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 GUIDANCEVISIBILITY MONITORING GUIDANCE DOCUMENT

U.S. ENVIRONMENTAL PROTECTION AGENCY Emissions Monitoring and Analysis Division Monitoring and Quality Assurance Group

MD-14 Research Triangle Park, NC 27711i

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 legalrights 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. EPAhas 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 andreferences 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 Membersiii 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 2-16iv 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 3-1v 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 (b abs ) 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 TechnicalInstructions 3-42 4.0 OPTICAL MONITORING 4-1 4.1 Transmissometer 4-1vi 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 TechnicalInstructions 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 4-40vii 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 5-13viii 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 7-1ix 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 4-35x

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 5-15xi 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/m 3 3-34 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 5-191 The IMPROVECommittee 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 andTerritorial 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) program 1

. 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 Abbreviations2 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 areas 2 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 collect3 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-NPSTable 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-FWSTable 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-FWSTable 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-NPSTable 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-FSTable 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-NPSTable 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-NPS1-12

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 ( I nteragency M onitoring of Pro tected V isual E nvironments). 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 managementagencies. 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 PM 2.5 network will also include IMPROVE samplers which may be used at background or transport sites required under the PM 2.5 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 ' b sg % b ag % b sp % b ap ' b scat % b

abs (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 rangewhich 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 (b ext ), 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 (b scat ) and absorption coefficient

(b aba ), 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 s cattering and absorption by g ases and p articles, 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 F m to 0.1 F m ! Accumulation mode- 0.1 F m to 1 - 3 F m ! Coarse mode - 1 - 3 F m to 50 - 100 F m Fine particles less than 2.5 F m affect light scattering more than particles greater than 2.5 F m. The most efficient light scattering particles are within the size range of the wavelength of visible light; 0.4 F m to 0.7 F m. 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(V r ) 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), b ext 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 qualityis 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 / 10 Mm

& 1 ) (2-3)

b ext ' b scat % b

abs ' b

Ray % b

sp % 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 (b ext ) is the sum of the light scattering coefficient (b scat ) and the light absorption coefficient (b abs ). Light scattering is the sum of the scattering caused by gases (b sg ) and the scattering caused by suspended particles (b sp ) in the atmosphere (aerosols). However, natural Rayleigh scatter (b Ray ) from air molecules (which causes the sky to appear blue) dominates the gas scattering component. Particle scatter (b sp ) 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 (b ag ) and particles (b ap ). Nitrogen dioxide (NO 2 ) 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 SO 2 ), nitrates (from NO x ), and secondary organics (from gaseous hydrocarbons). Two other aerosol concepts with respect to visibility are size distributionand chemical composition . For visibility purposes, it is critical to distinguish fine particles ( < 2.5 F m) from coarse particles (> 2.5 F m), because fine particles are much more efficient at scattering light than2-7 b ext ' b Ray % ' $ 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 PM 10 (particles with diameters between 2.5 F m and 10 F m) and other suspended particles (those with diameters greater than 10 F m) 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, C i is the atmospheric concentration of species i (μg/m 3 ), 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 NO 2 ). The above units, when multiplied, yield units for b ext of 10 -6 m

-1 or (10 6 m) -1 , or as typically labeled, inverse megameters (Mm -1 ). An equation used by the IMPROVE program to estimate reconstructed aerosol extinction is: b ext = b ray+ (3)

f (RH) [Sulfate] + (3)

f (RH) [Nitrate] + (4) [Organic Mass Carbon] + (1) [Soil] + (2-6) (0.6) [Coarse Mass] + b abs Alternatively, b abs 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 aerosols2-8 f (RH ) ' b scat (RH ) / b scat (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 F m and a geometric size distribution of 1.5 F m (Malm et al., 1996). The function of RH, f (RH), illustrated in Figure 2-3 is:

where b scat

(0%) and b scat

(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 m 2/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.2-10

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 308.2-11 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.2-12

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 te chnology 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"). ! Establishprograms 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 ( I nteragency M onitoring of Pro tected V isual E nvironments). The 1990 amendments to the Clean Air Act included a new section 169B emphasizing regionalvisibility 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.2-13

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 responsibleorganization. For example, the U.S. Fish and Wildlife Service may define its affirmative responsibilityto 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 Ensurethat High Quality, Comparable Data are Collected by All Monitoring Organizations Through Adoption of Standard Monitoring Protocols. Itis 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 andcapable 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 referencemethod 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 IMPROVEprotocols include Standard Operating Procedures (SOPs) and Technical Instructions (TIs) that define the monitoring methods, laboratory methods, data reduction and2-14

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 regulat ory, planning, and research purposes is the I nteragency M onitoring of Pro tected V isual E nvironments (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 spatialscale 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( M easurement O f H aze And V isual E ffects) and the Mount Zirkel reasonable Attribution Study. An example of recent research programs that included visibility components are SEAVS ( S outh E astern A erosol and V isibility S tudy) and NFRAQS ( N orthern F ront R ange Air Q uality S tudy). 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.2-15

2) Knowledgeof 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. Visibilityvaries 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 Inorder 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 distributionof 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 disperseand 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 contributedto 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). 2-16 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
specificallyidentify 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 requiredto 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 wouldbe 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 improveupon 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 pollutionexists when improvement is the goal. The EPA and/or regulatory agencies must define what continualimprovement 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 andmajor modifications locating in areas designated as nonattainment for the NAAQS. The Preventionof Significant Deterioration (PSD) permitting program applies to new major stationary sources andmajor 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. Forthe 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. 72-17

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 beendesignated 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 dataused 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 visualrange. 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 orother 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 methodo logy, 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. Additionalconsiderations 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 requiredis 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 bean integral part of the monitoring program and address: primary parameters, network design, and2-18

qualityassurance. 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 PM 2.5 and PM 10 particulates at least every third day. ! Determinethe 24-hour average PM 2.5 (fine), PM 10 and PM 10 minus PM 2.5 (coarse) mass concentration of the filter samples with an overall accuracy of 10%. ! AnalyzePM 2.5 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 PM 2.5 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 ! Derivethe liquid water associated with hygroscopic species from associated RH measurements and species growth curves. ! Determineadditional 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).2-19

2.3.1.2 Optical Opticalmonitoring measures the light scattering and absorbing properties of the atmosphere, independent

of physical scene characteristics or illumination conditions. Optical monitoring recommendations are the following: ! Determinethe hourly average ambient atmospheric light extinction coefficient with an overallaccuracy 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 withoptical 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 ± 0.5 E C 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 examplenetwork configurations are provided in Section 2.6. However, the principle considerations in network design are the following: ! Eachsite must be selected to represent visual air quality within the air mass of interest. For example, the visual air qualityof a Class I area should be monitored at an elevation typical of the Class I area, and withinthe 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 downwindof a suspected source region, but may only operate for a short period of time (several months to a year or more).2-20

! “Represe ntative” sites should be determined on a case-by-case basis. Important considerations should include common elevation, common source region of emissions, andsimilar location relative to major topographic features. (See additional discussion in section 2.6.) ! Year-roundmonitoring 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. ! Visibilitysite 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 PM 2.5 mass, PM 10 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 costconsiderations, aerosol monitoring alone can be used to calculate reconstructed light extinctionusing 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 collocatedwith 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 overallcharacteristics 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 canoften 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 change s 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 be2-21 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 extinctionmeasurements 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 determineexisting conditions, the most scientifically sound configuration would include a comprehensiveconfiguration of aerosol, optical, and scene parameters where a transmissometer wouldmeasure b ext . If a transmissometer installation were not possible due to logistic limitations, a nephelometer-basedinstallation 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 b ext /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: ! Standardoperating 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. ! Standardscientifically accepted methods to determine, calculate, and report measurements:

- Standard visibility variables and units: b ext , b scat , b abs , (inverse megameters) deciview index (in dv) visual range (in km)

- Standard aerosol mass concentrations units: F g/m 32-22 - 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.

- Validityflags and weather effects flags. These should be associated with data values. Qualityassurance, 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 Comments PM 2.5 PM 10 b ag Trans Neph Still-Frame Time-Lapse Mass Elements Ions b ap Mass Elements NO 2 Gas b ext b scat 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 Needed2-24

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 F m (PM 2.5 ) and aerodynamic diameters # 10 F m

(PM 10 ). To identify and track the relative visibility impacts caused by various pollution species, a complete aerosol characterization is recommended. This would include PM 2.5 compositional analysis for all of the major components responsible for visibility impacts, including sulfates, nitrates, organic carbonspecies, inorganic carbon, earth crustal components, and the chemical constituents of other fine mass. Wherewind erosion may be a concern, the coarse particle mass concentration (particle diameter from 2.5 F m to 10 F m) should also be characterized. An understanding of the liquid water associated with hygroscopic particlecomponents is also important. With present technology, the liquid water particle component cannot bedirectly 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 relativehumidity monitoring is a desirable supplement to aerosol monitoring. However, aerosol data together with climatological meteorological parameters can be used to estimate extinction. Opticalmonitoring 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 (b ext ), defined as the fraction of light lost per unit distance as light traverses the atmosphere. It is the sum of scattering and absorption coefficients (b scat and b abs ) of atmospheric gases and aerosols. Optical monitoring can be performed using a transmissometer to obtain ambient extinctionmeasurements. 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 b ext measurement is important. Relative humidity data can be usedto clarify observedvisibility 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 recorddocuments the appearance of a scene. Scene characteristics include color, texture, contrast, clarity, andobserver visual range. Photography is uniquely suited for identifying ground-based or elevated layers orplumes that may impact Class I or protected areas, as well as documenting conditions for interpreting aerosol and optical data. Sinceits formation in 1985, researching the most effective and efficient means of monitoring visibility andapplying 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 IMPROVEsampling 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 b ext , b scat , and b abs canbe 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 samplingprotocols. Although IMPROVE protocols support a full site configuration of aerosol, optical, and scenemonitoring, 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 Component 1 Instrument Monitoring Method/ Measured Parameter Sampling Frequency (Reporting Interval) System Accuracy Instrument Uncertainty (Precision) Aerosol IMPROVE Aerosol Filter

Sampler: Module Filter A: PM 2.5 , 25mm Teflon B: PM 2.5 , 25mm Nylon C: PM 2.5 , 25mm Quartz D: PM 10 , 25mm Teflon Point measurement of aerosol mass and aerosol species as noted below:

PM 2.5 mass, elements (H, Na-Pb), coefficient of absorption PM 2.5 nitrate, sulfate, and chloride ions PM 2.5 organic and elemental carbon PM 10mass 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 (b ext ) Continuous (hourly-average) ! No absolute calibration standard ! Accuracy inferred from comparison to measured b scat + b abs and to reconstructed b ext 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 (b scat ) 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 ±0.3 E C Relative Humidity ±1.5% RH from (0 to 100%) Precision determined by collocated samplers Repeatability: Temperature ±0.1 E C RelativeHumidity ±0.3% RH 1. Goals and objectives addressed by each monitoring type are provided in Table 2-12-27

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 b ext to aerosol relationships. Scene monitoring by itself can lead to the identification and characterizationof 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 orfewer sites with more instruments) are real considerations. Site logistics may also restrict the operation of certain instruments at some sites. Ad ditional 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. ! NO 2 analyzer - b ag(light absorption by NO 2 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 instrumentationthat 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 Programhas 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 samplecollection and consistency with the PM 2.5 program. IMPROVE protocols for aerosol monitoring employ four (4) independent sampling modules at eachsite. As described below, three of the four samplers collect fine particles with aerodynamic diameters # 2.5 F m: ! 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 PM 10 particles with aerodynamic diameters up to 10 F m, using a Teflon filter. Particles >2.5 F m are less efficient light scatterers than PM 2.5 particles. By subtracting collocatedPM 2.5 from PM 10 mass concentrations, an estimate of coarse particles (2.5 F m <10 F m) can be made. Analysis of IMPROVE filters for mass concentrations of separate aerosol species is a key to aerosol-based reconstructed extinction (b ext ) techniques. The measured mass concentration of the species that contribute to visibility degradation multiplied by their extinction efficiencies can yield an estimateof 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 Opticalmonitoring 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 b ext and/or b scat

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 knowndistance (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 electronicallyconverted to hourly averaged light extinction (b ext ). If practical constraints make it impossibleto operate a transmissometer at a particular area, ambient scattering (b scat ) can be measured withan ambient-temperature nephelometer. Ambient nephelometers draw air into a chamber and measurethe scattering component of light extinction. On days when aerosol samples are taken, the determinedscattering coefficient can be combined with the absorption coefficient, estimated from aerosol monitoring filters, to estimate the average total light extinction (b ext ) 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 reductionand 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. IMPROVEprotocols recommend that color photographs (i.e., 35 mm slides or digital images) betaken several times a day. The data collection schedule can be tailored to capture the periods whenvisibility 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, datacollection, 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 becalculated from measurements using various assumptions (Section 2.1). Visibility related indexes canalso 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). Table2-4 provides the recommended standard reporting units. Tracking, reporting, archive, and database formats should be consistent to promote comparable visibility data nationwide. Onesource of confusion concerning visibility related measurements and standard units has beenthe common practice of converting measurement data to a different index. Such conversions usuallyrequire 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 Units 1

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 F m, particulate matter less than 2.5 F m F g/m 3 ng/m 3

Particle composition Elemental and ion concentrations F g/m 3 ng/m 3 Physical characteristics Shape, structure, and index of refraction Extinction coefficient (b ext ) Total loss of light due to absorption and scattering Mm -1 Scattering coefficient (b scat ) The portion of light loss due to scattering by particles and gases Mm -1

Absorption coefficient (b abs ) The portion of light loss due absorption by particles and gases Mm -1

Scattering phase function Angular distribution of scattered light Rayleigh scattering coefficient (b Ray ) 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 (b ext ) 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 EPAfor 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 exchangewill 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 bearchived 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 Visibilitydata 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. Primaryconsiderations 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 begenerated in a manner consistent with promulgated regulations and this EPA Visibility Monitoring GuidanceDocument 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 lookoutobservations should not be used as a surrogate for measured extinction values (see Section 2.1.1). Visibilitymonitoring data are used to address existing and potential data requirements set forth in each of the following applications: ! VisibilityProtection 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 E C (DRI) O2 = Organic carbon, 120 E C - 250 E C (DRI) O3 = Organic carbon, 250 E C - 450 E C (DRI) O4 = Organic carbon, 450 E C - 550 E C (DRI) OP = Pyrolized organic, 550 E C, 2% O2, reflectance # initial (DRI) E1 = Elemental carbon + pyrolized organic, 550 E C, 2% O2 (DRI) E2 = Elemental carbon, 550 E C - 700 E C, 2% O2 (DRI) E3 = Elemental carbon, 700 E C - 800 E C, 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 b ext(Mm -1 ) 6 b extuncertainty (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 b extvalidity code 1 13 Temperature ( E C) 14 Temperature uncertainty ( E C) 15 Temperature validity code 2 16 Relative humidity (%) 17 Relative humidity uncertainty (%) 18 Relative humidity validity code 2 19 Haziness (dv x 10)

