United States Office of Air Quality EPA-454/R-99-003

Environmental Protection Planning and Standards June 1999

Agency Research Triangle Park, NC 27711

Air

 VISIBILITY 

 MONITORING

 GUIDANCE
VISIBILITY MONITORING GUIDANCE DOCUMENT

U.S. ENVIRONMENTAL PROTECTION AGENCY

Emissions Monitoring and Analysis Division

Monitoring and Quality Assurance Group

MD-14

Research Triangle Park, NC 27711
i

PREFACE

This EPA Visibility Monitoring Guidance Document was prepared to provide assistance to

those organizations responsible for collecting visibility and particulate matter data for regulatory and

planning purposes. This document contains EPA policy and, therefore, does not establish or affect

legal rights or obligations. It does not establish a binding norm and is not finally determinative of the

issues addressed. In applying this policy in any particular case, the EPA will consider its applicability

to the specific facts of that case, the underlying validity of the interpretations set forth in this

document, and any other relevant considerations, including any that may be required under applicable

law and regulations.

EPA has cited examples of and references to existing instruments and protocols that are

currently being used in operational visibility monitoring programs in this document. These examples

and references to specific instrument models or manufacturers are not intended to constitute an EPA

endorsement or recommendation for use.
ii

ACKNOWLEDGMENTS

The Draft Visibility Monitoring Guidance Document was originally compiled by Air Resource

Specialists, Inc. for the Environmental Protection Agency - Air Quality Strategies and Standards

Division (Order No. 6D0418NASA). Many individuals were involved in the preparation and review

of this final document including:

Rich Damberg

Joe Delwiche

Dave Dietrich

Bob Eldred

Dan Ely

Neil Frank 

Tom Moore

Marc Pitchford

Bruce Polkowsky

Kristie Savig

Marc Scruggs

IMPROVE Steering Committee Members
iii

TABLE OF CONTENTS

Section Page

Preface I

Acknowledgments ii

Table of Contents iii

1.0 INTRODUCTION 1-1

1.1 Purpose 1-1

1.2 Document Organization 1-2

1.3 Background 1-3

1.4 Statutory and Regulatory Requirements 1-4

1.4.1 1970 Clean Air Act 1-4

1.4.2 1977 Clean Air Act Amendments: Section 169A 1-4

1.4.3 1980 EPA Regulations 1-12

1.4.4 State and Federal Implementation Plans 1-12

1.4.5 1990 Clean Air Act Amendments 1-13

1.4.6 EPA Regional Haze Regulation 1-14

2.0 MONITORING PROGRAM CONSIDERATIONS 2-1

2.1 Visibility Definitions and Theory 2-1

2.1.1 Characterizing Visibility Impairment 2-5

2.1.2 Relationship Between Light Extinction and Aerosol

Concentrations 2-6

2.1.3 Importance of Relative Humidity on Light Scattering 2-7

2.2 Visibility Goals and Monitoring Objectives 2-9

2.2.1 Visibility Goals 2-9

2.2.2 Monitoring Objectives 2-13

2.2.2.1 Ensure that High Quality Comparable Data are

Collected by All Monitoring Organizations Through

Adoption of Standard Monitoring Protocols 2-13

2.2.2.2 Establish Current Visual Air Quality Conditions 2-14

2.2.2.3 Identify Sources of Impairment 2-15

2.2.2.4 Document Long-Term Trends 2-16

2.2.2.5 Provide Data for the New Source Review and Prevention of

Significant Deterioration Permitting Programs 2-16
iv

TABLE OF CONTENTS (cont.)

Section Page

2.3 Visibility Data Quality Objectives 2-17

2.3.1 Primary Parameters 2-18

2.3.1.1 Aerosol 2-18

2.3.1.2 Optical 2-19

2.3.1.3 Scene 2-19

2.3.2 Network Design 2-19

2.3.3 Quality Assurance 2-21

2.4 Monitoring Methods 2-23

2.4.1 Aerosol Monitoring 2-26

2.4.2 Optical Monitoring 2-27

2.4.3 Scene Monitoring 2-28

2.4.4 Standard Units 2-28

2.5 Data Archive and Data Applications 2-30

2.5.1 National Visibility Archive 2-30

2.5.2 Data Uses 2-30

2.6 Network Design 2-34

2.6.1 Assessment Criteria 2-35

2.6.1.1 Spatial Considerations 2-37

2.6.1.2 Temporal Considerations 2-41

2.6.1.3 Historical and Existing Monitoring Program

Considerations 2-43

2.6.1.4 Monitoring Parameter Considerations 2-43

2.6.1.5 Capital and Operational Considerations 2-52

2.6.2 Example Network Configurations 2-53

2.6.2.1 Routine Monitoring Network 2-53

2.6.2.2 Special Study Monitoring Site (Network) 2-54

2.6.2.3 Non-Class I (Urban or Sensitive Area) Monitoring Site 2-56

3.0 AEROSOL MONITORING 3-1

3.1 Measurement Criteria and Instrumentation 3-1
v

TABLE OF CONTENTS (cont.)

Section Page

3.2 Siting Criteria 3-8

3.3 Installation and Site Documentation 3-9

3.4 System Performance and Maintenance 3-10

3.4.1 Routine Servicing 3-10

3.4.2 Instrument Calibration and Maintenance 3-10

3.5 Sample Handling and Data Collection 3-11

3.5.1 Procurement and Pretesting of IMPROVE Aerosol Filters 3-11

3.5.2 Processing of Clean Aerosol Filters 3-12

3.5.3 On-Site Filter Handling 3-14

3.5.4 Processing Exposed Filters and Preparation for Filter Analysis 3-14

3.6 Filter Analyses and Data Reduction and Validation 3-15

3.6.1 Gravimetric Mass 3-15

3.6.2 Absorption (babs) 3-15

3.6.3 Analysis of Aerosol Species 3-15

3.6.4 Data Reduction and Validation of Laboratory Analyses 3-18

3.7 Data Reporting and Archive 3-21

3.7.1 Data Reporting 3-21

3.7.2 Data Archive 3-22

3.8 Supplemental Analysis Including Composite Variables 3-27

3.9 Quality Assurance 3-30

3.9.1 Instrument Audits 3-30

3.9.2 Concentration and Precision of Measured Variables 3-31

3.9.3 Concentration and Precision of Composite Variables 3-35

3.10 Data Analysis and Interpretation 3-38

3.10.1 Calculating Reconstructed Aerosol Extinction 3-38

3.10.2 Source-Type Tracer Analysis 3-40

3.11 Aerosol Monitoring Standard Operating Procedures and

Technical Instructions 3-42

4.0 OPTICAL MONITORING 4-1

4.1 Transmissometer 4-1
vi

TABLE OF CONTENTS (cont.)

Section Page

4.1.1 Measurement Criteria and Instrumentation 4-1

4.1.2 Siting Criteria 4-5

4.1.3 Installation and Site Documentation 4-6

4.1.4 System Performance and Maintenance 4-7

4.1.4.1 Routine Servicing 4-7

4.1.4.2 Annual Site Visits 4-8

4.1.4.3 Instrument Calibration 4-8

4.1.4.4 Annual Servicing 4-10

4.1.5 Data Collection 4-11

4.1.6 Data Reduction and Validation 4-11

4.1.6.1 Data Reduction 4-11

4.1.6.2 Data Validation 4-12

4.1.7 Data Reporting and Archive 4-14

4.1.7.1 Data Reporting 4-14

4.1.7.2 Data Archive 4-20

4.1.8 Quality Assurance 4-20

4.1.8.1 Instrument Precision and Accuracy 4-20

4.1.8.2 Measurement Uncertainties 4-22

4.1.8.3 Instrument Audits 4-28

4.1.9 Data Analysis and Interpretation 4-29

4.1.10 Transmissometer Standard Operating Procedures and

Technical Instructions 4-31

4.2 Nephelometer 4-33

4.2.1 Measurement Criteria and Instrumentation 4-33

4.2.2 Siting Criteria 4-36

4.2.3 Installation and Site Documentation 4-37

4.2.4 System Performance and Maintenance 4-38

4.2.4.1 Routing Servicing 4-38

4.2.4.2 Annual site Visits 4-38

4.2.4.3 Instrument Calibration 4-39

4.2.4.4 Annual Servicing 4-39

4.2.5 Data Collection 4-40

4.2.6 Data Reduction and Validation 4-40
vii

TABLE OF CONTENTS (Cont.)

Section Page

4.2.6.1 Data Reduction 4-40

4.2.6.2 Data Validation 4-41

4.2.7 Data Reporting and Archive 4-43

4.2.7.1 Data Reporting 4-43

4.2.7.2 Data Archive 4-48

4.2.8 Quality Assurance 4-48

4.2.8.1 Instrument Precision 4-48

4.2.8.2 Instrument Audits 4-51

4.2.9 Data Analysis and Interpretation 4-52

4.2.10 Nephelometer Standard Operating Procedures and 

Technical Instructions 4-52

5.0 SCENE MONITORING 5-1

5.1 35 mm Slide Photography 5-1

5.1.1 Measurement Criteria and Instrumentation 5-1

5.1.2 Siting Criteria 5-4

5.1.3 Installation and Site Documentation 5-4

5.1.4 System Performance and Maintenance 5-5

5.1.4.1 Routine Servicing 5-5

5.1.4.2 Biannual Laboratory Servicing 5-6

5.1.5 Data Collection 5-7

5.1.6 Data Reduction and Validation 5-7

5.1.6.1 Data Reduction 5-7

5.1.6.2 Data Validation 5-8

5.1.7 Data Reporting and Archive 5-10

5.1.7.1 Data Reporting 5-10

5.1.7.2 Data Archive 5-11

5.1.8 Quality Assurance 5-12

5.1.9 Data Analysis and Interpretation 5-12

5.1.10 Scene Monitoring Standard Operating Procedures and

Technical Instructions 5-12

5.2 Time-Lapse Photography 5-13
viii

TABLE OF CONTENTS (cont.)

Section Page

5.2.1 Measurement Criteria and Instrumentation 5-13

5.2.2 Siting Criteria 5-16

5.2.3 Installation and Site Documentation 5-17

5.2.4 System Performance and Maintenance 5-17

5.2.5 Data Collection 5-17

5.2.6 Data Reduction and Validation 5-18

5.2.6.1 Data Reduction 5-18

5.2.6.2 Data Validation 5-18

5.2.7 Data Reporting and Archive 5-20

5.2.7.1 Data Reporting 5-20

5.2.7.2 Data Archive 5-21

5.2.8 Quality Assurance 5-21

5.2.9 Data Analysis and Interpretation 5-21

5.2.10 8 mm Time-Lapse Scene Monitoring Systems Standard

Operating Procedures and Technical Instructions 5-21

6.0 REFERENCES 6-1

7.0 VISIBILITY MONITORING-RELATED GLOSSARY AND ABBREVIATIONS 7-1
ix

LIST OF FIGURES

Figure Page

2-1 Properties of the Atmosphere that affect the Transmission of

Light from a Scenic Feature to a Human Observer 2-2

2-2 Size Distribution and Sources of Atmospheric Particles 2-3

2-3 The Relationship between the Scattering Efficiency of Ammonium Sulfate

Aerosols and Relative Humidity (Malm, et al., 1996) 2-8

2-4 Standard ASCII File Format IMPROVE Protocol Aerosol Visibility Data 2-32

2-5 Standard ASCII File Format IMPROVE Protocol Transmissometer

Visibility Data 2-33

2-6 Standard ASCII File Format IMPROVE Protocol Integrating Nephelometer

Visibility Data 2-34

3-1 Diagram of the IMPROVE Aerosol Sampler 3-2

3-2a Schematic of the IMPROVE PM 2.5 Module used before 1999 3-3

3-2b Schematic of the IMPROVE PM 2-5 Module used after 1999 3-4

3-2c Schematic of the IMPROVE PM-10 Module used after 1999 3-5

3-2d Schematic of the IMPROVE Controller Module used after 1999 3-6

3-3 Flow Diagram of Aerosol Filter Handling Procedures Before and

During Collection 3-13

3-4a Quarterly Data Report: Site Specific Elements 3-23

3-4b Quarterly Data Report: Site Specific Mass and Major Components 3-24

3-4c Quarterly Data Report: Site Specific Means and Distributions 3-25

3-5 Standard ASCII File Format IMPROVE Protocol Aerosol Data 3-26

3-6 The Relationship Between Scattering Efficiency and Relative Humidity 3-40

4-1 Transmissometer Receiver and Transmitter Components 4-4

4-2 Example Seasonal Transmissometer Data Summary 4-17

4-3 Example Annual Transmissometer Data Summary 4-18

4-4 Standard ASCII File Format IMPROVE Protocol

Transmissometer Visibility Data 4-21

4-5 Entire Nephelometer System Set on a Tower 4-34

4-6 Close-Up of a Nephelometer and Cross-View of Its Internal Components 4-35
x

4-7 Example Seasonal Nephelometer Data Summary 4-45

4-8 Example Annual Nephelometer Data Summary 4-46

4-9 Standard ASCII File Format IMPROVE Protocol

Integrating Nephelometer Visibility Data 4-49

5-1 Automatic Camera System in a Remote Location 5-3

5-2 Station Components 5-3

5-3 Time-Lapse Video Recording Module (Time-Lapse Recorder,

Monitor, and Power Systems 5-15

5-4 Weatherproof Video Camera Enclosure 5-15
xi

LIST OF TABLES

Table Page

1-1 List of Mandatory Class I Areas as of August 7, 1977 1-5

(Source: 44 CFR 69124, November 30, 1979)

2-1 Visibility Goals and Monitoring Objectives 2-11

2-2 A Summary of Appropriate Site Configurations for Common

Monitoring Objectives 2-23

2-3 IMPROVE Visibility Monitoring Protocols Instrument-Specific

Monitoring Considerations 2-26

2-4 Recognized Visibility-Related Indexes and Standard Units 2-30

2-5 Assessment Criteria Related to Designing a Visibility Monitoring Program 2-37

2-6 IMPROVE and IMPROVE Protocol Sites According to

Region (Sisler, et al., 1996) 2-41

2-7 Monitoring Parameter Considerations 2-46

2-8 Example Particle Samplers (Chow, 1995) 2-49

3-1 Summary of IMPROVE Aerosol Sampler Data Collection Parameters 3-2

3-2 Carbon Components as a Function of Temperature and Added Oxygen 3-17

3-3 Commonly Reported Measured Variables 3-19

3-4 Commonly Reported Composite Variables 3-20

3-5 Relative Precision of Key Measured Variables Ratio of Mean Precision

Divided by Mean Concentration 3-33

3-6 Minimum Detectable Limits of Elements in ng/m33-34

3-7 Fraction of Cases with Statistically Significant Concentrations 3-34

3-8 Common Source Types of Measured Trace Elements (Chow, 1995) 3-41

4-1 IMPROVE Protocol Monitoring Optical Instrument Specifications 4-2

5-1 Example Slide Condition Code Key 5-9

5-2 Example Tape/Film Condition Code Key 5-19
 

1 The IMPROVE Committee consists of representatives from the six cooperating federal agencies: National Park Service

(NPS), EPA, National Oceanic and Atmospheric Administration (NOAA) , United States Forest Service (USFS), Bureau

of Land Management (BLM), and United States Fish and Wildlife Service (USFWS); and four state consortiums: State

and Territorial Air Pollution Program Administrators and the Association of Local Air Pollution Control Officials

(STAPPA/ALAPCO, Western States Air Resources Council (WESTAR), Northeast States for Coordinated Air Use

Management (NESCAUM) and Mid-Atlantic Regional Air Management Association (MARAMA).

1-1

1.0 INTRODUCTION

1.1 PURPOSE

The purpose of this Visibility Monitoring Guidance Document is to provide a written

reference for organizations conducting monitoring of visibility and particulate matter for

regulatory, planning, or research purposes. Possible users include the government sector

(Federal, State, regional, local, and Tribal air quality agencies), industry, consulting firms,

academia, or nonprofit organizations. The information in this document includes:

! Background on the visibility protection requirements of the Clean Air Act and related

regulations. 

! A summary of visibility monitoring goals and objectives set forth in the Clean Air Act

and related EPA regulations.

! Considerations and recommendations for developing effective visibility monitoring

sites and networks, particularly for implementation of the monitoring requirements for

the PM-2.5 and regional haze regulatory programs. These considerations and

recommendations address visibility definitions and theory, monitoring goals and

objectives, data quality objectives, monitoring methods, data archive and data

applications, and network design.

! Descriptions of current visibility measurement methods and monitoring protocols,

particularly those used under the Interagency Monitoring of Protected Visual

Environments (IMPROVE) program1.

It is assumed that the reader of this document is generally familiar with aerometric

monitoring principles and has the responsibility to design and operate a monitoring program to

characterize visibility and/or particulate matter. This document is not meant to dictate EPA

monitoring requirements or to define policy, standards, or data interpretation methods, but to

provide a strategic framework that can be used by those with a need to monitor visibility for

planning or regulatory purposes. The guidance is intended to assist monitoring organizations in

developing effective, consistent, visibility monitoring sites and networks that use state-of-the-art

methods to best meet individually defined objectives. The document does not address specific

research monitoring requirements, and it does not address methods to evaluate the human

perception of visual air quality.

This document focuses on instruments and analytical methods that are currently in use and

are considered by EPA and the IMPROVE Program to be best suited for use at this time. Like 

any monitoring approach, visibility monitoring instrumentation and analytical methods are

continually evolving in order to minimize uncertainty and improve quality assurance. 
1-2

References made to specific instrument models or manufacturers are not intended to constitute an

EPA endorsement. It should be recognized that this document may be updated periodically to

reflect new and improved instruments and monitoring methods as they become available and are

proven reliable.

1.2 DOCUMENT ORGANIZATION

This Visibility Monitoring Guidance Document is comprised of seven primary sections. 

Each section is described below: 

Section 1.0 Introduction

Presents the purpose of the document, the document organization, and a

summary of legislative and regulatory requirements that provide the basis

for visibility protection and visibility monitoring.

Section 2.0 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 3.0 Aerosol Monitoring

Provides detailed examples of standard operating procedures for aerosol

monitoring, including monitoring of PM-10 and PM-2.5 (including

chemical composition analysis for sulfates, nitrates, organic and elemental

carbon, and primary PM).

Section 4.0 Optical Monitoring

Provides detailed examples of optical monitoring protocols, including

transmissometer and nephelometer monitoring systems.

Section 5.0 Scene Monitoring

Provides detailed examples of scene monitoring protocols, including 35mm

and time-lapse camera monitoring systems.

Section 6.0 References 

Section 7.0 Glossary of Terms and Abbreviations
2

 See Table 1-1 for the list of mandatory Class I Federal areas.

1-3

1.3 BACKGROUND

Visibility impairment is probably the most easily recognizable effect of air pollution in the

atmosphere. It is caused by the scattering and absorption of light by particles and gases in the air. 

Under the Clean Air Act (Act), Congress recognized that good visibility is a resource to be valued

and preserved, now and for future generations. In section 169A of the Act, Congress set forth a

national goal that calls for "the prevention of any future, and the remedying of any existing,

impairment of visibility in mandatory class I Federal areas2 which impairment results from

manmade air pollution.” EPA is responsible for establishing regulations ensuring that “reasonable

progress” toward the national goal is achieved in the 156 mandatory class I Federal areas

(primarily national parks and wilderness areas) identified under the Act. 

Visibility is also protected under section 109 (relating to the National Ambient Air Quality

Standards, or NAAQS) and section 165 (requirements for new or reconstructed sources) of the

Act. Section 109 calls for EPA to establish primary and secondary NAAQS in order to protect

the public health and public welfare, respectively. For many years, visibility has been recognized

as a “welfare effect” of particulate matter. In July 1997, EPA established new air quality

standards for PM-2.5. The annual PM-2.5 standard, to be averaged over a period of 3 years, is

15 micrograms per cubic meter. The 24-hour standard is 65 micrograms per cubic meter. In this

action, EPA also set secondary standards for PM-2.5, equivalent to the suite of primary standards.

In addition, EPA noted that promulgation of a regional haze program under section 169A would

address the welfare effects of particulate matter in class I areas. 

The PM-2.5 monitoring regulations at 40 CFR Part 58 recognize the importance of

monitoring for protection of secondary National Ambient Air Quality Standards and also allow

the use of the IMPROVE protocol for the purpose of characterizing background or transported

levels of PM-2.5. The PM-2.5 and IMPROVE programs are closely related through this

provision. It will be important to understand the regional nature of PM-2.5 levels in order to

improve the accuracy of regional PM models and ultimately to develop effective control

strategies. Monitoring of visibility in non-class I areas (such as urban and suburban areas) can

also provide important information for State or local governments in developing a local visibility

standard (such as exists in Denver), as well as useful data for future EPA reviews of the

secondary standards for particulate matter. 

Section 165 of the Act provides for preconstruction review of the air quality impacts

associated with new or modified major sources. The prevention of significant deterioration (PSD)

program protects class I areas by allowing only a small increment of air quality deterioration in

these areas and by providing for assessment of the potential impacts on the air quality related

values (AQRVs) of class I areas. AQRV’s include visibility and other fundamental purposes for

which these lands have been established.

 A number of federal, state, tribal, and local visibility monitoring sites and monitoring

programs have been established to date, some dating back to the 1970's. In order to support

implementation of the PM2.5 standards and the regional haze program, EPA is providing for a

significant expansion of the IMPROVE visibility monitoring network in 1999. EPA recognizes

the need to provide visibility monitoring guidance to ensure that the methodologies used to collect
3

 H.R. Rep. No. 294, 95th Congress, 1st Session, 203-204 (1977).

4

 See 45 Federal Register 80084 (December 2, 1980) and 40 CFR 51.300-307.

1-4

and analyze aerosol and visibility data are consistent and applicable for tracking progress toward

visibility goals in the future.

1.4 STATUTORY AND REGULATORY REQUIREMENTS

1.4.1 1970 Clean Air Act

The 1970 Clean Air Act was the first national legislation to address air quality throughout

the United States. The Act included requirements for protecting visibility from adverse effects of

air pollution. Visibility was identified as a welfare effect of concern for EPA to consider in setting

primary and secondary national ambient air quality standards. The total suspended particulate

(TSP) standard established by the EPA in 1971 provided a minimal amount of visibility

protection, since visibility impairment is predominantly caused by fine particulate matter.

1.4.2 1977 Clean Air Act Amendments: Section 169A

The Clean Air Act was amended in August 1977, and included a new section 169A for the

protection of visibility in areas of great scenic importance, such as national parks and wilderness

areas. Congress adopted these provisions to protect the “intrinsic beauty and historical and

archaeological treasures” of certain federal lands, noting that “areas such as the Grand Canyon

and Yellowstone Park are areas of breathtaking panorama; millions of tourists each year are

attracted to enjoy the scenic vistas.”3 In section 169A, Congress established the following

national goal for visibility protection: 

"the prevention of any future, and the remedying of any existing, impairment of visibility

in mandatory Class I Federal areas which impairment results from man-made air

pollution."

Mandatory Class I federal areas are national parks greater than 6,000 acres in size,

wilderness areas greater than 5,000 acres in size, and international parks that were in existence on

August 7, 1977. The list of 156 mandatory Class I areas is provided in Table 1-1. Section 169A

required the EPA to promulgate regulations requiring states to adopt measures into their State

Implementation Plans (SIPs) that would protect visibility in these areas. EPA promulgated the

first of these regulations on December 2, 1980.4 These regulations addressed visibility impairment

that is “reasonably attributable” to a source or group of sources.
1-5

Table 1-1

List of Mandatory Class I Areas

as of August 7, 1977

(Source: 44 CFR 69124, November 30, 1979)

Area Name Acreage Public Law Establishing Federal Land Manager

Alabama

Sipsey Wild. 12,646 93-622 USDA-FS

Alaska

Bering Sea Wild. 41,113 91-622 USDI-FWS

Mount McKinley NP 1,949,493 64-353 USDI-NPS

Simeonof Wild. 25,141 94-557 USDI-FWS

Tuxedni Wild. 6,402 91-504 USDI-FWS

Arizona

Chiricahua National Monument Wild. 9,440 94-567 USDI-NPS

Chiricahua Wild. 18,000 88-577 USDA-FS

Galiuro Wild. 52,717 88-577 USDA-FS

Grand Canyon NP 1,176,913 65-277 USDI-NPS

Mazatzal Wild. 205,137 88-577 USDA-FS

Mount Baldy Wild. 6,975 91-504 USDA-FS

Petrified Forest NP 93,493 85-358 USDI-NPS

Pine Mountain Wild. 20,061 92-230 USDA-FS

Saguaro Wild. 71,400 94-567 USDI-FS

Sierra Ancha Wild. 20,850 88-577 USDA-FS

Superstition Wild. 124,117 88-577 USDA-FS

Sycamore Canyon Wild. 47,757 92-241 USDA-FS

Arkansas

Caney Creek Wild. 14,344 93-622 USDA-FS

Upper Buffalo Wild. 9,912 93-622 USDA-FS

California

Agua Tibia Wild. 15,934 93-632 USDA-FS

Caribou Wild. 19,080 88-577 USDA-FS

Cucamonga Wild. 9,022 88-577 USDA-FS

Desolation Wild. 63,469 91-82 USDA-FS

Dome Land Wild. 62,206 88-577 USDA-FS

Emigrant Wild. 104,311 93-632 USDA-FS

Hoover Wild. 47,916 88-577 USDA-FS

John Muir Wild. 484,673 8-577 USDA-FS

Joshua Tree Wild. 429,690 94-567 USDI-NPS

Kaiser Wild. 22,500 94-577 USDA-FS

Kings Canyon NP 459,994 76-424 USDI-NPS

Lassen Volcanic NP 105,800 64-184 USDI-NPS
Table 1-1 (cont.)

List of Mandatory Class I Areas

as of August 7, 1977

(Source: 44 CFR 69124, November 30, 1979)

Area Name Acreage Public Law Establishing Federal Land Manager

1-6

California (cont.)

Lava Beds Wild. 28,640 92-493 USDI-NPS

Marble Mountain Wild. 213,743 88-577 USDA-FS

Minarets Wild. 109,484 88-577 USDA-FS

Mokelumme Wild. 50,400 88-577 USDA-FS

Pinnacles Wild. 12,952 94-567 USDI-NPS

Point Reyes Wild. 25,370 94-544, 94-567 USDI-NPS

Redwood NP 27,792 90-545 USDI-NPS

San Gabriel Wild. 36,137 90-318 USDA-FS

San Gorgonio Wild. 34,644 88-577 USDA-FS

San Jacinto Wild. 20,564 88-577 USDA-FS

San Rafael Wild. 142,722 90-271 USDA-FS

Sequoia NP 386,642 26 Stat. 478 (51st Cong.) USDI-NPS

South Warner Wild. 68,507 88-577 USDA-FS

Thousand Lakes Wild. 15,695 88-577 USDA-FS

Ventana Wild. 95,152 91-58 USDA-FS

Yolla-Bolly-Middle-Eel Wild. 109,091 88-577 USDA-FS

Yosemite NP 759,172 58-49 USDI-NPS

Colorado

Black Canyon of the Gunnison Wild. 11,180 94-567 USDI-NPS

Eagles Nest Wild. 133,910 94-352 USDA-FS

Flat Tops Wild. 235,230 94-146 USDA-FS

Great Sand Dunes Wild. 33,450 94-567 USDI-NPS

La Garita Wild. 48,486 88-577 USDA-FS

Maroon Bells-Snowmass Wild. 71,060 88-577 USDA-FS

Mesa Verde NP 51,488 59-353 USDI-NPS

Mount Zirkel Wild. 72,472 88-577 USDA-FS

Rawah Wild. 26,674 88-577 USDA-FS

Rocky Mountain NP 263,138 63-238 USDI-NPS

Weminuche Wild. 400,907 93-632 USDA-FS

West Elk Wild. 61,412 88-577 USDA-FS

Florida

Chassahowitzka Wild. 23,360 94-557 USDI-FWS

Everglades NP 1,397,429 73-267 USDI-NPS

St. Marks Wild. 17,745 93-632 USDI-FWS
Table 1-1 (cont.)

List of Mandatory Class I Areas

as of August 7, 1977

(Source: 44 CFR 69124, November 30, 1979)

Area Name Acreage Public Law Establishing Federal Land Manager

1-7

Georgia

Cohotta Wild. 33,776 93-622 USDA-FS

Okefenokee Wild. 343,850 93-429 USDI-FWS

Wolf Island Wild. 5,126 93-632 USDI-FWS

Hawaii

Haleakala NP 27,208 87-744 USDI-NPS

Hawaii Volcanoes 217,029 64-171 USDI-NPS

Idaho

Craters of the Moon Wild. 43,243 91-504 USDI-NPS

Hells Canyon Wild.

Hells Canyon Wilderness, 192,700 acres overall,

of which 108,900 acres are in Oregon and

83,800 acres are in Idaho.

83,800 94-199 USDA-FS

Sawtooth Wild. 216,383 92-400 USDA-FS

Selway-Bitterroot Wild.

Selway Bitterroot Wilderness, 1,240,700 acres

overall, of which 988,700 acres are in Idaho and

251,930 acres are in Montana.

988,770 88-577 USDA-FS

Yellowstone NP

Yellowstone National Park, 2,219,737 acres

overall, of which 2,020,625 acres are in

Wyoming, 167,624 acres are in Montana, and

31,488 acres are in Idaho.

31,488 17 Stat. 32 (42nd Cong.) USDI-NPS

Kentucky

Mammoth Cave NP 51,303 69-283 USDI-NPS

Louisiana

Breton Wild. 5,000+ 93-632 USDI-FWS

Maine

Acadia NP 37,503 65-278 USDI-NPS

Moosehorn Wild. 7,501 USDI-FWS

 (Edmunds Unit) (2,782) 91-504

 (Baring Unit) (4,719) 93-632

Michigan

Isle Royale NP 542,428 71-835 USDI-NPS

Seney Wild. 25,150 91-504 USDI-FWS
Table 1-1 (cont.)

List of Mandatory Class I Areas

as of August 7, 1977

(Source: 44 CFR 69124, November 30, 1979)

Area Name Acreage Public Law Establishing Federal Land Manager

1-8

Minnesota

Boundary Waters Canoe Area Wild. 747,840 99-577 USDA-FS

Voyageurs NP 114,964 99-261 USDI-NPS

Missouri

Hercules-Glades Wild. 12,315 94-557 USDA-FS

Mingo Wild. 8,000 94-557 USDI-FWS

Montana

Anaconda-Pintlar Wild. 157,803 88-577 USDA-FS

Bob Marshall Wild. 950,000 88-577 USDA-FS

Cabinet Mountains Wild. 94,272 88-577 USDA-FS

Gates of the Mtn. Wild. 28,562 88-577 USDA-FS

Glacier NP 1,012,599 61-171 USDI-NPS

Medicine Lake Wild. 11,366 94-557 USDI-FWS

Mission Mountain Wild. 73,877 93-632 USDA-FS

Red Rock Lakes Wild. 32,350 94-557 USDI-FWS

Scapegoat Wild. 239,295 92-395 USDA-FS

Selway-Bitterroot Wild.

Selway-Bitterroot Wilderness, 1,240,700 acres

overall, of which 988,770 acres are in Idaho and

251,930 acres are in Montana.

251,930 88-577 USDA-FS

U. L. Bend Wild. 20,890 94-557 USDI-FWS

Yellowstone NP

Yellowstone National Park, 2,219,737 acres

overall, of which 2,020,625 acres are in

Wyoming, 167,624 acres are in Montana, and

31,488 acres are in Idaho.

167,624 17 Stat. 32 (42nd Cong.) USDI-NPS

Nevada

Jarbidge Wild. 64,667 88-577 USDA-FS

New Hampshire

Great Gulf Wild. 5,552 88-577 USDA-FS

Presidential Range-Dry River Wild. 20,000 93-622 USDA-FS

New Jersey

Brigantine Wild. 6,603 93-632 USDI-FWS

New Mexico

Bandelier Wild. 23,267 94-567 USDI-NPS

Bosque del Apache Wild. 80,850 93-632 USDI-FWS

Carlsbad Caverns NP 46,435 71-216 USDI-NPS
Table 1-1 (cont.)

List of Mandatory Class I Areas

as of August 7, 1977

(Source: 44 CFR 69124, November 30, 1979)

Area Name Acreage Public Law Establishing Federal Land Manager

1-9

New Mexico (cont.)

Gila Wild. 433,690 88-577 USDA-FS

Pecos Wild. 167,416 88-577 USDA-FS

Salt Creek Wild. 8,500 91-504 USDI-FWS

San Pedro Parks Wild. 41,132 88-577 USDA-FS

Wheeler Peak Wild. 6,027 88-577 USDA-FS

White Mountain Wild. 31,171 88-577 USDA-FS

North Carolina

Great Smoky Mountains NP

Great Smoky Mountains National Park, 514,758

acres overall, of which 273,551 acres are in

North Carolina, and 241,207 acres are in

Tennessee.

273,551 69-268 USDI-NPS

Joyce Kilmer-Slickrock Wild.

Joyce Kilmer-Slickrock Wilderness, 14,033 acres

overall, of which 10,201 acres are in North

Carolina, and 3,832 acres are in Tennessee.

10,201 93-622 USDA-FS

Linville Gorge Wild. 7,575 88-577 USDA-FS

Shining Rock Wild. 13,350 88-577 USDA-FS

Swanquarter Wild. 9,000 94-557 USDI-FWS

North Dakota

Lostwood Wild. 5,557 93-632 USDI-FWS

Theodore Roosevelt NP 69,675 80-38 USDI-NPS

Oklahoma

Wichita Mountains Wild. 8,900 91-504 USDI-FWS

Oregon

Crater Lake NP 160,290 57-121 USDA-NPS

Diamond Peak Wild. 36,637 88-577 USDA-FS

Eagle Cap Wild. 293,476 88-577 USDA-FS

Gearhart Mountain Wild. 18,709 88-577 USDA-FS

Hells Canyon Wild.

Hells Canyon Wilderness, 192,700 acres overall,

of which 108,900 acres are in Oregon, and

83,800 acres are in Idaho.

108,900 94-199 USDA-FS

Kalmiopsis Wild. 76,900 88-577 USDA-FS

Mountain Lakes Wild. 23,071 88-577 USDA-FS
Table 1-1 (cont.)

List of Mandatory Class I Areas

as of August 7, 1977

(Source: 44 CFR 69124, November 30, 1979)

Area Name Acreage Public Law Establishing Federal Land Manager

1-10

Oregon (cont.)

Mount Hood Wild. 14,160 88-577 USDA-FS

Mount Jefferson Wild. 100,208 90-548 USDA-FS

Mount Washington Wild. 46,116 88-577 USDA-FS

Strawberry Mountain Wild. 33,003 88-577 USDA-FS

Three Sisters Wild. 199,902 88-577 USDA-FS

South Carolina

Cape Romain Wild. 28,000 93-632 USDI-FWS

South Dakota

Badlands Wild. 64,250 94-567 USDI-NPS

Wind Cave NP 28,060 57-16 USDI-NPS

Tennessee

Great Smoky Mountains NP

Great Smoky Mountains National Park, 514,758

acres overall, of which 273,551 acres are in

North Carolina, and 241,207 acres are in

Tennessee.

241,207 69-268 USDI-NPS

Joyce Kilmer-Slickrock Wild.

Joyce Kilmer Slickrock Wilderness, 14,033 acres

overall, of which 10,201 acres are in North

Carolina, and 3,832 acres are in Tennessee.

3,832 93-622 USDA-FS

Texas

Big Bend NP 708,118 74-157 USDI-NPS

Guadalupe Mountains NP 76,292 89-667 USDI-NPS

Utah

Arches NP 65,098 92-155 USDI-NPS

Bryce Canyon NP 35,832 68-277 USDI-NPS

Canyonlands NP 337,570 88-590 USDI-NPS

Capitol Reef NP 221,896 92-507 USDI-NPS

Zion NP 142,462 68-83 USDI-NPS

Vermont

Lye Brook Wild. 12,430 93-622 USDA-FS

Virgin Islands

Virgin Islands NP 12,295 84-925 USDI-NPS
Table 1-1 (cont.)

List of Mandatory Class I Areas

as of August 7, 1977

(Source: 44 CFR 69124, November 30, 1979)

Area Name Acreage Public Law Establishing Federal Land Manager

1-11

Virginia

James River Face Wild. 8,703 93-622 USDA-FS

Shenandoah NP 190,535 69-268 USDI-NPS

Washington

Alpine Lakes Wild. 303,508 94-357 USDA-FS

Glacier Peak Wild. 464,258 88-577 USDA-FS

Goat Rocks Wild. 82,680 88-577 USDA-FS

Mount Adams Wild. 32,356 88-577 USDA-FS

Mount Rainer NP 235,239 30 Stat. 993 (55th Cong.) USDI-NPS

North Cascades NP 503,277 90-554 USDI-NPS

Olympic NP 892,578 75-778 USDI-NPS

Pasayten Wild. 505,524 90-544 USDA-FS

West Virginia

Dolly Sods Wild. 10,215 93-622 USDA-FS

Otter Creek Wild. 20,000 93-622 USDA-FS

Wyoming

Bridger Wild. 392,160 88-577 USDA-FS

Fitzpatrick Wild. 191,103 94-567 USDA-FS

Grand Teton NP 305,504 81-787 USDI-NPS

North Absaroka Wild. 351,104 88-577 USDA-FS

Teton Wild. 557,311 88-577 USDA-FS

Washakie Wild. 686,584 92-476 USDA-FS

Yellowstone NP

Yellowstone National Park, 2,219,737 acres

overall, of which 2,020,625 acres are in

Wyoming, 167,624 acres are in Montana, and

31,488 acres are in Idaho.

2,020,625 17 Stat. 32 (42nd Cong.) USDI-NPS
1-12

1.4.3 1980 EPA Regulations

The 1980 visibility regulations were designed to address impairment that is “reasonably

attributable” to a single source or small group of sources. EPA deferred action addressing

“regional haze” until improvements were made in monitoring techniques, in regional scale

modeling, and in our understanding of the relationships between specific pollutants and visibility

impairment. Regional haze is caused by a multitude of sources, located across a broad geographic

area, which emit fine particles and their precursors into the atmosphere. The 1980 regulations

consisted of a number of requirements to be addressed by the States, including:

! A long-term strategy to make reasonable progress toward the national visibility goal,

with progress reviews every 3 years and SIP revisions as necessary.

! The review of certain existing major sources and the determination of best available

retrofit technology (BART) for any such source that emits any air pollutant which may

reasonably be anticipated to cause or contribute to visibility impairment in any class I

area where that impairment is reasonably attributable to that source.

! Requirements to perform preconstruction review of the potential visibility impacts due

to new or modified sources, and procedures for federal land manager notification and

consultation.

! A monitoring plan to assess visibility in Class I areas and to track trends over time.

1.4.4 State and Federal Implementation Plans

The 1980 EPA regulations required certain states covered by the regulations to revise its

SIP to address visibility. Only seven SIPs with visibility provisions were approved between 1980

and 1985.

In 1985, the settlement of a lawsuit brought by the Environmental Defense Fund (EDF)

against the EPA required the EPA to establish Federal Implementation Plans (FIPs) for the

remaining states without approved visibility provisions in their SIPS. As part of the FIPs, EPA

regulations called for the establishment of a cooperative visibility monitoring effort between the

EPA, the National Oceanic and Atmospheric Administration (NOAA) and primary federal land

management agencies: the National Park Service (NPS), the United States Fish and Wildlife

Service (USFWS), the Bureau of Land Management (BLM), and the United States Forest Service

(USFS). This cooperative visibility monitoring effort became a reality in the mid-1980s and was

named IMPROVE (Interagency Monitoring of Protected Visual Environments). In 1991, several

additional organizations joined the effort: State and Territorial Air Pollution Program

Administrators and the Association of Local Air Pollution Control Officials (STAPPA/ALAPCO),

Western States Air Resources Council (WESTAR), and Northeast States for Coordinated Air Use

Management (NESCAUM). The Mid-Atlantic Regional Air Management Association

(MARAMA) was added in 1998 for broader participation of State agencies. The IMPROVE

program has been collecting data since 1988, and continues to collect and analyze visibility data

from Class I area monitoring sites throughout the United States. The objectives of IMPROVE

are to provide data needed to assess the impacts of new emission sources, to identify existing

man-made visibility impairment, and to assess progress toward the national visibility goals that

define protection of 156 Class I areas.
5

The Commission as created focused on 16 Class I areas of the Colorado Plateau, including: Grand

Canyon, Bryce Canyon, Zion, Canyonlands, Mesa Verde, Capitol Reef, Arches, and Petrified Forest National Parks.

The GCVTC was comprised of the Governors of eight western States (Arizona, California, Colorado, Nevada, New

Mexico, Oregon, Utah, and Wyoming), the leaders of five Indian tribes (Navajo, Hopi, Hualapai, Acoma Pueblo, and

the Columbia River Intertribal Fish Commission), and non-voting federal representatives, including EPA and several

land management agencies. The GCVTC submitted to EPA its Recommendations for Improving Western Vistas in

June 1996. The Commission’s work involved more than four years of technical assessment and discussion, and it

included participation by a wide range of stakeholders.

6

See Clean Air Act, section 169B(e)(1).

1-13

1.4.5 1990 Clean Air Act Amendments

As part of the development of the Clean Air Act Amendments of 1990, Congress

reviewed EPA's progress in protecting visibility in Class I areas. Recognizing that greater

emphasis was needed on the role of regional transport of pollutants responsible for visibility

impairment, Congress established a new section 169B. Section 169B provides for the following: 

1) Expanded research on air quality monitoring, modeling, atmospheric chemistry and

physics, and sources of impairment and factors leading to good visibility, including the

concept of clean air corridors.

2) A Report to Congress by EPA on visibility improvement that is expected from the

implementation of the 1990 Amendments, and periodic reviews every 5 years on actual

progress made in class I areas. 

3) Establishment of interstate visibility transport commissions for class I areas

experiencing visibility impairment. Section 169B required the establishment of the Grand

Canyon Visibility Transport Commission (GCVTC).5 EPA can establish commissions on

its own initiative, or by a petition from two or more States. Any visibility transport

commission is to assess the nature of adverse impacts on visibility due to potential or

projected growth of emissions, and to provide recommendations to EPA within 4 years. 

These recommendations must address measures to remedy such adverse impacts, including

the promulgation of regulations under section 169A. 

4) Within 18 months of receiving recommendations from any visibility transport

commission, the EPA is required to “carry out the Administrator’s regulatory

responsibilities under section 169A, including criteria for measuring “reasonable progress”

toward the national goal.”6

5) Section 169B also requires States to revise their visibility SIPs under section 110 of the

Act to include emission limits, schedules of compliance, and other measures as may be

necessary to carry out the new EPA regional haze regulations.
1-14

1.4.6 EPA Regional Haze Regulation

In July 1997, EPA proposed revisions to the existing 1980 visibility regulations. These

revisions would require States to revise their SIPs to address visibility impairment in the form of

regional haze. The regional haze regulations would also serve as a vital component of EPA's

overall approach to protect the public welfare from visibility impairment effects associated with

particulate matter. The regional haze regulation includes requirements for establishing baseline

and current conditions based on monitoring data, and for tracking visibility changes over time.

States also are required to submit a monitoring strategy within the time frame specified in the

regional haze rule.

To support implementation of the regional haze rule, EPA has funded the deployment of

the PM-2.5 monitoring network and the expansion of the IMPROVE network. During 1999,

approximately 78 new IMPROVE aerosol monitors will be sited in the vicinity of Class I areas. 

EPA is working closely with the States and Federal land managers through the IMPROVE

Steering Committee on implementing this expansion during FY99. The new PM2.5 network will

also include IMPROVE samplers which may be used at background or transport sites required

under the PM2.5 monitoring regulations. This network has a variety of monitors useful for

visibility assessments. These include nephelometers and other continuous analyzers as well as

aerosol samplers capable of assessing chemical speciation of particulate matter.
2-1

b

ext ' bsg

% b

ag

% b

sp

% b

ap

' b

scat % babs (2-1)

SVR ' 3912 / (b

ext & Ray % 10) (2-2)

2.0 MONITORING PROGRAM CONSIDERATIONS

2.1 VISIBILITY DEFINITIONS AND THEORY

A simple definition of visibility is "the appearance of scenic features when viewed from a

distance." The most popular term to characterize visibility is observer visual range which is the

greatest distance at which a large black object can just be seen against the horizon sky. Most in

the technical community prefer to use the term extinction coefficient (bext), which is the loss of

image-forming light per unit distance due to scattering and absorption by particles and gases in the

atmosphere. The extinction coefficient is the sum of the scattering coefficient (bscat) and

absorption coefficient (baba), which are similarly defined as the loss of light per unit distance by

scattering and absorption mechanisms respectively.

The extinction coefficient can be represented mathematically as:

where s, a, g, and p refer to scattering and absorption by gases and particles, respectively. 

Figure 2-1 illustrates how these properties affect the transmission of light from a scenic feature to

an observer. A pristine, particle free atmosphere where the only affect on light transmission is

caused by the scattering of light by atmospheric gases is called a Rayleigh atmosphere. The only

gas normally found in the atmosphere that absorbs light is nitrogen dioxide. The extinction

coefficient increases as particles and gases are added to the atmosphere. Therefore, visibility is

reduced due to increased particle scattering and absorption.

Figure 2-2 illustrates the size ranges of atmospheric particles that affect visibility. Particle

sizes are generally separated into three modes:

! Nuclei mode - 0.005 Fm to 0.1 Fm

! Accumulation mode - 0.1 Fm to 1 - 3 Fm

! Coarse mode - 1 - 3 Fm to 50 - 100 Fm

Fine particles less than 2.5 Fm affect light scattering more than particles greater than 2.5 Fm. The

most efficient light scattering particles are within the size range of the wavelength of visible light;

0.4 Fm to 0.7 Fm.

A simple model allows the observer visual range to be estimated from the extinction

coefficient by dividing a constant by the extinction coefficient. The magnitude of the constant

depends on the units used and assumptions concerning the minimal contrast detectable by the

observer. Visual range (Vr

) is the common name given to the resulting estimate. To compare

visibility data from different sites, visual range estimates can be normalized to a Rayleigh

scattering coefficient of 10 Mm-1 (particle-free atmosphere conditions at an altitude of 1.524 km

or 5000 feet). This normalized estimate is called the standard visual range (SVR) and can be

expressed as: 
2-2

where the units for SVR are kilometers (km), bext is the extinction coefficient expressed in inverse

megameters (Mm-1), Ray is the site specific Rayleigh value (elevation dependent) in inverse

megameters (Mm-1), 10 is the Rayleigh coefficient used to normalize visual range, and 3912 is a

constant derived assuming a 2% contrast detection threshold.

Visual air quality is a term which describes the air pollution aspects of visibility. Visual air

quality is what must be monitored and preserved, not the overall visibility which is influenced by

non-pollution factors (i.e., clouds, snow cover, sun angle, etc.). The atmospheric extinction

coefficient and parameters derived from the extinction coefficient describe visual air quality.

The distribution and extent of pollutants in the atmosphere relative to the observer's sight

path has a large effect on the appearance of visibility impairment. If the pollutants are uniformly

distributed both horizontally and vertically from the ground to a height well above the highest

terrain, it is known as a uniform haze. If the top edge of the pollution layer is visible, as is often

Figure 2-1. Properties of the Atmosphere that Affect the Transmission of Light from a Scenic

Feature to a Human Observer.
2-3

Figure 2-2. Size Distribution and Sources of Atmospheric Particles.

the case when a pollution layer is trapped below an inversion, then it is called a surface layer. A

pollution distribution that is not in contact with the ground is an elevated layer. Plumes can be

thought of as a special case of an elevated layer, though from many vantage points it may not be

possible to distinguish a plume from an elevated layer. It is possible to have combinations of

pollutant distributions such as multiple elevated layers superimposed upon a uniform haze.

Uniform haze and surface layered haze can be monitored by a variety of methods on the

ground. Elevated layers must be either remotely monitored from the ground or by instruments

carried aloft.
2-4

Visibility-related measurements can be partitioned into three (3) groups that describe and

define the visual characteristics of the air.

Aerosol The physical properties of the ambient atmospheric particles (particle

origin, size, shape, chemical composition, concentration, temporal and

spatial distribution, and other physical properties) through which a scene is

viewed. 

Optical The ability of the atmosphere to scatter or absorb light passing through it. 

The physical properties of the atmosphere are described by extinction,

scattering, and absorption coefficients, plus an angular dependence of the

scattering known as the normalized scattering phase function. Optical

characteristics integrate the effects of atmospheric aerosols and gases.

Scene The appearance of a scene viewed through the atmosphere. Scene

characteristics are more nearly in line with the simple definition of visibility

than aerosol or optical characteristics. Scene characteristics include

observer visual range, scene contrast, color, texture, clarity, and other

descriptive terms. Scene characteristics change with illumination and

atmospheric composition.

Aerosol and optical characteristics depend only on the properties of the atmosphere

through which light passes and therefore can be used to describe visual air quality. However,

scene characteristics are also dependent on scene and lighting conditions.
2-5

2.1.1 Characterizing Visibility Impairment

Visibility has historically been characterized either by visual range or by the light

extinction coefficient. These two measures of visibility are inversely related; visual range

decreases as the extinction coefficient increases. Visual range is presented in common units such

as miles or kilometers and is commonly used in military operations and transportation safety by

providing information to determine the minimum distance required to land an aircraft, the distance

to the first appearance of a military target or an enemy aircraft or ship, and safe maneuvering

distances under impaired visibility conditions. Because of the use of familiar distance units, the

simple definition, and the ability of any sighted person to characterize visual conditions with this

parameter without instruments, visual range is likely to remain a popular method of describing

atmospheric visibility. However, extreme caution must be applied when interpreting visual range

data from historical sources where human observations were the source of the data (e.g., airport

observations). The varying methods and procedures used by observers, the quality of the

observer measurements, and the availability of adequate visibility targets all can have a dramatic

effect on historical, observer-based data.

Extinction coefficient is used most by scientists concerned with the causes of reduced

visibility. Direct relationships between concentrations of atmospheric constituents and their

contribution to the extinction coefficient exist. Apportioning the extinction coefficient to

atmospheric constituents provides a method to estimate the change in visibility caused by a

change in constituent concentrations. This methodology, known as extinction budget analysis, is

important for assessing the visibility consequences of proposed pollutant emission sources, or for

determining the extent of pollution control required to meet a desired visibility condition. Interest

in the causes of visibility impairment is expected to continue and the extinction coefficient will

remain important in visibility research and assessment.

Neither visual range nor extinction coefficient measurements are linear with respect to the

human perception of visual scene changes caused by uniform haze. For example, a given change

in visual range or extinction coefficient can result in a scene change that is either unnoticeably

small or very apparent depending on the baseline visibility conditions. Presentation of visibility

measurement data or model results in terms of visual range or extinction coefficient can lead to

misinterpretation by those who are not aware of the nonlinear relationship.

To rigorously determine the perceived visual effect of a change in extinction coefficient

requires the use of radiative transfer modeling and psychophysical modeling. Radiative transfer

modeling is used to determine the changes in light transmission from the field of view arriving at

the observer location. Psychophysical modeling is used to determine the response to the light by

the eye-brain system. Results are dependent not only on the baseline and changes to atmospheric

optical conditions, but also on the characteristics of the scene and its lighting. The complexity of

employing such a procedure and the dependence of the results on non-atmospheric factors

complicate its widespread use to characterize perceived visibility changes resulting from changes

in air quality.
2-6

dv ' 10 ln(b

ext /10Mm &1

) (2-3)

b

ext ' bscat % babs ' bRay % bsp

% b

ag

% b

ap (2-4)

Parametric analysis methods have been used to suggest that a constant fractional change in

extinction coefficient or visual range produces a similar perceptual change for a scene regardless

of baseline conditions. Simplifying assumptions eliminates the need to consider the visibility

effects of scene and lighting conditions. Using the relationship of a constant fractional change in

extinction coefficient to perceived visual change, a new visibility index called deciview (dv) was

developed, and is defined as:

where extinction coefficient is expressed in Mm-1 (Pitchford and Malm, 1993). One (1) dv change

is approximately a 10% change in extinction coefficient, which is a small, but perceptible scenic

change under many circumstances. The deciview scale is near zero (0) for a pristine atmosphere

(dv = 0 for a Rayleigh condition at about 1.5 km elevation) and increases as visibility is degraded. 

Like the decibel scale for sound, equal changes in deciview are equally perceptible. Because the

deciview metric expresses visual scene changes that are linear with respect to human perception,

EPA supports the use of the deciview metric in characterizing visibility changes for regulatory

purposes.

2.1.2 Relationship Between Light Extinction and Aerosol Concentrations

The light extinction coefficient (bext) is the sum of the light scattering coefficient (bscat) and

the light absorption coefficient (babs). Light scattering is the sum of the scattering caused by gases

(bsg) and the scattering caused by suspended particles (bsp) in the atmosphere (aerosols). 

However, natural Rayleigh scatter (bRay) from air molecules (which causes the sky to appear blue)

dominates the gas scattering component. Particle scatter (bsp) can be caused by natural aerosol

(e.g., wind-blown dust and fog) or by man-made aerosols (e.g., sulfates, nitrates, organics, and

other fine and coarse particles). Light absorption results from gases (bag) and particles (bap). 

Nitrogen dioxide (NO2) is the only major light absorbing gas in the lower atmosphere; its strong

wavelength-dependent scatter causes yellow-brown discoloration if present in sufficient quantities. 

Soot (elemental carbon) is the dominant light absorbing particle in the atmosphere. Thus, the

total light extinction is the sum of its components:

Suspended particles in the atmosphere (i.e., collectively known as aerosols) usually

account for the dominant part of light extinction except under extremely clean conditions, when

natural Rayleigh gas scattering predominates. Thus, understanding visibility requires

understanding the basic concepts of aerosol air quality. 

