05 5.27 0.0393 22 29 164.9 107.0 0.65 23.92 0.15 19.04 0.12 8.85 0.05 6.04 0.0494 22 29 166.8 111.0 0.67 19.32 0.12 18.08 0.11 8.74 0.05 9.66 0.0695 21 29 173.9 126.5 0.73 16.73 0.10 15.19 0.09 6.66 0.04 8.78 0.0596 23 28 162.0 120.2 0.74 11.59 0.07 13.93 0.09 7.95 0.05 8.31 0.0597 21 29 176.6 133.3 0.76 9.03 0.05 16.82 0.10 5.99 0.03 11.40 0.0698 20 30 189.0 145.9 0.77 4.23 0.02 21.67 0.11 9.37 0.05 7.84 0.04
9

Lye Brook Wilderness Area, VT-------------------------------------------------- SITE=LYBR GROUP=10 --------------------------------------------------

SYEAR SVR DV TBEXT ESO4 F_ESO4 ENO3 F_ENO3 EOC F_EOC ELAC F_ELAC ECM F_ECM

92 171 8 12.81 7.71 0.60 1.16 0.09 2.00 0.16 0.78 0.06 1.16 0.0993 154 9 15.35 8.55 0.56 1.90 0.12 2.33 0.15 0.73 0.05 1.83 0.1294 157 9 14.90 7.11 0.48 1.74 0.12 2.62 0.18 1.21 0.08 2.21 0.1595 148 10 16.44 9.66 0.59 3.18 0.19 1.61 0.10 1.20 0.07 0.79 0.0596 140 10 17.83 12.39 0.69 1.53 0.09 1.71 0.10 1.11 0.06 1.09 0.0697 146 10 16.83 9.57 0.57 2.59 0.15 2.75 0.16 0.91 0.05 1.00 0.0698 146 10 16.74 8.96 0.54 1.91 0.11 3.17 0.19 1.19 0.07 1.51 0.09

-------------------------------------------------- SITE=LYBR GROUP=50 --------------------------------------------------

SYEAR SVR DV TBEXT ESO4 F_ESO4 ENO3 F_ENO3 EOC F_EOC ELAC F_ELAC ECM F_ECM

92 81 16 38.42 24.35 0.63 5.89 0.15 4.59 0.12 2.27 0.06 1.32 0.0393 93 14 32.06 19.19 0.60 4.08 0.13 4.66 0.15 1.93 0.06 2.20 0.0794 78 16 39.98 22.58 0.56 6.12 0.15 5.27 0.13 2.55 0.06 3.46 0.0995 83 16 37.28 23.70 0.64 5.32 0.14 4.22 0.11 2.38 0.06 1.65 0.0496 76 16 41.69 29.50 0.71 3.96 0.09 4.60 0.11 2.21 0.05 1.42 0.0397 85 15 35.77 23.72 0.66 3.52 0.10 4.77 0.13 1.88 0.05 1.88 0.0598 73 17 43.41 25.67 0.59 6.87 0.16 6.42 0.15 2.60 0.06 1.85 0.04

-------------------------------------------------- SITE=LYBR GROUP=90 --------------------------------------------------

SYEAR SVR DV TBEXT ESO4 F_ESO4 ENO3 F_ENO3 EOC F_EOC ELAC F_ELAC ECM F_ECM

92 32 25 113.6 86.79 0.76 9.23 0.08 10.61 0.09 4.71 0.04 2.31 0.0293 30 26 119.5 88.21 0.74 9.93 0.08 12.44 0.10 5.84 0.05 3.09 0.0394 29 26 125.6 93.23 0.74 10.34 0.08 12.08 0.10 5.48 0.04 4.50 0.0495 31 26 117.9 91.14 0.77 5.88 0.05 13.10 0.11 5.36 0.05 2.44 0.0296 35 24 101.4 73.45 0.72 8.51 0.08 12.12 0.12 4.86 0.05 2.41 0.0297 32 25 113.0 91.89 0.81 5.02 0.04 9.77 0.09 4.15 0.04 2.14 0.0298 27 27 135.0 107.3 0.79 6.21 0.05 12.95 0.10 5.93 0.04 2.64 0.02
10