1 b extvalidity 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 b ext> maximum threshold x x x x x x x x b extuncertainty > threshold x x x x x x x x ) b ext> 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: b extbelow 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 1234567890123456789012345678901234567890123456789012345678901234567890123456789012345678901234567890123456789012345678901234567 89012345678901234567890123456789012345678901234567890123456789012345678901
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 < = b scat less than Rayleigh scattering 22-24 Nephelometer Serial Number XZ = Data point immediately preceded and followed by interference 26-32 b scat (Mm -1 ) X? = Interference of type ? 34-40 b scat Estimated Precision (%/100) 42-43 b scat 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 scat > 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 b scat rate of change > threshold x x x x x x x x 76-81 b scat Rate of Change Interference Threshold 83-88 Maximum b scat 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 b scat 104 Number of missing data points 118-124 Slope of Calibration Line Used to Calculate b scat 105 Number of power failure codes 126-131 Average Ambient Temperature ( E C) 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 ( E C) 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 ImplementationPlans (TIPs) - Visibility data can be used to quantify existing conditions, supporttrend 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. ! FederalDocuments, (e.g. regional assessments, management plans, Environmental Impact Statements, etc.) - Visibility data that describeexisting 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. ! FireEmissions 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. ! FineParticulate Standards - Existing visibility-related PM 2.5 and PM 10 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. Visibilitymonitoring 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 needto 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 effective2-36

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. Visibilitymonitoring 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 beused to represent the visual air quality of nearby Class I areas if the nearby areas are generally affected by the same air mass (Section2.6.1.1). 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. Designof a special visibility study network is often more locally oriented and more intensive thanroutine network designs. Special studies include site-specific pre- and post-operation monitoring relatedto 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 oftenbe coordinated with and even funded by the proposed source. Visibility monitoring using routine monitoring techniques in conjunction withstandard ambient PSD measurements can define andhelp 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 pollutionemission 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 berequired to supplement the routine monitoring information. Monitoring and other sources of information(e.g., emissions characterization, model outputs, etc.) must allow the identification of substantialvisibility 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 otherresearch topics. These studies are usually designed to address scientific theses and include traditional and research instrumentation and analytical techniques.

2.6.1 Assessment Criteria Basedon 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 designphase of visibility monitoring. Each set of criteria parameters are independent, however they shouldbe 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 orsupport 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. Reasonablyattributed 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 - PM 10 , NAMS, SLAMS, other studies 1. Aerosol point

measure - PM 2.5 , PM 10 2. Optical -b extpath measurement - b ext 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 changes2-38

2.6.1.1 Spatial Considerations Spatialconsiderations 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 objectiveor 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. Thedimensions of a local or urban area can rangefrom 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 ensurethat both vertical and horizontal air quality characteristics are considered at this scale. Existing conditions, long-term trends

National and Global Thesemeasurement 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

Unlikesite-specific objectives, which can be met at isolated individual locations without referenceto 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 andfrequency of exposure to visibility influencing pollution sources, andsimilar terrain. Representative Class I areas should share the same air basin or geographic2-39

province(e.g., not be on opposite sides of a major mountain range). They should be closer to each otherthan the average distance to any major stationary point source of visibility reducing emissions. Theyshould roughly share the same average elevation (e.g., mountain tops are not representative of valleyfloors). 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 individualsite 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. Severalcriteria 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 oftenor 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 onsitepersonnel 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 couldbe conducted that would include some level of monitoring, for at least a short period of time, atall of the Class I areas within a "representative area." A pilot study could provide specific data to evaluaterepresentative 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, andexposure to visibility influencing pollution sources. Monitoring objectives and monitoring data collectedmust be compatible to provide a common basis for the interpretation and application of the data. Regional Representative Conditions Regionalareas can cover a broad geographic area. Generally, a number of sites will be requiredto 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 regionmay 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 ex ample, 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 timingof the event were different. One site was not purely representative of the next, but data from bothcan 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 summarizespatial 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 thatoccur 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 Area2-42

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 thatinvolved several stages. In a scoping stage, two criteria were applied to assess the feasibility of individualmonitoring platforms to be applicable to more than one Class I area. The criteria required thatmonitoring must be within 100km of the protected area and that the monitoring site elevation bewithin 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 becovered by these criteria. Then the criteria were used to identify the locations and elevations that wouldbe 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 detailedknowledge 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 coastof 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 valuableinformation about the existing conditions and long-term trends of visibility. Data from long-term sites can be used to track progress toward the nationalvisibility goals, to support permit applications, and to support a range of resource-related researchprojects. 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-termmonitoring sites are established to address specific visibility concerns. Examples of short-term monitoring include pre- and post-construction source-specific monitoring sites, source attributionstudy sites, and/or specialized research. Short-term sites can also be established as a precursorto 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 beclassified "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. Specialstudies range from simple to sophisticated. In the case of a plume or layer from a largenearby 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 contributionof 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 conjunctionwith 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 generallyrequire collection periods from several hours to 24 hours depending on the ambient concentrations and analyses techniques. Most particulate samples in long-term programs are generallytaken 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 t o 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, andanalysis phase of visibility monitoring. Meteorological conditions, fire emissions, regional haze, andindustrial 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 Programconsiderations 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 bemonitored. Do the data provide a record of average aerometric conditions that represent the spatialand 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. Manyeconomic and logistic benefits can be obtained by establishing cooperative monitoring efforts between representative air monitoring sites and programs. Capital equipment, land use fees, androutine 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 Inthe process of network design, what visibility parameters will be necessary to base conclusions, support hypotheses (objectives), or address defined legal standards? What parameter2-45

considerations regarding measurement accuracy and precision, temporal resolution, spatial resolution, andcomparability need to be evaluated given site-specific or network-specific objectives? A number o f these monitoring issues were addressed by Marc Pitchford for the IMPROVE Network (September

1993). Excerpts of his recommendations to IMPROVE Committee members are providedin the following subsections. Table 2-7 provides a tabular listing of the data sources, associatedtemporal resolution and spatial representativeness, and data comparability for each visibility monitoring parameter. Example parameter and instrument specifications based on the IMPROVEProgram 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 approachfor 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. ! Elementalcomposition provides information about the chemical and physical properties of aerosols and about probable sources and source types. For example, identifying a sulfateaerosol 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. ! Particlesizing 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 Temporal Resolution Data Comparability
Aerosol Aerosol components: PM 2.5 Fine Mass Elemental Analysis (H, Na-Pb) Coefficient of absorption (b abs ) Nitrate, Sulfate, and Chloride ions Organic and elemental carbon PM 10 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 (b ext ) 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 (b scat ) Point Measurement Nephelometry* Continuous sampling, commonly summarized as 1-hour, 4-hour, or 24-hour averages Data can be combined with

collocated absorption (b abs ) measurements to estimate total light extinction (b ext ). Does not define the source of impairment. Particle Absorption (b ap ) Point Measurement Filter-based particle absorption measurements Continuous

sampling (e.g., aethalometer) Data can be combined with

collocated scattering (b scat ) measurements to estimate total light extinction (b ext ). Does not define the source of impairment. Intermittent sampling (e.g., integrating plate, integrating sphere analysis method) Data can be combined with

collocated scattering (b scat ) measurements to estimate total light extinction (b ext ). 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 (b ag ) Point Measurement NO 2gas analyzer Continuous sampling commonly summarized as 1-hour averages NO 2is 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; PM 2.5 and PM 10 . 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 PM 2.5 mass concentration and elemental analyses at least twice a week. However, in order to identify and track visibility impacts causedby various pollutant species, a more complete aerosol characterization is strongly recommended. This more complete approach should include both PM 2.5 and PM 10 sampling. PM 2.5 filter samples should generally be analyzed for mass, optical absorption, elements, sulfates, nitrates, chlorides, organic carbon, and elemental carbon. PM 10 filters should be analyzed for mass and elements. With this informationit is possible to use analytical techniques to estimate the extinction coefficient from these aerosol constituents. This method of reconstructing extinctionfrom 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 discussedin Section 3.0 of this document. Other samplers would also be applicable as long as the entiresystem 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

(b ext ) and/or the absorption and/or scattering components of b ext independent

of physical scenecharacteristics 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 (b abs + b scat = b ext ). 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) havebeen 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 ( F m) Sizing Device Flow Rate (L/min) Sampling

Surfaces Filter Holders Filter Media Features
Western Region Air Quality Study (WRAQS) Sampler PM 15 Aluminum highvolume impactor 113 out of

1,130 Aluminum and

copper Nuclepore

polycarbonate in-line 47 mm Teflonmembrane 47 mm quartz-fiber PM 2.5 Steel mediumvolume cyclone 113 Aluminum and copper Nuclepore

polycarbonate in-line 47 mm Teflonmembrane 47 mm quartz-fiber Size Classifying Isokinetic Sequential Aerosol (SCISAS) Sampler PM 15 Aluminum highvolume impactor 113 out of

1,130 Aluminum and

polyvinyl chloride Nuclepore

polycarbonate open-face 47 mm Teflonmembrane 47 mm quartz-fiber Sequential

sampling.

PM 2.5 Steel mediumvolume cyclone 113 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 PM 10 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. PM 2.5 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 nylonmembrane47 mm etched polycarbonate Sequential Filter Sampler (SFS) PM 10 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. PM 2.5 Aluminum

medium-volume cyclone 20 out of 113 Teflon-coated aluminum Nuclepore

polycarbonate open-face 47 mm Teflonmembrane 47 mm quartz-fiber47 mm nylonmembrane 47 mm impregnated cellulose-fiber California Acid Deposition Monitoring Program (CADMP) Dry Deposition Sampler PM 10 Aluminum medium-volume impactor 20 of 113 Aluminum Savillex openface 47 mm Teflonmembrane 47 mm impregnated cellulose-fiber Includes nitric acid

denuders. Sequential sampling. PM 2.5 Teflon-coated

steel mediumvolume cyclone 20 of 113 PFA Tefloncoated aluminum Savillex PFA

Teflon openface 47 mm Teflonmembrane47 mm nylonmembraneTable 2-8 (cont.) Example Particle Sampling Systems (Chow, 1995)

Filter-based Research Particle Sampling Systems

Sampling System Particle

Size ( F m) Sizing Device Flow Rate (L/min) Sampling

Surfaces Filter Holders Filter Media Features

2-50 Versatile Ambient Pollutant Sampler (VAPS) PM 10 ,

PM 2.5 Teflon-coated

aluminum lowvolume elutriatorand 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 PM 10 Aluminum lowvolume impactor 16.7 Stainless steel and aluminum Gelman

stainless steel in-line 47 mm Teflonmembrane 47 mm quartz-fiber PM 2.5 Aluminum lowvolume cyclone 22 Teflon-coated aluminum and glass Gelman

stainless steel in-line 47 mm Teflonmembrane 47 mm quartz fiber47 mm nylonmembrane Interagency Monitoring of Protected Visual Environments (IMPROVE) Sampler PM 10 Aluminum lowvolume cyclone 19 Aluminum Nuclepore polycarbonate open-face 25 mm Teflonmembrane Uses Wedding Beta

Gauge PM 10 inlet.

PM 2.5 Aluminum lowvolume cyclone 22.7 Aluminum Nuclepore polycarbonate open-face 25 mm Teflonmembrane 25 mm quartz fiber25 mm nylonmembrane Nitric acid

denuders ahead of nylon filter.

Stacked Filter Unit (SFU) PM 2.5 Large-pore etched polycarbonate filters 10 Polycarbonate Nuclepore polycarbonate open-face 25 mm Teflonmembrane Uses large-pore

etched polycarbonate filter as PM 2.5 sizing device. BYU Organic Sampling System (BOSS) PM 2.5 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 todetermine semivolatile organic compounds. BYU Organic Sampling System (BOSS) PM 2.5 ,

PM 0.8 , PM 0.4 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 todetermine semivolatile organic compounds. Harvard/EPA Annular Denuder System (HEADS) PM 2.5 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 ( F m) 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 ) PM 2.5 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 PM 10 ,

PM 2.5 Nylon lowvolume impactor 5 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 PM 10

Sampling System Particle

Size ( F m) Sizing Device Flow Rate (L/min) Filter Media Reference/Equivalent Method Designation Number) Federal Register Citation (Notice Date) Wedding & Associates PM 10 Critical Flow High-Volume Sampler PM 10 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 PM 10 HighVolume Air Sampler System PM 10 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 PM 10 HighVolume Air Sampler System PM 10 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 PM 10 HighVolume Air Sampler System PM 10 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 PM 10 PM 10 SA 254 impaction-type inlet 47 mm Teflonmembrane47 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 PM 10

Sampling System Particle

Size ( F m) Sizing Device Flow Rate (L/min) Filter Media Reference/Equivalent Method Designation 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 PM 10 Low Volume Dichotomous Samplers PM 10 ,

PM 2.5 SA 246 B or G

246 impactiontype inlet, 2.5 um virtual impactor assembly Total:

16.7 for PM 10 Coarse: 1.67 Fine: 15.03 for PM 2.5 and less 37 mm PM 2.5

37 mm coarse [PM 10 minus PM 2.5 ] Reference method

(RFPS-0389-073) Vol. 54, 31247 (07/27/89)

Andersen Instruments Model FH621-N PM 10 Beta Attenuation Monitor PM 10 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 PM 10 Monitor PM 10 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 PM 10 Beta Gauge Automated Particle Sampler PM 10 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 PM 10 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 (b s cat ) by particles and gases. These instruments are called nep helometers 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 onlya portion of the scattered light is measured, however, and since absorption is completely unaccountedfor, these instruments will mis-measure visibility under atypical aerosol conditions. Integrating nephelometers measure scattering over nearly the entire range of angles from 0 E to 180 E