The first concept concerns the origins of atmospheric particles. Particle origins can be

either anthropogenic (man-made) or natural. Another origin classification is primary versus

secondary. Primary particles are those that are directly emitted into the atmosphere as particles,

such as organic and soot particles in smoke plumes or soil dust particles. Secondary particles are

those that are formed from gas-to-particle conversion in the atmosphere, such as sulfates (from

SO2), nitrates (from NOx), and secondary organics (from gaseous hydrocarbons).

Two other aerosol concepts with respect to visibility are size distribution and chemical

composition. For visibility purposes, it is critical to distinguish fine particles (< 2.5 Fm) from

coarse particles (> 2.5 Fm), because fine particles are much more efficient at scattering light than
2-7

b

ext ' bRay % '$i

C

i

(2-5)

larger particles. The major constituents of ambient fine particulate matter consist of five species

(and their compounds): sulfates, nitrates, organic carbon, elemental carbon, and soil dust. In

addition to these chemical species, the effect of water associated with sulfate, nitrate, and some

organics needs to be considered for assessment of visual air quality(see Section 2.1.3 below). 

Significant differences exist among each of these species, in sources, atmospheric behavior, size

distributions, and visibility effects. The coarse fraction of PM10 (particles with diameters between

2.5 Fm and 10 Fm) and other suspended particles (those with diameters greater than 10 Fm) can

be considered separately and are generally not subdivided into separate species.

The relationship between atmospheric aerosols and the light extinction coefficient can

usually be approximated as the sum of the products of the concentrations of individual species and

their respective light extinction efficiencies, better known as reconstructed light extinction. 

Reconstructed extinction is expressed as:

where $i is the light extinction efficiency (m2/g) of species i, Ci is the atmospheric concentration of

species i (μg/m3), and the summation is over all light-interacting species (i.e., sulfate, nitrate,

organic carbon, elemental carbon, other fine particles, coarse particles, other suspended particles,

and NO2). The above units, when multiplied, yield units for bext of 10-6 m-1 or (106 m)-1, or as

typically labeled, inverse megameters (Mm-1).

An equation used by the IMPROVE program to estimate reconstructed aerosol extinction

is:

bext = bray + (3)f(RH) [Sulfate] + (3)f(RH) [Nitrate] +

(4) [Organic Mass Carbon] + (1) [Soil] + (2-6)

(0.6) [Coarse Mass] + babs

Alternatively, babs can be replaced by 10 times elemental carbon mass. Sisler and Malm (1999)

discuss this issue. In the above formula, all the terms in square brackets refer to the mass

associated with those entities.

Note that this aerosol/light extinction relationship is derived from externally mixed particles and

does not account for all of the complex interactions possible in the atmosphere. However, the

relationship is a good approximation.

2.1.3 Importance of Relative Humidity on Light Scattering

Because some aerosols including sulfates, nitrates, and some organics are hygroscopic

(have an affinity for water), their scattering properties can change as a function of relative

humidity (RH). As the relative humidity increases these hygroscopic aerosols can grow to

become more efficient light scatterers. The aerosol growth curve is particularly significant for

relative humidities greater than 70%. Figure 2-3 illustrates the relationship between RH and

scattering efficiency for ammonium sulfate aerosols 
2-8

f(RH) ' b

scat (RH) / bscat (0%) (2-7)

Figure 2-3. The Relationship between the Scattering Efficiency of

 Ammonium Sulfate Aerosols and Relative Humidity

 (Malm et al., 1996).

with a mass mean diameter of 0.3 Fm and a geometric size distribution of 1.5 Fm (Malm et al.,

1996). The function of RH, f(RH), illustrated in Figure 2-3 is:

where bscat (0%) and bscat (RH) are the dry and wet scattering, respectively. This function

describes the scattering efficiencies for ammonium sulfate and ammonium nitrate.

Various functions for the humidity-related scattering efficiencies of organics have been

proposed. These functions must consider the solubility of individual organic species and fractions

of various organic species in the atmosphere. The types and concentrations of organics can vary

geographically and the associated RH functions can change. White (1990) discusses this issue.
2-9

To perform reconstructed particle scattering estimates, the scattering efficiencies (in m2/g)

of atmospheric species as a function of relative humidity and the concentration of the species must

be considered. Malm et al. (1996) explores the analytical consideration required to reconstruct

particle scattering using the Grand Canyon as an example. Ideally, relative humidity would be

measured continuously at each site in order to better understand its effect on day-to-day

variations and annual changes in visual air quality. If on-site meteorological data are not

available, however, humidity can be estimated from climatological databases for appropriate

nearby locations to represent the humidity characteristics of the Class I area. In either case,

analysis of visibility trends in accordance with the tracking requirements of the regional haze rule

should utilize long-term average f(RH) factors which are representative of best and worst

visibility conditions. This approach will provide measures of visual air quality which are more

directly related to the changes in the pollutants that cause visibility impairment, and are less

affected by day-to-day or year-to-year changes in humidity.

2.2 VISIBILITY GOALS AND MONITORING OBJECTIVES

The purpose of visibility monitoring is to collect high quality, consistent data that can be

used in analyses to assess whether progress is being made toward meeting visibility goals, and to

understand the types of emissions sources contributing to visibility impairment. The Clean Air

Act and related EPA regulations define the nation's visibility protection goals. Monitoring

objectives outline the types of monitoring required for specific analyses or actions needed to make

progress toward these goals. These visibility goals and monitoring objectives are outlined in

Table 2-1 and discussed in the following subsections.

2.2.1 Visibility Goals

The primary visibility-related goals found in the Act and EPA regulations are summarized

below and in Table 2-1:

Section 169A of the Clean Air Act provides two primary goals:

! "...the prevention of any future, and the remedying of any existing, impairment of

visibility in mandatory Class I Federal areas which impairment results from man-made

air pollution."

! State implementation plans must ensure “reasonable progress” toward the national

visibility goal. 

Section 109 of the Act:

! Any national secondary NAAQS should specify a level of air quality that is requisite to

protect the public welfare from any known or anticipated adverse effects associated

with the presence of the pollutant in the ambient air.
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Section 172 of the Act (re: NAAQS): 

! The attainment of any primary NAAQS should be achieved as expeditiously as

practicable, but no later than 5 years after nonattainment designation. Areas with

more severe problems can be considered for an additional 5-year extension. 

! The attainment of any secondary NAAQS should be achieved “as expeditiously as

practicable.”

Section 165(d)(2) of the Clean Air Act charged federal land managers (FLM) with the

following visibility-related goal:

! FLMs have an affirmative responsibility to "protect the air quality related values

(AQRVs) of any mandatory Class I federal area."

 The visibility regulations in 40 CFR 51.300-309 

! States are required to “assess the impacts of existing and proposed new sources of Class

I area visibility impairment." Specifically, this requirement includes provisions related to

new source review in 307, to BART in 302 and 308, and to progress goals in 308.
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Table 2-1

Visibility Goals and Monitoring Objectives

Visibility Goals

1 National Visibility Goal - "...the prevention

of any future, and the remedying of any

existing, impairment of visibility in

mandatory Class I Federal areas which

impairment results from man-made air

pollution...." Ensure reasonable progress

toward the National Goal.

5 Ensure that SIPs contain: 1) a long-term

strategy, BART, and other measures necessary

to make “reasonable progress” toward the

national visibility goal, 2) visibility analysis in

preconstruction review process, 3) monitoring

program.

2 NAAQS: The protection of public health and

welfare through attainment of NAAQS as

expeditiously as practicable. 

3 The FLM has an affirmative responsibility

to "protect the air quality related values

(AQRVs) of any mandatory Class I federal

area."

4 The FLM has the responsibility to "assess

existing and proposed sources of Class I

area visibility impairment."

9 Measuring reasonable progress as specified

in the Regional Haze Rule

Visibility Monitoring Objectives

1 Adopt monitoring protocols to ensure that high

quality, nationally consistent, comparable data

are collected by all monitoring organizations.

4 Document long-term trends and track progress

toward visibility improvement goals.

2 Establish current visual air quality conditions

that for each site are representative of a fairly

broad geographic region, based on 

! Aerosol characteristics, and when possible

for

! Optical characteristics

! Surface and elevated haze characteristics

5 Provide data for the new source review

permitting process.

3 Identify sources through source attribution

analysis that are “reasonably anticipated to

cause or contribute” to visibility impairment in

any class I area.

6 Provide data for the prevention of significant

deterioration permitting process.
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EPA’s 1980 visibility regulations address reasonably attributable visibility impairment. The

primary regulatory agency and FLM goals presented in these regulations are to:

! Ensure that SIPs contain a long-term strategy, measures addressing best available retrofit

technology for certain sources, and other measures as necessary to make “reasonable

progress” toward the national visibility goal ("the prevention of any future, and the

remedying of any existing, impairment of visibility in mandatory Class I Federal areas

which impairment results from man-made air pollution").

! Establish programs providing for preconstruction visibility impact analyses by new source

permit applicants and appropriate review by States and Federal land managers

! Establish a monitoring program to assess current conditions, track progress toward the

national goal, and identify the sources contributing to visibility impairment.

When a number of states failed develop SIPs, the Environmental Defense Fund sued the EPA

to enforce the 1980 regulations. The lawsuit settlement required the EPA to develop new source

review and visibility monitoring provisions for those states in the form of Federal Implementation

Plans (FIPs). 

! As part of the FIPs, EPA regulations called for the establishment of a cooperative

visibility monitoring effort between the EPA, principle federal land management agencies,

the states, and state organizations. The first formal cooperative visibility monitoring

effort became a reality in the mid-1980s and was named IMPROVE (Interagency

Monitoring of Protected Visual Environments).

The 1990 amendments to the Clean Air Act included a new section 169B emphasizing

regional visibility impairment issues. Section 169B outlines four specific goals for future visibility

protection:

! To expand scientific knowledge and technical tools on visibility. 

! To assess how implementation of various CAA programs may result in improvement in

visibility in Class I areas; and

! To provide for establishment of the Grand Canyon Visibility Transport Commission and

to allow for the establishment of other Visibility Transport Commissions.

! To require EPA to develop regional haze regulations, including “criteria for measuring

reasonable progress toward the national goal.”

As part of the IMPROVE monitoring program, the EPA, federal land managers, state

agencies, and local governments have developed individual goals and objectives in response to

visibility regulations set forth in the CAA and EPA regulations. Primary objectives, seen by the EPA

as essential when establishing a visibility-related monitoring network, follow in Section 2.2.2,

Monitoring Purpose and Objectives. Additional programs and applications which benefit from the

information obtained by visibility monitoring are defined in Section 2.4.2, Data Uses.
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2.2.2 Monitoring Objectives

The purpose of visibility monitoring is to collect high quality data that can be used in analyses

to assess whether or not progress is being made toward meeting the visibility goals. Without

measurements there is no quantifiable method of tracking progress. The monitoring objectives listed

in Table 2-1 and discussed below outline the types of data required to perform goal oriented analyses.

The monitoring objectives address the visibility protection regulations for mandatory Class

I areas and other areas of concern. The mandatory Class I areas were designated by Congress and

are listed in Table 1-1 of this document. Other natural areas of concern include non-mandatory Class

I areas and Class II areas of particular interest to the land management agency, state, tribe, or other

responsible organization. For example, the U.S. Fish and Wildlife Service may define its affirmative

responsibility to protect visibility to include selected resource areas, or a state may decide to protect

a region of special interest. These non-mandatory areas do not fall under EPA's jurisdiction but could

be included in the monitoring objectives of responsible agencies.

The principle objectives for visibility monitoring are as follows:

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.

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.

6) Provide data for Prevention of Significant Deterioration (PSD) analyses.

2.2.2.1 Ensure that High Quality, Comparable Data are Collected by All Monitoring

Organizations Through Adoption of Standard Monitoring Protocols.

It is essential that data be collected in a technically sound, quality-assured manner by all

monitoring organizations. It also must be regionally and nationally comparable, consistent over time

and capable of supporting the visibility goals of the Act and EPA regulations. In order to satisfy the

visibility monitoring objectives described above, the regional haze rule does not specify a Federal

reference method for visibility monitoring. Instead, this document constitutes official EPA guidance

on visibility monitoring. The protocols contained herein generally follow those established under the

IMPROVE Program, have been peer-reviewed and are widely accepted. 

These IMPROVE protocols include Standard Operating Procedures (SOPs) and Technical

Instructions (TIs) that define the monitoring methods, laboratory methods, data reduction and
2-14

 validation procedures, quality assurance requirements, and archive formats for aerosol, optical and

scenic monitoring. Federal land management agencies and a number of state and municipal

organizations have adopted these protocols. These protocols are more fully described in Sections

3.0 through 5.0 of this document. 

 The guideline protocols may be implemented by individual organizations or cooperative

monitoring programs. A county or state agency, an industrial source, a federal land manager, Indian

tribe, or a combination of public and private organizations can design and implement a monitoring

site or network.

Cooperative monitoring programs have advantages that include: reducing duplication of

effort, sharing resources allowing economy of scale, involving more participants, and providing a

consistent, comprehensive database. Most cooperative programs are based on a memorandum of

understanding between cooperators that clearly defines the program's goals and objectives. The

activities of most cooperative programs are defined by a steering committee, composed of

representatives from the cooperating organizations, and generally functions like a board of directors.

The steering committee generally designates an operating agent (most often one of the committee

members agencies) to manage the day-to-day monitoring functions including fiscal and contract

management.

The primary example of a long-term, effective cooperative effort to monitor visibility for

regulatory, planning, and research purposes is the Interagency Monitoring of Protected Visual

Environments (IMPROVE) Program. IMPROVE is a cooperative visibility monitoring effort among

the EPA, NOAA, FLMs (NPS, USFS, USFWS), and state air agencies (STAPPA/ALAPCO,

WESTAR, NESCAUM and MARAMA). Established in 1985, IMPROVE supports routine visibility

monitoring in Class I areas nationwide and also conducts research on visibility issues. The broad

spatial scale of the IMPROVE Program allows for regional and national scale assessment of visibility.

The IMPROVE Program has also established operational visibility monitoring protocols that are used

by many other projects.

Other cooperative efforts have been formulated to address specific visibility issues. Examples

of public and private partnerships to assess specific visibility impacts on Class I areas include Project

MOHAVE (Measurement Of Haze And Visual Effects) and the Mount Zirkel reasonable Attribution

Study. An example of recent research programs that included visibility components are SEAVS

(South Eastern Aerosol and Visibility Study) and NFRAQS (Northern Front Range Air Quality

Study).

Because visibility issues generally include an important regional component, cooperative

efforts that cross protected area and state boundaries are an effective way to design and implement

visibility monitoring programs.

2.2.2.2 Establish Current Visual Air Quality Conditions

This objective is necessary for two reasons: 

1) Visibility levels monitored in or near a specific Class I area, when compared to

surrounding area visibility or area estimates of natural levels, may be sufficient to indicate

man-made impairment.
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2) Knowledge of existing visibility conditions is required to model the anticipated visibility

effects of proposed emission sources, or of proposed emissions reductions.

3) A baseline level of visibility impairment is needed in order to judge reasonable progress

in accordance with the requirements of the Regional Haze rule.

Establishing present visibility levels requires routine monitoring that documents the frequency,

duration, and intensity of both surface and elevated hazes. Aerosol, optical, and scene monitoring

methods are appropriate for surface haze monitoring, while scene monitoring is the only practical way

to routinely monitor elevated layers. 

Visibility varies with time. Diurnal, weekly, seasonal, and inter-annual variations occur. In

accordance with the Regional haze rule, five years of data should be used in establishing a baseline

of seasonal and annual average conditions to reduce the normal year-to-year fluctuations due to

meteorology.

 

The magnitude of visible effects from a modeled increment of additional air pollution depends

on the aerosols already in the atmosphere. For example, 1 microgram per cubic meter of additional

fine particles is visible when added to ambient concentrations of 5 micrograms per cubic meter, but

may not be perceptible when added to 30 micrograms per cubic meter. Without adequate knowledge

of existing visibility levels, the potential impact of new source emissions on the protected resource

will be difficult to determine.

2.2.2.3 Identify Sources of Impairment

In order to make progress toward the national goal of no manmade impairment in mandatory

Class I areas, as called for by Congress, the States and EPA need to conduct monitoring to identify

the sources responsible for the impairment. Regional haze attribution refers to the identification of

average contributions by different aerosol species, source categories, or specific sources. 

Distinguishing man-made from natural impairment, which is fundamental to the congressional goals,

requires information derived from monitoring data. Regional haze characterization identifies the time

distribution of visibility levels (e.g., diurnal patterns, frequency, intensity, and duration). Monitoring

is the principle means of gathering information needed to identify the contribution by emission sources

to overall impairment levels and to time distributions of impairment as well.

Scene and aerosol monitoring methods are primarily used to identify emission sources.

Photography of a plume emanating from a source and impacting a Class I area is sufficient to indicate

impairment. A series of photographs can be evaluated to characterize the intensity, frequency, and

duration of the visible plume. Unfortunately, most visibility impairment does not lend itself to this

simple type of source attribution. Sources are often not visible from the Class I area, or their plumes

disperse and are transformed into a uniform haze before reaching the area. In addition, visibility

impacts are often caused by secondary aerosols formed over time from gaseous pollutants.

Understanding the characteristics of the aerosols in a haze can help identify the type of sources that

contributed to the haze. It is possible to statistically estimate what portion of a haze is caused by each

aerosol type. This approach, known as an extinction budget analysis, can narrow the list of possible

sources responsible for visibility impacts. For example, if sulfate is shown to be responsible for 75%

of the extinction coefficient, the major sources responsible for the haze must emit sulfur dioxide.
7

 Section 51.307 of EPA’s visibility regulations requires any new or modified source locating

within a nonattainment, attainment, or unclassifiable area for a NAAQS to evaluate the potential

adverse impact of the proposed source on visibility in the relevant Class I area(s).

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Another related approach for source identification using aerosol data is known as receptor

modeling. Instead of using only the major aerosol components that are directly responsible for the

impairment, receptor models use relative concentrations of trace components which can more 

specifically identify the influence of individual sources (or source types). For example, the presence

of arsenic may be a good indicator of copper smelter emissions.

2.2.2.4 Document Long-Term Trends

With the establishment of a long-term goal of no man-made visibility impairment in protected

areas, Congress imposed the responsibility to show progress towards meeting that goal. Long-term

consistent monitoring and trends analysis is an ideal approach for tracking the visibility conditions of

Class I and other areas of concern.

The same monitoring methods used to establish present visibility levels will provide the data

required to determine long-term visibility trends. To determine the individual effectiveness of several

concurrent emission reduction programs, it will be necessary to conduct aerosol monitoring to

support extinction budget analysis as described above.

Determining the specific visibility strategy for any area of concern requires an understanding

of the effect that man-made aerosols have on the existing conditions, and projecting what the visibility

would be like if the man-made aerosols were changed. This type of analysis can range from simple

to complex for specific areas. In areas where man-made aerosols exist, the long-term goal is to

improve upon existing conditions. The concept of continual improvement toward no man-made

impairment is significant. It is not enough to maintain existing conditions in areas where man-made

pollution exists when improvement is the goal. The EPA and/or regulatory agencies must define what

continual improvement means, but monitoring of ambient air quality will likely be a principle method

for tracking and verifying whether improvement occurs.

2.2.2.5 Provide Data for the New Source Review and Prevention of Significant Deterioration

Permitting Programs 

The New Source Review (NSR) permitting program applies to new major stationary sources

and major modifications locating in areas designated as nonattainment for the NAAQS. The

Prevention of Significant Deterioration (PSD) permitting program applies to new major stationary

sources and major modifications locating in areas designated as attainment or unclassifiable for the

NAAQS. 

These programs generally require the permit applicant to conduct a source impact analysis.

For the NSR program, the impact analysis must demonstrate that the new or modified source will not

cause or contribute to a violation of state or national air quality standards (NAAQS) or cause an

adverse impact to visibility in any Federal class I area.7 
2-17

The PSD program, in addition to providing protection of the NAAQS, is generally designed

to provide a more comprehensive source impact analysis than the NSR program. Included in this

impact analysis is the protection of Federal lands (national parks, wilderness areas, etc.) which have

been designated as Class I areas for PSD purposes. A special feature of the protection of air quality

in Class I areas is the responsibility to assure that air pollution will not adversely affect air quality

related values (including visibility) that have been identified for these areas. 

The company or other entity proposing to build a new stationary source or major modification

may be required to apply air quality models to carry out the source impact analysis. The air quality

data used to provide existing conditions for these models most often come from routine monitoring

sites. State and/or national monitoring networks (e.g., IMPROVE) generally provide the aerosol,

optical, and/or scene information necessary to understand existing visibility conditions in Class I

areas, represented as the annual frequency distribution of the extinction coefficient and/or standard

visual range. Understanding the existing conditions is important in determining whether a new or

modified source’s emissions may have an adverse impact on visibility. If a potential for visibility

impairment exists, the source emissions are generally mitigated (or offset) during the permit process

to significantly lower the probability of impacts. 

In some cases, if visibility-related monitoring does not exist which represents a Class I area

or other area of concern, the implementation plan must define a method to determine how

representative data from existing monitoring sites can be used to evaluate potential impacts to Class

I areas. To evaluate whether an existing monitoring site is representative of other sensitive areas

requires an analysis which must consider several factors, including the geography, topography,

meteorological patterns, and potentially contributing sources. 

Using monitoring to help evaluate representativeness may only require that a selected

methodology, such as a single filter aerosol monitor (e.g., mass and elements only) or an optical

monitor (e.g., nephelometer), be placed at the area of interest for comparison to a nearby primary site.

Additional considerations to determine local and/or regional representative conditions are described

in Section 2.6.1.1. 

Under some circumstances, when the uncertainty of modeled results is high, a permit may

require pre- and/or post-construction monitoring to better define local existing conditions (if nearby

monitoring data are not available) and to verify that no impacts occur. The type of monitoring

required is generally defined in the permit and may be limited to a few critical parameters. Most

resulting monitoring efforts are local to the proposed source. The basis for visibility monitoring under

a permit requirement is often a negotiated process among the state, federal land management agency,

and the source. The monitoring techniques applied in this type of program for specific visibility

parameters will generally parallel those required for routine monitoring, however, the temporal

frequency or local spatial distributions may be enhanced as compared to the more regional monitoring

networks so that more information can be gathered over a shorter time period to support timely

mitigation decisions.

2.3 VISIBILITY DATA QUALITY OBJECTIVES

To meet the established objectives of a visibility monitoring program, data quality objectives

must be adopted or established by the monitoring organization. These data quality objectives must

be an integral part of the monitoring program and address: primary parameters, network design, and
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quality assurance. Recommendations and considerations for defining data quality objectives are

outlined below and further discussed throughout this document.

2.3.1 Primary Parameters

Monitoring of the primary visibility parameters can be separated into three categories: aerosol,

optical, and scene. The data quality recommendations in each category are summarized below.

Detailed descriptions and examples of each monitoring method are provided in Section 2.4.

2.3.1.1 Aerosol

Aerosol monitoring obtains concentration and composition measurements of atmospheric

constituents that contribute to visibility impairment. Recommended aerosol monitoring quality

objectives are:

! Collect 24-hour filter samples of PM2.5 and PM10 particulates at least every third day.

! Determine the 24-hour average PM2.5 (fine), PM10 and PM10 minus PM2.5 (coarse) mass

concentration of the filter samples with an overall accuracy of 10%.

! Analyze PM2.5 filters to determine 24-hour mass concentrations (with an overall accuracy

of 10%) of the following individual visibility impairing particulate constituents that either

contribute to visibility impairment or serve as indicators of the sources of PM2.5 particles:

- Major contributors to visibility impairment (large contributors to mass and

important for reconstructed extinction)

Sulfates

Nitrates

Organic carbon

Elemental carbon (light absorbing carbon)

Chlorides

Earth crustal elements

Light absorption (optical parameter from filter light transmission

measurement)

- Elements and compounds that further serve as indicators of sources of visibilityrelated particles

Trace elements

Ions

! Derive the liquid water associated with hygroscopic species from associated RH

measurements and species growth curves.

! Determine additional particulate characteristics that may be useful in source attribution

analysis. For example, certain trace elements may be used in Chemical Mass Balance

(CMB) to estimate specific source contributions of interest (e.g., vanadium and nickel as

indicators of oil refining).
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2.3.1.2 Optical 

Optical monitoring measures the light scattering and absorbing properties of the atmosphere,

independent of physical scene characteristics or illumination conditions. Optical monitoring

recommendations are the following:

! Determine the hourly average ambient atmospheric light extinction coefficient with an

overall accuracy of 10%. The total extinction can be measured directly or derived from

measurements of the light scattering and absorbing components of extinction.

! Air temperature and relative humidity measurements should be collected simultaneously

with optical measurements. These readings provide the information required to assess

weather interferences and humidity related visibility affects. The overall accuracy of

temperature and relative humidity measurements should be ± 0.5EC and ± 2% RH

respectively. The meteorological parameters should be measured in accordance with EPA

guidance.

2.3.1.3 Scene

Scene monitoring refers to the use of still and/or time-lapse photography (including digital

imagery) to provide a qualitative representation of visual air quality. Scene monitoring data quality

objective recommendations are to document the appearance of scenes of interest under a variety of

air quality and illumination conditions at different times of day and different seasons. The quality

(resolution) of the data collection media is important. Photographs should be obtained using 35 mm

color slide film. Color video or digital images should be S-VHS format or better.

2.3.2 Network Design

A visibility monitoring program to characterize a Class I area or other area of concern could

consist of one site or a network of sites. Detailed site and network design considerations and

example network configurations are provided in Section 2.6. However, the principle considerations

in network design are the following:

! Each site must be selected to represent visual air quality within the air mass of interest.

For example, the visual air quality of a Class I area should be monitored at an elevation

typical of the Class I area, and within the area or as close as possible to the Class I area

boundary.

! The spatial and temporal aspects of a monitoring network must be designed to meet the

monitoring goals and objectives of the network. For example, long-term trend monitoring

of a remote area may only require one well placed site that will operate in perpetuity. A

specific source attribution study may require a network of many sites placed upwind and

downwind of a suspected source region, but may only operate for a short period of time

(several months to a year or more).
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! “Representative” sites should be determined on a case-by-case basis. Important

considerations should include common elevation, common source region of emissions,

and similar location relative to major topographic features. (See additional discussion in

section 2.6.)

! Year-round monitoring may not be practical at certain mandatory class I sites due certain

geographic or safety limitations, such as the extremely remote location of a class I area.

The IMPROVE Steering Committee and relevant States should address such situations

on a case-by-case basis. 

! Visibility site and network designs may vary due to cost, logistical, or historical data

considerations, but an ideal site design would include the full complement of aerosol,

optical, and scene monitoring. The relevant monitoring organization should fully

document the reasons for any site or network monitoring design decisions.

General visibility network design guidelines are the following:

! Aerosol, optical, and scene information is desired for each site.

! At a minimum, aerosols should be monitored at one or more sites representative of an

area of concern. These measurements should include PM2.5 mass, PM10 mass, and the

mass concentrations of aerosol species that include sulfates, nitrates, organic carbon,

inorganic carbon, earth crustal components, ions, and other major and trace elements.

Without aerosol monitoring the causes of visibility impairment can not be quantified.

Initially, all aerosol constituents must be addressed. An individual constituent may be

eliminated if historical data indicate the constituent is minor or below detection limits.

However, this decision should be revisited periodically to ascertain if underlying

conditions have changes. In situations where optical monitoring is not possible due to

cost considerations, aerosol monitoring alone can be used to calculate reconstructed light

extinction using known or assumed extinction efficiencies for principal aerosol

components. 

! Continuous optical monitoring is recommended at all sites. Continuous optical

monitoring by nephelometer or transmissometer (hourly averages) provides an

understanding of the temporal dynamics of visibility. When an optical monitor is

collocated with an aerosol sampler, the optical data provides a valuable cross-check for

reconstructed extinction analyses.

! Scene monitoring (35 mm photography, time-lapse video) documents the visual

appearance of uniform haze, ground-based layered haze, elevated layered haze, and the

overall characteristics of the scene. Scene monitoring is the only ground-based way to

observe and characterize elevated layers or plumes. Scene monitoring at long-term sites

can often be reduced after an extended period of time (i.e., five years) if a sufficient

photographic record that covers the broad range of expected conditions has been

established.

! The configurations of monitoring sites need to be periodically evaluated to determine if

changes are warranted. For example, changes in area-wide emissions may warrant

changes in the monitoring strategy applied at a site. Or, a network site could be
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eliminated or its configuration simplified if it correlates well with another network site

that could be considered representative.

! New monitoring and analysis technologies need to be evaluated and implemented where

appropriate to enhance the information gained at monitoring sites.

Site and network designs vary depending on monitoring objectives, logistic considerations,

and cost considerations. Table 2-2 summarizes appropriate configuration sites designed to meet a

number of common monitoring objectives, including: 1) Sites to determine existing conditions, track

long-term trends, and source attribution; 2) Monitoring for PSD and NSR where only total light

extinction measurements or visual range are required; and 3) Short-term pilot study options for initial

evaluations or spatial representativeness tests. 

The table highlights several approaches for each common objective. For example, to

determine existing conditions, the most scientifically sound configuration would include a

comprehensive configuration of aerosol, optical, and scene parameters where a transmissometer

would measure bext. If a transmissometer installation were not possible due to logistic limitations, a

nephelometer-based installation would be a viable alternative. If no optical monitoring were possible

due to cost limitations, an aerosol-based approach could be used. In fact, if the primary objective

is to establish a multi-year baseline, then aerosol monitoring is sufficient to evaluate visual air quality.

 For an aerosol-based configuration, light extinction would have to be reconstructed from known or

assumed bext/aerosol relationships. Such relationships are already well-established for certain regions

of the country. Table 2-2 highlights similar configuration considerations for other objectives. The

ultimate site and network design must address both scientific and practical issues.

2.3.3 Quality Assurance

All monitoring programs must operate in accordance with documented quality control and

quality assurance procedures that address:

! Standard operating procedures and technical instructions for calibration, monitoring, data

collection, data processing, reporting, archive, and audit procedures.

! Data recovery and quality goals. Recommended values are:

- Data recovery better than 90% (including all weather influences).

- Precision and accuracy better than 10%.

- Detection limits for all aerosol species based on the specific analytical technique

must be defined and measurements must be evaluated against the detection limits.

! Standard scientifically accepted methods to determine, calculate, and report

measurements:

- Standard visibility variables and units:

bext, bscat, babs, (inverse megameters)

deciview index (in dv)

visual range (in km)

- Standard aerosol mass concentrations units:

Fg/m3
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- Weather influences on visual air quality. These must be addressed in data

analyses.

- Specific precision, accuracy, and /or detection limit references. These should be

associated with data values.

- Validity flags and weather effects flags. These should be associated with data

values.

Quality assurance, sampling methods, and standard unit considerations are addressed further

in Section 2.4.
Table 2-2

A Summary of Appropriate Site Configurations for

Common Monitoring Objectives

Common

Applications

(to meet

monitoring

objectives)

Monitoring

Approach

Aerosol Optical Scene

Meteorology PM2.5 PM10 bag Trans Neph Still-Frame Time-Lapse Comments

Mass Elements Ions bap Mass Elements NO2 Gas bext bscat Instantaneous Dynamic AT/RH

Determine existing

conditions, track

long-term trends,

and source

attribution

Most scientifically

sound - Aerosol,

Optical

(transmissometer), and

Scene

T T T T T AN AN T T T Scene monitoring can be

terminated after approx. 5 years

if a sufficient visual record is

compiled

Aerosol, Optical

(nephelometer), and

Scene

T T T T T AN AN T T T Scene monitoring can be

terminated after approx. 5 years

if a sufficient visual record is

compiled

No optical possible,

Aerosol-Based

(reconstructed

extinction)

T T T T T AN AN T T Scene monitoring can be

terminated after approx. 5 years

if a sufficient visual record is

compiled

PSD or NSR when

only extinction

measurements are

required

Most scientifically

sound - Optical

(transmissometerbased)

T T

Optical (nephelometerbased)T AN T T

No optical possible -

Aerosol-Based

(reconstructed

extinction)

T T T T AN T

Scene only (elevated

layer characterization

or visible plume

attribution)

T AN

Short-term pilot

study options for

initial evaluations or

spatial

representativeness

tests

Aerosol-Based T T T IMPROVE Module A only is

commonly applied

Optical - 

(nephelometer-based)

T T

Scene-Based T AN Cameras are often a first step to

document the presence of

ground-based or elevated layers

T = Recommended

AN = As Needed
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2.4 MONITORING METHODS

 Adequate monitoring is an essential element for assessing whether the visibility goals adopted as part

of the CAA and EPA regulations are being met. Visibility monitoring consists of three distinct monitoring

components that describe and define the visual characteristics of the air: aerosol monitoring, optical

monitoring, and scene monitoring.

Aerosol monitoring is used to obtain concentration measurements of atmospheric constituents that

contribute to visibility impairment. Primary techniques include filter-based aerosol samplers that collect

samples on various substrates in two size ranges, aerodynamic diameters #2.5 Fm (PM2.5) and aerodynamic

diameters #10 Fm (PM10). To identify and track the relative visibility impacts caused by various pollution

species, a complete aerosol characterization is recommended. This would include PM2.5 compositional

analysis for all of the major components responsible for visibility impacts, including sulfates, nitrates, organic

carbon species, inorganic carbon, earth crustal components, and the chemical constituents of other fine mass.

Where wind erosion may be a concern, the coarse particle mass concentration (particle diameter from 2.5 Fm

to 10 Fm) should also be characterized. An understanding of the liquid water associated with hygroscopic

particle components is also important. With present technology, the liquid water particle component cannot

be directly measured, nor is it possible to determine liquid water content from subsequent analysis of particle

samples. Relative humidity data can be used to infer the visibility impacts associated with liquid water. Due

to the significance of this component for visibility effects for assessment of daily visibility levels, continuous

relative humidity monitoring is a desirable supplement to aerosol monitoring. However, aerosol data together

with climatological meteorological parameters can be used to estimate extinction. 

Optical monitoring is used to measure the light scattering and absorption properties of the

atmosphere, independent of physical scene characteristics or illumination conditions. It requires accurate and

precise measurements of the ambient optical properties of the atmosphere. The primary optical parameter

is the ambient extinction coefficient (bext), defined as the fraction of light lost per unit distance as light

traverses the atmosphere. It is the sum of scattering and absorption coefficients (bscat and babs) of atmospheric

gases and aerosols. Optical monitoring can be performed using a transmissometer to obtain ambient

extinction measurements. Where practical considerations limit the use of a transmissometer, direct

measurements of scattering (using a nephelometer) can be combined with collocated aerosol measurements

of absorption to estimate extinction. Similar to aerosol monitoring, an understanding of the liquid water

associated with the observed bext measurement is important. Relative humidity data can be used to clarify

observed visibility impacts that are associated with liquid water. Due to the significance of this component,

continuous relative humidity monitoring should also be a part of optical monitoring.

Scene monitoring refers to still and/or time-lapse photography (including digital imagery) that is used

to provide a qualitative representation of the visual air quality in the area of interest. The photographic

record documents the appearance of a scene. Scene characteristics include color, texture, contrast, clarity,

and observer visual range. Photography is uniquely suited for identifying ground-based or elevated layers

or plumes that may impact Class I or protected areas, as well as documenting conditions for interpreting

aerosol and optical data.

Since its formation in 1985, researching the most effective and efficient means of monitoring visibility

and applying these methods in a national monitoring program have been primary objectives of the IMPROVE

Program. IMPROVE protocol defines that, where possible, aerosol, optical, and scene monitoring should

be conducted at each site.
2-25

Instrumentation used to fulfill IMPROVE protocols include:

! Aerosol - IMPROVE modular aerosol sampler

! Optical - transmissometer or nephelometer (collocated with an air temperature/ relative humidity

sensor)

! Scene - automatic camera systems

IMPROVE sampling and instrumentation protocols serve as the basis for NPS, USFS, USFWS, and a number

of state and local visibility monitoring programs today.

By implementing full IMPROVE protocols, precise and reliable measurements of bext, bscat, and babs

can be obtained to characterize the parameters of the atmosphere and allow for the determination of effects

due to specific pollution species. Table 2-3 summarizes standard IMPROVE monitoring instrumentation and

sampling protocols. Although IMPROVE protocols support a full site configuration of aerosol, optical, and

scene monitoring, some visibility related objectives can be met with a subset of the monitoring components.

Sites without aerosol monitoring but with optical and scene monitoring can still meet the objectives required

for baseline models that require an extinction estimate and for surface haze characterization. 
Table 2-3

IMPROVE Visibility Monitoring Protocols

Instrument-Specific Monitoring Considerations

Monitoring

Component1

Instrument Monitoring Method/

Measured Parameter

Sampling 

Frequency

(Reporting Interval)

System

Accuracy

Instrument

Uncertainty

(Precision)

Aerosol IMPROVE Aerosol Filter

Sampler:

Module Filter

 A: PM2.5, 25mm Teflon

 B: PM2.5, 25mm Nylon

 C: PM2.5, 25mm Quartz

 D: PM10, 25mm Teflon

Point measurement of aerosol mass

and aerosol species as noted below:

PM2.5 mass, elements (H, Na-Pb),

coefficient of absorption

PM2.5 nitrate, sulfate, and chloride

ions

PM2.5 organic and elemental carbon

PM10 mass

Integrated (24-hour samples)

IMPROVE protocols state

samples are taken every third

day.

Special studies or short-term

monitoring may require

alternate sampling

schedule(s)

! Filter mass accuracy as

measured by

electromicrobalance that is

calibrated to traceable weight

standards

! Sampler flow accuracy

calibrated to traceable flow

standards

! Collocated samplers required to determine

system precision. Normally one set of

collocated samplers per study (region)

! Measured in terms of a minimum

detectable limit (MDL) for the species

! Uncertainty in a measured concentration is

the square root of the sum of the squares of

the uncertainties of measured mass (M),

volume of air sampled (V), and artificial

mass (A)

! Elemental dependant precisions are

provided in Section 3.0, Aerosol

Monitoring

Optical Transmissometer Path measurement

Calculated measure of extinction

(bext)

Continuous

(hourly-average)

! No absolute calibration standard

! Accuracy inferred from

comparison to measured bscat +

babs and to reconstructed bext

from aerosol measurements

Path dependent: ±0.003 km-1

10 km working path and 0.010 nominal

extinction value or ±3% transmission

Nephelometer Point measurement

Calculated measure of scattering

(bscat)

Continuous

(hourly average)

! Calculated from regular (usually

weekly) zero/span calibrations.

Generally ±10% of true value

for air near Rayleigh and using

two minutes of integration

(longer integrations will

increase the accuracy i.e., 10

minutes of integration will

increase accuracy to ±4.5%)

Collocated samplers required to determine

precision tests indicate precision

approximately ±5%

Scene 35 mm Camera Qualitative representation of a

scene, haze characterization

3 times per day N/A N/A

Time-Lapse Video Camera

(Super 8 mm camera)

Qualitative representation of a

scene, haze characterization, and

documentation of air flow and

visibility/meteorological related

dynamics in relation to the scene

Continuous during daylight

hours

N/A N/A

Meteorology Air Temperature and

Relative Humidity

Point measurement (aspirated

AT/RH sensor)

Continuous

(hourly average)

Temperature ±0.3EC

Relative Humidity ±1.5% RH from

(0 to 100%)

Precision determined by collocated samplers

Repeatability: Temperature ±0.1EC

 RelativeHumidity ±0.3% RH

 1. Goals and objectives addressed by each monitoring type are provided in Table 2-1
2-27

Sites without optical monitoring but with aerosol and scene monitoring can be used to determine

long-term trends of man-made impairment and surface haze attribution, given a periodic re-evaluation

of bext to aerosol relationships. Scene monitoring by itself can lead to the identification and

characterization of elevated layers. (Pitchford, IMPROVE Committee "Discussion of Issues for

Monitoring of Visibility-Protected Class I Areas," September 1993.)

The deployment of instrumentation and initiation of operational monitoring often depends on

the availability of funds. The financial resources (total budget) and financial tradeoffs (e.g., more sites

or fewer sites with more instruments) are real considerations. Site logistics may also restrict the

operation of certain instruments at some sites.

Additional monitoring techniques exist and more will be developed that are applicable to

visibility monitoring. Listed below are several currently available techniques that are sometimes used

to collect visibility-related data for regulatory and planning purposes.

! NO2 analyzer - bag (light absorption by NO2 gas)

! Aethalometer - continuous particle absorption

! Enhanced filter analysis techniques

- enhanced resolution on organic measurements

- enhanced tracer techniques and relationships

! Multi-wavelength optical instruments (transmissometer and nephelometer)

These techniques may be appropriate for research monitoring, may have value at specific sites, and

may be recommended in the future.

The following subsections describe each visibility monitoring method and the current

instrumentation that are considered by the EPA and IMPROVE Committee to be best suited for use.

References made to specific instruments or manufacturers are not intended to constitute endorsement

or recommendations for use. New or improved instruments and monitoring methods may become

available at any time.

2.4.1 Aerosol Monitoring

Aerosol monitoring data are used to determine the gravimetric mass and chemical composition

of size differentiated particles. Practical considerations (i.e., budget and logistics) often limit

filter-based data collection to a selected number of 24-hour samples per week. The IMPROVE

Program has historically collected two 24-hour samples per week (Wednesday and Saturday).

Starting in December 1999, the sampling protocol changes to once every third day for increased

sample collection and consistency with the PM2.5 program. IMPROVE protocols for aerosol

monitoring employ four (4) independent sampling modules at each site. As described below, three

of the four samplers collect fine particles with aerodynamic diameters #2.5 Fm: 

! A Teflon filter is used to measure fine mass, sulfur, soil elements, organic mass,

absorption, and trace elements (H and those elements with atomic weights from Na to

Pb).

! A nylon filter is used to measure nitrate, sulfate, and chloride ions.
2-28

! A quartz filter is used to measure organic and elemental carbon.

Fine particles with diameters less than 2.5 microns are especially efficient at scattering light. 

The fourth sampler collects PM10 particles with aerodynamic diameters up to 10 Fm, using

a Teflon filter. Particles >2.5 Fm are less efficient light scatterers than PM2.5 particles. By subtracting

collocated PM2.5 from PM10 mass concentrations, an estimate of coarse particles (2.5 Fm <10 Fm)

can be made.

Analysis of IMPROVE filters for mass concentrations of separate aerosol species is a key to

aerosol-based reconstructed extinction (bext) techniques. The measured mass concentration of the

species that contribute to visibility degradation multiplied by their extinction efficiencies can yield an

estimate of the extinction coefficient. The relationship of relative humidity and hygroscopic aerosols

is also an important component in this analysis; therefore, it is strongly recommended that

temperature and relative humidity sensors be collocated with aerosol monitors when the data are used

to assess current, short-term visibility conditions.

Using the IMPROVE monitoring protocols as the example, a complete description of aerosol

monitoring criteria, instrumentation, installation and site documentation, system performance and

maintenance, sample handling and data collection, filter analysis and data reduction, validation,

reporting, and archive, supplemental analysis including composite variables, quality assurance, and

analysis and interpretation are provided in Section 3.0 of this Visibility Monitoring Guidance

Document.

2.4.2 Optical Monitoring

Optical monitoring provides a quantitative measure of ambient light extinction (light

attenuation per unit distance) or its components to represent visibility conditions. IMPROVE

protocols provide continuous measures of bext and/or bscat using ambient long-path transmissometers

and/or nephelometers respectively. Water vapor in the air can affect the growth of hygroscopic

aerosols and thus affect visibility; therefore, it is strongly recommended that temperature and relative

humidity sensors be collocated with the chosen optical instrument.

Transmissometers measure the amount of light transmitted through the atmosphere over a

known distance (generally between 0.5 km and 10.0 km) between a light source of known intensity

(transmitter) and a light measurement device (receiver). The transmission measurements are

electronically converted to hourly averaged light extinction (bext). If practical constraints make it

impossible to operate a transmissometer at a particular area, ambient scattering (bscat) can be measured

with an ambient-temperature nephelometer. Ambient nephelometers draw air into a chamber and

measure the scattering component of light extinction. On days when aerosol samples are taken, the

determined scattering coefficient can be combined with the absorption coefficient, estimated from

aerosol monitoring filters, to estimate the average total light extinction (bext) for the period.

Using the IMPROVE Program as the example, a complete description of optical monitoring

criteria, instrumentation, installation and site documentation, routine operations, data collection, data

reduction and reporting, quality assurance, and analysis and interpretation are provided in Section 4.0

of this Visibility Monitoring Guidance Document.
2-29

2.4.3 Scene Monitoring

Scene monitoring documents the visual condition observed at a monitoring site.

IMPROVE protocols recommend that color photographs (i.e., 35 mm slides or digital images)

be taken several times a day. The data collection schedule can be tailored to capture the periods

when visibility impairment is most likely at specific sites. For example, photographs during stable

periods may yield more information in areas susceptible to ground-based or elevated layered hazes.

Time-lapse movies (generally time-lapse video or super 8 mm film) have also been used at selected

monitoring sites and during special studies to document the visual dynamics of a scene or source.

To the extent possible, the selected scene should be collocated with or include the aerosol and optical

monitoring equipment, so that conditions documented by photography can aid in the presentation of

these data.

Using the IMPROVE Program as an example, a complete description of scene monitoring

criteria, instrumentation, installation and site documentation, system performance and maintenance,

data collection, reduction, validation, and reporting, and quality assurance procedures are provided

in Section 5.0 of this Visibility Monitoring Guidance Document. 

2.4.4 Standard Units

As indicated in the previous sections, visibility monitoring is not well defined by one single

method. In turn, many of the indices for characterizing visibility are not directly measurable, but must

be calculated from measurements using various assumptions (Section 2.1). Visibility related indexes

can also be separated into three groups: aerosol, optical, and scene. Table 2-4 includes some of the

most useful indexes for each group. Monitoring methods can similarly be subdivided based upon

these measured indexes (Section 2.6.1.4). 

Table 2-4 provides the recommended standard reporting units. Tracking, reporting, archive,

and database formats should be consistent to promote comparable visibility data nationwide.

One source of confusion concerning visibility related measurements and standard units has

been the common practice of converting measurement data to a different index. Such conversions

usually require models with assumptions that are not always met. (Known conversions are noted in

Sections 2.1, 3.0, 4.0, and 5.0). Direct measurement of the indexes of interest avoids these concerns

and is recommended.
2-30

Table 2-4

Recognized

Visibility-Related Indexes

and Standard Units1

Index Example Standard

Unit

Secondary Unit/Comments

Mass concentration of particles for

size ranges based on aerodynamic

diameters

Total suspended particulate

matter, particulate matter

less than 10 Fm,

particulate matter less than

2.5 Fm

Fg/m3ng/m3

Particle composition Elemental and ion

concentrations

Fg/m3ng/m3

Physical characteristics Shape, structure, and index

of refraction

Extinction coefficient (bext) Total loss of light due to

absorption and scattering

Mm-1

Scattering coefficient (bscat) The portion of light loss

due to scattering by

particles and gases

Mm-1

Absorption coefficient (babs) The portion of light loss

due absorption by particles

and gases

Mm-1

Scattering phase function Angular distribution of

scattered light

Rayleigh scattering coefficient (bRay) The portion of light loss

due to natural atmospheric

molecules

Mm-1 Varies with atmospheric

pressure, altitude. Standard

Rayleigh scattering at 5,000 feet

is 10 Mm-1

Visual range (VR) Furthest distance that a

suitable object can be seen

km Standard Visual Range

(SVR km), standardized to a

Rayleigh atmosphere at

5,000 feet

Deciview An index representing the

loss of light (bext) with a

constant fractional change

in relation to visual range

dv One dv is approximately a 10%

change in extinction

Contrast Contrast between two

points, most often the

horizon and sky

Unitless

ratio

Apparent radiance of scenic elements Photograph or video

Color Chromaticity or color

contrast

Detail Scene modulation

 

1

 Adapted from Table 24-4 of the NAPAP Report.
2-31

2.5 DATA ARCHIVE AND DATA APPLICATIONS

2.5.1 National Visibility Archive

The need for a national archive of collected visibility data continues to increase. Numerous

monitoring programs, special studies, and research efforts have been conducted since the Clean Air

Act was enacted. In order to adequately protect all Class I areas and address other resource issues,

FLMs, states, tribes, and other monitoring entities must share information and evaluate the

representativeness of available visibility data. A centrally located database will be coordinated by the

EPA for all historical and future aerosol, optical, and scene visibility monitoring information and

visibility data. Uniform tracking, reporting, and archive formats will be established to assure that

data collected today can be used in future applications and future new source review models. Data

exchange will be available in standard ASCII format by FTP or Internet access. Standard file formats

currently used for IMPROVE protocol data are presented in Figures 2.4, 2.5, and 2.6. All data will

be archived in the standard units noted in Table 2-4. These file formats will be used as the standard

for the future National Visibility Archive.

2.5.2 Data Uses

Visibility data are collected and used by air resource managers, scientists, and private

organizations to address the visibility goals set forth in Section 169A and Section 169B (See Section

2.2 herein). Environmental policy and actions, as well as organizational goals and objectives, are

often a result of or a catalyst to visibility monitoring programs. 

Primary considerations when evaluating the representativeness or adequacy of collected data

for meeting defined monitoring objectives include: 1) the monitoring location, 2) the type of data,

3) the quality of the data, and 4) the time period of the data. Visibility monitoring information must

be generated in a manner consistent with promulgated regulations and this EPA Visibility Monitoring

Guidance Document to be acceptable as a primary source of visibility data for mandatory Class I

areas, or any area of concern. For example, human observer-based visibility such as airport or fire

lookout observations should not be used as a surrogate for measured extinction values (see Section

2.1.1).

Visibility monitoring data are used to address existing and potential data requirements set

forth in each of the following applications:

! Visibility Protection Program - Data are used to identify existing conditions and determine

long-term trends. Program data are also used to assess progress towards existing national

goals.

! PSD Program Requirements - Visibility data that describes existing conditions can be used

as input for new source review (NSR) models and to assess a proposed source's potential

impact on a particular PSD area. (Ref. EPA CFR 40, Parts 51 & 52) (Ref. EPA-450/4-

87-007) 
2-32

ACAD1 03/20/93 0000 0.00 0.0 BSO4 2070.50 79.00 47.10 NM

ACAD1 03/20/93 0000 0.00 0.0 CL- 65.10 163.40 326.20 NM

ACAD1 03/20/93 0000 0.00 0.0 NO2- -24.00 0.90 0.30 NM

ACAD1 03/20/93 0000 0.00 0.0 NO3- 2444.50 104.70 22.40 NM

Records of the data files are written in the following format:

 Field Description

1 Site Code

2 Sample Date

3 Start Time

4 Duration

5 Flow Rate

6 Species

7 Amount

8 Error

9 Minimum Detectable Limit

10 Species Status

If the Amount, Error, and Minimum Detectable Limit are all zero there is not valid measurement for that species.

All species amounts, errors, and minimum detectable limits are in values nanograms per cubic meter except for 'BABS.' 'BABS' values are in

10**(-8) inverse meters.

Start times are in military hours.

Sample durations are in decimal hours.

Flow rate is in liters per minute (ambient).

SPECIES STATUS CODES:

NM = Normal

QU = Questionable; Undetermined

QD = Questionable Data

AA = Organic Artifact Corrected

AP = Possible Organic Artifact (No correction performed)

' ' = No Analysis Available for this Species

NOTE: From 9/90 through 2/92 we received some Teflon filters with an organic contamination. This artifact influenced only the Hydrogen and

Fine Mass measurements in less than 7% of the samples (marked AA). All other measurements of Hydrogen and Fine Mass during this period are

marked with a status AP.

SPECIES CODES:

MF = Fine Mass (UCD)

MT = PM-10 Mass (UCD)

BABS = Optical Absorption (UCD)

H = Hydrogen (UCD)

BSO4 = Sulfate on Nylon (RTI, GGC)

NO2- = Nitrite (RTI, GGC)

NO3- = Nitrate (RTI, GGC)

CL- = Chloride (RTI, GGC)

SO2 = Sulfur Dioxide (DRI)

O1 = Organic carbon, #120 EC (DRI)

O2 = Organic carbon, 120 EC - 250 EC (DRI)

O3 = Organic carbon, 250 EC - 450 EC (DRI)

O4 = Organic carbon, 450 EC - 550 EC (DRI)

OP = Pyrolized organic, 550 EC, 2% O2, reflectance # initial (DRI)

E1 = Elemental carbon + pyrolized organic, 550 EC, 2% O2 (DRI)

E2 = Elemental carbon, 550 EC - 700 EC, 2% O2 (DRI)

E3 = Elemental carbon, 700 EC - 800 EC, 2% O2 (DRI)

All other species are elemental values from UCD Elemental Analysis.

Figure 2-4. Standard ASCII File Format IMPROVE Protocol Aerosol Visibility Data.
2-33

Field Number

 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19

 

GRCA 900702 183 700 12 1 4 0 18 10 300 0 17 1 0 38 3 0 134

GRCA 900702 183 800 -99 -99 0 4 18 10 300 4H -99 -99 0 -99 -99 0 -99

Field Description

1 Site abbreviation

2 Date in year/month/day format

3 Julian Date

4 Time using a 24-hour clock in hour/minute format

5 bext (Mm-1)

6 bext uncertainty (Mm-1)

7 Number of readings in average

8 Number of readings not in average due to weather

9 Uncertainty threshold (Mm-1)

10 ) threshold (Mm-1)

11 Maximum threshold (Mm-1)

12 bext validity code 1

13 Temperature (EC)

14 Temperature uncertainty (EC)

15 Temperature validity code 2

16 Relative humidity (%)

17 Relative humidity uncertainty (%)

18 Relative humidity validity code 2

19 Haziness (dv x 10)

1

 bext validity codes:

0 = Valid

1 = Invalid: Site operator error

2 = Invalid: System malfunction or removed

3 = Valid: Data reduced from alternate logger

4x = Weather: a letter code representing specific conditions as noted below:

Condition Letter Code

A B C D E F G H I J K L M N O 

RH > 90% x x x x x x x x

bext > maximum threshold x x x x x x x x

bext uncertainty > threshold x x x x x x x x

) bext > delta threshold x x x x x x x x

Z Weather observation between 2 other

weather observations.