Moosehorn Wilderness Area, ME-------------------------------------------------- SITE=MOOS GROUP=10 --------------------------------------------------

SYEAR SVR DV TBEXT ESO4 F_ESO4 ENO3 F_ENO3 EOC F_EOC ELAC F_ELAC ECM F_ECM

95 133 11 19.30 10.76 0.56 2.12 0.11 3.47 0.18 1.51 0.08 1.45 0.0896 143 10 17.32 9.67 0.56 1.19 0.07 3.17 0.18 1.35 0.08 1.93 0.1197 153 9 15.51 8.07 0.52 1.25 0.08 3.13 0.20 1.18 0.08 1.88 0.1298 136 11 18.72 10.02 0.54 1.14 0.06 3.78 0.20 1.67 0.09 2.11 0.11

-------------------------------------------------- SITE=MOOS GROUP=50 --------------------------------------------------

SYEAR SVR DV TBEXT ESO4 F_ESO4 ENO3 F_ENO3 EOC F_EOC ELAC F_ELAC ECM F_ECM

95 83 16 37.25 22.94 0.62 4.00 0.11 5.91 0.16 2.46 0.07 1.93 0.0596 85 15 36.06 21.22 0.59 2.55 0.07 6.52 0.18 2.67 0.07 3.10 0.0997 85 15 36.01 21.68 0.60 2.73 0.08 6.11 0.17 2.26 0.06 3.22 0.0998 88 15 34.35 19.46 0.57 3.15 0.09 6.15 0.18 2.55 0.07 3.03 0.09

-------------------------------------------------- SITE=MOOS GROUP=90 --------------------------------------------------

SYEAR SVR DV TBEXT ESO4 F_ESO4 ENO3 F_ENO3 EOC F_EOC ELAC F_ELAC ECM F_ECM

95 42 22 83.33 55.92 0.67 6.98 0.08 13.90 0.17 3.92 0.05 2.62 0.0396 44 22 79.03 53.55 0.68 5.53 0.07 12.63 0.16 4.63 0.06 2.69 0.0397 43 22 80.40 55.67 0.69 3.47 0.04 14.58 0.18 3.75 0.05 2.93 0.0498 43 22 80.98 60.15 0.74 4.22 0.05 10.83 0.13 3.93 0.05 1.85 0.02
11

Washington, D.C.-------------------------------------------------- SITE=WASH GROUP=10 --------------------------------------------------

SYEAR SVR DV TBEXT ESO4 F_ESO4 ENO3 F_ENO3 EOC F_EOC ELAC F_ELAC ECM F_ECM

89 50 21 68.34 31.55 0.46 10.28 0.15 9.81 0.14 11.52 0.17 5.18 0.0890 47 21 73.60 30.41 0.41 9.86 0.13 8.85 0.12 10.69 0.15 13.81 0.1991 52 20 65.66 33.30 0.51 11.40 0.17 8.76 0.13 8.67 0.13 3.53 0.0592 51 20 66.53 36.77 0.55 8.10 0.12 9.26 0.14 8.93 0.13 3.47 0.0593 44 22 77.95 42.31 0.54 11.49 0.15 11.13 0.14 9.24 0.12 3.78 0.0594 51 20 66.60 29.88 0.45 12.40 0.19 9.40 0.14 9.69 0.15 5.23 0.0895 66 18 49.66 27.62 0.56 6.66 0.13 5.99 0.12 6.23 0.13 3.16 0.0696 58 19 57.91 30.91 0.53 8.39 0.14 7.33 0.13 7.05 0.12 4.23 0.0797 63 18 52.15 31.10 0.60 4.82 0.09 6.65 0.13 6.29 0.12 3.30 0.0698 65 18 50.56 25.08 0.50 6.24 0.12 8.31 0.16 7.74 0.15 3.19 0.06