. 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 (b scat ). The polar nephelometer measures the light scattered from any chosenangle. 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 l aboratory situations. Since a nephelometer makes a point measurement, direct comparisons to collocatedaerosol 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.
Opticalabsorption (b abs ) 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 b abs from Teflon filters. An aethalometer is one instrument that continuously measures particle light absorptionon a filter media. Other experimental methods have also been developed. Absorption methods used to estimate the absorption coefficient can be combined withnephelometer 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 f orm. Specifically, visual range observations and target contrast data are converted to extinction coefficient

values (b ext ). 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 cooperativ e monitoring programs are established between state, federal, tribal, and private2-54

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 onsitepersonnel 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 bedemonstrated 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 IMPROVEProgram 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 bedeveloped 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 thatwere 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 IMPROVEprotocols, 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 combinationof 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 PM 2.5 samples (Modules A, B, and C) and one PM 10 sample (module D). Module A uses a Teflon filter that is analyzed for PM 2.5 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 PM 10 mass. Additionalspecifications regarding the IMPROVE aerosol sampler are provided in Section 3.0. Transmissometers are currently employed to measure the optical light-extinction coefficient (b ext ) at selected IMPROVE Program sites. Nephelometers are employed at other sites to measure the optical light scattering coefficient (b scat ). Absorption measurements (b abs ) 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 Programsites in association with aerosol and optical monitoring. Most sites, however, discontinue scenemonitoring 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 qualitativerecord 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 visibilityresearch 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 proposedregulations 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 CanyonNational 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 ( M easurement o f H aze a nd V isual E ffects). The primary goal of Project MOHAVE was to determine the contribution of the Mohave Power Project (MPP), a 1580 Megawatt, coal-fired steam electric powerplant, 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

! Ident ifying 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 NationalParks and Wilderness Areas Committee of the National Research Council, National Academyof 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 CanyonNational 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. Instrumentationincluded 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 couldbe 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 witha transmissometer. Surface meteorological data were collected at two of the transmissometer sites. ! BackgroundSites - Twenty-one (21) background sites were selected to characterize high elevationand low elevation transport into the study area and to show detailed concentrationpatterns within the study area. Module A of the IMPROVE aerosol sampler and a filter pack for SO 2 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 throughoutthe 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 andto help identify the interaction between MPP and southern California emissions. Tracer data also servedas 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 SO 2 , andto 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 depthof 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. Basedon 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 hazewith a defined boundary) in the Lake Tahoe urbanized areas. Thresholds were established to achievevisual 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 standardattainment 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 PM 10 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 w as established at Bliss State Park to monitor regional air within the Lake Tahoe Basin. A full IMPROVEaerosol sampler, integrating (ambient) nephelometer, and transmissometer were installed in November 1990. The13.3 km transmissometer sight path extended from the Zephyr Point Fire Towerto the Bliss State Park monitoring location. Meteorological measurements, temperature, relativehumidity, 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. Collecteddata 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 (PM 2.5 ) and aerodynamic diameters < 10 μm (PM 10 ). The particulate monitoring portion of the IMPROVE program measures the concentration of PM 2.5 particles for mass, optical absorption, major and trace elements, organic and elemental carbon, and sulfate, nitrate, and chloride ions, and the concentration of PM 10 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 PM 10 module with Teflon filters, and three PM 2.5 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 PM 2.5 module with Teflon filters for quality assurance. The samplers were designed by Crocker Nuclear Laboratory (CNL) at the University of California, Davis3- 2 electrical to controller Module A
PM 2.5 (Teflon)
mass, elements absorption Module B
PM 2.5 (nylon) sulfate, nitrate ions Module C
PM 2.5 (quartz) organic, elemental carbon Module D
PM 10 (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 ( PM 2.5 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 [SO 4 = ], nitrates [NO 3 - ], nitrites [NO 2 - ], & 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 (PM 10 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 PM 2.5 modules used before and after 1999, for the PM 10 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

MAGNEHELIC 30 25 20 0 .20

ZERO SET .80

.60 1.0

Figure 3-2a. Schematic of the IMPROVE PM 2.5 module used before 1999.3- 4 

## PM 2.5 

## 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 PM 2.5 module used after 1999.3- 5 

## PM 10 

## Filter Module

1 stack compression sleeve 2 inlet stack 3 sampler retainer pin 4 PM 10 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 PM 10 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 PM 2.5 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 PM 10 particles is accomplished with a commercial PM 10 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 PM 2.5 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 PM 10 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 against3- 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 PM 2.5 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 PM 10 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 HNO 3 from the air stream before it reaches the filter. Since 1988, the denuders have been changed annually. Tests indicate that with respect to SO 2 , 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 HNO 3 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 calculatedflow 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 Crocker3- 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.

• Po st-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.

• L eak 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

carbon ions 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 PM 2.5 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 (b abs ) The coefficient of light absorption for fine particles, b abs , 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 b abs 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 PM 10 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 PM 10 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 (HNO 3 ) 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 (K2 CO 3 ), is placed in the ModuleB inlet to remove HNO 3 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 CO 2 using an oxidizer (MnO 2 at 912 ° C).

• Reducing the CO 2 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 is3- 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 (PM 10 ) 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 PM 2.5 from total aerosol mass PM 10 . 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% O 2 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 Table3-4 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 SO 4 =(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 PM 2.5 Fine Mass A Gravimetric ng/m 3 Fine Mass H 1 Hydrogen A PESA ng/m 3 Major Element Na 11 Sodium A PIXE ng/m 3 Marine Mg 12 Magnesium A PIXE ng/m 3 Soil Elements Al 13 Aluminum A PIXE ng/m 3 Soil Elements Si 14 Silicon A PIXE ng/m 3 Soil Elements S 16 Sulfur A PIXE ng/m 3 Major Element Cl 17 Chlorine A PIXE ng/m 3 Marine K 19 Potassium A PIXE ng/m 3 Soil Elements Ca 20 Calcium A PIXE ng/m 3 Soil Elements Ti 22 Titanium A PIXE ng/m 3 Soil Elements V 23 Vanadium A PIXE ng/m 3 Metallic Tracer Mn 25 Manganese A PIXE ng/m 3 Soil Elements Fe 26 Iron A XRF ng/m 3 Soil Elements Co 27 Cobalt A XRF ng/m 3 Multiple Ni 28 Nickel A XRF ng/m 3 Metallic Tracer Cu 29 Copper A XRF ng/m 3 Metallic Tracer Zn 30 Zinc A XRF ng/m 3 Metallic Tracer As 33 Arsenic A XRF ng/m 3 Metallic Tracer Se 34 Selenium A XRF ng/m 3 Metallic Tracer Br 35 Bromine A XRF ng/m 3 Metallic Tracer Pb 82 Lead A XRF ng/m 3 Metallic Tracer

NO 3 - N/A Nitrate Ion B IC ng/m 3 Major Ion NO 2 - N/A Nitrite Ion B IC ng/m 3 Major Ion SO 4 = N/A Sulfate Ion B IC ng/m 3 Major Ion Cl - N/A Chloride Ion B IC ng/m 3 Marine

OC1 6 Low Temperature Organic Carbon C TOR ng/m 3 Organic Carbon OC2 6 High Temperature Organic Carbon C TOR ng/m 3 Organic Carbon OC3 6 High Temperature Organic Carbon C TOR ng/m 3 Organic Carbon OC4 6 High Temperature Organic Carbon C TOR ng/m 3 Organic Carbon EC1 6 Low Temperature Elemental Carbon C TOR ng/m 3 Elemental Carbon EC2 6 High Temperature Elemental Carbon C TOR ng/m 3 Elemental Carbon EC3 6 High Temperature Elemental Carbon C TOR ng/m 3 Elemental Carbon

PM 10 N/A PM 10Mass D Gravimetric ng/m 3 PM 10Mass Note: For consistency across all parameters, the IMPROVE data for PM 2.5 Fine Mass and PM 10 Mass total mass is generally reported in ng/m 3 . Conversion to μ g/ m 3 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

[ (NH 4 ) 2 SO 4 ] 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

[(NH 4 )NO 3 ] B 1.29[NO 3 - ]; 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 PM 10- PM 2.5 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 b extfrom 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 SO 2 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 Elements3- 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 Components3- 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 Distributions3- 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 = El emental 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 NH 4 +, NO 3 -, and SO 4 = 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+,NH 4 +, NO 3 -, and SO 4 =. 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 (NH 4 NO 3 ). (HNO 3 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 (Watsonet 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 NH 4 +, NO 3 -, and SO 4 = are all measured. However, since nitrate volatilizes from Teflon during sampling, the equation cannot account for the hydrogen in (NH 4 )NO 3 . 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 (Al 2 O 3 , SiO 2 , CaO, K 2 O, FeO, Fe 2 O 3 , TiO 2 ), plus a correction for other compounds such as MgO, Na 2 O, 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 PM 2.5 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 PM 2.5 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 PM 2.5 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 K 2 O 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 (PM 2.5 ) concentration from total aerosol mass (PM 10 ) concentration:
[CM] = [PM 10 ] - [PM 2.5 ] (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 PM 2.5 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 PM 10 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 appro priate programs and site-specific information, • four filter cartridges, with each cartridge having four filters with different pressure drops, • one calibrated audit device for PM 2.5 modules and one for the PM 10 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 flow3- 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 b abs

• 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 the3- 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, f v , 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, f a . 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, σ a , 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, σ stat . 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% PM 2.5 , PM 10 , H, S, Si, K, Ca, Fe, Zn,

SO 4 = , NO 3 - , SO 2 PM 2.5 , PM 10 , S, Si, K, Ca, Fe, Cu, Zn, SO 4 = , NO 3 - , SO 2 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/m 3

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% PM 2.5 , PM 10 , H, S, Si, K, Ca, Ti, Fe,

Zn, Br, SO 4 = , NO 3 - , SO 2 , OP, E1 PM 2.5 , PM 10 , H, S, Si, K, Ca, Fe, Cu, Zn, Br, Pb, SO 4 = , NO 3 - , SO 2 , 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, E33- 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 (SOIL) 2.20 (Al) + 2.49 (Si) + 1.63 (Ca) + 2.42 (Fe) + 1.94 (Ti) s s s s s s

= (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 m 3 , 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 NO 3 -

.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 (b abs )

• Atmospheric Rayleigh Scattering ( b Ray ) 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 μ m 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) = b (RH) / b (0%)

scat scat (3-15) where b scat (0%) and b scat (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 M ass Carbon] + (1) [Soil] + (0.6) [CM

, Coarse Ma ss] + b (3-16)

where the first 5 components represent the light scattering by aerosol species, b abs represents the coefficient of light absorption for fine particles, and b Ray 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 i ndicate the mass concentration of the aerosol species or element. Three (3) m 2 /g is the dry scattering efficiency of sulfates and nitrates, four (4) m 2 /g is the dry scattering efficiency of organics, and one (1) m 2 /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 Reporting4-1 4.0 OPTICAL MONITORING As a n example of an existing visibility-related optical monitoring program, this sectio n describes IMPROVE optical monitoring and data management techniques. References made t o manufacturers or trade name s are not intended to constitute EPA endorsement or recommendations for use. N ew or improved instruments, instrument upgrades, and methods of monitoring ar e continually being developed. Opt icalmonitoring provides a quantitative measure of ambient light extinction (ligh t attenuati on per unit distance) or its components to represent visibility conditions. IMPROV E pro tocols collect continuous measures of b and/or b using ambient long-path transmissometers ext scat an d/ornephelometers respectively. A tabular summary of optical instrument specifications ar e pro vided in Table 4-1. Water vapor in the air can affect visibility, therefore IMPROVE protocol s state t hat temperature and relative humidity sensors must be collocated with the chosen optica l 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, qua lityassurance, and analysis and interpretation required for transmissometer and nephelomete r mon itoring respectively. Operation manuals and manufacturer's specifications are provided i n 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 irradianc e at the end of the path with the calibrated initial intensity of the light source. Usin g 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 b without perturbing ext or selectively sampling atmospheric aerosols or gases. Several measurement criteria ca utions should be considered. Transmissometers require path lengt hs of a few kilometers to achieve the necessary sensitivity to resolve extinctions near th e Rayleigh limit. In areas with non-uniform distribution of aerosols, comparison of measured extinction and reconstructed extinction from concurrent particulate sampl es can often be misleading. Extinction measurements from transmissometers also are affecte d by any meteorological or optical interferences present along the path which are independent from the ambient aerosol. An additional concern for trans missometers is the lack of an absolute calibration standard. Uncertainty measurement s 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 b 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 ext (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 -20 E C to +45 E C 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 -20 E C to +45 E C nominal4-3

The Opt ec, Inc. LPV-2 long-path transmissometer has been in use since 1986. Over 3 0 ins truments 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 s ource transmitter and a computer-controlled photometer receiver. Other specific transmissometer system components include transmitter and receiver alti-azimuth bases, a te rminal 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 i n Fig ure 4-1. Detailed information regarding transmissometer instrumentation or operation can b e found i n Model LPV Long Path Visibility Transmissometer Technical Manual for Theory o f Operation and Operating Procedures (Optec, Inc., 1991) and Standard Operating Procedures and Technical Instructions for Transmissometer Systems (Air Resource Specialists, Inc., 1993-1996). The t ransmitter 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 s ource or transmitter. Transmitter optics concentrate light from a 15 watt tungsten filament lamp into a narrow, well-defined uniform cone, magnif ying the beam to the equivalent of a bare 1500 watt lamp, allowing the operator to precis ely aim the light beam at the receiver. Although a 1 E cone of light is emitted from the

transmitter, only the center 0.17 E portion is used for routine monitoring. Field and laboratory measurements of beam isotropy have indicated that the central 0.17 E cone has less than 1% variation. Lighti ntensity emitted from the transmitter is precisely controlled by an optical feedbac k system, that continuously samples the center 0.17 E portion of the outgoing beam and performs fine adjustments to keep the light output con stant. Light emitted from the transmitter is "chopped" at 78 pulses a second by a mechanical spinning disk in front of the lam p. This allows the receiver computer to differentia

te the lamp signal from background or ambient lighting. An eyepiece lets the operator precisely aim the light beam. The receiver gathers light from the tra nsmitter, converts it to an electrical signal, isolates and measures th e received transmitter light, and calculates and outputs visibility results in the desire d 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 th e 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 t o calculate a one-minute average reading. The resultant readin g 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 an d 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 funda mental requirement for operation of the LPV-2 transmissometer is a clear , unobstructedline-of-sight (sight path) between the transmitter and receiver. To reduce the effects of thermal turbulenc e, 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 applicatio ns, 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 whethe r 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 k m lengths. If the mean visual range for the area is known, a usable path distance can be calculated as follows: (4-1) Unless o therwise 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 (>1.0 E ) sight path vertical angle, orientation of the r eceiver telescope to lighting conditions throughout the year should be thoroughly considered (e.g., a receiver teles cope 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 criteri on is to ensure that the air mass along the entire sight path between the receiver a nd transmitter is representative of the larger air mass to be monitored. Selecte d 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 l ength and height for representative monitoring of the air mass ! Be rep resentative 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., vehicl e exhaust,wood smoke, road dust, etc.) ! Be secure from vandalism ! Have available servicing personnel (operator) ! Be reasonably accessible during all months of the year4-6

Vari ous siting criteria to be considered as they apply to the actual transmitter and receive r station locations are: ! Stabi lityof 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 l and owner will be cooperative in allowing installation of the sites and continuou s access to the sites for the duration of the study. ! Vegetation growth -- growth of vegetation into the sight pa th 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 i s sensitive to strong radio signals. Avoid siting close to broadcast antennas or repeaters. ! Snow ac cumulation -- 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, orother large reflective surfaces near the transmitter can saturate the receiver detector and affect readings.