Threshold values may be different for each site. See Appendix A.

8 = Missing:Data acquisition error

9 = Invalid: bext below Rayleigh

A = Invalid: Mis-alignment

L = Invalid: Defective Lamp

S = Invalid: Suspect Data

W = Invalid: Unclean optics

2

 Meteorology validity codes:

0 = Valid

1 = Invalid: Site operator error

2 = Invalid: System malfunction or removed

3 = Valid: Data reduced from alternate logger

5 = Invalid: Data > maximum or < minimum

8 = Missing:Data acquisition error

A -99 in any data field indicates missing or invalid data.

Figure 2-5. Standard ASCII File Format IMPROVE Protocol Transmissometer Visibility Data.
NGN_PULL V1.91:2/15/94 02-15-1994 14:12:39------------------------------------------------------------------------------------------------------------------------------------------------------------

LEVEL-0: NGN_SEAS 1.3 3/2/94 03-02-1994 15:01:19----------------------------------------------------------------------------------------------------------------------------------------------------------

LEVEL-1: NGN_SEAS 1.3 3/2/94 03-02-1994 17:43:10----------------------------------------------------------------------------------------------------------------------------------------------------------

---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------

---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------

---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------

---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------

---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------

---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------

---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------

SITE YYMMDD JD HHMM INS BSCAT PREC VA RAW-M RAW-SD # N/A SD/M DEL MAX RH 0123456789MPM0T YINTER SLOPE AT AT-SD # AT-PR CT CT-SD # CT-PR RH RH-SD # RH-PR N/A

LOPE 931130 334 1900 014 57 0.000 XL 122.68 25.49 12 -99.0 10.0 0.10 5.00 -99 0C0000000000000 -0.0450 0.00083 -0.97 0.20 12 1.00 0.22 0.20 12 1.00 88.01 1.18 12 2.00XXXX

LOPE 931130 334 2000 014 80 0.000 V 151.25 8.71 12 -99.0 10.0 0.10 5.00 -99 0C0000000000000 -0.0457 0.00083 -1.47 0.11 12 1.00 -0.25 0.10 12 1.00 90.46 0.88 12 2.00XXXX

LOPE 931130 334 2100 014 87 0.000 V 160.71 8.58 12 -99.0 10.0 0.10 5.00 -99 0C0000000000000 -0.0465 0.00083 -1.78 0.28 12 1.00 -0.44 0.19 12 1.00 90.71 0.96 12 2.00XXXX

LOPE 931130 334 2200 014 72 0.000 XD 143.10 22.18 12 -99.0 10.0 0.10 5.00 -99 0C0000000000000 -0.0472 0.00083 -2.65 0.21 12 1.00 -1.16 0.19 12 1.00 92.16 0.32 12 2.00XXXX

LOPE 931130 334 2300 014 70 0.000 XD 142.32 21.74 12 -99.0 10.0 0.10 5.00 -99 0C0000000000000 -0.0479 0.00083 -3.17 0.15 12 1.00 -1.65 0.11 12 1.00 91.63 0.51 12 2.00XXXX

Column Number

 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

123456789012345678901234567890123456789012345678901234567890123456789012345678901234567890123456789012345678901234567890123456789012345678901234567890123456789012345678901234567890123456789012345678901

Column Data

1-4 Site Abbreviation

6-7 Year

8-9 Month

10-11 Day

13-15 Julian Day V = Valid

17-18 Hour I = Invalid

19-20 Minute < = bscat less than Rayleigh scattering

22-24 Nephelometer Serial Number XZ = Data point immediately preceded and followed by interference

26-32 bscat (Mm-1) X? = Interference of type ?

34-40 bscat Estimated Precision (%/100)

42-43 bscat Validity/Interference Code Type (?) of Interference Letter Code

45-51 Raw Nephelometer Hourly Average (Counts) A B C D E F G H I J K L M N O

53-59 Standard Deviation of Raw Nephelometer Average (Counts) RH > max. threshold x x x x x x x x

61-62 Number of Data Points in Hourly Nephelometer Average bscat > max. threshold x x x x x x x x

64-68 (Not Used) St. Dev./Mean>threshold x x x x x x x x

70-74 Standard Deviation/Mean Interference Threshold bscat rate of change > threshold x x x x x x x x

76-81 bscat Rate of Change Interference Threshold

83-88 Maximum bscat Interference Threshold

90-92 Relative Humidity Interference Threshold

94-108 Composite Nephelometer Code Summary 94-103 Nephelometer diagnostic code (internal use)

110-116 Y-intercept of Calibration Line Used to Calculate bscat 104 Number of missing data points

118-124 Slope of Calibration Line Used to Calculate bscat 105 Number of power failure codes

126-131 Average Ambient Temperature (EC) 106 Number of manual QA invalidation codes

133-138 Standard Deviation of Hourly AT Average 107 Number of Level-0 invalidated data points

140-141 Number of Data Points in Hourly AT Average 108 Number of times non-serial data were used

143-148 Estimated Precision of Ambient Temperature

150-155 Average Nephelometer Chamber Temperature (EC)

157-162 Standard Deviation of Hourly CT Average

164-165 Number of Data Points in Hourly CT Average

167-172 Estimated Precision of Chamber Temperature

174-179 Average Relative Humidity (%)

181-186 Standard Deviation of Hourly RH Average

188-189 Number of Data Points in Hourly RH Average

191-196 Estimated Precision of Relative Humidity

197-200 (Not Used)

Note: The first 10 lines are for data reduction information.

Figure 2-6. Standard ASCII File Format IMPROVE Protocol Integrating Nephelometer Visibility Data.
2-35

! State Implementation Plans (SIPs), Federal Implementation Plans (FIPs), and Tribal

Implementation Plans (TIPs) - Visibility data can be used to quantify existing conditions,

support trend analysis, and support impairment designation policies in SIPs, FIPs, and

TIPs. Monitoring programs in turn, enable the enforcement of emission limitations and

other air quality related control measures.

! Federal Documents, (e.g. regional assessments, management plans, Environmental Impact

Statements, etc.) - Visibility data that describe existing conditions are often referenced

in federal documents to denote resource conditions (i.e., AQRVs) prior to land

management changes. Data presentations can also be used in political forums to aid in

the understanding of existing conditions and need for future air quality related policy

and/or regulations. 

! Acid Rain Program - The links between acid rain and visibility degradation, although

indirect are quite strong. Of particular importance is the relationship of visibility to the

air pollutants associated with acid deposition - i.e., the relationship of visibility to nitrogen

dioxide, nitrate aerosols, and (especially) sulfate aerosols.

! Fire Emissions Inventories - Natural and prescribed fire emissions often impact visibility

in Class I and other protected natural areas. With the development of increased fire

programs, existing and future visibility data can be used to evaluate the visibility impacts

of fire emissions.

! Fine Particulate Standards - Existing visibility-related PM2.5 and PM10 data may be used

to supplement Federal Reference Method measurements (e.g. to estimate regional

background concentrations) in association with new fine particulate standards.

! Other Uses for Non-Class I Area Management - Document the frequency, dynamics,

intensity, and causes of urban hazes, establish visual air quality acceptance criteria and

evaluate daily air quality indexes.

2.6 NETWORK DESIGN

To address the visibility protection provisions of the CAA and EPA regulations, states and

appropriate federal agencies must have access to high quality visibility data representative of the Class

I or other areas of concern. Ideally, long-term routine monitoring would be conducted in every area

of concern and every site would have a full aerosol, optical, and scene configuration. In some of the

larger Class I areas or areas with dramatic differences in elevation, monitoring should be conducted

at more than one location. State, urban, and tribal monitoring is often designed in association with

existing ambient (i.e., SLAMS, NAMS) air quality monitoring programs. Funding and logistic

realities, however, often limit the number of visibility monitoring sites and the configuration of the

sites used to define a network. 

Visibility monitoring objectives must be clearly defined prior to the design and implementation

of any visibility monitoring network or individual site. Background information from historical and

existing aerometric monitoring programs, climatological summaries, and local geographical resources

need to be obtained. Visibility protection goals, monitoring objectives, EPA regulations, background

information, data quality objectives, spatial, temporal, logistic, and economic considerations must be

evaluated by all supporting proponents. A thorough review will ensure the design of an effective
2-36

monitoring program that meets common objectives, and that data collected can be interpreted and

applied, in accordance with the law, for regulatory and planning purposes.

Visibility monitoring information generated in a manner consistent with this EPA Visibility

Monitoring Guidance Document will be acceptable as a primary source of visibility data for

mandatory Class I areas, or any area of concern. IMPROVE Program monitoring sites that measure

aerosol, optical, and scene components and those following IMPROVE protocol configurations are

consistent with the methods described in this guideline. Data from individual IMPROVE sites can

be used to represent the visual air quality of nearby Class I areas if the nearby areas are generally

affected by the same air mass (Section 2.6.1.1). Collecting a single aerosol or optical parameter at

these nearby sites can provide a quantitative link to the IMPROVE data from a fully configured site.

Documenting the scenic qualities at these nearby sites can provide an additional qualitative link to the

quantitative IMPROVE data.

Design of a special visibility study network is often more locally oriented and more intensive

than routine network designs. Special studies include site-specific pre- and post-operation monitoring

related to a proposed PSD source, pollution attribution analyses to define the causes of existing

impairment, or other research programs. Pre- and post-operation monitoring for a PSD source can

often be coordinated with and even funded by the proposed source. Visibility monitoring using

routine monitoring techniques in conjunction with standard ambient PSD measurements can define

and help to mitigate the specific impacts of a PSD source. As provided for under the 1980 EPA

visibility regulations, an attribution analysis may be required for a Class I area where one or more

pollution emission sources are thought to contribute substantially to visibility impairment. Often,

routine data will not be sufficient for attribution analysis. In such circumstances, special studies may

be required to supplement the routine monitoring information. Monitoring and other sources of

information (e.g., emissions characterization, model outputs, etc.) must allow the identification of

substantial visibility impairment source(s) and the assessment of the frequency, duration, and intensity

of impairment from the identified sources(s). Other research programs could include studies of

aerosol conversion, aerosol growth, optical parameters, scenic parameters, instrument trials, and

other research topics. These studies are usually designed to address scientific theses and include

traditional and research instrumentation and analytical techniques.

2.6.1 Assessment Criteria

Based on established overall program monitoring objectives a series of spatial, temporal,

logistical, legal, and economic issues must be assessed prior to the implementation of a visibility

monitoring site or network. Table 2-5 identifies a series of criteria that are considered in the network

design phase of visibility monitoring. Each set of criteria parameters are independent, however they

should be evaluated in association with other selected criteria. The following subsections further

define these considerations and summarize the benefits and tradeoffs of each.
Table 2-5

Assessment Criteria

Related to Designing a Visibility Monitoring Program

Criteria to Consider

Identify:

Purpose of

Data Collection

Define:

the Spatial Extent of

the Program

Define:

the Temporal Extent

of the Program

Determine:

How Data from

Existing Monitoring

Programs Could be

Integrated

Determine:

Parameters to be

Monitored

Develop:

Cost Guideline and

Budgeting Limits

Identify:

Possible Data Applications

Assessment Consideration(s)

What is the network

or site-specific

objective(s)?

What is the

physical extent of

land that needs to be

monitored to meet

the objective?

How often and how

long must monitoring

continue to obtain an

accurate assessment of

visibility conditions

for the objective?

Does any additional

monitoring need to

occur?

What data/information

will be necessary to

form conclusions or

support hypothesis (objectives)?

What are the economical

and logistical tradeoffs

that will need to be

considered prior to

implementation?

Are there

associated

programs or

research efforts

that could benefit

from the data

collected

Assessment Criteria

1. Reasonably

attributed impairment

2. Existing

conditions,

document for

future protection.

Trend analysis

3. New source

review, pre- and 

post- construction

monitoring

4. Regional haze 

assessment

5. Research

1. Local

2. Regional

3. National

4. International

5. Site-specific 

objectives

6. Network-specific

objectives

1. Long-term -

decades of routine

monitoring

2. Short-term -

several years of

specialized

monitoring

3. Special study

- simple

- complex

1. Representativeness

2. Historical review of

ambient AQ trends

3. Cooperative 

monitoring efforts

4. Meteorological 

records

5. Other programs - 

PM10, NAMS, 

SLAMS, other 

studies

1. Aerosol point 

measure

 - PM2.5, PM10

2. Optical -bext path

measurement - bext

point measurement

3. Scene

- 35 mm still

- time-lapse film or

 video

1. Capital costs

2. Operational costs

3. Access, personnel,

logistics

1. PSD

2. New Source 

Review (NSR)

3. Attributable

impairment

4. Regional

Assessments

(AQRVs)

5. Acid Rain,

Fire Emission

Inventories

Other Considerations

Consider scenic

sensitivity

Consider anticipated

visibility changes
2-38

2.6.1.1 Spatial Considerations 

Spatial considerations consist of a set of general criteria that identify candidate monitoring

locations in terms of the physical characteristics which most closely match a specific monitoring

objective or set of objectives. The goal is to correctly match the spatial scale represented by the

visibility monitoring data collected with the spatial scale most appropriate for the given monitoring

objective(s). The spatial scale of representativeness is described in terms of the physical dimensions

of the regional or local air mass in which pollutant concentrations and visibility are expected to be

reasonably similar.

The scales of representativeness of most interest for visibility monitoring are:

Definition Example Monitoring Objectives

Local/Urban

This scale defines conditions within an area

that has relatively uniform land use and

common geographical and climate features.

The dimensions of a local or urban area can

range from 4 to 50 kilometers square.

Broader ranges will usually require more

than one site for definition.

Existing conditions, source attribution, daily

index

Regional

This usually defines a rural area of

reasonably homogeneous geography and air

quality and extends from tens to hundreds of

kilometers square. Care must be taken to

ensure that both vertical and horizontal air

quality characteristics are considered at this

scale.

Existing conditions, long-term trends

National and Global

These measurement scales represent

concentrations characterizing the nation

and/or global conditions as a whole.

National data for policy analyses/trends

and for reporting to the public

Unlike site-specific objectives, which can be met at isolated individual locations without

reference to measurements made elsewhere, network-specific objectives often require simultaneous

monitoring at several sites. In other words, these objectives require comparison among different

sites. Class I and non-Class I local and regional representative considerations are described below.

Temporal resolution, data sources, and data comparability issues associated with meeting networkspecific data objectives are described in the following subsections.

Local Representative Considerations

To demonstrate that data collected at one location are representative of one or more nearby

Class I area(s) requires an analysis of existing conditions that includes consideration of common

meteorology, a similar degree and frequency of exposure to visibility influencing pollution sources,

and similar terrain. Representative Class I areas should share the same air basin or geographic
2-39

province (e.g., not be on opposite sides of a major mountain range). They should be closer to each

other than the average distance to any major stationary point source of visibility reducing emissions.

They should roughly share the same average elevation (e.g., mountain tops are not representative of

valley floors). Representative analyses should be shared with and approved by state agencies, the

EPA, and cooperating federal land managers.

To evaluate the adequacy of individual network monitoring sites, it is necessary to examine

individual site objectives and determine each site's spatial scale of representativeness. This will do

more than ensure compatibility of stations with the same purpose. It will also provide a physical basis

for the interpretation and application of the data.

Several criteria should be considered when selecting a monitoring site among several Class

I areas that are likely to be mutually representative: 

! If a proposed emission source or any other development is anticipated that could change

the visibility impacts in the candidate areas, then the area with the greatest estimated

change in visibility should be chosen. 

! Similarly, higher priority should be given to areas with more visually sensitive vistas (e.g.,

longer views). 

! If existing impairment from man-made sources is known to impact one of the areas more

often or with greater intensity than the others, then the area of greater impact should be

chosen for a monitoring location. 

If none of the above criteria are applicable, then the most desirable location would be the one

that best represents the group of Class I areas. This could be the one nearest the center of a group

of visibility protected areas.

Practical considerations such as the availability of power, security, year-round access, and onsite personnel should also be considered when selecting the location of a monitoring site. Such

considerations, however, should be treated as secondary unless it can be demonstrated that practical

constraints would substantially jeopardize the data quality or data recovery. Ideally, a pilot study

could be conducted that would include some level of monitoring, for at least a short period of time,

at all of the Class I areas within a "representative area." A pilot study could provide specific data to

evaluate representative monitoring decisions. Pilot studies are encouraged; however, budget, time,

and logistic considerations often restrict their application.

Representative considerations for non-Class I areas of scenic importance generally parallel

those of Class I areas. Representative areas should share common meteorology, geographic features,

and exposure to visibility influencing pollution sources. Monitoring objectives and monitoring data

collected must be compatible to provide a common basis for the interpretation and application of the

data.

Regional Representative Conditions

Regional areas can cover a broad geographic area. Generally, a number of sites will be

required to effectively characterize a regional area. The Colorado Plateau would be an example of

a regional area that includes the "Golden Circle" of national parks. The climate patterns throughout

the region are similar and, therefore, the air mass influences throughout the region are similar.
2-40

Monitoring visibility in only one Class I area in the region may provide a qualitative understanding

of the existing conditions, dynamics, and trends that could generally affect the region, but the

quantitative data collected at one site may not be representative of another site in the region. For

example, one site in the region may record a significant visibility event at noon and a site further

downwind may record the same event but with less magnitude later in the day. The same air mass

influenced both regional sites, the visibility reducing species were the same, but the magnitude and

timing of the event were different. One site was not purely representative of the next, but data from

both can lead to a better understanding of how an air mass from the same source area influences a

geographic region.

The methods used to define regions can vary, but generally each method used differentiates

one region from another in a similar fashion. The parameters used to characterize and define regions

include:

! Weather and climate

! Elevation

! Terrain

! Vegetation and dominant ecosystem types

! Dominant land use

! Geology

! Air pollution source types

! Air pollution chemistry

As an example, the IMPROVE Program has defined twenty-one regions by which to

summarize spatial distribution data in their historical summary reports (Sisler, et al., 1996). A list of

these regions is provided as Table 2-6. Sites should be located to document the range of conditions

that occur in the region. All data collected in the region should be analyzed and compared to identify

regional patterns and trends. These patterns and trends can then be compared to other regions.
2-41

Table 2-6

IMPROVE and IMPROVE Protocol Sites According to Region (Sisler, et al., 1996)

Alaska (AKA)

! Denali NP (DENA)

Appalachian Mountains (APP)

! Great Smoky Mountains NP (GRSM)

! Shenandoah NP (SHEN)

! Dolly Sods WA (DOSO)

Boundary Waters (BWA)

! Boundary Waters Canoe Area (BOWA)

Cascade Mountains (CAS)

! Mount Rainier NP (MORA)

Central Rocky Mountains (CRK)

! Bridger WA (BRID)

! Great Sand Dunes NM (GRSA)

! Rocky Mountain NP (ROMO)

! Weminuche WA (WEMI)

! Yellowstone NP (YELL)

Coastal Mountains (CST)

! Pinnacles NM (PINN)

! Point Reyes NS (PORE)

! Redwood NP (REDW)

Colorado Plateau (CPL)

! Bandelier NM (BAND)

! Bryce Canyon NP (BRCA)

! Canyonlands NP (CANY)

! Grand Canyon NP (GRCA)

! Mesa Verde NP (MEVE)

! Petrified Forest NP (PEFO)

Florida (FLA)

! Chassahowitzka NWR (CHAS)

! Okefenokee NWR (OKEF)

Great Basin (GBA)

! Jarbidge WA (JARB)

! Great Basin NP (GRBA)

Lake Tahoe (LTA)

! D.L. Bliss State Park (BLISS)

! South Lake Tahoe (SOLA)

Mid Atlantic (MAT)

! Edmond B. Forsythe NWR (EBFO)

Mid South (MDS)

! Upper Buffalo WA (UPBU)

! Sipsey WA (SIPS)

! Mammoth Cave NP (MACA)

Northeast (NEA)

! Acadia NP (ACAD)

! Lye Brook WA (LYBR)

Northern Great Plains (NGP)

! Badlands NM (BADL)

Northern Rocky Mountains (NRK)

! Glacier NP (GLAC)

Sierra Nevada (SRA)

! Yosemite NP (YOSE)

Sierra-Humboldt (SRH)

! Crater Lake NP (CRLA)

! Lassen Volcanoes NP (LAVO)

Sonoran Desert (SON)

! Chiricahua NM (CHIR)

! Tonto NM (TONT)

Southern California (SCA)

! San Gorgonio WA (SAGO)

Washington, D.C. (WDC)

! Washington, D.C. (WASH)

West Texas (WTX)

! Big Bend NP (BIBE)

! Guadalupe Mountains NP (GUMO)

NP = National Park NWR = National Wildlife Refuge

NM = National Monument NS = National Seashore

WA = Wilderness Area
2-42

The IMPROVE network expansion from 30 to 108 sites during 1999 and 2000 is an example

of how a regional scale network with specific goals can be planned. The goal of the expansion is to

provide data needed to represent regional haze conditions for all 156 visibility-protected Class I areas

where monitoring is feasible. The IMPROVE Steering Committee devised a plan for the expansion

that involved several stages. In a scoping stage, two criteria were applied to assess the feasibility of

individual monitoring platforms to be applicable to more than one Class I area. The criteria required

that monitoring must be within 100km of the protected area and that the monitoring site elevation

be within 100 feet or 10% of the elevation range of the protected area. These criteria were first

applied to the 30 then current IMPROVE monitoring sites to identify other Class I areas that would

be covered by these criteria. Then the criteria were used to identify the locations and elevations that

would be required for the smallest number of monitoring sites that could represent the remaining

protected Class I areas. Wherever the location requirements by these criteria could be met by an

existing IMPROVE protocol site (i.e. a site using IMPROVE methods but not operated by the

Steering Committee) it was identified as a possible candidate site.

The names and location of existing and required additional monitoring sites generated in the

scoping stage of the planning were displayed on a map and in a table. These were widely circulated

for review including to the federal land manager, EPA staff, and State and local air quality agencies

to ask for comments. The Steering Committee asked for suggested changes that reflected more

detailed knowledge of additional regional siting criteria such as nearness to large sources or source

areas, local meteorology, and topography. Reviewers were also asked to comment on the feasibility

of monitoring at any of the sites. One of the Class I areas (Bering Sea, an island over 200km off the

coast of Alaska) was indicated as infeasible due to its remoteness, lack of power and an operator.

Comments received by the Steering Committee were incorporated as modifications to the tables and

maps that indicated where additional monitoring was needed. The final stage in the network design

involves visiting potential sites to determine their suitability for siting the monitoring equipment.

Again all organizations with an interest in the monitoring were invited to participate in the final site

selection visits.

 2.6.1.2 Temporal Considerations

Temporal considerations consist of a set of criteria that specify the type, frequency, and

duration of data required to accurately assess visibility conditions.

Monitoring Period Criteria/Duration

Long-term monitoring sites provide valuable information about the existing conditions and

long-term trends of visibility. Data from long-term sites can be used to track progress toward the

national visibility goals, to support permit applications, and to support a range of resource-related

research projects. It is recommended that long-term sites established and supported to evaluate

trends or track progress should continue taking data for decades. Periodic evaluation of long-term

sites is necessary to ensure their benefit (historical or future) to overall network goals and objectives.

A network monitoring plan should define the frequency of periodic reviews. In cooperation with

state agencies and the EPA, data from long-term trend sites can be adopted as regionally

representative of a series of nearby Class I areas for permit review purposes.

Short-term monitoring sites are established to address specific visibility concerns. Examples

of short-term monitoring include pre- and post-construction source-specific monitoring sites, source

attribution study sites, and/or specialized research. Short-term sites can also be established as a

precursor to long-term sites. Collected data are often evaluated in association with the nearby long-
2-43

term monitoring sites to determine the representativeness of the monitored region. Sites may also

be classified "short-term" due to abbreviated/seasonal monitoring periods. Many Class I area

monitoring sites are in remote locations and at certain sites monitoring is limited to the warm season

(e.g., June through September) due to weather, accessibility, and/or available servicing personnel.

Short-term sites will generally operate from a single season to several years.

Special studies, unlike routine monitoring, often do not lend themselves to standard design

recommendations. The design is tailored to: 

! The nature of the impairment (e.g., ground-based or elevated, short-term intermittent or

long-term frequent, etc.).

! The characteristics of the source(s) (e.g., continuous or intermittent, point or area,

primary particle or gas, or precursor gas for secondary particle, etc.).

! Existing information deficiencies.

Special studies range from simple to sophisticated. In the case of a plume or layer from a

large nearby point source of primary particles, deployment of additional cameras to document the

impairment may suffice (time-lapse photography may be particularly appropriate). To document the

contribution of a more distant source of gaseous precursors for secondary particles, a substantial

effort may be required which could include a supplemental monitoring network, instrumented aircraft,

and stack release and ambient monitoring of unique tracer materials.

To increase the likelihood of the success of a special study, it should be designed in

conjunction with those who are responsible for conducting the attribution analysis and with the

involved industry. In some circumstances, a special study may be better accomplished in several

phases, where data from the earlier phase(s) are used to help design the later phases.
2-44

Data Collection Criteria

Instrument or parameter-specific temporal resolution criteria include instrument limitations,

instrument detection limits, and data reporting methods. Continuous data collection should be

summarized hourly to be consistent with other aerometric monitoring methods. Filter-based data

generally require collection periods from several hours to 24 hours depending on the ambient

concentrations and analyses techniques. Most particulate samples in long-term programs are

generally taken for 24 hours (midnight to midnight). This approach is also consistent with filter

monitoring by SLAMS. IMPROVE protocol sites collect 24-hour filter samples twice per week. In

remote areas tested by IMPROVE, no statistical difference in seasonal averages were observed in

aerosol data collected daily versus bi-weekly. Filter data collected in urban areas may or may not

yield similar statistical results.

Similar to spatial representativeness, site objectives and temporal parameters must be shown

to be representative of nearby monitoring areas to ensure network compatibility and provide a

physical basis for the interpretation and application of the data.

Temporal considerations must be evaluated repeatedly throughout the design, implementation,

and analysis phase of visibility monitoring. Meteorological conditions, fire emissions, regional haze,

and industrial processes can vary substantially from day to day and year to year. The selected period

of data collection must be qualified as representative of average visibility conditions for the site. This

requires an assessment of historical climate and visibility conditions and comparison of historical

conditions with the conditions for the period of data collection.

2.6.1.3 Historical and Existing Monitoring Program Considerations

Program considerations involve taking a closer look at past and present visibility monitoring

programs and other monitoring data that can be used to support defined objectives and proposed data

applications. It is possible that one or more representative sites' data could satisfy the majority of

objectives defined. 

A review should be conducted of historical and existing data from all visibility,

meteorological, ambient, and PM monitoring sites within the representative boundaries of the site to

be monitored. Do the data provide a record of average aerometric conditions that represent the

spatial and temporal objectives defined above? Given the data are representative of the proposed

monitoring location, existing monitoring data can often be used to define existing meteorology and/or

visibility conditions, support trend analysis, or support regional haze assessment research.

Many economic and logistic benefits can be obtained by establishing cooperative monitoring

efforts between representative air monitoring sites and programs. Capital equipment, land use fees,

and routine monitoring site operator resources can be shared between associated FLMs and state

agencies. Data collected can also be used to support other monitoring programs, research, or future

trend analysis.

2.6.1.4 Monitoring Parameter Considerations

In the process of network design, what visibility parameters will be necessary to base

conclusions, support hypotheses (objectives), or address defined legal standards? What parameter
2-45

considerations regarding measurement accuracy and precision, temporal resolution, spatial resolution,

and comparability need to be evaluated given site-specific or network-specific objectives? A number

of these monitoring issues were addressed by Marc Pitchford for the IMPROVE Network

(September 1993). Excerpts of his recommendations to IMPROVE Committee members are

provided in the following subsections. Table 2-7 provides a tabular listing of the data sources,

associated temporal resolution and spatial representativeness, and data comparability for each

visibility monitoring parameter. Example parameter and instrument specifications based on the

IMPROVE Program are provided in Sections 3.0, 4.0, and 5.0. These monitoring methods and

instruments are currently considered by the EPA and IMPROVE Committee to be best suited for use

(field tested, known precision and accuracy, widely used). References made to manufacturers or

trade names are not intended to constitute endorsement or recommendations for use. New or

improved instruments, instrument upgrades, and methods of monitoring are being developed each

year. This guidance document will be revised over time to reflect the ongoing changes of the science

and monitoring instruments most appropriate (researched, tested, and recommended) for use.

Aerosol Parameter Considerations

The primary objective of visibility-related aerosol monitoring is to gather information required

to establish the relative contributions of various species to visibility impairment. The most popular

approach for particle monitoring uses any of a variety of samplers which size selectively separate the

particles from the gases by filtration, inertial impaction, and denuding. The size selective particle

samples are subsequently analyzed for mass and elemental composition.

This combination of particle sizing with elemental composition analyses is important for

visibility monitoring because:

! Scattering is highly dependent on particle size. Collecting particles in visibility-sensitive

size ranges allows aerosol concentrations to be better correlated to extinction.

! Elemental composition provides information about the chemical and physical properties

of aerosols and about probable sources and source types. For example, identifying a

sulfate aerosol would indicate a hygroscopic aerosol that can grow in high relative

humidities to be an efficient light scatterer and that the probable source of the aerosol is

sulfur rich fossil fuel combustion. Specific elements may also be used as source

indicators. For example, the presence of arsenic may be a good indicator of copper

smelter emissions.

! Particle sizing provides further information about sources or source types. For example,

a given element from separate sources may be differentiated by particle size.
2-46

Table 2-7

Monitoring Parameter Considerations

Parameter Spatial

Representativeness Data Sources TemporalResolution Data Comparability

Aerosol

Aerosol

components:

PM2.5 Fine Mass

Elemental Analysis

(H, Na-Pb)

Coefficient of

absorption (babs)

Nitrate, Sulfate,

and Chloride ions

Organic and

elemental carbon

PM10

Point Measurement Multiple filter*

system

Commonly

24-hour samples

at least twice per

week

Best available method for

source attribution. 

Temporal sampling

limitations minimize

analysis comparisons to at

best seasonal averages. In

the absence of optical data,

aerosol data can be used to

estimate visibility levels by

using generally accepted

models. (MIE scattering

theory or literature values

for extinction efficiencies to

determine reconstructed

extinction).

Optical

Light Extinction

(bext)

Path Measurement Transmissometry* Continuous

sampling,

commonly

summarized as

1-hour, 4-hour,

or 24-hour

averages

Most direct measure of

absorption and scattering

properties. Does not define

the source of impairment.

Light Extinction

Components:

Scattering (bscat) Point Measurement Nephelometry* Continuous

sampling,

commonly

summarized as

1-hour, 4-hour,

or 24-hour

averages

Data can be combined with

collocated absorption (babs)

measurements to estimate

total light extinction (bext). 

Does not define the source

of impairment.

Particle Absorption

(bap)

Point Measurement Filter-based

particle absorption

measurements

Continuous

sampling (e.g.,

aethalometer)

Data can be combined with

collocated scattering (bscat)

measurements to estimate

total light extinction (bext). 

Does not define the source

of impairment.

Intermittent

sampling (e.g.,

integrating plate,

integrating

sphere analysis

method)

Data can be combined with

collocated scattering (bscat)

measurements to estimate

total light extinction (bext). 

Does not define the source

of impairment.

 * Monitoring methods and instruments considered by the EPA and IMPROVE Committee to be well suited (field

tested, high precision and accuracy, widely used) for use.
2-47

Table 2-7 (Continued)

Monitoring Parameter Considerations

Parameter Spatial

Representativeness

Data Sources Temporal

Resolution

Data Comparability

Optical (Cont.)

Gas Absorption

(bag)

Point Measurement NO2 gas analyzer Continuous

sampling

commonly

summarized as

1-hour averages

NO2 is the only common

atmospheric gas that is

important to light

absorption.

Air Temperature

and Relative

Humidity

Point Measurement Aspirated AT/RH

sensor*

Continuous

sampling

commonly

summarized as

1-hour, 4-hour,

or 24-hour

averages

Used to screen weather

effects from optical data. 

Used to determine

humidity-related

hygroscopic aerosol growth

functions applicable to

reconstructed extinction

estimates.

Scene

Haze

Characterization

Qualitative

representation of a

scene

Still photography* Commonly 3

photographs or

more per day

(e.g., 0900,

1200, 1500)

Often used to document

source impacts for public

presentation or to aid in the

interpretation or

quantitative data.

Visual Dynamics Qualitative

representation of a

scene

Time-lapse or

video photography

Commonly set to

photograph in 1-

minute or less

intervals during

daylight hours

Often used to document the

visual dynamics of a scene

in relation to source

impacts and local

meteorology.

 * Monitoring methods and instruments considered by the EPA and IMPROVE Committee to be well suited (field

tested, high precision and accuracy, widely used) for use.
2-48

Aerosol samplers used in visibility monitoring programs most commonly collect aerodynamic

diameters in two size ranges; PM2.5 and PM10. Numerous sampler designs exist (Chow, 1995). As

examples, several of these samplers are included in Table 2-8 along with their general specifications.

Table 2-8 is not intended to be a comprehensive list.

Both monitoring and analytical considerations need to be evaluated when establishing an

aerosol monitoring site. The sample frequency, particle size, filter substrate, flow rate, and analytical

methods are all important considerations when measuring major aerosol components and trace

element constituents.

Aerosol monitoring for visibility should include at a minimum PM2.5 mass concentration and

elemental analyses at least twice a week. However, in order to identify and track visibility impacts

caused by various pollutant species, a more complete aerosol characterization is strongly

recommended. This more complete approach should include both PM2.5 and PM10 sampling. PM2.5

filter samples should generally be analyzed for mass, optical absorption, elements, sulfates, nitrates,

chlorides, organic carbon, and elemental carbon. PM10 filters should be analyzed for mass and

elements. With this information it is possible to use analytical techniques to estimate the extinction

coefficient from these aerosol constituents. This method of reconstructing extinction from aerosol

species is an important evaluation and quality assurance tool. Knowing the relative contribution of

visibility reducing aerosol species allows an agency to focus on the source types responsible for

impairment and to develop mitigation strategies.

Samplers such as the IMPROVE Modular Aerosol Sampler provide the flexibility to collect

all or part of the recommended samples. Each module uses an appropriate filter substrate to support

specific laboratory analyses. As an example, IMPROVE aerosol monitoring methods are further

discussed in Section 3.0 of this document. Other samplers would also be applicable as long as the

entire system including the selected sampler, sizing devices, flow rate, filter substrate, and analytical

techniques were all integrated to meet the visibility-related size selection, mass, and speciation

recommendations.

Optical Parameter Considerations

The primary objective of optical monitoring is to measure the atmospheric extinction

coefficient (bext) and/or the absorption and/or scattering components of bext independent of physical

scene characteristics or illumination conditions. Optical measurements, however, do not define the

source of impairment. 

Light Extinction

Transmissometers measure the combined effects of light absorption and scattering over a

known site path (babs + bscat = bext). The useful measurement range for a transmissometer is related

to its precision and the path length over which it is operated. Longer path lengths are required for

accurate measurements in cleaner air (e.g., 10 km paths in remote western locations of the United

States), while shorter paths are used in more polluted situations (e.g., paths of approximately one

kilometer in eastern regions). Short-path transmissometers (on the order of several hundred meters)

have been used for years at many airports. These have a useful range of measurements only up to a

few kilometers visual range. Though useful for airport safety in fog or other severe conditions, such

measurements are of little value for routine visibility monitoring. Long-path transmissometers are

required for visibility monitoring.
2-49

Table 2-8

Example Particle Samplers (Chow, 1995)

Filter-based Research Particle Sampling Systems

Sampling System

Particle

Size

(Fm)

Sizing Device Flow Rate

(L/min)

Sampling

Surfaces

Filter Holders Filter Media Features

Western Region

Air Quality Study

(WRAQS)

Sampler

PM15 Aluminum highvolume impactor113 out of

1,130

Aluminum and

copper

Nuclepore

polycarbonate

in-line

47 mm Teflonmembrane

47 mm quartz-fiber

PM2.5 Steel mediumvolume cyclone113 Aluminum and

copper

Nuclepore

polycarbonate

in-line

47 mm Teflonmembrane

47 mm quartz-fiber

Size Classifying

Isokinetic

Sequential

Aerosol (SCISAS)

Sampler

PM15 Aluminum highvolume impactor113 out of

1,130

Aluminum and

polyvinyl

chloride

Nuclepore

polycarbonate

open-face

47 mm Teflonmembrane

47 mm quartz-fiber

Sequential

sampling.

PM2.5 Steel mediumvolume cyclone113 out of

1,130

Stainless steel

and aluminum

Nuclepore

polycarbonate

open-face

47 mm Teflonmembrane

47 mm quartz-fiber

Southern

California Air

Quality Study

(SCAQS) Sampler

PM10 Aluminum

medium-volume

impactor

35 out of 113 Stainless steel

and aluminum

Gelman

stainless steel

in-line

47 mm Teflonmembrane

47 mm quartz-fiber

Option to add 20

cm length flow

homogenizer.

PM2.5 Bendix 240

cyclone

35 out of 113 Teflon-coated

aluminum

Gelman

stainless steel

in-line

47 mm Teflonmembrane

47 mm quartz-fiber

47 mm impregnated

quartz-fiber

Option to add 20

cm length flow

homogenizer.

Teflon Savillex PFA

Teflon in-line

47 mm nylonmembrane

47 mm etched polycarbonate

Sequential Filter

Sampler (SFS)

PM10 Aluminum

medium-volume

impactor

20 out of 113 Aluminum Nuclepore

polycarbonate

open-face

47 mm Teflonmembrane

47 mm quartz-fiber

Option to add nitric

acid denuders in

the sampling

stream. Sequential

sampling.

PM2.5 Aluminum

medium-volume

cyclone

20 out of 113 Teflon-coated

aluminum

Nuclepore

polycarbonate

open-face

47 mm Teflonmembrane

47 mm quartz-fiber

47 mm nylonmembrane

47 mm impregnated

cellulose-fiber

California Acid

Deposition

Monitoring

Program

(CADMP) Dry

Deposition

Sampler

PM10 Aluminum

medium-volume

impactor

20 of 113 Aluminum Savillex openface47 mm Teflonmembrane

47 mm impregnated

cellulose-fiber

Includes nitric acid

denuders.

Sequential

sampling.

PM2.5 Teflon-coated

steel mediumvolume cyclone

20 of 113 PFA Tefloncoated aluminumSavillex PFA

Teflon openface

47 mm Teflonmembrane

47 mm nylonmembrane
Table 2-8 (cont.)

Example Particle Sampling Systems (Chow, 1995)

Filter-based Research Particle Sampling Systems

Sampling System

Particle

Size

(Fm)

Sizing Device Flow Rate

(L/min)

Sampling

Surfaces

Filter Holders Filter Media Features

2-50

Versatile Ambient

Pollutant Sampler

(VAPS)

PM10,

PM2.5

Teflon-coated

aluminum lowvolume elutriator

and Tefloncoated aluminum

low-volume

virtual impactor

33 Teflon-coated

aluminum

University

Research

Glassware glass

filter pack

(Model 2000-

30F)

47 mm Teflonmembrane

47 mm etched

polycarbonate

membrane

47 mm quartz-fiber

Includes annular

denuders to capture

nitric acid, nitrous

acid, and sulfur

dioxide: and

polyurethane foam

(PUF) to collect

organic

compounds.

California

Institute of

Technology

Sampler

PM10 Aluminum lowvolume impactor16.7 Stainless steel

and aluminum

Gelman

stainless steel

in-line

47 mm Teflonmembrane

47 mm quartz-fiber

PM2.5 Aluminum lowvolume cyclone22 Teflon-coated

aluminum and

glass

Gelman

stainless steel

in-line

47 mm Teflonmembrane

47 mm quartz fiber

47 mm nylonmembrane

Interagency

Monitoring of

Protected Visual

Environments

(IMPROVE)

Sampler

PM10 Aluminum lowvolume cyclone19 Aluminum Nuclepore

polycarbonate

open-face

25 mm TeflonmembraneUses Wedding Beta

Gauge PM10 inlet.

PM2.5 Aluminum lowvolume cyclone22.7 Aluminum Nuclepore

polycarbonate

open-face

25 mm Teflonmembrane

25 mm quartz fiber

25 mm nylonmembrane

Nitric acid

denuders ahead of

nylon filter.

Stacked Filter

Unit (SFU)

PM2.5 Large-pore

etched

polycarbonate

filters

10 Polycarbonate Nuclepore

polycarbonate

open-face

25 mm TeflonmembraneUses large-pore

etched

polycarbonate filter

as PM2.5 sizing

device.

BYU Organic

Sampling System

(BOSS)

PM2.5 Teflon-coated

aluminum

medium-volume

cyclone

140 L/min

through inlet

and 35 L/min

per channel

Teflon-coated

stainless steel

University

Research

Glassware glass

filter pack

(Model 2000-

30F)

47 mm quartz-fiber

47 mm activatedcharcoal impregnated

filter (CIF)

A multichannel

diffusion denuder

sampler to

determine semivolatile organic

compounds.

BYU Organic

Sampling System

(BOSS)

PM2.5,

PM0.8,

PM0.4

Aluminum highvolume virtual

impactor

1,130 L/min

through inlet,

with 11, 60,

93, and 200

L/min per

channel

Teflon-coated

stainless steel

University

Research

Glassware glass

filter pack

(Model 2000-

30F)

47 mm quartz-fiber

47 mm activatedcharcoal impregnated

filter (CIF)

compounds

A multichannel

diffusion denuder

sampler to

determine semivolatile organic

compounds.

Harvard/EPA

Annular Denuder

System (HEADS)

PM2.5 Teflon-coated

low-volume glass

impactor

10 Glass GrasebyAndersen openface ring

37 mm Teflonmembrane

37 mm impregnated

quartz-fiber etched

polycarbonate

membrane

Includes sodium

carbonate coated

denuders to collect

acidic gases (e.g.,

nitric acid, nitrous

acid, sulfur dioxide

organic acids) and

citric acid coated

denuders to collect

ammonia.
Table 2-8 (cont.)

Example Particle Sampling Systems (Chow, 1995)

Filter-based Research Particle Sampling Systems

Sampling System

Particle

Size

(Fm)

Sizing Device Flow Rate

(L/min)

Sampling

Surfaces

Filter Holders Filter Media Features

2-51

New York

University

Medical

Center/Sequential

Acid Aerosol

Sampling System

(NYUMC/SAASS

)

PM2.5 Teflon-coated

glass low-volume

impactor

4 Teflon-coated

glass

Graseby

Andersen openface ring

37 mm Teflonmembrane

37 mm nylon

membrane

Sequential

sampling.

Minivol Portable

Survey Sampler

PM10,

PM2.5

Nylon lowvolume impactor5 Polycarbonate Nuclepore

polycarbonate

open-face

47 mm Teflonmembrane

47 mm quartz-fiber

Battery-powered

sampler weighs 18

pounds.

Filter-based Systems Designated by U.S. EPA as Reference or Equivalent Methods for PM10 

Sampling System

Particle

Size

(Fm)

Sizing Device Flow Rate

(L/min) Filter Media Reference/Equivalent MethodDesignation Number)

Federal Register

Citation

(Notice Date)

Wedding &

Associates PM10

Critical Flow

High-Volume

Sampler

PM10 Cyclone-type

inlet

1,130 20.3 cm x 25.4

cm filters

Reference method

(RFPS-1087-062)

Vol. 52, 37366

(10/06/87)

Sierra-Andersen

(SA) or General

Metal Works

(GMW) Model

1200 PM10 HighVolume Air

Sampler System

PM10 Impaction-type

size-selective

inlet

(SA or GMW1200)

1,130 20.3 cm x 25.4

cm filters

Reference method

(RFPS-1287-063)

Vol. 52, 45684

(12/01/87)

Vol. 53, 1062

(01/15/88)

Sierra-Andersen

(SA) or General

Metal Works

(GMW) Model

321 B PM10 HighVolume Air

Sampler System

PM10 Impaction-type

size-selective

inlet

(SA or GMW321 B)

1,130 20.3 cm x 25.4

cm filters

Reference method

(RFPS-1287-064)

Vol. 52, 45684

(12/01/87)

Vol. 53, 1062

(01/15/88)

Sierra-Andersen

(SA) or General

Metal Works

(GMW) Model

321 C PM10 HighVolume Air

Sampler System

PM10 Impaction-type

size-selective

inlet

(SA or GMW321 C)

1,130 20.3 cm x 25.4

cm filters

Reference method

(RFPS-1287-065)

Vol. 52, 45684

(12/01/87)

Vol. 53, 1062

(01/15/88)

Oregon DEQ

Medium-Volume

Sequential Filter

Sampler for PM10

PM10 SA 254

impaction-type

inlet

47 mm Teflonmembrane

47 mm Quartzfiber

Reference method

(RFPS-0389-071)

Vol. 54, 12273

(03/24/89)
Table 2-8 (cont.)

Example Particle Sampling Systems (Chow, 1995)

Filter-based Systems Designated by U.S. EPA as Reference or Equivalent Methods for PM10 

Sampling System

Particle

Size

(Fm)

Sizing Device Flow Rate

(L/min) Filter Media Reference/Equivalent MethodDesignation Number)

Federal Register

Citation

(Notice Date)

2-52

Sierra-Andersen

Models SA 241

and SA 241M, or

General Metal

Works Models G

241 and GA

241M PM10 Low

Volume

Dichotomous

Samplers

PM10,

PM2.5

SA 246 B or G

246 impactiontype inlet,

2.5 um virtual

impactor

assembly

Total:

16.7 for PM10

Coarse:

1.67

Fine:

15.03 for

PM2.5 and less

37 mm PM2.5

37 mm coarse

[PM10 minus

PM2.5]

Reference method

(RFPS-0389-073)

Vol. 54, 31247

(07/27/89)

Andersen

Instruments

Model FH621-N

PM10 Beta

Attenuation

Monitor

PM10 SA 246 B

impaction-type

inlet

16.7 40 mm filter tape Equivalent method

(EQPM-0990-076)

Vol. 55, 38387

(09/18/90)

Rupprecht &

Patashnik TEOM

Series 1400 and

1400a PM10

Monitor

PM10 Impaction-type

inlet

3.00 out of

16.7

12.7 mm

diameter filter

Equivalent method

(EQPM-1090-079)

Vol. 55, 43406

(10/29/90)

Wedding &

Associates PM10

Beta Gauge

Automated

Particle Sampler

PM10 Cyclone-type

inlet

18.9 32 mm filter tape Equivalent method

(EQPM-0391-081)

Vol. 56, 9216

(03/05/91)

Rupprecht &

Patashnik Partisol

Model 2000 Air

Sampler

PM10 Impaction-type

inlet

16.7 47 mm diameter

filter

Equivalent method

(EQPM-0694-098)

Vol. 59, 35338

(07/11/94)
2-53

Light Extinction Components

A number of instruments measure light scattering (bscat) by particles and gases. These

instruments are called nephelometers and are classified according to the scattering angle that is

measured: forward scattering, back scattering, integrating, and polar. Forward and back scattering

instruments have been evaluated and used on limited basis for transportation safety purposes. Since

only a portion of the scattered light is measured, however, and since absorption is completely

unaccounted for, these instruments will mis-measure visibility under atypical aerosol conditions.

Integrating nephelometers measure scattering over nearly the entire range of angles from 0E to 180E.

The integrating nephelometer has been a popular instrument for monitoring the variations of particle

concentrations in air pollution studies. Integrating nephelometer measurements can be directly related

to the scattering coefficient (bscat). The polar nephelometer measures the light scattered from any

chosen angle. While helpful in predicting the effects of aerosols on the appearance of a scene, the

polar nephelometer is not easily adapted to routine monitoring and has not been used except in

laboratory situations. Since a nephelometer makes a point measurement, direct comparisons to

collocated aerosol measurements are practical. In addition, the system can be absolutely calibrated

using clean (Rayleigh) air and various dense gases with a known multiple of Rayleigh scattering.

Optical absorption (babs) has traditionally been measured by evaluating the light absorption

characteristics of particles collected on a filter media. This type of analysis can be performed in the

laboratory on collected filters. For example, the IMPROVE Program applies a combination of Laser

Integrating Plate and Laser Integrating Sphere Methods (LIPM and LISM, respectively) to estimate

babs from Teflon filters. An aethalometer is one instrument that continuously measures particle light

absorption on a filter media. Other experimental methods have also been developed. Absorption

methods used to estimate the absorption coefficient can be combined with nephelometer scattering

measurements to estimate extinction.

Scene Parameter Considerations

The primary objective of scene monitoring is to provide a qualitative representation of the

scenic appearance of visual air quality. Commonly used monitoring methods include documentation

of the scene by photography, human observations of visual range, and contrast measurements. Scene

monitoring data are often converted to optical indexes because of the usefulness of information in that

form. Specifically, visual range observations and target contrast data are converted to extinction

coefficient values (bext). Concerns associated with these data transformations, however, have limited

their usefulness. One key assumption often violated is that the inherent contrast is known. Target

inherent contrast changes as a function of the sun position in the sky (i.e., time of day and day of the

year), cloud cover, and target cover. Another source of error is associated with cloud shading of the

sight path but not the target. These non-uniform lighting conditions will cause the extinction

coefficient to be significantly underestimated. Since the development of alternative optical monitoring

instrumentation, IMPROVE protocols use scene monitoring data for qualitative purposes only.

2.6.1.5 Capital and Operational Considerations

Economical and logistical tradeoffs also must be considered prior to establishing a visibility

monitoring site or network. Long-term and short-term objectives also must be reviewed with respect

to available funding. Capital outlay for instrumentation and installation can often be reduced when

cooperative monitoring programs are established between state, federal, tribal, and private
2-54

participants. As program budgets are enhanced or trimmed, site and network-specific objectives must

be further evaluated.

Practical considerations such as the availability of power, security, year-round access, and onsite personnel should also be considered when selecting the location of a monitoring site. Such

considerations, however, should be treated as secondary to spatial and temporal criteria, unless it can

be demonstrated that practical constraints would substantially jeopardize data quality or data

recovery.

2.6.2 Example Network Configurations

 Visibility monitoring information must be generated in a manner consistent with CAA, EPA

regulations, and this EPA Visibility Monitoring Guidance Document to be acceptable as a primary

source of visibility data for regulatory or planning purposes. IMPROVE Protocols, adopted by the

IMPROVE Program in 1988, are consistent with these requirements and are reviewed on an ongoing

basis by IMPROVE Committee participants. Although additional monitoring protocols are or may

be developed that meet CAA and EPA regulations, the remaining sections of this document will focus

on IMPROVE Visibility Monitoring Protocols. Examples of three types of monitoring configurations

are described below. Each example addresses one or more network-specific/site-specific objectives

for Class I or Non-Class I areas. 

2.6.2.1 Routine Monitoring Network

IMPROVE is a cooperative visibility monitoring effort between the EPA, federal land

management agencies, and state air agencies. Network-specific objectives of the IMPROVE Program

are:

! To establish existing visibility conditions in Class I areas.

! To identify chemical species and emission sources responsible for existing man-made

visibility impairment.

! To document long-term trends.

The IMPROVE Visibility Monitoring Program was established in 1985. Due to resource and

funding limitations it was not practical to place monitoring stations at all 156 mandatory Class I areas

where visibility is an important attribute. Instead, the IMPROVE Committee selected a set of sites

that were representative of the Class I areas. Thirty-six (36) full-IMPROVE and IMPROVE Protocol

sites were originally selected to represent the distribution of visibility and aerosol concentrations over

the United States. In 1998, thirty (30) IMPROVE Program sites have various configurations of

optical and aerosol monitoring equipment. Additional Class I area monitoring sites that have adopted

IMPROVE protocols, but are not part of the IMPROVE Program network, are often called

IMPROVE Protocol Sites.
2-55

Aerosol monitoring is conducted at all IMPROVE Program sites and is accomplished by a

combination of particle sampling and sample analysis. At most sites, the 4-module IMPROVE

sampler used has been programmed to collect two 24-hour duration samples per week. Starting in

December of 1999, the sampling will be conducted once every three days. The sampler collects four

simultaneous samples: three PM2.5 samples (Modules A, B, and C) and one PM10 sample (module D).

Module A uses a Teflon filter that is analyzed for PM2.5 mass, elements, and light absorption. Module

B uses a nylon filter that is analyzed for sulfates, nitrates, and chloride ions. Module C uses a quartz

filter that is analyzed for organic and elemental carbon. Module D uses a Teflon filter to determine

total PM10 mass. Additional specifications regarding the IMPROVE aerosol sampler are provided

in Section 3.0. 

Transmissometers are currently employed to measure the optical light-extinction coefficient

(bext) at selected IMPROVE Program sites. Nephelometers are employed at other sites to measure

the optical light scattering coefficient (bscat). Absorption measurements (babs) are made using

combined laser integrating plate and laser integrating sphere laboratory methods on the IMPROVE

Module A filter. Both a transmissometer and nephelometer are located at Grand Canyon to research

existing and future visibility monitoring methods. Relative humidity is measured continuously in

association with all optical monitoring sites (transmissometer and nephelometer).

Scene monitoring using 35 mm automatic cameras was initially conducted at all IMPROVE

Program sites in association with aerosol and optical monitoring. Most sites, however, discontinue

scene monitoring after 5 years of data collection because a sufficient visual record of the range of

visibility conditions has been collected. In some cases scene monitoring continues to provide a

qualitative record of the appearance of the scene for further interpretation of aerosol and optical data.

The IMPROVE monitoring program objective of documenting long-term trends will require

monitoring in perpetuity. IMPROVE encourages FLMs, states, and others that have IMPROVE

protocol sites in Class I areas to also make a long-term commitment to monitoring. The IMPROVE

Program has also been a leader in visibility research and in the development of visibility monitoring

instrumentation. The commitment to these efforts continues.