-------------------------------------------------- SITE=WASH GROUP=50 --------------------------------------------------

SYEAR SVR DV TBEXT ESO4 F_ESO4 ENO3 F_ENO3 EOC F_EOC ELAC F_ELAC ECM F_ECM

89 31 26 117.9 56.70 0.48 20.93 0.18 16.39 0.14 16.92 0.14 7.00 0.0690 30 26 121.1 50.79 0.42 20.83 0.17 15.34 0.13 17.25 0.14 16.89 0.1491 27 27 134.3 76.79 0.57 20.70 0.15 17.07 0.13 15.40 0.11 4.37 0.0392 28 26 129.1 70.15 0.54 22.68 0.18 16.23 0.13 15.15 0.12 4.85 0.0493 26 27 137.8 73.73 0.53 24.01 0.17 19.19 0.14 15.15 0.11 5.73 0.0494 30 26 119.8 59.81 0.50 19.27 0.16 17.98 0.15 17.12 0.14 5.60 0.0595 37 24 96.11 51.72 0.54 17.20 0.18 12.08 0.13 10.71 0.11 4.40 0.0596 36 24 97.91 51.24 0.52 16.34 0.17 14.77 0.15 10.78 0.11 4.78 0.0597 38 23 93.93 50.33 0.54 17.13 0.18 13.48 0.14 10.03 0.11 2.95 0.0398 40 23 87.95 48.86 0.56 12.55 0.14 12.77 0.15 10.49 0.12 3.28 0.04

-------------------------------------------------- SITE=WASH GROUP=90 --------------------------------------------------

SYEAR SVR DV TBEXT ESO4 F_ESO4 ENO3 F_ENO3 EOC F_EOC ELAC F_ELAC ECM F_ECM

89 21 29 179.9 99.44 0.55 27.34 0.15 21.88 0.12 21.73 0.12 9.49 0.0590 20 30 182.0 79.03 0.43 25.63 0.14 27.56 0.15 27.23 0.15 22.56 0.1291 16 32 236.2 159.0 0.67 24.52 0.10 27.12 0.11 19.14 0.08 6.46 0.0392 16 32 242.2 158.0 0.65 32.00 0.13 24.82 0.10 20.40 0.08 6.99 0.0393 16 32 233.6 131.2 0.56 35.21 0.15 35.74 0.15 23.29 0.10 8.21 0.0494 18 31 206.0 123.5 0.60 21.86 0.11 30.49 0.15 23.39 0.11 6.78 0.0395 21 29 179.7 108.8 0.61 23.86 0.13 24.80 0.14 16.88 0.09 5.29 0.0396 20 30 186.9 129.8 0.69 12.90 0.07 22.35 0.12 17.38 0.09 4.48 0.0297 21 29 179.3 116.4 0.65 21.27 0.12 23.62 0.13 13.58 0.08 4.43 0.0298 21 29 178.2 127.8 0.72 3.53 0.02 26.69 0.15 17.37 0.10 2.87 0.02
12

Key:GROUP 10 = 20% least impaired visibility daysGROUP 50 = 40 – 60% mid-range visibility daysGROUP 90 = 20% most impaired visibility daysSYEAR = Sample year (March – February)SVR = Standard visual range (kilometers)DV = Deciviews (includes Rayleigh scattering of 10 Mm-1)

TBEXT = Reconstructed particle mass extinction (Mm-1), which excludes Rayleigh scattering

ESO4 = Ammonium sulfate extinction (Mm-1)

ENO3 = Ammonium nitrate extinction (Mm-1)

EOC = Organic carbon extinction (Mm-1)

ELAC = Light absorbing carbon extinction (Mm-1)

ECM = Crustal material extinction (fine and coarse soil) (Mm-1)

F_*** = Extinction fraction of speciated particle relative to reconstructed particle mass extinctionData from IMPROVE, http://alta_vista.cira.colostate.edu/NOTE: Great Gulf Wilderness Area data tables not available from IMPROVE web site.
13