4.1.3 Installation and Site Documentation Tra nsmissometer

installation requires stable mounting posts, adequate sheltering, and a reliable power supply. Continuous, correct transmitter an d receiver telescope alignment is critical for proper transmissometer operati on. 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 pr e-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 rec eiver 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 a rray is comprised of three large solar panels which charge four deep-cycle batteries. Afte rcomponent installation, a distance measurement must be made from the front of th e receiver telescope tube to the front of the transmitter telescope tube. Transmissometer calibration nu mbers using this accurate distance value are then recalculated and dialed in on the receive r computer.4-7

System operation

is verified after the instrument settings and system timing have been set at th e transmitter and receiver. Upon completing the installation and verifying system operation, al l operat ors, back-up operators, and any other involved or interested on-site personnel should b e tra ined, including reviewing a site operator's manual. The manual contains standard operatin g procedures and technical instructions for operator maintenance, troubleshooting, system diagrams, rep lacingand shipping components, annual site visit procedures, field audit procedures, an d manufacturer's manuals (ARS, Inc. SOP 4110, TI 4110-3100, TI 4110-3300, TI 4 110-3350, TI 4110- 337 5, SOP 4115, TI 4115-3000, SOP 4710, Technical Manual for Theory of Operation an d Operating Procedures (Optec, Inc.), and Instruction Manual for Primeline 6723 (Solte c 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 rep ort, photographic documentation (including photographs of the shelters, all components , shelter supports, sight path, power supply, etc.), and documentat ion of any miscellaneous information necessary t o 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 s ervicing, 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 shelte rs at 7 to 10 day intervals. Routine servicing involves documenting the initial condition an d operation o f the components, inspecting and correcting alignment of both the transmitter an d receiver, cleaning optics of the system (including shelter windows , telescope lenses, and solar panels), recording the lamp vo ltage and battery voltages, and recording receiver display readings and switch settings. Timing should be che cked 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 Additionalroutine servicing, to be performed monthly or at a two-month interval, includes checking the t

ransmitter lamp status (changing the lamp every two months), inspecting the physical conditio n of solar panels, batteries, battery fluid levels, DCP antenna, and strip chart recorde r operation.4-8

4.1.4.2 Annual Site Visits Annual site visits are performed to exchan ge the existing transmissometer system for a newly servic edsystem, and to train site operators in servicing and maintaining the monitoring syste m 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 performe d to discuss the purpose of the monitoring program and theory of transmissometer system operation.

4.1.4.3 Instrument Calibration Calibrationof the LPV-2 transmissometer involves determining the irradiance from th e transmit terlamp that would be measured by the receiver if the optical sight path between the tw o units allowed 100% transmission. All co mponents 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. Recalibrati on of an instrument with a receiver computer other than the one used at calibration does not require instrument reca libration, but only recalculation of calibration numbers. No other system compon ent, including lamps, may be interchanged with another transmissometer withou t recalibration. All calibrations are cu

rrently 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. Th e calibration path (the distanc e between transmitter and receiver during calibration) is 0.3 km. At this distance, th e atmospheric transmission can be estimated with a high degree of accuracy for use i n calculating the calibration number. Because lamp brightness is dependent on lamp voltage, the lamp voltage is m

easured 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 ! Docu mentation 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 i nstrument. The burn-in cycle should be performed in the laboratory to stabilize th e filament position and reduce the incidence of premature lamp failure in the operational network. Asta ndardized calibration number is used in calculating lamp brightening and varies fro m instrument

to instrument. The standardized calibration number is calculated using the followin g 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 a ny cleaning or servicing of the instrument and includes: a receiver detector uniformity check, calibration of all op erational lamps, and calculating a lamp brightening factor for each post-calibrated lamp. The transmitted light intensit y 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-fiel d 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 manne r assumes a linear increase in lamp brightness. A lamp brighten ing database has been developed, which includes the shift in lamp brightness (based on a comparison of pre-field and post-field calibratio n numbers) as a function

of lamp-use hours. All post-calibrated lamp data are added to this database. Lamp brightening statistics are then an alyzed (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 windo w transmitta nce should be performed at the test facility and follow the basic measurement procedures described for other c alibrations. Individual and combined transmittance should be measured for the transmitter an d 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 averag e readings with the windows in to the average readings with the windows out, is the windo w 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 calibratio n. Annual servicing includes a post-field instrument inspection, functional test, an d 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 calibration4-11

4.1.5 Data Collection Transmissometers operate in a cycled mode, collecting a 1 0-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 receiv er then uses the 10 one-minute averages to calculate and output an analog 10-minute average value for the received lamp irradiance. Data ar e logged on data collection platforms (DCPs) and are processed by several entitie s before being available for downloading via modem. Monitoring stations with DCPs undergo th e following data downloading sequence: ! The DCP logs transmissometer data at pre-programmed intervals. ! At t hree-hour intervals, the DCP transmits the past three hours' data (three 10-minut e average s) 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 co llected 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. Ai r 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-minut

e 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 plo ts may be generated bi-monthly from raw data files. Data from operator lo g sheet s should be checked against data collected via data collection platform (DCP) to identif y inconsistencies and errors. Level -Atransmissometer data should be plotted bi-monthly and reviewed monthly

. I nconsistent 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-mo nthly plots. This procedure helps to identify the exact time of lamp changes, alignmen t corrections, and other actions done by the site operator affecting instrument operation. Thi s 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 v alidation levels: Level-A, Level-0, and Level-1. All three levels of v alidation include hourly average data. Level-A validation includes visual review and examinati on of the raw data and error files. Level-0 validation includes searching fo r questionable or physically unrealizable data. Level-1 validation includes c alculating 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. Standar d 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 c odes. The seasonal Level-A files should be checked for inconsistencies with a screenin g program that verifies data integrity and assigns validity co des. 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 datascreening program. At Level-0, transmissometer data are corrected for lamp brightening and converted to b using site-specific calibratio n information. The lamp brightening correction is based

ext 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: 3F drift (% ) ' 0

. 270 ( t 0

. 4405 3

T corr ' [ 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 ( F ) is a function of the lamp -on hours ( t ) defined by the following drift 3 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 ! Identificationof 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 b > maximum threshold x x x x x x x x ext b uncertainty > threshold x x x x x x x x ext TM b > Delta threshold x x x x x x x x ext Z Weather obser vation 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. Ascreening program should be used to again check all data and validity codes fo r inconsistenc ies. The data should then be reduced to four-hour average values of extinction (b ) , ext standardvisual 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 review ed to identify data reduction and validation errors, instrument operation problems, and calibration inconsistencies. Any identified problem s sho uld be immediately investigated and resolved by following the procedures detailed in standar d operating procedures and technical instructions. 4.1.7 Data Reporting and Archive 4.1.7.1 Data Reporting Data rep orts should be prepared in a format that generally conforms to the Guidelines fo r Preparing Reports for the NPS Air Quality Division(AH Technical S ervices, 1987). A separate data report should be prepared for each instrument type; transm issometer data reports should contain only trans missometer

data. Reporting consists of various text discussions and graphics presentation s 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 introdu ction should contain a conceptual overview of the purpose of the monitorin g pro gram and a description of the monitoring networks. The data collection and reduction sectio n should include data collection methods, data file review, data validation, application of validity codes, p rocessing through various validation levels, and discussion of file formats, theoretical concepts of uncert ainty measurements, and identification of meteorological and optical interferences that affect the calculation of b from transmissometer measurements. Various units of measurement, including ext haziness (dv), extinction (b ), and standard visual range (SVR) should be discussed. ext Th e site configuration section should contain a brief discussion of instrumentation at eac h transmissometer site, basic principles of operation, measurement principles, and data collectio n 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 sit e specifica tions. Site specifications include site name and abbreviation, latitude an d long itude of both the receiver and transmitter, elevation of both the receiver an d transmitter, the sight pa

th 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 Tra nsmissometer 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 eac h report. Seasonal Transmissometer Data Summaries include the following five data presentations: ! 4-H ourAverage Variation in Visual Air Quality (Excluding Weather-Affected Data)

- Plotof four-hour averaged b , SVR, and dv geometric mean values (without weather- ext influenced observations) for each day of the repor ting season. A mean value is calculated for each four-hour period from the valid transmissions for that day. Gaps in the plo t ind icate that data were missing, weather-influenced, or failed edit procedures. Fo r 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 humid ity measurements. This al lows rapid determination of the effect of increasing relative humidity on measured b ext and SV R. Long periods of relative humidity near 100% usually result in corresponding periods o f 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 a verage 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 fr

equency values for b are listed to the right of the plot and haziness to the ext lef t of the plot. SVR values are listed in the corresponding cumulative frequenc y summary table. Note that SVR and b are inversely related; for example, as the ai r ext becomes cleaner, b values decrease and SVR values increase. ext For deciview, the 10%, 50%, and 90% values are linear with respect to b changes. A ext one dv change is approximately a 10% change in b . Clean daysare characterized by low ext 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

! Vis ibility

Metric (Excluding Weather) - This table presents mean values excludin g weather for dv, b , and SVR. The best, worst, and average conditions using th e ext 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 Poss ible Hourly Averages in the Time Period - The total possible category i s calculatedby subtracting the number of hourly averages included in periods when th e instr ument

was removed due to conditions unrelated to system performanc e (con struction, site relocation, etc.) from the theoretical maximum number of hourl y 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 repres ents the number of valid hourly averages compared to the total possible hourly averages. Valid H ourly Averages Excluding Weather-Affected Data - The number of valid hourly averages (excluding any data affected by weather) collected during a season. Th e percentage represents the number of valid hourly averages compared to the total possible hourly averages. Percent o f All Valid Hourly Averages Not Affected by Weather - This percentag e collectio n 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 M edian Visual Air Quality - Plot of median monthly b , SVR, and dv value s ext both with a nd without weather-affected data. The left axis of the graph is labeled a s ha ziness (dv) and the right axis as b and SVR. Note that SVR and b are inversel y ext ext related. ! Monthl y

Cumulative Frequency Summaries: All Data - Table of cumulative frequenc y di stributionaverage 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 dat a recovery stati stics (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 b , SVR, and haziness values, both with and without weather-influenced ext data. The 10% to 90% values are plotted in 10% increments. Transmissometer data summaries should follow their description. Summaries should b e prepare dfor each site that operated during the reporting period. A brief discussion of events an d circums tances that influence data recovery should follow the data summaries. Operational statu s thro ughoutthe 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 co llected data, data collection losses or problem description, and problem resolutions. An analysis summary table should also be pre pared (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 numberb ext ' & ln ( T ) / r

* bext ' ± U

T / 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 th e trans missometer network, including changes in operational techniques, and a general conclusion of the monitoring period in review. A reference s ection should include technical references (documents cited in the report), and re lated 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 proces sed digital data for a given season, and constants, calibration, and data processing file s should be performed on a seasonal basis, after da ta 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, an d Level-1) on magnetic tape and CD-RO M. 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 speci fications, monitoring timelines, data coordinator/site operator corre spondence, site operator log sheets, trip reports, bi-monthly and seasonal summary plots , instrument

calibration records, instrument maintenance logs, and field audit reports. All validate d Level-1 data should be delivered as ASCII files (on PC-comp atible 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 sit e 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 Qualityassurance of transmissometer data is performed during Level-1 validation, an d 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 extinct

ion (b ) of the transmissometer optical path (r ) is calculated from the transmittance ext measurement ( T

) by:

Since the path length r

is measured to an extremely high precision, the precision in b can b e ext

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 ( E C) 14 Temperature uncertainty ( E C) 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 b > maximum threshold x x x x x x x x ext b uncertainty > threshold x x x x x x x x ext ) b > delta threshold x x x x x x x x ext Z Weather observation between 2 other weather observations. Threshold values may be different for each site. 8 = Missing: Data acquisition error 9 = Invalid: b below Rayleigh ext 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 ( I

cal )

U x ' * 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 extincti on calculations should also be determined. The calibration equation assumes clean glass surfaces o f constant transmittance. Any change in the window transmittance results in a bias to the calculated extinction. If the window trans mittance decreases the calculated extinction will increase. If the window tran smittance 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 Mea surement 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

U T ' ( 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

U cal ' 2 U 2 CP % 2 U 2 WP % U 2 WG % U 2 CG % 2 U 2 WA % 2 U 2 CA % U 2 WT % U 2 FT % U 2 CR 1 / 2

4-23 (4-12)

(4-13)

(4-14)

(4-15) Using propaga

tion of error analysis the relative uncertainty of the path transmittance can be calculated from the relative uncertainties of the measured variables as:

where: U = relative uncertainty of T T U = relative uncertainty of I Ir r U = relative uncertainty of I Ical cal U = relative uncertainty of F lamp lamp Unde rstanding the uncertainty of a transmittance measurement requires a thoroug h investigation of the precision of each of the following: ! Precision in calibration to determine I cal ! Precision in the measurement of I r ! Precision in the measurement of F lamp Relative Uncertainty of I - The pre cision in calibration value I can be determined by investigating cal cal the calibration equ ation. 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 al l cal windows in the path, and size of working aperture used. I is determined from: cal

Using propagat

ion of uncertainty analysis the relative uncertainty in I can be shown to be: cal

Pathdistances 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 b y differencing techniques, thusthey do not require absolute calibration. The standard deviation of the raw readings (CR) are calculated at each calibration. The typical working values, measuremen t 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 relativ e uncertainty for I : U = 0.005. cal Ical Relative Un certainty of I - Under ambient operating conditions the irradiance measured by th e r 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 p recision of each 10-minute irradiance measurement is calculated by the receive r comput er as the standard deviation of the ten one-minute average irradiance measurements. Th e measured standard deviation is a direct estimation of atmospher ic optical interference. Typical values of I and various opera

tional precision estimates that have been observed in the monitoring network r are listed below.