2.6.2.2 Special Study Monitoring Site (Network)

A series of monitoring studies were conducted in 1987 and 1990 to determine emission

impacts and haze sources at Grand Canyon National Park, Arizona. Based on these studies, EPA

proposed regulations that would require substantial reduction of sulfur dioxide emissions from the

Navajo Generating Station (NGS). While the NGS has been linked to a portion of the haze at Grand

Canyon National Park, it is generally recognized that a number of other area and point sources also

contribute to the haze. In response to a 1991 congressional mandate to further determine the sources

of visibility impairment, the EPA established a short-term special study titled Project MOHAVE

(Measurement ofHaze and VisualEffects). The primary goal of Project MOHAVE was to determine

the contribution of the Mohave Power Project (MPP), a 1580 Megawatt, coal-fired steam electric

power plant, to haze at Grand Canyon and other mandatory Class I areas where visibility is an

important air quality related value (attribution analysis). Additional goals included:

! Determining the improvement in visibility that would result from the control of MPP

emissions.
2-56

! Identifying other sources that contribute to haze in Grand Canyon National Park,

including those sources that are regionally transported.

The Project MOHAVE study plan was developed and evaluated by the Project MOHAVE

Steering Committee (composed of government and industry scientists), members of the Haze in

National Parks and Wilderness Areas Committee of the National Research Council, National

Academy of Sciences participants, and various other individuals. Study plan considerations included

an overview of the MPP and Grand Canyon National Park geography, regional transport regimes,

regional meteorological conditions, and historical study findings. 

The field measurement portion of the study was scheduled to last one year, from September

1991 through August 1992. Intensive monitoring and tracer release periods were scheduled for

January 4-31, 1992, and July 15-August 25, 1992. During the intensive periods a tracer was emitted

from the MPP stack, and tracer and particulate data were collected continuously at more than 30

sites. Different artificial tracers were released from the Los Angeles Basin and San Joaquin Valley

during the summer intensive to gain insight into the transport of emissions from these large source

areas. Each site was equipped with a programmable Brookhaven atmospheric tracer sampler. During

the non-intensive periods when a tracer was not released, no tracer sampling was conducted, the

number of particulate monitoring sites was scaled back considerably, and samples were collected only

two days per week. Meteorological, optical, and scene monitoring was conducted continuously

throughout the study. 

Four classes of sites were established for the MOHAVE study:

! Receptor Sites - Four (4) sites were selected within or in very close proximity to Grand

Canyon National Park. Most of these sites had some degree of existing or planned

monitoring prior to Project MOHAVE. All sites operated during the entire study period.

Instrumentation included a full IMPROVE aerosol sampler, transmissometer,

nephelometer, 35 mm camera, and surface meteorology at three of the four sites. The

fourth site had a DRUM sampler for particle monitoring and a nephelometer.

! Other Class I Sites - Six (6) existing Class I sites were selected to represent areas that

could be impacted by MPP and/or serve as background sites. Class I sites operated

during the entire study period. Instrumentation consisted primarily of full IMPROVE

aerosol samplers and cameras. Three of the six sites had additional optical measurements

with a transmissometer. Surface meteorological data were collected at two of the

transmissometer sites.

! Background Sites - Twenty-one (21) background sites were selected to characterize high

elevation and low elevation transport into the study area and to show detailed

concentration patterns within the study area. Module A of the IMPROVE aerosol

sampler and a filter pack for SO2 were used to collect 24-hour samples (aerosol and

tracer) during each day of the intensive periods. No background data were collected

during non-intensive periods.

! Scene Sites - Camera monitoring sites with broad views and panoramas were selected

throughout the study domain. Both 35 mm still-frame and 8 mm time-lapse photography

were taken to document the visual air quality throughout the study.

Site selection considerations included the proximity to Grand Canyon National Park, location

in respect to possible pollution transport corridors and "clean" (no emissions) corridors, and location

with respect to regional air flow, as well as the availability of power and accessibility. 
2-57

Tracer monitoring data were used to identify the general transport patterns for the MPP plume

and to help identify the interaction between MPP and southern California emissions. Tracer data also

served as a "check" for transport model predictions. Air quality (particle and optical) data served as

input for hybrid and receptor models, to document the regional distribution of particulate and SO2,

and to identify boundary conditions for other pollutants transported into the study area. Camera

(scene) monitoring provided documentation of the visual impairment of specific unique vistas under

various air quality conditions. Meteorological monitoring characterized the speed, direction, and

depth of transport into the region. Upper air and surface data were also used for model initiation and

validation. 

2.6.2.3 Non-Class I (Urban or Sensitive Area) Monitoring Site

The Tahoe Regional Planning Agency (TRPA) established a visibility monitoring program in

the Lake Tahoe Basin in December 1988. The Lake Tahoe Basin, with its nearly pristine lake

surrounded by the Sierra Nevada Mountains, is a nationally recognized area of scenic beauty. The

basin's visibility has been acknowledged as one of its finest attributes. 

Based on data collected during an initial short-term 1981-82 visual air quality study, the

Tahoe Regional Planning Agency established regional and sub-regional environmental thresholdcarrying capacities for the Tahoe Basin. Regional visibility is defined as the overall prevailing

visibility in the Tahoe Basin. Sub-regional visibility is characterized by the layered haze (regional

haze with a defined boundary) in the Lake Tahoe urbanized areas. Thresholds were established to

achieve visual ranges of given kilometers (miles), as estimated from measured particulate

concentrations. Both regional and sub-regional goals also included the desire to reduce wood smoke

emissions by 15% from 1981 base values. The TRPA monitoring program was established to confirm

standard attainment or non-attainment with the established thresholds and to further understand the

causes of visibility degradation in the Basin.

Two monitoring sites were selected for the Lake Tahoe study. The primary site was located

on Lake Tahoe Boulevard adjacent to California Air Resource Board (CARB) criteria pollutant and

PM10 monitors. A full IMPROVE aerosol sampler, integrating (ambient) nephelometer, and an

automatic camera system were installed in December 1988 to monitor sub-regional visibility from this

location. The camera system viewed across Lake Tahoe to the north. A second monitoring station

was established at Bliss State Park to monitor regional air within the Lake Tahoe Basin. A full

IMPROVE aerosol sampler, integrating (ambient) nephelometer, and transmissometer were installed

in November 1990. The 13.3 km transmissometer sight path extended from the Zephyr Point Fire

Tower to the Bliss State Park monitoring location. Meteorological measurements, temperature,

relative humidity, wind speed, and wind direction are also continuously measured at both primary

monitoring locations. As of this publication all these instruments are still operating. Two additional

camera-only monitoring locations were initially proposed for viewing the south shore of Lake Tahoe

and north of the Lake Tahoe Basin, but as of this publication, they have not been installed.

Collected data are reviewed annually by the Tahoe Regional Planning Agency and compared

to established visibility thresholds. Monitoring is scheduled to continue.
3-1

3.0 AEROSOL MONITORING

As an example of an existing visibility-related aerosol monitoring program, this section describes

IMPROVE aerosol monitoring and data management techniques. References made to

manufacturers or trade names are not intended to constitute EPA endorsement or

recommendations for use. New or improved instruments, instrument upgrades, and methods of

monitoring are continually being developed.

Aerosol monitoring is used to identify chemical species and obtain concentration

measurements of atmospheric constituents that contribute to visibility impairment. Primary

techniques include filter-based aerosol samplers that collect samples on various substrates in two

size ranges, aerodynamic diameters < 2.5 μm (PM2.5) and aerodynamic diameters < 10 μm

(PM10). The particulate monitoring portion of the IMPROVE program measures the

concentration of PM2.5 particles for mass, optical absorption, major and trace elements, organic

and elemental carbon, and sulfate, nitrate, and chloride ions, and the concentration of PM10

particles for mass.

An understanding of the liquid water associated with hygroscopic particles is also critical.

With present technology, the liquid water particle component cannot be directly measured, nor is

it possible to determine liquid water content from subsequent analysis of particle samples.

Relative humidity data can be used to infer the visibility impacts associated with liquid water.

Due to the significance of this component for visibility effects, continuous relative humidity

monitoring is a desirable supplement to aerosol monitoring.

The following subsections describe the monitoring criteria, instrumentation, installation

and site documentation, system performance and maintenance, data collection, filter analysis, data

reduction, validation, reporting, and archive, supplemental analysis, quality assurance, and analysis

and interpretation recommended for aerosol monitoring. Operation manuals and manufacturers

specifications are provided in Appendix B.

3.1 MEASUREMENT CRITERIA AND INSTRUMENTATION

Both monitoring and analytical considerations need to be evaluated when establishing an

aerosol monitoring site. The sample frequency, particle size, filter substrate, flow rate, and

analytical methods are all important considerations when measuring major aerosol components

and trace element constituents. For good monitoring statistics, a high recovery rate is essential.

The factors here are sampler reliability and the ability to service the sampler (change filters) in all

weather conditions.

The standard IMPROVE aerosol sampler, shown in Figure 3-1, consists of one PM10

module with Teflon filters, and three PM2.5 modules, one with Teflon, one with nylon, and one

with quartz filters. Not shown is the separate controller module. The power for the pumps is

through a switched outlet with a signal from the controller. Each module is optimized for a

specific purpose and matched to its analytical protocols as shown in Table 3-1. The use of this

standard setup of four modules is strongly recommended in order to maintain the quality

assurance of redundant measurements. All IMPROVE sites the IMPROVE network use this

standard setup. Approximately 10% of the sites in mandatory Class I areas have an additional

PM2.5 module with Teflon filters for quality assurance. The samplers were designed by Crocker

Nuclear Laboratory (CNL) at the University of California, Davis
3-2

electrical to

controller

Module A

PM2.5

(Teflon)

mass,

elements

absorption

Module B

PM2.5

(nylon)

sulfate,

nitrate

ions

Module C

PM2.5

(quartz)

organic,

elemental

carbon

Module D

PM10

(Teflon)

mass

carbonate

denuder

electrical to

controller

electrical to

controller

electrical to

controller

Figure 3-1. Diagram of the IMPROVE Aerosol Sampler.

Table 3-1 Summary of IMPROVE Aerosol Sampler Data Collection Parameters

Module Particle Size Filter Type Analytical Method

(Variables)

A 0.0-2.5 μm Teflon®• Gravimetric Analysis (PM2.5 mass)

• Hybrid Integrating Plate/Sphere Method

(coefficient of optical absorption)

• Particle Induced X-Ray Emission (elements Na-Mn)

• X-Ray Fluorescence (elements Fe-Pb)

• Proton Elastic Scattering Analysis (H)

B 0.0-2.5 μm Nylon • Ion Chromatography

(sulfates [SO4

=

], nitrates [NO3

-

], nitrites [NO2

-

], & chloride

[Cl-])

C 0.0-2.5 μm Quartz • Thermal Optical Reflectance Carbon Combustion Analysis

(carbon in eight temperature fractions)

D 0.0-10.0 μm Teflon®• Gravimetric Analysis (PM10 mass)
3-3

Each module has an independent air stream with a sizing device, a flow controller, and a pump,

plus solenoid valves for exposing two or three filters between weekly sample changes. Figure 3-2

shows schematics for PM2.5 modules used before and after 1999, for the PM10 module used after

1999 and for the controller module used after 1999. The primary change in the IMROVE sampler

in 1999 is the controller module. In the version used from 1998 to 1999, programmable clock

controlled the pump and solenoid valve switching for each filter module. A new version of the

sampler, installed in 1999, uses a microprocessor to (1) control the pumps and solenoid valves,

(2) read and record the flow rate pressure transducers, (3) read and record the temperature at the

filter during and after sampling, and (4) optionally read and record the relative humidity. The

microprocessor will permit sampling on a 1-day-in-3 schedule. The collection data will be stored

on a removable magnetic card that is sent between the central laboratory and the site in the box

with the filters. The magnetic card will also have the sampler programs and the site-specific flow

rate calibration equations. The operator will read all collection data on the microprocessor

screen. With the microprocessor, the readable pressure gauges and elapsed timers in the earlier

version of the sampler are unnecessary. The pumps are housed separately.

cassette manifold

cup for coarse particles

timer #2

cyclone

# 2

elapsed

inlet

stack

hold down plate

# 2

critical

solenoid valve #1

orifice

hose to

timer #1

quick connect

manual override switches

filter

cassette

# 1

# 1

solenoid valve #2

pump

elapsed

15

in Hg

VACUUM

ZERO

5

1

10

INCHES OF WATER

.40

30 MAGNEHELIC

25

20

0

.20

ZERO SET

.80 .60

1.0

Figure 3-2a. Schematic of the IMPROVE PM2.5

 module used before 1999.
3-4

PM2.5 Filter Module

1 stack compression sleeve

2 inlet stack

3 inlet tee

4 cyclone / cassette manifold

5 cartridge with 4 filter cassettes

6 solenoid value assembly

7 solenoid valve (4)

8 manifold nut drive

9 leadscrew

10 handwheel

11 timing pulleys for motor

12 gear motor

13 electronics enclosure

14 critical orifice valve

15 Teflon hose with stainless steel

braid

16 enclosure box (outdoor

sampler)

17 belt guard

18 sampler retainer pin

Figure 3-2b. Schematic of the IMPROVE PM2.5 module used after 1999.
3-5

PM10 Filter Module

1 stack compression sleeve

2 inlet stack

3 sampler retainer pin

4 PM10 cassette manifold

5 cartridge with 4 filter cassettes

6 solenoid value assembly

7 solenoid valve (4)

8 manifold nut drive

9 leadscrew

10 handwheel

11 timing pulleys for motor

12 gear motor

13 electronics enclosure

14 critical orifice valve

15 Teflon hose with stainless steel

braid

16 enclosure box (outdoor sampler)

17 belt guard

18 funnel extension

Figure 3-2c. Schematic of the IMPROVE PM10 module used after 1999.
3-6

24 Volt

power

supply

12 Volt

power

supply

display screen

keyboard

receptacles for connectors to modules

A B C D QA

electronics board

microprocessor board

solenoid relays (4)

1 2 3

4 5 6

7 8 9

0 sp

Y N

bks

01/22/99 15:50:21

Temp 20 C 61% RH

A B C D

off off off off

yes no

etr

Figure 3-2d. Schematic of the IMPROVE controller module used after 1999.
3-7

The particle sizing for PM2.5 particles is accomplished with a cyclone operating with an

ambient flow rate of 22.8 L/min. Flow control is maintained by a critical orifice between the filter

and pump. The flow rate is measured both in front of and behind the filter. The flow rate in front

of the filter is determined from the pressure drop across the cyclone, while the flow rate behind

the filter is determined from the pressure at the front of the critical orifice. The dual

measurements provide a quality assurance check for every sample and shows the operator that the

cassettes are properly seated prior to sample collection. The standard deviation of flow rates over

a year is typically 2%-3%. Precision tests using collocated samplers typically indicate that the

flow rate precision is 3%.

The particle sizing for PM10 particles is accomplished with a commercial PM10 inlet. Inlets

of the Wedding design operate at 19 L/min. Inlets of the Sierra-Anderson design operate at 16.7

L/min. Flow control is also maintained by a critical orifice. The flow rate is measured only

behind the filter, using the pressure at the front of the critical orifice.

The filters are transported to the site and loaded into the samplers using a system of

cassettes and cartridges. A cartridge is a circular disk holding four cassettes. Clean filters are

loaded into two or three cassettes at a central laboratory. Each cartridge is labeled for the desired

module and change date, and also identified by color. The cartridges are mailed directly to the

site in sealed, insulated shipping containers. During the weekly site visits, the cartridge of clean

filters in each module is exchanged for a cartridge of exposed filters. For 1-day-in-3 sampling, the

samplers will be operating on the day of sample change once every third week. The cartridge for

this change will have only three cassettes and one hole. The operator will suspend sampling,

move a specially marked cassette from the exposed cartridge and place it in the hole in the clean

cartridge. The operator will resume sampling after the clean cartridges are all in place. The

cartridges of exposed filters are returned to the laboratory for processing. The PM2.5 Teflon filter

deposits are analyzed for the concentrations of deposit mass, hydrogen, elements with atomic

weights from sodium to lead, and for an optical parameter, the coefficient of absorption. The

nylon filters are analyzed for the concentrations of nitrate, sulfate, and chloride ions, the quartz

filters for the concentrations of organic and elemental carbon, and the PM10 Teflon filters for the

concentration of deposit mass.

There are two factors concerning whether it is better to have samplers in shelters or

completely outdoors. The first factor is temperature during sampling and between the end of

sampling and the removal of the filters. During sampling it is important to maintain an

approximately constant temperature of the air stream to avoid changing the relative humidity and

the gas-particle equilibrium. (Changes in relative humidity would effect the particle size of sulfate

particles. If the particle diameter is in the region of 2.5 μm, the change would effect the passage

through the particle sizing device.) After sampling is completed, it is important to avoid

volatilizing particles by excessively heating the sample. The sampler must not be in a shelter that

overheats nor in direct sunlight. The second factor in whether to use shelters is protecting the

integrity of the samples during sample change and allowing the operator to be able to perform the

change in extreme weather conditions. In regions of extreme winter cold and during periods of

heavy precipitation and or high winds, it may not be possible to obtain valid samples with an

outdoor sampler.

Therefore, in the IMPROVE network, samplers are normally inside a well-ventilated

shelter that shades the sampler from direct sunlight and protects the integrity of the sample during

sample changing in inclement weather. In regions of high summer temperature and mild winters,

the wall opposite the samplers may have only a screen. The shelter in this case protects against
3-8

direct sunlight, rain, and high wind. One consequence with using a shelter is that the stacks must

be longer than in an outdoor site, in order to have a 1 m clearance above the shelter roof. The

standard height of inlet stack for IMPROVE samplers is 2 m (when used in a shelter, the height of

the inlet can be more than 2 m above the ground). The temperature at the filter is monitored

during sampling and between sampling periods. The shelters are not heated or air-conditioned.

The IMPROVE particle sampler has been in use since 1988. In 1998, over 70 IMPROVE

sampler sites were operating in various visual air quality monitoring programs in North America,

from highly-polluted urban areas to pristine wilderness environments. Of those, approximately

25% of the sites operate with a single PM2.5 module. By the end of 1999, over 100 IMPROVE

sites will be operating throughout the U.S. Detailed and updated information regarding

IMPROVE particle sampler instrumentation or operation can be found IMPROVE Particulate

Monitoring Network Standard Operating, Air Quality Group, Crocker Nuclear Laboratory,

University of California, Davis). This is available as a pdf file on a National Park Service Web

site, http://www.nature.nps.gov/ard/vis/sop/index.html. The Sampler Operations Manual is

included as a Technical Instruction, TI201A IMPROVE Aerosol Sampler Operations Manual.

3.2 SITING CRITERIA

IMPROVE aerosol samplers are generally sited in conjunction with other IMPROVE

protocol optical and/or scene monitoring equipment. Therefore aerosol sampler protocols closely

resemble siting protocols for transmissometer, nephelometer, and scene monitoring equipment,

described in Sections 4.1.2, 4.2.2, and 5.2 respectively.

The primary siting criterion is to ensure that the air mass monitored is representative of the

area or region of interest. To assure consistent quality data, aerosol sampling sites are selected to

meet most if not all of the following criteria:

• For a mandatory Class I area, it must be within 100 km and have an elevation that is

between the minimum and maximum elevations. A given sampling site may represent

multiple mandatory Class I areas.

• Have good ventilation. (That is, not be in a valley with meteorological inversions.)

• Be removed from local sources such as diesel, wood smoke, automobile, road dust,

construction, etc.

• Be located in an area free from large obstructions, such as trees or buildings, that

would hinder sampling of representative aerosols. (Sampler inlets must be located

between 2 and 15 meters above the ground.)

• Be representative of the same air mass measured by other optical or scene monitoring.

• Have adequate AC power (a 20 Amp circuit of 110 V, 60 Hz line power for a

standard configuration). The primary power should not be provided by electric

generators.

• Be secure from potential vandalism.
3-9

• Be located in a region with available servicing personnel (operator).

• Be accessible during all months of the year.

3.3 INSTALLATION AND SITE DOCUMENTATION

The standard samplers are installed in a well-ventilated shelter with the inlet stacks and

cyclones mounted vertically. Mounting structures must be stable to avoid vibration or shifting,

and strong enough to support the weights of all installed samplers. Each IMPROVE module and

controller weighs approximately 40 pounds.

After the sampler hardware is installed, the critical orifice in each module is adjusted to

give the desired nominal flow rate. The flow rate calibration equations for each sampler are

determined by the audit procedures described further in Section 3.4 (System Performance and

Maintenance). (The flow rate calibration is audited every six months by either site operators or

field technicians from the central laboratory. If necessary the critical orifice is adjusted at these

times.)

When the flow rate calibration is complete, cartridges of test filters are placed in the

sampler and the operation of the sampler is tested using the system diagnostics magnetic card.

After the system is verified, the installing technician will train all operators, back-up

operators, and any other involved or interested on-site personnel. This includes reviewing the

sampler manual (Crocker Nuclear Laboratory Technical Instruction TI201A IMPROVE Aerosol

Sampler Operations Manual). Hard copies of this manual are left with the on-site personnel.

Additional copies are obtained as a pdf file on http://www.nature.nps.gov/ard/vis/sop/index.html.

The manual provides documentation on sampler operation, repair, and audits, and

troubleshooting.

Finally, the installing technician will complete the following:

• A site visit trip report

• Photographic documentation (including photographs of the shelters, all components,

shelter supports, local surroundings, sight path, power supply, etc.)

• Instrument and site configuration documentation, including site map and site

specifications (latitude, longitude, instrument elevations, elevation angle, sight path

distance, etc.)
3-10

3.4 SYSTEM PERFORMANCE AND MAINTENANCE

System performance and maintenance includes routine servicing, and instrument

calibration and maintenance.

3.4.1 Routine Servicing

Routine servicing is primarily the responsibility of the site operator, although any

deviations from expected behavior are reported to and solved in conjunction with the lab manager

or field specialist. Repairs are performed by the site operator under the supervision of a field

specialist. Similarly, biannual audits are performed by the site operator under the supervision of a

field specialist.

During the weekly sample changes, the site operator shall review the field log sheet and

verify that the sample collection parameters are within the acceptable ranges specified in the

IMPROVE Aerosol Sampler Manual. The microprocessor program will make internal checks and

note discrepancies on the viewing screen. The site operator should contact the central laboratory

when problems occur. The site operator should also inspect the equipment and the shelter to

verify cleanliness and identify possible problems. Weekly procedures are further detailed in

TI201A IMPROVE Aerosol Sampler Manual.

Additional routine servicing, to be performed monthly includes emptying the water bottle

on the Module D PM10 inlet for sites with Sierra-Anderson inlets, and verifying the integrity of the

mounting platform and filter mounting ports.

The purpose of the denuder in Module B (nylon filter) is to remove HNO3 from the air

stream before it reaches the filter. Since 1988, the denuders have been changed annually. Tests

indicate that with respect to SO2, the denuders will saturate during this time at most IMPROVE

sites. However, test with old and new denuders indicate that there is no decrease in the efficiency

to collect HNO3 over this period. Tests will be continued to monitor this. If necessary, the

frequency of changing the denuders will be increased to quarterly.

For quality control purposes, roughly 2% of the IMPROVE sampler filters are field

blanks. Field blanks are collected to determine the amount of material (artifact), picked up by the

filter cassettes during the shipping, installation, removal, and laboratory processing procedures.

No extra steps are required of the site operators for handling field blanks. All cartridges have four

cassettes; normally one or two will have no filters.

3.4.2 Instrument Calibration and Maintenance

Flow rate audits are performed whenever the sampler gauges indicate a potential error in

the flow rate and biannually at randomly selected sites. If an audit indicates the calculated flow

rates in any module are off more than 5%, a complete four point audit is performed. Flow rate

audit devices are delivered through the mail, and the audit is performed by the site operator.

Biannual audit procedures consist of nominal flow checks for two clean, newly installed filter

cassettes, for two consecutive sampling periods. If the biannual audit indicates the calculated

flow rates in any module are off by more than 3%, the sampling module in error must be recalibrated. Calibration and flow rate audit procedures are described further in the Crocker
3-11

Nuclear Laboratory SOP 176, Calibration, Programming, and Site Documentation and TI201A

IMPROVE Aerosol Sampler Operations Manual.

Annual site visits are performed by field specialists. Annual maintenance includes:

• Pre-maintenance inspections and site inventory.

• Cleaning individual cyclones, stacks, and inlets.

• Checking module components and electronics.

• Auditing each module and recording updated annual calibrations.

• Post-calibration verification checks.

• Site operator training.

3.5 SAMPLE HANDLING AND DATA COLLECTION

Sample handling includes pretesting (preliminary validation) of aerosol filters prior to use,

processing the clean filters and shipment to the site, routine field procedures used by site

operators, and processing the exposed filters in preparation for ionic, carbon, or elemental

analysis.

The standard operating procedures used in the handling of IMPROVE aerosol filters are

summarized in Figure 3-3.

3.5.1 Procurement and Pretesting of IMPROVE Aerosol Filters

The central laboratory is responsible for:

• Purchasing Teflon and nylon filters from commercial vendors.

• Acceptance testing of the filters.

• Preparing filter collection masks.

The carbon analysis laboratory is responsible for:

• Purchasing quartz filters from commercial vendors.

• Acceptance testing of the filters.

• Prefiring all filters.

Procedures for purchasing, acceptance testing, preparing, and assembling filters and

cassettes for the field are fully described in Crocker Nuclear Laboratory SOP 101, Procurement

and Acceptance Testing and its associated Technical Instructions.
3-12

3.5.2 Processing of Clean Aerosol Filters

The standard operating procedures for processing the clean aerosol filters include:

• Measuring the tare masses of the Teflon filters.

• Loading clean filters into cassettes and the cassettes into cartridges.

• Attaching identification tags to the cassettes and color codes and identification tags to

the cartridges.

• Leak testing cassettes.

• Sending the cartridges/cassettes with clean filters to the sites in specially designed

shipping containers.

Approximately 1500 field blanks are collected each year in the IMPROVE network.

These are used to determine the amount of material (artifact), picked up by the filter cassettes

during the shipping, installation, removal, and laboratory processing procedures. The

determination of when to include a field blank is determined by the sample handling software at

the time of loading the clean filters. Normally one or two of the four cassettes in each cartridge

will have no filters. When instructed, the laboratory technician will add a field blank in the

cassette in position four. This will be processed in the same manner as a normal filter except no

air is drawn through. No extra steps are required of the site operators for handling field blanks.

Procedures for processing filters and gravimetric analysis are fully described in Crocker Nuclear

Laboratory SOP 251 Sample Handling.
3-13

A B C D

purchase purchase purchase

filters filters filters

premeasure premeasure

mass mass

purchase

filters

filters

prefire

send to

central lab

load clean filters into cassettes and attach ID labels

acceptance

test

acceptance

test

store box in clean area at site

load cassettes into sampler and measure flow rate

measure flow rate and remove cassettes

collect sample

receive cassettes with exposed filters from site

review field log sheet, enter readings into database

transfer fillters and identification tags to Petri dishes

measure measure

mass mass

mount in

slides

store in

freezer

send to send to

ions carbon

contractor contractor

archive in

slide

trays

XRF

PIXE/PESA

slides

central

site

store in

freezer

leak-test all cassettes

PM2.5 Teflon PM2.5 nylon PM2.5 quartz PM10 Teflon

A B C D

mount in

U.S. Mail

U.S. Mail

absorption

measure

PM2.5 Teflon PM2.5 nylon PM2.5 quartz PM10 Teflon

acceptance

test

laboratory

central

laboratory

Figure 3.3. Flow diagram of filter handling procedures before, during, and after sample

collection. U.C. Davis has been the central laboratory for IMPROVE since 1988.
3-14

3.5.3 On-Site Filter Handling

Aerosol filter cassettes are changed weekly by the site operator every Tuesday. The filters

are loaded into the samplers using a system of cassettes and cartridges. A cartridge is a circular

disk holding four cassettes. Clean filters are loaded into two or three cassettes at a central

laboratory. Each cartridge is labeled for the desired module and change date. The desired

module is also identified by color. The cartridges are mailed directly to the site in sealed,

insulated shipping containers.

During the weekly site visits, the operator first activates the check flow rate program on

the microprocessor. For 1-day-in-3 sampling, the samplers will be operating on the day of sample

change once every third week. This step will suspend sampling during the sample change. The

operator records the information of the screen on the provided log sheet. Next, the operator

removes the cartridge of exposed filters in each module and inserts the cartridge of clean filters.

If this is a day with current sampling, the cartridge for this change will have only three cassettes

and one hole. The operator will move the partially exposed filter from the exposed cartridge and

place it in the hole in the clean cartridge. This cassette is clearly labeled by color. The operator

will then activate the program to check the initial flow rates of the new filters and record the

information from the screen to the log sheet. The microprocessor includes programs to check that

the flow rates are within specifications. The operator will be alerted if their are problems. If this

is a sampling day, the microprocessor will resume sampling. During this process, the operator

never directly touches the filters.

The operator returns the exposed filter cassettes, log sheets, and memory card to the

central laboratory by mail. The purpose of the log sheet is to maintain a record of collection data

even if the memory card were to be lost or damaged in transit.

3.5.4 Processing Exposed Filters and Preparation for Filter Analysis

Filter cassettes returned from the field are processed and prepared for analysis as follows:

• The data on the memory card are downloaded. The dates are compared to those on

the field log. If there is a match, the data are transferred to the tracking/analysis

database.

• All log sheet information and written notes are entered into the tracking/analysis

database.

• Site operators are contacted if any errors or equipment malfunctions are noted.

• The nylon and quartz filters (Modules B and C) and identification tags are transferred

to Petri dishes.

• The Teflon filters (Modules A and D) are weighed and the filters are loaded into slide

frames for further analysis. The identification numbers are written of the slide frames.

• All gravimetric mass measurements are entered into the tracking/analysis database.
3-15

3.6 FILTER ANALYSES AND DATA REDUCTION AND VALIDATION

The laboratory analysis of the PM2.5 Teflon filters (Module A) are performed at the central

laboratory. The analysis of the nylon filters (Module B) and quartz filters (Module C) are done by

two outside laboratories on separate contracts. The analytical results from these outside

laboratories are returned to the central laboratory as mass per filter without artifact correction or

sample volumes. At the central laboratory, the laboratory analysis of the Teflon filters, except for

gravimetric analysis, is performed quarterly, following the standard season for IMPROVE. The

data processing and validation are also done quarterly. The specific procedures are summarized

in the following subsections.

3.6.1 Gravimetric Mass

Gravimetric analysis of Module A and Module D IMPROVE Teflon filters uses the

difference method to determine the mass of the collected aerosol. The pre-weight of each filter is

measured prior to loading the filter into a cassette. Once exposed and returned to the laboratory,

the filter is removed from the cassette, and the post-weight of the filter is measured. Level-1

validation includes determination of the mass of the aerosol by calculating the difference between

the pre- and post-weights.

3.6.2 Absorption (babs)

The coefficient of light absorption for fine particles, babs, is determined from the Module A

Teflon filters using a Hybrid Integrating Plate and Sphere (HIPS) method. This involves direct

measurement of the absorption of a laser beam by a sample, over the area of the sample, to obtain

an ambient babs value. With the HIPS method, it is not necessary to analyze the clean filter before

collection. Currently, the method is being re-evaluated to determine its accuracy in determining

the coefficient of absorption in the atmosphere. Until, this evaluation is completed, the coefficient

is not being reported.

3.6.3 Analysis of Aerosol Species

Starting December 1999, the standard IMPROVE protocol is to collect 24-hour aerosol

data samples once every third day. Prior to December 1999, two samples were collected each

week, on Wednesday and Saturday. All major fine aerosol components plus PM10 mass are

measured, including several redundant measurements for quality assurance.

The IMPROVE aerosol sampler has four (4) separate modules. Three (3) modules

(denoted A, B, and C) are fine particle samplers with cyclone systems that operate at a nominal

flow rate of 22.8 liters per minute and collect particles up to 2.5 μm in diameter. The fourth

module (D) is a PM10 sampler operated at nominal flow rates of 19.1 liters per minute (Wedding

inlet) and 16.7 liters per minute (Sierra-Anderson inlet) and collect particles up to 10 μm. The

measurement and data reduction protocols associated with each module are described below.
3-16

Module A

The Module A Teflon filters are analyzed for elements with atomic weights from sodium

to manganese by Particle Induced X-ray Emission (PIXE), from iron to lead by X-ray

fluorescence (XRF), and simultaneously for hydrogen by Proton Elastic Scattering Analysis

(PESA). Both PIXE and PESA subject the collected aerosol sample to a beam of 4.5 MeV

protons, in vacuum, at the laboratory cyclotron. In PIXE, each element present in the sample is

induced by the proton beam to emit X-rays whose energy is characteristic of the element, and

whose number is proportional to the mass of the element. In PESA, the protons in the cyclotron

beam, which are elastically scattered through a given angle (30°) by the hydrogen atoms in the

sample, are also easily discriminated and counted, to give an accurate measure of the amount of

hydrogen. XRF analysis employs a grounded anode diffraction type X-ray tube with a

molybdenum anode. The X-rays produced by the tube are collimated and directed onto an

aerosol sample. The sample deposit absorbs the Mo X-ray energy and re-emits the energy as

X-rays characteristic to the elements present on the sample. The X-rays are detected by

high-resolution SiLi detectors with pulsed optical feedback to provide high count rate capabilities.

Module B

The Module B nylon filters are analyzed by Ion Chromatography (IC) for sulfate, nitrate,

and chloride ions, from which the sulfate and nitrate compounds are estimated. A sample is

prepared for IC analysis by desorption of the collected material in 15 mL water. This solution is

applied to strips of filter paper and allowed to dry, and the various ion species are separated in the

standard way according to their solubilities, by suspending the strips over a solvent and allowing it

to pass up through the paper by capillary action. Ambient gaseous nitric acid (HNO3) is subject

to adsorption by the nylon filter and subsequent transformation to the solid nitrate form, which

would bias measurements of the latter. Therefore, a gas denuder, consisting of a set of concentric

cylindrical aluminum sheets coated with potassium carbonate (K2CO3), is placed in the Module B

inlet to remove HNO3 before collection.

Module C

The Module C quartz filters are analyzed by Thermal Optical Reflectance (TOR) for

organic and elemental carbon. A second quartz filter behind the first is used to estimate the

artifact due to adsorption of organic gases. TOR involves:

• Heating a sample through a series of temperature increases or steps in a pure helium

atmosphere. Oxygen is added in the later stages to enable the volatilization of

elemental carbon.

• Converting the carbon evolved at each step into CO2 using an oxidizer (MnO2 at

912°C).

• Reducing the CO2 to methane which is then quantified by passage through a flame

ionization detector. Over the mid-range of the TOR heating (between about 130°C

and 550°C), charring of the sample occurs due to pyrolysis of organic particles; this is

monitored as a decrease in the reflectance from the sample surface. When the

reflectance reaches a minimum, 2% oxygen is added to the atmosphere. This allows

the elemental carbon in the sample, including the char produced by pyrolysis of

organic matter, to oxidize. The reflectance of the sample increases as the char is
3-17

removed. All carbon measured up to the point where the reflectance reattains its initial

value is interpreted as organic carbon. Carbon evolved beyond this point is reported

as elemental carbon. Table 3-2 outlines the eight carbon fractions reported as a

function of temperature and added oxygen. OP is the portion of elemental carbon

before the reflectance returns to the initial value. The total organic carbon (OC) is the

sum of the four organic fractions plus the pyrolytic fraction:

total organic carbon = OC = OC1 + OC2 + OC3 + OC4 - OP (3-1)

The total elemental carbon, also known as light-absorbing carbon (LAC), is the sum of the three

elemental carbon fraction minus the pyrolytic fraction

total elemental carbon = EC= LAC = EC1 + EC2 + EC3 - OP (3-2)

Module D

The gravimetric mass of all sampled particles up to 10 μm (PM10) is measured as the

difference between the weight of the primary Teflon filter before and after sampling, using an

electromicrobalance. Coarse mass is estimated by subtracting fine mass PM2.5 from total aerosol

mass PM10. Except under special circumstances, no further chemical analysis is performed on

individual Module D filters. It is assumed that coarse mass consists primarily of insoluble airborne

soil particles.

Table 3-2. Carbon Components as a Function of Temperature and Added Oxygen

Fraction Pyrolized

Fraction

Temperature

Range

Atmosphere Reflectance

vs. Initial

OC1 Ambient to 120°C 100% He At Initial

OC2 120°C – 250°C Under Initial

OC3 250°C – 450°C

OC4 450°C – 550°C

EC1 OP Remains at 550°C 98% He

2% O2

Over Initial

EC2 550°C – 700°C

EC3 700°C – 800°C

IMPROVE sample analysis procedures are fully documented Crocker Nuclear Laboratory

SOP 276, Optical Absorption Analysis; SOP 301, X-Ray Fluorescence Analysis; and SOP 326,

PIXE and PESA Analysis.
3-18

3.6.4 Data Reduction and Validation of Laboratory Analyses

All aerosol data, both measured and calculated, are entered into the project database and

validated according to IMPROVE protocols. Procedures for processing and validation of the

laboratory analysis data include:

• Calculating concentrations and uncertainties of the measured variables. These

calculations use standard IMPROVE equations for determining volume, mass, optical

absorption, and concentrations from XRF, PIXE/PESA, IC, and TOR analysis results.

Table 3-3 lists the commonly reported measured variables. In addition to these

measured variables, composite variables can be derived from the measured variables by

applying reasonable assumptions. These composite variables are included in Table 3-4

and discussed in more detail in Section 3.8.

• Entering the measured and composite variables data into the Concentration Database

and checking for internal consistency

• Validating the data to identify anomalous variations with time using the following

techniques:

A. Correlation plots between:

1) Si and Fe

2) 3[S] (Teflon, PIXE) and SO4

=

 (Nylon, IC)

3) Organic mass from carbon and organic mass from hydrogen

4) Mass and reconstructed mass

B. Timeline plots of major variables

C. Statistical comparisons

D. Examination of individual anomalies and errors transcribing data

Concentration uncertainty and precision estimates are presented in Section 3.8.

IMPROVE data processing and validation procedures are fully documented in Crocker Nuclear

Laboratory SOP 351, Data Processing and Quality Assurance.
3-19

Table 3-3. Commonly Reported Measured Variables

MEASURED VARIABLES

Abbreviation Atomic

No.

Component Module Analytical

Method

Reporting

Units

General Reporting

Category

 MASS N/A PM2.5 Fine Mass A Gravimetric ng/m3Fine Mass

 H 1 Hydrogen A PESA ng/m3 Major Element

 Na 11 Sodium A PIXE ng/m3 Marine

 Mg 12 Magnesium A PIXE ng/m3Soil Elements

 Al 13 Aluminum A PIXE ng/m3Soil Elements

 Si 14 Silicon A PIXE ng/m3Soil Elements

 S 16 Sulfur A PIXE ng/m3 Major Element

 Cl 17 Chlorine A PIXE ng/m3 Marine

 K 19 Potassium A PIXE ng/m3

Soil Elements

 Ca 20 Calcium A PIXE ng/m3Soil Elements

 Ti 22 Titanium A PIXE ng/m3Soil Elements

 V 23 Vanadium A PIXE ng/m3 Metallic Tracer

 Mn 25 Manganese A PIXE ng/m3Soil Elements

 Fe 26 Iron A XRF ng/m3Soil Elements

 Co 27 Cobalt A XRF ng/m3 Multiple

 Ni 28 Nickel A XRF ng/m3 Metallic Tracer

 Cu 29 Copper A XRF ng/m3 Metallic Tracer

 Zn 30 Zinc A XRF ng/m3 Metallic Tracer

 As 33 Arsenic A XRF ng/m3 Metallic Tracer

 Se 34 Selenium A XRF ng/m3 Metallic Tracer

 Br 35 Bromine A XRF ng/m3 Metallic Tracer

 Pb 82 Lead A XRF ng/m3 Metallic Tracer

 NO3

- N/A Nitrate Ion B IC ng/m3 Major Ion

 NO2

- N/A Nitrite Ion B IC ng/m3 Major Ion

 SO4

= N/A Sulfate Ion B IC ng/m3 Major Ion

 Cl- N/A Chloride Ion B IC ng/m3 Marine

 OC1 6 Low Temperature Organic Carbon C TOR ng/m3 Organic Carbon

 OC2 6 High Temperature Organic Carbon C TOR ng/m3 Organic Carbon

 OC3 6 High Temperature Organic Carbon C TOR ng/m3 Organic Carbon

 OC4 6 High Temperature Organic Carbon C TOR ng/m3 Organic Carbon

 EC1 6 Low Temperature Elemental Carbon C TOR ng/m3 Elemental Carbon

 EC2 6 High Temperature Elemental Carbon C TOR ng/m3 Elemental Carbon

 EC3 6 High Temperature Elemental Carbon C TOR ng/m3 Elemental Carbon

 PM10 N/A PM10 Mass D Gravimetric ng/m3 PM10 Mass

Note: For consistency across all parameters, the IMPROVE data for PM2.5 Fine Mass and

PM10 Mass total mass is generally reported in ng/m3 . Conversion to μg/ m3 is accomplished by

multiplying by 1000.
3-20

Table 3-4. Commonly Reported Composite Variables

COMPOSITE VARIABLES FOR FINE PARTICLES

(Brackets [ ] indicate the mass concentration of aerosol species or elements)

Abbreviation Component Module Composite Equation

KNON Nonsoil Potassium A [K] - 0.6[Fe];

a qualitative smoke tracer

NHSO Ammonium Sulfate

[(NH4)2SO4]

A 4.125[S];

a standard form of sulfate

SOIL Soil (fine soil) A 2.20[Al] + 2.49[Si] + 1.63[Ca] +

2.42[Fe] + 1.94[Ti]

OMH Organic Mass by Hydrogen

(assumes all sulfur is ammonium

sulfate and there is no hydrogen

from nitrate)

A 13.75([H] - [S]/4)

NHNO Ammonium Nitrate

[(NH4)NO3]

B 1.29[NO3

-

];

a standard form of nitrate

OC Total Organic Carbon C [OC1] + [OC2] + [OC3] + [OC4] +

[OP]

OMC Organic Mass by Carbon C 1.4[OC]

LAC Light Absorbing Carbon C [EC1] + [EC2] + [EC3] - [OP]

TC Total Carbon C [OC1] + [OC2] + [OC3] + [OC4] +

[EC1] + [EC2] + [EC3]

RCMC Reconstructed without Nitrate A & C [NHSO] + [SOIL] + [OMC] + [LAC] +

1.4[KNON] + 2.5[Na]

CM Coarse Mass A & D PM10 - PM2.5

RCFM Reconstructed Fine Mass with

Nitrate

A to C [NHSO] + [NHNO] + [LAC] + [OMC]

+ [SOIL]
3-21

3.7 DATA REPORTING AND ARCHIVE

3.7.1 Data Reporting

Aerosol data reports are prepared quarterly and annually. A separate data report is

prepared for each instrument type; aerosol data reports contain only IMPROVE sampler data.

Reporting consists of various text discussions and graphics presentations concerning the

instrumentation and collected data. Specific contents of the reports are defined by the contracting

agency.

Quarterly reports are normally completed within three months after the end of a

monitoring season. Standard meteorological monitoring seasons are defined as:

Spring (March, April, and May)

Summer (June, July, and August)

Fall (September, October, and November)

Winter (December, January, and February)

Annual data reports are provided for each year, beginning with samples collected in

March. The annual reports should contain the following major sections:

• Introduction

• Data Collection and Reduction

• Site Configuration

• Seasonal and Annual Data Summaries

• Summary

• References

The introduction should contain a conceptual overview of the purpose of the monitoring

program and a description of the monitoring network(s). The data collection and reduction

section should include data collection methods, data file review, data validation, application of

validity codes, processing through various validation levels and discussion of file formats, and

identification of meteorological and optical interferences that may affect the calculation of

reconstructed bext from IMPROVE sampling measurements.

The site configuration section should contain a brief discussion of instrumentation at each

aerosol monitoring site, basic principles of operation, measurement principles, and data collection

specifications, including:

• A map depicting the location of all monitoring network sites.

• A Monitoring History Summary Table, listing for each monitoring site the name, type

of instrumentation, and period of operation for each instrument type.

• A Site Specifications Summary Table, listing for each monitoring site the site name,

abbreviation, latitude, longitude, and elevation of the IMPROVE sampler, the weekly

sampling schedule, and the operating period during the season.
3-22

Data summaries are prepared for each site that operated during the reporting period.

Summaries should include concentrations and distributions of major and trace elements as well as

fine mass and its components, including determined composite variables. An example Seasonal

Aerosol Data Summary is presented as Figure 3-4. Sample recovery rates which describe the

percent of possible samples validated for each reported network site, by year, are reported as

required.

A summary section that provides a synopsis of the aerosol monitoring network, including

any changes in operation or analysis techniques and a general conclusion of the monitoring period

in review, is included in the reports. A reference section should include technical references

(documents cited in the report), and related reports and publications (including all prior reports

pertaining to the monitoring program).

3.7.2 Data Archive

The digital tracking/analysis database is archived on a monthly basis. All raw and

processed data for a given season, constants, calibration, and data processing files are archived on

a seasonal basis after data have been finalized and reported. All data are archived in ASCII

format. Files are stored in their original formats (Level-1, Level-2) on magnetic tape and on CDROM. At least two copies of each media are created; one copy is stored at the data processing

location and the other off-site.

Filter media, supporting documentation, and reports are archived on a continual basis.

Archives include site specifications, monitoring timelines, data coordinator/site operator

correspondence, site operator log sheets, trip reports, summary plots, instrument calibration and

maintenance logs, and file audit reports. All validated data are available in an FTP Internet site

maintained by the central laboratory. For instructions on obtaining data, e-mail

<wakabayashi@crocker.ucdavis.edu>. Supplemental quality assurance information is also on the

site. The standard file format currently used for IMPROVE protocol aerosol data are shown in

Figure 3-5.
3-23

SMOKY MOUNTAINS N.P. MAR 01,1998 - MAY 31,1998

26-OCT-98 IMPROVE PARTICULATE NETWORK

 Major elements, tracer elements and SO2

 24-hour concentrations in nanograms/cubic meter

 Soil elements Smoke

 DATE HOUR H S SO2 SI K CA TI MN FE KNON

 03/04/98 0000 513.6 1286.8 997 70.3 34.5 22.7 *2.2 2.0 21.2 21.8

 03/07/98 0000 226.3 401.7 459 29.9 34.3 3.3 *1.4 *0.8 3.1 32.5

 03/11/98 0000 293.7 774.1 3204 55.4 33.5 22.1 6.0 2.6 23.0 19.7

 03/14/98 0000 581.9 1173.0 4077 96.5 54.0 37.7 *1.8 2.2 35.9 32.5

 03/18/98 0000 217.7 400.3 736 37.1 29.1 13.4 *2.2 *1.4 5.9 25.6

 03/21/98 0000 184.7 420.7 366 24.7 11.5 4.5 *2.1 2.1 2.3 10.1

 03/25/98 0000 485.7 1295.3 2043 66.5 49.8 22.1 3.8 *1.5 21.7 36.8

 03/28/98 0000 536.3 1468.9 2034 152.5 89.9 60.6 6.3 2.3 41.6 65.0

 04/01/98 0000 194.6 312.9 461 288.0 64.6 47.5 8.2 *1.3 72.7 21.0

 04/04/98 0000 537.9 1598.2 483 157.2 41.6 24.1 6.5 *1.1 47.9 12.9

 04/08/98 0000 969.3 2801.3 1691 287.6 123.8 87.9 9.0 *1.6 73.1 80.0

 04/11/98 0000 300.4 690.2 2414 414.1 117.9 142.2 15.5 4.2 118.5 46.8

 04/15/98 0000 791.5 2455.3 1205 183.4 137.0 63.5 5.3 *1.6 47.1 108.8

 04/18/98 0000 483.9 1198.8 344 80.0 64.9 20.6 7.5 *1.5 19.3 53.3

 04/22/98 0000 262.6 674.8 433 37.7 28.5 6.1 *2.0 *1.2 6.1 24.9

 04/25/98 0000 1004.4 2978.0 2647 168.1 55.6 51.5 *3.2 *2.0 50.0 25.6

 04/29/98 0000 615.7 1581.6 2086 161.5 103.6 55.8 10.3 6.6 51.8 72.5

 05/02/98 0000 522.7 1411.3 591 178.0 56.9 46.3 7.1 *1.4 56.3 23.2

 05/06/98 0000 897.0 2610.5 5675 184.4 60.7 46.1 10.5 4.1 49.4 31.1

 05/09/98 0000 1227.3 3956.4 2134 105.1 41.3 23.2 6.6 3.0 35.0 20.2

 05/13/98 0000 1298.9 3238.5 4571 216.0 96.9 54.8 9.5 *2.1 61.9 59.8

 05/16/98 0000 2270.6 4455.3 7190 338.8 254.8 84.0 17.2 7.2 109.2 189.3

 05/20/98 0000 1855.4 3924.2 3933 405.2 131.4 114.7 12.1 6.7 113.5 63.4

 05/23/98 0000 1601.4 3685.9 2166 281.9 170.4 65.5 9.9 *2.4 79.7 122.6

 05/27/98 0000 1038.8 2088.7 1262 162.2 152.3 48.9 3.7 *1.8 45.3 125.1

 05/30/98 0000 1057.7 2595.8 1126 151.0 93.1 32.4 *2.4 *1.4 41.4 68.2

 Marine Metallic tracers .

 DATE HOUR NA CL- V NI CU ZN AS SE BR PB

 03/04/98 0000 *19.28 ?-13.2 *1.86 0.25 0.68 7.27 *0.07 0.72 2.48 2.82

 03/07/98 0000 *11.13 ?-10.4 1.80 *0.12 0.35 2.44 *0.06 0.36 1.30 1.91

 03/11/98 0000 *12.81 ?4.0 ?1.63 *0.13 0.66 6.47 *0.07 1.10 2.08 2.33

 03/14/98 0000 *16.62 ?-12.5 *1.49 *0.17 2.00 12.67 0.45 1.12 4.98 2.89

 03/18/98 0000 33.85 ?-6.7 5.23 *0.14 *0.17 1.90 ?0.16 *0.09 1.79 1.07

 03/21/98 0000 *14.27 ?-4.6 *1.76 *0.14 0.23 1.83 *0.07 *0.08 0.54 0.78

 03/25/98 0000 *19.64 ?-11.9 *2.05 *0.14 0.87 6.48 0.91 1.17 3.36 2.61

 03/28/98 0000 576.15 ?1.7 *2.08 *0.14 0.31 3.64 0.43 0.84 8.23 0.97

 04/01/98 0000 *16.76 ?-78.2 *1.88 *0.15 0.30 2.14 0.27 *0.08 1.55 0.65

 04/04/98 0000 *19.60 ?-2.5 ?1.77 *0.13 0.58 6.54 0.59 1.16 1.94 2.26

 04/08/98 0000 203.84 6.10 *0.18 1.93 5.57 0.68 1.03 4.73 1.63

 04/11/98 0000 *20.84 ?-4.1 *1.89 *0.19 1.07 8.86 1.08 1.17 3.23 3.35

 04/15/98 0000 271.13 *2.32 *0.15 0.53 5.74 0.96 1.09 7.83 1.20

 04/18/98 0000 *21.47 ?-7.3 2.62 *0.14 0.69 4.60 0.34 0.80 2.46 2.11

 04/22/98 0000 *15.53 ?-5.3 2.99 0.18 0.77 2.20 0.42 1.18 1.03 0.78

 04/25/98 0000 84.30 *2.77 *0.18 0.87 11.28 1.16 1.13 3.31 3.34

 04/29/98 0000 129.38 ?-3.8 *2.15 *0.16 1.21 12.06 1.46 0.93 4.60 4.94

 05/02/98 0000 *22.47 ?-6.6 *1.99 *0.15 0.52 6.38 0.45 0.86 2.18 2.45

 05/06/98 0000 *30.35 *2.03 *0.17 2.76 8.21 0.60 1.41 2.42 3.22

 05/09/98 0000 *37.99 *2.34 *0.15 1.27 8.76 0.54 2.16 1.75 2.89

 05/13/98 0000 116.09 *2.99 *0.19 1.39 10.42 0.89 1.50 3.37 3.12

 05/16/98 0000 *58.33 24.0 *3.57 *0.23 1.08 17.40 *0.11 3.00 7.39 5.59

 05/20/98 0000 *54.87 *3.28 *0.20 1.17 14.06 0.86 2.19 5.41 2.34

 05/23/98 0000 100.25 31.7 5.80 0.64 0.74 8.67 0.96 1.64 4.63 1.96

 05/27/98 0000 *31.10 20.0 *2.53 *0.16 1.89 10.65 0.42 1.18 4.30 1.96

 05/30/98 0000 *29.18 ?10.5 5.11 *0.14 0.86 5.97 0.74 1.32 4.08 1.63

 *=minimum detectable limit ?= < (2 x uncertainty) #= MASS>PM10; diff<uncertainty

Figure 3-4a. Quarterly Data Report: Site Specific Elements
3-24

GREAT SMOKY MOUNTAINS N.P. MAR 01,1998 - MAY 31,1998

26-OCT-98 IMPROVE PARTICULATE NETWORK

 Fine mass and its major components.