Ambient Extinction (km -1) I r

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, I = 210 cal As can be seen the relative uncertainty of the measured intens ity 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 IrLamp Brightening (% ) ' a o ( t a 1

4-25 (4-16) Relative Uncertainty of F - The major source of uncertainty in the transmissometer data lamp is lamp drift correction. The transmitter employs an optical feedback loop designed to maintai n cons tantirradiance within the 10 nm bandwidth of the receiver filter/detector module. However , comparisonof pre and post lamp calibrations show that the transmitter lamp output increase s (brightens) with increased hours of lamp use. Tests have shown that the brightening is definitely a fun ctionof the lamp rather than the feedback circuit or filter. It is important to note that a 1 % increasein 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% o f -1 Rayleigh!!); i.e., the instrument measurement indicates the air to be cleaner than it actually is. Lamp brightening percentages and lam p "on" hours for all systems and lamps post-calibrated at the Fort Collins, Colorado t ransmissometer calibration facility are entered into a lamp brightening database. T he 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 ho urs. The mean and standard deviation of operational hours and percent lamp brightening wer e calc ulatedfor each bin. Power law functions are fitted to these data to define a statistically base d mean la mp 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 th e correction is calculated from the upper and lower bounds for the number of hours on the lamp at the time of the reading. If, u pon 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 continu ally

updated as additional lamps are post-calibrated. Periodically, the lamp brightenin g statis tics are reanalyzed to provide a more accurate description of the lamp drift correction and the precision associated with this correction. Variat ions in lamp brightening characteristics for a given lamp design may occur due t o variatio ns 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) a = 0.2700 0 a = 0.4405 1 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 0.204-26

Meteorological data uncertainties and limits are obtained from the manufacturer's literature. The values used are listed below:

U = 1 E C temp U = 2% (Rotronics MP100F Sensor) RH Maximum temperature = 60 E C Minimum temperature = -50 E C Maximum relative humidity = 100% Minimum relative humidity = 0% Optica l interferences uncertainties must also be considered. The transmissometer directl y measures the irradiance of a light source after the light has traveled over a finite atmospheric path. The aver age extinction coefficient of the sight path is calculated from this measurement and i s attri butedto the average concentration of atmospheric gases and ambient aerosols along the sigh t 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 lig

ht intensity by insects, birds, animals, or vegetation along the sight path, or on the optical surfaces of the instrumentation or shelter windows. ! Fluctuations in lig

ht intensity both positive and negative due to optical turbulence, beam wander, atmospheric lensing, and miraging caused by variation s in the atmospheric optical index of refraction along the sight path. An algorithm has been developed to identify transmissometer extinction data that may b e 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 t o aerosol monitor s, the algorithm has been designed to be a conservative filter on the extinction data. Thatis, if an hourly extinction measurement indicates the slightest possibility of meteorological or optical interfer ence by failing any one of the above tests, it is flagged with identifier codes in th e Level-1 data file. The following describes each of the five tests:4-27

Relative Humidity

- When the relative humi dity measured at the transmissometer receiver is greater tha n 90%, the corresponding transmissometer measurement is flagged as having a possibl e interference. The 90% level has been chosen due to the following considerations: ! The relativ e humidity is only measured at the receiver location and not at any othe r position along the sight path. ! A 1.5 E C change in dew point temperature results in a 10% change in relative humidity. ! The atmosphere is continu ously 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 a bsolute humidity fluctuations along the path can lead to condensation of water vapor causin g meteorological interferences. Thus, in accordance with the conser vative philosophy expressed above, the 90% relative humidity limit was selected for this test. Maximum Extinction. For every transmissometer sight path, a maximum b can be calculated e xt that corresponds to a 5% transmittance for the path. All sight paths were selected, such that based on histor ical visibility data, this maximum b occurs less than 1% of the time. When the measured ext b is greater than this threshold va lue, 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. Unc ertainty 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 deviationof 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 b will increase dramatically. The presence ext of any m eteorological or optical interferences along the sight path will lead to large standar d deviations in lamp irradiance, thus large uncertainties in b . With the conservative assumption o f ext constant b during any ten m inute measurement period, any increase in the uncertainty of b above ext ext 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. Rat e of Change of Extinction (Delta Threshold). Transmissometer data collected befor e September1, 1990, did not include standard deviation of measured irradiance values. For dat a collected before this da

te, another test was developed to identify periods of interferences associated with rapidly fluctuating irradiance measurements. This test consists of comparing the hourly average extinctionto 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 ext4-28

ea chsight path by analyzing extinction data collected after September 1990, which hav e corresponding uncertainty thresholds to determine appropriate Delta thresholds for the sight path

. The Delta threshold is typically not as low as the uncertainty th reshold, 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 hourlyextinction data. It is used to identify data points that have passed the above thresholds, but are located b etween hourly b data that have failed the above thresholds. The conservativ e ext 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 transmissomete r measur ements by comparing measurements made with the audit reference transmissometer. Th e reference transmissometer s hould be calibrated at the test facility before and after each field audit to ensure that t

he 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 au dit transmissometer system should be operated with the replacement transmissometer compute r during the audit. Gain measurements should be made on all instruments during instrument servicing. Thes e gain measurements should then be incorporated into the calculation of calibration number s 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 al so includes a window transmittance test, which verifies the combined transmittance of the transmitter and receiver station windows. This test is typicall y incor porated into the end of the audit, which is performed on site, but can also be performe d separately if necessary. The window transmittance test should include three 10-minute readin g segments wit h the first operational lamp of the replacement transmissometer. The first and las t 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 res ults verify the operational integrity of the on-site and replacement instruments. Auditresults statistics should be used to define error limits for comparison of path transmittanc e measure ments obtained with an instrument being audited or path transmittance measurement s obtained with an audit instrument. Lamps used operationally with transmissometers being removed from the field (on-sit e instruments) typically have accumulated 400 to 600 hours of "on" time. This accumulated operatingSVR ' 3912 ( b ext & b ray % 10 Mm

& 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: ! On e set of audit result statistics should be generated for audit instrument and on-sit e in strument comparisons applying the standard lamp brightening correction factor. This da taset should be used only as an early indicator of the quality of the data collecte d during the operational period for the on-site transmissometer. ! Operationa l

instruments should be post-calibrated after removal from a site. On-sit e instrument audit data should be corrected usingpost-calibration lamp brightening factors. The second set of audit results statistics should be generated using these data. This data set shou ld be incorporated into ongoing analyses of lamp brightening effects on dat a quality. ! The th ird set of audit results statistics should be based on measurement comparison s betwee n the replacement transmissometer and the audit transmissometer. Becaus e 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 an d 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 Transmissom

eter 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, blac k fe ature 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 s cattering 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, b , and the standard Rayleigh ext scattering coefficient of 10 Mm is added back. The value 3912 is the constant derived fro m -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 wit h 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 atmosphe re (dv=0 for Rayleigh conditions at abouthaziness (dv ) ' 10 ln ( b

ext 10 Mm

& 1 ) ' 10 ln ( 391 km

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 chan ge in the deciview scale (i.e., a 10% to 20% fractional change in extinction coefficient) reg ardless of the baseline visibility level. Similarly, a change of any specific number of dv shoul d 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 v isibility monitoring data that are available in visual range or extinction coefficient are easil y converted to the new visibility index expressed in deciview. Use of t he dv scale is an appropriate way to compare and combine data from differen t visibility perception and valuation studies. When results from multiple studies are presented in terms of a co mmon perception index, the effects of survey approach and other factors influential to th e results can be evaluated. Transmissometer data provide a quantitative measure of real time visibility conditions. Data c a n be used to provide the basis for background conditions and trend analysis; however, data must be c ombined with associated meteorological and aerosol concentrations to understand the sourc e and/or composition of the impairment observed. Caution should be taken, how ever, when comparing reconstructed extinction with measured ext inction. Reconstructed extinction is typically 70% - 80% of the measured extinction. Th e following differences/similarities should be considered: ! Da tacollection. Reconstructed extinction measurements represent 24-hour sample s coll ectedtwice per week. Transmissometer extinction estimates represent continuou s measurements summarized as hourly means, 24 hours per day, seven days per week. ! Point versus path measurements. Reconstructed extinction represents an indirect measure of extinct ion 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. ! Relativehumidity (RH) cutoff. Daily average reconstructed measurements are flagged as invalid w hen the daily average RH is greater than 98%. Hourly averag e 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 Operati ng Procedures and Technical Instructions for Transmissometer Systems , includes th e 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 Ro utine Site Operator Maintenance Procedures for LPV-2 Transmissomete r

Systems (IMPROVE Protocol) TI 4110-3300 Troubl eshooting 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 Pro cedures for LPV-2 Transmissometer Systems

(IMPROVE Protocol) SOP 4115 Annual Site Vi sits for Optical Monitoring Instrumentation (IMPROVE Protocol) TI 4115-3000 Annual Site Visit Procedures for Optec LPV-2 Transmissometer System s

(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 Dat a

(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 Procedures4-33

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 integratin g nephelometer would collect all the light scattered by aerosols and gases from 0 E to 180 E in an enclosed sample volume through a defined band of visible wavelengths to yi eld a direct measurement of b . Since a nephelometer makes a point measurement, direc t scat com parisons to collocated aerosol measurements are practical. In addition, the system can b e ab solutely calibrated using clean (Rayleigh) air and various dense gases with a known multiple o f Rayleigh scattering. The Opt ec NGN-2 ambient nephelometer has been developed to minimize modification o f ambienta erosols and address problems associated with Belfort nephelometers: sizing by the inlet , lar ge truncation error, poorly-defined optical response, and outdated, unstable electronics. Th e systemin corporates sensors, signal detection techniques, and electronics developed for the Opte c tran smissometer 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 stabl e 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-mes h screen cov ers the inlet opening to prevent insects, leaves, or other large masses from entering th e scatteringchamber. 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, lam p cooling heat sink, clean air pump, and span gas solenoid activated inlet val ve. The exhaust air from the optical chamber passes across the finned heat sink as it exits , removing heat from the system. The electronics chamber contain s the projector lamp, chopper motor, scattered l ight detector/electrometer, computer, interface board, and door motor. A thick meta l shieldaround t he 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 volum e allows for integration of scattered light from 5 E to 175 E . A low-voltage (13.8 VDC), quartz halogen projector bulb with dichroic reflector illuminates an opal glass diffuser. In the light path between the d i ffuser and bulb, a heat-absorbing filter blocks all radiation longer than 700 nm in wavelength and a mechan ical chopper modulates the beam at 10 Hz. A telescope with a precisely defined field o f 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 termi nates in a light trap. A small lens behind the field stop images the entran ce pupil (objective lens) of the telescope onto the active area of a photodiode detector. This de tectormeasures light scattered by the gases and aerosols in the scattering volume plus ligh t reflected from the surfaces and stop edges in the optical chamber. This wall component of th e 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

Wit hin the optical chamber, directly in front of the diffuser, is an identical photodiod e detector. This detector directly measures the intensity of the lamp. Using the output of this detector to normalize the scattered light signal com pensates 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 : sc attered light measurement, clean-air zero calibration, span gas calibration, moisture detection t o close the optical chamber door during rain or snow conditions, optical chamber temperatur e measurement, initial data reduction, various error detection schemes, and diagnostic tests. Integ rating nephelometers estimate the atmospheric scattering coefficient (b ) by directl y scat measuring the light scattered by aerosols and gases in the sampled air volume. Scattered radiation from an illumination source is inte grated 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 desi gnthat 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 essentiall y unchanged, thus the aerosol is negligibly modif ied when brought into the optical measuring chamber. Extinctio n

due to scatter can accurately be measured from Rayleigh to 100% saturated fo g conditions. The Nat ional Park Service instituted the use of ambient nephelometers in 1993. This ne w technology enhanced other methods of visibility monitoring and increased the accuracy with which amb ient optical data are measured. The nephelometer has proven to be an effective method o f collecting scattering data over a wide range of environmental conditions. Detailed information regarding nephelometer instrumentation or operation can be found i n Model NGN-2 Open-air Integrating Nephe lometer, Technical Manual for Theory of Operation and Ope rating Procedures (Optec, 1993) and Standard Operating Procedures and Technica l 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 fin e particulate sampler, camera system, meteorological instrumenta tion, or a criteria pollutant monitoring station. Because the nephe lometer 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 monitored4-37

! Be removed from local pollution sources and away from obstr uctions 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 asso ciated 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 Nephe lometer

system components are typically mounted on a 4 meter (14 foot ) mete orological tower. The tower must be installed with one face oriented to true north. Th e nephelometer will be mounted on this northward face. The tower may b e 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 cont rol 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 ope rator'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 si te documentation includes completion of a site visit trip report, photographi c docu mentation (including photographs of vistas in all directions from the tower, telephone and AC wiring, local sources or ob structions to air flow to the station, landmarks used to locate the site, the statio n itself, and other detailed close-ups), and documentation of any miscellaneous informatio n necessary t o make a complete site description, including site map and site specifications (latitude ,4-38

longitu de, instrument elevation, etc.)., dominating pollutant influences, (listing the source an d 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 s ervicing, 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 an d 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 maj ority 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 vis its are performed to exchange the existing nephelometer for a newly serviced instrum ent, 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 performe d 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 complet e calibrati on. Simple calibrations are initiated weekly by site operators and occasionally by fiel d 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 avera ge of ten (10) 1-minute readings of particle-free air, using the nephelometer' s internal air filtering system. Comple te calibrations are performed by the field specialist or instrument technician durin g 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 optim um 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 ! Cleaning4-40

! 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 ambien t scattering, along with the associated status code at five-minute intervals. The on-site datalogge r co llects 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 platform s (DCPs).

4.2.6 Data Reduction and Validation 4.2.6.1 Data Reduction Nephelom eterdata should be compiled into site-specific Level-A files. Data processin g 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 su mmaries. Data should be reviewed daily by data analysts to determine the operational ch aracteristics 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-Aincludes visual review and examination of the raw data and extracting codes, Level- 0 includes searching for que stionable 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. Standar d 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 oper ator-initiatedclean air zero and span calibrations are extracted from the raw data file an d ap pendedto nephelometer-specific quality assurance calibration files. The three validity code s 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-sp ecific 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 performedon a nephelometer during a specific time period, including the initial zero and span pe rformedduring installation. Uncertainty estimates generated with the QA calibration plots ar e 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 problemsInitial 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 b data affected by meteorological interference scat ! Estimation of precision Hourly averages are computed from Level-0 data. The zero calibrat ion information in the QA calibration files is used to calculate a calibration line for each d ata 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 deter mined by interpolating (in time) between the valid clean air calibrations prior to, and following the data point. ! The initia l spanis determined from the initial calibration of the instrument upo n installation. (4-19)

! The Rayleigh

coefficient is the s ite-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 i s -1 -1 scat calculated from the calibration line as follows:4-43

The following additional va lidation 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 f

iltered to identify periods likely affected by meteorological interference. Th e following filter criteria are used to identify these periods: ! Rate of change: If the rate of change between hourly b data exceeds 50 Mm , the b scat scat -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 b value exceeds 95%, the b value scat scat 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 an d validatio n

errors, instrument operation problems, and calibration inconsistencies. Any identifie d pr oblems should be immediately investigated and resolved by following the procedures detailed i n standard operating procedures and technical instructions.

4.2.7 Data Reporting and Archive 4.2.7.1 Data Reporting Data rep orts should be prepared in a format that generally conforms to the Guidelines fo r Preparing Reports for the NPS Air Quality Division(AH Technical S ervices, 1987). A separate data rep ort should be prepared for each instrument type; nephelometer data reports should contain only nephe lometer

data. Reporting consists of various text discussions and graphics presentation s 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 reporte d 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 introdu ction should contain a conceptual overview of the purpose of the monitorin g pro gram and a description of the monitoring networks. The data collection and reduction sectio n should include data collection methods, data file review, data validation, application of validity codes, process ingthrough various validation levels and discussion of file formats, and identification o f meteorol ogicaland optical interferences that affect the calculation of b from nephelomete r scat measurements. Th e site configuration section should contain a brief discussion of instrumentation at eac h nephel ometer

site, basic principles of operation, measurement principles, and data collectio n 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. ! ASite S pecifications Summary Table, listing for each monitoring site the site name , abbr eviation, latitude, longitude, and elevation of the nephelometer, the number o f 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 p resented as Figure 4-7 and an example Annual Nephelometer Data Summary is presented a s Figure 4-8. The following is a detailed explanation of the contents of the data summaries in eac h report. Seasonal Nephelometer Data Summaries include the following five data presentations: ! 4-H ourAverage Variation in Visual Air Quality (Filtered Data) - Plot of four-hou r av eragedb values (without interference-influenced observations) for each day of th e

scat reporting season. Gaps in the plot indicate that data were missing, interference

influenced, 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

! Rel ativeHumidity - Timeline of hourly average relative humidity measurements. Thi s 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 b values, both unfiltered and filtere d for meteorological interference. The 10%

scat to 90% values are plotted in 10% increments and are summarized in the table to the right of the plot. ! Vis ibility

Metric (Filtered Data) - This table presents mean values of filtered b dat a scat affectedby meteorological interference. The best, worst, and average conditions using the ari thmetic means of the 20th percentile least impaired visibility, the 20th percentil e most impaired visibility, and for all data for the season are presented. ! Data Recovery Statistics Total Poss ible Hourly Averages in the Time Period - The total possible category i s calculatedby subtracting the number of hourly averages included in periods when th e instrument was removed due to conditi ons unrelated to system performance (installation, construction, site relocation, etc.) from the theoretical maximum number of hourl y average periods possible during a season. ValidHourly Averages (Filtered and Unfiltered) - the number of valid hourly average s collected durin g 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 dataindicating meteorological interference) collected during a season. The percentage represents the number of valid hourly averages compared to the total possible hourl y averages. FilteredData Percent of Filtered and Unfiltered Hourly Averages - This percentag e collectionefficiency represents the number of filtered hourly averages compared to the number of all valid hourly averages. Annual Nephelometer Data Summaries include three data presentations: ! Month ly

Median Visual Air Quality - Plot of median monthly b for all data and fo r scat filtered data only. As the visual air quality improves, b values decrease. A Rayleigh scat 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. Summar ies should be prepared for each site that operated during the reporting period. A brief discussion of events an d circums tances that influence data recovery should follow the data summaries. Operational statu s thro ughoutthe reporting period should be presented for each site in an operation summary table , listing for each site, site name and abbrevi ation, the number of seasonal hourly averages possible, the number and percentage of valid hourly averages for all data and for filtered data only, and th e cumulative frequency distribution (10%, 50%, and 90% b val ues) for all data and filtered data only. scat Finally, a summary section should be included in reports, and provide a synopsis of th e nephelometer

network, including changes in operation techniques, and a general conclusion of the mon itoring period in review. A reference section should include technical references (document s cited in the report), and re lated 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 proces sed digital data for a given season, and constants, calibration, and data processing file s should be performed on a sea sonal 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-RO M. 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 speci fications, monitoring timelines, data coordinator/site operator corresponden ce, site operator log sheets, trip reports, weekly, seasonal, and annual summary plots, instrument calibration and maintenance logs, and fil e 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 th e quarterly an d annual reports. The standard file format currently used for IMPROVE protoco l nephelometer data is presented in Figure 4-9.

4.2.8 Quality Assurance Quality assurance of nephelom eter 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 def

ined by the factory-specified precision for the sensors. The estimated precision o f 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 th e Leve l-1 data files. The relative error (uncertainty) in scattering due to drift of the slope of th e calibra tion 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 123456789012345 678901234567890123456789012345678901234567890123456789012345678901234567890123456789012345678901234567890123456789012345678901234567890123456789012345678901234567890123456789012345678901
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 < = b less than Rayleigh scattering scat 22-24 Nephelometer Serial Number XZ = Data point immediately preceded and followed by interference 26-32 b (Mm ) X? = Interference of type ? scat -1 34-40 b Estimated Precision (%/100) scat 42-43 b Validity/Interference Code Type (?) of Interference Letter Code scat 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 b rate of change > threshold x x x x x x x x scat 76-81 b Rate of Change Interference Threshold scat 83-88 Maximum b Interference Threshold scat 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 b 104 Number of missing data points scat 118-124 Slope of Calibration Line Used to Calculate b 105 Number of power failure codes scat 126-131 Average Ambient Temperature ( E C) 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 ( E C) 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 ) ' b scat , o % m ( V ( t )

& V o ( t ) )

m ( t ) ' ( b scat , s & b scat , o ) / ( V s ( t )

& V o ( t ) )

b ' scat ( t ) ' b scat , o % m ( t ) ( V ( t )

& V o ( t ) )

relative error ' (

b scat ( t )

& b ' scat ( t ) ) / b scat ( 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 b = Scattering coefficient for SUVA 134a scat,s V = Average normalized clean air reading o V = Average normalized SUVA 134a reading f 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 consta nt 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 ) ) / b scat ( t ) |

| relative error | < | (m

& m ( t ) ) / m |

| m

& m ( t ) | < 2 s

| ( b scat ( t )

& b ' scat ( t ) ) / b scat ( t ) | < | 2

s / 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 s with k degrees of freedom, based on k+1 sample values of m(t), m and using the two-t ailed 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 ne phelometer 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, p erforming 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. Th e 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 thei r operational configuration and that the nephelometer is in ambient mode.4-52

4.2.9 Data Analysis and Interpretation Nephel ometer

data are a measure of the scattering component of atmospheric extinction

. Da taare typically presented in scattering units, expressed in kilometers (km ). These units ar e -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 asso ciated meteorological and aerosol concentrations to understand the source and/o r com position 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 Th e Air Resource Specialists, Inc. document entitled Standard Operating Procedures an d Technical Instructions for Nephelometer Systems , includes the following nephelometer-relate d 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 Mo nitoring Instrumentation (IMPROVE Protocol)4-53

TI 4115-3005 Annu alSite Visit Procedures for Optec NGN-2 Nephelometer System s

(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-C ollected Data (IMPROVE

Protocol) TI 4300-4006 Nephelo meter Data Collection Via Campbell Scientific Data Storage Modul e (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 e xample of an existing visibility-related scene monitoring program, this sectio n des cribes IMPROVE scene monitoring and data management techniques. References made t o manufacturers or trade name s are not intended to constitute EPA endorsement or recommendations for use. N ew or improved instruments, instrument upgrades, and methods of monitoring ar e continually being developed. Scene monitoring pro vides a qualitative representation of the visual air quality in the area of inte rest. The photographic record documents the appearance of a scene. Scene characteristic s 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 impactCl ass I or protected areas, as well as documenting conditions for interpreting aerosol an d optical data. IMPR OVE protocols recommend that color photographs (35 mm slides) be taken severa l 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-b ased or elevated layered hazes. Time-lapse movies (generally time-lapse video or supe r 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 sit e docume ntation, system performance and maintenance, data collection, reduction, validation , reporting, a nd archive, quality assurance, and data analysis and interpretation required for 35 mm slide an d 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 syst ems 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, an d seasonal conditions. Scene characteristics include observer visual range, scene contrast, color, texture, and clarity. ! Recordthe 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

! Determinethe 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. ! Prov idequality media for visually presenting program goals, objectives, and results t o decision-makers and the public. ! Support computer image modeling of potential impairment. ! Support color and human perception research. Photograp hicslides, however, do not provide quantitative information about the cause o f visibility impairment. Aerosol and optical properties of the atmosphere must be independentl y monitored where cause and effect relationships are required. Automatic camera systems should meet the following requirements: ! Havea 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 no t continuously operating. ! Have an appropriate size lens to capture the full extent of a sc enic 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. ! Havea 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 0 E F to 120 E F. (To achieve the specification of 0 E F, a heated and insulated shelter requiring 110V line power i s 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. Figure5-1 is a photograph of the automatic camera station in a remote mountain location

. Figure 5-2 shows th e components of a station, including a weatherproof shelter and mounting post, ca meras, automatic timers, and batteries. The station can be outfitted with a variety of camer a configurations. Detailed information regarding camera instrumentation or operation can b e found in Standard Operatin g Procedures and Technical Instructions for Automatic Camera Systems (Air Resourc e 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 t he character of the area being monitored. When selecting a site, servicing, installatio n logistics, aesthetics, and security should also be consider ed. 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 co nsistent, quality data and minimize data loss, selected camera sites should have most or all of the following characteristics: ! Be located to photograph a hig hly-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 mountingpost should be appropriately aligned on t

he 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 installationinvolves three processes: mounting the sunshield, the enclosure, and the camer a equipment. Follo wing the completion of the camera system installation and configuration, operato r training shoul d be performed. Site operators should be trained on camera system requirements and5-5

routin e maintenance procedures. A Site Operator's Manual for Automatic Visibility Monitorin g Camera Systems should be provided. This manual contains standard operating procedures an d te chnicalinstructions applicable to the specific camera monitoring equipment located at the site

. Ad ditionalmanufacturer's instruction booklets and pertinent maintenance documentation form s should also be provided. Site docu mentation for the automatic camera system visibility monitoring station include s completionof the Visibility Monitoring Photographic Site and Target Specifications Form, whic h 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 conta cts and mailing/shipping address; vista name, distance, elevation, bearing, and elevatio n 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 th e 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 mon itoring schedule includes taking three photographs a day at 0900, 1200, and 1500

. Assuming th is schedule, site operators service the camera approximately every 10 days to chang e film, check the perf

ormance of the camera(s), clean the system components, and perform scheduled prevent ive

maintenance. Identifying and troubleshooting system malfunctions are carried out a s required. Regular servicing and the identification and documentation of film rolls are essential. During each r outine site visit, the operator should thoroughly document all pertinent data collectio n 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. ! V erifying 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 camera s and support systems is performed by mailing replacement parts and/or systems to the site operators and repairing those components returned. Operational camera systems ar e biannually cycled out of a monitoring network. Shelters remain in place and the cameras an d 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 checks5-7

! 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 require d interval, and the mailing of exposed film rolls and accompanying documentation. Kodachrome ASA-64 color slide film (36-exposure ro lls) should be used. The film possesses fine grain and excellent color reproduction qualities. Enough film (from a single emulsion number) should be pu rchased from a Kodalux direct distributor to cover several months of a monitorin g program. Film should be refrigerated or frozen until used. When servicing a site, the operator sho uld 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 sh ould 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/assess ment sheet via first class mail for processing. All film should be sent by courier to a Kodalux processing laboratory. Roll and fil m proces singmailer numbers should be documented so all shipments can be tracked and traced i f 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 fo r documentation or as a s upplemental visibility document should be kept. Any blank slides preceding or following the normal date/time sequence should be discarded.5-8

Extr aneous 35 mm slides should be removed and documentation and target photograph s 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 place d 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 prope r 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 slid e 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 condition s present on each slide, including sky conditions, observed haze s, plumes, weather conditions, unusable or missing observations, anomalies, or client-specified areas of interest. Qualitativeslide 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 b e marked directly on the slides (slide frames) and later entered into site-specific digital fil es. An example code key sheet is presented as Table 5-1. Codes may be tailored to the contracting agenc y's needs. For example, codes may be developed that define amount of ur

ban 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 b e 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 an d specific software are used to create digital files. Files are na med by site and season and contain site abbreviation, slide number, date, time, and slid e 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 rep orts should be prepared in a format that generally conforms to the Guidelines fo r Preparing Reports for the NPS Air Quality Division(AH Technical S ervices, 1987). A separate data reportshould be prepared for each instrument type; photographic data reports should contain only photograph icdata. Reporting consists of various text discussions and graphics presentation s 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 reporte d 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 introdu ction should contain a conceptual overview of the purpose of the monitorin g 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. Alsoincluded 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 in stalled, and the historical periods of operation for each instrum ent. The section briefly describes the slide review and coding process, as well as th e compilation of the summary ta bles, 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 agenc y requirements. Each type of data summary should be accompanied by an explanation. Each report conta ins a Site and Target Specifications Summary Table listing complete target and sit e 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, distan ce, azimuth, and elevation angle of the site path; number of observations taken per day; an d operating period during the reported period). A Qualitative Slide Analysis Summary Table provides a site-by-site accounting of observed haze and target-con cealed conditions for each site that operated during the reporting period. The section also includes a brief discussion of s lide and digital file archive, a discussion of the events and circumstances that influenced data recovery, operational summar ies 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 proble m description, and resolutions and/or recommendations relating to the noted operational problems. The refe rence 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: ! Sl ideduplicates 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 stor ed in non-gassing, polyethylene protector sheets and filed by site, season, and date (roll). All files should be kept alphabetically in standard file cabinets. Eve n under the most ideal storage conditions, film emulsions will slowly degrade over time. Supporting hard copy documentation, including statu s/assessment sheets, slide coding sheets, film tracking logs, and correspondence should be filed in standa rd file cabinets, in chronological order by site. Digital d ata produced from 35 mm photographic slides (containing qualitative conditio n 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 automati c camera equipment is based primarily on visual review of developed visibility monitoring film. Alignment, exposure, and data collection efficiency can all be asses sed from developed film. Any noted problems should initiate corrective action. Ongoin g 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 visu ally seen in the 35 mm sl ides can be compiled and interpreted. A more thorough analysis would be to use the slides i n 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 o r visibility analysis.