 24-hour concentrations in micrograms/cubic meter

 DATE HOUR PM10 MASS RCMC RCMA NHSO NHNO SOIL OMCN OMH LACN

 03/04/98 0000 9.79 8.19 8.12 9.02 5.31 0.56 0.27 2.14 2.64 0.34

 03/07/98 0000 8.12 6.13 4.04 4.18 1.66 0.06 0.11 1.90 1.73 0.32

 03/11/98 0000 9.24 5.16 4.87 5.40 3.19 0.32 0.31 1.02 1.38 0.31

 03/14/98 0000 #11.41 #11.49 9.98 10.23 4.84 0.59 0.40 4.14 3.97 0.55

 03/18/98 0000 9.07 3.24 3.45 4.04 1.65 0.11 0.14 1.31 1.62 0.23

 03/21/98 0000 3.14 2.67 3.17 1.74 0.09 0.08 0.70 1.09 0.12

 03/25/98 0000 11.70 10.30 8.92 9.22 5.34 0.29 0.34 2.66 2.23 0.49

 03/28/98 0000 18.67 12.03 11.74 11.69 6.06 0.72 0.76 3.03 2.32 0.36

 04/01/98 0000 6.61 4.20 4.61 4.43 1.29 ?-0.03 1.30 1.79 1.60 0.18

 04/04/98 0000 11.99 8.82 9.31 10.05 6.59 0.25 0.72 1.61 1.90 0.35

 04/08/98 0000 22.43 16.25 17.43 18.55 11.56 1.30 3.50 3.70 0.46

 04/11/98 0000 14.27 7.45 7.35 7.39 2.85 0.92 2.05 1.94 1.76 0.42

 04/15/98 0000 21.20 16.49 15.63 15.40 10.13 0.69 3.49 2.44 0.49

 04/18/98 0000 15.20 9.75 8.29 8.89 4.95 0.23 0.30 2.47 2.53 0.47

 04/22/98 0000 10.56 4.23 4.28 4.66 2.78 0.14 0.13 1.08 1.29 0.24

 04/25/98 0000 20.67 17.32 16.55 18.38 12.28 0.75 2.77 3.57 0.51

 04/29/98 0000 22.90 14.66 11.65 12.72 6.52 0.36 0.87 3.03 3.03 0.79

 05/02/98 0000 11.83 11.71 8.86 9.93 5.82 0.38 0.86 1.81 2.34 0.31

 05/06/98 0000 19.09 15.34 15.14 16.44 10.77 0.87 2.87 3.36 0.55

 05/09/98 0000 29.64 23.09 19.92 21.41 16.32 0.41 2.57 3.28 0.55

 05/13/98 0000 28.32 21.81 20.33 22.78 13.36 0.81 5.08 6.73 0.70

 05/16/98 0000 56.61 44.96 35.31 39.86 18.38 0.83 1.59 13.71 15.91 1.30

 05/20/98 0000 41.57 31.10 27.35 32.53 16.19 1.90 8.21 12.02 0.90

 05/23/98 0000 41.11 29.97 25.92 28.16 15.20 0.38 1.24 8.33 9.35 0.72

 05/27/98 0000 22.44 18.25 15.66 17.72 8.62 0.45 0.61 5.64 7.10 0.58

 05/30/98 0000 30.18 26.19 16.60 18.31 10.71 0.18 0.54 4.60 5.62 0.62

 Fine mass and its major components.

 24-hour concentrations in micrograms/cubic meter and percent of fine mass.

 DATE HOUR MASS RCMC% RCMA% NHSO% NHNO% SOIL% OMCN% OMH% LACN%

 03/04/98 0000 8.19 99% 110% 65% 7% 3% 26% 32% 4%

 03/07/98 0000 6.13 66% 68% 27% 1% 2% 31% 28% 5%

 03/11/98 0000 5.16 94% 105% 62% 6% 6% 20% 27% 6%

 03/14/98 0000 #11.49 87% 89% 42% 5% 3% 36% 35% 5%

 03/18/98 0000 3.24 106% 125% 51% 4% 4% 40% 50% 7%

 03/21/98 0000 3.14 85% 101% 55% 3% 3% 22% 35% 4%

 03/25/98 0000 10.30 87% 90% 52% 3% 3% 26% 22% 5%

 03/28/98 0000 12.03 98% 97% 50% 6% 6% 25% 19% 3%

 04/01/98 0000 4.20 110% 105% 31% ? -1% 31% 43% 38% 4%

 04/04/98 0000 8.82 106% 114% 75% 3% 8% 18% 22% 4%

 04/08/98 0000 16.25 107% 114% 71% 8% 22% 23% 3%

 04/11/98 0000 7.45 99% 99% 38% 12% 27% 26% 24% 6%

 04/15/98 0000 16.49 95% 93% 61% 4% 21% 15% 3%

 04/18/98 0000 9.75 85% 91% 51% 2% 3% 25% 26% 5%

 04/22/98 0000 4.23 101% 110% 66% 3% 3% 26% 31% 6%

 04/25/98 0000 17.32 96% 106% 71% 4% 16% 21% 3%

 04/29/98 0000 14.66 79% 87% 44% 2% 6% 21% 21% 5%

 05/02/98 0000 11.71 76% 85% 50% 3% 7% 15% 20% 3%

 05/06/98 0000 15.34 99% 107% 70% 6% 19% 22% 4%

 05/09/98 0000 23.09 86% 93% 71% 2% 11% 14% 2%

 05/13/98 0000 21.81 93% 104% 61% 4% 23% 31% 3%

 05/16/98 0000 44.96 79% 89% 41% 2% 4% 30% 35% 3%

 05/20/98 0000 31.10 88% 105% 52% 6% 26% 39% 3%

 05/23/98 0000 29.97 86% 94% 51% 1% 4% 28% 31% 2%

 05/27/98 0000 18.25 86% 97% 47% 2% 3% 31% 39% 3%

 05/30/98 0000 26.19 63% 70% 41% 1% 2% 18% 21% 2%

 *=minimum detectable limit ?= < (2 x uncertainty) #= MASS>PM10; diff<uncertainty

Figure 3-4b. Quarterly Data Report: Site Specific Mass and Major Components
3-25

GREAT SMOKY MOUNTAINS N.P. MAR 01,1998 - MAY 31,1998

26-OCT-98 IMPROVE PARTICULATE NETWORK

 Distribution of Concentrations in nanograms/cubic meter

 % of cases Arithmetic Maximum

 Cases Significant Mean Minimum Median Maximum occurs

 H 26 100% 768.07 184.75 559.91 2270.65 05/16/98

 S 26 100% 1903.02 312.88 1525.29 4455.30 05/16/98

 SO2 26 100% 2089.53 344.10 1862.80 7190.30 05/16/98

 SI 26 100% 166.65 24.68 159.32 414.12 04/11/98

 K 26 100% 82.01 11.50 62.69 254.83 05/16/98

 CA 26 100% 46.21 3.35 46.20 142.22 04/11/98

 TI 26 69% 6.62 1.39 6.43 17.20 05/16/98

 MN 26 42% 2.53? 0.85 1.95? 7.16 05/16/98

 FE 26 100% 47.42 2.33 46.21 118.47 04/11/98

 KNON 26 100% 53.56 10.10 34.66 189.32 05/16/98

 NA 26 30% 75.66? 11.13 29.76? 576.15 03/28/98

 CL- 19 15% -3.96? -78.20 -5.30? 31.70 05/23/98

 V 26 26% 2.77? 1.49 2.24? 6.10 04/08/98

 NI 26 11% 0.18? 0.12 0.16? 0.64 05/23/98

 CU 26 96% 0.96 0.17 0.81 2.76 05/06/98

 ZN 26 100% 7.39 1.83 6.51 17.40 05/16/98

 AS 26 76% 0.57 0.06 0.50 1.46 04/29/98

 SE 26 88% 1.13 0.08 1.12 3.00 05/16/98

 BR 26 100% 3.50 0.54 3.27 8.23 03/28/98

 PB 26 100% 2.34 0.65 2.30 5.59 05/16/98

 Distribution of Concentrations in micrograms/cubic meter

 % of cases Arithmetic Maximum

 Cases Significant Mean Minimum Median Maximum occurs

 PM10 25 100% 20.18 6.61 15.20 56.61 05/16/98

 MASS 26 100% 14.67 3.14 11.87 44.96 05/16/98

 RCMC 26 100% 12.85 2.67 10.81 35.31 05/16/98

 RCMA 26 100% 14.02 3.17 10.96 39.86 05/16/98

 NHSO 26 100% 7.85 1.29 6.29 18.38 05/16/98

 NHNO 19 94% 0.36 -0.03 0.29 0.92 04/11/98

 SOIL 26 100% 0.74 0.08 0.71 2.05 04/11/98

 OMCN 26 100% 3.52 0.70 2.72 13.71 05/16/98

 OMH 26 100% 4.02 1.09 2.59 15.91 05/16/98

 LACN 26 100% 0.49 0.12 0.48 1.30 05/16/98

 Distribution of Concentrations in micrograms/cubic meter and percent of fine mass

 % of cases Arithmetic Maximum

 Cases Significant Mean Minimum Median Maximum occurs

 MASS 26 100% 14.67 3.14 11.87 44.96 05/16/98

 RCMC% 26 100% 91% 63% 91% 110% 04/01/98

 RCMA% 26 100% 98% 68% 98% 125% 03/18/98

 NHSO% 26 100% 54% 27% 51% 75% 04/04/98

 NHNO% 26 96% 3% 0% 2% 12% 04/11/98

 SOIL% 26 100% 6% 2% 4% 31% 04/01/98

 OMCN% 26 100% 25% 11% 25% 43% 04/01/98

 OMH% 26 100% 28% 14% 26% 50% 03/18/98

 LACN% 26 100% 4% 2% 4% 7% 03/18/98

 A significant value is greater than 2 times the uncertainty of that value.

 ?=the percentage of significant values is less than 65%

Figure 3-4c. Quarterly Data Report: Site Specific Means and Distributions
3-26

SITE SAMDAT JULIAN STRTIM ETA FLOWA ETB FLOWB ETC FLOWC ETD FLOWD MF MF_ERR

ACAD1 03 01 1997 59 0000 -99.00 -99.0 -99.00 -99.0 -99.00 -99.0 -99.00 -99.0 -99.00 -99.00...

ACAD1 03 05 1997 63 0000 24.00 22.0 24.00 22.0 24.00 22.0 24.00 22.0 6281.60 245.80...

ACAD1 03 08 1997 66 0000 24.00 22.2 24.00 22.2 24.00 22.2 24.00 22.2 4817.30 213.00...

ACAD1 03 12 1997 70 0000 24.00 22.0 24.00 22.0 24.00 22.0 24.00 22.0 5618.70 230.90...

ACAD1 03 15 1997 73 0000 24.00 22.0 24.00 22.0 24.00 22.0 24.00 22.0 2746.20 178.00...

 MF_ERR MF_MDL MF_STAT MT MT_ERR MT_MDL MT_STA

 ... -99.00 -99.00 NA -99.00 -99.00 -99.00 NA ...

 ... 245.80 315.70 NM 16455.30 528.50 377.40 NM ...

 ... 213.00 312.80 NM 6558.60 275.50 385.80 NM ...

 ... 230.90 315.70 NM 10924.30 385.50 406.10 NM ...

 ... 178.00 315.70 NM 8373.00 320.10 396.80 NM ...

A value of -99.00 indicates an invalid value.

All species amounts, errors, and minimum detectable limits are in nanograms per cubic meter.

Start times are in military hours.

Sample durations are in decimal hours.

Flow rate is in liters per minute (ambient).

SPECIES STATUS CODES:

NM = Normal

QU = Questionable; Undetermined

QD = Questionable Data

AA = Organic Artifact Corrected

AP = Possible Organic Artifact (No correction performed)

NA = No Analysis Available for this Species

NOTE: From 9/90 through 2/92 we received some Teflon filters with an organic contamination. This artifact influenced only the Hydrogen and

Fine Mass measurements in less than 7% of the samples (marked AA). All other measurements of Hydrogen and Fine Mass during this period are

marked with a status AP.

SPECIES CODES:

MF = Fine Mass (UCD)

MT = PM-10 Mass (UCD)

H = Hydrogen (UCD)

BSO4 = Sulfate on Nylon (RTI, GGC)

NO2- = Nitrite (RTI, GGC)

NO3- = Nitrate (RTI, GGC)

CL- = Chloride (RTI, GGC)

SO2 = Sulfur Dioxide (DRI)

O1 = Organic carbon, ≤120 °C (DRI)

O2 = Organic carbon, 120 °C - 250 °C (DRI)

O3 = Organic carbon, 250 °C - 450 °C (DRI)

O4 = Organic carbon, 450 °C - 550 °C (DRI)

OP = Pyrolized organic, 550 °C, 2% O2, reflectance ≤ initial (DRI)

E1 = Elemental carbon + pyrolized organic, 550 °C, 2% O2 (DRI)

E2 = Elemental carbon, 550 °C - 700 °C, 2% O2 (DRI)

E3 = Elemental carbon, 700 °C - 800 °C, 2% O2 (DRI)

All other species are elemental values from UCD Elemental Analysis.

Figure 3-5. Standard ASCII File Format IMPROVE Protocol Aerosol Data.
3-27

3.8 SUPPLEMENTAL ANALYSIS INCLUDING COMPOSITE VARIABLES

At most continental sites, fine aerosol species are classified into five major types: sulfates,

nitrates, organic mass, elemental and light-absorbing carbon, and soil. Methods for

apportionment of measured mass to the various aerosol species are detailed in Malm et al. (1994).

Major aerosol types are composites of the elements and ions measured by IMPROVE samplers.

Concentrations or masses are calculated from the masses of the measured elements and ions

according to their presumed or probable composition as summarized below and in Table 3-3 and

Table 3-4. The convention used to denote the mass concentration of a measured element, ion, or

species is enclosing its symbol in brackets ([ ]).

Sulfates

In the West, most sulfur is in the form of ammonium sulfate. In the East, or other

environments where ammonia can be limited, acidic species, such as ammonium bisulfate and

sulfuric acid, are common. However, for a first approximation, all elemental sulfur and sulfate ion

is interpreted as being in the form of ammonium sulfate, and ammonium sulfate concentrations are

estimated by multiplying elemental sulfur concentrations by 4.125, or sulfate ion concentration by

1.375. For simplicity, ammonium sulfate is referred to as sulfate.

At sites where NH4+, NO3-, and SO4= are measured, but not H+, it is possible to calculate

the dry weight of sulfate, even is it not fully neutralized. The assumption is that there is an ionic

balance between H+,NH4+, NO3-, and SO4=. The concentration for actual sulfate is given by:

[sulfate] = 1.021 [SO4=] + 0.944 [NH4+] - 0.274 [NO3-] (3-3)

Ammonium ion measurements have been made at three IMPROVE sites in the Appalachian

mountains, Shenandoah National Park, Dolly Sods Wilderness, and Great Smoky Mountains

National Park. These sites have the highest sulfur concentrations in the IMPROVE network and

probably have the most acidic aerosol in the network. For one year of measurements starting in

June 1997 at these three sites, the actual sulfate calculated by Equation 3-3 averages 10% less

than the calculation assuming ammonium sulfate. For the average site, the ammonium sulfate

assumption will probably be only slightly larger than the actual sulfate.

Nitrates

Particulate nitrate is assumed to be present as fully neutralized ammonium nitrate

(NH4NO3). (HNO3 is a gas.) The concentration of ammonium nitrate is 1.29 times the

concentration of nitrate ion and is referred to as nitrate.

Organic Mass

Organic mass (by carbon) concentrations (organics, OMC) is estimated by:

[OMC] = 1.4 [OC] (3-4)

where OC is the total organic carbon defined by equation 3-1. The factor 1.4 assumes that

organic mass contains a constant 71% carbon by weight (Watson et al., 1988). The actual factor

depends on the compounds present. Organic carbon from industrial emissions may well have a

different factor than organic carbon from biomass combustion.
3-28

Organic mass can also be estimated from hydrogen by:

assuming all sulfur is ammonium sulfate and there is no hydrogen from nitrate. The factor of

13.75 gives excellent agreement when the organic mass is primarily from wood smoke. At sites in

the eastern United States, a factor that is 20% lower (11) gives a better fit with organic carbon

(assuming a carbon factor of 1.4).

A more accurate calculation that accounts for acidity is possible if NH4+, NO3-, and SO4= are all

measured. However, since nitrate volatilizes from Teflon during sampling, the equation cannot

account for the hydrogen in (NH4)NO3.

Elemental Carbon/Light Absorbing Carbon

The total elemental carbon is given by Equation 3-2.

Soil

Soil mass concentration is estimated by summing the elements predominantly associated

with soil, plus oxygen for the normal oxides (Al2O3, SiO2, CaO, K2O, FeO, Fe2O3, TiO2), plus a

correction for other compounds such as MgO, Na2O, water, and carbonate. There are two

weaknesses in this methodology. (1) Some of these elements, such as Fe, may be associated with

industrial emissions rather than suspended soil. This problem is more important in urban sampling

than in remote sampling. It can be important in some remote sites, if there are nearby iron

smelters. (2) For both urban and rural sites, K may be associated with smoke as well as soil. The

particle diameters of this smoke K is always must less than 2.5 μm. One possible approach is to

estimate the fraction of K as smoke and subtract this from the soil estimate. In the nomenclature

of the IMPROVE network, this nonsoil potassium is called KNON. The approach is to determine

the K to Fe ratio for typical soils and use this factor in calculating the PM2.5 soil concentration.

Based on measurements made at mostly western sites between 1979 and 1986 with the stacked

filter sampler (which collects particles greater than 2.5 μm on a separate filter), the K/Fe ratio for

coarse particles averages 0.6. A final equation for fine soil is:

[SOIL] = 2.2[Al] + 2.49[Si] + 1.63[Ca] + 2.42[Fe]+ 1.94[Ti] (3-6)

The equation for nonsoil potassium is:

[KNON] = [K] - 0.6 * [Fe] (3-7)

Components of these factors were confirmed in comparisons of local resuspended soils and

ambient aerosols in the western United States (Cahill, et al., 1981; Pitchford et al., 1981).

[OMH] = 13.75 ( [H] - [S] / 4) (3-5)
3-29

Na (Marine)

Sodium is an important factor in the PM2.5 mass only at marine sites. If this is assumed to

be NaCl, the total mass is 2.5 times the Na concentration. An alternative calculation would be to

use 1.6 times the Cl elemental or ionic concentration. In a highly reactive atmosphere some of the

Cl may be lost before reaching the sampler or during sampling.

Reconstructed Fine Mass

The sum of the above seven composite variables should provide a reasonable estimate of

the ambient dry PM2.5 mass concentration in the atmosphere. The inclusion of nitrate in the

calculation is optional. If the concern is the reconstructed dry mass concentration in the

atmosphere, then nitrate should be included. However, if the concern is comparison with the

gravimetric mass on the Teflon filter, then it is recommended excluding nitrate. The reason is that

a variable fraction of nitrate will volatilize from the Teflon filters during sampling. If all of the

water on the particles were to be removed before gravimetric analysis, the gravimetric mass

would be between the two calculations. The equations for reconstructed without nitrate (RCMC)

and with nitrate (RCFM) are:

[RCMC] = 4.125 [S] + 1.4 [OC] + [EC] + [SOIL] + 1.4 [KNON] + 2.5 [Na] (3-8)

[RCFM] = [RCMC] + 1.29 [NO3-] (3-9)

Note that the sum of [SOIL] and 1.4 [KNON] includes the measured K as K2O independent of

the validity of the assumed K/Fe ratio. At most sites in the IMPROVE network, nitrate is a small

component of the fine mass. Therefore, the RCFM is only slightly larger than RCMC.

Coarse Mass

Coarse mass (CM) is estimated gravimetrically by subtracting fine mass (PM2.5)

concentration from total aerosol mass (PM10) concentration:

[CM] = [PM10] - [PM2.5] (3-10)

In the IMPROVE Program, additional chemical analysis is not carried out on the coarse fraction.

However, it is known that in rural or remote areas of the country the primary constituent of

coarse mass is naturally occurring wind-blown dust along the some vegetative material (Noll,

1991).
3-30

3.9 QUALITY ASSURANCE

Quality assurance of aerosol monitoring data consists of comparing operational flow rates

during annual field audits and Level-1 validation, and determining the concentration and precision

of measured variables during Level-2 validation.

3.9.1 Instrument Audits

Quality assurance field audits are performed annually by field specialists and include the

determination of system flow rate measurement error and verification of the performance of the

aerosol sampler and routine filter sampling schedules.

Flow Rate Audit Procedures

All flow rates and air volumes in IMPROVE are based on local conditions and are not

corrected for standard temperature and pressure. At a flow rate of 22.8 lpm, the IMPROVE

cyclone has a 50% efficiency for 2.5 μm aerodynamic diameter particles. At a flow rate of 25 lpm

(+10%) the cut point is 1.74 μm. At a flow rate of 20.5 lpm (-10%) the cut point is 3.26 μm.

Operational flow rates are calculated from the sampler's pressure transducers, as well as

the temperature of the air and the elevation of the site. The PM2.5 modules have are two

transducers, one measuring the pressure drop across the cyclone and the other measuring the

pressure in front of the critical orifice. The PM10 module has only the transducer in front of the

critical orifice. Each transducer has a specific calibration equation determined by the audit

procedures. Audit flow rates are determined by inserting a calibrated orifice in the inlet stack and

measuring the pressure drop using an audit transducer. The audit device is calibrated at the

central laboratory using an NIST-traceable spirometer.

Flow audits may be conducted by personnel from the central laboratory or by the site

operator. This is normally performed during one of the non-sampling days. Equipment needed

for a flow audit includes:

• a removable magnetic card with appropriate programs and site-specific

information,

• four filter cartridges, with each cartridge having four filters with different

pressure drops,

• one calibrated audit device for PM2.5 modules and one for the PM10 module,

• a log sheet and an instruction sheet

The initial step is to remove all existing filter cartridges and replace the normal removable

magnetic card with the audit magnetic card. The appropriate cartridge is installed in the module

and the pressure values of both system transducers for each of the four filters are read. These are

recorded on the magnetic card and on the log sheet. The audit device is inserted in the inlet and

the pressure values for the audit transducer is similarly recorded. The program then calculates the

calibration equations, checks for consistency , and compares with the previous equations. If the

nominal flow rate differs from the desired nominal flow rate, the critical orifice needs adjustment.

The operator will make the necessary adjustment, with assistance by the processor. The flow
3-31

audit will then be repeated for this module. The entire process will be repeated for the remaining

modules.

The normal filter cartridges will then be returned to the sampler and the standard magnetic

card installed. The program will be instructed to use the revised calibration equations. After

audits performed by the site operator, the equipment will be returned to the central laboratory.

When received by the central laboratory, the calibration of the audit device using the spirometer

will be repeated.

Annual calibration and flow rate audit procedures are described further in the Crocker

Nuclear Laboratory SOP 176, Calibration, Programming, and Site Documentation and TI201A

IMPROVE Aerosol Sampler Operations Manual.

3.9.2 Concentration and Precision of Measured Variables

The self consistency and overall quality of the aerosol measurements are assured by

redundancy and intercomparisons between independently measured species. A detailed

description of validation and quality assurance procedures are available (Malm et al., 1994; Sisler

et al., 1993; and Eldred et al., 1988). In the most general sense, validation is a matter of

comparing chemically-related species that have been measured by different module filters.

Fortunately, the design of the IMPROVE sampler allows for redundancy between certain Module

A measurements and Module B and C measurements of the ions and carbons enabling quality

control checks (Sisler, et al., 1996). IMPROVE network quality assurance includes comparisons

of the following:

• PIXE and XRF measurements

• Sulfur by PIXE on Teflon and Sulfate by Ion Chromatography on nylon

• Organic mass from carbon (OMC) and organic mass from hydrogen (OMH)

• Light-absorbing carbon (LAC) and babs

• Fine mass with reconstructed mass (from Module A) and fine mass with reconstructed

mass (from Module A plus C)

IMPROVE procedures for evaluating the precision of measured species follow.

The general equation for the concentration of a given variable is

c =

A B

V

−

 (3-11)

where A is the measured mass of the variable (i.e. chemical species), 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. Artifact B may be produced by contamination in the
3-32

filter material, in handling and analysis, and by adsorption of gas during collection. The artifact is

negligible for all Teflon measurements. It is determined from designated field blanks for ions and

from secondary filters for carbon.

Precision in each concentration is included in the database. 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 a 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 organics, the uncertainties are less than would be

estimated from the individual fractions. This will be discussed in the section on 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 X-Ray Fluorescence (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:

[ ] [ ] [ ]

2 2

v

2

a

a

2

stat (c) = f c + f c +

V

+

V

s

s s





















 (3-12)

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 minimum detectable limits (mdl), the precision increases to 50%.

Table 3-5 separates the relative precisions of key measured variables into three groups.

The relative precision 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%.
3-33

Table 3-5 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 7% 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 average minimum detectable limits (mdl) are provided with each concentration in the

database. A concentration is assumed to be statistically significant only if it 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 minimum detectable limit corresponds to twice

the analytical precision determined by controls. For PIXE, XRF, and PESA, the minimum

detectable limit is based on the background under the peaks in the spectrum and is calculated

separately for each case. The assumption for all elements except arsenic is that there is no

interference from other elements. Because the measurement for arsenic requires subtracting the

value for lead, the mdl for arsenic depends on the lead concentration and is generally larger than

the value estimated from the background. When calculating averages, if the value is below the

minimum detectable limit, one-half of the minimum detectable limit is used as the concentration

and the precision in the concentration. In all cases, the relative precisions are around 50% at the

mdl.

The minimum detectable limits of trace elements heavier than iron changed in June 1992

with the addition of a high-sensitivity XRF systemThe minimum detection limits for iron through

lead decreased by a factor of 10. The minimum detectable limits of standard network samples for

elements measured by PIXE and XRF are given in Table 3-6. 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 3-7 separates these into four ranges. A significant change for

aluminum occurred with samples beginning February 1993. Because of detector problems,

aluminum, which is on the shoulder of the spike, was often not detected. Before this date,

aluminum was observed on 65% of all samples; afterward it was found on almost every sample.

Sodium, chlorine, and chloride ion were observed in significant amounts only at sites with marine

influences.
3-34

Table 3-6 Minimum Detectable Limits of Elements in ng/m3

Dates Na Mg Al Si P S Cl K Ca Ti V Cr Mn

before 5/92 8.70 2.90 1.80 1.40 1.30 1.20 1.30 0.83 0.64 0.57 0.50 0.41 0.39

after 6/92 13.00 4.80 3.00 2.20 1.90 1.90 2.00 1.20 0.90 0.81 0.69 0.57 0.52

Fe Ni Cu Zn Ga Se Br Rb Sr Zr Pb

before 5/92 0.34 0.24 0.24 0.21 0.20 0.22 0.25 0.37 0.42 0.65 0.57

after 5/92 0.11 0.05 0.05 0.05 0.03 0.03 0.03 0.06 0.07 0.11 0.06

 Table 3-7. Fraction of Cases with Statistically Significant Concentrations

Range Before 6/1/92 After 6/1/92

90% to 100% PM2.5, PM10, H, S, Si, K, Ca, Ti, Fe,

Zn, Br, SO4

=

, NO3

-

, SO2, OP, E1

PM2.5, PM10, H, S, 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

<40% P, V, Ni, Se, As, Rb, Sr, Zr, O1, E3 P, V, Ni, Zr, O1, E3
3-35

3.9.3 Concentration and Precision of Composite Variables

The composite variables listed in Table 3-4 can be derived from the measured variables

based on reasonable assumptions.

The uncertainty in all composites except for the four involving the quartz measurements is

calculated by quadratically adding the uncertainties of the constituent terms times the appropriate

multiplicative constant. For example, the uncertainty for soil would be:

[ ] [ ] [ ] [ ] [ ] [ ]

2 2 2 2 2 2

s(SOIL) = 2.20 s(Al) + 2.49 s(Si) + 1.63 s(Ca) + 2.42 s(Fe) + 1.94 s(Ti) (3-13)

Because temperature separation plays a much larger role for carbon fractions than for

composites, and because the fractions are not independent, the above calculation method cannot

be followed for OC, OMC, LAC, and TC. For these fractions the following equations for

24-hour samples are recommended:

s(OC) = (120 ) + (0.05*OC )

2 2

s(OMC) = (168 ) + (0.05* OMC )

2 2

s(LAC) = (34 ) + (0.07* LAC )

2 2

s(TC) = (133 ) + (0.05* TC )

2 2

 (3-14)

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 two.

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 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

-

.
3-36

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, multiplying the total carbon by

1.4, which assumes that carbon accounts for 71% of the organic mass, is recommended. 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. It is also assumed that no significant

hydrogen from nitrate remains. If one assumes that the sulfate is fully neutralized ammonium

sulfate, one can estimate the organic concentration by subtracting the hydrogen from sulfate and

multiplying the difference by a constant representing the fraction of hydrogen. (A constant of

13.75 is suggested. 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, 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 summer of 1996 at 30 sites in

the western United States (excluding 6 with elevated nitrate or marine influences), the correlation

coefficient (r2) between OMH and OMC was 0.96 and the slope of the best fitting line was 0.98.

The main advantage of using OMH at these sites is that its precision is better than that for OMC

during periods of low organics 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 organics.

The relationship under acidic conditions is considerably improved when ammonium ion is also

available. However, there is still a problem with precision.

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 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. The test for this effect is included in the acceptance procedures. The

condition has not recurred.

Elemental or Light-Absorbing Carbon from Module C (LAC)

This is the sum of elemental carbon fractions. The pyrolized fraction is subtracted.

Preliminary analyses indicate that some of the OC4 fraction may absorb light and that OP may

overestimate the pyrolytic mass.
3-37

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. This has

been eliminated from the calculation and Fe has been substituted 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 in 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 ration of K/Fe of 0.6 measured on coarse samples (2.5 μm 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 (i.e., 0.5 μm), 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)

The reconstructed mass is the sum of sulfate (assuming ammonium sulfate), soil, and

sodium from the Teflon filter (Module A) and organic and elemental carbon from the quartz filter

(Module C). The nitrate from the nylon filter (module B) is not included. The reason is the

RCMC is generally used as a comparison with the gravimetric mass measured on the Teflon filter.

Because the Teflon filter loses a large fraction of the particulate nitrate by volatilization during

sampling, it would be preferred not to include the nitrate from the nylon filter in the

reconstruction. At most sites, the nitrate mass is a few percent of 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.
3-38

3.10 DATA ANALYSIS AND INTERPRETATION

Aerosol data can be used to describe the spatial and temporal variation of visibility as

measured by the chemical composition of the visibility-degrading aerosol. Data can also be used

for source apportionment and as background information for New Source Review and PSD

modeling applications. Aerosol data are also used to further explore the relationship between

optical extinction (absorption and scattering) and various aerosol species. In-turn, reconstructed

extinction data can be used to depict visibility changes for NSR and PSD modeling applications.

Several application examples and analysis considerations are presented in the following

subsections.

3.10.1 Calculating Reconstructed Aerosol Extinction

Atmospheric extinction can be estimated from the mass of various particulate species

collected with the IMPROVE samplers if the scattering cross section of each species is known,

and if the hourly ambient relative humidity during sampling is also known. The equations used to

determine reconstructed aerosol extinction follow IMPROVE Program protocol and are outlined

below.

Species that contribute to atmospheric extinction are classified as:

• Sulfates

• Nitrates

• Organics

• Soil

• Coarse Mass

• Particle Absorption (babs)

• Atmospheric Rayleigh Scattering (bRay)

In general, the higher the relative humidity (RH) the greater the scattering of soluble aerosols.

The relationship between RH and scattering efficiency for ammonium sulfate aerosols with a mass

mean diameter of 0.3 μm and a geometric size distribution of 1.5 is shown in Figure 3-6. This

function, referred to as f(RH), is given by:

f(RH) = bscat (RH)/ bscat (0%) (3-15)

where bscat(0%) and bscat(RH) are the dry and wet scattering, respectively. Ammonium sulfate and

ammonium nitrate mass are associated with this function.
3-39

An equation used by the IMPROVE Program to estimate reconstruct aerosol extinction is:

ext

abs

b = (3) f(RH) [Sulfate]

+ (3) f(RH)[Nitrate]

+ (4) [OMC, Organic Mass Carbon]

+ (1) [Soil]

+ (0.6) [CM, Coarse Mass]

+ b

 (3-16)

where the first 5 components represent the light scattering by aerosol species, babs represents the

coefficient of light absorption for fine particles, and bRay represents the light scattered by

molecules of gas in the natural atmosphere which varies with atmospheric pressure and is a

site-specific measurement based on altitude. Brackets indicate the mass concentration of the

aerosol species or element. Three (3) m2/g is the dry scattering efficiency of sulfates and nitrates,

four (4) m2/g is the dry scattering efficiency of organics, and one (1) m2/g and 0.6 m

2

/g are the

respective scattering efficiencies for soil and coarse mass (Sisler, 1996).

Caution should be taken when comparing reconstructed extinction with measured

extinction from optical transmissometer measurements (Section 4.1). Reconstructed extinction is

typically 70% - 80% of the measured extinction. The following differences/similarities are

considered:

• Data collection. Reconstructed extinction measurements represent 24-hour samples

collected twice per week. Transmissometer extinction estimates represent continuous

measurements summarized as hourly means, 24 hours per day, 7 days per week.

• Point versus path measurements. Reconstructed extinction represents an indirect

measure of extinction at one point. The transmissometer directly measures the

irradiance of light (which calculated gives a direct measure of extinction) over a finite

atmospheric path.

• Relative humidity (RH) cutoff. Daily average reconstructed measurements are flagged

as invalid when the daily average RH is greater than 98%. Hourly average

transmissometer measurements are flagged invalid when the hourly average RH is

greater than 90%. These flagging methods often result in data sets that do not reflect

the same period of time, or do not properly interpret short-term meteorological

conditions.
3-40

 Figure 3-6. The Relationship Between Scattering Efficiency and Relative Humidity

3.10.2 Source-Type Tracer Analysis

Tracer analysis is another analysis approach that uses aerosol data to identify source types

or individual sources. For example, the presence of arsenic is a good indicator of copper smelter

emissions. Table 3-7 summarizes the common source types of a number of measured trace

elements by abundances in percent mass (Chow, 1995). Tracer analysis can also be used to

estimate source contributions and to identify general transport patterns.
3-41

Table 3-8

Common Source Types of Measured Trace Elements (Chow, 1995)
3-42

3.11 AEROSOL MONITORING STANDARD OPERATING PROCEDURES AND

TECHNICAL INSTRUCTIONS

The Crocker Nuclear Laboratory document entitled IMPROVE Particulate Monitoring

Network Standard Operating Procedures is available as a pdf file on

http://www.nature.nps.gov/ard/vis/sop/index.html. This includes the following aerosol-related

Standard Operating Procedures and Technical Instructions:

Document Number Title

SOP 101 Procurement and Acceptance Testing

TI 101A Filter Procurement and Acceptance Testing

TI 101B Sampler Construction and Testing

TI 101C Filter Cassette Construction

SOP 126 Site Selection

SOP 151 Installation of Samplers

TI 151A Installation of Controller Module

SOP 176 Calibration, Programming, and Site Documentation

TI 176A Calibration of Audit Devices Using Spirometer

TI 176B Final Flow Rate Audit Calculations

TI 176C Flow Rate Audits and Adjustment

SOP 201 Sampler Maintenance by Site Operators

TI 201A IMPROVE Aerosol Sampler Operations Manual

TI 201B Forms for Flow Audits by Site Operators

SOP 226 Annual Site Maintenance

TI 226A Sampler Wiring Diagrams

SOP 251 Sample Handling

SOP 276 Optical Absorption Analysis

SOP 301 X-Ray Fluorescence Analysis

SOP 326 PIXE and PESA Analysis

SOP 351 Data Processing and Quality Assurance

SOP 376 Data Archiving and Reporting
4-1

4.0 OPTICAL MONITORING

As an example of an existing visibility-related optical monitoring program, this section

describes IMPROVE optical monitoring and data management techniques. References made to

manufacturers or trade names are not intended to constitute EPA endorsement or recommendations

for use. New or improved instruments, instrument upgrades, and methods of monitoring are

continually being developed.

Optical monitoring provides a quantitative measure of ambient light extinction (light

attenuation per unit distance) or its components to represent visibility conditions. IMPROVE

protocols collect continuous measures of b and/or b using ambient long-path transmissometers ext scat

and/or nephelometers respectively. A tabular summary of optical instrument specifications are

provided in Table 4-1. Water vapor in the air can affect visibility, therefore IMPROVE protocols

state that temperature and relative humidity sensors must be collocated with the chosen optical

instrument.

Sections 4.1 and 4.2 describe the measurement criteria, instrumentation, installation and site

documentation, routine operations, data collection, reduction and validation, reporting and archive,

quality assurance, and analysis and interpretation required for transmissometer and nephelometer

monitoring respectively. Operation manuals and manufacturer's specifications are provided in

Appendix B.

4.1 TRANSMISSOMETER

4.1.1 Measurement Criteria and Instrumentation

Transmissometers directly measure the irradiance of a light source after the light has traveled

over a finite atmospheric path. The transmittance of the path is calculated by dividing the measured

irradiance at the end of the path with the calibrated initial intensity of the light source. Using

Bouger's law, the average extinction of the path is calculated from the transmittance and length of

the path. It is attributed to the average concentration of all atmospheric gases and ambient aerosols

along the path. Transmissometers make a completely ambient measurement of bext without perturbing

or selectively sampling atmospheric aerosols or gases.

Several measurement criteria cautions should be considered. Transmissometers require path

lengths of a few kilometers to achieve the necessary sensitivity to resolve extinctions near the

Rayleigh limit. In areas with non-uniform distribution of aerosols, comparison of measured extinction

and reconstructed extinction from concurrent particulate samples can often be misleading. Extinction

measurements from transmissometers also are affected by any meteorological or optical interferences

present along the path which are independent from the ambient aerosol. An additional concern for

transmissometers is the lack of an absolute calibration standard. Uncertainty measurements

associated with these measurement cautions are presented in Section 4.1.8.
Table 4-1

IMPROVE Protocol Monitoring

Optical Instrument Specifications

Parameter Instrument Sample Frequency System Accuracy System Precision Resolution Range Sensor Specifications Traceability Probe Placement Calibration Reporting

Interval

Atmospheric Optec LPV-2 Long a. 10-minute average of Hourly ! No absolute calibration Path dependent: 0.001 km 0.001 km to ! 550 nm ±2 nm center wavelength and 10 nm N/A ! 1 km to 10 km ! No absolute

Extinction Range 1-minute, integrated standard ±0.003 km for 1.0 km ±1 nm bandwidth separation between calibration

Coefficient Transmissometer samples taken once ! Accuracy inferred from 10 km working ! Output analog (see system transmitter and ! System with

bext an hour between 3 comparison to path and 0.010 - b ; 0 V to 10 V, 0.01 V = 0.001 km accuracy receiver depending operational and

(at 550 nm) and 13 minutes after (b + b ) and nominal extinction - VR; 0 V to 10 V, 0.01 V = 1 km statement) on average visual air reference lamps

the hour. reconstructed b from value or ±3% - raw counts; 0 V to 10 V quality calibrated at 300 m

b. Hourly average of integrated samples terrain drop offs to ! Calibrations

1-minute integrated ! Output serial (RS232) 8 bits, 1 stop bit, no parity, avoid surface performed

samples. 9600 baud default heating-based annually, prior to

scat abs

ext

aerosol measurements transmission - Std. Dev. (N-1 samples) of 1-minute ! Ends placed near path distance

-1

-1 -1

-1

ext

-1

! Power required 12V DC optical interferences field installation,

! 2 components include a transmitter & receiver ! Secure optical and immediately

separated by ~1 km to 10 km based on average mounting after field removal

visual air quality platforms/mounts ! Calibrations

! Operating temperature range -20EC to +45EC required compared with

nominal collocated

reference

transmissometer

during annual site

visit

Ambient Optec NGN-2 a. 2-minute integrated Hourly ±10% of true value for air ! Calculated from ±1 count, 0 to 32,768 count ! 550 nm center wavelength, 100 nm bandwidth N/A Normally at 3 m to zero:

Scattering Open Air sample every 5 near Rayleigh and using two regular (usually (Serial Output) (Serial Output) photopic response 5 m above ground at particle free Rayleigh

Coefficient Integrating minutes reduced to minutes of integration weekly) (one Rayleigh is (typically equal to ! 2 analog channels, 0 V to 10.000 volt, 0.00244 probe height of air provided internally

b Nephelometer hourly averages. (longer integrations will zero/span ~12 counts) 0.01 km to volt steps or 0 V to 5.000 volt, 0.00122 volt steps, collocated particulate with filters at 6-hour scat

(at 550 nm) increase the accuracy calibrations 24.00 km after jumper selected, 2 S output impedance, current samplers intervals

i.e., 10 minutes of ! Generally less ±2.44 mv post processing) limited

integration will increase than 10% (Analog Channel Channel 1: NORMALIZED SCATTERED span:

accuracy to ±4.5%) 1 or 2) 0 volts to LIGHT upscale span usually

(one Rayleigh is 10.00 volts (Analog Channel 2: STATUS value performed weekly

~12.0 mv) Channel 1 or 2) ! Output serial using SUVA 134a

-1

-1

(typically equal to RS-232, RX, TX, GND refrigerant gas with a

0.01 km to 8 data bits, 1 stop bit, no parity, known scattering -1

7.00 km after post televideo 920 emulation, FULL-DUPLEX mode, coefficient -1

processing) 9600 baud default, others selectable

STATUS, Raw SCATTERED LIGHT Count, zero and span

Raw LAMP BRIGHTNESS Count, calibrations are also

NORMALIZED SCATTERED LIGHT Count, performed during

INTEGRATION TIME in Minutes, installation, removal,

TEMPERATURE, DATE in year:month:day, and laboratory testing

TIME in hour:minutes

! Power required: 13.8 volt ±0.3 volt DC,

4.5 amps, regulated required

! Operating temperature range

-20EC to +45EC nominal
4-3

The Optec, Inc. LPV-2 long-path transmissometer has been in use since 1986. Over 30

instruments are currently operating in various visual air quality monitoring programs in North

America, from highly-polluted urban areas to pristine wilderness environments. The system consists

of a constant output light source transmitter and a computer-controlled photometer receiver. Other

specific transmissometer system components include transmitter and receiver alti-azimuth bases, a

terminal strip, an air temperature/relative humidity sensor, a DCP and antenna, and a strip chart

recorder. A general diagram of the standard transmissometer system components is provided in

Figure 4-1. Detailed information regarding transmissometer instrumentation or operation can be

found in Model LPV Long Path Visibility Transmissometer Technical Manual for Theory of

Operation and Operating Procedures (Optec, Inc., 1991) and Standard Operating Procedures and

Technical Instructions for Transmissometer Systems (Air Resource Specialists, Inc., 1993-1996).

The transmitter emits a uniform, chopped, incandescent light beam of constant intensity at

regular intervals for a programmed duration. It has two components: an electronic control box, and

a light source or transmitter. Transmitter optics concentrate light from a 15 watt tungsten filament

lamp into a narrow, well-defined uniform cone, magnifying the beam to the equivalent of a bare 1500

watt lamp, allowing the operator to precisely aim the light beam at the receiver. Although a 1E cone

of light is emitted from the transmitter, only the center 0.17E portion is used for routine monitoring.

Field and laboratory measurements of beam isotropy have indicated that the central 0.17E cone has

less than 1% variation.

Light intensity emitted from the transmitter is precisely controlled by an optical feedback

system, that continuously samples the center 0.17E portion of the outgoing beam and performs fine

adjustments to keep the light output constant. Light emitted from the transmitter is "chopped" at 78

pulses a second by a mechanical spinning disk in front of the lamp. This allows the receiver computer

to differentiate the lamp signal from background or ambient lighting. An eyepiece lets the operator

precisely aim the light beam.

The receiver gathers light from the transmitter, converts it to an electrical signal, isolates and

measures the received transmitter light, and calculates and outputs visibility results in the desired

form. The receiver has three components: a long focal-length telescope, a photodetector eyepiece

assembly, and a low power computer.

The telescope gathers the transmitter light, which includes both background illumination and

the transmitter signal, focuses it through a narrow band 550 nm interference filter, and focuses it on

a photodiode that converts it to an electrical signal. The receiver computer "locks-on" to the

transmitter light's chopped frequency and separates the transmitter light from ambient lighting. The

computer compares the measured transmitter light with the known (calibrated) transmitter light to

calculate the transmission of the intervening atmosphere.

Effects of atmospheric turbulence are minimized by using 6,250 samples of the signal to

calculate a one-minute average reading. The resultant reading is held in the computer and is available

to a datalogger (DCP) until the next value is calculated. Like the transmitter, the receiver is equipped

with an eyepiece to precisely aim the detector, and an interval timer to control the interval and

duration of measurements.
4-4

Figure 4-1. Transmissometer Receiver and Transmitter Components.
Sight Path Length ' Mean Visual Range x 0.033

4-5

4.1.2 Siting Criteria

The fundamental requirement for operation of the LPV-2 transmissometer is a clear,

unobstructed line-of-sight (sight path) between the transmitter and receiver. To reduce the effects

of thermal turbulence, the sight path should be elevated as far above the terrain surface as practical.

In rural applications, the transmitter and receiver are typically located near terrain drop-offs; in urban

applications, the sight path can be from one building to another. If possible, locating the sight path

over a body of water should be avoided due to the increased frequency of temperature inversions,

fog, etc.

The primary consideration in determining whether a path length is acceptable, is the expected

range of visual air quality in that area. Generally, remote areas in the western United States require

path lengths from 4-8 km, while eastern sites require 1-4 km lengths. If the mean visual range for the

area is known, a usable path distance can be calculated as follows:

(4-1)

Unless otherwise specified in the monitoring objectives for a transmissometer site, the sight

path should be as level as possible. If siting constraints result in a significant (>1.0E) sight path

vertical angle, orientation of the receiver telescope to lighting conditions throughout the year should

be thoroughly considered (e.g., a receiver telescope viewing approximately south at an upward angle

could be susceptible to periods of receiver detector saturation, especially with low winter sun angles).

It is generally preferable in such situations to configure the site with the receiver at the higher point

and viewing downward toward the transmitter.

The primary siting criterion is to ensure that the air mass along the entire sight path between

the receiver and transmitter is representative of the larger air mass to be monitored. Selected

transmissometer sites should have most of the following characteristics:

! Be located in an area representative of the air mass to be monitored

! Have a clear, unobstructed sight path between the receiver and transmitter

! Have adequate sight path length and height for representative monitoring of the air mass

! Be representative of the same air mass measured by other aerosol or optical monitoring

! Have AC power or adequate solar exposure for continuous year-round operation

! Be oriented so that lighting conditions do not affect measurements

! Be removed from local pollution influences (e.g., vehicle exhaust,wood smoke, road dust,

etc.)

! Be secure from vandalism

! Have available servicing personnel (operator)

! Be reasonably accessible during all months of the year
4-6

Various siting criteria to be considered as they apply to the actual transmitter and receiver

station locations are:

! Stability of ground surface -- frost-heaving, downslope soil movement, soil saturation,

and other earth movements will affect instrument alignment.

! Lightning exposure -- sites that are susceptible to lightning strikes should be avoided.

! Local land manager or land owner cooperation -- establish whether the local land manager

or land owner will be cooperative in allowing installation of the sites and continuous

access to the sites for the duration of the study.

! Vegetation growth -- growth of vegetation into the sight path must be taken into account.

! Data collection platform (DCP) transmission clearance -- verify that DCP transmissions

will not be blocked by vegetation, geographical features, or structures.

! Isolation from radio interference -- instrument circuitry is sensitive to strong radio signals.

Avoid siting close to broadcast antennas or repeaters.

! Snow accumulation -- the effects of significant snowfall accumulations on instrument,

DCP, and solar panel operation should be considered.

! Avoidance of lighting interference -- sunlight reflecting from solar panels, large windows,

or other large reflective surfaces near the transmitter can saturate the receiver detector

and affect readings.

4.1.3 Installation and Site Documentation

Transmissometer installation requires stable mounting posts, adequate sheltering, and a

reliable power supply. Continuous, correct transmitter and receiver telescope alignment is critical for

proper transmissometer operation. The transmitter and receiver mounting posts must be installed in

such a manner that any movement due to earth movement, temperature fluctuations, vibration, etc.

is minimized. Mounting posts can be attached to pre-existing rock or concrete surface, to a concrete

pier in the soil, or to a concrete pad. Alti-azimuth instrument bases allow precise alignment of the

transmitter and receiver telescopes. Sheltering must be waterproof, but heating or cooling are not

recommended.

Transmissometer installations may be powered by line power (AC) or solar power (DC). A

standard receiver station solar panel array is comprised of two large solar panels which charge four

deep-cycle batteries. A third, smaller solar panel provides power to a data collection platform (DCP).

A standard transmitter station solar panel array is comprised of three large solar panels which charge

four deep-cycle batteries.

After component installation, a distance measurement must be made from the front of the

receiver telescope tube to the front of the transmitter telescope tube. Transmissometer calibration

numbers using this accurate distance value are then recalculated and dialed in on the receiver

computer.
4-7

System operation is verified after the instrument settings and system timing have been set at

the transmitter and receiver. Upon completing the installation and verifying system operation, all

operators, back-up operators, and any other involved or interested on-site personnel should be

trained, including reviewing a site operator's manual. The manual contains standard operating

procedures and technical instructions for operator maintenance, troubleshooting, system diagrams,

replacing and shipping components, annual site visit procedures, field audit procedures, and

manufacturer's manuals (ARS, Inc. SOP 4110, TI 4110-3100, TI 4110-3300, TI 4110-3350, TI 4110-

3375, SOP 4115, TI 4115-3000, SOP 4710, Technical Manual for Theory of Operation and

Operating Procedures (Optec, Inc.), and Instruction Manual for Primeline 6723 (Soltec

Distribution, Inc.). A copy of the manual should be left at the transmitter site, the receiver site, and

at the office of on-site personnel. Other on-site documentation includes the completion of a site visit

trip report, photographic documentation (including photographs of the shelters, all components,

shelter supports, sight path, power supply, etc.), and documentation of any miscellaneous information

necessary to make a complete site description, including site map and site specifications (latitude,

longitude, instrument elevations, elevation angle, sight path distance, etc.).

4.1.4 System Performance and Maintenance

System performance and maintenance includes routine servicing, annual site visits, instrument

calibration, and annual servicing.

4.1.4.1 Routine Servicing

Site operators should perform routine servicing by visiting both the receiver and transmitter

shelters at 7 to 10 day intervals. Routine servicing involves documenting the initial condition and

operation of the components, inspecting and correcting alignment of both the transmitter and

receiver, cleaning optics of the system (including shelter windows, telescope lenses, and solar panels),

recording the lamp voltage and battery voltages, and recording receiver display readings and switch

settings. Timing should be checked and corrected if necessary. The transmissometer system should

follow the following timing sequence:

HR:MI:SEC Action

XX:00:00 Transmitter lamp turns on

XX:03:00 Receiver begins 10-min. average reading (cannot be observed)

XX:13:20 Receiver finishes reading, updates display, and changes toggle state

XX:16:00 Transmitter lamp turns off

XX:00:00 Sequence repeats hourly

Additional routine servicing, to be performed monthly or at a two-month interval, includes

checking the transmitter lamp status (changing the lamp every two months), inspecting the physical

condition of solar panels, batteries, battery fluid levels, DCP antenna, and strip chart recorder

operation.
4-8

4.1.4.2 Annual Site Visits

Annual site visits are performed to exchange the existing transmissometer system for a newly

serviced system, and to train site operators in servicing and maintaining the monitoring system

components. Primary tasks for a typical annual site visit include:

! Documenting initial conditions of the components

! Verifying instrument operation

! Conducting site inventory

! Performing site servicing

! Conducting an annual field audit

! Performing a post-audit verification check

Site operator training should be performed to discuss the purpose of the monitoring program

and theory of transmissometer system operation.

4.1.4.3 Instrument Calibration

Calibration of the LPV-2 transmissometer involves determining the irradiance from the

transmitter lamp that would be measured by the receiver if the optical sight path between the two

units allowed 100% transmission. All components of the LPV-2 transmissometer must be calibrated

as a unit. Each transmissometer lamp has its own calibration number for use at a specific site with

a specific transmissometer system. Receiver computers are individually calibrated during annual

servicing and may be interchanged for emergency maintenance or for use with the audit instrument.

Recalibration of an instrument with a receiver computer other than the one used at calibration does

not require instrument recalibration, but only recalculation of calibration numbers. No other system

component, including lamps, may be interchanged with another transmissometer without

recalibration.

All calibrations are currently performed at the Fort Collins Transmissometer Calibration and

Test Facility, located at Colorado State University's Christman Field. The facility includes sheltering

and all support equipment required to conduct operational transmissometer calibrations. The

calibration path (the distance between transmitter and receiver during calibration) is 0.3 km. At this

distance, the atmospheric transmission can be estimated with a high degree of accuracy for use in

calculating the calibration number. Because lamp brightness is dependent on lamp voltage, the lamp

voltage is measured in the laboratory prior to calibration, at the test facility during calibrations, and

again in the laboratory following calibration. A shift in lamp voltage may indicate damage to the lamp

or a malfunction of the lamp control circuitry.

To ensure that the detector alignment is valid over a longer path, a detector uniformity test

is performed at the test facility as the first step in performing any calibration.

Calibrations should be performed annually, prior to field installation, and immediately after

field removal. Pre-field calibration includes the following procedures:
Calibration No. ' (CP/WP)

2 ( (WG/CG) ( (WA/CA)2 ( (1/FT) ( WT ( (1/T) ( CR

4-9

! Burn-in of transmissometer lamps

! Measurement of pre-calibration lamp voltages

! Setup of instrumentation at the test facility

! Measurement of receiver detector uniformity

! Preliminary calibration of 4 lamps

! Final calibration of 10 lamps

! Documentation of calibration configuration, weather and visibility conditions, and lamp

voltage measurements on the calibration form

! Measurement of pre-field lamp voltages

! Quality assurance review of calibration data

! Entry of calibration data into the calibration database

! Calculation of site-specific pre-field calibration numbers for each lamp

All transmissometer lamps require a 72-hour burn-in cycle prior to being assigned to an

operational instrument. The burn-in cycle should be performed in the laboratory to stabilize the

filament position and reduce the incidence of premature lamp failure in the operational network.

A standardized calibration number is used in calculating lamp brightening and varies from

instrument to instrument. The standardized calibration number is calculated using the following

equation:

(4-2)

where:

CP = calibration path length, 0.300 km

WP = working path length, 0.500 to 10.000 km

 (5.000 km for standardized calibration number)

CG = calibration gain, nominal values are 100, 300, 500, 700, or 900

WG = working gain, nominal values are 100, 300, 500, 700, or 900

 (500 for standardized calibration number)

CA = calibration aperture, 101.51 mm

WA = working aperture, approximately 110.00 mm

 (110.00 for standardized calibration number)

FT = calibration filter (NDF) transmittance, 2.74% or 0.0274

WT = total window transmittance for the operational system (typically 80% or 0.800)

 (1.000 for standardized calibration number)
4-10

T = estimated atmospheric transmittance for the calibration path (T=e )

-bext*CP

CR = normalized average of 10-12 readings over the calibration path

Post-field calibration should be performed prior to any cleaning or servicing of the instrument

and includes: a receiver detector uniformity check, calibration of all operational lamps, and calculating

a lamp brightening factor for each post-calibrated lamp.

The transmitted light intensity of transmissometer lamps increases (brightens) with increased

hours of lamp use. On a lamp-by-lamp basis, this brightening factor is calculated by comparing the

pre-field and post-field calibration numbers and applying this change over the total number of lamp

hours accumulated during field operation. Calculating a lamp brightening factor in this manner

assumes a linear increase in lamp brightness. A lamp brightening database has been developed, which

includes the shift in lamp brightness (based on a comparison of pre-field and post-field calibration

numbers) as a function of lamp-use hours. All post-calibrated lamp data are added to this database.

Lamp brightening statistics are then analyzed (using a set of lamps with specific lamp factors such as

operating voltage or lamp manufacturer). A lamp brightening curve is defined for these lamps and

a lamp drift correction factor applied to the operational transmissometer data.

Calibration of a shelter window for use in a transmissometer network requires measurement

of light loss as transmitted light passes through the window. Initial measurements of window

transmittance should be performed at the test facility and follow the basic measurement procedures

described for other calibrations. Individual and combined transmittance should be measured for the

transmitter and receiver windows. The transmittance is determined by measuring the light received

at the receiver with the window(s) in place and the window(s) removed. The ratio of the average

readings with the windows in to the average readings with the windows out, is the window

transmittance.

4.1.4.4 Annual Servicing

Each transmissometer returned from a field site for annual laboratory maintenance should be

inspected and tested prior to initiating any servicing procedures that could invalidate the instrument

calibration. Annual servicing includes a post-field instrument inspection, functional test, and

calibration. Maintenance also performed includes:

! Disassembly and cleaning

! Optics alignment checks and realignment

! Chopper motor replacement

! Instrument timing checks

! Receiver computer gain measurements and calibration checks

! Internal batteries replacement

! Operational lamps replacement

! Instrument upgrades and modifications (as required)

! Pre-field calibration
4-11

4.1.5 Data Collection

Transmissometers operate in a cycled mode, collecting a 10-minute average of the transmitter

irradiance at the start of each hour of the day. The receiver is programmed to begin sampling three

minutes after the transmitter lamp turns on. Over the next 10 minutes, the receiver collects and stores

10 one-minute averages. The receiver then uses the 10 one-minute averages to calculate and output

an analog 10-minute average value for the received lamp irradiance.

Data are logged on data collection platforms (DCPs) and are processed by several entities

before being available for downloading via modem. Monitoring stations with DCPs undergo the

following data downloading sequence:

! The DCP logs transmissometer data at pre-programmed intervals.

! At three-hour intervals, the DCP transmits the past three hours' data (three 10-minute

averages) and its internal battery voltage to the GOES (Geostationary Orbiting Earth

Satellite).

! The GOES satellite retransmits the data to a downlink facility.

! The data are made available via the dissemination facility.

! The data are downloaded via telephone modem.

Data can be automatically collected from the DCP via computer software through telephone

modem. For periods when data are lost due to failure of on-site dataloggers, strip charts from the

backup recorders can be mailed and reviewed to retrieve as much useful data as possible. Air

temperature and relative humidity data should also be collected with transmissometer data.

4.1.6 Data Reduction and Validation

4.1.6.1 Data Reduction

Transmissometer data should be compiled into site-specific Level-A files. These files include

hourly data (one 10-minute average) and should be reviewed daily by data analysts to determine the

operational characteristics of each site. Any apparent problem should result in a telephone call to the

site operator in an attempt to resolve the inconsistencies.

Raw data plots may be generated bi-monthly from raw data files. Data from operator log

sheets should be checked against data collected via data collection platform (DCP) to identify

inconsistencies and errors.

Level-A transmissometer data should be plotted bi-monthly and reviewed monthly.

Inconsistent or suspicious data can then be identified and troubleshooting procedures initiated. As

completed log sheets from transmissometer sites are received, the pertinent information (visibility

conditions, alignment, system timing, instrument problems, etc.) should be manually transferred to

the bi-monthly plots. This procedure helps to identify the exact time of lamp changes, alignment

corrections, and other actions done by the site operator affecting instrument operation. This

information is used to update the lamp and code files for Level-A validation.
t

3

' L ( t

1

/t

2

4-12

(4-3)

4.1.6.2 Data Validation

Transmissometer data should undergo three validation levels: Level-A, Level-0, and Level-1.

All three levels of validation include hourly average data. Level-A validation includes visual review

and examination of the raw data and error files. Level-0 validation includes searching for

questionable or physically unrealizable data. Level-1 validation includes calculating uncertainty values

and identifying values affected by weather or optical interferences.

Level-A data files should be compiled into seasonal data files for each site. Standard

meteorological seasons are defined as:

Winter December, January, and February

Spring March, April, and May

Summer June, July, and August

Fall September, October, and November

Site-specific code files should be updated to include the most current information available

regarding calibration parameters, instrument and support equipment operation, operator notes, and

validity codes. The seasonal Level-A files should be checked for inconsistencies with a screening

program that verifies data integrity and assigns validity codes. Level-A validity codes should include:

0 = Valid

1 = Invalid: Site operator error

2 = Invalid: System malfunction or removed

3 = Valid: Data reduced from an alternate logger

6 = Valid: b data exceeds maximum (overrange) ext

8 = Missing: Data acquisition error

9 = Valid: b data below Rayleigh (underrange) ext

A = Invalid: Misalignment

L = Invalid: Defective lamp

S = Invalid: Suspect data

W = Invalid: Unclean optics

Level-0 data files should be generated from the Level-A data with a separate but redundant

data screening program. At Level-0, transmissometer data are corrected for lamp brightening and

converted to bext using site-specific calibration information. The lamp brightening correction is based

on the calculated average drift of a number of lamps. The algorithm for calculating the drift-related

offset applied to each b value is: ext

Let t = 16; number of minutes per hour the lamp is on. 1

t = 60; number of minutes in an hour. 2

t = number of lamp-on hours for current lamp. 3

L = number of hours the lamp resides in the transmitter.

r = path length.

The lamp-on time (t ) for the current lamp is: 3
F

drift (%) ' 0.270 ( t

0.4405

3

Tcorr' [1& (F

drift/100)](T

b

ext,corr

' %ln(

1

T

corr

) /r

4-13

(4-4)

(4-5)

(4-6)

The lamp drift correction factor (Fdrift) is a function of the lamp-on hours (t3) defined by the following

curve for Olympus lamps operating at a nominal voltage of 5.9 VDC:

The lamp drift corrected transmittance (T ) is: corr

where T is the measured transmittance. The drift corrected b is: ext

where r = path distance.

Level-1 data should be generated from the Level-0 files with a third data and validity code

screening and the addition of:

! Calculation of uncertainty values for all hourly data, and

! Identification of hourly valid b data that may be affected by meteorological or optical ext

interferences.

Level-1 validity codes are:

0 = Valid

1 = Invalid: Site operator error

2 = Invalid: System malfunction or removed

3 = Valid: Data reduced from an alternate logger

4x = Weather: A letter code representing specific conditions as noted below:

Condition Letter Code

A B C D E F G H I J K L M N O

RH > 90% x x x x x x x x

bext > maximum threshold x x x x x x x x

bext uncertainty > threshold x x x x x x x x

TMbext > Delta threshold x x x x x x x x

Z Weather observation between two other weather observations.
4-14

Threshold values are different for each site.

8 = Missing: Data acquisition error

9 = Invalid: b data below Rayleigh (underrange) ext

A = Invalid: Misalignment

L = Invalid: Defective lamp

S = Invalid: Suspect data

W = Invalid: Unclean optics

Validity codes for meteorological data include:

0 = Valid

1 = Invalid: Site operator error

2 = Invalid: System malfunction or removed

3 = Valid: Data reduced from an alternate logger

5 = Invalid: Data > maximum or < minimum

8 = Missing: Data acquisition error

A -99 in any data field indicates missing or invalid data.

See Section 4.1.8, Quality Assurance, for a detailed discussion regarding uncertainty

measurements.

A screening program should be used to again check all data and validity codes for

inconsistencies. The data should then be reduced to four-hour average values of extinction (b ),

ext

standard visual range (SVR), and haziness (dv). The time periods of the four-hour average values

are:

0300 0000 - 0359 hours

0700 0400 - 0759 hours

1100 0800 - 1159 hours

1500 1200 - 1559 hours

1900 1600 - 1959 hours

2300 2000 - 2359 hours

Seasonal data plots can then generated and reviewed to identify data reduction and validation

errors, instrument operation problems, and calibration inconsistencies. Any identified problems

should be immediately investigated and resolved by following the procedures detailed in standard

operating procedures and technical instructions.

4.1.7 Data Reporting and Archive

4.1.7.1 Data Reporting

Data reports should be prepared in a format that generally conforms to the Guidelines for

Preparing Reports for the NPS Air Quality Division (AH Technical Services, 1987). A separate data

report should be prepared for each instrument type; transmissometer data reports should contain only

transmissometer data. Reporting consists of various text discussions and graphics presentations

concerning the instrumentation and collected data. Specific contents of the reports are defined by the

contracting agencies' COTR.
4-15

Seasonal transmissometer reporting should be completed within three months after the end

of a monitoring season, and annual reporting within three months after the end of the last reported

season. Standard meteorological monitoring seasons are defined as:

Winter (December, January, and February)

Spring (March, April, and May)

Summer (June, July, and August)

Fall (September, October, and November)

Reports should contain the following major sections:

! Introduction

! Data Collection and Reduction

! Site Configuration

! Data Summary Description

! Transmissometer Data Summaries

! Summary

! References

The introduction should contain a conceptual overview of the purpose of the monitoring

program and a description of the monitoring networks. The data collection and reduction section

should include data collection methods, data file review, data validation, application of validity codes,

processing through various validation levels, and discussion of file formats, theoretical concepts of

uncertainty measurements, and identification of meteorological and optical interferences that affect

the calculation of bext from transmissometer measurements. Various units of measurement, including

haziness (dv), extinction (b ), and standard visual range (SVR) should be discussed. ext

The site configuration section should contain a brief discussion of instrumentation at each

transmissometer site, basic principles of operation, measurement principles, and data collection

specifications, including:

! A map depicting the location of all monitoring network sites.

! A Monitoring History Summary Table, listing for each monitoring site the name, type of

instrumentation, and period of operation for each instrument type.

! A Site Specifications Summary Table, listing for each monitoring site complete site

specifications. Site specifications include site name and abbreviation, latitude and

longitude of both the receiver and transmitter, elevation of both the receiver and

transmitter, the sight path distance between the two components, azimuth, and elevation

angle (receiver to transmitter) of the sight path. The table should also include the number

of readings taken each day, and the operating period during the season.
4-16

A data summary description section describes seasonal and annual data summaries. Annual

data summaries should be prepared for each site that operated during the reporting period, and should

be based on a calendar year instead of season. An example Seasonal Transmissometer Data Summary

is presented as Figure 4-2 and an example Annual Transmissometer Data Summary is presented as

Figure 4-3. The following is a detailed explanation of the contents of the data summaries in each

report.

Seasonal Transmissometer Data Summaries include the following five data presentations:

! 4-Hour Average Variation in Visual Air Quality (Excluding Weather-Affected Data) -

Plot of four-hour averaged b , SVR, and dv geometric mean values (without weather- ext

influenced observations) for each day of the reporting season. A mean value is calculated

for each four-hour period from the valid transmissions for that day. Gaps in the plot

indicate that data were missing, weather-influenced, or failed edit procedures. For

example, values are not calculated if the transmissometer was misaligned. The left axis

of the graph is labeled as haziness (dv) and the right axis as b and SVR. ext

! Relative Humidity - Timeline of four-hour averaged relative humidity measurements. This

allows rapid determination of the effect of increasing relative humidity on measured bext

and SVR. Long periods of relative humidity near 100% usually result in corresponding

periods of high b (low SVR), and are likely associated with precipitation events. This ext

assumption can only be verified by reviewing simultaneous photographic data.

! Frequency of Occurrence: Hourly Data - This plot is a frequency distribution of hourly

average b , SVR, and haziness values, both with and without weather-influenced data. ext

The 10% to 90% values are plotted in 10% increments. The 10%, 50%, and 90%

cumulative frequency values for bext are listed to the right of the plot and haziness to the

left of the plot. SVR values are listed in the corresponding cumulative frequency

summary table. Note that SVR and b are inversely related; for example, as the air ext

becomes cleaner, b values decrease and SVR values increase. ext

For deciview, the 10%, 50%, and 90% values are linear with respect to bext changes. A

one dv change is approximately a 10% change in bext. Clean days are characterized by low

haziness values (small dv) and dirty days are characterized by high haziness values (large

dv).
4-17

Figure 4-2. Example Seasonal Transmissometer Data Summary.
4-18

Figure 4-3. Example Annual Transmissometer Data Summary.
4-19

! Visibility Metric (Excluding Weather) - This table presents mean values excluding

weather for dv, bext, and SVR. The best, worst, and average conditions using the

arithmetic means of the 20th percentile least impaired visibility, the 20th percentile most

impaired visibility, and for all data for the season are presented.

! Data Recovery Statistics

Total Possible Hourly Averages in the Time Period - The total possible category is

calculated by subtracting the number of hourly averages included in periods when the

instrument was removed due to conditions unrelated to system performance

(construction, site relocation, etc.) from the theoretical maximum number of hourly

average periods possible during a season.

Valid Hourly Averages Including Weather-Affected Data - The number of all valid hourly

averages collected during a season. The percentage represents the number of valid hourly

averages compared to the total possible hourly averages.

Valid Hourly Averages Excluding Weather-Affected Data - The number of valid hourly

averages (excluding any data affected by weather) collected during a season. The

percentage represents the number of valid hourly averages compared to the total possible

hourly averages.

Percent of All Valid Hourly Averages Not Affected by Weather - This percentage

collection efficiency represents the number of valid hourly averages (excluding any data

affected by weather) compared to the number of all valid hourly averages.

Annual Transmissometer Data Summaries include three data presentations:

! Monthly Median Visual Air Quality - Plot of median monthly b , SVR, and dv values ext

both with and without weather-affected data. The left axis of the graph is labeled as

haziness (dv) and the right axis as bext and SVR. Note that SVR and bext are inversely

related.

! Monthly Cumulative Frequency Summaries: All Data - Table of cumulative frequency

distribution average b and dv values both with and without weather-influenced data.

ext

The 10% to 90% values are presented in 10% increments. Also included are data

recovery statistics (total possible readings, number of collected readings, and number of

valid (both with and without weather-affected data).

! Annual Frequency of Occurrence: Hourly Data - This plot is a frequency distribution of

hourly average bext, SVR, and haziness values, both with and without weather-influenced

data. The 10% to 90% values are plotted in 10% increments.

Transmissometer data summaries should follow their description. Summaries should be

prepared for each site that operated during the reporting period. A brief discussion of events and

circumstances that influence data recovery should follow the data summaries. Operational status

throughout the reporting period should be presented for each site in an operation summary table,

listing for each site, site name and abbreviation, the actual time period during the season that each site

collected data, data collection losses or problem description, and problem resolutions. An analysis

summary table should also be prepared (for all data and for all data excluding weather events) based

on actual monitoring periods. The table lists for each site, site name and abbreviation, the number
b

ext ' & ln(T )/r

*bext ' ± UT/r

4-20

(4-7)

(4-8)

of seasonal hourly averages possible, the number and percentage of hourly averages usable, and the

cumulative frequency distribution (10%, 50%, and 90% dv, b , and SVR values). ext

Finally, a summary section should be included in reports, and provide a synopsis of the

transmissometer network, including changes in operational techniques, and a general conclusion of

the monitoring period in review. A reference section should include technical references (documents

cited in the report), and related reports and publications (including all prior reports pertaining to the

monitoring program).

4.1.7.2 Data Archive

Archiving of raw digital data should be performed on a monthly basis. Archiving of all raw

and processed digital data for a given season, and constants, calibration, and data processing files

should be performed on a seasonal basis, after data have been finalized and reported. All files should

be in ASCII format. Files should be stored in their original formats (raw, Level-A, Level-0, and

Level-1) on magnetic tape and CD-ROM. At least two copies of each media should be created; one

copy should be stored at the data processing location and the other off-site.

Hard copies of supporting documentation and reports should be duplicated and archived on

a continual basis, and include site specifications, monitoring timelines, data coordinator/site operator

correspondence, site operator log sheets, trip reports, bi-monthly and seasonal summary plots,

instrument calibration records, instrument maintenance logs, and field audit reports. All validated

Level-1 data should be delivered as ASCII files (on PC-compatible diskettes and/or CD-ROM) to the

COTR with the quarterly and annual reports. The standard file format currently used for IMPROVE

protocol transmissometer data is presented in Figure 4-4.

Transmissometer data and accompanying site and calibration information should also be kept

current on a database. The database should contain both raw and Level-1 validated data.

4.1.8 Quality Assurance

Quality assurance of transmissometer data is performed during Level-1 validation, and

includes precision and accuracy of the instrument, and various uncertainty measurements. Annual

field audits are also a component of quality assurance.

4.1.8.1 Instrument Precision and Accuracy

Precision of extinction estimates from transmittance measurements should be determined. The

average extinction (bext) of the transmissometer optical path (r) is calculated from the transmittance

measurement (T) by:

Since the path length r is measured to an extremely high precision, the precision in bext can be

approximated from propagation of error analysis as:
4-21

Field Number

 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19

 

 GRCA 900702 183 700 12 1 4 0 18 10 300 0 17 1 0 38 3 0 134

 GRCA 900702 183 800 -99 -99 0 4 18 10 300 4H -99 -99 0 -99 -99 0 -99

Field Description

1 Site abbreviation

2 Date in year/month/day format

3 Julian Date

4 Time using a 24-hour clock in hour/minute format

5 b (Mm ) ext

-1

6 b uncertainty (Mm ) ext

-1

7 Number of readings in average

8 Number of readings not in average due to weather

9 Uncertainty threshold (Mm )

-1

10 ) threshold (Mm )

-1

11 Maximum threshold (Mm )

-1

12 b validity code ext

1

13 Temperature (EC)

14 Temperature uncertainty (EC)

15 Temperature validity code 2

16 Relative humidity (%)

17 Relative humidity uncertainty (%)

18 Relative humidity validity code 2

19 Haziness (dv x 10)

 b validity codes: 1

ext

0 = Valid

1 = Invalid: Site operator error

2 = Invalid: System malfunction or removed

3 = Valid: Data reduced from alternate logger

4x = Weather: A letter code representing specific conditions as noted below:

Condition Letter Code

A B C D E F G H I J K L M N O 

RH > 90% x x x x x x x x

bext > maximum threshold x x x x x x x x

bext uncertainty > threshold x x x x x x x x

) bext > delta threshold x x x x x x x x

Z Weather observation between 2 other

 weather observations.

Threshold values may be different for each site.

8 = Missing: Data acquisition error

9 = Invalid: bext below Rayleigh

A = Invalid: Mis-alignment

L = Invalid: Defective Lamp

S = Invalid: Suspect Data

W = Invalid: Unclean optics

 Meteorology validity codes: 2

0 = Valid

1 = Invalid: Site operator error

2 = Invalid: System malfunction or removed

3 = Valid: Data reduced from alternate logger

5 = Invalid: Data > maximum or < minimum

8 = Missing: Data acquisition error

A -99 in any data field indicates missing or invalid data.

Figure 4-4. Standard ASCII File Format IMPROVE Protocol Transmissometer Visibility Data.
T ' I

r

/(F

lamp ( Ical)

Ux' *x

/x ̄

4-22

(4-10)

(4-11)

The relative uncertainty in transmittance leads to an additive uncertainty in extinction that

depends on the path length of the transmittance measurement.

Bias in extinction calculations should also be determined. The calibration equation assumes

clean glass surfaces of constant transmittance. Any change in the window transmittance results in a

bias to the calculated extinction. If the window transmittance decreases the calculated extinction will

increase. If the window transmittance increases the calculated extinction will decrease. As with the

precision, the bias is a function of the relative change in window transmittance and path distance:

Bias = (relative change in window transmittance)/r (4-9) 

The possibility exists for errors to arise from changes in the transmittance of the windows due

to:

! Pitting of the windows by wind blown dirt.

! Staining of the windows by pollution.

! Dirt collecting on the window surface due to dust, rain, or snow.

! Fogging of the windows at high humidities.

! Improper servicing resulting in smudging of the windows.

! Removal of the windows due to breakage.

4.1.8.2 Measurement Uncertainties

Measurement uncertainties are considered during Level-1 validation. Uncertainties include

transmittance uncertainties, meteorological data uncertainties, and optical interferences uncertainties.

Transmittance uncertainties are based on various parameters. Operationally the basic equation

used to calculate path transmittance is:

where:

T = Transmittance of atmosphere of path r

I = Intensity of light measured at r r

F = Variability function of lamp output lamp

I = Calibration value of transmissometer cal

The relative uncertainty (U ) of any measured parameter x is defined as: x

where:

x ̄ = arithmetic mean of all x measurements

* = precision of measurements x defined as x
*x

'

1

n&1

n

j

i'1

(x

i

&x ̄)

2

1/2

UT' (U

2

Ir % U

2

Ical % U

2

lamp)

1/2

' (CP/WP)

2

x (WG/CG) x (WA/CA)

2

x WT x (1/FT) x (1/T) x

Ucal' 2U

2

CP% 2U

2

WP% U

2

WG% U

2

CG% 2U

2

WA% 2U

2

CA% U

2

WT% U

2

FT% U

2

CR

1/ 2

4-23

(4-12)

(4-13)

(4-14)

(4-15)

Using propagation of error analysis the relative uncertainty of the path transmittance can be

calculated from the relative uncertainties of the measured variables as:

where:

UT = relative uncertainty of T 

U = relative uncertainty of I Ir r

U = relative uncertainty of I Ical cal

Ulamp = relative uncertainty of Flamp

Understanding the uncertainty of a transmittance measurement requires a thorough

investigation of the precision of each of the following:

! Precision in calibration to determine Ical

! Precision in the measurement of Ir

! Precision in the measurement of Flamp

Relative Uncertainty of Ical - The precision in calibration value Ical can be determined by investigating

the calibration equation. I is the value that would be measured by the transmissometer detector if cal

the atmospheric path was a vacuum. I incorporates the path distance r, transmittance of all cal

windows in the path, and size of working aperture used. I is determined from: cal

Using propagation of uncertainty analysis the relative uncertainty in I can be shown to be: cal

Path distances are measured using a laser range finder. Calibration apertures are measured

with a precision micrometer. Gain settings are measured with a precision voltmeter. Window and

neutral density filter (NDF) transmittances are measured with a reference transmissometer by

differencing techniques, thus they do not require absolute calibration. The standard deviation of the

raw readings (CR) are calculated at each calibration. The typical working values, measurement

precision, and relative uncertainties of these values are:
4-24

Parameter Value Precision Relative

Uncertainty

CP Calibration Path 0.3 km 1 x 10 km 3.3 x 10 -6 -6

WP Working Path 5.0 km 1 x 10 km 2.0 x 10 -6 -7

CG Calibration Gain 100 1 x 10 1.0 x 10 -2 -4

WG Working Gain 500 1 x 10 2.0 x 10 -2 -5

CA Calibration Aperture 100 mm 1 x 10 mm 1.0 x 10 -2 -4

WA Working Aperture 110 mm 1 x 10 mm 9.1 x 10 -2 -5

WT Window Transmittance 0.810 0.001 1.2 x 10-3

FT NDF Transmittance 0.274 -0.001 3.6 x 10-3

T CP Transmittance 0.975 0.003 3.1 x 10-3

CR Raw Readings 900 2.0 2.2 x 10-3

Combining the above values into the uncertainty equation leads to a typical relative

uncertainty for I : U = 0.005. cal Ical

Relative Uncertainty of Ir

 - Under ambient operating conditions the irradiance measured by the

transmissometer receiver will fluctuate due to:

! Atmospheric optical turbulence causing scintillation.

! Atmospheric optical aberrations causing beam wander.

! Varying meteorological conditions along the path: rain, snow, fog.

! Insect swarms causing beam interference.

The precision of each 10-minute irradiance measurement is calculated by the receiver

computer as the standard deviation of the ten one-minute average irradiance measurements. The

measured standard deviation is a direct estimation of atmospheric optical interference. Typical values

of Ir and various operational precision estimates that have been observed in the monitoring network

are listed below.

Ambient

Extinction

(km-1)

Ir

Value

No Optical Interferences Optical Interference

Precision Precision Relative Relative

Uncertainty Uncertainty

0.010 200 1 0.0050 20 0.100

0.020 190 1 0.0053 20 0.105

0.030 180 1 0.0056 20 0.111

0.050 163 1 0.0061 20 0.123

0.100 127 1 0.0079 20 0.158

0.500 17 1 0.0580 20 1.117

Working Path = 5.0 km, Ical = 210

As can be seen the relative uncertainty of the measured intensity is a function of the extinction

of the path. For typical extinction measurements free from optical interference in the network, the

average relative uncertainty in I is approximately: U = 0.0055.

r Ir
Lamp Brightening(%)' a

o

(t

a

1

4-25

(4-16)

Relative Uncertainty of Flamp - The major source of uncertainty in the transmissometer data

is lamp drift correction. The transmitter employs an optical feedback loop designed to maintain

constant irradiance within the 10 nm bandwidth of the receiver filter/detector module. However,

comparison of pre and post lamp calibrations show that the transmitter lamp output increases

(brightens) with increased hours of lamp use. Tests have shown that the brightening is definitely a

function of the lamp rather than the feedback circuit or filter. It is important to note that a 1%

increase in irradiance over a path length of approximately five kilometers (the Grand Canyon sight

path for example) results in the apparent extinction being decreased by 0.002 km (20% of

-1

Rayleigh!!); i.e., the instrument measurement indicates the air to be cleaner than it actually is.

Lamp brightening percentages and lamp "on" hours for all systems and lamps post-calibrated

at the Fort Collins, Colorado transmissometer calibration facility are entered into a lamp brightening

database. The data in this database are used to create statistics on lamp brightening. Lamp

brightening percentages for post-calibrated lamps are sorted into time bins based on lamp operational

hours. The mean and standard deviation of operational hours and percent lamp brightening were

calculated for each bin. Power law functions are fitted to these data to define a statistically based

mean lamp brightening and the one sigma upper and lower bounds. Applying the mean function to

the raw transmissometer irradiance readings corrects for lamp brightening. The precision of the

correction is calculated from the upper and lower bounds for the number of hours on the lamp at the

time of the reading.

If, upon post-calibration, a system exhibits abnormally high or low lamp brightening,

previously reported extinction data are flagged for further review. The lamp brightening database is

continually updated as additional lamps are post-calibrated. Periodically, the lamp brightening

statistics are reanalyzed to provide a more accurate description of the lamp drift correction and the

precision associated with this correction.

Variations in lamp brightening characteristics for a given lamp design may occur due to

variations in manufacturing processes between manufacturers. All lamps used with the LPV-2

transmissometer are purchased from the transmissometer manufacturer, Optec, Inc.

The equation for calculating lamp brightening using this curve is:

where:

t = accumulated lamp "on" time (hours)

a0 = 0.2700

a1 = 0.4405

From the above analysis, the relative uncertainty in path transmittance can be calculated for

each 10-minute transmittance measurement by the transmissometer. The typical values are:

Condition Relative Uncertainty

(U )T

No Optical Interference 0.02

Optical Interference 0.20
4-26

Meteorological data uncertainties and limits are obtained from the manufacturer's literature.

The values used are listed below:

Utemp = 1EC

U = 2% (Rotronics MP100F Sensor) RH

Maximum temperature = 60EC

Minimum temperature = -50EC

Maximum relative humidity = 100%

Minimum relative humidity = 0%

Optical interferences uncertainties must also be considered. The transmissometer directly

measures the irradiance of a light source after the light has traveled over a finite atmospheric path.

The average extinction coefficient of the sight path is calculated from this measurement and is

attributed to the average concentration of atmospheric gases and ambient aerosols along the sight

path. The intensity of the light, however, can be modified not only by intervening gases and aerosols,

but also by:

! The presence of condensed water vapor in the form of fog, clouds, and precipitation along

the sight path.

! Condensation, frost, snow, or ice on the shelter windows.

! Reduction in light intensity by insects, birds, animals, or vegetation along the sight path,

or on the optical surfaces of the instrumentation or shelter windows.

! Fluctuations in light intensity both positive and negative due to optical turbulence, beam

wander, atmospheric lensing, and miraging caused by variations in the atmospheric optical

index of refraction along the sight path.

An algorithm has been developed to identify transmissometer extinction data that may be

affected by the interferences described above. This algorithm contains five major tests:

1) Relative Humidity

2) Maximum Extinction

3) Uncertainty Threshold

4) Rate of Change of Extinction

5) Isolated Data Points

Due to the large volume of extinction data collected by transmissometers as compared to

aerosol monitors, the algorithm has been designed to be a conservative filter on the extinction data.

That is, if an hourly extinction measurement indicates the slightest possibility of meteorological or

optical interference by failing any one of the above tests, it is flagged with identifier codes in the

Level-1 data file. The following describes each of the five tests:
4-27

Relative Humidity - When the relative humidity measured at the transmissometer receiver is greater

than 90%, the corresponding transmissometer measurement is flagged as having a possible

interference. The 90% level has been chosen due to the following considerations:

! The relative humidity is only measured at the receiver location and not at any other

position along the sight path.

! A 1.5EC change in dew point temperature results in a 10% change in relative humidity.

! The atmosphere is continuously undergoing both systematic and random variations in its

spatial and temporal properties.

! The typical precision of relative humidity measurements is ±2%.

The above considerations all indicate that inferring a precise knowledge of the meteorological

conditions along a sight path at high relative humidity from a single point measurement is very

difficult. When the relative humidity is above 90% at one end of the path, small random temperature

or absolute humidity fluctuations along the path can lead to condensation of water vapor causing

meteorological interferences. Thus, in accordance with the conservative philosophy expressed above,

the 90% relative humidity limit was selected for this test.

Maximum Extinction. For every transmissometer sight path, a maximum bext can be calculated

that corresponds to a 5% transmittance for the path. All sight paths were selected, such that based

on historical visibility data, this maximum bext occurs less than 1% of the time. When the measured

b is greater than this threshold value, it is assumed that meteorological or optical interferences, not ext

ambient aerosols, are causing the high extinction. All measurements greater than the calculated sitespecific maximum threshold are flagged in the data file.

Uncertainty Threshold. The normal operating procedure for the transmissometer is to take

10 one-minute measurements of transmitter irradiance each hour, and report the average and standard

deviation of the ten values. A mean hourly extinction and associated uncertainty is then calculated

from these measurements. In remote, rural areas, the ambient aerosol concentration typically varies

quite slowly with time constants on the order of a few hours rather than minutes. This leads to the

expectation of relatively constant extinction during the 10 minutes of receiver measurements and a

low standard deviation of measured transmitter irradiance. If only one of the ten irradiance values

varies more than 20% from the mean, the uncertainty in bext will increase dramatically. The presence

of any meteorological or optical interferences along the sight path will lead to large standard

deviations in lamp irradiance, thus large uncertainties in b . With the conservative assumption of ext

constant bext during any ten minute measurement period, any increase in the uncertainty of bext above

a selected threshold flags the measurement as affected by one of these interferences. The uncertainty

threshold is determined for each sight path and is included in each Level-1 data file for reference.

Rate of Change of Extinction (Delta Threshold). Transmissometer data collected before

September 1, 1990, did not include standard deviation of measured irradiance values. For data

collected before this date, another test was developed to identify periods of interferences associated

with rapidly fluctuating irradiance measurements. This test consists of comparing the hourly average

extinction to the preceding and following hours, and calculating a rate of change in each direction.

If the absolute value of this rate of change is greater than some assigned Delta threshold, the hourly

b value is flagged as being affected by interferences. Delta thresholds have been determined for ext
4-28

each sight path by analyzing extinction data collected after September 1990, which have

corresponding uncertainty thresholds to determine appropriate Delta thresholds for the sight path.

The Delta threshold is typically not as low as the uncertainty threshold, due to the possibility of larger

hourly variations in b as compared to variations during ten minutes of measurements. Each sight ext

path has its own Delta threshold and it is listed in the Level-1 data file for reference.

Isolated Data Points. This test is performed after the above four thresholds are applied to the

hourly extinction data. It is used to identify data points that have passed the above thresholds, but

are located between hourly bext data that have failed the above thresholds. The conservative

assumption is, if data before and after the isolated hour indicates interferences, the hour in question

probably is also affected by interferences. These data are also flagged as weather-affected.

4.1.8.3 Instrument Audits

The transmissometer field audit verifies accurate on-site and replacement transmissometer

measurements by comparing measurements made with the audit reference transmissometer. The

reference transmissometer should be calibrated at the test facility before and after each field audit to

ensure that the accuracy of the measurements has not been affected by handling and/or transport of

the instrument. To reduce the amount of equipment shipped to and from a transmissometer site, the

audit transmissometer system should be operated with the replacement transmissometer computer

during the audit. Gain measurements should be made on all instruments during instrument servicing.

These gain measurements should then be incorporated into the calculation of calibration numbers

generated for the audit transmissometer.

To ensure a quality audit, it is important that the audit be performed during a period of good

weather and stable conditions. If the weather and/or conditions are not suitable, the audit should be

rescheduled. The audit should be comprised of a defined series of 10-minute readings with various

lamps calibrated with the on-site, audit, and replacement transmissometer units (2 lamps on-site, 2

lamps audit, and 3 lamps replacement). The sequence of instruments and lamps should be configured

to provide the best possible intercomparison between individual lamps calibrated with a

transmissometer system and also between respective transmissometer systems.

The transmissometer field audit also includes a window transmittance test, which verifies the

combined transmittance of the transmitter and receiver station windows. This test is typically

incorporated into the end of the audit, which is performed on site, but can also be performed

separately if necessary. The window transmittance test should include three 10-minute reading

segments with the first operational lamp of the replacement transmissometer. The first and last

segments should be with the receiver and transmitter windows installed. The middle segment should

be performed with both windows removed. This allows determination of window transmittance and

provides an indication of the stability of ambient conditions.

The audit results verify the operational integrity of the on-site and replacement instruments.

Audit results statistics should be used to define error limits for comparison of path transmittance

measurements obtained with an instrument being audited or path transmittance measurements

obtained with an audit instrument.

Lamps used operationally with transmissometers being removed from the field (on-site

instruments) typically have accumulated 400 to 600 hours of "on" time. This accumulated operating
SVR '

3912

(b

ext&bray

% 10Mm &1)

4-29

(4-17)

time results in a shift in lamp brightness. Audit data for lamps used in the field should be corrected

for lamp brightening. Three sets of audit results statistics should be created as follows:

! One set of audit result statistics should be generated for audit instrument and on-site

instrument comparisons applying the standard lamp brightening correction factor. This

data set should be used only as an early indicator of the quality of the data collected

during the operational period for the on-site transmissometer.

! Operational instruments should be post-calibrated after removal from a site. On-site

instrument audit data should be corrected using post-calibration lamp brightening factors.

The second set of audit results statistics should be generated using these data. This data

set should be incorporated into ongoing analyses of lamp brightening effects on data

quality.

! The third set of audit results statistics should be based on measurement comparisons

between the replacement transmissometer and the audit transmissometer. Because

replacement instrument lamps should be calibrated prior to installing the instrument at a

field site, the lamps should not have accumulated any "on" time prior to the audit and

lamp brightening should not be a factor. These statistics should be used to define error

limits for acceptance of replacement instrument audits.

4.1.9 Data Analysis and Interpretation

Transmissometer data are a complete, continuous measure of atmospheric extinction. Data

are typically presented in three units: extinction, standard visual range, and deciview.

Extinction is expressed in inverse megameters (Mm ). These units are directly stored in the -1

data files.

Standard visual range (SVR) can be interpreted as the farthest distance that a large, black

feature can be seen on the horizon. It is a useful visibility index that allows for comparison of data

taken at various locations.

SVR is calculated to normalize all visual ranges to a Rayleigh scattering coefficient of 10 Mm-

 or an altitude of 1.524 km (5000 ft.). The Rayleigh scattering coefficient, b , for the mean sight 1

ray

path altitude is subtracted from the calculated extinction coefficient, bext, and the standard Rayleigh

scattering coefficient of 10 Mm is added back. The value 3912 is the constant derived from

-1

assuming a 2% contrast detection threshold. The theoretical maximum SVR is 391 km.

An easily understood visibility index uniformly describes visibility impairment. The scale of

this visibility index, expressed in deciview (dv), is linear with respect to perceived visual changes over

its entire range, analogous to the decibel scale for sound. A one dv change is about a 10% change

in extinction coefficient, which is a small but perceptible scenic change under many circumstances.

Since the deciview scale is near zero for a pristine atmosphere (dv=0 for Rayleigh conditions at about
haziness(dv) ' 10 ln (

b

ext

10Mm &1

) ' 10 ln(

391km

vr

)

4-30

(4-18)

1.8 km elevation) and increases as visibility is degraded, it measures perceived haziness. Expressed

in terms of extinction coefficient (b ) and visual range (vr): ext

Ideally, a just noticeable change (JNC) in scene visibility should be approximately a one or

two dv change in the deciview scale (i.e., a 10% to 20% fractional change in extinction coefficient)

regardless of the baseline visibility level. Similarly, a change of any specific number of dv should

appear to have approximately the same magnitude of visual change on any scene.

The dv scale provides a convenient, numerical method for presentation of visibility values.

Any visibility monitoring data that are available in visual range or extinction coefficient are easily

converted to the new visibility index expressed in deciview.

Use of the dv scale is an appropriate way to compare and combine data from different

visibility perception and valuation studies. When results from multiple studies are presented in terms

of a common perception index, the effects of survey approach and other factors influential to the

results can be evaluated.

Transmissometer data provide a quantitative measure of real time visibility conditions. Data

can be used to provide the basis for background conditions and trend analysis; however, data must

be combined with associated meteorological and aerosol concentrations to understand the source

and/or composition of the impairment observed.

Caution should be taken, however, when comparing reconstructed extinction with measured

extinction. Reconstructed extinction is typically 70% - 80% of the measured extinction. The

following differences/similarities should be considered:

! Data collection. Reconstructed extinction measurements represent 24-hour samples

collected twice per week. Transmissometer extinction estimates represent continuous

measurements summarized as hourly means, 24 hours per day, seven days per week.

! Point versus path measurements. Reconstructed extinction represents an indirect measure

of extinction at one point source. The transmissometer directly measures the irradiance

of light (which calculated gives a direct measure of extinction) over a finite atmospheric

path.

! Relative humidity (RH) cutoff. Daily average reconstructed measurements are flagged

as invalid when the daily average RH is greater than 98%. Hourly average

transmissometer measurements are flagged invalid when the hourly average RH is greater

than 90%. These flagging methods often result in data sets that do not reflect the same

period of time, or properly interpret short-term meteorological conditions.
4-31

4.1.10 Transmissometer Standard Operating Procedures and Technical Instructions

The Air Resource Specialists, Inc. document entitled Air Resource Specialists, Inc. Standard

Operating Procedures and Technical Instructions for Transmissometer Systems, includes the

following transmissometer Standard Operating Procedures and Technical Instructions:

SOP 4050 Site Selection for Optical Monitoring Equipment (IMPROVE Protocol)

TI 4050-3010 Site Selection for Optec LPV-2 Transmissometer Systems

SOP 4070 Installation and Site Documentation for Optical Monitoring Equipment

TI 4070-3010 Installation and Site Documentation for Optec LPV-2 Transmissometer Systems

(IMPROVE Protocol)

SOP 4110 Transmissometer Maintenance (IMPROVE Protocol)

TI 4110-3100 Routine Site Operator Maintenance Procedures for LPV-2 Transmissometer

Systems (IMPROVE Protocol)

TI 4110-3300 Troubleshooting and Emergency Maintenance Procedures for Optec LPV-2

Transmissometer Systems (IMPROVE Protocol)

TI 4110-3350 Transmissometer Monitoring System Diagrams and Component Descriptions

TI 4110-3375 Replacing and Shipping Transmissometer Components

TI 4110-3400 Annual Laboratory Maintenance Procedures for LPV-2 Transmissometer Systems

(IMPROVE Protocol)

SOP 4115 Annual Site Visits for Optical Monitoring Instrumentation (IMPROVE Protocol)

TI 4115-3000 Annual Site Visit Procedures for Optec LPV-2 Transmissometer Systems

(IMPROVE Protocol)

SOP 4200 Calibration of Optical Monitoring Systems (IMPROVE Protocol)

TI 4200-2100 Calibration of Optec LPV-2 Transmissometers (IMPROVE Protocol)

TI 4200-2110 Transmissometer Lamp Preparation (Burn-in) Procedures

SOP 4250 Servicing and Calibration of Optical Monitoring Dataloggers

TI 4250-2000 Servicing and Calibration of Campbell Scientific 21XL Dataloggers

TI 4250-2010 Servicing and Calibration of the Handar 540/570 DCP

TI 4250-2020 Servicing and Calibration of Primeline 6723 Strip Chart Recorders

SOP 4300 Collection of Optical Monitoring Data (IMPROVE Protocol)
4-32

TI 4300-4000 Data Collection via DCP (IMPROVE Protocol)

TI 4300-4023 Transmissometer Daily Compilation and Review of DCP-Collected Data

(IMPROVE Protocol)

TI 4300-4025 Transmissometer Data Collection via Strip Chart Recorder, January 1994

SOP 4400 Optical Monitoring Data Reduction and Validation

TI 4400-5000 Transmissometer Data Reduction and Validation (IMPROVE Protocol)

SOP 4500 Optical Monitoring Data Reporting

TI 4500-5100 Transmissometer Data Reporting (IMPROVE Protocol)

SOP 4600 Optical Monitoring Data Archives

TI 4600-5010 Transmissometer Data Archives (IMPROVE Protocol)

SOP 4710 Transmissometer Field Audit Procedures
4-33

4.2 NEPHELOMETER

4.2.1 Measurement Criteria and Instrumentation

The total light scattered out of a path is the same as the reduction of light along a path due

to scattering. An ideal integrating nephelometer would collect all the light scattered by aerosols and

gases from 0E to 180E in an enclosed sample volume through a defined band of visible wavelengths

to yield a direct measurement of b . Since a nephelometer makes a point measurement, direct

scat

comparisons to collocated aerosol measurements are practical. In addition, the system can be

absolutely calibrated using clean (Rayleigh) air and various dense gases with a known multiple of

Rayleigh scattering.

The Optec NGN-2 ambient nephelometer has been developed to minimize modification of

ambient aerosols and address problems associated with Belfort nephelometers: sizing by the inlet,

large truncation error, poorly-defined optical response, and outdated, unstable electronics. The

system incorporates sensors, signal detection techniques, and electronics developed for the Optec

transmissometer previously discussed. As shown in Figure 4-5, the ambient nephelometer features

low-power (45-watt) operation, solid compact design, and digital electronics resulting in a stable

linear performance over a wide temperature range. The complete system is contained in a single unit

and is separated into three (3) chambers: optical, pump, and electronics. A cross sectional view of

the Optec NGN-2 is represented in Figure 4-6. The optical chamber features a single large door that

opens a complete side of the chamber to unrestricted ambient air flow. A stainless-steel, 24-mesh

screen covers the inlet opening to prevent insects, leaves, or other large masses from entering the

scattering chamber. The chamber is completely sealed by a double wall from the rest of the system

to prevent either heat or air from modifying the ambient aerosol as it passes through the scattering

volume. Separate and sealed from the electronics chamber, the pump chamber houses the exhaust

fan, exhaust port door, lamp cooling heat sink, clean air pump, and span gas solenoid activated inlet

valve. The exhaust air from the optical chamber passes across the finned heat sink as it exits,

removing heat from the system. The electronics chamber contains the projector lamp, chopper motor,

scattered light detector/electrometer, computer, interface board, and door motor. A thick metal

shield around the lamp absorbs and conducts most of the waste heat from the bulb, infrared heat

filter, and electronics into the heat sink located in the pump chamber. The internal CMOS computer

controls all operating functions and outputs data and system parameters in digital and analog format.

The optical design of the detector field of view, illumination cone, and scattering volume

allows for integration of scattered light from 5E to 175E. A low-voltage (13.8 VDC), quartz halogen

projector bulb with dichroic reflector illuminates an opal glass diffuser. In the light path between the

diffuser and bulb, a heat-absorbing filter blocks all radiation longer than 700 nm in wavelength and

a mechanical chopper modulates the beam at 10 Hz. A telescope with a precisely defined field of

view, collects the light from a cylindrical pencil (6 mm x 260 mm) of air slightly above the diffuser.

The opposite end of the path terminates in a light trap. A small lens behind the field stop images the

entrance pupil (objective lens) of the telescope onto the active area of a photodiode detector. This

detector measures light scattered by the gases and aerosols in the scattering volume plus light

reflected from the surfaces and stop edges in the optical chamber. This wall component of the

measured light is constant and corrected for by zero and span calibrations.
4-34

Figure 4-5. Entire Nephelometer System Set on a Tower.
4-35

Figure 4-6. Close-Up of a Nephelometer and Cross-View of Its Internal Components.
4-36

Within the optical chamber, directly in front of the diffuser, is an identical photodiode

detector. This detector directly measures the intensity of the lamp. Using the output of this detector

to normalize the scattered light signal compensates for lamp brightness changes due to power supply

fluctuations, lamp aging, and dust on the optical surfaces.

The single board computer controls all operating functions of the NGN-2 which include:

scattered light measurement, clean-air zero calibration, span gas calibration, moisture detection to

close the optical chamber door during rain or snow conditions, optical chamber temperature

measurement, initial data reduction, various error detection schemes, and diagnostic tests.

Integrating nephelometers estimate the atmospheric scattering coefficient (bscat) by directly

measuring the light scattered by aerosols and gases in the sampled air volume. Scattered radiation

from an illumination source is integrated over a large range of scattering angles, in a defined band of

visible wavelengths. Because the total light scattered out of a path is the same as the reduction of

light along a path due to scattering, the integrating nephelometer gives a direct estimate of b .

scat

The Optec, Inc. NGN-2 (Next Generation Nephelometer) uses a unique integrating open-air

design that allows accurate measurement of the scattering extinction coefficient of ambient air.

Because of the open-air design, relative humidity and temperature of the air sample are essentially

unchanged, thus the aerosol is negligibly modified when brought into the optical measuring chamber.

Extinction due to scatter can accurately be measured from Rayleigh to 100% saturated fog

conditions.

The National Park Service instituted the use of ambient nephelometers in 1993. This new

technology enhanced other methods of visibility monitoring and increased the accuracy with which

ambient optical data are measured. The nephelometer has proven to be an effective method of

collecting scattering data over a wide range of environmental conditions.

Detailed information regarding nephelometer instrumentation or operation can be found in

Model NGN-2 Open-air Integrating Nephelometer, Technical Manual for Theory of Operation and

Operating Procedures (Optec, 1993) and Standard Operating Procedures and Technical

Instructions for Nephelometer Systems (Air Resource Specialists, Inc., 1993-1996).

4.2.2 Siting Criteria

The primary siting criteria involves selecting a location that represents the air mass of interest.

A nephelometer can be easily collocated with other monitoring instrumentation such as a fine

particulate sampler, camera system, meteorological instrumentation, or a criteria pollutant monitoring

station. Because the nephelometer operates under ambient conditions, climate-controlled sheltering

is not necessary, but a precipitation/solar radiation shield is suggested.

An external power supply, calibration span gas supply, and datalogging system are required.

The low power requirements of the system accommodate line power or solar power installations.

Selected nephelometer sites should have most of the following characteristics:

! Be located in an area representative of the air mass to be monitored
4-37

! Be removed from local pollution sources and away from obstructions that could affect the

air flow in the area of the instrument

! Have AC power and telephone lines available

! Allow for orientation of the nephelometer sample inlet towards true north

! Be representative of the same air mass measured by associated aerosol (particle monitors)

and scene (camera) instrumentation

! Meet the same criteria used to site particle samplers, including:

- Have a distance from the instrument to the nearest obstruction greater than 2.5 times

the difference in heights of the instrument and the obstruction

- Be representative of regional (not local) visibility

- Be removed from local pollution influences (e.g., vehicle exhaust, wood smoke, road

dust, etc.)

! Be secure from vandalism

! Have available servicing personnel (operator)

! Be reasonably accessible during all months of the year

4.2.3 Installation and Site Documentation

Nephelometer system components are typically mounted on a 4 meter (14 foot)

meteorological tower. The tower must be installed with one face oriented to true north. The

nephelometer will be mounted on this northward face. The tower may be placed in sand or loose soil,

or rock, and is secured with guy wires. The nephelometer is mounted, along with a solar radiation

and precipitation shield, a precipitation hood, a datalogging and control subsystem, an AT/RH sensor,

a force-aspirated shield, and a span gas calibration system. The system is generally AC powered and

a telephone line is generally required.

System operation is verified and calibration is performed after all components are installed.

Upon completing the installation and verifying system operation, all operators, back-up operators,

and any other involved or interested on-site personnel should be trained, including reviewing a site

operator's manual. The manual contains technical instructions for operator maintenance,

troubleshooting, system diagrams, replacing and shipping components, and a manufacturer's manual

(ARS, Inc., TI 4100-3100, TI 4100-3350, TI 4100-3375, and Model NGN-2 Open-Air Integrating

Nephelometer Technical Manual for Theory of Operation and Operating Procedures (Optec, Inc.).

Other site documentation includes completion of a site visit trip report, photographic

documentation (including photographs of vistas in all directions from the tower, telephone and AC

wiring, local sources or obstructions to air flow to the station, landmarks used to locate the site, the

station itself, and other detailed close-ups), and documentation of any miscellaneous information

necessary to make a complete site description, including site map and site specifications (latitude,
4-38

longitude, instrument elevation, etc.)., dominating pollutant influences, (listing the source and

pollutant), type of land use within 1/2 km of the site, collocated equipment, and general climate.

4.2.4 System Performance and Maintenance

System performance and maintenance includes routine servicing, annual site visits, instrument

calibration, and annual servicing.

4.2.4.1 Routine Servicing

Routine site operator maintenance for a nephelometer should be performed weekly and

includes the following general tasks:

! Inspecting the condition of all structural hardware, nephelometer components, support

system components, and meteorological sensors.

! Verifying power system status.

! Checking system timing.

! Initiating a zero and upscale/span calibration check.

! Observing the Power-On Self Test (POST)

! Exchanging the data storage module.

! Documenting system readings.

The majority of nephelometer problems are due to moisture in the nephelometer, lamp

malfunction, electrical power outages or surges, and lightning induced voltage spikes.

4.2.4.2 Annual Site Visits

Annual site visits are performed to exchange the existing nephelometer for a newly serviced

instrument, and to train site operators in servicing and maintaining the monitoring components.

Primary tasks for a typical annual site visit include:

! Documenting initial conditions of the components.

! Verifying existing system operation and calibration (pre-removal).

! Performing clean air (zero) and upscale span calibration of the existing system.

! Conducting site inventory.

! Replacing the nephelometer, datalogging and control subsystem, and AT/RH sensor.
4-39

! Verifying replacement system operation and calibration (post-installation).

! Performing clean air (zero) and upscale span calibrations of the replacement system.

Site operator training should be performed to discuss the purpose of the monitoring program

and theory of nephelometer system operation.

4.2.4.3 Instrument Calibration

Two methods of calibrating nephelometers are the simple calibration and the complete

calibration. Simple calibrations are initiated weekly by site operators and occasionally by field

specialists to check the operation of the nephelometer system. Simple calibration includes:

! A span check consisting of ten (10) minutes of gas introduction, then an average of ten

(10) 1-minute readings of a span gas with known scattering properties, usually SUVA134a.

! A clean air zero check consisting of five (5) minutes of internal air filtering, then an

average of ten (10) 1-minute readings of particle-free air, using the nephelometer's

internal air filtering system.

Complete calibrations are performed by the field specialist or instrument technician during

installations, removals, and laboratory testing. Complete calibrations are performed upon acceptance

testing of a new instrument, installation or removal at a field site, during laboratory maintenance, or

during annual or audit site visits. Complete calibration includes:

! Nephelometer Power-On Self Test (POST) information.

! Twenty 1-minute clean air zero readings.

! Twenty 1-minute span readings.

4.2.4.4 Annual Servicing

Nephelometers are precision instruments that require careful cleaning and inspection to ensure

optimum measurement accuracy. This level of servicing must be performed in a laboratory

environment using specialized electronic and optical test equipment. Nephelometers operating in the

IMPROVE network are replaced in the field and serviced on an annual basis.

Each instrument must be fully serviced before it is reinstalled at a field site. Servicing includes

the following major tasks:

! Visual inspection

! Post-field calibration

! Cleaning
4-40

! Hardware upgrade/modifications

! Component functional tests

! Pre-field calibration

4.2.5 Data Collection

The nephelometer outputs a two-minute integrated average value for measured ambient

scattering, along with the associated status code at five-minute intervals. The on-site datalogger

collects nephelometer data, along with instantaneous measurements of air temperature and relative

humidity at five-minute intervals. At sites with telephone lines, the on-site datalogger is interrogated

daily via telephone modem. At sites where telephone access is unavailable, preliminary data from the

on-site datalogger are transmitted daily via GOES satellite and Handar data collection platforms

(DCPs).