5.1.10 Scene Monitoring Standard Operating Procedures and Technical Instructions Th e Air Resource Specialists, Inc. document entitled Standard Operating Procedures an d Technical Instructions for 35 mm Scene Monitoring Systems , includes the f ollowing scene monitoring Standard Operating Procedures and Technical Instructions: SOP 4005 Procurement and Acceptance Testing Procedures for Scene Monitorin g Equipment TI 4005-1000 Procurement an d 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 Routin e Site Operator Maintenance Procedures for 35 mm Automatic Camer a

System - Canon EOS 630 TI 4120-3110 Routin e Site Operator Maintenance Procedures for 35 mm Automatic Camer a

System - Contax 167MT TI 4120-3120 Routin e Site Operator Maintenance Procedures for 35 mm Automatic Camer a

System - Contax 137 MA TI 4120-3130 Routin e Site Operator Maintenance Procedures for 35 mm Automatic Camer a

System - Olympus OM2N TI 4120-3140 Routin e Site Operator Maintenance Procedures for 35 mm Automatic Camer a

System - Pentax PZ-205-13

TI 4120-3300 Troubleshooting an d Emergency Maintenance Procedures for 35 mm Automatic

Camera System - Canon EOS 630 TI 4120-3310 Troubleshooting an d Emergency Maintenance Procedures for 35 mm Automatic

Camera System - Contax 167MT TI 4120-3320 Troubleshooting an d Emergency Maintenance Procedures for 35 mm Automatic

Camera System - Contax 137 MA TI 4120-3330 Troubleshooting an d Emergency Maintenance Procedures for 35 mm Automatic

Camera System - Olympus OM2N TI 4120-3340 Troubleshooting an d Emergency Maintenance Procedures for 35 mm Automatic

Camera System - Pentax PZ-20 TI 4120-3500 Biannua l Laboratory Maintenance Procedures for 35 mm Automatic Camer a 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 hav e always been a valuable and convenient tool to document, view, and int erpretactual dynamic events in reduced time. Time-lapse images have been used to support scientific studies, document project activities, support legal enforcement, and present importan t findings to decision-makers and the public. Today, h igh 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 easil y5-14

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 enhance d 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. Reve rse and stop frame functions further aid the interpretive process. Time-l apse monitoring can be accomplished by 8 mm film or by videotape. The majo r 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 (industr ial

plumes or emissions from hazardous waste remediation projects) can b e documented. ! Weath er

Observations - The day's weather can be documented to support academi c studies as well as daily television news summaries. ! Construction Projects - Moni toring 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 traffi c count-related applications may be monitored. ! IndustrialProcesses - Applied engineering practices or equipment performance may be evaluated, and production may be tracked. ! Surveillance - T he use of a recreational area may be tracked, or legal investigations may be supported. Time- lapseimages do not provide quantitative information about the cause of visibility impairme nt. Aerosol and optical properties of the atmosphere must be independently monitore d where cause and effect relationships are required. Time-lapse video systems have two primary components, a camera and a recorder (se e 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 programm edfor daily on and off recording times. A range of time-lapse intervals can easily b e selectedon the recorder. More advanced systems can employ options such as programmable , motorized pan/tilt camera housings and zoom lenses that respond to a ser ies 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 fo r remote locations, but for many installations it is often convenient to use an existin g building. T he camera and recorder units are connected with signal and power cables. System s 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 cam era can be conveniently housed in a weatherproof shelter identical to, or i n conjunction with 35 mm cameras (see Figure 5-2). Deta iled information regarding video camera instrumentation or operation can be found i n Standard Operating Procedures and Technical Instruction s 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 l ocated so that the camera views a recognizable, important vi sta 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 c amera is located with other monitoring equipment such as a transmissometer, a nephelometer, an aerosol sam

pler or other monitoring systems that support comprehensive air quality evaluations. To assure co nsistent, quality data and minimize data loss, selected camera sites should have most or all of the following characteristics: ! Be located to photograph a hig hly-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 cooperation5-17

5.2.3 Installation and Site Documentation Instal lationis 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. Foll owing the completion of the time-lapse system installation and configuration, operato r training shoul d be performed. Site operators should be trained on camera system requirements and routine maintenance procedures. Additional manufacturer's instruction booklets and pertinen t maintenance documentation forms should also be provided. Sit e documentation for a time-lapse system monitoring station includes completion of sit e speci fications (station name, number of observations per day, elevation, latitude, longitude, map referenc e, site abbreviation, installation date and name of the installer, site contacts an d 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 mon itoring 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 b atteries 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 videotap e cassettes or film rolls, cassette or film mailers, status/assessment sheets, and syste m operating instructions. The time-lapse systems may be programmed to record a full day of tape (client-specifie d on/off times). The videotape s ystem 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

Allvideo tapes and film should be mailed by the site operator(s) along with sit e 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 revi ewed 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 , emissio ns, visibility, and anomaly events. Tapes should be reviewed in S-VHS format on a hig h resolution monitor. Qualitative 2-digit (or other) tape/film condition codes are assigned to eac h morning a nd afternoon period of tape. The codes identify specific visibility conditions in th e 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 t hese categories are presented in Table 5- 2. Meteorological conditions are based on visual observations only. The result of the qualitative coding process i s a digital file for each site that contains a 2-digit code for each half-day of tape or film. Final data summary table s and graphic plots can then be made. It is important to note that videotapes or film can onlybe used to document the presence of observed condit ions. The cause of the condition generally must be obtained from supplemental data or from interpreta tion 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 ar e ini tiallyreviewed for proper exposure, alignment, and correct operatin g period.5-19

! Level II: Daily me

teorological conditions and patterns are documented, as well as the presen ce of any anomalies. Tapes/film are reviewed on a high-resolutio n co lor monitor or projector. A tape/film condition code is assigned to eac h 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 fo r Preparing Reports for the NPS Air Quality Division(AH Technical S ervices, 1987). A separate data reportshould be prepared for each instrument type; photographic data reports should contain only photograph icdata. Reporting consists of various text discussions and graphics presentation s 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 reporte d 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 introdu ction should contain a conceptual overview of the purpose of the monitorin g program and specific objectives and tasks of the program. The data collection and reduction section includes discussions of site configuration, camera system components, exposure sched ule, and basic system operation. Also included should be a map of the United States depicting the location of each monitorin g site, and a monitoring history summary table, describing each monitoring site, the type of instrumen tation 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. Tim e-lapsedata may be presented in various forms depending on contracting agenc y 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 , longi tude, and elevation of the camera monitoring site; number of exposures taken per day; an d operating period during the reported period). A Qualitative Slide Analysis Summary Table provides a site-by-site accounting of observed haze and target-con cealed conditions for each site that operated during the reporting period. Separate discussions detailing each observed anomaly may also b e prepared.5-21

The section also includes a brief discussion of videotape/film and digital file archive, a discussion of the events a

nd circumstances that influenced data recovery, operational summaries for each s ite including: site name and abbreviation, data collection period, number of total possibl e observations, collection efficiency (numb er and percent), a description of the cause or causes of data loss or problem description, and resolutions and/or recommendations rela ting to the noted operational problems. The refe rence 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 copi es of the videotapes or film.

5.2.7.2 Data Archive Duplicates of the vide otapes or film rolls should be stored in standard storage cabinets, filed by sit e, season, and date. Supporting hard copy documentation, including operational notes an d correspondence, should be appropriately filed in chronological order by site.

5.2.8 Quality Assurance Internal quality assurance of time-lapse came ra 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 fi lm. 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 th e vid eotapes/film

can be compiled and interpreted. A more thorough analysis would be to use th e 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 Th e Air Resource Specialists, Inc. document entitled Standard Operating Procedures an d 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 Monitorin g Equipment5-22

TI 4005-1001 Pr ocurement and Acceptance Testing Procedures for 8 mm Automatic Camer a 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 Rout ine Site Operator Maintenance Procedures for 8 mm Automatic Camer a System - Minolta XL 401/601 TI 4120-3210 Rout ine Site Operator Maintenance Procedures for 8 mm Automatic Camer a 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 Bian

nual 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 Archives6.0 REFERENCES

6.1 SECTION 2.0 REFERENCES
Aerosol and Visibility Subcommittee Grand Canyon Visibility Transport Commission, GrandCanyon VisibilityTransport 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 MOHAVESummer 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.

-----, ProjectMOHAVE 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 withAmbient 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., Visibilityfrom 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.), Spatialand 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.), Spatialand Temporal Patterns and

the Chemical Composition of the Haze in the United States: An Analysis of Data from the IMPROVENetwork, 1988 - 1991 - Appendices Vol. II (ISSN No. 0737-5352-26), February 1993. IMPROVE, Visibility Protection , August 1994.
Lati mer, 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, - Examiningthe 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, CleanAir Act Handbook - A Practical Guide to Compliance , ISBN 0-87632-814-1, 1991. National Park Service, National Park Service Visibility Reference Document , April 1983.

-----, IMPROVEProgram Description, Appendix A taken from Rocky Mountain National Park Visibility and Air Quality Data Summary , Date Unknown.
NationalAcid 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.), NAPAPReport 24, Visibility: Existing and Historical Conditions - Causes and Effects , October 1990.
NationalResearch Council: Committee on Haze in National Parks and Wilderness Areas; Board on EnvironmentalStudies 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., FederalRegional Haze Protection for Class I Areas: A Proposed Strategy (91-50.3 AWMA), June 1991. -----, EPA-EMSL, Visibility Monitoring Strategy Guidance , Circa 1991.

-----, VisibilityResearch 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., Guidelineon 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., andMalm, 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., PerformanceCriteria 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.

-----, QualityAssurance Handbook for Air Pollution Measurement Systems: Volume I, A Field Guide to Environmental Quality Assurance , EPA-600R-94/038a, April 1994.

-----, QualityAssurance 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., CleanAir 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., andMatsumura, 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., Spatialand 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 TeflonFilters 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.
CrockerNuclear Laboratory, IMPROVEParticulate Monitoring Network Standard Operating Procedures , available as a pdf file on http://www.nature.nps.gov/ard/vis/sop/index.html.
CrockerNuclear 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.
CrockerNuclear 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.ENSRConsulting and Engineering, QualityAssurance Audits of the IMPROVE Aerosol Network ,

January 1995. Malm, W.C., J.V. Molenar, R.A. Eldred, and J.F. Sisler, - Examiningthe relationship among atmospheric aerosols and light scattering and extinctionin 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., Examiningthe 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, Spatialand Seasonal Trends in ParticleConcentration 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.
NationalPark Service, AnnualReport Aerosol Collection and Compositional Analysis for IMPROVE July 1993 - June 1994 , Date Unknown. Noll, K.E., Collectionand 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, Spatialand 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, Sp atial 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 andM.L. Pitchford, Spatial and Seasonal Patterns and Long Term Variability of the Compositionof 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
AHTechnical 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., StandardOperating Procedures and Technical Instructions for Transmissometer Systems , 1993-1996.
Air Resource Specialists, Inc., StandardOperating Procedures and Technical Instructions for Nephelometer Systems , 1993-1996. CampbellScientific, 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

AHTechnical Services, , Guidelines for Preparing Reports for the NPS Air Quality Division. Product NPS/AQD-87/001. Boulder, CO. 1987.
Air Resource Specialists, Inc., StandardOperating Procedures and Technical Instructions for 35 mm Scene Monitoring Systems , 1993-1996.
Air Resource Specialists, Inc., StandardOperating 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., HumanPerception 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, WesternRegional 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 i n diameter, primarily generated by abrasion of solids. Absorption Capture of incident light by particles or gases in the atmosphere. Absorption Propo rtionof incident light absorbed per unit distance. Typical units ar e coefficient inverse megameters (Mm ). -1 Accumulation mode A size range of particles, from about 0.1 to 3 micrometers, formed largely by

accumula tionof 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 depo sition of acid chemicals (incorporated into rain, snow, fog, o r precipitation) mist) from the atmosphere to water or land surfaces. The pH of rain i s

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 administere d Information by the EPA Office of Air Quality Planning and Standards. Retrieval System (AIRS) Aerosol As uspension of microscopic solid or liquid particles in air. Atmospheri c

aero sols govern variations in light extinction and, therefore, visibility reduction. Aerosol extinction See reconstructed light extinction. Aethalometer Anaerosol monitoring instrument that continuously measures particle ligh t

absorption (aerosol black carbon) on a quartz fiber filter. Agglomeration The proces s of collisions of particles that stick together to become large r

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 Degra dationof air quality resulting from unwanted chemicals or othe r

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, so il, water, and virtually all resources that are dependent upon an d (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 Re sources 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 t o

light extinction or aerosol mass. Artifact Any component of a si gnal or measurement that is extraneous to the variable

represented by the signal or measurement. AT Ambient Temperature Atomic absorption Amet hod of chemical analysis based on the absorption of light of specifi c spectroscopy wa velengths of light by disassociated atoms in a flame or high temperatur e

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 Anin vestigation of the ability of a system of procedures and activities t o

produce data of a specified quality. b Absorptioncoefficient. A measure of light absorption in the atmosphere by abs particles and gases. Standard reporting units are inverse megameters (Mm ). -17-3

b Extinction coefficient. Measured directly by a transmissometer. Can b e ext reconstr ucted from nephelometer and aerosol data. It is equal to the sum of b and b . Represents the proportion of r adiation reduced by scattering and scat abs absorption per unit distance. Standard reportingunits are inverse megameters (Mm ). -1 b Scat tering coefficient. Measured directly by a nephelometer, the scatterin g scat coefficient includes scattering due to particles and atmospheric gase s

(Rayleigh scattering). Standard reporting units are inverse megameters (Mm
- ). 1 BAPMON Background Air Pollution Monitoring Network BART Best Available Retrofit Technology Best Available Aso urce emission limitation, based on the maximum degree of reductio n 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 d istinct ranges of values. The siz e distributions of aerosols often show two peaks corresponding t o about 1 and 10 micrometers in diameter. Biological effects Ecological stu dies 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 bet ween 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 submitt ing 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 Board7-4

Cascade impactor An instrument that samples particlesby impacting on solid surfaces via jets of

air. After passing the first surface, the air is accelerated toward the nex t surface by a higher speed jet, in order to capture smaller particles than could be captured by the previous one. Charge Ap rocess of removing static electric charges. This is done to particle

neutralization sampling filters in order to prevent electrostatic forces from distorting th e

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 Nationalparks and wilderness areas managed by the National Park Service,

U.S. Fish and Wild

life 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 , ecosys tem

integrity, and visibility, that need protection from air pollution

. National Parks larger than 6,000 acres, National M emorial 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 fo r some what

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 Lo w-pollutionfuels that can replace ordinary gasoline, including gasohol ,

natural gas, and propane. CMB Chemical Mass Balance Coarse mode Asize range of particles between 2.5 microns and 10 microns. Coars e

particles are mostly co mposed 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 o f analysis the analyte with reagents.7-5

Condensation Aninstrument that counts nucleation mode particles by causing the m counternuclei to grow i n a humid atmosphere, and observing light reflections from th e

individual enlarged particles. Continuous Anair analyzer that measures air quality components continuously. (Se e 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 contra st to inherent contrast. The ability of an atmosphere transmittance to transmit an image without loss of contra st. 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 backg roundthe value varies from 0 to infinity. When the contras t transmittance is equal to 0, the object cannot be seen. Current conditions Contemporary, or modern, atmospheric conditions affe cted by human activity. Datalogger An electronic device for measuring a nalog or digital signals and recording the resu lts on a storage media. Many of them can record inputs on a number of separate locations, reporting them as separate "channels." Deciview (dv) Ah aziness index designed to be linear with respect to human perception o f

visibility

. A 1-2 dv change in haziness corresponds to a small, visibl y pe rceptiblechange in scene appearance. Higher deciview values indicat e more extinction and a corresponding decrease in visual range. Deliquescence The pr ocess that occurs when the vapor pressure of the saturated aqueou s

solution of a substance is lessthan the vapor pressure of water in the ambient air. Water vapor is collected until the substance is dissolved and is i n equilibrium with its environment. Dew point The temp erature at which humidity in the air will condense upon a soli d

surface. Dichotomous An y particle sampler that separately collects coarse and fine particle s 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 Balance7-6

Dose-response The relationship between t he 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 th e

atmosphere to water and land surfaces. This dryfall can include acidifyin g compou nds 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 sort s

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 standar d

measure or constant. Externally mixed Partic ulate species that co-exist as separate particles without co-mingling or

combining. Extinction Process of reducing radiation transfer by scattering and absorption. Extinction budget Apport ioningthe extinction coefficient to atmospheric constituents t o

anal ysisestimatethe change in visibility caused by a change in constituen t concentrations. Extinction Propor tionof radiation reduced by scattering and absorption per uni t coefficient dis tance. Standard units are inverse megameters (Mm ). The atmospheri c -1 extinction coefficient, loosely referred to as "extinction," represents the ability of the atmo sphere to absorb and scatter light. It equals the sum of th e scattering and absorption coefficients. Fine particles Particu latematter with an aerodynamic diameter of 2.5 microns or les s

(PM ). Fine particl es are responsible for most atmospheric particle-induced 2.5 extinction. Ambient fine particulate matter consists basically of five species: sulfates, ammonium nitrate, organics, elemental carbon, and soil dust. FIPS Federal Implementation Plans7-7

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 o f aerosols. Condition of the atmosphere in whic h 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 Attr ibuteof color that determines whether it is red, yellow, green, blue, o r

other color. It is most strongly related to wavelength of light. Humidity Water i n air, as a gas. Often measured as a percentage, compared to th e

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 Characte ristic of substances (e.g., particles in the atmosphere) having th e

prop erty of absorbing water vapor from air. Also pertains to a substanc e (e.g., a erosols) 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 Inter agencyMonitoring of Protected Visual Environments, a collaborativ e

moni toring program established in the mid-1980's as a part of the Federa l Implementati on Plans. IMPROVE objectives are to provide data needed to asses s the impacts of new emission sources, identify existing man-mad e visibil ity 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-op ticalatmospheric effects of aerosols on cloud albedo and formatio n

(e.g., as condensation nuclei for cloud droplets).7-8

Inhalable particulate Particles smaller than about 12 micrometers in diameter, capable of bein g matter drawninto 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. Sameas 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 qua lity components device over a period of time (e.g., 24 hours to two weeks) through laboratory analysis of the sampler's medium. Integrating Instrumen t that measures the light scattered from a light beam by an nephelometer enclosed air sample through scattering angles between 5 E and 175 E

. Internally mixed Refers to the situation where individua l 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 notice able 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 re cognition of a change in a given landscape (scenic) appearanc e. 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 Ameas ure of change in image appearance that affects image sharpness

. difference (JND) Count ingthe number of JND's (detectable changes) in scene appearance i s

regarded as an alternative method of quantifying visibility reduction (ligh t extinction). Koschmeider The constant in the reciprocal relationship between standard visual rang e constant and the extinction coefficient (see standard visual range). Layered haze Haze that obscures a horizontal layer of a vista. Light extinction The absorpt ion and scattering of light. The attenuation of light per uni t

distance du e to absorption and scattering by the gases and particles in th e atmosphere. LIPM Laser Integrating Plate Method7-9

LOD Limit of Detection LQL Lower Quantifiable Limit Magnehelic gauge Adiffe rential pressure gauge suitable for measuring pressure differences a s

small as 0.1 inches of water. Major source A stationary facility that emits a regulated pollutant in an amount exceeding

the thr eshold level (100 or 250 tons per year, depending on the type o f facility). Matrix filter A filte r 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 Scat tering by particles whose size is comparable to the wavelength o f

radiation. The attenuation of light in the atmosphere by scattering due t o particles of a size

comparable to the wavelength of the incident light. This is the phenomenon largely responsible for the reduction o f 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 tur bulent mixing, usually due to solar heating of the ground. It is often capped by a stable layer of air. Mm Inverse mega meter. A unit of extinction related to SVR and dv. Highe r -1 extinct

ion coefficients correspond to lower SVR values and higher deciview values. Mobile sources Moving objects that release regulat ed air pollutants, (e.g., cars, trucks, buses, airpla nes, trains, motorcycles, and gas-powered lawn mowers). See als o 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 Sciences7-10

National Acid The 10 -year (1980-1990) interagency research program designed t o Precipitation investigate acid deposition and its effects nationwide. The products o f Assessment thi s program are the series of State of the Science and Technology Program (NAPAP) documents that summarize what we know about the severity of aci d

deposition and the resources it affects. National Ambient Perm issible levels of criteria air pollutants established to protect publi c Air Quality health and welfare. Established and maintained by EPA under authority Standards of the Clean Air Act. (NAAQS) National Anational network of about 200 sites where wet deposition is collecte d Atmospheric weekly and sent to the Central Analytical Laboratory in Illinois for Deposition Program che mical analysis. This network has operated since 1977 and is funde d (N ADP) by seven federal agencies, and numerous cooperators in agencies , unive rsities, and industry. This network of predominately rural sites i s 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 co efficient (b ) of ambient scat air by directly measuring the light scattered by aeros ols 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 isbombarded 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 stand ard" is sufficient to require remedial action; a boundary is determ ined

around the location of the violations. the area within that boundary is designated to be in non-attainment of the particular NAAQ S standard and an enforceable plan is developed to pr event additional violations. NPS National Park Service NSR New Source Review Nuclei mode Asize r ange of particles below about 0.1 micrometer in diameter. Thes e

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 particl e concentration. Often used interchangeably with "turbidity." Optical monitoring Opticalmonitoring refers to directly measuring the behavior of light in th e

ambient atmosphere. Optical particle Anins trument which measures the size of individual particles by th e

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 a nthropogenic (man-made) or natural. Another origin classi ficationis primary (particles that are emitted into the atmosphere a s pa rticles, such as organic and soot particles in smoke plumes or soil dus t 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 Radianceper 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 sigh t line, or path, between a viewer and the object (target). Perceptible Capable of being seen. Phase function Relati onship 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 Ins trument for measuring photometric quantities such as luminance , illuminance, luminous intensity, and luminous flux. An instrument fo r measuring the brightness of an object. It has been suggested that this name be res erved for those instruments which have been adjusted to match th e wavelengthresponse 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 t he cones of a normal eye when exposed to a luminance of at least 3.4 candelas per square meter. Plume Airbor neemissions from a specified source and the path through th e

atmosphere of these emissions. PM Th e acronym for airborne "particulate matter," an air quality parameter fo r

which standards are maintained within NAAQS. PM The acronym for that por tion of PM that has an aerodynamic diameter of 2.5 2.5 microns or less. PM The acronym for that portion of PM that has an aerodynamic diameter of 10 10 microns or less. Polarization A property of light. Light can be linearly polarized in any directio n

pe rpendicular

to the direction of travel, circularly polarized (clockwise o r counterclockwise), unpolarized, or mixtures of the above. Precursor A substance or condition whose pres ence generally precedes the formation of

another, more notable, condition or substance. Prescribed burn A wildland fire whose progress has been controlled by a combination o f

strategies, including: construction of artificial fire breaks, selection of natural fi rebreaks 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 acceptabl e 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 o f 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 Deterioration7-13

Psychrometer An instrument for measuring humidity based on the temperature drop of a

thermometer with a wet wick on the bulb. Pyanometer Anin strument that measures directly the loss of total solar radiance unde r

clear sky conditions. QDM Quadratic Detection Model Quality assurance An overall plan undertaken to quantify, control, and perhaps improve th e

quality of data acquired by a system. Quality control Acti ons routinely taken to maintain a specified level of quality of acquire d (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 theoretica l 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 extinctio n extinction co efficient. Can usually be approximated as the sum of the products of th e

concen trations of individual species and their respective light extinctio n efficiencies. Reflectance Ratio of reflected to incident light. Reflection Return of radiation by a surface without a change of frequency. Regional haze Acl oud of aerosols extending up to hundreds of miles across a region an d

promoting noticeably hazy cond itions. 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 descript ion of color, it qualitatively corresponds to the purity of color: the lack of mixed black or white.7-14

Scattering Changing the direction of radiation at collisions with particles and ga s

molecules. The diversion of light from its original path. It can be caused by molecules or particles. Scattering Proport ionof incident light scattered per unit distance. Standard units ar e 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 les s 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 a tmosphere. Scene monitoring captures the effects of all atmospheri c parameters simultaneously, but in an inherently difficult manner to quantify. It is , for example, difficult to determine quantitatively which of tw o phot ographs represent "better" visibility conditions. Scene monitoring i s 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 b y chemical reactions involving smog-forming chemicals. See also haze. Soot Black particles with high concentrations of carbon in graphitic and amorphous elem entalforms. It is a product of incomplete combustion of organi c compounds. Source Any plac e 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 i n Mountain Initiative the highland regions of the southeastern United States. The objective o f (SAMI) this re gional cooperative is to determine the current and future impacts o f

regional air pollutants, suc h as ozone and acid deposition, and to recommend regionalair management strategies to control the formation of thes e pollutants. SRP Salt River Project7-15

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 v isual range standardized to Rayleigh scattering at an elevation o f 5,000 feet (10 Mm ). The distance under daylight and uniform lightin g -1 conditions at which the apparent contrast between a specified target and its backgroun dbecomes 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 pro cess of separating a database into different groups according to (o f data) some detail of their origin, for the purposes of i mproving statistical sensitivity. Strip chart recorder A device for making a time record of some signal, usually an applied voltage.

The sign al 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 f or 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 th e 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-VH S, an high definition video format which is capable of achievin g

horizon tal 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, promotin g inv ersionstagnationand increased concentrations of air pollutants. A condit ionof a layer of atmosphere in which temperature increases with altitude. Such a layer is stab le, and pollutants migrate through it very slowly. Also known as an inversion layer. Texture Roughness of the landscape.7-16

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 Anelementwhich is emitted most strongly by a specific source or class o f

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 attenuatio n 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

rece ived from a distant light source. Total light extinction is measured b y integrating light scattering and absorption properties of the atmosphere. Transmittance The rat io of the light transmitted through a medium to the incident light

.

Light is attenuated by scattering and adsorption from gases and particles. Tribal Acolle ction of regulations used by the indian tribes to carry out it s Implementation responsibilities under the Clean Air Act. Plan (TIP) TRPA Tahoe Regional Planning Agency TSP The acr onym for total suspended particulates, that portion of PM that i s

captured by a PM sampler which does not attempt to discriminate according to particle size. Turbidity A condition that reduces atmospheric transparency to radiation, especiall y

light. The degree of cloudiness, or haziness, caused by the presence o f 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 Service7-17

USFWS United States Fish and Wildlife Service VHS Video H ome System, a video tape format commonly used on vide o

recorder/players. VIEW Vi sibilityIntensive Experiment in the West, a project of the US EPA, with

coopera tionof the National Park Service, to measure visibility at man y statio ns throughout the western United States to document current visibility and examine trends. Violation of Aregu latory situation, (i.e., NAAQS), where the pattern of "exceedence s standard of standard" is greater than the frequency allowable under that standard. Virtual impactor Atype of dichotomous sampler which separates large particles from an ai r

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 atmospheri c

pa rticles (particle origin, size, shape, chemical composition, concentration , temporal and spatial distribution, and other physical properties). Optica l indexes include coefficient s for scattering, extinction, and absorption, plus an angul ar dependence of the scattering known as the normalized scatterin g 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 t he cleanest 20% of the samples, the median (or mean) of al l

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 o r 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 o f

processingatmospheric optical parameters on a scene. The process starts with a photo graph of landscape features viewed in clean atmospheric condition s and models the effects of changes in atmospheric composition. Visual range (VR) Anexpr ession of visibility; the maximum distance at which a large blac k

object just disappears against the horizon. Washout The process by which particles are r emoved from air by capture by raindrops. WESTAR Western States Air Resources Council7-18

Wet deposition The deposit of atmospheric gas es 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 conditio ns deteriorate and become unacceptable, as described in the burning plan. XRF X-Ray Fluorescence