4.2.6 Data Reduction and Validation

4.2.6.1 Data Reduction

Nephelometer data should be compiled into site-specific Level-A files. Data processing

includes processing each daily file into:

! 5-minute nephelometer, ambient temperature, and relative humidity data.

! Hourly average wind speed, wind direction, temperature, and relative humidity data.

! Hourly nephelometer status code and support system status code summaries. Data should

be reviewed daily by data analysts to determine the operational characteristics of each site.

Any apparent problem should result in a telephone call to the site operator in an attempt

to resolve the inconsistencies.

Weekly plots are generated from raw data files. Information from operator log sheets should

be checked against data collected to identify inconsistencies and errors. Inconsistent or suspicious

data can then be identified and troubleshooting procedures initiated. As completed log sheets from

nephelometer sites are received, the pertinent information (visibility conditions, instrument problems,

etc.) should be manually transferred to the weekly plots. This procedure helps to identify the exact

time of calibrations and other actions done by the site operator affecting instrument operation.
4-41

4.2.6.2 Data Validation

Nephelometer data should undergo three validation levels: Level-A, Level-0, and Level-1.

Level-A includes visual review and examination of the raw data and extracting codes, Level-0

includes searching for questionable or invalid data, and Level-1 includes computing hourly averages

and extracting data having meteorological influences.

Level-A data files should be compiled into seasonal data files for each site. Standard

meteorological seasons are defined as:

Winter December, January, and February

Spring March, April, and May

Summer June, July, and August

Fall September, October, and November.

Level-A validation begins immediately after collection. Parameters are extracted from the raw

data file and appended to site-specific seasonal data files. Automatic clean air zero calibrations and

operator-initiated clean air zero and span calibrations are extracted from the raw data file and

appended to nephelometer-specific quality assurance calibration files. The three validity codes

extracted from the raw data and assigned to the Level-A data file are:

! The power code, generated by the datalogger, is an hourly summary of any AC or DC

power problems that occurred during the previous hour.

! The nephelometer status code, is generated by the nephelometer to indicate the type of

measurement (ambient, clean air zero or span calibration), or problem (rain, lamp out,

chopper motor failure).

! The type code, indicates the source of nephelometer data (serial, analog, DCP).

Level-0 validation begins with updating the quality assurance database and calibration files.

The QA database files are site-specific files containing data validation codes and comments detailing

the history of the site's nephelometer. The QA calibration files contain all zero and span calibrations

performed on a nephelometer during a specific time period, including the initial zero and span

performed during installation. Uncertainty estimates generated with the QA calibration plots are

entered manually in the QA database files. The uncertainty estimates appear in the Level-1 data file

for reference. Level-0 validation of nephelometer and meteorological data is performed seasonally

and serves as an intermediate data reduction step. Level-A data are reviewed to identify periods of

invalid nephelometer data caused by the following:

! Burned out lamp

! Power failures

! Water contamination

! Sensor failures

! Other problems
Initial span ' Initial upscale span gas calibration & Initial clean air calibration

Designated span ' 7.1 x Rayleigh

Slope ' (designated span & Ray) / Initial span

Intercept ' (Ray & slope x zero)

b

scat ' (slope x Raw Neph Value) % Intercept

4-42

(4-20)

(4-21)

(4-22)

Level-1 validation is performed seasonally and includes the following tasks:

! Computation of hourly averages from Level-0 data

! Automatic validation of QA calibration file entries

! Conversion of hourly average data to engineering units

! Overrange/underrange checks

! Identification of nephelometer bscat data affected by meteorological interference

! Estimation of precision

Hourly averages are computed from Level-0 data. The zero calibration information in the QA

calibration files is used to calculate a calibration line for each data point. The nephelometer scattering

coefficient of total extinction is calculated by determining a calibration line for each raw nephelometer

scattering data point as follows:

! The zero is determined by interpolating (in time) between the valid clean air calibrations

prior to, and following the data point.

! The initial span is determined from the initial calibration of the instrument upon

installation.

(4-19) 

! The Rayleigh coefficient is the site-specific altitude-dependent scattering of particle-free

air.

! The designated span is determined by the span gas used during the initial calibration, and

the Rayleigh coefficient. The span gas SUVA (HFC-134a) (Dupont) has been shown to

scatter 7.1 times that of particle-free (Rayleigh) air.

! The slope and intercept of the calibration line are:

! Nephelometer data and calibrations are in unitless counts. If the units for the Rayleigh

coefficient are km , the units for b will also be in km . Nephelometer scattering is

-1 -1

scat

calculated from the calibration line as follows:
4-43

The following additional validation checks are performed to complete the Level-1 validation

process:

! Data invalid at Level-0 are invalid at Level-1.

! Calculated b data less than Rayleigh scattering are invalid. scat

! Meteorological data are not validated beyond Level-0.

Data are filtered to identify periods likely affected by meteorological interference. The

following filter criteria are used to identify these periods:

! Rate of change: If the rate of change between hourly bscat data exceeds 50 Mm , the bscat

-1

value is coded as filtered.

! Maximum: If the b data exceeds 5000 Mm , the b value is coded as filtered. scat scat

-1

! Relative humidity: If the RH corresponding to the bscat value exceeds 95%, the bscat value

is coded as filtered.

! */μ: If the standard deviation of the hourly raw nephelometer data divided by the mean

of the hourly raw data exceeds 10%, the value is coded as filtered.

Data identified as affected by meteorological interference are still considered valid.

Seasonal data plots can then be generated and reviewed to identify data reduction and

validation errors, instrument operation problems, and calibration inconsistencies. Any identified

problems should be immediately investigated and resolved by following the procedures detailed in

standard operating procedures and technical instructions.

4.2.7 Data Reporting and Archive

4.2.7.1 Data Reporting

Data reports should be prepared in a format that generally conforms to the Guidelines for

Preparing Reports for the NPS Air Quality Division (AH Technical Services, 1987). A separate data

report should be prepared for each instrument type; nephelometer data reports should contain only

nephelometer data. Reporting consists of various text discussions and graphics presentations

concerning the instrumentation and collected data. Specific contents of the reports are defined by the

contracting agencies' COTR.

Seasonal nephelometer reporting should be completed within three months after the end of

a monitoring season, and annual reporting within three months after the end of the last reported

season. Standard meteorological monitoring seasons are defined as:

Winter (December, January, and February)

Spring (March, April, and May)

Summer (June, July, and August)

Fall (September, October, and November)
4-44

Reports should contain the following major sections:

! Introduction

! Data Collection and Reduction

! Site Configuration

! Data Summary Description

! Nephelometer Data Summaries

! Summary

! References

The introduction should contain a conceptual overview of the purpose of the monitoring

program and a description of the monitoring networks. The data collection and reduction section

should include data collection methods, data file review, data validation, application of validity codes,

processing through various validation levels and discussion of file formats, and identification of

meteorological and optical interferences that affect the calculation of b from nephelometer scat

measurements.

The site configuration section should contain a brief discussion of instrumentation at each

nephelometer site, basic principles of operation, measurement principles, and data collection

specifications, including:

! A map depicting the location of all monitoring network sites.

! A Monitoring History Summary Table, listing for each monitoring site the name, type of

instrumentation, and period of operation for each instrument type.

! A Site Specifications Summary Table, listing for each monitoring site the site name,

abbreviation, latitude, longitude, and elevation of the nephelometer, the number of

readings taken each day, and the operating period during the season.

A data summary description section describes seasonal and annual data summaries. Annual

data summaries should be prepared for each site that operated during the reporting period, and should

be based on a calendar year instead of season. An example Seasonal Nephelometer Data Summary

is presented as Figure 4-7 and an example Annual Nephelometer Data Summary is presented as

Figure 4-8. The following is a detailed explanation of the contents of the data summaries in each

report.

Seasonal Nephelometer Data Summaries include the following five data presentations:

! 4-Hour Average Variation in Visual Air Quality (Filtered Data) - Plot of four-hour

averaged bscat values (without interference-influenced observations) for each day of the

reporting season. Gaps in the plot indicate that data were missing, interferenceinfluenced, or failed validation procedures.
4-45

Figure 4-7. Example Seasonal Nephelometer Data Summary.
4-46

Figure 4-8. Example Annual Nephelometer Data Summary.
4-47

! Relative Humidity - Timeline of hourly average relative humidity measurements. This

allows for a comparison of the effect of increasing relative humidity on measured b .

scat

! Frequency of Occurrence: Hourly Data - This plot is a frequency distribution of hourly

average bscat values, both unfiltered and filtered for meteorological interference. The 10%

to 90% values are plotted in 10% increments and are summarized in the table to the right

of the plot.

! Visibility Metric (Filtered Data) - This table presents mean values of filtered bscat data

affected by meteorological interference. The best, worst, and average conditions using

the arithmetic means of the 20th percentile least impaired visibility, the 20th percentile

most impaired visibility, and for all data for the season are presented.

! Data Recovery Statistics

Total Possible Hourly Averages in the Time Period - The total possible category is

calculated by subtracting the number of hourly averages included in periods when the

instrument was removed due to conditions unrelated to system performance (installation,

construction, site relocation, etc.) from the theoretical maximum number of hourly

average periods possible during a season.

Valid Hourly Averages (Filtered and Unfiltered) - the number of valid hourly averages

collected during a season. The percentage data recovery represents the number of valid

hourly averages compared to the total possible hourly averages.

Valid Hourly Averages (Filtered) - The number of valid hourly averages (excluding any

data indicating meteorological interference) collected during a season. The percentage

represents the number of valid hourly averages compared to the total possible hourly

averages.

Filtered Data Percent of Filtered and Unfiltered Hourly Averages - This percentage

collection efficiency represents the number of filtered hourly averages compared to the

number of all valid hourly averages.

Annual Nephelometer Data Summaries include three data presentations:

! Monthly Median Visual Air Quality - Plot of median monthly b for all data and for scat

filtered data only. As the visual air quality improves, bscat values decrease. A Rayleigh

atmosphere is defined by a b of approximately 10 Mm .

scat

-1

! Monthly cumulative Frequency Summaries - Table of cumulative frequency distribution

average b values for all data and for filtered data only. The 10%, 50%, and 90% values scat

are presented. Also included are data recovery statistics (total possible readings, number

and percent of collected readings, and number and percent of valid readings (both all data

and filtered data only)).

! Annual Frequency of Occurrence: Hourly Data - This plot is a frequency distribution of

hourly average b values for all data and for filtered data only. The 10% to 90% values scat

are plotted in 10% increments. Numerical values are presented in the adjacent cumulative

frequency summary table.
4-48

Nephelometer data summaries should follow their description. Summaries should be prepared

for each site that operated during the reporting period. A brief discussion of events and

circumstances that influence data recovery should follow the data summaries. Operational status

throughout the reporting period should be presented for each site in an operation summary table,

listing for each site, site name and abbreviation, the number of seasonal hourly averages possible, the

number and percentage of valid hourly averages for all data and for filtered data only, and the

cumulative frequency distribution (10%, 50%, and 90% b values) for all data and filtered data only. scat

Finally, a summary section should be included in reports, and provide a synopsis of the

nephelometer network, including changes in operation techniques, and a general conclusion of the

monitoring period in review. A reference section should include technical references (documents

cited in the report), and related reports and publications (including all prior reports pertaining to the

monitoring program).

4.2.7.2 Data Archive

Archiving of raw digital data should be performed on a monthly basis. Archiving of all raw

and processed digital data for a given season, and constants, calibration, and data processing files

should be performed on a seasonal basis, after data have been finalized and reported. All files are in

ASCII format. Files should be stored in their original formats (raw, Level-A, Level-0, and Level-1)

on magnetic tape CD-ROM. At least two copies of each media should be created; one copy should

be stored at the data processing location and the other off-site.

Hard copies of supporting documentation and reports should be duplicated and archived on

a continual basis, and include site specifications, monitoring timelines, data coordinator/site operator

correspondence, site operator log sheets, trip reports, weekly, seasonal, and annual summary plots,

instrument calibration and maintenance logs, and file audit reports. All validated Level-1 data should

be delivered as ASCII files (on PC-compatible diskettes and/or CD-ROM) to the COTR with the

quarterly and annual reports. The standard file format currently used for IMPROVE protocol

nephelometer data is presented in Figure 4-9.

4.2.8 Quality Assurance

Quality assurance of nephelometer data is performed during Level-1 validation, and includes

precision of the instrument, and annual field audits.

4.2.8.1 Instrument Precision

Precision of scattering measurements should be determined. The precision of meteorological

data are defined by the factory-specified precision for the sensors. The estimated precision of

nephelometer data for a given time period is based on calibrations performed during that time period.

The precision estimates are recorded in the site-specific quality assurance files and placed in the

Level-1 data files. The relative error (uncertainty) in scattering due to drift of the slope of the

calibration line is evaluated based on the instrument-specific zero and span checks performed. The

following statistical analysis was applied to calculate potential uncertainty:
NGN_PULL V1.91:2/15/94 02-15-1994 14:12:39------------------------------------------------------------------------------------------------------------------------------------------------------------

LEVEL-0: NGN_SEAS 1.3 3/2/94 03-02-1994 15:01:19----------------------------------------------------------------------------------------------------------------------------------------------------------

LEVEL-1: NGN_SEAS 1.3 3/2/94 03-02-1994 17:43:10----------------------------------------------------------------------------------------------------------------------------------------------------------

---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------

---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------

---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------

---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------

---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------

---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------

---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------

SITE YYMMDD JD HHMM INS BSCAT PREC VA RAW-M RAW-SD # N/A SD/M DEL MAX RH 0123456789MPM0T YINTER SLOPE AT AT-SD # AT-PR CT CT-SD # CT-PR RH RH-SD # RH-PR N/A

LOPE 931130 334 1900 014 57 0.000 XL 122.68 25.49 12 -99.0 10.0 0.10 5.00 -99 0C0000000000000 -0.0450 0.00083 -0.97 0.20 12 1.00 0.22 0.20 12 1.00 88.01 1.18 12 2.00XXXX

LOPE 931130 334 2000 014 80 0.000 V 151.25 8.71 12 -99.0 10.0 0.10 5.00 -99 0C0000000000000 -0.0457 0.00083 -1.47 0.11 12 1.00 -0.25 0.10 12 1.00 90.46 0.88 12 2.00XXXX

LOPE 931130 334 2100 014 87 0.000 V 160.71 8.58 12 -99.0 10.0 0.10 5.00 -99 0C0000000000000 -0.0465 0.00083 -1.78 0.28 12 1.00 -0.44 0.19 12 1.00 90.71 0.96 12 2.00XXXX

LOPE 931130 334 2200 014 72 0.000 XD 143.10 22.18 12 -99.0 10.0 0.10 5.00 -99 0C0000000000000 -0.0472 0.00083 -2.65 0.21 12 1.00 -1.16 0.19 12 1.00 92.16 0.32 12 2.00XXXX

LOPE 931130 334 2300 014 70 0.000 XD 142.32 21.74 12 -99.0 10.0 0.10 5.00 -99 0C0000000000000 -0.0479 0.00083 -3.17 0.15 12 1.00 -1.65 0.11 12 1.00 91.63 0.51 12 2.00XXXX

Column Number

 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

123456789012345678901234567890123456789012345678901234567890123456789012345678901234567890123456789012345678901234567890123456789012345678901234567890123456789012345678901234567890123456789012345678901

Column Data

1-4 Site Abbreviation

6-7 Year

8-9 Month

10-11 Day

13-15 Julian Day V = Valid

17-18 Hour I = Invalid

19-20 Minute < = bscat less than Rayleigh scattering

22-24 Nephelometer Serial Number XZ = Data point immediately preceded and followed by interference

26-32 bscat (Mm ) X? = Interference of type ? -1

34-40 bscat Estimated Precision (%/100)

42-43 bscat Validity/Interference Code Type (?) of Interference Letter Code

45-51 Raw Nephelometer Hourly Average (Counts) A B C D E F G H I J K L M N O

53-59 Standard Deviation of Raw Nephelometer Average (Counts) RH > max. threshold x x x x x x x x

61-62 Number of Data Points in Hourly Nephelometer Average b > max. threshold x x x x x x x x scat

64-68 (Not Used) St. Dev./Mean>threshold x x x x x x x

70-74 Standard Deviation/Mean Interference Threshold bscat rate of change > threshold x x x x x x x x

76-81 bscat Rate of Change Interference Threshold

83-88 Maximum bscat Interference Threshold

90-92 Relative Humidity Interference Threshold

94-108 Composite Nephelometer Code Summary 94-103 Nephelometer diagnostic code (internal use)

110-116 Y-intercept of Calibration Line Used to Calculate bscat 104 Number of missing data points

118-124 Slope of Calibration Line Used to Calculate bscat 105 Number of power failure codes

126-131 Average Ambient Temperature (EC) 106 Number of manual QA invalidation codes

133-138 Standard Deviation of Hourly AT Average 107 Number of Level-0 invalidated data points

140-141 Number of Data Points in Hourly AT Average 108 Number of times non-serial data were used

143-148 Estimated Precision of Ambient Temperature

150-155 Average Nephelometer Chamber Temperature (EC)

157-162 Standard Deviation of Hourly CT Average

164-165 Number of Data Points in Hourly CT Average

167-172 Estimated Precision of Chamber Temperature

174-179 Average Relative Humidity (%)

181-186 Standard Deviation of Hourly RH Average

188-189 Number of Data Points in Hourly RH Average

191-196 Estimated Precision of Relative Humidity

197-200 (Not Used)

Note: The first 10 lines are for data reduction information.

Figure 4-9. Standard ASCII File Format IMPROVE Protocol Integrating Nephelometer Visibility Data.
m '

(b

scat,s

& b

scat,o

)

(V

s

(t) & V

o

(t))

b

scat(t) ' bscat,o

% m(V(t) & V

o

(t))

m(t) ' (b

scat,s

& b

scat,o

)/(V

s

(t) & V

o

(t))

b'

scat(t) ' bscat,o

% m(t) (V(t) & V

o

(t))

relative error ' (b

scat(t) & b'scat(t))/bscat(t)

relative error ' ((m & m(t)) (V(t) & V

o

(t))) /(b

scat,o

% m(V(t) & V

o

(t)))

' (m & m(t)) /(b

scat,o

/(V(t) & V

o

(t)) % m)

' | (m & m(t)) /(b

scat,o

/(V(t) & V

o

(t)) % m) |

4-50

(4-23)

(4-24)

(4-25)

(4-26)

(4-27)

V(t) = Normalized nephelometer reading at time t

V (t) = Normalized clean air reading at time t o

V (t) = Normalized SUVA 134a reading at time t s

b = Scattering coefficient for clean air scat,o

bscat,s = Scattering coefficient for SUVA 134a

Vo = Average normalized clean air reading

Vf = Average normalized SUVA 134a reading

b (t) = Theoretical scattering coefficient tat time t scat

m = Slope of the calibration line used to calculate

the theoretical scattering coefficient b (t) scat

Given a normalized nephelometer reading V(t), the theoretical b at time t is: scat

assuming that V (t) and V(t) are known without error. o

The slope of the calibration line is not constant as defined above, but changes (drifts) with time. The

actual slope of the calibration line at time t is:

The actual b (denoted b' ), given a nephelometer reading V(t), is: scat scat

The relative error between the theoretical b and actual b' is: scat scat

(4-28)
| relative error | ' | (b

scat(t) & b'scat(t)) /bscat(t) |

| relative error | < | (m & m(t)) /m |

| m & m(t) | < 2s

| (b

scat(t) & b'scat(t))/bscat(t) | < | 2s / m |

| relative error | < t

k,0.025

( s

m

/ m

4-51

(4-29)

(4-30)

(4-31)

(4-32)

(4-33)

The magnitude of the relative error is:

The magnitude of the relative error is bounded by the slopes such that:

Assuming that the calculated slopes, m(t), of the calibration lines are normally distributed about the

average slope m with a standard deviation s, then for a probability (confidence level) of 95%:

so that

Assuming that s is estimated by sm with k degrees of freedom, based on k+1 sample values of m(t),

and using the two-tailed t distribution, the relative error at a 95% confidence level (which for a two

tailed t distribution is read from the 97.5 column of the t table) is:

4.2.8.2 Instrument Audits

The nephelometer field audit verifies accurate on-site nephelometer calibrations by comparing

calibrations made with an audit calibration system. The audit results assess the validity of operatorperformed calibrations, and how the instrument has changed since installation, by comparing the audit

calibration to the installation calibration.

Nephelometers are typically audited at least once a year, but can be audited at any time. A

standard audit begins with a pre-inspection audit calibration (checking the physical condition of the

instrument, performing a calibration using the station calibration system, then a calibration using an

audit calibration system). The nephelometer is then inspected to verify that the instrument is capable

of making an ambient reading and that the instrument's components are not contaminated. The

inspection includes checking the inlet screen, fan outlet, light trap, and clean air filter. Finally, a postinspection is performed. The post-inspection audit calibration represents the state of the instrument

after the audit is complete. The calibration is identical to the pre-inspection audit calibration.

Following the audit, the nephelometer components are verified that they are in their

operational configuration and that the nephelometer is in ambient mode.
4-52

4.2.9 Data Analysis and Interpretation

Nephelometer data are a measure of the scattering component of atmospheric extinction.

Data are typically presented in scattering units, expressed in kilometers (km ). These units are

-1

directly stored in the data files.

Nephelometer data provide a quantitative measure of visibility conditions. Data can be used

to provide the basis for background conditions and trend analysis; however, data must be combined

with associated meteorological and aerosol concentrations to understand the source and/or

composition of the impairment observed. They must also be combined with absorption data to get

values of total extinction.

4.2.10 Nephelometer Standard Operating Proccedures and Technical Instructions

The Air Resource Specialists, Inc. document entitled Standard Operating Procedures and

Technical Instructions for Nephelometer Systems, includes the following nephelometer-related

Standard Operating Procedures and Technical Instructions:

SOP 4050 Site Selection for Optical Monitoring Equipment (IMPROVE Protocol)

TI 4050-3000 Site Selection for Optec NGN-2 Nephelometer Systems

SOP 4070 Installation and Site Documentation for Optical Monitoring Equipment

TI 4070-3000 Installation of Optec NGN-2 Nephelometer Systems (IMPROVE Protocol)

TI 4070-3001 Site Documentation for Optec NGN-2 Nephelometer Systems

SOP 4100 Nephelometer Maintenance (IMPROVE Protocol)

TI 4100-3100 Routine Site Operator Maintenance Procedures for Optec NGN-2 Nephelometer

Systems (IMPROVE Protocol)

TI 4100-3101 Routine Site Operator Maintenance Procedures for Optec NGN-2 Nephelometer

Systems (IMPROVE Protocol) Zirkel Special Study

TI 4100-3150 Routine Site Operator Maintenance Procedures for Optec NGN-2 Nephelometer

Systems (CASTNet Installations)

TI 4100-3350 NGN-2 Nephelometer Monitoring System Diagrams and Component Descriptions

TI 4100-3375 Replacing and shipping Nephelometer System Components

TI 4100-3400 Nephelometer Annual Laboratory Maintenance (IMPROVE Protocol)

SOP 4115 Annual Site Visits for Optical Monitoring Instrumentation (IMPROVE Protocol)
4-53

TI 4115-3005 Annual Site Visit Procedures for Optec NGN-2 Nephelometer Systems

(IMPROVE Protocol)

SOP 4200 Calibration of Optical Monitoring Systems (IMPROVE Protocol)

TI 4200-2000 Calibration of Optec NGN-2 Nephelometers (IMPROVE Protocol)

SOP 4250 Servicing and Calibration of Optical Monitoring Dataloggers

TI 4250-2000 Servicing and Calibration of Campbell 21X Dataloggers

TI 4250-2010 Servicing and Calibration of the Handar 540A/570A DCP

SOP 4300 Collection of Optical Monitoring Data (IMPROVE Protocol)

TI 4300-4000 Data Collection Via DCP (IMPROVE Protocol)

TI 4300-4002 Nephelometer Data Collection Via Telephone Modem (IMPROVE Protocol)

TI 4300-4004 Nephelometer Data Compilation and Review of DCP-Collected Data (IMPROVE

Protocol)

TI 4300-4006 Nephelometer Data Collection Via Campbell Scientific Data Storage Module

(IMPROVE Protocol)

SOP 4400 Optical Monitoring Data Reduction and Validation

TI 4400-5010 Nephelometer Data Reduction and Validation (IMPROVE Protocol)

SOP 4500 Optical Monitoring Data Reporting

TI 4500-5000 Nephelometer Data Reporting (IMPROVE Protocol)

SOP 4600 Optical Monitoring Data Archives

TI 4600-5000 Nephelometer Data Archives (IMPROVE Protocol)

SOP 4700 Optec NGN-2 Nephelometer Audit Procedures (IMPROVE Protocol)
5-1

5.0 SCENE MONITORING

As an example of an existing visibility-related scene monitoring program, this section

describes IMPROVE scene monitoring and data management techniques. References made to

manufacturers or trade names are not intended to constitute EPA endorsement or recommendations

for use. New or improved instruments, instrument upgrades, and methods of monitoring are

continually being developed.

Scene monitoring provides a qualitative representation of the visual air quality in the area of

interest. The photographic record documents the appearance of a scene. Scene characteristics

include color, texture, contrast, clarity, observer visual range, and other descriptive terms.

Photography is uniquely suited for identifying ground-based or elevated layers or plumes that may

impact Class I or protected areas, as well as documenting conditions for interpreting aerosol and

optical data.

IMPROVE protocols recommend that color photographs (35 mm slides) be taken several

times a day. The data collection schedule can be tailored to capture periods when visibility

impairment is most likely at specific sites. For example, photographs during stable periods may yield

more information in areas susceptible to ground-based or elevated layered hazes. Time-lapse movies

(generally time-lapse video or super 8 mm film) have also been used at selected monitoring sites and

during special studies to document the visual dynamics of a scene or source. To the extent possible,

the selected scene should be collocated with or include aerosol and optical monitoring equipment,

so that conditions documented by photography can aid in the presentation of these data.

Sections 5.1 and 5.2 describe the monitoring criteria, instrumentation, installation and site

documentation, system performance and maintenance, data collection, reduction, validation,

reporting, and archive, quality assurance, and data analysis and interpretation required for 35 mm

slide and time-lapse photography, respectively. Example users' manuals and manufacturers'

specifications are provided in Appendix B.

5.1 35 mm SLIDE PHOTOGRAPHY

5.1.1 Measurement Criteria and Instrumentation

Automatic 35 mm camera systems take color photographs of selected vistas at user-selected

times. Day-to-day variations in visual air quality captured on 35 mm color slides can be used to:

! Document how vistas appear under various visual air quality, meteorological, and

seasonal conditions. Scene characteristics include observer visual range, scene contrast,

color, texture, and clarity.

! Record the frequency that various visual air quality conditions occur (e.g., incidence of

uniform haze, layered haze, or weather events).

! Provide a quality assurance reference for collocated measurements.
5-2

! Determine the visual sensitivity of individual areas or views to variations in ambient air

quality.

! Identify areas of potential impairment.

! Estimate the optical properties of the atmosphere under certain conditions.

! Provide quality media for visually presenting program goals, objectives, and results to

decision-makers and the public.

! Support computer image modeling of potential impairment.

! Support color and human perception research.

Photographic slides, however, do not provide quantitative information about the cause of

visibility impairment. Aerosol and optical properties of the atmosphere must be independently

monitored where cause and effect relationships are required.

Automatic camera systems should meet the following requirements:

! Have a rugged, reliable 35 mm camera body with automatic film winder. The camera's

exposure meter must be designed so it is on only the actual time of exposure and not

continuously operating.

! Have an appropriate size lens to capture the full extent of a scenic vista (usually a 135 mm

or 50 mm lens).

! Have a databack that will imprint on the film the day and time the exposure was taken.

! Have a battery-powered, programmable timer that will trigger the camera at least three

times daily, or on selected days of the week.

! Be able to operate within an ambient temperature range of 0EF to 120EF. (To achieve

the specification of 0EF, a heated and insulated shelter requiring 110V line power is

recommended).

! Be housed in a stand-alone, lockable, weatherproof environmental enclosure.

! Be able to operate unattended for at least 10 days or a maximum of 30 days.

Figure 5-1 is a photograph of the automatic camera station in a remote mountain location.

Figure 5-2 shows the components of a station, including a weatherproof shelter and mounting post,

cameras, automatic timers, and batteries. The station can be outfitted with a variety of camera

configurations.

Detailed information regarding camera instrumentation or operation can be found in Standard

Operating Procedures and Technical Instructions for Automatic Camera Systems (Air Resource

Specialists, Inc., 1993-1996).
5-3

Figure 5-1. Automatic Camera System in a Remote Location.

Figure 5-2. Station Components.
5-4

5.1.2 Siting Criteria

Stations are normally located so that the camera views a recognizable, important vista that

highlights the character of the area being monitored. When selecting a site, servicing, installation

logistics, aesthetics, and security should also be considered. At many locations, the camera is located

with other monitoring equipment such as a transmissometer, a nephelometer, an aerosol sampler or

other monitoring systems that support comprehensive air quality evaluations.

To assure consistent, quality data and minimize data loss, selected camera sites should have

most or all of the following characteristics:

! Be located to photograph a highly-visited scenic vista or important scenic features of the

visibility sensitive area being monitored

! View north or away from direct sun angles to minimize lens flare and overexposure

! Include a vista encompassing the same air mass monitored by associated aerosol (particle

monitors) and/or optical instrumentation

! Be removed from local pollution sources (e.g., vehicle exhaust, wood smoke, road dust,

etc.)

! Be representative of regional (not local) visibility

! Be secure from vandalism

! Have available servicing personnel (operator)

! Be reasonably accessible during all months of the year

! Be located considering environmental factors (e.g., snow depth, temperature extremes,

precipitation type and amount, relative humidity, etc.) that could affect camera operations

or site accessibility

! Be located free from viewing obstructions or interferences

! Have local land manager or land owner cooperation

5.1.3 Installation and Site Documentation

Before the automatic camera system can be installed, a mounting post should be appropriately

aligned on the selected monitoring vista (target). Mounting post installation procedures depend on

the type of installation and surface material to which the post is mounted. The posts may be attached

to pre-existing concrete or rock, in soil, in a wood platform, or to a new concrete pad. Enclosure

installation involves three processes: mounting the sunshield, the enclosure, and the camera

equipment.

Following the completion of the camera system installation and configuration, operator

training should be performed. Site operators should be trained on camera system requirements and
5-5

routine maintenance procedures. A Site Operator's Manual for Automatic Visibility Monitoring

Camera Systems should be provided. This manual contains standard operating procedures and

technical instructions applicable to the specific camera monitoring equipment located at the site.

Additional manufacturer's instruction booklets and pertinent maintenance documentation forms

should also be provided.

Site documentation for the automatic camera system visibility monitoring station includes

completion of the Visibility Monitoring Photographic Site and Target Specifications Form, which

includes: site name; focal length; number of observations per day; elevation, latitude, and longitude

of the camera location; map reference; site abbreviation; installation date and name of the installer;

site contacts and mailing/shipping address; vista name, distance, elevation, bearing, and elevation

angle; and site path elevation; vista cover type; and photographic reference.

5.1.4 System Performance and Maintenance

System performance and maintenance of 35 mm automatic camera systems includes routine

servicing and biannual laboratory servicing. Both of these servicing types are discussed in the

following subsections.

5.1.4.1 Routine Servicing

Site operator maintenance for an automatic camera system should be performed on a routine

basis. Routine servicing schedules are based on the number of photographs taken each day. A

common monitoring schedule includes taking three photographs a day at 0900, 1200, and 1500.

Assuming this schedule, site operators service the camera approximately every 10 days to change

film, check the performance of the camera(s), clean the system components, and perform scheduled

preventive maintenance. Identifying and troubleshooting system malfunctions are carried out as

required.

Regular servicing and the identification and documentation of film rolls are essential. During

each routine site visit, the operator should thoroughly document all pertinent data collection

information, any maintenance performed, and any equipment or monitoring inconsistencies. If further

action is necessary, immediate corrective action should be taken.

Regular maintenance performed at each film change includes:

! Inspecting the overall system and cleaning the shelter window.

! Verifying that the film has advanced in the camera and that camera settings are correct.

! Rewinding and removing the film, and completing a film canister label.

! Loading new film and completing a film canister label.

! Inspecting and cleaning the camera lens.

! Checking system batteries.
5-6

! Checking databack settings.

! Checking timer settings.

! Photographing the film documentation board.

! Aligning the camera.

! Verifying system operation.

! Completing documentation:

- Documenting any equipment or monitoring discrepancies found.

- Documenting all servicing or maintenance actions performed.

- Describing weather conditions.

- Describing visibility conditions.

! Closing and locking the camera enclosure.

! Mailing the film and a copy of the documentation.

Scheduled maintenance performed as required includes:

! Changing 35 mm databack batteries annually.

! Changing 35 mm camera batteries every 6 months.

! Changing 35 mm batteries every 6 months.

5.1.4.2 Biannual Laboratory Servicing

Servicing all cameras and support systems is performed by mailing replacement parts and/or

systems to the site operators and repairing those components returned. Operational camera systems

are biannually cycled out of a monitoring network. Shelters remain in place and the cameras and

timers are cycled for laboratory maintenance.

Automatic camera system maintenance is normally provided by local factory-authorized repair

facilities capable of performing the following:

! Cleaning, lubricating, and adjusting of all 35 mm camera components

! Automatic exposure calibration checks
5-7

! Ambient/cold testing of:

- Current draw

- Shutter speed and curtain travel time

- Automatic exposure meter readout

- Film transport

! Lens focus checks

! Battery and camera cabling integrity checks and necessary repair

! Timer circuitry checks

5.1.5 Data Collection

Collection procedures include site servicing visits to perform film changes at the required

interval, and the mailing of exposed film rolls and accompanying documentation. 

Kodachrome ASA-64 color slide film (36-exposure rolls) should be used. The film possesses

fine grain and excellent color reproduction qualities. Enough film (from a single emulsion number)

should be purchased from a Kodalux direct distributor to cover several months of a monitoring

program. Film should be refrigerated or frozen until used.

When servicing a site, the operator should complete a film canister label and attach it to each

new film roll loaded into the camera. A photograph of a photo documentation board should be taken

as the first exposure of each roll. The board should contain monitoring site identification, date, time,

and film roll number. Each camera should also be equipped with a databack that records the date and

time that the photograph was taken on the lower right corner of each photograph. When the operator

returns to remove the film, he or she should complete the information on the label, place the film in

a padded envelope, and mail it along with a status/assessment sheet via first class mail for processing.

All film should be sent by courier to a Kodalux processing laboratory. Roll and film

processing mailer numbers should be documented so all shipments can be tracked and traced if

necessary, by the mailer number. Receipt of the developed film from Kodalux should be recorded.

Film rolls should be stored chronologically in a pollutant-free controlled environment.

5.1.6 Data Reduction and Validation

5.1.6.1 Data Reduction

Processed 35 mm slides should be first checked for extraneous photographs. Only slides that

represent the standard date and time sequence of the correct vista or were taken purposely for

documentation or as a supplemental visibility document should be kept. Any blank slides preceding

or following the normal date/time sequence should be discarded.
5-8

Extraneous 35 mm slides should be removed and documentation and target photographs

should be arranged in polyethylene protector sheets by date and time. Following verification of slide

arrangement, each slide should be numbered sequentially and stamped with a four-letter site code.

The slide set should be placed in a manila folder along with a completed slide log and the associated

status/assessment sheet.

Slides should also be reviewed to verify that the vista alignment is correct, the slides are in

proper focus, the databack date and time is recorded on the film, the slides are arranged in proper

order, and that no exposure inconsistencies exist. Any discrepancies should be documented by site

and roll number and corrective action should be initiated.

5.1.6.2 Data Validation

Not all 35 mm slides undergo a qualitative coding process. Slides are only coded if summaries

of observed slide conditions are required by the contracting agency. Each photographic slide

designated for coding should be visually reviewed, chronologically numbered, and assigned a two-,

four-, or client-specified-digit slide condition code. These codes document the visual conditions

present on each slide, including sky conditions, observed hazes, plumes, weather conditions, unusable

or missing observations, anomalies, or client-specified areas of interest.

Qualitative slide coding is normally performed at the end of a season on all slides collected

during the season. Standard meteorological seasons are:

Winter December, January, and February

Spring March, April, and May

Summer June, July, and August

Fall September, October, and November

To begin the coding process, each valid slide should be viewed on a light table with the naked

eye and an eight-power, hand-held lens. Codes should be marked directly on the slides (slide frames)

and later entered into site-specific digital files. An example code key sheet is presented as Table 5-1.

Codes may be tailored to the contracting agency's needs. For example, codes may be developed that

define amount of urban or industrial activity in the view, or that define observed conditions in Class

I and non-Class I areas of the view. Digital files are created after all slides from a season are coded

and are then used to prepare qualitative summaries of observed haze types. Digital files can be

searched in a variety of ways to fulfill specific data reports.

All photographs should be considered valid except for:

! Supplemental visibility photographs.

! Out-of-alignment photographs (e.g., the target is not in the picture).

! Blank photographs.

! Extremely under- or overexposed photographs.
5-9

Table 5-1

Example Slide Condition Code Key

Sky Conditions Code Description

0 No clouds No clouds visible anywhere in the sky.

1 Scattered clouds < half of Less than one-half of the sky has clouds present.

sky

2 Overcast > half of sky More than one-half of the sky has clouds present.

5 Weather concealing scene Clouds or precipitation are such that determination of the

sky value is impossible.

9 No observation or cannot To be used with target code of 9 or if sky value cannot be

be determined determined due to reasons other than weather.

Layered Haze Code Description

0 No layered haze No layered haze boundary (intensity of coloration edge) is

perceptible.

1 Ground-based layered Only a single-layered haze boundary is perceptible with the

haze only haze layer extending to the surface.

2 Elevated layered haze only An elevated layered haze with two boundaries is perceptible;

e.g., horizontal plume.

3 Multiple haze layers More than a single ground-based or elevated layered haze is

perceptible. This can be multiple ground-based layers or a

combination of both.

5 Weather concealing scene Cloud or precipitation are such that determination of the

presence of layered hazes is impossible.

9 No observation or cannot To be used with target code of 9 or if a layered haze value

be determined cannot be determined due to reasons other than weather.
5-10

! Out-of-focus photographs.

! Photographs taken through a fogged or icy shelter window.

An IBM PC-compatible computer and specific software are used to create digital files. Files

are named by site and season and contain site abbreviation, slide number, date, time, and slide

condition codes. Digital files are used to prepare qualitative summaries of observed haze types.

5.1.7 Data Reporting and Archive

5.1.7.1 Data Reporting

Data reports should be prepared in a format that generally conforms to the Guidelines for

Preparing Reports for the NPS Air Quality Division (AH Technical Services, 1987). A separate data

report should be prepared for each instrument type; photographic data reports should contain only

photographic data. Reporting consists of various text discussions and graphics presentations

concerning the instrumentation and collected data. Specific contents of the reports are defined by the

contracting agency.

Seasonal photographic reporting should be completed within three months after the end of

a monitoring season, and annual reporting within three months after the end of the last reported

season. Standard meteorological monitoring seasons are defined as:

Winter (December, January, and February)

Spring (March, April, and May)

Summer (June, July, and August)

Fall (September, October, and November)

Reports should contain the following major sections:

! Introduction

! Data Collection and Reduction

! Photographic Data Summaries

! References

The introduction should contain a conceptual overview of the purpose of the monitoring

program and specific objectives and tasks of the program.

The data collection and reduction section includes discussions of site configuration, camera

system components, and basic system operation. Also included should be a map of the United States

depicting the location of each monitoring site, and a monitoring history summary table, describing

each monitoring site, the type of instrumentation installed, and the historical periods of operation for

each instrument. The section briefly describes the slide review and coding process, as well as the

compilation of the summary tables, and the quality control and quality assurance procedures applied

during the data collection and reduction process.
5-11

Photographic data may be presented in various forms depending on contracting agency

requirements. Each type of data summary should be accompanied by an explanation. Each report

contains a Site and Target Specifications Summary Table listing complete target and site

specifications for each scene monitoring site operational during the period, (including site name and

abbreviation, latitude, longitude, and elevation of the camera monitoring site; target name, elevation,

distance, azimuth, and elevation angle of the site path; number of observations taken per day; and

operating period during the reported period). A Qualitative Slide Analysis Summary Table provides

a site-by-site accounting of observed haze and target-concealed conditions for each site that operated

during the reporting period.

The section also includes a brief discussion of slide and digital file archive, a discussion of the

events and circumstances that influenced data recovery, operational summaries for each site including:

site name and abbreviation, data collection period, number of total possible observations, collection

efficiency (number and percent), a description of the cause or causes of data loss or problem

description, and resolutions and/or recommendations relating to the noted operational problems.

The reference section includes technical references (documents that are cited in the report),

and related reports and publications (all prior reports pertaining to the monitoring program).

Supplemental data products that may accompany data reports include:

! Slide duplicates or digital images representative of good, medium, and poor visibility

conditions for each season that sufficient data are available for qualitative review.

! PC-compatible diskettes of seasonal slide condition code files.

! Optical (nephelometer/transmissometer) data summaries for collocated optical monitoring

equipment.

5.1.7.2 Data Archive

All original slides should be stored in non-gassing, polyethylene protector sheets and filed by

site, season, and date (roll). All files should be kept alphabetically in standard file cabinets. Even

under the most ideal storage conditions, film emulsions will slowly degrade over time.

Supporting hard copy documentation, including status/assessment sheets, slide coding sheets,

film tracking logs, and correspondence should be filed in standard file cabinets, in chronological order

by site.

Digital data produced from 35 mm photographic slides (containing qualitative condition

codes) should be archived on a seasonal basis. ASCII files should be stored in the original format

(non-compressed) on diskette. Two copies of each archive should be created.
5-12

5.1.8 Quality Assurance

Internal quality assurance of automatic camera equipment is based primarily on visual review

of developed visibility monitoring film. Alignment, exposure, and data collection efficiency can all

be assessed from developed film. Any noted problems should initiate corrective action. Ongoing

review of film and site operator identified problems often initiates corrective actions.

5.1.9 Data Analysis and Interpretation

Photographic data analysis can be qualitative only. Only conditions visually seen in the 35 mm

slides can be compiled and interpreted. A more thorough analysis would be to use the slides in

conjunction with other forms of data, such as optical or aerosol data. Quantitative analysis of slides

has been used in the past, but has been determined to not be an accurate method of air quality or

visibility analysis.

5.1.10 Scene Monitoring Standard Operating Procedures and Technical Instructions

The Air Resource Specialists, Inc. document entitled Standard Operating Procedures and

Technical Instructions for 35 mm Scene Monitoring Systems, includes the following scene monitoring

Standard Operating Procedures and Technical Instructions:

SOP 4005 Procurement and Acceptance Testing Procedures for Scene Monitoring

Equipment

TI 4005-1000 Procurement and Acceptance Testing Procedures for 35 mm Automatic Camera

Systems

SOP 4055 Site Selection for Scene Monitoring Equipment

SOP 4075 Installation and Site Documentation for Scene Monitoring Equipment

SOP 4120 Automatic Camera System Maintenance (IMPROVE Protocol)

TI 4120-3100 Routine Site Operator Maintenance Procedures for 35 mm Automatic Camera

System - Canon EOS 630

TI 4120-3110 Routine Site Operator Maintenance Procedures for 35 mm Automatic Camera

System - Contax 167MT

TI 4120-3120 Routine Site Operator Maintenance Procedures for 35 mm Automatic Camera

System - Contax 137 MA

TI 4120-3130 Routine Site Operator Maintenance Procedures for 35 mm Automatic Camera

System - Olympus OM2N

TI 4120-3140 Routine Site Operator Maintenance Procedures for 35 mm Automatic Camera

System - Pentax PZ-20
5-13

TI 4120-3300 Troubleshooting and Emergency Maintenance Procedures for 35 mm Automatic

Camera System - Canon EOS 630

TI 4120-3310 Troubleshooting and Emergency Maintenance Procedures for 35 mm Automatic

Camera System - Contax 167MT

TI 4120-3320 Troubleshooting and Emergency Maintenance Procedures for 35 mm Automatic

Camera System - Contax 137 MA

TI 4120-3330 Troubleshooting and Emergency Maintenance Procedures for 35 mm Automatic

Camera System - Olympus OM2N

TI 4120-3340 Troubleshooting and Emergency Maintenance Procedures for 35 mm Automatic

Camera System - Pentax PZ-20

TI 4120-3500 Biannual Laboratory Maintenance Procedures for 35 mm Automatic Camera

Systems

SOP 4305 Collection of Scene Monitoring Photographs and Film (IMPROVE Protocol)

TI 4305-4000 Collection, Processing, and Handling of 35 mm Slide Film

SOP 4420 Scene Monitoring Qualitative Data Reduction

TI 4420-5000 Qualitative Scene Coding and Data Reduction of 35 mm Color Slides

SOP 4520 Scene Monitoring Data Reporting

TI 4520-5000 Scene Monitoring Reporting of 35 mm Slides (IMPROVE Protocol)

SOP 4610 Scene Monitoring Archives

TI 4610-5000 35 mm Photographic Slide Archives

TI 4610-5020 Slide Spectrum Archives, (In process)

TI 4610-5030 Photographic-Based Teleradiometric Data Archives

5.2 TIME-LAPSE PHOTOGRAPHY

5.2.1 Measurement Criteria and Instrumentation

Time-lapse images have always been a valuable and convenient tool to document, view, and

interpret actual dynamic events in reduced time. Time-lapse images have been used to support

scientific studies, document project activities, support legal enforcement, and present important

findings to decision-makers and the public.

Today, high resolution video systems are replacing film for recording time-lapse images.

Advancing video technology provides a wide range of imaging options, and systems can be easily
5-14

installed and operated. Time-lapse imaging reduces the viewing time of long term dynamic events

to practical levels. The understanding and interpretation of certain dynamic patterns can actually be

enhanced through the use of time-lapse images. The ability to review high resolution video images

at a variety of speeds enhances the interpretive power of the media. Reverse and stop frame functions

further aid the interpretive process.

Time-lapse monitoring can be accomplished by 8 mm film or by videotape. The major

advantages of videotape over film are that the videotape images are immediately available for viewing

(you do not have to wait to develop film) and reproduction costs are minimal as compared to film

products. Also, 8 mm cameras and film are becoming obsolete in the camera industry.

Applications of time-lapse monitoring include:

! Air Pollution - Urban and rural haze dynamics, and source-specific emission surveillance

(industrial plumes or emissions from hazardous waste remediation projects) can be

documented.

! Weather Observations - The day's weather can be documented to support academic

studies as well as daily television news summaries.

! Construction Projects - Monitoring may track progress of high-rise construction, as well

as monitoring activities and emissions of earth moving projects.

! Traffic Studies - The level of service at busy intersections, and a wide range of traffic

count-related applications may be monitored.

! Industrial Processes - Applied engineering practices or equipment performance may be

evaluated, and production may be tracked.

! Surveillance - The use of a recreational area may be tracked, or legal investigations may

be supported.

Time-lapse images do not provide quantitative information about the cause of visibility

impairment. Aerosol and optical properties of the atmosphere must be independently monitored

where cause and effect relationships are required.

Time-lapse video systems have two primary components, a camera and a recorder (see

Figures 5-3 and 5-4). Systems can be configured to meet a wide range of monitoring requirements.

In its simplest configuration, a camera can be positioned to view a selected scene with the recorder

programmed for daily on and off recording times. A range of time-lapse intervals can easily be

selected on the recorder. More advanced systems can employ options such as programmable,

motorized pan/tilt camera housings and zoom lenses that respond to a series of commands throughout

the day, each with a different viewing direction, inclination, field of view, and focus setting.
5-15

Figure 5-3. Time-Lapse Video Recording Module (Time-Lapse Recorder,

 Monitor, and Power Systems).

Figure 5-4. Weatherproof Video Camera Enclosure.
5-16

The video camera and selected lens can be conveniently housed in a weatherproof, heated and

ventilated shelter that can be easily mounted to almost any structure. The recorder must be housed

in a clean, dry environment at or near room temperature. Custom heated and cooled shelters can be

fabricated for remote locations, but for many installations it is often convenient to use an existing

building. The camera and recorder units are connected with signal and power cables. Systems

require 115 volt AC service. A broad range of lenses are available for the camera with wide-angle,

telephoto, or zoom options. The recorder uses a high resolution S-VHS format that yields extremely

high quality images.

The 8 mm camera can be conveniently housed in a weatherproof shelter identical to, or in

conjunction with 35 mm cameras (see Figure 5-2).

Detailed information regarding video camera instrumentation or operation can be found in

Standard Operating Procedures and Technical Instructions for 8 mm Time-Lapse Scene Monitoring

Systems (Air Resource Specialists, Inc., 1993-1996).

5.2.2 Siting Criteria

Time-lapse monitoring stations are normally located so that the camera views a recognizable,

important vista that highlights the character of the area being monitored. When selecting a site,

servicing, installation logistics, aesthetics, and security should also be considered. At many locations,

the camera is located with other monitoring equipment such as a transmissometer, a nephelometer,

an aerosol sampler or other monitoring systems that support comprehensive air quality evaluations.

To assure consistent, quality data and minimize data loss, selected camera sites should have

most or all of the following characteristics:

! Be located to photograph a highly-visited scenic vista or important scenic features of the

visibility sensitive area being monitored

! View north or away from direct sun angles to minimize lens flare and overexposure

! Have AC power available (video systems only)

! Be secure from vandalism

! Have available servicing personnel (operator)

! Be reasonably accessible during all months of the year

! Be located considering environmental factors (e.g., snow depth, temperature extremes,

precipitation type and amount, relative humidity, etc.) that could affect camera operations

or site accessibility

! Be located free of viewing obstructions or interferences

! Have local land manager or land owner cooperation
5-17

5.2.3 Installation and Site Documentation

Installation is site-specific, depending on the topography, project goals, and client's needs.

Time-lapse systems may be installed on a post, a tower, or attached to a building.

Following the completion of the time-lapse system installation and configuration, operator

training should be performed. Site operators should be trained on camera system requirements and

routine maintenance procedures. Additional manufacturer's instruction booklets and pertinent

maintenance documentation forms should also be provided.

Site documentation for a time-lapse system monitoring station includes completion of site

specifications (station name, number of observations per day, elevation, latitude, longitude, map

reference, site abbreviation, installation date and name of the installer, site contacts and

mailing/shipping address).

5.2.4 System Performance and Maintenance

Videotape and 8 mm time-lapse systems are easy to configure, install, and operate. Videotape

recorder programming is done on-screen similar to a home VCR. The recorder can be programmed

for record/playback speeds from real time (2 hours per videotape) to various time-lapse intervals up

to 480 hours per videotape. Depending on the user-selected record interval and programmed on and

off times, the recorder can collect from several days to several weeks of time-lapse images on a single

videotape. An operator can be easily trained to perform regular system servicing and tape exchanges.

A TV monitor is usually included on-site so that operators can verify system operation. Recorded

S-VHS tapes can be played back on the recorder unit or any S-VHS compatible VCR. Tapes can be

duplicated to VHS format for more widespread distribution and review on any VCR.

The 8 mm cameras may be programmed to photograph one frame per second to one frame

per minute. The film rolls may last several days to weeks, depending on the monitoring schedule.

Operators should perform site servicing visits once a week to once a month, depending on

the monitoring schedule. Servicing visits include changing the film or videotape, completing an

operations log, identifying film rolls or videotapes, and inspecting all system components for correct

operations during each film/tape change. Fresh film or tape is loaded into the cameras, lenses and

enclosure windows are cleaned, all batteries are checked, the camera and timer settings are checked,

the cameras are aligned, and film/tape and documentation logs are mailed.

5.2.5 Data Collection

Site operators should be trained and provided with an operator's kit that includes a supply of

videotape cassettes or film rolls, cassette or film mailers, status/assessment sheets, and system

operating instructions.

The time-lapse systems may be programmed to record a full day of tape (client-specified

on/off times). The videotape system records on S-VHS tape and is capable of operating unattended

for up to 30 days. Site operator(s) should service the site bi-monthly to inspect the system and clean

the camera optics.
5-18

All videotapes and film should be mailed by the site operator(s) along with site

status/assessment sheets. Film rolls should be sent to Kodak for developing. When they arrive back,

or when the videotapes arrive, they should be initially reviewed to verify that the system was working

properly. Any noted inconsistencies should initiate immediate corrective action. All tapes and rolls

should be numbered. The location of each morning and afternoon period should be recorded from

the videotapes.

5.2.6 Data Reduction and Validation

5.2.6.1 Data Reduction

Videotapes and film rolls should be reviewed to document observed weather, activity,

emissions, visibility, and anomaly events. Tapes should be reviewed in S-VHS format on a high

resolution monitor. Qualitative 2-digit (or other) tape/film condition codes are assigned to each

morning and afternoon period of tape. The codes identify specific visibility conditions in the

following general categories:

! Sky conditions

! Urban activity

! Project-interest related industrial emissions

! Uniform haze intensity

! Layered haze occurrence

! Visual anomalies

Detailed descriptions of the criteria used for coding these categories are presented in Table 5-

2. Meteorological conditions are based on visual observations only.

The result of the qualitative coding process is a digital file for each site that contains a 2-digit

code for each half-day of tape or film. Final data summary tables and graphic plots can then be made.

It is important to note that videotapes or film can only be used to document the presence of observed

conditions. The cause of the condition generally must be obtained from supplemental data or from

interpretation of other conditions observed in the vista. For example, though videotape or film can

document that a white plume emanated from a stack, the chemical constituents of the plume cannot

be directly determined from the tape/film.

5.2.6.2 Data Validation

Videotapes/film should be reviewed in conjunction with site documentation and other data

if available. Two levels of validation are summarized below:

! Level I: Tapes/film are labeled by site, date, and time (loaded/removed). They are

initially reviewed for proper exposure, alignment, and correct operating

period.
5-19

! Level II: Daily meteorological conditions and patterns are documented, as well as the

presence of any anomalies. Tapes/film are reviewed on a high-resolution

color monitor or projector. A tape/film condition code is assigned to each

morning and afternoon period. Codes for all periods are entered into a digital

ASCII file.

Table 5-2

Example Tape/Film Condition Code Key

Sky Conditions Code Description

0 No clouds No clouds visible anywhere in the sky.

1 Scattered clouds < half of Less than one-half of the sky has clouds present.

sky

2 Overcast > half of sky More than one-half of the sky has clouds present.

5 Weather concealing scene Clouds or precipitation are such that determination of the

sky value is impossible.

9 No observation or cannot To be used with target code of 9 or if sky value cannot be

be determined determined due to reasons other than weather.

Layered Haze Code Description

0 No layered haze No layered haze boundary (intensity of coloration edge) is

perceptible.

1 Ground-based layered Only a single-layered haze boundary is perceptible with the

haze only haze layer extending to the surface.

2 Elevated layered haze only An elevated layered haze with two boundaries is perceptible;

e.g., horizontal plume.

3 Multiple haze layers More than a single ground-based or elevated layered haze is

perceptible. This can be multiple ground-based layers or a

combination of both.

5 Weather concealing scene Cloud or precipitation are such that determination of the

presence of layered hazes is impossible.

9 No observation or cannot To be used with target code of 9 or if a layered haze value

be determined cannot be determined due to reasons other than weather.
5-20

5.2.7 Data Reporting and Archive

5.2.7.1 Data Reporting

Data reports should be prepared in a format that generally conforms to the guidelines for

Preparing Reports for the NPS Air Quality Division (AH Technical Services, 1987). A separate data

report should be prepared for each instrument type; photographic data reports should contain only

photographic data. Reporting consists of various text discussions and graphics presentations

concerning the instrumentation and collected data. Specific contents of the reports are defined by the

contracting agency.

Seasonal photographic reporting should be completed within three months after the end of

a monitoring season, and annual reporting within three months after the end of the last reported

season. Standard meteorological monitoring seasons are defined as:

Winter (December, January, and February)

Spring (March, April, and May)

Summer (June, July, and August)

Fall (September, October, and November)

Reports should contain the following major sections:

! Introduction

! Data Collection and Reduction

! Photographic Data Summaries

! References

The introduction should contain a conceptual overview of the purpose of the monitoring

program and specific objectives and tasks of the program.

The data collection and reduction section includes discussions of site configuration, camera

system components, exposure schedule, and basic system operation. Also included should be a map

of the United States depicting the location of each monitoring site, and a monitoring history summary

table, describing each monitoring site, the type of instrumentation installed, and the historical periods

of operation for each instrument. The section briefly describes the videotape/film review and coding

process, as well as the compilation of the summary tables, and the quality control and quality

assurance procedures applied during the data collection and reduction process.

Time-lapse data may be presented in various forms depending on contracting agency

requirements. Each type of data summary should be accompanied by an explanation. Each report

contains a Site and Target Specifications Summary Table listing complete site specifications for each

monitoring site operational during the period, (including site name and abbreviation, latitude,

longitude, and elevation of the camera monitoring site; number of exposures taken per day; and

operating period during the reported period). A Qualitative Slide Analysis Summary Table provides

a site-by-site accounting of observed haze and target-concealed conditions for each site that operated

during the reporting period. Separate discussions detailing each observed anomaly may also be

prepared.
5-21

The section also includes a brief discussion of videotape/film and digital file archive, a

discussion of the events and circumstances that influenced data recovery, operational summaries for

each site including: site name and abbreviation, data collection period, number of total possible

observations, collection efficiency (number and percent), a description of the cause or causes of data

loss or problem description, and resolutions and/or recommendations relating to the noted operational

problems.

The reference section includes technical references (documents that are cited in the report),

and related reports and publications (all prior reports pertaining to the monitoring program).

Supplemental data products that may accompany data reports include copies of the videotapes

or film.

5.2.7.2 Data Archive

Duplicates of the videotapes or film rolls should be stored in standard storage cabinets, filed

by site, season, and date. Supporting hard copy documentation, including operational notes and

correspondence, should be appropriately filed in chronological order by site.

5.2.8 Quality Assurance

Internal quality assurance of time-lapse camera equipment is based primarily on visual review

of developed visibility monitoring film. Alignment, exposure, and data collection efficiency can all

be assessed from videotape or developed film. Any noted problems should initiate corrective action.

Ongoing review of film and site operator identified problems often initiates corrective actions.

5.2.9 Data Analysis and Interpretation

Time-lapse data analysis can be qualitative only. Only conditions visually seen in the

videotapes/film can be compiled and interpreted. A more thorough analysis would be to use the

videotapes/film in conjunction with other forms of data, such as optical or aerosol data. All noted

anomalies should be evaluated. Any coding or comment inconsistencies should be resolved and the

digital code files updated if appropriate.

5.2.10 8 mm Time-Lapse Scene Monitoring Systems Standard Operating Procedures and

Technical Instructions

The Air Resource Specialists, Inc. document entitled Standard Operating Procedures and

Technical Instructions for 8 mm Time-Lapse Scene Monitoring Systems, includes the following 8 mm

time-lapse-related Standard Operating Procedures and Technical Instructions:

SOP 4005 Procurement and Acceptance Testing Procedures for Scene Monitoring

Equipment
5-22

TI 4005-1001 Procurement and Acceptance Testing Procedures for 8 mm Automatic Camera

Systems

SOP 4055 Site Selection for Scene Monitoring Equipment

SOP 4075 Installation and Site Documentation for Scene Monitoring Equipment

SOP 4120 Automatic Camera System Maintenance (IMPROVE Protocol)

TI 4120-3200 Routine Site Operator Maintenance Procedures for 8 mm Automatic Camera

System - Minolta XL 401/601

TI 4120-3210 Routine Site Operator Maintenance Procedures for 8 mm Automatic Camera

System - Minolta D12

TI 4120-3400 Troubleshooting and Emergency Maintenance Procedures for 8 mm Automatic

Camera System - Minolta XL 401/601

TI 4120-3410 Troubleshooting and Emergency Maintenance Procedures for 8 mm Automatic

Camera System - Minolta D12

TI 4120-3520 Biannual Laboratory Maintenance Procedures for 8 mm Automatic Time-Lapse

Camera Systems

SOP 4305 Collection of Scene Monitoring Photographs and Film (IMPROVE Protocol)

TI 4305-4003 Collection, Processing, and Handling of 8 mm Time-Lapse Movie Film

SOP 4420 Scene Monitoring Qualitative Data Reduction

TI 4420-5010 Qualitative 8 mm Time-Lapse Movie Film Review

SOP 4520 Scene Monitoring Data Reporting

TI 4520-5010 Scene Monitoring Reporting of 8 mm Time-Lapse Movie Film

SOP 4610 Scene Monitoring Archives

TI 4610-5010 8 mm Time-Lapse Film Archives
6.0 REFERENCES

6.1 SECTION 2.0 REFERENCES

Aerosol and Visibility Subcommittee Grand Canyon Visibility Transport Commission, Grand Canyon

Visibility Transport Commission Methods for Measuring and Assessing Visibility, June 1993.

Air Resource Specialists, Inc., Tahoe Regional Planning Agency Visibility Monitoring Program Site

Selection Report, May 1988.

-----, Final Draft Lake Tahoe Visibility Monitoring Program, June 1988.

-----, Project MOHAVE Summer 1992 Intensive (7/1-9/3/92) and Interim Monitoring Period (3/1-

6/30/92) Data Transmittal Report for Nephelometer, Transmissometer, Tonto Plateau

Meteorology & Photography, Volume II Interim Monitoring Period, March 1993.

-----, Project MOHAVE Winter 1992 Intensive Data Transmittal Report for Nephelometer

Transmissometer Tonto Plateau Meteorology Photography, May 1992.

-----, National Park Service Visibility Monitoring Strategy, May 1993.

ANSI/ASQC, American National Standard - Specifications and Guidelines for Quality Systems for

Environmental Data Collection and Environmental Technology Programs, January 1995.

Bureau of National Affairs, Inc., BNA Policy and Practice Series - Air Pollution Control, Section

131, Washington, D.C.

Chow, J.C., Measurement Methods to Determine Compliance with Ambient Air Quality Standards

for Suspended Particles, Air and Waste Management Association, ISSN 1047-3289, May

1995.

Fox, D.G., Bernabo, J.C., and Hood, B., Visibility from Guidelines for Measuring the Physical,

Chemical, and Biological Condition of Wilderness Ecosystems - General Technical Report,

November 1987.

Haas, P.J., Technical Note - Visibility: Modeling, Monitoring and Regulation, March 1980.

IMPROVE-CIRA (Sisler, J.F., Huffman, D., and Latimer, D.A.), Spatial and Temporal Patterns and

the Chemical Composition of the Haze in the United States: An Analysis of Data from the

IMPROVE Network, 1988 - 1991 - Vol. I (ISSN No. 0737-5352-26), February 1993.
IMPROVE-CIRA (Sisler, J.F., Huffman, D., and Latimer, D.A.), Spatial and Temporal Patterns and

the Chemical Composition of the Haze in the United States: An Analysis of Data from the

IMPROVE Network, 1988 - 1991 - Appendices Vol. II (ISSN No. 0737-5352-26), February

1993.

IMPROVE, Visibility Protection, August 1994.

Latimer, D.A., Final Report - Alternative Methods of Protecting Visibility in the Rocky Mountain

States, Phase II: Technical Considerations, August 1984.

Malm, W.C., J.V. Molenar, R.A. Eldred, and J.F. Sisler, - Examining the relationship among

atmospheric aerosols and light scattering and extinction in the Grand Canyon area. Journal

of Geophysical Research, Vol. 101, No. D12, pages 19,251-19,265, August 27, 1996.

Moyer, C.A. and M.A. Francis, Clean Air Act Handbook - A Practical Guide to Compliance, ISBN

0-87632-814-1, 1991.

National Park Service, National Park Service Visibility Reference Document, April 1983.

-----, IMPROVE Program Description, Appendix A taken from Rocky Mountain National Park

Visibility and Air Quality Data Summary, Date Unknown.

National Acid Precipitation Assessment Program (Principal Author: Trijonis, J.C.; Primary Coauthors: Malm, W.C., Pitchford, M., White, W.H.; Contributing Authors: Charlson, R. and

Husar, R.), NAPAP Report 24, Visibility: Existing and Historical Conditions - Causes and

Effects , October 1990.

National Research Council: Committee on Haze in National Parks and Wilderness Areas; Board on

Environmental Studies and Toxicology; Commission on Geosciences, Environment and

Resources, Protecting Visibility in National Parks and Wilderness Areas, January 1993.

Pitchford, M., Visibility Monitoring Plan for Class I Areas, Circa 1986.

-----, and Shaver, C.L., Federal Regional Haze Protection for Class I Areas: A Proposed Strategy

(91-50.3 AWMA), June 1991.

-----, EPA-EMSL, Visibility Monitoring Strategy Guidance, Circa 1991.

-----, Visibility Research at Environmental Monitoring and Systems Laboratory - Las Vegas, Date

Unknown.

-----, IMPROVE Committee, Discussion of Issues for Monitoring of Visibility - Protected Class I

Areas, September, 1993.
Rhodes, R.C., Guideline on the Meaning and Use of Precision and Accuracy Data Required by 40

CRF Part 58 Appendices A and B, EPA-600/4-83/023, June 1983.

Sisler, J., and Malm, W., Interpretation of Trends of PM2.5 and Reconstructed Visibility from the

Improve Network, Journal of the Air and Waste Management Association, 1999 (In Press).

Southern Appalachian Man and the Biosphere Cooperative, The Southern Appalachian Assessment

Atmospheric Technical Report, Report 3 of 5, July 1996.

Tombach, I., Walther, E.G., Huang, A., and Ligh, D., Performance Criteria for Monitoring VisibilityRelated Variables (AV-FR-87/635), November 1990.

U.S. Environmental Protection Agency (Authors: Malm, W.C. and Walther, E.G.), A Review of

Instrument-Measuring Visibility-Related Variables (EPA-600/4-80-016), February 1980.

-----, Interim Guidance for Visibility Monitoring (EPA-450/2-80-082), November 1980.

-----, Workbook for Estimating Visibility Impairment (EPA-450/4-80-031), November 1980.

-----, Ambient Monitoring Guidelines for Prevention of Significant Deterioration (PSD) (EPA-450/4-

87-007), May 1987.

-----, Ambient Monitoring Guidelines for Prevention of Significant Deterioration (PSD), EPA-450/4-

87-007.

-----, Code of Federal Regulations - Title 40 - Protection of the Environment, Parts 51 and 52.

EPA-450/4-87-007.

-----, Guidance for the Data Quality Objectives Process, EPA QA/G-4, September 1994.

-----, List of Designated Reference and Equivalent Methods. Available from U.S. EPA, National

Exposure Research Laboratory, Quality Assurance Branch, MD-77B, Research Triangle

Park, NC.

-----, Quality Assurance Handbook for Air Pollution Measurement Systems: Volume I, A Field

Guide to Environmental Quality Assurance, EPA-600R-94/038a, April 1994.

-----, Quality Assurance Handbook for Air Pollution Measurement Systems: Volume II, Ambient Air

Specific Methods, EPA-600/4-77-027a, as revised.

White, W.H., Contributions to light scattering, in Acidic Deposition: State of Science and

Technology, Tech. Rep. 24, pages 85-102, Natl. Acid Precip. Assess. Program, Washington,

D.C., 1990.

Wooley, D.R., Clean Air Act Handbook - A Practical Guide to Compliance, Fifth Edition, ISBN 0-

87632-419-7, 1996.
6.2 SECTION 3.0 REFERENCES

AeroVironment Inc., The Design and Operation of a Regional Visibility and Aerosol Monitoring

Network, August 1985.

AH Technical Services, Guidelines for Preparing Reports for the NPS Air Quality Division, 1987.

Beveridge, P., Gearhart, B., and Matsumura, R., Draft - IMPROVE Aerosol Sampler: Instructions

and Forms for Siting and Installation, August 1993.

Cahill, T.A., L.L. Ashbaugh, R.A. Eldred, P.J. Feeney, B.H. Kusko, and R.G. Flocchini,

Comparisons between Size-Segregated Resuspended Soil Samples and Ambient Aerosols in

the Western United States. Atmospheric Aerosol: Source/Air Quality Relationships, Am.

Chem. Soc. Symp. Ser., 167, edited by E. Macias, Washington, D.C., 1981.

Cahill, T.A., Eldred, R.A., Wilkinson, L.K., Perley, B.P., and Malm, W.C., Spatial and Temporal

Trends of Fine Particles at Remote US Sites (AWMA Annual Meeting & Exhibition), June

1990.

Campbell, D., Copeland, S., and Cahill, T., Measurement of Aerosol Absorption Coefficient from

Teflon Filters Using Integrating Plate and Integrating Sphere Techniques. Aerosol Science

& Technology 22:287-292, Unknown 1995.

Chow, J.C., Measurement Methods to Determine Compliance with Ambient Air Quality Standards

for Suspended Particles. Journal of the Air & Waste Management Association, ISSN 1047-

3289, May 1995.

Crocker Nuclear Laboratory, A Guide to Interpret Data, August 1995.

Crocker Nuclear Laboratory, IMPROVE Particulate Monitoring Network Standard Operating

Procedures, available as a pdf file on http://www.nature.nps.gov/ard/vis/sop/index.html. 

Crocker Nuclear Laboratory, TI 101-42 Construction and Testing of IMPROVE Aerosol Samplers,

available as a pdf file on http://www.nature.nps.gov/ard/vis/sop/index.html. 

Crocker Nuclear Laboratory, TI201A IMPROVE Aerosol Sampler Operations Manual, available as

a pdf file on http://www.nature.nps.gov/ard/vis/sop/index.html. 

Eldred, R.A., T.A. Cahill, M. Pitchford, and W.C. Malm, IMPROVE - A New Remote Area

Particulate Monitoring System for Visibility Studies. Proc. APCA (Air Pollution Control

Assoc.) Ann. Mtg., 81, 1-16, 1988.

Eldred, R.A., and Cahill, T.A., Trends in Elemental Concentrations of Fine Particles at Remote Sites

in the United States. Atmospheric Environment 28-5:1009-1019, 1994.
ENSR Consulting and Engineering, Quality Assurance Audits of the IMPROVE Aerosol Network,

January 1995.

Malm, W.C., J.V. Molenar, R.A. Eldred, and J.F. Sisler, - Examining the relationship among

atmospheric aerosols and light scattering and extinction in the Grand Canyon area. Journal

of Geophysical Research, Vol. 101, No. D12, pages 19,251-19,265, August 27, 1996.

Malm, W.C., Gebhart, K.A., Molenar, J., Cahill, T.A., Eldred, R.E., and Huffman, D., Examining the

Relationship Between Atmospheric Aerosols and Extinction at Mount Rainier National Park.

Atmospheric Environment Vol. 28, No. 2, 347-360, 1994.

Malm, W.C., J.F. Sisler, D. Huffman, R.A. Eldred, and T.A. Cahill, Spatial and Seasonal Trends in

Particle Concentration and Optical Extinction in the United States. J. Geo. Res., 99(D1),

1347-1370, 1994.

Malm, W.C., Mauch, L., Molenar, J.V., and Sisler, J.F., Assessing the Improvement in Visibility of

Various Sulfate Reduction Scenarios. "Visibility and Fine Particles," a Transactions of the

Air & Waste Management Association edited by C.V. Mathai, 1990.

National Park Service, Annual Report Aerosol Collection and Compositional Analysis for IMPROVE

July 1993 - June 1994, Date Unknown.

Noll, K.E., Collection and Characteristics of Atmospheric Coarse Particles, Final Report, Dept. of

Environmental Engineering, Illinois Institute of Technology, Chicago, 1991.

Noll, K.E., A. Pontius, R. Frey, and M. Gould, Comparison of Atmospheric Coarse Particles at an

Urban and Non-Urban Site. Atmospheric Environment 19(11): 1931-1943, 1985.

Pitchford, M., R.G. Flocchini, R.G. Draftz, T.A. Cahill, L.L. Ashbaugh, and R.A. Eldred, Silicon in

Submicron Particles in the Southwest. Atmospheric Environment, 15, 321-333, 1981.

Sisler, J.F., D. Huffman, D.A. Latimer, W.C. Malm, and M.L. Pitchford, Spatial and Temporal

Patterns and the Chemical Composition of the Haze in the United States: An Analysis of Data

from the IMPROVE Network 1988-1991 - Vol. I (ISSN No. 0737-5352-26), February 1993.

Sisler, J.F., D. Huffman, D.A. Latimer, W.C. Malm, and M.L. Pitchford, Spatial and Temporal

Patterns and the Chemical Composition of the Haze in the United States: An Analysis of Data

from the IMPROVE Network 1988-1991 - Appendices Vol. II, (ISSN No. 0737-5352-26),

February 1993.

Sisler, J.F., with contributions from W.C. Malm, K.A. Gebhart, Principal Investigators W.C. Malm

and M.L. Pitchford, Spatial and Seasonal Patterns and Long Term Variability of the

Composition of the Haze in the United State: An analysis of Data from the IMPROVE

Network, July 1996.
U.S. Environmental Protection Agency, Air Quality Criteria for Particulate Matter and Sulfur Oxides,

Volume III (EPA-600/8-82-029c), December 1982.

Watson, J.G., J.C. Chow, L.C. Pritchett, W.R. Pierson, C.A. Frazier, R.G. Purcell, I. Olmez, The

1987-88 Metro Denver Brown Cloud Study. Desert Research Institute, Doc.8810 1F2,

Desert Research Institute Reno, NV, 1988.

6.3 SECTION 4.0 REFERENCES

AH Technical Services, Guidelines for Preparing Reports for the NPS Air Quality Division. Product

NPS/AQD-87/001. Boulder, CO. September, 1987.

Air Resource Specialists, Inc., Status of IMPROVE and National Park Service IMPROVE Protocol

Optical Monitoring Networks, November 1988.

Air Resource Specialists, Inc., Operational Assessment of Optec NGN-2 Nephelometers, July 1994.

Air Resource Specialists, Inc., Standard Operating Procedures and Technical Instructions for

Transmissometer Systems, 1993-1996.

Air Resource Specialists, Inc., Standard Operating Procedures and Technical Instructions for

Nephelometer Systems, 1993-1996.

Campbell Scientific, Inc., Model 207 Temperature and Relative Humidity Probe Instruction Manual,

February 1990.

Optec, Inc., Model LPV Long Path Visibility Transmissometer Version 2 Technical Manual for

Theory of Operation and Operating Procedures Revision 2, April 1991.

Optec, Inc., Model NGN-1 Open-air Integrating Nephelometer, Technical Manual for Theory of

Operation and Operating Procedures. Lowell, MI, 1992.

Optec, Inc., Model NGN-2 Open-air Integrating Nephelometer, Technical Manual for Theory of

Operation and Operating Procedures. Lowell, MI, 1993.

Soltec Distribution, Instruction Manual Primeline 6723. Sun Valley, CA.

U.S. Environmental Protection Agency, On-Site Meteorological Program Guidance for

Regulatory Modeling Applications (EPA-450/4-87-013), June 1987.
6.4 SECTION 5 REFERENCES

AH Technical Services, , Guidelines for Preparing Reports for the NPS Air Quality Division.

Product NPS/AQD-87/001. Boulder, CO. 1987.

Air Resource Specialists, Inc., Standard Operating Procedures and Technical Instructions for 35 mm

Scene Monitoring Systems, 1993-1996.

Air Resource Specialists, Inc., Standard Operating Procedures and Technical Instructions for 8 mm

Time-Lapse Scene Monitoring Systems, 1993-1996.

Air Resource Specialists, Inc., Draft - Preliminary Analysis of Uncertainty Associated with Extinction

Estimates from 35mm Color Slide Densitometry of Natural Targets, July 1994.

Malm, W.C., Leiker, K.K., Molenar, J.V., Human Perception of Visual Air Quality, February 1980.

Malm, W., Molenar, J., and Chan L.L., Photographic Simulation Techniques for Visualizing the

Effect of Uniform Haze on a Scenic Resource, Date Unknown.

U.S. Environmental Protection Agency, Western Regional Visibility Monitoring Teleradiometer and

Camera Network (TS-AMD-8035b), April 1983.
7-1

7.0 VISIBILITY MONITORING-RELATED GLOSSARY AND ABBREVIATIONS

Abrasion mode A size range of particles, typically larger than about 3 micrometers in

diameter, primarily generated by abrasion of solids.

Absorption Capture of incident light by particles or gases in the atmosphere.

Absorption Proportion of incident light absorbed per unit distance. Typical units are

coefficient inverse megameters (Mm ). -1

Accumulation mode A size range of particles, from about 0.1 to 3 micrometers, formed largely by

accumulation of gases and particles upon smaller particles. They are very

effective in scattering light.

Acid deposition Wet and/or dry deposition of acidic materials to water or land surfaces. The

chemicals found in acidic deposition include nitrate, sulfate, and ammonium.

Acid rain (or acid The deposition of acid chemicals (incorporated into rain, snow, fog, or

precipitation) mist) from the atmosphere to water or land surfaces. The pH of rain is

considered acid when it is below about 5.2 pH.

Adverse impact A determination that an air-quality related value is likely to be degraded within

a Class I area.

Aerometric A computer-based repository of US air pollution information administered

Information by the EPA Office of Air Quality Planning and Standards.

Retrieval System

(AIRS)

Aerosol A suspension of microscopic solid or liquid particles in air. Atmospheric

aerosols govern variations in light extinction and, therefore, visibility

reduction.

Aerosol extinction See reconstructed light extinction.

Aethalometer An aerosol monitoring instrument that continuously measures particle light

absorption (aerosol black carbon) on a quartz fiber filter.

Agglomeration The process of collisions of particles that stick together to become larger

particles.

Air light Light scattered by air (molecules or particles) toward an observer, reducing

the contrast of observed images.

Air pollutant An unwanted chemical or other material found in the air.

Air pollution Degradation of air quality resulting from unwanted chemicals or other

materials occurring in the air.
7-2

Air quality (In context of the national parks): The properties and degree of purity of air

to which people and natural and heritage resources are exposed.

Air quality Values including visibility, flora, fauna, cultural and historical resources,

related values odor, soil, water, and virtually all resources that are dependent upon and

(AQRVs) affected by air quality. "These values include visibility and those scenic,

cultural, biological, and recreation resources of an area that are affected by air

quality" (43 Fed. Reg. 15016).

AIRWeb Air Resources Web, an air quality information retrieval system for US parks

and wildlife refuges developed by the Air Resources Division of the National

Park Service and the Air Quality Branch of the US Fish and Wildlife Service.

Albedo Ratio of the light reflected by a surface to the incident light.

Ambient air Air that is accessible to the public.

Anion A negative ion, such as sulfate, nitrate, or chloride.

Anthropogenic Caused by human activities (i.e., man-made).

Apparent contrast Contrast at the observer of a target with respect to some background, usually

an element of horizon sky directly above the target.

Apportionment The act of assessing the degree to which specific components contribute to

light extinction or aerosol mass.

Artifact Any component of a signal or measurement that is extraneous to the variable

represented by the signal or measurement.

AT Ambient Temperature

Atomic absorption A method of chemical analysis based on the absorption of light of specific

spectroscopy wavelengths of light by disassociated atoms in a flame or high temperature

furnace. It is sensitive only to elements.

Atmospheric clarity An optical property related to the visual quality of the landscape viewed from

a distance (see optical depth and turbidity).

Attainment area A geographic area in which levels of a criteria air pollutant meet the healthbased National Ambient Air Quality Standard for that specific pollutant.

Audit An investigation of the ability of a system of procedures and activities to

produce data of a specified quality.

babs Absorption coefficient. A measure of light absorption in the atmosphere by

particles and gases. Standard reporting units are inverse megameters (Mm ). -1
7-3

bext Extinction coefficient. Measured directly by a transmissometer. Can be

reconstructed from nephelometer and aerosol data. It is equal to the sum of

bscat and babs. Represents the proportion of radiation reduced by scattering and

absorption per unit distance. Standard reporting units are inverse megameters

(Mm ). -1

bscat Scattering coefficient. Measured directly by a nephelometer, the scattering

coefficient includes scattering due to particles and atmospheric gases

(Rayleigh scattering). Standard reporting units are inverse megameters (Mm-

). 1

BAPMON Background Air Pollution Monitoring Network

BART Best Available Retrofit Technology

Best Available A source emission limitation, based on the maximum degree of reduction

Control Technology for each pollutant, that must be applied by sources subject to the Prevention

(BACT) of Significant Deterioration program.

Bias An unfair influence, inclination, or partiality of opinion.

Bimodal distribution A distribution containing much of its elements in two distinct ranges of values.

The size distributions of aerosols often show two peaks corresponding to

about 1 and 10 micrometers in diameter.

Biological effects Ecological studies to determine the nature or extent of air pollution injury to

biological systems.

BLM Bureau of Land Management

Brightness A measure of the light received from an object, adjusted for the wavelength

response of the human eye, so as to correspond to the subjective sensation of

brightness. For visually large objects, the brightness does not depend on the

distance from the observer.

Brightness contrast The ratio of the difference in brightness between two objects to the brightness

of the brighter of the two. It varies from 0 to -1.

CAA Clean Air Act (including all of its amendments).

Calibration The process of submitting samples of known value to an instrument, in order

to establish the relationship of value to instrumental output.

Camera Device for recording visual range on film.

CARB California Air Resources Board
7-4

Cascade impactor An instrument that samples particles by impacting on solid surfaces via jets of

air. After passing the first surface, the air is accelerated toward the next

surface by a higher speed jet, in order to capture smaller particles than could

be captured by the previous one.

Charge A process of removing static electric charges. This is done to particleneutralization sampling filters in order to prevent electrostatic forces from distorting the

apparent weight of the sample.

CIE Commission International de l'Eclairage

CIRA Cooperative Institute for Research in the Atmosphere

Clarity Relative distinctness or sharpness of perceived scene elements.

Class I areas National parks and wilderness areas managed by the National Park Service,

U.S. Fish and Wildlife Service, and the USDA Forest Service and defined by

the Clean Air Act Amendments of 1977 as having "special protection" from

effects of air pollution. These federal lands have been defined as having "airquality related values" (AQRVs), such as water quality, native vegetation,

ecosystem integrity, and visibility, that need protection from air pollution.

National Parks larger than 6,000 acres, National Memorial Parks and National

Wilderness Areas larger than 5,000 acres, and International Parks.

Class II areas Areas of the country protected under the Clean Air Act, but identified for

somewhat less stringent protection from air pollution damage than Class I,

except in specified cases.

Clean Air Act Originally passed in 1963, the current national air pollution control program

is based on the 1970 version of the law. Substantial revisions were made by

the 1990 Clean Air Act Amendments.

Clean fuels Low-pollution fuels that can replace ordinary gasoline, including gasohol,

natural gas, and propane.

CMB Chemical Mass Balance

Coarse mode A size range of particles between 2.5 microns and 10 microns. Coarse

particles are mostly composed of soils. The sum of the masses of coarse and

fine particles (all particles smaller than 10 microns) is called PM . 10

Color A qualitative sensation described by hue, brightness, and saturation.

Color contrast or Contrast between two adjacent scene element colors. Any difference in color

difference hue, saturation, or brightness, between two perceived objects.

Colorimetric Chemical analysis based on the colors of dyes formed by the reaction of

analysis the analyte with reagents.
7-5

Condensation An instrument that counts nucleation mode particles by causing them

counternuclei to grow in a humid atmosphere, and observing light reflections from the

individual enlarged particles.

Continuous An air analyzer that measures air quality components continuously. (See

sampling device also monitoring, integrated sampling device).

Contrast Relative difference in light coming from a target compared to the surrounding

background, usually the horizon sky. Any difference in the optical quality of

two adjacent images.

Contrast change Minimum change in contrast perceptible to an observer.

threshold

Contrast threshold Minimum apparent contrast at which a target is just perceptible.

Contrast Ratio of apparent contrast to inherent contrast. The ability of an atmosphere

transmittance to transmit an image without loss of contrast. It varies from 0% to 100% and

depends on the length of the viewing path. When the object is darker than its

background, it has a value between 0 and -1. For objects brighter than their

background the value varies from 0 to infinity. When the contrast

transmittance is equal to 0, the object cannot be seen.

Current conditions Contemporary, or modern, atmospheric conditions affected by human activity.

Datalogger An electronic device for measuring analog or digital signals and recording the

results on a storage media. Many of them can record inputs on a number of

separate locations, reporting them as separate "channels."

Deciview (dv) A haziness index designed to be linear with respect to human perception of

visibility. A 1-2 dv change in haziness corresponds to a small, visibly

perceptible change in scene appearance. Higher deciview values indicate

more extinction and a corresponding decrease in visual range.

Deliquescence The process that occurs when the vapor pressure of the saturated aqueous

solution of a substance is less than the vapor pressure of water in the ambient

air. Water vapor is collected until the substance is dissolved and is in

equilibrium with its environment.

Dew point The temperature at which humidity in the air will condense upon a solid

surface.

Dichotomous Any particle sampler that separately collects coarse and fine particles

samplerfrom one atmosphere. Often refers to virtual impactor instruments.

Discoloration Any change in the apparent color of an image. Often refers to the loss of blue

sky color due to air pollution.

DMB Differential Mass Balance
7-6

Dose-response The relationship between the dose of a pollutant and its effect on a biological

system.

DRUM Davis Rotating-drum Universal-size-cut Monitor

Dry deposition Also known as dryfall, includes gases and particles deposited from the

atmosphere to water and land surfaces. This dryfall can include acidifying

compounds such as nitric acid vapor, nitrate and sulfate particles, and acidic

gases.

Edge sharpness Describes a characteristic of landscape features. Landscape features with

sharp edges contain scenic features with abrupt changes in brightness.

Electrical aerosol A particle sampler that puts electrical charges on particles and sorts

analyzerthem by their different drift rates in an electric field.

Elevated layer A pollution distribution that is not in contact with the ground.

Emissions Release of pollutants into the air from a source.

EMSL Environmental Monitoring Systems Laboratory

EOF Empirical Orthogonal Function

EPA United Stated Environmental Protection Agency

Equilibration A balancing or counter balancing to create stability, often with a standard

measure or constant.

Externally mixed Particulate species that co-exist as separate particles without co-mingling or

combining.

Extinction Process of reducing radiation transfer by scattering and absorption.

Extinction budget Apportioning the extinction coefficient to atmospheric constituents to

analysisestimate the change in visibility caused by a change in constituent

concentrations.

Extinction Proportion of radiation reduced by scattering and absorption per unit

coefficient distance. Standard units are inverse megameters (Mm ). The atmospheric

-1

extinction coefficient, loosely referred to as "extinction," represents the ability

of the atmosphere to absorb and scatter light. It equals the sum of the

scattering and absorption coefficients.

Fine particles Particulate matter with an aerodynamic diameter of 2.5 microns or less

(PM2.5). Fine particles are responsible for most atmospheric particle-induced

extinction. Ambient fine particulate matter consists basically of five species:

sulfates, ammonium nitrate, organics, elemental carbon, and soil dust.

FIPS Federal Implementation Plans
7-7

FLM Federal Land Manager

FTP File Transfer Protocol

FWS United States Fish and Wildlife Service

GC Gas Chromatography

Hazardous air Airborne chemicals that cause serious health and environmental effects.

pollutants (HAP)

Haze (hazy) A visual phenomenon resulting from scattering of light in a volume of

aerosols. Condition of the atmosphere in which particles obscure a significant

part of the vista.

High volume A simple particle sampler consisting of a filter holder and a vacuum sampler

(HI-VOL) cleaner blower, in a simple rain shelter. Some units have flow measuring or

controlling features.

Hue Attribute of color that determines whether it is red, yellow, green, blue, or

other color. It is most strongly related to wavelength of light.

Humidity Water in air, as a gas. Often measured as a percentage, compared to the

maximum amount of water vapor the air can contain at that temperature.

Hydrophobic Lacking affinity for water, or failing to adsorb or absorb water.

Hygroscopic Characteristic of substances (e.g., particles in the atmosphere) having the

property of absorbing water vapor from air. Also pertains to a substance

(e.g., aerosols) that have an affinity for water and whose physical

characteristics are appreciably altered by the effects of water.

Illumination Application of visible radiation to an object.

Impairment The degree to which a scenic view or distance of clear visibility is degraded

by man-made pollutants.

IMPROVE Interagency Monitoring of Protected Visual Environments, a collaborative

monitoring program established in the mid-1980's as a part of the Federal

Implementation Plans. IMPROVE objectives are to provide data needed to

assess the impacts of new emission sources, identify existing man-made

visibility impairment, and assess progress toward the national visibility goals

that define protection of 156 Class I areas.

IN Ice Nuclei

INAA Instrumental Neutron Activation Analysis

Indirect effects Non-optical atmospheric effects of aerosols on cloud albedo and formation

(e.g., as condensation nuclei for cloud droplets).
7-8

Inhalable particulate Particles smaller than about 12 micrometers in diameter, capable of being

matter drawn into the human bronchial system. Larger particles tend to be filtered

out in the upper respiratory tract.

Inherent contrast Contrast of the target against the horizon sky background when viewed at the

target. Same as intrinsic contrast. The contrast that would be seen between

two adjacent scenic elements if there were no intervening atmosphere.

Integral vistas Scenic views which extend beyond Class I boundaries, that are critical to the

enjoyment of the area.

Integrated sampling An air sampling device that allows estimation of air quality components device

over a period of time (e.g., 24 hours to two weeks) through laboratory

analysis of the sampler's medium.

Integrating Instrument that measures the light scattered from a light beam by an

nephelometer enclosed air sample through scattering angles between 5E and 175E.

Internally mixed Refers to the situation where individual particles contain one or more species.

For example, water is internally mixed with its hygroscopic hosts.

Ion A charged molecular group or atom.

Ion chromatography A method of separating ions by their different speeds of passage through an

ion-exchange resin. The ions are usually detected by their conductivity.

IP Inhalable Particle network

Just noticeable A variation of just noticeable difference that relates directly to human change

(JNC) visual perception. A JNC corresponds to the amount of optical change

in the atmosphere required to evoke human recognition of a change in a given

landscape (scenic) appearance. The change in atmospheric optical properties

may be expressed as the number of JNC's between views of a given scene at

different intervals of time.

Just noticeable A measure of change in image appearance that affects image sharpness.

difference (JND) Counting the number of JND's (detectable changes) in scene appearance is

regarded as an alternative method of quantifying visibility reduction (light

extinction).

Koschmeider The constant in the reciprocal relationship between standard visual range

constant and the extinction coefficient (see standard visual range).

Layered haze Haze that obscures a horizontal layer of a vista.

Light extinction The absorption and scattering of light. The attenuation of light per unit

distance due to absorption and scattering by the gases and particles in the

atmosphere.

LIPM Laser Integrating Plate Method
7-9

LOD Limit of Detection

LQL Lower Quantifiable Limit

Magnehelic gauge A differential pressure gauge suitable for measuring pressure differences as

small as 0.1 inches of water.

Major source A stationary facility that emits a regulated pollutant in an amount exceeding

the threshold level (100 or 250 tons per year, depending on the type of

facility).

Matrix filter A filter that is formed of a mat or matrix of fibers. It is physically thick, and

particles are trapped deep in its structure.

MDL Minimum Detectable Limit

Membrane filter A thin filter, usually made of a synthetic polymer, with microscopic holes in

it. Particles are collected only on the surface facing the air flow.

Mie scattering Scattering by particles whose size is comparable to the wavelength of

radiation. The attenuation of light in the atmosphere by scattering due to

particles of a size comparable to the wavelength of the incident light. This is

the phenomenon largely responsible for the reduction of atmospheric visibility.

Visible solar radiation falls into the range from 0.4 to 0.8 μm, roughly, with

a maximum intensity around 0.52 μm.

Mixing layer An unstable layer of air that has turbulent mixing, usually due to solar heating

of the ground. It is often capped by a stable layer of air.

Mm Inverse megameter. A unit of extinction related to SVR and dv. Higher

-1

extinction coefficients correspond to lower SVR values and higher deciview

values.

Mobile sources Moving objects that release regulated air pollutants, (e.g., cars, trucks, buses,

airplanes, trains, motorcycles, and gas-powered lawn mowers). See also

source; stationary source.

MOHAVE Measurement of Haze and Visual Effects

Monitoring Measurement of air pollution and related atmospheric parameters. See also

continuous sampling device, integrated sampling device.

MPP Mohave Power Project

MTF Modulation Transfer Function

NAMS National Air Monitoring Stations

NAS National Academy of Sciences
7-10

National Acid The 10-year (1980-1990) interagency research program designed to

Precipitation investigate acid deposition and its effects nationwide. The products of

Assessment this program are the series of State of the Science and Technology Program

(NAPAP) documents that summarize what we know about the severity of acid

deposition and the resources it affects.

National Ambient Permissible levels of criteria air pollutants established to protect public

Air Quality health and welfare. Established and maintained by EPA under authority

Standards of the Clean Air Act.

(NAAQS)

National A national network of about 200 sites where wet deposition is collected

Atmospheric weekly and sent to the Central Analytical Laboratory in Illinois for Deposition

Program chemical analysis. This network has operated since 1977 and is funded

(NADP) by seven federal agencies, and numerous cooperators in agencies,

universities, and industry. This network of predominately rural sites is

designed to represent broad, regional patterns of deposition.

Natural conditions Prehistoric and pristine atmospheric states (i.e., atmospheric conditions that

are not affected by human activities).

Nephelometer An optical instrument that measures the scattering coefficient (b ) of ambient scat

air by directly measuring the light scattered by aerosols and gases in a sampled

air volume. See also integrating nephelometer.

NESCAUM Northeast States for Coordinated Air Use Management

Neutron activation A method of chemical analysis in which the sample is bombarded with analysis

neutrons in a nuclear reactor. The nuclei of various elements in the sample are

modified to radioactive forms, and the concentrations of the elements are then

determined by the intensities and wavelengths of the radiation emitted.

NGS Navajo Generating Station

NOAA National Oceanic and Atmospheric Administration

Nonattainment area A geographic area in which the level of a criteria air pollutant is higher than

the level allowed by the federal standards. For NAAQS, where the pattern of

"violations of standard" is sufficient to require remedial action; a boundary is

determined around the location of the violations. the area within that

boundary is designated to be in non-attainment of the particular NAAQS

standard and an enforceable plan is developed to prevent additional violations.

NPS National Park Service

NSR New Source Review

Nuclei mode A size range of particles below about 0.1 micrometer in diameter. These

particles are the nuclei around which larger particles grow.
7-11

OAQPS EPA Office of Air Quality Planning and Standards

Optical depth The degree to which a cloud or haze prevents light from passing through it.

It is a function of physical composition, size distribution, and particle

concentration. Often used interchangeably with "turbidity."

Optical monitoring Optical monitoring refers to directly measuring the behavior of light in the

ambient atmosphere.

Optical particle An instrument which measures the size of individual particles by the

counteramount of reflected light from a microscopic illuminated volume.

Organic compounds Chemicals that contain the element carbon.

Orifice audit device A device which measures air flow based on the known relationship of air flow

through and orifice to the pressure drop across it.

Origins Particle origins can be anthropogenic (man-made) or natural. Another origin

classification is primary (particles that are emitted into the atmosphere as

particles, such as organic and soot particles in smoke plumes or soil dust

particles), and secondary (those formed from gas-to-particle conversion in the

atmosphere, such as sulfates, nitrates, and secondary organics).

PESA Proton Elastic Scattering Analysis

PIXE Particle Induced X-ray Emission

Particle sampler An instrument to measure particulate matter in ambient air.

Particle scattering Proportion of incident light scattered by particles per unit distance (Mm ). -1

coefficient

Particulate matter Dust, soot, other tiny bits of solid materials that are released into and move

around in the air.

Path function Radiance per unit path length from a specified point along the path radiated

towards the observer.

Path radiance Radiance of path directed towards the observer. Or "airlight," is a radiometric

property of the air resulting from light scattering processes along the sight

line, or path, between a viewer and the object (target).

Perceptible Capable of being seen.

Phase function Relationship of scattered to incident light as a function of scattering angle;

volume scattering function.

Photochemical Any chemical reaction which is initiated by light. Such processes are

processimportant in the production of ozone and sulfates in smog.
7-12

Photometer Instrument for measuring photometric quantities such as luminance,

illuminance, luminous intensity, and luminous flux. An instrument for

measuring the brightness of an object. It has been suggested that this name

be reserved for those instruments which have been adjusted to match the

wavelength response of the human eye, but established usage is not yet this

consistent, and radiometers are sometimes called photometers.

Photometry Study of photometric quantities of light.

Photopic Vision or wavelength response of the cones of a normal eye when exposed to

a luminance of at least 3.4 candelas per square meter.

Plume Airborne emissions from a specified source and the path through the

atmosphere of these emissions.

PM The acronym for airborne "particulate matter," an air quality parameter for

which standards are maintained within NAAQS.

PM2.5 The acronym for that portion of PM that has an aerodynamic diameter of 2.5

microns or less.

PM10 The acronym for that portion of PM that has an aerodynamic diameter of 10

microns or less.

Polarization A property of light. Light can be linearly polarized in any direction

perpendicular to the direction of travel, circularly polarized (clockwise or

counterclockwise), unpolarized, or mixtures of the above.

Precursor A substance or condition whose presence generally precedes the formation of

another, more notable, condition or substance.

Prescribed burn A wildland fire whose progress has been controlled by a combination of

strategies, including: construction of artificial fire breaks, selection of natural

firebreaks and burnout of vulnerable fuels within the fire control line. A

wildfire may be declared a controlled burn if ignition occurs within an area for

which an approved burning plan exists and weather conditions fall within the

acceptable range. While a forest management burn is referred to as a

prescribed burn in the planning stage, the same project may be referred to as

a controlled burn in the implementation stage.

Prevention of A program established by the Clean Air Act that limits the amount of

Significant additional air pollution that is allowed in Class I and Class II areas.

Deterioration (PSD)

Primary particles Suspended in the atmosphere as particles from the time of emission (e.g., dust

and soot).

PSD Prevention of Significant Deterioration
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Psychrometer An instrument for measuring humidity based on the temperature drop of a

thermometer with a wet wick on the bulb.

Pyanometer An instrument that measures directly the loss of total solar radiance under

clear sky conditions.

QDM Quadratic Detection Model

Quality assurance An overall plan undertaken to quantify, control, and perhaps improve the

quality of data acquired by a system.

Quality control Actions routinely taken to maintain a specified level of quality of acquired

(QC) data.

R-MAP Resource Management Assessment Program.

Radiometer A name for light-measuring instruments which do not match the wavelength

response of the human eye.

RAPS Regional Air Pollution Study

RASS Radio Acoustic Sounding Systems

Rayleigh scattering Scattering by gas molecules, whose size is small compared to the wavelength

of radiation. Light scattering (principally blue light) by atmospheric gases.

Perfectly clean air (100 percent Rayleigh scattering) would correspond to an

SVR of 391 km at an elevation of 5,000 feet, which is the theoretical

maximum for an SVR. Rayleigh scattering also corresponds to 

b = 10 Mm , and is defined as 0 deciview. ext

-1

Reconstructed light The relationship between atmospheric aerosols and the light extinction

extinction coefficient. Can usually be approximated as the sum of the products of the

concentrations of individual species and their respective light extinction

efficiencies.

Reflectance Ratio of reflected to incident light.

Reflection Return of radiation by a surface without a change of frequency.

Regional haze A cloud of aerosols extending up to hundreds of miles across a region and

promoting noticeably hazy conditions. Condition of the atmosphere in which

uniformly distributed aerosol obscures the entire vista irrespective of direction

or point of observation. Is not easily traced visually to a single source.

RH Relative Humidity

Saturation One part of the description of color, it qualitatively corresponds to the purity

of color: the lack of mixed black or white.
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Scattering Changing the direction of radiation at collisions with particles and gas

molecules. The diversion of light from its original path. It can be caused by

molecules or particles.

Scattering Proportion of incident light scattered per unit distance. Standard units are

coefficient inverse megameters (Mm ). -1

Scattering efficiency The relative ability of aerosols and gases to scatter light. A higher scattering

efficiency means more light scattering per unit mass or number of particles,

this in turn means poorer visibility. In general, fine particles (diameter less

than 2.5 microns) are efficient scatterers of visible light.

Scene element Discrete segment of a landscape scene.

Scene monitoring Scene monitoring is the monitoring of a specific vista or target. Optical and

aerosol monitoring measure an abstract, but easily quantifiable parameter of

the atmosphere. Scene monitoring captures the effects of all atmospheric

parameters simultaneously, but in an inherently difficult manner to quantify.

It is, for example, difficult to determine quantitatively which of two

photographs represent "better" visibility conditions. Scene monitoring is

generally done to help relate quantitative data in a "user-friendly" format.

Secondary particles Formed in the atmosphere by a gas-to-particle conversion process.

Sight path The straight line between the observation point and the target.

SLAMS State and Local Air Monitoring Stations

Smog A mixture of air pollutants, principally ground-level ozone, produced by

chemical reactions involving smog-forming chemicals. See also haze.

Soot Black particles with high concentrations of carbon in graphitic and amorphous

elemental forms. It is a product of incomplete combustion of organic

compounds.

Source Any place or object from which air pollutants are released. Sources that are

fixed in space are stationary sources; sources that move are mobile sources.

(See also major source).

Southern A consortium of government agencies, industry, and environmental

Appalachian groups, formed to investigate the status of air quality and its effects in

Mountain Initiative the highland regions of the southeastern United States. The objective of

(SAMI) this regional cooperative is to determine the current and future impacts of

regional air pollutants, such as ozone and acid deposition, and to recommend

regional air management strategies to control the formation of these

pollutants.

SRP Salt River Project
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Standard visual Visual range is the furthest distance that a human observer can resolve range

range (SVR) a large dark target under the prevalent atmospheric conditions. Standard visual

range is visual range standardized to Rayleigh scattering at an elevation of

5,000 feet (10 Mm ). The distance under daylight and uniform lighting

-1

conditions at which the apparent contrast between a specified target and its

background becomes just equal to the threshold contrast of an observer,

assumed to be 0.02.

STAPPA/ALAPCO State and Territorial Air Pollution Program Association/Administrators and

the Association of Local Air Pollution Control Officials

State A collection of regulations used by the state to carry out its Implementation

Implementation responsibilities under the Clean Air Act.

Plan (SIP)

Stationary source A fixed source of regulated air pollutants (e.g., industrial facility). See also

source; mobile sources.

Stratification The process of separating a database into different groups according to (of

data) some detail of their origin, for the purposes of improving statistical sensitivity.

Strip chart recorder A device for making a time record of some signal, usually an applied voltage.

The signal drives a pen in one direction, while paper is moved under the pen

in the perpendicular direction at a uniform rate.

Sun radiometer A device for measuring the intensity of sunlight falling on the ground. If the

sky is cloudless and the angle of the sun is known, then a measure of the

clarity of the air can be had by this measurement.

Surface layer A concentration of air pollution that extends from the ground to an elevation

where the top edge of a pollution layer is visible. 

S-VHS Super-VHS, an high definition video format which is capable of achieving

horizontal resolution of over 400 lines. A tape recorded in S-VHS format

cannot be played on a recorder which is designed to accommodate only the

VHS format. See also VHS.

Target Object in the distance observed by a person or instrument for visibility

measurements.

Temperature Weather condition in which warm air sits atop cooler air, promoting

inversionstagnation and increased concentrations of air pollutants. A

condition of a layer of atmosphere in which temperature increases with

altitude. Such a layer is stable, and pollutants migrate through it very slowly.

Also known as an inversion layer.

Texture Roughness of the landscape.
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Threshold contrast A measure of human eye sensitivity to contrast. It is the smallest increment

of contrast perceptible by the human eye.

TMBR Tracer Mass Balance Regression

Total light The sum of scattering (including Rayleigh scattering) and absorption 

extinction coefficients. See also extinction coefficient.

Total suspended Total particulate matter in a sample of ambient air.

particulates (TSP)

Toxic air See hazardous air pollutants.

pollutants

Tracer elements An element which is emitted most strongly by a specific source or class of

sources, and can therefore be used as evidence for an impact by such a source

when the element is detected in an air pollution sample.

Transmission gauge A device for determining the amount of particles collected on a filter by the

attenuation of light passing through the filter. Beta rays are sometimes used

in place of visible light, and the resulting instrument is called a beta gauge.

Transmissometer A device for assessing visibility conditions by measuring the amount of light

received from a distant light source. Total light extinction is measured by

integrating light scattering and absorption properties of the atmosphere.

Transmittance The ratio of the light transmitted through a medium to the incident light.

Light is attenuated by scattering and adsorption from gases and particles.

Tribal A collection of regulations used by the indian tribes to carry out its

Implementation responsibilities under the Clean Air Act.

Plan (TIP)

TRPA Tahoe Regional Planning Agency

TSP The acronym for total suspended particulates, that portion of PM that is

captured by a PM sampler which does not attempt to discriminate according

to particle size.

Turbidity A condition that reduces atmospheric transparency to radiation, especially

light. The degree of cloudiness, or haziness, caused by the presence of

aerosols, gases, and dust.

UCD University of California-Davis

Uniform haze Pollutants that are uniformly distributed both horizontally and vertically from

the ground to a height well above the highest terrain.

USFS United States Forest Service
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USFWS United States Fish and Wildlife Service

VHS Video Home System, a video tape format commonly used on video

recorder/players.

VIEW Visibility Intensive Experiment in the West, a project of the US EPA, with

cooperation of the National Park Service, to measure visibility at many

stations throughout the western United States to document current visibility

and examine trends.

Violation of A regulatory situation, (i.e., NAAQS), where the pattern of "exceedences

standard of standard" is greater than the frequency allowable under that standard.

Virtual impactor A type of dichotomous sampler which separates large particles from an air

stream by impacting them on the "virtual surface" of a slowly moving column

of air.

Visibility The ability to see an object or scene as affected by distance and atmospheric

conditions; to perceive form, color and texture.

Visibility indexes Aerosol indexes include the physical properties of the ambient atmospheric

particles (particle origin, size, shape, chemical composition, concentration,

temporal and spatial distribution, and other physical properties). Optical

indexes include coefficients for scattering, extinction, and absorption, plus an

angular dependence of the scattering known as the normalized scattering

phase function. Scenic indexes comprise visual range, contrast, color, texture,

clarity, and other descriptive terms.

Visibility A statistical summary of a set of visibility data including the median (or

Metric mean) of the cleanest 20% of the samples, the median (or mean) of all

samples, and the median (or mean) or the dirtiest 20% of the samples.

Visibility reduction The impairment or degradation of atmospheric clarity. It becomes significant

when the color and contrast values of a scene to the horizon are altered or

distorted by airborne impurities.

Visual air quality Air quality evaluated in terms of pollutant particles and gases that affect how

well one can see through the atmosphere.

Visual image The digitizing, calibration, modeling, and display of the effects of

processingatmospheric optical parameters on a scene. The process starts with

a photograph of landscape features viewed in clean atmospheric conditions

and models the effects of changes in atmospheric composition.

Visual range (VR) An expression of visibility; the maximum distance at which a large black

object just disappears against the horizon.

Washout The process by which particles are removed from air by capture by raindrops.

WESTAR Western States Air Resources Council
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Wet deposition The deposit of atmospheric gases and particles (incorporated into rain, snow,

fog, or mist) to water or land surfaces.

Wildfire Any wildland fire that requires a suppression response. A controlled burn may

be declared a wildfire if part of it escapes from the control line or if weather

conditions deteriorate and become unacceptable, as described in the burning

plan.

XRF X-Ray Fluorescence